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39686977 | PMC11646789 | pmc | 2,125 | {
"abstract": "Metabolic engineering-driven microbial cell factories have made great progress in the efficient bioproduction of biochemical and recombinant proteins. However, the low efficiency and robustness of microbial cell factories limit their industrial applications. Harnessing microbial heterogeneity contributes to solving this. In this review, the origins of microbial heterogeneity and its effects on biosynthesis are first summarized. Synthetic biology-driven tools and strategies that can be used to improve biosynthesis by increasing and reducing microbial heterogeneity are then systematically summarized. Next, novel single-cell technologies available for unraveling microbial heterogeneity and facilitating heterogeneity regulation are discussed. Furthermore, a combined workflow of increasing genetic heterogeneity in the strain-building step to help in screening highly productive strains - reducing heterogeneity in the production process to obtain highly robust strains (IHP-RHR) facilitated by single-cell technologies was proposed to obtain highly productive and robust strains by harnessing microbial heterogeneity. Finally, the prospects and future challenges are discussed.",
"introduction": "1 Introduction Constructing highly productive and robust strains is the foundation for efficient bioproduction of biochemical and recombinant proteins, which requires obtaining microorganism strains with a high titer, yield, and productivity, meanwhile maintaining the highly productive state stably during fermentation [ [1] , [2] , [3] ]. However, in the cultivation of a single strain, growth and metabolism heterogeneity can often be observed due to genetic variation induced by plasmid loss and mutation as well as non-genetic variation caused by stochastic gene expression, asymmetric cell division, copy number variation, and heterogeneous local environments [ 4 , 5 ]. In terms of biosynthesis of target products, microbial heterogeneity is a double-edged sword. It can be increased to generate libraries of diverse variants, from which highly productive strains can be obtained through growth-based directed evolution or fluorescence signal-based high-throughput screening [ [6] , [7] , [8] ]. It can also be increased to improve biosynthesis efficiency through metabolic division of labor [ 9 , 10 ]. Unfortunately, microbial heterogeneity can also be deleterious. During the fermentation of highly productive strains, microbial heterogeneity can cause the emergence of low- and non-productive cell subpopulations. Because biosynthesis of target biochemicals or recombinant protein often confers metabolic stress on engineered strains and impairs cell growth, emerging low- and non-productive cells have higher growth rates and can gradually replace high-productive cells during long-term or large-scale fermentation, therefore restricting bioproduction robustness and then hampering the industrialization of bioprocess [ 11 , 12 ]. Therefore, increasing microbial heterogeneity can facilitate the building of highly productive strains, and reducing heterogeneity can improve production robustness. Proper regulation of microbial heterogeneity is expected to obtain highly productive and robust strains. Fueled by synthetic biology, efficient tools and strategies to increase and reduce microbial heterogeneity have recently been developed ( Table 1 ). In addition, novel single-cell technologies for unraveling microbial heterogeneity are available and widely used. These advances facilitate microbial heterogeneity analysis and regulation. As for microbial heterogeneity occurring in the cultivation of a single strain, previous reviews have mainly focused on the origins and functional roles of microbial heterogeneity, tools for the measurement and analysis of microbial heterogeneity and just one side of harnessing genetic heterogeneity (increasing genetic heterogeneity to construct diverse libraries of mutants or reducing genetic heterogeneity for highly robust strains) [ 4 , [13] , [14] , [15] , [16] , [17] ]. However, the synthetic biology-driven tools and strategies that can be used to improve biosynthesis by increasing and reducing genetic and non-genetic heterogeneity have not been systematically summarized and discussed, especially how to cooperatively utilize two sides of harnessing heterogeneity (increasing and reducing) for highly productive and robust strains, and how to use novel single-cell technologies to facilitate microbial heterogeneity regulation. Therefore, a discussion on current progress and future perspectives of increasing and reducing microbial heterogeneity for improved biosynthesis fueled by synthetic biology is now relevant. Table 1 Tools and strategies to harness microbial heterogeneity. Table 1 Categories Tools and strategies Description Refs Increasing genetic heterogeneity In vivo mutagenesis plasmid A potent, inducible, broad-spectrum mutagenesis plasmid for E. coli constructed by manipulating DNA methylation state, cytosine deamination, base-excision repair and mutagenic nucleobase export. [ 47 ] Genome replication engineering-assisted continuous evolution (GREACE) A strategy to accelerate the evolution process in E. coli by introducing dnaQ (proofreading elements of the DNA polymerase complex) mutant library to disturb genome replication. [ 49 ] A synthetic SIM module A strategy to accelerate E. coli adaptive evolution by harnessing stress-induced mutagenesis (SIM). A genetic toggle switch was used to control the expression of the genes related to SIM in a bistable manner. [ 48 ] Autonomous evolution mutation system (AEMS) A system to promote the occurrence of mutations in B. subtilis . The system uses hierarchical dynamic control to switch between the high-fidelity module and the mutagenic module. [ 7 ] Feedback-regulated evolution of phenotype (FREP) An adaptive evolution system with autonomously adjustable mutation rates. Target product-responsive biosensor was used to control mutator gene mutD5 so that the mutation rate increased in the absence of the target product to generate diversity in the population and reduced in the presence of the target product with a high concentration. [ 50 ] Self-directed evolution based on a digital pH-sensing system A directed evolution system with adjustable mutation rates depending on intracellular pH environments. [ 6 ] CRISPR- and RNA- assisted in vivo -directed evolution (CRAIDE) A CRISPR-assisted evolution system with RNA, not DNA, as a repair template. Variants of chimeric donor gRNAs composed of gRNA guiding Cag9/dCas9 and the RNA segment as a repair template, which are continuously transcribed by an error-prone T7 RNA polymerase, are used to introduce mutations by RNA-mediated repair. [ 60 ] OrthoRep A system with an orthogonal DNA polymerase–plasmid pair in yeast. It stably and orthogonally mutates at a rate about 100,000-fold faster than the host genome i n vivo . [ 61 ] Highly error-prone DNA polymerase I-based targeted gene evolution A system resulting in a strong mutagenesis of a target sequence encoded in a Pol I-dependent plasmid. Point mutations that can increase the error rates of DNA polymerase I (Pol I) replication were introduced. [ 62 ] Retrotransposon Ty1-based in vivo continuous evolution A retrotransposon Ty1-based system that can be used for in vivo continuous evolution of genes and pathways in yeast. In vivo continuous evolution was enabled by coupling with growth selection. [ 63 ] T7-targeted dCas9-limited in vivo mutagenesis (T7-DIVA) system An in vivo evolution platform-based T7 RNA polymerase (T7RNAP) and catalytically dead Cas9 (dCas9) in E. coli . The platform uses T7 RNA polymerase to target mutagenic enzymes (base deaminase) to the target sequence and uses catalytically dead Cas9 (dCas9) combined with custom-designed crRNAs as a “roadblock” to constrict the size of the mutation window. [ 64 ] Expanded MutaT7 toolkit Targeted mutagenesis platforms mediated by nucleotide base deaminase-T7 RNA polymerase fusions with higher mutation frequencies and expanded utility. [ 66 ] Targeted in vivo diversification enabled by T7 RNAP (TRIDENT) A mutagenesis platform that uses T7 RNA polymerase to target two different types of base deaminases to the target sequence to broaden the mutation spectra and localize DNA repair factors to sites of deaminase-driven mutations to enhance the mutation rate. [ 65 ] Increasing non-genetic heterogeneity Asymmetry distribution-based synthetic consortium (ADSC) An asymmetry distribution-based synthetic consortium (ADSC) that can coordinate the ratio of production cells and growing cells in the population by asymmetric cell division, thereby improving production by metabolic division of labor. [ 10 ] Integrase-mediated differentiation circuits Circuits that divide the population into two cell types, progenitors (responsible for replication and proliferation) and differentiators (responsible for biosynthesis) by terminal differentiation, therefore improving the evolutionary stability of burdensome and toxic functions in E. coli . [ 9 ] Asymmetric plasmid partitioning-based asymmetric cell division A synthetic system for asymmetric cell division in E. coli based on asymmetric plasmid partitioning from C. crescentus. [ 72 ] Reducing genetic and non-genetic heterogeneity Synthetic symbiosis combining plasmid displacement A strategy to construct a phenotype-stable microbial system. It maintains plasmid stably by expressing essential genes and genes of interest in the same plasmid backbone and uses plasmid displacement to simplify the workflow. [ 74 ] Choosing appropriate host cells Different host cells have different characteristics, and choosing appropriate host cells is also a promising way of reducing microbial heterogeneity. [ 76 , 77 ] Constructing chassis with reduced mutation rates Deleting or inhibiting unstable elements in the genome, including prophage, insertion sequence elements and error-prone DNA polymerases, is a promising approach to constructing chassis with reduced mutation rates. [ [83] , [84] , [85] , [86] , [87] ] Deleting recA Deleting recA helps construct robust chassis with reduced homologous recombination rate to express multicopy genes stably. [ 89 ] Periodic reselection for evolutionarily reliable variants (PResERV) A directed evolution strategy for characterizing new targets that replicate ColE1-type plasmids with higher fidelity in E coli [ 90 ] Combinatorial assembly platform A strategy to overcome genetic instability, which requires the construction of a library of metabolic pathway-encoding variants using efficient DNA assembly methods. Then, stable variants were selected from the library. [ 78 ] Metabolic coupling of cell growth with biosynthesis A pyruvate-driven growth-coupled strategy to improve bioproduction robustness. By deleting endogenous pyruvate-releasing pathways, E. coli was engineered to use the target product biosynthesis pathway as the sole endogenous pyruvate-releasing pathway to support growth. [ 79 ] Synthetic sequence entanglement A strategy to constrain the evolution path by overlapping a sequence of interest with an essential gene. [ 80 ] Synthetic addiction based on product-responsive biosensor Strategies to couple cell growth with biosynthesis by using the (intermediate or end) product-responsive biosensor to control the expression of growth-related key genes, such as essential genes and amino acid synthesis-related genes. [ 12 , 40 , 81 , 82 ] Engineering global gene regulatory A strategy to enable homogeneous expression of green fluorescent protein (GFP) in Bacillus subtilis by CodY R214C mutation [ 91 ] Engineered promoters with constant gene expression at any copy number in bacteria Gene parts overcoming heterogeneity caused by copy number variation between individual cells. An incoherent feedforward loop (iFFL) was engineered into E. coli promoters using transcription-activator-like effectors (TALEs). [ 93 ] Stable and tunable plasmid (STAPL) system A system used to minimize cell-to-cell variation of a plasmid-based expression system under antibiotic-free conditions. The essential gene infA is encoded on the plasmid instead of the chromosome. [ 20 ] (Inducible) Population quality control Strategies to exploit non-genetic heterogeneity to improve biosynthesis. Coupling of growth with biosynthesis was used to enrich high-performing cell subpopulations. [ 11 , 40 ] By exploiting the advantages of different species, synthetic microbial consortia based on co-cultivation of multiple species also use heterogeneity to achieve sophisticated functions for reduced metabolic burden [ 18 ] and high substrate conversion capacity [ 19 ]. Although gaining much attention, co-cultural microbial consortia are very different from microbial heterogeneity occurring in the cultivation of a single strain. Here, we only focus on the latter. This review summarizes the origin of microbial heterogeneity and its impact on biosynthesis. It highlights advances in synthetic biology-driven tools and strategies and novel single-cell technologies that aid in understanding and regulating microbial heterogeneity. Furthermore, a combined workflow facilitated by single-cell technologies, namely increasing genetic heterogeneity in the step of strains building to help in building highly productive strains - reducing heterogeneity in the production process to obtain highly robust strains (IHP-RHR) was proposed to obtain highly productive and robust strains by harnessing microbial heterogeneity. Finally, prospects and future challenges were proposed."
} | 3,407 |
26442023 | PMC4563166 | pmc | 2,126 | {
"abstract": "Higher plants have evolved intimate, complex, subtle, and relatively constant relationships with a suite of microbes, the phytomicrobiome. Over the last few decades we have learned that plants and microbes can use molecular signals to communicate. This is well-established for the legume-rhizobia nitrogen-fixing symbiosis, and reasonably elucidated for mycorrhizal associations. Bacteria within the phytomircobiome communicate among themselves through quorum sensing and other mechanisms. Plants also detect materials produced by potential pathogens and activate pathogen-response systems. This intercommunication dictates aspects of plant development, architecture, and productivity. Understanding this signaling via biochemical, genomics, proteomics, and metabolomic studies has added valuable knowledge regarding development of effective, low-cost, eco-friendly crop inputs that reduce fossil fuel intense inputs. This knowledge underpins phytomicrobiome engineering: manipulating the beneficial consortia that manufacture signals/products that improve the ability of the plant-phytomicrobiome community to deal with various soil and climatic conditions, leading to enhanced overall crop plant productivity."
} | 302 |
37789847 | PMC10544973 | pmc | 2,127 | {
"abstract": "Various types of electroactive microorganisms can be enriched to form biocathodes that reduce charge-transfer resistance, thereby accelerating electron transfer to heavy metal ions with high redox potentials in microbial fuel cells. Microorganisms acting as biocatalysts on a biocathode can reduce the energy required for heavy metal reduction, thereby enabling the biocathode to achieve a lower reduction onset potential. Thus, when such heavy metals replace oxygen as the electron acceptor, the valence state and morphology of the heavy metals change under the reduction effect of the biocathode, realizing the high-efficiency treatment of heavy metal wastewater. This study reviews the mechanisms, primary influencing factors (e.g., electrode material, initial concentration of heavy metals, pH, and electrode potential), and characteristics of the microbial community of biocathodes and discusses the electron distribution and competition between microbial electrodes and heavy metals (electron acceptors) in biocathodes. Biocathodes reduce the electrochemical overpotential in heavy metal reduction, permitting more electrons to be used. Our study will advance the scientific understanding of the electron transport mechanism of biocathodes and provide theoretical support for the use of biocathodes to purify heavy metal wastewater.",
"conclusion": "5. Conclusion Biocathodes can reduce internal resistance and improve electron transfer. Therefore, biocathodes not only improve the electrical production performance of the MFC, but quickly remove heavy metals. Several key factors, such as electrode materials, initial heavy metal concentration, and pH, could affect the performance of the removal of heavy metals using biocathode MFCs. For different heavy metals, the corresponding dominant populations can be particularly cultivated on the cathode material to improve their removal rate. This can facilitate further investigation of the effect of different electrode materials in the treatment of heavy metal pollutants by the biocathode MFC, as well as the selection of the electrode materials that are more favorable for electrons. In addition, existing studies on the treatment of heavy metal wastewater using biocathode MFCs have primarily focused on single heavy metal ions, and further study on the treatment of multiple, mixed heavy metals using biocathodes should be performed. Although the removal of heavy metal pollutants using biocathode MFCs is still far from a practical application, this mechanism will be further improved as research progresses.",
"introduction": "1. Introduction Heavy metal pollution is a severe water problem globally ( Nan et al., 2013 ). Untreated heavy metal effluents can cause serious water and soil pollution in surrounding areas, resulting in potentially significant harm to humans ( Kapahi and Sachdeva, 2019 ). Traditional remediation methods, such as chemical precipitation, ion exchange, and membrane filtration, can reduce the biological effectiveness of heavy metals in the environment by converting them to an inactive state ( Azimi et al., 2017 ; Zamri et al., 2017 ). However, these techniques are limited by the treatment environment and can cause secondary contamination and incur high costs. Recently, researchers have applied bioelectrochemical systems based on extracellular electron transfer from microorganisms, such as microbial fuel cells (MFCs), to the remediation of heavy metals in wastewater. In a typical MFC system, electroactive microorganisms metabolize and oxidize organic matter under anaerobic conditions to produce electrons and protons. The electrons reach the cathode from the external circuit, while the protons reach the cathode through the proton exchange membrane. Here, the electrons, protons, and final electron acceptor (typically oxygen) that reach the cathode undergo a reduction reaction in the cathode chamber, producing H 2 O and generating electricity ( Santoro et al., 2017 ). Certain heavy metals with high redox potentials, such as V(V), Cr(VI), and Cu(II), can replace oxygen as the electron acceptor in MFCs and obtain electrons from the cathode, reducing the toxicity of heavy metals via chemical reduction or producing easily recoverable monomers ( Wu et al., 2015 ; Qiu et al., 2017 ; Wang et al., 2020 ). However, cathode activation energy and ohmic losses, as well as mass-transfer processes, reduce the performance of the cathode ( Rismani-Yazdi et al., 2008 ). Therefore, the kinetic performance of the MFC can be improved by increasing the reaction area or oxidant concentration, lowering the activation potential, and reducing activation losses ( Massazza et al., 2021 ). Regarding ohmic losses, reducing the internal resistance of the electrode and electrolyte drives the electron-and proton-transfer processes and improves the power-generation performance of the MFC ( Lawson et al., 2020 ). Mass-transfer loss, owing to reactant depletion or product accumulation, typically occurs at high current densities ( Choi and Sang, 2016 ). Hence, modifying the cathode materials, increasing the ionic strength and oxygen concentration, and reducing the reduction reaction overpotential of oxygen at the cathode can reduce the internal resistance to cathodic mass transfer and improve the cathode reaction rate ( Venkata Mohan et al., 2014 ). This ultimately results in an improvement in cathode performance. When microorganisms are enriched on the cathode, thereby forming a biocathode, electroactive microorganisms can significantly reduce the charge-transfer resistance, accelerate electron transfer, and effectively transfer electrons from the cathode to heavy metal ions with a high valence state. Moreover, the interaction between the microorganisms and electrode surface can increase the initial potential of the biocathode and reduce the energy required for heavy metal reduction. Therefore, microorganisms can act as catalysts to obtain electrons directly or indirectly from the cathode and transfer them to electron acceptors, such as oxygen and heavy metals, promoting their reactions on the biocathode ( Wu et al., 2015 ). This study systematically investigated the electron-transfer mechanism of biocathodes, key factors influencing heavy metal removal by biocathodes (e.g., electrode material, initial concentration and species of heavy metals, pH, and electrode potential), and influence of the microbial community structure on the electrical production performance and removal effect of MFCs. The results of this study will provide new ideas and important references for using biocathode MFCs to treat heavy metal wastewater."
} | 1,651 |
35751080 | PMC9233362 | pmc | 2,128 | {
"abstract": "Background Lignocellulosic conversion residue (LCR) is the material remaining after deconstructed lignocellulosic biomass is subjected to microbial fermentation and treated to remove the biofuel. Technoeconomic analyses of biofuel refineries have shown that further microbial processing of this LCR into other bioproducts may help offset the costs of biofuel generation. Identifying organisms able to metabolize LCR is an important first step for harnessing the full chemical and economic potential of this material. In this study, we investigated the aerobic LCR utilization capabilities of 71 Streptomyces and 163 yeast species that could be engineered to produce valuable bioproducts. The LCR utilization by these individual microbes was compared to that of an aerobic mixed microbial consortium derived from a wastewater treatment plant as representative of a consortium with the highest potential for degrading the LCR components and a source of genetic material for future engineering efforts. Results We analyzed several batches of a model LCR by chemical oxygen demand (COD) and chromatography-based assays and determined that the major components of LCR were oligomeric and monomeric sugars and other organic compounds. Many of the Streptomyces and yeast species tested were able to grow in LCR, with some individual microbes capable of utilizing over 40% of the soluble COD. For comparison, the maximum total soluble COD utilized by the mixed microbial consortium was about 70%. This represents an upper limit on how much of the LCR could be valorized by engineered Streptomyces or yeasts into bioproducts. To investigate the utilization of specific components in LCR and have a defined media for future experiments, we developed a synthetic conversion residue (SynCR) to mimic our model LCR and used it to show lignocellulose-derived inhibitors (LDIs) had little effect on the ability of the Streptomyces species to metabolize SynCR. Conclusions We found that LCR is rich in carbon sources for microbial utilization and has vitamins, minerals, amino acids and other trace metabolites necessary to support growth. Testing diverse collections of Streptomyces and yeast species confirmed that these microorganisms were capable of growth on LCR and revealed a phylogenetic correlation between those able to best utilize LCR. Identification and quantification of the components of LCR enabled us to develop a synthetic LCR (SynCR) that will be a useful tool for examining how individual components of LCR contribute to microbial growth and as a substrate for future engineering efforts to use these microorganisms to generate valuable bioproducts. Supplementary Information The online version contains supplementary material available at 10.1186/s13068-022-02168-0.",
"conclusion": "Conclusions We are interested in improving the economic potential of advanced cellulosic biorefineries by valorizing the associated carbon waste streams. Currently, these waste streams are dried and subsequently burned to generate power for the biorefinery [ 2 ]. With over half the chemical potential of the original lignocellulosic hydrolysate being contained in the soluble waste stream [ 3 ], this material has untapped potential for additional economic value through bioproduct generation [ 1 ]. The first steps towards this goal are to identify the carbon-containing components within this waste material and genetically tractable microorganisms capable of catabolizing those components. The current study determined the composition of a model conversion residue derived from AFEX- and enzyme-treated switchgrass hydrolysate that was fermented by Z. mobilis and distilled to remove bioethanol. The remaining carbohydrates and C1–C4 compounds in this conversion residue supported the growth of diverse collections of Streptomyces and yeast species and a mixed microbial consortium derived from a wastewater treatment plant. Both Streptomyces and yeasts are well-established as industrial producers of valuable bioproducts, suggesting these abilities can be extended to valorizing LCR. Growth assays identified several Streptomyces and yeast species that catabolized over a third of the total soluble COD in the LCR and could therefore serve as chassis for future bioproduct generation from LCR. We also developed a defined, synthetic conversion residue that mimics LCR to examine the effects of individual components of conversion residue on microbial growth. Using this synthetic conversion residue, we showed that LDIs, which had previously been predicted as inhibitors of microbial growth on conversion residue, actually have minimal effect on the growth of Streptomyces strains or the composition of the MMC. Taking this work forward, we envision the development of a series of microbial chassis that can be customized for both the catabolism of the LCR, which may vary depending on the biorefinery pipeline, and the generation of bioproducts that can be selectively produced depending on the current economic demands.",
"discussion": "Results and discussion Determining the composition of a model lignocellulosic conversion residue Given that high levels of plant material deconstruction and xylose consumption are the major engineering goals for hydrolysate production and primary microbial fermentation, respectively, we aimed to characterize a LCR with minimal plant material and decreased xylose concentration. The chosen LCR was derived from an ammonia fiber expansion (AFEX)- and enzyme-treated switchgrass hydrolysate that was filtered to remove the majority of remaining insoluble plant materials [ 29 ]. This filtered hydrolysate was then subjected to fermentation by Zymomonas mobilis and distillation to remove bioethanol. Engineered Z. mobilis 2032 is known to catabolize xylose more efficiently than the similarly engineered and evolved S. cerevisiae Y128 [ 29 , 30 ]; thus, we anticipated the remaining xylose in this LCR would be significantly reduced in comparison to the yeast-fermented LCR. Furthermore, glucose was not expected to be a major component of this LCR as it was predicted to be almost fully consumed during primary fermentation. Consistent with these hypotheses, Z. mobilis -based fermentation resulted in approximately 90% xylose consumption, almost complete glucose consumption, and a final LCR COD of approximately 70 g COD/L (compared to about 146 g COD/L of the hydrolysate) [ 29 ] (Additional file 1 : Table S1). To better understand the composition of this model LCR, a combination of HPLC- and GC–MS-based assays were employed to analyze several batches of this LCR. These analyses identified and quantified the amounts of sugars and other metabolites present that may be used as substrates for further fermentation to additional bioproducts (Fig. 1 , Additional file 1 : Table S1). This LCR was mostly liquid with about 0.7% solids by weight. The largest component of the COD of LCR was oligomeric sugars (54.2 ± 1.8%). The monomeric sugars were the next largest component at 15% of the total COD and included mostly arabinose (6.8 ± 0.2%) and xylose (5.4 ± 0.8%), with trace amounts of glucose, galactose, mannose, fucose, and rhamnose. Metabolites containing up to four carbons (C1–C4) comprised about 11% of the total COD and included primarily acetate (5.4 ± 0.1%), pyruvate (2.5 ± 0.3%), and several other organic compounds. Acetamide, the main residue produced during the nitrogen-rich AFEX pretreatment [ 31 ], was one of the largest single components of the LCR other than sugars (ca. 6%). The alcohols glycerol and xylitol made up a very small percent of the total COD of LCR, 2.6 ± 0.9%. Other compounds present in the LCR could be inhibitory to cell growth, such as monolignols from the plant matter (1.8 ± 0.2%) [ 11 – 13 , 32 ]. The remaining insoluble fraction of the COD (ca. 5%) is most likely residual cell debris from the hydrolysate-fermenting microorganisms (e.g., Zymomonas ). Any remaining material and any leftover COD in the form of amino acids or sugars not accounted for previously were designated as ‘other’ (ca. 0.8%). Fig. 1 Composition of lignocellulosic conversion residue. Lignocellulosic conversion residue (LCR) was generated from “Cave in Rock” switchgrass harvested in 2016, subjected to AFEX and enzyme pretreatments, fermented by Zymomonas mobilis , and finally distilled to remove ethanol. The total potential chemical energy of the remaining LCR was determined by COD analysis while the remaining carbon sources, Zymomonas waste products, and other compounds that might affect future microbial metabolism were quantified via a combination of different separation techniques combined with HPLC and GC–MS analysis then converted to g/L COD to calculate the percent composition of the LCR. The most abundant components of this LCR were oligomeric sugars shown in shades of green (54.2%), monomeric sugars in shades of blue (14.7%), C1–C4 metabolites in shades of purple (10.8%) and acetamide in red (6.4%). These numbers are the average of five batches of LCR Growth of microorganisms on model lignocellulosic conversion residue We tested 71 Streptomyces and 163 yeast species aerobically in batch cultures grown at standard growth temperatures until they reached stationary phase to identify strains in these two groups of organisms that grew well in the model LCR. For comparison, activated sludge from a wastewater treatment plant was also fed with the model LCR and samples taken were grown aerobically in batch culture for 7 days at room temperature. Growth on LCR was measured as the average dry cell weight (DCW) of several biological replicates. Of the 71 Streptomyces strains tested, more than half were able to grow in LCR. Of these, 28 had at least moderate growth (≥ 5 mg/mL DCW) and 22 of those had high growth of ≥ 10 mg/mL DCW (Additional file 2 : Table S2). A phylogenetic analysis of a subset of these Streptomyces strains showed that strains capable of growing to high DCW form distinct phylogenetic groupings with the majority of strains capable of growth on LCR falling into 3 clades, suggesting that there might be multiple factors that contribute to the ability of Streptomyces to grow on LCR (Fig. 2 A). While each of these three clades contained at least one strain capable of high growth, the majority of high-growth strains occurred in clade III. A sizable fraction of yeast species, 34 out of 163, showed moderate growth on the model LCR (Fig. 2 B). Some species, including S. cerevisiae , were likely unable to grow in LCR due to the low concentration of glucose, their preferred carbon source [ 33 ], confirming our hypothesis that an appetite for diverse carbon sources is vital to yeast growth in LCR. Other species, such as Lipomyces starkeyi , are known to consume xylose and other diverse substrates [ 34 ], so the lack of growth is likely due to factors beyond carbon source availability. Several species in the same family, Lipomycetaceae, grew in LCR which suggests that essential traits are variable among close relatives. The highest growing yeast species fell into two distinct groups; several of these yeasts were in the Dipodascaceae/Trichomonascaceae clade, particularly in the genus Blastobotrys, and the rest were in the CUG-Ser1 clade, particularly in the genus Debaryomyces (major clade terminology based on [ 35 ]) . Both of these genera contain yeasts with traits of biotechnological interest, including lipid production capacity in some Blastobotrys yeasts, food applications of Debaryomyces species, and tolerance by both groups to an array of stressors [ 36 ]. Fig. 2 Phylogenetic trees and growth on lignocellulosic conversion residue. Phylogenetic trees of select Streptomyces ( A ) and yeast species ( B ) show the diversity within the tested strains. The bar graphs depict growth of these microorganisms in LCR as the average dry cell weight (mg/mL) of at least 2 mLs of culture from at least two biological replicates with the average dry cell weight (mg/mL) of the microbial consortium at the bottom of each panel. Streptomyces strains capable of moderate (≥ 5 mg/mL DCW) and high (≥ 10 mg/mL DCW) growth after seven days at 28 °C with shaking formed distinct phylogenetic groupings indicated as clade 1 (blue), 2 (red), and 3 (yellow) above. Similarly, the highest growing yeast species after four days rolling at room temperature were from two distinct clades: the Dipodascaceae/Trichomonascaceae clade containing the Blastobotrys or the CUG-Ser1 clade containing the Debaryomyces . The number (n) of species in condensed yeast clades is indicated, and the reported values are the mean and standard deviation of values for all species in that clade. Full growth data are available in Additional file 2 : Table S2. Clade, species, and strain designations are available in Additional file 5 : Table S7 The Streptomyces species capable of high growth had a significantly higher maximum DCW than the tested yeasts, with 8069 B3-B at 81.5 ± 2.1 mg/mL and Blastobotrys capitulata at 19.6 ± 1.6 mg/mL. For comparison, growth yield from the microbial consortium was high, at approximately 14 mg/mL DCW. Although this was lower than several of the Streptomyces strains, the growth yield was comparable to the highest growing Blastobotrys yeasts. Utilization of lignocellulosic conversion residue components While COD gives a measurement of potential chemical energy contained in the tested media, we wanted to perform a more detailed analysis on which carbon and energy sources the Streptomyces and selected yeasts were using for growth. All Streptomyces that grew in LCR, the highest growing yeast species of the Blastobotrys and Debaryomyces genera, and some related species were chosen for further characterization. We quantified the amounts of sugar alcohols, glucose, xylose, cellobiose, pyruvate, succinate, lactate, formate, acetate, and ethanol in LCR before and after growth from the previous experiment. The sum of COD concentrations of these components was reported as characterized COD (Fig. 3 , Additional file 2 : Table S2), and all other LCR components (i.e., oligomeric carbohydrates, monolignols from the plant matter, AFEX pretreatment residues, cell debris, or other metabolic byproducts) were reported as uncharacterized COD (Fig. 3 , Additional file 2 : Table S2). Individual Streptomyces strains were capable of consuming up to 62.9 ± 1.1% of the characterized COD (i.e., SID14171, 14.6 ± 0.3 g COD/L) and 33.4 ± 10.0% of the uncharacterized COD (i.e., SID8358, 13.9 ± 4.2 g COD/L), and a maximum of 37.7 ± 1.5% of the total soluble COD (i.e., SID809, 25.4 ± 1.0 g COD/L) (Fig. 3 , Additional file 2 : Table S2). Yeast strains consumed a similar amount of the overall COD; 36.1 ± 1.7% of the total soluble COD (e.g., Blastobotrys raffinosifermentans , 21.8 ± 1.0 g COD/L), but generally consumed a greater portion of the characterized components (e.g., Debaryomyces fabryi , 82.3 ± 0.2%, 8.3 ± 0.0 g COD/L) than Streptomyces (Fig. 3 , Additional file 2 : Table S2). Most individual microbes consumed a larger percentage of the characterized components as compared to the uncharacterized components. Streptomyces strains SID3915 and SID8358 were exceptions to this pattern, consuming a higher percentage of the uncharacterized COD (19.4 ± 1.7%, 8.8 ± 0.7 g COD/L; 33.4 ± 10.0%, 13.9 ± 4.2 g COD/L, respectively) than the characterized COD (14.2 ± 40%, 3.2 ± 0.9 g COD/L; 27.3 ± 3.7%, 6.1 ± 0.8 g COD/L, respectively), suggesting that these strains had a preference for the components in the uncharacterized portion of the LCR or were perhaps better at accessing those components than the other strains tested (Additional file 2 : Table S2). For comparison, the MMC consumed the highest percent of the soluble COD at 65.7 ± 1.9% (40.4 ± 1.2 g COD/L), nearly 90% (ca. 14 g COD/L) of the characterized substrates comprising LCR, and almost 60% (ca. 26 g COD/L) of the uncharacterized components (Fig. 3 , Additional file 2 : Table S2). This consumption was approximately 25% higher overall than any individual microbe, mostly through consumption of the uncharacterized material. It was surprising that although Streptomyces strains had the highest biomass accumulation as indicated by DCW, they were not the highest consumers of LCR COD. The microbial consortium likely had a higher rate of respiration than any individual species tested which would explain the comparatively low biomass for the amount of COD consumption. Although the MMC consumed a majority of the COD in LCR, a large concentration of soluble organic compounds (both characterized and uncharacterized components) was still present following a 7-day incubation, ca. 20 g COD/L. This suggests that a portion of the LCR COD may be inaccessible to this consortium and may be entirely inaccessible to biofuel- and bioproduct-producing microbes, such as Zymomonas , Streptomyces and yeasts. Reducing the residual fraction of COD is a potential target for further improvements of the upstream processing of biomass prior to primary fermentation. Fig. 3 Utilization of lignocellulosic conversion residue by Streptomyces , yeasts, and mixed microbial consortium. Microbes were incubated in LCR then subjected to COD assays and metabolite analyses via HPLC. Streptomyces are shown in orange, yeasts in purple, and the mixed microbial consortium (MMC) in black on each panel. Percent of soluble COD utilized after incubation of indicated microbes in LCR is calculated relative to a media control. Characterized metabolites include C1–C6 compounds formate, acetate, ethanol, succinate, pyruvate, propionate, lactate, glycerol, xylitol, xylose, and glucose, as well as the glucose dimer cellobiose. The uncharacterized fraction includes all other soluble components such as oligomeric sugars, monolignols from the plant matter, AFEX pretreatment residues, cell debris, or other metabolic byproducts. Values reported are the average of at least two biological replicates with standard deviation denoted by error bars HPLC analysis of the characterized components of LCR after microbial growth focused on three groups of compounds: C1–C4 metabolites, monomeric sugars, and sugar alcohols (Fig. 4 ). One limitation of this HPLC analysis is that xylose and galactose, both known components of LCR, eluted from the column at the same time. Since galactose is only present in small amounts in LCR (Additional file 1 : Table S1), we will refer to this combined value as xylose going forward. Fig. 4 Lignocellulosic conversion residue metabolite utilization by Streptomyces , yeasts, and mixed microbial consortium. Patterns of indicated characterized metabolites present in LCR after incubation with microbes are shown relative to media controls. Analysis of at least two biological replicates was averaged. Metabolites that were present in lower levels than the media control are shown in red, metabolites that were present in higher levels than the media control are shown in blue, and white indicates no change relative to the media control. This gives a pattern of characterized metabolite consumption (red) and generation (blue) for these LCR degrading microbes As expected, the levels of many of the assayed compounds were lower after incubation with these microorganisms as they were energy sources for cell growth. However, some of the spent LCR samples tested showed increased levels of pyruvate, succinate, xylitol, xylose, cellobiose, and/or glucose after microbial growth. (Fig. 4 ) The majority of Streptomyces strains produced high amounts of pyruvate, a known behavior of Streptomyces growing in media with high nitrate concentrations [ 37 ]. Three of the yeast species produced noticeable levels of succinate, a known anaerobic byproduct of some yeasts that is hypothesized to be driven by membrane energization, which may suggest that even though the cultures were grown with rolling, oxygen was limiting under these growth conditions [ 38 ]. Since xylose, cellobiose, and glucose are rare extracellular products for microorganisms, they were most likely being generated as breakdown products from the solubilized cellulose (cellobiose, glucose) and hemicellulose (xylose) dimers or small polymers remaining from hydrolysis of the original plant material and that were not metabolized during primary fermentation. This hypothesis is consistent with the utilization of uncharacterized COD depicted in Fig. 3 . The abundance of these sugars after microbial growth is likely due either to their production at a rate higher than their uptake or whose uptake was prevented by catabolite repression. Furthermore, the patterns of metabolite consumption could indicate a preference for cellulose over hemicellulose by Streptomyces , as many strains show higher consumption of glucose and cellobiose than xylose and xylitol. However, the apparent accumulation of glucose in spent LCR from the MMC and several Streptomyces strains was surprising, as glucose is a preferred carbon source for many microorganisms, and we hypothesized that the consortium would utilize all available sugars. Further examination of the HPLC traces suggest that another byproduct from these samples eluted from the HPLC at approximately the same time as glucose (Additional file 1 : Figure S1). From these growth and LCR consumption assays, we can identify microorganisms that are good candidate chassis for generating valuable bioproducts from LCR. A high overall soluble COD consumption indicates that more energy would be available to be pushed towards the production of these compounds. As microbes are engineered for higher COD consumption, we hypothesize that it will be easier to increase consumption of the characterized LCR components than the uncharacterized. This would make microbes that already have high consumption of the uncharacterized portion of the LCR more desirable production chassis. For the Streptomyces , SID14171 and SID809 perform well in overall COD consumption, but SID8358 is perhaps a more attractive target due to its superior performance on the uncharacterized portion of the LCR. For the yeast species, performance on the characterized portion of COD was strong for all species analyzed. Generally, performance was also similar across species on the uncharacterized portion, but several species including Sugiyamaella smithiae , Wickerhamiella dulciola , and Blastobotrys arbuscula proved weaker in this regard. Blastobotrys raffinosifermentans has recently been highlighted due to its potential for lipid production and may prove to be a strong chassis for bioproduct formation from LCR [ 39 ]. Development of synthetic conversion residue Given the complexity and limited availability of LCR, we wanted to develop a defined media that mimicked LCR for future experiments. This synthetic conversion residue (SynCR) would allow us to examine how individual components affect the growth of our microorganisms and if any uncharacterized components have a relevant contribution to growth phenotypes. To design SynCR, we used the analysis of the LCR as a starting point. We included the sugar alcohols, C1–C4 metabolites, cellular waste products, and the most abundant monomeric sugars. Since it was not possible to determine the chain length of the oligomeric sugars and adding variable chain-length purified hemicellulose or cellulose consistent with our observed compositions was not logistically feasible, we added the most abundant hemicellulose components as monomers and used Sigmacell50 to represent the cellulose. Cysteine, methionine, and tryptophan were not detected in our analyses, but they were added to the SynCR at 150 μM to ensure growth and optimize future production of bioproducts [ 40 , 41 ]. The remaining amino acids were added at the concentrations measured in LCR. The most abundant minerals and metals (≥ 3 mg/mL), as well as any required for growth by either yeasts or Streptomyces , were also included in the final SynCR. Acetamide was included in SynCR as it is a significant component of LCR. After the addition of all these components except for the Sigmacell50, the SynCR was filtered and adjusted to pH 6.5, the same pH as LCR for microbial growth. The Sigmacell50 was sterilized by autoclaving and added to the SynCR after final filtration (recipe in Additional file 1 : Table S3). To begin investigating how microbes utilize the wide variety of carbon sources in the LCR, we used SynCR to examine the metabolite consumption patterns of a subset of Streptomyces and yeasts that had a range of growth and metabolite consumption patterns on LCR. Since SynCR is a minimal version of LCR with approximately the same calculated COD (ca. 65 g/L) and the hemicellulose components converted to monomers, we hypothesized that we would see a greater percentage of the SynCR utilized by our microorganisms than the LCR. That was true for most of the Streptomyces strains tested, where the strains utilized as much or more of the SynCR than they did the characterized components of the LCR (Fig. 5 , Additional file 3 : Table S5). However, 8069 B3-B had a lower overall percent of SynCR utilized as compared to LCR, suggesting that breakdown and utilization of the uncharacterized components of LCR are an important factor in metabolite utilization by this strain. The most striking difference in the metabolites characterized in SynCR after the growth of the indicated Streptomyces strains was a relative increase in the “other” component as compared to the uninoculated SynCR (Fig. 5 ). Streptomyces are known to produce many specialized metabolites [ 42 ] and may be converting some of the SynCR carbon into these metabolites, which would account for the increase in the “other” COD component. It also makes it unclear how much of the uncharacterized portion of LCR was new compounds produced by the microbes assayed or material initially in the LCR that was not broken down or consumed during incubation. Another notable difference in SynCR utilization as compared to LCR utilization (Fig. 3 b) was the lack of cellobiose accumulation in all strains except SID8358. Since that metabolite is present due to cellulose breakdown in LCR, this result suggests that the insoluble Sigmacell50 was not as accessible to most of the Streptomyces tested as the soluble switchgrass-derived lignocellulose polymers in LCR. Further, the ability of SID8358 to degrade both the uncharacterized, oligomeric-containing portion of LCR and Sigmacell50 indicate that it could serve as a potential source for future mining of cellulose-degrading enzymes. Fig. 5 Utilization of synthetic conversion residue by Streptomyces and mixed microbial consortium. Microbes were incubated aerobically in synthetic conversion residue (SynCR) with crystalline cellulose and with or without lignocellulose-derived inhibitors (LDIs) for seven days then subjected to COD assays and metabolite analyses via HPLC. The bars labeled SynCR show the metabolite levels in the uninoculated media controls while the remaining bars indicate the amounts of the those metabolites present in spent SynCR after 7 days of incubation with either the mixed microbial consortium (MMC) or the indicated Streptomyces strains. Values reported are the average amounts of metabolites remaining after incubation from 3 biological replicates Interestingly, only one of the seven tested yeast species was able to grow in the SynCR (Additional file 1 : Table S4). Since these yeasts grew in LCR, this suggested that a component of the LCR essential for yeast growth was not included in the SynCR recipe. Standard yeast synthetic media [ 43 ] contains the vitamins biotin, inositol, and the B vitamins pyridoxine and niacin. Vitamin supplementation restored growth of yeasts in SynCR (Additional file 1 : Table S4) and LC–MS/MS analysis confirmed that those vitamins were present in LCR at concentrations greater than those required for growth of the tested yeast species. In the future, any LCR generated will need to be evaluated for vitamins to assess viability of yeast growth. The MMC was also grown on SynCR to show the maximum amount of SynCR available for microbial degradation. The MMC was able to metabolize almost the entirety of the soluble SynCR (95.2 ± 1.8%, 34.1 ± 1.6 g COD/L), which was not surprising as the consortium was also able to metabolize such a large portion of the characterized components of the LCR. The composition of future SynCR recipes could also be adjusted to focus on separate carbohydrate components, e.g., arabinose versus xylose, in order to identify or engineer microorganisms better able to metabolize these components. One of the uses for SynCR is to test how individual components affect the growth of our microorganisms. Since our microbes were able to grow in LCR, they obviously are tolerant of LDIs which had been reported in the literature to be inhibitory to some microbes [ 32 ]. We wanted to determine if LDIs had any negative impact on the growth and LCR utilization of our microbes that might be reduced by future engineering efforts. Growth experiments using SynCR both with and without LDIs allowed us to test the effect these compounds had on our organisms. Interestingly, LDIs appear to have minimal effect on the Streptomyces strains tested. Only two of the Streptomyces strains tested, SID10536 and SID809, showed differential behavior in percent SynCR consumed in the presence or absence of LDIs. The higher percent of metabolites consumed by SID10536 when grown in SynCR without LDIs suggests that LDIs may be inhibitory or inducing other pathways that shift metabolism away from consumption, while conversely the LDIs may be inducing consumption in SID809. Due to the difficulty in getting yeasts to grow on SynCR, they were not evaluated for inhibition by LDIs. Comparisons between the most abundant OTUs in the SynCR experiments with and without LDIs showed only minimal changes in microbial abundances. This is reflected in non-metric multidimensional scaling (NMDS)-space, where the LCR consortium plots more distantly from the two SynCR consortia (Additional file 1 : Fig. S2). Only one OTU, Corynebacterium , had a higher relative abundance in both the LDI-containing LCR and SynCR with LDIs experiment, consistent with the observation that some Corynebacterium species have shown tolerance to LDIs [ 44 ]. The similarity of the microbial consortia grown on SynCR with and without LDIs suggests these potential toxins have a minimal effect on the microbial consortium structure. Furthermore, the similar abundance of microbial consortium members in both SynCR incubations (Fig. 5 ) and the data from the Streptomyces species tested both suggest that the LDIs were not universally an impediment to microbial growth. This observation is counter to previous studies demonstrating the inhibitory effect of these compounds on fermentative organisms [ 11 – 13 ]. Consortium differences in model LCR compared to SynCR The mixed microbial consortium serves as both a representative of the maximum LCR utilization possible and as a potential source of genetic material to engineer microbes for increased LCR utilization. The SynCR can be used to assist in identification of OTUs that are responsible for utilization of specific components of the LCR. For example, to identify which OTUs in the MMC contribute to mannose utilization, we can monitor the change in consortium composition when the MMC is grown in SynCR with mannose as compared to SynCR without mannose. Similarly, as SynCR consists mostly of the characterized components of LCR, comparisons between consortium composition when grown on LCR as compared to SynCR will allow us to examine which OTUs contribute to the utilization of the uncharacterized portion of the LCR. Since we predict that it will be more difficult to engineer strains to utilize this portion of the LCR, the MMC can thereby serve as a uniquely valuable resource for that genetic material. For these experiments, genomic DNA extracted from the initial inoculum and biomass pellets ( n = 4) from the microbial consortia grown as indicated was subjected to 16S rRNA gene amplicon sequencing analysis. A total of 2931 unique operational taxonomic units (OTUs) were identified across all samples with the OTUs present in the initial wastewater consortium included for comparison (Additional file 4 : Table S6). Subsequent analyses focused on the most abundant taxonomic groups which had a relative abundance of 1% or greater at the genus level. This procedure resulted in 24 highly abundant taxonomic groups across all samples representing approximately 90% of the total DNA reads (Fig. 6 ). The number of distinct highly abundant taxonomic groups in each sample tested were similar (inoculum, 17; LCR, 11; SynCR with LDIs, 15; SynCR without LDIs, 14), with a slightly less diverse microbial consortium present after seven days of growth in LCR than in SynCR, which is most likely due to less easily available carbon for microbial metabolism. Fig. 6 Distribution of bacterial taxa in the mixed microbial consortium on different growth media. Bacterial taxa were identified within the initial inoculum source and following a 7-day incubation period in LCR or SynCR with crystalline cellulose and with and without LDIs. Individual OTUs were clustered to the highest taxonomic level (c, class; o, order; g, genus), with clusters greater than 1% total relative abundance shown above, organized by phylum ( Pa ., Patescibacteria ; Sa ., Saccharibacteria ; Bacter ., Bacteroidota ; Actino ., Actinobacteriota ). Taxa with distinct differences in abundance between the microbial consortia grown on different types of CR are indicated in bold The microbial consortium analysis revealed several key differences in consortia composition when grown on LCR as compared to SynCR. The most profound difference in microbial consortium composition between the LCR and SynCR experiments was the variable abundance of Enterococcus and Enterobacter . In the LCR-fed cultures, Enterococcus represented approximately a quarter of the 16S rRNA sequence reads, but they were present at about 5% relative abundance in the inoculum and in both SynCR experiments. Conversely, Enterobacter represented 15–24% of the microbial population in the inoculum and SynCR experiments but less than 4% of the LCR consortium (Fig. 6 ). Enterobacter are endophytes, which have been associated with numerous plant species, including switchgrass [ 45 ]. These taxa have also been shown to metabolize cellulose and components of hemicellulose, such as xylose [ 46 – 48 ]. Species of Enterococcus are facultative anaerobes that are both typical commensal members of the human gut microbiome and potentially pathogenic, so their presence in these experiments is unsurprising due to the origin of the inoculum. Cellulolytic activity, as well as metabolism of other carbohydrate polymers, such as pectin, have also been reported in Enterococcus species [ 49 – 52 ], which is consistent with a typical greater abundance of these taxa in the gut microbiomes of vegetarians [ 53 ] and in fermented plant products [ 54 ]. The prevalence of lignocellulose-degrading enzymes and cellulolytic activity in Enterobacter and Enterococcus indicates a likely role that these taxa play in the LCR and SynCR consortia; however, the abundance of free monomer carbohydrates in SynCR likely allowed the Enterobacter to outcompete the Enterococcus in these experiments. Because of the apparent opportunistic behavior of the Enterobacter , we anticipate genomic studies of the Enterococcus members of the consortium may be a more promising resource for microbial engineering. The other relevant difference between the LCR and SynCR microbial consortia was that Dysgonomonas and Paucilactobacillus were present in both consortia, but at a significantly increased relative abundance in LCR (ca. 11% and ca. 6%, respectively, Fig. 6 ) as compared to SynCR. Dysgonomonas are gut symbionts of termites and wood-boring insects, and recent genomic studies of the species have revealed an abundance of glycoside hydrolase enzymes, which suggests a role in lignocellulose degradation [ 55 – 57 ]. Similar to Enterococcus , abundance of Dysgonomonas in the LCR consortium is likely a result of their putative role in the degradation of oligomeric carbohydrates, which comprise half of the potential carbon energy in LCR, and is consistent with the high observed consumption of the uncharacterized portion of COD (Fig. 3 ). In contrast, Paucilactobacillus is a heterofermentative lactic acid bacteria notable for the uncommon ability to metabolize pentoses [ 58 ], so would be expected to be more abundant in SynCR experiments due to the greater concentration of monomer pentoses in the SynCR as compared to LCR. However, most of the characterized species of this genus were isolated from fermented plant material and some strains have been shown to metabolize disaccharides, such as melibiose by Paucilactobacillus hokkaidonensis [ 58 ], and may therefore be able to utilize some of the less commonly metabolized plant breakdown sugars. Depending on the carbohydrate composition of future LCRs, Dysgonomonas or Paucilactobacillus related members of the consortium may be a beneficial bioengineering resource for genes related to oligomeric or less commonly metabolized sugar utilization."
} | 9,387 |
39958145 | PMC11827584 | pmc | 2,129 | {
"abstract": "ABSTRACT Fracture-based interfacial breakage has shown promise in efficiently removing ice accretion. Here, intrigued by the response of human skin to stress-induced deformation, we present a strategy to design tough-skin de-icing surfaces (TSDSs) that actively manipulate crack-induced ice-substrate interfacial breakage during ice removal. This design leverages the surface instability of thin films to generate extensive wrinkling at the ice-substrate interface, which serves as crack initiation sites. We demonstrate efficient ice shedding by creating wrinkles at two length scales: macro-wrinkles for actively initiating the cracks at the rim of the ice and micro-wrinkles for further promoting the stress concentration at the ice-substrate interface. The TSDS ( τ < 10 kPa) displays excellent durability and weather resistance, achieving a large-area ice-self-shedding effect solely through gravity. The universality of the proposed mechanism is verified on multiple materials and potential applications. This design concept offers valuable insights into the creation of durable de-icing materials with enhanced ice-shedding properties.",
"conclusion": "CONCLUSIONS In this study, we propose a strategy to design de-icing surfaces by generating dual-scale crack initiates at/in the ice-solid interface. The designed micro-wrinkled TSDS displays excellent de-icing performance, taking advantage of surface instability-induced wrinkles. Following the design principle, we verified the universal applicability of this design strategy and its effectiveness in different environments. The protective skin significantly enhances the robustness of the TSDS, as demonstrated through a series of environmental tests. We envision that this designed surface is expected to have broad significance for the de-icing field, especially in complex and harsh icing environments.",
"introduction": "INTRODUCTION Ice accretion tightly adheres to surfaces due to strong interaction forces such as van der Waals force, electrostatic force and hydrogen bonds between them [ 1 , 2 ]. This significantly complicates de-icing efforts across various fields, including transportation systems [ 3 , 4 ], power systems [ 5 ] and infrastructure [ 6 , 7 ]. From an interfacial perspective, the primary challenge lies in effectively disrupting the ice-solid interface and therefore removing ice accumulations that cling to various surfaces. This issue underscores the necessity for efficient methods to fracture the ice-solid interface and reduce ice adhesion. For conventional structural substrates, their inherent rigidity prevents surface deformation under shearing forces (Fig. 1a ). This leads to a state of pure shear stress at the surface. The strong interaction between ice and substrate requires significant energy to remove the ice accretion. Typical hard structural surfaces, such as aluminum and steel, exhibit ice-adhesion strengths of >1000 kPa [ 1 ]. Recent strategies for reducing ice adhesion, including those inspired by nature [ 8–12 ], have focused on superhydrophobic surfaces to minimize the ice-solid contact [ 13–17 ] and liquid-infused surfaces to introduce a thin fluid layer between the ice and the substrate [ 18–22 ]. However, these methods may present new challenges: superhydrophobic surfaces are structurally fragile, while liquid-infused surfaces risk losing their liquid medium. Figure 1. Design strategy of the TSDS. (a) and (b) Schematics of de-icing processes from the high-/low-modulus surface by shear stress. (c) Deformation of the mismatched-modulus surface as a shear force applied on the ice. In the enlarged image on the right, deformation causes the transformation from shear stress into peel stress at localized regions, resulting in multiple peeling sites generated at the ice-solid interface. (d) 3D schematic diagram of the de-icing process on the TSDS. (e) Ice-adhesion strength measured for three types of surfaces. An alternative effective way to reduce ice adhesion is to introduce a soft layer that promotes cavitation at the interface [ 23–26 ]. From the viewpoint of fracture mechanics, the ice-adhesion strength can be estimated by \n (1) \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{eqnarray*}\n{\\tau _{{\\mathrm{ice}}}} = \\sqrt {\\frac{{E^*G}}{{\\pi l \\Lambda }}},\n\\end{eqnarray*}\\end{document} \n where E* is the apparent elastic modulus, G is the material surface energy, l is the crack length on the ice–solid interface and ᴧ is a non-dimensional constant that is affected by the geometric configuration of the crack [ 23 ]. In terms of the stress state, shear stress transforms into a peeling force due to deformation of the soft substrate at the front end of the cavity (Fig. 1b ). The peeling force enables the separation of two adhered objects with less effort compared with shearing force, resulting in a significant reduction in the ice adhesion ( Video S1 and Table S1 ). Additionally, the deformation of the elastic material promotes the generation of more crack sources at the ice-solid interface, which increases l . The soft property of the substrate facilitates the ice shedding, yet removing ice from a surface with a low modulus may lead to stick-slip motion (Fig. 1b and Video S2 ), as evidenced by the fluctuating shearing curve shown in Fig. 1e . The Schallamach wave, associated with stick-slip movement, nucleates due to the buckling instability of the elastic surface [ 27 ]. During the de-icing process, trapped air cavities propagate as pulses along the ice-solid interface. The detached interface reattaches, causing the ice to slip continuously along the surface [ 28 ]. For surfaces with a modulus that is too low, the stick-slip motion increases the energy consumption for de-icing and the low mechanical properties limit their application, especially in harsh service environments. Increasing the crack length or number of crack initiation sites could effectively reduce ice-adhesion strength, but achieving this is challenging. When water freezes and transitions from liquid to solid, the ice shape adapts to the morphology of the solid surface, causing cracks to be eliminated during the phase-change process. Consequently, the challenge persists in designing and fabricating durable de-icing materials with crack sources that perform reliably under practical conditions. Recent attempts to use prefab cavitation by integrating rigid components into soft layers [ 24 ] or the soft phase is wrapped in the hard phase [ 23 , 25 , 26 ] have shown promise in reducing ice-removal energy. However, these methods are constrained by limited crack initiation sites and reduced durability in practical applications. The design and fabrication of durable de-icing materials that function effectively under harsh conditions remain significant challenges in this field. Here, we present a design strategy and a versatile approach to actively transform the stress state at the ice-solid interface by creating a tough-skin de-icing surface (TSDS). This design features a modulus mismatch between a thin, hard top film and a soft substrate (Fig. 1c and d ). Inspired by human skin, in which the soft dermis and subcutaneous tissue are encased by the protective epidermis, our TSDS mimics this natural structure. When subjected to external forces, skin deforms and folds (Fig. 1d ). Similarly, in our design, wrinkles form on the surface due to the instability of the tough skin under the shear stress exerted by the ice. These wrinkles initiate cracks at the interface and the high modulus of the top film promotes brittle fracture, effectively preventing the stick-slip effect that is typically caused by the soft substrate. The outcome significantly reduces the energy required for ice removal by effectively managing disruptions at the ice-solid interface (Fig. 1e ). We show the mechanism of the wrinkles-induced interfacial crack boosting in two length scales. The tough-skin coating exhibits ice adhesion of <10 kPa. Leveraging the hard skin system, this de-icing material exhibits excellent durability across a series of tests. Finally, we demonstrate the applications of this strategy for mitigating the impacts of ice accretion in various systems.",
"discussion": "RESULTS AND DISCUSSION Design strategy of TSDS Our design strategy, illustrated in Fig. 1d , controls the surface instability between a thin, high-modulus film and a low-modulus-compliant substrate ( Video S3 ). This instability results in a wrinkled pattern, the characteristics of which can be tailored by adjusting the modulus ratio and film thickness. Wrinkling in thin films on elastomeric substrates due to mechanical stresses is a well-studied phenomenon [ 29 , 30 ]. Here, we show that these surface wrinkles concentrate at the rim of the ice and weaken the interface adhesion strength (to <10 kPa), as shown in Figs 1d and 2a . Figure 2. Mechanism of wrinkle generation on the TSDS and impact on ice-adhesion strength. (a) Photograph depicting the wrinkles invading the ice-solid interface upon shearing (top view and bottom view in the enlarged image). Pictures on the bottom display the resulting wrinkles on surfaces with parylene layer thicknesses of 1.2, 1.9 and 23.7 μm, respectively. (b) Contour map of the critical wave number of wrinkles as a function of the thickness of the parylene layer and the ratio of the moduli of the two layers. E f and E s represent the modulus of the top film and the substance, respectively. (c) A plot of the work of de-icing as a function of the parylene thickness of the peeling de-icing materials. The curves in the inset figures indicate shearing curves of de-icing. (d) Critical wave numbers and the maximum shear stress on the wrinkles as a function of the thickness of the parylene layer. It is commonly believed that peeling stress is particularly damaging for bonded structures and significantly reduces their load-bearing capacity ( Fig. S1 and Table S1 ) [ 31 ]. The soft substrate, due to the deformation of the material, induces the peeling effect at the interface of the cavitation [ 32 ]. Compared with soft substrates that use cavitation to weaken the ice-substrate interface, the wrinkles induced by surface instability offer a more effective method. Firstly, surface instability is universal when mechanical stress is applied to the top film, leading to immediate cavitation initiation upon the application of shear force to the ice, unlike soft substrates that require a certain degree of deformation to initiate cavitation. Secondly, the hard-modulus top surface avoids the viscoelastic properties that are typical of soft surfaces, thereby preventing the surfaces from sticking back together, i.e. Schallamach wave. To validate the proposed design strategy, we created a model surface with a thick, soft substrate made from polydimethylsiloxane (PDMS, CA = 109.5 ± 4.5°) and a thin hard top layer from parylene (mono-chlorinated poly- p -xylylene [ 33 ], CA = 102.2 ± 1.4°). The high-modulus layer (parylene C) was deposited onto the PDMS film by using a parylene-deposition system. The preparation details can be found in the Methods. The modulus of the PDMS can be tuned from 0.04 to 8.63 MPa ( Fig. S2 ). Parylene was chosen as the thin film for the model surface due to several key advantages: (i) it has a high modulus (in the range of 2.5–3.0 GPa [ 34 ]) and low surface energy, (ii) its film thickness can be precisely tuned from nanometers to micrometers and (iii) it provides strong adhesion to the PDMS substrate [ 35 ], preventing their separation during de-icing processes. Figure 1e shows the ice-adhesion strength measured from the hard, soft and TSDS (see Methods for detailed testing and set-up, and Figs S3 and S4 ). The TSDS ( τ = 7.1 ± 1.8 kPa) demonstrates significantly lower ice adhesion compared with both the pure parylene surface ( τ = 399.9 ± 75.3 kPa) and the unmodified PDMS surface ( τ = 18.5 kPa). Mechanism of wrinkle-induced reduction in ice adhesion by TSDS We first explored how the mismatched modulus impacted the ice-solid interfaces. Figure 2a depicts the state of the surface before the ice cube detaches from the TSDS. The ice-substrate contact line is encased in wrinkles, which predominantly form in front of and around the ice cube. During the act of pushing the ice cube, these wrinkles invade the ice-substrate interface, as shown in the insect of Fig. 2a . The characteristics of the wrinkles, such as their wavelength, amplitude and number, are significantly influenced by the thickness of the film (Fig. 2a bottom, and Figs S5 and S6 ). It is intuitive that the greater the number of wrinkles, the more significant their influence on the initiation of cracks and thereby the breakdown of the interface. This drives us to study the characteristics of surface wrinkles. Previous research has demonstrated that the properties of wrinkles in film-substrate systems can be controlled by modifying the modulus ratio ( E f /E s , where E f and E s represent the modulus of the hard film and the soft substrate, respectively) and the film thickness ( h ) [ 29 , 30 ]. The critical number of wrinkles, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${k_{\\mathrm{c}}}$\\end{document} , can be approximated by \n (2) \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{eqnarray*}\n{k_c}\\,\\,\\sim \\,\\,\\frac{1}{h}{\\left( {\\frac{{3E_s^*}}{{E_f^*}}} \\right)^{\\frac{1}{3}}},\n\\end{eqnarray*}\\end{document} \n \n (3) \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{eqnarray*}\nE_s^{\\mathrm{*}} = {\\mathrm{\\,\\,}}\\frac{{{E_s}}}{{( {1 - v_s^2} )}},\n\\end{eqnarray*}\\end{document} \n \n (4) \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{eqnarray*}\nE_f^{\\mathrm{*}} = {\\mathrm{\\,\\,}}\\frac{{{E_f}}}{{( {1 - v_f^2} )}},\n\\end{eqnarray*}\\end{document} \n where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${E^*}$\\end{document} represents the plane strain elastic modulus and ν the Poisson's ratio. Figure 2b presents a contour map showing the critical number of wrinkles as a function of the film thickness and modulus ratio ( E f /E s ) ( Fig. S7 ). The parylene-PDMS system tends to have a large number of wrinkles when E f /E s is <10 4 and the film thickness is <10 μm, suggesting abundant cavitation initiates. We evaluated the ice-adhesion strength by varying the number of wrinkles, which is controlled by changing the thickness of the parylene layer while keeping the modulus of the PDMS substrate constant. Figure 2c shows the work of de-icing and the ice-adhesion strength at different film thicknesses. Contrary to our previous prediction, the TSDS with a moderately mismatched modulus (e.g. parylene layer thickness of ∼6.1 μm, as shown in the inset of Fig. 2c ) exhibited the lowest ice-adhesion strength, despite the fact that excessively thin films may develop numerous wrinkles. The results also suggest that thinner films require additional energy for complete ice detachment. The additional energy required could be attributed to the mode of interfacial fracture. Specifically, the de-icing curve for a TSDS with a 50-μm parylene layer shows characteristics that are akin to brittle fracture. In contrast, a TSDS with a 0.7-μm film exhibits traits that are more typical of ductile fracture—a gradual process in which plastic deformation and crack propagation occur simultaneously, continuously consuming a significant amount of energy [ 36 ]. To clarify the impact of wrinkles on adhesion strength during the de-icing process, we used a finite-element (FE) model to simulate the stress distribution within the wrinkles across different film thicknesses. We initially varied the film thickness from 1.8 to 24 μm and the resulting wrinkle formation closely matched that of the experimental data, as shown in Fig. 2d . Wrinkle count and the simulated peak stress distribution are plotted against the film thickness. Notably, as the film thickness increases, the stress concentration rises, showing a trend that is opposite to that of wrinkle formation. Moreover, the underlying mechanism of wrinkles formation is not affected by ice-cube size or shape. It should be noted that the out-of-plane amplitude of the wrinkles also plays a key role in initiating cracks at the ice-substrate interface. The interface between the ice and substrate, where wrinkles meet the flat ice surface, is particularly vulnerable to disruption. Larger out-of-plane wrinkles are more likely to cause tearing at the ice-substrate interface. In essence, while thinner films produce more wrinkles, the smaller out-of-plane amplitude and reduced stress concentration in these wrinkles are insufficient to disrupt the ice-substrate interface (see Fig. 2c and Fig. S8 ). Additionally, the ice adhesion could be further reduced if the active method is adopted to generate the wrinkles ( Fig. S9 ). The synergetic effect of wrinkles at two length scales on the interfacial crack boosting The measurement of ice adhesion on the TSDS suggests that surface instability-induced wrinkles significantly impact ice adhesion. This leads us to consider whether pre-generated wrinkles could further disrupt the interface and initiate cracks (Fig. 3a ). To test this hypothesis, we prepared TSDS with pre-generated micro-wrinkles (termed as micro-wrinkled TSDS in the following discussion). We employed the wrinkles with a Turing pattern that was generated during the deposition process of the parylene film, as detailed in Fig. S10 (refer to Methods for fabrication specifics). Wrinkles with a Turing pattern are well documented in thin-film preparation through surface instability [ 37–41 ]. As shown in the insert of Fig. 3b , the isotropic Turing pattern was uniformly distributed on the surface. It should be noted that the Turing pattern was employed due to its isotropy, which eliminates the influence of the applied stress direction on the adhesion strength ( Fig. S11 ) [ 42 ]. The characteristics of this pattern can be easily modified by the moduli of the PDMS, as illustrated in Figs S12 and S13 . Compared with macro-wrinkles that are generated by shear stress, those with dual-scale peeling sites exhibit a significant reduction in ice-adhesion strength, dropping to <10 kPa (Fig. 3b and c , and Video S4 ). Figure 3. Optimization of designing micro-wrinkled TSDSs. (a) Schematic showing the synergetic effect of macro- and micro-wrinkles on the ice adhesion. (b) De-icing curves of the TSDS and micro-wrinkled TSDS, respectively. Insert is the image of the Turing micro-wrinkles taken from white-light interference microscopy. (c) Ice-adhesion strength as a function of the modulus of PDMS (substrate) for the two surfaces. (d) Photos of the finite-element models displaying stress distribution upon shearing on the two types of surfaces. The top is the wrinkled PDMS surface with an amplitude of 2 μm and the bottom is the micro-wrinkled TSDS with the same amplitude. (e) A plot of the ice-adhesion strength as a function of the number of micro-wrinkles per area. (f) Surface with a striped pattern composed of TSDS (T) and micro-wrinkled TSDS (M) regions. Micro-wrinkled TSDS regions are detached earlier than TSDS regions. The area with a dotted line indicates the detached interface. It is commonly believed that the introduction of roughness, such as wrinkles, would increase ice adhesion due to the increased ice-substrate contact area. However, it is surprising to observe that wrinkles significantly decrease ice adhesion in the micro-wrinkled TSDS system. To understand the mechanism behind this, we developed an FE model to simulate the stress distribution on surfaces with and without micro-wrinkles under shearing conditions. Figure 3d illustrates the comparison of stress distributions, showing a significantly high stress concentration on the micro-wrinkled TSDS. On the other hand, micro-wrinkled soft surfaces exhibit almost no stress concentration under shearing conditions. The concentration of the shear stress is attributed to the synergistic relationship between the micro-wrinkle and the mismatched modulus. To validate these findings, we measured the ice adhesion on constant- and mismatch-modulus substrate with the same micro-wrinkle to elucidate the role of the micro-wrinkle and mismatched modulus, as detailed in the Methods ( Figs S15 and S16 ). Fig. S17 shows that a significant reduction in ice-adhesion strength is only achieved when both micro-wrinkles and modulus mismatches are present. Conversely, the presence of micro-wrinkles alone not only fails to reduce adhesion strength, but may even increase it. This clearly demonstrates the synergistic effect between micro-wrinkles and mismatched-modulus macrostructures. We then investigate the impact of the wrinkles size (number) on the ice-adhesion strength (Fig. 3e ). Different numbers of micro-wrinkled samples are fabricated via a molding process ( Fig. S15 ). For a smaller size, the stress concentration is higher, resulting in a smaller ice adhesion. To make the contrast more obvious, we prepared a composite surface that consisted of striped TSDS (T) and micro-wrinkled TSDS (M) regions ( Fig. S18 ; see Methods for details on fabrication). Video S5 and Fig. 3f indicate that the micro-wrinkled TSDS regions are detached first, even though they are surrounded by TSDS, which means micro-wrinkled TSDS regions are unable to generate macro-wrinkles on either side. On the contrary, no interface fracture has been observed in the TSDS, and even complete separation was completed in the micro-wrinkled TSDS region. Applicability and application of micro-wrinkled TSDSs As de-icing materials are commonly used in the real world for complex freezing conditions, we tested the de-icing properties of micro-wrinkled TSDSs under common icing conditions, including micro-droplets, bulk water, high humidity, rime ice and clear ice (Fig. 4a ). ‘Bulk water’ means adding water to the surface and freezing it in situ , which is a static freezing method. The icing methods that are not specified in the article are all performed in this way. The ‘high humidity’ is a condition with ∼90% relative humidity ( Figs S19 and S20 ; see Methods for details on the experiment). The ‘rime ice’ and ‘clear ice’ icing conditions are achieved in an icing wind tunnel (see Methods for details on the experiment, Fig. S21 and Table S2 ). The results display that micro-wrinkled TSDSs show a great de-icing effect ( τ ice < 10 kPa) under the mentioned conditions. Furthermore, when the icing temperature is varied from –10°C to –50°C, there is a limited effect on the adhesion strength of the micro-wrinkled TSDSs ( Fig. S22 ). These results indicate the micro-wrinkled TSDSs have excellent performance stability. The mechanical stability was further examined by using a series of tests. Figure 4b shows that the micro-wrinkled TSDS maintained an ice-adhesion strength of <10 kPa even after 100 icing-de-icing cycles and it is supposed that the high-modulus top layer performs as a robust crust to protect the soft inside. It also can be proved by repeating the tape-peeling test >500 times ( Fig. S23 ). In addition, other severe durability tests were conducted, including ultraviolet aging ( Fig. S24 ), resistance to chemical corrosion (salt spray atmosphere with 5 wt% of NaCl solution for 31 days, Fig. S25 ) and the antifouling test ( Fig. S26 ). Our micro-wrinkled TSDSs maintain great de-icing properties under these conditions, which indicates that the micro-wrinkled TSDSs have the potential to be applied in harsh environments. Figure 4. Applicability and application of micro-wrinkled TSDSs. (a) Ice-adhesion strength measured for micro-wrinkled TSDSs under different freezing conditions. (b) Influence of icing and de-icing cycles on de-icing performance. Inset shows the shedding of ice by gravity. (c) Shear strength and tensile strength of three typical surfaces made of micro-TSDS, SLIPS and PDMS, respectively. (d) Adaptability of the TSDS strategy on different engineering materials. Considering the practical application conditions of de-icing materials, not all cases are achieved by applying shear forces for de-icing. The ice accretion should be able to detach spontaneously from the desired de-icing materials through natural forces (gravity, wind) or as little energy as possible. Both the shear strength and the tensile strength of different types of low-adhesion-strength surfaces have been measured ( Fig. S27 ), including those of the micro-wrinkled TSDS, slippery substrate (SLIPS) and soft substrate. As shown in Fig. 4c , the tensile strength of all the material systems shows an increase compared with the shear strength. However, the micro-wrinkled TSDS expresses the smallest difference between these two types of strength due to the same mechanism of micro-/macro-wrinkles. A slippery surface provides a small shear strength due to the oil at the interface between the ice and the substrate, although the capillary force of the oil makes the tensile strength high. As for the soft substrate, the same trend was observed with a tensile strength that was much higher than the shear strength. This is majorly attributed to less crack initiation by the tensile stress at the interface. On the contrary, the micro-wrinkled TSDS has a relatively low tensile strength (15.4 ± 0.9 kPa). To verify the universality of the mismatched-modulus strategy, we demonstrated the reduction of ice adhesion with multiple types of materials. Different kinds of micro-wrinkled TSDSs were fabricated, including PVDF (polyvinylidene difluoride)-micro-wrinkled TSDS (elastic modulus of PVDF is 2.5 GPa [ 43 ]), PE (polyethylene)-micro-wrinkled TSDS (elastic modulus of PP is ∼1 GPa [ 44 ]), PP (polypropylene)-micro-wrinkled TSDS (elastic modulus of PP is 1.14–1.55 GPa [ 45 ]), by using a hot press ( Fig. S16 ; see Methods for details). The fabrication of micro-wrinkles on surfaces is well established, including methods such as thermal instability, hot pressing, photoinduction and solvent induction [ 29 , 30 , 37 , 38 , 46 , 47 ], many of which are suitable for large-scale production. Figure 4d shows the measured ice-adhesion strengths for several high-modulus materials and the corresponding micro-wrinkled TSDSs. These materials all achieve the effect of efficiently reducing ice-adhesion strength through the design principle of micro-wrinkled TSDS. To evaluate the application potential of micro-wrinkled TSDSs, we investigated ice shedding by centrifugal force on a simulated wind turbine ( Figs S28–S30 and Video S6 ; see Methods for details on surface preparation). Ice on the micro-wrinkled TSDSs detached automatically at relatively low centrifuge velocities, with line speeds of <30 m/s, while ice remained adhered to other surfaces, such as superhydrophobic and metal surfaces, even at 40 m/s. Additionally, self-shedding of ice under gravity was demonstrated (inset of Fig. 4b , Fig. S31 and Video S7 ; see Supplementary Methods for details). A 1 m × 0.7 m micro-wrinkled TSDS was fabricated and fixed to a larger aluminum sheet, allowing a 0.9 m × 0.6 m ice layer to form at –10°C in a walk-in freezer. Once fully frozen, the ice detached completely when the aluminum plate was tilted upright ( Video S8 ; see Supplementary Methods for details). The spontaneous shedding of ice of various thicknesses suggests that the micro-wrinkled TSDS surface may facilitate automatic de-icing through natural forces. To summarize, the micro-TSDSs demonstrate excellent icephobic properties and durability under laboratory conditions, as well as in preliminary tests. However, given the complexity of real-world freezing conditions and the need for efficient de-icing, it is important to explore the combination of the micro-TSDS with an active anti-icing system, which may amplify the benefits of both low adhesion and rapid crack propagation, enabling more effective ice removal."
} | 7,255 |
21304454 | PMC3182659 | pmc | 2,132 | {
"abstract": "Many microbial cells have the ability to form sessile microbial communities defined as biofilms that have altered physiological and pathological properties compared to free living microorganisms. Biofilms in nature are often difficult to investigate and reside under poorly defined conditions 1 . Using a transparent substratum it is possible to device a system where simple biofilms can be examined in a non-destructive way in real-time: here we demonstrate the assembly and operation of a flow cell model system, for in vitro 3D studies of microbial biofilms generating high reproducibility under well-defined conditions 2,3 . The system consists of a flow cell that serves as growth chamber for the biofilm. The flow cell is supplied with nutrients and oxygen from a medium flask via a peristaltic pump and spent medium is collected in a waste container. This construction of the flow system allows a continuous supply of nutrients and administration of e.g. antibiotics with minimal disturbance of the cells grown in the flow chamber. Moreover, the flow conditions within the flow cell allow studies of biofilm exposed to shear stress. A bubble trapping device confines air bubbles from the tubing which otherwise could disrupt the biofilm structure in the flow cell. The flow cell system is compatible with Confocal Laser Scanning Microscopy (CLSM) and can thereby provide highly detailed 3D information about developing microbial biofilms. Cells in the biofilm can be labeled with fluorescent probes or proteins compatible with CLSM analysis. This enables online visualization and allows investigation of niches in the developing biofilm. Microbial interrelationship, investigation of antimicrobial agents or the expression of specific genes, are of the many experimental setups that can be investigated in the flow cell system.",
"discussion": "Discussion We have demonstrated a flow cell system that represents a powerful tool in biofilm investigations. Combined with 3D imaging by confocal microscopy, the system has a range of advantages in comparison to other methods of analyzing microbial biofilms by means of more traditional microscopic techniques. This system allows 3D visualization of living microbial biofilm communities without disturbance of the community. Light microscopy will not provide detailed information about niches of the biofilm and while electron microscopy provides nanoscale resolution of the biofilm, it does not allow live cell imaging. Using the described flow channel system we have previously elucidated the spatial distribution of bacterial cells sensitive to several antibiotics 5-8 (Figure 4a), distribution of extracellular compounds, e.g. DNA 9-11 and, the distribution of motile and non-motile cells of the same species within a bacterial community 4,6,9 (Figure 4c). We envision that the flow cell system can be used to study aspects of yeast biofilms. This may be the spatio temporal distribution of yeast biofilm in response to environmental factors such as fungicides as well as identification of genes involved in yeast biofilm development. Though yeast is not known to differentiate into motile and non-motile cells, other aspects of biofilm diversification may be studies such as the morphological shift from yeast to pseudohyphal cells and the shift from haploid to diploid cells. We have shown a system that comply with several microbial species and will work with several staining techniques. A variety of different staining probes and fluorescent proteins, such as GFP, enable specific niche investigations in the developing biofilm and is an efficient tool in analyzing the effect of antimicrobial agents or other environmental factors. The information that can be gained is very detailed (Figure 4) and features in the biofilm can be quantified with computer programs such as COMSTAT 12,13 . Overall, the most critical aspect of the protocol is the fact that it is a time-consuming process. It is also a limitation that the cells need to be able to grow on a non-fluorescent, transparent surface. Since the biofilm formed is analyzed using a confocal microscope, the depth that can be investigated is limited to a few hundred micrometres 14 .There are further technical limitations inherent in the design: the system is not suited for high throughput screening, as an experienced researcher can handle at most about 15 channels per experiment, which in turn can take several days to prepare. However, antibiotics or mutants that are considered relevant for biofilm studies can initially be mass screened with other methods such as crystal violet staining before the most interesting candidates are transferred to the flow cell system. The cover glass sheets are very thin and break easily, and care should be taken when handling the systems. In addition the tubing should be examined daily during the run of an experiment; as considerable \"back-growth\" in the inlet tubes just upstream of the flow cells can occur. Such contamination can be solved by removing several centimeters of silicone tube from the inlet side of the flow cells, using sterile technique. Figure 4. a) 4 day old PAO1 - GFP biofilm treated for 24h with Colistin and Propidium iodide for dead staining (red stain) b) 3D presentation of a three day old P. aeruginosa PAO1 ( P. aeruginosa wild type) - GFP biofilm 6 c) 3D picture presentation of a PAO1 - CFP pilA mutant (blue) with an PAO1 wild type YFP (yellow) d) 5 day old PAO1 - GFP biofilm presented as a 3D picture e) 26 h S. cerevisiae (PTR3 mutant in CEN.PK background) biofilm stained with Syto-9 15 ."
} | 1,395 |
35434553 | PMC9010633 | pmc | 2,133 | {
"abstract": "Summary Feeding the world’s growing population requires continuously increasing crop yields with less fertilizers and agrochemicals on limited land. Focusing on plant belowground traits, especially root-soil-microbe interactions, holds a great promise for overcoming this challenge. The belowground root-soil-microbe interactions are complex and involve a range of physical, chemical, and biological processes that influence nutrient-use efficiency, plant growth and health. Understanding, predicting, and manipulating these rhizosphere processes will enable us to harness the relevant interactions to improve plant productivity and nutrient-use efficiency. Here, we review the recent progress and challenges in root-soil-microbe interactions. We also highlight how root-soil-microbe interactions could be manipulated to ensure food security and resource sustainability in a changing global climate, with an emphasis on reducing our dependence on fertilizers and agrochemicals.",
"conclusion": "Concluding remarks and perspectives The major challenge in feeding the world’s growing population is to continuously increase crop yields with less fertilizers and agrochemicals on limited land. A systematic understanding and manipulation of the root-soil-microbe interactive processes to maximize the biological potential for improving crop yields and resource-use efficiency is a credible solution to meet this challenge. However, such understanding is reliant on considering the multi-directional and dynamic complexity of root-soil-microbe interactions. Future studies should comprehensively consider plant, soil, microorganisms, and their interactions to seek optimal ways of rhizosphere manipulation. In particular, non-invasive, real-time and in situ visualization and characterization of rhizosphere processes are needed urgently to identify key components involved in amalgamating the multi-directional and dynamic interactions in the rhizosphere. Interdisciplinary approaches are needed to integrate plant biology, genetics, soil science, microbial ecology, and breeding to select highly efficient varieties with excellent belowground traits based on a systematic understanding of the rhizosphere, supported by optimal nutrient management strategies and cultivation techniques, to achieve the global goal of food security and resource sustainability.",
"introduction": "Introduction Global population growth and resource depletion place an existential emphasis on improving food security and environmental health. Producing more food using less nutrients and water on less land in the future will require us to develop new and effective agricultural technologies. Since the synthesis of ammonia and the advent of modern chemical industry, fertilizers have made a great contribution to increasing grain production ( Erisman et al., 2008 ). FAO statistics show that as early as 2012 the world’s consumption of synthetic nitrogen (N) fertilizers reached 100 million tons per year, and total energy consumption in agriculture peaked at 8,728 trillion joules per year. Even though the application of synthetic fertilizers supports the continuous increase of grain yield worldwide, it also may cause serious environmental problems such as soil acidification, air pollution and water eutrophication ( Guo et al., 2010 ; Savci, 2012 ). Attaining food security, resource efficiency, and environmental health has become a major challenge to the sustainable development of global agriculture and is also the key component of the future agricultural science and technology revolution. Achieving the goal of “producing more food with fewer resources” requires harmonizing nutrient-use efficiency, crop productivity and environmental health ( Chen et al., 2014 ; Shen et al., 2020 ). The rhizosphere, as the interface between roots and soil, is the gateway for nutrients and water to enter the plant from the soil ( Curl and Truelove, 2012 ; Wang and Shen, 2019 ; Zhang et al., 2010 ). Roots absorb nutrients and water from the soil and exert influence on adjacent soil through rhizodeposition ( Curl and Truelove, 2012 ). The roots of neighboring plants directly or indirectly affect the interaction processes between target plants and soil ( Callaway and Li, 2019 ; Zhang et al., 2019a ). Soil microorganisms also actively participate in root-soil interactions, with the soil-microbe and microbe-microbe interactions frequently regulated by roots ( Berendsen et al., 2012 ; Hakim et al., 2021 ). The rhizosphere components (soil, roots, microorganisms, and their interactions) can all be manipulated or engineered to increase efficiency of nutrient resource use by plants ( Ahkami et al., 2017 ; Dessaux et al., 2016 ; Hakim et al., 2021 ; Kumar and Dubey, 2020 ; Ryan et al., 2009 ; Zhang et al., 2010 ), but the extensive spatial and temporal variability makes achieving such manipulations uncertain. Root management (or rhizosphere engineering) can maximize the biological potential of roots by optimizing root-soil-microbe interactions and ultimately reduce our reliance on fertilizers and agrochemicals, but this is contingent on our understanding of the complex rhizosphere interactions ( Hakim et al., 2021 ; Wang and Shen, 2019 ; Zhang et al., 2010 ). Addressing the global challenges of food insecurity exacerbated by climate change and population growth through better understanding and manipulation of rhizosphere processes will be one of the most important scientific frontiers of the forthcoming decades ( Wang et al., 2020b )."
} | 1,376 |
35630952 | PMC9148095 | pmc | 2,134 | {
"abstract": "As the amount of data has grown exponentially with the advent of artificial intelligence and the Internet of Things, computing systems with high energy efficiency, high scalability, and high processing speed are urgently required. Unlike traditional digital computing, which suffers from the von Neumann bottleneck, brain-inspired computing can provide efficient, parallel, and low-power computation based on analog changes in synaptic connections between neurons. Synapse nodes in brain-inspired computing have been typically implemented with dozens of silicon transistors, which is an energy-intensive and non-scalable approach. Ion-movement-based synaptic devices for brain-inspired computing have attracted increasing attention for mimicking the performance of the biological synapse in the human brain due to their low area and low energy costs. This paper discusses the recent development of ion-movement-based synaptic devices for hardware implementation of brain-inspired computing and their principles of operation. From the perspective of the device-level requirements for brain-inspired computing, we address the advantages, challenges, and future prospects associated with different types of ion-movement-based synaptic devices.",
"conclusion": "5. Conclusions The development of synaptic devices for brain-inspired computing has progressed in the last few years. In this review, we discussed the fact that ion-movement-based synaptic devices of different types can be used to realize brain-inspired computing. In addition, we reviewed the strengths and weaknesses of each of these synaptic devices when applied to ANNs in brain-inspired computing. However, each device has remaining issues to be resolved for fully satisfying the specifications of a synaptic device for ANN: (1) linearity and cycle-to-cycle variation for a filamentary system based on cation and anion movement; (2) linearity and device-to-device variation for a cation-movement-based ferroelectric; and (3) dynamic range for an ion-movement-based electrochemical three-terminal device. To address these issues, various fields must be involved, from materials science to device design. In addition, synaptic devices should be optimized using circuit- or system-level simulators based on a compact model of reliability degradation for performance benchmarking and circuit design. If the challenges for each of the different types of synaptic devices are resolved, large-scale integration based on ion-movement-based synaptic devices will be realized in the near future, leading to the implementation of brain-inspired computing chips with low energy consumption, high scalability, and high processing speed. Therefore, ion-movement-based synaptic devices for brain-inspired computing continue to represent a potentially attractive solution to the problem of highly parallel and distributed processing of massive amounts of data, and thus can be expected to remain an active area of research.",
"introduction": "1. Introduction Explosively increasing data set sizes in artificial intelligence (AI) and the Internet of Things have resulted in us facing limitations in energy efficiency and the challenges of the von Neumann bottleneck approaching the end of Moore’s law [ 1 , 2 , 3 , 4 , 5 ]. In more detail, the AI algorithm that runs on the complementary metal oxide semiconductor (CMOS)-based von Neumann hardware seems to be somewhat inefficient [ 6 ], since: (1) the separation of processor and memory causes heavy data traffic between devices, especially in data-intensive tasks; (2) CMOS uses a “0” and “1” binary logic system rather than a gradual weight change; (3) the connections of transistors in silicon chips are usually in two dimensions; (4) CMOS-based computers consume a thousand times as much energy as the human brain to perform the same task [ 6 , 7 ]. For example, a supercomputer (IBM Watson) [ 8 ] has 2880 computing cores (10 refrigerators’ worth in size and space) and requires about 80 kW of power and 20 tons of air-conditioned cooling capacity, while the human brain occupies a space of less than 2 l and consumes low power, of the order of 10 W [ 9 , 10 ]. Additionally, if data storage and communication continue to increase at the current rate, the total energy consumed by binary operations using CMOS will reach ~10 27 J in 2040, surpassing the total energy produced worldwide [ 11 , 12 ]. In order to improve the performance of computing systems in the so-called “big data” era [ 13 ], it is necessary to fundamentally change the way computing is executed [ 14 ]. We need to shift to a data-centric paradigm rather than a computer-centric one [ 14 ]. The growth of computational power, the availability of big data, and the rapid development of training methods have resulted in significant advances in data-centric computing methods, such as the artificial neural network (ANN), which is inspired by the co-location of logic and memory, tolerance to local failures, hyper-connectivity, and parallel processing present in the human brain [ 12 , 15 , 16 ]. The human brain is a massively parallel computing structure that processes input information by synaptic transmission. Each synaptic event consumes only around 1–10 fJ [ 5 , 17 ]. The hardware in brain-inspired computing architecture is required to mimic stochastic behaviors by introducing a new logic device such as an orthogonator gate and to physically emulate synapses in the human brain at the small circuit or device levels, consuming significantly reduced energy [ 12 , 18 , 19 , 20 , 21 , 22 , 23 , 24 ]. Recently, synaptic devices based on various types of resistive switching devices have been utilized for brain-inspired computing [ 25 , 26 , 27 , 28 , 29 , 30 ]. Brain-inspired computing based on synaptic devices has achieved particular progress from ion-movement-based resistive switching mechanisms such as cation-movement-based filaments [ 31 , 32 , 33 , 34 , 35 , 36 ], anion-movement-based filaments [ 37 , 38 , 39 , 40 , 41 , 42 , 43 ], cation-movement-based ferroelectric polarization reversal [ 44 , 45 , 46 , 47 , 48 , 49 ], and ion-movement-based electrochemical electrolytes [ 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ]. These ion-movement-based resistive switching devices can show a gradual change in conductance and nonvolatile characteristics, which have not been implemented in Mott-insulator-based resistive switching devices. Resistive switching based on the phase transition of Mott insulators under an electric field shows an abrupt change in conductance and volatile behaviors, which are suitable for neuron devices [ 58 , 59 , 60 ]. In this review, we summarize in detail the different ion-movement-based mechanisms and discuss the advances in the development of ion-movement-based resistive switching devices for artificial synaptic elements. In addition, we discuss the challenges that need to be addressed in future research on synaptic devices towards developing brain-inspired computing systems."
} | 1,741 |
34712914 | PMC8529082 | pmc | 2,135 | {
"abstract": "Summary Superhydrophobic coatings have tremendous potential for protecting porous structures from corrosion. However, the weak adhesion and poor abrasion resistance have long been challenges for their real-life applications. Inspired by tree roots, we prepared a robust superhydrophobic coating by spraying fluorinated nanodiamonds (FNDs) on a permeable epoxy coating. The epoxy can not only coat the surface but also permeate deeply inside a porous substrate and consolidate in situ as tree roots in soil. Thus, the structure is thoroughly reinforced where the pull-off strength reaches 9.4 MPa for concrete. On the other hand, the surface is covered with immobilized FNDs, forming a superhydrophobic surface. Thanks to the ultra-hard FNDs, the coating surface has high abrasion resistance and its superhydrophobicity holds even after 100 abrasion cycles. Moreover, it exhibits self-cleaning, anti-icing, and anticorrosion performance. It is promising in protecting various porous structures such as concrete, wood, and untreated corroded steel.",
"introduction": "Introduction Porous materials such as concrete, wood, and textiles are widely used in our life, where the porous structure often leads to corrosion. For example, concrete that has been used in roads, bridges, harbors, and other civil engineering projects suffers from corrosion in its service. Once Cl − , SO 4 2− , and other ions permeate into its vacancy, they would cause corrosion of steel bars and salt crystallization swelling. These corrosive ions are carried by water with good penetrating property. Therefore, prevention of water ingress can effectively improve the durability of porous materials. Superhydrophobic coatings with remarkable waterproof ability have received much attention for protecting porous structures and other facilities ( Feng and Jiang, 2006 ; Gao and Jiang, 2004 ; Blossey, 2003 ; Lu et al., 2015 ; Jung et al., 2012 ; Zhang et al., 2008 ; She et al., 2013 ; Li et al., 2019 ; Xue et al., 2011 ). Generally, a superhydrophobic surface can be constructed with low-surface-energy materials with micro- and nanoscale architectures, where templating, spraying, etching, and electrochemical deposition have been used ( Wang et al., 2016 ; Li et al., 2014 ; Gong et al., 2016 ; Xue et al., 2014a , 2014b ; Tesler et al., 2015 ). However, the low-surface-energy materials weakly bond to the substrates, and thus the surface structures are readily damaged or corrosive. The weak adhesion and poor abrasion resistance become an obstacle to their large-scale applications. To solve the problems, adhesive layers were added, discrete microstructures were randomly introduced to bear abrasion, the surface structures were renewed, but the robustness was not significantly improved ( Wang et al., 2020 ). In nature, trees can grow and withstand the storms because their roots are deeply and tightly consolidated in soils. In this study, inspired by tree roots, a superhydrophobic coating has been prepared using fluorinated nanodiamonds (FNDs) and epoxy with reactive solvent of furfural and acetone ( Scheme 1 ). The epoxy coating is first coated on porous structure (e.g., concrete), and FND suspension is sprayed on the incompletely cured epoxy to fabricate a superhydrophobic surface (designated as Ep-FND-S). The epoxy coating has high permeability so that it can penetrate small pores and cracks with size from about 0.1 to 10 μm in the substrate and consolidate in situ behaving like tree roots in soil reinforcing the concrete. On the other hand, the hydrophobic FNDs with ultra-high hardness are strongly adhered on the surface, which provides the surface not only superhydrophobicity but also abrasion resistance. For comparison, a mixture of permeable coating and FND was applied directly on concrete (designated as Ep-FND-B), which hardly permeates inside owing to its high viscosity. The schematic illustration of the difference between the two materials is shown in Figure S1 . The properties of coatings applied on mortar and other porous substrates were investigated. We attempt to develop a high-performance coating for reinforcement and protection of porous structures. Scheme 1 Schematic of fabricating a robust superhydrophobic coating for a porous structure (A) The reactions related to preparing the permeable epoxy coating. (B) The preparation of fluorinated nanodiamond (FND). (C) The procedures of preparing the superhydrophobic coating based on the permeable epoxy and FNDs.",
"discussion": "Discussion Inspired by tree roots, a robust superhydrophobic coating Ep-FND-S with self-cleaning, anti-icing, and anticorrosion properties has been fabricated to protect porous structures by a facile method. The permeable epoxy can penetrate into concrete and consolidate in situ , forming an epoxy-concrete composite. This is further supported by EDS linear scan spectra and cross-sectional morphologies of mortar coated with Ep-FND-S ( Figure S4 ). At the cross section of mortar, Si can be detected owing to its existence in the cement and standard sand that do not contain any F. For Ep, F is undetected, and Si is only detected beyond ∼50 μm, because the region of 0–50 μm consists of the epoxy coating and the region beyond 50 μm consists of the coating/mortar composite layer. As to Ep-FND-B, although F and Si should theoretically be detected in the coating, none was observed. This is because FNDs were embedded by the epoxy. F is observed in the upper layer of Ep-FND-S, and the F content gradually decreases to zero as the depth increases, indicating that the sprayed FNDs are only partly deposited in the epoxy, but mostly on surface. As a result, the concrete is significantly reinforced by the epoxy, where the adhesion strength between the concrete and epoxy is 9.4 MPa, two times higher than that of mortar control. FNDs fixed on the surface form a superhydrophobic surface with micro- and nanostructures, and it has a higher WCA (154°) and a lower sliding angle (4.5°). FNDs with superior hardness makes the surface with excellent mechanical performance possible. Ep-FND-S holds superhydrophobicity after harsh abrasion for 100 times, indicating remarkable mechanical robustness. Moreover, the coating is also able to resist cold, various contaminants, and corrosive ions. Ep-FND-S is a versatile protective coating not only for concrete but also for a variety of porous structures and objects including wood, fiber, and even untreated corroded steel. It is readily prepared by spraying nanoparticle suspension on brushed coating. The coating is promising to find applications in several fields. Limitations of the study Apart from the above breakthroughs, there are a few limitations in this study. In principle, other hard nano-fillers may also be used to fabricate such enduring superhydrophobic coatings, and this work focuses on nanodiamond. It would be interesting to utilize hard nano-fillers with other structures (e.g., layer and tube structures) and sizes. In addition, the superhydrophobic coating was prepared by a two-step (coat-spray) method in this work. It would be possible to use a one-step process if the permeation of epoxy coating can be further tuned. These will be explored in the future."
} | 1,803 |
38299118 | PMC10829482 | pmc | 2,136 | {
"abstract": "ABSTRACT Atmospheric water harvesting is an emerging strategy for decentralized and potable water supplies. However, water nucleation and microdroplet coalescence on condensing surfaces often result in surface flooding owing to the lack of a sufficient directional driving force for shedding. Herein, inspired by the fascinating properties of lizards and catfish, we present a condensing surface with engineered hydrogel patterns that enable rapid and sustainable water harvesting through the directional pumping and drag-reduced sliding of water droplets. The movement of microscale condensed droplets is synergistically driven by the surface energy gradient and difference in Laplace pressure induced by the arch hydrogel patterns. Meanwhile, the superhydrophilic hydrogel surface can strongly bond inner-layer water molecules to form a lubricant film that reduces drag and facilitates the sliding of droplets off the condensing surface. Thus, this strategy is promising for various water purification techniques based on liquid–vapor phase-change processes.",
"conclusion": "CONCLUSION In summary, we successfully incorporated nature-inspired principles into an artificial system for designing the geometry and surface properties of hydrogel fibers. The anisotropic hydrogel patterns with arch structures printed on silicate glass showed rapid and sustainable condensation for atmospheric water harvesting. By synergistically combining radial and axial droplet manipulation, randomly dispersed water droplets were directionally pumped to the HWT surface and slid swiftly with negligible drag. Consequently, the condensing sites were regenerated, facilitating effective and sustainable condensation. This strategy fully utilized the classical merits of hydrogels and is also feasible on typical heat-conducting materials such as copper and aluminum ( Fig. S22 ), making it more flexible and applicable for water purification, extraction, and energy conversion techniques related to condensation processes, including water desalination, solar water production, fog harvesting, and heating/cooling systems.",
"introduction": "INTRODUCTION Atmospheric water harvesting can potentially address the global water crisis, especially in areas lacking clean water sources [ 1 ]. Condensation is a fundamental step for water-harvesting systems and is ubiquitous in water purification and energy conversion [ 2 ]. It is an energy-intensive exothermic phase-change process involving two key steps: droplet growth and shedding. Generally, nanoscale droplets preferentially form on hydrophilic sites, which release latent heat, and grow through random cohesion between neighboring droplets [ 2 , 3 ]. However, droplet overgrowth and heat release often block condensing sites and choke sustainable condensation. Thus, condensing site regeneration is vital for water harvesting, which relies on fast droplet growth and transport [ 2 , 4 , 5 ]. Unfortunately, surface design strategies suffer from an intrinsic trade-off between these processes [ 4 ]. Conventional strategies mainly rely on (dis)ordered microstructures and superhydrophobic/philic treatment to regulate droplet movement and facilitate condensation. However, the condensing sites are sacrificed due to hydrophobicity [ 4 , 6–9 ]. Moreover, droplets must reach a critical size through coalescence to gain sufficient energy for movement, which introduces uncertainties in the trajectory. During droplet shedding, a lack of engineered pathways causes continued growth through random cohesions with smaller droplets. Amplified contact angle hysteresis, especially on the microscale, results in an insufficient driving force and condensing site flooding [ 10 ]. Therefore, surfaces capable of directional transport of micrometer droplets and possessing regenerating condensing sites are highly desirable for sustainable condensation. A promising strategy to circumvent this barrier involves creating the motion trajectory and orienting droplet movement to avoid droplet overgrowth [ 6 , 11 , 12 ]. Many bionic functional surfaces, including lotus leaves, pitcher plants, cactuses, and spider silks, have inspired micro-/nanostructure designs and wetting gradient surfaces used in different fields like water collection, printing, and drug delivery. They offer great insights into the droplet driving force resulting from the engineered composition and geometry [ 13–15 ]. Among them, for droplet navigation, moisture-harvesting lizards, including the Australian thorny devil ( Moloch horridus ) and Texas horned lizard ( Phrynosoma cornutum ), harvest and ingest water in arid areas [ 16 ]. Their integuments contain grooved structures comprising scales surrounded by interconnected capillary channels, which could induce a wettability gradient and Laplace pressure difference [ 17 , 18 ]. Therefore, water droplets of various diameters can be harvested and pumped directionally from the scale surface to the capillary channels between the scales (Fig. 1 a). With the capillary channels, even a small volume of water can fully disperse over the lizard's integuments, resulting in easier storage and increased availability to its mouth. Moreover, another necessary process after the droplets’ gathering and coalescence is creating a water track that transports water with low drag. In this regard, the skin of most fish (e.g. catfish) is covered with an epidermal mucus layer, which can reduce swimming drag and enhance adaptability to aqueous environments [ 19 ]. Fish mucus, a hydrophilic biopolymer, is a lubricant with an ultralow friction coefficient in water (≤5 × 10 −3 ) [ 20 ]. A shear layer forms between the water and mucus layer, making swimming smoother and the fish more difficult to catch (Fig. 1 b) [ 19 , 21 ]. Thus, the merits of both these species can be integrated to design hydrophilic patterns with engineered geometries and properties for sustainable water harvesting. Figure 1. Biomimetic HWT design for rapid water harvesting. (a) Schematic of continuous water capture and directional water movement for drinking by moisture-harvesting lizards enabled by the capillary channels between the scale (side length is ∼1 mm). (b) Schematic of the drag-reduction effect of catfish enabled by mucus. (c) HWTs printed on a silicate glass to collect condensed water droplets and regenerate condensing sites. The blue semi-cylinders represent the HWTs (1 mm in diameter), and the yellow arrows indicate the droplet pumping direction. (d) Schematic diagram of the molecular structure of HWTs. (e) ESEM images of rough HWT surfaces resulting from the drying process. (f) Underwater AFM images of the surface morphologies of dry (left) and wet (right) HWTs. Using principles derived from moisture-harvesting lizards and surface-lubricated catfish, we herein report on a new design concept for water harvesting. Our engineered pattern consists of ordered hydrogel fibers printed on silicate glass with an arch structure (Fig. 1 c). Along the radial direction of the fiber, the arch structure and the superhydrophilicity of the hydrogel surface synergistically create a difference in Laplace pressure and a surface energy gradient across the hydrogel–glass interface, respectively. Mimicking the droplet spreading selectively into the lizards’ capillary channels, condensed water droplets on silicate glass were pumped to the hydrogel fiber surface along its radial direction, and the condensing sites of the glass were regenerated (Fig. 1 a and c). Meanwhile, along the axis, the surface of the hydrogel was partially polymerized with abundant branched dangling chains, forming a precursor water film. As shown in Fig. 1 b and d, this simulates the mucus of the catfish, as the superhydrophilic hydrogel fiber surface strongly bonds inner-layer water molecules and forms a shear layer for the outer-layer water molecules to swiftly slide off the condensing surface by gravity with low drag resistance. Results show that the engineered hydrogel fibers functioned as tracks for water transport, synchronously enabling favorable radial directional pumping and axial drag-reduced sliding of water droplets. The hydrogel water tracks (HWTs) could effectively regenerate condensing sites and achieve sustainable condensation.",
"discussion": "RESULTS AND DISCUSSION Characteristics of HWTs HWT was fabricated by interpenetrating sodium alginate (SA) and polyvinyl alcohol (PVA) polymer chains. The HWT was designed with an arch structure and was aligned to form anisotropic patterns (Fig. 1 c and d). According to environmental scanning electron microscopy (ESEM), the HWT surface morphology varied significantly during dehydration. Thorough dehydration resulted in dramatic shrinkage ( Fig. S1 ), with ridges and trenches forming along the extensively dried HWTs (Fig. 1 e). The HWT surface morphology was also studied in situ using underwater atomic force microscopy (AFM). The dry HWT surface was rough (root-mean-square roughness, R q = 16.9 nm) at the nanoscale with numerous wrinkles (Fig. 1 f, Fig. S2 ). After soaking in water, the surface wrinkles of HWT disappeared, with the root-mean-square roughness decreasing by 92.5% ( R q = 1.26 nm). This demonstrated that water molecules could interact with the polymeric chains of HWTs, supporting the skeleton and the formed arch structure. FTIR spectroscopy was utilized to further verify the interactions between water molecules and HWT. The HWT comprised an interpenetrating polymeric network of SA–PVA and strongly bonded water molecules ( Fig. S3a ). The broad peak centered at 3294 cm −1 (∼3645 to 2700 cm −1 ) was attributed to –OH stretching on the HWT surface, which endows the HWTs with superhydrophilicity to induce the directional droplet movement similar to the moisture-harvesting lizard. When swollen in water, this broad peak was strengthened ( Fig. S3b ). No absorption peaks were observed at 3756 and 3656 cm −1 , and the H–O–H bending vibration (∼1630 cm −1 ) overlapped the characteristic –COOH peaks, suggesting that most water molecules on the hydrogel surface were not free [ 22 , 23 ]. The characteristic methyl and methylene peaks around 2920 cm −1 weakened significantly after hydration, indicating partial polymerization of the HWT surface because of its polymerization process against hydrophobic air [ 24–26 ]. Owing to the branched dangling chains, the synthesized HWT exhibited great hydration ability, and the surface polymer chain concentration decreased significantly in the presence of water molecules, forming a well-developed hydration layer to mimic catfish mucus (Fig. 1 d). Directional pumping across the glass–HWT interface We designed HWTs with arch structures and utilized fluorescence to visualize the motion of condensed water droplets since the HWT pumping effect is the first step for sustainable condensation. First, HWT was placed upside down, in its condensing condition, and was observed by an inverted microscope from the bottom. A fluorescent pattern was immobilized on the glass 200 μm away from an HWT (Fig. 2 a). Fluorescent molecules were redispersed in the condensed droplets to show the droplet motion trajectory. Following condensation for 9.3 s, condensed droplets grew gradually to contact the HWT–glass interface, and a strong fluorescence signal appeared at the HWT–glass interface, confirming directional water pumping from the glass to the HWT. An incline of 0.5° allowed rapid water transfer along this interface (Fig. 2 b), with water penetrating the entire microscope field in 0.9 s. Moreover, the fluorescence image showed that water was mainly confined within ∼50 μm of the HWT (Fig. 2 c). Notably, the fluorescence intensity was nearly 3-fold compared to the immobilized fluorescence pattern, which showed a concomitant decrease. This indicates that water droplets were directionally transferred from the glass toward the HWT, confirming the pumping effect. Figure 2. The directional pumping effect of water molecules at the HWT–glass interface. (a) Schematic illustration of the method used to detect the pumping effect of HWTs. Pre-dipped fluorescent molecules enable the tracing of water molecule movement and increase detection sensitivity. The orange straight arrows represent the fluorescence. (b) Fluorescence signals before and after condensation illustrate the directional pumping of water molecules from the glass surface to the HWT (scale bar: 100 μm). (c) Average fluorescence intensity vs. position at various times after condensation. (d) Surface energy gradient and difference in Laplace pressure (inset) between the glass and the HWT. The black solid arrows indicate the direction of the induced pumping effect. MD simulations of water molecule motion over (e) a silicate glass control and (f) an HWT-printed glass surface. (g) The decrease of system energy during motion of the water molecules. Similar to the droplet pumping effect of moisture-harvesting lizards, droplet movement on the HWT–glass interface can be ascribed to differences in affinity for water molecules between the HWT and silicate glass. The water contact angle on the dry HWT film was 35.7°, much lower than that on bare glass (52.9°; Fig. S4a and b), illustrating its better affinity for water molecules. This gap widened further in wet HWT. The HWT surface was rich in oxygen-containing functional groups, which could form hydrogen bonds to hold water molecules in the polymeric network. The retained water molecules formed a precursor water film on the HWTs, leading to the rapid spread (instantaneous contact angle ∼16.7°) of subsequent water molecules. As a result, the HWT surface became super-wettable ( Fig. S4c ). This difference in hydrophilicity induced a chemical wetting gradient, as given by Eq. 1 [ 27 , 28 ]: \n (1) \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{equation*}\n{{F }} = \\mathop \\int \\nolimits_{{{\\mathrm{L}}}_{\\mathrm{g}}}^{{{\\mathrm{L}}}_{\\mathrm{h}}} {\\mathrm{\\gamma }}\\!\\left( {{\\mathrm{cos}}{{\\mathrm{\\theta }}}_{{A}} - {\\mathrm{ cos}}{{\\mathrm{\\theta }}}_{{R}}} \\right){{\\ dl}},\\end{equation*}\\end{document} \n where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\theta }_A$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\theta }_R$\\end{document} are the advancing and receding angles of a water droplet at the glass–hydrogel interface, respectively, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n$\\gamma $\\end{document} is the surface tension of water (73 mN m −1 ), and dl is the integration variable along the length from the glass to the HWT. Compared to \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\theta }_R$\\end{document} , \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\theta }_A$\\end{document} was negligible, driving the water droplets from the less hydrophilic glass to the more hydrophilic HWT (Fig. 2 d). Ideally, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\theta }_R$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\theta }_A$\\end{document} are 52.9° and 16.7°, l is the horizontally projected length of the 1/2 HWT (∼500 μm), so the wetting gradient F is estimated as ∼0.013 mN. The arch geometry of HWT is also critical for the pumping effect, which acts like the meniscus-mediated coarsening effect [ 29 ]. It facilitates generating a difference in the Laplace pressure (Young–Laplace equation) [ 29 , 30 ]: \n (2) \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{equation*}\n{P}_{\\mathrm{s}} = {\\mathrm{ \\gamma}}\\! \\left(\\frac{{\\mathrm{1}}}{{{R}_{\\mathrm{2}}}}{\\mathrm{ + }}\\frac{{\\mathrm{1}}}{{{R}_{\\mathrm{1}}}} \\right),\\end{equation*}\\end{document} \n where R 1 and R 2 are the radii of the water surface curvature. Ideally, R 1 and R 2 are ∼1.63 mm and ∼ −0.77 mm ( Figs S4b and S5c ), P s is estimated as ∼ −50 Pa, which points to the exterior of the droplet. For its direction, as illustrated in Fig. 2 d (inset), the contact angle of water on bare glass creates a downward curvature with radius R 1 , inducing F 1 pointing to the droplet's interior. When the droplet completely deposits on the glass, the droplet is horizontally symmetrical, so no net force exists horizontally. When the droplet reaches HWT, the superhydrophilicity of HWT induces a tiny contact angle at the water–hydrogel surface, creating an upward curvature with radius R 2 and F 2 pointing to the exterior of the droplet ( Fig. S5 ). The resultant force ( F 3 ) of F 1 , F 2 , and gravity points toward the HWT, driving the water droplet to move from the glass to the HWT. Overall, the surface energy gradient and difference in Laplace pressure cooperatively induce the HWT pumping effect. These findings were further verified by using molecular dynamic (MD) simulations. A water droplet released on bare glass spread rapidly, with the boundary becoming unclear after 4.0 ps owing to the affinity of water for the glass surface and Brownian motion (Fig. 2 e). However, droplet boundary deformation occurred axisymmetrically with no directional tendency. Conversely, the tendency was evident in the HWTs (Fig. 2 f). The water molecules moved quickly, encountering the HWT within 0.5 ps. Subsequently, the top edge of the water droplet tilted toward the HWT, and water molecules even entered the HWT skeleton after 4.0 ps. The free spread of water droplets on bare glass is an entropy-increasing but energy-decreasing process (by ∼20%) as water molecules move spontaneously to areas with higher surface energy (Fig. 2 g). Comparatively, the system energy decreases by ∼40% for water molecules spreading near HWTs, demonstrating that HWTs provide additional forces that account for the directional pumping effect. Therefore, the semicircular convex shape and superhydrophilicity of the HWTs are critical for directional droplet pumping, mimicking the capillary channels of lizards to directionally pump droplets and regenerate condensing sites. Drag-reduced water sliding along HWTs After pumping droplets into the HWT, rapid movement along the HWT is necessary to ensure sustainable pumping and avoid surface flooding [ 31 ]. As shown in Fig. S6 , once the droplet contacts the HWT surface, an inclination of only 0.5° can lead to a quick spreading and rapid water sliding within 0.1 s and 1.0 s, respectively. The instantaneous advancing angle at 0.1 s was as low as 2.7° and quickly disappeared. In contrast, the droplet tended to pin onto the glass surface ( Fig. S7 ). When inclined at 90.0°, the advancing angle increased from 55.4° to 74.7°, but the droplet was still unable to roll off the glass surface. Therefore, it was easier to remove water on the HWT surface than on glass. Ionic fluorescent dyes rhodamine B and sodium fluorescein were used to monitor the movement of surface water molecules. As shown in Fig. 3 a, sliding a rhodamine B droplet along the glass surface formed a trail with a uniform fluorescence signal profile 45 μm above the surface. Similarly, after wetting the bare glass surface, the subsequent rhodamine B mixed thoroughly with water in the previously formed thin film, resulting in a fluorescence signal resembling that of the rhodamine B droplet only (Fig. 3 a). Furthermore, when the rhodamine B droplet was followed by a sodium fluorescein droplet, mixing resulted in a uniform vertical distribution of these two fluorescences on the glass surface (Fig. 3 b). Figure 3. Mechanism of water transport on the HWT surface. (a) A rhodamine B droplet sliding on the glass fully mixing with former droplets. (b) Successive rhodamine B and sodium fluorescein droplets sliding and fully mixing on the glass surface. (c) A rhodamine B droplet sliding on the hydrogel surface illustrates hydration layer formation, with subsequent water droplets advancing without direct contact with the hydrogel surface. (d) Successive rhodamine B and sodium fluorescein droplet sliding illustrate the water division on the hydrogel surface into inner and outer layers. The background shading represents the color of the droplet, where Sod. corresponds to green, Rho. corresponds to pink, and water corresponds to blue. (e) Change in Raman shift at ∼3220 cm −1 upon water molecules approaching the hydrogel surface. (f) Schematics of the hindered droplet transport on bare glass control and rapid sliding on HWT-printed glass. (g) DFT-calculated charge transfer intensity for water molecules at various distances from the HWT interface. Water molecule movement on the hydrogel surface differed. With only the rhodamine B droplet sliding on the hydrogel surface, the vertical distribution was uniform, similar to that on the glass surface (Fig. 3 a and c). However, when the hydrogel surface was first wetted by water, the subsequently sliding rhodamine B mainly distributed in the outer layer of the water film, indicating that it advanced without approaching the hydrogel surface, remaining distributed in the outer layer of the water film (Fig. 3 c). This phenomenon was further verified by successively sliding rhodamine B and sodium fluorescein on the HWT surface (Fig. 3 d). Sodium fluorescein completely washed away the outer rhodamine B layer, whereas the inner rhodamine B layer was still preserved. Thus, sodium fluorescein and rhodamine B mainly occupied the outer and inner layers, respectively. These results indicate that the inner-layer water molecules are more inert and have a stronger affinity for the hydrogel surface than those in the outer layer. MicroRaman was applied to quickly switch the focus between the glass and the HWT surface to monitor the O–H stretching modes of water molecules at different heights away from these two surfaces. The obtained signals were differentiated using Gaussian functions ( Fig. S8 ). The peaks at ∼3220 cm −1 (Peak A) and ∼3410 cm −1 (Peak B) corresponded to the in-phase and out-of-phase vibrations of water molecules with four hydrogen bonds, respectively, whereas that at ∼3610 cm −1 (Peak C) corresponded to the O–H stretching vibrations of weakly or non–hydrogen-bonded water molecules [ 32 , 33 ]. Upon approaching the hydrogel surface, the percentage of weakly bonded water molecules decreased, indicating an increase in water molecules with tetragonal structures ( Fig. S9 ). A corresponding frequency decrease in Peak A suggested O–H bond elongation due to the hydrogen bonds between the interfacial water molecules and the –OH and –COOH groups of the hydrogels being stronger than those between bulk water molecules (Fig. 3 e) [ 34 ]. The superhydrophilic branched dangling chains on the HWT surface held water molecules even after the water droplets left the surface, thus improving the precursor water film around the condensing droplets and facilitating the rapid formation of a stable water film ( Fig. S10 ) [ 35 , 36 ]. Comparing the droplet movement on both wet and dry HWTs, we found that on the dry HWT surface, successive droplets were pinned and accumulated into a larger one ( Fig. S11a , movie S1 ), similar to the bare glass surface ( Fig. S11c ). Comparatively, successive droplets released on the wet HWT surface could rapidly slide away without flooding the surface ( Fig. S11b and movie S2 ). Therefore, the formation of precursor water film is crucial to act as a lubricant layer between the inner and outer water layers to make the outer water molecules advance without direct hydrogel contact, thus dramatically reducing drag (Fig. 3 f). However, on silicate glass, water molecules advanced as a whole with successive sliding and friction against the glass surface. Hydration layer formation relies strongly on hydrogen bonds, which are electrostatic interactions or covalent chemical bonds that are closely related to electron distribution [ 37 , 38 ]. Using density functional theory (DFT) calculations, the charge transfer intensity was determined to evaluate interactions between a water molecule and its neighbors. Away from the HWT surface, charge transfer between water molecules was weak, corresponding to natural hydrogen bonding in liquid water (Fig. 3 g). In bulk water, hydrogen bond formation between neighboring molecules is statistically homogeneous and isotropic, leading to negligible net charge transfer [ 39 , 40 ]. Upon approaching the HWT surface, the charge transfer intensity increased significantly, eventually becoming 249% greater than that in bulk water, suggesting a loss in symmetry for the interfacial water molecules. Thus, the hydrogen bonds between water molecules and the HWT surface were stronger than those between neighboring molecules in bulk water, leading to a net charge transfer, in agreement with the Raman results [ 39 , 41 ]. However, when water molecules entered the HWT skeleton, the charge transfer intensity decreased dramatically, becoming similar to that away from the HWT surface ( Fig. S12 ). As the water molecules within the HWT skeleton could uniformly form hydrogen bonds with the surface, they remained centrosymmetric, and no net charge transfer was observed. Therefore, the superhydrophilicity of the branched dangling chains on the HWT surface favors hydration layer formation. Similar to catfish mucus, this shear layer enables outer-layer water to slide swiftly on the smooth HWT surface with reduced drag. Sustainable water harvesting via directional pumping and drag-reduced sliding Owing to the unique pattern and properties of the HWT, the condensation behavior observed in situ on silicate glass and the HWT pattern differed. HWTs are 1.0 mm hydrogel fibers, and HWT- x denotes the interval between HWTs are x mm. On silicate surface control, water droplets formed quickly as condensation began (Fig. 4 a). Subsequently, the border of these water droplets expanded, resulting in successive collisions and cohesion (diameter >100 μm). Finally, a water film flooded the glass surface, blocking the condensation sites and hindering further condensation ( Fig. S13a ). Conversely, on the HWT pattern, water droplets formed quickly on the glass (Fig. 4 b; 0 s), and a thin water film formed instantly on the HWT ( Fig. S14 ). When the water droplet grew, its boundary expanded and encountered the HWT ( Fig. S13 ; 40.2 s). The water droplet was rapidly pumped by the HWT and transported axially along the HWT, as traced by the small-particle trajectory from the middle of the water droplet to the HWT ( Fig. S13b , position 1–4). Finally, the water droplet boundary on the glass receded, condensation sites were regenerated, and new water droplets formed (Fig. 4 b; 201.0 s). Figure 4. Coupled water droplet growth and directional pumping for accelerated water vapor condensation. (a) In situ optical images of rapid water droplet formation, growth, cohesion, and film-forming processes on bare glass control. (b) In situ optical images showing rapid condensation, water droplet growth, directional pumping, drag-reduced sliding effect, and condensing site regeneration on HWT-printed glass (scale bar: 100 μm). (c) Optical microscope images of the HWT pumping effect (needle diameter: 0.5 mm). (d) Water droplet collection rates on the HWT pattern and bare glass. (e) Illustration of the pilot study of condensed water collection. (f) Condensed water from outdoor solar evaporation devices with glass and HWT-printed glass condensing cover. The reference data were obtained or calculated from previous reports. The radial pumping and axial sliding of water droplets were verified by placing the HWT-printed surface upside down and using a time-resolved camera from the side. Three representative initial locations were selected to observe the directional pumping effect ( Fig. S15 ). When the water droplet was released directly on the HWT, it spread rapidly ( Fig. S15a ). Interestingly, this droplet spilled over the HWT boundary before being swiftly dragged back (within 1 s), forming an afterimage. This behavior was because of the balance between the effect of gravity on the water droplet and the HWT pumping effect. Owing to the 0.5° inclination along the HWT, the water droplet left the focal plane within 5 s, regenerating the initial boundary between the HWT and glass. This HWT pumping effect was also observed when water droplets were released at the HWT–glass interface. Even when the water droplet was released between two HWTs, it was quickly pumped to the HWTs and formed a concave meniscus between the HWTs within 1 s (Fig. 4 c; labeled with arrows). The meniscus gradually disappeared after the water slid along the HWTs ( Fig. S15c , 20 s). The water collection properties were investigated using HWT-patterned glass as the inclined top of a container. In the container, the relative humidity and temperature were controlled at 97.5 \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\mathrm{ \\pm }}$\\end{document} 0.06% and 40 \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\mathrm{ \\pm }}$\\end{document} 0.2°C, respectively ( Fig. S16 ). For bare glass control, condensation resulted in instant and randomly formed fine water droplets that firmly adhered to the surface, causing fog ( Fig. S17 ), deteriorating the light transmittance by 18.80 \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\mathrm{ \\pm }}$\\end{document} 1% ( Fig. S18 ). Moreover, this adhesion led to minimal harvesting of the water and uneven increases in the mass of collected water, with sharp changes at 67 and 96 min corresponding to the formation of water droplets that were sufficiently heavy to be shed (Fig. 4 d). Additionally, the condensation rate on bare glass deteriorated over time owing to the retention of condensed water on the condensation sites. Comparatively, increasing the hydrophilicity of glass can lead to smoother droplet shedding and increase the water collection rate by 27.6% while still suffering from unsustainable condensing sites [ 2 , 42 ]. When the HWT pattern was applied, the formed droplets could be quickly pumped from the glass to the HWTs, and the condensed water was mainly concentrated at the glass–HWT interface with several growing droplets still on the interval between HWTs. No notable flooding happened between the two HWTs ( Fig. S17 ). The condensed water was first collected after 10 min, earlier than on bare glass and hydrophilic glass control. Moreover, the condensation rate increased by 85.9% and remained stable, demonstrating reduced retention and sustainable condensation of water droplets on the HWT pattern. After condensation, the light transmittance of HWT-printed glass only decreased by 4.030 ± 2%, indicating the quick shedding of the droplets ( Fig. S18 ). As shown in Fig. S19 , when the HWTs were closer (HWT–0.4; 0.4 denotes the gap (mm) between HWTs), condensed water droplets could be collected earlier than HWT–1.0, attributable to the decreased pumping distance ensuring earlier shedding of the condensed droplets on the glass. However, when intensive condensation occurred, droplets grew rapidly to contact the left and right HWT concurrently, resulting in partial flooding between the neighboring HWTs and slightly deteriorating condensation performance. In contrast, when the interval between the HWTs (HWT–2.0) was enlarged, water collection was delayed compared to HWT–0.4 and HWT–1.0 since the droplets needed to grow larger to contact the HWT and be pumped away. As expected, the delayed shedding of the droplet gradually affected condensing performance. Therefore, directional pumping of HWT is critical for sustainable condensation, and its most effective pumping range was around 200–500 μm. Solar evaporation has been widely regarded as the zero-carbon water purification technique and has received intense attention for its potential to resolve the clean water crisis. However, previous solar evaporation studies mainly focused on solar-to-vapor conversion, but the vapor-to-water process has long been overlooked. Condensation has been regarded as the bottleneck for acquiring purified water in sunlight-generated water vapor [ 43–45 ]. Thus, we applied the HWT-printed glass to solar evaporation devices under natural conditions to further demonstrate its applicability and scalability. The devices with a larger condensing area (200.0 × 200.0 mm 2 ) were placed outside to collect purified water under natural daily irradiance and other weather conditions. We applied our HWT-printed glass as the condensing cover of solar evaporation equipment and used bare glass as the control group (Fig. 4 e). For the bare glass control, the water production rate was within 1.12 to 2.88 L m −2 day −1 , corresponding to an average solar-to-water efficiency of 30.34%, comparable to previous reports (Fig. 4 f, Table S1 ) [ 44–48 ]. In contrast, with the HWT pattern, the water production rate drastically increased, ranging from 2.05 to 7.12 L m −2 day −1 (efficiency ≈61.3%), close to the theoretical maximum [ 49 ]. Evidently, with an enlarged surface area, the distance for the droplets to be shed off also increases, further challenging the condensing performance of bare glass. As expected, the elevation for larger-sized HWT-printed glass is 109%, higher than that of the lab scale (85.9%), demonstrating that the pumping effect enabled by HWT patterns promotes condensation by accelerating the droplets away from the glass edges to be shed and is especially critical in large-area sustainable condensation. Moreover, HWT is stable in natural environments (solar irradiance), the release of Ca 2+ is negligible, and the produced water with the HWT (∼10 μS cm −1 ) showed no difference from that of bare glass ( Figs S20 and S21 ). This demonstrated that HWT could be scaled up to increase the condensing rate without external energy input and with no threat to the quality of the condensed water."
} | 8,985 |
35520797 | PMC9063782 | pmc | 2,137 | {
"abstract": "In this paper, we first fabricate a 3D porous FZCF (FAS-modified ZnO-grown copper foam) with robust superhydrophobicity in air and superoleophilicity under water and the repeatable superwettability, and then mainly explore and analyze its corrosion resistance. The superhydrophobic–superoleophilic FZCF as an immiscible oil/organic solvent separation material shows high adsorption capacity and separation efficiency due to its heterogeneous micro–nano structures and low surface energy. It has excellent corrosion resistance under various pH conditions, and can serve as a corrosion protective barrier that prevents metal from contacting corrosive seawater in marine applications. Adsorbed oils also make superoleophilic FZCF keep its durability and stability after suffering attack in strong acid and alkali environments for a long time. Superwetting porous FZCF material that possesses outstanding excellent corrosion resistance demonstrates potential applications in many industrial fields such as oily wastewater treatment and marine oil spill accidents.",
"conclusion": "4. Conclusions In summary, we prepared a 3D superwetting porous FZCF with robust superhydrophobicity in air and superoleophilicity under water for adsorption/separation of immiscible oil/water mixtures and corrosion resistance tests were carried out in different environments. The porous FZCF exhibits excellent adsorption capacity, separation efficiency and robust corrosion resistance. Based on potentiodynamic polarization tests, superhydrophobic–superoleophilic FZCF has excellent corrosion resistance. The corrosion resistance of FZCF is ascribed to the combined protection effect of the trapped air film inside the superhydrophobic FZCF in various pH conditions, which can serve as a corrosion protective barrier that prevents metal from contacting with corrosive seawater in marine. What's more, adsorbed-oils make superoleophilic FZCF keep this property after suffering the attack in NaCl aqueous solution for a long time compared to untreated copper foam. Furthermore, the durability and stability of the FZCF in the practical adsorption and separation for immiscible oils/organic solvents and water also can be verified in highly acidic, alkaline, and salty environments. We expect that the superwetting anti-corrosion FZCF material can be further utilized as a promising candidate for oil/water mixtures separation, industrial oily wastewater treatment and oil removal in marine oil spill accidents and oil-repelling pipeline manufacture for industrial water transportation.",
"introduction": "1. Introduction Nowadays, due to the increasing demand of environmental protection and economic development, large quantities of oily wastewater and sanitary sewage have caused serious environmental problems. In addition, oil spill accidents all over the world have resulted in the waste of precious resources and damage to the environmental system such as the Deepwater Horizon and the Gulf of Mexico oil spills, which have polluted the oceans and rivers by discharging millions of tons of crude oil. 1–3 It is extremely important to make the purity of the fuel oil reach a certain standard in the ocean transportation field, because oil mixed with a little water will increase the risk of oil exploration and finally result in serious accidents. Therefore, there exists an urgent need for effectively separating oil/water mixtures. Jiang and co-workers proposed that the superwetting polytetrafluoroethylene coated mesh could efficiently achieve oil/water separation. 4 In 2017, Faze Chen etc reported a facile organic solvent free method was described to prepare a porous PVDF–MWCNT foam to separate immiscible oils/organic solvents and aqueous solutions. 5 Therefore, many superwettability materials such as coating meshes, 6–8 sponges, 9–11 membranes, 12–15 foams, 16,17 textiles, 18,19 aerogels, 20,21 particles, 22,23 and others 24–26 are applied for oils/water separation. 27–30 Superwetting porous copper foam with superhydrophobicity and superoleophilicity are of greatest concern since these materials are affordable and well-prepared 3 dimensional (3D) network composite structures and large surface area compared with their counterparts in the form of membrane, sponges, textiles, fiber and particle. 31–37 Moreover, the material could achieve the rapid separation of sundry immiscible oil/water mixtures and high adsorption capacity with superwettability caused by the hierarchical micro–nano structures and chemical compositions, revealing the coactions of structure and performance. 38 In the current study, the researches are limited to preparation and application of oil/water separation materials. However, these materials cannot be applied in some solutions such as seawater are highly corrosive. Little attention is paid to corrosion resistance of oil/water separation materials resulting in impractical application. In this paper, we prepare superwetting (superhydrophobic and superoleophilic) 3D porous FZCF (FAS-modified ZnO-grown copper foam) through hydrothermal process under appropriate pH conditions and FAS-modification, and focus on the study of its corrosion resistance. Due to the surface giving rise to heterogeneous micro–nano structures of flower-like protrusions and petals and low surface energy, the roughened FZCF shows the repeatable superwettability that includes superhydrophobicity in air and superhydrophilicity under water. The corrosion resistance of the FZCF is tested by a potentiodynamic polarization method. The superhydrophobic FZCF has excellent corrosion resistance and superoleophilicity can largely improve the corrosion resistance of the copper foam in corrosive solutions. Moreover, the durability and stability of the FZCF in the practical adsorption and separation for immiscible oils/organic solvents and water also can be kept in highly acidic, alkaline, and salty environments. The FZCF as a kind of oil/water separation material has potential practical applications due to the improved corrosion resistance.",
"discussion": "3. Results and discussion 3.1 Surface morphology, chemical characterization and superwettability in different pH solutions of the porous FZCF In order to investigate whether the reaction process provided enough surface roughness and furthermore produced enough superwettability, the surface morphology of the prepared FZCF is characterized by scanning electron microscopy (SEM). The surface morphologies were observed using a field-emission scanning electron microscope (FE-SEM, TESCAN VEGA). Fig. 1d shows a low-resolution scanning electron microscopy (SEM) image of the as-prepared FZCF with a pore size of 300 μm and the porosity of 98%. Fig. 1e shows tiny heterogeneous protrusions often form dense growths on the porous FZCF skeleton. At higher resolution, the porous FZCF surface is uniformly covered by hierarchical micro–nano structures of flower-like protrusions and petals which are presumably caused by the spherical structures of ZnO ( Fig. 1f ). The local magnification image ( Fig. 1g–h ) further indicates the flower-like structures of the FZCF similar with the physical photos of the petals of Sedeveria silver frost ( Fig. 1a–b ). The petals of the flower-like structures are almost 200–300 nm in diameter ( Fig. 1g ) with its multilayered structure consisting of hierarchically packed nanoslices and the thickness of nanoslices is estimated to be 80 nm ( Fig. 1h ). Due to Sedeveria silver frost has the special wettabilities that the leaves are hydrophobic, such a biomimetic hierarchical micro–nano structures of flower-like protrusions and petals can help supporting water droplets ( Fig. 1c ) on the FZCF and is vitally essential for the superhydrophobicity of the FZCF. Fig. 1 (a) and (b) Photos of the petals of Sedeveria silver frost. (c) Picture of as-prepared porous FZCF with water droplets on top. (d–h) SEM images with different magnifications of the porous FZCF sample (10 μm, 2 μm and 1 μm, 500 nm and 200 nm). (i) Optical images of water droplets deposited on corresponding surface showing the superhydrophobicity in air and superhydrophilicity under water. The CA and SA of water droplets were measured by an optical contact-angle meter system (Data Physics Instrument GmbH, Germany) at ambient temperature. The water CA and SA reported were the mean values measured with 5 μL of water droplets at five different positions on each test surface. The average CA value was an average of the five measurements at different spots of the same sample. The corresponding water contact angle (CA) measurements on the sample surface show that the porous FZCF is both superhydrophobic in air and superoleophilic in water in Fig. 1i . FZCF has a static water CA in air of 165° and the water droplet quickly permeates with a static oil CA in water of 0° indicating superhydrophobicity and superoleophilicity. EDS of the sample surface is also detected in a random area eight times ( Fig. 2a ). The corresponding element distributions were determined by energy dispersive X-ray spectroscopy (EDX). The elemental analysis performed using energy dispersive X-ray spectroscopy (EDS; attached to SEM) on as-prepared FZCF sample shows the major element content included zinc, copper, carbon oxygen, fluorine and silicon based on quantitative analysis. The results are incapable of being perceived as different indicating that the ZnO flower-like heterogeneous structures are uniformly distributed on the FZCF surface. Fig. 2 (a) The EDS spectrum from an as-prepared sample. (b) XRD patterns of the FZCF. All the peaks can be indexed to hexagonal phase of zinc and pure copper. The X-ray diffraction (XRD) patterns of the sample were performed on an Empyrean diffractometer (Panalytical, Dutch) using Cu Kα 1 radiation ( λ = 0.15418 nm) with the 2 θ ranging from 20° to 80°. The X-ray powder diffraction (XRD) is utilized to characterize the composition of micro–nano structures formed over the FZCF sample. XRD pattern of the FZCF sample are shown in Fig. 2b . Diffraction peaks of the sample are all indexed to pure copper [PDF file: 04-0836] and zinc oxide [PDF file: 36-1451], and no other crystal phases exist. According to the XRD patterns of the copper foam after hydrothermal procedure, the three strong peaks located at 31.769°, 34.421° and 36.252° are ascribed to (100), (002) and (101) planes of ZnO, respectively. The peaks ascribed to (102), (110), (103) and (112) planes of ZnO can be observed from the XRD patterns. It is indicated that ZnO is the main composition of micro–nano structures formed on the copper foam substrate after hydrothermal procedure. After the FZCF preparation, three strong peaks of Cu ascribed to (111), (200) and (220) planes are also observed in Fig. 3 . The result reveals that the main compositions of copper foam substrate remain unchanged. Namely, the hierarchical flower-like structures of ZnO grown on the surfaces of the as-prepared FZCF are at the micro–nano scale, and the bulk of the sample is Cu. Fig. 3 (a) Schematic of the superhydrophobic porous FZCF sample. (b) Picture of as-prepared FZCF with different pH values solutions droplets on top. (c) Static water contact angles of the FZCF in different pH values solutions. Other chemical characterization results of the prepared FZCF also reveal the mechanism of the improved superwetting performances by means of XPS, FTIR and Roman spectral analysis (Fig. S1–S3, ESI † ) for providing the basis to perfecting the immiscible oils/organic solvents separation ability and the adsorption capacity (or chemical durability and stability). The surface morphology has influenced on wettability that can be explained by Cassie–Baxter equation. The equation demonstrates that the air trapped in the rough surface will greatly improve the wettability. 39 Due to the porosity of FZCF, it is in a combined Cassie–Wenzel state on the surface that the water droplets penetrate into the pores in some extent leaving air pockets below it. Herein, estimating the solid fraction of solid/water interface per unit area is 0.15 (based on SEM image shown in Fig. 1 ) demonstrating that more than 89% of the contact area belongs to the air/solid interface. Due to the solid fraction of solid/water interface is smaller than that of air/solid interface, the tiny heterogeneous protrusions grown on the porous FZCF skeleton, air and liquid phase can increase the bulk of the air layer to improve the superhydrophobicity in a combined Cassie–Wenzel state shown in Fig. 3a . Based on three phase contact line, the FZCF shows favorable superhydrophobicity in air and can be utilized in immiscible oil/organic solvents and water adsorption and separation. Moreover, the stability in acidic and alkaline environments of the practical separation for immiscible oils/organic solvents and water is investigated as well. As-prepared FZCF with different pH values solutions droplets on top is shown in Fig. 3b . It can keep the static contact angles which are more than 150°. When the as-prepared FZCF samples are immersed into in deionized water with different pH values (1 to 13) for 24 hours, the FZCF sample are still superhydrophobic with static WCAs higher than 152°, indicating the FZCF is insusceptible to the extreme acid and alkaline environments ( Fig. 3c ). For some strong acid or alkali solutions (pH value is 1, 3, 11 and 13), the CAs decline to less than 153°, demonstrating that the chemical damage has influenced the superhydrophobicity of the FZCF surfaces in harsh circumstances. When the pH value ranges from 4 to 6, the superhydrophobicity of the FZCF is improved and the contact angles are able to reach 160° in comparative faintly acid (pH value is 5), neutral solutions (pH value is 7), and alkalescence solutions (pH value is 9). From a view of practical application, these results reveal that the superwetting FZCF has the chemical durability and stability for oil/organic solvents and water separation, further proving that can utilize for industrial oily wastewater treatment and marine oil spill accidents. 3.2 Immiscible oils/organic solvents and water adsorption/separation experiments of the porous FZCF The superoleophilicity and superhydrophobicity make the porous FZCF exhibits excellent adsorption capacities towards various oils and organic solvents, ranging from 17.0 to 31.0 times of its own weight based on the tested organic liquids (Fig. S5, ESI † ). The rapid oil/water adsorption behavior of the porous FZCF either on water or underwater can be attributed to its the porous micro–nano structures of flower-like protrusions and superhydrophobic/superoleophilic properties. 40 Oil/organic solvents are adsorbed in the pores formed by the layered foam skeleton of the FZCF while water is completely repelled by the superhydrophobic surface. Due to the capillarity and low surface energy, the superoleophilicity and superhydrophobicity is further reinforced when the oil molecules spread into the inner pores of the FZCF modified with the FAS on the layered foam skeleton. \n Fig. 4b shows the toluene–water separation efficiency and the water contact angles (WCAs) of the FZCF sample after 40 recycling separation times. Even though the separation efficiency and the water contact angles gradually decrease (which can be attributed to abrasion of the superhydrophobic FZCF sample surface during the separation process) when the FZCF sample is applied to separate toluene and water. It still holds remarkable superhydrophobic properties (>152°) after 40 separation cycles, meanwhile the separation efficiency remains at above 96.1%. More importantly, FZCF can be retrieved after the absorbed oil is easily removed by washing with absolute alcohol and then dried in vacuum oven after each separation, demonstrating the outstanding recyclability of adsorption/desorption and anti-fouling property of the FZCF material. Fig. 4c and d shows the SEM images of the FZCF sample after 5 and 30 recycle times separation tests. Though the FZCF surface is contaminated by oils/organic solvents and the FAS modified on the FZCF is destroyed in a certain extent, the superhydrophobic–superoleophilic property of the FZCF just decrease a little resulting in keeping oil–water separation performance after multiple separation times. By contrast, the surface morphology has no huge changes such as micro–nano structures, and it still proves the chemical durability of the porous FZCF. Fig. 4 (a) The solely gravity driven oil/water separation test of the FZCF. (b) The oil/water separation efficiency and water contact angle as a function of 40 recycle times by taking the toluene–water mixture as an example. (c) and (d) SEM images the FZCF sample after 5 and 30 recycle times separation tests. \n Fig. 5 shows the adsorption capacity and separation efficiency of FZCF for three typical organic liquids (motor oil, hexane and toluene) in different pH solutions. Motor oil, hexane, and octane are added into the corrosive aqueous solutions respectively. Then the oil/organic liquid droplets are removed by the FZCF sample rapidly. The results indicate that the adsorption capacity was still above 20 for motor oil in strong acid and strong alkaline. Others keep on a steady value of 20 and 25, respectively. As shown in Fig. 5b , the motor oil has the highest separation efficiency of 99.2% under neutral conditions compared with the other two corresponding to Fig. 5a . SE% of three oils are all up to above 96.4% in strong acid and strong alkaline. The as-prepared FZCF shows robust separation performance for various light oils and heavy oils (Fig. S5, ESI † ). For these oils, the separation efficiencies range from the 97.8% to 99.4%. The result suggests that the as-prepared FZCF can easily remove oil/organic solvents either on water or underwater or separate both. The chemical durability of the FZCF can be verified also demonstrates the feasibility of the proposed method for preparing advanced oil/water separation FZCF material. Fig. 5 (a) Adsorption capacity and (b) separation efficiency of the FZCF for different oil/organic solvents in different pH value aqueous solutions. 3.3 Corrosion resistance analysis of the porous FZCF in harsh circumstances The polarization curves (Tafel) presented in Fig. 6a show that the untreated surface, cleaned FZCF and adsorbed-oils FZCF reveals a narrow passive range and a breakdown between −0.2 V and −0.3 V, where the current density increases abruptly with slowly increased anodic polarization potential. Fig. 6 (a) Tafel polarization curves (b) Bode-modulus plots and (c) Bode-phase plots of the untreated surface, cleaned FZCF and adsorbed-oils FZCF, after 7 days of immersion in 3.5 wt% NaCl solution. (d) Nyquist plots of the untreated surface cleaned FZCF and adsorbed-oils FZCF immersion in simulated seawater for 7 days. The corrosion potential ( E corr ) of the untreated surface is −0.305 V and its corrosion current density ( I corr ) is 8.5 × 10 −7 A cm −2 . While, after the formation of superhydrophobic FZCF, the E corr changes to −0.232 V and the I corr of cleaned FZCF decreases slightly to 4.82 × 10 −9 A cm −2 due to the superhydrophobic ZnO layer reduces the corrosion rate and protects the underneath copper foam from corrosion attack, which indicated that the improvement of the protective properties of the superhydrophobic FZCF generated significant alterations in the corrosion behaviour. If the cleaned FZCF had adsorbed immiscible oils/organic solvents, the E corr shifts positively to −0.215 V. Simultaneously, the I corr of the adsorbed-oils FZCF decreases to 3.18 × 10 −9 A cm −2 which is less than that of the untreated surface and cleaned FZCF. Therefore, the adsorbed-oils FZCF further enhances the corrosion protection by adsorbing oils as a protective layer. The corrosion potential moving to right demonstrates that both trapped air and adsorbed oils are good physical barriers to isolate copper foam from 3.5% NaCl aqueous solution in a short time. It can be concluded that cleaned FZCF and adsorbed-oils FZCF have the potential to inhibit the corrosion of the copper foam substrates. The adsorbed-oils FZCF is more effective than the air layer to protect the copper foam from corrosion. The protective capability of the FZCF probably originates from both the superhydrophobicity and superoleophilicity based the physical diffusion barriers. To further explore the corrosion inhibition capability of the superhydrophobic FACF, the corrosion protection performance of the FZCF was also studied by the electrochemical impedance spectra (EIS). Fig. 6b displays the Bode-modulus plots untreated copper foam, cleaned FZCF and adsorbed-oils FZCF. The | Z | decreases with the decrease of frequency (Hz) in solution for 7 days, indicating the responses of inductive impedance at low frequencies. The | Z | value of the adsorbed-oils FZCF is ca. 1 and ca. 2 orders of magnitude larger than the untreated copper foam, cleaned FZCF in the low frequency region and high frequency region. The result reflects that adsorbed oils endows FZCF an excellent anti-corrosion property, which is consistent well with the result from Tafel curves. The Bode-phase plots presented in Fig. 6c show a well-defined time-constant at high frequencies (Hz) throughout the whole immersion period. High frequency capacitive loop is ascribed to charge transfer of the corrosion process, while the inductive loop at low frequencies is attributed to stability layer by adsorbed intermediate products of the corrosion reaction on the electrode surface. 41 For superhydrophobic cleaned FZCF, only a capacitive character is observed in the Bode-phase plots. As the capacitive responses appear at high frequencies, they can be attributed to the responses of protective superhydrophobic cleaned FZCF. After 7 days water immersion, Cassie-to-Wenzel wetting transition would occur to cleaned FZCF. The EIS spectra reveals that superhydrophobic cleaned FZCF can serve as a good corrosion protection coating. Similarly, it is inferred that adsorbed-oils FZCF still has a high corrosion resistance though the wetting transition from Cassie wetting state to Wenzel wetting state compared to the superhydrophobic FZCF. The Nyquist plots in Fig. 6d show three depressed semicircles in the high frequency range during further immersion (7 days). The impedance spectra of the adsorbed-oils FZCF shows a large impedance semicircle whose diameter is around several hundreds of kΩ cm 2 , while the impedance semicircle diameter of the cleaned FZCF and the untreated surface is dozens of kΩ cm 2 . These large impedance semicircles indicate that three samples all have good anti-corrosion properties after immersion for 7 days, especially the adsorbed-oils FZCF. Therefore, the adsorbed-oils FZCF presents an excellent corrosion resistance after suffering the attack in NaCl aqueous solution for a long time. These results demonstrate that superhydrophobic–superoleophilic FZCF has excellent corrosion resistance and oils can largely improve the corrosion resistance of the copper foam in NaCl aqueous solution."
} | 5,781 |
29213132 | PMC5719049 | pmc | 2,140 | {
"abstract": "Commercial scale production of biofuels from lignocellulosic feed stocks has been hampered by the resistance of plant cell walls to enzymatic conversion, primarily owing to lignin. This study investigated whether DypB, the lignin-degrading peroxidase from Rodococcus jostii , depolymerizes lignin and reduces recalcitrance in transgenic tobacco ( Nicotiana benthamiana ). The protein was targeted to the cytosol or the ER using ER-targeting and retention signal peptides. For each construct, five independent transgenic lines were characterized phenotypically and genotypically. Our findings reveal that expression of DypB in the cytosol and ER does not affect plant development. ER-targeting increased protein accumulation, and extracts from transgenic leaves showed higher activity on classic peroxidase substrates than the control. Intriguingly, in situ DypB activation and subsequent saccharification released nearly 200% more fermentable sugars from transgenic lines than controls, which were not explained by variation in initial structural and non-structural carbohydrates and lignin content. Pyrolysis-GC-MS analysis showed more reduction in the level of lignin associated pyrolysates in the transgenic lines than the control primarily when the enzyme is activated prior to pyrolysis, consistent with increased lignin degradation and improved saccharification. The findings reveal for the first time that accumulation and in situ activation of a peroxidase improves biomass digestibility.",
"conclusion": "Conclusion Current biomass pretreatment technologies are capital- and energy-intensive, making this step one of the most expensive operations in conversion of lignocellulose, and often requiring chemicals that are environmentally unsafe. Here we report a novel method of ligninolysis, whereby a bacterial lignin degrading enzyme can be accumulated in its active form, activated in planta , and used to improve biomass saccharification efficiency with several lines of evidence suggesting the mechanism is by depolymerizing intact lignin. This approach has the potential to tremendously reduce the cost and environmental impact of biomass pretreatment. To our knowledge this is the first report concerning the heterologous expression of a ligninase that breaks biomass recalcitrance in planta . Future research will explore other bacterial and fungal DyP-type peroxidases and ligninolytic enzymes for their potential application in the conversion of lignocellulosic bioenergy crops (switchgrass, Miscanthus , Pennisetum purpureum , Populus etc .) to biofuels. Furthermore, it is interesting to study DyP-mediated lignin modification using tetramethylammonium hydroxide (TMAH)-GC/MS thermochemolysis 125 and in situ lignin modification using designer monolignols 126 , 127 and a fluorogenic dye 128 for lignin visualization, localization and quantification during lignification. To understand the potential of DyP-peroxidases, it will be important to study the compatibility of the recombinant ligninases with simultaneous saccharification and fermentation, consolidated bioprocessing, and other conversion strategies to improve the production of biofuels as well as high-value products from lignocellulose.",
"introduction": "Introduction Increasing concern over global climate change has necessitated the development of alternative and renewable energy sources. ‘First generation’ biofuels such as ethanol have been produced from starch and sugar-based raw materials including corn, sorghum, sugarcane and sugar beet in U.S., Brazil and the E.U. countries. However, production of biofuels from these feedstocks has raised public concerns due to competition for land, food and feed supplies. While lignocellulosic biomass-based ‘second generation’ biofuels are advancing rapidly 1 – 3 , the technologies required for large-scale, cost-effective conversion of lignocellulosic biomass to biofuels are still under development. The main challenge is biomass recalcitrance ( i . e . the resistance of the plant cell wall to deconstruction) owing to the presence of lignin 4 – 7 . Lignin is a complex heterogeneous alkyl-aromatic polymer derived primarily from three hydroxycinnamyl alcohol monomers (p-coumaryl, coniferyl- and sinapyl-alcohols) via radical coupling, and occurs in tight association with polysaccharides cellulose and hemicellulose 4 , 8 . Lignin is the second most abundant biopolymer on Earth (after cellulose), comprising 15–30% dry weight of the lignocellulose component of plant cell walls, and consists of phenylpropanoid units linked via carbon-oxygen-carbon (C-O-C, ether) and carbon-carbon (C-C) bonds 9 , 10 . Many research laboratories are focused on developing commercially viable biomass pretreatment strategies to reduce or eliminate cell wall recalcitrance in order to increase enzyme accessibility and cellulose digestibility. Over the last several decades, various pretreatment strategies have been developed including physical (mechanical disruption), chemical (dilute acid, alkali, solvents etc.) and physico-chemical (ammonia fiber or steam explosion) methods 3 , 11 , 12 . While these strategies can reduce biomass recalcitrance to some extent, they suffer from one or more challenges such as high energy demand, high chemical costs, formation of fermentation inhibitors, low sugar yield, generation of toxic compounds or reactor corrosion 3 , 12 – 14 . Biological pretreatment using ligninolytic microorganisms such as white, brown, and soft-rot fungi and bacteria is another approach that has been well studied 13 , 15 – 17 . This approach is believed to require lower operating costs, is relatively safe and environmentally friendly 3 , 13 , 15 , and may enable enzyme (laccases and lignin-peroxidase)-mediated detoxification of fermentation inhibitors 18 , 19 . However, there are techno-economic problems associated with biological treatment including low saccharification efficiency, the need for large pretreatment space, and careful optimization of microbial growth conditions 3 , 17 . In addition, most ligninolytic microorganisms hydrolyze hemicellulose and cellulose as well as lignin, and potential degradation of sugar polymers makes this approach less attractive commercially 17 , 20 . Indeed, despite tremendous efforts to develop commercially viable methods, pretreatment remains the most expensive unit operation in the conversion of lignocellulosic feedstocks to biofuels, accounting for nearly $0.30/gallon of ethanol produced 21 . Several biotechnological and genetic approaches have been attempted to reduce biomass recalcitrance, but none have been utilized in the biofuel industry on a commercial scale thus far 22 . A number of glycoside hydrolase (GH) enzymes have been expressed in planta aimed at reducing the cost of enzyme production as compared to fungal sources 23 – 27 . While encouraging achievements have been reported, this method also suffers drawbacks including the need of the plants to produce a large amount of enzyme, thereby placing a metabolic burden on plants, increasing fertilizer inputs and the risk of undesirable effects on normal plant development, and requiring additional capital and operating costs 22 . Another interesting attempt to reduce biomass recalcitrance has involved manipulating the expression of genes and transcription factors that are involved in the lignin biosynthetic pathway. For example, antisense RNA-mediated downregulation of the shikimate hydroxycinnamoyl transferase (HCT) significantly reduces lignin content and improved cell wall digestibility in alfalfa ( Medicago sativa ) 5 . Likewise, overexpression of the transcription factor PvMYB4 which regulates monolignol pathway genes resulted in reduced lignin content, and increased sugar release efficiency in transgenic switchgrass ( Panicum virgatum) by approximately three-fold 28 . Similarly, ectopic overexpression of the maize non-coding small RNAs (miR156) in transgenic switchgrass 29 has been shown to reduce lignin content and improve biomass saccharification efficiency with or without pretreatment. Naturally, members of the Basidiomycetes fungi depolymerize lignin by using powerful oxidative enzymes 30 – 32 such as lignin peroxidases (LiPs, EC 1.11.1.14) 33 , manganese peroxidases (MnPs, EC 1.11.1.13) 34 , versatile peroxidases (VPs, EC 1.11.1.16; that possess the structural-functional properties of LiPs and MnPs) 35 , and laccases (EC 1.10.3.2) 36 . While these enzymes are exclusively reported from fungi 37 , the ability to depolymerize lignin has also been documented in bacteria 38 although the enzymology of bacterial lignin degradation was poorly understood until recently 32 . The first heme-containing peroxidase named DyP (dye-decolorizing peroxidase, EC1.11.1.19) was isolated from the fungus Bjerkandera adusta (initially described as Geotrichum candidum ), and bore no homology to known peroxidases 39 . Subsequently, a number of genes belonging to the DyP-type peroxidases superfamily were identified from other fungi including Termitomyces albuminosus \n 40 , Marasmius scorodonius \n 41 , Thanatephorus cucumeris Dec 1 42 and Auricularia auricula-judae \n 43 . Over the last decade, several DyP-type proteins have also been isolated from a number of bacterial species including E . coli \n 44 , Rodococcus jostii RHA1 45 , Amycolatopsis sp. 75iv2 46 , Pseudomonas spp . 47 , 48 and Bacillus subtilis \n 49 . The DyP-type peroxidases catalyze the oxidation of a range of substrates including synthetic dyes, non-phenolic methoxylated aromatics, lignin, β-carotene and Mn 2+ \n 50 . At least four phylogenetically distinct subfamilies with varying specificities towards substrates such as the anthraquinone compound (reactive blue) have been identified 38 , 51 . The DyPs from bacteria belong to the A, B and C subfamilies, while the fungal enzymes fall in the D-subfamily. Bioinformatic analysis of peroxidase genes in the soil bacterium R . jostii RHA1 genome sequence identified two DyP genes DypA and DypB \n 45 . A study of gene deletion mutants using a colorimetric assay showed greatly reduced lignin degradation activity for the ∆dypB mutant revealing its role in lignin degradation, while the recombinant DypB catalyzes oxidative Cα–Cβ cleavage of a β-aryl ether lignin model compound, and Mn II to Mn III[45] . Given that the DypB is the first bacterial enzyme to be well-characterized for oxidation of polymeric lignin in wheat straw as well as hardwood Kraft lignin 38 , 48 , 51 , we were interested to heterologously express this protein in planta to see whether it maintains its catalytic activity to depolymerize lignin. Moreover, since targeting of proteins to the Endoplasmic Reticulum (ER) has been shown to improve protein accumulation, folding, stability and reduce protein degradation 52 , 53 , and to sequester the protein away from the cell wall where lignin polymerization takes place, we were also interested to target the protein to the ER. Here we report that heterologous expression of the R . jostii RHA1 DypB in N . benthamiana and activation of the recombinant enzyme in situ improved subsequent saccharification by a cocktail of cellulase and glucosidase enzymes releasing remarkably more fermentable sugars, likely due to lignin depolymerization in planta . Moreover, targeting the protein to the ER enhanced protein accumulation without interfering with plant growth and development, revealing the potential of such transgenic plants as biofactories for large-scale production of ligninolytic enzymes. To our knowledge, this is the first attempt to express a lignin-degrading enzyme in planta that leads to improved lignocellulosic biomass saccharification.",
"discussion": "Discussion The genome of R . jostii RHA1 contains two genes (DypA and DypB) encoding members of the DyP superfamily 45 . Both proteins exhibit peroxidase activity using a chromogenic compound ABTS, pyrogallol and RB4 in H 2 O 2 -dependent manner, but only DypB is implicated in oxidizing Mn II [44,54] and polymeric lignin also in a H 2 O 2 -dependent manner 45 . Phenotype of DypB expressing transgenic plants In this study, the DypB was expressed in tobacco without a signal peptide for cytosol-targeting or with an N-terminus signal peptide and a C-terminus retention signal for ER-targeting. Importantly, the transgenic lines were not phenotypically different from the non-transformed control (Fig. 1 ), suggesting that the DypB did not interfere with lignin deposition and normal plant growth and development despite its ability to degrade model lignin compounds as well as lignocelluloses 53 , 65 . We hypothesize this is due to sequestration of the enzyme in the intracellular compartments away from the apoplast, where lignin polymerization takes place. Targeting the DypB to the apoplast may lead to in situ lignin degradation which may interfere with plant fitness since lignin plays an important role, for example, in providing structural support, water transport and protection against chemical and biological attack 10 , 66 , 67 . Reduced plant lignin content caused by mutation, trait improvement though breeding or transgenic approaches may negatively impact their agricultural fitness, while positive or absence of effect have also been reported 68 , 69 . Transgenic expression of other classes of fungal peroxidases such as the P . chrysosporium manganese peroxidase isozyme H3 (MnP-2) in tobacco chloroplast 70 , MnP from Coriolus versicolor \n 71 and the secretory Trametes . versicolor LiP 72 also in tobacco, and T . versicolor MnP 73 in hybrid aspen, did not markedly affect plant growth. In contrast, transgenic accumulation of MnP from P . chrysosporium in the ER of alfalfa 74 and maize 75 adversely affected plant growth and development depending on the level of protein accumulation. Transgenic alfalfa plants showed growth stunting and yellowing of foliage 74 while maize plants expressing the MnP showed leaf lesions and were capable of producing seeds 73 , which may be due to metabolic burden of accumulation and maintenance of a foreign protein, for example, through competition for precursors that are otherwise utilized for maintaining normal plant growth. Accumulation of the DypB in the ER of transgenic tobacco Heterologous protein accumulation in the intracellular compartments has been an effective strategy to increase protein yield and stability in plants 76 – 78 . Accordingly, a number of plant cell wall-modifying enzymes have been accumulated at higher levels in plant cellular compartments such as the ER, chloroplast, mitochondria or the apoplast 23 , 27 , 78 , 79 . In this study, targeting of DypB to the ER of tobacco under the control of enhanced 35S promoter and tobacco etch virus translation enhancer 80 led to increased protein level as detected by anti-HIS antibody (Fig. 2 ). This is achieved likely due to both N-terminal signal peptide and the ER tetrapeptide retention signal (HDEL) 81 . Simultaneous fusion of the signal peptide and the retention motif to the N-and C-termini, respectively, of recombinant proteins enables retrieval of the proteins from the Golgi apparatus to the ER lumen, resulting in more than 10–100 fold enhancement as compared to without the retention motif 52 , 82 , 83 . Moreover, the DypB nucleotide sequence used for ER-targeting was codon-optimized for N . benthamiana , and the constructs have an N-terminus tobacco etch virus leader sequence which has been shown to enhance mRNA translation 80 , 83 . Furthermore, ER-targeting has a number of advantages including the presence of a suitable environment for correct folding and disulfide bridge formation by the ER-chaperones, such as binding proteins (BiP) and protein disulfide isomerase (PDI) 52 , 53 , and low levels of protolytic activity in the ER-lumen as compared to the cytosol. Various recombinant proteins including industrial enzymes, medical antibodies and antigens, and other therapeutic proteins have been successfully produced in plants 84 , 85 . Increased accumulation of the DypB in N . benthamiana in this study suggests that plants can be used as a biofactories for the production of ligninolytic enzymes. In contrast with the ER targeted construct, the DypB protein was barely detected for the cytosolic-targeting construct (Fig. 2 ). This is likely due to either the native bacterial sequence not being optimized for tobacco translation machinery, resulting in low DypB protein synthesis, or due to a position effect ( i . e . site of the transgene insertion on the chromosome) 86 , 87 resulting in reduced transcription of the protein as compared to the ER-targeting lines. Generally, recombinant proteins targeted to the cytosol are detected at very low levels despite high mRNA levels, resulting in accumulation rates below 0.1% of total soluble protein (TSP) in several cases 88 , 89 . For example, cytosol targeting of the tomato mosaic virus antibody ‘rAb29’ 60 and a human growth hormone 90 in tobacco leaf resulted in very weak accumulation rates (0.01–0.1% of TSP). Interestingly, the same transgenes coupled with a signal peptide for extracellular secretion 52 or apoplast 90 resulted in accumulations up to 10% of TSP. Low levels of cytosol expression could also be due to unfavorable redox potential 91 as well as important post-translational modifications (such as glycosylation), which may modulate folding, assembly and/or structural stability of several proteins 92 , and/or the effective housekeeping activity of the ubiquitin–proteasome proteolytic pathway 93 , 94 , which is involved in the recognition and degradation of incorrectly folded proteins. However, stable and high-level expression of some recombinant proteins in the cytosol has also been reported 95 . Catalytic activity of recombinant DypB in vitro Previous characterization of the DypB catalytic properties revealed that it catalyzes the peroxide-dependent oxidation of lignin and divalent manganese (Mn 2+ ) 45 , 51 , 64 . In this study recombinant DypB purified from the leaves of transgenic lines consistently showed higher peroxidase activity than extract from the wild type control in oxidizing standard peroxidase substrates ABTS and DMP as well as lignin-related substrates Kraft lignin and VA (Fig. 3 ), indicating that functionally active DypB protein can be produced in planta . Generally, the specificity constant ( k \n cat / K \n m ) values for A and B-type Dyps for ABTS is in three orders of magnitude lower than those of C- and D-type DyPs 46 , 48 , 50 . The Dyp1B enzyme recently isolated from Pseudomonas fluorescens Pf-5 has been shown to oxidize Kraft lignin and Mn 2+ , releasing an oxidized lignin dimer in the presence of Mn 2+ \n 96 . Likewise, a DyP-type C peroxidase enzyme that has been identified from the soil bacterium Amycolatopsis sp . 75iv2 ATCC 39116, shows Mn 2+ oxidation activity with much higher catalytic efficiency than R . jostii RHA1 DypB, approaching the activity of fungal Mn peroxidase enzymes 45 . An effort towards improving the specific activity of the DypB through substitution of an active site Asn246 in DypB by Ala has been found to increase the k cat for Mn 2+ oxidation 80-fold 54 , suggesting a potential for improving the activity of these enzymes through protein engineering, for example, via substitution of amino acid residues and/motifs by directed evolution or saturated mutagenesis 97 , 98 or domain-swapping with more active DyPs such as the C- or D-type subfamily. In situ activation of the DypB improves biomass saccharification Although plant heterologous expression of ligninolytic enzymes such as LiP and MnP have been reported previously, those prior studies were aimed at studying the feasibility of recombinant enzyme production 70 , 71 , 99 and phytoremediation of toxic chemicals from the environment 71 – 73 . Accumulation of lignin degrading enzymes such as LiP, MnP, DyPs and laccases with the purpose of improving saccharification efficiency has never been reported. Therefore, given that the DypB has been shown to degrade standard peroxidase substrates such as ABTS and DMP, lignin related compounds Kraft lignin and VA (Fig. 3 ) as well as lignocellulose in vitro [ref. 45 and this study], we hypothesized that the DypB would be able to degrade intact lignin in the cell wall, and thus reduce biomass recalcitrance. While plant lignin content and structure varies with factors such as growth stage, genotype, morphological fraction (leaf blade, leaf petiole, stem, inflorescence), and environmental conditions 67 , tobacco ( N . benthamiana ) contains about 13% lignin 6 . In this study, the top portion of wild type and transgenic tobacco biomass was pulverized by mortar and pestle under liquid N 2 and incubated in the presence of Mn 2+ and H 2 O 2 to activate the recombinant DypB in planta . The resulting biomass was subjected to saccharification by a cocktail of cellulase and glucosidase enzymes, prior to analysis of sugar species and yield in the hydrolysate. The amount of fermentable sugars released from most of the transgenic lines was significantly higher than that of the non-transgenic control (Fig. 4 ). Glucose was the dominant sugar species released, accounting for over 80% of the total sugar in both control and transgenic lines. However, despite lower level of protein expression (Fig. 2b and c ), and relatively lower enzymatic activity in Cyto7 as compared to ER lines (Fig. 3 ), the amount of glucose released from Cyto7 was higher than the ER lines. This discrepancy could be due to the biomass preparation method, which might have resulted in the release of more enzyme from Cyto7 and allowed interaction with lignin in the cell wall as compared to the ER lines, where the DypB may be more strongly sequestered in the ER organelle. Moreover, enzyme activity is also modulated by posttranslational modification such as protein phosphorylation, glycosylation, which might be more pronounced in the Cyto7 lines. However, further study is needed to determine the precise mechanism of regulation of the recombinant DypB, as well as how to maximize its efficacy. This large increase in saccharification efficiency in the transgenic lines is likely due to depolymerization of intact lignin since there was no marked difference in the content of structural and non-structural carbohydrates and lignin (Fig. 5 , and Supplementary Tables S2 and S3 ). Therefore, to decipher the underlying biochemical mechanisms for the improved cell wall digestibility, we performed pyrolysis -GC-MS analysis of biomass with or without preactivation of the DypB enzyme in planta . As presented in Table 1 , acetic acid was the dominant compound of the pyrolysates in all the tobacco lines. Importantly, the amount of lignin degradation products such as phenol, 2-methyl-phenol, 4-methyl-phenol, 2, 4-dimethoxy-phenol and hydroquinone was lower in the transgenic lines than was observed in non-transformed and empty-vector control lines, most noticeably from samples in which the enzyme was activated prior to pyrolysis (Table 1 ). Given that the DypB protein was sequestered in the cytosol and the ER, in situ modification of intact lignin during polymerization can be ruled out. Therefore, the observed reduction in the amount of lignin associated pyrolysate is likely due to activation of the DypB enzyme in situ , which appears to have depolymerized lignin in the cell wall, releasing lignin monomers into the hydrolysate, and making cellulose accessible for saccharification. However, the decrease in pyrolysate yield may also be due to recondensation of lignin monomers because of DypB activation, and increased char formation. A model summarizing intracellular DypB accumulation, biomass processing, enzyme activation and mode of action, and subsequent saccharification or pyrolysis of the biomass is presented in Supplemental Fig. 4 to enable readers understand the processes reported in the current study. To see whether lignin-monomers are released during in situ activation of the enzyme, the hydrolysate was extracted with a mixture of dichloromethane and ethylacetate, and the organic fractions were immediately analyzed by GC-MS after being concentrated and filtered. However, we were not able to detect compounds that are typically derived from lignin. The compounds that were detected included 1-cyclohexyl ethanol, 2-propane-1-ol-3-phenyl, benzyl alcohol, phenyl ethyl alcohol, and other compounds, many of which contained aromatic rings, and appeared to be more abundant in the hydrolysate from the transgenic lines as compared to the non-transformed control. Our inability to detect typical lignin degradation products may be due to radical-based reactions occurring during the activation and extraction procedures; in the absence of a mechanism to remove lignin fragments that are likely susceptible to oxidation and repolymerization, these may produce heavier lignin-based products that are beyond the detection or identification limit of GC-MS 100 – 103 . If the latter is the case, addition of radical inhibitor such as boric acid as a capping agent during the activation process 102 , and perhaps butylated hydroxytoluene during the organic extraction could help in the identification of uncompromised lignin products. This technique will be implemented in future studies. Other methods for future studies of lignin modification include the NMR technique previously applied to tobacco plants in which lignification enzymes cinnamyl alcohol dehydrogenase and cinnamoyl-CoA reductase were down-regulated 104 , and non-catalytic Pyrolysis-GC-MS which can be used to characterize lignin by its H-, G- or S subunits 105 . Mechanism of lignin degradation by DypB Lignin degrading enzymes identified to date exhibit diverse modes of action. Lignin peroxidases such as LiPs catalyze oxidative cleavage of C–C or ether (C–O–C) bonds in non-phenolic aromatic substrates of high redox potential, and MnPs oxidize Mn 2+ to Mn 3+ , which facilitates the degradation of phenolic compounds or, in turn, oxidizes a second mediator to the breakdown non-phenolic compounds 9 . The MnP from P . chrysosporium has been reported to catalyze Cα-Cβ cleavages, Cα-oxidation and alkyl-aryl cleavages of phenol syringyl type β-1 lignin structure 106 . Likewise, DypB has been shown to catalyze Cα-Cβ oxidative cleavage of a β-aryl ether lignin model compound releasing vanillin as a product 54 , this oxidative cleavage was inhibited by addition of diaphorase (EC 1.8.1.4), an enzyme that catalyzes di- and tri-phosphopyridine nucleotides-dependent reduction of various dyes 107 , consistent with a radical mechanism for C-C bond cleavage. Ahmad et al . 45 also reported that DypB shows activity toward guaiacol and vanillin, and suggested that the mechanism is likely via one-electron oxidation of the phenolic ring, followed by C-C bond cleavage. Our suggestion of in planta lignin degradation is consistent with previous reports demonstrating in vitro degradation of lignocellulosic substrates such as wheat straw lignocellulose and Kraft lignin by recombinant DyP-type peroxidases including DypB 45 , 51 , 54 \n Pseudomonas fluorescens Dyp1B 38 , 96 and Irpex lacteus DyP 108 . Some DyPs have been shown to oxidize substrates that are too large to fit in the active site. For example, DypB showed saturation kinetics towards the large molecules of Kraft lignin 65 . The authors suggested a long-range electron transfer (LRET) between the surface of DypB enzyme involving several residues and the hydrophobic substrate through Tyr287 and Asp288, which forms a hydrogen bond with His226, which is the fifth ligand to the heme cofactor. The LRET-pathway has also been reported for Aau DyPI of Auricularia auricula - judae \n 109 , 110 and a lignin peroxidase (LiP) from the plant superfamily of peroxidases 111 , 112 , while in LiP from P . chrysosporium , a surface-exposed tryptophan is reported to be the interaction site for VA 113 . Biotechnological applications of DypB Despite the identification of many ligninolytic enzymes such as LiPs, MnPs and laccases in fungi, they have not been used for commercial production of ligninolytic enzymes owing to the inherent complexity of fungal genetics and challenges of their protein expression 38 , 45 , 112 . Bacterial ligninolytic enzymes circumvent these limitations and offer great potential for biotechnological applications including lignocellulosic biomass conversion to biofuels, biopulping and biobleaching in paper industries, food industries, bioremediation of phenolic compounds etc. 112 , 114 . Furthermore, bacteria have the ability to survive under different environments, and hence, their enzymes may possess wider range of activities, pH and thermal stabilities relative to fungal lignin-degrading enzymes 115 . The potential of the DyP-type peroxidases in wide-ranging applications is revealed by their ability to degrade synthetic dyes 111 and delignification of recalcitrance biomass 38 , 45 , 106 . Our findings revealed that accumulation of DypB in transgenic tobacco increased glucose yield by as much as 91% as compared to the non-transgenic control (248 mg/g vs 130 mg g −1 DM) which appears to be due to modification of lignin in planta prior to saccharification. To our knowledge, this is the first report showing an increase in saccharification efficiency by producing and activating a lignin-degrading enzyme in planta without any pretreatment, revealing the potential of the DypB in breaking recalcitrance and facilitating the conversion of liginocellulosic biomass to biofuels. However, A and B-type DyPs show 100-fold lower activity than C- and D-type peroxidases 51 , suggesting the potential for incorporating the latter enzymes in future research programs addressing biomass recalcitrance through transgenic technology. Alternatively, protein engineering via directed-mutagenesis of amino acid residues as well as motif-swapping among these peroxidases can potentially produce a superior lignin degrading variant. Furthermore, given the synergistic relationship between two or more ligninolytic enzymes that has been shown to improve biomass delignification 9 , 116 , 117 , simultaneous introduction of a set of lignin-degrading enzymes into bioenergy crops may lead to an even more dramatic reduction in biomass recalcitrance. These and similar biotechnology solutions to recalcitrance would tremendously benefit the emerging lignocellulosic biomass-based biofuel and biochemical industry. Several other important industrial applications of lignin degradation biotechnology are anticipated. Since lignin is one of the most abundant biopolymers, and is being produced in large quantities by the paper/pulp and bioethanol industries; there is a need to convert this polymer to a renewable source of high-value aromatic chemicals 10 , 118 . This requires efficient biocatalytic routes for lignin deconstruction using ligninolytic enzymes such as the DyP-type peroxidases as well as microorganisms with pathways engineered for the conversion of the degradation products to high value chemicals. To this end, Sainsbury et al . 118 reported accumulation of vanillin (a valuable food/flavor chemical) and a small amount of ferulic acid and 4-hydroxybenzaldehyde in the ligninolytic bacteria R . jostii RHA1 in which vanillin dehydrogenase gene has been deleted, when cultured on minimal medium containing wheat straw lignocellulose and glucose. Bacterial species with even more active forms of the DyP-type peroxidases, such as Pseudomonas fluorescens Pf-5 96 \n , \n 119 and Amycolatopsis sp . ATCC 39116 strains 75iv2 120 , offer a great potential for extracellular lignin degradation and intracellular aromatic catabolism as a means to valorize lignin in a single step 114 . Such ligninolytic bacteria can also be used for targeted pathway engineering for producing high-value coproducts from lignocellulose. Furthermore, in planta manipulation of enzymes on these pathways may prove a cost-effective way to commercialize chemicals from lignin. Given the reduced amount of lignin derived pyrolysates from biomass in which DypB is pre-activated, such biomass may also improve the quality of bio-oil produced by fast-pyrolysis, a low-cost thermal liquefaction 121 . The use of pyrolysis-derived bio-oil as a refinery feedstock and in wider applications has been hampered by its chemical and physical properties, including several products derived from lignin such as coniferyl alcohol, sinapyl alcohol, isoeugenol, vanillin, vinylguaiacol, methyl guaiacol, guaiacol, and catechol 122 , 123 . Biomass pretreatment that degrades lignin has been shown to improve yield and quality of pyrolysis bio-oil 124 , and using biotechnology to enhance lignin degradation is likely to have similar effects. The approach demonstrated here at laboratory-scale, with accumulation and activation of lignin degrading enzymes such as the DypB in planta and subsequent removal of lignin degradation products prior to biomass pyrolysis, has scale-up potential for the production of higher grade bio-oil that can be refined into transportation fuels as well as higher value products."
} | 8,323 |
35455001 | PMC9032683 | pmc | 2,141 | {
"abstract": "A variety of yeast species have been considered ideal hosts for metabolic engineering to produce value-added chemicals, including the model organism Saccharomyces cerevisiae , as well as non-conventional yeasts including Yarrowia lipolytica , Kluyveromyces marxianus , and Pichia pastoris . However, the metabolic capacity of these microbes is not simply dictated or implied by genus or species alone. Within the same species, yeast strains can display distinct variations in their phenotypes and metabolism, which affect the performance of introduced pathways and the production of interesting compounds. Moreover, it is unclear how this metabolic potential corresponds to function upon rewiring these organisms. These reports thus point out a new consideration for successful metabolic engineering, specifically: what are the best strains to utilize and how does one achieve effective metabolic engineering? Understanding such questions will accelerate the host selection and optimization process for generating yeast cell factories. In this review, we survey recent advances in studying yeast strain variations and utilizing non-type strains in pathway production and metabolic engineering applications. Additionally, we highlight the importance of employing portable methods for metabolic rewiring to best access this metabolic diversity. Finally, we conclude by highlighting the importance of considering strain diversity in metabolic engineering applications.",
"conclusion": "5. Conclusions These studies ( Figure 1 ) collectively illustrate some important considerations for metabolic engineering. Specifically, (1) strain variation must be considered to identify optimal performing cells, (2) basal production levels are not necessarily indicative of rewiring potential, and (3) a variety of generalizable tools are required to tackle strain engineering in non-conventional and non-type organisms. For the latter point, rapid metabolic engineering strategies featuring streamlined plug-and-play cloning [ 61 , 62 , 63 ] and CRISPR-based metabolism rewiring [ 30 , 64 , 65 ] have been developed and tested. Despite these advances, major challenges in non-type strains include polyploid chromosomes and unknown genetic information. Nevertheless, CRISPR-based rewiring approaches, including multiplexed activation, interference, gene disruption, and knock-in, have great potential. The effectiveness of CRISPR proteins and effectors [ 66 , 67 , 68 ], the expression of sgRNA cassettes, and off-target effects need to be tested further when considering non-type strains. With the challenges of engineering aside, strain selection is an underappreciated aspect of metabolic engineering and is poised to become an important parameter in the future. In many of the examples outlined above, the highest production was only achievable upon selecting a non-standard strain. As much as the importance of strain variation is recognized, it remains difficult to predict the strain performance without knowing the genetic, transcriptomic, and metabolomic information of the strains. Moreover, the rewiring potential of a strain is perhaps a more important metric. In this regard, screening through a large number of non-type strains is required and thus necessitates high-throughput screening along with rapid and portable metabolism rewiring approaches. Although still in an early stage, the studies reviewed here provide valuable insights into the importance of considering strain diversity in metabolic engineering applications. With ongoing studies using non-type strains, it is clear that this is a new and important direction to expand yeast cell factories.",
"introduction": "1. Introduction Microbial cell factories provide a renewable means to produce value-added compounds [ 1 , 2 , 3 ]. In contrast to using fossil fuels in chemical synthesis, microbes can utilize renewable bio-resources and alternative substrates, such as agricultural and environmental waste, to build carbon-based molecules [ 4 ]. This shift to sustainable and renewable production is possible due to advances in metabolic engineering. To this end, a significant number of bio-derived chemicals have been demonstrated using microbial cell factories including industrial precursors [ 5 ], fatty acid derivatives [ 6 ], nutrition and health supplements [ 7 ], pharmaceuticals [ 8 ], and other plant-derived natural products [ 9 ]. Across potential microbes of interest, yeasts have unique advantages as eukaryotic microbial cell factories [ 10 ]. As points of evidence, physiological and metabolic differences across yeast hosts, including model yeast Saccharomyces cerevisiae and non-conventional yeasts Yarrowia lipolytica , Kluyveromyces marxianus , and Pichia pastoris , have enabled a high-level production of various polyketides [ 11 , 12 ], terpenes [ 13 , 14 ], and alkaloids [ 15 , 16 ]. Existing P450-related enzymes and secondary metabolite intermediates in yeasts make them uniquely suitable for the production of plant-based products [ 9 ]. In other cases, oleaginous yeast Y. lipolytica and Rhodosporidium toruloides have also been optimized to produce fatty acids and their derivatives [ 17 , 18 ]. Across these hosts, exquisite fermentation condition tolerization (esp. in species like Y. lipolytica and K. marxianus ) [ 19 , 20 ] are favorable for industrial productions. A number of thorough reviews have been published on the topic of yeast cell factories [ 21 , 22 , 23 ] and metabolic engineering of non-conventional yeasts [ 24 , 25 , 26 ]. Even within a specific yeast genus and species, there exists a wide range of strain variation and metabolic potential. Recent studies have highlighted the importance of this variation for successful metabolic engineering. For example, the production of triacetic acid lactone was seen to vary by up to 63-fold across 13 industrial S. cerevisiae strains [ 27 ]. S. cerevisiae CEN.PK was reported to be a better host for p -coumaric acid production compared with S. cerevisiae S288C [ 28 ]. Engineered S. cerevisiae Sigma strains produce more itaconic acid and 2,3-butanediol than engineered CEN.PK and BY4741 strains in the same condition [ 29 , 30 ]. These examples point toward an important facet of metabolic engineering: how to identify the best starting strain. With such production variation abound, the ability to rapidly prototype metabolism through classic and new genetic tools is enabling a broader survey of metabolic potential. Plasmid-based overexpression is generally portable across different strains within the same species [ 27 , 28 , 29 , 30 ]. In addition, advances in genetic manipulation through the use of clustered regularly interspaced short palindromic repeats (CRISPR) and RNA interference (RNAi) contribute to the development of new yeast cell factories [ 29 , 31 ]. Specifically, CRISPR techniques not only accelerate genome-scale engineering in yeasts such as S. cerevisiae [ 32 ] but also establish standardized approaches for rapid metabolic engineering in non-conventional yeasts [ 33 ]. These advances help bypass the previously limited set of genetic tools for these hosts. Certainly, the topic of CRISPR-mediated genome and metabolic engineering in yeasts has been reviewed extensively in the literature [ 34 , 35 , 36 , 37 ]. It will take the combination of diverse starting strains with new genome editing techniques to make truly effective microbial cell factories of the future. In this review, we specifically highlight recent advances that survey yeast metabolic potential, assess non-model and non-type strains for metabolic engineering, and employ portable methods for metabolic rewiring, all of which are summarized in Figure 1 . Through this review, we provide a perspective on how to establish more efficient microbial biotransformation."
} | 1,951 |
33411416 | PMC8248167 | pmc | 2,142 | {
"abstract": "Abstract While the fascinating field of soft machines has grown rapidly over the last two decades, the materials they are constructed from have remained largely unchanged during this time. Parallel activities have led to significant advances in the field of dynamic polymer networks, leading to the design of three‐dimensionally cross‐linked polymeric materials that are able to adapt and transform through stimuli‐induced bond exchange. Recent work has begun to merge these two fields of research by incorporating the stimuli‐responsive properties of dynamic polymer networks into soft machine components. These include dielectric elastomers, stretchable electrodes, nanogenerators, and energy storage devices. In this Minireview, we outline recent progress made in this emerging research area and discuss future directions for the field.",
"introduction": "1 Introduction For centuries, machines and devices have been developed to assist in the undertaking of work in applications such as manufacturing, construction, and healthcare. During this time, significant advances in materials science, engineering, and computation have led to the creation of complex assemblies of rigid materials that are capable of carrying out the most intricate of tasks. However, there are specific application areas where the use of these advanced machines has been limited. This is, in part, because of the high density, high hardness, and low compliance of the materials that they are made from, which confine them to a single specific task. It can also make them energy inefficient during operation, and make them dangerous to use alongside, or when interacting with, humans. In response to these limitations, there has been intensive research effort in recent years towards the development of soft machines \n [1] \n that can consist of soft components, such as sensors, \n [2] \n actuators, \n [3] \n and energy generators. \n [4] \n \n From a materials perspective, since the 1990s, silicone, acrylic (3M™ VHB™), and polyurethane have been the dielectric elastomers most commonly used in soft machine applications due to their large mechanical strain to failure (300–900 %), high energy density (10–150 kJ m −3 ), and rapid response (10 −3 s). \n [5] \n However, these materials possess intrinsic limitations to their performance, such as low relative permittivity ( ϵ \n r =2–10), high viscous losses, and poor tear resistance. In addition, stress‐relaxation and creep strongly influence the behaviour of elastomers during stress cycling, as the energy from an applied mechanical strain is dissipated through a variety of mechanisms, such as polymer chain movement and chain disentanglement. This gives rise to hysteresis effects that reduce the energy required to strain these elastomers, often resulting in mechanical and electromechanical instabilities that make them more susceptible to failure over time. \n [6] \n The lifetime of these materials can be enhanced by operating at low strains to prevent damage, \n [7] \n or by introducing cross‐links that simultaneously inhibit creep, whilst retaining high strain properties. Device efficiency is benefitted by the latter strategy, however, the permanent nature of conventional covalent cross‐links is detrimental to the sustainability of these materials, since they limit the potential for recycling. \n [8] \n \n To overcome this challenge, the emerging chemistry of dynamic polymer networks (DPNs) is shedding light on a new generation of smart and reprocessable materials. These systems consist of dynamic interactions that allow for rearrangements of their network topology and adaptation of their properties in response to an environmental stimulus. \n [9] \n The cross‐linking of DPNs can be covalent or non‐covalent, and the materials they form may be classified as either dissociative, associative, or supramolecular networks, depending on the exchange chemistry of their dynamic bonds, as summarised in Figure 1 . Dissociative networks, illustrated in Figure 1 a , possess an equilibrium between the association and dissociation of their cross‐links. After the formation of the network, the equilibrium can be shifted towards dissociation through the application of an external stimulus, such as heat or light, which decreases the cross‐link density and eventually results in the formation of free polymer chains. In contrast, associative networks, sometimes termed vitrimers, \n [10] \n respond to these stimuli by undergoing exchange reactions, such as those given in Figure 1 b , which facilitates bond exchange whilst also maintaining a constant number of cross‐links in the network. \n [11] \n Supramolecular networks have the same exchange mechanism as dissociative networks but are formed when molecules are linked through physical associations; for this Minireview we will specifically refer to their formation between macromolecules, as shown in Figure 1 c .\n Figure 1 Illustration of important bonds found in a) dissociative networks, b) associative networks, and c) supramolecular networks. In a similar way to conventional covalent cross‐links, dynamic covalent bonds can reduce creep in elastomers, \n [8b] \n whilst also allowing efficient reprocessing of the material and imparting self‐healing functionality. \n [12] \n Supramolecular interactions can also contribute to the formation of a creep resistant elastomer, however, since their bond strength is typically lower than dynamic covalent bonds these linkages are less effective in reducing creep. \n [13] \n The creation of specific combinations of dynamic covalent bonds and supramolecular interactions has a high potential to generate autonomously self‐healing, reprocessable, and low creep elastomers, \n [14] \n which are electromechanically stable, have a high extensibility, and can be subjected to large applied electric fields with a reduced likelihood of premature failure. There are several excellent reviews on the synthesis and characterisation of DPNs, \n [15] \n ranging from the polymerisation of functional monomers to the functionalisation of commercial elastomers. Emerging work on the application of DPNs in fields such as polymeric actuators, engineering rubbers, and tissue engineering has also been recently reviewed. \n [16] \n However, ongoing research is demonstrating that the adaptive and reprocessable features of DPNs offer new opportunities for next generation electroactive polymers for smart soft machines. It is therefore timely to analyse the potential for exploiting DPNs in stretchable electronics and soft machine applications, including dielectric elastomers, flexible and stretchable electrodes, nanogenerators, and soft components for energy storage. For each application we will critically evaluate the design strategies of the DPNs, and how the mechanisms of exchange can influence the electromechanical, thermomechanical, and electrochemical performance of the materials and devices."
} | 1,728 |
35564424 | PMC9099716 | pmc | 2,144 | {
"abstract": "With the rapid development of industrialization and urbanization, soil contamination with heavy metal (HM) has gradually become a global environmental problem. Lead (Pb) is one of the most abundant toxic metals in soil and high concentrations of Pb can inhibit plant growth, harm human health, and damage soil properties, including quality and stability. Arbuscular mycorrhizal fungi (AMF) are a type of obligate symbiotic soil microorganism forming symbiotic associations with most terrestrial plants, which play an essential role in the remediation of HM-polluted soils. In this study, we investigated the effects of AMF on the stability of soil aggregates under Pb stress in a pot experiment. The results showed that the hyphal density (HLD) and spore density (SPD) of the AMF in the soil were significantly reduced at Pb stress levels of 1000 mg kg −1 and 2000 mg kg −1 . AMF inoculation strongly improved the concentration of glomalin-related soil protein (GRSP). The percentage of soil particles >2 mm and 2–1 mm in the AMF-inoculation treatment was higher than that in the non-AMF-inoculation treatment, while the Pb stress increased the percentage of soil particles <0.053 mm and 0.25–0.53 mm. HLD, total glomalin-related soil protein (T-GRSP), and easily extractable glomalin-related soil protein (EE-GRSP) were the three dominant factors regulating the stability of the soil aggregates, based on the random forest model analysis. Furthermore, the structural equation modeling analysis indicated that the Pb stress exerted an indirect effect on the soil-aggregate stability by regulating the HLD or the GRSP, while only the GRSP had a direct effect on the mean weight diameter (MWD) and geometric mean diameter (GMD). The current study increases the understanding of the mechanism through which soil degradation is caused by Pb stress, and emphasizes the crucial importance of glomalin in maintaining the soil-aggregate stability in HM-contaminated ecosystems.",
"conclusion": "5. Conclusions Medium and high concentrations of Pb stress (>1000 mg kg −1 ) significantly inhibited the growth and development of AMF, with a significant decrease in MC, HLD, SPD, and AMF-secreted glomalin. Meanwhile, the AMF showed a certain tolerance to Pb stress, and there were no significant differences in the MC, HLD, SPD, and glomalin contents under low concentrations of Pb stress (500 mg kg −1 ) compared with the control. This was also possibly due to the low availability of Pb under slightly alkaline conditions. The Pb stress increased the mass percentages of fine sand, silt, and clay particles (<0.25 mm), while it decreased the mass percentages of gravel (>1 mm), resulting in a significant negative correlation between the soil-aggregate stability and the Pb concentration. AMF hyphals and glomalin play important roles in the formation of large soil aggregates, and HLD and glomalin content are both significantly and positively correlated with the stability of soil aggregates. According to the random forest model and structural equation model, we further determined that the HLD of the AMF, EE-GRSP, and T-GRSP were the most important factors driving the stability of the soil aggregates, while the Pb stress mainly affected the soil-aggregate stability indirectly, by regulating the HLD and the glomalin. The HLD also indirectly influenced the stability of the soil aggregates by regulating the glomalin. Therefore, focusing on the protection of glomalin and AMF is the key strategy to achieving rapid soil-structure restoration in degraded ecosystems polluted by HM.",
"introduction": "1. Introduction Arbuscular mycorrhiza fungi (AMF) are a group of soil fungi with a wide distribution and important ecosystem functions. They can establish mutualistic symbiosis with approximately 80% of terrestrial plants [ 1 ], and they play an essential role in facilitating plant nutrient uptake, improving plant stress resistance, modifying soil structure, and restoring degraded ecosystems [ 2 , 3 ]. The extraradical hyphae formed by AMF can extend beyond the nutrient-deficient zone of the rhizosphere and enhance the absorption of phosphorus, nitrogen, and water. In turn, the host plant supplies 4–20% of the carbon hydration produced by photosynthesis to AMF to meet its growth and development needs [ 4 ]. In addition, AMF can also improve the adaptability of plants to environmental stresses by enhancing the expression of antioxidant enzymes, aquaporin, metallothionein, and other related genes [ 5 , 6 , 7 ]. AMF form a common mycorrhizal network among different plant species, thereby regulating important ecological processes such as nutrient distribution [ 8 ], plant competition [ 9 ], and community structure and succession [ 10 ]. However, the essential role of AMF in the stability of soil aggregates in degraded ecosystems remains unclear. Soil is not only an important component of the terrestrial ecosystem, but also the source of the nutrients in our food supply. Soil structure is one of the most important soil properties, which determines structure, determines the retention, transformation, and transfer efficiency of water, air, heat, and nutrients in soil. The composition and stability of soil aggregates, which are the foundations of soil structure, are essential factors affecting soil fertility and ecosystem functions. Moreover, AMF hyphae and the produced glycoprotein (glomalin) can bind soil particles together through the “bonding–joining–packing” mechanism, and then act as bio-glue to promote the formation of large aggregates and increase the stability of the soil’s structure [ 11 ]. Glomalin is a special type of glycoprotein, produced specifically by hyphae and spores of AMF and released into the soil after decomposition; it is widely distributed, hydrophobic, insoluble, and recalcitrant in nature [ 12 ]. Previous studies indicated that AMF inoculation increased the GRSP content, mean weight diameter (MWD), and geometric mean diameter (GMD) of soil aggregates [ 13 ]. However, the relationships between the AMF growth index, GRSP, MWD, and GMD, and whether the effects of AMF on soil-aggregate stability are linked to GRSP, remain unclear. Soil contamination by HMs constitutes a serious environmental problem. Pb is one of the most widely distributed and harmful toxic HMs in soil. China is the world’s largest producer of mineral Pb, with 63.9% of the world’s total mineral Pb production in 2020 (China Lead Industry Development Report 2020). In recent years, Pb contamination caused by mining, smelting, processing and other activities is increasing, and HM pollution incidents, such as blood Pb overload, have occurred from time to time [ 14 ]. In order to effectively address soil Pb contamination and restore degraded ecosystems, related research and practice have been comprehensively carried out in China. Most previous studies focused on distribution patterns [ 15 , 16 ], health-risk assessments [ 17 , 18 ], and remediation technology related to Pb-contaminated soil [ 19 , 20 ]. However, the positive effects of AMF on HM contamination as a bioremediation strategy to reduce the damage caused by Pb are still unclear. In view of this, a three-compartment root box was used in this study to investigate the effects of AMF inoculation on GRSP and the composition, and stability of soil aggregates under Pb stress. The objectives of this research are (1) to clarify the effects of Pb stress on AMF growth, GRSP, and the composition and stability of soil aggregates; and (2) to analyze of the effect of the AMF pathway on soil aggregates’ stability under Pb stress. This study provides a scientific basis for understanding the physiological and ecological functions of AMF and their potential value in restoring degraded ecosystems.",
"discussion": "4. Discussion 4.1. Effect of Pb Stress on AMF Growth Parameters and Glomalin-Related Soil Proteins Lead is an extremely dangerous and toxic pollutant for the growth and development of organisms, and it is widely distributed in nature. Pb stress induces the production of large amounts of reactive oxygen species (ROS) in biological cells, mainly including superoxide anion (O 2 − ), hydrogen peroxide (H 2 O 2 ), and hydroxyl radical (-OH). Small amounts of ROS generated by external stimulation during signal transmission can stimulate signaling pathways, participate in cellular signal transduction processes and activate antioxidant signaling pathways in the body [ 29 ]. However, the accumulation of ROS can lead to oxidative stress in cells, causing cell membrane degeneration, ion leakage, lipid peroxidation, DNA/RNA denaturation, and, eventually, cell lysis. In addition, Pb 2+ can lead to reduced enzyme activity or even inactivation by both competing for the ion-binding site of the enzyme and inhibiting the active center of the enzyme, further aggravating the accumulation and toxicity of ROS in the cells. In this study, compared with the control treatment (0 mg kg −1 Pb), the hyphal density and spore density of AMF were significantly reduced at medium and high levels of Pb stress (1000 mg kg −1 and 2000 mg kg −1 ), but there was no significant difference at low levels of Pb stress (500 mg kg −1 ) ( Figure 2 ). This was mainly due to the oxidative stress response of the AMF cells to medium and high concentrations of Pb stress, and the accumulation of ROS caused lipid peroxidation, cell membrane rupture, and an imbalance in the content and ratio of ions, which finally affected the growth and development of the AMF, resulting in a significant decrease in hyphal density and spore density. However, at low levels of Pb stress, Pb 2+ induced an increase in the activities of the AMF cellular antioxidant substances (vitamins, glutathione, etc.) and antioxidant enzymes (oxide dismutase, ascorbate peroxidase, catalase, etc.), which eventually transformed the ROS into harmless H 2 O molecules through a series of chemical reactions, achieving a balance between ROS production and elimination. It can be seen that the AMF had a certain tolerance to Pb stress, which was closely related to the Pb concentration. When the Pb concentration exceeded 500 mg kg −1 , the growth, development, and proliferation of the AMF were significantly inhibited. Additionally, the toxic effect of Pb largely depends on its bioavailability. The slightly alkaline condition (pH = 7.61) in this study might have caused the low mobility of the Pb in the soils, which could also partly explain the low toxic effects of the Pb on the AMF growth parameters [ 30 , 31 , 32 ]. Glomalin-related soil proteins (GRSP) are a special class of glycoprotein, specifically released by the hyphals and spores of AMF, which are abundant in soil and can be classified into two types: total glomalin-related soil proteins (T-GRSP) and easily extractable glomalin-related soil proteins (EE-GRSP) [ 12 ]. GRSPs have a long turnover time in soil and are not easily degradable. They play an important role in promoting soil organic carbon (TOC) accumulation, improving soil water and thermal conditions, improving the stability of soil aggregates, and regulating plant growth and community development. In this study, the T-GRSP and EE-GRSP contents gradually decreased with the increasing Pb stress, while there was no significant difference between the control treatment and the low-concentration Pb-stress treatment ( Figure 3 ). These results were consistent with the pattern of the changes in the hyphal density and spore density of the AMF under Pb stress, indicating that the GRSP was a glycoprotein produced and secreted into the soil by the hyphals and spores of the AMF. A study by Yang et al. showed that both T-GRSP and EE-GRSP contents in AMF inoculation treatments were significantly and negatively correlated with heavy-metal Pb concentration, which was consistent with the results of this study [ 33 ]. Nevertheless, the present study found that there was no significant difference in the content of the GRSP (T-GRSP and EE-GRSP). This was mainly because the GRSP was specifically secreted by the AMF, and since there were no hyphals or spores in the uninoculated AMF treatment, no EE-GRSP was produced. 4.2. Effects of Pb Stress on Soil-Aggregate Stability At present, studies on aggregates generally focus on the particle size, composition, and stability, nutrient content characteristics, and organic carbon content of aggregates, but the content and enrichment characteristics of heavy metals in aggregates and their effects on the stability of aggregates are rarely reported [ 34 , 35 , 36 ]. In this study, it was found that the Pb treatment significantly increased the proportion of soil grains <0.053 mm, while it significantly decreased the proportion of soil grains >2 mm and 2–1 mm, inhibiting the formation of soil macroaggregates ( Figure 4 ), leading to a significant negative correlation between the Pb concentration and the soil-aggregate stability ( p < 0.001). This was mainly due to the inhibitory effect of the Pb stress on the growth and development of the AMF ( Figure 2 ), which significantly reduced the glomalin-related soil protein content released into the soil ( Figure 3 ). The glomalin-related soil proteins, as special glycoproteins, played an important role in the formation of soil aggregates, which could bind soil particles together and then gradually form macroaggregate structures through the “bonding–joining–packing” hyphal mechanism, thereby improving the stability of the soil aggregates [ 37 ]. Therefore, the reduction in hyphal density and glomalin-related soil protein content caused by Pb stress might be the primary cause of decreases in soil aggregate stability. 4.3. Pathways of Pb Affecting Soil-Aggregate Stability The colonization characteristics of AMF are important factors affecting the stability of soil aggregates. In order to reveal the relationship between AMF and the stability of soil aggregates under Pb stress, previous studies mostly used ANOVA and correlation analysis to analyze the direct relationship between the relevant factors, the mean weight diameter, and the geometric mean diameter while ignoring the complex interactions between these factors and failing to distinguish the possible direct or indirect pathways of action. In this study, we used random forest modeling and structural equation modeling to determine the mechanism through which Pb stress indirectly affects the stability of soil aggregates by impacting the AMF colonization characteristics. The results of the random forest model analysis showed that the hyphal density (HLD), easily extractable glomalin-related soil protein (EE-GRSP), total glomalin-related soil protein (T-GRSP) and spore density (SPD) had significant effects on the mean weight diameter (MWD) ( p < 0.05), and the mean square error increases in the four characteristic variables were 6.47%, 6.42%, 5.40%, and 4.46%, respectively ( Figure 7 ). Furthermore, only the HLD, EE-GRSP, and T-GRSP had a remarkable effect on the GMD ( p < 0.05), with mean square error increases of 6.32%, 5.80%, and 5.29% for the three characteristic variables, respectively ( Figure 7 ). These results indicated that the HLD, EE-GRSP, and T-GRSP were the dominant factors affecting the stability of the soil aggregates. These findings were consistent with previous findings that AMF colonization characteristics and specific secreted GRSP play an important role in soil-aggregate stability [ 38 ]. In this study, we further considered the interaction between multiple factors under Pb stress and used structural equation modeling to reveal the pathway through which Pb indirectly affects soil-aggregate stability through HLD and GRSP ( Figure 8 ). The Pb stress had a negative direct effect on the HLD (−0.831) and GRSP (−0.679), and the GRSP had a positive direct effect on both the MWD (0.956) and the GMD (0.871), but the HLD had a positive indirect effect on the soil-aggregate stability through the GRSP (0.364). This might have been due to the fact that the Pb stress significantly inhibited the growth and development of the AMF, and the hyphal structure was disrupted, releasing a large amount of GRSP into the soil and weakening its direct contribution to the stability of the aggregates. Therefore, in HM-contaminated ecosystems, it is important to focus on maintaining the GRSP content in the soil, thus contributing to the improvement of the soil-aggregate stability and preventing the destruction of the soil structure."
} | 4,117 |
29806719 | null | s2 | 2,147 | {
"abstract": "Quorum sensing (QS) exists widely among bacteria, enabling a transition to multicellular behaviour after bacterial populations reach a particular density. The coordination of multicellularity enables biotechnological application, dissolution of biofilms, coordination of virulence, and so forth. Here, a method to elicit and subsequently disperse multicellular behaviour among QS-negative cells is developed using magnetic nanoparticle assembly. We fabricated magnetic nanoparticles (MNPs, ∼5 nm) that electrostatically collect wild-type (WT) Escherichia coli BL21 cells and brings them into proximity of bioengineered E. coli [CT104 (W3110 lsrFG"
} | 161 |
29215064 | PMC5719441 | pmc | 2,148 | {
"abstract": "Bio-inspired technologies have remarkable potential for energy harvesting from clean and sustainable energy sources. Inspired by the hummingbird-wing structure, we propose a shape-adaptive, lightweight triboelectric nanogenerator (TENG) designed to exploit the unique flutter mechanics of the hummingbird for small-scale wind energy harvesting. The flutter is confined between two surfaces for contact electrification upon oscillation. We investigate the flutter mechanics on multiple contact surfaces with several free-standing and lightweight electrification designs. The flutter driven-TENGs are deposited on simplified wing designs to match the electrical performance with variations in wind speed. The hummingbird TENG (H-TENG) device weighed 10 g, making it one of the lightest TENG harvesters in the literature. With a six TENG network, the hybrid design attained a 1.5 W m −2 peak electrical output at 7.5 m/s wind speed with an approximately linear increase in charge rate with the increased number of TENG harvesters. We demonstrate the ability of the H-TENG networks to operate Internet of Things (IoT) devices from sustainable and renewable energy sources.",
"conclusion": "Conclusions In this paper, a functional TENG is developed for wind energy harvesting through an innovative hummingbird wing-inspired design. The lightweight, low-cost TENGs are fully enclosed within the wing design with a fluttering wing inside to induce contact-separation and free-standing electrification modes with external contact-separation flags for multiple triboelectric material combinations. Mimicking the unique strokes of the hummingbird’s wings, the fluttering of H-TENG can operate with low-frequency wind excitations at harsh conditions. The 10 g lightweight H-TENG device is reported to be one of the lightest TENG device ever made, realized by the bio-inspired design of the hummingbird wings. This provides enormous potential for TENGs to be more competitive than ever in terms of energy efficiency with low mass and low-cost for deployment and installation as opposed to current wind energy technologies. Parallel connections of single TENG units were fabricated in a hybridized wind harvester network. The hybrid system of six H-TENG units is capable of achieving a peak electrical output of 1.5 W m −2 at an optimum wind speed of 7.5 m/s. Varying the number of TENG units experienced a linear relation with the output power density and charge rate, making it highly desirable for a multi-modal and more comprehensive wind energy harvesting. Furthermore, an IoT device is powered by the presented nanogenerators for wireless sensor networks and remote operations such as humidity, temperature, and atmospheric pressure sensors.",
"introduction": "Introduction Energy harvesting has been an increasingly desirable field of research and progress for the past two decades due to its reliability, cost-efficiency and sustainability 1 . External energy sources like solar, wind, vibration, acoustic, and thermal are in perpetual development to fully actualize sustainable energy farms in the near future 2 , 3 . To that end, the role of green technologies is fundamental in minimizing dependence on depleting energy sources and their ensuing environmental impact 4 , 5 . Wind energy is regarded as one of the most opportune sources of clean and sustainable energy 6 , 7 for functional energy harvesting against elaborate conditions 8 , 9 . Other energy harvesting sources have adopted wind energy techniques of rotary/turbine configurations due to the established knowledge from the wind energy harvesting sector 10 , 11 , indicating its dominance in development and reliability for projected large-scale power plants 12 , 13 . However, the current standards of wind energy techniques are not without environmental consequences. Multiple studies have stressed the significant environmental impacts of existing wind turbines on local and regional climates 14 . Moreover, the complex, bulky and expensive wind turbines are hardly employed for small systems or personal devices. To counter such negative effect, research on miniature or smaller-scale energy harvesters has evolved rapidly in the past decade 1 . Their conceptual simplicity, higher cost-effectiveness, and mobility in various scientific fields elicit minimal interference upon ecosystems 15 , 16 . The current field of microscale energy harvesting is still in its infancy, and is in a growing need for enhanced and innovative designs towards adaptive and sustainable energy conversion prospects. Bio-inspired and biomimetic engineering has illustrated strong potential in enhanced design performance in multiple scientific fields due to unique Multiphysics within the hierarchy of biological structures and organisms 17 , 18 . Numerous studies adopted biomimicry in solar cell harvesting, mainly by photosynthesis imitations 19 , 20 , such as in enhanced flight of miniature unmanned vehicles (MUVs) 21 , 22 . The work flight path of certain creatures (like birds and insects) were investigated to examine their aerodynamics and flight kinematics 23 , 24 . The hummingbird has been a subject of interest for quite some time due to its sustained hovering and unique wing-stroke maneuvers 25 , 26 . The aerodynamics of such birds induce vortices over the wing while the wing segments suffer from high temporal deformation patterns during flights in low-wind force scales 27 , 28 . Recently, the knowledge obtained from the newly developed TENGs 29 – 31 has been applied in bio-inspired and biomimetic engineering. TENGs utilize contact electrification and electrostatic induction to convert external stimuli to electrical current 32 , 33 for air pollution cleaning 34 , wind energy harvesting 35 , water energy harvesting 36 , 37 , self-powered machine interfacing 38 , micro/nano-system actuating 39 , etc. TENGs are desirable due to their low-mass density, simple fabrication 40 , 41 , high-transferability, environmental friendly 42 and adaptive modes of operation 43 , 44 . In a bio-inspired TENG model, researchers developed a wireless sensor network (WSN) for enhanced hydrokinetic energy conversion from water-contacted TENGs using a duck-shaped harvester for superior stability 35 . In another example, TENGs were arranged in forest-like arrays of lawn on rooftops to exploit upcoming wind at a multitude of force scales 45 . However, the TENGs have yet to be fully integrated with a bio-inspired design mechanism for enhanced adaptivity and reconfigurability against highly fluctuating wind flow, which could allow the bio-mimetic TENGs to be used in more applications. In the present work, we investigate a fabricated hummingbird wing fitted with TENGs for reconfigurability and performance against established conditions. The developed design is aimed to shift through weak and strong winds in multiple directions in the simulated environment. The work examines the flapping (Strokes) of the synthesized wings on a contact surface as a contact triboelectric mode. A second mode is introduced by flapping flag objects within the wings to enhance the energy harvesting mechanism from hummingbird mimicry. We have developed a novel, lightweight TENG which harvests wind energy from the environment as well as from human breath and generates power for self-powered applications. Because of its lightweight and extremely simple structure, it has great application prospects for fabricating sustainable wind energy harvesters. We also report high-energy density for one of the lightest TENG harvester with a mass of 10 g, made possible by the bio-inspired hummingbird TENG wing. Moreover, the H-TENG has the advantage of harvesting wind energy from different directions and different angles of attack. Electrical and fluid analyses are incorporated to capture the interplay dependence between the two disciplines during the upstroke and downstroke phase motions of the wing. The harvested energy can be either stored in battery packs or directly integrated with devices. Such characteristics precisely define micro-scale sensing and small-scale wind energy harvesting applications. The developed apparatus is also used to power up humidity, atmospheric pressure and temperature sensors fitted in an Internet of Things IoT infrastructure 46 .",
"discussion": "Results and Discussion The design of the H-TENG Harvester In this study, a bio-inspired H-TENG design is utilized to simulate the bird wing kinematics for power harvesting and sensing applications. The fabricated harvester induces high-speed wing flutter that captures the commendable flapping-path of this adaptive creature. The H-TENG based wind harvesting system is demonstrated in Fig. 1 . The energy generation of the proposed design is majorly governed by two mechanisms: external flag motion and internal single-electrode TENG. The first mechanism utilizes upper and lower flags that flap onto their respective surfaces, creating a high sequence of oscillatory contact-propagation-separation motion. Thus, the total contact area of the two tribo-layers is increased and decreased steadily as a result of wind turbulence. Therefore, an effective contact area strongly dictates the electrical output from the fluttering behavior. Figure 1b shows the images of wing kinematics behavior for the single and double-contact modes (see supporting Movie S1 ), The H-TENG configuration, shown in Fig. 1c–i , was designed based on these working mechanisms. The H-TENG consists of a metal (Al) and an insulator (Fluorinated Ethylene Propylene, FEP) structure in contact. FEP tends to gain electrons on its surface due to electrification effects and becomes negatively charged. Strong electrostatic attraction ensures adequate contact of the Al with FEP flag under no external flow. When a wind flow is induced, the flag experiences a backward and forward movement resembling a pendulum motion. In the separate state, the electrical charge difference is reduced to zero as no contact is established. In the contact state, the propagation process occurs immediately after contact that causes a sequential process of gradual increase and decrease in contact surface area. To put it simply, a higher electrical potential upon the FEP flag is amplified with a steady increase in the contact surface and vice versa. An alternating current from the Al electrode and FEP flag is generated from the applied potential difference that originates when the flag sequentially approaches the plate. Figure 1 Schematic and experimental structure of a hummingbird wind TENG. ( a ) 3D modeling of the proposed H-TENG wind harvester (with SEM photo at 1 μm scale bar for the Al surface on the left, and SEM image of the FEP polymer nanowires at sale bar is 500 nm on the right), Inset photos represent the real hummingbird bird and the real hummingbird TENG. ( b ) H-TENG kinematics analysis in front and top views ( c ) 3D model of the hummingbird wing with description of the three TENGs configurations; at the top (TENG 1), at the bottom (TENG 2) and inside the wing (TENG 3) (i) Working mechanism of the flag TENG which is placed on the top and bottom of the H-TENG harvester wing. (ii) Working mechanism of the flag inside the wing as a second mode to harvest the mechanical motion resulting from the wind and mimicking the hummingbird flapping motion, ( d ) Potential distribution of the device for different flags using COMSOL. \n Another wind energy harvesting mechanism, displayed in Fig. 1c–ii , is also investigated in our H-TENG. In this case, electricity is generated from two TENG units embedded within the wing design with a vertical contact-separation TENG mode. Full contact is secured from fractions of the top Al and FEP film such that a triboelectric polarity difference induces triboelectric charges. When the FEP film moves towards the top, the electrical measurements on the two TENGs inside the wing reveal an output current/voltage signal on each TENG as in contact state with the top Al (Fig. 1c–ii ). To understand the underlying mechanisms, a computational analysis was conducted on a single H-TENG by finite element method (FEM) in COMSOL software. A two-dimensional schematic flow of the contact-propagation-separation motion with charge distribution simulations is presented in Fig. 1d . Figure 1d–1 shows the initial contact between the flag and plate without external flow, while Fig. 1d–2,3 demonstrates the decrease in contact area during external flow. Finally, Fig. 1d–4 shows the maximum amplitude of fluttering motion phase. Figure 2 Wing aerodynamics modeling and experimental setup. ( a ) Wing geometry parameters and components of the total aerodynamic force in upstroke and downstroke. ( b ) The averaged trajectory of the wing tip in the XZ-plane. ( c ) Measuring setup inside the closed system wind tunnel while monitoring the wind speed values and the wind tunnel. \n Figure 3 H-TENG characteristic studies. ( a ) Output voltage of the TENG at different flag length ratios. ( b ) The output voltage of the TENG at different heights of the channel inside the wing from 5 mm to 15 mm. ( c ) The output voltage of the TENG at different angles of attack of the channel from −36° to 36°. ( d ) Dependence of the Short-circuit current, I SC of the H-TENG with varying wind speeds from 3 to 15 m/s. ( e ) Load resistance dependency on the current, voltage and power density for one unit of H-TENG. ( f ) Dependence of the power output with a number of units, n (n = 1, 2, 4 and 6) on the resistance load. ( g ) Charging curves of a capacitor (capacity: 1 µF) for energy storage by one, three and six hummingbird TENGs. Inset figure is a tree shape network of hummingbird TENG units for portable wind harvesting applications, ( h ) Image of 50 powered LEDs using one unit of the H-TENG. \n Figure 4 ( a ) A circuit diagram of the self-powered wireless environmental node (pressure-temperature-humidity) for IoT applications enabled by H-TENG. ( b ) The power management circuit, battery, router, environmental sensor node, H-TENG and a wireless module. ( c ) The temperature, pressure, and humidity are transmitted from the wireless sensor node system to a mobile and a computer screen. The inset figure shows the enlarged values of sensor outputs on a web browser in a laptop as its IoT application. \n Aerodynamics modeling and experimental setup A Multiphysics computational analysis was conducted to evaluate the fluid-solid interactions and the aerodynamic performance of the TENG device. The main force components of the present study are wing translation forces with normal and tangential part F N \n tr and F T \n tr , wing rotation forces F Nr and added wing mass inertia forces F Na . Figure 2a illustrates the applied normal and tangential components and their direction, along with their respective relations with drag and lift forces. During the upstroke of the wing, the pressure and velocity vector distribution results are calculated and depicted in Supplementary Figure 2(a) , whereas Fig. 2a displays the essential geometric parameters of the wing with wing length R and mean chord length c. It is worth mentioning that variations in the force occur only with the velocity of the center of pressure UCP at a specified angle of attack α and a given form of the wing. The angle between the wing’s negative x-axis and the UCP velocity vector is what we have defined as the angle of attack as shown in Fig. 2a . When the normal component of the forces F N is set at the z- direction, the positive values are obtained during the downstroke and negative at upstrokes for right hovering case hovering. The tangential component of the force F T , which acts in the x-axis, is either positive or zero during hovering. The lift forces F L are attributed to the resultant normal forces within the instantaneous stroke plane, while drag F D is defined as the opposing force to the direction of the instantaneous tip velocity vector. Over on cycle, the lift C L and drag C D coefficients are calculated and portrayed in Supplementary Figure 2(b,c) , respectively. The positive dependency of the drag on the vertical forces is represented in Supplementary Figure 2(b) during the first half of the downstroke. The second half of the downstroke shows minor negative/detrimental relations between the two quantities. Drag was observed to be negative, on the most part, during upstrokes of the wings with small magnitudes. Excluding the vertical-drag forces would not render the lift coefficient C L symmetric between downstroke and upstrokes, as observed in Supplementary Figure 2(d) , along with its vertical component, C L , Z. A similar, asymmetric trend to the vertical forces is perceived in Supplementary Figure 2(c) for the power coefficient. Additionally, the computational analysis has shown that the ratio of powers exerted between downstroke and upstrokes is about 2.8. The power coefficient value was averaged throughout the cycle magnitudes and was found to be C P ~ 2. Trajectories from cycle-averaged calculations were obtained for the right-wing tip in the XZ plane, where the plot in Fig. 2b represents the deviation from the mean stroke plane. Decomposition of the generated force into aerodynamic lift and drag is provoked from the mean observations of the figure. From Fig. 2a , the aerodynamic lift corresponds to the force perpendicular to the wing translation while aerodynamic drag is attributed to the force opposite to the wing translation. Moreover, as illustrated in Fig. 2c , all measurements were conducted inside a closed wind tunnel. This enabled effortless control of the wind speeds while observation recordings were made. System Optimization The geometrical and material properties of the device were calibrated according to the highest performance achieved by the TENG setup. Initially, the H-TENG is optimized for output results with different triboelectric materials as shown in Supplementary Figure 1(b,c) (see Supplementary Note 1). Moreover, the number of flag strips inversely affects the output voltage as illustrated in Fig. 3a and Supplementary Figure 1(a) . Wind cross flow on the FEP flags generates a distinct vibration mode on each flag that causes a chaotic status in contact-separation behavior between the triboelectric layers. The interfacial charge transfer can thus be suppressed by this behavior, leading to a lower output. Furthermore, the aerodynamic energy is converted into electricity by the flag-shaped TENG device by changing contact status on the FEP/Al foil. The output voltage first increases and then decreases as the height of the TENG flag inside the wing is increased (Fig. 3b ). The maximum output voltage is attained at a height of 7 mm, and thereafter all subsequent experiments are conducted at 7 mm height between the two wings. This arrangement is selected to ensure effortless and effective switching between the FEP film and Al electrode in contact-separation mode at the fabricated optimum height. As a result, the flag is allowed to harness more wind energy than the other configurations since the mechanical motion and the electrical power output of the H-TENG design is heavily influenced by the angle of attack. The optimum output was achieved at an angle of attack of approximately −18°, as illustrated in Fig. 3c . This would permit the wing to have a higher lift coefficient and a lower drag force. The angle of attack is made adjustable in the current design in order to control the wind direction. Extremely low and variable motion frequencies are inherent in wind flows. Ultimately, device performance must be investigated intensely against different wind speeds for practical applications. The wind speeds are made to vary from 3–15 m/s to examine a multi-unit H-TENG from low to high wind speeds. The bio-inspired design not only achieves a unique kinematic excitation for superior energy harvesting but also enhances the lightweight limit a TENG device can reach. The H-TENG device weighed just 10 g, illustrating a high potential for large energy harvesting networks with a high-density H-TENG distribution. To our knowledge, our current design is one of the lightest TENG for wind energy harvesting. This holds a promising position for energy efficiency, transferability, and deployment which makes the design more competitive with current state-of-the-art wind energy harvesting technologies. The short-circuit current I SC results are shown in Fig. 3(d) for multiple wind speeds. The output current is notably small at low levels of wind speeds. At higher wind speeds, the measured parameters have a drastic increase in their respective peak amplitudes, suggesting a linear dependence between the current and wind speed. Such performance originates from large aerodynamic forces with lesser contact times between the surfaces. This entails a wide variety of a potential application involving our flag-like TENG for wind speed detection, humidity, and pressure estimations. For wind speed values larger than 9 m/s, the voltage and current do not experience the same dramatic increase when higher speeds dominate the wind flow. On a single TENG unit, external loads are crucial to voltage, current and power performances of the device. For characterizing the H-TENG outputs under different loads, three TENG flags were made on a single H-TENG unit, connected in parallel with a variable resistor box. The effect of changing the external loads on voltage and current values at a wind speed of 7.5 m/s is captured in Fig. 3e . An exponential increase in voltage is noticed as the resistance increases, where the peak value matches the highest resistance state. However, with an external load of the minimum resistance value, the Ohmic losses impose a disproportionate behavior on current, thus attaining a maximum current output at that minimum. A maximum power output is observed at an external load of 10 MΩ. At this resistance value, a peak power density value of 0.3 W m −2 was gained for the overall device. Multi-network integration feasibility was also assessed for the nanogenerators. To investigate the effect of the number of H-TENG units on output power, six identical H-TENG units were fabricated to contain three TENGs each as shown in Fig. 3g . The hybridized system is thus obtained by connecting the units in parallel for subsequent testing at a wind speed of 7.5 m/s. The power generated against load resistances for different numbers of integrated TENG units (n = 1, 2, 4, 6) is shown in Fig. 3f . It was observed that the power peak value would significantly enhance as the number of units is increased up to a maximum peak power of 1.5 W m −2 for n = 6. Therefore, the hybrid system of H-TENGs would be an excellent option for wind energy harvesting networks. One such case of network generators is exemplified in Fig. 3g . Simplified attachments of H-TENG unit series can be fitted with wind guides for directional adjustment of oscillating units to accommodate the wind incidence angle to maximize energy harvesting from multi-directional wind flow. Moreover, this adjustment in the angle would minimize external interactions of the devices to alleviate the effects of excessive forces from harsh environmental conditions. A direct and proportional correlation is derived from between the number of H-TENG harvesters and the charging accumulation rate. A larger number of TENG units is expected to generate triboelectric charges faster with a higher charging accumulation rate. This is substantiated in Fig. 3g , where the TENG peak power output is vastly enhanced with higher harvester numbers. A capacitor with a 1 μF charge rate is affected by the parallel-connected TENG harvester networks, evident from Fig. 3g , with a specified number of units at 7.5 m/s. The same time interval of roughly 0.6 h. Resulted in a voltage of 3.3 V for the chosen capacitor charged by a hybrid system of six parallel units. This further attests to our previous assertion that integrated harvester networks would have a linear-proportional impact on the electrical power output with an elevated number of units. The experimental platform is shown in Fig. 3h and supporting information Movie S2 . H-TENG based self-powered device for IoT and environmental sensing From the recent advancement in technologies, Internet of Things IoT has a practically huge social and economic impact around the globe 46 . Owing to the small size and unique self-powered operation ability, the proposed bio-inspired H-TENG has enormous potential to be used for IoT devices as a consistent power supplier or sensor for each device. In this study, we used a wireless temperature sensor (ESP8266 module) with the proposed TENG device to estimate the power harvesting performance for IoT node operation (see supplementary note 2 Methods section). Energy harnessed by the H-TENG device was stored by the rectifier (70 mAh) and a battery charging module, shown in Fig. 4a , which could then be applied to an environmental IoT sensor module for processing and transmission of signals and sensor functions (Fig. 4b ). The hybrid system of six TENG devices was connected in parallel and run for 60 mins at a wind speed of 7.5 m/s. Thereafter, the discharged power from the battery unit was used to operate the environmental sensor node for transmitting data at 1-second intervals. Personal computers or mobile devices act as receivers for displaying the data in any web browser by assigning the proper IP into the URL field (see Fig. 4c ). This portable device can provide immediate feedback of the environmental conditions, and it can be used to retrieve useful real-time data from inaccessible areas in coastal, high-elevation and suburban locations. Once installed, the self-powered sensors in these devices can readily provide essential information on temperature, pressure, and humidity for environmental monitoring."
} | 6,484 |
39619531 | PMC11603206 | pmc | 2,150 | {
"abstract": "Inspired by brain-like\nspiking computational frameworks, neuromorphic\ncomputing-brain-inspired computing for machine intelligence promises\nto realize artificial intelligence (AI) while reducing the energy\nrequirements of computing platforms. In this work, we show the potential\nof advanced learnings of butane-1,4-diammonium based low-dimensional\nDion-Jacobson hybrid perovskite (BDAPbI 4 ) memristor devices\nin the realm of artificial synapses and neuromorphic computing. Memristors\nvalidate Hebbian learning rules with various spike-dependent plasticity\nwithin a 10 ± 2 ms time frame, reminiscent of the human brains\nunder flat and bending conditions (∼5 mm radium). A high recognition\naccuracy of ∼94% of handwritten images from the MNIST database\nvia an artificial neural network (ANN) is achieved with only 50 epochs.\nAn efficient demonstration of second-order memristors and the Pavlovian\ndog experiment exhibit significant promise in expediting learning\nand memory consolidation. To showcase the in-memory computing potential,\na flexible 4 × 4 crossbar array is designed with measured data\nretention up to ∼10 3 s along with 26 multilevel\nresistance states. The crossbar array is successfully programmed for\nthe facile configurability of image “Z”. In conclusion,\nthe integration of supervised, unsupervised, and associative learning\nholds great promise across a spectrum of future technologies, ranging\nfrom the realm of spiking neural networks to neuromorphic computing,\nbrain-machine interfaces, and adaptive control systems.",
"conclusion": "4 Conclusions Our investigation demonstrated\nthe adaptability of Dion-Jacobson\nmemristor devices, which are prepared using an extensive solution\nprocedure designed specifically for memristive applications. Hebb’s\nlearning rule was successfully illustrated through the application\nof several spike-dependent plasticities as STDP, SRDP, SDDP, and SNDP.\nSTDP demonstrated a transmission time of ∼10 ± 2 ms, which\nis compatible with the human brain. The study’s applications\nof ANN through MNIST pattern recognition were an outstanding ∼94%\nwithin 50 epochs. Additionally, we explored higher-order spike-dependent\nplasticity and associative learning via the Pavlov’s dog experiment.\nFurthermore, we fabricated the 4 × 4-crossbar array, in which\nthe potential of in-memory computing was tested. These results imply\nthat the hybrid DJ perovskite crossbar arrays have great potential\nfor implementing neuromorphic computing and wearable electronics applications\nthat are flexible and inspired by the intricate workings of the human\nbrain.",
"introduction": "1 Introduction As modern computers based\non von Neumann architecture struggle\nwith escalating energy consumption while integrating with complex\nAI algorithms, 1 neuromorphic computing,\ndrawing inspiration from the human brain, offers a promising alternative.\nThrough artificial synapses, it seamlessly integrates information\nprocessing and memory tasks, improving efficiency and overcoming the\nvon Neumann bottleneck. 2 In neuromorphic\nsystems, nanoscale memristive devices play a crucial role by mimicking\nbiological synapses’ dynamic resistance adjustment. Spike-dependent\nplasticity, akin to Hebbian learning, enables synaptic connections\nto adapt based on temporal correlations of neuron spikes, vital in\nboth artificial neural networks and neuroscience. Integrating mechanisms\nfor potentiation and depression enhances adaptability, resembling\nbrain plasticity. This convergence of biological principles and AI\napplications fosters more efficient computing solutions. 3 , 4 Advancing toward a physical model of computing crossbar arrays\nrepresents a significant step in the evolution of neuromorphic computing.\nOptimizing these structures focuses on improving efficiency and performance\nfor computational tasks, addressing von Neumann architecture’s\nlimitations. This shift toward a more parallel and efficient computing\nparadigm aligns with neuromorphic computing principles, promising\nsubstantial improvements in performance and efficiency while unlocking\nnew possibilities for advanced computing applications. 5 , 6 Computing crossbar arrays facilitates high-density integration within\na crosspoint array, supports multilevel memory, and offers favorable\nscalability. However, challenges such as the sneak path problem require\nthe incorporation of two-terminal selector devices. 7 − 9 Programmable\nmetastable states-based nonvolatile memristors have predominantly\nbeen developed using oxides, 10 − 12 2D transition metal dichalcogenides, 13 and organic semiconductors. 14 Although hybrid organic–inorganic perovskites (HOIPs)\nwere first widely used in solar and photonic applications, 15 − 17 their importance in neuromorphic computation is increasingly acknowledged.\nIon migration, defect tolerance, variable carrier density, and light-induced\ndomain phase separation are just a few of the advantageous characteristics\nthat HOIPs demonstrate. 18 , 19 The distinct ion movement\nseen in the soft HOIPs lattice can be deliberately employed to create\ndevices that resemble biological synapses and neurons. 20 − 22 In this work, we develop the memristor device and crossbar\narray\nusing a low-dimensional hybrid perovskite (Butane 1,4-diammonium (BDA)\nbased Dion-Jacobson) material for artificial synapse applications\nin neuromorphic computing. Our work establishes a connection between\nthe fundamental functions of biological neurons and synapses, aligning\nwith the behavior of memristor devices. The memristor devices are\nemployed in supervised learning (e.g., image recognition using ANN),\nunsupervised learning (e.g., SRDP, SNDP, SDDP, STDP, and second order),\nand associative learning, as exemplified by the Pavlov dog experiment.\nAdditionally, a 4 × 4-crossbar array was fabricated to explore\nthe potential of in-memory computing. Synaptic characteristics were\nevaluated to demonstrate mechanical stability under both flat and\nbending conditions, catering to flexible applications. This work bridges\nthe gap between electronics and neurobiology, paving the way for next-generation\ncomputing paradigms capable of replicating the human brain’s\nintricate information-processing capabilities.",
"discussion": "2 Results\nand Discussion In this work, we present the potential of\nDion-Jacobson-based hybrid\nperovskite (BDAPbI 4 ) in the memristors. The X-ray diffraction\n(XRD) analysis of BDAPbI 4 confirmed the polycrystalline\nstructure of the film( Figure 1 a). 23 , 24 The UV–vis absorption\nspectrum reveals the optical properties of the film, showing absorption\npeaks at 520 nm with a bandgap of ∼2.3 eV ( Figure 1 b). The energy dispersive spectroscopy\n(EDX) validates the elemental composition of the BDAPbI 4 film, showing mass% corresponding to C, N, I, and Pb ( Figure 1 c). The scanning electron microscopic\n(SEM) image confirms a uniform morphology of the film with no observable\npinholes ( Figure 1 d).\nFurther, the flexible memristor devices comprise the structure of\npolyethylene terephthalate (PET)/indium tin oxide (ITO)/Poly(3,4-ethylenedioxythiophene)\npolystyrenesulfonate (PEDOT:PSS)/BDAPbI 4 /Phenyl-C61-butyric\nacid methyl ester (PCBM)/Silver (Ag) ( Figure 1 e). Here, BDAPbI 4 is the active\nlayer, and PCBM and PEDOT:PSS are the interfacial layers, with the\ntop and bottom electrodes being silver (Ag) and ITO, respectively. 25 The presence of a thin PCBM layer prevents the\ndirect penetration of Ag ions from the electrode to the perovskite\nlayer, while PEDOT:PSS layer smoothens the ITO surface, resulting\nin a homogeneous and more uniform perovskite layer. BDAPbI 4 comprises a 2-dimensional crystal structure where the BDA layer\nis sandwiched between two consecutive PbI 6 octahedral layers.\nThe presence of the BDA layers reinforces the mechanical and operational\nstability for flexible applications by providing additional intermolecular\nforces that support the perovskite crystal lattice by introducing\nhydrogen bonds ( Figure S1a ). Figure 1 f demonstrates the current–voltage\n( I–V ) characteristics of perovskite memristor\ndevices measured under a DC voltage sweep (0 V → 0.8 V →\n0 V → −1 V → 0 V), (multiple I–V scan cycles in Figure S1b ). This structure\nexhibits resistive switching behavior through (i) the formation and\nrupture of conductive filaments (CFs), driven by ion migration, and\n(ii) chemical and physical reactions at the BDAPbI 4 /PCBM/Ag\ninterface, which modifies the energy barrier. Intrinsic vacancy defects\n(such as I – , BDA i , Pb i , V I , V BDA , and V Pb ) are initially randomly\ndistributed in perovskite film, which facilitates the easy diffusion\nof ions across its octahedral structure, resulting in an intimate\ncoupling of ionic transport with electronic processes. 26 − 28 Upon applying a positive bias (0–0.2 V) to the top Ag electrode,\nI – ions in the perovskite layer preferentially migrate\ntoward the Ag electrode due to their lower activation energy, while\noppositely charged vacancies migrate toward the ITO electrode, initiating\nthe formation of conductive paths across the layer. 29 − 31 In this voltage\nrange, the current is directly proportional to the applied bias ( I ∝ V ), with a slope value of approximately\n1, and the device remains in a high resistance state (HRS) ( Figure S1c ). As the applied bias increases, the\nmigration of ions accelerates, forming CFs and reacting with highly\nelectrochemically active Ag + to form an AgI monolayer (Ag + + I – ↔ AgI + e – ) at the PCBM/Ag interface as the SET process. This process fills\nthe traps, causing a sharp rise in current (slope ∼20, I ∝ V n where n > 2), indicating the trap-filling region.\nWith a further increase in voltage (>0.3 V), all traps are filled,\nand CFs are formed across the active layer, transitioning the device\nresistance from HRS to a low resistance state (LRS), representing\nthe trap-free region. RESET of the devices occurs by applying a negative\nvoltage bias at the Ag electrode, causing the CFs to rupture by migrating\nthe ions in the opposite direction and the dissolution of the AgI\nmonolayer at the interface, modifying the injection properties to\ncontrol charge transfer. Detailed mechanisms are discussed in our\nprevious publications. 25 , 32 − 35 During the RESET process, the\ndominance of the slow migration of ions leads to partial rupture of\nCFs, resulting in small variations in the current observed. The significant\ndrop in current with a slow voltage scan rate confirms our hypothesis\nin the reverse direction during RESET. 36 − 38 Figure 1 (a) X-ray diffraction\n(XRD) pattern, (b) Absorbance in Ultraviolet–visible\n(UV–vis) spectroscopy, (c) mass% of elements in Energy Dispersive\nX-ray Analysis (EDX), and (d) Morphology in scanning electron microscope\n(SEM) of BDAPbI 4 thin film (500 nm). (e) Device structure:\nPET/ITO/PEDOT:PSS/BDAPbI 4 / PCBM/Ag, (f) current–voltage\ncharacteristics. Synaptic Characteristics In the human brain, there\nare ∼10 10 neurons and ∼10 15 synaptic\nconnections. Neurons consist of four primary components ( Figure 2 a): dendrites, facilitating\ninformation reception; the cell body, responsible for information\nprocessing and integration; the axon, conveying information over substantial\ndistances within the neuron; and the axon terminal, transmitting information\nto subsequent neurons. The synapse, the connection between two neurons,\nestablishes a crucial link between the presynapse and postsynapse,\nfacilitating information transmission (insert: Figure 2 a). 39 − 41 In memristor devices, the top\nelectrode, active layer, and bottom electrode resemble the biological\nsynapse structure as pre-neuron, synaptic cleft, and post-neuron,\nrespectively. For the initial assessment of the conductance changes\nin the artificial synapse (memristor device), excitatory postsynaptic\ncurrent (EPSC) was performed. In Figure S2 , the EPSC responses are shown for different pulse widths (5, 8,\n30, and 50 ms) at a pulse amplitude of 0.5 V, under both flat and\nbending conditions. The results demonstrate a gradual increase in\npostsynaptic current with longer pulse widths, resembling short-term\nplasticity (STP) in biological neurons. 42 − 44 Figure 2 Biological synapse: (a)\nSynaptic connection of two neurons, zoom\ninto the synaptic cleft between the pre- and post-synaptic neuron;\nSpike time-dependent plasticity (STDP): flat and bending condition\n( r ∼ 5 mm, after 200 cycles), respectively;\n(b and d) Asymmetric anti-Hebbian, (c and e) Asymmetric Hebbian. Here, we investigate Hebbian learning rules, considered\na form\nof long-term plasticity one of the activities of the human brain,\nby varying parameters such as pulse rate: spike-rate-dependent plasticity\n(SRDP), pulse number: spike-number-dependent plasticity (SNDP), pulse\nduration: spike-duration dependent plasticity (SDDP), and pulse time:\nspike-timing-dependent plasticity (STDP) ( Figure 2 and 3 and Figures S3 and S4 ). Refer to the SI for more\ndetails. These parameters showcase the tunability of the device with\ndifferent parameters and under flat and bending conditions, with bending\nperformed after 200 cycles at radii around 5 mm. 2 , 45 , 46 In a biological neuron, repeated firing\nof action potentials enhances neurotransmitter release and boosts\nthe ion flow across the postsynaptic neuron. In these devices, equilibrium\nlevels of ions (I – , V I, or iodine ions\nand vacancies) post-action potential can be obtained through variations\nin pulse number, rate, duration, and time-inducing changes in synaptic\nweights ( Figures 2 and 3 and S3 and S4 ). This\nsynaptic activity can be modulated by adjusting the ion influx at\nsynapses. This modulation, governed by spike-dependent plasticity,\nillustrates the potential for dynamic control over synaptic function\nin a manner akin to that of biological neurons. Figure 3 Spike-dependent plasticity:\nflat and bent ( r ∼\n5 mm, after 200 cycles) condition, respectively: (a, b) SNDP according\nto the spike numbers n = 2, 3, . . ..10, (c, d) SRDP\naccording to the spike rate from 1 to 10 ms/spike, (e, f) SDDP according\nto spike duration from 10 to 150 ms. The STDP is the biological process responsible for this adaptive\ncapability. 47 The weight change (Δ w ) in the synapse between two neurons is governed by STDP.\nThe fundamental concepts of these learning processes vary with the\ntime interval (Δt) between the spikes in pre- and postsynaptic\nneurons. Specifically, when the postsynaptic spike follows the presynaptic\nspike (Δ t > 0), there is a strengthening\nof\nsynaptic plasticity, leading the device to transition into a state\nof long-term potentiation (LTP). Conversely, if the presynaptic spike\nfollows the postsynaptic spike (Δ t < 0),\nthe connection between the synapses weakens, resulting in a state\nof long-term depression (LTD). Utilizing DJ-based memristors, we successfully\nemulate asymmetric anti-Hebbian ( Figure 2 b, d) and asymmetric Hebbian ( Figure 2 c, e) synaptic learning under\nboth flat and bending conditions, respectively (input spikes are shown\nin Figure.S3 ). The LTP and LTD are fitted\nwith the equation: , where A and Δ W o are constants of synaptic function and τ\nis firing rate. Importantly, DJ-based flexible memristor devices exhibit\na comparable communication time of 10 ± 2 and 16 ± 1 ms\nfor flat and bending conditions, respectively, akin to the speed observed\nin the human brain. The applications of spike-dependent learning extend\nbeyond the realm of neuroscience, finding resonance in artificial\nneural networks, neuromorphic computing, and various domains of machine\nlearning. 48 − 50 Additionally, the number of spikes enhanced\nin synaptic strength\nor weight as in a DJ-based artificial synapse increases from 2 to\n10 under flat and bending conditions, respectively (referred to in Figure 3 a and b; input pulse\nin Figure S4b ). Synaptic responsiveness\nadapts continuously through spike-number-dependent plasticity (SNDP)\nin reaction to repetitive synaptic stimulation. Governed by a specific\nlearning rule, the synaptic connection undergoes a pronounced transformation\nin strength in response to a frequency series of presynaptic spikes\nwith a spike-rate ranging from 1 to 10 ms per spike (SRDP refers\nto Figures 3 c, d, and Figure S4b for input pulse Figure S4a ). Enhancing presynaptic spike duration proves to\nbe more effective in amplifying strength than simply increasing spike\namplitude. The continuous extension of spike duration leads to the\ngrowth of synaptic strength, facilitating the formation of conducting\nchannels with an increased number of ions, thereby reinforcing SDDP\n(refer to Figure 3 e,\nf and for input pulse in Figure S4c ). These\nfindings suggest that, under repeated stimulation, the process of\nV I migration to form conducting filaments is accelerated,\nresulting in an augmented current flow through the memristors. 51"
} | 4,204 |
25904900 | PMC4389539 | pmc | 2,153 | {
"abstract": "Trait-based approaches provide a mechanistic framework to understand and predict the structure and functioning of microbial communities. Resource utilization traits and trade-offs are among key microbial traits that describe population dynamics and competition among microbes. Several important trade-offs have been identified for prokaryotic and eukaryotic microbial taxa that define contrasting ecological strategies and contribute to species coexistence and diversity. The shape, dimensionality, and hierarchy of trade-offs may determine coexistence patterns and need to be better characterized. Laboratory measured resource utilization traits can be used to explain temporal and spatial structure and dynamics of natural microbial communities and predict biogeochemical impacts. Global environmental change can alter microbial community composition through altering resource utilization by different microbes and, consequently, may modify biogeochemical impacts of microbes.",
"conclusion": "Concluding Remarks Classical mathematical descriptions of resource utilization and competition in microbes, as well as novel models including more realism provide a firm foundation for exploring the principles of microbial community organization at present and under future environmental conditions. Parameters of these models are key functional traits of microbes that determine their community structure, dynamics, and biogeochemical impacts. Characterizing these traits for many diverse microbial species through lab measurements using novel culturing techniques and “omic” approaches should provide rich data for model parameterizations. Trade-offs at different levels of biological organization and of different dimensionality are essential for predicting microbial community assembly and evolution and should be better characterized. Together, trait and trade-off information and realistically parameterized mathematical models, will be instrumental in increasing our mechanistic understanding of how natural ecosystems function.",
"introduction": "Introduction Understanding the structure, dynamics and functioning of diverse microbial communities, and their effects on biogeochemical cycles has become one of the most fast-moving and exciting areas in biology. New high throughput methods of characterizing microbial community composition have resulted in an unprecedented wealth of data that can be analyzed to make inferences about the mechanisms operating in the microbial universe. One of the promising approaches gaining momentum in microbial ecology is the trait-based framework to understand and predict community composition and dynamics. As in community ecology of macroscopic organisms such as terrestrial plants, we can use trait-based approaches to seek general patterns of community organization and identify the mechanisms structuring microbial communities. In addition, key microbial traits can give us insights into the microbial impacts on biogeochemistry and how these impacts may change in the future. Microbes have extremely diverse metabolisms, occupy virtually all habitats on Earth and play key roles in major biogeochemical cycles. Despite all this diversity, there are some common underlying principles that govern the organization and functioning of microbial species and communities. Among those are the kinetics of resource utilization and competition for resources ( Tilman, 1982 ; Button, 1985 ; Hibbing et al., 2010 ). There is a tremendous variety of substrates, ranging from simple inorganic ions to complex organic molecules that act as resources for different microbial groups, including the waste products of other microbes. Many of the putative resources are still poorly characterized and it is not always known what microbial groups can utilize them. However, for many resources, the Michaelis–Menten enzyme kinetics equation can be used as an adequate descriptor of microbial resource uptake ( Droop, 1973 ; Button, 1998 ; Litchman and Klausmeier, 2008 ). Growth rate is then described by a separate equation as a function of intracellular nutrient concentration ( Droop, 1973 ). Alternatively, the growth rate dependence on a resource can be described by a Monod equation, where growth rate is a saturating function of external resource concentration ( Button, 1985 ; Grover, 1990 ). The parameters of these equations can be viewed as functional traits related to resource utilization and resource-dependent growth ( Litchman and Klausmeier, 2008 ). These traits directly affect organism’s fitness and, therefore, are among key functional traits of organisms ( Litchman et al., 2007 ; Violle et al., 2007 ). Resource utilization traits of individual microorganisms determine their requirements for those resources and can be used to predict how a given microorganism responds to environmental conditions (resource-dependent growth). Therefore, these traits can be classified as response traits ( Lavorel and Garnier, 2002 ; Suding et al., 2008 ). At the same time, resource utilization by microorganisms has direct effects on biogeochemical processes in ecosystems and, therefore, traits associated with resource uptake and growth are also effect traits ( Lavorel and Garnier, 2002 ; Suding et al., 2008 ). Not all traits in microbes or macroscopic organisms can simultaneously be classified into these two categories. For example, traits characterizing growth rate responses to temperature, pH or other environmental parameters are response traits but not effect traits. Traits that are simultaneously response and effect traits tightly link the environment, microbial community structure, and biogeochemical processes and may have a higher predictive power for determining the biogeochemical impacts ( Lavorel and Garnier, 2002 ). It would be of interest to systematically examine the relative importance of different types of traits on biogeochemistry. Eco-physiological traits, including the resource acquisition and utilization traits, are often correlated with each other and these correlations may constitute trade-offs, if their increase or decrease has opposing effects on fitness. Organismal trade-offs prevent a single super-species from dominating, making them fundamental in determining community structure and diversity ( Tilman, 1990 ; Kneitel and Chase, 2004 ) and have been described for microbes, starting with classical work by Pirt (1965) . Trade-offs defines diverse ecological strategies that are selected for in different environments and allow coexistence of competitors ( Tilman, 1982 ; Bohannan et al., 2002 ; Porter and Rice, 2012 ; Wallenstein and Hall, 2012 ). Therefore, characterizing trade-offs in microbes should allow us to better understand the mechanisms of community organization. At present, there are a number of trade-offs postulated for diverse microorganisms and for some microbial groups there is enough empirical data to confirm those trade-offs ( Litchman et al., 2007 ; Winter et al., 2010 ; Edwards et al., 2012 ; Wallenstein and Hall, 2012 ). However, many more trade-offs remain not even theoretically derived, much less empirically documented. Most observed and hypothesized trade-offs are pairwise but higher-dimensional trade-offs are possible ( Edwards et al., 2011 ; Shoval et al., 2012 ) and may provide even more opportunities for coexistence and diversity of strategies. Here we discuss how resource utilization traits and the potential trade-offs among them can be used to explain patterns of microbial community structure, diversity, temporal dynamics, spatial distribution, and biogeochemical impacts at present and in the future. Obviously, there are many other microbial traits that are important for understanding the structure and dynamics of communities, such as traits determining responses to diverse environmental factors (pH, temperature, pressure), quorum sensing traits, dormancy, etc., but we focus on resource utilization traits because they provide the most direct link between microbial community structure and biogeochemistry and are well described and modeled for many microbes. We provide examples for both prokaryotic and eukaryotic microbes, phytoplankton in particular, because many relevant phytoplankton traits have been measured, compiled, and used to infer the mechanisms of community organization. Phytoplankton are globally important microbes contributing about half of the Earth’s primary productivity and playing a major role in many biogeochemical cycles, such as carbon, nitrogen, phosphorus, and silica ( Field et al., 1998 ). Recently, much progress has been achieved in applying trait-based approaches to understand the structure and dynamics of phytoplankton communities in both marine and freshwater environments ( Edwards et al., 2013b , c ). Resource utilization and competition for resources is thought to be a major structuring force in phytoplankton communities ( Tilman, 1982 ), hence, resource-related traits provide crucial information on how individual species respond to environmental conditions, resource supply in particular."
} | 2,264 |
27917019 | PMC5129565 | pmc | 2,155 | {
"abstract": "ABSTRACT This Highlight presents an overview of the rapidly growing field of dynamic covalent polymers. This class of polymers combines intrinsic reversibility with the robustness of covalent bonds, thus enabling formation of mechanically stable, polymer‐based materials that are responsive to external stimuli. It will be discussed how the inherent dynamic nature of the dynamic covalent bonds on the molecular level can be translated to the macroscopic level of the polymer, giving access to a range of applications, such as stimuli‐responsive or self‐healing materials. A primary distinction will be made based on the type of dynamic covalent bond employed, while a secondary distinction will be based on the consideration whether the dynamic covalent bond is used in the main chain of the polymer or whether it is used to allow side chain modification of the polymer. Emphasis will be on the chemistry of the dynamic covalent bonds present in the polymer, in particular in relation to how the specific (dynamic) features of the bond impart functionality to the polymer material, and to the conditions under which this dynamic behavior is manifested. © 2016 The Authors. Journal of Polymer Science Part A: Polymer Chemistry Published by Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2016 , 54 , 3551–3577.",
"conclusion": "CONCLUSION While relatively late to arrive at the scene compared to supramolecular polymers (based on noncovalent interactions), dynamic covalent polymers have gained a lot of attention in recent years in the area of smart polymer materials. In this Highlight we have demonstrated how the inherent dynamic nature of various dynamic covalent bonds constituting these polymers can impart features such as adaptivity and responsiveness to the materials.",
"introduction": "INTRODUCTION Compared to other types of materials, polymer‐based materials offer various distinct advantages, such as their low density, processability, and the broad range of monomer building blocks. However, classic polymeric materials, i.e. polymers derived from covalent bonds, typically suffer from unrepairable damage, resulting in a progressive decrease in functionality and/or economic value as the material ages. In addition, such polymers are generally insensitive to their environment. To overcome these limitations, dynamic interactions can be incorporated in polymer materials, thus imparting these materials with dynamic features such as environmental adaptivity, malleability, or self‐healing properties. Over the last decades, supramolecular interactions, e.g. hydrogen bonds or aromatic interactions, have been successfully incorporated into polymers as a means to achieve such dynamic material behavior. 1 , 2 , 3 , 4 More recently, however, researchers have also relied on dynamic covalent (DC) bonds 5 , 6 , 7 , 8 to achieve such dynamic behavior, as DC bonds combine the robustness of classic covalent bonds with the reversibility of non‐covalent bonds. More formally, a covalent bond can be considered dynamic if it has the ability to be formed and broken reversibly under equilibrium control. 5 To achieve equilibrium conditions, exchange should be sufficiently fast, implying a bond life time on a scale of milliseconds to minutes. 9 By virtue of their reversibility, DC bonds have been successfully harnessed in the synthesis of dynamic combinatorial libraries 10 , 11 or mechanically interlocked species. 12 , 13 \n In this highlight we will discuss how DC bonds can be used to synthesize robust polymers whose properties are dictated by the inherent dynamic nature of the bonds, which can thus influence the material's relaxation behavior or mechanical response. The dynamic nature on the molecular level is thus translated to the macroscopic level of the polymer, giving access to a range of applications, such as self‐healing or stimuli‐responsive materials, as reviewed extensively by others. 14 , 15 , 16 , 17 , 18 , 19 Herein, we primarily discuss the underpinning chemistry that imparts the dynamic behavior or function to the polymer material. Definition and Scope The aim of this Highlight is to present an overview of the rapidly growing field of DC polymers. 20 We have limited ourselves to a discussion of DC bonds, not including supramolecular interactions. For a recent overview of the combination of DC and supramolecular bonds, jointly considered as constitutional dynamic chemistry , the reader is referred to excellent reviews by Lehn, 21 and Zhang and Barboiu. 22 While a distinction can be made between DC reactions relying on the formation of new bonds, or on exchange reactions, 6 herein this distinction will not be explicitly used. This Highlight will primarily distinguish DC polymers based on the type of DC bond employed. We will make a further distinction based on the consideration whether the DC bond is used in the main chain of the polymer (i.e. it is responsible for linking the individual monomers together into the macromolecule), or whether it is used to allow side chain modification of the polymer (which itself is then formed by purely covalent bonds). As explained above, our emphasis will be on the chemistry of the DC bonds present in the polymer, in particular in relation to how the specific (dynamic) features of the bond impart functionality to the polymer material."
} | 1,334 |
38004884 | PMC10673119 | pmc | 2,156 | {
"abstract": "This study introduces the utilization of self-powered microbial fuel cell (MFC)-based biosensors for the detection of biotoxicity in wastewater. Current MFC-based biosensors lack specificity in distinguishing between different pollutants. To address this limitation, a novel approach is introduced, capitalizing on the adaptive capabilities of anodic biofilms. By acclimating these biofilms to specific pollutants, an enhancement in the selectivity of MFC biosensors is achieved. Notably, electrochemically active bacteria (EAB) were cultivated on 3D porous carbon felt with and without a model toxicant (target analyte), resulting in the development of toxicant-resistant anodic biofilms. The model toxicants, Pb 2+ ions and the antibiotic neomycin sulfate (NS), were deployed at a concentration of 1 mg L −1 during MFC operation. The influence of toxicity on biofilm growth and power production was investigated through polarization and power density curves. Concurrently, the electrochemical activity of both non-adapted and toxicity-adapted biofilms was investigated using cyclic voltammetry. Upon maturation and attainment of peak powers, the MFC reactors were evaluated individually as self-powered biosensors for pollutant detection in fresh wastewater, employing the external resistor (ER) mode. The selected ER, corresponding to the maximum power output, was positioned between the cathode and anode of each MFC, enabling output signal tracking through a data logging system. Subsequent exposure of mature biofilm-based MFC biosensors to various concentrations of the targeted toxicants revealed that non-adapted mature biofilms generated similar current–time profiles for both toxicity models, whereas toxicity-adapted biofilms produced distinctive current–time profiles. Accordingly, these results suggested that merely by adapting the anodic biofilm to the targeted toxicity, distinct and identifiable current–time profiles can be created. Furthermore, these toxicity-adapted and non-adapted biofilms can be employed to selectively detect the pollutant via the differential measurement of electrical signals. This differentiation offers a promising avenue for selective pollutant detection. To the best of our current knowledge, this approach, which harnesses the natural adaptability of biofilms for enhanced sensor selectivity, represents a pioneering effort in the realm of MFC-based biosensing.",
"conclusion": "4. Conclusions This comprehensive evaluation of MFC reactors as self-powered biosensors for detecting pollutants in wastewater yielded significant insights. This study demonstrated that the electroactivity of biofilms, both non-adapted and adapted to specific toxicants, plays a pivotal role in the MFC’s sensitivity and response to pollutants. The influence of salinity on MFC performance further underscored the importance of environmental factors in determining the efficacy of these biosensors. The ability to track voltage drops using fixed external resistors, without the need for additional equipment, not only reduces operational costs but also enhances the feasibility of on-site monitoring, providing timely alerts for wastewater treatment plant operations. Furthermore, this study highlighted the potential of biofilm adaptation as a strategy to enhance the specificity and selectivity of MFC biosensors. While non-adapted biofilms exhibited a generalized response to a wide range of pollutants, adapted biofilms showcased a more targeted and pronounced response to specific toxicants. This distinction in response profiles offers a promising avenue for the development of MFC biosensors that can not only monitor overall toxicity but also differentiate between various contaminants in complex solutions. In light of the findings of this study, a deeper understanding of the microbiological structure of biofilms during their growth in the presence of pollutants emerges as a critical avenue for future research. By delving into the intricate interactions and adaptive mechanisms at the microbial level, it is possible to gain insights into the specific bacterial species that thrive under toxicant exposure and those that are inhibited. Advanced techniques, such as fluorescent analysis and metagenomic sequencing, can reveal the distribution of live vs. dead bacteria, as well as the compositional shifts in microbial communities. Such studies can not only validate the electrochemical findings of biofilm adaptation but also shed light on the broader ecological implications of pollutant exposure. Investigating the microbiological intricacies will undoubtedly enrich the understanding of biofilm dynamics, offering a more holistic view of their resilience and adaptability in the face of environmental challenges. In conclusion, the findings of this study highlight the potential of MFC-based biosensors as robust tools for the real-time monitoring of wastewater pollutants. The insights gained pave the way for further research aimed at optimizing these systems for broader applications in environmental monitoring and pollution control.",
"introduction": "1. Introduction Environmental contamination stemming from anthropogenic activities, including mining, agriculture, and urbanization, consistently introduces a plethora of chemical contaminants (heavy metals, hydrocarbons, pesticides, drugs, endocrine disruptors, etc.) into water resources [ 1 , 2 ]. The consequent release of highly toxic waste streams poses significant threats to the functionality of downstream wastewater treatment plants (WWTPs), sometimes leading to irreversible damage [ 3 , 4 ]. Extended recovery periods for WWTPs have been observed post-toxicity shocks, and many WWTPs exhibit limited capability in effectively treating non-biodegradable compounds. As a result, they often act as concentrated pollutant discharge points, exacerbating ecological and human health risks [ 5 ]. For wastewater quality control, traditional analytical methods, such as liquid chromatography (HPLC), LC-tandem MS, immunoassays, atomic absorption spectrometry (AAS), and other spectrometric techniques, remain predominant [ 6 ]. While these techniques exhibit high sensitivity and accuracy in toxicity detection, their complexity, need for specialized equipment, and reliance on highly skilled personnel render them less suitable for on-site and real-time monitoring [ 7 ]. Moreover, these methods often fail to reflect the true biological impact of contaminants [ 8 ]. Stricter environmental regulations have necessitated the development of cost-effective and sensitive tools for on-site environmental analyses. Recent advancements emphasize the significance of on-line water quality monitoring, both in ensuring potable water safety and enhancing WWTP operations. In this realm, microbial fuel cell (MFC)-based biosensors have garnered substantial attention [ 9 ]. MFCs are bioelectrochemical systems that capitalize on microorganisms to transform chemical energy into electrical energy [ 10 , 11 , 12 , 13 ]. The biofilms, composed of electrochemically active bacteria (EAB), facilitate the oxidation of organic matter in the anodic compartment, producing protons and electrons. These electrons are then harnessed at the anode and relayed to the cathode via an external circuit, generating electricity [ 14 , 15 ]. The electrical output of MFCs is intrinsically linked to the metabolism of the EAB populating the anodic surface. Hence, the introduction of biotoxic compounds into wastewater can inhibit EAB metabolic processes, leading to a discernible decline in the MFC signal. Recent advancements in MFC-based biosensors have expanded their applications, ranging from monitoring water quality to detecting air pollutants [ 16 , 17 ]. For instance, Li et al. explored the use of a 2D smooth-anode-based MFC toxicity sensor for the enhanced detection of Pb 2+ in wastewater [ 18 ]. Other studies by Haddour et al. and Cui et al. provided a comprehensive review of MFC-based biosensors, emphasizing their potential in biochemical oxygen demand (BOD) and toxicity detection [ 9 , 17 ]. Qiu et al. introduced a novel MFC biosensor capable of simultaneously detecting sodium acetate and glucose in mixed solutions [ 19 ]. Furthermore, Wang et al. developed a soil MFC-based self-powered cathodic biosensor for the sensitive detection of heavy metals [ 20 ]. Despite these advancements, challenges persist, particularly in enhancing the specificity of these biosensors. Most MFC biosensors detect overall toxicity, making it arduous to pinpoint the exact nature and origin of toxic substances in the water samples [ 9 , 17 , 21 ]. Addressing the specificity challenge, recent endeavors have either harnessed individual bacterial strains or genetically tailored strains for enhanced pollutant sensitivity [ 16 , 17 ]. Nevertheless, the financial implications of cultivating pure bacterial strains or their genetic modifications remain substantial. Few cost-effective alternatives are documented, save for some work emphasizing the role of external resistance in achieving relative specificity [ 22 ]. The present study proposes a novel configuration of a single-chamber air-cathode MFC-based biosensor designed for batch-mode operation. For targeted contaminant detection, EAB were cultivated on 3D carbon felt anodes in the presence of a toxic model (target to be analyzed), leading to the development of anodic biofilms resistant to the specific toxicant. Drawing inspiration from bioremediation techniques, this method promotes the enrichment of bacterial strains capable of metabolizing and degrading specific pollutants [ 19 , 20 ]. As a result, the presence of the target pollutant in a water sample might not inhibit the metabolic activity of the adapted biofilm, especially when contrasted with a non-adapted biofilm (biofilm formed in the absence of the pollutant). Thus, selective detection of pollutants can be achieved by simultaneously measuring signals from biosensors utilizing both adapted and non-adapted biofilms. This methodology yields more-stable signals from the adapted biofilm-based biosensor when exposed to pollutants, as opposed to biosensors based on non-adapted biofilms. To the best of our knowledge, such a differential measurement technique has never been previously described. In this study, Pb 2+ ions and the neomycin sulfate (NS) antibiotic were chosen as representative toxicity models to assess their impact on anodic biofilm growth and power generation within MFCs. Upon maturation of both the non-adapted and adapted biofilms and the attainment of peak power outputs, the MFC reactors underwent evaluation as self-powered biosensors, exposed to varying concentrations of toxicants, utilizing the aforementioned differential measurement approach. The present study serves as an initial exploration to validate the feasibility of this novel methodology.",
"discussion": "3. Results and Discussion 3.1. Toxicity Effect on Biofilm Growth and Power Generation To assess the effects of specific pollutants on biofilm growth and electrochemical performance, the MFCs were subjected to two conditions: a control without pollutants and an experimental condition with a pollutant concentration of 1 mg L −1 (either NS antibiotic or Pb 2+ ions). Figure 3 A,B present the output voltages recorded over a 22-day operational span. These voltages provide a metric for evaluating the growth kinetics and maturation of anodic biofilms on CF anodes under both conditions. From the voltage–time profiles, it is evident that, after an initial seven-day period, all the MFCs achieved a stable output voltage, oscillating between 300 and 350 mV. This stabilization suggests the attainment of biofilm maturity, a finding consistent with previous observations from conventional air-cathode, single-chamber, bottle-type MFCs. The uniformity in voltage outputs across MFCs indicates that the introduction of pollutants, whether NS or Pb 2+ ions, did not markedly alter the growth dynamics of the biofilms on the anodic surfaces. On the 11th operational day, after biofilm maturation confirmation via stable voltage outputs, LSV assessments were conducted at a rate of 10 mV s −1 using a two-electrode system configuration. The resulting polarization and power density curves for both non-adapted and pollutant-adapted biofilms are illustrated in Figure 3 C,D. As delineated in Figure 3 C, the incorporation of NS antibiotic during biofilm formation corresponded to around a 45% decrement in both the maximum power density and the maximum current density of the MFCs. This reduction can be attributed to the NS antibiotic’s potential inhibitory action on the metabolic processes of the electrogenic bacteria within the CF anode, subsequently slowing the consumption kinetics of the NaAc substrate. In contrast, as depicted in Figure 3 D, while the maximum power density remained relatively invariant in the presence of Pb 2+ ion concentrations, there was a discernible decrease (around 40%) in the maximum current density. These results suggest that although Pb 2+ ions might hinder substrate transport to the anodic biofilm, the overall power generation remains largely unaffected. 3.2. Electroativity of a Mature Biofilm Adapted to Different Concentrations of Toxicity To comprehensively assess the influence of toxicants on biofilm growth and electroactivity, CV tests were conducted in the MFCs. During these tests, a cyclic potential sweep was applied to the anodic biofilm relative to an external Ag/AgCl reference electrode (RE) at a scan rate of 10 mV s −1 . Notably, these CV tests were conducted in the same effluents in which the biofilms were cultivated, containing 10 mM NaAc, in the absence and in the presence of 1 mg L −1 of toxicant. The initial CV recordings, taken after 3 days of MFC operation, exhibited no discernible redox peaks within the selected potential range (−0.8 V to +0.7 V), suggesting the absence of mature electroactive biofilms on the anode surfaces ( Figures S4 and S5 ). However, by the seventh day, the voltammograms began to display characteristic faradaic peaks, indicative of the electrochemical behavior and electron transfer mechanisms inherent in the biofilms. By the 11th day, consistent voltammogram profiles emerged, corroborating the biofilm maturation hypothesis. Figure 4 shows the CVs of MFC anodes recorded on the 11th days of the experiment both in the absence and presence of toxicants (NS or Pb 2+ ions). The CVs of all the MFCs exhibited two peaks in both positive and negative potential regions. The sharp redox peaks observed at around −300 mV (vs. AgCl/Ag) and the oxidative peak at 400 mV (vs. AgCl/Ag) suggest that the direct electron transfer was the major EET mechanism, as previously described [ 23 ]. Based on previously reported values, the negative potential region corresponded to the mediated electron transfer of Shewanella oneidensis and/or heterogeneous electron transfer via the nanowires of Geobacter sulfurreducens EAB [ 24 , 25 ]. At positive potentials, the direct electron transfer was the major EET mechanism, and it could occur via the c-type cytochrome as in Clostridium , Geobacter, or Shewanella [ 26 ]. The similarities in the CVs of the anodes in all the MFCs suggest that the electron transfer mechanisms in the biofilms were not significantly influenced by the presence of the toxicants. However, the CVs displayed lower peak intensities with adapted biofilms, especially for peaks in negative region, in comparison with non-adapted biofilms. These results suggest that the presence of a toxicant during biofilm formation either reduces the catalytic electroactivity of the anodic biofilms or diminishes the amount of EAB in the biofilms, or both. A combined metaproteomics and metagenomics approach would offer a more comprehensive insight into both aspects. 3.3. Effect of Salinity on MFC Performance Salinity is recognized as a pivotal factor influencing both the conductivity of the medium and the sensitivity of MFC-based biosensors [ 27 ]. To understand its implications, the influence of salinity on the output current of MFCs, with biofilms cultivated both in the absence and presence of toxicants (NS or Pb 2+ ions), was examined. After the electroactive biofilms matured and the maximum electrical power generated by the MFCs stabilized, the existing solution was substituted with a fresh, oxygen-depleted medium. A multihead peristaltic pump facilitated the replacement process, ensuring that the integrity of the anodic biofilms remained undisturbed. This new medium solely comprised dehydrated activated sludge and the NaAc substrate. Following the stabilization of output voltages, a concentration of 60 mM NaCl (σ ≈ 7 mS cm −2 ) was introduced to all the MFCs. This concentration was deliberately chosen below the threshold observed in MFCs utilizing domestic wastewater as an inoculum to prevent any adverse effects on the biofilm’s physiology [ 28 , 29 ]. Figure 5 A,B illustrate the effect of NaCl addition on the output currents produced by biofilm-based MFCs non-adapted and adapted to 1 mg L −1 of NS antibiotic or Pb 2+ ions. A notable increase of 35% and 33% in current output was observed in MFCs with biofilms exposed to NS and Pb 2+ ions, respectively, after NaCl addition. All current–time trajectories exhibited consistent patterns after NaCl addition, suggesting that the MFC biosensor’s response to salinity remains uniform, irrespective of prior toxicant exposure. Otherwise, the process of biofilm adaptation to toxicity had no impact on the response of the MFC-based biosensor to the NaCl salt with respect to the non-adapted ones. Figure S6 further highlights the influence of salinity on the electrochemical activity of mature anodic biofilms. Employing the three-electrode setup, the CV measurements spanned a potential range of −1 V to +0.7 V vs. Ag/AgCl at a scan rate of 10 mV s −1 . The results underscored a significant enhancement in the electrochemical activities of anodic biofilms following NaCl addition. For the subsequent application of these bioelectrochemical systems in biosensing or monitoring specific toxicants, it is imperative to maintain consistent salinity levels. Similarly, the response of the MFC biosensor should not be dependent on the NaAc substrate. Therefore, during toxicity sensing, the MFC biosensors should be at their maximum regardless of optimal NaAc substrate and NaCl salt concentrations. 3.4. MFC Biosensor Response to Toxicity Following the effective operation of MFCs with electroactive biofilms cultivated in the absence and presence of various toxicant concentrations and having achieved a stable output voltage signal, the MFC reactors were evaluated as self-powered biosensors for detecting pollutants in wastewater. Control modes can influence MFC performance metrics, including sensitivity, dynamic range, recovery, and response times. Utilizing a fixed ER offers the advantage of monitoring the voltage drop across the resistor without the necessity for a potentiostat, external power supply, or reference electrode, thereby reducing operational costs [ 9 ]. This mode is particularly beneficial for the on-site monitoring of sudden toxicity events in wastewater, providing early alerts to WWTP personnel to take timely preventive measures. Initially, the MFC chambers were replenished with a fresh medium solution, comprising activated sludge, 10 mM NaAc substrate, and 60 mM NaCl. Once stable output voltage signals were established, the polarization and power density curves were derived using LSV at a scan rate of 10 mV s −1 . This facilitated the determination of the maximum power densities for all the MFCs. Subsequently, the anode and cathode of each MFC biosensor were connected across a newly selected 270 Ω external resistor, chosen based on the maximum power density output of each MFC. Figure 6 A,B depict the temporal variations in the output currents of the MFC biosensors, based on both non-adapted and toxicant-adapted (1 mg L −1 of NS or Pb 2+ ions) mature electroactive biofilms. The biofilms were subsequently challenged with successive additions of NS in the concentration range 0.01–20 mg L −1 and Pb 2+ in the concentration range 0.01–5 mg L −1 using a syringe. It is worth noting that each concentration was administered only once to avoid prolonged exposure of the non-adapted biofilm. This approach was taken to prevent the inadvertent development of resistance within the biofilm, which could compromise its sensitivity, especially when considering higher toxicant concentrations. As can be seen clearly for both NS and Pb 2+ ion shocks, the responses of the non-adapted biofilms toward toxicity addition showed almost similar profiles. The introduction of either toxicant resulted in a comparable decline in the MFC’s current output, suggesting that non-adapted biofilms can detect a broad spectrum of pollutants, providing a holistic toxicity overview of both anticipated and unanticipated contaminants in real samples. This observation aligns with prior studies indicating that non-adapted biofilms cannot discern specific toxic shocks [ 9 ]. Moreover, during toxicant exposures, non-adapted biofilm-based MFC biosensors displayed a rapid current output reduction post-toxicant introduction, followed by a return to an elevated baseline. This baseline shift was more pronounced at lower concentrations and diminished at higher levels. Such results might be attributed to the fact that the minimal toxicant concentrations were insufficient to inhibit the entire catalytic activity of the bacterial population in the anodic biofilms. Furthermore, the elevated baseline during low toxicant exposure might be indicative of the acclimatation process of non-adapted biofilms to the toxicant, leading to enhanced bacterial activity for energy production. This acclimatation process has been previously described when exposing anodic biofilms to repetitive acute toxicity event tests, increasing the pollutant degradation activity of biofilms and reducing their sensitivity of toxicity detection [ 30 ]. On the contrary, anodic biofilm-based MFC biosensors adapted to 1 mg L −1 NS or Pb 2+ ions showed different MFC output current profiles during toxicity shocks. Indeed, the current production obtained with the MFC biosensor based on the NS-adapted biofilm was lower than the non-adapted one during shocks with NS. This result could prove that the anodic biofilm acclimated and formed with 1 mg L −1 NS has developed bacterial resistance to NS shocks. Unlike NS shocks, drops in the current output during Pb 2+ shocks of the MFC biosensor based on the Pb 2+ -adapted electroactive biofilm, were higher than those provided by the non-adapted MFC. These results may prove that the anodic biofilm’s adaptation to Pb 2+ ions improved the sensitivity of the MFC biosensor to Pb 2+ biosensing in wastewater. In summary, while non-adapted biofilm-based MFC biosensors exhibited similar current–time profiles for both NS and Pb 2+ exposures, distinct profiles were observed for the MFC biosensors with Pb 2+ and NS-adapted biofilms. However, by adapting the anodic biofilm to a targeted toxicant, distinct and characteristic current–time profiles can be generated during toxicant exposures. Based on these profiles, biosensor responses to such a toxicant can be easily distinguished, thereby achieving specific and selective detection of toxicants using MFC-based biosensors. The concept of anodic biofilm acclimation/adaptation to toxicants can be leveraged in a differential sensing approach, facilitating the development of biosensors to monitor the overall toxicity of environmental contaminants and distinguish various analytes in complex solutions."
} | 5,938 |
37920817 | PMC10618112 | pmc | 2,158 | {
"abstract": "Clarifying the general rules behind microbial community assembly will foster the development of microbiome-based technological solutions. Here, we study microbial community assembly through a computational analysis of phylogenetic core groups (PCGs): discrete portions of the bacterial phylogeny with high prevalence in the ecosystem under study. We first show that the existence of PCGs was a predominant feature of the varied set of microbial ecosystems studied. Then, we re-analyzed an in vitro experimental dataset using a PCG-based approach, drawing only from its community composition data and from publicly available genomic databases. Using mainly genome scale metabolic models and population dynamics modeling, we obtained ecological insights on metabolic niche structure and population dynamics comparable to those gained after canonical experimentation. Thus, leveraging phylogenetic signal to help unravel microbiome function and assembly rules offers a potential avenue to gain further insight on Earth’s microbial ecosystems.",
"conclusion": "5 Conclusion The results presented here show that the proposed PCG-based approach can provide ecological insights comparable to those obtained after canonical experimentation. While it is undisputable that appropriate experimentation provides more direct evidence than our approach, the latter can be of great value for cases in which experimentation is not possible or practical, or as a complement. As previously discussed in detail [3] , the conceptual framework and proposed methodological approach has some limitations including its reliance on sufficient sequencing depth, the low resolution of the 16S rRNA phylogeny at deep and shallow nodes, and its incapacity to help explain microbial ecosystems that do not show a phylogenetic signal or those with strong succession patterns or frequent and strong perturbations [3] . Nonetheless, we show the presence and high relative abundance of PCGs in a large and diverse array of environments, suggesting PCGs are a predominant feature of microbial ecosystems that, when detectable, can be used to explore microbiome function and assembly rules. Leveraging this phylogenetic signal thus offers a relatively quick (and cost effective) way to gain further insight on Earth’s microbial ecosystems.",
"introduction": "1 Introduction Microbes represent a large fraction of the Earth’s biomass and most of its biodiversity. They also drive global biogeochemical cycles and significantly impact the fitness of most multicellular organisms with whom they develop symbiotic relationships. Microorganisms in nature normally appear as communities, or groups of potentially interacting populations that co-exist in space and time [1] . The rules that govern the assembly of these populations, which are each formed of genetically homogeneous individuals, are still poorly understood [2] . Greater knowledge of microbial community assembly will not only increase our understanding of the role that microbiomes play in sustaining life on Earth but will also foster the development of microbiome-based technological solutions. In this regard, the bottom-up design of functional synthetic consortia would benefit from an appropriate understanding of microbial community assembly, as would top-down strategies if eco-evolutionary forces are to be controlled to produce functional consortia. Despite their evident complexity, microbial communities often present shared characteristics: they are highly diverse (comprising various bacterial phyla), species rich (large number of species), feature coexisting populations that should theoretically exclude one another given their genomic characteristics, can show remarkable functional stability despite large species turnover in the community, and trait-based selection can significantly impact their assembly [3] . Moreover, in most microbial communities, bacteria tend to co-occur with phylogenetically related populations more often than expected by chance, a phenomenon termed phylogenetic clustering (i.e. microbial communities often bear a phylogenetic signal) [4] , [5] , [6] . These common patterns of microbial communities lead to the idea that a set of common principles governs microbial community assembly [7] . The prevailing view in the field is that microbiomes assemble on the basis of function, without a significant role for phylogenetic assembly [8] . This idea is supported by the predominant observation that different species compositions can translate into functionally equivalent microbial ecosystems [8] . However, the lack of a significant role for phylogenetic assembly is undermined by the extensive phylogenetic signal observed in microbial communities. In an effort to better understand microbial community assembly, we recently investigated this community characteristic [3] by taking into consideration that traits and ecological function are, to some extent, conserved from an evolutionary standpoint [9] , [10] . Considering these points and phylogeny as a proxy for evolutionary history, we proposed a conceptual framework for the phylogenetically constrained assembly of microbial communities [3] . The framework is linked to Vellend’s synthesis of community ecology [1] and its four basic assembly principles (drift, dispersal, selection, and diversification), and extends it to account for ecosystem patchiness, sampling bias, and phylogeny-related selection. The framework is centered around two facts: first, phylogenetic clustering in a microbial ecosystem can be studied in terms of phylogenetic core groups (PCGs), discrete portions (i.e. specific nodes) of the bacterial phylogeny that are present in all instances of a given ecosystem type; and second, the 16S rRNA gene-based phylogeny of bacteria presents significant functional coherence [10] . However, the strength of this coherence varies with phylogenetic depth along the phylogenetic tree [10] ; thus, deep branching nodes may not maintain functional coherence. So far, PCGs have been clearly detected in the rice rhizosphere [3] and human gut [11] environments. The framework contends that the most plausible explanation for the existence of a PCG in a given environment is that populations belonging to that PCG present a phylogenetically conserved set of traits that improve the fitness of those populations under the particular biotic and abiotic factors in that environment. The framework also proposes that populations belonging to the same PCG would be ecologically cohesive (to the extent that they are affected by the same selective forces), and hence, its intra-group structure would be governed mainly by immigration and drift (neutral processes). Significantly, as PCGs can be easily detected in replicated ecosystem samples by sequencing the 16S rRNA gene, it was proposed that the analysis of PCG phylogeny and genomic databases could elucidate the shared niche characteristics of PCGs, potentially offering a rapid approach that can be used to characterize microbial ecosystem functioning and identify the role that resident populations play in it. However, it is still unclear whether PCGs are a predominant feature of microbial ecosystems or a rare phenomenon. Also, predicted intra-PCG characteristics could prove invalid, hence limiting the utility of the framework. To gauge the practical usefulness of the framework, we evaluate the existence of PCGs in a wide array of diverse microbial ecosystems, including various human and plant-associated environments, as well as some animal-associated and environmental microbial communities. Then, we assess the predicted PCG characteristics relating to local community assembly. Taking into account, with noteworthy exceptions (e.g. see [12] , [13] ), that microbial ecosystem samples comprise different microenvironments and patches [14] , we then re-analyze the community assembly data of the simple artificial communities published by Goldford et al. [7] . We show that leveraging phylogenetic signal has great potential to illuminate the selective pressures experienced by microbes in natural environments, providing a systematic computational strategy to identify functional groups without requiring exhaustive experimentation [15] .",
"discussion": "4 Discussion We analyzed 16S rRNA gene datasets from various human and plant-associated environments, as well as from animal-associated and environmental microbial communities. PCGs were detected in terms of nodes of a phylogenetic tree present in all instances of each community type. Here, we provide evidence of the presence of PCGs in all datasets analyzed, indicating they could be a predominant feature of microbial ecosystems. Previously, we proposed the conceptual framework of PCGs and an approach for their study [3] . In the present work, we aimed to exemplify how phylogenetic signal (i.e. PCGs) in a microbial ecosystem could be used to help understand its metabolic niches and assembly rules. Drawing from the well supported ideas that traits and ecological function show some degree of phylogenetic conservatism [10] , [39] and that the core pangenome of a clade can be translated to its core ecological niche [11] , [40] , we re-analyzed Goldford et al.'s [7] experimental community composition dataset using solely phylogenetic signal and available genomic resources in order to gauge how much of this community’s ecology could be inferred without further in-depth experimentation. In Goldford et al. [7] , the observed phylogenetic signal was restricted to two families, Enterobacteriaceae and Pseudomonadaceae. Our more fine-grained analysis showed the same restriction to the two families, but it, more importantly, revealed that the PCGs were significantly more restricted than the corresponding taxonomic families. Thus, we argue that phylogenetic signal should be finely delimited before attempting to map phylogeny to shared eco-functional traits based on genomic information. Having finely delimited the PCGs present in the ecosystem, we explored their metabolic niches through a core pangenome analysis. The results pinpointed a potential advantage of E when grown on glucose, derived from its more efficient transport system and the possibility that P processes some or all of the glucose through a less efficient pathway. Subsequent analyses of inter-PCG metabolic models indicated that the experimental P/E could be recapitulated if E consumed glucose or citrate and P consumed the resulting acetate by-product, thus providing an indication of the ecosystem’s niche structure. Our analysis of the community at the population level showed that, contrary to our starting hypothesis, the intra-PCG populations did not present equal fitness. Nonetheless, after the first selective transfer in our drift model with phylogenetic constraints, the resulting diversity metrics were similar to those observed experimentally. Our results are in line with those of Datta et al. [41] , who showed that, during the early stages of community assembly, environmental filtering couples the dynamics of functionally equivalent populations, which, as a result, initially behave in a non-neutral fashion. The ability of the model to approximate experimental observations is noteworthy, though several a priori caveats must be taken into account. These include the inability to model populations that are initially present below the sequence depth-based detection threshold, the use of total community sizes based on normalized sequence numbers instead of experimental cell counts, and the apparent distance between a stepwise growth simulation and in vivo bacterial growth dynamics. Another interesting finding from our general exploration of the glucose dataset was the indirect evidence of biotic interactions. For instance, a single E population (4454257; GreenGenes reference number) could either dominate or co-dominate (alongside 4399988) the endpoint experimental replicates in a non-neutral fashion, depending on the starting community context ( Suppl. Fig. 5 ). However, we hypothesize that the results of our analytical approach to detect possible biotic interactions using co-abundance networks are more consistent with changes in niche sizes. A recent in-depth metabolism study of Goldford’s experimental system indicated that each transfer cycle followed an E to P succession driven by the consumption of glucose and the concomitant accumulation of acetate (see below). Possible fluctuations in sampling times or cycle dynamics could alter PCG abundance; therefore, observed correlations would be related to succession stage instead of actual biotic interactions, as recently cautioned by Pascual García et al. [42] . Given this, sampling of multi-replicated enrichment communities [43] should be adjusted on the basis of community metabolic or abiotic parameters to better serve as model systems, though the implementation of this may prove difficult. Recently, Pascual-García [44] provided a commentary on our proposed conceptual framework. We acknowledge that our initial description provided a tautological formulation, and agree that the detection of PCGs could benefit from using a methodological pipeline independent of the number of samples or their depth. In this regard, we detected PCGs in terms of 16S rRNA gene sequence clusters and nodes of a phylogenetic tree at different depths that are present in all samples from the same ecosystem type. While this is a useful heuristic approach, other criteria, such as a Poisson distribution [45] , a competitive lottery schema [46] , invariance metrics [47] , or the use of neutral models, could also be employed. On the other hand, we feel that the commentary presents misinterpretations regarding our propositions and framework. Significantly, Pascual-García's commentary presents a mental exercise with different assembly scenarios, with the author exploring these scenarios in search of PCGs [44] . However, Pascual-García apparently analyzed only a single sample per scenario, despite the fact that our framework requires the analysis of a large number of samples from the same scenario [3] . This key difference likely accounts for the disparity in the results and interpretations reported in the commentary as pertaining to the framework compared to our own evaluation of the reported exercise. Nonetheless, we both seem to agree on the potential of the PCG approach, which also aligns with Goyal et al.’s recent call to clarify how phylogenetic signal maps to ecological functions [36] . As alluded to above, Estrela et al. [48] recently followed-up on Goldford et al.'s [7] results using a canonical experimental approach, which has provided an overlapping study with which we can compare our results. They first repeated the original experimental set-up with glucose, then isolated several strains that represented a large percentage of the experimental communities and measured their growth rate on the experimental glucose medium. They found that Enterobacteriaceae isolates had higher growth rates than Pseudomonadaceae isolates, contradicting their initial hypothesis that both families coexisted due to similar growth rates [7] . Rather, their results suggest that Pseudomonadaceae populations were sustained in the community owing to the higher competitive ability of the metabolic by-products secreted by the Enterobacteriaceae populations. To confirm this idea, the authors analyzed the secreted by-products of the Enterobacteriaceae strains and showed that acetate was dominant and that the Pseudomonadaceae isolates had a higher growth rate in acetate compared with the Enterobacteriaceae isolates. They proposed that the ecosystem has two phylogenetically conserved metabolic niches: fermenters (Enterobacteriaceae) and respirators (Pseudomonadaceae), which are selected according to the organic acids released by the fermenters on which they specialize. Significantly, as mentioned above, they measured the ratio of P to E at different time points during a 48-h growth cycle and, concomitantly, quantified glucose and acetate levels. In this manner, they demonstrated the differential growth advantage of the two types of isolates: Enterobacteriaceae had an advantage early during the incubation period when glucose was abundant, and Pseudomonadaceae, later, when glucose was absent and acetate was abundant. Thus, each transfer cycle represented a succession from E to P. They also modeled P and E interactions using well-curated metabolic models. They found, as we did with our automated models, that the experimental P/E could be recapitulated only when glucose is completely metabolized to acetate by Enterobacteriaceae, and Pseudomonadaceae fully respires acetate to CO 2 . In summary, their valuable experimental follow-up study shows essentially the same results as those obtained by our purely bioinformatic approach, further supporting the potential usefulness of PCG analyses in evaluating microbial community assembly."
} | 4,246 |
19639401 | PMC2940037 | pmc | 2,159 | {
"abstract": "The complexity of biological neural networks does not allow to directly relate their biophysical properties to the dynamics of their electrical activity. We present a reservoir computing approach for functionally identifying a biological neural network, i.e. for building an artificial system that is functionally equivalent to the reference biological network. Employing feed-forward and recurrent networks with fading memory, i.e. reservoirs, we propose a point process based learning algorithm to train the internal parameters of the reservoir and the connectivity between the reservoir and the memoryless readout neurons. Specifically, the model is an Echo State Network (ESN) with leaky integrator neurons, whose individual leakage time constants are also adapted. The proposed ESN algorithm learns a predictive model of stimulus-response relations in in vitro and simulated networks, i.e. it models their response dynamics. Receiver Operating Characteristic (ROC) curve analysis indicates that these ESNs can imitate the response signal of a reference biological network. Reservoir adaptation improved the performance of an ESN over readout-only training methods in many cases. This also held for adaptive feed-forward reservoirs, which had no recurrent dynamics. We demonstrate the predictive power of these ESNs on various tasks with cultured and simulated biological neural networks.",
"conclusion": "Conclusion The implications of our results are manifold. Firstly, our results indicate that reservoir computing is a potential candidate for modeling neural activity including neural encoding and decoding. With their expressive power for different activity measures (e.g. spike rates, correlations etc.), reservoir computing tools might help for analysis of neural data. In our experiments, ESNs of leaky integrator neurons proved successful for modeling response-dynamics (e.g. stimulus-response relations and spatio-temporal dynamics) of simulated and cultured biological neural neural networks. On the methodological side, we showed that ESN learning algorithms can be adapted for event data , such as spikes or spike groups, using a point process framework. We proposed a reservoir adaptation method for event data , which can be used to adapt connectivity and time constants of the reservoir neurons. The experimental results indicate that reservoir adaptation can significantly improve the ESN performance over readout-only training. We utilized feed-forward networks with leaky-integrator neurons as reservoirs with a comparable predictive power to recurrent reservoirs when trained with log-likelihood propagation. In modeling stimulus-response relations of simulated BNNs, feed-forward reservoir adaptation outperformed other methods up to 500 neurons. This outperformance was statistically significant. For the event timing prediction task in neuronal cultures, adaptive recurrent reservoir adaptation outperformed the other methods (in 2 of 3 cultures), whereas feed-forward adaptation were better in the next-event type prediction task in all 3 cultures. This might indicate that the type of encoding in neural systems (order or timing) favors different architectures for decoding. An analysis of the structure-coding relations, however, is beyond the scope of this note. Why feed-forward reservoir adaptation can work better than recurrent reservoir adaptation necessitates also more theoretical analysis. We manually optimized global parameters (spectral radius, learning rates and A) for recurrent fixed reservoirs. Recurrent adaptive reservoirs started from these values. Although we can think of no obvious disadvantage for recurrent reservoirs, feed-forward adaptation outperformed recurrent adaptation in some tasks. We experimentally showed that one-step propagation approximates the gradients better in feed-forward reservoirs than in recurrent ones. In our opinion, better structuring of the reservoir parameters, i.e. separation of the memory parameters from the reservoir connectivity, might further underlie the relative better performance of feed-forward adaptation. For instance, a small connectivity change in the recurrent adaptation might have a more dramatic effect on the reservoir memory than in case of feed-forward adaptation. Our findings on feed-forward networks are also in accordance with the recent work by Ganguli et al. ( 2008 ), Goldman ( 2009 ), Murphy and Miller ( 2009 ), who show that stable fading memory can be realized by feed-forward or functionally feed-forward networks and that feed-forward networks have desirable properties in terms of trade-off between noise amplification and memory capacity.",
"introduction": "Introduction One central goal in neuroscience is to understand how the brain represents, processes, and conveys information. Starting from Hebb’s cell assemblies (Brown and Milner 2003 ; Hebb 1949 ), many neurobiologically founded theories and hypotheses have been developed towards this goal. It stands clear now that spikes are the elemental quanta of information processing in the mammalian cortex (Hodgkin and Huxley 1952 ; Kandel et al. 2000 ). As a result of extensive experiments of cortical recordings, it has been widely postulated and accepted that function and information of the cortex are encoded in the spatio-temporal network dynamics (Abeles et al. 1993 ; Lindsey et al. 1997 ; Mainen and Sejnowski 1995 ; Prut et al. 1998 ; Riehle et al. 1997 ; Villa et al. 1999 ). The right level of describing the dynamics, however, is a matter of intensive discussions (Prut et al. 1998 ; Rieke et al. 1999 ). Are spike rates or spike timings more relevant? What is the right temporal precision if the latter proves significant? What should be the spatial resolution of this description? How far can the population activity of neurons be related to function or behavior? Does the correlated activity of multiple neurons indicate a functionally relevant state? Depending on the answers to the above questions one would preferably apply different models to relate the network activity to function. Another approach is to employ a generic network model, which can be assumed to be universal for problems of neural encoding. The parameters of the model would be learned by adaptive algorithms. Obviously, such a model should be able to deal with single spikes with high temporal precision as well as population rates. It should also be able to catch, with the appropriate parameters, network synchrony and polychrony (Izhikevich 2006 ). Reservoir computing Liquid State Machines (LSM) and Echo State Networks (ESN) have been introduced as efficiently learning recurrent neural networks (Jaeger 2001 ; Maass et al. 2002 ). The common key contribution of these approaches is the proposal of a recurrent neural network with a fixed connectivity, i.e. a reservoir , which does not have stable states and has a fading memory of the previous inputs and network states. In response to an input stream, the reservoir generates a higher-dimensional spatio-temporal dynamics reflecting the structure in the input stream. The higher dimensional reservoir state can be mapped to a target output stream online, with a second module, namely a readout. LSMs are networks of spiking integrate-and-fire (IAF) neurons whereas ESNs use continuous valued sigmoid neurons and a single layer of readout neurons (see Section 2 ). With the appropriate parameters, reservoir dynamics can be sensitive to different features of the input such as correlations, polychronous and synchronous spikes, different frequency bands or even temporally precise single spikes. For instance, LSMs can approximate any time invariant filter with fading memory if their traces of internal states differ at least for one time point in response to any two different input streams ( Separation Property, SP ) and if the readout modules can approximate any continuous function from ℝ m → ℝ, where m ∈ ℕ ( Approximation Property, AP ) (Maass et al. 2002 ). Satisfying the separation property depends on whether the reservoir is composed of sufficient basis filters. A random reservoir needs to have a rich repertoire of basis filters in order to approximate the target time-invariant filter. This could be achieved for several tasks with sufficiently large random reservoirs (Maass et al. 2002 ). Furthermore, reservoirs have been shown to simulate a large class of higher order differential equations with appropriate feedback and readout functions (Maass et al. 2007 ). These findings suggest that reservoir computing can be used as a generic tool for the problems of neural encoding. Biological neural networks, in vivo , process a continuous stream of inputs in real time. Moreover, they prove successful to react and compute fast, independent of their instantaneous state and ongoing activity, when prompted by sudden changes in stimuli. In other words, they perform any time computing . Reservoir computing has also been suggested as a model of cortical information processing for their capability of online and anytime computing, for their fading memory and for their separation properties. It has been argued that specific cortical circuitry is possible to build into generic LSM framework (Maass et al. 2004 ). Bringing reservoir computing into the problem will not only deliver expressive models that can distinguish a rich set of input patterns, but also may provide more biological relevance to the theoretical tool. Neuronal cell cultures as biological neural networks While brain tissue has highly specialized architecture and developmental history, generic biological networks can be created as cell cultures of mammalian cortical neurons that have been dissociated and regrown outside an organism. They are closed system in vitro living networks, which are frequently used to study physiological properties of neural systems (Marom and Shahaf 2002 ). Although the anatomical structure of the brain is not preserved in cultures, their inherent properties as networks of real neurons, their accessibility and small size make them very attractive for investigating information processing in biological networks. Using cultured networks also eliminates the problem of interference with ongoing activity from different parts of the brain. Compared to in vitro brain slices, cultured networks are more accessible in terms of ratio of the recorded neurons to the whole network. In other words, they pose a less serious under-sampling problem. Studying such networks can provide insight into the generic properties biological neural networks, independent of a specific anatomy (Marom and Shahaf 2002 ). Another motivation to study cultures is understanding and employing them as biological computers. For instance, neuronal cell cultures have been shown to be able to learn. Shahaf and Marom ( 2001 ) demonstrated how the response of the network to a stimulus can be ‘improved’ by systematically training the culture. Jimbo et al. ( 1999 ) showed how neuronal cultures can increase or decrease their overall response to pulse inputs stimulus by tetanic stimuli training. Micro-Electrode Arrays (MEA) have commonly been employed to both stimulate and record from neuronal cultures and slices (Egert et al. 2002 ; Marom and Shahaf 2002 ) (Fig. 1 ). Standard MEAs allow for simultaneous recordings and stimulations from up to 60 electrodes from a surface area of around 2 mm \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$^\\text{2}$\\end{document} . Each electrode picks up the extracellular electrical field of one or several (1 to 3) neurons. Neurons transmit information by action potentials , or spikes , which can be extracted by adaptive high-pass filtering of the extracellular signals (Egert et al. 2002 ; Wagenaar et al. 2005 ).\n Fig. 1 A photo image of a neuronal culture with MEA electrodes. We aim at generating an equivalent network in terms of input–output relations. Photo was taken by Steffen Kandler from BCCN Freiburg \n The activity in neuronal cultures is composed of irregular network-wide bursts of spikes, even in absence of an external stimulation (Marom and Shahaf 2002 ). These networks display little or no spiking activity most of the time (that is, between bursts) and very high spiking activity during the bursts (Fig. 2 ). Although the inter-burst intervals are not necessarily regular, there seem to be spatio-temporal patterns that occur within bursts (Feber le et al. 2007 ; Rolston et al. 2007 ). For example, a burst might always start with the activity of the same channel and continue with the activity of another particular channel.\n Fig. 2 Spike activity in neuronal cultures. Burst activity ( left ). Zoom into a burst. Each dot shows a spike detected on the corresponding electrode at the corresponding time ( right ) \n Problem statement Although we cannot relate the activity dynamics to a physiological function in random in vitro BNNs, by studying their activity dynamics, we gain experience and information about generic network properties forming the basis of in vivo networks. Moreover, one can assign pseudo-functions to random BNNs by artificially mapping network states to a predefined set of actions (Chao et al. 2008 ). One can also regard the response spike train of a BNN to a stream of various stimuli as a very detailed characterization of its pseudo-function and aim at modeling stimulus-response relations. In the present work, we take this approach. We record the output responses of simulated and cultured BNNs to random multivariate streams of stimuli. We tackle the question whether it is possible to train an artificial neural network that predicts the response of a reference biological neural network under the applied stimulus range. In other words, we aim at generating an equivalent network of a BNN in terms of stimulus-response relations. Given the same stimulus, the equivalent network should predict the output of the biological neural network. A model or a predictor for biological neural networks can be useful for relating the physiological and physical determinants of its activity and thereby, can be a tool for analyzing information coding in these networks. It can also be helpful for interacting with BNNs by means of electrical stimulation. Here, we employ Echo State Networks (ESN) as a reservoir computing tool and propose an algorithm to find appropriate models for the relations between continuous input streams and multi-unit recordings in biological neural networks. The algorithm uses point process log-likelihood as an optimization criterion and adapts the readout and reservoir parameters of ESNs accordingly. Moreover, we investigate the performance of our approach on different feed-forward and recurrent reservoir structures and demonstrate its applicability to stimulus-response modeling problem in BNNs. We shortly review ESNs in Section 2 and point process modeling of spike data in Section 3 . An elaboration of ESN adaptation for point processes is presented in Section 4 . In Section 5 we present our evaluation methods. A detailed experimental section and their implications can be found in Sections 6 and 7 , respectively."
} | 3,853 |
22363331 | PMC3282478 | pmc | 2,160 | {
"abstract": "The anaerobic oxidation of Fe(II) by subsurface microorganisms is an important part of biogeochemical cycling in the environment, but the biochemical mechanisms used to couple iron oxidation to nitrate respiration are not well understood. Based on our own work and the evidence available in the literature, we propose a mechanistic model for anaerobic nitrate-dependent iron oxidation. We suggest that anaerobic iron-oxidizing microorganisms likely exist along a continuum including: (1) bacteria that inadvertently oxidize Fe(II) by abiotic or biotic reactions with enzymes or chemical intermediates in their metabolic pathways (e.g., denitrification) and suffer from toxicity or energetic penalty, (2) Fe(II) tolerant bacteria that gain little or no growth benefit from iron oxidation but can manage the toxic reactions, and (3) bacteria that efficiently accept electrons from Fe(II) to gain a growth advantage while preventing or mitigating the toxic reactions. Predictions of the proposed model are highlighted and experimental approaches are discussed.",
"conclusion": "Conclusion Our central hypothesis is that the mechanisms used by neutrophilic anaerobic nitrate-dependent iron-oxidizing bacteria likely exist along a continuum from purely abiotic reactions between microbially produced nitrogen oxides to mixed biotic/abiotic mechanisms involving direct electron donation from iron to cellular components. This fascinating and geochemically important process may also be unique in that the microbial metabolisms themselves might take advantage of abiotic reactions, for example by using NO 2 - as a shuttle (Miot et al., 2009a ; Chakraborty et al., 2011 ), or through the electron sparing hypothesis in Figure 1 D. With the growing number of pure isolates of robust iron oxidizing microorganisms, we are optimistic that the mechanistic proposals in this paper can be tested in the laboratory.",
"introduction": "Introduction In recent years, significant progress has been made toward understanding the biochemical mechanisms used by bacteria to catalyze the aerobic and anaerobic oxidation of Fe(II) in the environment. Recent reviews focus on aerobic/microaerobic iron oxidation (Emerson et al., 2010 ) and iron oxidation by acidophiles and anoxygenic phototrophs (Bird et al., 2011 ), however a number of microorganisms have been described which can couple iron oxidation to nitrate reduction (Chaudhuri et al., 2001 ; Weber et al., 2001 , 2006a , b ; Finneran et al., 2002 ; Lack et al., 2002 ; Muehe et al., 2009 ) in the absence of oxygen and light. The growth benefit from anaerobic iron oxidation varies widely. In both photosynthetic and nitrate reducing bacteria, oxidation of Fe(II) may represent an important detoxification strategy (Muehe et al., 2009 ; Poulain and Newman, 2009 ), and in some cases may have also evolved into a metabolic strategy (Widdel et al., 1993 ; Croal et al., 2007 ; Jiao and Newman, 2007 ; Muehe et al., 2009 ; Weber et al., 2009 ; Chakraborty et al., 2011 ). In this paper, we suggest that the success of an iron-oxidizing microorganism depends on the extent to which electron donation from Fe(II) can be controlled and toxic reactions prevented or managed. We propose working models to analyze the results of experiments aimed at elucidating the mechanisms of iron oxidation by anaerobic nitrate reducing bacteria. We also highlight some of the predictions of the models that future experiments should address. Our intention is not to exhaustively review the literature, but rather to highlight some of the salient features of anaerobic nitrate-dependent iron oxidation and provide insight for new research directions."
} | 911 |
26994377 | null | s2 | 2,161 | {
"abstract": "The explosion of genomic sequence data and the significant advancements in synthetic biology have led to the development of new technologies for natural products discovery and production. Using powerful genetic tools, the yeast Saccharomyces cerevisiae has been engineered as a production host for natural product pathways from bacterial, fungal, and plant species. With an expanding library of characterized genetic parts, biosynthetic pathways can be refactored for optimized expression in yeast. New engineering strategies have enabled the increased production of valuable secondary metabolites by tuning metabolic pathways. Improvements in high-throughput screening methods have facilitated the rapid identification of variants with improved biosynthetic capabilities. In this review, we focus on the molecular tools and engineering strategies that have recently empowered heterologous natural product biosynthesis."
} | 229 |
35755759 | PMC9217564 | pmc | 2,163 | {
"abstract": "The problem of joint optimization of inventory and transportation in agricultural logistics and distribution is a typical logistics problem, but agricultural logistics and distribution also have their own characteristics, such as uneven distribution of outlets, complex road conditions, very many outlets, a single order with few goods but high frequency of ordering, centralized distribution, and unified channels. To promote the sustainable development of the economy, it is necessary to save energy and reduce emissions, and eventually enter a new era of “low consumption, low pollution, and low emissions.” Modern logistics vehicle-scheduling process is complex and changeable, and the existing mathematical methods are not perfect in solving this problem, lacking scientific theory as a guide. The joint optimization problem introduces the inventory change factor on the basis of periodic vehicle path optimization and optimizes the inventory decision and path planning in an integrated manner. As a system to support the logistics industry, the visualized logistics information system is capable of video viewing and querying logistics information. In order to reduce gas emissions and save costs, it is necessary to optimize the transportation link, and the focus of optimization is the route optimization of distribution vehicles. Ant colony algorithm (ACA) is an emerging search and optimization technique, which emerged from the research of ACA. In this study, we study the joint optimization and visualization of inventory transportation in agricultural logistics based on ACA. In addition, the experimental results show that the inventory cost/total cost of improved ACA is 0.006 when the unit mileage transportation cost is 10, and the IBM ILOG CPLEX is 0.031, which is reduced by 0.0025, that is to say, in the case of high inventory cost per unit product, the use of improved ACA can lead to a significant reduction in inventory costs. Therefore, it can realize the whole process of control, traceability, and dynamic optimization to ensure the timeliness of emergency finished food security and provide real-time information for decision-making in command as well.",
"conclusion": "5. Conclusions The development of modern logistics technology and the widespread use of the automated three-dimensional warehouse, resulting in an automated three-dimensional warehouse in the joint optimization of inventory transportation and scheduling problems, have become the bottleneck in modern logistics technology that has yet to be solved. The modern economy is a more important part of modern logistics, the development of modern logistics to improve the country's economy, optimize the system configuration, save time costs, etc. is of great significance. In addition, the traditional information system of finished grain cannot meet the needs of users, and the visualization of the information system is getting more and more attention. The ACA can complete the construction of a global solution by local solution with the help of positive and negative feedback function; in addition, it can prevent the algorithm from entering the local optimal mode with the help of negative feedback function. Therefore, in this study, based on the analysis of the current development of China's agricultural logistics system, the research focuses on the inventory and transportation aspects to improve the comprehensive decision-making level, and proposes the joint optimization of inventory and transportation with the “efficiency backward” relationship. This study introduces ACA into logistics vehicle scheduling and explores the joint optimization of inventory and transportation of transportation vehicles by using ACA to pursue the optimal solution with the lowest total cost and the greatest total benefit of the transportation system. Therefore, the study of joint optimization and visualization of inventory transportation in agricultural logistics based on ACA takes into account the constraints closer to the reality and has the advantages of simplicity, intuition, easy-to-understand, and easy-to-design algorithms to solve and strengthen expandability.",
"introduction": "1. Introduction China's agricultural products are not only rich in resources but also rank steadily among the top in the world in terms of production, but the problem of agricultural logistics has been plaguing agricultural players [ 1 ]. The so-called logistics refers to the flow process of material materials in physical form from the place of supply to the place of consumption in social reproduction [ 2 ]. Through the study and application of optimal scheduling of logistics transport vehicles, it is possible to improve the economic efficiency of logistics and achieve scientific logistics [ 3 ]. In the process of logistics distribution, to reduce resource consumption, it is necessary to start from the distribution path, which is the main basis and ultimate goal of sustainable development [ 4 ]. Agricultural product logistics and distribution are the end of frustrated agricultural product logistics, connecting agricultural product logistics centers with the final sales outlets such as various farmers' markets and supermarkets [ 5 ]. At the same time, with the development of information technology and the changing needs of e-commerce consumers, e-commerce merchants more urgently need third-party logistics to provide personalized and specialized logistics services [ 6 ]. Both merchants and consumers want to visualize the entire logistics service process to improve logistics efficiency, reduce logistics costs, and thus, better meet the needs of consumers [ 7 ]. The consumption level of the population has gradually increased, the structure of the agricultural industry has gradually made adjustments, and the circulation and production of fresh agricultural products have gradually increased every year [ 8 ]. Therefore, more stringent requirements are put forward for the quality and the safety of products [ 9 ]. To improve the operational efficiency of the railroad transport industry, reduce costs and enhance service quality, and achieve industrial upgrading, the active development of modern logistics services is the way to go, and the use of computer technology to realize the informationization of logistics is one of the important means [ 10 ]. On the one hand, the rapid development of computers promotes the continuous development of optimization methods, on the other hand, it also makes the engineering optimization problems become larger and larger, and the nature of the optimization objective function becomes more and more complex [ 11 ]. How to use scientific and effective methods to optimize inventory transportation to improve the economic efficiency of enterprises under the condition of satisfying the diversified needs of customers is an important issue of concern and research focus in the field of logistics today [ 12 ]. Chinese logistics enterprises want to grasp the pulse of the future era and become the world market leader, understand the industry competition, win market exclusivity, and seize market opportunities in order to stand firm in this big market economy [ 13 ]. In solving multiobjective optimization problems, since the objectives are often in conflict with each other, there is often no constraint that can satisfy all constraints [ 14 ]. Instead, there is a set of Pareto optimal solutions [ 15 ]. Therefore, the ACA is introduced into this problem to provide technical measures to build an integrated logistics system, establish a modern scheduling and command system, develop an intelligent transportation system, and carry out modern e-commerce with the help of process simulation technology, in view of the comprehensive, complex, and uncertain characteristics of joint optimization and visualization of inventory transportation in agricultural logistics. The innovative points of this study are as follows: Considering the influence of freshness input on freshness level and quantitative loss, the functional relationship between freshness and quantitative loss is portrayed. Considering the cost of vehicles, such as fixed cost, refrigeration cost, transportation cost, penalty cost, cargo damage cost, and setting the goal of distribution as the total cost minimization, an optimization model is constructed, i.e., the joint optimization model of inventory transportation based on ACA. To conduct a joint optimization study, inventory level and distribution path are affected by market demand, product deterioration rate, and other factors at the same time, and the cost-minimization path can be planned according to the demand node location and distribution volume. The research framework of this study contains five major parts, which are organized as follows. The first part of this study introduces the research background and significance, and then introduces the main work of this study. The second part introduces the work related to the joint optimization and visualization of inventory transportation in agricultural logistics, and the development of an e-commerce platform based on ACA for logistics transportation optimization. In the third part, the establishment of ACA-based inventory and transportation optimization model and the establishment of ACA-based inventory and transportation visualization platform are explained, so that the readers of this study can have a more comprehensive understanding of the idea of ACA-based inventory and transportation optimization and visualization in agricultural logistics. The fourth part is the core of the thesis, which describes the application analysis of ACA in the joint optimization and visualization of inventory transportation in agricultural logistics from two aspects, namely, the improvement of ACA analysis and the improvement of the process analysis of ACA for agricultural logistics. The last part of the thesis is the summary of the full work."
} | 2,484 |
28491136 | PMC5424312 | pmc | 2,165 | {
"abstract": "Background Microalgae have shown clear advantages for the production of biofuels compared with energy crops. Apart from their high growth rates and substantial lipid/triacylglycerol yields, microalgae can grow in wastewaters (animal, municipal and mining wastewaters) efficiently removing their primary nutrients (C, N, and P), heavy metals and micropollutants, and they do not compete with crops for arable lands. However, fundamental barriers to the industrial application of microalgae for biofuel production still include high costs of removing the algae from the water and the water from the algae which can account for up to 30–40% of the total cost of biodiesel production. Algal biofilms are becoming increasingly popular as a strategy for the concentration of microalgae, making harvesting/dewatering easier and cheaper. Results We have isolated and characterized a number of natural microalgal biofilms from freshwater, saline lakes and marine habitats. Structurally, these biofilms represent complex consortia of unicellular and multicellular, photosynthetic and heterotrophic inhabitants, such as cyanobacteria, microalgae, diatoms, bacteria, and fungi. Biofilm #52 was used as feedstock for bioenergy production. Dark fermentation of its biomass by Enterobacter cloacae DT-1 led to the production of 2.4 mol of H 2 /mol of reduced sugar. The levels and compositions of saturated, monosaturated and polyunsaturated fatty acids in Biofilm #52 were target-wise modified through the promotion of the growth of selected individual photosynthetic inhabitants. Photosynthetic components isolated from different biofilms were used for tailoring of novel biofilms designed for (i) treatment of specific types of wastewaters, such as reverse osmosis concentrate, (ii) compositions of total fatty acids with a new degree of unsaturation and (iii) bio-flocculation and concentration of commercial microalgal cells. Treatment of different types of wastewaters with biofilms showed a reduction in the concentrations of key nutrients, such as phosphates, ammonia, nitrates, selenium and heavy metals. Conclusions This multidisciplinary study showed the new potential of natural biofilms, their individual photosynthetic inhabitants and assembled new algal/cyanobacterial biofilms as the next generation of bioenergy feedstocks which can grow using wastewaters as a cheap source of key nutrients. Electronic supplementary material The online version of this article (doi:10.1186/s13068-017-0798-9) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions Algal/cyanobacterial-based biofilms are getting increasingly popular as an alternative to suspension-based culture systems because of their low-cost algal harvesting [ 21 , 73 – 75 ]. Moreover, in algal biofilm systems, high algal concentration can be achieved with a significantly reduced amount of medium compared to the same biomass grown in suspension cultures [ 21 , 22 ]. In this study, multidisciplinary research was applied to analyse different aspects of natural algal/cyanobacterial-based biofilms, their compositions, growth rates in response to the changing environmental conditions, as well as the interaction between individual inhabitants and assessments of their cumulative contributions to biofilm’s stability and chemical composition. We showed that the level and composition of photosynthetic inhabitants within biofilms could be tailored for the production of novel biofilms which are stable when growing in the new environmental ecosystems. These assembled biofilms can be specifically used for the (i) concentration of commercial microalgal species, working as bio-flocculating agents; (ii) for high-efficiency and low-energy strategies of treatment specific types of commercial wastewaters, and (iii) as novel sustainable feedstocks with compositions suitable for production of renewable bioenergy: bio-hydrogen and biodiesel."
} | 982 |
37399189 | PMC10762510 | pmc | 2,166 | {
"abstract": "Abstract Plant lignocellulosic biomass, i.e. secondary cell walls of plants, is a vital alternative source for bioenergy. However, the acetylation of xylan in secondary cell walls impedes the conversion of biomass to biofuels. Previous studies have shown that REDUCED WALL ACETYLATION (RWA) proteins are directly involved in the acetylation of xylan but the regulatory mechanism of RWAs is not fully understood. In this study, we demonstrate that overexpression of a Populus trichocarpa PtRWA-C gene increases the level of xylan acetylation and increases the lignin content and S/G ratio, ultimately yielding poplar woody biomass with reduced saccharification efficiency. Furthermore, through gene coexpression network and expression quantitative trait loci (eQTL) analysis, we found that PtRWA-C was regulated not only by the secondary cell wall hierarchical regulatory network but also by an AP2 family transcription factor HARDY (HRD). Specifically, HRD activates PtRWA-C expression by directly binding to the PtRWA-C promoter, which is also the cis -eQTL for PtRWA-C . Taken together, our findings provide insights into the functional roles of PtRWA-C in xylan acetylation and consequently saccharification and shed light on synthetic biology approaches to manipulate this gene and alter cell wall properties. These findings have substantial implications for genetic engineering of woody species, which could be used as a sustainable source of biofuels, valuable biochemicals, and biomaterials.",
"introduction": "Introduction Plant lignocellulosic biomass is one of the important alternative sources of bioenergy to meet growing energy use demands and alleviate our dependence on fossil fuels ( Carroll and Somerville 2009 ; Chen et al. 2020 ). The majority of plant lignocellulosic biomass is found in the carbohydrate-rich walls that surround every plant cell. Some cells deposit a thickened secondary wall after elongation ceases, typically consisting of lignin, cellulose, and hemicellulose. Hemicelluloses are a group of diverse polysaccharides that include xylans, xyloglucans, (gluco)mannans, and mixed-linked glucans ( Scheller and Ulvskov 2010 ). Recently, multidimensional analysis of plant biomass using solid-state nuclear magnetic resonance (NMR) spectroscopy has begun to reveal molecular-level information regarding the organization of native cell walls and shedding light on structure-function relationships of polymer classes that impact the 3D molecular architecture of lignocellulose ( Kirui et al. 2022 ). Almost all noncellulosic polysaccharides in the cell walls of dicots are esterified to varying degrees with O -acetyl moieties. Xylan in the secondary cell walls of woody plants can be highly acetylated, which affects its physicochemical properties ( Ebringerová 2005 ). Investigation of 13 C-labeled poplar ( Populus × canadensis ) stems to study contacts between polymers in spatially packed woody biomass identified key intramolecular interactions between xylan acetyl groups with lignin and cellulose in a xylan conformation-dependent manner ( Kirui et al. 2022 ). Unrestrained molecular dynamics (MD) simulations of acetylated xylan further supports the notion that both the spacing and position of substituents on xylosyl residues play key roles in tuning xylan-cellulose interactions ( Gupta et al. 2021 ). Acetylation of xylans and other polysaccharides has implications for the use of biomass as feedstocks for biofuel production, and the presence of acetyl groups has a negative impact on saccharification and fermentation ( Selig et al. 2009 ; Jönsson et al. 2013 ). Deacetylation of lignocellulose by chemical or enzymatic methods increases sugar release during enzymatic hydrolysis ( Zhang et al. 2011 ). Taken together, understanding the identity, function, and genomic and biochemical regulation of enzymes involved in polysaccharide O -acetylation can give insights into how to manipulate wood architecture for the more facile production of next-generation fuels and materials. The acetylation and deacetylation of polysaccharides are regulated by complex enzymatic reactions. During polysaccharide biosynthesis in the Golgi apparatus, acetyl groups are transferred from an as yet to be definitively confirmed O -acetyl donor to polysaccharides with the participation of the REDUCED WALL ACETYLATION (RWAs), ALTERED XYLOGLUCAN 9 (AXY9), and TRICHOME BIREFRINGENCY–LIKE (TBL) gene families ( Gille et al. 2011 ; Manabe et al. 2013 ). The Arabidopsis ( Arabidopsis thaliana ) axy9 mutant has reduced acetylation of xylan and xyloglucan ( Schultink et al. 2015 ). Similarly, mutants of TBL29 ( ESKIMO1 ), TBL32 , and TBL33 exhibit an irregular xylem phenotype and decreased xylan acetylation ( Xiong et al. 2013 ; Yuan et al. 2016 ). In contrast, the deacetylation of polysaccharides can be catalyzed by carbohydrate esterases. An Arabidopsis clade Id member of the GDSL esterase/lipase (GELP) family, At GELP7 (also named as acetyl xylan esterase1, [ At AXE1]), is regulated by secondary cell wall (SCW) master switch At MYB46 and has acetyl xylan esterase (AXE) activity and functions to reduce xylan acetylation levels ( Rastogi et al. 2022 ). In addition, the use of biotechnology to introduce related enzymes from other species into plants has also become an effective strategy for altering plant acetylation levels. Pawar et al. (2016) expressed An AXE1 from Aspergillus niger , a Carbohydrate Esterase family 1 (CE1) enzyme that deacetylates polymeric xylan but not pectin, to deacetylate xylan in Arabidopsis and improved the sugar saccharification efficiency and ethanol yields. Expression of the Hypocrea jecorina CE5 family gene HjAXE in poplar driven by a wood-specific promoter also effectively reduces wood acetylation levels and improves cellulose accessibility ( Wang et al. 2020 ). Members of the RWA family were the first class of proteins reported to be involved in plant cell wall acetylation ( Manabe et al. 2011 ). In Arabidopsis , 4 RWA genes ( AtRWA1 - 4 ) are regulated by the secondary cell wall master regulator SND1 and are functionally and redundantly associated with secondary wall thickening. The quadruple rwa mutant has cell walls with a significant reduction in the acetylation level of xylan and a defect in secondary wall thickening ( Lee et al. 2011 ). The RWA gene family in Populus also has 4 genes ( PtRWA-A , -B , -C , and -D ), which are grouped into 2 clades and have been shown to also be functionally and redundantly involved in wood acetylation. In addition, suppression of the 4 members resulted in improved saccharification efficiency ( Pawar et al. 2017b ). In this study, a Populus activation-tagged mutant with substantial changes in lignin content and S/G ratio was identified and TAIL-PCR confirmed that the PtRWA-C gene was activated in this dominant mutant. Analysis of the coexpression network of PtRWA-C reveals that several known secondary cell wall-related transcription factors (TFs) such as NST1 , SND2 , and MYB46/83 are coexpressed with PtRWA-C , implying a potential role of PtRWA-C in secondary cell wall biosynthesis. We discovered that overexpression of PtRWA-C does not affect growth and biomass but does affect stem acetylation level and transcriptome. Expression QTL (eQTL) analysis and yeast 1-hybrid (Y1H) assay indicate that PtRWA-C is directly regulated by an AP2 family transcription factor HARDY (HRD). These results provided insights into the function of PtRWA-C in cell wall modification and its regulatory pathway.",
"discussion": "Discussion As the major hemicellulose component in cell walls of many woody species, acetylated xylan hinders the conversion of lignocellulosic biomass to biofuels ( Carroll and Somerville 2009 ; Chen et al. 2020 ). Therefore, understanding the biochemical pathway and key players involved in xylan acetylation and its regulatory mechanism is important not only for our understanding of basic biological processes but also for the directional improvement of bioenergy plants targeting biofuels. During biosynthesis in the Golgi apparatus, polysaccharides in plant cell walls are O -acetylated using acetyl-coenzyme A (CoA) as a donor substrate ( Pauly and Scheller 2000 ). The pattern and degree of acetylation differ not only between plant species but also within cell types and/or developmental stages of plants. In plants, the process of polysaccharide O -acetylation requires 3 category enzymes: TBLs, AXY9, and RWAs. The TBL and AXY9 proteins contain a single TM domain that anchors the proteins to the Golgi membrane and their C-termini are oriented towards the Golgi lumen containing putative catalytic motifs. In contrast, RWA proteins have at least 10 TM helical structures ( Manabe et al. 2011 ). RWA is thought to be responsible for translocation of the acetyl group of acetyl-CoA (or another unidentified donor) from the cytoplasmic pool to the Golgi apparatus in order to provide substrates for the other 2 families of OatAs (i.e. TBLs and AXY9) ( Pauly and Scheller 2000 ). In Populus , there are 4 RWA genes, with the same number as that in the Arabidopsis genome ( Pawar et al. 2017b ), indicating that no gene family expansion has occurred in the Populus RWA gene family. Comparative genomics studies have indicated that homologous genes in poplar typically occur in 1.4 to 1.6 times the number of Arabidopsis genes, which has been attributed to the Salicoid duplication even ( Tuskan et al. 2006 ). Homologous maintenance of RWA gene numbers in poplar relative to Arabidopsis suggests RWA function has been conserved during speciation and evolution of the 2 species. Expression patterns of the 4 PtRWA genes indicated that all PtRWAs are highly expressed in SDX cells and in the SCW forming stage of xylem development ( Fig. 2 ). Different from the other 3 members, PtRWA-C is also highly expressed in the phloem and cambium regions and its expression can be induced by SND1-B1 , which suggests that PtRWA-C may affect the acetylation process of other cell wall matrix components. This is similar to its homolog AtRWA2 in Arabidopsis (amino acid identity 72.4%), which is also expressed in primary cell walls and has a broad acetylation to pectic/nonpectic polysaccharides and xyloglucan ( Manabe et al. 2011 ). The single-mutant rwa2 in Arabidopsis had no obvious growth or developmental phenotypes, but triple and quadruple rwa mutants showed severe growth phenotypes. Expression of a single RWA2 gene in the quadruple mutant compensated for its growth phenotype, suggesting that the RWA homologs are functionally redundant. However, different members have preferences for acetylated substrates such as xylan, (gluco)mannan, and xyloglucan ( Manabe et al. 2013 ). Similarly, suppression of 2 genes in the AB clade or 2 genes in the CD clade in the poplar RWA gene family did not affect its growth but had an effect on its acetylation level of cell wall. When all RWA genes, i.e. A-D, were suppressed in poplar, the acetylation level of xylan in wood was significantly reduced and the saccharification efficiency of biomass was improved ( Pawar et al. 2017b ). In our study, PtRWA-C contains 11 helical TM structures and its subcellular localization is on the Golgi apparatus ( Fig. 2 ). In addition, the acetyl content in the cell wall of plants overexpressing PtRWA-C is significantly increased ( Fig. 3 ). These results indicate that PtRWA-C is likely involved in the translocation of the O -acetyl donor, increasing the available substrate pool for OatAs in the Golgi. Furthermore, overexpression of PtRWA-C caused changes in the expression levels of a series of genes in poplar stem including a large number of TFs ( Fig. 6 ). It is unclear how the acetylation level of cell wall components directly affects gene expression, and we propose that changes in xylan structure or substrate utilization trigger a feedback regulation mechanism. Overexpression of a single PtRWA-C gene not only led to an increase in xylan acetylation levels but also resulted in a decrease in the release of glucose and fructose ( Fig. 3 ). This is consistent with the negative effect of xylan acetylation on saccharification efficiency. In addition, the lignin content and S/G ratio in the overexpression plants were increased ( Fig. 3 ), indicating that acetylation of xylan has an impact on the biosynthesis of lignin components. Pramod et al. (2021) used a wood-specific promoter to constitutively express the fungal acetyl xylan esterases ( An AXE1) in hybrid aspen. The transgenic plants showed lower acetylation levels and a small reduction in lignin S/G ratio, but no significant differences in carbohydrate or lignin contents. Similarly, an earlier study concluded that when the acylation levels of xylan were altered, the composition and solubility of lignin were dramatically modified ( Pawar et al. 2017a ). However, the direct effect of increase of xylan acetylation level on an increase in lignin content and S/G ratio needs further study. Figure 6. Transcriptomic changes in Populus transgenic plants overexpressing PtRWA-C . A) DEGs overlapped in leaf and stem of the 2 PtRWA-C overexpression lines (#1 and #2) compared to control plant (Ctrl). A total of 481 DEGs (286 upregulated and 194 downregulated) overlapped in stem of the 2 transgenic lines were identified as core-DEGs. B) Enriched biological process (BP) terms of GO enrichment analysis of the core-DEGs. C) Transcription factor binding site (TFBS) enrichment analysis of 2-kb promoter regions of the core-DEGs. D) Expression patterns of genes in the 7 coexpression modules. Numbers in parentheses indicate the number of genes ( n ) in each module. The bold line in the center of the boxplots represents the median, the box edges represent the 25th (lower) and 75th (upper) percentiles, and the whiskers extend to the most extreme data points that are no more than 1.5× the length of the upper or lower segment. Our results related to the gene regulatory pathway associated with RWA have bioenergy and biomaterial applications. Previous studies analyzed c. 1-kb promoter sequences of the 4 RWA genes in poplar and found that RWA-A and RWA-B , but not RWA-C and RWA-D , were strongly regulated by homologs of SCW synthesis master switches NST1 and MYB46 ( Pawar et al. 2017b ). Our comprehensive gene coexpression network analysis found that PtRWA-C was also coexpressed with SCW-TFs such as NST1 and MYB46 ( Fig. 2 ), implying that it may also be regulated by the SCW hierarchical regulatory network. Further analysis of the cis -acting elements indicates that there are multiple SNBE and SMRE located between 1∼2 kb upstream of the PtRWA-C gene promoter, which may serve as binding sites for NAC and MYB TFs, respectively ( Fig. 5 ). The Y1H assay also confirmed that NAC and MYB (including the master switches NST1 , SND2 , and MYB46 ) directly bind to the promoter of PtRWA-C ( Fig. 5 ), indicating that PtRWA-C is also directly regulated by the SCW hierarchical regulatory network. eQTL analysis developed based on population genetics and bioinformatics in recent years has pointed to gene regulatory mechanisms. In this analysis, gene expression levels are considered as quantitative traits and gene expression phenotypes are mapped to specific genomic loci by combining the study of gene expression pattern variation with genome-wide genotyping ( Gilad et al. 2008 ). In forest trees, the potential transcriptional regulatory relationships identified by eQTL mapping have been confirmed experimentally. For example, using GWAS analysis, it was found that a hydroxycinnamoyl-CoA:shikimate hydroxycinnamoyl transferase gene PtHCT2 in poplar is a key gene that controls the biosynthesis of metabolites such as 3- O -caffeoylquinic acid. In parallel, the eQTL analysis discovered that PtHCT2 expression was regulated by the upstream WRKY-HCT2 regulatory module through cis -eQTL ( Zhang et al. 2018b ). In this study, we found that the expression of PtRWA-C was strongly regulated by cis -eQTL through eQTL mapping and the cis -element containing the cis -eQTL is the binding site of HRD, which is close to another strong trans -eQTL associated with PtRWA-C expression ( Fig. 4 ). Y1H and Dual-LUC experiments also confirmed the direct regulation of PtRWA-C by HRD ( Fig. 5 ). These results indicate that eQTL mapping analysis is an effective platform for exploring regulatory relationships in woody plants, the application of which needs to be further expanded. In summary, our study provides insights into the functional roles of PtRWA-C in modulating xylan acetylation and saccharification efficiency, which has important implications for the genetic engineering of forest trees for bioenergy or biomaterial production. Specifically, we identified upstream regulatory genes and cis -eQTL that regulate PtRWA-C expression, which could serve as potential targets for gene and promoter editing to alter gene expression levels and acetylation patterns, ultimately affecting bioprocessing recalcitrance. These findings have important implications for the development of engineered wood species as sustainable sources of biofuels and biomaterials."
} | 4,328 |
38272896 | PMC10811339 | pmc | 2,168 | {
"abstract": "Memristor-based neural networks provide an exceptional energy-efficient platform for artificial intelligence (AI), presenting the possibility of self-powered operation when paired with energy harvesters. However, most memristor-based networks rely on analog in-memory computing, necessitating a stable and precise power supply, which is incompatible with the inherently unstable and unreliable energy harvesters. In this work, we fabricated a robust binarized neural network comprising 32,768 memristors, powered by a miniature wide-bandgap solar cell optimized for edge applications. Our circuit employs a resilient digital near-memory computing approach, featuring complementarily programmed memristors and logic-in-sense-amplifier. This design eliminates the need for compensation or calibration, operating effectively under diverse conditions. Under high illumination, the circuit achieves inference performance comparable to that of a lab bench power supply. In low illumination scenarios, it remains functional with slightly reduced accuracy, seamlessly transitioning to an approximate computing mode. Through image classification neural network simulations, we demonstrate that misclassified images under low illumination are primarily difficult-to-classify cases. Our approach lays the groundwork for self-powered AI and the creation of intelligent sensors for various applications in health, safety, and environment monitoring.",
"introduction": "Introduction Artificial intelligence (AI) has found widespread use in various embedded applications such as patient monitoring, building, and industrial safety 1 . To ensure security and minimize energy consumption due to communication, it is preferable to process data at the edge in such systems 2 . However, deploying AI in extreme-edge environments poses a challenge due to its high power consumption, often requiring AI to be relegated to the “cloud” or the “fog” 3 , 4 . A promising solution to this problem is the use of memristor-based systems, which can drastically reduce the energy consumption of AI 5 , 6 , making it even conceivable to create self-powered edge AI systems that do not require batteries and can instead harvest energy from the environment. Additionally, memristors provide the advantage of being non-volatile memories, retaining stored information even if harvested energy is depleted. The most-energy efficient memristor-based AI circuits rely on analog-based in-memory computing: they exploit Ohm’s and Kirchhoff’s laws to perform the fundamental operation of neural networks, multiply-and-accumulate (MAC) 7 – 9 . This concept is challenging to realize in practice due to the high variability of memristors, the imperfections of analog CMOS circuits, and voltage drop effects. To overcome these challenges, integrated memristor-based AI systems employ complex peripheral circuits, which are tuned for a particular supply voltage 10 – 16 . This requirement for a stable supply voltage is in direct contrast with the properties of miniature energy harvesters such as tiny solar cells or thermoelectric generators, which provide fluctuating voltage and energy, creating a significant obstacle to realizing self-powered memristor-based AI 17 . In this work, we demonstrate a binarized neural network, fabricated in a hybrid CMOS/memristor process, and designed with an alternative approach that is particularly resilient to unreliable power supply. We demonstrate this robustness by powering our circuit with a miniature wide-bandgap solar cell, optimized for indoor applications. Remarkably, the circuit maintains functionality even under low illumination conditions equivalent to 0.08 suns, experiencing only a modest decline in neural network accuracy. When power availability is limited, our circuit seamlessly transitions from precise to approximate computing as it begins to encounter errors while reading difficult-to-read, imperfectly-programmed memristors. Our fully digital circuit, devoid of the need for any analog-to-digital conversion, incorporates four arrays of 8,192 memristors each. It employs a logic-in-sense-amplifier two-transistor/two-memristor strategy for optimal robustness, introducing a practical realization of the near-memory computing concept initially proposed in refs. 18 , 19 . The design is reminiscent of the smaller-scale memristor-based Bayesian machine recently showcased in ref. 20 , with the added novelty of logic-in-memory functionality. This feature is achieved by executing multiplication within a robust precharge differential sense amplifier, a circuit initially proposed in ref. 21 . Accumulation is then performed using a straightforward digital circuit situated near-memory. Our system also integrates on-chip a power management unit and a digital control unit, responsible for memristor programming and the execution of fully pipelined inference operations. We first introduce our integrated circuit and provide a comprehensive analysis of its electrical characteristics and performance across a variety of supply voltages and frequencies. We then characterize the behavior of the circuit under solar cell power, demonstrating its adaptability and resilience even when the power supply is significantly degraded due to low illumination. To further showcase the robustness of the circuit, we present results from neural network simulations using the popular MNIST and CIFAR-10 datasets. These results highlight the capability of the circuit to perform well even under extremely low illumination conditions.",
"discussion": "Discussion Our circuit exhibits an original behavior when solving tasks of varying difficulty levels. For simpler tasks such as MNIST, the circuit maintains accuracy even when energy is scarce. When addressing more complex tasks, the circuit becomes less accurate as energy availability decreases, but without failing completely. This self-adaptive approximate computing feature has several roots and can be understood by the circuit’s memory read operations. They are highly robust due to their differential nature: fluctuations of the power supply affect both branches of the sense amplifier equally. Still, when power voltage fluctuates or becomes low, some memory reads fail. Nevertheless, binarized neural networks are highly robust to weight errors, which in many cases do not change neuron activation 33 , 34 . Even in the worst case, weight errors cause some images to be misclassified, but these are typically atypical or edge cases. Therefore, when the power supply degrades, the AI naturally becomes less capable of recognizing harder-to-classify images. In this context of low-quality power supply, memristors offer distinct advantages over conventional static RAMs. While static RAMs lose stored information upon power loss, memristors retain data. Furthermore, when the supply voltage becomes low, static RAMs are prone to read disturb, meaning that a read operation can change the bit stored in a memory cell. In contrast, memristors exhibit near-immunity to read disturb effects, especially when read by precharge sense amplifiers 20 (we observed no read disturb in our experiments), and are non-volatile (ten-years retention has been demonstrated in hafnium-oxide memristors 35 ). After eliminating the energy used by the digital control circuitry (finite state machine), our circuit has an energy efficiency of 2.9 tera-operations per second and per watt (TOPS/W) under optimal conditions (10 MHz frequency, supply voltage of 0.7 volts). We have already mentioned that our circuit burns unnecessary energy due to its absence of clock gating, a choice made to ensure its functionality. By subtracting the energy consumption of clock distribution and neuron registers that can be eliminated through clock gating, and simultaneously optimizing the read operation (see Methods), energy efficiency increases to 22.5 TOPS/W. Due to the digital nature of our circuit, this number would scale favorably if a more current CMOS process was used. For example, employing the physical design kit of a fully-depleted silicon-on-insulator 28-nanometer CMOS process, we found that the energy efficiency of a clock-gated design would reach 397 TOPS/W (see Methods). Supplementary Note 5 compares these numbers and other properties of our digital system with fabricated emerging memory-based analog in-memory computing circuits. The most noteworthy comparison is with a recent study that presents an analog magnetoresistive memory (MRAM) based 64x64 binarized neural network fabricated in a 28-nanometer process 14 , which has a measured energy efficiency of 405 TOPS/W, which surpasses our projection slighly. However, this energy efficiency comes with the need for complex compensation and calibration circuits, matched to a stable power supply, which is not suitable with the unreliable power supply delivered by energy harvesters. Our integrated circuit embeds the necessary circuitry to handle single-layer computations. In a final commercially-oriented chip, data formatting processes, storage, and serial communication management would be integrated into a computing core. This core would include a working static RAM associated to manage the sending and receiving of activations, and reconfigurable on-chip communications, e.g., using a network on chip, capable of implementing fully-connected, convolutional, or recurrent neural networks. Multiple proposals of weight-stationary architectures in the literature could serve as inspiration 36 – 38 . Our circuit can function with power supplies as low as 0.7 volts, enabling us to power it with a wide-bandgap solar cell optimized for indoor applications, with an area of only a few square millimeters, even under low illumination equivalent to 0.08 suns. Such lightweight, ultrathin solar cells can also be transferred into a fully-integrated, self-powered device 39 , 40 . A more conventional alternative to our approach could be to insert a dedicated power management unit between the energy harvester and the AI circuit, which would allow using less robust design styles for it. However, such power management units come with a high area and complexity overhead and have some energy loss. Supplementary note 8 lists power management units that could be used and compares them with our approach. Supply voltages lower than 0.7 volts result in significant inaccuracies in memristor readings due to the high threshold voltages of the thick-oxide transistors in our process. Employing a process with a lower threshold voltage thick-oxide transistor option – such processes are widely available – could be a natural way to enable operation at lower supply voltages, broadening compatibility with various solar and non-solar energy harvesters. Some very low-voltage harvesters (e.g., thermoelectrics) may still require the voltage to be raised, which can be accomplished on-chip using switched capacitor circuits like Dickson charge pumps 41 . Self-powered AI at the edge, therefore, offers multiple opportunities to enable the development of intelligent sensors for health, safety, and environmental monitoring."
} | 2,773 |
39966475 | PMC11836362 | pmc | 2,169 | {
"abstract": "Vetiveria zizanioides , renowned for its robust stability and exceptional capacity to sequester heavy metals, has garnered widespread application in tailings ecological restoration efforts. Arbuscular mycorrhizal fungi (AMF), which are capable of forming symbiotic relationships with more than 80% of terrestrial plant roots, play a pivotal role in enhancing plant nutrient uptake and bolstering resilience. In this study, we conducted a comprehensive investigation into the physiological and biochemical responses of Vetiveria zizanioides subjected to varying levels of copper stress (with copper concentrations ranging from 0 mg/kg to 400 mg/kg), with or without AMF inoculation. Additionally, we performed nontargeted metabonomic analyses to gain deeper insights into the metabolic changes that occur in vetiver grass under AMF inoculation and copper stress. Our findings revealed that Vetiveria zizanioides inoculated with AMF consistently demonstrated superior growth performance across all copper stress levels compared with noninoculated counterparts. Using nontargeted metabonomic analyses, inoculation with AMF affects the metabolism of phenylalanine and related pathways in vetiver as well as contributing to the promotion of the formation of phytochelatins (PCs) from glutamate, thereby alleviating copper stress. The results highlight the potential of AMF-inoculated Vetiveria zizanioides as a promising bioremediation tool capable of effectively mitigating the adverse effects of heavy metal pollution.",
"conclusion": "Conclusions This comprehensive study investigated the impacts of AMF inoculation on the growth, physiological responses, and biochemical profiles of Vetiveria zizanioides under various levels of Cu stress. Additionally, we explored the molecular intricacies governing the enhanced copper tolerance of Vetiveria zizanioides via metabonomic analyses. Our findings indicate that vetiver grass inoculated with AMF has better growth performance than its noninoculated counterparts; AMF inoculation significantly broadens the tolerance range of vetiver grass to copper stress. AMF inoculation influences the metabolism of phenylalanine and related pathways in vetiver grass, leading to the synthesis of crucial secondary metabolites such as anthocyanins, lignin, rutin, and chlorogenic acid through a complex metabolic network centered on phenylalanine. These secondary metabolites bolster the resistance of vetiver grass to copper stress. Inoculation with AMF facilitates the increased formation of phytochelatins (PCs) from glutamate, thereby mitigating copper stress.",
"introduction": "Introduction Tailings are defined as the waste or nonvaluable byproduct generated during mining activities and the processing of minerals and other materials; they contain small amounts of residual valuable minerals, chemicals, water, and heavy metals 1 . According to a survey, the output of industrial solid waste in China exceeded 3 billion t/year in 2020, with an average annual growth rate of approximately 7% 2 . Tailings production accounts for approximately 80% of total industrial waste, and the total reserves exceed 60 billion tons 3 . Tailings contain a large number of metal elements, which can cause substantial harm to ecosystems and agricultural systems 4 , 5 . For example, excessive copper can inhibit plant growth, reduce photosynthesis by affecting photosystem II 6 , reduce root activity, and inhibit the absorption of other mineral elements, reducing yield 7 . Therefore, it is necessary to formulate a solution to solve this serious problem. Phytoremediation is a sustainable, cost-effective and environmentally friendly method 8 , 9 in which plants are used to remove metals and organic pollutants in soil 10 . Vetiveria zizanioides is a perennial herbaceous plant of the genus Vetiveria in the family Gramineae that has been widely used in the field of ecological restoration of tailings because of its remarkable characteristics, such as resistance to many kinds of heavy metals, strong root system, high biomass, and rapid growth rate 11 , 12 . However, plants growing in tailings are at risk of toxic stress and irreversible damage from heavy metals, which leads to low biomass, reducing remediation efficiency 13 . Therefore, effective techniques must be introduced to improve the efficiency of phytoremediation. Arbuscular mycorrhizal fungi (AMF) are plant-related microorganisms that establish a reciprocal relationship with 70–90% of land plant roots in various soils 14 , 15 . In addition to having great potential for alleviating heavy metals in plants, AMF are also affordable and eco-friendly bioremediation tools for soils polluted by heavy metals 16 . AMF can greatly improve the ability of plants to absorb nutrients through mycelial networks, thus directly and indirectly affecting plant physiological characteristics and improving plant growth 14 , 17 . AMF can not only improve the ability of plants to absorb mineral nutrients and trace metals but also affect the accumulation and transportation of metals in plants to reduce plant toxicity under heavy metal stress 18 , 19 . In recent years, many reports have shown that AMF improve heavy metal tolerance in plants 20 – 24 . However, the mechanism by which AMF inoculation improves the tolerance of Vetiveria zizanioides plants is still not clear. Therefore, this study aimed to explore the changes in the physiological, biochemical and metabolite contents of Vetiveria zizanioides with or without AMF inoculation under Cu stress. These results could help to address the following questions: (1) Does the tolerance range of Vetiveria zizanioides to Cu stress expand after inoculation with AMF? (2) What is the mechanism by which AMF enhance the Cu tolerance of Vetiveria zizanioides ? At the same time, this study will help deepen the understanding of the mechanism of plant stress resistance, promote the implementation of precision agriculture, enhance ecosystem services, and expand the application of biotechnology.",
"discussion": "Discussion Plant height and fresh weight serve as reliable indicators of a plant’s overall growth status and vitality. Our study consistently revealed that when Vetiveria zizanioides plants were inoculated with arbuscular mycorrhizal fungi (AMF), their plant height and fresh weight surpassed those of their uninoculated counterparts. This finding aligns with the research of Wang et al. 19 , who reported a significant increase in alfalfa biomass following AMF inoculation under heavy metal stress. Similarly, Yang et al. 38 reported that, under lead (Pb) stress, AMF-inoculated plants presented greater dry weights in their roots, stems, and leaves than nonmycorrhizal plants did, mirroring the results of our current study. These converging findings suggest that AMF inoculation not only promotes plant growth and development under heavy metal stress but also contributes to the development of metal tolerance, ultimately increasing plant biomass. This is further supported by the work of Riaz et al. 39 , who underscored the beneficial effects of AMF on plant resilience in contaminated environments. Roots, in addition to their vital function as the primary organ for absorbing water and minerals from the soil, are pivotal in perceiving and responding to external stimuli 40 , 41 . This sensory role underscores their crucial role in facilitating plant adaptation to adverse conditions. When confronted with environmental stressors, plants tend to evolve adaptive mechanisms, including the reconfiguration of their root system architecture, to accommodate variations in nutrient availability and effectiveness 42 . Our study revealed that as the copper concentration increased from 0 to 200 mg/kg, the total root length, root surface area, root volume, and total number of root tips in the plant root system notably increased. This observation aligns with the findings of Xiong et al. 43 , who reported that under environmental stress, larger and more intricate root systems develop, enhancing water and nutrient uptake capabilities and ultimately contributing to increased plant biomass and resilience. Thus, the observed increase in root complexity in our experiment could be a consequence of copper stress, further validating the adaptive potential of plant roots in response to adverse environmental conditions. The accumulation of Cu ions within plant root cells can significantly impact root development through multiple mechanisms. It can modulate the proliferation rate of cells in the meristematic tissues of the root, thereby altering root growth dynamics. Furthermore, it can regulate the levels of key phytohormones, such as indole-3-acetic acid (IAA, also known as auxin) and cytokinin (CTK), which play pivotal roles in regulating plant growth and development 44 , 45 . Interestingly, studies have shown that the inoculation of arbuscular mycorrhizal fungi (AMF) can influence the endogenous hormone levels in plants, thereby exerting a profound effect on root growth and development 46 , 47 . This finding is consistent with the outcomes of our study, in which AMF-inoculated plants presented greater total root length, total root surface area, total root volume, and total root tip number than their noninoculated counterparts did. Moreover, other studies have shown that AMF inoculation increases IAA levels, which in turn stimulates root growth 39 . This positive influence on IAA production underscores the symbiotic relationship between AMF and host plants, highlighting the potential of AMF as a tool to promote robust root systems and improve plant resilience under varying environmental conditions. Our study revealed a noteworthy phenomenon: the copper transfer coefficient of vetiver was greater at a copper concentration of 0 mg/kg, while the copper content of both the above- and below-ground parts of plants inoculated with AMF was significantly greater than that of uninoculated plants. This might be because plants require a certain amount of copper to maintain their vital life processes and to ensure that material cycling, energy flow and information transfer within the plant proceed smoothly 48 . AMF, known for their heavy metal chelating ability, can accumulate large amounts of copper ions in the soil. These copper ions are actively taken up by plant cells and bind to metallothionein or specific soluble copper ion chaperone proteins. They are subsequently transported to various organelles, including vesicles, chloroplasts and mitochondria 49 . However, under relatively high copper stress levels (200 mg/kg and 400 mg/kg), a significant decrease in copper enrichment occurred in the aboveground parts of vetiver inoculated with AMF compared with that in the noninoculated group. This phenomenon can be attributed to the robust heavy metal sequestration ability of AMF, which effectively bind heavy metal ions in the soil through both surface adsorption and the secretion of compounds such as globocystin-related protein (GRSP). GRSP, in particular, enhances the adsorptive capacity of soil particles for heavy metal ions, reducing the levels of metals in the bioavailable state and bioavailability. This, in turn, restricts the translocation of heavy metals from the soil to plants, resulting in a lower accumulation of heavy metals in aboveground plant tissues 50 – 52 . The accumulation of osmoregulatory substances, particularly carbohydrates, constitutes a pivotal mechanism in the plant arsenal against adverse stress 53 . Both soluble proteins and proline are important osmoregulators in plants 54 , and their accumulation is a defense response to abiotic stress 55 . Increasing the levels of osmoregulatory substances represents a strategic adaptation in plants to mitigate the adverse effects of stress. However, our current study reveals an intriguing deviation: inoculation with arbuscular mycorrhizal fungi (AMF) led to a reduction in soluble sugar content within plants. This phenomenon can be rationalized by considering two primary hypotheses. First, soluble sugars function as primary osmoregulators, bolstering the stability of plasma membranes and protoplasts while safeguarding enzymes against the detrimental effects of excess inorganic ions within plant cells 56 , 57 . In the AMF-treated group, the reduced transfer of Cu ions to the aerial portions of balsamgrass resulted in a reduction in osmotic potential difference. Conversely, the uninoculated vetiver grass presented relatively high Cu ion concentrations in its upper sections, triggering a robust self-preservation mechanism in which elevated soluble sugar levels reduce the osmotic potential and increase cellular water uptake or retention capabilities. Second, the symbiotic relationship between vetiver and AMF may involve the consumption of soluble nutrients by plants. This process, as suggested by Gadkar et al. 58 , could contribute to the observed decrease in soluble sugar content following AMF inoculation. In the present study, we observed a significant increase in the proline content of vetiver leaves subjected to copper stress at concentrations of 200 mg/kg and 400 mg/kg; the proline content was significantly greater in the AMF-inoculated group than in the non-AMF-inoculated group, highlighting the key role of proline as an important regulatory agent in plants for coping with abiotic stress challenges. Furthermore, the symbiotic relationship of the plant with AMF significantly increased the tolerance of vetiver to Cu, mainly through the promotion of proline synthesis, thereby increasing the ability of the plant to recover from unfavorable conditions 59 . Heavy metal toxicity leads to the accumulation of reactive oxygen species (ROS) in plants, which results in oxidative stress and damage to proteins, lipids and DNA 60 . Excess copper catalyzes the formation of reactive oxygen species (ROS) through the Haber-Weis and Fenton reactions 61 . However, plants have gradually evolved antioxidant defense systems to help mitigate the harmful effects of ROS 62 . Plants can activate their antioxidant defense system in response to heavy metal-induced ROS accumulation. This system includes enzymes that help remove and neutralize ROS, such as superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) 63 , 64 . SOD, POD, and CAT can maintain the dynamic balance of free radical production and removal in plants under normal conditions, thereby eliminating the potential damage caused by free radicals to the plant cell membrane structure 65 . By assessing the activities of these antioxidant enzymes, we gain insights into the toxic impact of heavy metals on plant cells. Our study demonstrated that arbuscular mycorrhizal fungi (AMF) inoculation enhances antioxidant enzyme activities in plants under copper stress. Specifically, under copper concentrations of 100 mg/kg, 200 mg/kg, and 400 mg/kg, AMF-treated comfrey plants presented increased antioxidant enzyme activities compared with uninoculated plants. This finding underscores the ability of AMF to bolster plant resilience against heavy metal stress by upregulating the antioxidant enzyme system, thereby improving overall plant tolerance and survival under adverse conditions. Malondialdehyde (MDA), a reliable indicator of membrane lipid peroxidation, is often directly correlated with the intensity of oxidative stress within plants 66 . An elevated MDA content in plants signifies an increased degree of cell membrane lipid peroxidation, which compromises membrane structural integrity, as emphasized by González-Guerrero et al. 67 . Our study reinforces the notion that AMF inoculation triggers a cascade of beneficial effects. Specifically, AMF inoculation activates a plant’s antioxidant enzyme system, effectively neutralizing the reactive oxygen species (ROS) generated under abiotic stress conditions. This, in turn, mitigates peroxidative damage to cell membranes, alleviates the deleterious effects of copper toxicity, and ultimately enhances plant resilience and adaptability to adverse environments. Numerous studies have convincingly demonstrated that inoculation with arbuscular mycorrhizal fungi (AMF) significantly enhances plant resilience against metal stress 16 , 68 – 70 . When confronted with stress, plants experience disruptions in their redox balance, and plants respond adeptly under the AMF‒plant symbiotic relationship by activating relevant genes 71 . Phenylalanine metabolism and associated pathways play pivotal roles in conferring stress tolerance to plants 72 . The intricate metabolic network centered on phenylalanine is involved in the synthesis of crucial secondary metabolites such as anthocyanins, lignins, rutin, and chlorogenic acid 73 . Anthocyanins, renowned for their potent antioxidant properties, not only increase the aesthetic appeal of fruits but also safeguard plants against UV radiation, pests, and diseases 74 . Moreover, lignin content is intimately tied to plant biomass accumulation, underscoring its importance in plant growth and development 75 . Crucially, the biosynthesis of L-phenylalanine (L-Phe), the cornerstone of this metabolic pathway, requires two compounds, phosphoenolpyruvate (PEP) and erythrose 4-phosphate (E4P) 76 . This finding underscores the importance of D-erythrose 4-phosphate as an indispensable precursor for L-Phe production, thereby linking it to the entire network of stress-responsive metabolites in plants. Furthermore, AMF inoculation effectively mitigates the deleterious effects of copper on plants, thereby contributing to an increase in photosynthetic efficiency. In the photosynthetic apparatus, light energy is harnessed within leaf cells and stored in the form of nicotinamide adenine dinucleotide phosphate (NADPH). This energy is subsequently transformed into intermediates such as D-erythritol-4-phosphate and glyceraldehyde-3-phosphate, which are integral to various physiological processes, including glycolysis and amino acid synthesis, within plant cells. These metabolic intermediates, in turn, impact the hormonal balance in plants 77 , ultimately orchestrating the stress response mechanisms of plants at the macroscopic level. Our study revealed a decrease in D-erythrose 4-phosphate under copper stress, suggesting that AMF inoculation influences the L-phenylalanine (L-Phe) synthesis pathway as a strategic means to combat this stress. This adaptive response underscores the intricate interplay between AMF, plant metabolism, and stress tolerance mechanisms. Chlorogenic acid is a pivotal antioxidant in plants and is classified as a carboxyl phenolic acid that arises from the condensation of quinic acid and caffeic acid within the trans-cinnamic acid framework 78 , 79 . Both quinic acid and chlorogenic acid occupy central stages in the phenylpropanoid metabolic pathway, serving as key intermediates 80 . These compounds can inhibit the lipid peroxidation resulting from metal stress, thereby safeguarding cellular integrity 81 . Oksana et al. 82 demonstrated the antioxidant properties of chlorogenic acid, revealing its capacity to shield plants from oxidative damage caused by environmental stressors. In line with this, studies have reported a substantial increase in chlorogenic acid concentrations and a concomitant increase in antioxidant defenses in plants subjected to salt stress, suggesting a potential interplay between these variables 83 , 84 . The inoculation of arbuscular mycorrhizal fungi (AMF) in Vetiveria zizanioides plants under copper (Cu) stress significantly increased the accumulation of quinic acid. This, in turn, promoted the production of additional chlorogenic acid, which acts as a robust defense agent against Cu stress, highlighting the symbiotic benefits of AMF in bolstering plant resilience. The results of this study indicate that inoculation with AMF under Cu stress leads to the formation of more phytochelatins (PCs) from glutamate. PCs are small cysteine-rich peptides that are able to bind metals (classes) through the -SH motif. Although the biosynthesis of PCs can be induced in vivo by a variety of metals (classes), PCs are involved mainly in the detoxification of cadmium and arsenic(III) as well as mercury, zinc, lead, and copper ions and are key components of plant defense against heavy metal stress 85 . In response to external heavy metal stress, peptides bind to heavy metals via sulfhydryl groups, forming low-molecular-weight complexes, which are sequestered in vesicles. In the vesicles, the PCN molecules further conjugate with other PCN molecules to effectively reduce the biological activity of the metal ions and produce high-molecular-weight compounds with minimal toxicity to plant cells, thus mitigating the damage caused by excess copper to plants 86 (Fig. 10 ). \n Fig. 10 Stress resistance mechanism diagram of vetiver grass inoculated with AMF under copper stress. \n In this study, the metabolite changes of AMF inoculation on the stems and leaves of Vetiver under CU stress were studied from non-targeted metabolomics, but in order to further investigate the reasons, it is necessary to analyze the multi-omics such as genomics, transcriptomics and proteomics to form a more complete life activity process."
} | 5,306 |
33205020 | PMC7649285 | pmc | 2,171 | {
"abstract": "Summary Biofilms are the habitat of 95% of bacteria successfully protecting bacteria from many antibiotics. However, inhibiting biofilm formation is difficult in that it is a complex system involving the physical and chemical interaction of both substrate and bacteria. Focusing on the substrate surface and potential interactions with bacteria, we examined both physical and chemical properties of substrates coated with a series of phenyl acrylate monomer derivatives. Atomic force microscopy (AFM) showed smooth surfaces often approximating surgical grade steel. Induced biofilm growth of five separate bacteria on copolymer samples comprising varying concentrations of phenyl acrylate monomer derivatives evidenced differing degrees of biofilm resistance via optical microscopy. Using goniometric surface analyses, the van Oss-Chaudhury-Good equation was solved linear algebraically to determine the surface energy profile of each polymerized phenyl acrylate monomer derivative, two bacteria, and collagen. Based on the microscopy and surface energy profiles, a thermodynamic explanation for biofilm resistance is posited.",
"conclusion": "Conclusions Seven monomers (i.e., phenyl acrylate and halogenated derivatives thereof) were successfully synthesized through a standard laboratory synthesis. Each monomer was added at variable concentrations (e.g., 5, 10, 15, and 20 weight percent) to a compatible industrial formulation that was subsequently UV cured onto various substrates. Examination via AFM illustrated that several of the cured coating formulations, including those of 3e and 3f , yielded exceptionally smooth coatings with limited surface areas evidenced by average peak to valley heights ( R z ) less than 1.0 μm and very low roughness ( R a ) measurements. 3f exhibited an inverse relationship of both R z and R a as concentration increased. The coatings were then analyzed for single (e.g., E. coli , P. aeruginosa , S. aureus , S. pneumoniae , and S. typhimurium ) and multiple (e.g., clarified raw sewage) species biofilm resistance. After normalizing the biofilm resistance studies, coatings incorporating the brominated phenyl acrylate monomers (e.g., 3e and 3f ), the monochlorinated 3c , and the monoiodinated 3g exhibited significant biofilm resistance. Because biofilm resistance is a symbiotic, multi-determinant system involving the physical and chemical interaction of both substrate and bacteria, we also examined the surface energies of the polymerized phenyl acrylate derivatives, collagen, and two representative bacteria (e.g., P. aeruginosa and S. aureus ). Comparative analysis of each surface energy component demonstrated that the polar component ( γ s A B ) is likely the primary thermodynamic contributor to the observed biofilm resistance. Small polar components of the substrate reduce the adhesiveness of bacteria to the substrate, whereas a large base component ( γ s − ) repels the bacterium. Repulsive intermolecular interactions between base components of both the substrate and bacteria prevent intimate bacterial association with the substrate. Secondarily, we posit that the presence of soft atoms (e.g., bromine and iodine) and/or polarizable moieties in the coating may allow bacterial association while inhibiting adhesion and biofilm formation during primary colonization.",
"introduction": "Introduction Biofilms allow the vast majority of microorganisms—infectious or otherwise—to persist in our world of antibiotics and antivirals. Biofilms are a complex, communicative aggregation of microorganisms in which 99% of all microorganisms persist ( Flemming, 2002 ). Because of the ubiquitous nature of biofilms, their influence is similarly widespread—from biofouling of naval vessels, drinking and wastewater treatment facilities, medical implants and inserts to persistent pathogenic pathways in health care including nosocomial infections ( Abbott et al., 2000 ; Cavitt and Faulkner, 2015 , 2017 ; Cleaveland, 2005 ; Cooney and Tang, 1999 ; Flemming, 2002 ; Iwamoto and Matsutomo, 2018 ; Kenawy et al., 2007 ; Monroe, 2007 ; Montanaro et al., 2007 ; O'Flaherty et al., 2004 ; Vertes et al., 2012 ). Likewise, biofilms are non-trivial in remediation methods and often require multiple modalities to simply reduce and impede biofilm growth. With the inherent difficulty of biofilm remediation, research is moving toward inhibiting biofilm growth and/or formation. Developing methods to inhibit biofilm growth and/or formation requires an intimate knowledge of the growth mechanism, which is parsed into five distinct categories: (1) primary colonization with reversible attachment, (2) aggregation and irreversible attachment, (3) growth and division, (4) maturation, and (5) dispersion ( Monroe, 2007 ; Vertes et al., 2012 ). The most logical moment to disrupt biofilm formation is primary colonization in which microorganisms initially contact and reversibly adhere to a substrate's surface. Primary colonization is a multi-determinant system based on the thermodynamic (i.e., static) and kinetic (i.e., dynamic) nature of both microorganism and substrate. One commonly investigated kinetic determinant involves the concentration dependence of biofilm inhibition. At a critical concentration (i.e., minimum inhibitory concentration [MIC]), biofilm growth is inhibited without introducing a cidal mechanism. The MIC likely addresses the kinetic effect based on the reversible attachment at primary colonization. At larger critical concentrations (i.e., minimum biocidal concentration [MBC]), a thermodynamic, cidal effect introduces disruptors to basic cellular function and, over time, shifts the microbial equilibrium away from homeostasis. Most commonly, biofilm inhibitory concentrations are in excess of the MBC with the thought that both kinetic and thermodynamic effects would be simultaneously addressed. As a motile species, Pseudomonas aeruginosa is likely most affected by the MIC-related kinetic effect, whereas the non-motile Staphylococcus aureus would be more affected by the MBC-related thermodynamic effect. Introducing antimicrobial components to the substrate is a very common method to inhibit biofilm formation; however, such focuses on the previously described concentration determinant. Substrates are often functionalized with quaternary ammonium compounds (e.g., polymeric, polymer-grafted) in excess of MBC that penetrate the cell wall causing leakage and subsequent apoptosis ( Kandiyote et al., 2019 ; Namivandi-Zangeneh et al., 2020 ; Valáriková et al., 2020 ). Upon apoptosis and in the absence of interfacial shear flow, the apoptotic fluids often remain associated with the substrate surface dynamically altering the nature of the substrate by concealing the quaternary ammonium under cellular debris. Furthermore, upon cell death, subsequent activation of lysosomes, and release of proteases, putrefaction of cellular proteins will produce free amines that neutralize protonated quaternary ammonium salts used in some of the aforementioned examples. The use of phenolic compounds to denature proteins necessary for cellular function are also common; unfortunately, like protonated quaternary ammonium compounds, the phenolic compounds are biocidal for a time until cellular debris and/or neutralization by free amines render them inert pending surface treatment ( Li et al., 2020 ; Namivandi-Zangeneh et al., 2020 ). Other more robust compounds are also used to disrupt biofilm growth such as sugar alcohols to prevent dental caries and substituted (e.g., fluoro, chloro, nitro, cyano) aryl hydrazones ( Kõljalg et al., 2020 ; Lu et al., 2020 ). Using metals associated with the substrate to disrupt cellular function is also a common method of biofilm inhibition. Nanoparticles (e.g., silver) are of peculiar interest for thermodynamically mediated biofilm inhibition and have enhanced efficacy when employed with a secondary antimicrobial component ( Moola et al., 2019 ; Namasivayam et al., 2019 ). However, nanoparticles often cannot endure rigorous surface treatments to recondition surfaces after eventual biofilm formation and/or fouling. Metal salts (e.g., Ce(IV)) have been shown to disrupt saccharide-dependent biofilm formation during the kinetically controlled reversible adhesion of primary colonization ( Bhatt et al., 2020 ). However, metal salts often do not persist long term in aqueous environments thereby rendering them inactive. Because of (1) significant genetic differentiation between microorganisms and (2) the colloidal nature of microorganisms, even adhesion is a complex process that is phenotypically heterogeneous and not a single determinant process ( Vissers et al., 2019 ). For example, the surface protein SdrC of S. aureus has been shown to use Ca 2+ -mediated chelation of the N2 domains as a primary contributor to biofilm formation; the use of a metal salt associated with the substrate may disrupt the aforementioned chelation illustrating how metal salts effectively inhibit biofilm formation ( Pi et al., 2020 ). To further illustrate the diversity in the adhesion process, McLay et al. were able to genetically alter Escherichia coli to demonstrate that the amount of fimbriation contributes to adhesion of the bacterium ( McLay et al., 2018 ). The concentration dependence of adhesion is probably a kinetic effect unique to each bacterium. In a paper examining P. aeruginosa and its interfacial behavior, Deng et al. noted that most bacteria align parallel to the oil-water interface ( Deng et al., 2020 ). The parallel alignment is likely thermodynamically driven, whereas non-parallel alignment is kinetically controlled. The kinetic (i.e., dynamic) component has been modeled using complex algorithms and applied theories to describe bacterial attachment ( Conrad and Poling-Skutvik, 2018 ; McLay et al., 2018 ; Vissers et al., 2019 ). In this paper, we primarily focus on the thermodynamic components that drive the interfacial interaction of substrates with microbes present in primary colonization. Our fundamental assumption throughout our biological experimentation is that biofilm growth cannot occur without primary colonization. Although we are not explicitly studying primary colonization, we are examining the results of microbial colonization that are possible only if primary colonization occurs via a significant substrate-bacteria interfacial interaction, an interaction that is limited in the latter stages of biofilm growth. Therefore, seven phenyl acrylate monomers, including six halogenated monomers, were synthesized and characterized. The substrate was coated with a formulation that included 5–20 weight percent of a phenyl acrylate derivative and subsequently polymerized. Using atomic force microscopy (AFM), the surface smoothness was determined for representative samples and compared with surgical grade steel. Induced single species biofilm growth and separate exposure to clarified sewage provided biological evidence of biofilm inhibition relative to each of the seven phenyl acrylate derivatives at varying concentrations. After solving the van Oss-Chaudhury-Good equation via a linear algebraic method for relevant samples, surface energy analyses and comparison of each polymerized phenyl acrylate derivative to collagen and two representative bacteria (e.g., P. aeruginosa and S. aureus ) inform potential thermodynamic efficacy. Thereafter, a thermodynamic explanation for the observed behavior was posited based on the evidence gathered.",
"discussion": "Results and Discussion Development of Potential Biofilm-Resistant Polymer Materials Given evidence that covalently bound halogenated moieties have demonstrated efficacy for biofilm resistance, we designed a series of monomers based on phenyl acrylate (an internal control) that are likely biofilm-resistant candidates ( Pickens, 2009 ). Table 1 details the reaction scheme and phenyl acrylate derivatives synthesized (see Transparent Methods ). Impurities in acryloyl chloride ( 1 ), technical grade (70% purity), contributed in part to the low to moderate average isolated yields ( Cavitt and Faulkner, 2015 , 2017 ). Table 1 Employing Different Phenols Entry R 1 /R 2 /R 3 (2) 3 Yield (%) a 1 H/H/H( 2a ) 3a 59 2 H/Cl/H( 2b ) 3b 33 3 H/H/Cl( 2c ) 3c 36 4 Cl/H/Cl( 2d ) 3d 30. 5 H/H/Br( 2e ) 3e 21 6 Br/H/Br( 2f ) 3f 39 7 H/H/I( 2g ) 3g <10 Reaction conditions: 1 (55 mmol), 2 (50. mmol), Et 3 N (55 mmol) in CH 2 Cl 2 (40 mL) at room temperature and under dry nitrogen atmosphere for 24 h with spectroscopic and physical characterization provided in Data S1 and S2 . See also Figure S9 . a Yields refer to average isolated yields. Monomers were shown to be stable upon exposure to broad spectrum UV radiation indicating that the aryl–halogen bonds persist upon irradiation thereto. Photo-differential scanning calorimetry (photo-DSC) was used to confirm that the aryl-halogen bond does not undergo homolytic cleavage to initiate polymerization at 10 weight percent of each monomer as compared with 1,6-hexanediol diacrylate. The aforementioned stability allowed for UV curing of the monomer to form both homo- and copolymeric coatings on several substrates (e.g., stainless steel, glass slides, and plastic slides) for subsequent analyses. The monomers were incorporated at 5, 10, 15, and 20 weight percent into a standard copolymer formulation. Each liquid coating was manually drawn down to a wet thickness of 100 μm and polymerized thereafter. Samples of the cured 20% monomer formulation were examined for methanol extractable monomer content using gas chromatographic (GC)-mass spectrometry (MS). No detectable monomer was observed in any of the samples to a detection limit of 100 μg/mL. Atomic Force Microscopy The average plate roughness ( R a ) and average peak-valley height ( R z ) was determined via AFM, contact scanning mode. The two controls included the uncoated stainless steel and cured acrylic formulation with no additional phenyl acrylate derivative; both yielded R z values of 0.819 μ m. The R a and R z were determined for each formulation at varying concentrations of representative monomers ( 3a , 3b , 3d , 3e , and 3f ). With the exception of 3a , the smoothness as determined by the R a and R z generally increases as the concentration of the monomer increases owing to the increased dipole-dipole interactions of the coating ( Table 2 ). Table 2 Surface Roughness Measured via AFM Monomer 5 wt % 5 wt % 10 wt % 10 wt % 15 wt % 15 wt % 20 wt % 20 wt % R z ( μ m) R a ( μ m) R z ( μ m) R a ( μ m) R z ( μ m) R a ( μ m) R z ( μ m) R a ( μ m) 3a 0.7185 0.1532 2.5917 0.1562 4.4568 0.1575 5.1233 0.1567 3b 2.265 0.1575 1.6857 0.1383 1.1517 0.107 0.8888 0.1077 3d 1.1553 0.1098 1.2905 0.1122 0.7758 0.1072 0.6703 0.105 3e 0.785 0.1532 1.3348 0.1552 0.819 0.1548 1.5117 0.1548 3f 1.4265 0.155 1.192 0.1545 0.7897 0.1537 0.7102 0.1528 Based on cantilever deflection values measured during the contact scanning mode. R z is the average peak-valley height of the cured coating. Values meeting minimum surgical grade steel requisites are italicized. R a is the average surface roughness of the cured coating. See also Figure S1 . Comparing R z of the cured coating formulations to the peak-valley requisite for surgical grade steel ( R z ≤ 1 μm, 320 grit, electropolished), several of the cured coating formulations were well within the requisite value for surgical grade steel with 3a as a notable exception, providing evidence of smoothness capable of inhibiting many types of microbial growth by reducing the available surface area for attachment ( Gillis and Gillis, 1996 ; Mei et al., 2011 ). Biofilm Resistance Studies Each bacterium (e.g., E. coli , P. aeruginosa , S. aureus , Streptococcus pneumoniae , and Salmonella typhimurium ) was specifically chosen for its contribution to common infectious pathways including, but not limited to, food poisoning and life-threatening and/or nosocomial infections. Having no halogenation, 3a was utilized as an internal standard having no inherent biofilm-resistant structural component. For reference, we also compared the standard control coating (no compound 3 ) to the uncoated portion of the slide. The motile bacteria examined (e.g., E. coli ., P. aeruginosa , and S. typhimurium ) had nominal or increased biofilm development on the control coating, whereas the non-motile cocci had nominal or decreased biofilm development on the control coating relative to the uncoated portion of the slide. As exhibited via the aforementioned variable biofilm development, the control coating likely has limited biofilm inhibitory effect. Overall (see Figures S2–S7 ), biofilm formation was observed on the uncoated portions and the levels of growth clearly fall over a wide spectrum. As a non-halogenated internal standard, 3a did not exhibit any biofilm resistance. The monohalogenated derivatives (e.g., 3b , 3c , 3e , and 3g ) showed some limited biofilm resistance especially at higher concentrations with 3e resisting biofilm formation best. Dihalogenated monomers ( 3d and 3f ) seemed to impede biofilm formation better than their monohalogenated counterparts. Comparing chlorinated, brominated, and iodinated derivatives, the brominated monomers were the most effective biofilm-resistant monomers. Brominated coatings tended to perform better than chlorinated coatings with 40% of the brominated coatings passing our qualitative examination and 14% failing. Chlorinated coatings had a 15% pass rate with a 44% failure rate. Laboratory conditions using lab-grown bacteria, which may have reduced immune functionality from multi-generational reproduction, may not provide an adequate environment for evaluating biofilm resistance. Therefore, we evaluated the coatings' biofilm resistance when exposed to 3.5 million gallons of raw clarified sewage for 2 days at the Abilene (Texas) Wastewater Reclamation Plant (see Figure S8 ). After preparing and evaluating the slides as before, the varying compositions' ( 3a-g ) biofilm resistance produced comparatively consistent results to the previous bacterial studies (see Figure S8 ). Interestingly, visible algae growth was restricted solely to the BRApp (and not the slides) thereby indicating cursory resistance to algae growth. To evaluate the monomers and concentrations for optimal biofilm resistance, all biofilm resistance data (single and multiple species biofilm resistance studies) were aggregated and normalized relative to the equivalent of no biofilm resistance differential between uncoated control and coating ( Figure 1 ). Figure 1 Normalized Quantitative Evaluation of Multiple Species Biofilm Resistance Species evaluated include E. coli , P. aeruginosa , S. aureus , S. pneumoniae , and S. typhimurium . Normalized relative to biofilm growth on control coating. Reduced biofilm resistance relative to the control is negative. Increased biofilm resistance relative to the control is positive. See also Figures S2–S7 . In order to determine the most biofilm-resistant monomers, the normalized quantitative data seem to indicate that biofilm resistance is directly related to concentration of the monomers with the exception of the internal, non-halogenated control ( 3a ). The normalized data demonstrate that 3b is not biofilm resistant at the incorporated amounts in the coating. 3d was more efficacious at lower concentrations indicating that the biostatic effect inherent to a MIC may be an important effect of biofilm resistance of this monomer. 3e also exhibited a biostatic effect overall at low concentration; however, biofilm resistance generally increased with concentration. Both 3f and 3g were the most consistently biofilm resistant with increasing efficacy up to 15 weight percent. Furthermore, halogenation at the para -position seems to produce a stereotypic effect for enhanced biofilm resistance. Finally, the presence of softer halogens (e.g., bromine and iodine) on the monomers seems to result in increased biofilm resistance. Surface Energy Analyses Surface energy analyses may be accomplished via many methods; however, we chose a goniometric method for its simplicity and affordability. Using three fully characterized liquids to obtain statistical contact angle averages, the van Oss-Chaudhury-Good Equation 1 was solved linear algebraically for the following surface energy components: nonpolar ( γ s LW ), acid ( γ s + ), and base ( γ s − ) components ( van Oss et al., 1987 ). (Equation 1) ( 1 + cos θ s l ) γ l t o t = 2 ( γ s L W γ l L W + γ s + γ l − + γ s − γ l + ) The polar component ( γ s AB ) and overall surface energy ( γ s ) was then calculated via Equations 2 and 3 , respectively ( van Oss et al., 1988 ). (Equation 2) γ A B = 2 γ + γ − (Equation 3) γ t o t = γ L W + γ A B Table 3 tabulates the surface energy profiles for each polymerized phenyl acrylate derivative ( 3a-g , see Data S3 for homopolymer characterization). Table 3 Surface Energy Profile of Derivatized Phenyl Acrylate Polymers Substrate γ s γ s LW γ s AB γ s + γ s − 3a 35.14 ± 1.40 29.13 ± 1.20 6.01 ± 0.80 1.93 ± 0.50 6.51 ± 1.46 3b a 41.44 ± 1.11 36.41 ± 0.70 5.04 ± 1.57 0.198 ± 0.077 51.39 ± 1.11 3c 28.46 ± 0.67 25.64 ± 0.67 2.83 ± 0.60 2.73 ± 0.61 1.31 ± 0.43 3d 39.08 ± 2.44 29.62 ± 0.63 9.46 ± 2.14 0.736 ± 0.230 32.47 ± 4.41 3e 29.91 ± 0.70 24.41 ± 0.46 5.50 ± 0.27 0.745 ± 0.043 10.22 ± 0.61 3f 36.06 ± 1.62 26.94 ± 0.56 9.12 ± 1.50 4.26 ± 0.91 9.70 ± 2.05 3g 34.48 ± 0.43 33.15 ± 0.39 1.33 ± 0.28 1.15 ± 0.24 0.485 ± 0.130 All units are mJ/m 2 ± SEM where number of samples ( N ) is 36 ( 3a ), 24 ( 3b ), 18 ( 3c ), 18 ( 3d ), 24 ( 3e ), 36 ( 3f ), and 18 ( 3g ). See Transparent Methods . Calculations based on contact angles from bromonaphthalene, formamide, and water. a Obtaining a smooth coating without smearing or orange peeling was difficult and may have contributed to an anomalous/inaccurate surface energy profile; however, for completeness, the surface energy profile for 3b was included in the dataset. In order to compare the surface energy profiles of the polymerized phenyl acrylate derivatives ( 3a-g ), the surface energy profile was similarly obtained for collagen (insoluble and soluble), S. aureus , and P. aeruginosa ( Table 4 ). Table 4 Surface Energy Profile of Various Biologic Materials Substrate γ s γ s LW γ s AB γ s + γ s − Collagen, insoluble a 45.75 ± 0.83 40.08 ± 0.46 5.67 ± 0.75 1.51 ± 0.39 6.90 ± 1.52 Collagen, soluble b 37.08 ± 2.15 30.13 ± 1.22 6.95 ± 1.70 0.806 ± 0.26 16.08 ± 3.99 S. aureus c 43.91 ± 0.50 39.63 ± 0.37 4.29 ± 0.49 0.066 ± 0.014 73.54 ± 0.69 P. aeruginosa c 39.26 ± 0.77 34.82 ± 0.46 4.44 ± 0.78 0.089 ± 0.029 69.07 ± 1.99 All units are mJ/m 2 ± SEM where number of samples ( N ) is 18 (collagen, insoluble), 36 (collagen, soluble), 21 ( S. aureus ), and 18 ( P. aeruginosa ). See Transparent Methods . a Calculations based on contact angles from bromonaphthalene, formamide, and water for insoluble collagen (100 μg/mL). b Calculations based on contact angles from bromonaphthalene, formamide, and water for soluble collagen (100 μg/mL) in phosphate buffer solution (1x, pH = 7.4). c Calculations based on contact angles from bromonaphthalene, dimethylsulfoxide, and water. The surface energy component values for soluble collagen (e.g., γ s L W , γ s A B , and γ s ) were slightly higher than established literature values with additional values for the acid ( γ s + ) and base ( γ s − ) components ( Lewandowska et al., 2016 ; Skopińska-Wiśniewska et al., 2009 ). Insoluble collagen is noticeably differentiated from the soluble collagen per the base ( γ s − ) components illustrating an increased substrate dipole for the soluble collagen. Often a quick comparison of the overall surface energy ( γ s ) of two interacting materials has been used to establish a degree of interfacial interaction between two materials. Based on the previous literature relating compositional variations to contact angles, the surface energy values for phenyl acrylate homopolymers could be inferred to impact the surface chemistry of copolymer formulations ( Cassie, 1948 ; Drelich et al., 1996 ). In order to directly compare the surface energies of the phenyl acrylic coatings with collagen and select bacteria, the overall surface energy ( γ s ) of each was plotted; however, no clear trend is apparent ( Figure 2 ). Figure 2 Overall Surface Energy Comparison ( γ s ) of Phenyl Acrylic Coatings, Collagens, and Bacteria All units are mJ/m 2 ± SEM where number of samples ( N ) is 36 ( 3a ), 24 ( 3b ), 18 ( 3c ), 18 ( 3d ), 24 ( 3e ), 36 ( 3f ), 18 ( 3g ), 18 (collagen, insoluble), 36 (collagen, soluble), 21 ( S. aureus ), and 18 ( P. aeruginosa ). See Transparent Methods . a Calculations based on contact angles from bromonaphthalene, formamide, and water for insoluble collagen (100 μg/mL). b Calculations based on contact angles from bromonaphthalene, formamide, and water for soluble collagen (100 μg/mL) in phosphate buffer solution (1x, pH = 7.4). c Calculations based on contact angles from bromonaphthalene, dimethylsulfoxide, and water. d Obtaining a smooth coating without smearing or orange peeling was difficult and may have contributed to an anomalous/inaccurate surface energy profile; however, for completeness, the surface energy profile for 3b was included in the dataset. Therefore, each individual component was examined for all phenyl acrylate monomer derivatives, collagens, and bacteria. The most interesting individual component comparisons involved the polar ( γ s A B ) and base components ( γ s − ) plotted in Figures 3 and 4 , respectively. Figure 3 Surface Energy Polar Component ( γ s AB ) Comparison of Phenyl Acrylic Coatings, Collagens, and Bacteria All units are mJ/m 2 ± SEM where number of samples ( N ) is 36 ( 3a ), 24 ( 3b ), 18 ( 3c ), 18 ( 3d ), 24 ( 3e ), 36 ( 3f ), 18 ( 3g ), 18 (collagen, insoluble), 36 (collagen, soluble), 21 ( S. aureus ), and 18 ( P. aeruginosa ). See Transparent Methods . a Calculations based on contact angles from bromonaphthalene, formamide, and water for insoluble collagen (100 μg/mL). b Calculations based on contact angles from bromonaphthalene, formamide, and water for soluble collagen (100 μg/mL) in phosphate buffer solution (1x, pH = 7.4). c Calculations based on contact angles from bromonaphthalene, dimethylsulfoxide, and water. d Obtaining a smooth coating without smearing or orange peeling was difficult and may have contributed to an anomalous/inaccurate surface energy profile; however, for completeness, the surface energy profile for 3b was included in the dataset. Figure 4 Surface Energy Base Component ( γ s − ) Comparison of Phenyl Acrylic Coatings, Collagens, and Bacteria All units are mJ/m 2 ± SEM where number of samples ( N ) is 36 ( 3a ), 24 ( 3b ), 18 ( 3c ), 18 ( 3d ), 24 ( 3e ), 36 ( 3f ), 18 ( 3g ), 18 (collagen, insoluble), 36 (collagen, soluble), 21 ( S. aureus ), and 18 ( P. aeruginosa ). See Transparent Methods . a Calculations based on contact angles from bromonaphthalene, formamide, and water for insoluble collagen (100 μg/mL). b Calculations based on contact angles from bromonaphthalene, formamide, and water for soluble collagen (100 μg/mL) in phosphate buffer solution (1x, pH = 7.4). c Calculations based on contact angles from bromonaphthalene, dimethylsulfoxide, and water. d Obtaining a smooth coating without smearing or orange peeling was difficult and may have contributed to an anomalous/inaccurate surface energy profile; however, for completeness, the surface energy profile for 3b was included in the dataset. Excepting 3a (internal control) and 3b (inaccurate profile), the substrates with the most similar γ s A B include 3d , 3e , 3f , insoluble collagen, P. aeruginosa , and S. aureus . Focusing on the 3d , 3e , 3f , and bacteria, the similarities in the polar component ( γ s A B ) likely indicates a more significant thermodynamic interaction. The single species biofilm resistance studies seem to qualitatively support a more significant interaction between 3d , 3e , 3f , and bacteria. The low γ s A B values for both 3c and 3g likely result in reduced polar interactions explaining the observed biofilm resistance. Because the magnitude of the acid components ( γ s + ) is comparatively small for most monomers, the base components ( γ s − ) shown in Figure 4 should be the most significant interaction. 3d is qualitatively less efficacious as a biofilm-resistant substrate perhaps owing to the larger nonpolar component, which may obfuscate the relatively hard (i.e., charge dense) chlorine atoms, especially when bound in an amorphous, cross-linked polymer matrix with little polar directionality. Furthermore, biofilm formation also seems to be more significantly inhibited by the softer halogens (e.g., bromine and iodine). Based on Figures 1 , 3c , 3e , 3f , and 3g were clearly the most biofilm-resistant substrates examined in this study with limited efficacy of 3d . Based on Figure 3 , biofilm resistance of 3c and 3g have reduced polar components ( γ s A B ) and thus limited polar interactions with bacteria and adhesins. Figure 4 shows 3d , 3e , and 3f having appreciable base components ( γ s − ). A significant intermolecular (base-base) repulsion may be a causative agent of biofilm resistance for monomers with significantly large base components ( γ s − ). S. aureus , a non-motile bacterium, was most affected by 3c and 3g , whereas both 3e and 3f equally inhibited biofilm formation of the motile P. aeruginosa . With surface interactions being diffusion controlled, S. aureus adhesion is thermodynamically controlled. The parallel movement of P. aeruginosa along a surface interface would contribute a competing kinetic effect to the thermodynamic driving force for surface adhesion. Owing to kinetic competition, the biofilm resistance of 3e and 3f is slightly diminished for P. aeruginosa relative to S. aureus as observed. The increased thermodynamic biofilm resistance may be 2-fold. First, as previously stated, polar interactions of the bacterium with the monomers contribute significantly to adhesion thereto. Diminished polar surface energy components of the substrate reduce the adhesive propensity for bacteria to bind to a substrate. Conversely, interacting base components ( γ s − ) of a stationary substrate with a diffusing bacterium would have an increasing intermolecular charge repulsion as the distance between substrate and bacterium decreases. Such would especially be present in the non-chelated N2 domain of the surface protein SdrC of S. aureus ( Pi et al., 2020 ). Second and likely to a lesser degree, a polarizable soft atom (e.g., bromine or iodine) or other polarizable moiety could allow the bacterium to remain associated with the substrate in the absence of reversible adhesion during primary colonization. The latter reasoning is used to explain, in part, limited bacterial attachment onto superhydrophilic substrates ( Noorisafa et al., 2016 ; Yuan et al., 2017 ). Conclusions Seven monomers (i.e., phenyl acrylate and halogenated derivatives thereof) were successfully synthesized through a standard laboratory synthesis. Each monomer was added at variable concentrations (e.g., 5, 10, 15, and 20 weight percent) to a compatible industrial formulation that was subsequently UV cured onto various substrates. Examination via AFM illustrated that several of the cured coating formulations, including those of 3e and 3f , yielded exceptionally smooth coatings with limited surface areas evidenced by average peak to valley heights ( R z ) less than 1.0 μm and very low roughness ( R a ) measurements. 3f exhibited an inverse relationship of both R z and R a as concentration increased. The coatings were then analyzed for single (e.g., E. coli , P. aeruginosa , S. aureus , S. pneumoniae , and S. typhimurium ) and multiple (e.g., clarified raw sewage) species biofilm resistance. After normalizing the biofilm resistance studies, coatings incorporating the brominated phenyl acrylate monomers (e.g., 3e and 3f ), the monochlorinated 3c , and the monoiodinated 3g exhibited significant biofilm resistance. Because biofilm resistance is a symbiotic, multi-determinant system involving the physical and chemical interaction of both substrate and bacteria, we also examined the surface energies of the polymerized phenyl acrylate derivatives, collagen, and two representative bacteria (e.g., P. aeruginosa and S. aureus ). Comparative analysis of each surface energy component demonstrated that the polar component ( γ s A B ) is likely the primary thermodynamic contributor to the observed biofilm resistance. Small polar components of the substrate reduce the adhesiveness of bacteria to the substrate, whereas a large base component ( γ s − ) repels the bacterium. Repulsive intermolecular interactions between base components of both the substrate and bacteria prevent intimate bacterial association with the substrate. Secondarily, we posit that the presence of soft atoms (e.g., bromine and iodine) and/or polarizable moieties in the coating may allow bacterial association while inhibiting adhesion and biofilm formation during primary colonization. Limitations of the Study Potential caveats of this published work could include the following. First, as mentioned in the text, our fundamental assumption throughout our biological experimentation is that biofilm growth cannot occur without primary colonization. Although we are not explicitly studying primary colonization, we are examining the results of microbial colonization that are possible only if primary colonization occurs via a significant substrate-bacteria interfacial interaction, an interaction that is limited in the latter stages of biofilm growth. Also because we used non-virulent bacterial strains for researcher safety, biofilm formation and resistance thereto may differ from virulent strains of the same species. Finally, goniometric surface energy analyses, like those reported herein, have been shown to differ from other surface energy analyses that do not use contact angle measurements (e.g., density functional theory [DFT] and cleaving method); however, the non-contact angle methods are most effectively implemented with well-defined structures unlike those examined herein ( Tran et al., 2016 ; Gilman, 1960 ; Jaccodine, 1963 ). Resource Availability Lead Contact Further information and requests related to the research published herein should be directed to and fulfilled by the Lead Contact, T. Brian Cavitt ( tbcavitt@lipscomb.edu ). Materials Availability All unique/stable reagents generated in this study are available on request from the Lead Contact but may require a payment and/or Materials Transfer Agreement if there is potential for commercial application. Data and Code Availability The published article includes all datasets generated or analyzed during this study."
} | 8,774 |
21995752 | PMC3212925 | pmc | 2,172 | {
"abstract": "Background To expand on the range of products which can be obtained from lignocellulosic biomass, the lignin component should be utilized as feedstock for value-added chemicals such as substituted aromatics, instead of being incinerated for heat and energy. Enzymes could provide an effective means for lignin depolymerization into products of interest. In this study, soil bacteria were isolated by enrichment on Kraft lignin and evaluated for their ligninolytic potential as a source of novel enzymes for waste lignin valorization. Results Based on 16S rRNA gene sequencing and phenotypic characterization, the organisms were identified as Pandoraea norimbergensis LD001, Pseudomonas sp LD002 and Bacillus sp LD003. The ligninolytic capability of each of these isolates was assessed by growth on high-molecular weight and low-molecular weight lignin fractions, utilization of lignin-associated aromatic monomers and degradation of ligninolytic indicator dyes. Pandoraea norimbergensis LD001 and Pseudomonas sp. LD002 exhibited best growth on lignin fractions, but limited dye-decolourizing capacity. Bacillus sp. LD003, however, showed least efficient growth on lignin fractions but extensive dye-decolourizing capacity, with a particular preference for the recalcitrant phenothiazine dye class (Azure B, Methylene Blue and Toluidene Blue O). Conclusions Bacillus sp. LD003 was selected as a promising source of novel types of ligninolytic enzymes. Our observations suggested that lignin mineralization and depolymerization are separate events which place additional challenges on the screening of ligninolytic microorganisms for specific ligninolytic enzymes.",
"conclusion": "Conclusions Microorganisms capable of growing on the complex lignin substrate may be a source of novel enzymes which can be of use for the valorization of waste lignin. Three soil isolates, namely Pandoraea norimbergensis LD001, Pseudomonas sp. LD002 and Bacillus sp. LD003 were identified as potential lignin depolymerizing bacteria, confirming that ligninolytic microorganisms can be found outside the fungal kingdom. All three strains demonstrated growth on both high molecular weight and low-molecular weight lignin fractions, although growth was generally slow and rather poor. The ability to utilize lignin monomers was also relatively limited for all three isolates. The best lignin-like dye decolourizing capacity was observed for the Bacillus sp. LD003 and the ligninolytic enzymes and their potential for biocatalytic Kraft lignin depolymerization, are currently under investigation.",
"discussion": "Discussion Three microbial soil inhabitants identified as Pandoraea norimbergensis LD001, Pseudomonas sp. LD002 and Bacillus sp. LD003 were isolated as potential lignin depolymerizing bacteria. The isolated strains showed growth on both high and low-molecular weight lignin fractions, although growth of Bacillus sp. LD003 was relatively poor. Typical lignin-associated monomers were utilized to a rather limited extent by all three isolates. Remarkably, the isolated strains appeared to lack the ability to oxidize aromatic alcohols or aldehydes to their corresponding carboxylic acid form. The ligninolytic potential of the isolates was furthermore assessed by establishing their ability to decolourize synthetic, lignin-like dyes. The recalcitrant thiazine dye Azure B (AB) is particularly suited for this purpose. This dye is decolourized by high redox potential agents, specifically LiP's [ 17 , 40 , 41 ], whereas it cannot be oxidized by nonperoxidase alcohol oxidases, MnP's or laccases alone [ 40 , 42 ]. In contrast to the other two isolates, Bacillus sp. LD003 readily decolourized AB as well as most of the other lignin-mimicking dyes tested. Also other Bacillus species as well as members of the Streptomyces genus have been reported to degrade AB within 4 - 6 days. These bacteria were isolated from wooden objects, and decolourization of AB was measured to demonstrate lignin peroxidase activity [ 43 ]. AB closely resembles methylene blue (MB) and toluidine blue O that were also readily degraded by Bacillus sp. LD003. MB has previously been found to be oxidized by lignin peroxidase [ 44 , 45 ]. The seemingly contradictory finding that the highest ligninolytic potential appeared to be associated with the strain that showed poorest growth on lignin may be understood from an ecological perspective. Often, recalcitrant compounds such as lignin are degraded by microbial consortia in which the individual strains have specialized roles: some attack the complex substrate whereas others provide essential nutrients [ 46 ]. Ligninolytic bacterial consortia can be found, e.g ., in the gut of wood-feeding termites[ 47 ]. Bacteria like Rhodococcus erythropolis, Burkholderia sp., Citrobacter sp. and Pseudomonas sp. have been isolated from the guts of wood-feeding termites and beetles. These bacteria typically degrade aromatic compounds [ 25 , 48 , 49 ], which suggests that they feed on the aromatic compounds liberated by the lignin degrading species of the gut microflora. However, lignin-degrading activity has also been reported for certain aromatic compound degraders such as Pseudomonas sp. and Burkholderia sp. Furthermore, genera such as Burkholderia, Pseudomonas, Sphingomonas, Bacillus and Pandoraea have been reported to degrade the structurally crucial biphenyl component of lignin, which composes up to 10% of the structure, depending on the lignin type [ 27 , 50 , 51 ]. Like in other lignin preparations, trace amounts of (hemi)-cellulose may be present in Kraft lignin. This however, is not likely to account for the observed growth on lignin, although the cellulolytic capacity of the isolated strains has not been investigated in detail. Many if not most soil bacteria have incomplete cellulolytic systems [ 52 ]. Especially Pandoraea norimbergensis is unlikely to utilize cellulose, since it was unable to utilize glucose or cellobiose, both comprising cellulose [ 53 ]. Indeed, several Bacillus sp . are able to utilize cellulose [ 54 ]. The limited growth observed however, on both the high and low molecular weight lignin fractions, in combination with the ability to utilize certain lignin-model dyes clearly indicate the ligninolytic potential of this strain. Other Bacillus sp. have accordingly been reported to degrade Kraft lignin [ 55 - 57 ]. In addition, several Pseudomonas sp. are able to degrade various lignin preparations such as milled wood lignin, dioxane lignin and lignin from poplar wood [ 58 ], further supporting our findings. In a ligninolytic consortium, Bacillus sp. LD003 may fulfill the role of lignin degrader that has to rely on other microbes for specific nutrients, as suggested by its requirement for yeast extract. The other isolates in this study, Pseudomonas sp. LD002 and P. norimbergensis LD001, showed lesser ligninolytic capacities, but utilized a somewhat wider range of aromatics and did not depend on additional nutrients. Thus, such strains may fulfill the role of nutrient-provider. The bacterial isolates in this study appear to have an alternative type of ligninolytic system. The enzymes are presumably cell-surface associated, in view of the large size of lignin, whereas fungal lignin degradation occurs via extracellular enzymes and secreted secondary metabolites [ 59 - 62 ]. Thus, a new and presumably vast source may be tapped for novel ligninolytic enzyme activities. A few considerations, however, must be taken into account when hunting for novel ligninolytic activities for lignin valorization. First, the type of lignin to be valorized is a key factor, since the process by which it is obtained will result in structural modifications [ 15 , 63 , 64 ]. Thus, \"natural\" ligninolytic systems like those associated with white-rot fungi may not be the most efficient to valorize \"industrial\" lignin streams such as the Kraft lignin employed in this study. Furthermore, the most efficient lignin mineralizing strains may not be the most efficient lignin depolymerizers. Therefore, lignin degradation should be monitored as directly as possible. Ideally, the actual substrate should be used in degradation assays, but the heterogeneous nature of lignin severely complicates the analytics. Alternatively, synthetic dyes may be used to mimic lignin as we did in the present study. However, the ligninolytic activities obtained by this approach should be evaluated for their utility on the proper type of lignin."
} | 2,128 |
31690310 | PMC6833302 | pmc | 2,173 | {
"abstract": "Background Oxygen-evolving photoautotrophic organisms, like cyanobacteria, protect their photosynthetic machinery by a number of regulatory mechanisms, including alternative electron transfer pathways. Despite the importance in modulating the electron flux distribution between the photosystems, alternative electron transfer routes may compete with the solar-driven production of CO 2 -derived target chemicals in biotechnological systems under development. This work focused on engineered cyanobacterial Synechocystis sp. PCC 6803 strains, to explore possibilities to rescue excited electrons that would normally be lost to molecular oxygen by an alternative acceptor flavodiiron protein Flv1/3—an enzyme that is natively associated with transfer of electrons from PSI to O 2 , as part of an acclimation strategy towards varying environmental conditions. Results The effects of Flv1/3 inactivation by flv3 deletion were studied in respect to three alternative end-products, sucrose, polyhydroxybutyrate and glycogen, while the photosynthetic gas fluxes were monitored by Membrane Inlet Mass Spectrometry (MIMS) to acquire information on cellular carbon uptake, and the production and consumption of O 2 . The results demonstrated that a significant proportion of the excited electrons derived from photosynthetic water cleavage was lost to molecular oxygen via Flv1/3 in cells grown under high CO 2 , especially under high light intensities. In flv3 deletion strains these electrons could be re-routed to increase the relative metabolic flux towards the monitored target products, but the carbon distribution and the overall efficiency were determined by the light conditions and the genetic composition of the respective pathways. At the same time, the total photosynthetic capacity of the Δ flv3 strains was systematically reduced, and accompanied by upregulation of oxidative glycolytic metabolism in respect to controls with the native Flv1/3 background. Conclusions The observed metabolic changes and respective production profiles were proposedly linked with the lack of Flv1/3-mediated electron transfer, and the associated decrease in the intracellular ATP/NADPH ratio, which is bound to affect the metabolic carbon partitioning in the flv3 -deficient cells. While the deletion of flv3 could offer a strategy for enhancing the photosynthetic production of desired chemicals in cyanobacteria under specified conditions, the engineered target pathways have to be carefully selected to align with the intracellular redox balance of the cells.",
"conclusion": "Conclusions The work presented here demonstrates the effects of the inactivation of the alternative electron acceptor Flv1/3 in engineered Synechocystis strains on the production of sucrose, PHB and glycogen, and associated photosynthetic gas fluxes under various light conditions. Besides assisting further design of the specified target pathways, the findings can directly be applied to enhance the photoautotrophic production of associated compounds such as the monomeric PHB derivative 3-hydroxybutyrate [ 19 , 27 ]. In a broader view, the results provide a generic perspective for optimizing the electron flux between photosynthetic light reactions and the downstream biosynthetic pathways, with the objective to funnel cellular resources more effectively towards the generation of target chemicals. The work also underlines the potential effects of the changes in the ATP/NADPH ratio whenever alternative electron acceptors are inactivated, which appears to be an important factor in determining carbon partitioning in engineered cyanobacteria.",
"introduction": "Introduction Photosynthetic cyanobacteria have been considered as potential next-generation biotechnological hosts for the production of different carbon-based products, as part of the development of new carbon neutral industrial solutions to replace petroleum-derived chemicals now in use [ 1 , 2 ]. The critical advantage of such autotrophic production platforms would be the possibility to convert CO 2 directly into the target metabolites by using photosynthetically captured solar radiation as the sole energy source, and cyanobacterial cells as biological catalysts. Importantly, this would decouple the production process from the dependence of biomass-based substrates, which is a key limitation in all currently existing large-scale biotechnological applications that use heterotrophic organisms as hosts. Although cyanobacteria have been engineered to produce a wide range of different chemicals [ 3 – 6 ], the development of commercially feasible technologies is still restricted by inadequate efficiency at which the solar energy harvested by the cells can be captured in the desired target products. The challenge, from biological engineering perspective, is that without extensive understanding of interactions between solar energy conversion and subsequent carbon reduction metabolism, the harvested energy is distributed to a number of cellular functions and easily lost in unwanted reactions, which compete with the pathways of interest. The objective of the study was to investigate whether the autotrophic production efficiency of specified end-metabolites can be improved in engineered cyanobacterial cells by the modification of endogenous regulatory systems, which are involved in the redistribution of photosynthetic electron fluxes when the light reactions and carbon fixation are not in balance. The focus was on a specific heterodimeric cyanobacterial Class C flavodiiron protein Flv1/3 (see review [ 7 ]), which directs electrons accumulated in the photosynthetic electron transfer chain via photosystem (PS) I to molecular oxygen. In this so-called Mehler-like reaction [ 8 , 9 ], Flv1/3 uses electrons which originate from the photosynthetic water-splitting in PSII and are thereafter directed via PSI to reduce O 2 to water (Fig. 1 ), without the formation of ROS [ 10 ]. This reaction has been shown to be particularly important for preventing the damage to PSI, especially under growth conditions such as fluctuating light that increase the reductive pressure inflicted on PSI [ 9 , 11 , 12 ]. Flv1/3-mediated O 2 photoreduction has also been observed in cells cultured under continuous light [ 8 , 10 ], as well as in the presence of saturating carbon where it has been reported to account for the loss of ~ 20% of the electrons originating from PSII [ 8 ], although under these conditions the enzyme is not essential for viability. Notably, the channeling of electrons to O 2 by Flv1/3 instead of NADP + , is bound to increase the intracellular ATP/NADPH ratio, thus potentially linking to a range of effects associated with the metabolic state of the cell. Fig. 1 Simplified representation of pathways engineered in Synechocystis to evaluate the possibility to enhance the photosynthetic electron flux to target products by the inactivation of the flavodiiron protein 3 (Flv3) and improving the strength of the electron sink (see Table 1 for strain descriptions). The engineering strategy made use of the native capacity of cyanobacterial cells to alleviate osmotic stress by the production of intracellular sucrose and glucosylglycerol as osmoprotective agents. Specific genetic modifications introduced in Synechocystis to maximize the production of sucrose include (i) the inactivation (red) of Flavodiiron protein 3 (Flv3 encoded by sll0550 ) which is involved in a photoprotective Mehler-like reaction of the photosynthetic electron transfer chain i.e. the loss of excited electrons to molecular oxygen, and (ii) the overexpression (blue) of sucrose permease (CscB from E. coli ) responsible for the active transport of sucrose out from the cell into the culture medium. In addition, the modifications include (iii) the inactivation (red) of glucosylglycerolphosphate synthase (ggpS encoded by sll1566 ) responsible for a committed step in the biosynthesis of glucosylglycerol, competing with the sucrose biosynthesis pathway, and (iv) the overexpression (blue) of sucrose phosphate synthase (SPS encoded by sll0045 ) which enhances one of the potentially limiting steps, conversion of UDP-glucose to sucrose-6-phosphate. The target product sucrose and the storage compounds, polyhydroxybutyrate and glycogen, quantitated in the study are shown in grey background. (See Additional file 1 : Table S2 for a more comprehensive list of the enzymatic reactions in the pathways, and the production and use of ATP and NADPH) The leading question here was whether the elimination of the native Flv1/3 reaction could be used to enhance the photosynthetic electron flux towards alternative carbon sinks in engineered cyanobacterial cells, thus improving the yield of target end-products without compromising the fitness of the host. The strategy was to inactivate the gene coding for Flv3 ( sll0550 ) to suppress the oxygen-dependent Flv1/3 Mehler-like activity [ 8 , 9 ] in the cyanobacterium Synechocystis sp. PCC 6803 ( Synechocystis from here on), followed by the analysis of the consequent effects on specific pathway flux distributions, cell growth, and photosynthetic gas fluxes. The experimental set-up was limited specifically to elevated carbon atmosphere, as to represent conditions where additional CO 2 is provided from available point sources, with the aim of assessing the engineering potential and obtaining new biological insight into the metabolic interactions involving Flv3.",
"discussion": "Discussion Normal cell metabolism has been optimized in the course of evolution for the allocation of available resources to different functions needed for cell proliferation, maintenance, and acclimation to varying environmental and metabolic cues. However, when microbial cells are recruited as biotechnological production hosts the specific objective is to effectively funnel the metabolic flux towards desired target metabolites, while minimizing the competing reactions and pathways. This means that biomass accumulation and generation of intracellular storage compounds should be avoided at the production phase when aiming at maximal yield of target products with the highest overall cost-efficiency. In the design of applications using cyanobacteria as biotechnological hosts that employ light as the sole energy source for the direct production of chemicals, the pipeline requires efficient coupling of (i) the photosynthetic light reactions, (ii) the subsequent CO 2 fixation reactions, and (iii) the downstream biosynthetic steps to the end-products excreted into the medium. From this perspective, we focused on the possibilities to enhance the capture of excited electrons and carbon in engineered Synechocystis strains by the inactivation of flavodiiron protein Flv1/3. Natively, this heterodimer plays a distinct role as an alternative sink for excess electrons from the photosynthetic light reactions, and is therefore linked with the metabolic electron flux distribution that affects the ATP/NADPH ratio of the cell. From engineering viewpoint, Flv1/3 activity may thus (i) compete with downstream reactions for reducing equivalents that could potentially be rescued for the production of specific target chemicals, and/or (ii) alter the intracellular redox equilibria to favor certain pathways (i.e. end-products) over others. With the objective to evaluate the effect of flv3 deletion on the metabolic flux distribution and efficiency in Synechocystis , a number of engineered strains excreting sucrose as the target end-product (Fig. 1 ) were constructed (Table 1 ) and characterized. As a systematic observation throughout the analyses, the oxygen photoreduction activity of the strains harboring the native flv3 appeared to be exceptionally high in the cells grown under 1% CO 2 and osmotic stress. The light-induced oxygen uptake reached up to 50% of the gross photosynthetic O 2 production as measured under high irradiancies by MIMS (Figs. 2 c, 3 c, 4 c, 5 c; red vs. black line). However, in the flv3 deletion strains, this activity was effectively reduced or lost, and the cells exhibited only residual O 2 uptake (Figs. 2 d, 3 d, 4 d, 5 d; red line) in comparison to the Flv1/3 control strains. While this residual oxygen uptake was expected to result, at least in part, from increased respiratory glycolytic metabolism associated with observed sucrose uptake and utilization in the Δ flv3 strains, there was no indication of any significant activity of other alternative native electron acceptors (like Cyd/Cox [ 17 ] or Flv2/4 [ 9 ]) under any of the conditions tested. This, together with restoration of oxygen uptake resulting from Flv3 over-expression in the Δ flv3 background (Additional file 1 : Fig. S4b), implicated that the Mehler-like reaction catalyzed by the Flv1/3 heterodimer [ 8 , 9 , 12 ] was the primary reason for the recorded O 2 consumption. Thus, the electrons normally consumed in by Flv1/3 could be available and potentially provide a biosynthetic advantage for the Δ flv3 mutant, especially as the fitness of the deletion strains appeared not to be compromised based on growth (Figs. 2 b, 3 b, 4 b, 5 b) (Additional file 1 : Fig. S2b). This was corroborated by the slight yet consistent increase in the total carbon uptake of the Δ flv3 mutant strains observed in MIMS (Figs. 2 c, d, 3 c, d, 4 c, d, 5 c, d; blue line) (Additional file 1 : Table S1), suggesting that the deletion of flv3 could under certain conditions be beneficial in respect to carbon fixation in comparison to the strains with the native Flv3 background. The enhancement of CO 2 fixation has also been reported earlier in engineered cyanobacteria, and linked with possible sink-effect where enhanced product formation creates a pull that upregulates the upstream photosynthetic reactions [ 14 , 18 ]. In our case, however, the PSII turnover (measured as the gross O 2 evolution) was significantly downregulated in the Δ flv3 strains under all the test conditions (Figs. 2 c, d, 3 c, d, 4 c, d, 5 c, d; black line). Together the findings indicated that (i) the Δ flv3 mutant strains exhibited lower total photosynthetic efficiency, but (ii) allocated a higher proportion of the resources downstream PSI for the biosynthesis of organic compounds as compared to the control strains with the native Flv1/3. In another words, although the overall photosynthetic efficiency was reduced, a higher total amount of energy could be funneled into productive use in the Δ flv3 strains. In this work we evaluated the effect of Flv1/3 inactivation on carbon distribution in Synechocystis in respect to three distinct end-products, sucrose generated via two engineered pathway variations, and the endogenous storage compounds PHB and glycogen. Clearly, the most significant benefit of flv3 deletion was observed in the production of PHB in Δ flv3 cells cultivated under high light 200 μmol photons m −2 s −1 under 1% CO 2 atmosphere (Additional file 1 : Fig. S5). Under these conditions PHB was the primary sink over sucrose and glycogen in the flv3 deletion strains (Table 1 ; strains S01:Δ flv3 and S02:Δ flv3 ), with the total amount exceeding two-fold in comparison to the corresponding control strains ( Table 1 ; strains S01 and S02) (Fig. 6 ). This demonstrates that the deletion of flv3 provides means for improving photoautotrophic production of PHB in Synechocystis , but could also be directly implemented for enhancing the flux towards 3-hydroxybutyrate [ 19 ]—an industrially relevant monomeric derivative of PHB that is spontaneously excreted out from the cell, and could be used for development of a continuous production system. The inactivation of Flv3 was also shown to improve sucrose production in the strain expressing the heterologous sucrose permease CscB (Table 1 ; strain S01:Δ flv3 ) under low or moderate light (Fig. 2 a) (Additional file 1 : Fig. S2a), but generally the absolute productivities were very low (Fig. 6 ). Notably, additional genetic modifications (i.e. sps over-expression and ggpS deletion in S02) that were initially introduced to reinforce the sucrose pathway (Table 1 ; strains S02) in fact decreased sucrose productivity of the Δ flv3 over the control strains—showing that sucrose is not the optimal end-product for the Flv1/3-deficient strains under the experimental set-up. The production of glycogen was enhanced in the S02:Δ flv3 strain grown under 50 μmol photons m −2 s −1 , but in regards to the total carbon flux, the impact of flv3 deletion was marginal (Fig. 6 ). The results implicitly demonstrate that the deletion of flv3 drastically modulates the electron flux distribution and carbon allocation in engineered Synechocystis cells. At the same time, the findings support the conception that the inactivation of alternative photosynthetic electron acceptors, such as Flv3, could potentially be used for enhancing specific downstream metabolic reactions. However, the flux ratios between the alternative electron sinks, as here represented by sucrose, PHB and glycogen (Fig. 6 ), are determined by environmental conditions such as the light intensity and the genetic layout of the associated pathways. Thus, targeting specific pathways of interest, requires comprehensive understanding of the complex endogenous regulatory networks and interlinked factors, which define the most favorable path for photosynthetic water-derived electrons under alternative metabolic environments. In the present work, the increased electron pressure and related changes in cellular redox balance that result from flv3 deletion—together with simultaneous sucrose production—are likely to interfere with the native mechanisms that regulate the accumulation and use of PHB and glycogen in Synechocystis [ 20 , 21 ]. One of the underlying causes for the observed effects is expected to be the ATP/NADPH ratio in the Δ flv3 cells, as many downstream processes and associated control circuits are affected by this homeostasis [ 22 ]. We have shown that the transfer of electrons by Flv1/3 to O 2 constitutes a significant share of the total photosynthetic electron flux under various conditions, especially under high light (Figs. 2 c, d, 3 c, d, 4 c, d, 5 c, d; red line). This alternative electron transfer is coupled to ATP production, while limiting the amount of electrons that are used for the reduction of NADP + to NADPH. Thus when functional, Flv1/3 contributes to the increase of the relative intracellular ATP/NADPH ratio via the native Mehler-like oxygen photoreduction. In reverse, the inactivation of Flv1/3 would be expected to increase the relative levels of NADPH, with a consequent reduction in the ATP/NADPH ratio. This condition could become especially relevant in the Δ flv3 cells under high light cultivation, as demonstrated by the decrease of the ATP/NADPH ratio of the deletion strain grown at 200 μmol photons m −2 s −1 in comparison to WT (Fig. 7 ). Despite the fact that the total carbon fixation was shown to be slightly increased in the Δ flv3 strains (Figs. 2 c, d, 3 c, d, 4 c, d, 5 c, d; blue line), this may pose a problem with many downstream biosynthetic processes that require higher ATP/NADPH ratios than primary CO 2 fixation. These pathways may consequently become limited by inadequate ATP, and result in metabolic responses such as the observed downregulation of the photosynthetic machinery that could compromise the overall production system efficiency. At the same time, such change in the metabolic redox state could be in the favor of pathways that function to counterbalance the effect, and compensate for the relative intracellular ATP deficiency. This is supported by the significant enhancement of PHB production in the Δ flv3 mutant, as the biosynthesis of PHB is not limited by the redox poise of the cell, and specifically increases the ATP/NADPH ratio that is reduced by the deletion of flv3 . The observation is consistent with the native redox control of PHB biosynthesis, which is induced under nitrogen limitation [ 23 , 24 ] that shifts the balance between NADP + and NADPH towards the reduced form (i.e. decreases the ATP/NADPH ratio) [ 23 ]. Under these conditions PHB serves as a redox sink to use excess NADPH in the cell [ 23 ], in analogy what is observed for the ∆ flv3 strain. Several computational analyses on engineered pathway fluxes in cyanobacteria have predicted analogous interconnections between the intracellular redox state and the target pathways. For example, the production of 1-octanol through an engineered NADPH-dependent pathway is expected to be enhanced by the inactivation of Flv1/3, that potentially increases the relative abundance of NADPH [ 18 ]. In a similar manner, stoichiometric network analysis has suggested that target pathways that have lower relative demand for ATP over NADPH than generally required for cell growth, can be favoured on the expence of biomass accumulation by genetic modifications that reduce the intracellular ATP/NADPH ratio [ 25 ]. In the case of the ∆ flv3 mutant, the observed upregulation of PHB biosynthesis is likely to be further interlinked with other reactions in the central carbon metabolism, as PHB is produced from the intracellular glycogen carbon pool [ 24 ], that may also affect the use of other available carbohydrate substrates. In line with this, we also observed significant increase in the sucrose uptake (Figs. 3 a, 4 a; red line) and respiratory metabolism (Figs. 3 d vs. 2 d, 4 d vs 5 d; red line) in the Δ flv3 strains under the same conditions that promoted PHB accumulation. Sucrose consumption has been previously reported for engineered Synechocystis strains that excrete sucrose [ 26 ], but the enhancement of the effect in the Δ flv3 mutant over the control strains may reflect metabolic acclimation to re-establish the native ATP/NADPH equilibrium in the absence of Flv1/3. This would take place through upregulated aerobic carbohydrate breakdown and cellular respiration which ultimately produces ATP, using sucrose that has been photosynthetically produced and secreted into the medium by the same cells. The founding idea in this work was to evaluate the possible biosynthetic advantage of disabling the Mehler-like activity catalyzed by the alternative electron acceptor Flv1/3, while recognizing that the function is important for protecting the cell against fluctuations in the photosynthetic redox poise. Flv1/3 has been shown to be essential for cyanobacteria specifically under fluctuating light [ 9 , 11 , 12 ], implying that biotechnological applications that use natural light would not be feasible for ∆ flv3 strains, unless introduced product pathways could provide sufficiently efficient redox sinks to rescue the phenotype. As observed before [ 9 , 12 ] and demonstrated in this study, however, the lack of Flv1/3 appears not to be critical under constant illumination, so the strategy could be applicable in strain engineering under controlled light systems. The metabolic effects associated with flavodiiron proteins are also linked with carbon availability [ 9 , 12 ], and while the limitation of CO 2 and consequent down-regulation of CBB cycle generally increases the need for alternative electron acceptors to dissipate excess electrons, different enzymes function under distinct conditions [ 12 ]. As Flv1/3 is expressed and active also when CO 2 is abundant, and serves as the main alternative electron sink responsible for oxygen photoreduction in Synechocystis under high carbon concentrations [ 12 ], it is a prominent deletion target specifically for applications that rely on additional supplemented CO 2 . In the cultivation setup used in this work, the flv3 deletion strain appears not to be critically damaged by light stress under constant illumination, while the elevated CO 2 level (1%) is sufficiently high to avoid overlap with other native alternative electron transfer routes (Flv2/4, NDH-1) which are active under atmospheric carbon concentrations [ 12 ]. Finally, although most of the observed effects resulting from flv3 deletion are directly or indirectly associated with the Mehler-like oxygen photoreduction activity of Flv1/3, it is still unclear whether or when the lack of the homo-oligomeric form Flv3/3 also contributes to the outcome. Over-expression of Flv3 has been previously shown to partially rescue the impaired growth of ∆ flv1 strain (devoid of Flv1/3 activity) under fluctuating light conditions [ 9 ], but the reaction is oxygen-independent and thus clearly distinct from the function of Flv1/3. As the biological role, associated reactions and interaction partners of Flv3/3 have not yet been elucidated, it is not known if the enzyme is involved in functions that affect electron partitioning towards different metabolic pathways under constant light."
} | 6,227 |
29523841 | PMC5844888 | pmc | 2,176 | {
"abstract": "Engineered nanoparticles offer the potential for remediation of land and water that has been contaminated by organics and metals. Microbially synthesized nano-scale magnetite, prepared from Fe(III) oxides by subsurface Fe(III)-reducing bacteria, offers a scalable biosynthesis route to such a nano-scale remediation reagent. To underpin delivery of “bionanomagnetite” (BNM) nanomaterial during in situ treatment options, we conducted a range of batch and column experiments to assess and optimise the transport and reactivity of the particles in porous media. Collectively these experiments, which include state of the art gamma imaging of the transport of 99m Tc-labelled BNM in columns, showed that non-toxic, low cost coatings such as guar gum and salts of humic acid can be used to enhance the mobility of the nanomaterial, while maintaining reactivity against target contaminants. Furthermore, BNM reactivity can be enhanced by the addition of surface coatings of nano-Pd, extending the operational lifetime of the BNM, in the presence of a simple electron donor such as hydrogen or formate.",
"conclusion": "Conclusion In summary we have demonstrated that the mobility of BNM can be tuned, in order to effectively utilize it in field applications for either delivery to a point source (by use of organic coatings) or usein a permeable reactive barrier (uncoated BNM). In addition the catalytic properties of the material can be optimized by adding a low loading of Pd as a nanocatalyst, extending activity for treatments including wastewater remediation 13 , 33 .",
"introduction": "Introduction Iron based nanoparticles including composite particles can be used to treat a variety of toxic organic compounds and heavy metals and show significant potential for industrial and remedial applications 1 . Amongst the nanomaterials that are available for use, chemically synthesized nano scale zero valent iron (nZVI) and magnetite have been most commonly used for in situ remediation techniques, as these can treat (via sorption and redox reactions) both, heavy metals and persistent organic compounds 2 – 4 . For example, magnetite and ZVI iron nanoparticles have been shown to be effective for the removal of toxic heavy metals including Cr(VI), Ni(II), Hg(II), Cd(II) and Pb(II) 5 – 7 and can also promote the reductive dehalogenation of organic compounds such as trichloroethane (TCE) and perchloroethylene (PCE) 8 . Synthesis of such nanoparticles is achieved largely by chemical processes that are fast, inexpensive and provide well defined size distributions of the end product. However, these processes often involve the use of relatively extreme conditions, including high temperature regimes and harsh chemicals. Microorganisms can offer an alternative green route to synthesize functional nanoparticles, which is scalable and cost effective, producing materials with high sorption characteristics and catalytic properties, and able to remediate a variety of target contaminants. Bionanomagnetite (BNM) is one such nanomaterial that is synthesized by Fe(III)-respiring subsurface bacteria e.g. Geobacter sulfurreducens and Shewanella oneidensis 9 , in the presence of an electron donor such as lactate, acetate or hydrogen and an insoluble Fe(III) electron acceptor, including waste iron materials 10 . The resultant nanomaterial is highly reactive against redox active pollutants due to an abundance of Fe(II) on the surface of material and within the magnetite structure 11 . Its synthesis can be regarded as a green chemistry process, operating at ambient pressures and temperatures in the absence of toxic reagents and capping agents, and it is also amenable to surface engineering for improved reactivity. For instance, BNM has been shown to abiotically reduce Pd(II) to Pd(0), producing a nanoscale heterostructure with extended reactivity against inorganic 12 , 13 and organic substrates 14 in the presence of external electron donors. Recent studies have shown that BNM synthesis is both tunable (with respect to particle size and magnetic properties) and scalable underpinning future commercial exploitation 10 , 15 . Further recent studies on the potential applications of BNM have shown that it can reduce model Cr(VI) solutions both in batch reactors 16 and in column systems 13 . Furthermore, it has been effective in reducing and source stabilization of Cr(VI) in leachates procured from chromite ore processing residue (COPR), from a contaminated landsite in Glasgow 12 . Targeted in situ applications of nanoparticles for contaminant land treatment will rely on delivery of the materials via direct injection techniques, where a highly concentrated nanomaterial slurry is injected at high flow velocities into the aquifer 17 . This subsurface injection primarily aims to remediate the contaminant through reduction (transformation) and immobilization 18 and relies on transport of the reactants from the injection point to the zone that requires remediation. A second approach involves the generation of a permeable reactive barrier, a matrix of immobile nanoparticles that have been placed in the subsurface, and aimed at treating a plume of contaminated groundwater as it passes through the barrier 3 , 19 . In this second scenario, mobility of the nanomaterial is not desirable. For in situ applications, properties of nanomaterials are optimized to regulate deposition kinetics and aggregation behaviour. Addition of stabilizers 20 , e.g. polyelectrolytes 21 , polysaccharides 22 , 23 , amino acids 24 or organic matter 25 – 28 , has been shown to improve the dispersal of nanomaterials by either electrostatic or steric stabilization mechanisms, thus enhancing their transport properties. The hydrochemical and hydrogeological characteristics of aquifers, such as the pH and ionic strength of the groundwater 29 – 32 , and the properties of the aquifer materials themselves, also influence the transport and reactivity of any nanoparticles delivered into the subsurface for remediation applications. In this study we investigate for the first time both, the transport behaviour of biogenic nanomagnetite (BNM) and its reactivity. Transport studies used columns filled with a porous medium, representative of subsurface aquifer materials, and further demonstrate that with the use of non-toxic and inexpensive stabilizers e.g. guar gum and humic acid salts, the mobility of BNM can be controlled without affecting its remediation and sorbent properties significantly. We have used Cr(VI) as a model redox active contaminant in batch reactors, as it is a potent carcinogen that is released from mining and other industrial activities, and has a maximum permissible concentration of 50 ppb in potable water, as recommended by the World Health Organization (WHO). Batch Cr(VI) reduction studies were conducted alongside column transport studies, to investigate the possible impact of stabilizers on reactivity. Furthermore, a novel 2D-gamma imaging method was used to investigate the transport of coated and uncoated BNM in columns. To do this, BNM was labelled with the γ-emitting metastable isomer of 99m Tc, offering an efficient, non-invasive technique to investigate the transport and deposition behaviour of BNM in porous media. The implications for in situ treatment of a range of contaminants by BNM are discussed.",
"discussion": "Discussion In this study the addition of organic coatings had pronounced impacts on the physical and surface properties of aggregated BNM nanomaterial, including the size, zeta potential, settling rates and viscosity of particle suspensions. Both guar gum and starch coatings increased the size of the BNM dramatically, although the humic acid salt coating resulted in smaller (micron-scale) dimensions. Addition of an agar agar coating marginally increased the size of the BNM. However, with all treatments studied, the apparent dimensions were considerably larger than the individual crystallites (10–50 nm) as reported previously 35 , presumably due to aggregation of primary nanomaterial. We should note that these micron-scale aggregates would still considered as nanomaterials at these dimensions by the European Union as they are composed of individual particles <100 nm as noted in E.U recommendation 2011/696/EU. Similar observations have also been noted for other iron based nanoparticles synthesised by abiotic processes 38 , 39 , and both Vander Waal forces and magnetic forces could contribute to these phenomena 40 . In this study, the coatings were added after biosynthesis of the BNM particles from ferrihydrite. An alternative approach to stabilizing the nanoparticles could be to add the coatings before or during BNM synthesis, which is a common approach during chemical synthesis routes 39 . Initial attempts to do this with humic coatings have suggested that this approach has potential (Figure S8 ). Addition of the humic salt increased the net negative charge on the BNM surface,which would stabilize the nanoparticles by creating mutual repulsive forces between the particles themselves, reducing aggregation 41 . The humic coating also influenced the deposition kinetics of the BNM slurry. Addition of positive or near neutral polysaccharides such as guar gum and starch had a lesser impact on the zeta potentials than the agar agar and humic salts. However, zetapotential is known to be a bulk parameter and represents aggregation behaviour only when significant changes occur. In fact, it has been reported to be insensitive to charge patches or heterogeneous charge distribution and cannot explain aggregation behaviour in all cases 42 . The addition of polysaccharides has been shown to increase steric repulsion and thus stabilize nanomaterial in suspension 43 , 44 which could partially explain the increase in the eluting capacity of BNM (50% in the case of guar gum and approximately 80% in agar agar), which is consistent with data presented in other studies 22 , 38 , 45 . The addition of polysaccharides also increases the viscosity of the slurries, which will also enhance mobility. Finally, it should be noted that since the BNM slurry is composed of aggregates therefore some preferential filtration of larger aggregates could have occurred promoting the selective transport of smaller particles through pore throats. The addition of coatings not only modified the physical properties of the BNM, but also affected its transport behaviour, demonstrated in a series of column studies. Of particular note is the imposition of an overall negative charge on BNM by addition of humics, which would minimise interactions with the quartz sand used in this study, and also with soils and sediments, enhancing transport during remediation applications. Here by creating a negative charge on BNM particles, less attachment to the porous medium would be expected, ensuring that fewer particles are deposited during transport. The zeta potential is an important parameter that can control not only interactions between the particles in solution, but also interactions with geological materials. It should be noted that subsurface sediments show a high variability in terms of mineral composition, ionic strength, and natural organic material (NOM). These variables will undoubtedly influence the transport behaviour of nanomaterials, in addition to their intrinsic properties 46 . For instance, starch coated nZVI can show increased aggregation in presence of calcium ions and humic acid as these could help bridge the nanoparticles and promote aggregation 47 . Addition of all the coatings tested had significant impacts on the viscosity of the suspensions, which will in turn alter the transport properties of the BNM in the columns tested, and in soils and sediments during field injections. This was most pronounced for the agar agar and guar gum reagents. The coatings used also influenced the surface reactivity of the BNM, measured by changes in the capacity to reduce Cr(VI).This was most likely due to passivation of the Fe(II) that was accessible on the surface of the magnetite, and is known to be a potent reductant for Cr(VI), resulting in reductive precipitation of Cr(III), and incorporation into the spinel structure 11 . The reduction in the reactivity of the coated BNM could also be due to enhanced aggregation of the constituent primary particles and warrants further investigation. The rate constant for Cr(VI) reduction was highest for uncoated BNM (Table S2 ) and was affected significantly by the addition of the organic coatings used in this study. However, the addition of an array of Pd nanoparticles to the surface of the BNM did help recover this loss in reactivity. At an iron loading of 0.5 g/l, the Pd-BNM nanomaterial with guar gum (Fig. 5b ) or starch (Supplementary Figure S7b for starch coated Pd-BNM) showed a higher reactivity in the presence of an external electron donor (Fig. 5b ), and the reaction rate (K) of the BNM coated with Pd with starch or guar gum was higher than for the non palladized counterparts with just these coatings (Supplementary Table S2 ). Finally, although this study has focused on Cr(VI) as a model contaminant, BNM can remediate a variety of other pollutants including organic contaminants such as PCE, TCE, nitrobenzene 14 and azo dyes 48 . The priority radionuclides Tc(VII) and Np(V) are also amenable to treatment via BNM-mediated reduction to reduced tetravalent phases 49 . It is worth mentioning that the remediation of emerging contaminants that include pharmaceutical products (steroids), surfactants and flame retardants and pesticides, such as metaldehyde,represent future challenges that may be targeted using novel functionalized bionanomaterials 50 . The financial and environmental costs of BNM, relative to conventional synthesis routes are currently being assessed, and the use of alternative “waste” sources of iron oxides amenable to bioconversion to magnetite are a priority. Recent studies 10 , 15 have shown that biosynthesis of magnetite is scalable, and revalorisation of waste or environmental sources offers a sustainable route to large-scale green chemistry production for field applications. The addition of palladium to BNM clearly enhances performance of the remediation material, although its use for environmental applications has been questioned 51 . However, as it is required in extremely low concentrations its usage may be justified for some specialised sites that are regulated and heavily contaminated, for instance, those contaminated with radioactive waste. Extraction of Pd and other metallic catalysts from waste streams may help keep the production costs low for such applications 52 , while magnetic recovery and re-use (where applicable) is feasible based on previous studies 33 ."
} | 3,690 |
24607644 | null | s2 | 2,178 | {
"abstract": "During growth on surfaces, diverse microbial communities display topographies with captivating patterns. The quality and quantity of matrix excreted by resident cells play major roles in determining community architecture. Two current publications indicate that the cellular redox state and respiratory activity are important parameters affecting matrix output in the divergent bacteria Pseudomonas aeruginosa and Bacillus subtilis. These and related studies have identified regulatory proteins with the potential to respond to changes in redox state and respiratory electron transport and modulate the activity of the signal transduction pathways that control matrix production. These developments hint at the critical mechanistic links between environmental sensing and community behavior, and provide an exciting new context within which to interpret the molecular details of biofilm structure determination."
} | 227 |
24607644 | null | s2 | 2,179 | {
"abstract": "During growth on surfaces, diverse microbial communities display topographies with captivating patterns. The quality and quantity of matrix excreted by resident cells play major roles in determining community architecture. Two current publications indicate that the cellular redox state and respiratory activity are important parameters affecting matrix output in the divergent bacteria Pseudomonas aeruginosa and Bacillus subtilis. These and related studies have identified regulatory proteins with the potential to respond to changes in redox state and respiratory electron transport and modulate the activity of the signal transduction pathways that control matrix production. These developments hint at the critical mechanistic links between environmental sensing and community behavior, and provide an exciting new context within which to interpret the molecular details of biofilm structure determination."
} | 227 |
36815664 | PMC9948223 | pmc | 2,180 | {
"abstract": "Abstract Protein nanowires are critical electroactive components for electron transfer of Geobacter sulfurreducens biofilm. To determine the applicability of the nanowire proteins in improving bioelectricity production, their genes including pilA , omcZ , omcS and omcT were overexpressed in G. sulfurreducens . The voltage outputs of the constructed strains were higher than that of the control strain with the empty vector (0.470–0.578 vs. 0.355 V) in microbial fuel cells (MFCs). As a result, the power density of the constructed strains (i.e. 1.39–1.58 W m −2 ) also increased by 2.62‐ to 2.97‐fold as compared to that of the control strain. Overexpression of nanowire proteins also improved biofilm formation on electrodes with increased protein amount and thickness of biofilms. The normalized power outputs of the constructed strains were 0.18–0.20 W g −1 that increased by 74% to 93% from that of the control strain. Bioelectrochemical analyses further revealed that the biofilms and MFCs with the constructed strains had stronger electroactivity and smaller internal resistance, respectively. Collectively, these results demonstrate for the first time that overexpression of nanowire proteins increases the biomass and electroactivity of anode‐attached microbial biofilms. Moreover, this study provides a new way for enhancing the electrical outputs of MFCs.",
"conclusion": "CONCLUSIONS Overexpression of nanowire proteins (e.g. PilA, OmcZ, OmcS and OmcT) can substantially increase electrical outputs of the MFCs with G. sulfurreducens . The increased bioelectricity production was attributed to the decreased internal resistance as well as improved biofilm formation on the anodes. These results demonstrate a new approach for enhancing the performance of MFCs. It should be noted that overexpression of nanowire proteins may cause metabolic burden for constructed cells and the performance of MFCs is close to the upper limit in this study. Rational engineering of the metabolic flux of G. sulfurreducens may further improve the electricity production of MFCs with this species.",
"introduction": "INTRODUCTION Microbial extracellular electron transfer (EET) is an important metabolic process, in which microorganisms exchange electrons with various extracellular acceptors such as metal oxides, organic compounds and electrodes (Jiang et al., 2019 ; Logan et al., 2019 ; Shi et al., 2016 ). The microorganisms with the capability to exchange electrons with electrodes are called as electroactive microbes that have shown great promise as biocatalysts in bioelectrochemical systems (BESs) for various biotechnological applications (Logan et al., 2019 ; Shi et al., 2019 ). One of extensively studied BESs is microbial fuel cells (MFCs) in which electroactive microbes convert chemical energy to electrical energy through transferring electrons, generated by the oxidation of organic substrates, to electrodes via EET (Santoro et al., 2017 ; Verma et al., 2021 ). Therefore, MFC is an attractive bioelectrochemical technology for coupling wastewater treatment and energy recovery from organic matter (Santoro et al., 2017 , Verma et al., 2021 ). However, the applications of MFCs have practically stagnated due to low output of power density (Mateo et al., 2018 ). Electroactivity of microbes is a primary bottleneck for improving electricity production of MFCs (Zhao et al., 2020 ). Geobacter spp. are promising for bioelectrochemical applications because of a strong capacity for EET (Reguera & Kashefi, 2019 ). For example, G. sulfurreducens generates the highest current density of wild‐type microbes available in pure culture (Nevin et al., 2008 ; Rotaru et al., 2015 ; Yi et al., 2009 ). The electrical output of MFCs is significantly impacted by the thickness and conductivity of G. sulfurreducens biofilm grown on the surfaces of electrodes (Hu et al., 2021 ; Malvankar et al., 2012 ; Reguera et al., 2006 ; Steidl et al., 2016 ). Generally, thick biofilms with high conductivity are expected to generate high current density. On the other hand, biofilm conductivity is a decisive variable for biofilm thickness (Steidl et al., 2016 ). The conductivity of G. sulfurreducens biofilm is conferred by membrane‐bound and matrix‐associated electroactive c ‐type cytochromes and protein nanowires (Jiménez Otero et al., 2021 ; Liu et al., 2021 ; Malvankar et al., 2012 ; Richter et al., 2009 , 2012 ; Yalcin et al., 2020 ). \n Geobacter sulfurreducens nanowires are conductive filaments with the base anchored in cell membrane and the distal end extending through the biofilm (Liu et al., 2021 ; Wang et al., 2019 ; Yalcin et al., 2020 ). The nanowires could transfer electrons from bacterial membrane to extracellular electrodes by direct contact (Liu et al., 2020 ; Reguera et al., 2005 ; Wang et al., 2019 ; Yalcin et al., 2020 ). Previous study revealed that EET across membrane and through the biofilm are two limiting steps for catalytic current generation (Strycharz et al., 2011 ). Therefore, protein nanowires are ideal targets for genetic engineering of G. sulfurreducens to improve electrical output of MFCs (Dantas et al., 2015 ; Leang et al., 2013 ). \n Geobacter sulfurreducens has been proposed to generate two types of nanowires, namely, conductive pili (e‐pili) comprising PilA protein (Liu et al., 2021 ) and c ‐type cytochrome filaments comprising OmcZ or OmcS proteins (Wang et al., 2019 ; Yalcin et al., 2020 ). E‐pili and OmcZ are required for thick electroactive biofilm and optimal current production of G. sulfurreducens (Nevin et al., 2009 ; Reguera et al., 2005 , 2006 ; Steidl et al., 2016 ; Vargas et al., 2013 ). However, deletion of OmcS and its homologue OmcT did not impair the current production of G. sulfurreducens (Nevin et al., 2009 ). Previous study suggested that the reciprocal relationship between expressions of omcS and omcZ genes may render the role of OmcS in current production underappreciated (Wang et al., 2019 , Yalcin et al., 2020 ). In addition, OmcZ is highly concentrated at the biofilm–electrode interface and may serve as an electrochemical gate facilitating electron transfer from biofilm to the electrode (Inoue et al., 2011 ). The EET efficiency of G. sulfurreducens could not be improved by replacing the endogenous e‐pili with the more conductive one from G. metallireducens (Tan et al., 2017 ). On the contrary, the G. sulfurreducens variants with greater abundance of e‐pili and c ‐type cytochromes have stronger capacity for current production in MFCs than the wild type (Hernández‐Eligio et al., 2022 ; Leang et al., 2013 ; Yi et al., 2009 ). These findings indicated that the abundance of nanowires may be critical for enhancing EET efficiency of G. sulfurreducens . To determine whether nanowire proteins are applicable for further improving the electrical output of MFCs, the genes encoding PilA, OmcZ, OmcS and OmcT proteins were overexpressed in G. sulfurreducens via a high‐copy‐number vector in this study. The results show for the first time the enhanced electricity production of G. sulfurreducens MFCs via overexpression of bacterial nanowire proteins.",
"discussion": "RESULTS AND DISCUSSION Growths and Fe( III ) reductions In this study, we constructed four G. sulfurreducens strains with the expression vectors of nanowire proteins, namely, GNW1 (pOEpilA), GNW2 (pOEomcZ), GNW3 (pOEomcS) and GNW4 (pOEomcT) (Table 1 ). Western blot analyses confirmed that PilA, OmcZ, OmcS and OmcT proteins were overexpressed in GNW1, GNW2, GNW3 and GNW4, respectively (Figure S1 ). All the constructed strains grew slower than the control strain (i.e. G. sulfurreducens PCA with empty pAWP78 vector) with fumarate as the electron acceptor (Figure S2 ). This finding suggested that overexpression of the nanowires maybe a metabolic burden and thus decreased cell growth. However, the constructed strains reduced soluble ferric citrate at comparable rates (Figure 1A ). It was also shown that ferrihydrite reduction by GNW1 and GNW3 was slightly faster than the remaining constructed and control strains (Figure 1B ). These results are consistent with previous reports that nanowires were not needed for reducing soluble Fe(III) and that PilA and OmcS have critical roles in reducing solid‐phase Fe(III) (Liu et al., 2014 , 2018 ; Mehta et al., 2005 ; Nevin et al., 2009 ; Reguera et al., 2005 ). FIGURE 1 Reduction in ferric citrate (A) and ferrihydrite (B) by the control and the constructed G. sulfurreducens strains. The expression constructs are displayed in parentheses. The values reported are the means and standard deviations of triplicate measurements. Biofilm formation After inoculation in the 24‐well plates, all the G. sulfurreducens strains formed cohesive biofilms on the bottom of the plate wells. The biomass of the biofilms reached their peaks between the 4th and 5th day and decreased subsequently (Figure 2 ). Compared with the control strain, biomass of the biofilms from the constructed strains increased 16% to 146% ( p < 0.05), which decreased in the order of GNW2 > GNW1 > GNW3 > GNW4 > control strain. To evaluate the effects of nanowire proteins on the biofilm‐forming capability of individual cells, the ratios of biofilm biomass to cell growth at the 4th day were calculated (Figure S3 ). The ratios for the constructed strains were significantly higher than that for the control strain ( p < 0.05). These results revealed that overexpression of PilA, OmcZ, OmcS and OmcT can promote the formation of G. sulfurreducens biofilm. Previous study also found that PilA deficiency impaired the biofilm formation of G. sulfurreducens on solid surface when fumarate was used as electron acceptor (Reguera et al., 2007 ; Richter et al., 2012 ). These findings suggested that pili plays an important structural role in cell–cell aggregation during biofilm differentiation (Reguera et al., 2007 , Richter et al., 2012 ). On the other hand, Geobacter pili may mediate the secretion of OmcS and OmcZ (Gu et al., 2021 ). In addition to their electron transfer roles, cytochromes may act as important structural components in biofilm matrix (Hu et al., 2021 ). Similarly, the results of this investigation also indicated the structural roles of OmcZ, OmcS and OmcT in biofilm formation. Comparison between the constructed strains also revealed that overexpression of OmcZ had the most significant promotion for biofilm formation in well plate, which provided further evidence for an important role of OmcZ in maintaining biofilm structure. FIGURE 2 Biofilm formation of the control and the constructed G. sulfurreducens strains. OD 570 , optical density at 570 nm. The expression constructs are displayed in parentheses. The values reported are the means and standard deviations of triplicate measurements. Asterisks represent significant differences between the constructed G. sulfurreducens strains and the control strain at the same day ( p < 0.05). Bioelectrochemical characterizations During the incubation period in the MFCs, the peak voltage outputs of the constructed G. sulfurreducens strains were 0.470–0.578 V in comparison with a peak value of 0.355 V for the control strain ( p < 0.05) (Figure S4 ). The maximum values of electrochemical curves were used for the following analyses. As shown in Figure 3A , the calculated current output of GNW3 and GNW4 increased much faster than the control strain, indicating that overexpression of OmcS and OmcT enhanced the attachment of G. sulfurreducens to electrode. Compared with the control strain, all the constructed strains generated much higher electrical outputs that increased by 32% to 62% ( p < 0.05) (Figure 3A ). The maximum current density of the constructed strains was 2.35 ± 0.06 A m −2 ( n = 3) to 2.89 ± 0.06 A m −2 ( n = 3), while the control strain only produced 1.78 ± 0.05 A m −2 ( n = 3) (Figure 3A ). FIGURE 3 Bioelectrochemical characterization of the control and the constructed G. sulfurreducens strains. (A) Current output curves, the values reported are the means and standard deviations of triplicate measurements; (B) polarization curves (output voltage vs. current density) generated by LSV at the scan rate of 0.1 mV s −1 ; (C) power density output curves (power density vs. current density); (D) Nyquist plots of MFCs. The expression constructs are displayed in parentheses. Curves in (B), (C) and (D) are representative ( n = 3). The polarization curves of the constructed strains were very similar and increased much faster than that of the control strain under linear sweep voltammetry (LSV) conditions (Figure 3B ). As shown on the power output curves (Figure 3C ), the power density of the constructed strains was elevated by 2.62‐ to 2.97‐fold in comparison with that of the control strain ( p < 0.05). The constructed strains produced the maximum power density of 1.39 ± 0.08 W m −2 ( n = 3) to 1.58 ± 0.08 W m −2 ( n = 3), while the control strain only produced 0.53 ± 0.62 W m −2 ( n = 3). Considering that the polarization curves reflect the increase of current density with the reduction in external potential, the reducing slope of polarization curves is thus positively correlated with the internal resistance of the MFCs. Compared with the control MFC, the MFCs of the constructed strains had very small reducing slope at the linear portion of the polarization curves (Figure 3B ), and therefore their internal resistance was smaller. This finding was also evidenced by the data of electrochemical impedance spectroscopy (EIS) (Figure 3D ). The diameter of the semicircle appearing in the Nyquist plots is positively correlated with charge transfer resistance (Malvankar et al., 2012 ). The MFCs of the constructed strains had shorter diameters in the Nyquist plots than that of the control strain ( p < 0.05) (Figure 3D ), indicating that overexpressed nanowires effectively reduced the charge transfer resistance of MFCs. Similarly, previous electrochemical impedance analysis revealed that the biofilm of an OmcZ‐deficient mutant was more electrically resistant than that of the wild‐type G. sulfurreducens (Richter et al., 2009 ). Results in this study demonstrate for the first time that overexpression of nanowire proteins can enhance current production through decreasing the internal resistance of MFCs. These findings are also consistent with the fact that the conductivity of protein nanowires is the critical factor for current production of electrode‐attached biofilms (Liu et al., 2021 ; Lovley & Walker, 2019 ; Wang et al., 2019 ; Yalcin et al., 2020 ). However, given that the known nanowire proteins have distinct electrochemical properties (Gu et al., 2021 ; Wang et al., 2019 ; Yalcin et al., 2020 ; Yalcin & Malvankar, 2020 ), the similar power density of the constructed strains is unexpected. According to the shape of polarization curves, the electrical output efficiency of MFCs probably reached the limitation of substrate turnover rate, which might be caused by the limited metabolic rate of G. sulfurreducens , or the substrate diffusion limitation between biofilm and bulk solution. The kinetics of redox reactions at cell‐electrode interfaces were also determined by cyclic voltammetry (CV) analysis through measuring current response at a low scan rate of voltage (Figure 4 ). The current density at the redox peaks of all the constructed strains showed significant increase compared with that of the control strain, indicating improved electroactivity of biofilms derived from the constructed strains. Previous investigation demonstrated that the peak current of CV curves is positively correlated with the cell density at the electrode surface and the number of membrane‐bound electron transfer proteins in the individual cells (Fricke et al., 2008 ). Therefore, the results of CV analysis were consistent with the increased biomass of electrode‐attached biofilms observed in the following section and overexpression of nanowire proteins in G. sulfurreducens . FIGURE 4 CV curves obtained at the scan rate of 5 mV s −1 . Shown are the CV data of the control strain and the constructed G. sulfurreducens strains overexpressing PilA (A), OmcZ (B), OmcS (C) and OmcT (D). The expression constructs are displayed in parentheses. Curves are representative ( n = 3). The first derivatives of CV data were used to calculate the midpoint potentials of electrode‐attached biofilms (Figure S5 ). GNW3 and the control strain had the same midpoint potential of −0.39 V (vs. Ag/AgCl). The midpoint potential of GNW1, GNW2 and GNW4 is between −0.37 V (vs. Ag/AgCl) and − 0.36 V (vs. Ag/AgCl), higher than that of the control strain. Given that the midpoint potentials of OmcZ and OmcS are −0.42 V (vs. Ag/AgCl) and − 0.41 V (vs. Ag/AgCl) respectively (Fricke et al., 2008 ; Inoue et al., 2010 ; Qian et al., 2011 ), GNW2 and GNW3 were expected to have midpoint potentials lower than that of the control strain, which was inconsistent with the present results. Therefore, these findings indicated a complex regulation of redox components in G. sulfurreducens as suggested in previous studies (Hernández‐Eligio et al., 2022 ; Park & Kim, 2011 ). In addition, reversible peaks near the top of the CV curves at approximately −0.30 V (vs. Ag/AgCl) were resolved in all the biofilms of the constructed strains. First derivate analysis also revealed a current wave near −0.30 V (vs. Ag/AgCl) for the control strain (Figure S5 ). Therefore, this reversible peak reflects an intrinsic electrochemical characteristic of G. sulfurreducens biofilm. Biomass and images of electrode‐attached biofilms The protein amounts of the electrode‐attached biofilms were measured to evaluate the abundance of electroactive cells on the anode (Figure 5 ). The protein amounts of the constructed strains increased by 39% to 62%, as compared with that of the control strain ( p < 0.05). The amounts of proteins from the biofilms of the constructed strains ranged from 7.23 ± 0.36 g m −2 ( n = 3) to 8.45 ± 0.35 g m −2 ( n = 3), while those for the biofilms of the control strain was 5.21 ± 0.28 g m −2 ( n = 3). In addition, comparison between the constructed strains revealed that overexpression of OmcS had the most significant enhancement for biofilm formation on electrode. However, overexpression of OmcZ had relatively weaker promotion for electroactive biofilm. This result may be ascribed to the inhibition of omcZ gene on the expression of omcS gene (Park & Kim, 2011 ). After normalization with measured proteins, the maximum power density of the constructed strains was 0.18 ± 0.01 W g −1 ( n = 3) to 0.20 ± 0.01 W g −1 ( n = 3), which were 1.74‐ to 1.93‐fold higher than that of the control strain with 0.10 ± 0.01 W g −1 ( n = 3) ( p < 0.05) (Figure 5 ). FIGURE 5 Protein amounts of electrode‐attached biofilms and biofilm biomass‐normalized maximum power density. Shown are the amounts of proteins normalized with the areas of anodes. The maximum power density was normalized with the biofilm‐associated protein amounts. The values reported are the means and standard deviations of triplicate measurements. The expression constructs are displayed in parentheses. Asterisks represent significant differences between the constructed G. sulfurreducens strains and the control strain ( p < 0.05). As shown in Figure 6 , Geobacter cells formed active biofilms on the surface of the carbon filaments of anodes. Three‐dimensional side‐view image revealed that the thickness of biofilms from the constructed strains was 110–130 μm, which were significantly larger than the thickness of biofilms from the control strain with only 75 ± 13 μm ( n = 3) ( p < 0.05). These results further evidenced the measured larger protein amounts of the constructed strains. FIGURE 6 Confocal scanning laser microscopy images of the electrode‐attached G. sulfurreducens biofilms. (A) control strain; (B) GNW1 (pOEpilA); (C) GNW2 (pOEomcZ); (D) GNW3 (pOEomcS); (E) GNW4 (pOEomcT). The images are three‐dimensional top views (middle panels), lateral side views (right panels) and horizontal side views (bottom panels) of biofilms. Side‐view images show denser biofilms for the constructed strains with overexpression of nanowire proteins than that for the control strain. Images are representative ( n = 5). Scale bar, 100 μm. Enhancement of biofilm‐formation capability was thought to be beneficial for increasing the abundance of active current‐producing cells on electrode. In this study, the biomass of electrode‐attached biofilm was increased for all constructed strains, and the current production was substantially improved. Moreover, increase in average power output normalized with protein amounts suggested that the EET efficiency of individual cells was also improved. These results were consistent with previous reports that PilA and OmcZ were critical components of conductive biofilms (Inoue et al., 2011 ; Nevin et al., 2009 ; Steidl et al., 2016 ). In previous study, the abundance of OmcS was positively correlated with the current productivity of electrode‐attached biofilm (Holmes et al., 2006 ). Consistent with this finding, the results from this study showed that overexpressed OmcS and OmcT also participated in electron transfer to electrodes. In addition, the present results revealed that the constructed strain with overexpressed OmcZ had lower current production than that with overexpressed OmcS. Given that omcZ can downregulate omcS expression (Park & Kim, 2011 ), the total abundance of extracellular cytochromes of the biofilms with overexpression of omcZ may be lower than that with overexpression of omcS . Thus, the results from this investigation suggested that all the Geobacter nanowire components play important roles in the development of conductive biofilm. Up to date, several genetic strategies have been developed to engineer G. sulfurreducens for improving its EET efficiency and current production (Dantas et al., 2015 ; Hernández‐Eligio et al., 2022 ; Leang et al., 2013 ; Tan et al., 2017 ). All these studies indicated the importance of protein nanowires for the formation of thick conductive biofilms as emphasized in this study. Therefore, bacterial nanowire proteins are promising synthetic biology parts for improving electrochemical performance of microbes by genetic engineering. Moreover, protein nanowires are interesting conductive bionanomaterials which can be constructed in G. sulfurreducens at low cost (Liu et al., 2020 )."
} | 5,662 |
25018558 | null | s2 | 2,181 | {
"abstract": "Collective behaviours are influenced by the behavioural composition of the group. For example, a collective behaviour may emerge from the average behaviour of the group's constituents, or be driven by a few key individuals that catalyse the behaviour of others in the group. When ant colonies collectively relocate to a new nest site, there is an inherent trade-off between the speed and accuracy of their decision of where to move due to the time it takes to gather information. Thus, variation among workers in exploratory behaviour, which allows gathering information about potential new nest sites, may impact the ability of a colony to move quickly into a suitable new nest. The invasive Argentine ant, "
} | 177 |
27257751 | null | s2 | 2,182 | {
"abstract": "Microbial biofilms and most eukaryotic tissues consist of cells embedded in a three-dimensional extracellular matrix. This matrix serves as a scaffold for cell adhesion and a dynamic milieu that provides varying chemical and physical signals to the cells. Besides a vast array of specific molecular components, an extracellular matrix can provide locally heterogeneous microenvironments differing in porosity/diffusion, stiffness, pH, oxygen and metabolites or nutrient levels. Mechanisms of matrix formation, mechanosensing, matrix remodeling, and modulation of cell-cell or cell-matrix interactions and dispersal are being revealed. This perspective article aims to identify such concepts from the fields of biofilm or eukaryotic matrix biology relevant to the other field to help stimulate new questions, approaches, and insights."
} | 208 |
24162473 | PMC3808813 | pmc | 2,186 | {
"abstract": "Spider silks combine a significant number of desirable characteristics in one material, including large tensile strength and strain at breaking, biocompatibility, and the possibility of tailoring their properties. Major ampullate gland silk (MAS) is the most studied silk and their properties are explained by a double lattice of hydrogen bonds and elastomeric protein chains linked to polyalanine β-nanocrystals. However, many basic details regarding the relationship between composition, microstructure and properties in silks are still lacking. Here we show that this relationship can be traced in flagelliform silk (Flag) spun by Argiope trifasciata spiders after identifying a phase consisting of polyglycine II nanocrystals. The presence of this phase is consistent with the dominant presence of the –GGX– and –GPG– motifs in its sequence. In contrast to the passive role assigned to polyalanine nanocrystals in MAS, polyglycine II nanocrystals can undergo growing/collapse processes that contribute to increase toughness and justify the ability of Flag to supercontract.",
"discussion": "Discussion Combination of the mechanical and microstructural data presented above allows establishing a coherent picture of the behaviour of Flag silk, in which the dynamics of polyglycine II nanocrystals are assigned a leading role. Thus, the overall true stress-true strain curves presented in Figure 1 are compatible with the assumption of three regimes in the mechanical behaviour of silks: initial deformation of hydrogen bonds, yielding of the protein chains from their initial configuration and stretching of the protein chains 22 23 . In this context, the increase in polyglycine II crystallinity would be the result of conformational changes induced in the proteins during the stretching step. Consistently with this model, it is found that crystallinity increases reversibly during the stretching of the fiber from the ground (i.e. maximum supercontracted) state due to the increase of the nanocrystal size along the direction parallel to the macroscopic axis of the fiber. This process can be reverted by supercontraction which, in turn, is shown to consist of the partial collapse of the nanocrystals. All these changes can be accounted for if it is assumed that stretching leads to a molecular reorganization of spatially close protein chains at the ends of polyglycine II nanocrystals. In this regard, fibers with larger values of α are shown to attain lower values of strain at breaking, since the conformational changes of the proteins are limited compared with those of fibers with lower values of α. With respect to its influence on the tensile behaviour, this mechanism of nanocrystal formation allows dissipating mechanical energy and, consequently, should represent a significant contribution to toughness. The parallels and differences observed between Flag and MAS immediately suggest the question of whether these features might represent general design principles in spider silks. Although not direct evidence of the presence of polyglycine II nanocrystals in MAS is presented in this work, several indirect facts indicate that this might be the case. Comparison of the tensile properties of Flag and MAS show a striking resemblance between the stress-strain curves of both materials at low values of α ( Figure 1b ). Significant differences are observed at increasing values of α, since the tensile strength of Flag silk does not increase with α, leading to an overall decrease in its work to fracture. Both silks also differ in the curvature of the stress-strain curves, which changes from convex to concave in MAS at large values of α, but remains convex in Flag independently of α, although this difference could be related with the larger values of α found in MAS, up to α = 1.44. The improved behavior of MAS at large values of α could be related with the presence of the β-nanocrystals 16 . Previous studies have shown that the crystalline unit cell and the size of the β-nanocrystals does not change during either stretching 24 or supercontraction 25 . However, the orientation of the nanocrystals with respect to the axis of the fiber and the crystalline fraction increase during stretching 24 . Supporting the importance of β-nanocrystals for the tensile behaviour at large strains, it was found by simulation that the length of the polyalanine runs in the sequence are optimized for the formation of β-nanocrystals 26 , whose size, in turn, is optimized to promote a redistribution of stresses in the material 27 . The combined effect of β- and (presumably) polyglycine II nanocrystals in MAS could explain the change from convex to concave curvature of the stress-strain curves at high values of α. Concave (convex) curvature of a stress-strain curve is usually labelled as enthalpic ( entropic ) behaviour and indicates that variations in the intensity of the interactions (conformational variations) are responsible for the performance of the material. The formation of polyglycine II nanocrystals in MAS would justify this transition since, after the extensive formation of the nanocrystals at large values of α, further stretching would imply the deformation of the nanocrystals, and not additional conformational changes in the chains. Evidently, it is necessary to assess the question of whether the results found in Flag can be extrapolated to MAS. The presence of a second ordered phase in MAS that differed from the β-nanocrystals had been suggested previously 28 29 , and its presence at the ends of the polyalanine nanocrystals have been established by different microstructural techniques 30 31 . Most studies 32 have extrapolated the β-pleated microstructure of the underlying polyalanine nanocrystals to the second ordered phase, but our present study suggests that the possibility of finding polyglycine II structures formed at the end of the β-nanocrystals should be considered. In addition, the XRD data presented in this work can justify the origin of the difficulty of identifying polyglycine II nanocrystals in MAS. Thus, it is found that the most intense reflection arising from polyglycine II nanocrystals corresponding to (100) overlaps with the much more intense reflections (020) and (210) arising from the polyalanine β-nanocrystals. There is, however, at least one report 33 on MAS silk in which a diffuse scattering ring with a Q close to that of the (210) reflection is observed, that is particularly strong along the polar direction. Furthermore, there are three indirect experimental evidences that substantiate the presence of polyglycine II nanocrystals in both Flag and MAS. (1) Comparison of the Flag and MAS sequences shows that both silks share the polyglycine II nanocrystal-forming motifs. This fact is also consistent with the simultaneous evolutionary occurrence of supercontraction and the –GGX– and –GPG– motifs 34 . In this regard, the analysis of recombinant Flag silk including the spacer region besides the glycine-rich motifs 35 suggests that the spacer might play a role in facilitating the alignment of the other two motifs. However, the properties of recombinant Flag fibers are still below from those of the natural material, so that extrapolating conclusions from recombinant to natural Flag fibers should be taken cautiously. (2) When the increase of crystallinity with α is analysed ( Figure 3b ), it is found that both silks present the same slope of the crystallinity vs. α curves, except for the presence of an initial offset in MAS 20 . This observation could be explained in part by the formation of the polyglycine II crystals in MAS, after completing the initial rotation of the polyalanine β-nanocrystals 36 . (3) Finally, the size of the nanoglobules observed by AFM was correlated with the longest crystal-forming fragments in silkworm silk 21 and minor ampullate gland silk 37 . This correlation failed in MAS if the longest polyalanine fragments were considered, but combination of sequential polyalanine fragments (–A 8 – corresponds to 3.5 nm if β-pleated conformation is assumed) and various –GGX– or –GPG– (approx. 0.65 nm each if polyglycine II conformation is assumed) would yield values close to the experimental size of 10–14 nm."
} | 2,056 |
22806947 | null | s2 | 2,187 | {
"abstract": "Hybrid biomaterials are systems created from components of at least two distinct classes of molecules, for example, synthetic macromolecules and proteins or peptide domains. The synergistic combination of two types of structures may produce new materials that possess unprecedented levels of structural organization and novel properties. This Review focuses on biorecognition-driven self-assembly of hybrid macromolecules into functional hydrogel biomaterials. First, basic rules that govern the secondary structure of peptides are discussed, and then approaches to the specific design of hybrid systems with tailor-made properties are evaluated, followed by a discussion on the similarity of design principles of biomaterials and macromolecular therapeutics. Finally, the future of the field is briefly outlined."
} | 203 |
26000479 | null | s2 | 2,188 | {
"abstract": "In the wild, bacteria are predominantly associated with surfaces as opposed to existing as free-swimming, isolated organisms. They are thus subject to surface-specific mechanics, including hydrodynamic forces, adhesive forces, the rheology of their surroundings, and transport rules that define their encounters with nutrients and signaling molecules. Here, we highlight the effects of mechanics on bacterial behaviors on surfaces at multiple length scales, from single bacteria to the development of multicellular bacterial communities such as biofilms."
} | 138 |
34434901 | PMC8381356 | pmc | 2,189 | {
"abstract": "Grasslands are major primary producers and function as major components of important watersheds. Although a concise definition of grasslands cannot be given using a physiognomic or structural approach, grasslands can be described as vegetation communities experiencing periodical droughts and with canopies dominated by grasses and grass-like plants. Grasslands have a cosmopolitan distribution except for the Antarctic region. Fungal interactions with grasses can be pathogenic or symbiotic. Herbivorous mammals, insects, other grassland animals, and fungal pathogens are known to play important roles in maintaining the biomass and biodiversity of grasslands. Although most pathogenicity studies on the members of Poaceae have been focused on economically important crops, the plant-fungal pathogenic interactions involved can extend to the full range of ecological circumstances that exist in nature. Hence, it is important to delineate the fungal pathogen communities and their interactions in man-made monoculture systems and highly diverse natural ecosystems. A better understanding of the key fungal players can be achieved by combining modern techniques such as next-generation sequencing (NGS) together with studies involving classic phytopathology, taxonomy, and phylogeny. It is of utmost importance to develop experimental designs that account for the ecological complexity of the relationships between grasses and fungi, both above and below ground. In grasslands, loss in species diversity increases interactions such as herbivory, mutualism, predation or infectious disease transmission. Host species density and the presence of heterospecific host species, also affect the disease dynamics in grasslands. Many studies have shown that lower species diversity increases the severity as well as the transmission rate of fungal diseases. Moreover, communities that were once highly diverse but have experienced decreased species richness and dominancy have also shown higher pathogenicity load due to the relaxed competition, although this effect is lower in natural communities. This review addresses the taxonomy, phylogeny, and ecology of grassland fungal pathogens and their interactions in grassland ecosystems.",
"conclusion": "Conclusions Natural grasslands are a vital component of several different types of terrestrial ecosystems but are not yet sufficiently studied ( Gibson, 2009 ). Grasslands are highly complex ecosystems comprised of perennials and are dominated by members of the family Poaceae ( Risser, 1988 ). With the high density of plants and the high density of below ground root systems, grasslands provide an ambient environment for microbial growth ( Mommer et al., 2018 ; Ampt et al., 2019 ). The composition of the flora of the grasslands in various regions is affected by unique biological and ecological factors ( Risser, 1988 ; Gibson, 2009 ). Hence, the interaction between the microbiota and their hosts becomes unique in each grassland system based on the floral composition. There is a wide range of fungal lifestyles in nature, but our concern in this paper was focused on the pathogenic lifestyle of the fungi associated with natural grasslands. The fungal- plant interactions in grasslands can be described using two approaches—host specificity based and density dependent based. Research on fungal pathogens can be based on either phylogeny or pathogenicity ( Janzen, 1970 ; Connell, 1971 ; Bever et al., 2015 ). Currently, there have been many taxonomy and phylogeny based studies on the fungi associated with grasses in different ecosystems, which are subject to change since many novel taxa are continuously being introduced. This situation provides the basis for developing an insight for resolving the taxonomic placement of identified and unidentified fungal taxa. In many cases these data cannot be used in accordance with the pathogenicity related studies unless the life mode is confirmed, specifically through the confirmation of the pathogenicity through the Koch postulate. Grasslands also cause disease of humans and other animals. Grassland ecosystems are characterized by complex interactions between pathogens and their hosts. Although the majority of the grassland plants are monocots, there are dicots present among the monocots plants ( Herben et al., 1993 ; Van Der and Sykes, 1993 ; Gibson, 2009 ). Furthermore, there is a high diversity of species in the family Poaceae. Hence, grasslands cannot be considered as a monoculture, and the interactions between monocots as well as between monocots and dicots need to be considered ( Herben et al., 1993 ; Van Der and Sykes, 1993 ). The fungal community below ground and above ground are highly diverse and contrasting. Furthermore, the distribution of fungal pathogens above and below ground in grasslands are complex ( Van Ruijven et al., 2003 ; Van Ruijven and Berendse, 2005 ; Van Ruijven and Berendse, 2009 ; Cong et al., 2014 ; Cappelli et al., 2020 ). Comparatively speaking, the ecology-based studies of fungal pathogens below ground are much more common than the ecology based studies of fungi above ground in natural grasslands. Studies of the fungal pathogens of members of the Poaceae are mainly focused on agricultural monocultures. Hence, there is a dearth of information on above ground fungal pathogens rather than those below ground. In certain cases, these data are applicable to natural grasslands as far as the same species is concerned. However, the effects of complex ecological intereactions in the natural grasslands cannot be neglected. Fungal pathogens of animals in grasslands are poorly studied. Natural grasslands provide grazing sites for large ruminants ( Gibson, 2009 ). In many instances those grazing ruminants directly or indirectly involve human activities and the economy. Hence it is important to study relationships between grassland animals and fungi. Chronic facial eczema caused by Pithomyces chartarum shows how important it is to understand fungal communities in grasslands ( Laven et al., 2020 ; Munday et al., 2020 ). In a way, grasslands can be a reservoir of fungal pathogens. In this review, we have provided four examples where a complete study has been carried out on the pathogenicity and genomics of a particular pathogen. They are based on agricultural monocultures with the help of natural grassland based data. There is a necessity of exploring the natural grasslands to identify novel fungal species. In the meantime, confirming the pathogenicity is also very important. Agronomically, it is important to study the pathogenic community in grasslands as a reservoir of fungal pathogens and understanding the dynamics of the fungal community further helps to understand the effects of fungal pathogens in agricultural multi-lines. The study of Pyrenophora tritici-repentis demonstrated just how important it is to perform a thorough study even on a well-known pathogen, since there are many races with different life modes and attributes. The behavior of the pathogen in natural grassland is also important to observe in order to understand changes in gene expression and pathogenicity. Plant diversity of grasslands is highly variable around the world. However, the stable natural grasslands are rich in host diversity. The belowground host components shapes the total fungal community and the above ground fungal community highly affects the productivity and the biomass of the grassland. Hence, the stability of grasslands is highly dependent upon the balanced interactions of those factors together with other biotic and abiotic factors. The behavior of specialist pathogens and generalist pathogens in grasslands is crucial for the stability of these communities. Heterospecific neighbors in grasslands disturbs the spread of specialist pathogens but also could facilitate the spread of generalist pathogens. However, fungal disease spread in grasslands depend on huge number of biotic and abiotic factors. Different fungal pathogens act differently on the hosts. Meantime, host respond is highly variable. Studies of Pyrenophora tritici-repentis on grasses provide good insight on how pathogenic response of different host genotypes vary towards the same pathogen. In addition, different hosts or genotypes of grasses can induce host-fungal pathogens without causing symptoms. Hence, in a way, grasslands can act as a reservoir for fungal pathogens. Even though pathogenic mechanisms of fungi have been well explained from monocultures, the virulence of the fungus varies with the high diversity in grass lands. Many factors such as heterospecific neighbors, tightly and closely arranged roots, effects of root exudates and root microbiomes, and different host traits can control disease spread. The knowledge of host-pathogen interactions in grasslands can be used for agricultural purposes. Strategic grasslands can be used among the crop fields to control the spread of diseases. Grasslands in between crop fields can act as dense heterospecific host sites for many pathogens and this can immensely reduce the disease spread among the adjusent crop fields. Furthermore, the presence of highly diverse grasslands can reduce the disease insidence of the specialist pathogens. Grass heterospecific neighbor effects of the soil-borne fungal pathogens can be explained in two ways. First, neighbor effects though plant traits or root exudates. Second, neighbor effects through root microbiome. However the loss of dominant plant species in grasslands can increase the extent of disease in the system ( Mitchell et al., 2002 ). Hence, proper understanding of the dominant species in the strategic grasslands and maintainance of the dominant species is important for disease control. Grasslands are an ecologically and economically important component of the earth’s vegitation. Fungal communities in grasslands play a huge role on the stability of grasslands. Having more complete knowledge of fungal pathogens in grass lands is important for developing an understanding of grassland ecology. In addition, understanding behaviour of fungal pathogens in highly diverse grasslands may provide novel insights towards being able to control the diseases in commercial crop fields. In this review, we address the effects of fungal pathogens in grasslands and discussed their complex interactions.",
"introduction": "Introduction There is no concise and unambiguous definition for grasslands ( Gibson, 2009 ). The definition of a grassland could be based on the absence of specific vegetation features ( Milner and Hughes, 1969 ) when using a physiognomic or structural approach ( Bazzaz and Parrish, 1982 ; Sims, 1988 ). A more promising definition, however, was given by Risser (1988) , who indicated that grasslands are “types of vegetation that are subject to periodic drought, that have a canopy dominated by grass and grass-like species, and that grow where there are fewer than 10 to 15 trees per hectare”. Grasslands are distributed throughout the world’s land area except on the continent of Antarctica ( Gibson, 2009 ). Based on the “The Pilot Analysis of Global Ecosystems (PAGE)” classification, grasslands cover 52,544,000 km 2 or 40.5% of the world’s land mass (excluding urban areas according to night time lights) ( White et al., 2000 ; Kassam, 2002 ). According to the PAGE classification, grasslands cover more land area than the other major vegetation cover types ( White et al., 2000 ). For example, forests cover 28.97 × 10 6 km 2 and agriculture covers 36.23 × 10 6 km 2 ( White et al., 2000 ). Furthermore, grasslands are the second largest land type inhabited by humans (nearly 800 × 10 6 people), second only to agricultural land, which holds 2.8 × 10 9 people according to 1995 estimates ( White et al., 2000 ; Gibson, 2009 ). Grasslands also occupy comparatively large areas of many major watersheds in the world ( Gibson, 2009 ). The effect of species diversity on the productivity of a community has been explained by two mechanisms. They are: (i) the sampling effects, which state that the probability of finding key-trait species in a community is reduced due to lower species richness ( Aarssen, 1997 ; Huston, 1997 ; Tilman et al., 1997 ) and (ii) the niche complementarity hypothesis, which states that less diverse communities with competing species utilize resources incompletely ( Naeem et al., 1994 ; Tilman et al., 1996 ; Hector et al., 1999 ). Furthermore, the loss of interactive competition and loss of species diversity have been shown to increase mutualism, predation, herbivory, and infectious disease transmission ( Bond, 1993 ; McNaughton, 1994 ; Chapin et al., 1997 ; Chapin et al., 2000 ). Mitchell et al. (2002) tested the long-standing hypothesis ( Elton, 1958 ; van der Plank, 1963 ) that the lower diversity of plant species increases the severity of diseases, focusing mainly on specific pathogens. Several studies have previously suggested that this hypothesis applies only to a small number of plant species and genotypes ( Garrett and Mundt, 1999 ; Zhu et al., 2000 ). The relaxed interspecific competition due to the decreased plant species richness has been shown to increase the abundance of one or more species existing in a local community, which typically also increases the abundance of one or more host species for specialist pathogens ( Aarssen, 1997 ; Huston, 1997 ; Tilman et al., 1997 ). The basic mechanism of the diversity-disease hypothesis is that a decreasing number of plant species allows for an increased local abundance of other singular species, which then facilitates the spread of diseases specific to that species within the community ( Burdon and Chilvers, 1976 ; Knops et al., 1999 ; Chapin et al., 2000 ). The extent of the differences among different species is correlated with the ecological effects of species diversity ( Tilman and Lehman, 2014 ); hence, the susceptibility of different species for a particular disease must vary. Thus, the local mechanisms of the diversity-disease hypothesis vary highly, as the host abundance depends on numerous biotic and abiotic factors in communities ( Mitchell et al., 2002 ). Apart from host abundance, many other factors such as microclimate and the competitive ability of host plants also influence the disease level in ecosystems with decreasing diversity ( Boudreau and Mundt, 1992 ; Boudreau and Mundt, 1994 ; Zhu et al., 2000 ; Boudreau and Mundt, 2018 ). Most studies examining the diversity-disease hypothesis have been focused on agriculture or silviculture ( Mitchell et al., 2002 ). However, studies by Kranz (1990) revealed that natural, communities with higher diversity did not necessarily have low disease levels, whereby the diversity of forest and pasture communities was higher while in meadow and agricultural field communities it was lower ( Kranz, 1990 ). As such, species diversity is related to species composition, microclimates, and many other factors ( Kranz, 1990 ; Mitchell et al., 2002 ). Agronomic intercropping, with increased species diversity, subsequently decreases the prevalence of diseases ( Mitchell et al., 2002 ), especially fungal diseases. Experimental studies on the diversity-disease hypothesis with regards to intercropping are fewer ( Boudreau and Mundt, 2018 ), but intercropping can change the microclimate and the competitive nature of the crops and all these factors together can either increase or decrease disease severity ( Boudreau and Mundt, 1992 ; Boudreau and Mundt, 1994 ; Zhu et al., 2000 ; Boudreau and Mundt, 2018 ). It has been shown that cultivating a variety mixture or multiline with multiple genotypes of one crop reduced the severity of airborne fungal diseases when compared with its intercrop cultivation ( Wolfe, 1985 ; Finckh and Wolfe, 1997 ; Garrett and Mundt, 1999 ; Zhu et al., 2000 ; Boudreau and Mundt, 2018 ). In agricultural systems, the main mechanism of reducing the spread of the disease is through reducing the host abundance ( Burdon and Chilvers, 1977 ; Burdon and Chilvers, 1982 ; Chin and Wolfe, 1984 ; Wolfe, 1985 ; Alexander et al., 1986 ; Burdon, 1987 ; Garrett and Mundt, 1999 ; Zhu et al., 2000 ; Boudreau and Mundt, 2018 ). We can overlook highly diverse natural grassland ecosystems through the modern knowledge of agricultural multiline even though natural grasslands are more complex than the agricultural multiline. Disease susceptibility and the dominant species present are two aggregated characteristics of a community that can influence the spread and severity of a disease ( Mitchell et al., 2002 ). Mitchell et al. (2002) tested several hypotheses relating to disease levels in a community and found that (1) the loss of less susceptible species in a community increased the disease levels within the community more than the loss of highly susceptible species, (2) the loss of less susceptible species from a plant community increased the disease levels in that community, and (3) the loss of the dominant species increased the prevalence of species-specific pathogens more than the loss of rare species, when all other conditions were equal. However, in certain instances, the most abundant species can be more susceptible to disease, and in such cases the above hypotheses are not valid and the effect of losing the dominant, highly susceptible species is countervailing ( Arneberg et al., 1998 ). Grasslands are highly diverse ecosystems with many interactions. Plant communities in grasslands are comprised mainly of diverse species of grasses, including genotypes of the same species, and various dicots. However, the major part of the community is represented by grasses. Population structure of grasslands is crucial for the productivity as well as the resource utilization of grasslands. However, pathogens in grasslands play a crucial role in the productivity of these communities. Herein we investigate how fungal pathogens presence affect the dynamics of grasslands. Population dynamics of fungal pathogens are highly influenced by the diversity and the population structure of grassland is in question. Furthermore, the dynamics of specialist pathogens and generalist pathogens are contrasting. Increased host diversity of grasslands increases generalist pathogens while reducing specialist pathogens. However, this may be highly vary based on the many biotic and abiotic factors in grasslands. Hence, interactions between pathogens and their host in natural grasslands are complex. This review brings together a vast amount of information on fungal pathogens in grasslands and then discusses their role within and effects on grassland ecosystems. This also describes the pathogenic fungal communities in grasslands and discusses well-studied pathogenic fungal species reported on host grasses."
} | 4,709 |
26081633 | PMC4471561 | pmc | 2,191 | {
"abstract": "ABSTRACT Selection for phage resistance is a key driver of bacterial diversity and evolution, and phage-host interactions may therefore have strong influence on the genetic and functional dynamics of bacterial communities. In this study, we found that an important, but so far largely overlooked, determinant of the outcome of phage-bacterial encounters in the fish pathogen Vibrio anguillarum is bacterial cell-cell communication, known as quorum sensing. Specifically, V. anguillarum PF430-3 cells locked in the low-cell-density state (Δ vanT mutant) express high levels of the phage receptor OmpK, resulting in a high susceptibility to phage KVP40, but achieve protection from infection by enhanced biofilm formation. By contrast, cells locked in the high-cell-density state (Δ vanΟ mutant) are almost completely unsusceptible due to quorum-sensing-mediated downregulation of OmpK expression. The phenotypes of the two quorum-sensing mutant strains are accurately reflected in the behavior of wild-type V. anguillarum , which (i) displays increased OmpK expression in aggregated cells compared to free-living variants in the same culture, (ii) displays a clear inverse correlation between ompK mRNA levels and the concentration of N -acylhomoserine lactone quorum-sensing signals in the culture medium, and (iii) survives mainly by one of these two defense mechanisms, rather than by genetic mutation to phage resistance. Taken together, our results demonstrate that V. anguillarum employs quorum-sensing information to choose between two complementary antiphage defense strategies. Further, the prevalence of nonmutational defense mechanisms in strain PF430-3 suggests highly flexible adaptations to KVP40 phage infection pressure, possibly allowing the long-term coexistence of phage and host.",
"introduction": "INTRODUCTION Vibrio anguillarum is a marine pathogenic bacterium which causes vibriosis in numerous fish and shellfish species, leading to high mortalities and economic losses in aquaculture worldwide ( 1 ). The use of bacteriophages to control bacterial infections in aquaculture has gained increased attention in the past few years, and successful application of phages to reduce vibriosis-related mortality has been demonstrated ( 2 ). Development of a phage-based treatment is, however, challenged by the wide variety of antiphage defense strategies observed in bacterial hosts ( 3 ). There is clear evidence that genetic mutation, normally causing disruption or modification of phage receptors in the host membrane, plays an important role in preventing phage infection in some cases ( 4 – 8 ). Such genetic changes may impose a fitness cost on the host cell as disruption of phage receptors can reduce the uptake of certain substrates ( 9 – 11 ). Alternative defense mechanisms which do not involve mutational changes have been described and also play a role in V. anguillarum ( 12 ). Aggregate formation and production of exopolysaccharides were suggested to provide protection against infection in V. anguillarum strain PF430-3 ( 7 , 12 ). Recently, a more flexible protection mechanism was discovered in Escherichia coli , involving a temporary downregulation of phage receptor production in response to N -acyl- l -homoserine lactone (AHL) cell-cell signaling molecules ( 13 ). This mechanism is controlled by quorum sensing (QS), i.e., the ability of bacteria to regulate gene expression according to population density via the production and subsequent detection of extracellular signaling molecules ( 14 ). Little is still known about the mechanisms of phage protection in natural Vibrio communities. The universal outer membrane protein K (OmpK) has previously been shown to be the infection site for vibriophage KVP40, which infects more than eight Vibrio species, including V. anguillarum , V. parahaemolyticus , V. harveyi , and V. cholerae ( 15 , 16 ). Mutations in this protein have been reported in V. parahaemolyticus R4000 upon exposure to KVP40 ( 15 ) but were not detected in KVP40-amended cultures of V. anguillarum PF430-3 ( 7 , 12 ). Thus, other mechanisms for preventing infection by KVP40 in the Vibrio community may also be prevalent. AHL-mediated QS circuits have been identified in many Vibrio species, including V. anguillarum ( 14 , 17 , 18 ). V. anguillarum controls QS-regulated genes via the transcription factor VanT, which is activated in response to extracellular signaling molecules ( 19 , 20 ). At low autoinducer concentrations (i.e., low cell density), the response regulator VanO becomes activated by phosphorylation and represses the expression of VanT. At high cell densities, autoinducer concentrations increase and bind to membrane-bound receptors ( 19 , 20 ). At a certain threshold concentration, VanO is dephosphorylated and VanT expression is induced, allowing gene regulation within the QS regulon ( 19 , 20 ). Several N -acylhomoserine lactone autoinducers have been identified in stationary-phase V. anguillarum spent culture supernatant ( 21 ). As densities of bacterial populations vary from sparsely populated environments to highly dense populations in nutrient-rich environments, and phages require a bacterial host in order to multiply, phage predation pressure is not constant and may be expected to correlate with the density of the bacterial host population, among other factors. Thus, bacteria could potentially benefit from altering their antiphage strategies depending on the perceived population density, thereby minimizing the metabolic burden often associated with resistance by genetic mutation ( 3 , 9 , 22 , 23 ). In this study, we identified a potent antiphage defense mechanism in V. anguillarum and showed that different antiphage strategies prevail at different population densities. Under high-cell-density conditions, QS-mediated downregulation of the OmpK receptor reduced phage adsorption and rendered individual cells almost unsusceptible to phage infection. Under low-cell-density conditions, on the other hand, OmpK expression was unaffected by QS and the individual cells were fully susceptible to infection. However, under these conditions, we have shown in a previous study that aggregation of the cells prevents phage from reaching the OmpK receptor ( 7 , 12 ). In neither case was phage protection associated with ompK mutation. Overall, the study shows that QS controls the choice of antiphage defense strategy in the examined V. anguillarum strain PF430-3, suggesting the presence of dynamic, temporary adaptations to phage infection pressure, while still securing the ability to produce a functional OmpK receptor. In a phage therapy context, these results are highly relevant, as a combination of phage-based and anti-QS targeted treatments could enhance the efficiency of phage control of vibriosis.",
"discussion": "DISCUSSION Given the recent findings that bacteria may employ QS to reduce phage receptor expression under conditions of high infection risk ( 13 ), we aimed at exploring the role of QS in regulating susceptibility to the broad-host-range phage KVP40 in V. anguillarum strain PF430-3 through downregulation of the phage receptor OmpK. The reduced susceptibility to phage KVP40 in V. anguillarum strain PF430-3 after addition of cell-free supernatant or synthetic AHLs provided the first indications of a QS-regulated mechanism of phage protection. This was further supported by our subsequent studies of phage susceptibility in the two constructed V. anguillarum QS mutants, the Δ vanT and Δ vanO strains. These results showed that phage susceptibility and adsorption were reduced in the Δ vanO strain and enhanced in the Δ vanT strain relative to the wild type, directly confirming that QS played a key role in the protection against KVP40 infection. The >100-fold-higher phage production and 3-fold-lower bacterial density in cultures of the Δ vanT strain relative to the Δ vanO strain after phage addition thus emphasized that QS signaling in the high-cell-density phenotype mediated an efficient protection against phage infection. Measurements of the ompK expression further resolved the underlying mechanisms of QS-mediated phage protection. Thus, the significant (4-fold) reduction in ompK expression in the Δ vanO strain and the verification that an OmpK receptor-deficient mutant (the Δ ompK strain) was resistant to phage KVP40 provided direct evidence for QS-mediated downregulation of ompK expression as an important mechanism for protection against phage infection in V. anguillarum . Interestingly, our results also showed that downregulation of ompK expression was not the only QS-regulated phage defense mechanism in the investigated V. anguillarum strain. Cell aggregation and formation of a biofilm in response to phage addition in the wild-type strain suggested that the transformation from a free-living life form to growth in a biofilm was also a mechanism of protection against phage infection, as also supported by a previous study ( 12 ). The exact mechanism by which phages induce cell aggregation, however, remains to be discovered. While the production of extracellular polymers by the host to create a physical barrier against phage infection has been suggested previously ( 3 , 24 ), the current results suggest that this mechanism is QS controlled in V. anguillarum . Addition of phage KVP40 strongly stimulated cell aggregation and biofilm formation in the wild type and low-cell-density mutant (Δ vanT ), whereas no aggregation was observed in the high-cell-density mutant (Δ vanO ). Hence, the data suggest that cell aggregation and biofilm formation are an important phage defense mechanism at low cell densities where QS regulation of ompK expression is inefficient. Consequently, we show that V. anguillarum PF430-3 alternates between these two types of phage defense mechanisms and that QS regulates the choice of strategy by upregulating one mechanism (removal of OmpK receptor) while downregulating another mechanism (cell aggregation) at high cell densities. Whether the overall reduction in OmpK receptors under high-cell-density conditions results in a general decrease in the number of receptors per cell in the population, thus reducing the encounter rate between phages and OmpK receptors, and/or if OmpK downregulation generates a fraction of cells completely without receptors (i.e., resistant cells), is not known. However, the presence of turbid plaques in the Δ vanO mutant upon exposure to KVP40 in spot assays indicated that some of the cells were, in fact, temporarily fully resistant to the phage. The presence of two distinct phage defense mechanisms in wild-type cells was confirmed by the observation that ompK expression was reduced in free-living cells relative to cells embedded in aggregates. Together with the significant negative correlation between extracellular AHL concentration and ompK expression during growth of the wild-type strain in batch cultures, this demonstrated the dynamic nature of phage defense and emphasized that the obtained results were not restricted to the extreme phenotypes of the QS mutants. Interestingly, ompK expression was in fact enhanced in phage-amended wild-type and Δ vanT cultures relative to control cultures without phages. OmpK is a porin-like protein which has been suggested to be involved in bile salt resistance, as well as iron acquisition ( 25 ). We show here that OmpK also plays a role in the ability of V. anguillarum to use glucose-1-phosphate, glucose-6-phosphate, cis -aconitic acid, l -alaninamide, and l -alanine as growth substrates. We speculate therefore that upregulation of ompK in aggregated cells may be an adaptation to stimulate nutrient uptake in an aggregate environment where supply of specific nutrients may be limited or for enhancing the bile salt resistance of the cell aggregates inside the host. However, in the short-term competition experiment that we carried out, the Δ ompK mutant was able to reach the same density as the wild-type strain in a mixed culture. Further studies are needed to determine the physiological role(s) of OmpK and hence the cost of its repression or loss. We note that in the wild-type cultures of V. anguillarum PF430-3, AHLs accumulate as the culture grows to high cell densities, but they largely disappear later in stationary phase ( Fig. 5 ). This phenomenon has been observed previously in cultures of Yersinia pseudotuberculosis and Pseudomonas aeruginosa , grown in LB medium, and was found to be caused by pH-dependent lactonolysis ( 26 ). We found, however, that the pH of the marine broth (MB) cultures used here remained stable around 7.6 for at least 13 h (data not shown). Alternative explanations for the disappearance of the AHLs in stationary phase are the possible production of an AHL lactonase enzyme as reported in Bacillus spp. ( 27 ) or the uptake of AHLs for use as a source of energy, carbon, and nitrogen, as reported for Variovorax paradoxus ( 28 ). Additional studies are required to determine the mechanism responsible for AHL removal in V. anguillarum strain PF430-3. One surprising observation from the current study was that QS reduced biofilm formation (see Fig. S4 in the supplemental material). Biofilm formation is in many bacterial pathogens found to be upregulated by QS and stimulated at high cell density, promoting virulence ( 29 ). This has also been observed in V. anguillarum (strain NB10), where a low-cell-density mutant (Δ vanT strain) showed significantly lower biofilm formation than the wild-type strain ( 30 ). The reason for this contrasting effect of QS on biofilm formation in PF430-3 is not clear. V. anguillarum strain NB10 showed limited susceptibility to phage KVP40 and produced turbid plaques (data not shown), suggesting that KVP40 is not an important predator on that strain; hence, other antiphage strategies may be favored. VanT expression is known to regulate physiological responses required for survival and stress response ( 19 ), and in the investigated strain PF430-3, this seems to include shifting from aggregation to ompK downregulation in response to increased cell density. In addition, since total protease activity correlates with VanT expression in V. anguillarum strain NB10 ( 30 ), it may be speculated that at high cell densities, when VanT is fully expressed, VanT activates protease activity to promote the release of cells from aggregates, in a manner similar to the action of the VanT homologue HapR in V. cholerae , where QS also downregulates biofilm formation ( 31 , 32 ). By QS-mediated ompK gene regulation, aggregate-associated bacteria may thus have evolved a mechanism of detaching a subpopulation of free-living cells with reduced phage susceptibility which can survive in phage-dense environments, thus allowing further spreading of vibriosis infections. In any case, the results support previous indications of large differences in phage defense strategies among different strains of V. anguillarum ( 12 ) and emphasize the need for further exploring whether the mechanisms described here are a general phenomenon in bacteria or are limited to a subset of V. anguillarum strains. Phages are known to be key drivers of bacterial evolution by selecting for phage-resistant mutants, and it has been proposed that phage-host interactions lead to either an arms race dynamic of antagonistic host and phage coevolution or a fluctuating selection dynamic involving frequency-dependent selection for rare host and phage genotypes ( 33 , 34 ). In this study, however, we found evidence for an alternative to these scenarios, as the defense mechanisms identified do not involve mutational changes or complete elimination of phage-susceptible host cells. The described antiphage mechanisms in V. anguillarum thus represent more flexible adaptations to dynamic changes in phage and host densities, adding to the complexity of phage-host coevolutionary interactions and phage-driven genetic and phenotypic changes in bacterial populations. Since mutational changes often result in a loss of fitness for the host ( 9 , 10 ), the mechanisms described here represent a potential fitness advantage for the host. It may be speculated that the development of this temporary protection mechanism in V. anguillarum PF430-3 is related to the fact that the OmpK receptor is widely conserved among Vibrio and Photobacterium species and thus probably executes an important function(s) in the cell. It is likely, therefore, that mutations in ompK could have significantly negative effects on host fitness in natural habitats, in which case development of alternative phage defense strategies that leave the ompK gene intact would be of strong selective advantage. Further studies are needed, however, to confirm this hypothesis. Successful application of phage therapy in the treatment of vibriosis requires detailed knowledge of the phage-host interactions and the regulation of antiphage strategies in Vibrio . Our results add to the suite of known phage defense mechanisms and their regulation in marine bacteria and further emphasize that the complexity of phage-host interactions poses a challenge for future use of phages in disease control. On the other hand, the evidence that QS regulates phage receptor expression may potentially be used actively by quenching QS signaling, hence preventing receptor downregulation. In support of that, QS inhibitors have been shown to impede expression of virulence factors ( 35 ), and recently, the addition of modified T7 phages producing quorum-quenching enzymes has resulted in inhibition of biofilm formation, suggesting that the use of QS inhibitors may be a promising strategy in future antimicrobial therapy ( 36 )."
} | 4,460 |
39999126 | PMC11856355 | pmc | 2,192 | {
"abstract": "Coral reefs are threatened by climate change and chronic local human disturbances. Although some laboratory studies have investigated the effects of combined stressors, such as nutrient enrichment and heat stress, on growth and survival of early life stage corals, in situ studies remain limited. To assess the influence of multiple stressors on juvenile corals, we quantified densities of corals ≤ 5 cm at 18 forereef sites with different exposure levels to underlying chronic local human disturbance before, during, and after the 2015-2016 El Niño. This marine heatwave caused prolonged heat stress and devastating losses of coral cover on the shallow forereef’s of Kiritimati, in the central equatorial Pacific Ocean. Here, we enumerated a total of 7732 juvenile corals from 13 different families. Over 80% of corals were from four families: 70% from Agariciidae, Merulinidae, or Poritidae, which all have stress-tolerant life history strategies, and 11% from Acroporidae which has a competitive life-history strategy. Both local disturbance and heat stress were significantly negatively related to juvenile coral densities. Prior to the heatwave, juvenile densities were on average 72% lower at the most disturbed sites (7.2 ± 1.9 m -2 ) compared to the least disturbed ones (15.3 ± 3.8 m -2 ). Overall, juvenile corals had a lower bleaching prevalence and lower mortality during the heatwave when compared to their adult counterparts. Still, the heatwave resulted in the loss of half (49%) of all juvenile corals, with those corals with competitive or weedy life history strategies undergoing greater declines than stress-tolerant ones. Although juvenile coral densities increased slightly in the year following the heatwave, the effect was statistically non-significant. Our results highlight the influence of chronic local anthropogenic and marine heatwaves on juvenile coral densities.",
"introduction": "Introduction Coral reefs are increasingly impacted by the effects of climate change, which are overlaid on chronic regional and local scale anthropogenic pressures [ 1 , 2 ]. Recent marine heatwaves, notably the 2015-2016 El Niño, have caused mass coral bleaching and extensive mortality [ 3 – 5 ]. The persistence of coral reefs is dependent on the recovery of corals, which can be driven by coral recruitment and the population dynamics of juvenile corals [ 6 – 8 ]. But while heatwave impacts have been documented extensively for adult corals, there has been comparatively less research on the effects of heat stress on juvenile corals. Previous studies have demonstrated that the demographics of juvenile corals can strongly influence recovery trajectories [ 6 , 7 , 9 ], with surviving juvenile corals rising through size classes, with corresponding increases in brood stock and reproductive output [ 10 ], to repair stock-recruitment relationships disrupted by the loss of adult colonies [ 10 , 11 ]. Studies of long-term reef recovery following the 1998 El Niño in the Indian Ocean (Scott Reef, Western Australia and the Maldives) found that juvenile corals stimulated reef recovery within 10-12 years of the event [ 10 , 12 , 13 ], and were likely especially critical on these isolated reefs that are reliant on self-seeding [ 10 , 14 ]. Overall, however, given their importance for recovery dynamics, and the lack of studies, there is a need to better understand the effects of climate change-amplified heat stress, and its interplay with local anthropogenic disturbance, on juvenile corals. Although studies from several regions, including the Caribbean, Mediterranean, Japan, Thailand, Indonesia, and Australia [ 15 – 19 ], have shown that juvenile corals can have greater heat stress tolerance than their conspecific adults, the reasons underlying this difference remain unclear [ 15 – 17 ]. Mumby [ 15 ] hypothesized that this enhanced survival could be due to reduced irradiance levels due to their cryptic microhabitats or capacity for heterotrophic feeding to replace lost autotrophic nutrition during bleaching. Further research has suggested additional mechanisms based on properties such as being non-reproductive, which may allow for more energy invested into maintenance [ 18 ], and the relatively flat [ 20 ] and small colonies of juveniles, which may allow for faster elimination of toxic by-products by mass transfer [ 21 ]. In addition to exploring mechanisms for survival, a few studies have investigated the effects of heat stress on juvenile corals. Two experimental laboratory studies investigated the effects of short term heat stress and found that it resulted in sub-lethal stress and negative allometric growth scaling in Porites [ 22 , 23 ]. A third experiment, which examined heat stress as well as the influence of a simulated river plume and terrestrial runoff nutrient enrichment event on 4-month-old Acropora corals, found that while heat stress alone led to increases in growth and mortality, when both stressors were present juvenile mortality was reduced, suggesting that nutrient enrichment can lessen the effects of thermal stress [ 24 ]. Juvenile survival through heat stress [ 7 , 18 ], and contributions to reef recovery through increases in coral cover [ 7 ], vary substantially amongst coral species and life history types. For example, a study by Doropoulos and colleagues [ 7 ] on the Great Barrier Reef, Australia found that when reef recovery is characterized by increases in coral cover, brooders may not contribute substantially to reef recovery due to their small colony sizes [ 7 , 25 ] despite their other ‘weedy’ life history characteristics (e.g., rapid generation times, opportunistically colonizing recently disturbed habitats) [ 25 , 26 ]. Rather, corals such as Acropora , that exhibit a ‘competitive’ life history strategy, grow large colonies, and excel at colonizing [ 25 ] can contribute considerably to coral cover [ 7 ], and thus play a major role in reef recovery. In comparison, massive corals that have a ‘stress-tolerant’ life history strategy often survive disturbance events [ 25 ], but do not contribute appreciably to increases in coral cover because of their slow growth rates [ 7 ]. Here we aimed to advance understanding of how heat stress, when combined with local anthropogenic stressors, affects the densities of juvenile corals and how these impacts vary across corals with different life history strategies. To do so, we capitalized on a prolonged marine heatwave that occurred on Kiritimati (Christmas Island) during the 2015-2016 El Niño, which was overlaid on the atoll’s gradient of chronic local anthropogenic disturbance [ 27 , 28 ]. Kiritimati is geographically isolated, and thus is largely reliant on self-seeding for coral recruits [ 29 , 30 ]. We censused juvenile corals via video assays at 18 sites along the disturbance gradient before, during, and one year after the El Niño. This ecosystem-scale natural experiment allowed us to examine the impacts of prolonged heat stress on juvenile corals at sites exposed to different intensities of local human disturbance, and its effect on an isolated island’s initial reef recovery. With respect to juvenile coral densities around the atoll prior to the heatwave, we hypothesized that: ( i ) due to the lower overall coral cover and reef structural complexity [ 31 ] at sites with high disturbance these sites would also have reduced overall juvenile coral densities, and ( ii ) that this would include reduced densities of competitive and stress-tolerant juvenile corals, but that due to weedy coral’s propensity to colonize disturbed areas, juvenile corals with this life history strategy would have greater densities at more highly disturbed sites. We also hypothesized that the heatwave would result: ( iii ) in increased juvenile coral bleaching around the island, and that corals at sites with the highest local human disturbance would have the greatest prevalence of bleaching due to pre-existing stressors; ( iv ) in a significant decline in juvenile coral densities around the atoll due to the prolonged heat stress; and ( v ) that sites with the lowest local human disturbance would suffer the greatest juvenile coral losses, given that corals at high disturbance sites would have likely already declined substantially; and ( vi ) that mortality would vary amongst coral life history strategies, with the highest survival in stress-tolerant juvenile corals, the lowest survival in competitive corals because of their sensitivity to thermal stress, and the greatest density increases in the year following the heatwave in weedy corals because of their fast growth rates.",
"discussion": "Discussion Our study provides evidence that both chronic local anthropogenic disturbance and prolonged heat stress significantly reduce the density of juvenile corals on shallow forereefs. Before the heatwave, there was an inverse relationship between juvenile coral densities and the local disturbance gradient overall, but varying impacts of disturbance on different coral life histories. The heatwave significantly reduced juvenile coral densities, and for each life history strategy shifted the relationship between their density and local human disturbance. Juvenile coral densities appeared to be increasing (by > 50%) just one year after the heatwave, but the differences were not statistically significant. The significant negative effect of local human disturbance on juvenile coral densities we detected is in accordance with previous studies that have documented the negative effects single [ 24 , 46 , 47 ] and multiple [ 48 ] chronic anthropogenic stressors have on juvenile corals. On Kiritimati, this effect is believed to be the result of poor water quality, due to sewage and other pollution outflow onto the reef [ 27 , 28 , 49 ], and direct damage from dredging at some sites [ 27 ], which had substantially decreased overall coral cover and habitat complexity at the most disturbed sites prior to the heatwave [ 27 ]. We note that prior to the heatwave, turf algae and sediment cover were highest at the most disturbed sites, all of which can negatively impact corals of all life stages [ 22 , 50 , 51 ]. Comparatively, however, examining the pre-heatwave coral communities, the influence of human disturbance was greater on adults [ 27 ] than it was on juveniles (this study), although the mechanism for this difference remains unclear. The 2015-2016 El Niño caused significant mortality of juvenile corals on Kiritimati, but this effect was only evident at our end of heatwave expedition (i.e., after 10 months of heat stress). Juvenile corals have been known to survive a few months of heat stress [ 15 – 17 , 52 ] which is hypothesized to be due to their small and flat structure increasing mass transfer of toxic by-products [ 20 , 21 ] and being non-reproductive [ 18 ]. Despite the apparent resilience of juvenile corals to short term heat stress, our study and others demonstrate juvenile coral’s susceptibility to long term elevated temperature conditions, similar to adult colonies [ 4 , 19 , 27 , 53 ]. Studies in the Seychelles documented 48% or greater loss of juvenile corals following the 2015-2106 El Niño [ 48 , 54 ] and a study in the Maldives recorded similarly low densities as our study (2.7 ± 4.6 to 5.8 ± 12.3 individuals m -2 [ 13 ];), and although they did not have pre-heatwave data, as mentioned by Perry and Morgan [ 13 ], in the context of densities reported after the 1998 El Niño [ 55 , 56 ] these are very low. In West Sumatra Province, Indonesia, the decline in juvenile corals was only 26% from before the El Niño to two years after (2018) [ 19 ]. On Kiritimati, recovery of juvenile corals may have occurred, as evidenced by the ability of reefs on Moorea to recover despite multiple acute disturbances resulting in low juvenile coral densities [ 57 ], however subsequent monitoring has been limited due to COVID-19 related international travel bans from 2020 to 2023. A comparison between the heatwave impacts we documented here to those documented for adult corals by Baum et al. [ 27 ] on Kiritimati, reveals that the heatwave had a greater impact on adult corals, with a higher occurrence of bleaching and 1.8 fold greater mortality in adult colonies [ 27 ]. Before the 2015-2016 El Niño, Kiritimati juvenile corals as a whole were more frequently bleached than the adults [ 27 ], which could indicate that they were competing with post-settlement stressors as the escapement size, irrespective of life-history and habitat, is 5 cm [ 7 ]. However, during the heatwave, the bleaching frequency in adults surpassed that of the juveniles ( S4 Table ) [ 27 ], possibly due to juvenile corals’ hypothesized better resistance to bleaching [ 15 , 17 , 18 , 20 ]. In an Australian study, Álvarez-Noriega et al. [ 18 ] also found an overall difference in bleaching induced mortality between adults and juvenile corals, but that it was taxon dependent. This seems to be location dependent however, as we only found Goniastrea spp. to have the same trend on Kiritimati where the adults were more affected. The biggest difference was in the Merulinidae family, where in Australia the juveniles did worse than their adult counterparts, but on Kiritimati, the majority of the Merulinidae juveniles increased in density while the adults declined [ 27 ]. Small colonies of Oculina patagonica also had higher survivorship than their adult counterparts during a bleaching event in the Mediterranean [ 52 ], whereas in the inner Seychelles, Dajka and colleagues [ 48 ] documented 70% mortality of juveniles due to heat stress which was similar to the adult community loss on those reefs. It was expected that corals at sites exposed to very high local disturbance before the heatwave would have been the most stressed and therefore have the highest prevalence of bleaching, however, before the heatwave bleaching prevalence was statistically similar across the island. This may suggest that the local human disturbance does not greatly exceed or add to that of post-settlement stressors. Interestingly, while there was a large decline in juvenile corals by the late time period across the atoll, the sites that had some of the highest bleaching percentages (medium disturbed sites) at the early time point had the smallest decline (~21%). Additionally, although bleaching prevalence 10 months into the heatwave (late time period) was highest at the very high and low disturbed sites, these sites saw larger increases in density 1 year after the El Niño than medium sites which had lower bleaching levels. This demonstrates a mismatch between bleaching prevalence and mortality levels similar as to what has previously been documented for adult corals [ 27 ]. Mechanisms for this have been proposed for adult colonies (e.g., resistance to bleaching but then can only survive temporarily in a bleached state [ 58 , 59 ]; symbiont switching mid heat event [ 32 ]), but to our knowledge this pattern has not been documented in juvenile corals. It is possible that juveniles follow some of the same mechanisms as adults but with their different physical structure [ 20 ], they may have other mechanisms. Juvenile corals with a stress-tolerant life history were dominant across the atoll at all time points in this study. While for the entire coral community, Baum et al. [ 27 ] also found that stress-tolerant corals dominated Kiritimati’s highly disturbed reefs and all reefs after the 2015-2016 El Niño, prior to the event, competitive corals dominated the lowest disturbance sites. Dominance of stress-tolerant corals was also documented on reefs in the Maldives in the years immediately following both the 1998 [ 55 ] and 2016 El Niños [ 13 ]. In contrast, after heatwaves other reefs have been dominated by competitive and weedy type corals (e.g., Acropora and Pocillopora ) that colonize open space on reefs and grow rapidly [ 10 , 16 , 57 , 60 ]; however, the timescale varies globally, likely due to differences in community dynamics and severity of disturbances. Our study only extended one year past the El Niño and we detected no significant increase in weedy and competitive corals compared to stress-tolerant corals, similar to what was recorded on nearby Jarvis Island [ 61 ]. This might indicate that recovery will be suppressed until these corals can contribute significantly to recruitment, as documented on other reefs severely impacted by heat stress [ 7 , 10 , 12 , 13 , 62 ] compared to reefs less impacted by extreme heatwaves [ 57 , 63 ]. Thus, with more studies, it may be possible to roughly calculate recovery times using the severity of the disturbance and composition and density of surviving juvenile corals. Overall, our study demonstrates the negative impacts that a prolonged heatwave and localized chronic anthropogenic stress had on juvenile corals. This study also highlights differences in impacts amongst juvenile corals with different life history strategies. Given the importance of juvenile corals for reef recovery, continued studies of the impacts of these stressors, the mechanisms by which they affect juvenile corals, and ongoing monitoring of their contributions to reef recovery trajectories is needed."
} | 4,304 |
38956705 | PMC11218364 | pmc | 2,194 | {
"abstract": "Background Functional redundancy (FR) is widely present, but there is no consensus on its formation process and influencing factors. Taxonomically distinct microorganisms possessing genes for the same function in a community lead to within-community FR, and distinct assemblies of microorganisms in different communities playing the same functional roles are termed between-community FR. We proposed two formulas to respectively quantify the degree of functional redundancy within and between communities and analyzed the FR degrees of carbohydrate degradation functions in global environment samples using the genetic information of glycoside hydrolases (GHs) encoded by prokaryotes. Results Our results revealed that GHs are each encoded by multiple taxonomically distinct prokaryotes within a community, and the enzyme-encoding prokaryotes are further distinct between almost any community pairs. The within- and between-FR degrees are primarily affected by the alpha and beta community diversities, respectively, and are also affected by environmental factors (e.g., pH, temperature, and salinity). The FR degree of the prokaryotic community is determined by deterministic factors. Conclusions We conclude that the functional redundancy of GHs is a stabilized community characteristic. This study helps to determine the FR formation process and influencing factors and provides new insights into the relationships between prokaryotic community biodiversity and ecosystem functions. \n Video Abstract Supplementary Information The online version contains supplementary material available at 10.1186/s40168-024-01838-5.",
"conclusion": "Conclusions Functional redundancy widely exists in prokaryotic communities in different environments, e.g., soil, ocean, and human. However, it is unclear the degree of functional redundancy, its formation process, and influencing factors in various environments. Here, based on a large-scale analysis of prokaryotic community genetic information at a global scale, we proposed two methods to respectively quantify the degree of functional redundancy within and between communities and applied them to the analysis of carbohydrate degradation. Our results suggested that various glycoside hydrolase functions showed broad functional redundancy; that is, the same function was encoded by multiple taxonomically distinct prokaryotes within a community and by taxa that were highly distinct between communities. The degree of functional redundancy was highly affected by community diversity and environmental factors (e.g., pH, temperature, and salinity), for both within-community and between-community. The degree of functional redundancy is not determined by random factors but is highly deterministic. Functional redundancy should be regarded as a stabilized community characteristic as well as a manifestation of the community diversity of prokaryotes capable of a particular metabolic function. These results promote our understanding of the relationships between prokaryotic community biodiversity and ecosystem functions.",
"discussion": "Discussion Recent multitude studies on environments, from soil to ocean and to human gut, suggested that multiple taxonomically distinct microorganisms capable of performing similar metabolic functions coexist in prokaryotic communities, and FR appears to be a common aspect of many microbial systems [ 8 ]. Nevertheless, quantitative assessment of FR has not been attempted until recently [ 13 , 22 ], and they are only for within-community FR. Here, we proposed two quantitative approaches to assess two aspects of FR based on a large-scale analysis of prokaryotic community genetic information at a global scale. On the one hand, the FRI a value is used to quantify the diversity of prokaryotes encoding the same metabolic function within a community. On the other hand, the FRI b value is used to quantify the identity dissimilarities of taxa encoding the same function between communities. These two methods can be widely used to measure the degree of FR for the metabolic functions in various environmental types, helping to determine the FR formation process and influencing factors, and providing new insights into the relationships between prokaryotic community biodiversity and ecosystem functions. GHs are a large class of enzymes that are key to degrading carbohydrates and affecting the carbon cycle in nature. The major complex polysaccharide-degrading enzymes, such as cellulases, xylanases, and chitinases, have received the most attention [ 25 , 55 , 56 ]. We determined that GHs, not only the typical polysaccharide degradation functions (cellulases, xylanases, and chitinases) but also each of the 151 GH families, are widely functionally redundant within and between prokaryotic communities. That is, each type of GH function is encoded by multiple taxonomically distinct prokaryotes within a community and by highly differentiated taxa between communities. The prokaryotic species with similar genes (functional potentials) tend to compete with each other by occupying the same metabolic niche, and thus, this widely-present FR appears to be inconsistent with the expectation that species should occupy distinct metabolic niches. It is known that deterministic (e.g., environmental selection and biotic interactions) and stochastic (e.g., speciation, birth, death, and immigration) processes simultaneously remodel prokaryotic community assemblies [ 57 – 59 ]. Our recent research indicated that deterministic processes tend to play a predominant role in free-living and plant-associated environments, whereas stochastic processes are the primary contributors to animal-associated environments [ 60 ]. However, unlike community assembly, the assembly of functional genes within communities is predominantly governed by deterministic processes across all environments [ 60 ]. The conserved function profile is in sharp contrast to the highly diverse taxa encoding the same function, which highlights the decoupling of prokaryotic community function and taxonomic composition. Environmental conditions can predict community functional traits well, but predictions regarding their taxonomic compositions are notably weak. FR is generally regarded as an indicator of neutral assembly: within-community FR reflects the quasi-neutral coexistence of competitors within a metabolic niche, and between-community FR results from ecological drift between equivalent organisms [ 61 , 62 ]. However, we found that the degree of FR is not random, and the redundancy extents of various GH functions within or between communities are mainly determined by the environment types and functions. The FR degree in free-living communities is significantly higher than that in host-associated communities. Furthermore, differences in the FR degree of GHs in various environments, within or between communities, are largely due to the combined effects of community diversity and environmental factors such as pH, temperature, and salinity. In particular, the degrees of within-community FR are most strongly affected by alpha diversity, while the between-community FR degrees are most strongly influenced by beta diversity. All these results suggest that there is a highly positive correlation between FR degree and community diversity and that functions with a higher redundancy degree tend to have a stronger correlation. Hence, the degree of FR is a stable prokaryotic community characteristic that is highly deterministic and influenced by community diversity and environmental factors. Within-habitat heterogeneity is a driver of animal or plant diversity and is also associated with microbial communities [ 63 – 65 ]. The habitat heterogeneity of free-living communities is generally higher than that of host-associated communities, thus leading to higher community diversity [ 66 ]. Highly dispersal environments, such as water, have lower habitat heterogeneity than structural environments, such as soil, and thus also have lower community diversity [ 67 ]. High habitat heterogeneity is thought to provide many unique ecological niches, which help to reduce competition and thus preserve high community diversity [ 68 ]. Our results indicate that the FR of prokaryotic communities is closely related to their habitats, and the highly positive correlation between the FR degree and community diversity might actually reflect the effects of habitat heterogeneity. Ignoring the niche diversification brought about by habitat heterogeneity can lead to the illusion of functional “redundancy”, while those functionally “redundant” taxa may actually play an integral role. Thus, functional redundancy should be seen as a community characteristic as well as a manifestation of the community diversity of prokaryotes capable of a particular metabolic function."
} | 2,202 |
35324328 | PMC9060454 | pmc | 2,195 | {
"abstract": "Significance Soft materials can be toughened by creating dissipative mechanisms in stretchy matrixes. Yet using them over a wide range of temperatures requires dissipative mechanisms independent of stretch rate or temperature. We show that sacrificial covalent bonds in multiple network elastomers are most useful in toughening elastomers at high temperature and act synergistically with viscoelasticity at lower temperature. We do not attribute this toughening mechanism only to the scission of bonds during crack propagation but propose that the highly stretched network diluted in a stretchy matrix acts by simultaneously stiffening the elastomer and delaying the localization of bond scission and the propagation of a crack. Such a toughening mechanism has never been proposed for elastomers and should guide network design.",
"conclusion": "Conclusion. We have simultaneously quantified the fracture energy and the extent of molecular damage occurring near the fracture surfaces in a series of prenotched multiple network elastomers tested at different stretch rates and temperatures. We find that while bond scission and viscoelastic dissipation are roughly proportional to each other in simple networks, the introduction of a prestretched sacrificial network creates a clear threshold level of bond scission for the crack to propagate that is still active in the absence of viscoelastic dissipation. This threshold value of bond scission necessary for crack propagation in MNE increases with prestretch λ 0 and has an almost two orders of magnitude toughening effect at T ≫ T g where viscoelastic dissipation is minimal. We showed with mechanochemistry that the large increase in the threshold Γ c for MNE is correlated to the existence of a large damage zone (over hundreds of network mesh sizes) ahead of the propagating crack, where filler network bonds break. We propose that bond scission in MNE occurs in three stages as described in Fig. 5 : ( i ) mean-field bond scission of the filler network far from the crack tip, ( ii ) correlated bond scission of the filler network closer to the tip leading to increased stretchability of this highly damaged zone, and ( iii ) localized scission of the matrix bonds in this highly damaged region, conducting to crack propagation. The existence of a large minimum size of the damage zone in MNE is due to a rate-independent mechanism of stress delocalization that delays the correlated bond scission needed to grow a crack. The values of the local stretch λ where the transition between these mechanisms is observed vary with network structure and decrease with filler network prestretch λ 0 . There is however a hard limit to the accessible filler network prestretch given by the average chain length between cross-links, above which correlated filler network damage ( ii ) and matrix failure ( iii ) may occur at too close values of stretch, leading to a saturation of Γ c with increasing λ 0 . This mechanism of stress delocalization introduces a threshold for crack nucleation that effectively protects elastomers from crack propagation even at a high temperature. This threshold damage remains active at lower temperatures, where viscoelastic dissipation additionally contributes to toughness. These results may have important implications on the design of intrinsically tough elastomers. In conventionally filled elastomers where nanoparticle fillers may play a role of sacrificial network, highly fractal fillers that form a network at low volume fraction may be intrinsically more effective at delaying crack nucleation, a mechanism which could become more important at high temperature.",
"discussion": "Discussion Coupling of Network Damage and Fracture Energy. To rationalize the remarkable performance of the multiple network architecture in conditions of low viscoelasticity at high temperature, we turn to the analysis of bond scission in these materials. As mentioned above, when plotting the areal density of bond scission Σ ¯ = Σ / Σ LT as a function of a T . v crack , we observe qualitatively similar trends in the evolution of the damage, with a threshold value at low crack velocity, which increases for increasing prestretch ( Fig. 4 B , horizontal dashed lines) and a power-law increase at larger crack speed for increasing viscoelasticity ( Fig. 4 B , oblique dashed lines). Given these similar trends, it is tempting to try to directly correlate the measured fracture energy with the areal density of broken sacrificial bonds Σ , as shown in Fig. 4 C . If a Lake and Thomas argument holds for the energy dissipated per broken strand ( 29 ) and this is the only dissipative mechanism during crack propagation, one would expect a linear relation between Γ c and Σ . Yet, although both quantities appear qualitatively correlated, we fail to see a linear relation independent of viscoelasticity and material’s degree of prestretch. Over this linear scale, the fracture energy is found to increase instead sublinearly with the areal density of broken bonds, as Γ c ∼ Σ γ , with γ ≈ 0.6 − 0.7 . These observations call for a more refined interpretation of the couplings between bond scission and fracture energy. Threshold bond scission at high temperature. To rationalize the increase in the threshold fracture energy Γ c λ 0 , * with increasing prestretch λ 0 , we first focus on the observation in Fig. 4 A and B of a threshold level of sacrificial bond scission Σ Σ LT at low viscoelasticity, which increases strongly when increasing the prestretch, from Σ ≈ Σ LT SN for λ 0 = 1 , to Σ ≈ 10 2 ⋅ Σ LT DN for λ 0 ∼ 1.6 , and up to Σ ≈ 10 3 ⋅ Σ LT TN for λ 0 ∼ 2.3 . The increase in threshold damage accordingly implies that in the absence of additional dissipation mechanisms such as viscoelasticity, the threshold number of layers of broken bonds necessary for the crack to propagate increases strongly when diluting the filler network, i.e., bonds break much further away from the fracture plane. Even in absolute terms, Σ increases by a factor of 200 between SN and TN. Understanding this effect of the molecular architecture on crack propagation is nontrivial. Considering the highly disordered nature of the filler network, the propagation of a macroscopic fracture in this material amounts to the nucleation of a localized percolating damage pathway. The increase in the total damage necessary for the crack to propagate would thus imply a delayed nucleation of this percolating pathway. Since no or little viscoelastic dissipation is present under these conditions, the corresponding mechanism must depend on the local architecture of the material and on the redistribution of stress upon chain scission. It is first instructive to examine statistical models of failure in disordered networks, such as the so-called fiber bundle models ( 30 ), which provide an analogy with the disordered structure of the random filler network. A key parameter describing failure in these random networks is the redistribution of load following the rupture of a single strand (or fiber). In the first limit of local load sharing, the load following a rupture event is mainly redistributed to the neighboring strands, which leads to a rapid localization of damage through avalanches and ultimately failure ( Fig. 5 A ). In the opposite limit of equal load sharing, all of the intact strands share equally the load of a broken strand, delaying localization of damage and macroscopic failure ( Fig. 5 B , i ). These limits correspond to extremes with respect to the spatial correlations in stress redistributions, and it is possible to interpolate in between to account for elastic correlations following a rupture event ( 31 ), leading accordingly to a transition between the critical and the mean-field behavior or, in other words, between correlated and random bond scission. Fig. 5. Onset of crack propagation in MNE. The pictured mechanisms are at play under threshold conditions (no viscoelastic dissipation). ( A ) In a single network, chain rupture (yellow stars) leads to direct localization of the stress to the neighboring chains (red area), leading to correlated scission of adjacent chains (black arrows and yellow stars) and propagation of a localized crack. ( B ) In MNE, the failure mechanism is completely different. ( i ) Following chain rupture of the dilute filler network (yellow stars), stress is delocalized over a large area (red area and black arrows), through interactions between the filler network and the entangled matrix. Far away from the crack tip, this delocalization mechanism allows for random damage in the first network, with no interaction between chain scission events. ( ii ) Closer to the crack tip, bond scission starts to occur in a correlated fashion (smaller red area and black arrows), leading to the creation of an extended damage zone, with holes in the filler network and transfer of stress to the matrix. ( iii ) At the tip of this zone, the crack propagates through localized failure of this softened zone. Red stars represent the presence of damage in the filler network. Green stars characterize the localized rupture of the matrix network. Based on these general concepts, we can now describe in more detail our vision of the role played by the network structure in delaying crack nucleation in MNE. In a single network, as shown schematically in Fig. 5 A , the presence of a crack leads to stress concentration at the crack tip. Under threshold conditions, the load following a scission event is probably redistributed to the very neighboring strands, and bonds fracture in a correlated and localized way very close to the fracture surface ( 22 ), in qualitative agreement with the Lake and Thomas model ( 32 ). As pictured in Fig. 5 B , the mechanism of failure we propose for MNE is completely different. Far from the tip (regime i ), bond scission occurs randomly in the filler network for the shorter and more highly stretched strands; upon scission of a single highly stretched strand, the load is redistributed by entangled matrix chains over an extended volume of matrix and filler network (depending on dilution) and not simply on the neighboring filler network strand (in the spirit of the equal load sharing scheme described above). The matrix network(s) must play a major role in this delocalization mechanism. Indeed, as demonstrated by Millereau et al. ( 7 ), the reinforcement is not observed when the matrix network(s) is replaced by oligomers or solvent or when the volume fraction of filler network is too high. The presence of the unstretched and entangled matrix is thus essential to carry and redistribute the load upon scission of a sacrificial bond, and this stress transfer further away from the broken bond can only work if the filler is dilute and the matrix is unstretched or weakly stretched. In this regime, bond scission can be described by a mean-field model as proposed by Lavoie et al. ( 33 ) and Bacca et al. ( 34 ) in their damage models where the stretch relative to the undeformed state of the MNE must be the same for all networks. Hence, the probability of strand scission only depends on λ 0 λ . SI Appendix , Fig. S3 B and D show that the bulk value of λ 0 λ at propagation increases significantly with prestretch, and if the strain fields around the crack tip are similar, regime i will extend much further from the tip of the crack as λ 0 increases. Closer to the tip two other mechanisms become active. At some distance from the tip, the failure of the filler network bonds becomes correlated, causing the opening of large holes and extensive transfer of stress to the matrix with a pronounced softening (domain ii of Fig. 5 B ). The existence of this large-scale stress transfer mechanism from filler network to matrix network close to the crack tip for high values of λ 0 has recently been demonstrated for elastomers ( 15 ) and is well-documented for gels ( 10 , 11 , 14 ). Depending on boundary conditions, this softening can lead to an increase in stretch in the damaged zone which greatly increases the energy dissipated per broken bond ( 7 ). The formation of this softened damage zone is due to a transition from a mean-field situation where the probability of scission of a given strand is uniquely dependent on the stretch experienced by that strand to a correlated scission of filler network bonds where the probability of scission of a given strand is dependent on whether adjacent strands are broken or not. Such a non–mean-field scission presumably leads to the formation of larger-scale holes and cracks in MNE. It appears reasonable to assume that this transition from mean-field scission to correlated scission occurs above a certain value of stretch of the filler network λλ 0 . Hence, the more the filler network is prestretched, the lower the value of macroscopic experimental stretch where this transition can occur. Finally, the steady state propagation of the crack requires the localized failure of this softened zone as shown in scheme iii of Fig. 5 B . Regarding this final step, the hypothesis made by Brown ( 12 ) is that the crack will propagate when the strain energy stored in the damaged zone is sufficiently large to create a stress concentration at the tip of the crack (green stars in scheme iii of Fig. 5 B ), which is able to break the bonds of the damaged network (matrix and filler networks) ( 12 ). This hypothesis of failure due to a stress concentration in the highly damaged zone [inspired by the failure criterion of a plastic zone in a glassy polymer ( 35 , 36 )] is difficult for us to verify directly since we do not have access to the local strain energy or exact size of the highly damaged zone. However, the threshold values reported on Fig. 4 A and B suggest that the criterion of propagation is not directly proportional to the total areal density of broken sacrificial bonds ( SI Appendix , Fig. S10 ). This propagation criteria must be more complex, involving other dissipative or damage mechanisms very close to the crack plane, as described above. The difference between DN and TN suggests that filler network scission in DN is more efficient at dissipating energy than in the TN. Such complex multiscale bond scission mechanisms are in principle only strain dependent and inherently strain rate independent. In the absence of viscoelasticity slowing down the crack (threshold conditions), they would result in a fast propagation, once the criterion of propagation outlined above is met. While mechanism iii has to be by definition very localized and requires the failure of both filler and matrix strands, regime ii and i only involve the failure of the filler network. Our mechanochemistry data show that, at the propagation point, damage occurs over a larger and larger volume as the degree of prestretch of the filler network and the stretch rate increase ( Figs. 4 B and 5 B ). This is a key result of our investigation showing that the complex process of delay in correlated bond scission and transfer of the stress to the matrix is able to create a much larger damage zone before the crack can propagate. We can interpret this effect as an interplay between mean-field scission far from the tip, creating a large damage zone for large λ 0 (regime i ) and delayed propagation of the crack through a highly damaged zone, where the stress is transferred to the matrix (regime ii and iii ). Because of the complexity of the multiscale process, predicting the onset of regime ii and of regime iii at the crack tip as a function of λ 0 remains a challenge and requires a molecular criterion related to the network architecture. Recent simulation studies may provide hints on the nature of such criteria ( 37 , 38 ). Coupling of sacrificial bond scission with viscoelasticity and macroscopic deformation. We can now address the role played by viscoelasticity in the increase in fracture energy Γ c and its coupling to sacrificial bond scission. For single networks ( λ 0 = 1), viscoelastic dissipation can couple to bond scission through macroscopic strains at the crack tip ( 22 ). To probe more closely this coupling in this series of MNE, we plot in Fig. 6 A the evolution of the areal density of broken chains Σ as a function of the macroscopic strain at break λ c for notched samples having all the same initial notch length. For a given material and notch length, Σ increases with λ c , i.e., with increasing viscoelasticity, and for a given λ c , Σ increases with increasing prestretch (comparing blue, red and black points). Interestingly, focusing on the result of the double network (red points), sacrificial bond scission appears first independent of λ c and then clearly increases for λ c > 2 . Fig. 6. Coupling of chain scission with viscoelastic dissipation and macroscopic deformation. ( A ) Areal density of broken chains Σ as a function of strain at break λ c , giving an estimation of the relative damage zone width during propagation. ( B ) Areal density of broken chains Σ as a function of the effective filler network strain at break λ c λ 0 . ( C ) Schematic illustrating the coupling of bond scission with macroscopic deformation. At low viscoelasticity, bond scission reaches a threshold value associated with damage percolation in the filler network (regime 1). At high viscoelasticity, two regimes can be observed, depending on the effective stretch on the filler network. When this effective stretch λ c λ 0 is much smaller than the limiting extensibility λ m , bond scission and viscoelastic dissipation are decoupled, leading to a purely additive contribution (regime 2). In the limit where λ c λ 0 ≈ λ m , additional bond scission occurs due to coupling with the macroscopic deformation field in the material (regime 3). It is then interesting to rescale the data, following similar ideas motivating Fig. 2 D , by plotting in Fig. 6 B the areal density of broken sacrificial bonds Σ , as a function of λ 0 λ c , the effective stretch of the filler network when the crack propagates. This normalization leads to a clear collapse of the data for the three levels of prestretch, from which we can identify three successive regimes. In regime 1, only observed for λ 0 = 1, viscoelasticity is coupled with localized bond scission and controls the crack tip stretch. In regime 2 mainly observed for λ 0 = 1.6 far from T g , Γ c increases ( Fig. 2 D ) but Σ stays constant ( Fig. 6 B ). Viscoelastic dissipation is weakly coupled to bond scission, with Σ ≈ cst ≈ 8 × 10 18 strands⋅m −2 controlled by the complex mechanism described above ( Fig. 5 ) and viscoelasticity acting as an additive dissipative mechanism without much influence on the crack tip strains. Regime 3 kicks in when the filler network chains become highly stretched, for which we observe a strong exponential coupling with macroscopic deformation with Σ ∼ ⋅ e α ⋅ λ c λ 0 for λ c λ 0 > 3.2 , with α = 1.75 . The upper axis shows the same data as a function of λ 0 λ c / λ max , the effective strain normalized by the average limiting extensibility of the sacrificial chains λ max ∼ 5.1 ( SI Appendix ). The observed transition between these two regimes occurs for λ c λ 0 ∼ 0.6 ⋅ λ max , suggesting that this change of regime in sacrificial bond scission occurs when filler network chains approach their maximal extensibility. In summary, under conditions of low viscoelasticity, fracture propagation is limited as discussed above, by the propagation of a crack in the matrix network, leading to a threshold amount of filler network bond scission before propagation can occur ( Fig. 4 B and 5 B ). This threshold level is highly dependent on the network prestretch and controls also the threshold fracture energy. For each material, increasing viscoelasticity leads to an increase in the bulk strain at break λ c and the strains at the crack tip. However, the situation differs for the three types of network. In single networks, chain rupture leads to direct localization, correlated bond scission, and catastrophic failure ( Fig. 5 A ), and most probably there is no well-defined softened zone. In this case, viscoelasticity increases the required energy release rate to propagate the crack at a certain speed and increased bond scission is a consequence of the higher crack tip strains ( 22 ). Because of this localization of rupture, no mechanism prevents the crack from moving even very slowly and threshold values of Σ / Σ LT and Γ c λ 0 , * are very low. In MNE, when the effective bulk strain at break on the filler network remains small compared to its limiting extensibility, i.e., λ 0 λ c < 0.6 λ max , the material forms a highly damaged zone at the crack tip. In this regime, fracture energy can then be simply expressed as the sum of a constant contribution due to bond scission at the damage percolation threshold and a strain rate-dependent viscoelastic contribution ( Fig. 6 C , λ 0 λ c ≪ λ m ). If the effective strains on the filler network become larger, i.e., λ 0 λ c > 0.6 λ max , the local probability of bond scission at the crack tip increases strongly, leading to an increase in the overall amount of bond scission Σ / Σ SN for increasing viscoelasticity and increasing strains ( Fig. 6 C , λ 0 λ c ≈ λ m ). However, the increase in sacrificial bond scission in this second regime appears more as a consequence of the increase in viscoelastic dissipation through the increase in local strains at the crack tip, rather than the cause for the reinforcement of the network when increasing viscoelasticity. Indeed, as evidenced in Fig. 2 D , no such cross-over is observed when plotting the normalized fracture energy Γ c λ 0 2 as a function of the effective strain λ c λ 0 . Variation of threshold fracture energy with prestretch. These observations pose the question of the existence of an optimal value of initial prestretch of the filler network to toughen the elastomer in the threshold regime at low viscoelasticity. In particular, when the strands of the filler network are close to their limiting extensibility already under static conditions, one may ask whether such a sacrificial network can still effectively delay crack propagation through the mechanism described in Fig. 5 . Fig. 7 shows the threshold fracture energy Γ c λ 0 , * as a function of prestretch for a series of PEA-based MNE (details of synthesis and mechanical properties in SI Appendix , Fig. S5 and ref. 7 ). Given the value of T g at −18 °C , this situation is close to threshold conditions. Although no damage data are available for this series, it is clear that there appears to be a threshold prestretch λ 0 ≈ 2 , above which Γ c increases more slowly. Fig. 7. Variation of the fracture energy as a function of degree of prestretch. Results are obtained for solvent-synthetized PEA materials, fractured close to threshold conditions, at stretch rate λ ˙ = 4 × 10 − 3 s −1 and temperature T = 25 ° C . Red dashed lines and gray areas highlight two successive regimes of , respective strong and weak increases of Γ c with λ 0 . Following Fig. 5 , the creation of the energy dissipating damage zone is due to the delay in correlated bond breakage which initially increases with dilution as seen in the first regime of Fig. 7 , for λ 0 ≤ 2 . However, when the filler network becomes close to its maximum stretch ( λ 0 ≥ 2 ), the transition from regime i to ii and ii to iii must occur at increasingly lower values of macroscopic stretch, which causes the saturation observed in Fig. 7 . This saturation is here observed at λ 0 ≈ 2 , for which the effective critical stretch at break on the filler network is λ 0 λ c ≈ 3.3 , approaching its limiting extensibility λ limit = 5.1 ( SI Appendix , Fig. S7 ) ( 7 ). Conclusion. We have simultaneously quantified the fracture energy and the extent of molecular damage occurring near the fracture surfaces in a series of prenotched multiple network elastomers tested at different stretch rates and temperatures. We find that while bond scission and viscoelastic dissipation are roughly proportional to each other in simple networks, the introduction of a prestretched sacrificial network creates a clear threshold level of bond scission for the crack to propagate that is still active in the absence of viscoelastic dissipation. This threshold value of bond scission necessary for crack propagation in MNE increases with prestretch λ 0 and has an almost two orders of magnitude toughening effect at T ≫ T g where viscoelastic dissipation is minimal. We showed with mechanochemistry that the large increase in the threshold Γ c for MNE is correlated to the existence of a large damage zone (over hundreds of network mesh sizes) ahead of the propagating crack, where filler network bonds break. We propose that bond scission in MNE occurs in three stages as described in Fig. 5 : ( i ) mean-field bond scission of the filler network far from the crack tip, ( ii ) correlated bond scission of the filler network closer to the tip leading to increased stretchability of this highly damaged zone, and ( iii ) localized scission of the matrix bonds in this highly damaged region, conducting to crack propagation. The existence of a large minimum size of the damage zone in MNE is due to a rate-independent mechanism of stress delocalization that delays the correlated bond scission needed to grow a crack. The values of the local stretch λ where the transition between these mechanisms is observed vary with network structure and decrease with filler network prestretch λ 0 . There is however a hard limit to the accessible filler network prestretch given by the average chain length between cross-links, above which correlated filler network damage ( ii ) and matrix failure ( iii ) may occur at too close values of stretch, leading to a saturation of Γ c with increasing λ 0 . This mechanism of stress delocalization introduces a threshold for crack nucleation that effectively protects elastomers from crack propagation even at a high temperature. This threshold damage remains active at lower temperatures, where viscoelastic dissipation additionally contributes to toughness. These results may have important implications on the design of intrinsically tough elastomers. In conventionally filled elastomers where nanoparticle fillers may play a role of sacrificial network, highly fractal fillers that form a network at low volume fraction may be intrinsically more effective at delaying crack nucleation, a mechanism which could become more important at high temperature."
} | 6,679 |
27105725 | null | s2 | 2,197 | {
"abstract": "There has been an increase in the scale and frequency of coral bleaching around the world due mainly to changes in sea temperature. This may occur at large scales, often resulting in significant decline in coral coverage. In order to understand the molecular and cellular basis of the ever-increasing incidence of coral bleaching, we have undertaken a comparative proteomic approach with the endangered Caribbean coral Acropora palmata. Using a proteomic tandem mass spectrometry approach, we identified 285 and 321 expressed protein signatures in bleached and unbleached A. palmata colonies, respectively, in southwestern Puerto Rico. Overall the expression level of 38 key proteins was significantly different between bleached and unbleached corals. A wide range of proteins was detected and categorized, including transcription factors involved mainly in heat stress/UV responses, immunity, apoptosis, biomineralization, the cytoskeleton, and endo-exophagocytosis. The results suggest that for bleached A. palmata, there was an induced differential protein expression response compared with those colonies that did not bleach under the same environmental conditions."
} | 292 |
32624976 | PMC6999068 | pmc | 2,198 | {
"abstract": "Abstract Kinetics generally describes bio‐(chemical) reaction rates in dependence on substrate concentrations. Kinetics for microalgae is often adapted from heterotrophs and lacks mechanistic foundation, e.g. for light harvesting. Using and understanding kinetic equations as the representation of intracellular mechanisms is essential for reasonable comparisons and simulations of growth behavior. Summarizing growth kinetics in one equation does not yield reliable models. Piecewise linear or rational functions may mimic photosynthesis irradiance response curves, but fail to represent the mechanisms. Our modeling approach for photoautotrophic growth comprises physical and kinetic modules with mechanistic foundation extracted from the literature. Splitting the light submodel into the modules for light distribution, light absorption, and photosynthetic sugar production with independent parameters allows the transfer of kinetics between different reactor designs. The consecutive anabolism depends among others on nutrient concentrations. The nutrient uptake kinetics largely impacts carbon partitioning in the reviewed stoichiometry range of cellular constituents. Consecutive metabolic steps mask each other and demand a maximum value understandable as the minimum principle of growth. These fundamental modules need to be clearly distinguished, but may be modified or extended based on process conditions and progress in research. First, discussion of kinetics helps to understand the physiological situation, for which ranges of parameter values are given. Second, kinetics should be used for photobioreactor design, but also for gassing and nutrient optimization. Numerous examples are given for both aspects. Finally, measuring kinetics more comprehensively and precisely will help in improved process development.",
"conclusion": "5 CONCLUDING REMARKS Kinetics forms the interface between cell physiology and conditions inside the reactor. The rational design of reactors, media, and processes can be based on these cell/reactor interactions. Microalgal intracellular processes connect to extracellularly measurable variables as projected by kinetics. Measuring kinetics of microalgae include specific issues such as light absorption and light gradients. Growth is a mechanistic function of the local light intensity based on the model by Han 19 and our physiological interpretation of macroscopically measurable parameters. To deduce the mean growth rate of the whole reactor, growth needs integration along the light path. Growth integration induces a deformation on measurable PI‐curves, a problem that might have hindered setting up mechanistic kinetics from measurements in the past. Numerous studies have been performed to measure light and CO 2 ‐ as well as other uptake kinetics and to deduce kinetics from physiological assumptions. Recording of kinetic data has not yet been completed, but a lot of physiological knowledge is available to set up kinetics based on biological facts and mechanisms. One step of implementing mechanisms shown in this review is to distinguish between light absorption and energy usage from the absorbed photons. Combining the set of light kinetics with assumptions on carbon annotation leads to an observable macromolecular stoichiometry of the cells. However, in practice interpretation often stops on the formal level of description. Especially couplings between different kinetics such as light absorptions and CO 2 ‐uptake would give hints to possible process improvement. In this review, we want to show that precise assessing of kinetics has a great potential to improve and accelerate reactor and process design. Besides given examples, other kinetics will be developed in more mechanistic precision to form a set of kinetics that copes with the complexity of the cell to a reasonable level.",
"introduction": "1 INTRODUCTION Photosynthesis is the major biochemical process to drive life on earth. Heterotrophic life only functions by respiration of oxygen supplied by phototrophs. Microalgae — next to terrestrial plants — contribute substantially to the oxygen evolution. The amount of oxygen produced by microalgae is remarkable due to their high photosynthetic efficiency. Efficient light use gives microalgae great potential for applications in pharmaceutical, cosmetic, food, feed, and chemical industries 1 . Designing microalgal production plants is an emerging field developing more and more into the direction of rational process design. For heterotrophic bio‐processes, the rational basis of process design is well elaborated. For photo‐bioprocesses, mechanistic knowledge is described in the literature, but not straightforwardly applied on process development. For process development, production plants can be hierarchically structured into a plant/reactor level, the level of the microalgal population (suspension), and the level of the intracellular metabolic network 2 . Kinetics on the population level links the reactor and the cell level. To represent valid connections the kinetics has to be as rational as possible. The structure of each kinetic equation should reflect the structure of the real system. Unknown kinetic parameters should at least have a clear physiological meaning. Further, the parameters have to be independent from scale 2 . Lee et al. 3 and Béchet et al. 4 recently reviewed kinetic models for microalgal growth. A short summary of different mathematical descriptions including examples is given in Table 1 . Next to classical kinetic models of Monod 5 , Blackman 6 , and Andrews 7 , new expressions have been proposed in the last decades especially for light kinetics 8 . Classical kinetics is based on mass action law and reaction kinetics, and uses enzyme kinetics as template. Both do not consider the physical step of light absorbance depending on chlorophyll content in the chloroplast. Other mathematical attempts are empiric or semi‐mechanistic 9 . Light limitation and light inhibition are completely different processes on different time scales, but are formulated with only one term in the kinetics, e.g. Steele 10 . This can be overcome with kinetics defined piecewise, where the classic piecewise linear photosynthesis irradiance response curve (PI‐curve) is one example. Most measured PI‐curves for adapted cultures in photo‐bioreactors exhibit a distinct saturation range before reaching inhibition. The broad range of saturation may be due to a limiting step downstream from sugar production in the metabolism, which is considered by Blackman kinetics 6 . The model according to Han is one of the few being directly derived from reaction kinetics of photosynthetic units 8 . This will be derived later in this review (see Section 2.1 ). Table 1 Overview of the structure of commonly used kinetics Mathematical approach Examples Advantages Disadvantages References Rational functions (different exponents in numerator and denominator) Andrews, Monod, Haldane Based on reaction or enzyme kinetics No specific consideration of phototrophic light processing \n 22 , 75 , 76 \n Rational function with mechanistic meaning in photosynthesis (formally as Monod) Han Based on chlorophyll reaction kinetics PSU and time constants not directly measurable \n 17 , 19 , 77 , 78 [see also this review] Special functions (exponential, hyperbolic tangent) Steele (exp), Jassby & Platt (tanh), van Oorschot (exp) Easy to use with some flexibility No claim to mechanistic background, if then thermodynamics \n 10 , 14 , 79 \n Piecewise defined functions Classical PI‐curve, Blackman Clear discrimination between dominant processes over light range Numerical point of discontinuity, over‐simplification in transition zones \n 24 , 80 [see also this review] Multiplication of different kinetic factors/equations Commonly applied to combination of different influences Simple to use even in complex environment Ignores intracellular stoichiometry \n 56 \n John Wiley & Sons, Ltd. Several aspects impede finding and validating kinetics for photo‐bioprocesses. The first one is the temporal aspect. Photo‐acclimation ranges from fractions of a second to hours or days 11 , 12 . The differences in time scales prohibit the transfer of short‐term measurements to outdoor cultivations. Another aspect is the spatial characteristic of light gradients. The gradients make the direct application of kinetics possible for only one light intensity. The necessary light integration over the reactor volume and the consequences for the appearance of the kinetics will be discussed later in this review. The third aspect is the variability of the cells. Cellular composition varies according to heterotrophic kinetics depending on nutrients in the medium. Substrates for heterotrophic pathways are carbohydrates formed in the chloroplast. The chloroplast performs light absorption and photosynthesis partially independent from the heterotrophic pathways of the cell. This variability of cellular reactions, time constants of reactions, and acclimation as well as light gradients are indispensable for the simulation of microalgal physiology. Only mechanistic models based on physiological understanding of the cell yield reliable predictions when applied to other process conditions later on. Well formulated and reasonably simplified kinetics can then be coupled to hydrodynamics and light attenuation in one model 13 . Such models help to analyze and optimize cultivation systems or to design new reactors and microalgae production plants. We will show that only one kinetic equation for growth as a function of light is not enough to consistently represent the cell's behavior. Building up on reactor conditions and intracellular stoichiometry, separate equations for photon absorbance and growth lead to a consistent and scale independent system of kinetics. The necessary biological knowledge for the kinetic equations is in many cases already available or can be retrieved in small scale experiments. Based on this kinetics, we will show how powerful such an approach can be for reactor and medium design as well as process development in general. The presented approach is not comprehensive for the diversity of technical and biological situations, but will encourage going further into the direction of more knowledge driven rational process development for photo‐bioprocesses."
} | 2,589 |
28154485 | PMC5287160 | pmc | 2,199 | {
"abstract": "In this study, we collected rhizosphere soils and root samples from a post-mining area and a natural forest area in Jecheon, Korea. We extracted spores of arbuscular mycorrhizal fungi (AMF) from rhizospheres, and then examined the sequences of 18S rDNA genes of the AMF from the collected roots of plants. We compared the AMF communities in the post-mining area and the natural forest area by sequence analysis of the AMF spores from soils and of the AMF clones from roots. Consequently, we confirmed that the structure of AMF communities varied between the post-mining area and the natural forest area and showed significant relationship with heavy metal contents in soils. These results suggest that heavy metal contamination by mining activity significantly affects the AMF community structure.",
"discussion": "RESULTS AND DISCUSSION Soil chemical analysis for heavy metals (As, Pb, Cd, Ni, and Zn) showed that the concentrations of As and Zn were significantly higher in the abandoned mines than in the natural forest ( Table 1 ). Pb was not detected in both the soils collected in this study, and Cd was detected in the soil at both sites but showed no significant difference between locations. Morphological and molecular analysis of spores in rhizosphere soils showed that 8 species of 7 genera were found in the post-mining area, and 6 species of 5 genera of AMF were found in the natural forest area ( Table 2 , Fig. 1 ). Relative abundance showed that Claroideoglomus etunicatum was the most dominant species in the post-mining area and that Rhizophagus irregularis was dominant in the natural forest area ( Table 2 ). Acaulospora longula and Ambispora leptoticha were found only in the mine area. The total spore numbers were higher in the mining area than those in the natural forests. Shannon's index and species evenness were also higher in the mining area than that in the natural forest but were not statistically significant. Correlation analysis of heavy metal concentration with relative abundance of spores showed that A. longula has a strong positive relationship with the heavy metals As and Zn, which were significantly higher in the mining area ( Table 3 ). The accumulation of heavy metals significantly influenced the AMF spore communities in the soil for a long period. Mycorrhizal root colonization rates were significantly higher in the mine area (81.33 ± 2.67%) than in the natural forest area (61.67 ± 2.85) at p < 0.05, suggesting that significantly high concentrations of heavy metals affect mycorrhizal symbiosis with host plants at the mining sites. Cloning results for AMF-colonizing roots allowed identification of 7 OTUs in the mine area and 5 OTUs in the species of the forest area ( Table 4 , Fig. 2 ). Relative abundance showed that Glo6 was dominant in both the mine and the natural forest areas. Glo2, Glo5, and Glo7 were found only in the mine area, and Glo4 was found only in the forest area. In this study, more diverse AMF sequence types were found in the roots of plants in the mining area with high concentration of heavy metals. However, some previous studies showed that OTU number and root colonization rates were decreased with increasing concentrations of heavy metals [ 23 ]. Thus, it is considered that diversity of AMF could be increased or decreased according to the intensity of the heavy metals which act as a disturbance. Shannon indices were not significantly different between the two areas ( Table 4 ), and correlation analysis showed no significant relationship between the relative abundances of AMF species and heavy metal concentrations. Significantly, higher heavy metal concentrations, especially of Zn, might be the reason for the higher colonization rates in the mining area. It has been reported that high accumulation of Zn stressed the host plants and increased AMF colonization in their roots [ 24 ]. The reason might be that though some AMF species are sensitive to heavy metals, other species are tolerant of high heavy metal concentration in soil [ 25 ]. Previous studies show that AMF species belonging to Claroideoglomus are often tolerant to heavy metals [ 26 ], and the results of this study showed that species of Claroideoglomus were significantly more in the mine area. Additionally, A. longula showed a strong positive correlation with As and Zn and is consistent with previous results [ 27 ] that the frequency of A. longula is higher in higher concentrations of Zn. In addition, A. leptoticha , which was found only in the mining area in this study, was also frequently found in contaminated soil containing Zn [ 28 ]. However it have been reported that AMF communities in soil contaminated by heavy metals more affected by other chemicals in the soil than heavy metals [ 29 ]. Thus, the diversity of AMF communities in abandoned mine area should be considered with factors of the soil environments as well as the intensity of the disturbance. The species mainly found in abandoned mines with a long period of ecological disturbance belonged to Glomaceae [ 23 30 ]. Previous studies showed that the Glomaceae species were dominant under stress conditions such as ecological disturbances, suggesting that Glomaceae species are better adapted to disturbed environments than other species [ 31 32 ]. In this study, AMF species, C. etunicatum , R. irregularis , R. intraradices in Glomaceae were species having a high relative abundance common to both abandoned and natural forest area. The result was consistent with previous studies of heavy metal contaminated areas [ 33 ], suggesting that the emergence of these species would be the results of strong selection pressure in the settlement process of plants than the intensity of the disturbance. In conclusion, this study showed that the anthropogenic disturbance of mining activities affects the AMF communities."
} | 1,465 |
30613813 | PMC6312631 | pmc | 2,200 | {
"abstract": "Aluminum (Al) is one of the most widely\nused metals for industry and household applications, but its longevity\nis limited by its tendency for corrosion. In this work, we report\na facile method to fabricate superhydrophobic Al surfaces that have\nexcellent anti-corrosion effect. The surface is obtained by etching\nAl in CuCl 2 solution to form the micro–nano-pit\nsurface texture followed by lowering its surface energy in an aqueous\nethanol solution of stearic acid. The superhydrophobic Al surfaces\nshow water contact angles as high as 165°. Electrochemical tests\ndemonstrate that the corrosion rate of the Al surface drops by 94.5%\nafter the superhydrophobic modification (corrosion current density\nlowers from 1.11 × 10 –4 to 6.10 × 10 –6 A cm –2 ). We also show that the\nsuperhydrophobic surface will protect the Al from corrosion even under\na very harsh environment. In addition, our method is scalable and\nthe superhydrophobic surfaces exhibit excellent flexible and reparable\nproperties. This anti-corrosive superhydrophobic Al surface will prolong\nAl in its broad usage.",
"conclusion": "Conclusions In summary, superhydrophobic Al surfaces are fabricated by a simple\napproach, first etching in CuCl 2 solution to form a micro–nano-pits\nsurface texture and then lowering its surface energy in an aqueous\nethanol solution of stearic acid. The modified Al surfaces show water\ncontact angles as high as 165°. Electrochemical tests demonstrate\nthat the CR of the Al surface drops by 94.5% after these treatments\n(corrosion current density lowers from 1.11 × 10 –4 to 6.10 × 10 –6 A cm –2 ).\nWe also show that the superhydrophobic surface will protect the Al\nfrom corrosion even under a very harsh environment. In addition, our\nmethod is scalable and the superhydrophobic surfaces exhibit excellent\nflexible and reparable properties. This anti-corrosive superhydrophobic\nAl surface will prolong Al in its broad usage.",
"introduction": "Introduction Throughout\nthe long-term evolution in nature, many organisms developed\nvarious characteristics with amazing properties. For instance, one\nsuch property is the superhydrophobicity of lotus leaves and water\nstrider legs, which describes the nonwetting characteristics of material\nsurfaces. 1 − 3 A superhydrophobic\nsurface, normally defined as a surface with a water contact angle\n(an angle that a liquid makes with a solid) larger than 150°,\nrepels water to form near spherical shapes that do not adhere to them\nbut instead bounce off, which has attracted intensive attention because\nof its excellent prospects in the fields of self-cleaning, anti-icing,\nanti-corrosion, and microfluidic devices. 4 − 14 As a light\nmetal, aluminum (Al) has widely used in general industry as well as\nin household activities thanks to its excellent heat and electrical\nconductivities, natural availability, and high mechanical properties. 15 However, these applications are seriously limited\nbecause of the easy corrosion or deterioration of Al surfaces. With\nthe extensive nano- and micro-scale surface textures and a layer of\nair trapped among these structures, a superhydrophobic layer can repel\nthe water and moisture from the surface, which results in a dry and\nclean surface. 4 , 16 Consequently, superhydrophobic\nsurfaces can slow down the corrosion or deterioration process on metal\nsurfaces. 7 , 8 , 17 It is therefore\nhighly desirable to create a protective superhydrophobic Al surface\nwith large area by facile and cost-effective approaches. In this work,\nwe report an easy method to produce superhydrophobic Al surfaces by\netching in CuCl 2 solution to form micro–nano-pit\nsurface textures followed by lowering its surface energy in an aqueous\nethanol solution of stearic acid. The fabricated superhydrophobic\nAl surfaces exhibit excellent properties of anticorrosion, flexibility,\nand reparability, which have significance to prolong Al materials\nin its broad usage.",
"discussion": "Results and Discussion The Al superhydrophobic surfaces\nare synthesized by two steps: first roughing the surface of a cleaned\nAl foil by chemical etching in CuCl 2 solution (5%), and\nthen lowering the surface energy of the roughed Al foil by immersing\ninto an aqueous ethanol solution of stearic acid (0.01 M). Detailed\nfabrication processes are described in the experimental part. Figure 1 a,b shows the scanning\nelectron microscope (SEM) images with sample photos (insets) of Al\nsurfaces before and after CuCl 2 etching. As can be seen,\nthe chemical etching totally changes the morphologies of Al surfaces,\nwhich results in micro–nano-pits on the surface of the Al foil.\nMore SEM images with a large area or high magnification are shown\nin Supporting Information Figure S1. The\ncross section of laser microscope shown in Figure\nS2 demonstrate that the height of the micro–nano-pits\nvariates to about 40 μm. The confocal UV laser microscope image\nof the three-dimensional surface profile can be found in Figure S3 . These structures are essential for\nsuperhydrophobicity. Without the surface roughness, water static contact\nangles on the Al surface before and after stearic acid modification\nare only about 48° and 90°, respectively, as shown in Figure 1 c,d. Surface modification\nby stearic acid solution does not change the morphologies of Al foils,\nas shown in Figure S4 . However, this modification\nis also very important to obtain the superhydrophobicity. The roughed\nAl surface without the chemical modification of stearic acid solution\nis totally hydrophilic. As shown in Figure 1 e, water drops disperse immediately on the\nroughed Al surface upon impact, which makes it difficult to measure\nthe static contact angle. After stearic acid modification on the rough\nAl surface, water static contact angle is found to be about 165°,\nas shown in Figure 1 f. Surface modification to lower the surface energy with stearic\nacid solution results in the formation of a sponge-like layer on the\nroughed Al surface due to the process of a carboxyl group that reacts\nwith the Al atom through the following dehydration process: Figure 1 SEM images and sample photos (insets) of Al surfaces before\n(a) and after (b) CuCl 2 etching. Contact angle measurement\nof the Al surface without surface roughness before (c) and after (d)\nstearic acid modification, and Al surface with surface roughness before\n(e) and after (f) stearic acid modification. Bonding of the long nonpositive end\nof the alkyl to the roughed Al surface creates a low energy surface,\nwhich results in the final superhydrophobic property. 15 , 18 This dehydration process is confirmed by our infrared spectra shown\nin Figure S5 . The roll-off angles for the\nsuperhydrophobic surfaces are measured, which are less than 5°.\nBecause of the excellent superhydrophobicity, when a drop of water\nis released and falls toward the superhydrophobic Al surface, the\nwater droplet is repelled by the Al surface to such a degree that\nit bounces off the surface, lands again due to gravity, and bounces\nagain and off the surface, as shown in Supporting\nInformation Movie S1. Top- and side-view photos of a water\ndrop locates on the surface of our prepared superhydrophobic Al foil\nare shown in Figure S6 , which is very similar\nas a water drop on lotus leaves. For the roughed Al surfaces\nafter modification by stearic acid solution, water droplets could\nmaintain a spherical shape on such surfaces with a water static contact\nangle of about 165° ( Figure 1 f). The droplets are repelled by the modified Al surface,\nand could roll off with a very small angle ( Movie S1 ). Therefore, the Al surface exhibits superhydrophobicity\nand ultralow adhesion to water droplets. The cooperation between the\netching-induced roughness and the low-surface-energy stearic acid\nlayer effectively inhibits the contact between the water droplet and\nthe hierarchical micro- and nano-scale surface. The water droplet\nis at the Cassie–Baxter contact state. 6 , 7 The\nwater droplet looks like being lifted by the hierarchical micro–nano-structures\nand touches just the top part of the structures. Therefore, the small\ncontact area between the hierarchical structure and the water droplet\nleads to the superhydrophobicity of such roughed Al surfaces. To check the mechanical durability of our superhydrophobic Al surfaces,\nwe carried out the experiment of mechanical abrasion by using sandpaper\n(grit no. 400). As show in Figure S7 , in\none abrasion cycle, the Al surface with a weight of 50 g was placed\nface-down to a sandpaper and moved for 10 cm along the ruler; and\nthen the sample was rotated by 90° (face to the sandpaper) and\nmoved for 10 cm along the ruler, which guarantees the surface is abraded\nlongitudinally and transversely in each cycle. Our experiment shows\nthat the Al surface can withstand at least 30 cycles of this sandpaper\nabrasion, which confirmed that the superhydrophobic Al surface has\ngood mechanical durability to some extent. In order to estimate\nthe anti-corrosion property, Tafel plots were measured for untreated\nAl surface and superhydrophobic Al surface when the stable OCP was\nobtained after the samples being immersed into NaCl solution (3.5\nwt %) for at least 1 h. 7 , 8 The measured Tafel plots are shown\nin Figure 2 . On the\nbasis of electrochemical kinetics of corrosion, the corrosion potential\n( E corr ) and corrosion current density\n( I corr ) can be obtained by the extrapolation\nmethod in this polarization (Tafel) plots. 9 , 19 − 21 The ordinate\nand the abscissa of the intersection of anodic slope (β a ) and the cathodic slope (β c ) represented\nthe I corr and E corr values, respectively, as shown in Figure 2 . The fitting slopes of the linear parts\nin the Tafel plots at anodic and cathodic branches are β a and β c , as shown in Figure\nS8 . The values of the E corr , I corr , β a and β c derived from Tafel plots are summarized in Table 1 . We can find that the E corr and I corr of the untreated\nAl surface are about −1.52 V and 1.11 × 10 –4 A cm –2 , respectively. In comparison to the untreated\nAl surface, the E corr and I corr of the superhydrophobic Al surface reach about −1.38\nV and 6.10 × 10 –6 A cm –2 ,\nrespectively. On the basis of electrochemical kinetics of corrosion,\nin such Tafel curves, a more positive E corr corresponds to a lower corrosion probability, while the I corr is a measurement of the corrosion rate\n(CR). 9 , 19 , 20 Therefore,\nthis result demonstrates that superhydrophobic modification reduces\nboth the corrosion probability and the CR of the Al surface obviously.\nThe corrosion performance in our system is further evaluated by the\nelectrochemical impedance spectroscopy (EIS) that is a powerful and\ncomplementary electrochemical technique. 8 Figure 2 b is the\nEIS spectrum of the untreated Al surface and superhydrophobic Al surface\nby immersing in 3.5 wt % NaCl solution. It is well known that a large\nNyquist loop means a low CR. 8 The diameter\nof the Nyquist loop of the superhydrophobic Al surface is significantly\nlarger than that of the normal Al surface, which indicates that the\ncorrosion resistance has been greatly enhanced because of the superhydrophobic\ntreatment. Figure 2 Tafel plots\n(a) and Nyquist\nplots (b) of the untreated Al surface and superhydrophobic Al surface\nin 3.5 wt % NaCl solution. Table 1 Corrosion Potential ( E corr ), Corrosion Current Density ( I corr ),\nAnodic Slope (β a ) and Cathodic Slope (β c ), CR and the CIE of the Untreated Al Surface and Superhydrophobic\nAl Surface sample E corr (V) I corr (A cm –2 ) β a (mV/dec) β c (mV/dec) CR (mm/year) CIE (%) untreated Al –1.52 1.11 × 10 –4 208.33 156.25 1.2099 0 superhydrophobic Al –1.38 6.10 × 10 –6 416.67 129.87 0.0665 94.5 On the basis of the obtained value of I corr (μA/cm 2 ), we can estimate the CR\naccording to the following equations where M is the relative atomic mass of the metal\n(g/mol), d is the density of the metal (g/cm 3 ), n is the number of electrons required\nto oxidize an atom of the element in the corrosion process, that is,\nthe valence of the metal, respectively. 21 , 22 Also the corrosion\ninhibition efficiency (CIE) can be calculated according to the following\nequation I corr and I corr ′ are the corrosion current densities before and after superhydrophobic\nmodification for our Al surface, respectively. 7 The calculated values of CR and CIE are also summarized on Table 1 . These electrochemical\nvalues demonstrate that the superhydrophobic modification really protects\nthe surface of Al. The CR drops by 94.5% after the superhydrophobic\nsurface treatment. The trapped air layer on the superhydrophobic surface\ndiminishes the contact of water with the substrate interphase, which\nresults in a barrier for the corrosion ions reaching the Al surface\nand corroding the metal. 7 , 8 Furthermore, the trapped\nair among the hierarchical micro- and nano-structures could repel\nthe corrosion ions due to the Laplace pressure. 7 , 8 Therefore,\nsuperhydrophobic modification can slow down the corrosion or deterioration\nprocess in the Al surface. In order to check the anti-corrosion\nproperty of the Al superhydrophobic surface more directly, we tested\nthe untreated Al foil and superhydrophobic Al foil under a harsh environment\nby using CuCl 2 solution (5%) as etching solution. Figure 3 a shows the surfaces\nof the superhydrophobic and untreated Al foils before the etching\ntest. Because of the strong diffusion of the roughed surface, the\nsuperhydrophobic Al foil looks much darker than the untreated one.\nAfter etching by CuCl 2 solutions with the same volume (4\ndrops) during the same time (65 s), these two Al foils display a totally\ndifferent appearance. As shown in Figure 3 b,c, the superhydrophobic Al surface only\nshows a very small etched area (the area with light brown color).\nBy contrast, the untreated Al surface is etched seriously. Brown Cu\nparticles are found obviously, which come from the etching of CuCl 2 solution, as shown in Figure 3 c. Detailed etching processes for these two foils can\nbe seen clearly in supporting formation Movie S2 . This experiment demonstrates undoubtedly that our superhydrophobic\nAl surface can slow down the corrosion of the Al foil even under a\nharsh environment. Figure 3 Photos of a superhydrophobic\nAl foil (rectangle\nsample at left side) and an untreated Al foil (round sample at right\nside) before (a) and after (b) etching by the same CuCl 2 solution (5%) for 65 s, and after (c) pouring off the rest of the\netching solution. Furthermore, our superhydrophobic Al surface\nis scalable. As shown in Figure 4 a, it is fast and easy to fabricate such surface with\na diameter of 10 cm. In addition, the superhydrophobic Al surfaces\nexhibit excellent flexible and repairable properties. As can be seen\nin Figure 4 , it still\nretains the superhydrophobic property after flattening the crumpled\nAl foil ( Figure 4 a–d).\nAlso the superhydrophobic property on our Al surface can be repaired.\nAs marked by the red arrows in Figure 4 , the sandpaper-abraded areas exhibit obvious hydrophilic\nproperty ( Figure 4 e,f).\nHowever, this hydrophilic area can easily be repaired to superhydrophobicity\nafter roughing the surface by CuCl 2 solution etching and\nthen lowering the surface energy by aqueous ethanol solution of stearic\nacid, which are described in experimental process and shown in Figure 4 g–j. It should\nbe noted that, during the surface repairing process, the dropped CuCl 2 solution only locates on the abraded hydrophilic area, as\nother areas are superhydrophobic ( Figure 4 h). After lowering the surface energy by\ndropping stearic acid solution, the superhydrophobic property recovers\non these abraded hydrophilic areas ( Figure 4 i,j). This selectively repairable ability\nshould have important significance for the practical application of\nsuperhydrophobic Al surfaces as touching and damaging the surface\nis unavoidable in real usage. Figure 4 Photos of a superhydrophobic Al foil before\n(a) and after (b) crumpling; top-view (c) and side-view (d) photos\nof the Al foil after flattening with water drops; top-view (e) and\nside-view (f) photos of the Al foil with water drops and some areas\nabraded by the sandpaper show hydrophilic property (marked by red\narrows); (g) top-view photos of the Al foil without water drops and\nwith some areas abraded by the sandpaper; (h) Al foil with abraded\nareas that are etching by CuCl 2 solution; and (i) top-view\nand side-view (j) photos of the Al foil with water drops after superhydrophobic\nmodification again (the repaired areas are marked by red arrows)."
} | 4,141 |
36090262 | PMC9448910 | pmc | 2,202 | {
"abstract": "Spiking neural networks (SNNs) are brain-inspired machine learning algorithms with merits such as biological plausibility and unsupervised learning capability. Previous works have shown that converting Artificial Neural Networks (ANNs) into SNNs is a practical and efficient approach for implementing an SNN. However, the basic principle and theoretical groundwork are lacking for training a non-accuracy-loss SNN. This paper establishes a precise mathematical mapping between the biological parameters of the Linear Leaky-Integrate-and-Fire model (LIF)/SNNs and the parameters of ReLU-AN/Deep Neural Networks (DNNs). Such mapping relationship is analytically proven under certain conditions and demonstrated by simulation and real data experiments. It can serve as the theoretical basis for the potential combination of the respective merits of the two categories of neural networks.",
"introduction": "1. Introduction In recent decades, Artificial Intelligence (AI) has taken a path that has been rising, then falling, and is now under steady development. Based on the understanding of the human cerebral cortex's mechanism, ANN is formulated and becomes one of the primary directions for AI, called connectionism (McCulloch and Pitts, 1943 ). ANNs are composed of artificial neurons (ANs) connected as a graph. The weights of the connections, mimicking the cerebral cortex's synapses, represent the network's plasticity and can be trained via gradient descent (Ruder, 2016 ) in supervised learning tasks. With a large amount of annotated training data, a deep large-scale network structure, and computing power, DNNs have achieved great success in many application fields. They have become the most popular AI technology. The performance of a DNN can reach the human level on specific tasks, such as image recognition (Krizhevsky et al., 2012 ; He et al., 2016 ; Jiang et al., 2018 ; Zhao et al., 2019 ), instance segmentation (Cao et al., 2020 ), speech understanding (Hinton et al., 2012 ), strategic game playing (Mnih et al., 2013 ), etc. DNNs employ a hierarchical structure with an exponentially-growing representation capacity. Such deep network structure was studied as early as the 1980s, but it was found difficult to train due to the vanishing of backpropagated gradients (Ivakhnenko and Lapa, 1965 ; Ivakhnenko, 1971 ; Schmidhuber, 2015 ). This problem was not solved until the deep learning era when the much simpler activation function called Rectified Linear Unit (ReLU) was used instead of conventional nonlinear functions such as the sigmoid (Jarrett et al., 2009 ; Glorot et al., 2011 ; Choromanska et al., 2014 ). Equipped with the ReLU activation function, DNNs have gained a powerful fitting capability on large-scale complex data. DNN is considered second-generation neural networks (Maass, 1997 ). It is widely considered that DNN's great success is attributable to big data, powerful computational technology (such as GPU), and training algorithms. As DNNs are widely applied in real applications, limitations are becoming apparent. For example, strong dependence on labeled data and non-interpretability are considered drawbacks of deep learning. With the increase of layers and parameters, DNNs require many annotated data and computing power for training. However, current research mainly focuses on network architecture and algorithms designed for specific AI tasks. A technical approach to general artificial intelligence aims to break the limitations that remain studied. In this regard, many methods have been proposed, including SNN (Maass, 1997 ), which is regarded as the third generation of neural networks. SNN uses spiking neurons primarily of the leaky-Integrate-and-Fire (LIF) type (Lapicque, 1907 ), which exchange information via spikes. Due to its accurate modeling of biological neural network dynamics, SNN is the most popular brain-inspired AI approach (Tan et al., 2020 ). There have been extensive studies of SNN-derived neural networks, such as full connected SNN (Diehl and Cook, 2015 ), deep SNN (Illing et al., 2019 ; Tavanaei et al., 2019 ) and convolution SNN (Kheradpisheh et al., 2018 ). The learning mechanism of SNN includes supervised learning (such as spike backward propagation) (Kulkarni and Rajendran, 2018 ; Wang et al., 2020 ), unsupervised learning (such as spiking timing-dependent plasticity) (Tavanaei and Maida, 2016 ; Nazari and faez, 2018 ), and reinforcement learning (Mozafari et al., 2018 ). However, SNNs have not yet achieved the performance of DNNs in many tasks. One of the most effective training algorithms is to transfer the trained weights of DNNs to SNNs with the same structure (Cao et al., 2015 ; Sengupta et al., 2019 ; Kim et al., 2020 ; Rathi et al., 2020 ). Establishing an effective SNN training algorithm or transformation mechanism is a challenging task. The fundamental question on the relationship between the second and third-generation neural networks is unclear. The major contributions of this paper are as follows: The parameter mapping relationship between the Linear LIF neuron model and the ReLU-AN model is established. Inspired by the perspective of biology as well as the proposed equivalence, the ReLU activation function is proved to be the bridge between SNNs and DNNs. Experiments conducted on MNIST and CIFAR-10 datasets demonstrate the effectiveness and superiority of the proposed SNN composed of the Linear LIF model. The experimental validation under various simulation conditions is presented to prove the equivalence. The rest of the paper is organized as follows. Section 2 explains the motivation of this study. Section 3 summarizes the related studies on ReLU-AN and the LIF model. Section 4 defines equivalence and presents the mapping relationship between Linear LIF model and ReLU-AN model. Simulations and analyses from single neuron to deep neural networks are carried out in Section 5. Finally, we make a brief conclusion and state the future opportunities in Section 6.",
"discussion": "6. Conclusion and discussion 6.1. Brief summary Despite the great successes of DNN in many practical applications, there are still shortcomings to be overcome. One way to overcome them is to look for inspiration from neuroscience, where SNNs have been proposed as a biologically more plausible alternative. This paper aims to find an equivalence between LIF/SNN and ReLU/DNN. Based on a dynamic analysis of the Linear LIF model, a parameter mapping between the biological neuron model and the artificial neuron model was established. We analyzed the equivalence of the two models from the aspects of weight, bias, and slop of activation function, and verified it both theoretically and experimentally, from a single neuron simulation to a neural network simulation. It shows that such an equivalence can be established, both the structural equivalence and behavioral equivalence, and the Linear LIF model can complete the information integration and the information processing of the linear rectification. This mapping is helpful for the combination of an SNN with an artificial neural network and increasing the biological interpretability of an artificial neural network. It is the first step toward answering the question of how to design more causal neuron models for future neural networks. Many scholars believe that interpretability is the key to a new artificial intelligence revolution. At the same time, the equivalence relationship is the bridge between machine intelligence and brain intelligence. Exploring new neuron models is still of great importance in areas such as unsupervised learning. As brain scientists and cognitive neuroscientists unravel the mysteries of the brain, the field of machine learning will surely benefit from it. Modern deep learning takes its inspiration from many areas, and it makes sense to understand the structure of the brain and how it works at an algorithmic level. 6.2. Future opportunities The architecture of SNN is still limited to the structure of DNN. Compared with DNN, SNN only has the synaptic connection weights which can be trained, while the weights, bias and activation function (dynamic ReLU, Microsoft Chen et al., 2020 ) can be trained in DNN. Therefore, we expect Linear LIF model and the parameter mapping relationship can bring innovation to SNN fromthose aspects. 6.2.1. A new way to convert ANN to SNN With the new approach of converting pre-trained ANN to SNN, we will have a better expression of bias in SNN. Most conversion methods restrict the structure of ANN and directly map the weight. However, bias is also an important parameter in the deep learning network, and we can convert bias into membrane conductance gl based on parameter mapping relationship. In this way, SNN and ANN can maintain high consistency and improve the effect of some tasks. Especially in the convolutional neural network, the connectable region of neurons is small, which is more conducive to the conversion of bias into the parameters in the Linear LIF model. 6.2.2. Parameters training of linear LIF model All the parameters of LIF model can be trained or transformed, which is the fundamental difference from other SNN. Based on the parameters mapping relationship, we can map the trained parameters of DNN to the biological parameters of LIF model, to ensure that each node in SNN has its own unique dynamic properties. At the same time, we know the meaning of each parameter, and we can also carry out the direct training of parameters. In biology, it is also worth investigating whether other parameters of neurons, besides weights, will change. 6.2.3. Dynamic activation function As the number of layers in the network increases, the number of spikes decreases. We generally adjust the spiking threshold to solve this problem. But we know that the shape of the action potential is essentially fixed, and the spiking threshold of neurons does not change. The membrane capacitance represents the ability to store ions, that is, the opening and closing of ion channels. So, when the number of spikes is low, we can reduce the membrane capacitance and increase the membrane capacitance instead. In parameter mapping, it is similar to dynamic ReLU."
} | 2,554 |
36986908 | PMC10058974 | pmc | 2,203 | {
"abstract": "Mining activity has an adverse impact on the surrounding ecosystem, especially via the release of potentially toxic elements (PTEs); therefore, there is an urgent need to develop efficient technologies to remediate these ecosystems, especially soils. Phytoremediation can be potentially used to remediate contaminated areas by potentially toxic elements. However, in soils affected by polymetallic contamination, including metals, metalloids, and rare earth elements (REEs), it is necessary to evaluate the behavior of these toxic elements in the soil-plant system, which will allow the selection of the most appropriate native plants with phytoremediation potential to be used in phytoremediation programs. This study was conducted to evaluate the level of contamination of 29 metal(loid)s and REEs in two natural soils and four native plant species ( Salsola oppositifolia , Stipa tenacissima , Piptatherum miliaceum , and Artemisia herba-alba ) growing in the vicinity of a Pb-(Ag)-Zn mine and asses their phytoextraction and phytostabilization potential. The results indicated that very high soil contamination was found for Zn, Fe, Al, Pb, Cd, As, Se, and Th, considerable to moderate contamination for Cu, Sb, Cs, Ge Ni, Cr, and Co, and low contamination for Rb, V, Sr, Zr, Sn, Y, Bi and U in the study area, dependent of sampling place. Available fraction of PTEs and REEs in comparison to total concentration showed a wide range from 0% for Sn to more than 10% for Pb, Cd, and Mn. Soil properties such as pH, electrical conductivity, and clay content affect the total, available, and water-soluble concentrations of different PTEs and REEs. The results obtained from plant analysis showed that the concentration of PTEs in shoots could be at a toxicity level (Zn, Pb, and Cr), lower than toxic but more than sufficient or natural concentration accepted in plants (Cd, Ni, and Cu) or at an acceptable level (e.g., V, As, Co, and Mn). Accumulation of PTEs and REEs in plants and the translocation from root to shoot varied between plant species and sampling soils. A. herba-alba is the least efficient plant in the phytoremediation process; P. miliaceum was a good candidate for phytostabilization of Pb, Cd, Cu, V, and As, and S. oppositifolia for phytoextraction of Zn, Cd, Mn, and Mo. All plant species except A. herba-alba could be potential candidates for phytostabilization of REEs, while none of the plant species has the potential to be used in the phytoextraction of REEs.",
"conclusion": "4. Conclusions This study emphasizes the importance of paying attention to abandoned mines and managing mine tailings because they can cause pollution to enter the surrounding soils. Results indicated that the degree of pollution of metal(loid)s and REEs in natural soils near mine areas is heterogeneous, and therefore, before starting remediation programs, a study of the spatial distribution of toxic elements in soil should be performed in order to identify the most polluted areas, in which more attention should be paid for their remediation. As shown, plants grown in soils with a higher concentration of toxic elements contained more metal(loid)s in their tissues, showing a higher phytoextraction ability of metal(loid)s, such as Cr, Ni, Zn, and Cd, which could pass into the food chain via herbivores, and thus provide more potential risk to humans. The results suggested that among the four species studied ( S. oppositifolia , S. tenacissima , P. miliaceum , and A. herba-alba ), the suitability of the plant for stabilization or extraction of metal(loid)s completely depends on the type of metal(loid)s and soil type. Although A. herba-alba was the least efficient plant in the phytoremediation process, P. miliaceum was a good candidate for phytostabilization of Pb, Cd, Cu, V, and As, and S. oppositifolia was a good candidate for phytoextraction of Zn, Cd, Mn, and Mo. All plant species except A. herba-alba could be potential candidates for the phytostabilization of REEs, while none of the plant species has the potential to be used in the phytoextraction of REEs. Therefore, the use of native plants is a recommended method for reclaiming polluted mine soils; the selection of the plant species to be used is a key factor for the success of the phytoremediation strategy.",
"introduction": "1. Introduction Since the industrial revolution, mining activities have been one of the most important sources of anthropogenic contamination in several soils around the world, particularly in regions with a long history of activity. One of the main concerns regarding mining operations is an inappropriate or uncontrolled abundance of numerous tailing deposits that contain a high content of potentially toxic elements (PTEs), during exploitation for metal(loid) extraction or after the closure of the activity, without any remediation treatments. These PTEs include metals (e.g., Zn, Pb, Cd, Cu, U, and Th), metalloids (e.g., Ge, Sb, As, and Bi), and rare earth elements (REEs) (e.g., Pr, Y, and La) which, especially in high concentrations, have seriously affected the physiological and biochemical processes in plants, animals, humans, as well as soil microorganisms [ 1 , 2 , 3 , 4 ]. In addition to the pollution in abandoned mine tailings ponds, previous studies have demonstrated that these places have a great adverse impact on the surrounding ecosystem by the transportation of PTEs through wind, surface water (including acid mine drainage, i.e., AMD), and groundwater seepage. Therefore, the distribution of PTEs throughout these districts could be affected by natural factors such as terrain (elevation and slope), wind direction, rainfall, and the distances from rivers as well as mine tailings PTE contents [ 5 , 6 , 7 , 8 , 9 ]. Additionally, the physic-chemical properties of soil, such as pH, electrical conductivity, etc., affect the mobility of PTEs [ 10 , 11 ]. In fact, chemical reactions between these elements and solid components of soil determine their bioavailability and solubility; Dimirkow et al. [ 11 ] concluded that Cd adsorption by goethite and clinoptilolite increases with the increase in pH and with the decrease in electrolyte concentration. In addition, sometimes, the lands around abandoned mines are used for agriculture, as well as for children’s parks or as tourist areas [ 9 , 12 , 13 ]. These different land uses can result in various exposure pathways which enter the PTEs in the human body via the food chain or direct intake and can pose risks to human health and safety, especially to those residing in the vicinity of these areas [ 14 ]. Therefore, there is an urgent need to develop efficient and sustainable soil remediation programs to reduce the risk associated with the mobility, transportation, dispersion, and ecotoxicity of PTEs from abandoned mine tailings to surrounding environments. These programs should be based on studies of ecological and health risks assessment which allow the selection of the most appropriate measures to reduce these risks. Apart from several chemical/physical technologies such as excavation of contaminated material, landfilling, incineration, immobilization, stabilization/solidification, and chemical extraction, phytoremediation can provide a less invasive, low-cost phytotechnology that is an environmentally friendly, long-lasting, and aesthetic solution to rehabilitate these contaminated areas [ 15 , 16 , 17 ]. Phytoremediation is the process of application of green plants to remove or render PTE contaminants harmless. Among phytoremediation techniques, phytoextraction and phytostabilization are the most promising options for mine tailings and surrounding soil reclamation [ 17 ]. Phytostabilization, by establishing a plant cover on the surface of contaminated soils, aims to deactivate and immobilize the PTEs within a limited area through root accumulation or precipitation within the rhizosphere, thereby diminishing uptake and transport of PTEs and the chances of any biological interactions with humans or animals. In contrast to phytostabilization, phytoextraction relies on the ability of plants to absorb and accumulate soil PTEs in their shoots, so that they can later be harvested in order to remove metal(loid)s from the soil [ 16 , 18 ]. Moreover, it was suggested that the plants exhibiting greater BCF (bioconcentration factor) and less than 1 TF (translocation factor) can be used as potential candidates for the phytostabilization of metal(loid)s. Plants with BCF and TF both greater than one have the potential to be used for phytoextraction [ 16 , 17 ]. Several studies have shown the efficiency of phytoextraction in reducing the concentration of a toxic element in soil; p.e. Kolodziej et al. [ 19 ] found that giant miscanthus was able to recover 47% of Mo, 39% of Mn, and 35% of Fe from municipal sewage sludge. In addition, phytoextraction can be improved by the application of various amendments; Grzegordka et al. [ 20 ] concluded that the application of a soil improver increases by 85% the mass of Miscanthus × giganteus compared to the soil without additives, increasing the uptake of Al, Fe, Co, Pb, Mn, Ni, and Cd. Additionally, plants used for phytoremediation need to effectively tolerate high concentrations of metal(loid)s, grow rapidly, and their root systems must be vigorous and show proper adaptability against a specific area [ 16 ]. Native plants, which can be found in wide geographical locations, are of particular interest in this perspective, since these spontaneous plant species are genetically adapted to the contaminant and, as such, can remove or retain it, reducing its toxicity in soil [ 15 , 21 ]. They could belong to a group known as hyperaccumulators, which can tolerate, absorb, accumulate, and translocate high levels of metal(loid)s, or excluder plants that can maintain relatively low levels in their shoot while still containing large amounts of metal(loid)s in their roots [ 22 ]. Furthermore, numerous studies have shown that native plants that grow in contaminated areas are either more resistant through higher disposal efficiency or have more metal(loid) accumulation and resistance to stressful prevailing conditions than plants grown in non-contaminated areas. Many native plant species have been identified and selected as potential phytoremediation plants to extract or stabilize metal(loid)s in impacted mines, for example, Salsola soda [ 23 ], Salsola , Eremopyrum , Aeluropus litoralis [ 24 ], Salsola oppositifolia Desf , Limonium delicatulum , Moricandia arvensis (L.) DC [ 18 ], Piptatherum caerulescens , Coris monspeliensis , Lobularia maritima [ 25 ] and Pinus halepensis , and Tetraclinisarticulata [ 26 ]. However, there are very few studies that evaluate the potential of native plants to be used in phytoremediation programs in soils affected by polymetallic contamination, including heavy metals as well as metalloids and rare earth elements. In particular, few studies have evaluated the behavior of rare earth elements in contaminated soils and their uptake by native vegetation. For hundreds of years, the Mazarron district (Murcia Region, southeast Spain) has been exposed to mining activity for Pb, Ag, and Zn extraction [ 27 ]. Although this site was abandoned in 1996, many tailing ponds remain in the area without any restoration [ 28 ]. The objective of this study was to test whether the two natural soils near this mining area are contaminated by metal(loid)s and REEs, and also to identify metal(loid) and REE accumulation patterns in native species present in soils and any relationships between the concentration of metals in plants and soils, in order to suggest suitable ones for use in phytoremediation (phytoextraction or phytostabilization) strategies.",
"discussion": "2. Results and Discussion 2.1. Physic-Chemical Characteristics of Soils Table 1 summarizes the characteristic of soil profiles from Unit S1 and Unit S2. Profile 1 was taken in Unit S1, and it has been developed on dacites. Three horizons were identified: A1, A2, and C/R. The pH in all horizons is slightly alkaline, which favors the development of vegetation but can result in a deficiency of nutrients such as P or Fe that are not widely available or soluble at high pH. In this pH range, most of the PTEs are precipitated and have little availability, thus reducing the risk of transfer of pollutants by leaching, runoff, or through the trophic chain. All three horizons are non-saline. The content of OC and TN decreases in depth. CEC was less than 10 cmol + kg −1 , which represents a moderate capacity for nutrient adsorption [ 29 , 30 ]. The three horizons presented clay-sandy loam textural class, with a predominance of sand (61–66%). This profile is classified as Leptic Regosol [ 31 ]. Profile 2 was taken in the southwest of Unit S2. It has also been developed on dacites. Three horizons were identified: A, AC, and C/R ( Table 1 ). The pH in all horizons was basic (8.04–8.18), which favors the development of vegetation; similarly to profile 1, all three horizons were non-saline. The content of OC and TN was higher in the surface horizon A, and decreased in depth, with relatively low values for forest soils, as a consequence of the degradation suffered by anthropic action. The horizons of this profile have a CEC lower than 10 cmol + kg −1 . The first two horizons of the profile have a clay-sandy loam textural class, with a predominance of sand (62–66%). The third horizon (C/R) presents a sandy loam texture, with a higher sand content (78%) than the upper horizons. Profile 2 is classified as Leptic calcisol [ 31 ]. Profile 3 was taken in the north of Unit S2, next to a P. halepensis pine forest. Like the previous profiles, this one has also been developed on dacites. Three horizons were identified: A, C1, and C2 ( Table 1 ). The pH in all horizons was basic (7.92–8.26). All three horizons are non-saline. The OC and TN content and CEC pattern were similar to other profiles. The first two horizons of the profile presented a clay-sandy loam textural class, with a predominance of sand (59–68%). The third horizon (C2) had a clay-sandy texture, with a higher clay content (42%) than the upper horizons. Profile 3 is classified as Leptic Calcisol [ 31 ]. As shown in Table 1 , the surface and subsurface soils in Unit S1 were slightly alkaline (7.86 and 7.97, respectively), which are lower than the pH from Unit S2 (8.13–8.27). The result from the previous study [ 27 ] showed that all the materials that made up the surface of mine ponds (sludge and gravimetric waste), which are near Unit S1 and Unit S2, showed a high acidity (3.86–3.15 and 4.89–3.15). A lower pH value of sludge near S1 [ 27 ] may result in lower pH values in the surface and subsurface soils of Unit S1 in comparison to Unit S2. In total, these pH conditions are suitable for plant growth, and it is also the key factor influencing the migration, adsorption, and precipitation of metal(loid)s and REEs in soil. The predominance of sand fraction in the natural soils ( Table 1 ) and mining residues near them [ 27 ] probably resulted in wind and water erosion to mobilize these particles to the nearby environment and promote water infiltration [ 32 ]. These soil samples exhibited small EC values (0.13–0.19 dsm −1 ), indicating low transfer of salts from mine waste to natural soils. Previous studies reported a correlation between low pH and high EC, since the presence of high amounts of sulfur ions in mining residues led to an increase in the EC, while their oxidation caused pH reduction by the formation of sulfuric acid [ 33 ]. 2.2. Metal(loid)s and REEs Concentrations in Soils 2.2.1. Distribution of Total Concentration in Soils Results showed that the highest concentrations of total metal(loid)s were mainly found for Fe, Al, Pb, Zn, and Mn in both Units ( Table 2 ). The previous study [ 27 ] reported that mining waste materials in the vicinity of these natural soils are composed of high concentrations of Fe, Pb, and Zn that originated from jarosite, clinochlore, and halloysite minerals [ 28 ]. Therefore, the enrichment of these elements in these Units possibly came from mining waste materials. The mean concentrations of total Al and Zn in Unit S1 were 48,505 and 2436 mg kg −1 , respectively, which were significantly higher than the corresponding values in Unit S2 (28,127 and 1187 mg kg −1 , respectively) ( Table 2 ). However, there were no significant differences in total concentrations of Al among mining wastes and different units [ 27 ] in the vicinity of these natural soils; the significant difference found in these natural units could be a result of different soil properties between these areas, such as pH, organic carbon, and carbonate ( Table 1 ). Al is the most abundant metal in the Earth’s crust and part of the structural components of clays, while the excess amount of its concentration in soils is toxic to most plants [ 34 ]. It is well known that AMD could be responsible for Al release, especially at low pH ranges, and followed by precipitation happens when the pH values enhances to 4.0–5.5 [ 35 ]. Units S1 and S2, are located downstream of the open-cast mining, which leads to the release of Al from the current tailings mine which are disposed as open dump. Sphalerite (ZnS) is the main sulfide of the ore vein in sulfurous mining areas that may release Zn into the environment. The result from the previous study [ 27 ] demonstrated that the total Zn concentration in gravimetric waste, located near Unit S1, was significantly higher than other residues. Zhang et al. [ 5 ] showed that the amounts of Zn leaving a tailings pond at a copper mine with drainage water were 21.6% of the amounts released from oxidation in the oxidized zone. There is no significant difference in the contents of total Pb between Unit S1 and Unit S2 ( Table 2 ). Gabarron et al. [ 28 ] concluded that the high concentration of Pb in natural soils could have happened as a result of Pb transfer from mining ponds, and parent material could be a secondary source of Pb pollution in agricultural and natural soil in the Mazarron district. On the other hand, the mean total Mn concentration in Unit S2 was higher than in Unit S1 (694 and 328 mg kg −1 , respectively) ( Table 2 ). Manganese forms many minerals such as todorokite, clinochlore, pyrolusite, and serandite and is highest in igneous rocks, gabbros, and basalts [ 36 ]. Furthermore, it is similar in size to Mg 2+ and Fe 2+ , and their substitution in oxides and silicates may enhance the specific surface area that finally contributes to the flux control of many heavy metals such as Co, Ni, Cu, and Zn [ 37 ]. Moreover, Mn and Fe are involved in a wide spectrum of biogeochemical pathways such as mineral dissolution, microbial processes, the formation of a wide range of highly reactive solid phases (Fe and Mn oxy-hydroxides), and the biogeochemical cycles of other major elements (e.g., carbon, sulfur, and phosphorus) [ 38 ]. The result showed that the mean Fe concentration in Unit S1 was higher than in Unit S2 (58,318 and 38,408 mg kg −1 , respectively) ( Table 2 ). It was suggested that the mining districts of Mazarron are composed of high amounts of Fe-oxyhydroxides, Pb, Zn, and Fe sulfides, that are related to the parent materials [ 28 , 39 ]. The fifth most abundant metal in studied soils was obtained for Sr, which was 2.39 times higher in Unit S2 than the concentration found in Unit S1 (459 and 135 mg kg −1 , respectively) ( Table 2 ). The high amount of Sr in Unit S2 can be related to the high level of Sr in waste materials (495 mg kg −1 ) [ 27 ] that are located in the vicinity of the study area. Sr is a trace element with a common concentration between 260 and 730 mg kg −1 and belongs to the alkaline earth metals; it behaves similarly to Ca and Mg, and the main source of Sr pollution is associated with coal combustion and sulfur mining [ 40 ]. The mean As concentrations found in Unit S1 and Unit S2 soils were 131 and 149 mg kg −1 , respectively ( Table 2 ), which were similar to the amount found in agricultural soils from Mazarron (149 mg kg −1 ) in the research of Gabarron et al. [ 28 ]; however, there were no significant differences between these two Units. Gabarron et al. [ 28 ] suggested that the high concentrations of As can be associated with ferrous minerals common in the studied area as arsenopyrite (FeAsS). The result of our study showed that there is no significant difference between the total concentration of Cr, Ni, In, Sn, Sb, Bi, and Rb in Unit S1 and Unit S2 (the ranges are 110–86.5, 34.5–38.1, 0.87–1.40, 4.70–6.87, 3.06–4.20, 0.29–0.47, and 66.0–73.8 mg kg −1 , respectively) ( Table 2 ). Chromium is quite abundant in most soils, and chromite (FeCr 2 O 4 ) and Crocoite (PbCrO 4 ) are the most common Cr-minerals, which usually are associated with pyroxenes, amphibolites and micas and heavy metals such as Ni and Co [ 36 , 40 ]. According to Kabata-Pendias and Mukherjee [ 40 ], Ni primarily often forms sulfides and sulfarsenides together with Fe and Co, and is associated with several Fe minerals. After weathering, it coprecipitates with Fe and Mn oxides, and can also be associated with carbonates, phosphates, and silicates minerals [ 41 ]. Oppositely, higher total concentrations of Co, Cu, Zr, and Cs were observed in Unit S2 than in Unit S1 (11.7–4.06, 71.1–39.8, 15.8–4.96, 42.6–6.89 mg kg −1 , respectively, which were 2.89, 1.78, 3.18, and 6.18 times higher) ( Table 2 ). The acid character of the mining waste around those areas, which favors the mobility of these metals, leads to leakage of them to surrounding natural soils, that is, Units S2 and S1, where the sorption phenomena happened since the conditions such as greater pH and CEC are present [ 42 ]. It was also observed that the total concentration of V, Se, Y, Mo, Cd, La, Ce, Pr, Th, Ge, and U were significantly higher in Unit S1 in comparison to Unit S2 (83.9–72.3, 2.16–1.32, 23.8–14.9, 3.44–2.22, 14.1–6.67, 54.1–26.3, 118–61.8, 15.3–7.89, 36.7–17.3, 4.94–2.84, and 7.92–4.26 mg kg −1 , respectively) ( Table 2 ). The accumulation of these metal(loid)s and REEs in Unit S1 can be attributed to the higher concentration of waste materials located in the vicinity of this area [ 27 ]. The oxidation of sulfides within mining waste materials can accelerate the dissolution of REE-bearing minerals (e.g., carbonates, silicates, and phosphates) and enhance the leaching of REE and other associated contaminants such as uranium, thorium, and niobium [ 43 , 44 , 45 ]. Among different REEs, the highest concentration in both areas was Ce ( Table 2 ). Pereira et al. [ 46 ] found the same result in a gold mining area in the Amazon. REEs are ingredients of several different minerals and can also be concentrated in phosphorites, being included in quite common minerals such as monazite ((CeLa)PO 4 ), bastnasite ((Ce F )CO 3 ), cheralite ((Ce, La, Y, Th)PO 4 ), and xenotime (YPO 4 ) [ 40 ], or as impurity elements spread in rock-forming minerals and rare metal minerals via isomorphic substitution. Such minerals are often mentioned as REE-containing minerals (e.g., apatite and fluorite) [ 47 ]. Mleczek et al. [ 44 ] mentioned that REE concentrations in the following few years may be related to a major new form of environmental pollutants, and this increase may also pose a hazard to both plant and human health. The evaluation of total metal(loid) and REE concentration distribution in depth ( Table 2 ) showed that there is no significant difference between the surface (0–15 cm) and subsurface (15–30 cm), except for Co, Ni, La, Ce, Pr, Sn, Th, and Ge. However, there was no significant difference in total Ni by increasing depth in Unit S1; in Unit S2, a higher amount of Ni was accumulated in surface soil (1.46 times higher than in the subsurface) ( Table 2 ). Moreover, in Unit S1, total Ce, Pr, and Th in the subsurface were 1.56, 1.46, and 1.87 times higher than surface soils, while they showed no differences in Unit S2 ( Table 2 ). In addition, the total concentration of La and Ge increased with depth in Unit S1, and they were 1.58 and 1.16 times more than those found in the subsurface soils and adversely were 0.82 and 0.83 times lower in Unit S2. Therefore, Unit S1 favored accumulating these REEs at the subsurface and Unit S2 at the surface ( Table 2 ). However, REE naturally tends to concentrate on the upper layers of a soil profile, as found in Ni, La, and Ge in Unit S2 [ 48 ]; they could occur at the depth of mine soils [ 49 ]. In general, REEs complexation in natural soils, which is known to enhance their mobility in soils, is mainly associated with clay minerals, organic matter, carbonates, and humic substances, or Fe (hydr)oxides and colloids [ 50 , 51 ], whereas phosphate complexation leads to decreased REE solubility [ 52 ]. 2.2.2. Contamination Factor Based on the Contamination Factor (CF) values, varying degrees of contamination were observed for the different metal(loid)s and REEs studied ( Figure 1 ). Very high contamination (CF ≥ 6) was found for Zn, Fe, Al, Pb, Cd, As, Se, and Th in both Unit S1 and Unit S2. Concentrations of Th, Pb, and Cd in Unit S1 and Unit S2 were 363–173, 239–258, and 117–55 times higher than background values [ 53 ], respectively, and exceed the proposed generic reference levels [ 53 , 54 ] (Figure). These high concentrations are mostly due to the mining activity that has contributed to concentrating and enriching of these pollutants and also to the geological substrate enriched with these elements, which finally bring high ecological risks to these soils [ 27 ]. Sahoo et al. [ 55 ], by the review of a total of 117 relevant reports from 19 different countries such as India, Iran, Slovakia, Brazil, China, and Morocco, reported that in soil plus overburden samples taken near mining sites, maximum CF values for Fe, Zn, Cd, Pb, and As were 10.5, 28.8, 320, 34, 754, respectively. Martinez-Carlos et al. [ 21 ] reported that As, Pb, Cd, and Zn exceed more than 10, 600, 40, and 80-fold the background level for natural soils in the study area located in the Cartagena-La Union mining district, Murcia Region (SE Spain), near the tailings ponds with a high concentration of Pb, Zn, Fe, Mn, or As. While considerable contamination (3 ≤ CF < 6) was found for Cu, Sb, and Cs in Unit S2 and Ge in Unit S1, which were 3.1, 3.8, 3, and 3.8 times higher than the regional background levels, moderate contamination (1 ≤ CF < 3) was found for Cu and Sb in Unit S1 and Ge in Unit S2 ( Figure 1 ). In addition, Cs in Unit S1 showed low contamination (CF < 1) ( Figure 1 ). Azizi et al. [ 27 ] reported that Cu, Sb, and Ge were more than 10, 8, and 4 times higher than the background level in waste materials of mine tailings in the vicinity of these natural soils, while Cs was within the background levels of the area. These results probably indicate that mine tailings could be responsible for the accumulation of these pollutants in the study area. However, the total Co, Ni, and Cr content in the studied mining waste was within the background levels of these elements in the Region of Murcia [ 27 ]; CF values showed moderate contamination (1 ≤ CF < 3) for Ni, Cr, and Co in Unit S2 and Ni and Cr in Unit S1 ( Figure 1 ). This probably happened as a result of leakage of these elements to surrounding soils or as dust deposition. In addition, moderate contamination (1 ≤ CF < 3) was found for Mo in both soils, Mn in Unit S2 and La and Ce in Unit S1 ( Figure 1 ). Low contamination (CF < 1), which means the total metal concentration is below background levels, was found for Rb, V, Sr, Zr, Sn, Y, Bi, and U in both Unit S1 and Unit S2, Mn, Co, and Cs in Unit S1, and La and Ce in Unit S2 ( Figure 1 ). Despite the total concentrations of Mn, Cs, Sn, Bi, and U being above the background levels of these elements in mining waste in this region [ 27 ], Rb, Sr, Zr, Y, La, V, Th, and Ce in mining ponds were below or only slightly exceeding the limits proposed by Ballesta et al. [ 56 ], which means the anthropic activities have a low impact on these soil metal concentrations in the study area, not presenting a significant risk and indicating a natural origin of these elements [ 27 ]. 2.2.3. Relation and Behavior among Metal(loid)s and REEs In this study, total V, Sr, Zr, and Cs positively correlated with pH, while Zn, Al, Fe, Sn, Mo, Cd, Ge, La, Th, Pr, Ce, U, and Y negatively correlated with soil pH ( Supplementary Material, Table S1 ). However, some studies did not show any correlation between the total metal content (Pb, Th, U, Zn, Cd, Rb, V, and Co) in the soil with pH [ 57 ]; others found a negative or positive correlation of total content of elements (Sb, As, and Cu) and (Cr, Ni, and As) in soils with pH, respectively [ 58 , 59 ]. Soils with a neutral and alkaline pH generally have high calcium carbonate content, and together with alkaline pH values, many dissolution and precipitation processes are controlled by pH, which can finally predict the retention or migration of metals in soil. Probably considering that the mining wastes are acid with a high PTE mobility, PTEs are spread from the contaminated landfills into the surrounding soils and to Unit areas, where the high pH favors their precipitation and accumulation. In addition, the wind deposition could contribute to this high level of PTEs in the Units evaluated. Among all evaluated elements, only Sr had a significant positive correlation with EC, while V, Y, La, Ce, Pr, Th, Ge, Zn, and Al negatively correlated with EC ( Supplementary Material, Table S1 ). Strontium may attribute in or near sedimentary rocks associated with beds or lenses of gypsum, anhydrite, and rock salt as well as in veins associated with limestone and dolomite, and dispersed in shales, marls, and sandstones [ 60 ], so the positive correlation with EC is possible. While most elements such as Ni, Mo, In, Ge, Zn, Fe, Se, and Sn are positively correlated with sand and negatively with clay, total Zr and Cs showed a negative correlation with sand fraction in the studied area ( Supplementary Material, Table S1 ). Moreover, Bi positively correlated with sand and silt fraction, while it was negatively correlated with clay. In addition, Mn, Co, Cu, and Sr are also positively correlated with silt ( Supplementary Material, Table S1 ). Adriano [ 61 ] reported that minerals present in silt fractions have elements such as Cu, Pb, Bi, Sn, and Fe in their composition. The accumulation of more alkali metals such as Cs, Rb, and K in the finer-than-sand fractions of the soils than in the sand fractions is a common phenomenon and is due to the dilution of the alkali metal-bearing phases with quartz [ 41 ]. In addition, the enrichment of coarser soil fraction by metals resulted in more distribution of these pollutants to nearby soils by wind and water erosion. The concentrations of several of the elements were positively correlated ( Supplementary Material, Table S2 ). Significant positive correlations between REEs and metal(loid)s containing La, Ce, Pr, Th, Y, U, V, and Cd with Ge, Al, Zn, and Fe were found ( Supplementary Material, Table S2 ). Moreover, a positive correlation between REEs and other metals such as Ce, Pr, Y, Th, Ni with Sn, and Se, and between REEs such as La, Ce, and Pr revealed that they had similar inputs or common geochemical characteristics [ 49 ]. Azizi et al. [ 27 ] indicated that Cr, Ni, La, Ce, Rb, Pr, Mo, U, Cd, Zn, V, and Co were associated with Al and/or Mn minerals as impurities. Like other studies, a positive correlation was found between Ni and Cr ( Supplementary Material, Table S2 ), which can be concluded that transport, accumulation, and sources of Ni and Cr could be similar due to a high correlation between them [ 23 ]. Similar to tailing near the study area [ 27 ], a positive correlation was found between Bi and Pb in soils, which indicates the same origin ( Supplementary Material, Table S2 ). 2.2.4. Available and Water-Soluble Metal(loid)s and Rees In most cases, the total concentration of an element will not be available for immediate uptake by plants. The result showed that the concentration of available V, As, Sr, Sb, Rb, and Cs were higher in Unit S2 than in Unit S1, while Y and Cd were higher in Unit S1 than in Unit S2 ( Table 3 ). The most available percentage of metal(loid)s and REEs evaluated were Pb, Cd, Mn, Cu, Sr, Co, Sb, Y, and Zn (14.45%, 16.53%, 10.04%, 6.98%, 5.30%, 4.09%, 3.37%, 3.24%, and 3.06% of total concentration, respectively). Available concentrations of Sn and Cs were almost equal to zero, and in the case of Cr, As, Th, and Rb were lower than 0.1 percent of the total content in the soils. The high amount of available fraction of contaminant in the soil will show whether this soil poses a possible risk of toxicity to some species of plants, soil fauna, or microorganisms [ 62 ]. Moreno-Jimenez et al. [ 62 ] showed that Cd and Mn were significantly more easily extractable than the other metals, while Cu showed low extractability and Fe was strongly retained in soils. Similar to our result, Loell et al. [ 63 ] showed that among different REEs, Yttrium was the most available element when the soil was extracted with ethylenediaminetetraacetic acid (EDTA). Availability is affected by many factors, including pH, redox status, macronutrient levels, available water content, and temperature [ 36 ]. Previous research showed that As tends to bind to a Fe oxide/hydroxide phase [ 64 ], Zn to CaCO 3, and Pb to Fe and Mn oxides and oxyhydroxides [ 65 ]. Correlation between soil properties and available concentration of elements showed that Cu, Mo, Cd, La, Bi, Rb, and Zn were negatively correlated with clay content ( Supplementary Material, Table S1 ). Moreover, a significant negative correlation was found between available Y, Cd, La, Pr, Fe, and Zn and soil pH ( Supplementary Material, Table S1 ). It can be stated that soils with a neutral and alkaline pH generally have high calcium carbonate content. Together with alkaline pH values, the presence of carbonates in the soil enhances the retention of metal(loid)s mainly as carbonate salts, as a consequence of the ionic exchange, which is the principal retention mechanism of metals [ 33 ]. Similar to available metal(loid)s and REEs, Unit S2 soils generally showed higher concentrations of water-soluble V, As, Sr, Sb, Rb, and Cs than Unit S1 soils ( Table 4 ). Moreover, water-soluble Mo, La, and Ce were higher in Unit S2 than Unit S1 and Mn in Unit S1 than Unit S2 ( Table 4 ). In spite of available concentration, which shows no significant changes with depth, the water-soluble concentrations of Cr, Mn, Co, Ni, As, Y, In, Pr, and Zn tended to be lower while depth increased, especially for In, Mn, Co, and Zn which showed 11.6-, 7.98-, 3.20- and 2.59-times decreases from the surface (0–15 cm) to subsurface (15–30 cm) soils. The same result was reported by Martínez-Martínez et al. [ 65 ], who found that the concentrations of soluble Pb and Zn were higher in the surface layer than in the subsurface layer. When the mean of all data was evaluated, it showed that among all elements, Sb and Mn were found more in water-soluble fraction (2.87% and 0.82%, in comparison to total concentration), and Bi and Sn were not found in a water-soluble form (lower than detection limit) ( Table 4 ). The water-soluble fraction of Pb, Cd, Mn, Cu, Sr, and Co decreased to less than 0.3% in comparison to the total concentration. These results indicate the lower mobility of these metals, assuming a lower risk of dispersion by runoff or leachate waters to the environment. The highlighted water-soluble Fe (2005–2024 µg kg −1 , in Units S1 and S2), Pb (1419 µg kg −1 in Unit S2), and Zn and Al (1333 µg kg −1 in Unit S1) are still high, which indicates that these metals can be transported by water and pollute the surrounding areas and act as secondary contamination sources ( Table 4 ). Martinez-Martinez et al. [ 65 ] have also reported the relatively high mobility of Zn in the soil environment. In addition, a negative correlation was found between clay content and water-soluble Mn, Co, Ni, Cu, Y, Cd, Ce, Pr, Ge, Rb, Zn, Fe, and Cr ( Supplementary Material, Table S1 ). It is well known that the increase in clay content in the soil increases the number of cations sorbed by available sites [ 51 ] and reduces their mobility. However, this depends on the clay mineral(s) present in the soil clay fraction. Other soil properties such as CaCO 3 content, other metals concentration, and soil organic carbon are also among important factors that may affect water-soluble forms of metal(loid)s and REEs in soils [ 63 , 65 ]. For example, Alvarez-Rogel et al. [ 66 ] found that water-soluble Cu was strongly correlated with water-soluble organic carbon, and the highest concentration of this metal in water extracts was found in a forest away from mine tailings soils, and a decrease in water-soluble Pb was observed when total Fe concentrations increased, while water-soluble Pb and total CaCO 3 were uncorrelated [ 66 ]. 2.3. Accumulation of Heavy Metals and Metalloids in Plant Tissues The concentrations of different metal(loid)s and REEs in plant tissues are shown in Table 5 , showing variable patterns of metal accumulation and distribution in their various parts and different soil units. Peñalver-Alcaraz et al. [ 15 ] and Martinez-Lopez et al. [ 18 ] reported that the growth of natural plants such as Salsola and P. miliaceum in harsh environments such as mine tailings that were polluted with metal(loid)s, indicating an adaptation and tolerance to contaminated conditions. The data showed the metal(loid) concentration in the plant tissues varied among species when compared in different units, indicating that the different capacities of plants for metal uptake could be affected by soil. The Zn concentration in plant shoots was found in variables ranging from deficient ( P. miliaceum in Unit S2) to 547 mg kg −1 ( S. oppositifolia in Unit 1), which is considered to be toxic according to Kabata-Pendias (100–400 mg kg −1 ) [ 67 ], and the maximum concentration was found in the root (687 mg kg −1 ) of P. miliaceum in Unit S1 ( Table 5 ). The result of this research is in accordance with Ha et al. [ 68 ], who found a range of 13.3–380 mg kg −1 Zn accumulated in 21 native plant species grown in the soil near mining areas, with no toxicity symptoms. BCF shoot > 1 and TF > 1 for Zn in S. oppositifolia revealed the effective absorption of Zn by roots and translocation to the aerial tissues, which could make this plant a candidate for the phytoextraction process only in Unit S1 ( Table 6 and Figure 2 ). Therefore, this plant was successful in the mobilization of Zn into plant tissues and storage in the aerial plant biomass (TF > 1), but had difficulties in mobilizing Zn in the root zone of Unit S2 (BCF root and BCF root < 1). Pb is not an essential element for plants, and its normal concentration is 5–10 mg kg −1 ; it becomes toxic to various plant species if it presents at 30–300 mg kg −1 in leaves [ 67 ]. The results showed that in S. oppositifolia and P. miliaceum , in Unit S1, Pb accumulated at a toxic level (31.4 and 31.1 mg kg −1 , respectively) ( Table 5 ). This should be considered the potential risk of incorporation of Pb into the food chain if local fauna feed on the leaves of S. oppositifolia and P. miliaceum . P. miliaceum , known as pioneer vegetation for the phytomanagement of metal(loid)-enriched tailings, could uptake 5.4 mg kg −1 Pb in leaves [ 26 ], which was lower than our result. The BCF root and BCF shoot index revealed that among all plants in the study area, P. miliaceum showed BCF root > 1 for Pb in Unit S1, and these factors were smaller than the ones in other plant species, and TF were less than 1 in all cases; therefore, P. miliaceum can be considered interesting for phytostabilization of Pb in soil ( Table 6 and Figure 2 ). Pb uptake studies in plants have demonstrated that roots have the ability to take up significant quantities of Pb, as in this study, P. miliaceum accumulated 1943 mg kg −1 in their roots, whilst it is simultaneously known as an immobile element in plant tissues, greatly restricting its translocation from root to shoot [ 33 , 69 ]. Similar to our study, Hasnaoui et al. [ 70 ] found that four plant species, Reseda alba , Cistus libanotis , Stipa tenacissima , and Artemisia herba-alba showed a strong capacity to tolerate and hyperaccumulate metal(loid)s, especially Pb, in their tissues. There is no evidence of the essential role of Cr in plant metabolism (as there is in animals and humans), although plants accumulate it when it is available in the soil [ 36 ]. Considering the phytotoxic concentration of Cr (5–30 mg kg −1 ) in leaf tissue for different plant species reported by Kabata-Pendias [ 67 ], P. miliaceum in Unit S1 showed toxicity, which reflects the ability of this plant to adsorb and accumulate Cr. Total Cr concentration in plant shoot samples ranged from 1.03 mg kg −1 ( A. herba-alba in Unit S2) to 6.61 mg kg −1 ( P. miliaceum in Unit S1), with the maximum level in the root of P. miliaceum (9.18 mg kg −1 ) in Unit S2. In addition, S. tenacissima showed an approximately high concentration of Cr in their shoots (3.6 mg kg −1 ) in both Unit S1 and Unit S2 ( Table 5 ). The BCF shoot and TF revealed that in all plant species, BCF shoot had Cr > 1 while the concentration of Cr in the shoots of P. miliaceum , S. tenacissima , and S. oppositifolia were 218, 79, and 50 times higher than those available in the soil of Unit S1, indicating a good capacity for bioaccumulation of Cr by these plants ( Table 6 and Figure 2 ). Sinha et al. [ 71 ] reviewed that the reduction in Cr(VI) to Cr(III) by chemical or enzymatic processes, compartmentalization of Cr in the cytoplasm or in the vacuole, and phytochelatin-based sequestration are among the mechanisms that different plants acquired to cope with a high level of absorbed Cr. TF of Cr in all studied plants was higher than 1, and we concluded that these plants are proper candidates for phytoextraction of Cr in soil ( Table 6 and Figure 2 ). Cd is not an essential element in plant metabolic processes, and there is also no evidence of an essential role of Ni in plant metabolism, while Cu is an essential element for vegetation. When the available concentration of these metals increases in soil, they may be highly absorbed by plants, finally leading to toxicity in the plant. Kabata-Pendias [ 67 ] proposed the level of concentration of Cd, Ni, and Cu in leaves that caused toxicity to be 5–30, 10–100, and 20–100 mg kg −1 , which in our study were lower in plants, since the highest concentrations of Cd and Cu were observed in S. oppositifolia in Unit S1 (3.48 and 15.5 mg kg −1 , respectively) and Ni in S. tenacissima (6.57 mg kg −1 ) in Unit S2 that exceed the supraoptimal values of these elements proposed by Kabata-Pendias [ 67 ] (0.05–0.20, 5–30 and 0.10–0.50 mg kg −1 , respectively). Moreover, except for Cd concentration in P. miliaceum in Unit S2 and Cu concentration in S. tenacissima and P. miliaceum in both soils, other plants showed more metal than the sufficient or normal concentration accepted in plant shoots [ 67 ] ( Table 5 ). Midhat et al. [ 33 ] found that the majority of the collected plant species from three mining sites (Southern Centre Morocco) showed higher PTE concentrations than the normal or phytotoxic levels. They concluded that these plant species were tolerant to the studied PTEs surviving in soils with a high concentration of PTEs which are toxic to other plants, showing the ability to accumulate PTEs in their tissues without symptoms of toxicity [ 33 ]. The results revealed that for Ni, BCF shoot was more than 1 in S. oppositifolia and S. tenacissima , and less than 1 in A. herba-alba while in P. miliaceum it was soil-dependent; that is, it was more than 1 in Unit S1 and less than 1 in Unit S2. Among different plants, only S. oppositifolia in Unit S2 showed BCF shoot > 1 and TF > 1 for Cd and A. herba-alba and P. miliaceum in Unit S1 BCF root > 1 and TF < 1 for Cd, which means they are suitable for phytoextraction and phytostabilization, respectively ( Table 6 and Figure 2 ). Hasnaoui et al. [ 70 ], in the screening of native plants growing on a Pb/Zn mining area in eastern Morocco, found that BCF root , BCF shoot , and TF for Cd in S. tenacissima and A. herba-alba were 2.72–0.80, 0.32–1.10, and 0.11–1.11, respectively. TF for Ni was more than 1 in all plants and soils except that of P. miliaceum in Unit S2. Briefly, while S. oppositifolia and S. tenacissima are good candidates for Ni phytoextraction, A. herba-alba is not a proper candidate in this regard, and P. miliaceum could phytoextract Ni only in Unit S1 ( Table 6 and Figure 2 ). Hasnaoui et al. [ 65 ] reported that in their study BCF root , BCF shoot , and TF for Ni in S. tenacissima and A. herba-alba were 0.40–0.54, 0.23–0.62, 0.59–1.24, respectively. S. oppositifolia , S. tenacissima , and P. miliaceum in Unit S1 and A. herba-alba in Unit S2 showed BCF root > 1 and TF < 1 for Cu, and could be a candidate for phytostabilization. Moreover, S. oppositifolia in Unit S1 was the only plant that had BCF shoot > 1 and TF > 1, and was suitable for the phytoextraction of Cu from soil ( Table 6 and Figure 2 ). Hasnaoui et al. [ 70 ] reported that in their study BCF root , BCF shoot , and TF for Cu in S. tenacissima and A. herba-alba were 1.55–3.36, 0.19–1.29, and 0.12–0.35, respectively. The results obtained from plant analysis showed that the concentration of V, As, Co, Mn, Mo, Se, and Sb in the shoots of plants are in the sufficient or normal range proposed by Kabata-Pendias [ 67 ] ( Table 5 ). In the average of two Unit soils, the minimum and maximum of V and As found in P. miliaceum and A. herba-alba (614–1380 and 947–7144 µg kg −1 , respectively), Mn, Co, and Se in S. oppositifolia and A. herba-alba (18,993–136,394, 102–351 and 47.3–67.6 µg kg −1 , respectively) while A. herba-alba showed the maximum (663 µg kg −1 ) and S. tenacissima minimum (306 µg kg −1 ) concentration of Mo ( Table 5 ). Different species from the Salsola genera are the major species in semiarid environments due to their fast growth, large biomass, drought tolerance, and universal adaptability, including in extremely harsh environments, and play an important role in phytoremediation processes of different metal(loid)s such as Co, Fe, Mn, Sr, As, V, Mo, and Cd [ 24 ]. According to data from TF, BCF root, and BCF shoot , it can be concluded that A. herba-alba has the ability for the phytoextraction of V (TF > 1 and BCF shoot > 1), while other plants could stabilize this element (TF < 1 and BCF root > 1). All plants accumulate high amounts of As in their roots (BCF root for P. miliaceum , S. tenacissima , and S. oppositifolia were 790, 80, and 69, respectively, in Unit S1) except for S. tenacissima in Unit S1; therefore, these native plant species with both the capacity to accumulate high amounts of As in their roots and have low values of the translocation from root to shoot (TF < 1), could be used to minimize the migration of As in soil ( Figure 2 ). Based on BCF root , TF, and BCF shoot values, none of the plant species have the potential to be used in Mn and Co phytoextraction or phytostabilization except for S. oppositifolia , which has the potential to extract Mn (BCF shoot and TF were 3.44 and 1.80, respectively) and stabilize Co (BCF root and TF were 1.47 and 0.70, respectively) in Unit S1 ( Figure 2 ). The high BCF shoot values for Mo in S. oppositifolia (29.6), S. tenacissima (11.5), and P. miliaceum (21.2), with TF > 1 (5.09, 1.52, and 1.44, respectively), were measured, which then suggested these plants were suitable for Mo phytoextraction from the soil. However, the BCF root >1 and TF < 1 of Mo (19.08) in A. herba-alba showed their high ability to tolerate and accumulate Mo in their roots, suggesting they are suitable for Mo phytostabilization ( Table 6 and Figure 2 ). In our study, total Al concentration in plant samples ranged from 578 mg kg −1 ( S. tenacissima in Unit S1) to 41.5 mg kg −1 ( S. oppositifolia in Unit S1), with the maximum level in the roots of S. tenacissima (750 mg kg −1 ) in Unit S1 and the roots of P. miliaceum (660 mg kg −1 ) in Unit S2 ( Table 5 ). Considering the mean concentration of Al (10–1000 mg kg −1 ) in leaf tissue for different plant species reported by Kabata-Pendias [ 67 ], in all plants, the Al concentration of shoots was in the given range, which means there is not any risk of toxicity entering the food chain. However, Aluminum toxicity is an important growth-limiting factor for plants in acid soils, especially below pH 5.0 [ 36 ]; the alkaline pH of the study area leads to a decrease in Al availability, despite the high total concentration in the soil ( Table 2 and Table 4 ). BCF root and BCF shoot in all plants were higher than 1 (maximum for S. tenacissima were 116 and 55.3 in Unit S1, respectively ( Table 6 and Figure 2 ), while TF was variable for plants according to soil unit (e.g., in the case of S. tenacissima TF < 1 in Unit S1 and TF > 1 in Unit S2), and only in the case of S. oppositifolia , it was less than 1 in both soils, so this plant has the ability to stabilize Al in both Units ( Table 6 and Figure 2 ). The result of REEs accumulation in plants revealed that Y, La, Ge, and Pr concentration in shoot showed maximum levels in S. oppositifolia and P. miliaceum in Unit S1 (512–517, 497–734, 133–261, and 110–198 µg kg −1 , respectively), Ce in S. oppositifolia , S. tenacissima , and P. miliaceum in Unit S1 (519, 542 and 1307 µg kg −1 , respectively) and Th in P. miliaceum (421 µg kg −1 ) in Unit S1 ( Table 5 ). Wiche and Heilmeier [ 72 ] found the mean concentrations of La as representative for the REEs ranged from 24 to 146 ng g −1 in grasses ( Hordeum vulgare , Zea mays , Avena sativa , P. miliaceum , and Phalaris arundinacea ) and 20–250 ng g −1 in herbs ( Lupinus albus , Lupinus angustifolius , Fagopyrum esculentum , and Brassica napus ) when grown in soil from a road construction site or mining affected area containing 25–26 µg g −1 total La. With the exception of hyperaccumulating plants, the content of REEs in plants is generally very low [ 47 ]. In general, the concentration of REEs in plants is influenced by several factors, namely soil properties, e.g., pH and total C, cation exchange capacity, redox potential, availability and nature of other elements, e.g., N, P, Ca, Mg, and Al, and plant species, especially in regard to root characteristics [ 47 ]. For instance, treatment of soil with organic material (OM) may inhibit REE uptake by Phytolacca Americana through competition between cations (e.g., Ca and Mg) and REEs, and adding biochar to soil may avoid the extensive precipitation of P and REEs on the root surface and root apoplast, thereby promoting REE uptake by plants [ 73 ]. Similarly, Saatz et al. [ 74 ] found significant correlations between the concentration of Gd and Y in the nutrient solution and the root tissue concentration of Ca, Mg, and P. The result of TF showed that A. herba-alba had TF > 1 for La, Ce, Pr, Y, and TF < 1 for Th; S. oppositifolia in Unit S1 had TF > 1 for La, and other plants had TF < 1 for all REEs ( Figure 2 ). Under normal circumstances, the TF of REEs is less than 1, except for hyperaccumulating ones [ 47 , 75 ]. By considering if BCF root > 1 and TF < 1, the plant could be a good candidate for phytostabilization, and BCF shoot > 1 and TF > 1 could select the plant for phytoextraction; it was found that for La, S. oppositifolia , S. tenacissima , and P. miliaceum had a BCF root of 1.45, 3.28, and 5.86, respectively, and could stabilize La in the root. For Ce, S. tenacissima and P. miliaceum had a BCF root of 2.14 and 5.26, for Th S. oppositifolia , S. tenacissima and P. miliaceum had a BCF root of 3.6, 6.74, and 10.1, and for Pr S. oppositifolia , S. tenacissima and P. miliaceum had a BCF root of 1.25, 3.85, and 5.18, and therefore, these native plant species with both the capacity to accumulate these REEs in their roots and low values of the translocation from root to shoot could be used for phytostabilization. None of the plant species has the potential to be used in phytoextraction of REEs and/or phytostabilization of Y ( Table 6 and Figure 2 ). The selective absorption of root cell walls (in the form of trivalent cations) and the co-precipitation of rare earth ions-salts (mostly in the form of insoluble oxalates or phosphates) are the main mechanisms through which plant roots fix REEs [ 76 ]. When REEs come in contact with plant roots, rare earth cations combine with free carboxyl groups such as cellulose and pectin on the cell wall, and the positive and negative charges attract each other, resulting in selective absorption by the cell wall [ 47 , 77 ]."
} | 13,312 |
37484473 | PMC10361787 | pmc | 2,205 | {
"abstract": "Grazing disturbance can change the structure of plant rhizosphere microbial communities and thereby alter the feedback to promote plant growth or induce plant defenses. However, little is known about how such changes occur and vary under different grazing pressures or the roles of root metabolites in altering the composition of rhizosphere microbial communities. In this study, the effects of different grazing pressures on the composition of microbial communities were investigated, and the mechanisms by which different grazing pressures changed rhizosphere microbiomes were explored with metabolomics. Grazing changed composition, functions, and co-expression networks of microbial communities. Under light grazing (LG), some saprophytic fungi, such as Lentinus sp., Ramichloridium sp., Ascobolus sp. and Hyphoderma sp., were significantly enriched, whereas under heavy grazing (HG), potentially beneficial rhizobacteria, such as Stenotrophomonas sp., Microbacterium sp., and Lysobacter sp., were significantly enriched. The beneficial mycorrhizal fungus Schizothecium sp. was significantly enriched in both LG and HG. Moreover, all enriched beneficial microorganisms were positively correlated with root metabolites, including amino acids (AAs), short-chain organic acids (SCOAs), and alkaloids. This suggests that these significantly enriched rhizosphere microbial changes may be caused by these differential root metabolites. Under LG, it is inferred that root metabolites, especially AAs such as L-Histidine, may regulate specific saprophytic fungi to participate in material transformations and the energy cycle and promote plant growth. Furthermore, to help alleviate the stress of HG and improve plant defenses, it is inferred that the root system actively regulates the synthesis of these root metabolites such as AAs, SCOAs, and alkaloids under grazing interference, and then secretes them to promote the growth of some specific plant growth-promoting rhizobacteria and fungi. To summarize, grasses can regulate beneficial microorganisms by changing root metabolites composition, and the response strategies vary under different grazing pressure in typical grassland ecosystems.",
"conclusion": "5 Conclusion In this study, plants root exude specific metabolites to selectively regulate functional rhizosphere bacteria and fungi from the soil environment. These increased plant growth and protected plants by modulating plant defense capacity to help plants resist grazing stresses and thereby enhancing their ability to adapt to the environment ( \n Figure 8 \n ). Grassland plants responded to grazing by actively regulating the synthesis of root metabolites under grazing interference, and then secreting them to regulate specific rhizosphere microorganisms, although the response strategies varied under different grazing pressures. Under light grazing, it is inferred that root metabolites, especially AAs such as L-Histidine, may regulate specific saprophytic fungi to participate in material transformations and the energy cycle and ultimately promote plant growth. Furthermore, to help alleviate the stress of heavy grazing and improve plant defenses, it is inferred that the root system actively regulates the synthesis of these root metabolites such as AAs, SCOAs, and alkaloids under grazing interference, and then secretes them to promote the growth of some specific plant growth-promoting rhizobacteria and fungi. Figure 8 Mechanistic model of beneficial microbial regulation by root metabolites under different grazing pressures. Under light grazing, the root metabolite L-Histidine may regulate specific saprophytic fungi to participate in the energy cycle of a grassland ecosystem and promote plant growth. Under heavy grazing, plants may promote the growth of plant growth-promoting rhizobacteria and beneficial mycorrhizal fungi by amino acids (AAs), short-chain organic acids (SCOAs), and alkaloids to help alleviate the stress and improve plant defenses.",
"introduction": "1 Introduction Grasslands are one of the largest and most important terrestrial ecosystems that not only effectively maintain global ecosystem services but also provide a resource with great potential for food production ( Fan et al., 2021 ). Many grasslands have been degraded due to climate change and improper anthropogenic interference, especially overgrazing ( Slimani et al., 2010 ). Grazing is a common form of land-use worldwide and it drives changes in composition of soil microbial communities ( Eldridge et al., 2017 ). Grazing by herbivores can directly and indirectly affect plant roots and soil microbial community composition by trampling, effects on litter decomposition, and deposition of animal dung and urine ( Eldridge and Delgado-Baquerizo, 2017 ). Moreover, effects vary with different grazing pressures. Light and moderate grazing can improve grassland ecosystem functions by increasing nutrient cycling rates, dry matter production, and energy storage and by facilitating activities of soil microbial communities ( Zhao et al., 2017 ; Chen et al., 2021 ). By contrast, heavy grazing decreases defoliation and decreases aboveground biomass, resulting in decreased photosynthesis and reduced inputs of belowground carbon ( Aldezabal et al., 2015 ). Plants and associated microbiomes form a “holobiont”, within which plant–soil microbiome interactions have key roles in nutrient acquisition and stress tolerance ( Miyauchi et al., 2020 ). Environmental stress can lead to changes in plant physiological states and metabolic pathways, which influence the composition of rhizodeposits, including root exudates and complex root tissue compounds. Plants likely adopt the “cry for help” strategy to actively seek cooperation with different microbes to combat environmental stresses and increase resistance, which includes the secretion of root compounds into the rhizosphere ( Toju et al., 2018 ; Li et al., 2022 ). Plant root exudates comprise primary metabolites such as sugars, amino acids, and organic acids, as well as secondary metabolites such as lipids, flavonoids, terpenes, phytohormones, and alkaloids, all of which are used as an energy source or as a metabolic signal for the recruitment of microorganisms in order to modulate plant performance ( Schmidt et al., 2019 ). Rhizodeposits attract specific soil microorganisms to colonize roots and rhizospheres and act as signals to mediate positive interactions with beneficial microorganisms such as rhizobia, mycorrhizal fungi, and plant growth-promoting rhizobacteria (PGPR) ( Vives-Peris et al., 2020 ). For example, malic acid can attract specific beneficial bacteria to the rhizosphere ( Rudrappa et al., 2008 ), and specific flavonoid compounds released by some legumes can recruit nitrogen-fixing bacteria ( Hassan and Mathesius, 2012 ). Compounds secreted by roots such as strigolactones are key in promoting colonization of mycorrhizal fungi ( Steinkellner et al., 2007 ). In addition, secretion of antimicrobial compounds, such as coumarin, alters assembly of root-associated microbial communities, triggers induced systemic resistance (ISR), and increases resistance to herbivores ( Stringlis et al., 2018 ). Thus, plants can alter the secretion pattern and composition of root exudates when attacked to regulate beneficial microbes and shape the microbial community. Corresponding intra-plant metabolic signals between aboveground and belowground parts are used to increase plant resistance ( Rasmann et al., 2005 ). Recent studies have shown that grazing disturbance can significantly alter the structure of plant rhizosphere microbial communities, and feedback acts on the plants to promote its growth ( Li et al., 2022 ). In addition, a negative correlation was found between grazing intensity and root exudates production, and root exudate regulated soil microbial community composition ( Zhao et al., 2017 ). In our previous study, the grass Leymus chinensis released metabolic signals to recruit key beneficial bacteria and alleviate grazing stress ( Yin et al., 2022 ). Leymus chinensis is one of the dominant C3 grasses of the Eurasian steppe, and it is important in maintaining grassland ecosystem functions as well as animal production because of its good palatability ( Wang and Ba, 2008 ). Here, we studied the changes of rhizosphere bacterial and fungal communities of L. chinensis under different grazing pressures in typical grasslands, and their relationship with root metabolites. We ask three key research questions. Can plants regulate specific beneficial microorganisms in response to grazing? Is there any difference in the beneficial microbiome regulated by plants between light and heavy grazing? Which metabolites produced by roots are responsible for this change? We hypothesized that plants can regulate beneficial microorganisms by changing root metabolites composition, and the response strategies vary under different grazing pressure in typical grassland ecosystems. The aim of this study was to (i) explore the effects of light and heavy grazing on L. chinensis root metabolites, rhizosphere microbial community composition, and soil properties, and (ii) determine the specific functions of L. chinensis root metabolites in the regulation of beneficial bacteria and fungi under light and heavy grazing. The changes in L. chinensis root metabolites were evaluated using LC-MS and changes in the rhizosphere microbiome using Illumina sequencing.",
"discussion": "4 Discussion 4.1 Effects of grazing on soil microbial communities The purpose of this study was to determine the interaction between plant roots and soil microorganisms in typical grasslands with different grazing pressures. Our results revealed that grazing changed microbial community composition, but no significant differences were found between grazing and no grazing treatments in alpha diversity of rhizosphere bacteria and fungi. Grazing can affect soil microbial communities in multiple ways, and different levels of grazing pressure have different effects on soil microbial diversity, composition, and structure ( Delgado-Baquerizo et al., 2016 ; Wang et al., 2020 ). A previous study confirmed that light grazing significantly affected soil fungal community composition but did not affect bacterial community composition in the semiarid grassland ecosystem ( Chen et al., 2021 ). Those results are consistent with the greater numbers of significantly enriched fungal genera than bacterial genera in LG than in NG in this study. Moreover, the numbers of significantly enriched core bacterial genera were greater under HG than under LG, with the dominant bacterial genera were mainly composed with Proteobacteria, Actinobacteria and Acidobacteria, which were significantly enriched( \n Figure 2A \n ). Those key bacterial phyla are associated with plants and contribute to resistance against environmental stresses ( Palaniyandi et al., 2013 ). In addition, light grazing is beneficial to plants that grow slowly and produce low-quality litter, which is conducive to the growth of soil fungi, whereas heavy grazing is beneficial to plants that grow rapidly and produce high-quality litter, which favors soil bacteria ( Strickland and Rousk, 2010 ). Similarly, relative abundances of some dominant fungal genera in the phyla Ascomycota and Basidiomycota shifted significantly in response to LG and HG treatments ( \n Figure 2B \n ). The results indicated that Basidiomycota and Ascomycota were dominant phyla of root-related fungi, possibly because of adaptation to grazing stress as well as nutrient limitation, which is consistent with previous studies ( Marcos et al., 2019 ; Chen et al., 2017 ). The co-occurrence network analysis of microbial communities indicated that LG significantly reduced the complexity of the bacterial network compared with that in NG ( \n Figures 3A, B \n ). The result is consistent with those of previous studies in which bacterial networks were smaller and less connected in grazed soil than in ungrazed soil ( Chen et al., 2020 ). By contrast, the connectivity of fungal networks in HG was more complex than that in NG, whereas changes in the bacterial network in HG were not obvious ( \n Figure 3 \n ). The results indicated that bacterial communities were more stable than fungal communities in HG. The difference in response between microbes might be because heavy grazing reduces the availability of soil C for microbial colonization. Fungi are more dependent on the soil C matrix than bacteria, and therefore, under C limitation with heavy grazing, competition for rhizosphere soil niches among fungi increases ( Chen et al., 2018 ). Heavy grazing decreases plant biomass and root productivity, which leads to a reduction in soil organic C ( Wang et al., 2017 ). Similarly, in this study, a significant reduction in TOC was observed in LG and HG compared with that in NG ( \n Table 1 \n ), which is consistent with previous findings that TOC decreases with an increase in grazing pressure ( He et al., 2008 ). As a result of the reduction in TOC, competition within the fungal community for the soil C matrix increases, thereby decreasing community stability under adverse environmental conditions ( Newman, 2006 ). Notably, the effect of grazing on bacterial networks was much greater than that on fungal networks, which is a result similar to those in a previous study that found bacterial communities have greater network complexity than that of fungal communities ( Wang et al., 2021 ). The cooperative relations among members of a bacterial network are stronger than those of a fungal network in the soil of a grazed grassland, indicating increased stability and tolerance to grazing disturbance ( Zhang et al., 2018 ). In addition, livestock consume nearly half of aboveground biomass and return it as manure rich in available nutrients and organic substrate, which can be conducive to bacterial growth ( Bagchi and Ritchie, 2010 ). According to Tax4Fun analysis of bacteria, pathways associated with Amino acid metabolism and Energy metabolism were upregulated in the bacterial function prediction analysis of HG treatment compared with NG treatment ( \n Figure 4A \n ). The results are similar to those obtained in a study of bacterial functions in wheat, barley, and tomato soils ( Pii et al., 2016 ; Qu et al., 2021 ), which is that the most representative pathways of rhizosphere soil after stress treatment are all amino acid metabolism and energy metabolism. After some metabolites associated with amino acid metabolism and energy metabolism being exuded, it is most likely used by soil microorganisms as C and N source ( Pii et al., 2015 ). These data further confirm that the rhizosphere microbial community respond to the plants by modifying their metabolic activities, aiming at promoting bacterial growth by, suggesting that root metabolites affect bacterial community composition and function as C and N sources. Thus, as one of the main signaling molecules and supplies of nutrients in HG, AAs might be crucial in reshaping bacterial communities under heavy grazing. The fungal Pathotroph-Saprotroph-Symbiotroph mode increased in LG but decreased in HG compared with that in NG ( \n Figure 4C \n ). The result indicated that LG promoted synergistic interactions among Pathotroph-Saprotroph-Symbiotroph ( Bello et al., 2021 ). Saprotrophic fungi can promote litter decomposition and nutrition cycling rates ( Wang et al., 2022 ). In this study, compared with NG, grazing resulted in significant increases in relative abundances of saprophytic fungi, which can promote nutrient cycling and formation of soil organic matter ( Zhang et al., 2019 ). Among functional guilds, relative abundances of Arbuscular Mycorrhizal in LG treatment were significantly higher in LG than in NG. Mycorrhizal fungi relieve C restrictions on saprophytic microorganisms, stimulate the growth of saprophytic microorganisms and the production of extracellular enzymes, and accelerate the decomposition of litter and organic matter through mycelial secretions or turnover of biomass. Moreover, C released after arbuscular mycorrhizal fungi infect roots induces changes in rhizosphere bacterial and fungal communities and stimulates extracellular enzyme production of saprophytic microorganisms to obtain N and P ( Toljander et al., 2007 ). These processes indicate that arbuscular mycorrhizal fungi might provide additional C and energy to saprophytic microbes. 4.2 Plant–rhizosphere microbial interactions 4.2.1 Plant root metabolites regulate rhizosphere beneficial fungi to promote plant growth under light grazing In grassland ecosystems, many saprophytic fungi in the Ascomycota promote the mineralization of nutrient elements in soil and thus increase nutrient availability and uptake to promote plant growth ( Barnes et al., 2018 ; Bastida et al., 2019 ). Symbiotic fungi are primarily mycorrhizal fungi, and mycorrhizae can indirectly interact with saprophytic microorganisms via stimulating saprophytic activity and nutrient competition to affect litter decomposition as well as improve host plant resistance and adaptability ( Frew et al., 2018 ). In the analysis of fungal community composition in this study, the saprophytic fungi Tubaria sp., Hyphoderma sp., Teichospora sp., Crinipellis sp., Ascobolus sp., and Lentinus sp. and the mycorrhizal fungus Schizothecium sp. were significantly enriched under LG ( \n Figure 2B \n ). \n Schizothecium sp., Ascobolus sp., Lentinus sp., and Hyphoderma sp. are involved in plant litter decomposition, including decomposition of herbaceous stems, wood, and dung, and therefore are important ecosystem saprophytes in helping to recycle nutrients in animal dung ( Barron, 2003 ; Lakshmanan et al., 2008 ; Mumpuni et al., 2020 ). Ramichloridium sp. have potential in the control of diseases and in the promotion of plant growth ( Peters et al., 2020 ). Moreover, certain active fungi, such as the mycorrhizal fungus Schizothecium sp., colonize soils and are involved in the assimilation of root exudate, indicating specific fungi–plant root associations ( Hugoni et al., 2018 ). Schizothecium sp. also has biocontrol activity against Fusarium wilt ( Santoyo et al., 2021 ). Therefore, saprophytic and mycorrhizal fungi are two important fungal groups involved in most litter decomposition and nutrient cycling processes. In this study, saprophytic and mycorrhizal fungi promoted nutrient cycling and litter decomposition in the rhizosphere soil under LG ( Lindahl et al., 2007 ). Compounds secreted by roots can promote the establishment of mutualistic relations with different fungi. Beneficial fungi are attracted by specialized plant metabolites, such as sugars, organic acids, hormones, AAs, and antimicrobial compounds, which are used by fungi as sources of energy ( Devi et al., 2020 ; Yadav et al., 2020 ). Such fungi provide antagonist compounds to improve plant growth and increase nutrient availability as well as stress tolerance. For example, arbuscular mycorrhizal fungi and rhizobium bacteria can be recruited by signaling compounds secreted by plant roots ( Besserer et al., 2006 ). Furthermore, root secretions can affect the metabolic activity of some fungi ( de Graaff et al., 2010 ). Plants produce defensive compounds, nutrients, and signaling molecules during AAs metabolism that interact with microorganisms; in particular, AAs may be crucial in establishing symbiotic interactions ( Moormann et al., 2022 ). Abiotic stress can result in increased exudation of proline and L-theanine, which can be used as energy sources to recruit dominant microbes ( Vives-Peris et al., 2020 ; Xie et al., 2022 ). Similarly, L-Histidine is essential for plant growth and development, as well as inducing resistance to bacterial pathogens ( Seo et al., 2016 ). Changes in rhizosphere microbial community assembly may be caused by root exudates, but our results only analyzed the differential root metabolites and found that some differential metabolites were significantly enriched after LG ( \n Figure 5A \n ), and these differential metabolites may be secreted through the root system and affect microbial community assembly. In addition, some compounds detected in root exudates are usually synthesized at the roots and 63–85% of root metabolites were found in rice root exudates ( Mclaughlin et al., 2023 ). In Our study, beneficial saprophytic and mycorrhizal fungi were significantly positively correlated with L-Histidine ( \n Figure 7B \n ), which suggested these significantly enriched beneficial saprophytic and mycorrhizal fungi may be caused by these differential root metabolites, especially L-Histidine, and the saprotrophic fungi gained energy with consumption of the root metabolite ( Buée et al., 2009 ). Therefore, it is inferred that the root system actively regulates the synthesis of these root metabolites under grazing interference, and then secretes them to regulate some specific rhizosphere beneficial fungi and thereby promote litter decomposition, fecal decomposition, and the absorption of soil mineral nutrients. In this study, most soil properties were not significantly correlated with fungi, likely because host roots maintained a relatively stable feeding environment and feedback interactions with fungi. Because of the root microenvironment had undergone strong environmental filtration and the alteration of soil properties had a low effect on the alteration of fungi community in roots ( Beck et al., 2015 ). Therefore, under light grazing, it is inferred that root metabolites, especially AAs such as L-Histidine, may regulate specific saprophytic fungi to participate in material transformations and the energy cycle and ultimately promote plant growth in grassland ecosystems ( Guyonnet et al., 2017 ). 4.2.2 Root metabolites promote the growth of beneficial rhizosphere growth-promoting bacteria and fungi to relieve the stress of heavy grazing Plant metabolites have crucial effects in shaping root microbiomes ( Jacoby et al., 2021 ). Plants selectively recruit beneficial rhizosphere microbes by releasing specific metabolites, which may be very helpful in the fight against biotic and abiotic stresses ( Qu et al., 2020 ). The potentially beneficial bacteria Lysobacter sp., Stenotrophomonas sp., Microbacterium sp., and Planctomycete_WWH14 sp. and the beneficial mycorrhizal fungus Schizothecium sp. were significantly enriched in HG compared with NG ( \n Figures 2A, B \n ). Lysobacter sp. and Stenotrophomonas sp. are in the family Xanthomonadaceae, which has members that can directly inhibit pathogens with the secretion of secondary metabolites ( Brescia et al., 2020 ; Deng et al., 2022 ). Berendsen et al. (2018) reported that foliar infection with a biotrophic pathogen systemically signals to Arabidopsis thaliana to promote the growth of Microbacterium sp., Xanthomonas sp., and Stenotrophomonas sp. in the rhizosphere, and collectively, the three bacteria can induce systemic resistance against pathogens. Moreover, recruitment of Stenotrophomonas sp. can regulate plant defenses ( Liu et al., 2021 ). In addition, the beneficial mycorrhizal fungus Schizothecium sp. has potential biocontrol activity ( Santoyo et al., 2021 ). Therefore, the potentially beneficial microbes may prime plant defense signaling pathways and consequently ameliorate plant stresses. According to the findings of this study, under heavy grazing, plants may regulate specific microbes to increase defensive capabilities. Specialized plant metabolites such as flavonoids, organic acids, AAs, hormones, and triterpenoids can be used as signal molecules, stimulants, and attractants to shape the composition of microbial communities ( Baetz and Martinoia, 2014 ). For example, small-molecule organic acids can recruit Comamonadaceae ( Wen et al., 2020 ). In addition, A. thaliana can recruit and stimulate specific Pseudomonas populations by secreting long-chain OAs and AAs to cope with pathogens ( Yuan et al., 2018 ). The Pseudomonas can then activate induced systemic resistance and protect plants from pathogens ( Wen et al., 2021 ). A recent study has shown that some compounds detected in root exudates are usually synthesized at the roots and most root metabolites were found in plant root exudates ( Mclaughlin et al., 2023 ). Therefore, in our study, we conclude that part of the metabolites in root metabolites may be secreted outside the roots and thus affect the assembly of soil microbial communities. In addition, root metabolites can selectively regulate the growth of Arabidopsis root bacteria from different taxa by acting as antibiotics or proliferating agents ( Huang et al., 2019 ). Similarly, in this study, AAs, SCOAs, and alkaloids were the most abundant root metabolites, whereas sugars and phenolic acids were the least abundant in both LG and HG ( \n Figure 5B \n ), which may be because more complex amino acids and alkaloids produce more selective effects ( Yuan et al., 2018 ). In addition, these low molecular weight AAs (N-Acetyl-L-Aspartic Acid, L-Tryptophan, L-Asparagine and L-Ornithine), SCOAs (3-Ureidopropionic Acid) and alkaloid (Diethanolamine and 3-Indoleacrylic acid) were positively correlated with several potentially beneficial rhizobacteria ( \n Figure 6C \n ), indicating that these significantly enriched beneficial rhizobacteria changes may be caused by these differential root metabolites and those metabolites may be secreted acting as nutrients and energy sources for specific microorganisms ( Bais et al., 2006 ). Tryptophan (Trp) has an essential role in regulating plant growth, development, and defense ( Ryu and Patten, 2008 ). In this study, Trp was positively correlated with six potentially beneficial rhizobacteria ( \n Figure 6C \n ), indicating that Trp may be secreted by roots and as a signaling molecule to effect beneficial rhizobacteria. Similarly, Diethanolamine, 6-Deoxyfagomine and 3-Indoleacrylic acid were also positively correlated with the enriched bacteria. This result is inconsistent with those of a previous study in which Ps. camelliae-sinensis inhibited secretion of alkaloids, organic acids, and AAs in tea seedlings but induced secretion of phenolic acids and flavonoids ( Wang et al., 2021 ). Such differences may be related to metabolic differences between plant species ( Wang et al., 2016 ). Therefore, to help alleviate heavy grazing stress, it is inferred that the root system actively regulates the synthesis of these root metabolites such as AAs, SCOAs, and alkaloids under grazing interference, and then secretes them to promote the growth of some specific plant growth-promoting rhizobacteria and fungi. We will collect root exudates and compare the differences between root exudates and root metabolites, and then conduct further verification tests in the future."
} | 6,722 |
24672514 | PMC3954026 | pmc | 2,206 | {
"abstract": "Lignocellulosic hydrolysate (LCH) inhibitors are a large class of bioactive molecules that arise from pretreatment, hydrolysis, and fermentation of plant biomass. These diverse compounds reduce lignocellulosic biofuel yields by inhibiting cellular processes and diverting energy into cellular responses. LCH inhibitors present one of the most significant challenges to efficient biofuel production by microbes. Development of new strains that lessen the effects of LCH inhibitors is an economically favorable strategy relative to expensive detoxification methods that also can reduce sugar content in deconstructed biomass. Systems biology analyses and metabolic modeling combined with directed evolution and synthetic biology are successful strategies for biocatalyst development, and methods that leverage state-of-the-art tools are needed to overcome inhibitors more completely. This perspective considers the energetic costs of LCH inhibitors and technologies that can be used to overcome their drain on conversion efficiency. We suggest academic and commercial research groups could benefit by sharing data on LCH inhibitors and implementing “translational biofuel research.”",
"conclusion": "Conclusions LCH inhibitors are major barriers for cellulosic biofuels. The cellular energy costs of coping with these compounds are a significant drain on the already thin margins of biofuel production. However, the increasingly powerful tools of systems biology can be used to gain a detailed understanding of the cellular consequences of individual and mixtures of fermentation inhibitors, which will serve as a basis for rational engineering of customizable microbes. The biofuel research community would benefit from shared computational and database resources that can improve communication between the academic and commercial sides of biofuels. Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.",
"introduction": "Introduction Lignocellulosic biofuels offer the promise of sustainable, domestically produced fuels with favorable carbon balances. Fast-growing grasses like Miscanthus and agricultural residues provide fermentable sugars at lower energy and fertilizer costs than grains (Schmer et al., 2008 ), making them preferable feedstocks for advanced biofuels. Cellulosic ethanol is an obvious next-generation biofuel to implement given its production and delivery infrastructures are compatible with existing fuels. Central to the success of cellulosic ethanol is efficient conversion of biomass-derived sugars to ethanol by microbes such as Saccharomyces cerevisiae , Escherichia coli , and Zymomonas mobilis (Alper and Stephanopoulos, 2009 ; Lau et al., 2010 ; Yang et al., 2010a ). Under optimal conditions, these microbes are powerful ethanologens; however, lignocellulosic hydrolysates (LCH) and industrial scale fermentation tanks are not optimal conditions. Thermal, osmotic, and ethanol stresses are just some of the environmental factors that inhibit fermentation and reduce yield (Attfield, 1997 ; Gibson et al., 2007 ; Jin et al., 2013 ). Industrial microbes are pushed to the limits of stress tolerance to make biofuel production energetically favorable. Although environmental stressors limit yields in present day ethanol facilities, cellulosic biomass conversion comes with new challenges. Specifically, LCH inhibitors, a group of small, bioactive molecules can significantly reduce conversion efficiency. LCH inhibitors such as aliphatic acids, furans, and phenolics are released or condensed from cellulose and hemicellulose during pretreatment and hydrolysis (Larsson et al., 1999 , 2000 ; Yang et al., 2010a ); however, chemical residues from newer hydrolysis strategies and synergies with biofuel end products (ethanol, isobutanol) are less well studied. Removal of these inhibitors can be expensive and may reduce titers of fermentable sugars; some estimates suggest that detoxification can remove up to 26% of total fermentable sugars (Larsson et al., 1999 ). Thus, a preferred strategy is to develop microbial strains with properties that minimize the effects of LCH inhibitors on biofuel yields. With commercially available industrial stains that are robust to thermal and ethanol stress (e.g., Ethanol Red, Fermentis, Milwaukee, WI, USA), recent attention has been directed to overcoming the challenge of LCH inhibitors. These compounds are ubiquitous in hydrolysates, and their abundance and composition depends on pretreatment (Chundawat et al., 2010 ), feedstock (Klinke et al., 2004 ; Almeida et al., 2007 ), and seasonality (Bunnell et al., 2013 ; Greenhalf et al., 2013 ). Given their chemical diversity, these compounds can target many cellular processes. LCH inhibitors can also generate a substantial cellular energy drain. Cells have evolved to detoxify, excrete inhibitors, or repair the resultant cellular damage fast enough to reproduce. However, evolved coping mechanisms may also negatively affect the efficiency of conversion by competing for cellular resources (Bellissimi et al., 2009 ; Miller et al., 2009 ). Although it is in the microbe's best interest to use its resources to limit the effects of LCH inhibitors and maintain cellular viability, this may be reducing biofuel production. In this perspective, we consider the diversity and cellular costs of LCH inhibitors from traditional and novel pretreatment and hydrolysis strategies, describe new technologies and their application to strain development, and finally identify key needs of the cellulosic biofuel community that will empower “translational biofuel research” to take discoveries quickly to industrial scale."
} | 1,442 |
27156712 | PMC4860589 | pmc | 2,207 | {
"abstract": "Spider silk is regarded as one of the best natural polymer fibers especially in terms of low density, high tensile strength and high elongation until breaking. Since only a few bio-engineering studies have been focused on spider silk ageing, we conducted nano-tensile tests on the vertical naturally spun silk fibers of the bridge spider Larinioides cornutus (Clerck, 1757) (Arachnida, Araneae) to evaluate changes in the mechanical properties of the silk (ultimate stress and strain, Young’s modulus, toughness) over time. We studied the natural process of silk ageing at different time intervals from spinning (20 seconds up to one month), comparing silk fibers spun from adult spiders collected in the field. Data were analyzed using Linear Mixed Models. We detected a positive trend versus time for the Young’s modulus, indicating that aged silks are stiffer and possibly less effective in catching prey. Moreover, we observed a negative trend for the ultimate strain versus time, attesting a general decrement of the resistance force. These trends are interpreted as being due to the drying of the silk protein chains and the reorientation among the fibers.",
"discussion": "Discussion Despite of the fact that our results could be affected by the number and arrangement of fibers composing the tested silk bundle, in general, we obtained stress-strain curves which are coherent with previously tensile test results reported in literature for naturally spun silk threads 2 10 45 49 and drops of stress values during testing 45 50 . Indeed, we collected multi-stranded silk threads composed of at least 2 major ampullate, 2 minor ampullate and abundant aciniform threads while the spider was descending. As a consequence of the presence of parallel multi-fibers, sudden slight drops of stress values are sometimes exhibited during tensile test before failure (see Fig. 1e,f ), but the stress-strain curves suddenly recover to their previous stiffness after these drops 45 . Note that the mechanical properties of a multi-fiber thread exhibiting this behavior were not noticeably different from tests where these drops did not appear and all the silk multi-fibers broke together. Concerning the variation in the silk properties with ageing, we observed a non-linear increase in the Young’ Modulus values ( Fig. 3 ), as well as a linear decrease of ultimate strain values over time ( Fig. 4 ). On the contrary, ultimate stress and toughness did not vary with time, at least up to 1 month. More specifically, silk ageing induces an increase of about + 88% in the Young’s Modulus, which is ~6 times higher than the increment of the dragline silk of Argiope trifasciata 10 and ~1.6 or 2.6 times higher than that measured for 1- or 4-year-aged dragline silks of different species of Araneomorphae 33 . In biological terms, aged silks are then stiffer and possibly less effective in catching prey. We also recorded a slight percentage decrement of − 13% in the ultimate stress. These results are not in line with values reported in literature 33 , where values are stable for 1-year-aged dragline silks but − 35% for 4-year-aged dragline silks. Toughness, on the other hand, showed no significant trend in respect to silk ageing, which is in line with results for 1-year-aged dragline silks reported in literature 33 . Overall, despite the individual variability and other ecological factors such as environment and food intake that may influence silk properties 30 31 32 , we underline a general decay of the silk over time. The degradation process during the monitored period of 1 month results probably from the loss of water as the result of establishing the thermodynamic equilibrium between the water content in the fiber and that of the atmosphere reducing the elastic mobility of silk proteins 33 51 52 . In addition, the highly mobile and extensible “nanosprings” of the silk protein chains could be degraded by processes other than mere drying, such as an increased cross-linking and reorientation among them, which indeed determines an increased stiffening of the silk structure with a simultaneous decrease of ultimate strain values 33 . The potential effects due to individual variability and sampling season were appropriately taken into account by the statistical methods here adopted. In particular, the use of the mixed regression procedure allowed us to include the possible variability at the individual level and provide a more realistic representation of the observed trends. Moreover, in order to avoid bias in the ageing process, all silk samples were stored under controlled laboratory conditions of temperature and humidity and protected from UV light. An additional source of bias may arise from the effect of the sampling period (“Summer” and “Autumn” populations). Accordingly, the categorical variable Season was introduced in the regression structure as a fixed term (categorical factors made up of less than five levels can not be introduced as random factors 53 ), in order to take into account potential variation induced by the sampling period. The sampling period explained variation in the data for both ultimate strain and toughness. Although differences between the two sampling periods are statistically significant, such variation could possibly be entirely driven by random variation due to the low number of individuals tested for each period. Tentatively, this trend can also be related to the spider senescence (i.e. its age), owing to the effect of the lower intake of food or, more generally, in relation to the natural decline of metabolic processes at the end of the season. The influence of the spider diet on growth, reproduction, survival and silk production is documented in literature 30 31 32 45 , showing that when resources are scarce, spiders spin thinner silk threads, being able to sustain lower applied loads although the maximum tensile stress remains unaffected. Given the small population size for the two sampling periods (n = 3), however, we are unable to fully support this hypothesis from a statistical standpoint. Inferences on spider senescence would need additional observations from different reproductive stages, and a higher population size for the two seasons. Nano-tensile tests on vertical naturally spun silk fibers of the bridge spider Larinioides cornutus revealed changes with silk ageing in some of the mechanical properties here tested (ultimate strain and Young’s modulus). The potential technological applications of silk threads with properties that change with ageing could be of huge interest in particular for medical applications as such as reabsorbable scaffolds for muscles, nerves, ligaments tissue repairs, as well as absorbable suture materials."
} | 1,681 |
39439005 | PMC11494790 | pmc | 2,210 | {
"abstract": "Background The symbiosis between arbuscular mycorrhizal fungi (AMF) and plants often stimulates plant growth, increases agricultural yield, reduces costs, thereby providing significant economic benefits. AMF can also benefit plants through affecting the rhizosphere microbial community, but the underlying mechanisms remain unclear. Using Rhizophagus intraradices as a model AMF species, we assessed how AMF influences the bacterial composition and functional diversity through 16 S rRNA gene sequencing and non-targeted metabolomics analysis in the rhizosphere of aluminum-sensitive soybean that were inoculated with pathogenic fungus Nigrospora oryzae and phosphorus-solubilizing fungus Talaromyces verruculosus in an acidic soil. Results The inoculation of R. intraradices , N. oryzae and T. verruculosus didn’t have a significant influence on the levels of soil C, N, and P, or various plant characteristics such as seed weight, crude fat and protein content. However, their inoculation affected the structure, function and nutrient dynamics of the resident bacterial community. The co-inoculation of T. verruculosus and R. intraradices increased the relative abundance of Pseudomonas psychrotolerans , which was capable of N-fixing and was related to cry-for-help theory (plants signal for beneficial microbes when under stress), within the rhizosphere. R. intraradices increased the expression of metabolic pathways associated with the synthesis of unsaturated fatty acids, which was known to enhance plant resistance under adverse environmental conditions. The inoculation of N. oryzae stimulated the stress response inside the soil environment by enriching the polyene macrolide antifungal antibiotic-producing bacterial genus Streptomyces in the root endosphere and upregulating two antibacterial activity metabolic pathways associated with steroid biosynthesis pathways in the rhizosphere. Although inoculation of pathogenic fungus N. oryzae enriched Bradyrhizobium and increased soil urease activity, it had no significant effects on biomass and N content of soybean. Lastly, the host niches exhibited differences in the composition of the bacterial community, with most N-fixing bacteria accumulating in the endosphere and Rhizobium vallis only detected in the endosphere. Conclusions Our findings demonstrate that intricate interactions between AMF, associated core fungi, and the soybean root-associated ecological niches co-mediate the regulation of soybean growth, the dynamics of rhizosphere soil nutrients, and the composition, function, and metabolisms of the root-associated microbiome in an acidic soil. Supplementary Information The online version contains supplementary material available at 10.1186/s40793-024-00624-y.",
"conclusion": "Conclusions Experimental results showed that the inoculation of AMF strain R. intraradices , pathogenic fungus N. oryzae and P-solubilizing fungus T. verruculosus modulated the interactions among bacteria residing in the host plant niches by affecting the structure, function, and dynamics of the resident bacterial community. The inoculation of AMF R. intraradices improved soybean resistance to acidic soil stress by upregulating the key metabolic pathway related to plant resistance promotion under adverse environmental conditions and recruiting specific PGPR. The N. oryzae application stimulated the stress response in the soil microenvironment through upregulating two antibacterial activity metabolic pathways in the rhizosphere and enriching the polyene macrolide antifungal antibiotic production bacterial genus Streptomyces in endosphere. However, although the addition of pathogenic fungus N. oryzae enriched Bradyrhizobium and increased soil urease activity, it had no significant effect on biomass and N content of soybean. Therefore, it is necessary for us to consider the potential effect on available P content of soil when applying some microbial agents to enhance plants growth in acidic soil. Lastly, the host niches had greater impact on the assembly and shift of soybean rhizosphere microbes than the microbial agents in this short-term study. Together, our results showed that microbial agents and host niches co-mediated the fine-tuning of the compositions, functions, and metabolisms of soybean rhizosphere microbiome and further improved the survival of Al-sensitive soybean BD2 in an acidic soil. Our findings also suggested that the application of microbial agents needs to consider the complex microbe-microbe and plant-microbe interactions in specific soil environments to achieve better application effects in ecological agriculture.",
"introduction": "Introduction Root-soil interactions are highly complex in natural conditions, involving a multitude of active microbes [ 1 ]. Rhizosphere microorganisms are indispensable regulators of plant adaptability and productivity, which play important roles in plant water and nutrients absorption, as well as in plant resistance to biotic and abiotic stresses, and were considered as the ‘second genome of plant’ [ 2 , 3 ]. The rhizosphere microbiome along the soil-plant continuum participates in the plant growth, nutrition, health, and yield mainly through the interaction between plants and microbes and between microbes and microbes [ 4 – 6 ]. Mycorrhizal fungi and nitrogen-fixing bacteria enable plants to obtain up to 80% of their nitrogen (N) and 75% of their phosphorus (P) resources [ 7 ]. As one of the key components of the rhizosphere microbial community, arbuscular mycorrhizal fungi (AMF) directly enhance the absorption of essential nutrients such as N and P by plants, increase their resistance to biotic/abiotic stresses (e.g., drought and pathogens), and promote the colonization of N-fixing rhizobia and other plant growth promoting rhizobacteria (PGPR) in the rhizosphere of host plants [ 8 – 10 ]. The AMF also facilitated bacterial translocation and boosted the combination of plants with beneficial fungi and bacteria via a wide network of extraradical mycelium (ERM) [ 11 ]. The AMF and Rhizobium spp. have also been reported to influence the composition and abundance of other rhizosphere bacteria, and further enhance the fatty acid content, seed size, and yield of soybean grown in a semi-arid environment [ 12 ]. Other rhizosphere microbes were also closely related to plant health and nutrition, for example, root-associated microorganisms with growth-inhibitory siderophores can suppress pathogens as compared to the members with growth-promotive ones [ 13 ]. Some phosphorus solubilizing bacteria/fungi (PSB/PSF) can also dissolve insoluble minerals and organic phosphates in soil to promoting phosphorus (P) uptake of plants [ 14 ]. Some endophytic fungi can also increase the diversity of nodular culturable endophytic bacteria due to their mycelia, which are the ideal dispersal networks for rhizobia enrichment in the legume rhizosphere soil [ 15 , 16 ]. Some other non-symbiotic PGPBs can promote the absorption and utilization of nutrients by improving the root structure [ 17 ], while some specific rhizosphere microorganisms can also indirectly improve the absorption of nutrients by plants and enhance their stress resistance by changing the structure and function of functional microbial communities through the interaction between microbes and microbes [ 18 , 19 ]. Thus, the rhizosphere microbiome plays an important role in plant nutrition, growth, development and environmental adaptability [ 5 , 20 ]. As one of the typical soil type in tropical and subtropical regions, acidic soil occupy approximately 30%/50% of the global/potential-cultivated land area [ 21 ]. Crop growth is inhibited in acid soils due to low pH value, low bio-available P and high aluminum (Al) toxicity. High levels of Al 3+ in soil can reduce crop growth and yield by immobilizing soil P, damaging root tips, stunting roots, and inhibiting water and nutrient absorption [ 22 , 23 ]. Due to the demand for the increase in crop production, some chemical fertilizers such as N fertilizers are often applied excessively, and their long-term application deteriorates soil quality, leading to further aggravation of soil acidification [ 24 ]. As a major oil and protein crop globally, soybean is also used as ‘pioneer crop’ to improve acidic soils because of N-fixing of its symbiotic rhizobia. The exudates of soybean, such as some organic acids like citric acid and malic acid, were found to chelate Al and closely related to the tolerance of soybean to acidic soil [ 25 ], and their root exudates had a notable impact on soil microscale environments and the composition of root-associated bacteria community [ 26 , 27 ]. However, its productivity is also significantly hampered by Al stress and low available P due to the major soybean-producing regions are predominantly located in regions with acidic soils [ 28 – 30 ]. Moreover, nutrient-poor or extreme environments, such as acidic soils, can severely affect the composition and function of root-associated microbiomes. For instance, acidic soil inhibits soil respiration and nitrification, and influences microbial degradation of organic C and soil enzyme activity, and thereby suppresses the microbial-mediated nutrient cycles, which affects plant growth indirectly [ 31 ]. The interactions between plants and microorganisms were also directly affected by acidic soil. For example, acidic soil was reported to inhibit the signal exchange between legumes and rhizobia, reduces the process of rhizobia infecting root hairs, interferes nodulation and ultimately influences N-fixing [ 30 ]. In summary, it was urgent for us to alleviate the stress of acidic soil on plants and microorganisms through crop improvement and microbial inoculation. Crop diversity has been successfully exploited for genetic improvement in modern breeding, which significantly contributes to yield and quality improvement in adverse environment and practical agricultural production, and produces satisfactory economic and social benefits for a long time [ 32 , 33 ]. Nowadays, the application of composite microorganism agents increasingly becomes a promising new approach for crop growth promotion and soil improvement [ 34 – 36 ]. The synthetic communities (SynComs) constructed by soybean root associated functional microorganisms can significantly promote soybean N and P acquisition and ultimately soybean yield (up to 36.1%) [ 37 ]. The SynComs isolated from alkaline soil can regulate the growth of rhizobia specifically, and alleviated the impact of salt alkali stress on rhizobia nodulation and its colonization in nodules [ 38 ]. Special SynComs including bacteria and fungi helped soybeans resist Al toxicity by enriching plant growth promoting microorganisms [ 39 ]. Recent study indicated that the addition of AMF Rhizophagus intraradices agent promoted soybean biomass and increased plant C and N content by recruiting specific PGPR, thereby enhancing soybean tolerance to acidic soil in a host dependent manner [ 40 ]. Moreover, AMF R. intraradices were surprisingly found to reduce the abundance of pathogenic fungus Nigrospora oryzae while enriched P-solubilizing fungus Talaromyces verruculosus in the rhizosphere soil [ 40 ]. As a P-soluble microorganisms, T. verruculosus is a beneficial endophytic fungus, which can improve the utilization rate of insoluble phosphorus, promote plant growth and improve plant stress resistance [ 41 ]. However, how the AMF R. intraradices and its regulated core fungi N. oryzae and T. verruculosus reshapes root-associated microbial community, alters soil N and P nutrient cycling and ultimately enhances soybean tolerance to acidic soil remains to be clarified. To address these issues, an Al-sensitive soybean was used to evaluate the alterations in the nutrient dynamics, the root-associated microbes, and the soil metabolism spectrum in response to the inoculation of the AMF and its regulated fungi. Our overall hypothesis was that the inoculation of SynComs would alter the metabolism and composition of root-associated bacterial community and soil nutrient dynamics by reshaping specific functional microbiota. We anticipate that host niches along the soil-plant continuum would determine the differentiation of root-associated bacterial community following SynComs application by enriching/reducing special functional plant-growth promoting or pathogenic microorganism under environmental stress.",
"discussion": "Discussion Microbial inoculants modified the structure and function of rhizosphere microbiome SynCom always represent viable, complex and stable community selected and engineered from a core microbiota [ 61 ]. Our recent study found that the abundance of pathogenic fungus N. oryzae and P-solubilizing fungus T. verruculosus was regulated by AMF R. intraradices . Thus, in this study, we used SynCom to represent these three artificial microbial agents above. In our study, host niches displayed differentiation of associated bacterial community following Syncoms inoculations. Both the single-strain inoculation and combined inoculations had no significant effects on bacterial alpha diversity. Endosphere had lower microbial richness (Chao1) and Shannon diversity than the rhizosphere, while higher Good’s coverage than rhizosphere (Fig. 3ABC). The beta diversity using PCoA revealed that endopshere and rhizosphere niches were clearly separated following both single strain and co-inoculation (Fig. 3DEF). Moreover, taxonomic studies revealed higher abundances of Chloroflexi, Acidobacteriota, Myxococcota and Gemmatimonadetes in the rhizosphere than in the endosphere (Figure S2 AB). Furthermore, the Rhizobium vallis was only detected in the root endosphere (Fig. 4 C). A recent study suggests that the rhizosphere microbiome is divided into the environment-dominated and plant genetic-dominated components, while the physical, chemical, and biological characteristics of rhizosphere soil mainly determine the assembly of the environment-dominated microbiome (up to 96.5%) [ 62 ]. Although the bacterial community was found to exhibit significant differences mainly between two host niches, significant statistical differences were also detected between N. oryzae and T. verruculosus treatments according to the analyses of ANOSIM and Adonis (Table 2 ). In addition, the co-inoculation of T. verruculosus and R. intraradices was found to increase the relative abundance of a N-fixer, Pseudomonas psychrotolerans , in the rhizosphere (Fig. 4 C). The potential P-soluble fungus T. verruculosus was also reported to have cellulolytic characteristic [ 41 , 63 ]. Pseudomonas populations were one of the famous plant growth-promoting rhizobacteria (PGPR), which can promote photosynthetic capacity by improving the plant chlorophyll content [ 64 ], and are directly involved in nutrient metabolism of C, N, and P in soil [ 65 , 66 ]. Therefore, inoculation with T. verruculosus not only improved soil P nutrition, but also had direct and indirect effects on C nutrition. Moreover, the N. oryzae inoculation enriched Bradyrhizobium and Streptomyces in endosphere (Figure S2 CD). The famous efficient antimycotic and antiprotozoal agent, polyene macrolide antibiotic, was produced by several soil bacterial species of the genus Streptomyces [ 67 , 68 ]. Thus, the addition of pathogenic fungi might directly stimulate the enrichment of anti-pathogenic fungal microorganisms in the soybean rhizosphere. Moreover, a new study suggested that, the carbon compounds exuded by AMF genus Rhizophagus were acquired by the bacterium which could mineralize organic P, while Streptomyces inhibited the bacteria with weak P-mineralizing ability and enhanced AMF to acquire P [ 69 ], which proved that the role of Streptomyces in the AMF-mediated rhizosphere microbial community needed deeper exploration. Functional classification revealed the itrogenase molybdenum-iron protein (COG2710) and phosphodiesterase/alkaline phosphatase D (COG3540) were enriched in the endosphere upon N. oryzae inoculation (Figure S3 BC). Our findings thus suggest that fungal inoculation could modulate the interactions among bacteria residing in the host plant niches, thus affecting the structure, function and dynamics of the resident bacterial community. These results also corroborate previous findings that the microbial inoculants could alter the diversity, network stability, structure and functionality of soil and plant microbiome [ 70 ], modify metabolite-soil-microbial interactions [ 71 ], and regulate secondary metabolites exudation and rhizosphere expansion [ 72 ]. Microbial inoculants adjusted the metabolic spectrum in the rhizosphere microenvironment The composition of the plant-associated microbiome is influenced by various factors, including host genotype, root morphology, and root exudates [ 73 ]. In turn, changes in plant metabolic profiles caused by microbial inoculations might have an impact on the patterns of root exudation [ 74 ]. Thus, understanding the chemical characteristics of rhizosphere soil can give us insights into its effects on microbial community structure [ 75 ]. LC-MS has higher detection sensitivity and is more sensitive to trace substances, while GC-MS has better separation and detection effect and a more comprehensive database. In our investigation, the effect of single strain or co-inoculation on the assembly and shift of soil microbes could be due to their ability to modify the metabolic profile of host plant via interfering root exudation patterns. To prove this, GC-MS of rhizosphere soil samples was performed, and it was observed that AMF application upregulated DEMs which belong to biosynthesis of unsaturated fatty acids, such as arachidic acid, behenic acid, and tetracosanoic acid, as compared to non-AMF addition groups (Fig. 5 A and Figure S5 C). Unsaturated fatty acids are known to have a significant influence on enhancing plant resistance under adverse environmental conditions [ 76 ]. One famous plant growth promoting rhizobacteria, Pseudomonas psychrotolerans [ 77 ], was found to be enriched in the rhizosphere under the co-inoculation of T. verruculosus and R. intraradices , which might be co-related to the upregulation of the expression levels of biosynthesis of unsaturated fatty acids. Pseudomonas species in soil have been proved to be closely related to soybean stress resistance by exudating key metabolites such as purine, which also supports the previously reported cry-for-help theory [ 78 , 79 ]. These findings imply that the inoculation of AMF R. intraradices may improve soybean resistance to acidic soil stress by modifying the chemical and microbiological composition of the soybean rhizosphere. Two DEMs involved in the steroid biosynthesis pathway, beta-sitosterol and stigmasterol, were found to have higher abundance in N. oryzae addition groups as compared to T. verruculosus treatments (Figure S5 D). The steroid hormones are considered to be regulators of plant growth, development, and stress responses, and beta-sitosterol and stigmasterol are also known for their antibacterial activity [ 80 – 82 ]. Thus, the application of N. oryzae activated the antibacterial reaction in the soil microenvironment, which was also consistent with our finding in the composition of the bacterial taxa, that the polyene macrolide antibiotic production bacterial genus Streptomyces was abundant in endosphere under N. oryzae inoculation (Figure S2 CD). Some metabolic pathways, such as taste transduction and renal cell carcinoma, existed significant differences between different treatments (Figure S6 B), which might be closely related to protozoon such as Caenorhabditis elegans [ 83 , 84 ]. Lastly, the LC-MS displayed about 25-fold identified metabolites and approximately 10-folds identified DEMs as compared with GC-MS, and the results of LC-MS indicated that AMF application decreased the abundance of almost 4/5 metabolites, which were also worth further study (Table S1 ). The application of microbial agents needs to consider the complex interactions in the rhizosphere microenvironment The N. oryzae inoculation enriched Bradyrhizobium in endosphere (Figure S2 CD). The Pearson correlation analysis showed that the total N of soybean at maturing stage exhibited co-occurrence correlations with Acidipila and Bradyrhizobium (Fig. 6 B). Bradyrhizobium is the dominant rhizobia in acidic soils, thus, the colonization of dominant rhizobia in acidic soil might directly increase plant N content. In addition, the co-inoculation of N. oryzae and R. intraradices significantly increased the activity of urease (Fig. 2 ). Through catalysing the breakdown of urea into CO 2 and NH 3 , urease has an important role in the N cycle by generating accessible N for plant growth and might be a good index of soil quality [ 85 ]. However, the N. oryzae application was found to have no significant effect on biomass and N content of soybean (Table 1 ). The RDA analysis showed that soil C and N content were negatively correlated with available P content of soil (Fig. 6 A). A previous study also proved that soil acidification induced by N addition decreased available P concentrations, and was associated with reductions in the relative abundance of phytase [ 86 ]. Thus, only the improvement of N nutrition in the rhizosphere microenvironment might not directly cause the plant growth promotion in available P-deficient acidic soil. Cooperation is common in nature and is a strategy conducive to community stability [ 87 – 89 ]. Previous studies also proved that, the bacterial community had more complex and compact associations under PGPB inoculants, the enhanced co-occurrence associations in the PGPB-inoculated bacterial network may contribute to the plant growth-promoting effects of PGPB [ 90 ], and microbial interactions may contribute to soil functions more than species diversity [ 91 ]. Thus, we believed that the addition of AMF and the enrichment of some PGPRs enhanced the stability of the rhizosphere environment and were beneficial for coping with acidic soil stress. Moreover, an increasing number of studies indicate that, in addition to complex mutual cooperation, competition may dominates the interactions among microbiome [ 92 ]. The disappearance of either cooperative party can lead to the collapse of the community, making cooperation a high-risk strategy [ 93 ]. In this study, the metabolism and absorption of N and P nutrients in plants seem to not always cause a win-win situation under environmental stress, and simply considering the enrichment/de-enrichment of certain species to evaluate the differential changes in the entire microenvironment ecology is far from enough. That’s why it is necessary to consider the reconciliation roles of complex Syncoms in the rhizosphere microenvironment through multi omics techniques. More comprehensive analysis method could lead to more stable conclusions. One significant limitation of our study was that only the composition, function and metabolism of soybean rhizosphere soil were evaluated. Whether and how the effects of Syncoms inoculation on the transcription and expression of soybean roots under stressful environments should also be examined in further studies, to better evaluate the mechanism of Syncoms regulating the rhizosphere microenvironment. Ecological fertilizer technology such as the use of Syncoms, is an important supplement to traditional synthetic chemical fertilizer technology to promote plant productivity and contribute to the abolition of hunger, but their application in ecological agriculture still needs to require extensive exploration of the complex cooperation and competition interactions in the rhizosphere microenvironment [ 94 – 96 ]."
} | 5,969 |
32467822 | null | s2 | 2,211 | {
"abstract": "Despite recent advances in our understanding of the unique mechanical behavior of natural structural materials such as nacre and human bone, traditional manufacturing strategies limit our ability to mimic such nature-inspired structures using existing structural materials and manufacturing processes. To this end, we introduce a customizable single-step approach for additively fabricating geometrically-free metallic-based structural composites showing directionally-tailored, location-specific properties. To exemplify this capability, we present a layered metal-ceramic composite not previously reported exhibiting significant directional and site-specific dependence of properties along with crack arrest ability difficult to achieve using traditional manufacturing approaches. Our results indicate that nature-inspired microstructural designs towards directional properties can be realized in structural components using a novel additive manufacturing approach."
} | 241 |
30218468 | PMC6334282 | pmc | 2,212 | {
"abstract": "Summary Here, we review the multiple mechanisms that the Gram‐positive bacterium Bacillus subtilis uses to allow it to communicate between cells and establish community structures. The modes of action that are used are highly varied and include routes that sense pheromone levels during quorum sensing and control gene regulation, the intimate coupling of cells via nanotubes to share cytoplasmic contents, and long‐range electrical signalling to couple metabolic processes both within and between biofilms. We explore the ability of B. subtilis to detect ‘kin’ (and ‘cheater cells’) by looking at the mechanisms used to potentially ensure beneficial sharing (or limit exploitation) of extracellular ‘public goods’. Finally, reflecting on the array of methods that a single bacterium has at its disposal to ensure maximal benefit for its progeny, we highlight that a large future challenge will be integrating how these systems interact in mixed‐species communities.",
"conclusion": "Concluding Remarks The molecular basis of multicellular processes has been primarily studied in single‐genotype populations under laboratory conditions. However, this is, of course, not representative of the complexity and diversity which exists in nature. For example, the properties and functions of biofilms are greatly dependent on interactions between species and have been termed ‘community‐intrinsic properties’ (Madsen et al., 2018 ). Indeed a combination of four species in a biofilm was found to result in a 3‐4 times increase in the biomass compared with the single isolate biofilms of its constituent species. In this experiment, the number of cells belonging to each of the four species was all increased by comparison to growth in pure culture. Additionally, the spatial organisation of the members in the four‐species biofilm was unpredictable based on analysis of two species models (Burmolle et al., 2006 ). This demonstrates the immense influence that each species has on the community in terms of growth and structure. While the effect that diverse species have on biofilm formation in B. subtilis remain largely underexplored, other soil bacteria have been found to induce or repress B. subtilis biofilm formation (Powers et al., 2015 ). Repression of biofilm development has been described as a result of co‐culture of B. subtilis with soil isolates of Pseudomonas putida and Pseudomonas protogens . P. protogens was found to produce the antifungal 2,4‐diacetylphloroglucinol (DAPG), responsible for B. subtilis biofilm inhibition (Powers et al., 2015 ). In contrast, most of the soil species that could induce biofilm formation in B. subtilis were members of the genus Bacillus (Shank et al., 2011 ). The identity of the secreted molecules produced by these soil isolates is largely unknown but they induce biofilm matrix production through two mechanisms; (1) induction of matrix gene expression via the Spo0A~P pathway that is activated by the sensor kinase KinD or (2) by preferentially killing the non‐matrix‐producing cells in the population. In addition to the direct effect that microorganisms have on each other in multicellular contexts, environmental conditions are also critical to shaping social interactions among microbes. As discussed above, this was demonstrated in B. subtilis , where growth under different multicellular conditions influenced the nature of the interactions among isolates (Lyons and Kolter, 2017 ). This is not specific to Bacillus species as similar findings have also been shown for Pseudomonas aeruginosa and Staphylococcus aureus which usually do not coexist, as P. aeruginosa outcompetes S. aureus through production of molecules that are under the control of QS systems. In the blood however, QS signalling is inhibited in P. aeruginosa due to binding on serum albumin to QS molecules, resulting in coexistence of the two organisms (Smith et al., 2017 ). Therefore, it will be interesting to address the relationship between kin discrimination, quorum sensing and cheating in the formation, competitive fitness and spatial organisation of cells within in environmental biofilms and couple this with an analysis of the impact exerted by diverse environmental settings.",
"introduction": "Introduction Although prokaryotes are widely viewed as single‐celled organisms, many forms of multicellularity are prevalent in the bacterial world. Bacterial multicellularity can be transient or permanent; for example, cells of some species can form aggregates and filaments temporarily, while others, such as filamentous Cyanobacteria, form permanent chains of differentiated cells (Claessen et al., 2014 ). Multicellular lifestyles have evolved independently in different bacterial species and are characterised by cell‐cell adhesion, division of labour, and intercellular cooperation (Claessen et al., 2014 ; Lyons and Kolter, 2015 ). Communal living provides bacteria with a multitude of benefits: resistance to environmental threats, increased nutrient acquisition, protection from predation and more efficient utilisation of available resources through cell differentiation (Lyons and Kolter, 2015 ). Intercellular cooperation is often mediated by the production of ‘public goods’, which are molecules that are produced by a subpopulation of cells in a community but are shared with producers and non‐producers alike (West et al., 2006 ). As public goods are secreted, extracellular products, they are also susceptible to exploitation by ‘cheaters’; cells that take advantage of the molecules produced by their neighbours without directly contributing to their production (Rainey and Rainey, 2003 ; Diggle et al., 2007 ; Sandoz et al., 2007 ; West et al., 2007 ). Given this, bacteria need not only to discriminate between species that are beneficial to cooperate with, and those that need to be competed against but also need to make similar decisions about isolates of the same species. A mechanism by which this process occurs is ‘kin discrimination’; the differential treatment of organisms based on how closely related they are. In such systems, conspecific cells (cells of organisms belonging to the same species) that are recognised as self are cooperated with, while cells that are recognised as non‐self are competed against [as reviewed by (Hamilton, 1964 ; Strassmann et al., 2011 ; Wall, 2016 )]. Here, we review the recent advances in understanding the social interactions between isolates of the Gram‐positive bacterium Bacillus subtilis highlighting the diversity of communication mechanisms that have evolved, while exploring their links with establishing a social, community life in a biofilm."
} | 1,667 |
34385986 | PMC8353452 | pmc | 2,214 | {
"abstract": "Magnetotactic bacteria (MTB) are a group of microbes that biomineralize membrane-bound, nanosized magnetite (Fe 3 O 4 ), and/or greigite (Fe 3 S 4 ) crystals in intracellular magnetic organelle magnetosomes. MTB belonging to the Nitrospirae phylum can form up to several hundreds of Fe 3 O 4 magnetosome crystals and dozens of sulfur globules in a single cell. These MTB are widespread in aquatic environments and sometimes account for a significant proportion of microbial biomass near the oxycline, linking these lineages to the key steps of global iron and sulfur cycling. Despite their ecological and biogeochemical importance, our understanding of the diversity and ecophysiology of magnetotactic Nitrospirae is still very limited because this group of MTB remains unculturable. Here, we identify and characterize two previously unknown MTB populations within the Nitrospirae phylum through a combination of 16S rRNA gene-based and genome-resolved metagenomic analyses. These two MTB populations represent distinct morphotypes (rod-shaped and coccoid, designated as XYR, and XYC, respectively), and both form more than 100 bullet-shaped magnetosomal crystals per cell. High-quality draft genomes of XYR and XYC have been reconstructed, and they represent a novel species and a novel genus, respectively, according to their average amino-acid identity values with respect to available genomes. Accordingly, the names Candidatus Magnetobacterium cryptolimnobacter and Candidatus Magnetomicrobium cryptolimnococcus for XYR and XYC, respectively, were proposed. Further comparative genomic analyses of XYR, XYC, and previously reported magnetotactic Nitrospirae reveal the general metabolic potential of this MTB group in distinct microenvironments, including CO 2 fixation, dissimilatory sulfate reduction, sulfide oxidation, nitrogen fixation, or denitrification processes. A remarkably conserved magnetosome gene cluster has been identified across Nitrospirae MTB genomes, indicating its putative important adaptive roles in these bacteria. Taken together, the present study provides novel insights into the phylogenomic diversity and ecophysiology of this intriguing, yet poorly understood MTB group.",
"conclusion": "Conclusion In summary, we have identified and characterized two novel MTB populations, Ca. Magnetobacterium cryptolimnobacter strain XYR and Ca. Magnetomicrobium cryptolimnococcus strain XYC, belonging to the Nitrospirae phylum, which expand the genomic diversity of this MTB lineage. Thoroughly comparative analyses of Nitrospirae MTB genomes reveal metabolic plasticity of this widely distributed MTB group and a remarkably conserved MGC. Results of this study deepen our understanding of the taxonomic diversity, genomic property, ecophysiology, and magnetosome biogenesis of MTB members within the Nitrospirae phylum. In the future, successful pure cultivation and a combination of metagenomics, metatranscriptomics, and other culture-independent analyses will further deepen our understanding of MTB belonging to the Nitrospirae phylum.",
"introduction": "Introduction A diverse group of bacteria in nature can sense and swim along the geomagnetic field, a behavior known as magnetotaxis or microbial magnetoreception ( Blakemore, 1975 ; Lefèvre and Wu, 2013 ; Lin et al., 2020a ). These unique microorganisms, referred to as magnetotactic bacteria (MTB), can actively uptake a large amount of Fe(II) and/or Fe(III) from environments and accumulate it within the cell during the biomineralization of nanosized, membrane-bound Fe 3 O 4 , and/or Fe 3 S 4 magnetosomes, which are usually arranged in well-ordered, chain-like structures that are responsible for magnetotaxis. Consequently, the intracellular iron content of MTB is much higher ( ca. 100- to 1,000-fold) than that in other microorganisms ( Lin et al., 2014a ; Amor et al., 2020a , c ). MTB have been discovered across various environments from freshwater to marine ecosystems, and they make important contributions to the global cycling of iron and other elements (such as sulfur, phosphorus, nitrogen, and carbon; Cox et al., 2002 ; Rivas-Lamelo et al., 2017 ; Schulz-Vogt et al., 2019 ; Monteil and Lefèvre, 2020 ). The determination of the genetic basis for magnetosome biogenesis reveals a complex sequence of steps controlled by dozens of genes clustered at one genomic locus, known as a magnetosome gene cluster (MGC; Grünberg et al., 2001 ; Murat et al., 2010 ; Uebe and Schüler, 2016 ; Lin et al., 2017a ; McCausland and Komeili, 2020 ). For many years, the taxonomic distribution of MTB has been considered to be restricted to a few bacterial phyla ( Amann et al., 2006 ). However, over the past decade, our knowledge of MTB diversity has been significantly expanded through the applications of cultivation-dependent and -independent approaches ( Kolinko et al., 2012 ; Bazylinski et al., 2013 ; Lefèvre and Bazylinski, 2013 ; Lin et al., 2017a ; Amor et al., 2020b ). MTB have thus far been identified in at least 16 phylum-level lineages ( Lin et al., 2018 , 2020b ; Uzun et al., 2020 ), suggesting unexpected taxonomic diversity of magnetosome biogenesis and magnetotaxis across the domain Bacteria . Magnetotactic bacteria phylogenetically affiliated within the Nitrospirae phylum are of great interest because of their biomineralization of up to several hundreds of Fe 3 O 4 magnetosomal crystals and formation of dozens of sulfur globules in a single cell, linking these microorganisms to the key steps of iron and sulfur cycling in aquatic ecosystems ( Spring et al., 1993 ; Jogler et al., 2010 ; Lin et al., 2014b ; Li et al., 2020 ). Historically, Nitrospirae MTB have only been discovered in freshwater environments ( Spring et al., 1993 ; Flies et al., 2005 ; Amann et al., 2006 ); however, recent studies have revealed that these MTB are globally distributed in a wider range of environments than anticipated previously, including hot springs ( Lefèvre et al., 2010 ; Uzun et al., 2020 ), estuary and marine ecosystems ( Lin et al., 2017a ; Qian et al., 2019 ), and acidic peatlands ( Lin et al., 2020b ). Due to the lack of cultivated representatives, much of our understanding of Nitrospirae MTB was obtained through 16S rRNA gene-based methods. Recently, since the first report of a nearly complete draft genome of Candidatus ( Ca. ) Magnetobacterium casensis through a targeted metagenomic approach ( Lin et al., 2014b ), a growing number of Nitrospirae MTB genomes have been reconstructed from distinct ecosystems through applications of genome-resolved metagenomics ( Lin et al., 2017b , 2018 , 2020b ; Koziaeva et al., 2020 ; Uzun et al., 2020 ) and single-cell genomics ( Kolinko et al., 2016 ). Genomic analyses of Ca. Magnetobacterium casensis ( Lin et al., 2014b ) and Ca. Magnetobacterium bavaricum ( Kolinko et al., 2016 ) indicate an autotrophic lifestyle with capacity of CO 2 fixation via the reductive acetyl-CoA (Wood-Ljungdahl or WL) pathway or reductive TCA (rTCA) pathway. Both species are predicted to conduct denitrification, sulfur oxidation, and/or sulfate reduction in different microenvironments across anoxic and microoxic layers near the oxic-anoxic transition zone ( Lin et al., 2014b ; Kolinko et al., 2016 ). Despite these glimpses into the diversity and metabolic potential of magnetotactic Nitrospirae , the vast majority of MTB in this group are underexplored, and a comprehensive phylogenomic and comparative genomic analysis spanning a broad representation of the Nitrospirae MTB remains lacking. Here, we report the identification and characterization of two novel Nitrospirae MTB populations and the reconstruction of their high-quality draft genome sequences. The newly recovered genomes were further compared with the reported Nitrospirae MTB genomes. Findings of this study extend our understanding of the phylogenomic diversity and metabolic potential of this intriguing, yet poorly understood MTB group.",
"discussion": "Results and Discussion Two Novel Magnetotactic Bacteria Populations Affiliated Within the Nitrospirae Phylum Light-microscope observation of surface sediments from freshwater Lake Xianyang showed two distinct morphotypes of MTB (rod-shaped and coccoid, Figure 1A ). TEM observation reveals that cells of both rods and cocci form intracellular bullet-shaped magnetosome crystals organized into several bundles of chains ( Figures 1C,D ). Analysis of retrieved 16S rRNA gene sequences revealed only two populations (defined by a 97% identity threshold) in magnetically enriched MTB cells and FISH results turned out that they were either rods or cocci ( Figure 1 ). To reconstruct their draft genomes, cells of MTB in the sediments were magnetically enriched using the “MTB trap,” and their metagenome was sequenced using Illumina techniques. Assembly and binning resulted in two near-complete genome bins (designated XYR and XYC), which consist of 195 and 91 scaffolds with average GC contents of 48.61 and 37.75%, respectively ( Table 1 ). Genomes of XYR and XYC were 4.23 and 3.58 Mbp and were estimated to be 96.97% complete with 2.73% contamination and 99.94% complete with 1.82% contamination, respectively. Each genome contained a complement of 23S, 16S, and 5S rRNA genes and >18 tRNAs, thus exceeding the high-quality level of the minimum information about a metagenome-assembled genome standard ( Bowers et al., 2017 ). 16S rRNA gene identities (91.98%) indicate that XYR and XYC belong to different genus ( Yarza et al., 2014 ). The average AAI value between XYR and XYC was 53.73%, indicating that they represent organisms from two distinct genera according to Konstantinidis et al. (2017) . The ANI value between XYR and XYC was too low (only ∼27%) to effectively define their genetic relationship. The pairwise value of the POCP between XYR and XYC was 50.32%, which is near the proposed genus threshold of 50% ( Qin et al., 2014 ). Taking together, XYR and XYC represent two MTB populations from different genus. BLASTn analysis of 16S rRNA gene sequences of XYR and XYC revealed their best hits to an uncultured Nitrospirae bacterium clone OTU7 (GenBank accession number , 99.66% identity) and to Ca. Magnetoovum mohavensis strain LO-1 (GU979422, 98.60% identity; Lefèvre et al., 2011 ), respectively. FIGURE 1 Phylogenetic and morphological identification of two novel Nitrospirae MTB. (A) Morphologies of Ca . Magnetobacterium cryptolimnobacter strain XYR cells (green arrows) and Ca . Magnetomicrobium cryptolimnococcus strain XYC cells (red arrows) as revealed by light microscopy (bar = 10 μm). (B) Phylogenetic tree based on comparative sequence analysis of 16S rRNA genes. Numbers at nodes are bootstrap support values ( n = 1,000, only bootstrap values greater than 75% are shown). (C,D) Transmission electron microscopy pictures (bar = 1 μm) and fluorescence in situ hybridization results (bar = 10 μm) of cells of XYR and XYC, respectively. BaP is the probe specific for most Nitrospirae MTB ( Spring et al., 1993 ; Lin et al., 2011 ). TABLE 1 Genome statistics of Ca. Magnetobacterium cryptolimnobacter strain XYR and Ca. Magnetomicrobium cryptolimnococcus strain XYC. \n Name \n \n Ca. Magnetobacterium cryptolimnobacter strain XYR \n \n Ca. Magnetomicrobium cryptolimnococcus strain XYC \n No. of scaffolds 195 91 Total length (bp) 4,233,998 3,588,292 Largest scaffold (bp) 210,971 361,266 N50 (bp) 61,028 130,433 No. of genes 3,839 3,216 No. of putative magnetosome genes 25 23 GC content (%) 48.61 37.75 Completeness (%) 96.97 99.94 Contamination (%) 2.73 1.82 According to FISH results, cells of XYR were a rod-shaped morphotype that was similar to previously characterized Ca. Magnetobacterium bavaricum ( Spring et al., 1993 ; Jogler et al., 2010 ) and Ca. Magnetobacterium casensis ( Lin et al., 2014b ), and the morphology of XYC cells represented coccoid and was similar to those of Ca. Magnetoovum mohavensis strain LO-1 ( Lefèvre et al., 2011 ) and MWB-1 ( Lin et al., 2012 ). According to TEM observation, cells of XYR are approximately 1–2 μm in width and 5–7 μm in length and contain up to 150 magnetosome crystals organized into two to three bundles of chains. The size of XYC cells ranges from 2 to 4 μm, containing approximately 50–145 magnetosome crystals that formed four to eight bundles of chains. The sizes of magnetosome crystals of XYR and XYC vary from 30 to 130 nm and 45 to 135 nm, respectively. Phylogenomic Analysis of Magnetotactic Nitrospirae Phylogenomic analysis of XYR and XYC and the available Nitrospirae MTB genomes was performed based on 120 bacterial single-copy concatenated protein sequence alignment ( Figure 2 ). The genome tree includes 36 previously reported draft genomes of Nitrospirae MTB as of October 2020 and 130 representative non-MTB Nitrospirae genomes. The majority of Nitrospirae MTB genomes are from freshwater lakes ( Lin et al., 2014b , 2017b , 2018 , 2020b ; Kolinko et al., 2016 ; Koziaeva et al., 2020 ; Uzun et al., 2020 ) and acidic peatland soils ( Lin et al., 2020b ) with one genome (Nitrospirae bacterium SG8_35_4) from a sulfate-rich zone estuary ( Lin et al., 2017a ) and one (Nitrospirae bacterium MAG_10313_ntr_31) from a hot spring ( Uzun et al., 2020 ). The average estimated completeness and contamination of available Nitrospirae MTB genomes was 87.35 ± 12.69% and 3.08 ± 6.15%, respectively. Their genome sizes ranged from 1.91 to 6.08 Mbp (average 3.36 ± 0.82 Mbp) with a genomic GC content from 35.15 to 49.89% (average 45.13 ± 4.19%). FIGURE 2 Phylogenomic analysis of 138 Nitrospirae genomes including 38 MTB genomes. A maximum likelihood tree was constructed using a concatenated alignment of 120 conserved bacterial markers with GTDB-Tk (120 conserved bacterial marker genes are provided by GTDB). Numbers at nodes are bootstrap support values ( n = 1,000, only bootstrap values greater than 75% are shown). The genome size and quality of each MTB genome were shown. The genome tree placed XYR as a close sister group of Ca. Magnetobacterium casensis ( Lin et al., 2014b ) with an average AAI value of 91.38% and an ANI value of 91.84%, indicating that XYR and Ca. Magnetobacterium casensis belong to the same genus but to two different species. Therefore, XYR was provisionally named Ca. Magnetobacterium cryptolimnobacter (Ma.gne.to.bac.te′ri.um. Gr. n. magnes, -etos a magnet; N.L. pref. magneto- pertaining to a magnet; N.L. neut. n. bacterium a rod; Cryp.to.lim.no.bac′ter. Gr. adj. kryptos hidden; Gr. fem. n. limne lake; N.L. masc. n. bacter a rod) while XYC represents a separated phylogenetic lineage of the genus level, sharing 55.48% AAI and 50.30% POCP with Ca. Magnetoovum chiemensis ( Kolinko et al., 2016 ). XYC was accordingly designated Ca. Magnetomicrobium cryptolimnococcus (Ma.gne.to.mi.cro′bi.um. Gr. n. magnes, -etos a magnet; N.L. pref. magneto- pertaining to a magnet; N.L. neut. n. microbium a microbe; Cryp.to.lim.no.coc′cus. Gr. adj. kryptos hidden; Gr. fem. n. limne lake; N.L. masc. n. coccus coccus). All available Nitrospirae MTB genomes were affiliated within the order Thermodesulfovibrionales except for Nitrospirae bacterium SG8_35_4 (belonging to the order UBA6902) based on phylogenomic analysis and GTDB taxonomy analysis ( Figure 2 ). These genomes were classified into four family-level groups with a majority of genomes ( n = 32) belonging to the family Magnetobacteriaceae . Interestingly, the Magnetobacteriaceae family exclusively consists of MTB, including previously well-characterized Ca. Magnetobacterium casensis ( Lin et al., 2014b ) and Ca. Magnetobacterium bavaricum ( Kolinko et al., 2016 ). Considering that multiple instances of MGC loss may occur across the bacterial tree of life, the Magnetobacteriaceae would be interesting and useful to investigate MTB favorable physiological background and mechanisms to maintain magnetosome formation and magnetotaxis during the evolution. However, those possibilities that Magnetobacteriaceae may diverge very recently leading to little opportunity to lose MGCs or that non-MTB members in this family have so far not been sequenced yet cannot be fully ruled out. Metabolic Potential of Magnetotactic Nitrospirae Thirteen high-quality, representative Nitrospirae MTB genomes were annotated and compared in this study, which revealed that members of Nitrospirae MTB generally encoded similar sets of functional genes ( Figure 3 ). Similar to previous studies ( Lin et al., 2014b ; Kolinko et al., 2016 ), all these microorganisms encode autotrophic lifestyles with potential capacity in fixation of CO 2 via the Wood–Ljungdahl pathway. Although RubisCO-encoding genes were identified in four of 13 genomes (including XYR and Ca. Magnetobacterium casensis), the lack of carboxylase and oxygenase activity of these genes as previously suggested ( Jogler et al., 2010 ) indicate that Nitrospirae MTB might not operate the Calvin–Benson–Bassham (CBB) cycle for CO 2 fixation. FIGURE 3 Completeness of metabolic pathways of representative Nitrospirae MTB genomes. The scale number represents the completeness of major metabolic pathways inferred from the presence or absence of genes as determined by the KEGG-Decoder. Dark red represents a complete or highly complete pathway, and dark blue represents a pathway that is absent or highly incomplete. nDJH14bin9, Nitrospirae bacterium nDJH14bin9; Mcas, Ca . Magnetobacterium casensis; HCH-1, Ca . Magnetominusculus xianensis strain HCH-1; XYR, Ca. Magnetobacterium cryptolimnobacter strain XYR; XYC, Ca. Magnetomicrobium cryptolimnococcus strain XYC; DC0425bin1, Nitrospirae bacterium DC0425bin1; nDJH15bin2, Nitrospirae bacterium nDJH15bin2; MYbinv3, Nitrospirae bacterium MYbinv3; nDJH8bin6, Nitrospirae bacterium nDJH8bin6; nDJH6bin1, Nitrospirae bacterium nDJH6bin1; nDJH13bin19, Nitrospirae bacterium nDJH13bin19; nMYbin1, Nitrospirae bacterium nMYbin1; and MAG_10313_ntr31, Nitrospirae bacterium MAG_10313_ntr31. Genomes of Nitrospirae MTB encode proteins involved in the energy-producing dissimilatory sulfate-reduction pathway, suggesting that these microorganisms could reduce sulfate to sulfite and further to sulfide in anoxic microenvironments ( Figure 3 ). In 11 of 13 genomes, we identified the potential for sulfide oxidation to elemental sulfur or sulfite either by sulfide:quinone oxidoreductase (Sqr) or by dissimilatory sulfite reductase complex (Dsr). Sulfite might be further oxidized to sulfate by adenosine 5′-phosphosulfate reductase (Apr) and 5′-triphosphate sulfurylase (Sat). Different from other Nitrospirae , the genome of XYC contains a small gene cluster encoding sulfite dehydrogenase (quinone) subunits SoeABC that may catalyze the oxidation of sulfite to sulfate in the cytoplasm ( Dahl et al., 2013 ). A nearly complete nitrogen fixation pathway has been identified in five Nitrospirae MTB genomes (including XYC), which indicates the potential of these MTB to reduce atmospheric molecular nitrogen to ammonia ( Figure 3 ). Several genomes appeared to perform the dissimilatory nitrate reduction to ammonium pathway. Consistent with previous studies ( Lin et al., 2014b ; Kolinko et al., 2016 ), the majority of Nitrospirae MTB may conduct a denitrification process in which nitrate or nitrite is reduced as a terminal electron acceptor to produce gaseous nitrogen compounds under low-oxygen or anoxic conditions. These bacteria also encode proteins involved in a series of B-vitamin biosynthesis, including thiamin (B1), riboflavin (B2), and cobalamin (B12). Not surprisingly, genes encoding components of the flagellar and chemotaxis machinery are present in all Nitrospirae MTB genomes because magnetotaxis is a flagellum-dependent motility that is generally recognized to be interconnected with chemotaxis ( Frankel et al., 1997 ). Magnetotactic Nitrospirae may use the Sec-SRP pathway and the type II secretion system to secrete a variety of proteins and other molecules to the extracellular space. Although a few genes responsible for the type I and VI secretion systems have also been identified in their genomes, whether Nitrospirae MTB can perform these pathways needs further experimental confirmation. A Remarkably Conserved Magnetosome Gene Cluster Across Magnetotactic Nitrospirae Genes responsible for biosynthesis and organization of magnetosomes are clustered in all known MTB genomes, referred to as an MGC ( Grünberg et al., 2001 ; Murat et al., 2010 ; Lin et al., 2017a ). We have identified nearly complete MGCs in both genomes of XYR and XYC ( Figure 4 ). Although XYR and XYC belong to different genera, the gene content and organization of MGCs between them are remarkably conserved, both of which contain genes homologous to magnetosome genes man1, mamK, man2, mad10, man3, mamP, mamM, mad31, mamQ-II, mamB, mad2, mamA, mamI, mamE, mamQ-I, man4, man5, man6, mamO, mad23, mad24, mad25 , and mad26. This Man1-Mad26 gene cluster is across a region of approximately 19 kb in length. Two mad28 genes located upstream of man1 of XYR are not identified in the same region of the MGC of XYC ( Figure 4 ). FIGURE 4 Comparison of MGCs recovered in this study with previously reported representative MGCs. Mcas, Ca . Magnetobacterium casensis; HCH-1, Ca . Magnetominusculus xianensis strain HCH-1; XYR, Ca. Magnetobacterium cryptolimnobacter strain XYR; XYC, Ca. Magnetomicrobium cryptolimnococcus strain XYC; DC0425bin1, Nitrospirae bacterium DC0425bin1; nDJH15bin2, Nitrospirae bacterium nDJH15bin2; MYbinv3, Nitrospirae bacterium MYbinv3; nDJH8bin6, Nitrospirae bacterium nDJH8bin6; nDJH6bin1, Nitrospirae bacterium nDJH6bin1; nDJH13bin19, Nitrospirae bacterium nDJH13bin19; nMYbin1, Nitrospirae bacterium nMYbin1; and MAG_10313_ntr31, Nitrospirae bacterium MAG_10313_ntr31. A further manual check of 13 representative Nitrospirae MTB genomes revealed the high stability of the man1 - mad26 gene cluster. A total of nine genomes have been identified to contain a complete man1 - mad26 gene cluster in a single scaffold except for the lack of the mad26 gene in the genome of nDJH8bin6 ( Figure 4 ). Both gene content and gene order of man1 - mad26 gene clusters are extraordinarily conserved across the Nitrospirae MTB from different environmental conditions with the only exception being nDJH14bin9, which suggests that magnetosome biosynthesis and magnetotaxis play important adaptive roles in this MTB group. Alternatively, recent horizontal gene transfer(s) of MGCs into this group or unknown selective pressure(s) to maintain the content and order of magnetosome genes are also possible. A group of six magnetosome genes ( mamABIKMQ ) was identified previously to be shared by the majority of MTB genomes across different bacterial phyla ( Lin et al., 2020b ). All these six genes have been identified in the man1 - mad26 gene cluster. Proteins encoded by these genes are identified to be either essential for magnetosomal biogenesis ( mamBIMQ ) or responsible for important accessory functions, including magnetosome membrane assembly ( mamA ) and magnetosome chain formation ( mamK ) in Magnetospirillum strains ( Murat et al., 2010 ; Lohße et al., 2014 ; Uebe and Schüler, 2016 ). Similar to their counterparts in Magnetospirillum , Nitrospirae MamE and MamP contain the PDZ domain that is often involved in organizing signaling complexes by forming protein–protein interactions. MamE is involved in localization of magnetosome proteins and in magnetosomal crystal maturation ( Murat et al., 2010 ; Siponen et al., 2012 ), and MamP is responsible for redox control of iron biomineralization ( Jones et al., 2015 ) in Magnetospirillum . Nitrospirae MamO-Cter contains a predicted TauE-like transporter domain and its homolog MamO in Magnetospirillum , and homologs MamO and TauE in Desulfovibrio magneticus RS-1 has been speculated to be directly involved in nucleation of iron oxide particles ( Quinlan et al., 2011 ; Rahn-Lee et al., 2015 ). In addition to the abovementioned Mam proteins with homology to well-characterized magnetosome proteins, the man1 - mad26 gene cluster contains additional genes ( man and mad genes) with no apparent homology to MTB belonging to the Magnetospirillum ( Figure 4 ). Among these genes, only mad2 has been functionally characterized previously. Mutant of mad2 in Desulfovibrio magneticus RS-1 resulted in cells containing rare, unusual-looking particles with no magnetic response, indicating the important role of Mad2 in magnetosome biomineralization in this magnetotactic bacterium ( Rahn-Lee et al., 2015 ). Although functions of the other man and mad genes in the Nitrospirae have not been investigated so far, their remarkable conservation suggests that they should govern important functions in magnetosome formation and magnetotaxis in Nitrospirae MTB. Despite the stability of man1 - mad26 gene clusters, a few differences were noticed across Nitrospirae MTB. For example, genes of man4 , man5 , and man6 are absent from MGC of nDJH14bin9 but are present in those of other magnetotactic Nitrospirae , and MGC of nDJH14bin9 contains mad21 and mad22 genes that are absent from other Nitrospirae MGCs ( Figure 4 ). A gene between mamK and man2 encoding a Uma2 family endonuclease is found in MGCs of XYR, Ca. Magnetobacterium casensis and DC0425bin1 but is absent from the rest of the genomes ( Figure 4 )."
} | 6,397 |
37181519 | PMC10167797 | pmc | 2,218 | {
"abstract": "The smart control of droplet transport through surface structures and external fields provides exciting opportunities in engineering fields of phase change heat transfer, biomedical chips, and energy harvesting. Here we report the wedge-shaped slippery lubricant-infused porous surface (WS-SLIPS) as an electrothermal platform for active droplet manipulation. WS-SLIPS is fabricated by infusing a wedge-shaped superhydrophobic aluminum plate with phase-changeable paraffin. While the surface wettability of WS-SLIPS can be readily and reversibly switched by the freezing–melting cycle of paraffin, the curvature gradient of the wedge-shaped substrate automatically induces an uneven Laplace pressure inside the droplet, endowing WS-SLIPS the ability to directionally transport droplets without any extra energy input. We demonstrate that WS-SLIPS features spontaneous and controllable droplet transport capability to initiate, brake, lock, and resume the directional motion of various liquid droplets including water, saturated NaCl solution, ethanol solution, and glycerol, under the control of preset DC voltage (∼12 V). In addition, the WS-SLIPS can automatically repair surface scratches or indents when heated and retain the full liquid-manipulating capability afterward. The versatile and robust droplet manipulation platform of WS-SLIPS can be further used in practical scenarios such as laboratory-on-a-chip settings, chemical analysis and microfluidic reactors, paving a new path to develop advanced interface for multifunctional droplet transport.",
"conclusion": "4. Conclusion In summary, we propose WS-SLIPS as a versatile and robust platform to manipulate the moving, braking, locking and relaunching of liquid droplets by electrothermal actions. The driving force for droplet transport originates from the unbalanced Laplace pressure induced by the curvature gradient of the wedge-shaped substrate. Infusing the wedge-shaped substrate with phase-changeable paraffin endows the surface with the ability to conveniently switch the wettability between a sticky solid-state, a slippery lubricating state and a unique locking state under proper electrical signals. We demonstrate that the on-demand liquid manipulation on WS-SLIPS can be realized via preset electrical signals. The force analysis on the droplet dynamics on WS-SLIPS reveals that both the droplet velocity and travel distance can be controlled by adjusting the electrical voltage, the apex angle and the droplet volume. In addition, WS-SLIPS can be used in manipulating different organic/inorganic droplets, including saturated NaCl solution, ethanol solution and glycerol. The self-healing feature also enables the WS-SLIPS to automatically repair itself from mechanical scratches and warrants extensive applications in more diverse situations. The removing, mixing, reacting and separating of single microvolume droplet as well as the intelligent regulation in the droplet transport channel can finally realize the collection, transportation, storage and manipulation of droplet, which promises important applications in digital microfluidics, chip cooling and biomedical sampling.",
"introduction": "1. Introduction On-demand manipulation of microvolume droplets on surfaces has attracted remarkable attention due to its crucial importance in the fields of microfluidic reactors, 1,2 bioassay, 3–5 and molecular sensing. 6–8 To serve this purpose, static approaches that integrates asymmetric surface textures have been devised to passively alter the dimension, direction, and velocity of droplet transport on designated functional surfaces. 9–14 Furthermore, surfaces incorporating stimulus-responsive elements that respond to electrical, 15–18 magnetic, 19–21 thermal 22–24 and acoustic 25–27 stimuli are endowed with intelligent functionalities to manipulate the mobility of residing droplets by reversible structural restructuring and chemical reactions. Most notably, electrowetting-on-dielectric (EWOD), 28,29 electro-dewetting 15,30 or opto-electrowetting 31,32 systems can transport discrete droplets by exploiting interactions between the solution and electrified surfaces. For magnetically actuated droplet manipulation, 33,34 the tilting angle of microplates or micropillar arrays can be swiftly tuned to create a structural anisotropy near a droplet to realize the controlled droplet transport. Despite remarkable progress, it is still challenging to achieve versatile and robust droplet manipulation without the need of sophisticated surface texturing, 35 electrode patterning 29 and magnetic structuring. 19 Moreover, the acoustically 25 or thermally 36,37 activated droplet transport usually requires a high energy input. In recent years, there is a sprout in research using phase change materials, such as paraffin, 37–43 to lubricate the solid–liquid contact and reversibly modulate droplet mobility. In an early effort to achieve controllable wettability switching, melted paraffin, 37 owing to its availability, transparency, chemical stability and biocompatibility, is infused into the porous surface structures to replace the traditional solid–liquid interface with a slippery liquid–liquid interface to facilitate droplet transport. At room temperature, paraffin solidifies and droplets are immobilized due to the strong interaction between water and paraffin molecules. In particular, the programmable transport of droplets with easy integration, minimal energy requirement, and exceptional stability 43 has been developed by leveraging the reversible freeze-melt phase transition cycles of paraffin. However, the driving force for droplet transport in relevant methods still comes from external factors, such as earth gravity, 38,40 and such droplet manipulation strategy hence becomes invalid in microgravity environment or in situations requiring anti-gravity droplet transport. Herein, we developed an electrothermal platform, i.e. , wedge-shaped slippery lubricant-infused porous surface (WS-SLIPS), to realize the spontaneous and controllable droplet transport. The WS-SLIPS features a laser-cut planar wedge structure that creates a substrate curvature gradient to drive the spontaneous droplet transport. The infused paraffin enables WS-SLIPS to rapidly transition from a sticky solid state to a lubricating liquid state to control the droplet transport. We demonstrate that the droplet moving, braking and locking in a programmable manner can be achieved on WS-SLIPS via preset electrothermal signals. Besides, WS-SLIPS possesses the broadband liquid-manipulating capability and self-healing feature due to the excellent chemical resistance and interfacial stability, and hence inspires promising applications in microfluidic reactors, bioanalysis, and laboratory-on-a-chip settings.",
"discussion": "3. Results and discussion 3.1 Electrothermally switchable wettability of WS-SLIPS To demonstrate the excellent electrothermal response for rapid and reversible transition between the solid state and the slippery state, we first investigate the temperature variation of WS-SLIPS under different electrothermal conditions using an infrared thermography. As shown in Fig. S4 and Movie S1, † the infused paraffin layer on WS-SLIPS is in the solid state at room temperature, and after turning on the switch, the surface temperature T s increases and plateaus at a steady value of 43.6 °C, 53.7 °C, 62.2 °C, and 73.4 °C after 200 s Joule heating at U 0 = 10 V, 12 V, 14 V, 16 V, respectively ( Fig. 2a ). Therefore, a voltage larger than 12 V is applied in the later experiment in order to melt the paraffin. After the switch is turned off, the surface temperature drops quickly down below the melting temperature. In this process, micro-cracks gradually develop and propagate as the volume of paraffin layer shrinks substantially during solidification (Fig. S2b † ), which act to maximize the pinning effect and immobilize the liquid droplet thereon. The rate of temperature rise and decrease was described by two constants τ 1 and τ 2 , defined as the time required for T s reaches T m during the heating process and vice versa . Fig. 2b reveals that τ 1 decreases and τ 2 increases as U 0 increases. Obviously, a higher voltage is preferred to improve the response rate of WS-SLIPS transitioning into the lubricating state, while it takes longer to immobilize a sliding droplet on WS-SLIPS after the voltage is turned off. Therefore, the applied voltage should be deliberately selected to leverage the transitioning behaviors of WS-SLIPS to realize the active control of droplet transport. Fig. 2 Switchable wettability of Joule-heated WS-SLIPS. (a) Temperature–time curves of WS-SLIPS under different applied voltages, room temperature RT = 23 °C, room humidity RH = 30%. (b) The heating and cooling time of the WS-SLIPS under different applied voltages, each data point is the average of three measurements. (c) Contact angle θ c and sliding angle θ s of droplets on different substrates. SHS is the superhydrophobic surface before infusing lubricant. Solid paraffin and liquid paraffin represent the unheated WS-SLIPS and WS-SLIPS heated above T m , respectively. Locking state indicates the heated WS-SLIPS cools down to the room temperature and the water droplet is enveloped by a thin layer of paraffin. (d) Sliding angle of WS-SLIPS under multiple heating cycles. To investigate the wettability change of WS-SLIPS under the thermal stimulus, we measure the contact angle θ c and sliding angle θ s of water droplets on WS-SLIPS. As shown in Fig. 2c , the superhydrophobic surface before infusing paraffin, i.e. , SHS, has a contact angle of θ c = 161° and a sliding angle of θ s = 3°, while they are 110° and 85°, respectively, on the solid-state WS-SLIPS, indicating its hydrophobicity but with an extraordinary contact angle hysteresis. This is possibly due to the strong intermolecular interactions between water and paraffin molecules, as well as the microscale surface imperfections developed during the solidification process. As a result, a water droplet tends to be immobilized once deposited onto the sticky substrate. As WS-SLIPS is heated above the melting temperature, the WS-SLIPS enters the slippery state with θ c = 81° and θ s = 4°. The water droplet now is lubricated by a thin layer of liquid paraffin and is able to spontaneously move along the substrate driving by the Laplace pressure gradient. Another observation on the WS-SLIPS is the locking of water droplets, which is associated with a solid paraffin layer enveloping the droplet after a heating–cooling cycle. In this work, the surface tension of water droplet, liquid paraffin, and the interfacial tension between water and liquid paraffin are γ = 72.1 mN m −1 , γ p = 20.0 mN m −1 , and γ wp = 50.3 mN m −1 , respectively. Since γ > γ p + γ wp , 44 the lubricant spontaneously spread over and cloak the droplet to minimize the total surface energy. The cloaking effect when WS-SLIPS is being heated is further confirmed by our experiments (Fig. S5 and S6, Movie S2 † ). When the Joule heating is unloaded, the cloaking lubricant solidifies, and after the complete cooldown of WS-SLIPS, the droplet is eventually enveloped by a thin solid paraffin film, which hurdles any droplet motion. We refer to this state as the locking state of WS-SLIPS, because the pinning force is strong enough to lock the droplet in place even when the surface is upside down, i.e. , θ s = 180° (Fig. S7 † ). Fig. 2d shows that WS-SLIPS is able to resume the slippery state after being heated again and such a reversible switch of surface wettability can be repeated for 10 cycles of heating and cooling. 3.2 Electrothermally controlled droplet transport on WS-SLIPS The electrothermally controlled wettability switch of the WS-SLIPS provides a facile way to manipulate the droplet transport. Fig. 3a shows the transport of a 15 μL on the WS-SLIPS with α = 6°, on which the droplet manipulation could be divided into four consecutive stages including moving, braking, locking, and relaunching. Specifically, the WS-SLIPS is first heated at U 0 = 12 V and entered into the slippery state (left column in Fig. 3b ). The droplet deposited on the surface moves and accelerates with a transport velocity up to 0.7 mm s −1 (Circle ii in Fig. 3c ) due to the lubrication of liquid paraffin and unbalanced Laplace pressure gradient. After the Joule heating is turned off at t = 18 s, both the droplet and paraffin begin to cool down and the lubricant starts to transition back to the sticky solid state, under which the lubricant that cloaks the droplet solidifies first, since the droplet temperature is always lower than that of the substrate. During this process, the droplet brakes with its velocity gradually decreasing to 0 (Circle iii in Fig. 3c ). At t = 29 s, the droplet comes into a complete stop and enters the locking state, presented by an enveloping layer of solid paraffin (right column in Fig. 3b ). To resume the translational motion of the droplet, we deliberately heat the surface again at U 0 = 16 V for a quick relaunching in 23 s (Circle v in Fig. 3c ). Notably, the droplet slows down at t = 77 s as it becomes unconstrained by the substrate curvature and completely stops at t = 96 s with a total travel distance of ∼25 mm. Here we argue that more sophisticated manipulation of droplet transport via controlling the droplet moving, braking, locking, and relaunching can be realized by leveraging programed electrothermal signals (Fig. S8 † ), WS-SLIPS geometry and droplet volume. Fig. 3 Electrothermally controlled droplet transport on the WS-SLIPS. (a) Time-lapse images of droplet manipulation on the WS-SLIPS with α = 6°. (b) Schematic showing the droplet moving and locking on the WS-SLIPS. (c) Evolution of displacement and velocity of the water droplet. 3.3 Spontaneous droplet transport on WS-SLIPS To explain the spontaneous droplet transport on the WS-SLIPS, detailed force analysis is conducted. As shown in Fig. 4a , when a water droplet is deposited onto the tip end of a heated WS-SLIPS with T s = 53.7 °C, it conforms to the wedge shape with unequal radii of curvature at the tip end and tail end. This geometric asymmetry leads to an unbalanced Laplace pressure inside the droplet scaled as 1 where r and R are the local radii of curvature at the tip end and tail end, respectively. Then the driving force F L can be approximated as 45–48 2 Fig. 4 Mechanism of spontaneous droplet transport on the WS-SLIPS. (a) Optical images of a droplet ∼15 μL moving on a WS-SLIPS with α = 8°. The right side shows the schematic of force analysis. (b) Maximum transport velocity v max and transport distance L max of a water droplet of ∼20 μL on the WS-SLIPS. The error bars denote standard deviations, obtained from repeated experimental measurements. The inset shows the temporal profile of droplet velocity on the WS-SLIPS with α = 4°. (c) Contour plot of L u at different apex angles α and droplet volume V . (d) Schematic illustration of the droplet fueling strategy on the WS-SLIPS. (e) Time-lapse images of swift and long-distance transport of droplets using the droplet fueling strategy. Obviously, F L is proportional to α , which indicates that a larger apex angle facilitates the droplet motion at the early stage. However, F L gradually decreases as R and r increase during the droplet motion. Since the contact angle hysteresis is negligible on the slippery WS-SLIPS, the resistance for droplet motion mainly comes from the viscous drag 49,50 F H as 3 F H ∼ ( μ 0 + μ 1 ) v π R where μ 0 = 10 mPa s, μ 1 = 0.5 mPa s and v are the lubricant viscosity at 53 °C, the water viscosity at 50 °C, and the droplet velocity, respectively. Fig. 4b presents the velocity profile of a moving water droplet of ∼20 μL on slippery WS-SLIPS. For α = 10°, the maximum velocity is v max = 2.48 mm s −1 , rendering a maximum drag F H ∼1.6 × 10 −7 N. If we use R 0 = (4 V /3π) 1/3 to approximate in eqn (2) , the average driving force is F L ∼2.0 × 10 −5 N, which is two orders of magnitude higher than F H . Therefore, we conclude that the droplet velocity is actually dominated by F L , which is in turn determined by the apex angle α . In this sense, a higher apex angle is desirable to realize a rapid droplet transport. The transport distance of water droplets on WS-SLIPS is also affected by α . From eqn (1) and (2) , F L eventually drops to 0 when R equals to r . Therefore, we use L u where the droplet becomes unconstrained by the substrate curvature to characterize the droplet travel distance 4 where L w = 2 mm is the width of the tip end. Fig. 4c displays the dependence of L u on α and V , where the droplet travel distance is monotonically decreasing with respect to α , indicating an inherent tradeoff between the droplet velocity and transport distance. Therefore, the apex angle of WS-SLIPS ought to be deliberately designed to achieve swift and long-distance droplet transport. Fig. 4c also demonstrates that the droplet travel distance can be enhanced by increasing the droplet volume. In this regard, we devise a droplet fueling strategy to increase the droplet travel distance without sacrificing the droplet transport velocity. As shown in Fig. 4d and e , we placed two booster droplets 2 and 3 that are 6.8 mm apart in addition to a main droplet of ∼15 μL at the tip on slippery WS-SLIPS (Movie S3 † ). The main droplet firstly moves from the tip and then meets with the first booster droplet 2 to merge into a large droplet 1 + 2. The increased volume of the merged droplet 1 + 2 induces an increased Laplace pressure gradient to sustain the rapid droplet transport until it meets the second booster droplet 3. We mark that using the droplet fueling strategy can transport the droplet for L max = 48 mm, a 37% increase compared to single droplet transport (Fig. S9 † ). 3.4 Versatility of the WS-SLIPS To further validate the universal applicability of the WS-SLIPS, systematic experiments were conducted on surface of different configurations with different liquids. Fig. 5a shows that a water droplet can climb an inclined substrate against gravity with an average velocity of 0.45 mm s −1 . Moreover, droplet merging chemical reactions are available on WS-SLIPS. Fig. 5b shows an experiment of controlled colored reaction between starch solution and iodine solution. The white starch drops is transported by the WS-SLIPS and then merge with an iodine solution drop to complete the colored reaction in 30 s. In addition, multiple droplets can be controlled simultaneously or sequentially by the time-sharing control of the WS-SLIPS to complete multi-step reactions. For example, separate droplets on the WS-SLIPS in a symmetric configuration converge to the joint simultaneously with identical velocities, as shown in Fig. 5c and d . Also, the sequence of droplet coalescence can be controlled on-demand by adjusting the electrical voltage applied on each branch ( Fig. 5e ), which gives rise to exciting applications in micro-sampling, microanalysis where multiple reagents need to meet and mix with specific sequence to complete chemical reactions. Fig. 5f further shows the delicate control of droplet speeding up, turning, stop, and restarting on a spiral-shaped WS-SLIPS (Movie S4 † ). Fig. 5 Application of WS-SLIPS in droplet manipulation. (a) Optical image of a 20 μL droplet moving against gravity on WS-SLIPS with α = 8° and an inclination angle of 2°. (b) Chemical colour reaction of starch solution droplet with iodine solution droplet on a single WS-SLIPS. (c) Controlled droplet transport and coalescence on a compass-shaped WS-SLIPS. (d) Controlled merging of three separate droplets on a tree-like WS-SLIPS. (e) Controlled droplet merging on a hexagonal WS-SLIPS. (f) Three-dimensional droplet manipulation on a spiral WS-SLIPS. (g) Droplet transport on scratched samples. (h) Mass change of WS-SLIPS during the sandpaper abrasion test. (i) Contact angle and sliding angle of water on WS-SLIPS during the sandpaper abrasion test. The slippery property of the WS-SLIPS offers the intrinsic advantage that the surface scratches can be automatically self-healed using Joule heating to melt and flatten the surface (Fig. S10 and Movie S5 † ). As shown in Fig. 5g , the WS-SLIPS were scratched by a knife at room temperature, resulting in several visible trenches on the sample. Although seriously damaged, we show that the droplet manipulation capability of WS-SLIPS is unaffected. A water droplet is placed at the tip end of damaged WS-SLIPS as shown in Fig. 5g . When WS-SLIPS is connected to U 0 = 16 V, the surface trenches are gradually being filled once the surface temperature rises above its melting temperature. In the meantime, the droplet starts to move along the sample and eventually stops at t = 43 s with all trenches flattened. The durability of WS-SLIPS against mechanical abrasion is shown in Fig. 5h . WS-SLIPS is put face down on the sandpaper (standard sandpaper, #240) with 100 grams of weights on it. The sample is moved for 10 cm, rotated by 90° and then moved for another 10 cm to make sure the sample is abrased longitudinally and transversely. This process is defined as an abrasion cycle. The sample is heated above its melting temperature after each abrasion cycle before entering the next cycle, during which the sample mass, static contact angle θ c of water, and sliding angle θ s of water are recorded as shown in Fig. 5i . It is found that WS-SLIPS can fully restore the liquid-repellency and droplet manipulating capability even after 10 abrasion cycles, the paraffin acts like a protective shell to protect the microscale surface structures of WS-SLIPS from being damaged in each abrasion cycle. In addition, we also conducted droplet manipulation experiment under low temperature environment. When the temperature is 0 °C, WS-SLIPS can still complete droplet manipulation under U 0 = 16 V, which provides a feasible strategy for droplet manipulation under cold environments (Fig. S11 † ). The WS-SLIPS can be harnessed as an electrothermal platform to actively manipulate not only water, but also organic/inorganic solutions with varying surface tension and viscosity. We use saturated NaCl solution, ethanol solution (volume fraction of 10%) and glycerol to showcase the broadband manipulation capability of WS-SLIPS, since those three solutions are most common liquids being used in daily life and laboratory applications. It is found that on the sticky solid-state WS-SLIPS, a strong contact angle hysteresis with the sliding angle around θ s = 80° exists for all three liquids. When the WS-SLIPS is heated into the slippery state, θ s decreases drastically to around 3°, demonstrating the excellent lubricating effect of liquid paraffin ( Fig. 6a–c ) on different liquids. Note that the locking state of WS-SLIPS after a heating–cooling cycle is also present for all three liquids, suggesting that it is a universal feature of WS-SLIPS. Fig. 6d–f shows that the moving, braking, locking and relaunching of all liquid droplets can be realized by utilizing the sticky, slippery and locking states of WS-SLIPS. We also made a series of ethanol/water solutions with the volume fraction of ethanol varying from 0% to 50%. As the surface tension of the ethanol/water solution decreases down to 28.1 mN m −1 , the droplet moving velocity remains unchanged, further demonstrating the versatility of WS-SLIPS (Fig. S12 † ). Fig. 6 Manipulation of various liquids on WS-SLIPS. The sliding angle θ s of (a) saturated NaCl solution, (b) ethanol solution (volume fraction of 10%, ∼5 μL) and (c) glycerol. Time-lapsed images of droplet (∼10 μL) manipulation of (d) NaCl solution, (e) ethanol solution (volume fraction of 10%) and (f) glycerol on WS-SLIPS, scale bar: 5 mm."
} | 5,997 |
36435899 | PMC9701309 | pmc | 2,219 | {
"abstract": "The importance and need of renewable-based, sustainable feedstocks increased in recent years. Lignin-derived monomers have high potential, energetic and economic value in the microbial bioconversion to valuable biomolecules. The bacterium Paraburkholderia aromaticivorans AR20-38 produces a remarkable yield of vanillic acid from ferulic acid at moderate and low temperatures and is therefore a good candidate for biotechnological applications. To understand this bioconversion process on a molecular level, a transcriptomic study during the bioconversion process was conducted to elucidate gene expression patterns. Differentially expressed genes, cellular transporters as well as transcriptional factors involved in the bioconversion process could be described. Additional enzymes known for xenobiotic degradation were differentially expressed and a potential membrane vesicle mechanism was detected. The bioconversion mechanism on a transcriptional level of P. aromaticivorans could be elucidated and results can be used for strain optimization. Additionally, the transcriptome study showed the high potential of the strain for other degradation applications. Supplementary Information The online version contains supplementary material available at 10.1186/s13568-022-01487-7.",
"introduction": "Introduction Lignin is the second most abundant component of plants. It is a three-dimensional complex molecule consisting of various aromatic compounds. To enter the carbon cycle, lignin is degraded to lignin monomers by extracellular enzymes of bacteria and fungi (Bugg et al. 2011 ). Subsequently, less complex aromatic compounds can be used as carbon source by other microbes. For example, lignin-derived bi- and monoaryls can be degraded by bacteria (Kamimura et al. 2017 ). These processes are crucial for ecosystem functioning of the natural environment and may be utilized in the valorization of renewable feedstocks for industrial applications. The substitution of fossil fuel-based to renewable-based, nonfood feedstocks has been suggested as sustainable solution for environmental problems (Anastas and Eghbali 2010 ). This leads to an increased interest in lignin valorization as well as biocatalytic bioconversion of e.g. ferulic acid (FA) as feedstock to produce valuable biomolecules (Cao et al. 2018 ; Civolani et al. 2000 ; Graf and Altenbuchner 2014 ; Mori et al. 2021 ). Moreover, microorganisms being good degraders of aromatic compounds could harbor applicable enzymes for pollutant or synthetic polymer degradation (Fuchs et al. 2011 ; Knott et al. 2020 ). Within this group of promising microbial candidates to be utilized for such applications are members of the genus Paraburkholderia . Paraburkholderia aromaticivorans BN5 T is a hydrocarbon degrading bacterium, which was previously isolated from gasoline-contaminated soil (Lee and Jeon 2018 ). Berger et al. ( 2021 ) described the isolation of the strain Paraburkholderia aromaticivorans AR20-from Alpine forest soil. The microorganism was able to utilize a high amount of lignin sulfonic acid and phenol as sole carbon source (Berger et al. 2021 ). The cold adapted, Gram-negative bacterium belongs to the group of Betaproteobacteria and exhibits its degradation capability over a wide range of temperatures (0–30 °C). A rich genomic toolkit enables the strain to express various enzymes capable of degrading additional lignin monomers, including p -coumaric acid, 4-hydroxybenzoic acid, FA, vanillic acid (VA) and benzoic acid (Margesin et al. 2021 ; Poyntner et al. 2020 ). The high bioconversion capacity (88–89%) of FA to vanillin and further to VA at low (10 °C) and moderate (20 °C, 30 °C) temperatures is particularly interesting for biotechnological applications. A comparable high yield from pure FA was previously only reported from an engineered Pseudomonas putida strain KT2440 (Upadhyay et al. 2020 ). The degradation of FA to vanillin has been intensively studied in different microbes due to the utilization of vanillin as a flavoring agent (Graf and Altenbuchner 2014 ). Additionally, there is a growing interest in the microbial production of medium chain-length polyhydroxyyalkanoates using FA as a non-fatty acid feedstock. Therefore, the improvement was studied in P. putida using CRISPR/Cas9 (Zhou et al. 2020 ). To date, however, studies on cold-adapted strains are scarce even though these strains may be of particular interest for cost-efficient applications in a number of circumstances where maintaining high process temperatures is not a viable option. To elucidate the gene expression patterns during the bioconversion of FA to VA in P. aromaticivorans we here investigated the transcriptomic response in the exponential growth phase with FA as sole carbon source. Therein, the differentially expressed genes responsible for the individual bioconversion stages of FA to VA in P. aromaticivorans were identified and putative transcription factors and transporters were linked to the FA bioconversion.",
"discussion": "Discussion Based on the strongly differentially expressed genes in the transcriptome of P. aromaticivorans during bioconversion of FA to VA in this study, the pathway depicted in Fig. 4 is proposed. 4-coumarate-CoA ligase is a known enzyme in FA metabolism responsible for the step FA to feruloyl-CoA and was previously reported in Streptomyces coelicolor (Kaneko et al. 2003 ) and in plants (Wohl and Petersen 2020 ). Subsequently, hydroxycinnamoyl-CoA hydratase lyase converts ferulolyl-CoA to vanillin, a coenzyme A dependent deacetylase, which was previously reported in Pseudomonas fluorescens (Bennett et al. 2008 ). Vanillin dehydrogenase is a known enzyme for Vanillin metabolization to VA. P. aromaticivorans was not able to further degrade VA through the protocatechuate pathway and bioaccumulated VA (Margesin et al. 2021 ). In other bacteria, this step is catalyzed by the enzyme vanillate O- demethylase encoded by the genes VanA and VanB, which were only slightly regulated in P. aromaticivorans , VanB was downregulated. In contrast, PcaU was slightly upregulated, a transcriptional factor reported to play a role in the protocatechuate pathway. P. aromaticivorans harbors the gene for protocatechuate-3,4-dioxygenase (Poyntner et al. 2021 ) but the gene was not upregulated during FA bioconversion (Additional file 1 : Table S3). This indicates that PcaU is involved in the previous steps of FA to VA bioconversion. Fig. 4 In this study proposed bioconversion pathway of ferulic acid to vanillic acid for P. aromaticivorans AR20-38 based on the differentially expressed genes. The chemical structures of ferulic acid, feruloyl CoA, vanillin and vanillic acid are depicted. Putative involved enzymes and their log 2 FC values are shown above the arrows The upregulated KEGG terms can be related to FA bioconversion. The main upregulated KEEG terms involve pathways with ring cleaving enzymes, which are important for the bioconversion of FA to VA. For example, the KEGG term microbial metabolism in diverse environments comprises various pathways including carbohydrate metabolism, energy metabolism, sulfur- and amino acid metabolism, as well as xenobiotic degradation. Further, the upregulated KEGG term benzoate degradation can be related to the frequently reported ability to degrade benzoate in Paraburkholderia strains (Donoso et al. 2016 ; Herpell et al. 2021 ; Vanwijnsberghe et al. 2021 ). The upregulated term fatty acid degradation contains fatty acid oxidation enzymes such as enoyl-SCoA hydratase. These are reported to be involved in the degradation of FA (Gasson et al. 1998 ). The upregulated KEGG term phenylalanine metabolism could be linked to osmotic stress response as previously reported in Burkholderia cenocepacia (Behrends et al. 2011 ) but also comprises enzymes involved lignin and FA biodegradation. The highly regulated mono(2-hydroxyethyl) terephthalate hydrolase was previously reported in I. sakaiensis (Yoshida et al. 2016 ) during PET degradation. I. sakaiensis did not show any activity against ethyl ferulate (Yoshida et al. 2016 ). Although the gene coding for PETase is missing the genome and transcriptome of P. aromaticivorans , the strain showed growth in presence of bisphenol A, a chemical plasticizer, in previous tests (data not shown). A closely related species, B. xenovorans , was reported to be an effective polychlorinated biphenyl degrader (Chain et al. 2006 ). Additionally, the KEGG term lysine biosynthesis was regulated, which was detected in B. xenovorans (Parnell et al. 2006 ) in presence of polychlorinated biphenyls. Therefore, P. aromaticivorans might be a good candidate for plastic but also xenobiotic degradation. In future studies, the involvement of mono(2-hydroxyethyl) terephthalate hydrolase in FA bioconversion needs to be studied in detail which could be also important for other FA bioconverting organisms. Uroporphyrinogen-III C -methyltransferase was highly regulated, which is involved in cobalamin biosynthesis. Similary, cobalt-precorrin-3B C (17)-methyltransferase was upregulated in a transcriptome study on lignin valorisation (Zhu et al. 2021 ). This enzyme is involved in the adenosyl cobalamin biosynthesis. Cobalamin produced by Rhizobium isolates from forest soils were shown to enhance methane oxidation of a methanotroph (Iguchi et al. 2011 ). A similar mechanism might play a role in P. aromaticivorans . The most regulated transporters in the transcriptome of P. aromaticivorans during bioconversion of FA were ABC transporters and MFS transporters. ABC transporters are reported in Enterobacter lignolyticus (DeAngelis et al. 2013 ) , Clostridium beijerinckii (Lee et al. 2015 ; Zhang and Ezeji 2013 ) and Lactobacillus brevis (Winkler and Kao 2011 ) to be involved in the transport of lignin-derived aromatic substances such as FA. The regulated ABC sugar transporter and spermidine/putrescine might be used for nutrient acquisition in P. aromaticivorans during FA bioconversion. Within the MFS group, the MFS_1 nitrate transporter was highly regulated, indicating utilization of nitrate. This is in contrast to previously reported results detecting no nitrate reduction capability in the strain P. aromaticivorans BNT5 T (Lee and Jeon 2018 ). Additionally, the NIRD_SALTY nitrite reductase small subunit was highly upregulated. It was previously shown in denitrifying bacteria that the addition of nitrate improved the biodegradation processes of toluene as nitrate can be used as an alternative electron acceptor (Leahy and Olsen 1997 ). Another putative transport mechanisms during FA bioconversion is the upregulated 3-(3-hydroxy-phenyl)propionate transporter, which also belongs to the MFS group. Phenylpropionate and its hydroxylated derivatives are degradation products of lignin and were shown to be degraded by various bacteria (Arai et al. 1999 ; Barnes et al. 1997 ; Burlingame and Chapman 1983 ; Dagley et al. 1965 ; Pérez-Pantoja et al. 2008 ; Xu et al. 2013 ). The regulated transcription factors MarR and TetR are known regulators of aromatic compounds transporters for degradation pathways including HpcR involved in the hydroxycinnamate pathway (Tropel and van der Meer 2004 ). Thus, this indicates an involvement of these transcription factors for transporting mechanisms in P. aromaticivorans during bioconversion of FA. Although many transcriptional factors are annotated in the genome of P. aromaticivorans , only a few of the highly differentially expressed transcriptional factors could be related to previously reported involvement in aromatic compound degradation. The targets of the differentially expressed transcription factors in this study still need to be studied. The enzymes for catabolizing FA might be transported through the highly regulated outer membrane porin protein. This is in line with the upregulation of the GO term transmembrane transport (Additional file 1 : Table S4). P. aromaticivorans might use a mechanism based on outer membrane vesicles (OMVs) as reported by Salvachúa et al. ( 2020 ) in P. putida . OMVs in P. putida are used to catabolize lignin-derived substances which are transported via porin proteins. The utilization of OMVs has also been suggested as a synthetic biology tool and the OMV model harbors several potential biotechnological applications (Salvachúa et al. 2020 ). Several downregulated genes during bioconversion of FA indicate plant interaction capabilities of P. aromaticivorans . Burkholderia species were previously reported to act as plant promoting (Herpell et al. 2021 ; Donoso et al. 2016 ). The ABC transporter for syringomycin was downregulated, reported as a potential plant virulence factor in B. thailandesis (Kovacs-Simon et al. 2019 ). The downregulation of the KEGG term chemotaxis indicates potential plant interaction capabilities. Sheibani-Tezerji et al. ( 2015 ) reported chemotaxis in the transcriptome of the endophyte B. phytophormans and Balsanelli et al. ( 2016 ) showed that chemotaxis plays an important role in initial plant contact. Further, due to the higher growth rate with glucose compared to FA, P. aromaticivorans needed more cell wall components and therefore might upregulated dTDP-L-rhamnose 4-epimerase in presence of glucose. This epimerase is involved in the production of L-rhammnose, a polysaccharide component of pathogenic or plant associated bacteria (Graninger et al. 1999 ). Additionally, the epimerase is involved in the interconversion to dTDP-6-deoxy-D-talose, which was shown in B. thailandensis (Yoo et al. 2011 ) to serve as building block for O-antigenic polysaccharide biosynthesis. The O-antigenic polysaccharide is a reported virulence factor in Burkholderia pseudomallei (DeShazer et al. 1998 ) . In presence of glucose, enterobactin, an iron siderophore, ferric iron reductase, ferrous iron permease and probable siderophore transport system were upregulated. This indicates the importance of iron during high growth rates but not during bioconversion of FA. Catechol-like siderophore production was previously reported from rhizospheric bacteria (Joshi et al. 2006 ) which gives them advantage to sequester iron from soil. The downregulated KEGG terms related to growth fit well with the higher growth rate with glucose as sole carbon source in comparison to FA. The regulated term 2-oxocarboxylic acid metabolism might be involved in the glucose metabolism in the cultivation of P. aromaticivorans with glucose as sole carbon source. The upregulated KEGG term synthesis and degradation of ketone bodies cannot be related to any P. aromaticivorans metabolism. In conclusion, the transcriptional profile of P. aromaticivorans during bioconversion of FA to VA elucidated the expressed genes involved in the bioconversion process. These genes were clustered within the ten most highly differentially expressed genes. These enzymes and the transcripts known from aromatic compound degradation and synthetic polymer degradation offer new gene targets for bioconversion optimization and metabolic engineering. In addition, the strong expression of an outer membrane porin was detected, indicating towards the occurrence of a recently proposed outer membrane vesicle mechanisms for bacterial lignin catabolism (Salvachúa et al. 2020 ). To confirm this hypothesis, further studies on exosomes using e.g. exoproteome experiments are needed. These could offer a number of new applications for synthetic biology that may even lead to novel biotechnological applications. Overall, the strain AR20-38 is a promising candidate not only for FA bioconversion applications but also for xenobiotic and synthetic polymer degradation, especially in moderate and cold temperature environments."
} | 3,964 |
34403199 | PMC8449653 | pmc | 2,221 | {
"abstract": "Summary Pseudomonas putida is a highly solvent‐resistant microorganism and useful chassis for the production of value‐added compounds from lignocellulosic residues, in particular aromatic compounds that are made from phenylalanine. The use of these agricultural residues requires a two‐step treatment to release the components of the polysaccharides of cellulose and hemicellulose as monomeric sugars, the most abundant monomers being glucose and xylose. Pan‐genomic studies have shown that Pseudomonas putida metabolizes glucose through three convergent pathways to yield 6‐phosphogluconate and subsequently metabolizes it through the Entner–Doudoroff pathway, but the strains do not degrade xylose. The valorization of both sugars is critical from the point of view of economic viability of the process. For this reason, a P. putida strain was endowed with the ability to metabolize xylose via the xylose isomerase pathway, by incorporating heterologous catabolic genes that convert this C5 sugar into intermediates of the pentose phosphate cycle. In addition, the open reading frame T1E_2822, encoding glucose dehydrogenase, was knocked‐out to avoid the production of the dead‐end product xylonate. We generated a set of DOT‐T1E‐derived strains that metabolized glucose and xylose simultaneously in culture medium and that reached high cell density with generation times of around 100 min with glucose and around 300 min with xylose. The strains grew in 2G hydrolysates from diluted acid and steam explosion pretreated corn stover and sugarcane straw. During growth, the strains metabolized > 98% of glucose, > 96% xylose and > 85% acetic acid. In 2G hydrolysates P . putida 5PL, a DOT‐T1E derivative strain that carries up to five independent mutations to avoid phenylalanine metabolism, accumulated this amino acid in the medium. We constructed P. putida 5PLΔ gcd ( xylABE ) that produced up to 250 mg l −1 of phenylalanine when grown in 2G pretreated corn stover or sugarcane straw. These results support as a proof of concept the potential of P. putida as a chassis for 2G processes.",
"introduction": "Introduction Society is in favour of replacing polluting fossil fuels (the main source of energy), and oil‐derived chemicals with alternative renewable sources to combat global climate change (Ragauskas et al ., 2006 ; Valdivia et al ., 2016 ). A variety of new green energy sources are currently being used (bio‐, eolic, thermosolar and photovoltaic energy); however, the sole and main alternative for oil‐derived chemicals today is a new ‘green chemistry’ based on plants as the only sustainable and renewable source of organic carbon on earth. This so‐called new chemistry is expected to move the organic chemical industry towards net zero emissions (Ragauskas et al ., 2006 , 2014 ; Linger et al., 2014 ; Isikgor and Becer, 2015 ; Beckham et al ., 2016 ; Ramos et al ., 2016 ; Duque and Ramos, 2019 ). At present, the major source of plant‐derived materials to produce a number of chemicals is starch, whose hydrolysis yields glucose, that in turn is converted into different chemicals through fermentation processes. The use of starch to obtain biofuels and biochemical commodities is, however, controversial because of the overlap with the food chain. This controversy provoked a shift at the end of the last century when scientists began working on replacing starch by non‐edible plant biomass such as lignocellulose, an attractive source of raw material due to its abundance and because it does not compete directly with foodstuffs. However, the use of lignocellulosic materials to produce bioethanol and biochemicals is challenging because biomass requires intensive pretreatment (mainly physico‐chemical) to deconstruct it and for the release of cellulose, hemicellulose and lignin (Alcántara et al ., 2016 ). Sugars can be obtained from cellulose and hemicellulose in a process called saccharification, which involves enzymatic hydrolysis by a set of enzymes generically known as cellulases that work synergistically to produce monomeric sugars (Öhgren et al ., 2007 ; Álvarez et al ., 2016 ). Glucose (about 57–70%) is the major product that results from the hydrolysis, followed by xylose (about 9–23%), and other minority sugars such as arabinose, rhamnose and galactose (van Maris et al ., 2006 ; Rocha‐Martín et al ., 2018 ; see Table S1 for data from Rocha‐Martín et al ., 2018 ). However, many industrially relevant microorganisms only ferment glucose and leave the other sugars untransformed. Techno‐economic studies by Valdivia et al . ( 2016 , 2020 ) revealed that the processing of the C5 xylose is a must in order to profitably produce bioethanol or other chemicals from biomass. A number of xylose catabolic pathways have been engineered for heterologous expression in industrially relevant microorganisms. Recombinant xylose‐utilizing strains of yeasts (García‐Sanchez et al., 2010 ) and various bacteria like Zymomonas mobilis (Zhang et al ., 1995 ) , Corynebacterium glutamicum (Kawaguchi, et al ., 2006 ), Bacillus subtilis (Chen et al ., 2013 ; Zhang et al ., 2016 ), Kluyveromyces marxianus (Suzuki et al ., 2019 ) and Pseudomonas putida (Meijnen et al ., 2008 , 2009 ; Le Meur et al ., 2012 ; Dvorák and de Lorenzo, 2018 ; Bator et al ., 2020 ) have been constructed and can be considered as a first step towards efficient biomass utilization. An aim of synthetic biology is to establish a universal platform for the synthesis of ‘all chemicals’. We are, however, far from that objective today and several microbial platforms based on recombinant microbes are being used to produce different chemicals (Calero and Nikel, 2019 ; Liu and Nielsen, 2019 ). Bioprocess yields depend on the metabolic route and on the stoichiometry of the pathways, as well as on the intrinsic properties of the chemicals and the microbial tolerance to the high concentrations of substrates and products that are demanded during the industrial production of commodities (Bator et al ., 2020 ). We have focused our attention on the production of aromatic chemicals from sugars. To this end, we have chosen P. putida DOT‐T1E as a production platform, because of its high resistance to a wide range of aromatic compounds, including aromatic hydrocarbons such as toluene, xylenes and styrene (Rojas et al ., 2003 ; Ramos et al ., 2015 ). This property confers significant advantage over other P. putida strains that are only moderately tolerant to solvents, for instance KT2440 (Segura et al ., 2012 ). DOT‐T1E is a non‐pathogenic strain of Pseudomonas putida . The pangenome of the species revealed a set of core genes common to all strains and which define the basic physiological properties of these microorganisms. The species has also a set of accessory genes that are present in only two or more but not all the strains of the species, which confer specific properties (e.g. biodegradation of lineal and/or aromatic hydrocarbons), and the ability to colonize different niches (Udaondo et al ., 2016 ). The pangenome showed that the species P . putida is characterized by a limited ability to consume sugars, that is glucose, gluconate and fructose, which are mainly metabolized through the Entner–Doudoroff pathway (Nelson et al ., 2002 ; del Castillo et al ., 2007 ; Daddaoua et al ., 2009 ; Daniels et al ., 2010 ; Tiso et al ., 2014 ; Calero and Nikel, 2019 ). KEGG analysis revealed that P. putida DOT‐T1E, similarly to other strains of the species, contains a set of genes that would allow xylose catabolism if different peripheral modules are added to transform xylose into central metabolic intermediates. In fact, Bator et al . ( 2020 ) described that up to three peripheral xylose pathways can be implemented in P . putida KT2440 to allow growth on xylose. These pathways are known as the isomerase pathway and the oxidative Dahms and Weimberg pathways (Meijnen et al ., 2008 , 2009 ; Bator et al ., 2020 ). Bator et al . ( 2020 ) analysed the biotransformation of xylose into 14 different chemicals by recombinant P. putida strains and showed that the maximal product yields of 12 of the 14 metabolites of xylose were produced by the isomerase pathway. In this metabolic pathway, xylulose‐5‐phosphate is part of the pentose phosphate cycle and is eventually transformed into erythrose‐4‐phosphate, a starting metabolite for the synthesis of aromatic amino acids via the shikimate pathway (Fig. 1 ). Fig. 1 Proposed synthesis of L‐phenylalanine (L‐Phe) from glucose and xylose in an engineered P . putida Δ gcd ( xylABE ) strain. Exogenous xylose transporter (blue) and xylose isomerase pathway enzymes (green) are highlighted. Green arrows indicate the exogenously supplemented xylose isomerase pathway. Brown arrows indicate native pentose phosphate pathway reactions. Dotted black arrows indicate native shikimate pathway reactions. Dotted red arrows indicate the glucose dehydrogenase ( gcd ) deleted reaction. Abbreviations: PQQ, pyrroloquinoline; G6P, D‐glucose‐6‐phosphate; 6PG, 6‐phosphogluconate; KDPG, 2‐dehydro‐3‐deoxyphosphogluconate; G3P, D‐glyceraldehyde 3‐phosphate; FBP, fructose‐1,6‐bisphosphate; F6P, fructose‐6‐phosphate; X5P, xylulose‐5‐phosphate; D‐Ri5P, L‐ribulose‐5‐phosphate; R5P, ribose‐5‐phosphate; S7P, sedoheptulose‐7‐phosphate; E4P, erythrose 4‐phosphate; PEP, phosphoenolpyruvate; DAHP, 3‐deoxy‐D‐arabino‐heptulosonate 7‐phosphate; DHQ, 3‐dehydroquinate; DHS, 3‐dehydroshikimate; SHIK, shikimate; SH3P, shikimate 3‐phosphate; EP5P, 5‐enolpyruvoylshikimate 3‐phosphate; CA, chorismate; PA, prephenate; PP, phenylpyruvate; Glu, glutamate; 2OG, 2‐oxoglutarate; L‐Phe, L‐Phenylalanine. The isomerase pathway is characterized by the presence of a xylose isomerase (XylA) that transforms xylose into xylulose and a xylulokinase (XylB) that subsequently phosphorylates the latter to xylulose‐5‐phosphate, which enters into the Pentose Phosphate (PP) cycle (Wilhelm and Hollenberg, 1985 ; Amore et al ., 1989 ; Mishra and Singh, 1993 ; Hahn‐Hägerdal and Pamment, 2004 ). The xylA and xylB genes from the isomerase pathway of E. coli have already been engineered into KT2440 and S12 strains to allow the use of xylose (Le Meur et al ., 2012 ; Dvorák and de Lorenzo, 2018 ). In both strains, the efficient use of xylose as a C source requires the inactivation of glucose dehydrogenase (Gcd) to avoid the misrouting of xylose to dead‐end xylonate. While S12 was able to grow on xylose upon incorporation of xylAB (Meijnen et al ., 2008 ), Dvorák and de Lorenzo ( 2018 ) and Elmore et al . ( 2020 ) described that KT2440 requires, in addition to xylAB , the xylE gene encoding a proton‐coupled symporter to facilitate the entry of xylose into the cell. This study shows that the isomerase pathway together with the xylE gene can be expressed in both P. putida DOT‐T1E wild‐type strain and its glucose dehydrogenase ( gcd ) mutant derivatives. The recombinant strains not only grew on xylose in minimal medium, but also on corn stover and sugarcane straw 2G hydrolysates, consuming >98% glucose and >96% xylose. Furthermore, P. putida 5PL, a mutant derivative of DOT‐T1E that overproduces L ‐phenylalanine (Molina‐Santiago et al ., 2016 ), was also engineered to inactivate the gcd gene and transformed with pSEVA633_ xylABE . The resulting 5PLΔ gcd ( xylABE ) strain produced L ‐phenylalanine from 2G hydrolysates confirming the potential of Pseudomonas putida as a chassis to produce value‐added goods from agricultural residues.",
"discussion": "Discussion 2G cell factories and Pseudomonas \n The increase in food prices due to the use of cereal grain in the production of so‐called first‐generation (1G) biofuels (including ethanol) led to the search of new sources of sugars for bioethanol production. The new source of raw material for the so‐called 2G technology is biomass, whose abundance allows for sufficient global feedstock, that is in the United States alone, biomass could reach more than 450 Mdryton/year and this amount, in terms of bioethanol equivalence, is 67 Ggal ethanol/year ( www.energy.gov/sites ). Bioethanol prices are highly volatile and, as such, industry searches for new opportunities in the production of added value products from 2G hydrolysates. Frank ( 2010 ) estimated that the economic potential of biochemicals produced from lignocellulosic residues could reach a value of ~$1 trillion USD, and that more than 60% of the world’s most‐used chemicals could be synthesized from lignocellulose. In spite of these promising prospects, over the last decade the number of ongoing large‐/medium‐scale biosynthetic processes that use biomass has remained rather limited (Aristodou and Penttilä, 2000 ; Chandel et al ., 2018 ). Examples of chemicals produced from 2G hydrolysates at different scales are as follows: ethanol, lactic acid, succinic acid, butanol, acetone, sorbitol and itaconic acid (Valdivia et al ., 2016 ; Chandel et al ., 2018 ). We now add to this list, the production of phenylalanine, an aromatic amino acid that can be transformed into other chemicals such as trans ‐cinnamic acid and styrene (McKenna and Nielsen, 2011 ; Molina‐Santiago et al ., 2016 ). A number of Pseudomonads expressing heterologous genes produced surfactants, organic acids, terpenoids, phenazines and bioplastics from glucose (Rojas et al ., 2003 ; Wittgens et al ., 2011 ; Loeschcke and Thies, 2015 ; Tiso et al ., 2017 ; Wittgens et al ., 2018 ; Wynands et al ., 2018 ). We envisage that the production of this set of chemicals from 2G sugars will be feasible once one of the xylose catabolic pathways described by Bator et al . ( 2020 ) is incorporated into these strains. A true challenge in using 2G technology at the industrial level is not only the conversion of highly recalcitrant and low solubility lignocellulose into monomeric sugars but also their efficient use for chemical production. This requires a series of physico‐chemical treatments to deconstruct plant structures and make cellulose and hemicellulose available for subsequent enzymatic hydrolysis to yield soluble sugars. Figure 2 shows that dilute‐acid steam explosion pretreatment of herbaceous residues resulted in appropriate levels of biomass disorganization of corn stover and sugarcane straw. This specific pretreatment released about 30% to 50% of xylose in the polymers but less than 3% of the glucose (see Table S1 and Rocha‐Martín et al ., 2018 ). Subsequent action of cellulase cocktails can release up 80% of total sugars as monomers (Álvarez et al ., 2016 ). In addition to sugars, the 2G hydrolysates contain acetic acid, furfural and lignin monomers. It is known that some of the chemicals generated from biomass during the pretreatment process are inhibitors of growth. Industrial production of biochemicals from 2G hydrolysates requires as high as possible load of 2G hydrolysates to warrant high production of commodities. The typical 2G bioethanol production processes operate at a solid ratio of 20% (Alcántara et al ., 2016 ); but to generate economic returns, the yields should be close to the theoretical, which in the case of 2G bioethanol production requires that the strains of Saccharomyces used in the process should consume > 96% glucose and > 90% xylose (Valdivia et al ., 2016 ). Co‐utilization of different sugars from lignocellulose by industrial microbes is complex and often subject to catabolite repression which most often prioritizes the use of glucose over other sugars. We have found that this is not the case in our constructs as glucose and xylose are simultaneously consumed. In fact, P . putida derivatives bearing xylABE genes consumed >96% of the sugars released in the saccharification step. The rates of substrate utilization (0.22–0.3 g l −1 h −1 ) were superior to those reported with engineered Saccharomyces to produce ethanol with 2G substrates (Heer and Sauer, 2008 ). This, in turn, resulted in the highest concentrations of L ‐phenylalanine being generated in quite a short time, which in industrial terms will lead to a reduction in the number of fermenters per plant, with a consequent saving in the initial investment, a relevant factor to make the 2G technology economically viable (Valdivia et al ., 2016 ). A current limitation in the use of Pseudomonas as a 2G platform is that P. putida growth in 2G hydrolysates was inhibited when the initial substrate loads were > 5% (w/v). Acetate – which is among the potential inhibitors of growth – seems not to be the responsible for P. putida growth inhibition, because the strain naturally uses acetic acid as a C source and consumed > 85% of the initial acetate in the 2G hydrolysates within 24 h. Other inhibitors present in 2G hydrosylates are furfural, and hydroxymethylfurfural, which are inhibitors of yeast growth (Heer and Sauer, 2008 ). Mutant strains of Saccharomyces tolerant to furfural and able to thrive in lignocellulose hydrolysates have been isolated. However, our preliminary results indicate that T1E tolerates concentrations of up to 20 mM furfural which is higher than those present in 2G hydrolysates; at present, we cannot discard the additive effects of different chemicals as being responsible for substrate toxicity. We are setting up a Laboratory Adaptation Evolution programme to select P. putida strains able to thrive in up to 20% (w/v) 2G hydrolysate load. These mutants are expected to be profitable not only for synthesis of L ‐phenylalanine, as determined in this study, but in general to exploit P. putida industrially to achieve high product concentrations from high initial substrate loads. In summary, we show that P . putida DOT‐T1E Δgcd (xylABE) is able to grow using the C‐sources available in 2G hydrolysates. As P. putida can be easily manipulated to express heterologous pathways, it has high potential for further development as an industrial platform."
} | 4,509 |
24478620 | PMC3898057 | pmc | 2,222 | {
"abstract": "Dynamic Field Theory (DFT) is an established framework for modeling embodied cognition. In DFT, elementary cognitive functions such as memory formation, formation of grounded representations, attentional processes, decision making, adaptation, and learning emerge from neuronal dynamics. The basic computational element of this framework is a Dynamic Neural Field (DNF). Under constraints on the time-scale of the dynamics, the DNF is computationally equivalent to a soft winner-take-all (WTA) network, which is considered one of the basic computational units in neuronal processing. Recently, it has been shown how a WTA network may be implemented in neuromorphic hardware, such as analog Very Large Scale Integration (VLSI) device. This paper leverages the relationship between DFT and soft WTA networks to systematically revise and integrate established DFT mechanisms that have previously been spread among different architectures. In addition, I also identify some novel computational and architectural mechanisms of DFT which may be implemented in neuromorphic VLSI devices using WTA networks as an intermediate computational layer. These specific mechanisms include the stabilization of working memory, the coupling of sensory systems to motor dynamics, intentionality, and autonomous learning. I further demonstrate how all these elements may be integrated into a unified architecture to generate behavior and autonomous learning.",
"introduction": "1. Introduction Organisms, such as animals and humans, are remarkable in their ability to generate behavior in complex and changing environments. Their neural systems solve challenging problems of perception and movement generation in the real world with a flexibility, adaptability, and robustness that surpasses the capabilities of any technical system available today. The question of how biological neural systems cope with the complexity and dynamics of real-world environments and achieve their behavioral goals, does not have a simple answer. Processes such as memory formation, attention, adaptation, and learning all play crucial roles in the biological solution to the problem of behavior generation in real-world environments. Understanding how these processes are realized by the neural networks of biological brains is at the core of understanding biological cognition and building cognitive artifacts that successfully contend with real world constraints. The field of neuromorphic engineering may contribute to the ambitious goal of understanding these cognitive processes by offering platforms in which neural models may be implemented in hardware using the VLSI (Very Large Scale Integration) technology. The analog neuromorphic hardware shares several properties with biological neural networks such as the presence of the inherent noise, the potential mismatch of computing elements, constraints on connectivity, and a limited number of learning mechanisms. Apart from these shared constraints, artificial and biological neural networks also maintain the advantages of pervasive parallel computation, redundant systems to handle sensory and motor noise, and low power consumption. Success in the implementation of cognitive models on neuromorphic hardware may lead to breakthroughs both in understanding the neural basis of human cognition and in the development of performant technical systems (robots) acting in real-world environments. VLSI technology allows one to implement large neural networks in hardware by configuring the VLSI device to simulate the dynamics and connectivity of a network of spiking neurons. Such networks may be efficiently configured, connected to sensors and motors, and operate in real time (Mead and Ismail, 1989 ; Indiveri et al., 2009 , 2011 ). However, a challenging question remains: how to develop these neuromorphic systems beyond simple feed-forward reactive architectures toward architectures capable of cognitive behavior? Soft winner-take-all (WTA) connectivity has been recently proposed as an important milestone on the way toward such functional cognitive neuromorphic systems (Indiveri et al., 2009 ; Rutishauser and Douglas, 2009 ). Soft WTA networks are computational elements that are hypothesized to play a central role in cortical processing (Douglas and Martin, 2004 ; Rutishauser and Douglas, 2009 ). Recently, a wide variety of WTA networks of spiking neurons have been implemented in hardware (Indiveri et al., 2001 ; Abrahamsen et al., 2004 ; Oster and Liu, 2004 ; Indiveri et al., 2009 ). These initial architectures have made use of WTA connectivity to enable the effective processing of sensory information (Liu and Delbruck, 2010 ) and the implementation of finite state machines (Neftci et al., 2013 ). Soft WTAs introduce a cognitive layer to the neuromorphic hardware systems, which enables reliable processing on unreliable elements (Neftci et al., 2013 ). The WTA networks contribute to making neuromorphic systems more cognitive, because they stabilize localized attractor patterns in neural networks. These stable attractors organize the dynamics of the neural system in a macroscopical way and enable the coupling of the network to sensors and motors despite noise, fluctuations, and neural mismatch. WTA connectivity therefore introduces macroscopic neural dynamic states which may persist long enough to interact with other parts of the neural-dynamic architecture, thus moving neuromorphic systems beyond mere reactive behavior. However, there are still open questions on the way toward cognitive processing with hardware WTAs. The first question concerns representational power: How can we add contents to the state in a WTA network and link this network state to perceptual or motor variables? How can the system represent associations and concepts such as “a red ball on the table” or “a hand moving toward an object” in this framework? The second line of open questions concerns movement generation and the motor behavior: How should the system represent and control movements in this framework? How should it decide when to initiate or terminate a movement? Finally, questions regarding learning also arise: How may a system learn WTA connectivity of its neural network? How may the system learn the connections between WTA networks in a complex architecture? Such questions are often addressed in the fields of psychophysics, cognitive science, and artificial intelligence, but the proposed models and solutions are often not compatible with neural implementations. Here, I propose that Dynamic Field Theory (DFT) is a framework which may make such cognitive models feasible for neuromorphic implementation because it formulates the principles of cognitive representations and processes in a language compatible with neuromorphic soft WTA architectures. Identifying the computational and architectural principles underlying these cognitive models may facilitate the development of large-scale neuromorphic cognitive systems. DFT is a mathematical and conceptual framework which was developed to model embodied human cognition (Schoner, 2008 ). DFT is an established framework in modeling many aspects of human cognition and development including visual and spatial working memory, object and scene representation, sequence generation, and spatial language (Johnson et al., 2008 ). DFT cognitive models have been used to control robots and demonstrate that the developed architectures can function autonomously in the real-world (Erlhagen and Bicho, 2006 ; Sandamirskaya et al., 2013 ). DFT builds on Dynamic Neural Fields (DNFs), which, as I will discuss in the Methods section, are analogous to soft WTAs in their dynamics and lateral connectivity within networks (Neftci et al., 2010 ). Accordingly, their dynamical and structural principles may be applied to the design of neuromorphic WTA architectures. In this paper, I discuss computational and architectural principles recently developed in DFT that may be applied to WTA neuromorphic networks. These principles can increase the representational power and autonomy of such networks, and thus contribute to the greater scalability and robustness of neuromorphic architectures. In particular, these principles enable the coupling of DNFs of differing dimensionality, the coupling of the architectures to sensors and motors, cognitive control over behavior, and autonomous learning. On a simple exemplar architecture, I demonstrate how these principles enable autonomous behavior and learning in a neural-dynamic system coupled to real-world sensors and motors. I also discuss the possibility of implementing DNF architectures in neuromorphic hardware.",
"discussion": "4. Discussion 4.1. General discussion The principles of DFT presented in this paper set a possible roadmap for the development of neuromorphic architectures capable of cognitive behavior. As modeling framework, DFT is remarkable in its capacity to address issues of embodiment, autonomy, and learning using neural dynamics throughout. In this paper, I have reviewed the DFT mechanisms that provide for the creation of stabilized sensory representations, learned associations, coupled sensory-motor representations, intentionality, and autonomous behavior and learning. In an exemplar architecture, I demonstrated how the computational and architectural principles of DFT come together in a neural-dynamic architecture, that coupled a neuromorphic sensor to motors and autonomously generated looking behavior while learning in a closed behavioral loop. The categorization properties of DNFs achieve the stabilization of the visual input against sensory noise, while the memory mechanisms allow the relevant representations to be kept active long enough to parameterize and initiate motor actions and also drive the learning process after a successful movement. Adaptive couplings between DNFs together with a mechanism that enables autonomous activation and deactivation of intentions make for an architecture in which autonomous learning accompanies behavior. In order to “translate” the language of behavior-based attractor dynamics of DFT to spiking networks implemented in VLSI, several possibilities have been reported recently. One solution (Neftci et al., 2013 ) constitutes a method to set parameters of the neuromorphic hardware in relation to parameters of a more abstract WTA layer. By measuring the activity of hardware units, the parameter mappings are calibrated in an automated procedure. Another way to translate DNF dynamics to spiking networks is to use the vector-encoding of a dynamical system in the neural-dynamic framework of Eliasmith ( 2005 ). This framework allows one to implement the attractor dynamics of DNFs in terms of a network of spiking units, which in its turn may define the parametrization for a VLSI neuromorphic network. These powerful tools allow one to translate between levels of description and can be used to implement different models of cognition in order to facilitate the development of behaving, neuromorphic cognitive systems. DFT is one of the frameworks that defines the principles and constraints critical to this goal. There are of course several other frameworks that may be used for this purpose, each with its own advantages and limitations. Thus, the probabilistic framework allows one to use noisy and incomplete sensory information to infer hidden states of the environment and weigh alternative actions, which may bring the agent closer to its goals. Such a Bayesian framework has been applied both in the field of modeling human cognition [e.g., Griffiths et al. ( 2008 )] and in robotics (Thrun et al., 2005 ). However, this framework has two limitations with respect to modeling human cognition. First, the probabilistic models focus on the functional or behavioral aspects of cognition and not the neuronal mechanisms underlying cognitive processing. They often require normalization procedures which are not trivial to implement neurally. Second, the probabilistic models often need an external mechanism to make inferences on the probability distributions and do not account for the process of decision making. Thus, the Bayesian architectures may achieve powerful performance and may be used to account for empirical data on human cognition, but they do not provide a process model of cognitive functions or offer a mechanism of how these functions are achieved or realized neurally. On the contrary, in neuronal modeling, the developed architectures are anchored in neuronal data and focus on the mechanisms and processes behind cognition. However, their functional implementations (i.e., embodiment) are typically limited and fail to address important problems such as representational coupling, autonomy, and development. DFT aims at bridging the two approaches to understanding cognitive processing—the functional (behavioral) and the mechanistic (neuronal)—and thus naturally fits the goal of providing for a tool to implement neuromorphic cognition. The scaling of DFT toward higher cognitive functions, such as concept representation, language, and complex action sequencing is currently under way. This paper aims to reveal the formalized DFT principles and concepts developed in embodied cognition and autonomous robotics in such a way that they may be integrated into the language of spiking neural networks in VLSI hardware through the structure of WTA networks. DNF may be considered a functional description of the soft WTA networks. The successful implementation of soft WTA networks in VLSI devices to date opens the way to employing the architectural elements of DFT in spiking hardware architectures. These structural elements as summarized here are (1) coupling between fields of different dimensionality, (2) coupling to sensors through space-coding, (3) coupling to rate-coded motor dynamics, (4) application of principles of autonomy (intentionality), and (5) autonomous neural-dynamic learning. Some of the DFT principles, such as categorization and memory formation, are already probed in VLSI WTA networks, resulting in a framework of state-based computing in spiking networks. In addition, this paper formalizes mechanisms that allow for autonomous transition between stable states through the introduction of elementary behavior structures, namely the intention and the conditions-of-satisfaction. This formalization also enables autonomous learning and the robust coupling of WTAs to each other, to sensors, and to motor dynamics. The DFT approach considers cognitive systems from a behavioral perspective while neuromorphic hardware system development aims at understanding the neuronal mechanisms underlying cognition. The fact that these two approaches converge to a mathematically equivalent object—a DNF or a soft WTA—as an elementary computational unit in the development of cognitive neuromorphic systems is a strong argument for the fundamental character of this computational element. Here, I aimed at establishing a common ground for future collaborative projects that can facilitate progress in both fields. The VLSI networks could scale up to produce cognitive autonomous behavior and the DFT framework could gain access to a neural implementation which is not only more efficient and biologically grounded, but also open to empirical links between the behavioral and neuronal dynamics. Bringing principles of DFT onto VLSI chips will, on the one hand, allow one to model human cognition and make predictions under both neuronal and behavioral constraints. On the other hand, the cooperation between the two fields could foster the development of powerful technical cognitive systems based on a parallel, low-power implementation with VLSI. Conflict of interest statement The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\n\n4.1. General discussion The principles of DFT presented in this paper set a possible roadmap for the development of neuromorphic architectures capable of cognitive behavior. As modeling framework, DFT is remarkable in its capacity to address issues of embodiment, autonomy, and learning using neural dynamics throughout. In this paper, I have reviewed the DFT mechanisms that provide for the creation of stabilized sensory representations, learned associations, coupled sensory-motor representations, intentionality, and autonomous behavior and learning. In an exemplar architecture, I demonstrated how the computational and architectural principles of DFT come together in a neural-dynamic architecture, that coupled a neuromorphic sensor to motors and autonomously generated looking behavior while learning in a closed behavioral loop. The categorization properties of DNFs achieve the stabilization of the visual input against sensory noise, while the memory mechanisms allow the relevant representations to be kept active long enough to parameterize and initiate motor actions and also drive the learning process after a successful movement. Adaptive couplings between DNFs together with a mechanism that enables autonomous activation and deactivation of intentions make for an architecture in which autonomous learning accompanies behavior. In order to “translate” the language of behavior-based attractor dynamics of DFT to spiking networks implemented in VLSI, several possibilities have been reported recently. One solution (Neftci et al., 2013 ) constitutes a method to set parameters of the neuromorphic hardware in relation to parameters of a more abstract WTA layer. By measuring the activity of hardware units, the parameter mappings are calibrated in an automated procedure. Another way to translate DNF dynamics to spiking networks is to use the vector-encoding of a dynamical system in the neural-dynamic framework of Eliasmith ( 2005 ). This framework allows one to implement the attractor dynamics of DNFs in terms of a network of spiking units, which in its turn may define the parametrization for a VLSI neuromorphic network. These powerful tools allow one to translate between levels of description and can be used to implement different models of cognition in order to facilitate the development of behaving, neuromorphic cognitive systems. DFT is one of the frameworks that defines the principles and constraints critical to this goal. There are of course several other frameworks that may be used for this purpose, each with its own advantages and limitations. Thus, the probabilistic framework allows one to use noisy and incomplete sensory information to infer hidden states of the environment and weigh alternative actions, which may bring the agent closer to its goals. Such a Bayesian framework has been applied both in the field of modeling human cognition [e.g., Griffiths et al. ( 2008 )] and in robotics (Thrun et al., 2005 ). However, this framework has two limitations with respect to modeling human cognition. First, the probabilistic models focus on the functional or behavioral aspects of cognition and not the neuronal mechanisms underlying cognitive processing. They often require normalization procedures which are not trivial to implement neurally. Second, the probabilistic models often need an external mechanism to make inferences on the probability distributions and do not account for the process of decision making. Thus, the Bayesian architectures may achieve powerful performance and may be used to account for empirical data on human cognition, but they do not provide a process model of cognitive functions or offer a mechanism of how these functions are achieved or realized neurally. On the contrary, in neuronal modeling, the developed architectures are anchored in neuronal data and focus on the mechanisms and processes behind cognition. However, their functional implementations (i.e., embodiment) are typically limited and fail to address important problems such as representational coupling, autonomy, and development. DFT aims at bridging the two approaches to understanding cognitive processing—the functional (behavioral) and the mechanistic (neuronal)—and thus naturally fits the goal of providing for a tool to implement neuromorphic cognition. The scaling of DFT toward higher cognitive functions, such as concept representation, language, and complex action sequencing is currently under way. This paper aims to reveal the formalized DFT principles and concepts developed in embodied cognition and autonomous robotics in such a way that they may be integrated into the language of spiking neural networks in VLSI hardware through the structure of WTA networks. DNF may be considered a functional description of the soft WTA networks. The successful implementation of soft WTA networks in VLSI devices to date opens the way to employing the architectural elements of DFT in spiking hardware architectures. These structural elements as summarized here are (1) coupling between fields of different dimensionality, (2) coupling to sensors through space-coding, (3) coupling to rate-coded motor dynamics, (4) application of principles of autonomy (intentionality), and (5) autonomous neural-dynamic learning. Some of the DFT principles, such as categorization and memory formation, are already probed in VLSI WTA networks, resulting in a framework of state-based computing in spiking networks. In addition, this paper formalizes mechanisms that allow for autonomous transition between stable states through the introduction of elementary behavior structures, namely the intention and the conditions-of-satisfaction. This formalization also enables autonomous learning and the robust coupling of WTAs to each other, to sensors, and to motor dynamics. The DFT approach considers cognitive systems from a behavioral perspective while neuromorphic hardware system development aims at understanding the neuronal mechanisms underlying cognition. The fact that these two approaches converge to a mathematically equivalent object—a DNF or a soft WTA—as an elementary computational unit in the development of cognitive neuromorphic systems is a strong argument for the fundamental character of this computational element. Here, I aimed at establishing a common ground for future collaborative projects that can facilitate progress in both fields. The VLSI networks could scale up to produce cognitive autonomous behavior and the DFT framework could gain access to a neural implementation which is not only more efficient and biologically grounded, but also open to empirical links between the behavioral and neuronal dynamics. Bringing principles of DFT onto VLSI chips will, on the one hand, allow one to model human cognition and make predictions under both neuronal and behavioral constraints. On the other hand, the cooperation between the two fields could foster the development of powerful technical cognitive systems based on a parallel, low-power implementation with VLSI."
} | 5,736 |
38107972 | PMC10720011 | pmc | 2,223 | {
"abstract": "This work reports a simple, stable, and environmentally\nfriendly\nmethod to prepare durable superhydrophobic surfaces. First, a polydopamine\ncoating is formed by oxidative polymerization of dopamine to form\na secondary reaction platform to provide reaction sites for subsequent\nexperiments. We applied a polydopamine layer onto a fiber surface\nusing the Michael addition-reaction-grafted tetrakis (3-mercaptopropionic\nacid) pentaerythritol ester, followed by the introduction of tetraallyl\nsilane and (mercapto) methyl siloxane-dimethyl siloxane copolymer\non the polydopamine by a thiol–ene click-reaction under ultraviolet\nlight. The resulting superhydrophobic Nylon 56 fabric exhibited a\n166° static contact angle as well as excellent stability. The\nsurface morphology of all samples was observed by field emission scanning\nelectron microscope, X-ray photoelectron spectroscopy and energy dispersion\nspectroscopy, and the elemental composition and surface chemical state\nof the samples were analyzed. It also had the ability of oil-water\nseparation. Fabric with such benefits broadens the applicability and\ninnovation of superhydrophobic textiles for environmental and industrial\napplications.",
"conclusion": "4 Conclusions This work reports the modification\nof Nylon 56 with oxidized and\npolymerized dopamine, further enriched (by a second-order reaction)\nwith hydroxyl groups to attach polydopamine aggregates to the fabric\nsurface. The resulting fabric was further modified with the superhydrophobic\ngroups, attached to the surface by a click coupling reaction involving\nPETMP, TETRA, and MMSDC, and grafted onto the polydopamine aggregates\nalready present on the Nylon 56 surface by Michael addition reaction.\nThis last modification step significantly increased the surface roughness\nof the fabric, which, in turn, substantially reduced its surface energy,\nallowing for superhydrophobic properties. The static contact angle\nof our prepared superhydrophobic material was 166°. It also demonstrated\nexcellent superhydrophobic stability and oil–water separation\nproperties. Moreover, Nylon 56 itself has the advantages of environmental\nprotection, high elasticity, high-temperature resistance, and wear\nresistance. All of these properties allow our novel modified Nylon\n56 to become a strong candidate for environmental applications, involving\nwater reservoir cleaning from oil and other organic pollutants. In\naddition, based on the superstrong adhesion of dopamine, the polydopamine\ncoating formed by oxidative polymerization can be adsorbed on different\nsubstrates through its covalent bonds to form a secondary reaction\nplatform, which can be endowed with superhydrophobic properties after\ngrafting other low surface energy substances.",
"introduction": "1 Introduction The unique wettability\nof superhydrophobic surfaces 1 , 2 attracts wide attention\nfrom scientists and engineers searching\nfor innovative solutions for issues related to corrosion protection,\nand ice accumulation, 3 , 4 a need for self-cleaning and oil–water\nseparating surfaces 5 , 6 as well as for applications associated\nwith antifouling, microfluid transportation, etc. 7 However, among the many superhydrophobic surface preparation\nprocesses, the sol–gel method can adapt to the surfaces of\ndifferent substrates, but the cost is expensive. 8 The coating prepared by the etching method has good mechanical\nproperties, but it is easy to be destroyed in strong acid and alkali\nenvironments, 9 and the template method\ncannot be used in industrial applications because of its complicated\npreparation process. 10 Under ultraviolet\nirradiation, the preparation of superhydrophobic surfaces by the thiol–ene\nclick reaction has attracted great attention, in which C=C\nfunctional groups react with thiol functional groups on the surface.\nThe click reaction of thiol–ene induced by ultraviolet light\nhas the advantages of fast reaction rate, environmental protection,\nhigh yield, and simple operation and is considered as an effective\nmethod of chemical modification. 11 , 12 In an attempt\nto solve all of these issues, this work developed a simple, rapid,\nenvironmentally friendly, and pollution-free method of preparation\nof superhydrophobic surfaces. Surface deposition technology\nbased on mussel 13 bionics is a recently\ndeveloped material surface modification\nmethod, and dopamine is also being sought after by an increasing number\nof scientists. In a weakly alkaline environment, dopamine can undergo\noxidative self-polymerization and polydopamine can be formed on the\nsurface of various substrates. Polydopamine can be easily oxidized\nto form active quinone, which can react with various functional groups\nincluding mercaptan and amine through Michael addition or a Schiff\nbase reaction to form covalently grafted functional coatings. The\nreaction with molecules containing amine or mercaptan is easy and\neasy to operate. The polydopamine layer is also used as an interface\nlayer for postmodification and allows the coating to be further modified\nby other functional materials such as nanoparticles, oligomers, or\npolymers. Based on the inherent advantage of polydopamine as a primer\nin conjunction with lignin to build a hydrophobic substrate, Jiang\net al. produced a low surface energy buffer layer to prevent water\npenetration. 14 Yang et al. incorporated\nTiN/polydopamine nanoparticles onto the polydopamine sponge by using\nhydrolytic methyltrimethoxysilane to endow it with solar-absorbing\ncapability. The addition of these nanoparticles not only reduced assembly\nenergy barriers but also enhanced hydrophobicity and stability. 15 Polydopamine’s strong adhesion properties\nprovide the modified technology unparalleled versatility. 16 − 18 It can be deposited on the surfaces of polymers, metals, metal oxides,\nand even low-surface-energy polytetrafluoroethylene. What researchers\nare most excited about is this technology’s postfunctionalization\ncapability as a secondary reaction platform, which provides a high\ndegree of freedom and maneuverability for constructing functional\nmaterials. We used Nylon 56 as the base material, which was\nthen coated with\npolydopamine (by oxidative in-solution polymerization of dopamine)\nfor subsequent functional grafting. First, we grafted the polymeric\nfilm (using a Michael addition reaction) with multiple sulfhydryl\nfunctional groups and then introduced tetraallyl silane (TETRA) and\n(mercapto)-methyl-siloxane-dimethylsiloxane copolymer (MMSDC) into\nthe modified fibers by a sulfhydryl-olefin click reaction. The resulting\nsuperhydrophobic fabric exhibited excellent physical and chemical\nstability.",
"discussion": "3 Results and Discussion 3.1 Brief Description of the Formation Mechanism\nof Superhydrophobic Fabric First, dopamine oxidatively self-polymerized\nin the aqueous solution, forming dispersed polydopamine aggregates,\nwhich underwent free Brownian motion in the aqueous solution, eventually\nadhering to the fabric fibers coating them. Then, during the second\nstep, PETMP and polydopamine were covalently cross-linked through\na Michael reaction, which modified the fabric surface with numerous\nsulfhydryl groups. Third, UV exposure to light and photoinitiator\naction forced TETRA to react sequentially with the surface sulfhydryl\ngroups on the polydopamine-modified coating. Simultaneously, MMSDC\nwas grafted onto the alkenyl group of TETRA by thiol-alkene click\nchemical reaction, which attached hydrophobic and low-surface-energy\ngroups to the fabric, yielding a superhydrophobic surface (the superhydrophobic\nreaction mechanism is shown in Figure 1 ). Figure 1 Formation mechanism of Nylon 56 functionalization to create\na superhydrophobic\nfabric. 3.2 Surface Morphology and Composition of the\nSuperhydrophobic Fabric Scanning electron microscopy (SEM)\nanalysis of the original fabric revealed a smooth surface ( Figure 2 a). After Nylon 56\nwas modified with polydopamine, aggregates of micro- and nanoparticles\nformed on the surface (see Figure 2 b). Michael’s reaction resulted in the grafting\nof PETMP onto Nylon 56, which translated into a formation of a series\nof closely arranged block polymer particles (see Figure 2 c), which roughened the surface\nof the Nylon 56 fibers significantly. After exposure to UV light,\nan A coating with low surface energy was formed on the surface of\nNylon 56 (see Figure 2 d) due to the formation of a thick polymeric film on its surface.\nThis dense network formed as a result of the incorporation of low\nsurface energy mercapto-alkene groups into the fabric surface by click-reaction. Figure 2 SEM micrographs\nof the (a) original and (b) dopamine-, (c) sulfhydryl-,\nand (d) mercapto-alkene-modified Nylon 56 fabric. The energy-dispersive spectrometry (EDS) energy\nspectra of Nylon\n56 fibers before and after finishing are shown in Table 1 and Figure 3 . Table 1 b shows that the proportion of N content in dopamine-modified\nNylon 56 fibers has increased significantly, indicating that polydopamine\nwas successfully coated on the table’s surface. PETMP was successfully\ndeposited on the polydopamine coating, as evidenced by the appearance\nof element S in Table 1 c. Furthermore, the newly appeared Si element on Nylon 56 fiber ( Table 1 d) evidences that\nthe thiol–ene click chemical reaction was successful. The low-surface-energy\nhydrophobic polymer has been grafted to the fiber’s surface\nand has been formed on the fabric’s surface. Table 1 Element Composition Content of (a)\nOriginal Nylon 56 Fiber, (b) Dopamine-Modified Nylon 56 Fiber, (c)\nSulfhydryl-Modified Nylon 56 Fiber, and (d) Superhydrophobic Nylon\n56 Fiber element C O N S Si total (a) (weight %) 44.732 40.314 14.954 0 0 100 (b) (weight %) 56.618 15.423 27.959 0 0 100 (c) (weight %) 50.460 30.779 16.605 2.156 0 100 (d) (weight %) 60.236 15.467 19.854 2.323 2.12 100 Figure 3 EDS spectra of (a) original Nylon 56 fiber, (b) dopamine-modified\nNylon 56 fiber, (c) sulfhydryl-modified Nylon 56 fiber, and (d) superhydrophobic\nNylon 56 fiber. X-ray photoelectron spectroscopy (XPS) of the original\nNylon 56\nshowed C, O, and N peaks (see Figure 4 a). XPS of the fully modified fabric showed additional\npeaks at 150.5, 100.1, 229.0, and 164.0 eV, which were attributed\nto the Si 2s, Si 2p, S 2s, and S 2p energy bands, respectively. These\nresults indicate that S-containing low surface energy groups were\nsuccessfully attached to the Nylon 56 surface by a click-coupling\nreaction. The C 1s peak in the XPS curve recorded for the original\nfabric was deconvoluted into subpeaks at 284.6, 285.7, 286.5, and\n288.2 eV, which correspond to the C–C/C–H, C–N,\nC–O, and O–C=O bonds, respectively (see Figure 4 b). The appearance\nof the peak corresponding to the C–N bond in the dopamine-modified\nfabric confirmed polydopamine adsorption on the Nylon 56 surface.\nAfter Michael’s reaction (which resulted in grafting the sulfhydryl\nfunctional groups to the Nylon 56 surface) followed by the click-reaction,\nthe Nylon 56 fibers were grafted with TETRA and MMSDC, which translated\ninto the appearance of the XPS peaks at 286.5 and 284.9 eV (see Figure 4 c–e), which\ncorrespond to C–S and C–Si bonds. Figure 4 Survey (a) and high-resolution\n(b–e) XPS spectra of the\noriginal fabric (a, b) as well as fabric modified with dopamine (c),\nsulfhydryl (d), and TETRA/MMSDC grafting (e). 3.3 Influence of the Ratio of Reactants on the\nSuperhydrophobic Finishing of Fabrics Herein, PETMP and MMSDC\nwere sequentially grafted via the thiol–ene click reaction\nand low-surface-energy substances were introduced on the fiber surface.\nTETRA and MMSDC are highly hydrophobic reagents, and the dose ratio\nbetween them has a significant influence on the wettability of the\nfabric surface. Figure 5 shows the relationship between CA and SA and the TETRA/MMSDC ratios.\nWhen the molar mass ratio of the two is 1:3, the static contact angle\nis 166°, the sliding angle is 7.5°, and the superhydrophobic\nperformance is optimal. This is attributed to PETMP already occupying\none double bond, leaving three double bonds available. MMSDC is in\ncharge of the grafting point. It embodies click-chemistry modular\nproperties. The CA did not rise upon an additional increase in the\namount of MMSDC. This could be because the sulfhydryl polymer on the\nfiber has reached a saturated state, and all the double bond grafting\npoints have been occupied. These results show that the best superhydrophobic\nperformance is achieved when the molar mass ratio of TETRA to MMSDC\nis 1:3. Figure 5 Changes in CA and SA correspond to the ratios of TETRA to MMSDC. 3.4 Wettability Tests of the Superhydrophobic\nFabric The wettability of our modified fabric was tested\nby using a static contact angle technique. A deionized water droplet\ncompletely penetrated the original fabric (see Figure 6 a). However, the droplets on the superhydrophobic\nfabric remained spherical and stayed on the fabric surface (see Figure 6 b) at the 166°\nangle. Thus, our 3-step fabric modification significantly decreased\nthe fabric permeability by water and yielded a superhydrophobic effect. Figure 6 Wettability\ntests of the original (a) and modified superhydrophobic\n(b) fabric. 3.5 Mechanical Stability of the Superhydrophobic\nFabric Taking current industrial production requirements\ninto account, the mechanical stability of the superhydrophobic fabric\ndetermines the durability and resistance to external forces. Thus,\nwe used a sandpaper abrasion test to quantitatively analyze the mechanical\ndurability of the superhydrophobic fabric. The fabric was placed on\n1000-Cw sandpaper, pressed with a weight of 500 g, and was then pulled\n15 cm along the ruler, as shown in Figure 7 a. To demonstrate the change in wettability,\nstatic CA and SA were recorded after every five wear cycles ( Figure 7 b). The CA of the\nfabric dropped from 166 to 151° subsequent to five wear cycles.\nThis could be because the low-surface-energy polymer was grafted with\nthe polydopamine coating via strong chemical bonds and the polydopamine\ncoating and fiber were then bonded together. The substrate’s\nsuper adhesion makes it difficult for external forces to damage and\npeel it off. Figure 7 (a) Image of the sandpaper abrasion test. (b) Changes\nin the CA\nand SA of superhydrophobic fabrics subsequent to 25 abrasion cycles. 3.6 Self-Cleaning Performance of the Superhydrophobic\nFabric Superhydrophobic fabrics exhibit exceptional antifouling\nand self-cleaning properties. When pollutants contaminate these fabrics,\nthey can be easily removed by rolling water droplets. In this test,\na reactive blue dye is used as a marker for the self-cleaning test.\nThe blue dye in the original fabric does not move with the water droplets,\nas shown in Figure 8 a,b; however, the pollution spreads over the entire fabric. Conversely,\nthe contaminants on the superhydrophobic fabric are easily removed\nby the water droplets, leaving a clean surface. To further demonstrate\nthe superhydrophobic fabric’s water repellency, both the original\nfabric and the superhydrophobic fabric were immersed in water. The\noriginal fabric sank into the water, whereas the superhydrophobic\nfabric floated on the water’s surface after being released\n( Figure 9 a). Furthermore,\nto investigate the practicality of coated fabrics for everyday use,\nwe performed antifouling tests with saltwater, coffee, milk, dyed\nwater, cola, and tea. The original fabric was wholly polluted and\nwetted, as shown in Figure 9 b,c; however, the droplets on the surface of the superhydrophobic\nfabric were spherical and three-dimensional. The test results show\nthat the modified fabric exhibits excellent self-cleaning and antifouling\nproperties. Figure 8 Self-cleaning test of fabric: (a) original fabric and (b) superhydrophobic\nfabric. Figure 9 (a) Water soaking phenomenon of the original fabric and\nthe superhydrophobic\nfabric, (b) state of different droplets on the original fabric, and\n(c) state of different droplets on the superhydrophobic fabric. 3.7 Oil–Water Separation Performance of\nthe Superhydrophobic Nylon 56 Fabric Superhydrophobic fabrics\nare widely used to alleviate marine oil pollution, because of their\nunique oil–water separation properties. Therefore, we tested\nthe oil/water separation performance of our superhydrophobic fabric.\nFor this purpose, we first dyed (with red color) methylene chloride\nand carbon tetrachloride with oil red O. After that, a piece of our superhydrophobic fabric was placed in\nthe solution, containing these dyed chemicals (see Figure 10 a,b). Our modified fabric\ncompletely absorbed the red droplets ( Figure 10 a,b), proving that it is capable of adsorbing\noil stains. Figure 10 Selective adsorption of methylene chloride (a) and carbon\ntetrachloride\n(b), both dyed with oil red O, in water by the superhydrophobic fabric.\n(c) Oil–water separation test of the superhydrophobic Nylon\n56 cotton interwoven fabric. We then further tested the oil–water separation\nperformance\nof our superhydrophobic fabric using a setup shown in Figure 10 c. We inserted a 6 ×\n6 cm piece of the modified Nylon 56 into the oil–water separation\nflask. Then, dichloromethane and water were dyed with oil red O and\nmethylene blue, respectively, and placed into the same beaker. The\noil/water mixture (containing 100 mL of each liquid) was then poured\nthrough the filtration setup containing our superhydrophobic material.\nThe red oil penetrated the fabric quickly, while blue water remained\ntrapped by the fabric. In addition, in order to test the oil–water\nseparation efficiency of the sample, we carried out the oil–water\nseparation test for 20 cycles. At the end of each separation test,\nwe calculate the separation efficiency by measuring the weight of\nthe remaining water. As shown in Figure 11 , the separation efficiency gradually decreases\nwith the increase of the separation period. However, after 20 cycles,\nthe separation efficiency is still high (above 98.0%). Thus, the superhydrophobic\nNylon 56 fabric developed in this work possessed excellent oil–water\nseparation ability and could be used to treat oil spills in water\nreservoirs. Figure 11 Oil–water separation test."
} | 4,524 |
26435881 | PMC4588217 | pmc | 2,224 | {
"abstract": "Mobile genetic elements in bacteria are enriched in genes participating in social behaviors, suggesting an evolutionary link between gene mobility and social evolution. Cooperative behaviors, like the production of secreted public good molecules, are susceptible to the invasion of non-cooperative individuals, and their evolutionary maintenance requires mechanisms ensuring that benefits are directed preferentially to cooperators. In order to investigate the reasons for the mobility of public good genes, we designed a synthetic bacterial system where we control and quantify the transfer of public good production genes. In our recent study, we have experimentally shown that horizontal transfer helps maintain public good production in the face of both non-producer organisms and non-producer plasmids. Transfer spreads genes to neighboring cells, thus increasing relatedness and directing a higher proportion of public good benefits to producers. The effect is the strongest when public good genes undergo epidemics dynamics, making horizontal transfer especially relevant for pathogenic bacteria that repeatedly infect new hosts and base their virulence on costly public goods. The promotion of cooperation may be a general consequence of horizontal gene transfer in prokaryotes. Our work has an intriguing parallel, cultural transmission, where horizontal transfer, such as teaching, may preferentially promote cooperative behaviors.",
"conclusion": "Conclusion In our recent study we have shown experimentally that horizontal transfer, via its effect on relatedness, favors cooperation. Moreover, our simulations suggest that epidemic spread of mobile elements is essential for this dynamics. Further, based on controlled lab experiments and numerical simulations, we expect our findings to apply to pathogenic bacteria, which regularly encounter new hosts and whose virulence and resistance is often based on secreted molecules encoded on mobile elements. The dynamics we describe could be an important force driving their ecology and evolution. Treatments countering plasmid conjugation, in addition to directly slowing the spread of antibiotic resistance could reduce virulence and resistance benefits. Moreover, because transfer acts on a social, cooperative behavior, resistance to such treatments may be less easy to evolve than resistance to more classical antibiotics. 23 Finally, transfer may be a cooperative behavior in and of itself, and also susceptible to cheating.",
"introduction": "Introduction Plasmids and other mobile elements frequently bear genes involved in social interactions between bacteria. 1 Particularly, they carry genes participating in the production of public goods, molecules that are accessible to other organisms than the producing ones. For instance, β-lactamases, secreted proteins that degrade antibiotics extracellularly, are a cooperative mode of antibiotic resistance, 2 predominantly located on plasmids. 3 More generally, a bioinformatic analysis of Escherichia genomes revealed that genes predicted to code for secreted proteins, likely to be involved in social interactions, are overrepresented on plasmids or mobile regions of the chromosome, 4 suggesting a link between genes involved in social interactions and gene mobility. The maintenance of cooperative behaviors is an important topic in evolutionary biology. Costly public goods can be exploited by cheaters, individuals that benefit from them without contributing to their production, leading to extinction of cooperators ( Fig. 1A ). Social evolution theory predicts that cooperation can be maintained when its benefits are directed preferentially to cooperative organisms ( Fig. 1B ), as summarized by Hamilton's rule 5 : a behavior will be selected when r b > c , with c being its direct fitness cost for the actor, b its indirect fitness benefit to recipients (all individuals benefiting from it), and r the relatedness between actors and recipients. Relatedness is a measure of the statistical association between cooperators, and high relatedness effectively means that recipients of cooperation benefits are likely to be cooperators themselves. High relatedness arises from actors and recipients sharing the cooperative alleles, which usually happens among kin, due to vertical gene transmission. However, horizontal transfer in bacteria can modify this pattern. Particularly, the genes responsible for social behaviors can spread in a population, 6 modifying relatedness at the social locus. 4 It has thus been proposed that horizontal gene transfer helps maintain cooperation in bacteria. 4,6 \n Figure 1. Scenarios for public good maintenance and horizontal transfer in bacteria. Producer cells (green) produce a public good that benefits growth of neighboring cells. Non-producer cells (yellow) benefit from the public good but do not produce it. Well-mixed populations are shown in ( A ) and ( C ) and structured populations where producers interact mainly with other producer cells are shown in ( B ) and ( D ). In ( C ) and ( D ) populations, producer and non-producer alleles can be transferred by conjugation (red pili). Non-producers outcompete producers in competition in a well-mixed population ( A ), but not in structured populations where public good benefits can be restricted to producers ( B ). In well-mixed populations transfer can promote public good production because of the infectious spread of the producer allele, but can spread the non-producer allele as well ( C ). In structured populations, transfer promotes public good production by increasing relatedness ( D ). \n Two explanations for the effect of transfer on cooperation have been put forward. The first hypothesis relies on the enforcement of cooperation in previously non-producing cells by horizontal transfer ( Fig. 1C ). 6 A public good gene, encoded on a transferable plasmid, converts non-producer cells into producers and thus compensates for the competitive disadvantage of the producing cells compared to cells that do not bear the production allele ( Fig. 1C , green cells). However, cheater plasmids bearing a non-producing allele are likely to appear quickly, for instance by deletion of the production allele from a producing plasmid. If cheater plasmids have the same or higher transfer rate compared to cooperative plasmids, cooperation would again be threatened by the spread of cheaters, now at the plasmid level 4 ( Fig. 1C , yellow cells). The second hypothesis addresses this issue of cheating plasmids by focusing on the effect of horizontal transfer on genetic relatedness in a structured population ( Fig. 1D ), rather than direct cooperation enforcement. Models show that horizontal transfer increases relatedness in a patch-structured metapopulation, increasing the probability that 2 individuals in a subpopulation carry the same allele by spreading this allele within the subpopulation. 4 As high relatedness favors cooperation, horizontal transfer should then promote cooperation. Testing the effects of horizontal gene transfer with a synthetic approach The mechanisms described here suggested 2 different ways in which plasmid transfer could promote cooperation, but both lacked experimental validation. More generally, mathematical models provide conclusions on the mechanisms by which a given factor can influence a system's outcome. However, they often do not tell if the parameter's values of living organisms and environments are in the range where the described effect is possible or relevant. Neither of the models here identifies the rates of transfer that would be sufficient to maintain cooperation, a key parameter. Moreover, models make numerous assumptions, that are not necessarily true or realistic, and can also overlook basic or complex processes occurring in living organisms that would affect the conclusions. In our case, important constraints influencing conjugation in natural systems, such as physical ones, could have been missed in the equations. We thus experimentally tested the 2 hypotheses and used numerically solved analytical models with experimentally determined parameters to help understanding population dynamics and explore a wider parameter range. 7 This combination allowed us to benefit from the advantages of both modeling and experimental methodologies. In order to rigorously test for the 2 mechanisms by which transfer could promote cooperation, we used synthetic biology techniques, enabling independent control of public good production and plasmid transfer. The synthetic approach aims at constructing and studying simpler systems where defined components are modified in a controlled way, reducing the complexity of the system. 8 Indeed, natural systems are typically complex, with multiple interactions shaped by evolution and selection. These interactions can be adaptive in natural environments, but will be confounding factors in an analysis where the goal is to precisely measure the effect of individual parameters. Synthetic systems are powerful tools, trading some complexity for control over factors, and can generally be viewed as intermediates between models and natural biological systems. 9 We constructed a synthetic system that combines 2 well-studied natural components: public good production genes from Pseudomonas aeruginosa quorum sensing, and the transfer control system of Escherichia coli F plasmid ( Fig. 2 ). In our case, working with a synthetic system reduced the risk of unwanted interactions between the components being tested. Both public good production 10 and plasmid transfer 11 are extremely regulated in natural systems and sensitive to multiple environmental factors. The relevant genes could thus be regulated by similar or antagonistic signals because of previous co-evolution of transfer and cooperation or could simply be affected by the same environmental conditions. Distinguishing between and controlling for such co-regulation is difficult, even under laboratory conditions. However, with our synthetic system, we could compete strains or plasmids that differ purely in public good production or transfer ability, allowing us to directly link the fitness effects with the transfer of specific alleles. Moreover, fluorescence markers allow us to precisely follow competing strains and plasmid transfer, quantifying the effect of transfer in our experiments. By decoupling transfer and its control, we can focus on the transfer of specific genes (here producer/non-producer alleles), excluding potential effects linked not only to the transfer of other genes involved in plasmid mobilisation and pili production, but also the entry exclusion or toxin-antitoxin systems. Finally, in order for all cells to be able to receive plasmids, we use an F plasmid with no entry exclusion genes to control for transfer.\n Figure 2. Synthetic control of horizontal gene transfer. F HR plasmid is a helper F plasmid bearing oriTm , a mutant oriT not recognized by the F conjugation machinery coded by F transfer operon. The transfer machinery acts only in trans , and mobilizes (blue arrow) the plasmids bearing the wild-type oriT . \n Horizontal transfer promotes the maintenance of public good production We started by experimentally showing that transfer can efficiently promote public good production purely by enforcement of gene expression in recipient cells. Transfer lead to allele frequency changes that largely counteracted the cost of public-good production. We thus demonstrated the validity of the first hypothesis proposing a link between transfer and cooperation, 6 in the short-term: enforcement through transfer can be a very efficient strategy for cooperative alleles to spread in the absence of population structure ( Fig. 1C , when considering that only green cells spread). However, when we competed producer and non-producer alleles that are both mobile, producers decreased in frequency even more than in the total absence of transfer ( Fig. 2C , when both green and yellow cells spread). We thus must conclude that enforcement can explain short-term maintenance and even invasion of public good genes, but not long-term dynamics. Indeed, mobile non-producer alleles will appear rapidly over evolutionary timescales, for instance simply by knockout of the producer gene in a mobile plasmid, and will then outcompete the mobile producer alleles. In the second part of the study, we addressed the hypothesis that transfer promotes cooperation by increasing relatedness 4 ( Fig. 1D ). In order to do so, we used a simple metapopulation consisting of 2 subpopulations that differ in the frequency of producer cells. Each subpopulation is well mixed, but on average, producers encounter more producer than non-producer cells at the metapopulation scale. We showed that public-good production was more favored at the metapopulation level when both producer and non-producer alleles are able to transfer, compared to a situation without any transfer. The effect of transfer was based on between-population dynamics: within subpopulations, the producer allele frequencies did not increase, but among populations growth differences were amplified by transfer. The outcome is analogous to the one arising from the Simpson's paradox, a scenario that was already shown to allow for cooperation maintenance by biasing its benefits toward cooperators. 12 Despite the fact that producers decline within each subpopulation, they outcompete non-producers at the metapopulation scale because populations enriched in producers are more successful and represent a greater proportion of the total population. With transfer, selection among populations was increased, which in turn favored producers at the metapopulation level. The synthetic approach allowed us to test and confirm modeling predictions, showing that our models sufficiently captured the crucial aspects of real biological systems. The key insight of our study is that the effect of transfer can take place within real organisms, and with realistic parameters concerning transfer, benefits and costs, and population structure. For example, the plasmid transfer rate in our experiments was well within, if on the high end, the range for the transfer rates in nature. On the other hand, some of the features of our system are actually likely to be less favorable for either transfer or public good production than the natural ones. Most prominently, the costs of transfer and secretion are probably stronger than in nature, due to the absence of natural regulations decreasing such costs 11,13 : transfer is derepressed and public good production is constitutive in our system, maximizing the cost to the cell. Finally, we focused on conditions where transfer is likely because plasmid-free cells are initially abundant, and avoided the case where most of the cells have plasmids. In natural systems with entry exclusion, there will be little opportunity for transfer in such situation; more complex phenomena like superinfection and virulence toward the host cell could also occur. 14 Our work confirms that maintenance of public good production through horizontal transfer is possible and likely in nature, at least with relatively high transfer rates and availability of plasmid-free cells. Reversely, the maintenance of cooperation could itself explain the existence of high rates of transfer in some natural isolates, 15 alternatively to the selection for a purely parasitic plasmid spread. Still, the full range of parameter values in nature remains unknown, motivating further research on this topic. Horizontal transfer acts through a gene-specific increase in relatedness Our experiments have shown that the stable promotion of public good production relies on the increase in relatedness created by horizontal transfer in structured populations: the association between public good producers increases at the metapopulation level. We got further insight into the dynamics and effect of genetic relatedness by studying it with simulations. We observed that soon after the plasmid invades, relatedness increases strongly ( Fig. 3A ). Because transfer happens at a local scale, it homogenizes local allele content in the cell's neighbors, resulting in relatedness increase. We examined the importance of the interplay between the population structure and the transfer dynamics by modeling horizontal transfer across - and not within – subpopulations. Our results have shown that when transfer is not local, plasmid invasion still occurs, but its effects on relatedness and in turn cooperation, disappear ( Fig. 3B ). We concluded that the effect of horizontal transfer on the maintenance of cooperative behaviors fundamentally relies on infectious transmission specifically at short spatial scales. It is only when transfer is local that the infectious transmission spreads alleles at a local scale while creating stronger assortment at a higher scale.\n Figure 3. Relatedness dynamics. ( A ) Genetic relatedness at the producer (P + ) locus (red) and the proportion of cells in the population that arose by transfer (transfer events, blue) are shown as a function of time. ( B ) Relatedness is shown as a function of the producer allele infectious spread, with local transfer (similar to the experiments, red line) and global transfer (simulating mixing of transferred plasmids across subpopulations, black line). \n Maintenance of cooperative behaviors by horizontal mobility in other systems In our work we focused on the case of plasmid conjugation, which naturally happens at a local scale, between neighboring cells. A number of other horizontally transferred mobile elements, such as integrative conjugative elements, 16 also use conjugation and should thus follow a similar dynamics. On the other hand, there are horizontally transferred elements, including bacteriophages, with an extracellular phase that may make their transmission less spatially constrained. Still, they are likely to infect cells close to the ones that they originated from, and in a patch-structured metapopulation, the infection will also disseminate genes mostly within patches. Another important factor, the cost of transfer, can also vary depending on the particular mobile element. The spread of phages by lysis makes them into virulent parasites, strongly increasing the cost of transfer. But some bacteriophages, such as the filamentous phages involved in Vibrio cholerae virulence, spread by secretion, without cell lysis, 17 and are likely to confer similar costs to the host as the plasmids do. Generally, we expect that our conclusions, derived for plasmid conjugation, extend to any costly, locally spread mobile genetic elements: the promotion of cooperation may be considered a general consequence of horizontal gene transfer in prokaryotes. In the study we consider here we have used a prokaryotic system, but can more generally wonder whether our conclusions would apply to mobile elements in eukaryotes. We believe the effect of transfer would be reduced since mobile elements in eukaryotes are spread through sexual reproduction. 18 Without fast horizontal transmission, the epidemic dynamics of the type we described will be strongly limited and cooperative genes would benefit less from the increase in relatedness arising from gene mobility. There is however another type of phenomenon with dynamics that matches our bacterial system quite well, namely cultural transmission. Cultural transmission generally refers to the way humans, or animals, learn and pass information within their societies. A given behavior can be transferred many times within a single generation, much faster than genetic transmission. When it happens within groups, cultural learning has been shown to increase variation among groups and promotes cooperative behaviors. 19 Early models of the effect of horizontal gene transfer on relatedness borrowed some of the cultural transmission formalism, 4 highlighting the similarities of both phenomena. Horizontal gene transfer in bacteria and cultural transmission in humans share a speed of transmission that is higher than the one for respectively vertical and genetic transmission, and increase assortment when they happen at a local scale. Both processes also have a high specificity: only some of the genes or behaviors are transmitted horizontally. The transferred entities will, on average, experience higher relatedness than others, and will be favored due to their social aspects. Finally, in cultural transmission as well as in plasmid conjugation, the benefits of horizontal spread of cooperation may in turn select for the mobility itself, further coupling cooperation and transfer. Transfer in natural environments and epidemic dynamics A key parameter affecting the possibility of transfer itself and its effect on cooperation is the availability of plasmid-free cells. We focused experimentally on conditions where plasmid-bearing cells are initially rare, leading to many transfer events. Despite the lack of quantitative data for natural ecosystems, the very existence of plasmid transfer mechanisms demonstrates that plasmid-free cells occur frequently enough so that transfer can be selected. Additionally, many plasmids exhibit transitory derepression, their transfer genes being strongly upregulated shortly after entering a new recipient cell, enabling invasive spread in the new host populations. 20 Such regulatory mechanism also suggests that plasmids indeed often encounter new, plasmid-free host populations and undergo epidemic spread. Our simulations showed that the effect of transfer on public good production is the strongest precisely during the epidemic plasmid spread, because the spread leads to a very high number of transfer events. With high transfer rates, sufficient relatedness results simply from the stochastic frequency variations among subpopulations when plasmid-bearing cells are initially rare. The transfer effect will thus be strongest when a few plasmid-bearing individuals repeatedly encounter populations of plasmid-free cells. This could be particularly relevant for the case of pathogens whose growth and virulence are promoted by secreted toxins, 17,21,22 or resistance enzymes. 2 The transfer of toxin or resistance genes to the host microbiome would amplify public good production upon infection, directly increasing fitness and promoting cooperation."
} | 5,607 |
34992140 | PMC8764690 | pmc | 2,226 | {
"abstract": "Significance The reductive acetyl-coenzyme A (acetyl-CoA) pathway is the only carbon fixation pathway that can also be used for energy conservation like it is known for acetogenic bacteria. In methanogenic archaea, this pathway is extended with one route toward acetyl-CoA formation for anabolism and another route toward methane formation for catabolism. Which of these traits is ancestral in evolution has not been resolved. By diverging virtually all substrate carbon from methanogenesis to flow through acetyl-CoA, Methanosarcina acetivorans can be converted to an acetogenic organism. Being able to deconstruct methanogenic into the seemingly simpler acetogenic energy metabolism provides compelling evidence that methanogens are not nearly as metabolically limited as previously thought and suggests that methanogenesis might have evolved from the acetyl-CoA pathway.",
"discussion": "Discussion Since their discovery, methanogenic microorganisms have been considered obligate methane producers ( 31 ), obviously because methane is the end product of their energy metabolism. Here, we demonstrate that a cytochrome-containing methanogen, M. acetivorans , is able to conserve energy and grow—in a sustained fashion—independent of methanogenesis. That the methane-releasing reaction catalyzed by Mcr remains, nonetheless, essential, we attribute to an anabolic requirement of the CoM-S-S-CoB heterodisulfide. That M. acetivorans can be converted from an aceto- and methylotrophic methanogen into a carboxidotrophic acetogen, solely by rewiring its endogenous metabolism (i.e., without introducing foreign genes), bears general consequence on our view of this important archaeal group. The anabolic reaction(s) in M. acetivorans which use(s) CoM-S-S-CoB as oxidant is/are currently unknown. It/they could follow the principle of the thiol-dependent fumarate reductase (TfrAB), which is used to provide Methanothermobacter thermautotrophicus with succinate for the synthesis of α-ketoglutarate ( 32 , 33 ). M. acetivorans does not encode TfrAB and lacks this activity ( SI Appendix , Fig. S6 ). Instead, its genome contains two conspicuous loci, MA4410 and MA4630-MA4631, which could be responsible for the anabolic requirement of CoM-S-S-CoB. The loci encode putative enzymes consisting of a (N-terminal domain of a) FAD/FMN-containing dehydrogenase (COG0277) and a (C-terminal domain of a) FeS cluster–containing homolog of the CoM-S-S-CoB–binding domain of Hdr, similar to TfrAB in predicted tertiary structure ( SI Appendix , Fig. S7 ). Unlike the TfrAB reaction in which the thiols HS-CoM and HS-CoB serve as electron donors for fumarate reduction, MA4410 and/or MA4630-MA4631 would use CoM-S-S-CoB as an electron acceptor for an oxidation reaction. Using CoM-S-S-CoB both as the terminal catabolic as well as an anabolic electron acceptor offers a simple mechanism to integrate energy conservation and biosynthesis in M. acetivorans by dynamically pacing both. The utilization of CO is energetically more favorable than that of H 2 +CO 2 by alleviating the requirement of energy input for the otherwise endergonic formyl-methanofuran formation ( 34 ) ( SI Appendix , Fig. S1 ). This fact might have been key for MKOmtr3 to forfeit its respiratory HdrED, and with it, catabolic methane formation, by possibly allowing to conserve energy via substrate level phosphorylation (SLP). Being able to remove HdrED raises the question about the redox cycling of the methanophenazine (MPh) pool, functioning in Methanosarcina analogous to quinones ( SI Appendix , Fig. S1 ). It was proposed that the Rnf complex couples oxidation of reduced ferredoxin (accruing from CO oxidation) to the reduction of MPh ( 35 – 37 ) ( SI Appendix , Fig. S1 ). The only known oxidant of reduced MPh in the respiratory chain of Methanosarcina is HdrED. Thus, either our understanding of the respiratory mechanism of M. acetivorans is incomplete, or the organism is able to thrive without MPh-dependent energetic coupling. Our experiments do not allow distinguishing between the two possibilities. Theoretically, 9 to 11 g biomass is produced per mol ATP gained through catabolism of chemotrophic anaerobes ( 38 , 39 ). The biomass yield determined for MKOmtrSF of 11.2 ± 2.2 g ⋅ mol −1 acetate produced from CO ( Table 1 ) is within that range. Since acetogenesis from acetyl-CoA yields 1 ATP via SLP ( 40 ), the data are consistent with MKOmtrSF growing acetogenically on CO solely via SLP. However, metabolite production from CO is not balanced for MKOmtrSF (and MKOmtr3, respectively) ( SI Appendix , Table S3 ). Unaccounted-for carbon and electrons indicate that beside the known catabolic products acetate, CO 2 , and formate [methanethiol and dimethylsulfide ( 41 ) were not produced], MKOmtrSF (and MKOmtr3, respectively) generate at least one additional metabolite from—and more reduced than—CO. It is, therefore, conceivable that reoxidation of MPhH 2 might be coupled to the formation of (an) unknown metabolite(s). Other questions raised by the data presented here are how the strain generates methyl-S-CoM from CO in the absence of Mtr and which of the many factors lost in the strain are responsible for its dramatic phenotypic shift ( SI Appendix , Fig. S1 and Supplementary Information Text ). Since acetogenic M. acetivorans MKOmtrSF was obtained solely by removing genes (and one codon of a gene, SI Appendix , Table S4 ) combined with adaptive evolution (i.e., selection-driven adjustment of the metabolic repertoire present), it is conceivable that an H 4 MPT-containing acetogenic ancestor of methanogens, lacking cytochromes, Mtr, Mcr, and Hdr (and the corresponding biosynthesis and maturation machinery) ( 42 ), might have evolved methanogenesis ( SI Appendix , Supplementary Information Text ). Such a scenario would be compatible with the substantial differences in the methyl branch of the bacterial and the archaeal variant of the reductive acetyl-CoA pathway ( 43 ) and with the idea of the reductive acetyl-CoA pathway being the first metabolism ( 3 ). Unlike other groups of chemolithotrophic microorganisms (e.g., acetogenic and sulfate-reducing bacteria) ( 44 , 45 ), methanogenic archaea are metabolically very restricted, both regarding the range of electron donors they use, which include only H 2 , C1 compounds, acetate, and a few secondary alcohols ( 31 ), and electron acceptors (CO 2 and methyl groups), which all lead to the formation of methane and of the CoM-S-S-CoB heterodisulfide ( 8 ). The number of experimentally validated electron donors for methanogenesis is increasing ( 46 – 48 ), and analyses of metagenomes even suggest sugar- and amino acid–dependent facultative methanogenic lifestyles so far not captured through cultivation ( 13 , 49 ). However, alternative electron acceptors were, thus far, not reported to confer to methanogens the ability to grow nonmethanogenically in a sustained fashion (i.e., for more than a few generations). Since such ability is routinely tested by using inhibitors of Mcr, most commonly BES ( 50 – 52 ), the anabolic requirement of the CoM-S-S-CoB heterodisulfide (the product of the Mcr reaction) reported here may shroud the capacity of methanogens for sustained nonmethanogenic energy conservation, which might be much more extensive than currently known."
} | 1,833 |
29691462 | PMC5915390 | pmc | 2,227 | {
"abstract": "In this work, we investigated the molecular basis of autotrophic vs. mixotrophic growth of Chlorella sorokiniana , one of the most productive microalgae species with high potential to produce biofuels, food and high value compounds. To increase biomass accumulation, photosynthetic microalgae are commonly cultivated in mixotrophic conditions, adding reduced carbon sources to the growth media. In the case of C . sorokiniana , the presence of acetate enhanced biomass, proteins, lipids and starch productivity when compared to autotrophic conditions. Despite decreased chlorophyll content, photosynthetic properties were essentially unaffected while differential gene expression profile revealed transcriptional regulation of several genes mainly involved in control of carbon flux. Interestingly, acetate assimilation caused upregulation of phosphoenolpyruvate carboxylase enzyme, enabling potential recovery of carbon atoms lost by acetate oxidation. The obtained results allowed to associate the increased productivity observed in mixotrophy in C . sorokiniana with a different gene regulation leading to a fine regulation of cell metabolism.",
"introduction": "Introduction Photosynthetic conversion of light provides the energy necessary for biomass formation in living organisms. Among photosynthetic species, unicellular microalgae are of great interest due to their high potential for industrial cultivation as light energy converting systems for the production of biomass, food and biofuels, without being in competition with traditional agriculture 1 , 2 . Photo-autotrophic growth of microalgae indeed requires light, CO 2 , water and nutrients yielding lipids, proteins and sugars rich biomass. However, some microalgae species have also the peculiar capability to grow in mixotrophic mode, where the autotrophic metabolism is integrated with a heterotrophic metabolism, that oxidizes the reduced carbon source available in the medium. Mixotrophic cultivation of microalgae holds the potential to significantly improve biomass production, thus fostering the revenues of industrial cultivation: this is particularly important for biofuels production, where productivity and cultivation costs must be respectively maximized and minimized to be sustainable 1 , 3 . The main substrates used for mixotrophic growth of microalgae are glucose, ethanol or cheaper waste products of several industrial processes as acetate or glycerol. Extensive work on Chlamydomonas reinhardtii , the model organism for green algae, demonstrated increased biomass and lipid productivity in mixotrophy compared to autotrophy 4 , 5 . Even in the case of non-model species as Chlorella spp . or Scenedesmus , mixotrophic growth is effective to increase the biomass and lipid productivity 3 , 6 , 7 . However, this is not a general feature of microalgae, since some species, as the marine algae Nannochloropsis gaditana , exhibited similar growth in autotrophy and in presence of different reduced carbon source, due to a reduced photosynthetic efficiency in mixotrophy 8 . In this work autotrophic growth of the thermotolerant high productive strain Chlorella sorokiniana was compared to its mixotrophic growth in the presence of acetate as reduced carbon source in the medium. Acetate was reported to be assimilated in C . reinhardtii as acetyl-CoA which enters the Krebs cycle upon condensation with oxaloacetate to produce citrate. Acetate assimilation in several algae species is strictly linked to the activity of isocitrate lyase enzyme which redirects isocitrate toward the glyoxylate cycle, thus preventing carbon loss as CO 2 upon completion of the Krebs cycle 6 , 9 – 11 . Acetyl-CoA is mainly produced in photosynthetic organisms by oxidation of pyruvate mediated by the mitochondrial pyruvate dehydrogenase enzyme and fueled by photosynthetic produced sugars. An alternative pathway for acetate assimilation is present in the chloroplast, where acetyl-CoA is used for de novo production of fatty acids 12 . The interaction between photosynthesis and acetate metabolism is further complicated by the reciprocal influence of mitochondria and chloroplasts redox state: for instance, in C . reinhardtii alteration of mitochondrial respiration and different NADH availability changed the NADPH content in the chloroplast, inducing different reduction state of plastoquinones 4 , 13 . To investigate the influence of mixotrophic growth in presence of acetate in C . sorokiniana , photosynthetic properties and differential gene expression of autotrophic vs . mixotrophic cultures were thus analyzed in order to identify strategy to further foster the metabolism and improve biomass production for industrial applications.",
"discussion": "Discussion The study describes the impact of acetate availability on gene expression and photosynthetic properties of C . sorokiniana . The availability in the medium of a reduced carbon source as acetate increased biomass yield, cell density and daily productivity of C . sorokiniana cells compared to autotrophic growth. Increase in biomass yield and productivity in mixotrophy was related mainly to an increase of starch and lipid content per cell, even if total protein content was also increased. Photosynthetic traits were not significantly affected in mixotrophy compared to autotrophy: however, upregulation of genes coding for electron acceptors downhill plastoquinones pool as plastocianine, ferrodoxin and FNR, and downregulation of PGR5-like subunit suggests increased electron transport from plastoquinones to NADPH and reduced cyclic electron transport across PSI. Increased reduction of plastoquinone pool in presence of acetate is indeed related to increase transferring of reducing power from mitochondria to the chloroplast, as a consequence of increased NADH production during acetate assimilation. The reduced chlorophyll content per cell observed in mixotrophy was not controlled by differential gene expression of chlorophyll biosynthetic enzymes but rather by downregulation of protein subunits involved in nitrogen assimilation, glycine biosynthesis, iron uptake and accumulation of thylakoid lipid SQDG. Assimilation of acetate has been reported in several organisms to be linked to glyoxylate cycle 9 , 10 and photorespiration 49 , by which glyoxylate is produced. The advantage of glyoxylate cycle toward acetate assimilation is the production of NADH without decarboxylation of isocitrate occurring in the Krebs cycle with the loss of two CO 2 molecules. However, the presence of acetate did not induce in C . sorokiniana any upregulation of glyoxylate cycle enzymes but only caused an increased expression in mixotrophy of the enzymes GOX and serine hydroxymethyltransferase (SHMT), which are both involved in the photorespiratory pathway (Fig. 6 ) 49 . Acetul-CoA produces by acetate assimilation is thus likely consumed in the Krebs cycle or through the glyoxylate produced by a photorespiratory-like pathway: it is important to note that assimilation of acetate through these pathways is accompanied by CO 2 release by isocitrate decarboxylation or by the activity of the SHMT enzymes respectively, increasing the relative CO 2 concentration in mixotrophic cells. Increased CO 2 production in mixotrophic conditions is confirmed by the downregulation in presence of acetate of several genes commonly induced in C . reinhardtii by relative low CO 2 concentration as carbonic anhydrase, RUBISCO activase or components of carbon contrating mechanism (Fig. 4 ) 26 , 50 . De novo transcriptomes reported in this or previous works 11 , demonstrate in C . sorokiniana the presence and expression of genes involved in C4-like carbon fixation pathway: interestringly, the key CO 2 fixing enzyme PPC is upregulated in mixotrophy (Fig. 4 ). These findings suggest that, carbon loss due to acetate oxidation is reduced by the activation in mixotrophy of an alternative carbon fixation pathway by PPC. This strategy allows to maximize the energetic yield of acetate assimilation, reducing the loss of carbon atoms. C4-like carbon fixation pathway has been already reported in the case of diatoms 51 , suggesting a peculiar properties of some unicellular microalgae to improve CO 2 assimilation using different pathway in parallel with the Calvin-Benson cycle. In conclusion, a fine regulation of cellular metabolism is induced by the availability of acetate in the growth medium. The metabolism shift was characterized by the downregulation of glycolysis, pentose phosphate pathway and acetyl-CoA production from pyruvate, while glyoxylate production, biosynthesis of several amino acids and protein translation are increased. Acetate induces also an increase of lipid accumulation which however is not directly related to differential expression of biosynthetic genes. Three transcription factors were identified as differently expressed in autotrophy vs . mixotrophy with TBP upregulated in mixotrophy and the plant specific SBP and Whirly transcription factors downregulated in mixotrophy. These transcription factors are putatively responsible for the different gene expression herein reported, even if the activation/inhibition of other transcription factor cannot be excluded. Several kinases and phosphatases were indeed differently expressed in presence or absence of acetate, which could be involved in the regulation of gene expression. Components involved in ethylene, auxin, salicylic acid and calcium signalling were downregulated in mixotrophy, pointing for a complex network of regulation of gene expression and cell functions. Even if further work is necessary, these signalling components may have a role in the regulation of gene expression in C . sorokiniana under autotrophic condition and possibly in other unicellular microalgae, similar to what described in multicellular higher plants."
} | 2,468 |
28991268 | PMC6003419 | pmc | 2,228 | {
"abstract": "Biological systems can generate microstructured materials that combine organic and inorganic components and possess diverse physical and chemical properties. However, these natural processes in materials fabrication are not readily programmable. Here, we use a synthetic-biology approach to mimic such natural processes to assemble patterned materials.. We demonstrate programmable fabrication of three-dimensional (3D) materials by printing engineered self-patterning bacteria on permeable membranes that serve as a structural scaffold. Application of gold nanoparticles to the colonies creates hybrid organic-inorganic dome structures. The dynamics of the dome structures' response to pressure is determined by their geometry (colony size, dome height and pattern), which is easily modified by varying the properties of the membrane (e.g., pore size and hydrophobicity). We generate resettable pressure sensors that process signals in response to varying pressure intensity and duration.",
"discussion": "Discussion Progress in programming spatial patterns in cell populations 25 , 30 - 34 has lagged behind other developments in synthetic biology, such as programming of logic functions 5 , 35 - 39 , temporal dynamics of single cells 40 , 41 , or temporal dynamics of cell populations 42 - 44 . The scarcity of successful pattern-forming circuits is due to the intrinsic challenges associated with both modeling and experiments 45 . In particular, modeling spatiotemporal dynamics is typically more time-consuming and less intuitive than modeling only temporal dynamics. Similarly, experimental demonstration of patterning dynamics is typically much more difficult than that of temporal dynamics alone. Our results demonstrate programming of 3D materials from a self-patterning colony by coupling gene circuit dynamics with modulation of environmental conditions. In contrast to previous efforts to assemble materials using engineered bacteria 21 , 46 , our work is based on the principle of programmed self-organization. Each bacterium carrying the circuit contains all the information to grow into the final structure (dome), without pre-patterning. The pressure-sensing capability that we demonstrate emerges from this engineered structure; it would have been difficult to achieve by direct assembly of gold nanoparticles by pre-patterning of curli expression 21 . In addition to pressure sensors, such biologically fabricated structured materials could have other applications, such as in plasmonics. For instance, if the domes containing gold could be used as a back contact with solar cells while coated with a dielectric material, the system could be applied to couple or trap sunlight for improved photon absorption in photovoltaics 47 , 48 . In future development of our approach, engineered curli could be used to assemble other inorganic materials to expand the functionality of the dome structure. For example, replacement of the gold nanoparticles with catalytic metal nanoparticles (i.e., CoP) could produce dome structures coated with catalytic sites for applications in water splitting 49 . Diverse tunable patterns could also be generated by varying the gene circuit and the growth conditions. Here we achieved tunability (varying height or width of the colony) primarily by controlling membrane properties. However, pattern formation can be further tuned by adjusting circuit parameters, such as the strength of positive feedback, the burden of circuit activation, or the strength of cell-cell communication 22 , 25 . Alternative circuits can generate other patterns 31 , 32 , 34 by one or multiple engineered populations, and the engineered curli can be replaced by other effector molecules to assemble soft materials, such as self-organized hydrogel formation 50 . Other organisms, such as yeast, could allow further variations in pattern formation 51 . Engineering at multiple time and length scales could enable the predictable 3D assembly of materials for diverse applications in medicine 52 , 53 , biotechnology 54 , 55 and environmental cleanup 56 , 57 . The ability to generate programmable 3D patterns may also facilitate the study of the design principles of natural 3D patterning processes, such as skeletal patterns in limb 58 , tooth 59 , 60 , and biofilms 61 , 62 ."
} | 1,071 |
34489402 | PMC8421398 | pmc | 2,231 | {
"abstract": "The archaeal phylum Woesearchaeota, within the DPANN superphylum, includes phylogenetically diverse microorganisms that inhabit various environments. Their biology is poorly understood due to the lack of cultured isolates. Here, we analyze datasets of Woesearchaeota 16S rRNA gene sequences and metagenome-assembled genomes to infer global distribution patterns, ecological preferences and metabolic capabilities. Phylogenomic analyses indicate that the phylum can be classified into ten subgroups, termed A–J. While a symbiotic lifestyle is predicted for most, some members of subgroup J might be host-independent. The genomes of several Woesearchaeota, including subgroup J, encode putative [FeFe] hydrogenases (known to be important for fermentation in other organisms), suggesting that these archaea might be anaerobic fermentative heterotrophs.",
"introduction": "Introduction The known scope of archaeal diversity has noticeably expanded in recent years after the discovery of novel lineages, enabled by the development of bioinformatics methodologies, the continually generated sequencing data, and cultivation. The expansion of the archaeal tree of life has changed the picture of the ecological and evolutionary importance of archaea. For example, we now know that Thaumarchaeota, ammonia oxidizers detected in aquatic and terrestrial environments, participate in the global nitrogen cycle 1 ; that some members of Bathyarchaeota, archaea from a non-euryarchaeal lineage, exhibit methanogenic characteristics 2 , 3 ; that the genomic content of Asgard archaea sheds light on the origin of eukaryotes 4 , 5 ; and that the DPANN (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanoarchaeota, Nanohaloarchaeota) archaea, a proposed monophyletic group of enigmatic archaea, are typically small cells harboring reduced genomes with a limited metabolic repertoire 6 , 7 . Notably, few DPANN members have been successfully enriched in co-culture and reportedly rely upon their hosts to proliferate 8 – 10 . For instance, Nanoarchaeum equitans is an obligate ectosymbiont of the host , Ignicoccus hospitalis , which provides growth factors, lipids, amino acids, and probably ATP, to N. equitans 8 . However, in a recent study, researchers generated single amplified genomes affiliated with DPANN lineage using fluorescence-activated cell sorting. They found minor heterogeneous DNA sources from potential hosts in the genomes, which raised the possibility that most DPANN archaea might not lead a symbiotic lifestyle in subsurface environments 11 . The Woesearchaeota phylum (formerly Euryarchaea DHVEG-6) was proposed within the DPANN superphylum in 2015 6 . Woesearchaeota are ubiquitous residents of various environments (e.g., groundwater 6 , soil 12 , marine sediments 13 , hydrothermal vents 14 , and freshwater sediments 15 ) where they may shape the surroundings and impact global biogeochemical cycles, interacting or not with other organisms. For instance, based on genome-resolved metagenomic analysis, Castelle et al. 6 proposed that Woesearchaeota AR20 may lead a symbiotic lifestyle, and are involved in anaerobic carbon and hydrogen cycles. Later, Castelle and Banfield 16 reported that some Woesearchaeota may employ the bacterial methylerythritol phosphate (MEP) pathway transferred from Firmicutes to synthesize isopentenyl pyrophosphate and dimethylallyl diphosphate precursors for cell membrane assembly. Investigation of approximately 1000 genomes reconstructed from several metagenomics-based studies revealed that a Woesearchaeota genome, with features suggesting a fermentation-based lifestyle, encodes a near-complete glycolysis pathway, components of a potential metal-reducing respiratory pathway involved in iron metabolism, and a cytoplasmic MvhD-HdrABC complex (F420-non-reducing hydrogenase iron-sulfur subunit D and heterodisulfide reductase ABC) functioning in the final step of methanogenic pathways 17 . Collectively, these studies suggest intriguing metabolic diversity among the Woesearchaeota. Liu et al. 18 reported a co-occurrence pattern between the operational taxonomic units (OTUs) affiliated with Woesearchaeota 16S rRNA genes, and those of Methanomicrobia and Methanobacteria, which indicated possible interactions between members of these groups. Based on these findings, the authors proposed that Woesearchaeota probably provide substrates for H 2 /CO 2 -utilizing methanogens and acetate-utilizing methanogens in return for amino acids and other compounds, to compensate for their own metabolic deficiencies. Meanwhile, a positive correlation of the Woesearchaeota relative abundance and bacterial community was reported in a study based on 16S rRNA gene amplicon sequences, suggesting possible interactions between these microbes 19 . Despite the above-mentioned glimpses into the metabolic potential of Woesearchaeota archaea and interactions with other organisms, their ecological patterns, metabolic diversity, and evolutionary history remain unclear. To address that, here, we retrieved the Woesearchaeota 16S rRNA gene sequences from the Earth Microbiome Project (EMP) datasets. We then analyzed genomes of Woesearchaeota from different environments, including 152 metagenome-assembled genomes (MAGs), with 49 MAGs reported for the first time in the current study. Our analyses help us to understand the global distribution patterns of Woesearchaeota in different biotopes, and shed new light on the metabolism and evolutionary history of Woesearchaeota diversification.",
"discussion": "Discussion Woesearchaeota are one of the most ubiquitously distributed lineages within the DPANN superphylum 18 , 27 . In the current study, we retrieved the Woesearchaeota 16S rRNA gene sequences from different biotopes, to understand the global distribution patterns of Woesearchaeota, and collated 103 Woesearchaeota genomes with 49 new ones reconstructed in this study to gain insights into the metabolism and evolutionary history of Woesearchaeota diversification. We here first updated the previously published 16S rRNA gene-based division of Woesearchaeota subgroups 18 , by inclusion and robust phylogenomic inference from newly reconstructed genomes (see Supplementary Note 1). We anticipated that the newly defined Woesearchaeota subgroups A–J would facilitate understanding of their global distribution pattern. We showed that Woesearchaeota abundance is relatively low in natural environments, although their roles in maintaining the community stability, considering their high diversity, might be important 28 , 29 . Based on the phylogenetic diversity index analysis, Woesearchaeota are more abundant and more diverse in saltmarshes and mangroves than in other biotopes. Sand and soil appear to be the least preferred habitats of Woesearchaeota. Finally, the approximate link between genome subgroups and 16S rRNA gene sequence clusters indicated subgroup G, I, and J may have high ecological adaptability. However, more 16S rRNA gene sequences from genomes are needed to accurately investigate subgroup distribution in the environment. Despite the wide distribution across 11 distinct biotopes, Woesearchaeota appear to share some common metabolic abilities, including the lack of complete TCA cycle and electron transport chains (complexes I−IV), and the minimal capacity to synthesize biomolecules, such as nucleotides, precursors for isoprenoids, amino acids, and vitamins. Further, a complete non-oxidative phase of the pentose phosphate pathway and some genes involved in fermentation, such as ldh , were recovered from most genomes. Hence, being consistent with the previous analyses 6 , 17 , 18 , these features highlight a conspicuous metabolic deficiency of Woesearchaeota, and indicate that most of these archaea might mainly lead an anaerobic and parasitic/fermentation-based lifestyle. How these organisms acquire nutrients and essential building blocks remains unclear because of the lack of pure cultures. These archaea may be intimately associated with other microorganisms, akin to the relationship between N. equitans and I. hospitalis 8 , so as to obtain necessary cellular metabolites, such as amino acids, nucleotides, and lipids. The diversity-generating retroelements abounding in DPANN (highly represented in Woesearchaeota) may also aid the adaption to such a lifestyle 30 . Despite the above unifying traits, the metabolic potentials of Woesearchaeota subgroups vary pronouncedly. Specifically, subgroup J microbes appear to harbor genes involved in the biosynthesis of amino acids and nucleotides more frequently than the other subgroups, suggesting a relatively greater biosynthetic capacity. Interestingly, the MEP pathway, prevalent in bacteria that synthesize isoprenoid precursors, appears to be specific to subgroup J. These differences highlight the notion that Woesearchaeota are diversified organisms, as also confirmed by the genomic size variation, and phylogenetic analysis based on both, the 16S rRNA gene and single-copy orthologs. More surprisingly, two nearly complete MAGs from subgroup J (Yap2000.bin4.8 and YT1_182) encode the complete glycolysis pathway and an amylase (GH57), suggesting their full potential to metabolize starch. In the glycolytic pathway, two NADH and four reduced ferredoxins are generated respectively in the conversion of glyceraldehyde 3-phosphate to 3-phospho-D-glycerol phosphate via glyceraldehyde-3-phosphate dehydrogenase and in the pyruvate decarboxylation by pyruvate/2-oxoacid-ferredoxin oxidoreductase. These two reducing agents could be synergistically utilized by [FeFe] hydrogenase driving the evolution of H 2 . Reduced ferredoxins could also fuel the translocation of sodium ion or proton across the membrane by Rnf complex, generating potential gradient and NADH. In EtfAB/Bcd complex, NADH donates electrons to reduce ferredoxin. Therefore, it is likely that the balance of the reducing pool is maintained by the glycolytic pathway, [FeFe] hydrogenase, Rnf complex, and EtfAB/Bcd complex in these Woesearchaeota. These results indicate that some subgroup J members, if not all, may be capable of anaerobic heterotrophy with fermentative metabolism. To some degree, their lifestyle may have a resemblance with some fermentative bacterial organisms like Thermotoga maritima 31 , 32 and Clostridium thermocellum 33 . According to previous studies 16 , 17 , most CAZymes of DPANN archaea are extracellular. It is also possible that subgroup J members secrete some CAZymes and peptidases into the surrounding medium to decompose starch or other organic matter derived from dead cells or exuded by living cells. Therefore, subgroup J might be able to associate themselves with particles. However, fluorescent in situ hybridization, isotopic labeling, or pure culture experiments are essential to confirm the actual state or lifestyle of these organisms 34 , 35 . [FeFe] hydrogenases are capable of catalyzing H 2 formation with efficiency hitherto unparalleled 22 . Ecologically, members of subgroup J might be important in anoxic environments like hydrothermal vents and marine sediments where they occur more frequently (Supplementary Fig. 5f ) and could benefit other microbes like H 2 -utilizing methanogenic archaea 18 by producing H 2 . Therefore, the above observations suggest that Woesearchaeota may impact the carbon and hydrogen cycle 6 . Whether DPANN archaea form a clan is still debated 36 , 37 , as some DPANN lineages exhibit high rates of sequence evolution, making them vulnerable to long-branch attraction. Some recent reports support the clanhood of DPANN archaea 36 , 37 . Further, inference of the ancestral metabolism of DPANN archaea revealed incomplete glycolysis pathway and TCA cycle in their common ancestor 37 . Woesearchaeota are placed together with Nanoarchaeota, Nanohaloarchaeota, Parvarchaeota, Pacearchaeota, Aenigmarchaeota, and Huberarchaeota in most reports 6 , 27 , 37 . Owing to their reduced genomes, DPANN archaea are thought to be symbionts or parasites of other prokaryotes 6 , 7 . Indeed, the host dependence of some of these organisms has been substantiated. For example, N. equitans , the first DPANN archaeon to be characterized, is obligately dependent on I. hospitalis 8 , and Candidatus Nanohaloarchaeum antarcticus requires Halorubrum lacusprofundi as a host for growth 10 , suggesting that symbiotic or parasitic lifestyle may be a common feature of these DPANN lineages. Nevertheless, the hypothetical lifestyle of DPANN has been recently challenged in a study that proposed that most DPANN archaea do not lead a symbiotic lifestyle in subsurface environments 11 . The presence of a complete glycolysis pathway and extensive repertoires of genes for amino acid and nucleotide biosynthesis as well as hydrogenase in subgroup J highlights the metabolic flexibility of these microbes. Subgroup J archaea first experienced gains of genes related to the transport and metabolism of amino acids and nucleotides and then genes of energy production and conversion. These two steps perhaps enable a reduced dependence on a host or shift to another life strategy that does not require cell–cell association to obtain exogenous cellular components, unlike many other auxotrophic microorganisms 38 . The acquisition of these genes has putatively enhanced the biosynthetic capacity and energy production of these organisms. However, currently, the underpinning drivers are unclear. The acquisition of genes may have been induced by symbiont switching or an alternative resource acquisition strategy 39 . Bacterial organisms, most likely, play major roles in the origination of additional metabolic traits in subgroup J. The acquisition of many genes related to isoprenoid and amino acid biosynthesis is predicted as origination events and likely from bacterial donors. Likewise, genes encoding protein complex vital for energy production like Rnf complex are also projected as originations and possibly transferred from bacteria. Although, pfk , pta, and ackA , important genes in carbohydrate metabolism, are not inferred as gain through originations at the nodes of subgroup J, phylogenetic analyses indicated that they are likely transferred from bacteria as well (Supplementary Figs. 39 − 41 ). For example, pfk of subgroup J are phylogenetically closely related to those of Candidatus Abyssubacteria (Supplementary Fig. 39 ). This is consistent with previous analysis which showed genes related to carbohydrate metabolism are prone to lateral gene transfer 37 ."
} | 3,635 |
31084582 | null | s2 | 2,232 | {
"abstract": "Structural DNA nanotechnology is beginning to emerge as a widely accessible research tool to mechanistically study diverse biophysical processes. Enabled by scaffolded DNA origami in which a long single strand of DNA is weaved throughout an entire target nucleic acid assembly to ensure its proper folding, assemblies of nearly any geometric shape can now be programmed in a fully automatic manner to interface with biology on the 1-100-nm scale. Here, we review the major design and synthesis principles that have enabled the fabrication of a specific subclass of scaffolded DNA origami objects called wireframe assemblies. These objects offer unprecedented control over the nanoscale organization of biomolecules, including biomolecular copy numbers, presentation on convex or concave geometries, and internal versus external functionalization, in addition to stability in physiological buffer. To highlight the power and versatility of this synthetic structural biology approach to probing molecular and cellular biophysics, we feature its application to three leading areas of investigation: light harvesting and nanoscale energy transport, RNA structural biology, and immune receptor signaling, with an outlook toward unique mechanistic insight that may be gained in these areas in the coming decade."
} | 326 |
28220113 | PMC5292420 | pmc | 2,233 | {
"abstract": "Similar to mycorrhizal mutualists, the rhizospheric and endophytic fungi are also considered to act as active regulators of host fitness (e.g., nutrition and stress tolerance). Despite considerable work in selected model systems, it is generally poorly understood how plant-associated fungi are structured in habitats with extreme conditions and to what extent they contribute to improved plant performance. Here, we investigate the community composition of root and seed-associated fungi from six halophytes growing in saline areas of China, and found that the pleosporalean taxa (Ascomycota) were most frequently isolated across samples. A total of twenty-seven representative isolates were selected for construction of the phylogeny based on the multi-locus data (partial 18S rDNA, 28S rDNA, and transcription elongation factor 1-α), which classified them into seven families, one clade potentially representing a novel lineage. Fungal isolates were subjected to growth response assays by imposing temperature, pH, ionic and osmotic conditions. The fungi had a wide pH tolerance, while most isolates showed a variable degree of sensitivity to increasing concentration of either salt or sorbitol. Subsequent plant–fungal co-culture assays indicated that most isolates had only neutral or even adverse effects on plant growth in the presence of inorganic nitrogen. Interestingly, when provided with organic nitrogen sources the majority of the isolates enhanced plant growth especially aboveground biomass. Most of the fungi preferred organic nitrogen over its inorganic counterpart, suggesting that these fungi can readily mineralize organic nitrogen into inorganic nitrogen. Microscopy revealed that several isolates can successfully colonize roots and form melanized hyphae and/or microsclerotia-like structures within cortical cells suggesting a phylogenetic assignment as dark septate endophytes. This work provides a better understanding of the symbiotic relationship between plants and pleosporalean fungi, and initial evidence for the use of this fungal group in benefiting plant production.",
"conclusion": "Conclusion Our work provides new insights into the biodiversity of the widespread pleosporalean fungi associated with halophytes. Future direction will thus be focused on addressing whether these fungi are involved in plant salt tolerance. Symbiotic interactions between plant and pleosporalean fungi may serves as a new model for studying fungal-mediated plant growth and stress tolerance.",
"introduction": "Introduction As intimate partners of plants, many groups of fungi can establish associations with roots and seeds and thereby facilitate plant growth and increase stress tolerance ( Ernst et al., 2003 ; Rodriguez et al., 2009 ; de Zelicourt et al., 2013 ). Plant-associated mycobiota comprise taxonomically diverse members, mainly including arbuscular mycorrhizal fungi (AMF), ectomycorrhizal fungi (EMF) and a number of ascomyceteous and non-mycorrhizal basidiomycetous fungi (NMF) ( Gardes and Dahlberg, 1996 ; Khidir et al., 2010 ; Zuccaro et al., 2014 ). Mycorrhizal symbioses have been extensively described due to their important role in improving plant nutrition and stress tolerance ( Evelin et al., 2009 ). Despite accumulating evidence that plant roots can host many more non-mycorrhizal endophytes than previous thought ( Vandenkoornhuyse et al., 2002 ; Porras-Alfaro et al., 2008 ; Toju et al., 2013 ), the ecological significance of NMF plant associations are poorly understood. Plant fungal endophytes have been categorized into four groups on the basis of a series of criteria including host colonization pattern, transmission model (vertical transmission via host seeds and horizontal transmission via soil- or air-borne spores) and fitness benefits ( Rodriguez et al., 2009 ). Notably, class 2 fungal endophytes can establish habitat-adapted symbiosis and confer specific stress tolerance to the host plant in different extreme habitats ( Rodriguez et al., 2008 ; Redman et al., 2011 ). Similarly, dark septate endophytes (DSEs) are considered to be class 4 endophytes and form melanized hyphae and microsclerotia-like structures in roots ( Knapp et al., 2015 ; Yuan et al., 2016 ). DSEs are the dominant root-associated fungi and more frequent than AMFs from plants grown in extreme environments (e.g., salinity and drought) ( Porras-Alfaro et al., 2008 ; Newsham et al., 2009 ). Some root opportunistic and rhizospheric fungi can also induce systemic resistance against crop diseases ( Shoresh et al., 2010 ; Druzhinina et al., 2011 ; Jogaiah et al., 2013 ) and improve abiotic stress tolerance ( McLellan et al., 2007 ). These findings underscore the importance of NMF in mediating plant productivity. However, it is generally poorly understood how plant-associated fungi are structured in in extreme conditions, and if so, to what extent they contribute to improving plant performance. The Pleosporales order is considered to be among the largest class within the class Dothideomycetes (Ascomycota) ( Phookamsak et al., 2014 ; Tibpromma et al., 2015 ). Some genera of this order comprise ecologically important plant endophytes, including numerous DSEs ( Hamayun et al., 2009 ; Knapp et al., 2015 ). Knapp et al. (2012) demonstrated that pleosporalean fungi occurred in all plant species in semi-arid grasslands of North America. Furthermore, microscopic analysis of the grass Bouteloua gracilis revealed that the fungal community of roots was dominated by a novel DSE belonging to Pleosporales ( Porras-Alfaro et al., 2008 ). Large-scale culture-based surveys show that some fungal genera of the Pleosporales are common endophytes in both coastal and inland arid soils ( Kageyama et al., 2008 ; Maciá-Vicente et al., 2008 ). Consequently, we surmise that pleosprolean fungi are generalist endophytes common within adverse environments. However, their basic physiological characters and potential ecological significance has received only very limited attention. In this work, a wide range of pleosporalean fungi were isolated from the rhizosphere, roots and seeds of halophytic plants in China. We then determined their phylogeny, sensitivity to diverse environmental stresses, and their ability to utilize various substrates of nitrogen. Further, we investigated their effects on plant growth in the presence of organic and inorganic nitrogen.",
"discussion": "Discussion Apart from AMF and EMF, NMF have now been recognized as an important component of the root-associated mycobiome ( Khidir et al., 2010 ; Andrade-Linares and Franken, 2013 ; Zuccaro et al., 2014 ). While there is accumulating evidence regarding the diversity and structure of NMF, their basic physiology and extended effects on plants are not well characterized, especially for plant-associated NMF under extreme conditions. In this work, we characterized halophyte-associated fungi from three geographic areas, six halophyte plant species and three habitats (rhizosphere, root, and seed endosphere), and found that the pleosporalean taxa can be frequently captured. This implies that they are generalist endophytes and/or epiphytes in high salinity environments, and might also mean that this group of fungi is the easiest to isolate and culture under the experimental conditions. This is consistent with other studies where pleosporalean fungi were found to be the dominant colonizers in halophytes ( El-Morsy, 2000 ; Sun et al., 2011 ; Okane and Nakagiri, 2015 ) and plants grown in arid conditions ( Porras-Alfaro et al., 2008 ; Khidir et al., 2010 ). Especially the genera Pleospora, Alternaria , and Phoma were often recorded. Here we show that all pleosporalean strains isolated from our study can be categorized into seven families. Some of them are newly discovered taxa as several clades separated from known fungal taxa by long and well-supported branches ( Figure 2 ). To the best of our knowledge, there is only a single report on a systematic morphological and phylogenetic analysis of diverse pleosporalean DSEs available ( Knapp et al., 2015 ). Consequently, the ubiquity, diversity and novelty of plant-associated pleosporalean fungi in adverse environments will not only provide good phylogenetic resolution within the Pleosporales, but also provide the impetus to elucidate their basic physiology and roles in plant fitness. To our knowledge, this study presents the first in vitro experimental evidence of the ability of pleosporalean fungi to adapt to a series of environmental stresses. Our data showed that the tested isolates are sensitive to ionic (imposed by NaCl and KCl) and non-ionic osmolytes (imposed by sorbitol) with varying degrees, which is consistent with previous observations ( Larsen, 1986 ; Nikolaou et al., 2009 ; Samapundo et al., 2010 ). Most of our isolates were more negatively affected by NaCl stress than KCl or sorbitol stress. It is possible that Na + is poorly taken up by fungi, and could in fact cause alkaline stress, while K + can be easily absorbed and would not accumulate as KOH in the medium ( Larsen, 1986 ). More importantly, some fungi may also utilize K + for surviving in unfavorable conditions ( Larsen, 1986 ). Despite their salt sensitivity, few of them still can grow and survive in 12% NaCl (approximately 2 M NaCl). This is consistent with earlier data that the pleosporalean fungi isolated from halophytes are more likely halotolerant but not halophilic ( Rodriguez et al., 2008 ; Lucero et al., 2011 ; Maciá-Vicente et al., 2012 ). Maciá-Vicente et al. (2012) further speculated that rhizospheric soil fungi may be more tolerant to salt stress than endophytes, as endophytes are protected within plant roots from harsh soil conditions. Our data did not, however, support this hypothesis since there was no significant difference of growth pattern under salinity stress between endophytes and rhizospheric fungi in our conditions. All fungi tested could grow well at high pH, which may imply that both soil and host provide a well-conditioned environment with high alkali for the rhizospheric and endophytic pleosporalean fungi. Taken together, the evidence from the present study suggests that the ability of coping with multiple ecological stresses in pleosporalean fungi should be taken into consideration for their utilization in saline-alkaline soils. It has been known that different nitrogen sources can affect ectomycorrhizal and DSEs fungal growth and biomass accumulation ( Yamanaka, 1999 ; Rosling et al., 2004 ; Mandyam et al., 2010 ). Our results demonstrated that fungal biomass formation on different inorganic and organic substrates significantly varied among species, but most preferred amino acids over inorganic nitrogen sources presumably due to energy and carbon savings for amino acid biosynthesis. Mandyam et al. (2010) also found that several DSEs produced more biomass in the organic N (Gly) than in the inorganic N. Besides that, fungi also can use them as carbon sources for growth. The effective utilization of BSA in many isolates may reflect the occurrence of fungal-derived proteolytic enzymes for hydrolyzing proteins ( Leake and Read, 1990 ; Bizabani and Dames, 2016 ). We suggest that this trait maybe related to their host plants N nutrition ( Cairney and Meharg, 2003 ) (see further discussion below). The influence of NMFs on growth and stress tolerance of plants are now beginning to be revealed. It has often been hypothesized that DSEs confer plant drought tolerance and nutrient acquisition ( Porras-Alfaro et al., 2008 ), whereas other NMFs have been reported to have weak or even negative effects on plant growth ( Jumpponen, 2001 ; Kageyama et al., 2008 ; Dovana et al., 2015 ). It is well-known that a number of factors determine the outcome of plant–fungal interactions, including plant genotype, the genotype and virulence of the fungi as well as the environmental conditions and nutrient status of the soil ( Schulz and Boyle, 2005 ; Singh et al., 2011 ; Murphy et al., 2014 ). The co-cultivation assay confirmed that our isolates colonized rice seedlings asymptomatically. This suggests that the inhibition of plant growth caused by pleosporalean fungi probably results from uncontrolled fungal growth, but not from the fungal virulence factors (mainly mycotoxins) ( Vahabi et al., 2013 ). Since plants obtain their carbon from carbon dioxide, N is the major nutrient they have to retrieve from the soil ( Blair et al., 1998 ). For most plants, inorganic nitrogen compounds are the major source of soluble N ( Roberts et al., 2009 ). In line with previous studies, our data strongly indicates that the nitrogen source influences plant–fungal interactions ( Newsham, 2011 ). In vitro closed co-cultivation system under axenic conditions has been often used for studying plant-NMF interactions. In this case, the most frequently used substrates supporting plant and fungal growth are the MS medium (half strength or one-tenth strength) ( Kageyama et al., 2008 ; Junker et al., 2012 ) and one-tenth strength of Marx-Melin-Norkrans (MMN) medium ( Keim et al., 2014 ), which contains N in the inorganic form. Using these media, researchers found that the majority of fungal endophytes adversely affected plant growth and health, and a few of them were even pathogenic to plants ( Jumpponen, 2001 ; Dovana et al., 2015 ). However, plant growth promotion can be measured in this experimental system if the fungi prove to produce auxin-like compounds in vitro ( Sirrenberg et al., 2007 ; Contreras-Cornejo et al., 2009 ; Redman et al., 2011 ) despite clear evidence of in situ hormone production in planta by endophytes is yet to be elucidated. In the presence of organic N condition, most pleosporalean fungi strongly enhance plant biomass accumulation compared to the presence of inorganic N. This raises the question of why and how the N source influences the interaction with plant roots. It is known that tryptophan (Trp) is a precursor for auxin biosynthesis in fungi and plants ( Redman et al., 2011 ). However, Trp is not present in the range of organic N sources we tested in the context of this study. Those which are present (Gly, Val, Glu, Phe, and Leu) are not known as precursors for the synthesis of plant-growth-promoters. Rather, we propose the possibility that the amino acids will become mineralized upon fungal colonization and therefore available for plant uptake. This hypothesis is supported by earlier reports showing that a wide range of DSE provide more benefits to plant in the presence of organic N than in the presence of inorganic N ( Mandyam and Jumpponen, 2005 ; Upson et al., 2009 ; Alberton et al., 2010 ; Newsham, 2011 ; Mahmoud and Narisawa, 2013 ). DSE has been shown to synthesize proteolytic enzymes, which can mineralize the organic N compounds into the free inorganic N ( Caldwell et al., 2000 ; Bizabani and Dames, 2016 ). This work further extends our view that apart from DSE, the rhizospheric and seed endophytic fungi may also possess a similar functional trait. It has been reported that insect pathogenic fungi and EMF can transport insect-derived organic nitrogen into the plant roots ( Klironomos and Hart, 2001 ; Behie et al., 2012 , 2013 ). More broadly, some rhizobacterial symbionts of plants also secrete proteases and degrade denatured proteins and scavenge organic nitrogen from soil ( White et al., 2015 ). We might say to strengthen this section that bacterial/fungal chitinase and protease activities are known to participate to the N cycle and are crucial for decomposition of soil organic nitrogen ( Heinonsalo et al., 2015 ; Rineau et al., 2015 ; Knapp and Kovács, 2016 ). Hence, it appears likely that diverse plant-associated fungi and bacteria are important players in the soil nitrogen cycle ( Behie et al., 2013 ). As the excessive use of inorganic nitrogen poses a great threat to natural ecosystems and crop yield ( Tilman et al., 2002 ), our findings underscore the enormous potential for utilizing organic N mineralizing microbes in sustainable agriculture. Indeed, some of our isolates have also been shown to promote the growth of trees (e.g., American sweetgum ( Liquidambar styraciflua ) seedlings) under organic N condition (data not shown), thus suggesting the application of this system over a wider range of plants."
} | 4,085 |
33595667 | PMC8351756 | pmc | 2,235 | {
"abstract": "ABSTRACT Unabated mining and utilisation of petroleum and petroleum resources and their conversion to essential fuels and chemicals have drastic environmental consequences, contributing to global warming and climate change. In addition, fossil fuels are finite resources, with a fast-approaching shortage. Accordingly, research efforts are increasingly focusing on developing sustainable alternatives for chemicals and fuels production. In this context, bioprocesses, relying on microorganisms, have gained particular interest. For example, acetogens use the Wood-Ljungdahl pathway to grow on single carbon C1-gases (CO 2 and CO) as their sole carbon source and produce valuable products such as acetate or ethanol. These autotrophs can, therefore, be exploited for large-scale fermentation processes to produce industrially relevant chemicals from abundant greenhouse gases. In addition, genetic tools have recently been developed to improve these chassis organisms through synthetic biology approaches. This review will focus on the challenges of genetically and metabolically modifying acetogens. It will first discuss the physical and biochemical obstacles complicating successful DNA transfer in these organisms. Current genetic tools developed for several acetogens, crucial for strain engineering to consolidate and expand their catalogue of products, will then be described. Recent tool applications for metabolic engineering purposes to allow redirection of metabolic fluxes or production of non-native compounds will lastly be covered.",
"introduction": "INTRODUCTION The modern economy and industry still rely almost entirely on fossil fuel resources for energy, chemicals, and fuels. Imminent shortage of these finite resources and alarming environmental carbon footprint, mostly through fossil fuel-based greenhouse gas (GHG) emissions have recently led to a renewed interest in developing sustainable processes to replace our reliance on fossil fuels. In this context, biological processes, mainly microbial fermentation, have gained interest as they allow efficient conversion of carbonaceous substrates into target products. Biofuels from biomass, such as ethanol production by bacteria and yeasts (Soleimani, Adiguzel and Nadaroglu 2017 ; Tian et al . 2017 ), or acetone, butanol, and ethanol fermentation by Clostridia (Lütke-Eversloh and Bahl 2011 ; Birgen et al . 2019 ), have historically been the predominant bioprocesses, but they cannot currently compete with fossil fuels volume-wise for use as transportation fuels. In addition, upstream lignin degradation for efficient downstream biofuel production remains challenging and expensive (Geddes, Nieves and Ingram 2011 ; Xu et al . 2018 ). Therefore, microbial hosts able to utilise alternative substrates, such as single carbon (C1) gases CO and CO 2 , are crucial to overcome these challenges. Acetogens can grow autotrophically on CO 2 or CO as their sole source of carbon, but also show a great metabolic flexibility through their ability to utilise a wide range of substrates, including methanol, formate or glycolate (Drake et al . 1997 ; Drake, Gößner and Daniel 2008 ; Müller 2019 ). They possess the Wood-Ljungdahl pathway (WLP) of carbon fixation (Wood 1952 ; Drake 1994 ), which allows the conversion of C1-gases into the biomass precursor acetyl-CoA, acetate, and other species-specific products, such as ethanol or butanol, while generating ATP for growth (Ragsdale, 2004 , 2008 ). Although scaling up can be challenging, gas fermentation is industrially promising and viable as the supply of C1-gases is virtually infinite. In fact, several gas fermentation plants are currently in operation with gas supplies derived from various industries such as steel mills (Liew et al . 2016 ; Köpke and Simpson 2020 ). Additionally, recent progresses in genetic (Köpke et al . 2010 ; Kita et al . 2013 ; Mock et al . 2015 ; Hoffmeister et al . 2016 ; Basen et al . 2018 ; Cheng et al . 2019 ; Shin et al . 2019 ) and metabolic engineering of acetogens can theoretically allow the expansion of the range of compounds produced by these bacteria to virtually any desired target. Such advances enable not only insertion and expression of heterologous genes required for the synthesis of the chosen target compound, but also improved performance of the obtained strain to manipulate metabolic fluxes and increase product titres. Acetogenic metabolism and the associated complex energy requirements are now reasonably well understood (Schuchmann and Müller 2014 , 2016 ). The thermophilic acetogen, Moorella thermoacetica (Fontaine et al . 1942 ; Collins et al . 1994 ) served as the model organism to describe the WLP and the relevant enzymology over 10 years ago (Drake, Gößner and Daniel 2008 ; Ragsdale 2008 ), while more recent studies have further strengthened our knowledge of acetogenic physiology and metabolism (Valgepea et al . 2017a , b ; Souza et al . 2019 ). In addition, genome sequences (Pierce et al . 2008 ; Humphreys et al . 2015 ; Li et al . 2015 ) and in some cases, genome-scale metabolic models (Nagarajan et al . 2013 ; Islam et al . 2015 ; Norman et al . 2019 ) are available for several acetogens, further supporting the development of genetic tools. Recent research efforts have also consolidated the availability of genetic tools for these host organisms to support rigorous metabolic engineering efforts. An improved genetic toolkit has been developed in the past few years for some mesophilic acetogens, including Clostridium ljungdahlii (Tanner, Miller and Yang 1993 ), Clostridium autoethanogenum (Abrini, Naveau and Nyns 1994 ), Acetobacterium woodii (Balch et al . 1977 ), and Eubacterium limosum (Roh et al . 2011 ; Kelly et al . 2016 ). Different genetic tools such as inducible promoters (Banerjee et al . 2014 ; Nagaraju et al . 2016 ) and CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas tools (Huang et al . 2016 ; Nagaraju et al . 2016 ; Woolston et al . 2018 ; Shin et al . 2019 ) have been adapted for these host organisms, and exploited to improve strain performance through metabolic engineering, as well as to diversify and enhance their metabolic capabilities. While these technological advances greatly strengthen the potential of gas fermentation for commercial implementation, some acetogens with promising industrial value such as the thermophile, M. thermoacetica or the butanol-producing acetogen, Clostridium carboxidivorans (Liou et al . 2005 ) still present challenges with respect to genetic modification. Although some rudimentary progress has been reported for these two acetogens (Kita et al . 2013 ; Cheng et al . 2019 ), efficient genetic manipulation remains limited as the required genetic tools are lacking. Nonetheless, M. thermoacetica has some attractive properties for industrial applications, as its thermophilic properties would reduce gas cooling and contamination risks in bioreactors. The mesophilic acetogen, C. carboxidivorans differs from other acetogens in its native capacity to produce butanol. As thermophilic properties are advantageous in an industrial context, another acetogenic thermophile, Thermoanaerobacterium kivui (Leigh, Mayer and Wolfe 1981 ) has also recently attracted interest, leading to the development of genetic tools (Basen et al . 2018 ; Jain et al . 2020 ). Disparity in the availability of genetic tools prevents equal opportunities for improving the industrial potential of different acetogens. To date, C. autoethanogenum , C. ljungdahlii , and A. woodii stand out as the most genetically accessible acetogens and therefore, the most promising hosts for industrial gas fermentation applications. Other acetogens such as Clostridium ragsdalei (Kundiyana et al . 2011 ) or Clostridium coskatii (Zahn and Saxena 2012 ) remain largely understudied. This review will explore the optimised genetic tools currently available for some acetogens and the strategies designed to surmount relevant obstacles. A parallel comparison will also be drawn between the progress made and the challenges still faced for other acetogens, for which previously described strategies might be applicable. As for many non-model organisms, successful introduction of foreign DNAs in acetogens depends on overcoming several barriers, including plasmid maintenance through plasmid replication and protection against host restriction-modification systems (Yan and Fong 2017 ). Methods to address these obstacles, described in this review, are crucial to the development of reliable genetic tools. As these tools allow rapid and reliable genetic modifications in hosts, they can further be applied for metabolic engineering purposes, including the production of non-native compounds or the manipulation of metabolic fluxes. Successful metabolic engineering efforts in acetogens will first be briefly summarised in this review followed by additional approaches relevant to achieving various metabolic engineering aims. As metabolic engineering is a broad field and its application in acetogens is rather scarce, only relevant metabolic engineering approaches and their recent or potential implementation in acetogens for further strain engineering purposes will be presented here."
} | 2,337 |
35503913 | PMC9171617 | pmc | 2,236 | {
"abstract": "Significance Multiheme cytochromes in Shewanella oneidensis MR-1 transport electrons across the cell wall, in a process called extracellular electron transfer. These electron conduits can also enable electron transport along and between cells. While the underlying mechanism is thought to involve a combination of electron hopping and lateral diffusion of cytochromes along membranes, these diffusive dynamics have never been observed in vivo. Here, we observe the mobility of quantum dot-labeled cytochromes on living cell surfaces and membrane nanowires, quantify their diffusion with single-particle tracking techniques, and simulate the contribution of these dynamics to electron transport. This work reveals the impact of redox molecule dynamics on bacterial electron transport, with implications for understanding and harnessing this process in the environment and bioelectronics.",
"discussion": "Results and Discussion Successful and Specific In Vivo Labeling of Cell Surface Cytochromes MtrC and OmcA. We used the labeling scheme described in refs. 27 , 28 , 31 to label cell surface cytochromes MtrC and OmcA in S. oneidensis MR-1. Briefly, as pictured in Fig. 1 B and C , a 15-amino acid biotin acceptor peptide (AP) tag from E. coli ( 32 ) was fused to the C termini of MtrC and OmcA. Once assembled in the periplasm and exported to the outer membrane, cytochromes expressing the AP tag can then be biotinylated externally by the addition of biotin ligase BirA. Finally, the biotinylated cytochromes can then be detected by streptavidin-conjugated probes, which would allow the labeled cytochromes to be imaged in real-time by microscopy. Another benefit of this labeling scheme, which combines a small peptide tag with extracellular labeling ( Fig. 1 C ), is to minimize interference to the localization of MtrC and OmcA on the outer surface of the cell, where peptides produced in the cytoplasm are transported to the periplasm for protein folding and heme assembly before being exported to the extracellular side of the outer membrane ( 33 ). DNA inserts for MtrC-AP and OmcA-AP ( SI Appendix , Figs. S1 and S2 ) were constructed by overhang polymerase chain reaction and cloned into the pBBR1-MCS2 plasmid ( 34 ). Plasmid constructs were transformed into respective S. oneidensis MR-1 Δ mtrC or Δ omcA deletion backgrounds from ref. 35 . All strains, plasmids, and primers used in this study are listed in Table 1 and SI Appendix , Table S1 . Cytochrome presence was then detected by staining SDS-PAGE gels with a heme-reactive peroxidase activity assay using 3,3′-diaminobenzidine and hydrogen peroxide ( SI Appendix , Fig. S3 ), which confirmed that the AP-tagged strains produced heme-containing proteins of expected size, compared to positive and negative controls (wild type and gene deletion mutant). Sanger sequencing of plasmids purified from final host strains also verified sequence integrity of the AP tag. Table 1. Strains and plasmids used in this study Strain or plasmid Description or relevant genotype Source or reference S. oneidensis MR-1 Wild type ( 8 ) S. oneidensis MR-1 Δ mtrC ( 35 ) S. oneidensis MR-1 Δ omcA ( 35 ) S. oneidensis MR-1 Δ mtrC pMtrC-AP, Km R This study S. oneidensis MR-1 Δ omcA pOmcA-AP, Km R This study S. oneidensis MR-1 ΔMtr/Δ mtrB /Δ mtrE ( 62 ) E. coli DH5α Host for cloning Lab collection E. coli DH5α pMtrC-AP, Km R This study E. coli DH5α pOmcA-AP, Km R This study pBBR1-MCS2 Broad range cloning vector, Km R ( 34 ) pMtrC-AP mtrC and 118 bp upstream sequence and biotin acceptor peptide (AP) tag in pBBR1-MCS2, Km R This study pOmcA-AP omcA and 114 bp upstream sequence and biotin acceptor peptide (AP) tag in pBBR1-MCS2, Km R This study Next, we performed Western blot and microscopy controls where we systematically omitted key components in the labeling process, to confirm that the labeling scheme works in our system ( Fig. 2 and SI Appendix , Fig. S4 ). In Western blots probing for biotinylated proteins using streptavidin-horseradish peroxidase, MtrC-AP (or OmcA-AP) were detected only when all key components of the labeling process were provided ( Fig. 2 A and SI Appendix , Fig. S4 A ), indicating that the tagged protein was successfully and specifically biotinylated and detected by the streptavidin probe. Similarly, microscopy labeling controls were performed, where biotinylated proteins were visualized by streptavidin-conjugated Alexa Fluor 647 ( Fig. 2 B and SI Appendix , Fig. S4 B ). Although cells were visible by standard brightfield imaging in all samples, strong fluorescent signal visualizing biotinylated proteins were only detected in the condition where all key labeling components were present. Taken collectively, these Western blot, fluorescence microscopy, and associated controls demonstrate successful and specific labeling of MtrC and OmcA. Furthermore, our ability to perform extracellular in vivo labeling and subsequent microscopic detection of MtrC and OmcA via a C-terminal AP tag is consistent with the recently published orientation of MtrC relative to the MtrAB transmembrane complex ( 10 ), where Heme 10 (C-terminal side) is extracellularly exposed and Heme 5 (N-terminal side) is facing the cell surface. Fig. 2. Key labeling controls demonstrate successful and specific labeling of MtrC. ( A ) Western blot labeling control for MtrC where key parts of the labeling process were systematically omitted. When using streptavidin (streptavidin-horseradish peroxidase, HRP) to probe for biotinylated proteins, a thick dark band of biotinylated MtrC-AP is detected only in lane 5 when all key components are present. The faint band slightly below labeled MtrC-AP (∼79.6 kDa) and present in all samples is an endogenously biotinylated protein (acetyl-CoA carboxylase, ∼76 kDa) ( 61 ). ( B ) Microscopy labeling control for MtrC where key parts of the labeling process were systematically omitted. Top row contains brightfield (BF) images showing many cells in each sample. Bottom row images show fluorescence (Fl) signal from streptavidin-conjugated Alexa Fluor 647 that was used to detect biotinylated MtrC-AP; fluorescence labeling was detected strongly in the bottom right image, and only when all key labeling components were present. (Scale bars: 5 μm.) Single-Particle Imaging and Tracking Reveals Mobility of MtrC and OmcA along Cell Surface and Membrane Extensions. Once the labeling scheme was established in our system, we investigated cell surface protein dynamics using targeted quantum dot (QD) labeling and single-particle tracking (SPT) ( 24 , 30 , 36 ). QDs were chosen as the fluorescent label due to their high signal-to-noise ratio and photostability, which makes them useful for SPT ( 30 , 36 ). In addition, this labeling scheme takes advantage of the very strong (femtomolar scale) binding affinity and very low dissociation rate between biotin and streptavidin, which makes biotin-streptavidin labeling schemes useful for single molecule labeling and other applications ( 37 , 38 ). The size of streptavidin probes is expected to negligibly affect membrane protein diffusion, which is mainly influenced by membrane viscosity ( 39 ), and past studies found no difference in diffusion of lipid-anchored proteins probed with QDs vs. small fluorescent dyes ( 40 , 41 ). To test the hypothesis that MtrC and OmcA are mobile along the cell surface and to quantify their diffusion behavior, we labeled cells expressing either MtrC-AP or OmcA-AP by in vivo biotinylation and streptavidin-conjugated QDs ( Fig. 1 B and C ) and imaged their dynamics on the surface of living cells by dual-color time-lapse TIRF microscopy. To visualize the cell outer membrane and membrane extensions, we used FM 1-43FX, a lipid membrane dye. To visualize individual cytochromes, we titrated the concentration of streptavidin-conjugated QDs until it was possible to distinguish individual particles (e.g., 1 to 5 QDs/cell). We observed that MtrC and OmcA are indeed mobile along the cell surface and outer membrane extensions, and we traced their mobility with SPT ( Fig. 3 and Movies S1–S3 ). Briefly, SPT detects the position of each QD molecule in each frame and connects these detected positions frame-by-frame to build trajectories over time. In our experiments, the typical QD localization precision was ∼15 nm. Fig. 3 highlights the workflow of single QD detection and tracking as applied to labeling of OmcA on the S. oneidensis cell surface. Starting with a large field of view ( Fig. 3 A ), the fluorescence of individual QDs across hundreds of cells was tracked, typically over 1 to 2 min, with an acquisition rate of 40 ms/frame to generate thousands of trajectories of cytochrome diffusion. Individual QD trajectories were typically punctuated by gaps resulting from the expected blinking behavior of single QD molecules ( 42 ). Zooming in on individual cells ( Fig. 3 B and C , corresponding to dashed areas in Fig. 3 A ) highlights the heterogeneous behavior of diffusing cytochromes, which was further analyzed to classify and quantify diffusive dynamics. Fig. 3. Imaging and single molecule tracking of quantum dot (QD)-labeled OmcA using total internal reflection fluorescence (TIRF) microscopy. ( A ) Snapshot of QD-labeled OmcA trajectories (white) in multiple cells (cyan). Trajectories from 1.5 min of time-lapse microscopy (40 ms/frame) were overlaid onto the corresponding mean intensity projection image of cells labeled with lipid membrane dye FM 1-43FX. Trajectories in white dashed boxes are blown up in ( B ) and ( C ). (Scale bar: 2 μm.) ( B and C ) Some example trajectories from the two cells outlined in ( A ), ranging from 0.16 to 1.16 s in duration. (Scale bars: 500 nm.) ( D and E ) Streptavidin-conjugated QD705 was used to detect exogenously biotinylated OmcA-AP (red). Cell membrane and membrane extensions are labeled by FM 1-43FX (cyan). ( D ) Trajectories from a single QD-labeled OmcA as it moved along the surface of a cell, as seen in Movie S1 . Here, QD signal (red) and its trajectories (white) are overlaid with the mean intensity projection image of the cell (cyan). For clarity, only the first frame of QD signal is shown; trajectories are from the entire video (86 s, 40 ms/frame). (Scale bar: 500 nm.) ( E ) Snapshot of QD-labeled OmcA trajectories overlaid on an outer membrane extension. Trajectories (white) are from 6 min (40 ms/frame) of time-lapse microscopy tracing several QD-labeled OmcA (red; mean intensity projection image) on a membrane extension that appears to connect two cells (cyan; mean intensity projection image). A short portion (12 s) of the time-lapse corresponding to this panel can be seen in Movie S2 . (Scale bar: 500 nm.) When viewed in the context of the cell surface ( Fig. 3 D ) and membrane extensions ( Fig. 3 E ), we observed that QD-labeled MtrC and OmcA can both explore a significant fraction of the underlying membrane surface. In addition, we observed significant overlap in diffusion trajectories for multiple cytochromes, notably along a membrane extension linking two cells shown in Fig. 3 E . These observations support our proposed collision-exchange mechanism for long-distance electron conduction ( Fig. 1 A ) ( 16 ), where diffusive dynamics can bridge gaps between cytochromes and, combined with direct electron hopping, lead to a continuous path for electron transport along the membrane. While long-distance multicell conduction was recently observed by electrochemical gating, and cytochrome diffusion was proposed to play a role ( 12 ), our measurements provide a direct look at these dynamics. Next, we sought to quantitatively analyze the diffusion characteristics in order to assess their contribution to biological electron transport over micrometer length scales. Quantifying the Dynamics of MtrC and OmcA along the Cell Surface and Membrane Extensions. To quantify the observed cytochrome mobility, we performed diffusion analyses for MtrC or OmcA trajectories diffusing either on the cell surface or on membrane extensions. Methods for SPT and determination of diffusion coefficients have previously been described in detail ( 26 , 30 , 43 – 45 ). All diffusion coefficients determined in this study are listed in Table 2 and described below. Table 2. Summary of diffusion coefficients ( D ) and confinement radii ( R ) determined in this study using a 1-component or 2-component model of diffusion ( Figs. 4 – 7 ) Protein Surface Fraction D (µm 2 /s) R (nm) MtrC Cell 100% 0.0192 ± 0.0018 80.0 ± 1.3 \n MtrC1 (Slow component) \n Cell 90% 0.00235 ± 0.00112 18.7 ± 2.3 \n MtrC2 (Fast component) \n Cell 10% 0.124 ± 0.010 264 ± 3 OmcA Cell 100% 0.0125 ± 0.0024 58.7 ± 2.2 \n OmcA1 (Slow component) \n Cell 94% 0.000577 ± 0.000152 18.3 ± 0.8 \n OmcA2 (Fast component) \n Cell 6% 0.0939 ± 0.0059 242 ± 3 MtrC OME 100% 0.00945 ± 0.00028 132 ± 1 \n MtrC1 (Slow component) \n OME 66% 0.00162 ± 0.00011 51.7 ± 0.6 \n MtrC2 (Fast component) \n OME 34% 0.0353 ± 0.0021 198 ± 2 OmcA OME 100% 0.0102 ± 0.0002 112 ± 0.3 \n OmcA1 (Slow component) \n OME 82% 0.00188 ± 0.00006 46.5 ± 0.2 \n OmcA2 (Fast component) \n OME 18% 0.0482 ± 0.0016 242 ± 1 Percentages indicate the fraction of all trajectories belonging to each respective component. D and R values were determined according to a confined diffusion model ( SI Appendix , Eq. 2 ) First, we evaluated the general diffusion of MtrC or OmcA on the cell surface by pooling data from all trajectories in each dataset and constructing ensemble mean squared displacement (MSD) curves ( Fig. 4 ). We found that both MtrC and OmcA exhibit confined diffusion behaviors, with MSD curves reaching a plateau over timescales <1 s. By fitting these curves with a confined diffusion model ( SI Appendix , SI Materials and Methods ), we determined the overall diffusion coefficients D and confinement radii R for QD-labeled MtrC ( D = 0.0192 ± 0.0018 µm 2 /s; R = 80.0 ± 1.3 nm) and OmcA ( D = 0.0125 ± 0.0024 µm 2 /s, R = 58.7 ± 2.2 nm). While quantitative information regarding the diffusion of bacterial cell surface proteins is limited, our measurements of MtrC and OmcA ( Table 2 ) are consistent in magnitude with the observations made for other bacterial outer membrane proteins, which are on the scale of D = 0.006–0.15 µm 2 /s and R = 15–300 nm ( 23 – 25 , 46 ). Moreover, the confinement radii of MtrC and OmcA are consistent with our previous measurements of center-to-center distances between putative cell surface cytochromes in S. oneidensis ( 16 ). We note that while a single cytochrome does not typically travel out of a confinement domain, multiple cytochromes might populate, diffuse, and collide within the same region. Proteins can also stochastically escape an area of confinement and diffuse more freely across a larger distance of the cell surface over time, before encountering other obstacles. Fig. 4. Ensemble mean squared displacement (MSD) analysis shows overall confined diffusion behavior by MtrC (blue) and OmcA (orange) on the cell surface. Y-axis shows mean displacement squared ( r 2 ) for each time lag (Δ t ) on the X-axis. Fitting the plots with a confined diffusion model ( SI Appendix , Eq. 2 ) yields diffusion coefficients D and confinement radii R as labeled. Error bars show ± r 2 N , where N is the number of independent data points (i.e., displacements) analyzed for a given Δt . These curves represent 7,678 QD-labeled MtrC and 7,109 QD-labeled OmcA trajectories on the cell surface, from 500 to 1,000 cells each. To estimate the smallest diffusion coefficient measurable under our experimental conditions, we also quantified the apparent diffusion of QDs imaged on coverslips, under cell-free conditions. Unsurprisingly, we observe much slower mobility, with D = 3.56 × 10 −5 ± 1.62 × 10 −5 µm 2 /s ( SI Appendix , Fig. S5 ), clearly distinct from the lateral diffusion of MtrC and OmcA ( Fig. 4 and Table 2 ). To rule out the possibility that the observed cytochrome diffusion is influenced by streptavidin-conjugated QDs binding multiple targets ( 30 ), SPT was also performed in the presence of excess free biotin, added to cells immediately after QD labeling in order to saturate residual streptavidin binding sites. Under biotin saturation, no change in the distribution of diffusion coefficients was observed ( SI Appendix , Fig. S6 ), indicating that the membrane mobility of MtrC and OmcA is not impacted by cross-linking from multivalent streptavidin QDs. We also confirmed that cells maintain viability throughout labeling and imaging; a uniformly low 1 to 4% of cells were membrane compromised even hours after QD labeling ( SI Appendix , Fig. S7 ). Some increased cytochrome expression is seen in cells expressing MtrC/OmcA-AP ( SI Appendix , Fig. S3 ), which does not affect cell viability ( SI Appendix , Fig. S7 ), but might contribute to protein crowding and an underestimate of cytochrome diffusion; in future work, this may motivate systematic analyses of diffusion in backgrounds with reduced or controlled cytochrome expression. As seen in Fig. 3 , heterogeneities in the shape of diffusing trajectories (e.g., Fig. 3 D and Movie S1 ) suggest that MtrC and OmcA might transition between multiple diffusing behaviors. To address this possibility, the ensemble of trajectories for each type of cytochrome was analyzed by probability distribution of square displacements (PDSD) ( 41 , 43 , 45 ) ( Fig. 5 ). We found that the diffusion of MtrC could be described by a 2-component model, with 90% of MtrC displaying a slow and confined mobility with diffusion coefficient D 1 = 0.00235 ± 0.00112 µm 2 /s and confinement radius R 1 = 18.7 ± 2.3 nm, while a 10% minority diffuses significantly faster over less confined membrane regions ( D 2 = 0.124 ± 0.010 µm 2 /s, R 2 = 264 ± 3 nm). Likewise, the majority of OmcA displayed a slow and confined diffusive behavior (94%, D 1 = 0.000577 ± 0.000152 µm 2 /s, R 1 = 18.3 ± 0.8 nm) together with a less prevalent but faster diffusion over large membrane domains (6%, D 2 = 0.0939 ± 0.0059 µm 2 /s, R 2 = 242 ± 3 nm). The faster, less confined diffusion detected by this analysis ( Fig. 5 B and D ) may represent events where generally confined redox proteins escape crowded areas and diffuse more freely across the bacterial membrane, their diffusion being limited by the overall size of the cell itself, typically 500 nm in diameter. The detection of two diffusive behaviors for MtrC and OmcA is also consistent with the heterogeneity in distribution of proteins along the cell surface previously observed by electron cryotomography ( 16 ), which is a common feature among membrane proteins in bacteria ( 25 , 47 ). Fig. 5. Diffusion analyses for MtrC (blue) and OmcA (orange) on the cell surface, using a 2-component model of diffusing behavior. ( A and B, Left ): MtrC. ( C and D, Right ): OmcA. On the cell surface, MtrC and OmcA diffusion can be described by two behaviors: ( A and C ) a slower, more confined majority and ( B and D ) a faster, less confined minority. Percentages indicate the respective fractions belonging to each component as determined by probability distribution of square displacement (PDSD) analysis, as described in ( 43 , 45 ). Ensemble mean squared displacement (MSD) curves were plotted as mean displacement squared r 2 as a function of time lag Δ t . Fitting these curves with a confined diffusion model ( SI Appendix , Eq. 2 ) yields diffusion coefficients D and confinement radii R , as labeled on each plot. Error bars show ± r 2 N , where N is the number of independent data points (i.e., displacements) analyzed for each component for a given Δ t . These curves represent 7,678 QD-labeled MtrC and 7,109 QD-labeled OmcA trajectories on the cell surface, from 500 to 1,000 cells each. Next, we investigated the dynamics of MtrC and OmcA on outer membrane extensions (OMEs) of S. oneidensis . Compared to cell surface measurements, imaging of QD-labeled cytochromes on OMEs presented technical challenges. Our previous work using a perfusion flow imaging platform ( 16 ) allowed robust epifluorescence observations of OME production over time by restricting OMEs to the focal plane using laminar media flow; under these conditions, we could observe a majority (∼78%) of cells producing OMEs ( 18 ). However, this flow was not desired during SPT experiments, since it may interfere with measurements of cytochrome movement. Thus, under our TIRF imaging conditions, OMEs frequently moved in and out of the evanescent excitation field, limiting our ability to easily image these structures and to track individual QDs along them. We therefore limited our analyses to nonmoving OMEs that were clearly connected to a cell and were labeled with a low density of QDs. To compensate for the reduced number of QD-labeled OMEs that were optimal for tracking compared to SPT on whole cells, and to record a sufficient number of diffusion steps for analysis, we tracked QDs on OMEs over periods of 6 min. Ensemble MSD analysis for MtrC and OmcA on OMEs revealed membrane mobilities similar to those observed on the cell surface. The overall diffusion coefficient and confinement radius for MtrC were D = 0.00945 ± 0.00028 µm 2 /s and R = 132 ± 1 nm, and for OmcA were D = 0.0102 ± 0.0002 µm 2 /s and R = 112 ± 0.3 nm ( Fig. 6 ). Compared to diffusion on the cell surface ( Fig. 4 ), larger confinement radii for both cytochromes indicate that they are less confined on OMEs than on the bacterial surface. Yet, their respective diffusion coefficients remain on the same order of magnitude, with diffusion being reduced by approximately twofold on OMEs compared to the cell surface for MtrC ( P < 0.0001) ( Figs. 4 and 6 and SI Appendix , Fig. S8 ). The reduced confinement of cytochromes on OMEs might stem from differences in the degree of molecular crowding between these extensions and the cell surface. The moderately slower dynamics on OMEs may be related to their morphology, since OMEs can present as vesicle chains with possible junction densities that might limit membrane fluidity at each junction ( 16 ). Furthermore, diffusion coefficients on both cells and OMEs may be underestimated by an additional 25 to 50%, as motion on a three-dimensional (3D) tubular membrane surface is projected onto a two-dimensional (2D) image plane during SPT and analysis ( 48 , 49 ); this may contribute to moderately slower dynamics on OMEs relative to cells, as this underestimate is greater for smaller tube diameters ( 49 ). Fig. 6. Ensemble mean squared displacement (MSD) analysis shows overall confined diffusion behavior by MtrC (blue) and OmcA (orange) on outer membrane extensions (OMEs). Y-axis shows mean displacement squared ( r 2 ) for each time lag (Δ t ) on the X-axis. Fitting the plots with a confined diffusion model ( SI Appendix , Eq. S2 ) yields diffusion coefficients D and confinement radii R as labeled. Error bars show ± r 2 N , where N is the number of independent data points (i.e., displacements) analyzed for a given Δ t . These curves represent 1,140 QD-labeled MtrC trajectories from 5 OMEs and 5,371 QD-labeled OmcA trajectories from 22 OMEs. In light of the heterogeneity in diffusion observed on the cell surface ( Fig. 5 ), we also investigated the possibility that MtrC and OmcA exhibit multiple diffusing behaviors on OMEs. Using PDSD analysis, we found that their dynamics on OMEs can also be described by two behaviors: ( i ) a slow and highly confined mobility for a majority of trajectories, and ( ii ) a faster and less confined diffusion for a smaller fraction of trajectories ( Fig. 7 ). Diffusion coefficients and confinement radii determined for slow (66%) and fast (34%) MtrC were D 1 = 0.00162 ± 0.00011 µm 2 /s, R 1 = 51.7 ± 0.6 nm and D 2 = 0.0353 ± 0.0021 µm 2 /s, R 2 = 198 ± 2 nm, respectively. Those determined for slow (82%) and fast (18%) OmcA were D 1 = 0.00188 ± 0.00006 µm 2 /s, R 1 = 46.5 ± 0.2 nm and D 2 = 0.0482 ± 0.0016 µm 2 /s, R 2 = 242 ± 1 nm. Generally, both slow and fast MtrC and OmcA had slower mobility on OMEs than their counterparts on the cell surface ( Figs. 5 and 7 , and SI Appendix , Fig. S8 B ), as predicted by their overall diffusion ( Figs. 4 and 6 , and SI Appendix , Fig. S8 A ). This is likely due to differences in structure outlined previously. Here, the slow diffusing MtrC and OmcA were noticeably less confined, with over 2.5-fold increase in R 1 on OMEs compared to the cell surface. This increase in membrane domain size, from R 1 ∼ 18 to 50 nm, may suggest that membrane rearrangement into OMEs allows the highly confined fraction of cytochromes to explore a larger area, their diffusion now being limited by the size of a vesicle/OME itself, ∼100 nm in diameter. Fig. 7. Diffusion analyses for MtrC (blue) and OmcA (orange) on outer membrane extensions (OMEs), using a 2-component model of diffusing behavior. ( A and B , Left ): MtrC. ( C and D , Right ): OmcA. On OMEs, MtrC and OmcA diffusion can be described by two behaviors: ( A,C ) a slower, more confined majority and ( B,D ) a faster, less confined minority. Percentages indicate the respective fractions belonging to each component as determined by probability distribution of square displacement (PDSD) analysis, as described in ( 43 , 45 ). Ensemble mean squared displacement (MSD) curves were plotted as mean displacement squared r 2 as a function of time lag Δ t . Fitting these curves with a confined diffusion model ( SI Appendix , Eq. 2 ) yields diffusion coefficients D and confinement radii R , as labeled on each plot. Error bars show ± r 2 N , where N is the number of independent data points (i.e., displacements) analyzed for each component for a given Δ t . These curves represent 1,140 QD-labeled MtrC trajectories from 5 OMEs and 5,371 QD-labeled OmcA trajectories from 22 OMEs. Altogether, MtrC and OmcA appear to display relatively similar diffusive behavior, whether on the cell surface ( Figs. 4 and 5 ) or on membrane extensions ( Figs. 6 and 7 ), which is not surprising, since they are structurally and functionally homologous ( 50 ). The slightly faster diffusion of MtrC on the cell surface compared to OmcA (+50%, P = 0.03) ( Fig. 4 and SI Appendix , Fig. S8 A ) may be partially attributed to a difference in protein interactions ( 25 ), as previous works using chemical cross-linkers revealed that OmcA can interact with more proteins than MtrC ( 51 , 52 ). Simulations Combine Electron Hopping and Cytochrome Dynamics to Reveal Long-Distance Electron Transport along Membrane Surfaces. To understand the magnitude of long-distance electron conduction that can arise from the interplay of electron hopping and cytochrome motion along membranes, we performed kinetic Monte Carlo simulations following an approach previously described by Blauch et al. ( 20 ) to analyze redox polymers. The simulation approach ( SI Appendix , SI Materials and Methods ) randomly incorporates electron hopping and diffusion of the cytochromes on two-dimensional lattices with dimensions chosen to represent either the cylindrical surface of a whole cell or membrane extension. The key input parameters to each simulation are the time constant of electron hopping ( t e ), the time constant of physical motion ( t p ), and the fractional loading of cytochromes on the lattice ( X, ratio of cytochrome density to maximum full packed density). The simulation output is the overall electron transport rate along the membrane surface. The ratio t e /t p plays a critical role in determining the overall electron transport behavior in the collision-exchange mechanism ( 16 , 20 ). When physical motion is faster than electron hopping ( t e /t p >1, illustrated in Movie S4 ), redox molecules redistribute on the lattice rapidly between successive electron hops, and the overall transport behavior can be well approximated with a mean-field model ( 16 , 20 ). We previously applied this mean-field approach to assess electron transport along membrane extensions in this scenario ( 16 ). However, when physical motion is slower than electron hopping ( t e /t p <1, illustrated in Movie S5 ), electron transport is in the percolation regime, where fast conduction requires high enough fractional loading to open up a conduction channel from an interconnected network of cytochromes spanning the entire lattice. In our system, t e (the electron residence time in the decaheme cytochromes) can be estimated from previous measurements and molecular simulations to be in the 10 −5 to 10 −6 s range ( 13 , 53 – 55 ). To find t p , we use D phys = 10 −2 to 10 −1 µm 2 /s, based on our in vivo diffusion coefficients ( Figs. 4 and 6 ); the latter value is particularly observed in fast diffusing MtrC and OmcA on cells ( Fig. 5 B and D ), and is also supported by ex vivo measurements of the MtrCAB transmembrane conduit on supported lipid bilayers, measured via fluorescence recovery after photobleaching to be approximately D = 10 −1 µm 2 /s ( 56 ). Thus, t p = 10 −3 to 10 −4 s ( SI Appendix , Eq. 4 ). Since for our system t e /t p is generally <1, the simplified mean-field approach previously applied ( 16 ) is no longer justified, and calculating the overall electron transport requires a stochastic simulation to account for the diffusion and electron hopping events of all redox carriers. We report the simulation results as electron transport rate along the surface of a whole cell or membrane extension, as a function of cytochrome fractional loading ( Fig. 8 ). Each curve depicts the simulation results for a particular combination of electron hopping constant and diffusion coefficient of cytochromes at the lower and upper limits of the realistic range described above ( t e = 10 −5 to 10 −6 s and D phys = 10 −2 to 10 −1 µm 2 /s). For both simulation geometries and all combinations of hopping/diffusion coefficients, the electron transport rates exhibit a strong dependence, increasing by 3 to 4 orders of magnitude as a function of cytochrome fractional loading, as expected for transport in the percolation regime ( 20 ). At higher fractional loading (e.g., X > 0.7), the choice of diffusion coefficient does not impact the overall electron transport rate; in this limit, there is less room for physical diffusion and conduction is largely controlled by the electron hopping rate. Conversely, at lower fractional loading (e.g., X < 0.3), the electron transport rate is less sensitive to the electron hopping rate; in this limit, direct electron hopping events are less frequent in a landscape with sparsely distributed cytochromes, and conduction is controlled by the physical diffusion of cytochromes. It is interesting to consider these simulation results in light of previous experimental estimates of cytochrome concentrations in S. oneidensis . Ross et al. ( 15 ) estimated a total per cell MtrC and OmcA concentration of 100,000 proteins/cell, equivalent to a surface density of up to 30,000 proteins/μm 2 for typical cell dimensions (e.g., 2 μm length and 0.5 μm diameter). This surface density, which is likely an upper limit since it assumes full localization of cytochrome to the outer membrane, translates to the upper range of fractional loading ( X > 0.5) ( SI Appendix , Eqs. 7 and 8 ). In this range of X = 0.5 to 1, our simulations ( Fig. 8 ) reveal significant electron transport rates, in the 10 4 to 10 5 s −1 range for whole cell and membrane extension surfaces, depending on the exact choice of electron hopping constant ( t e ). We note that while these simulations account for the diffusion of the outer membrane electron transport proteins, other redox molecules may also contribute, leading to higher electron transport along membrane surfaces. For example, outer membrane cytochromes in S. oneidensis have flavin-binding sites ( 57 , 58 ) which may allow flavins to act as electron carriers between neighboring cytochromes. Similarly, the periplasm contains soluble as well as outer membrane-associated cytochromes ( 4 ) which may also exhibit the proposed collision-exchange mechanism. These possible contributions to conduction may be examined in future studies that extend our 2D simulation framework to 3D, to account for the diffusion of periplasmic cytochromes and the docking/undocking of flavin electron carriers on outer membrane cytochromes. Fig. 8. Simulation results of overall electron transport (ET) along the surface of whole cells or membrane extensions, based on experimentally measured diffusion coefficients. ET rates on the Y-axis are plotted on a log scale as a function of the fractional loading of redox carriers ( X ) on ( Left ) the surface of a whole cell (2 µm long and 0.5 µm in diameter) or ( Right ) the surface of an outer membrane extension (1 µm long and 100 nm in diameter). These results come from simulations using either t e = 10 −5 s (filled shapes) or 10 −6 s (unfilled shapes) for a range of experimentally derived diffusion coefficients D phys = 10 −1 µm 2 /s (black squares) or 10 −2 µm 2 /s (red circles). To understand whether the simulated electron transport rates are consistent with experiments, we compare our results to existing measurements of the apparent electron diffusion coefficient ( D ap ) in electroactive biofilms and recent estimates of the redox conductivity (σ) in S. oneidensis biofilms. Using Fick’s law of diffusion, our calculated electron transport rate and the concentration gradient of reduced cytochromes along the cylindrical cell surface can be used to obtain D ap ( SI Appendix , SI Materials and Methods ). Taking an electron transport rate of 10 4 s −1 and a cytochrome concentration resulting from a representative fractional loading X = 0.5, this procedure results in D ap ∼1 µm 2 /s, which is on the lower end of D ap reported for electroactive bacterial biofilms ( 22 ). More recently, estimates of the redox conductivity of S. oneidensis have become available from electrochemical gating measurements of light patterned biofilms bridging interdigitated electrodes ( 59 ). From the measured conduction currents (which did not account for flavin contributions) and using the full biofilm volume to define the conduction path (rather than only the cellular membrane surface), a biofilm conductivity (σ) of several nS/cm was estimated for S. oneidensis . Using the Nernst-Einstein relation ( SI Appendix , SI Materials and Methods ) to relate the apparent diffusion coefficient and conductivity ( 20 ), our calculated D ap of ∼1 µm 2 /s translates to σ ∼ 7 nS/cm, in remarkable agreement with the electrochemical gating measurements ( 59 ). These comparisons suggest that the simulated combination of electron hopping and cytochrome diffusion can explain many features of the observed redox conductivity of bacterial biofilms, at least in the case of S. oneidensis . Accounting for the contribution of additional factors to biofilm conductivity may require measurements in specific contexts (e.g., with controlled flavin concentrations) or using mutants deficient in periplasmic cytochromes."
} | 8,823 |
39407628 | PMC11478207 | pmc | 2,238 | {
"abstract": "This study examines a new approach to hybrid neuromorphic devices by studying the impact of omeprazole–proteinoid complexes on Izhikevich neuron models. We investigate the influence of these metabolic structures on five specific patterns of neuronal firing: accommodation, chattering, triggered spiking, phasic spiking, and tonic spiking. By combining omeprazole, a proton pump inhibitor, with proteinoids, we create a unique substrate that interfaces with neuromorphic models. The Izhikevich neuron model is used because it is computationally efficient and can accurately simulate the various behaviours of cortical neurons. The results of our simulations show that omeprazole–proteinoid complexes have the ability to affect neuronal dynamics in different ways. This suggests that they could be used as adjustable components in bio-inspired computer systems. We noticed a notable alteration in the frequency of spikes, patterns of bursts, and rates of adaptation, especially in chattering and triggered spiking behaviours. The findings indicate that omeprazole–proteinoid complexes have the potential to serve as adaptable elements in neuromorphic systems, presenting novel opportunities for information processing and computation that have origins in neurobiological principles. This study makes a valuable contribution to the expanding field of biochemical neuromorphic devices and establishes a basis for the development of hybrid bio-synthetic computational systems.",
"conclusion": "5. Conclusions This study has shown the complex and mode-specific signal processing capacities of omeprazole–proteinoid complexes in different spiking regimes. The results of our study demonstrate that these molecular assemblies possess exceptional flexibility in their response to various input patterns, such as accommodation, chattering, induced, phasic, and tonic spiking modes. The main findings include a notable decrease in signal strength, a non-linear shift in form, and time-dependent patterns that are specific to each mode, with certain modes exhibiting interesting predictive tendencies. The distinctive characteristics of these omeprazole–proteinoid systems indicate possible uses in molecular computing, bio-inspired signal processing, and intelligent drug delivery systems. The reported ability to process several modes of information and the strong ability to normalise signals could lead to new methods in processing information at the nanoscale and in developing sensor systems at the molecular level. Future study should prioritise investigating the fundamental foundations of these behaviours using molecular dynamics simulations and examining responses that are reliant on frequency. Furthermore, exploring the ways in which these features can be adjusted by chemical alterations could result in customised molecular computer components. Overall, this study not only enhances our understanding of molecular-level information processing but also connects the fields of pharmacology and computational neuroscience, creating opportunities for interdisciplinary research and technological advancements in the areas of bio-inspired computing and drug delivery systems.",
"introduction": "1. Introduction Unconventional computing is a field that investigates different ways of processing information and performing computations, going beyond the use of classic silicon-based technologies [ 1 ]. Bio-inspired computing systems have attracted considerable attention in this field because of their promising potential for the energy economy, versatility, and parallel processing capabilities [ 2 ]. Recent progress in the field has resulted in the examination of several biological and chemical materials for use in computation. These include DNA-based computing [ 3 ], reaction–diffusion systems [ 4 ], and neuromorphic computing [ 5 ]. The latter, which draws inspiration from the form and function of biological neural networks, has demonstrated significant potential in tasks such as pattern recognition and adaptive learning [ 6 ]. Our research specifically examines the relationship between omeprazole–proteinoid complexes and Izhikevich neuron models. Omeprazole, primarily recognised as a proton pump inhibitor (PPI) for reducing gastric acid secretion in various gastrointestinal disorders [ 7 ], has recently attracted attention for its potential effects on neuronal function. Numerous studies indicate that PPIs, such as omeprazole, might have neuroprotective properties and could affect neuronal activity in addition to their primary gastric functions [ 8 ]. Research indicates that omeprazole is capable of crossing the blood–brain barrier and interacting with multiple ion channels and receptors within the central nervous system [ 9 ]. Additionally, PPIs have been shown to influence intracellular pH and membrane potential across different cell types, including neurons [ 10 ]. The findings have prompted investigations into the potential applications of omeprazole in neurological conditions and its effects on neuronal-like systems [ 11 ]. Proteinoid microspheres, as simplified models for protocells, demonstrate electrical potential changes akin to neuronal spiking [ 12 ]. The application of omeprazole enables an investigation into the impact of a clinically relevant compound, recognised for its effects on proton pumps, on these primitive, neuron-like behaviours. This approach improves our understanding of the physiological effects of omeprazole and offers insights into the essential characteristics of protocellular systems and their reactions to pharmaceutical agents. The study of omeprazole’s impact on proteinoid microspheres holds significance for unconventional computing. Unconventional computing paradigms, including those using biological or chemical systems, aim to take advantage of the computational capabilities of unconventional substrates [ 13 ]. Proteinoid microspheres demonstrate neuron-like spiking behaviour, indicating their potential as foundational components for bio-inspired computing systems [ 14 ]. Investigating the modulation of the electrical properties of microspheres by omeprazole provides insights into controlling and programming unconventional computing elements [ 15 ]. This research could advance the development of innovative computational architectures that use the distinct characteristics of protocellular systems, possibly resulting in more efficient or specialised computing solutions for specific problem types [ 16 ]. Omeprazole is combined with proteinoids, which are thermal proteins capable of forming microspheres and have been extensively explored in the field of artificial cells [ 17 ]. The Izhikevich neuron model, known for its computational efficacy and capacity to replicate a diverse array of neuronal firing patterns [ 18 ], serves as our framework for exploring the computational characteristics of these biochemical complexes. We analyse five specific neuronal behaviours: accommodation, chattering, triggered spiking, phasic spiking, and tonic spiking. These behaviours indicate diverse ways in which biological neural networks perform computations [ 19 ]. Our objective is to discover new methods for information processing and computing by studying the effects of omeprazole–proteinoid complexes on neuronal dynamics. This technique connects the fields of pharmacology, proteinoid chemistry, and neuromorphic computing, potentially creating opportunities for the advancement of adaptive, bio-inspired computational systems [ 13 , 15 , 20 ]. Our research adds to the expanding field of neuromorphic substrates and could impact the development of future hybrid bio-synthetic computational architectures. Moreover, it offers valuable information about the possible neuromodulatory impacts of pharmacological drugs when paired with proteinoids, which could have significant implications for the fields of computing and neuropharmacology. To fully understand the spiking behaviour and signal-processing abilities of the omeprazole–proteinoid complex, it is essential to have a solid foundation of the molecular structures of the proteinoid (L-Glu:L-Asp:L-Phe) and omeprazole. Figure 1 depicts these structures and their possible interactions. The amino acid composition of the proteinoid offers a range of functional groups that can engage in hydrogen bonding and other non-covalent interactions with omeprazole. These interactions are highly likely to have a crucial impact on the voltage-sensitive conformational changes and charge redistribution pathways that are described in our mechanistic model. The precise configuration of atoms and chemical bonds in omeprazole, specifically its sulphoxide group and benzimidazole ring, could potentially impact the electrical characteristics of the proteinoid. This influence may arise from the modulation of local pH gradients or the modification of conductive pathways within the complex. The Izhikevich neuron model is described by a system of two differential equations: (1) d v d t = 0.04 v 2 + 5 v + 140 − u + I \n (2) d u d t = a ( b v − u ) \nwith the auxiliary after-spike resetting: (3) if v s . ≥ 30 mV , then v ← c u ← u + d \nHere, v represents the membrane potential of the neuron, u is a recovery variable, and I is the input current. The parameters a , b , c , and d are dimensionless parameters that can be adjusted to produce various types of neuronal behaviour: a : the time scale of the recovery variable u ; b : the sensitivity of the recovery variable u to the subthreshold fluctuations of the membrane potential v ; c : the after-spike reset value of the membrane potential v ; d : after-spike reset of the recovery variable u . In the Izhikevich model, the 30 mV threshold signifies the spike initiation threshold, founded in empirical findings regarding typical mammalian cortical neurons [ 18 ]. When v reaches or exceeds this threshold, it is considered that the neuron has generated an action potential. The model thereafter executes a swift reset of the membrane potential to a lower level ( c ) and an elevation of the recovery variable ( u is increased by d ), emulating the refractory time seen in biological neurons [ 19 ]. For v < 30 mV, the neuron’s dynamics are controlled by the continuous differential Equations ( 1 ) and ( 2 ), which characterise the subthreshold behaviour of the neuron. The subthreshold regime includes methods like synaptic input integration and subthreshold oscillations, which are essential for neural information processing [ 22 ]. This model’s adaptability enables the simulation of diverse neuronal firing patterns found in cortical neurons by the modification of parameters a , b , c , and d [ 18 , 19 ]. Figure 2 illustrates the conceptual framework of our unconventional computing approach, showing how omeprazole–proteinoid complexes interact with the Izhikevich neuron model to potentially modulate various neuronal behaviours. Proton pump inhibitors (PPIs) are a type of drug that decreases the production of acid in the gut by permanently blocking the hydrogen/potassium adenosine triphosphatase enzyme system in the cells of the stomach lining [ 10 ]. Omeprazole, the subject of this investigation, is among a number of proton pump inhibitors (PPIs) presently being used in clinical practice. Table 1 displays a comparison of omeprazole and other prevalent PPIs, emphasising their chemical formulae, half-lives, and pKa values. Although these medications have a similar way of working, they have slight variations in their pharmacokinetic and pharmacodynamic characteristics [ 23 , 24 , 25 , 26 ]. We selected omeprazole for this work due to its extensive use and well-established characteristics, which make it an excellent candidate for investigating the potential neuromodulatory effects in conjunction with proteinoid structures.",
"discussion": "4. Discussion The detailed examination of omeprazole–proteinoid complexes using several spiking modes demonstrates a complex and adaptable signal processing system. The results of our study indicate that these complexes have unique responses to various input patterns, indicating the possibility of processing many types of information at the molecular level. 4.1. Comparative Analysis of Spiking Modes We detected considerable signal attenuation and change in all spiking modes, including accommodation, chattering, induced, phasic, and tonic. Nevertheless, the extent and characteristics of this change differed significantly among different modes: Amplitude modulation: All modes showed a significant decrease in signal amplitude, with output ranges constantly falling within a range of ±4 mV, whereas input ranges often exceeded ±60 mV. This implies the presence of a strong buffering mechanism that could protect molecular fluctuations downstream from extreme fluctuations in voltage. As seen in Figure 5 d, Figure 6 d, Figure 7 d and Figure 8 d The red dashed line depicts the theoretical relationship that would exist if the two distributions were identical, whereas the blue curve shows the relationship that actually exists between the input and output quantiles. Due to the output signal’s narrower range of negative values than the input, the blue curve drops below the red line for input levels below roughly − 70 mV. This implies that there is a minimum voltage that the system may produce, or a \"floor\". Because the output signal has the ability to produce higher positive voltages than those found in the input, the blue curve rises above the red line for input quantities over roughly 70 mV. This indicates the system has some amplification or non-linear response for large positive inputs. The omeprazole-proteinoid system’s non-linear characteristics of the input signal transformation are revealed by these deviations from the red line, especially the asymmetric processing of large positive versus negative inputs. Temporal dynamics: The temporal delay between the input and output signals exhibited significant variation across different modes, ranging from − 1981 ms in the chattering mode to 1590 milliseconds in the induced mode. The negative lag found in accommodation ( − 306 ms), phasic ( − 359 ms), and tonic ( − 1231 ms) modes is particularly remarkable. This suggests the presence of anticipatory behaviour, which could have important consequences for information processing and response preparation in biological systems. Signal correlation: The correlation between the input and output signals varied from moderate (0.4503 in phasic mode) to strong (0.7937 in chattering mode). This suggests that the complexes effectively modify the input signal while retaining the different levels of the original signal properties. Distribution transformation: The Kolmogorov–Smirnov tests consistently revealed significant differences between the distributions of the input and output data in all modes. The KS statistics ranged from 0.9276 (tonic) to 0.9945 (phasic). This implies the use of non-linear processing techniques that have the potential to amplify specific signal characteristics while simultaneously reducing the prominence of others. 4.2. Implications for Molecular Computing The behaviours shown by omeprazole–proteinoid complexes when subjected to various spiking regimes have significant implications for molecular computing and bio-inspired signal processing: Multi-modal processing: The diverse reactions to various spiking patterns indicate that these complexes have the ability to function as versatile molecular processors, adjusting their behaviour according to input parameters. Non-linear transformation: The persistent non-linear alteration of input signals, as indicated by the results of the KS test and Q-Q plots, suggests that these complexes perform complex signal processing procedures that go beyond mere filtering or amplification. Anticipatory behaviour: The presence of negative time delays in several modes indicates the occurrence of predictive processing at the molecular level. These findings could have important consequences for the development of molecular systems that can anticipate events or for understanding the biological reactions that occur before an event. Robust signal normalisation: The consistent output range observed in all input modes indicates that these complexes have the potential to function as reliable signal normalisers, which could be valuable in molecular-scale sensor systems [ 36 ] or signal processing units [ 37 ]. 4.3. Potential Mechanisms and Future Directions The observed behaviours are most likely a result of complex interactions among the omeprazole molecules, the proteinoid structure, and the electrical fluctuations that were applied. Possible mechanisms encompass voltage-dependent alterations in the proteinoid structure, emergence, and disintegration of transient conductive pathways within the complex, accumulation and redistribution of charges with distinct time constants, and interactions between omeprazole’s inhibition of proton pumps and local pH gradients. Future research should prioritise conducting molecular dynamics simulations to uncover the underlying structural mechanisms of the observed behaviours. In addition, it should investigate the frequency-dependent responses of these complexes, explore potential applications in molecular-scale signal processing and computing, and examine how these properties can be adjusted or changed through chemical modifications. Our analysis concludes that omeprazole–proteinoid complexes possess diverse signal-processing capacities that vary depending on the mode. These findings not only improve our understanding of molecular-scale information processing but also create new opportunities for the advancement of bio-inspired computing systems and smart drug delivery mechanisms. The complex behaviours observed in various spiking modes are presumably the result of a combination of molecular-level mechanisms within the omeprazole–proteinoid complexes. Figure 10 depicts many suggested mechanisms that could potentially contribute to the observed signal-processing capabilities. These factors include changes in the proteinoid structure that are sensitive to voltage ( Figure 10 A), which could explain the different responses depending on the mode; the creation and breakdown of temporary pathways for conducting signals ( Figure 10 B), which may account for the non-linear transformation of the signal; processes of accumulating and redistributing charges ( Figure 10 C), which could explain the observed delays and anticipatory behaviours; and the interaction between omeprazole’s inhibition of proton pumps and local differences in pH ( Figure 10 D), which may contribute to the consistent normalisation of the signal across all modes. The interaction between these mechanisms could elucidate the diverse and flexible behaviour of the omeprazole–proteinoid system under different patterns of stimulation. Additional research into these processes at the molecular level will be essential for gaining a complete understanding and perhaps utilising these capabilities in molecular computing [ 38 ] and smart drug delivery systems [ 39 ]. The study of the omeprazole–proteinoid complex unveils a complex mechanism [ 40 ] for spike emergence, as depicted in Figure 11 . The scanning electron microscope (SEM) image ( Figure 11 a) depicts a complex network structure that serves as the foundation for the observed electrical behaviour. Our hypothesis suggests that the process of spike formation consists of a sequence of stages, starting with the attachment of omeprazole molecules to the proteinoid network ( Figure 11 a). The occurrence of this binding event can be mathematically represented by Equation [ 10 ]: (21) P + O ⇌ PO \nwhere P represents the proteinoid binding site, O represents omeprazole, and PO is the bound complex. Omeprazole binding modifies the local distribution of electric charge inside the complex. This alteration can be represented as a disturbance to the nearby electric field: (22) E = E 0 + Δ E ( PO ) \nwhere E 0 is the initial electric field and Δ E ( PO ) is the change induced by the omeprazole binding. The modified electric field stimulates the activation of ion channels [ 41 ] located near the binding site. The probability of an ion channel opening can be described by a Boltzmann distribution: (23) P open = 1 1 + e − z ( V − V 1 / 2 ) / k T \nwhere z is the gating charge, V is the membrane potential, V 1 / 2 is the half-activation voltage, k is the Boltzmann constant, and T is the temperature. The activation of these channels results in a fast movement of ions, which in turn generates a spike potential. The membrane potential during a spike can be represented using the Hodgkin–Huxley equations [ 32 ], which have been simplified in this context for the sake of simplicity.\n (24) C m d V d t = − ∑ I ion + I ext \nwhere C m is the membrane capacitance, ∑ I ion represents the sum of ionic currents, and I ext is any external current. The resulting spike potential over time is depicted in Figure 11 b, showing the characteristic rapid rise and fall of the membrane potential. The network structure of the omeprazole–proteinoid complex, as observed in the SEM image, plays a crucial role in facilitating the propagation of these spikes. The interconnected nature of the complex allows for the spread of the electrical signal, which can be modelled as a reaction–diffusion process [ 42 ]: (25) ∂ V ∂ t = D ∇ 2 V + f ( V ) \nwhere D is the diffusion coefficient and f ( V ) represents the non-linear reaction terms that account for the spike generation and propagation dynamics. This proposed process establishes a connection between the structural characteristics exhibited in the SEM image and the functional electrical properties of the omeprazole–proteinoid mixture. The observed spiking behaviour is a result of the interaction between omeprazole binding, ion channel kinetics, and the network topology of the complex. This suggests a new method for bio-inspired signal processing [ 43 ] and possible uses in neuromorphic computing [ 44 ]."
} | 5,529 |
29785358 | null | s2 | 2,239 | {
"abstract": "While microalgae are a promising feedstock for production of fuels and other chemicals, a challenge for the algal bioproducts industry is obtaining consistent, robust algae growth. Algal cultures include complex bacterial communities and can be difficult to manage because specific bacteria can promote or reduce algae growth. To overcome bacterial contamination, algae growers may use closed photobioreactors designed to reduce the number of contaminant organisms. Even with closed systems, bacteria are known to enter and cohabitate, but little is known about these communities. Therefore, the richness, structure, and composition of bacterial communities were characterized in closed photobioreactor cultivations of "
} | 179 |
29785358 | null | s2 | 2,240 | {
"abstract": "While microalgae are a promising feedstock for production of fuels and other chemicals, a challenge for the algal bioproducts industry is obtaining consistent, robust algae growth. Algal cultures include complex bacterial communities and can be difficult to manage because specific bacteria can promote or reduce algae growth. To overcome bacterial contamination, algae growers may use closed photobioreactors designed to reduce the number of contaminant organisms. Even with closed systems, bacteria are known to enter and cohabitate, but little is known about these communities. Therefore, the richness, structure, and composition of bacterial communities were characterized in closed photobioreactor cultivations of "
} | 179 |
23555206 | PMC3605063 | pmc | 2,243 | {
"abstract": "Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns ( Paratya australiensis ). We show that these exhibit a stereotypical ‘phase transition’, whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have ‘memory’ of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture the observed locality of interactions. Traditional self-propelled particle models fail to capture the fine scale dynamics of the system. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics, while maintaining a biologically plausible perceptual range. We conclude that prawns’ movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.",
"introduction": "Introduction The most striking features of the collective motion of animal groups are the large-scale patterns produced by flocks, schools and other groups. These patterns can extend over scales that exceed the interaction ranges of the individuals within the group [1] – [4] . For most flocking animals, the rules dictating the interactions between individuals, which ultimately generate the behaviour of the whole group, are still not known in any detail. Many ‘self-propelled’ particle models have been proposed for collective motion, each based on a relatively simple set of interaction rules between individuals moving in one, two or three dimensions [2] , [5] – [8] . Typically these models implement a simple form of behavioural convergence, such as aligning the focal individual's velocity in the average direction of its neighbours or attraction towards the position of those neighbours. Generally such rules are explicitly kept as simple as possible while remaining realistic, with the aim of explaining as much as possible of collective motion from the simplest constituent parts. Each of the models in the literature is capable of reproducing key aspects of the large-scale behaviour of one or more biological systems of interest. Together these models help explain what aspects of inter-individual interactions are most important for creating emergent patterns of coherent group motion. With this proliferation of putative interaction rules has come the recognition that some patterns of group behaviour are common to many models, and that different models can have large areas of overlapping behaviour depending on the choice of parameters [4] . Common patterns of collective behaviour are also observed empirically across a diverse range of animal and biological systems. For example, a form of phase transition from disorder to order has been described in species as diverse as fish [9] , ants [10] , locusts [11] , down to cells [12] and bacteria [13] . In all these systems, as density of these species is increased there is a sudden transition from random disordered motion to ordered motion with the group collectively moving in the same direction. These studies indicate that a great deal can be understood about collective behaviour without reduction to the precise rules of interaction. In many contexts however the rules of interaction are of more interest than the group behaviour they lead to. For example, when comparing the evolution of social behavior across different species, it is important to know if the same rules evolved independently in multiple instances, or whether each species evolved a different solution to the problem of behaving coherently as a group [1] . Recently researchers in the field have become interested in using tracking data from real systems on the fine scale to infer what precise rules of motion each individual uses and how they interact with the other individuals in the group [14] – [19] . This is an important trend in the field of collective motion as we move from a theoretical basis, centred around simulation studies, to a more data-driven approach. The most frequent approach to inferring these rules has been to find correlations between important measurable aspects of the behaviour of a focal individual and its neighbours. For example, Ballerini et al. \n [14] looked at how a focal individual's neighbours were distributed in space relative to the position of the focal individual itself in a group of starlings. Significant anisotropy in the position of the nearest neighbour, averaged over all individuals, was regarded as evidence for an interaction between each bird and that neighbour. More recently Katz et al. \n [18] and Herbert-Read et al. \n [19] investigated how the change in velocity of each individual in groups of fish was correlated to the positions and velocities of the neighbouring fish surrounding the focal individual. This provides evidence not only for the existence of an interaction between neighbours but also estimates the rules that determine that interaction. In these studies the rules of interaction are presented non-parametrically and cannot be immediately translated into a specific self-propelled particle model. Nor are these models validated in terms of the global schooling patterns produced by the fish. An alternative model-based approach that does fit self-propelled particle and similar models to data is proposed by Eriksson et al. \n [16] and Mann [17] . Under this approach, the recorded fine-scale movements of individuals are used to fit the parameters of, and select between, these models in terms of relative likelihood or quality-of-fit. This approach has the advantage of providing a parametric ‘best-fit’ model and can provide a quantitative estimate the relative probability of alternative hypotheses regarding interactions. What all previous empirical studies have lacked is a simultaneous verification of a model at both the individual and collective level. Either fine scale individual-level behaviour is observed without explicit fitting of a model [18] , [19] or global properties, such as direction switches [11] , [20] , speed distributions [21] , [22] or group decision outcome [23] have been compared between model and data. Verification at multiple scales is the necessary next step now that inference based on fine-scale data is becoming the norm. Just as simulations of large-scale phenomena can appear consistent with observations of group behaviour without closely matching the local rules of interaction, so can fine-scale inferred rules be inconsistent with large-scale phenomena if these rules of inferred from too limited a set of possible models or from correlations between the wrong behavioural measurements. The closest that any study so far has come to finding consistency between scales has been Lukeman et al. \n [15] . In their study the local spatial distribution of neighbouring individuals in a group of scoter ducks was used to propose parametric rules of interaction, with some parameters measured from the fine-scale observables, but with others left free to be fitted using large-scale data. We suggest that if group behaviour emerges from individual interactions, then the form of these interactions should be inferable solely from fine-scale data without additional fitting at the large-scale. An inability to replicate the group behaviour using a selected model demonstrates that the model space has been insufficiently explored. When faced with alternative hypothesised interaction rules, model-based parametric inference provides the best means of quantitatively selecting between them. In this paper we study the collective motion of small groups of the glass prawn, Paratya australiensis . Paratya australiensis is an atyid prawn which is widepsread throughout Australia [24] . Although typically found in large feeding aggregations, it does not appear to form social aggregations and has not been reported to exhibit collective behaviour patterns in the wild. We conduct a standard ‘phase transition’ experiment [9] , [11] , [12] , studying how density affects collective alignment of the prawns. We complement this approach by using Bayesian inference to perform model selection based on empirical data at a detailed individual level. We select between models by calculating the probability of the fine scale motions using a Bayesian framework specifically to allow fair comparison between competing models of varying complexity. Comparison of the marginal likelihood, the probability of the data conditioned on the model, integrating over the uncertain parameter values, is a well developed and robust means of model selection that forms the core of the Bayesian methodology [25] – [28] and which has been applied to compare models in the biological sciences, particularly neuroscience [29] . Bayesian methods are also well established in animal behaviour through consideration of optimal decision making in the presence of conflicting information, both environmental [30] and social [31] , [32] . In adopting this approach, we reject the dichotomy of model inference based on either fine scale behaviour of the individuals or the motion of the group. Instead we use reproduction of the large scale dynamics through simulation as a necessary but not sufficient condition of the correct model.",
"discussion": "Discussion A number of physical [36] – [38] , technological [39] and biological systems, including animals [9] – [11] , [40] , tissue cells [12] , microorganisms [13] , [41] are known to increase their collective order with density. Glass prawns are one additional example of such a system, which is particularly interesting since they are not known as gregarious or social species. By confining the prawns to a ring we facilitated their interactions and in doing so generated collective motion. This adds further support to the idea that collective motion is a universal phenomenon independent of the underlying interaction rules [4] , [11] , [42] . While we do not expect that prawns often find themselves confined in rings in a natural setting, they and other non-social animals do aggregate in response to environmental features such as food and shelter. Such environmental aggregations can, above a certain density, result in an apparently ‘social’ collective motion. The true value of this study, however, is found not in the addition of one more species to this growing list, but in demonstrating a rigorous methodology for selecting an optimal and multi-scale consistent model for the interactions between individuals in a group. We have used a combination of techniques to identify the optimal model for our experiments: Bayesian model selection, validation against global properties and consistency with biological reasoning. We applied Bayesian model selection to identify the model that best predicts the fine-scale interactions between prawns. This approach allows us to perform model selection in the presence of many competing hypotheses of varying complexity, while avoiding over fitting [17] . This indicated the selection of a non-Markovian model with a persistent ‘memory’ effect. We find that interactions are governed by a perceptual range which is symmetric about the focal individual which is somewhat greater than the average body length of the prawns (approximately radians). Reproduction of the large-scale dynamics is frequently used to validate mathematical models of biological systems, but presents only a necessary and not a sufficient condition for model validation. Indeed, all of the models we have assessed in this work can, with the appropriate parameters, generate aligned motion consistent with experiment. The fact that our mean-field model reproduces global dynamics, but fails at a fine-scale level is not particularly surprising. Mean-field models are not designed to reproduce spatially local dynamics [1] . More illuminating, however, is the failure of Markovian spatial models to reproduce the fine-scale dynamics when the locality of interactions between individuals is imposed. Models S1, S2, S3, S4 are variants of the standard one dimensional Vicsek self-propelled particle model [43] , which has previously been validated against the global alignment patterns of marching locusts [11] . For the prawns these models perform poorly on both capturing the fine scale dynamics of interactions and in reproducing the large scale alignment patterns seen in the data. This inconsistency allowed us to reject standard self-propelled particle models as a good model of the data. To identify a better model we first visually inspected the interactions between the prawns. These observations suggested a ‘memory effect’, whereby a prawn would remain influenced by individuals beyond the moment of interaction. The resulting models are able reproduce the fine scale and large scale dynamics of the prawns, while also maintaining the biologically-intuitive locality of interactions between individuals. More generally, we would expect other examples of animal motion to be non-Markovian, with individuals taking time to react to others, to complete their own actions and also potentially reacting through memory of past situations. In this context, it is important to consider the limitations of recent studies identifying rules of interaction of fish [18] , [19] . These studies concentrated on quantifying local interactions, but do not try to reproduce global properties. It may be that non-Markovian and other effects are needed to produce these properties. In what circumstances can we expect non-Markovian effects to play an important role in collective behaviour? Inference based on a Markovian model must account for behavioural changes of a focal individual in terms of their current environment. As such the crucial factor is how much the local environment changes between when the animal receives information and when it responds. Large changes in the local environment can be caused by long response times or by rapid movements of other animals relative to the focal individual. Where behavioural changes are strongly discontinuous, such as the binary one-dimensional movement in this study, non-Markovian effects may become especially important. This is because the focal individual may have to execute a number of small changes (such as stopping and turning through a several small angles) in order to register as having changed its direction of motion. Over the course of making many adjustments the environment can change dramatically from the moment that the change was initiated. We have compared the models on the large scale by evaluating the quality-of-fit between the distribution of large scale outcomes predicted by model simulations with that seen in experiments. The model we select from the fine scale analysis is also evaluated as the best on this large scale analysis, and produces simulation results that are qualitatively consistent with experiment (see Figure 6 ). Because the same model is selected from both analyses we have not been forced to weight the relative importance of each. In future it may be necessary to decide on an appropriate weighting of these different criteria where they disagree on the optimal model. The research presented here provides a first step towards the use of multi-scale inference in the study of collective animal behaviour and in other multi-level complex systems."
} | 4,099 |
36798193 | PMC9934648 | pmc | 2,244 | {
"abstract": "Many bacteria use quorum sensing to control changes in lifestyle. The process is regulated by microbially derived “autoinducer” signalling molecules, that accumulate in the local environment. Individual cells sense autoinducer abundance, to infer population density, and alter their behaviour accordingly. In Vibrio cholerae , quorum sensing signals are transduced by phosphorelay to the transcription factor LuxO. Unphosphorylated LuxO permits expression of HapR, which alters global gene expression patterns. In this work, we have mapped the genome-wide distribution of LuxO and HapR in V. cholerae . Whilst LuxO has a small regulon, HapR targets 32 loci. Many HapR targets coincide with sites for the cAMP receptor protein (CRP) that regulates the transcriptional response to carbon starvation. This overlap, also evident in other Vibrio species, results from similarities in the DNA sequence bound by each factor. At shared sites, HapR and CRP simultaneously contact the double helix and binding is stabilised by direct interaction of the two factors. Importantly, this involves a CRP surface that usually contacts RNA polymerase to stimulate transcription. As a result, HapR can block transcription activation by CRP. Thus, by interacting at shared sites, HapR and CRP integrate information from quorum sensing and cAMP signalling to control gene expression. This likely allows V. cholerae to regulate subsets of genes during the transition between aquatic environments and the human host.",
"introduction": "INTRODUCTION Vibrio cholerae is a Gram-negative bacterium responsible for the human disease cholera 1 . Estimates suggest 3 million annual infections, of which 100 thousand are fatal 2 . Most disease instances are attributed to the El Tor V. cholerae biotype, which is responsible for the ongoing 7 th cholera pandemic 3 . Globally, over 1 billion people inhabit areas of endemicity and future climatic change is likely to exacerbate the risk of illness 2 , 4 . The success of V. cholerae as a pathogen is underpinned by an ability to colonise both aquatic ecosystems and the human intestinal tract 1 . In waterways, V. cholerae prospers by forming biofilms on arthropod exoskeletons. Degradation of these chitinous surfaces ultimately liberates N -acetylglucosamine (GlcNAc) for metabolism by the microbe 5 . Upon ingestion by a human host, V. cholerae express genetic determinants for acid tolerance, intestinal colonisation, and virulence. Diverse transcription factors regulate the transition and respond to signals including bile 6 , temperature 7 , nucleotide second messengers 8 , 9 , and chitin availability 5 . Understanding these regulatory networks is important to determine how V. cholerae can switch between environments to cause disease outbreaks 3 , 10 , 11 . Quorum sensing is key for the transition of V. cholerae between ecological niches 12 . Briefly, V. cholerae produce at least 3 autoinducer (AI) signalling molecules: cholera AI-1 (CAI-1), AI-2, and 3,5-dimethylpyrazin-2-ol (DPO) 13 . In the environment, these compounds are detected by receptors in neighbouring cells and indicate population density. Importantly, whilst AI-2 and DPO are produced by multiple bacterial species, CAI-1 is only made by other members of the Vibrio genus 14 . Thus, V. cholerae can determine the crude composition of bacterial populations. In the absence of their cognate AIs, when population density is low, the receptors for CAI-I and AI-2 target the transcription factor LuxO for phosphorylation via a phosphorelay system 13 , 15 , 16 . When phosphorylated, LuxO upregulates the production of four small quorum regulatory RNAs (Qrrs) 17 . In turn, the Qrrs control expression of two global transcription factors: AphA and HapR 17 – 19 . Importantly, whilst AphA production is activated by Qrrs, synthesis of HapR is repressed. Hence, AphA and HapR control gene expression at low and high cell density respectively 13 , 19 . A simplified outline of the LuxO dependent regulatory pathway for HapR is illustrated in Figure 1a . Identified as a regulator of hapA , required for V. cholerae migration through intestinal mucosa, HapR is a TetR-family member that binds DNA as a homodimer via a N-terminal helix-turn-helix motif 20 , 21 . Many clinical isolates of pandemic V. cholerae have lost the ability to properly express HapR and this may indicate adaptation to a more pathogenic lifestyle 3 , 10 , 22 . In V. cholerae , HapR regulates the expression of ~100 genes to promote ‘group behaviours’ including natural competence, repression of virulence genes, and escape from the host intestinal mucosa 23 . In other Vibrio spp., equivalent regulons are larger. For example, LuxR in Vibrio harveyi regulates over 600 genes 24 . Expression of HapR can be influenced by other factors. In particular, cAMP receptor protein (CRP), a regulator that controls metabolism of alternative carbon sources, including chitin, upregulates HapR 25 . In this study, we used chromatin immunoprecipitation and DNA sequencing (ChIP-seq) to identify direct DNA binding targets of HapR and its upstream regulator, LuxO. We show that the degenerate DNA consensus bound by HapR frequently overlaps targets for CRP. At such sites, HapR and CRP co-operatively bind offset faces of the double helix. Strikingly, this occludes a key CRP surface required to activate transcription. This simple mechanism allows V. cholerae species to integrate quorum sensing, and cAMP signalling, in the control of gene expression.",
"discussion": "DISCUSSION Previously, two studies have mapped DNA binding by HapR homologs in Vibrio species. For V. harveyi , van Kessel and co-workers used ChIP-seq to identify 105 LuxR binding targets 30 . At 77 of these sites, LuxR repressed transcription. Using ChIP-seq and global DNAse I footprinting, Zhang et al . found 76 LuxR bound regions in Vibrio alginolyticus 31 . Regulatory effects were evident for 37 targeted genes, with 22 cases of LuxR mediated repression. In the present study, we identified 32 HapR bound sections of the V. cholerae genome. Consistent with prior work, repression of target genes was the most common regulatory outcome. Furthermore, the DNA binding consensus derived here for HapR is almost identical to motifs for LuxR binding in V. harveyi and V. alginolyticus . Contrastingly, Tsou and colleagues used bioinformatic tools to predict HapR binding in V. cholerae 28 . Two different HapR binding motifs were proposed. Both partially match the HapR target sequence proposed here. Most likely, the analysis of Tsou et al . was hampered by a paucity of targets from which a full consensus could be derived. We note that our list of 32 HapR targets does not include all known targets. However, on inspection, whilst insufficient to pass our stringent selection criteria, weaker signals for HapR are evident at many such locations ( Figure 1-figure supplement 2 and Supplementary file 1 ). In particular, we note evidence for binding of HapR upstream of hapA , which has previously been only inferred ( Figure 1-figure supplement 2b ). We note that previous relied on computational predictions and in vitro DNA binding assays to identify potential HapR targets. That not all such targets are bound in vivo , in the single growth condition tested here, is to be expected. Recognition of shared DNA targets provides a simple mechanism for integration of quorum sensing signals, relayed by HapR, and cAMP fluctuations, communicated by CRP. In the example presented here, HapR acts to prevent transcription activation by co-binding the same DNA target with CRP ( Figure 4 ). Hence, at P murQP , the function of CRP switches from that of an activator to a co-repressor with HapR ( Figure 6b ). This regulatory strategy is a logical consequence of V. cholerae forming biofilms on chitinous surfaces. At low cell density, rapidly dividing cells must continually remodel their cell wall. In these conditions, HapR is not expressed. Thus, MurQ and MurP are produced and can convert cell wall derived MurNAc to GlcNAc-6P. Conversely, in high cell density scenarios, usually involving adherence to chitin, cells divide infrequently, and remodelling of the cell wall is reduced. In addition, GlcNAc-6P can be derived readily from chitin oligosaccharides. Hence, cells locked in the high cell density state are defective for growth when supplied with MurNAc as the sole carbon source ( Figure 6a ). We suggest that HapR and CRP are likely to coordinate the expression of other metabolic enzymes in a similar way. Interestingly, AphA, another quorum sensing responsive regulator, also acts alongside CRP at many V. cholerae promoters 40 . Indeed, AphA and CRP binding sites can overlap but this results in competition between the factors 40 . Together with results presented here, these observations highlight close integration of quorum sensing with gene control by cAMP in V. cholerae ."
} | 2,235 |
31252652 | PMC6789541 | pmc | 2,247 | {
"abstract": "In recent years, metabolic engineering of microorganisms has attained much research interest to produce biofuels and industrially pertinent chemicals. Owing to the relatively fast growth rate, genetic malleability, and carbon neutral production process, cyanobacteria has been recognized as a specialized microorganism with a significant biotechnological perspective. Metabolically engineering cyanobacterial strains have shown great potential for the photosynthetic production of an array of valuable native or non-native chemicals and metabolites with profound agricultural and pharmaceutical significance using CO 2 as a building block. In recent years, substantial improvements in developing and introducing novel and efficient genetic tools such as genome-scale modeling, high throughput omics analyses, synthetic/system biology tools, metabolic flux analysis and clustered regularly interspaced short palindromic repeats (CRISPR)-associated nuclease (CRISPR/cas) systems have been made for engineering cyanobacterial strains. Use of these tools and technologies has led to a greater understanding of the host metabolism, as well as endogenous and heterologous carbon regulation mechanisms which consequently results in the expansion of maximum productive ability and biochemical diversity. This review summarizes recent advances in engineering cyanobacteria to produce biofuel and industrially relevant fine chemicals of high interest. Moreover, the development and applications of cutting-edge toolboxes such as the CRISPR-cas9 system, synthetic biology, high-throughput “omics”, and metabolic flux analysis to engineer cyanobacteria for large-scale cultivation are also discussed.",
"conclusion": "5. Concluding Remarks and Future Perspectives Recent developments of metabolic engineering and synthetic biology based sophisticated and state-of-the-art tools, in the last two decades, have presented noteworthy progress in making cyanobacteria as a promising photosynthetic platform for the manufacturing of biofuels, and many commodity chemicals by fine-tuning cyanobacterial metabolism. Despite numerous successful proof-of-concept reports, however, limited work is currently being carried out to scale-up this technology. Since the commercial realization lies in the titer, productivity, and steadiness, the attributes that can only be achieved by genetically engineered cyanobacterial strains at the industrial level. This scenario quests the experimental determination of the theoretical production rates. Many concerted research efforts are required to direct or redirect a significant percentage of the fixed carbon towards the target products. In addition to the upgrade of low-cost bioreactors or open ponds infrastructure, the resulting products harvesting technology also needs to be established. Notwithstanding many challenges to the commercial feasibility of cyanobacterial chassis, the distinct perspective of these photosynthetic microorganisms is attracting continuous metabolic engineer’s interest as a green and sustainable production system.",
"introduction": "1. Introduction Increasing apprehensions over energy and environmental issues are the key drivers for the development of renewable bio-based chemical products and fuels. Accelerating understanding of genomics and genetic manipulations enabled rapid improvement in the construction of microbial cell factories to produce an array of value-added bio-chemicals using diverse, sustainable bio-resources ( Figure 1 ) [ 1 , 2 , 3 ]. Among the numerous microbial hosts, cyanobacteria have fascinated considerable research attention in the last few years as a promising platform for the sustainable and cost-effective production of industrially pertinent chemicals [ 4 , 5 , 6 ]. Following the green chemistry principles, cyanobacteria utilize atmospheric carbon dioxide (CO 2 ) as a renewable feedstock and transform it into enormous valuable products, fuels, and commodity chemicals using sunlight as the potential energy source. The resultant carbon capturing and consumption technologies might exhibit a great perspective in alleviating the detrimental effects of raised CO 2 levels if the technology scaled up to an industrial level. Notwithstanding the budding potential, several technical challenges need to be considered and address for rendering cyanobacteria-derived bioprocesses commercially feasible [ 2 ]. Cyanobacteria are photosynthetic prokaryotes inhabiting almost any environment that comprises water and possess the ability to grow in diverse environmental conditions [ 7 ]. These microbial hosts use photosynthesis and the Calvin–Benson cycle (CBC) for biomass production using merely CO 2 and sunlight as the carbon and energy sources [ 4 , 8 ]. Engineering and rewiring the metabolic pathway of cyanobacteria offers the prospect for direct transformation of CO 2 into value-added products. This approach could be beneficial over heterotrophic bio-production hosts necessitating plant-based fermentable sugars that have been intensively criticized due to their competition with humans and animals food supply. Interestingly, these photosynthetic prokaryotes offer distinctive advantages over plants as well as green algae and can capture solar energy more efficiently than plants. Also, they possess 9% conversion ability of the solar energy into biomass relative to higher plants transforming only 0.5–3% [ 9 , 10 ]. Cyanobacteria can be cultured in bioreactors in the arid or unfarmable land, which additionally diminishes the competition with food crops [ 11 ]. Nevertheless, the inevitability of significantly limited and expensive resources such as nitrogen and phosphorus inputs are a notable issue in these organisms as compared to plants or eukaryotic green algae [ 11 , 12 ]. Cultivation of the cyanobacteria in waste or salt water along with implementing nitrogen-fixing strains might be a partial solution to the shortcoming mentioned above [ 13 ]. After the elucidation of foremost metabolic engineering of a cyanobacterium for fuel ethanol production by Deng and Coleman [ 14 ], several succeeding research studies have revealed heterologous pathways expression to produce numerous compounds including alcohols, fatty acids, diols, and organic acids over the past twenty years ( Table 1 ). Besides, cyanobacteria have been documented to synthesize thousands of bioactive molecules [ 27 , 28 ]. Despite the long list of commodity chemicals produced by metabolically engineered strains, it is important to mention that the majority of these bioproducts are derived from the exploration of only a limited number of central metabolites. More recently, numerous sophisticated synthetic and metabolic engineering approaches have been introduced to improving the cyanobacterial genomic function for CO 2 fixation and carbon rewiring flux to increase the ultimate photosynthetic product [ 29 , 30 ]. Recent advancements revealed that 50% of organic carbon had been successfully fixed during the photosynthetic reaction by engineered cyanobacteria [ 31 ]. While cyanobacterial systems can produce a great variety of industrially useful chemicals ( Figure 2 ) in an energetically favorable way with a net negative atmospheric carbon contribution, they are considered as a promising platform for sustainable chemicals production [ 32 ]. Nevertheless, there are many limitations associated with the use of cyanobacteria in the production of chemicals at a commercial level. CO 2 fixation is an intrinsically slow reaction occurred in the range of 1–4 reactions per second [ 33 ]. Furthermore, most of the heterologous pathways are initially designed and established on heterotrophic microbial candidates and subsequently transferred to photosynthetic prokaryotes, i.e., cyanobacteria [ 18 ]. Prominent dissimilarities in metabolism, transcription, and translation in these hosts make direct transfer often challenging and non-viable. Recent innovations in metabolic engineering led to the development of novel genetic tool such as the clustered regularly interspaced short palindromic repeats (CRISPR)-cas9 system, Cpf1 genome editing tool, high-throughput “omics”, and metabolic flux analysis. Adaptation to these tools has extended our capability to generate predictions and target-specific manipulations in cyanobacteria for the production of numerous chemicals at increasing titers [ 19 , 26 , 34 , 35 , 36 , 37 ]. This review encompasses the recent advances in engineering cyanobacteria for the production of biofuel and many other industrially relevant fine-chemicals. The development and applications of advanced technique and toolboxes for engineering cyanobacteria for their large-scale cultivation are also discussed.\n\n3.1. Introducing Heterologous Stress Tolerance Proteins Extremophilic bacteria can grow, reproduce, and survive in severe environmental situations. Identification and installation of tolerance-relevant genes from extremophiles appear as a promising approach to improve the metabolic physiology and cellular robustness of cyanobacteria [ 5 ]. Following the introduction of molecular devices from a halotolerant cyanobacterium, the salinity stress tolerance of freshwater cyanobacterial strains has been effectively improved. Numerous salts-tolerance pertinent genes have recently been identified and characterized in a halotolerant cyanobacterium Aphanothece halophytica , which can grow and survive in hyper-osmotic settings in the presence of 3 M NaCl salt [ 68 ]. Waditee et al. [ 69 ] isolated a nhaP gene from A. halophytica and introduced into a cyanobacterial strain S. elongates PCC7942. Results showed that the resulting recombinant strain was able to grow and survive in the presence of 0.5 M NaCl [ 69 ]. In addition, the PCC7942 strain showed an optimized growth performance in seawater by the co-expression of nhaP (encoding a Na+/H+ antiporter) with katE ( E. coli -sourced catalase gene). However, the salt tolerating capacity was not further enhanced [ 69 ]. The production and accumulation of glycine betaine are regarded as another indispensable way for A. halophytica to tolerate high osmotic stress imposed by high concentrations of salt. For example, incorporation of the glycine betaine encoding devices or system to two freshwater cyanobacteria Anabaena sp. PCC7120 and A. doliolum resulted in the production of glycine betaine, which in turn effectively enhanced salt tolerance [ 70 ]. Improvement in system biology and simulation of metabolic network’s tools enable more effective identification and prediction of functional devices related to the resistance under harsh environmental conditions."
} | 2,658 |
34177865 | PMC8219869 | pmc | 2,248 | {
"abstract": "Endophytes are highly associated with plant growth and health. Exploring the variation of bacterial communities in different plant niches is essential for understanding microbe-plant interactions. In this study, high-throughput gene sequencing was used to analyze the composition and abundance of bacteria from the rhizospheric soil and different parts of the Macleaya cordata . The results indicated that the bacterial community structure varied widely among compartments. Bacterial diversity was observed to be the highest in the rhizospheric soil and the lowest in fruits. Proteobacteria, Actinobacteria, and Bacteroidetes were found as the dominant phyla. The genera Sphingomonas (∼47.77%) and Methylobacterium (∼45.25%) dominated in fruits and leaves, respectively. High-performance liquid chromatography (HPLC) was employed to measure the alkaloid content of different plant parts. Significant correlations were observed between endophytic bacteria and alkaloids. Especially, Sphingomonas showed a significant positive correlation with sanguinarine and chelerythrine. All four alkaloids were negatively correlated with the microbiota of stems. The predicted result of PICRUST2 revealed that the synthesis of plant alkaloids might lead to a higher abundance of endophytic microorganisms with genes related to alkaloid synthesis, further demonstrated the correlation between bacterial communities and alkaloids. This study provided the first insight into the bacterial community composition in different parts of Macleaya cordata and the correlation between the endophytic bacteria and alkaloids.",
"conclusion": "Conclusion This study provided the first insight into the bacterial communities of different plant tissues and rhizospheric soil in Macleaya cordata . There were significant differences in bacterial communities among different ecological niches under the influence of plants’ vertical stratification structure. A strong correlation between the endophytic bacteria and the alkaloids was found by the Spearman correlation analysis. The predicted results of PICRUST2 further demonstrated that alkaloids might contribute to the variation of bacterial communities in different niches. All in all, this experiment can support the subsequent search of functional microorganisms and guide the cultivation, protection, and increase of crucial metabolites and resource utilization of Macleaya cordata .",
"introduction": "Introduction Endophytes are widely present inside plants during part or all stages of their life cycle. They are able to survive in the root, stem, leaf, fruit, flower, and seed due to the specific colonization conditions provided by plant tissues and organs ( Loaces et al., 2010 ; Bulgarelli et al., 2013 ; Wellner et al., 2013 ; Glassner et al., 2015 ). Plant microbial community composition is influenced by environmental factors, including climate, temperature, geographic location, vegetation density, and host genotype ( Overbeek and Elsas, 2008 ; Meyer and Leveau, 2012 ; Ramond et al., 2013 ; Campisano et al., 2017 ; Yana et al., 2017 ; Ting et al., 2019 ; Sharaby et al., 2020 ). However, several studies have shown that plant compartment is the main driver of bacterial community composition, while the season, location, and plant species only play a minor role ( Miller and Rudgers, 2014 ; Junker and Keller, 2015 ; Fonseca-García et al., 2016 ; Cregger et al., 2018 ). Soil microorganisms were partially the source of endophytic bacteria ( Zarraonaindia et al., 2015 ; Mangeot-Peter et al., 2020 ). They migrated and colonized the area around the root of plants under the influence of the roots’ secretions ( Tahtamouni et al., 2015 ). Rhizospheric microbial community composition was significantly influenced by the physical and chemical parameters in soil ( Winston et al., 2017 ; Hartman et al., 2018 ; Ziyuan et al., 2020 ), which also affected the plant compartments in part ( Mighell et al., 2019 ). However, Two studies on Arabidopsis showed that the endophytic microbial community composition in the Arabidopsis plants growing on four different soils was similar ( Davide et al., 2012 ; Lundberg et al., 2012 ), indicating the existence of host mediated control mechanisms. Significant plant compartment effects were also observed in the microbiome of plants such as Populus , Cycas panzhihuaensis , and Stellera chamaejasme L ( Jin et al., 2014 ; Cregger et al., 2018 ; Zheng and Gong, 2019 ). Endophytes and plants can be considered as mutualistic symbiosis. They survived and evolved together ( Hardoim et al., 2015 ; Vandenkoornhuyse et al., 2015 ). Endophytes are an essential part of the plant micro-ecosystem. They were thought to complement the host plant’s gene library and could regulate metabolism, enhance stress resistance, and transform host plants’ secondary metabolites ( Zhou et al., 2015 ; Prasad et al., 2018 ; Cordovez et al., 2019 ; Víctor and Juan, 2019 ). Some endophytic bacteria were able to synthesize bioactive compounds such as saponins, terpenoids, and alkaloids, which are potential sources of antibacterial, anti-insect, anticancer, and other properties ( Yu et al., 2010 ; Pimentel et al., 2011 ; Gutierrez et al., 2012 ). Considering the various effects of plant-associated bacteria on plants, recording the spatial variability of these bacterial communities is critical for further understanding of plant-microbe interactions and the potential value of endophytic bacteria. Macleaya cordata , a perennial plant mainly distributes in China, Europe, and North America, has been considered as a traditional folk herbal medicine. Its chemical composition and biological activity were a matter of concern because of its detoxifying, analgesic, anti-inflammatory, antimicrobial, and antitumoral properties ( Liu et al., 2013 ; Khadem et al., 2014 ; Li et al., 2017 ; Huang et al., 2018 ). Its extract has been used as a good alternative of antibiotics in feed additives for animal production, and has achieved European Food Safety Certification for its effectiveness in treating inflammation and regulating the intestinal flora of livestock and poultry. Modern pharmacological studies showed that isoquinoline alkaloids are the primary bioactive substances in Macleaya cordata . Some of them possess a prominent apoptotic effect on cancer cells. For instance, sanguinarine could inhibit cell invasion and the MMP-9 and COX-2 expression in TPA-induced breast cancer cells by inducing HO-1 expression ( Park et al., 2014 ). The four main alkaloids in Macleaya cordata are sanguinarine, chelerythrine, allocrytopine, and protopine ( Kosina et al., 2010 ). Significant differences in the accumulation of these four alkaloids were reported in the root, stem, leaf, and fruit of Macleaya cordata . Sanguinarine and chelerythrine were observed to accumulate mainly in the fruits, with allocrytopine and protopine being most abundant in roots and leaves, respectively. The alkaloids content in the stem was very low. Endophytic bacterial communities in different parts might be affected by this difference. Bacterial communities across different niches covering below-ground and above-ground tissue-level microbial habitats (rhizospheric soil, root, stem, leaf, and fruit) were characterized in this study by using 16S rRNA gene-targeted Illumina MiSeq sequencing. The content of four main alkaloids was also detected to explore the relationship between alkaloids and endophytic bacteria. We hypothesized that: (i) Niche differentiation among different sample types influenced the composition and diversity of the Macleaya cordata associated microbial communities (ii) Alkaloids might contribute to the variation of bacterial communities in different niches. This experiment can support the subsequent search of functional microorganisms and guide the cultivation, protection, and increase of crucial metabolites and resource utilization of Macleaya cordata .",
"discussion": "Discussion The Composition and Diversity of Bacterial Communities Differ in Niches Bacterial community composition was significantly ( P < 0.01) different among plant compartments ( Table 1 ). The NMDS diagram ( Figure 2A ) also showed that the separation in the bacterial community structure between different plant compartments at the OTU level, indicating differences in the microbes in different niches. Although soil microorganisms were a source of plant endophytes, the migration of soil microorganisms to the root was still mediated by the host ( Davide et al., 2012 ; Lundberg et al., 2012 ). For above-ground plant tissues, endophytes also derived from horizontal dispersal in the atmosphere and vertical transmission through seeds ( Maignien et al., 2014 ; Fonseca-García et al., 2016 ), which resulted in bacterial differences between above-ground organs and soil. Similar results have also been reported in maize and wheat ( Xiong et al., 2020 ), poplar ( Beckers et al., 2017 ), Arabidopsis thaliana ( Davide et al., 2012 ), and other plant species ( Edwards et al., 2015 ; Lu et al., 2020 ). As demonstrated by rarefaction curves and the alpha diversity indices, there were significant differences in species diversity between rhizospheric soil and plant compartments of Macleaya cordata . As an ideal habitat for various microorganisms, the bacterial diversity of rhizospheric soil was significantly higher than roots and above-ground niches. This finding is consistent with the general view of microbial colonization ( Beckers et al., 2017 ). No significant difference was observed in the Shannon diversity of bacterial communities in roots, stems, and leaves, while the bacterial diversity in fruits was the lowest. The bacterial diversity within the plant compartments was low, probably because plant tissues were highly variable and complex. Bacterial colonization is limited by the host’s immune system, nutritional conditions, and metabolites ( Compant et al., 2010 ). The highest evenness of bacterial communities was found in the stem among plant parts. It should be noticed that there was no significant difference in bacterial diversity between stems and roots, while many studies have determined that bacterial diversity was highest in roots ( Santana et al., 2016 ; Wang et al., 2019 ). The variation of endophytic bacterial communities in different compartments was primarily driven by tissue-specific filtering mechanisms within the host ( Bonito et al., 2014 ; Chao et al., 2020 ). Under the host-mediated control, only a limited number of microorganisms could maintain a symbiotic lifestyle with the host. This pressure sequentially increased from the soil to the plant compartments ( Chao et al., 2020 ; Pasquale et al., 2020 ), which might be responsible for the lowest diversity of bacterial communities in fruits of Macleaya cordata . Niche Preference Exists for Bacteria of Macleaya cordata We identified several prokaryotic taxa (>0.1%), including microbiota members belonging to Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, TM7, Firmicutes. Bacterial diversity varied among plant-associated habitats, and the dominant phylum found in each habitat was highly comparable to other plant hosts in each habitat. Many studies have reported that plants’ bacterial microbiota is generally dominated by three major phyla (Proteobacteria, Actinobacteria, and Bacteroidetes) in both above- and below-ground tissues ( Tahtamouni et al., 2015 ; Wang et al., 2020 ). This is also consistent with our study. Proteobacteria was the most abundant in the above-ground compartment, while Actinobacteria was widely distributed in the below-ground. Many microorganisms were detected in rhizospheric soil but hardly found in other niches, such as Acidobacteria, Bacteroidetes, and Gemmatimonadetes, which were often discovered in the soil in other studies ( Cregger et al., 2018 ; Wang et al., 2020 ). Bacteria in the stem were affected by both the above-ground parts (leaf and fruit) and the below-ground part (root) and dominated by Proteobacteria with the enrichment of Actinobacteria, Bacilli, Mollicutes, and TM7. However, some of the microorganisms did not spread from the stem to the leaf and fruit. This might be caused by nonuniform colonization of different compartments, the microbial source difference, or other environmental factors. As shown in Figure 3B , only a few bacterial genera were dominant in fruit and leaves. Sphingomonas and Pseudomonas were found to be the dominant bacterial genera in the fruit, and Methylobacterium , Sphingomonas , and Deinococcus were detected as predominant groups in the endophytic communities of the Macleaya cordata leaf. Different studies have reported that these genera represented a substantial part of various plant species’ endophytic microbiota ( Mano and Morisaki, 2008 ; Delmotte et al., 2009 ). In the previous study, Sphingomonas played an essential role in plant stress tolerance, plant growth promotion, and biodegradation of polycyclic aromatic hydrocarbon ( Wilkes et al., 1996 ; Halo et al., 2015 ; Asaf et al., 2020 ). Microbial colonization is related to its ability to adapt to the host’s internal environment and its utilization of substrates. Leaves are more often exposed to the vagaries of the environment, including nutrient stress, desiccation, and ultraviolet radiation, providing a special habitat for microorganisms ( Hunter et al., 2010 ). Methylobacterium , often isolated from the leaf surface and interior, could specifically colonize the plant by profiting from methanol released by the plant ( Galbally and Kirstine, 2002 ) and has been reported to be drought and radiation-resistant ( Yoshida et al., 2017 ; Jorge et al., 2019 ; Kim et al., 2019 ). Therefore, Methylobacterium were able to successfully colonize the leave extensively ( Delmotte et al., 2009 ). Cystobacter was found only in the fruits and leaves, and Erwinia was found only in above-ground tissues. Colonization of these two genera might be due to horizontal transmission ( Frank et al., 2017 ). Bacterial communities of different ecological niches were assembled under the effect of environmental filtering, ecological drift, and dispersal limitations ( Nemergut et al., 2013 ; Moroenyane et al., 2021 ). However, there is still a lack of understanding of these processes. Plants are exposed to diverse and highly variable environmental factors, physiological structure (thickness and shape), chemical properties (nutrients contents, water, and secondary metabolites) of each compartment drive the differences in bacterial communities to some extent ( Delmotte et al., 2009 ; Hunter et al., 2010 ; Arturo et al., 2012 ). In a study on soybean, the secondary metabolites (ethylamine and betaine) were considered as a robust environmental filter for bacterial communities ( Shintaro et al., 2019 ). Furthermore, the bacterial communities in Stevia rebaudiana and Coptis teeta , were also demonstrated to be significantly correlated with secondary metabolites ( Yu et al., 2015 ; Liu et al., 2020 ). On the other hand, the functional capacity of bacterial species is key to their recruitment by hosts, and Burke et al. (2011) proposed that bacterial community assembly is associated with function rather than the taxonomy. The Alkaloids May Contribute to the Variation of the Endophytic Bacterial Communities Protopine and allocrytopine are considered as precursors of sanguinarine and chelerythrine, respectively, and they are abundant in the root. In a previous study on the dynamics of the four alkaloids of Macleaya cordata , it was found that after entering the mature fruiting season, the content of protopine in the fruit decreased significantly, while the content of sanguinarine and chelerythrine increased rapidly. This suggested that protopine and allocrytopine were transported into the fruit and converted into sanguinarine and chelerythrine. The transcriptome, proteome, and metabolism data in a previous study conducted by Jianguo Zeng et al. (2013) revealed that the root of Macleaya cordata is the primary organ for the biosynthesis of isoquinoline alkaloids. In this study, significant differences were found in alkaloids accumulation in various organs. The content of allocrytopine in the root, leaf, and fruit showed a decreasing trend. Besides, the highest accumulation of protopine was found in leaves, followed by roots and fruit. The sanguinarine and chelerythrine in fruit were much higher than those in other tissues. The accumulation of all four alkaloids in stems was low. Some common endophytes, such as Firmicutes, have been reported to be abundant in the above-ground part, whereas in this study, it was only abundant in the stem. It can be speculated that this may explain to some extent the higher microbial diversity in stems since these four alkaloids have antibacterial effects ( Beuria et al., 2005 ; Li et al., 2009 ; Razan et al., 2014 ; Yu et al., 2014 ). The CCA analysis also showed that all four alkaloids were negatively correlated with the microbiota of the stem of Macleaya cordata . The correlation tests between alkaloids and microorganisms also showed that most endophytic bacteria were significantly ( P < 0.05) correlated with alkaloids. Endophytes and host plants are closely related, and they adapt to each other and coevolve. Studies have shown that genes and abilities that evolve in one lineage are usually acquired steadily by another lineage ( Papke and Gogarten, 2012 ). Direct gene transfer between species has occurred in all major taxa and seems to occur more frequently in prokaryotes ( Moran, 2007 ). This leads to the possibility that microorganisms could respond to environmental toxins by selecting specific gene sequences that give them a competitive advantage over other organisms. It can be hypothesized that the microbes colonized in the plant might be affected by alkaloids produced by the host. Through the analysis of the functional annotation in Hierarchical level 2, endophytic bacteria in roots was found to contribute most to the gene abundance of the Cytochrome P450, ABC transporters, and secondary metabolite synthesis pathway including the isoquinoline alkaloid synthesis pathway. This was consistent with Jianguo Zeng’s reports that all enzymes for protopine and allocrytopine biosynthesis were highly expressed in the host root. Cytochrome P450 is considered as a large family of enzymes involved in many important metabolic pathways, and many enzymes related to the biosynthesis of benzylisoquinoline alkaloids belong to the P450 family ( Zeng et al., 2013 ). Simultaneously, the ABC transporters are involved in transporting secondary metabolites such as alkaloids ( Shitan and Yazaki, 2007 ). The number of genes annotated to the Staurosporine biosynthesis pathway was significantly higher in fruits than that in other parts, which may be due to the high accumulation of sanguinarine in the fruit. Staurosporine, an alkaloid with a diindole chemical structure, has been reported to partially block the accumulation of sanguinarine induced by a fungal activator ( Peter et al., 1996 ). Since the primary function of stems is transport and there is almost no alkaloid stored in the stem, this may contribute to the low gene abundance of the microbiota genes related to the synthesis of secondary metabolites in the stem."
} | 4,845 |
29708554 | PMC5933500 | pmc | 2,250 | {
"abstract": "Microfluidic components need to have various shapes to realize different key microfluidic functions such as mixing, separation, particle trapping, or reactions. A microfluidic channel that deforms even after fabrication while retaining the channel shape enables high spatiotemporal reconfigurability. This reconfigurability is required in such key microfluidic functions that are difficult to achieve in existing \"reconfigurable\" or \"integrated\" microfluidic systems. We describe a method for the fabrication of a microfluidic channel with a deformable sidewall consisting of a laterally aligned array of the ends of rectangular pins. Actuating the pins in their longitudinal directions changes the pins' end positions, and thus, the shape of discretized channel sidewalls.Pin gaps can cause unwanted leakage or adhesion to adjacent pins caused by meniscus forces. To close the pin gaps, we have introduced hydrocarbon-fluoropolymer suspension-based gap filler accompanied by an elastomeric barrier. This reconfigurable microfluidic device can generate strong temporal in-channel displacement flow, or can stop the flow in any region of the channel. This feature will facilitate, on demand, the handling of cells, viscous liquids, gas bubbles, and non-fluids, even if their existence or behavior is unknown at the time of fabrication.",
"introduction": "Introduction Microfluidic devices - micro-sized devices that control small amounts of liquid and their flows - offer miniaturization of biomedical procedures into a \"chip\" format with increased portability and, often, affordability. As described in a recent review 1 , various microfluidic components consisting of spaces and positive features have been developed to realize basic and key fluidic functions such as mixing, separation, particle trapping, or reactions. While the behavior of many microfluidic devices is determined at the design stage, some kinds of microfluidic devices allow post-fabrication changes of their structure or behavior. Here we refer to this feature as \"reconfigurability\". The reconfigurability of microfluidic systems generally reduces the time and cost required to design a device, and/or enables customization of the microfluidic layout or functions over time. Previously described reconfigurable microfluidic devices fall into the following three categories. In the first, deformation of elastomeric channels allows flow rates and directions to be changed during use. To gain reconfigurability, elastomeric channels are deformed by various external and controllable forces such as pneumatic pressure sources 2 , Braille actuators 3 , or compression sealing 4 . In the second, reconfigurable devices rely on modular designs, such as multi-layer fluidic circuits, modular channels with magnetic interconnects, and tubing-based microfluidics 5 . In the third, the device itself is not reconfigurable, but microdroplet transportation on electrode arrays (often referred to as digital microfluidics) 6 7 and hanging drop-based microfluidic devices 8 enable on-demand switching of the flow or the route of fluid. Nonetheless, many of these reconfigurations are limited at the topological and macroscopic levels. For example, many integrated microfluidic devices stop flow or change the flow direction by collapsing microchannels in predefined regions. However, the position and number of regions to be collapsed are not reconfigurable. Although the digital microfluidics has a variety of fluid handling abilities, possible flows should be largely limited by the volume of each droplet. In addition, when cells are cultured in such droplets of cell culture media, extra effort is needed to prevent evaporation and gas dissipation from droplets and avoid osmolality shock and sudden pH change. To realize channel feature-level reconfigurability, we proposed a microfluidic device with movable sidewalls that consisted of arrays of machine elements to dynamically reconfigure them when in use 9 . To form a deformable sidewall, small rectangular pins were lined up so that each end of the pins defined a segment of the sidewall. Sliding the pins allowed the deformation of the sidewall which allowed transport or patterning of cells, bubbles, and particles inside the channel. To minimize dead volume and maximize reconfigurability, the distance between the adjacent pins had to be minimized. However, strong capillary action acting on the small gaps between pins connecting the inside and outside of the microchannel causes leakage of any liquid entering the pin gap, causing media evaporation, bacterial or cytotoxic contamination, and eventually cell death. Therefore, we have developed leak-free discretized sidewall-type reconfigurable microfluidic channels that withstand cyclic pin actions and long-term cell culture 10 . In this article, we provide a protocol to build microfluidic cell culture device with a discretized sidewall that can be reconfigured following the gradual increase in the cell culture area. Airtightness of the discrete channel sidewalls is tested using fluorescence imaging. The cell-culture compatibility and the ability of cell patterning are evaluated using on-chip cell culture. This microfluidic system is suitable whenever appropriate channel design cannot be predetermined and must be changed on demand. For example, this system could be used to adjust the channel width and flow rate based on the cell growth or migration, to flow or trap active nematodes or other small objects that behave unexpectedly in the channel, or to accept various raw samples or bioproducts that were not yet conceived at the time of design.",
"discussion": "Discussion The pin-discretized microchannel is a full-featured microfluidic channel, and we believe that it has obviously high reconfigurability in channel shape compared with any existing microfluidic channels. The protocol we provided here will enable microfluidic devices capable of cell culture with gradually expanding cell culture surface area to keep the cultures under confluency for a long duration. The device will also provide in-channel patterning of cells without patterning proteins on the substrate beforehand or any other consideration at the time of design or fabrication. In addition, this reconfigurable microfluidic device easily generates strong in-channel displacement flow, which would help implement handling of such difficult-to-flow materials that very few existing microfluidic devices can handle. This means that the interaction between the cells and other microorganisms, gases, and other non-fluids can be evaluated using this device without large modifications in device design. We have considered applying Laplace pressure or hydrostatic pressure to one inlet of the channel as external flow control methods. We do not recommend pushing liquid at a dead end because it will generate flow toward the air vent channel through the gaps between pins and the ceiling/floor of the channel. Many fluid operations do not require such pin operations. For example, mixing can be accomplished by mashing liquid by one pin ( i.e., moving only one pin back and forth several times). The most critical parts of the device are the pins. Precision in length, parallelism, perpendicularity and surface quality are required for the pins, as they must form a microchannel, must move smoothly, and must guide the movement of adjacent pins. Therefore, we recommend that the pins should be ordered from a company that specializes in precision machining by submitting a drawing similar to Figure 2 A . There may be companies that require additional geometric dimensioning and explicit surface roughness directions. However, the pins are reusable if they are handled with care and occasionally passivated with nitric acid. The elastomeric barrier is another critical feature, and its formation is the most critical step in the fabrication processes of the device. A precisely machined base will be needed to obtain repeatable and reliable results. Placing the pins on the uncured barrier is also a critical step. The pins should be kept well aligned, and embedded in the gap filler and the barrier without air bubbles. These steps prevent leakage through the pins, which is a common problem with this microfluidic device. Other common issues in using this device are a) frictionally restrained pins, and b) cell death, and low growth rate. Possible causes for these in a) include uneven (tapered or wavy) etching of the pin middle, poor quality of the etched surface, and dimensional misfit between the pin tip height and the height of the photoresist layer on a mold for silicone slabs. Adjustment of etchant formulation, temperature, and agitation may help improve the pin movement. In addition, trial fitting without using wax or adhesive will provide hints to solve the problem. Possible factors in b) are insufficient passivation of the pins, errors in selection of adhesives for elastomeric barriers, and incomplete curing of the adhesives. Some cells may require coating inside the microchannel with fibronectin or other proteins or polymers that promote cell adhesion. In addition, optimization in cell culture practice such as trypsinization and centrifugation will decrease dead cells in the microchannel. One of the limitations of the presented fabrication protocol is that only one of the sidewalls is discretized. The reconfigurability of the channel will further improve if the both sidewalls are built by pin arrays. Although it requires double the amount of pins and longer fabrication steps, this is a technically viable option."
} | 2,391 |
36070388 | PMC9451144 | pmc | 2,251 | {
"abstract": "Designed and engineered protein and DNA nanopores can be used to sense and characterize single molecules and control transmembrane transport of molecular species. However, designed biomolecular pores are less than 100 nm in length and are used primarily for transport across lipid membranes. Nanochannels that span longer distances could be used as conduits for molecules between nonadjacent compartments or cells. Here, we design micrometer-long, 7-nm-diameter DNA nanochannels that small molecules can traverse according to the laws of continuum diffusion. Binding DNA origami caps to channel ends eliminates transport and demonstrates that molecules diffuse from one channel end to the other rather than permeating through channel walls. These micrometer-length nanochannels can also grow, form interconnects, and interface with living cells. This work thus shows how to construct multifunctional, dynamic agents that control molecular transport, opening ways of studying intercellular signaling and modulating molecular transport between synthetic and living cells.",
"introduction": "INTRODUCTION Nanoscale channels are fundamental mechanisms for directing transport across membranes in living systems. Synthetic nanopores and nanochannels that mimic the selectivity ( 1 – 3 ) and gating ( 4 , 5 ) functions of biological membrane channels have become powerful tools in biosensing ( 6 – 8 ) and drug delivery ( 9 , 10 ). Biomimetic channels assembled from different materials, such as peptides ( 11 , 12 ), polymers ( 13 ), DNA ( 14 ), metal-organic complexes ( 15 , 16 ), and carbon nanotubes ( 17 ), can mediate cross-membrane transport of a range of ions and molecules. Most of these biomimetic channels have diameters of less than 2 nm and thus allow transport of ions, but not larger molecular species. Self-assembled DNA-based synthetic nanopores, particularly those built from scaffolded DNA origami, benefit from the extensive design space of DNA as building materials. DNA nanopores with inner diameters of more than 3 nm have been shown to mediate the passage of large biomolecules, such as double-stranded DNA and proteins, across lipid bilayer membranes ( 18 – 22 ). Moreover, highly predictable DNA interactions are the basis for the creation of programmable DNA nanopores that initiate transport only in the presence of specific chemical or spatial cues ( 20 , 23 ). Advancements in DNA modifications using chemical groups and aptamers and control over pore geometries have further enabled selective transport of solute species across DNA nanopores ( 21 , 24 ). In addition to their potential applications in biosensing and drug delivery ( 25 ), DNA nanopores can have functions as transporters in systems of synthetic cells ( 22 ): The lack of specificity of many types of membrane pores and the lack of reliable transport mechanisms between synthetic cells are central challenges in reconstituting complex signaling systems in synthetic cells ( 26 ). The programmability and specificity of DNA nanopores could allow delivery of target genetic and signaling materials to make efficient communication possible. However, existing large-diameter DNA nanopores have lengths of less than 100 nm and act as cross-membrane transporters ( 27 , 28 ). Longer DNA-based channel structures, once built, could establish connections between nonadjacent cells or compartments for communication and molecular exchange. These channels could enable the development of complex transport networks that connect specific pairs of compartments in a synthetic tissue to create transport networks. Here, we demonstrate bulk transport of molecules through micrometer-long DNA-based nanochannels and investigate the transport phenomena within them ( Fig. 1A ). DNA nanochannels that span up to several micrometers in length are self-assembled from double-crossover DNA tiles, on top of DNA origami pores with approximately 7-nm inner diameter. Observations that fluorescent dyes move across lipid membranes confirm that molecular transport can occur through both DNA pores and nanochannels. Further analysis of the kinetics of these processes suggests a continuum diffusion description of the transport within nanopores. By showing a DNA origami cap that closes the channel opening and prevents channel-mediated transport, we demonstrate specific gating of the nanochannel and that the transport is predominantly end to end rather than across channel walls. Fig. 1. Scheme for studying the transport of small molecules through micrometer-length self-assembled DNA nanochannels. ( A ) End-to-end transport of small molecules through micrometer-length channels could allow for controlled transport between channel end points. Diffusion across the channel walls leads to transport loss. ( B ) The assay used to characterize the rate of transport through a micrometer-long channel. When the channel attached to a pore enters a lipid membrane of a giant unilamellar vesicle (GUV), fluorescent dyes diffuse into the vesicle because of the concentration gradient across the membrane until equilibration of the concentration of fluorescent dyes inside and outside the vesicle. ( C ) A DNA origami nanostructure functionalized on one end with hydrophobic moieties serves as a transmembrane pore. DNA tiles hybridize to sticky ends on the DNA pore’s opposite end to self-assemble a DNA nanotube hundreds of nanometers to micrometers in length that serves as a nanofluidic channel. ( D ) A cap that binds to and plugs the opening of the nanotube channel would prevent transport through the channel end into the vesicle but not transport across channel walls. A DNA channel cap with a designed constriction binds to the nanotube channel end via complementary DNA sticky ends. The designed DNA nanochannels thus mediate leakless transport from one end of a channel to the other over distances ranging from tens of nanometers to micrometers, and this transport can be completely halted by the programmable binding of a DNA cap. The rates of transport in these channels are consistent with those in bulk solutions, allowing for precise design of flow rates. These advances suggest a toolkit of self-assembling elements for building nanoscale fluid transport networks to connect compartmentalized structures separated in space. These transport networks have great potential for studying intercellular communications and building artificial multicellular structures.",
"discussion": "DISCUSSION Here, we have designed DNA origami pores and micrometer-long DNA nanochannels that could spontaneously insert into GUV membranes. Dye influx assays enabled measurements of the kinetics of small-molecule diffusion into the GUVs. These kinetic measurements verified that both DNA pore and DNA nanochannels could transport small molecules at rates predicted by the continuum diffusion model. Last, binding of a DNA cap to either a DNA pore or DNA nanochannel’s end stopped transport, demonstrating that transport is end to end with minimal leak across the channel. This end-to-end transport through a nanochannel can direct how a molecule diffuses well beyond the spanning ends of a membrane; it could presumably enable transport between two compartments that are micrometers apart. The self-assembled nanochannels studied here can self-repair ( 44 ) and form interconnects between molecular landmarks ( 45 ), suggesting how they might be used to form nanoscale flow networks for building artificial multicellular systems, widely used in studying cell-to-cell signaling. Large channel diameters could allow the transport of macromolecules such as proteins and DNA. Long channel lengths would also be advantageous for characterizing the DNA-protein or protein-protein interactions within a channel because the residence time should scale with the square of channel length, allowing more time for characterization in a longer channel than in a short one. Functionalizing nanotube interiors with antibodies or DNA aptamers could also allow nanotube channels to be used for detecting proteins of interest or other biosensing applications."
} | 2,017 |
25215482 | null | s2 | 2,253 | {
"abstract": "The more that biologists study symbiotic microorganisms and their vast influence on animals, the more nature's networkism unfolds in a continuum at different biological scales. In this issue, Van Leuven et al. illuminate how a stable and longstanding animal-microbe mutualism increased its intergenomic network without gaining any new genomes."
} | 85 |
33032255 | null | s2 | 2,254 | {
"abstract": "Saccharomyces cerevisiae, Baker's yeast, is the industrial workhorse for producing ethanol and the subject of substantial metabolic engineering research in both industry and academia. S. cerevisiae has been used to demonstrate production of a wide range of chemical products from glucose. However, in many cases, the demonstrations report titers and yields that fall below thresholds for industrial feasibility. Ethanol synthesis is a central part of S. cerevisiae metabolism, and redirecting flux to other products remains a barrier to industrialize strains for producing other molecules. Removing ethanol producing pathways leads to poor fitness, such as impaired growth on glucose. Here, we review metabolic engineering efforts aimed at restoring growth in non-ethanol producing strains with emphasis on relieving glucose repression associated with the Crabtree effect and rewiring metabolism to provide access to critical cellular building blocks. Substantial progress has been made in the past decade, but many opportunities for improvement remain."
} | 263 |
27698381 | PMC5048113 | pmc | 2,255 | {
"abstract": "Bioleaching has been employed commercially to recover metals from low grade ores, but the production efficiency remains to be improved due to limited understanding of the system. This study examined the shift of microbial communities and S&Fe cycling in three subsystems within a copper ore bioleaching system: leaching heap (LH), leaching solution (LS) and sediment under LS. Results showed that both LH and LS had higher relative abundance of S and Fe oxidizing bacteria, while S and Fe reducing bacteria were more abundant in the Sediment. GeoChip analysis showed a stronger functional potential for S 0 oxidation in LH microbial communities. These findings were consistent with measured oxidation activities to S 0 and Fe 2+ , which were highest by microbial communities from LH, lower by those from LS and lowest form Sediment. Moreover, phylogenetic molecular ecological network analysis indicated that these differences might be related to interactions among microbial taxa. Last but not the least, a conceptual model was proposed, linking the S&Fe cycling with responsible microbial populations in the bioleaching systems. Collectively, this study revealed the microbial community and functional structures in all three subsystems of the copper ore, and advanced a holistic understanding of the whole bioleaching system.",
"discussion": "Discussion Bioleaching has been employed commercially to recover precious metals (e.g., copper, gold) from low grade ores, but one obvious shortcoming is overlong production cycle 2 . Therefore, to enhance the production efficiency becomes one of the major goals of biohydrometallurgy research. However, previous studies only focused on one of the three subsystems of bioleaching, lacking a systematic insight. Revealing the geochemical conditions as well as microbial communities change across the three subsystems would provide a holistic view of the bioleaching mechanism, and ultimately benefit achieving the goal of improving leaching efficiency. The major finding of this study was that microbial communities of three subsystems had different Fe/S oxidation activity. It is commonly acknowledged that the ecological function of microbial communities is largely depended on their composition and structure 19 20 . The relative abundances of OTUs related to S and Fe oxidation were higher in LH and LS than in Sediment, resulting in higher S and Fe oxidation activity in LH and LS. Previous studies supported that the oxidation of sulfur and iron usually took place in mine tailings or acid mine drainage, and Fe/S oxidizers were frequently detected in these environments, such as Acidithiobacillus and Leptospirillum 2 5 14 . OTUs capable of Fe or S reduction were more abundant in Sediment. Oxygen content is usually a key factor determining the abundances and ecological niches of acidophiles 21 22 . In Sediment, relatively low oxygen levels resulted in greater abundances of anaerobic or facultative anaerobic bacteria, such as Metallibacterium , Acidiphilium , and Desulfitobacterium . Therefore, though not characterized, Sediment microbial communities might have stronger S and Fe reduction potentials, which requires further experimental validation. Sulfur oxidation activity was higher by microbial communities from LH than those from LS, coincident with observations based on GeoChip analysis, that the intensity of genes involved in sulfur oxidation ( soxB and soxC ) was higher in LH than LS. It has been proved that AMD microorganisms adapted to the different environmental conditions via regulating the functional composition and expression of genes 23 . Here, the availability of energy resource was a key factor determining the difference of LH and LS microorganisms in sulfur oxidation. Most of RIS were insoluble in LS, including AVS (FeS, Fe 3 S 4 ), CRS (FeS 2 ) and S 0 . We detected lower levels of S 0 (0~22.1 mg/L) in LS samples than LH, which explained lower elemental sulfur oxidation activity of LS microorganisms. The result was also supported by a previous study which indicated that the main role of attached acidophilic bacteria was to oxidize elemental sulfur and dissolution of chalcopyrite 24 . Interactions among microorganisms might be another reason resulted in the different Fe/S oxidation activity of three groups of microbial communities. By phylogenetic molecular ecological network analysis, we found that LHN had the largest number of nodes and links while SN had the fewest, suggesting there were strongest interactions among microbial populations in LH. A few studies suggest certain environmental conditions may result in tighter connected networks 25 26 , but the relationship between co-occurrence pattern of a community and its ecological roles have been rarely assessed 27 . Major dissolution reactions took place on the surface of ores in the leaching heap 28 , in this study microbial communities of LH showed highest S and Fe oxidizing activities, which might resulted from tight connection among microorganisms. It was reported that the co-culture of Acidithiobacillus ferrooxidans and Acidiphilium acidophilum enhanced their growth and iron oxidation activity 29 , supporting our speculation. Spatial relationship of three subsystems also influenced their microbial composition and function. Because leaching solution was pumped and sprinkled on the LH periodically, LS shared a large percent of OTUs with LH and Sediment respectively, but relatively few OTUs were shared by LH and Sediment. However, previous studies about microbial ecology of mine environments only focused on the relationship between microbial communities and physical-chemical conditions of the environment 4 30 31 , so the biochemical Fe&S cycling was modeled only within the environment 6 32 . Unlike many abandoned mining sites or naturally formed AMD or acidic river, Dexing bioleaching system is still in industrial application and under artificial management, thus iron and sulfur cycles among three environments ( Fig. 3 ). Take sulfur cycling as an example: metal sulfides (chalcopyrite and pyrite) in LH were oxidized by Fe 3+ , oxygen, or microorganisms (mainly Acidithiobacillus and Thiomonas ), generating RIS, including thiosulfate and elemental sulfur 33 34 . Then sulfur-oxidizing bacteria would oxidize RIS to generate sulfuric acid, which may accelerate mineral dissolution through the function of several detected genes ( SoxABCVY , Sqr , Fccab ). Later, all of these S compounds, including RIS and sulfuric acid, were washed into the LS, where RIS continued to be oxidized into sulfate 33 34 . Then a small part of RIS and most of the sulfate precipitated into the sediment, where anaerobic bacteria (e.g., Geobacter and Desulfitobacterium ) reduced sulfate into S 0 or HS − through functional genes like dsrA and dsrB . The reduced inorganic sulfur may be utilized by microorganisms in LS or Sediment, or be pumped back to LH and oxidized again, thereby closing the S cycle. In previous studies, Acidithiobacillus was reported as the major sulfur oxidizer both in abandoned Mynydd Parys mine and Tinto River 15 32 , but different valence state of sulfur and sulfur metabolism related genes were not involved in their models. Therefore, our Fe&S cycling model provided more detailed insight into the bioleaching process. Besides, each bioleaching subsystem had its own Fe&S micro-cycles. Because three subsystems had different physicochemical conditions and microbial communities, their Fe&S micro-cycle was different from each other too. For LH and LS, iron oxidation was predominant process in their Fe cycles while iron reduction was more active for Fe cycles in Sediment. Capable of reducing iron, Acidiphilium was reported to reduce iron in Tinto River 15 , and it was also the major iron reducers in Sediment of Dexing bioleaching system. Predominant iron-oxidizing bacteria in LH were Acidithiobacillus , Leptospirillum and Acidiferrobacter . Particularly, Acidiferrobacter was an acidophilic, thermo-tolerant, facultatively anaerobic iron- and sulfur-oxidizer 35 . It accounted for 15.14% of all reads in LH samples, and thus might play an important role inside the leaching heap where oxygen was scarce. However, H. Korehi et al . reported the iron cycles with the involvement of Acidithiobacillus , Sulfobacillus and Alicyclobacillus during pyrite dissolution in mine tailings 14 . It might result from different geochemical conditions of two mining sites 13 36 , for pH, oxygen content and energy source were all key factors impacting microbial communities. Our study showed drastic changes in geochemical properties, as well as significant shift in structure, function and co-occurrence patterns of the microbial communities among LH, LS and Sediment subsystems in Dexing Copper Mine. A biochemical Fe&S cycling model was also constructed to unveil the bioleaching process. Mineral leaching capability of microbial communities would be investigated in the future to relate the shift pattern of microbial communities to bioleaching efficiency directly. As essential elements related to growth of microorganisms, how carbon, nitrogen and phosphorus cycle in bioleaching system also need to be explored further."
} | 2,310 |
37965023 | PMC10641815 | pmc | 2,256 | {
"abstract": "Introduction As a crucial factor in determining ecosystem functioning, interaction between plants and soil-borne fungal pathogens deserves considerable attention. However, little attention has been paid into the determinants of root-associated fungal pathogens in subtropical seedlings, especially the influence of different mycorrhizal plants. Methods Using high-throughput sequencing techniques, we analyzed the root-associated fungal pathogen community for 19 subtropical forest species, including 10 ectomycorrhizal plants and 9 arbuscular mycorrhizal plants. We identified the roles of different factors in determining the root-associated fungal pathogen community. Further, we identified the community assembly process at species and mycorrhizal level and managed to reveal the drivers underlying the community assembly. Results We found that plant species identity, plant habitat, and plant mycorrhizal type accounted for the variations in fungal pathogen community composition, with species identity and mycorrhizal type showing dominant effects. The relative importance of different community assembly processes, mainly, homogeneous selection and drift, varied with plant species identity. Interestingly, functional traits associated with acquisitive resource-use strategy tended to promote the relative importance of homogeneous selection, while traits associated with conservative resource-use strategy showed converse effect. Drift showed the opposite relationships with functional traits compared with homogeneous selection. Notably, the relative importance of different community assembly processes was not structured by plant phylogeny. Drift was stronger in the pathogen community for ectomycorrhizal plants with more conservative traits, suggesting the predominant role of stochastic gain and loss in the community assembly. Discussion Our work demonstrates the determinants of root-associated fungal pathogens, addressing the important roles of plant species identity and plant mycorrhizal type. Furthermore, we explored the community assembly mechanisms of root-associated pathogens and stressed the determinant roles of functional traits, especially leaf phosphorus content (LP), root nitrogen content (RN) and root tissue density (RTD), at species and mycorrhizal type levels, offering new perspectives on the microbial dynamics underlying ecosystem functioning.",
"introduction": "1 Introduction Based on the premise that a natural enemy has restricted ability to disperse ( Adler and Muller-Landau, 2005 ) and a certain degree of specificity ( Sedio and Ostling, 2013 ), fungal pathogens could result in conspecific negative density dependence (CNDD) on seedlings, facilitating the coexistence of plant species ( Janzen, 1970 ; Connell, 1971 ). Root-associated fungi serve as an effective indicator of plant-fungus network, which has been considered to mediate the diversity maintenance and population dynamics( Tedersoo et al., 2020 ; Kuang et al., 2021 ). However, the community structure and assembly processes of root-associated fungal pathogens belonging to forest seedlings remains poorly understood. Given this, understanding the properties and drivers of root-associated fungal pathogens is important for better understanding of the forest dynamics ( Trivedi et al., 2017 ; Zitnick-Anderson et al., 2020 ; Yang et al., 2021 ). Both biotic and abiotic factors influence the composition of soil-borne fungal communities. The important role of species identity has been stressed in various studies ( Morris et al., 2009 ; Liu et al., 2021 ; Sweeney et al., 2021 ). Notably, the influence of plant species identity on fungal community could be modulated by plant functional groups ( Sweeney et al., 2021 ). Abiotic environments ( Tedersoo et al., 2016 ) and neighboring plants ( Bahram et al., 2013 ; Morris et al., 2013 ; Chen et al., 2018 ) are also believed to be important drivers of community composition. Plant species identity tended to dominate at local scale ( Leff et al., 2018 ) while plant community composition seemed more important at larger scale ( Prober et al., 2015 ) in terms of soil fungal community. However, there are few studies concerning the community determinants of root-associated fungal pathogens that regulate ecosystem functioning ( Bever et al., 2015 ). Revealing the relative importance of biotic and abiotic factors for such root-associated fungal pathogen communities could contribute to filling the research gap in belowground fungal communities. As mediators of plant interactions with pathogens, mycorrhizal fungi play a crucial role in plant productivity and community dynamics. There are two major mycorrhizal types in the study site Heishiding Nature Reserve, including arbuscular mycorrhiza (AM) and ectomycorrhiza (ECM). Arbuscular mycorrhiza exist in nearly 80% of plant species and tend to experience more negative feedback resulting from soil biota ( Kadowaki et al., 2018 ). In comparison, ectomycorrhizal plants show positive density dependence in temperate and subtropical forests ( Chen et al., 2019a ; Sasaki et al., 2019 ), probably due to more effective resistance to pathogens ( Tedersoo et al., 2020 ). Though many studies have confirmed the evolutionary and functional differences of these two major mycorrhizal types ( Brundrett and Tedersoo, 2018 ; Kadowaki et al., 2018 ), few studies have explored the effects of mycorrhizal type on host-associated microbiome ( Bahram et al., 2020 ; Liang et al., 2020 ), especially root-associated pathogens. Two processes simultaneously function in the formation of microbial communities, namely, deterministic and stochastic processes ( Ofiteru et al., 2010 ; Stegen et al., 2016 ). Deterministic processes imply that deterministic factors, such as species traits and environmental conditions, play a central role in community structure ( Chesson, 2000 ). Conversely, stochastic processes stress the importance of birth, death, colonization, extinction, and speciation ( Chave, 2004 ). Currently, their relative contribution to the formation of the microbial community is at the forefront of research ( Gao et al., 2020 ; Huo et al., 2023 ; Jiao et al., 2023 ). Many studies have confirmed the potential drivers of the fungal community assembly process ( Gao et al., 2020 ; Wang et al., 2022 ; Zheng et al., 2022 ), stressing the importance of global change and plant traits. However, less attention has been paid into the root-associated fungal pathogen community. Elucidating the assembly processes and underlying drivers of root-associated fungal pathogen community could help reveal the belowground microbial dynamics in the forests. Besides, understanding the effects of mycorrhizal type on root-associated pathogen community assembly, which could differentiate in alleviating negative density dependence ( Tedersoo et al., 2020 ), would provide essential insights into the mutualistic relationships in the forest community. In this study, we examined the impacts of abiotic and biotic factors, namely plant species identity, plant habitat, and plant mycorrhizal type, on the composition of the root-associated fungal pathogen community. We hypothesized that species identity and mycorrhizal type play more important roles on the fungal pathogen community than habitat conditions. Regarding the pathogen assembly mechanisms, we hypothesized that the relative importance of different community assembly process should vary with plant species identity and could be explained by the plant functional traits or plant phylogeny. The comparison of different community assembly process between AM plants and ECM plants should be in consistence with the findings at species level.",
"discussion": "4 Discussion The present study unveiled the effect of different factors on the root-associated fungal pathogen community composition, stressing the importance of plant species identity, plant habitat, and plant mycorrhizal type. In terms of the relative importance of community assembly process, species identity and plant mycorrhizal type could also explain the variations based on functional traits. We focused on abiotic environments and neighboring plants to explore the effects of plant habitat. In terms of abiotic environments, many studies have confirmed the corresponding effect in root-associated fungi ( Yu et al., 2013 ; Blaalid et al., 2014 ; Zhong et al., 2018 ), and our results showed that pH, SOM, TP, AP, and convexity had significant effects on root fungal pathogen community. Soil pH and organic matter are considered as two main factors in driving belowground microbiome ( Guo and Gong, 2014 ; Montiel-Rozas et al., 2017 ; Ballauff et al., 2021 ), and our study confirmed such widespread effects on the root-associated fungal pathogens. Regarded as the nutrient that most strongly limit the plant growth in the subtropical forest ( Condit et al., 2013 ; Liu et al., 2018 ), soil phosphorous was also testified to impose significant effect on the root-associated fungi in our study. Available phosphorous also functions in plant immunity ( Chan et al., 2021 ), which directly affects plant susceptibility to different pathogens. The potential role of convexity suggests the importance of topography when considering the factors affecting the belowground microbiome, which has been demonstrated for soil microbial activity and composition ( Taş et al., 2018 ; Chen et al., 2019b ; Fairbanks et al., 2020 ). The plant neighborhood is a great indicator of soil fungal composition, including pathogenic or mycorrhizal fungi ( Hubert and Gehring, 2008 ; Hantsch et al., 2014 ; Chen et al., 2018 ), and was confirmed as a significant determinant of root-associated fungal pathogens in our study, in which the basal area of conspecific adults played a major role. Based on the detailed dataset and comprehensive analysis, we emphasized that host habitat, including abiotic environments and neighboring plants, could explain root-associated fungal pathogens to some extent. Plant species identity has been demonstrated to play a significant role in root-associated fungal community when considering plant habitat or plant mycorrhizal type, indicating its dominant role among various determinants ( Botnen et al., 2020 ; Francioli et al., 2020 ). Based on the plant–pathogen interaction network, our findings confirmed host specificity for the root fungal pathogen community, which aligns with the finding from prior research ( Cheng and Yu, 2020 ). Understanding the mechanisms underlying community diversity is a central topic in ecology, especially in microbial ecology ( Zhou and Ning, 2017 ). Under the framework that infers community assembly mechanisms by phylogenetic bin-based null model analysis ( Ning et al., 2020 ), we quantify the relative importance of different community assembly process of the root-associated fungal pathogen community of nineteen species. Ecological ( Vivanco and Austin, 2008 ) and evolutionary ( Botnen et al., 2020 ) processes may be related to species identity, in which plant functional traits ( Leff et al., 2018 ) and plant phylogeny ( Barberan et al., 2015 ) serve as important indicators. Our results showed that rather than plant phylogeny, functional traits mediated the community assembly process. Traits associated with acquisitive resource-use strategy promoted homogeneous selection and weaken the effect of drift, while opposite direction was detected for traits associated with conservative resource-use strategy. Using comprehensive traits indexes, our findings supplemented the available knowledge on the relationships between plant traits and root-associated fungal pathogen community assembly, indicating combined effects from aboveground and belowground functional traits on root-associated fungal pathogens. In summary, our results indicated that plant traits rather than plant phylogeny could explain the effect of plant species identity on root-associated fungal pathogen community assembly. Owing to their association with plant nutrient acquisition strategies, mycorrhizal associations also influence plant resistance to soil-borne pathogens ( Tedersoo et al., 2020 ). In our study, plant mycorrhizal type accounted for the variations in root-associated fungal pathogen community, indicating host specificity for fungal pathogens at the mycorrhizal-type level. Many studies have stressed the effects of plant functional groups on soil-borne fungi ( Davison et al., 2020 ; Francioli et al., 2021 ; Sweeney et al., 2021 ), while less attention has been paid to the influence of plant mycorrhizal type, which also implies distinct functionalities in terms of habitat modification ( Tedersoo et al., 2020 ). In accordance with previous researches ( Valverde-Barrantes et al., 2018 ; De La Riva et al., 2021 ), our findings showed that ECM plants were associated with more conservative traits than AM plants, that is, lower LP, SSL and RN while higher RTD. Consistent with the relationship between functional traits and community assembly based on species level, stronger effect of drift and weaker homogeneous selection was detected in the root-associated fungal community assembly of ECM plants. This could also possibly be explained by the differences in mycorrhizal structure. Mycelium mantles are formed by ECM fungi surrounding the tips of roots ( Agerer, 1991 ), whereas AM fungi stimulate the deposition of root callose around infected root cells ( Pozo et al., 2002 ), which results in a greater physical barrier in the fine root of ECM plants. To be noted, weaker homogeneous selection or stronger drift could indicate the pathogen community with less similar composition, likely facilitating the escape from negative density dependence. Overall, our results provide new insights into the belowground microbial dynamics for different mycorrhizal plants, which associated with the differences in negative density dependence. Notably, functional classification of fungi through FUNGuild database ( Nguyen et al., 2016 ) could present potential problem caused by the DNA sequences-based prediction and the annotations at larger taxon. Despite the deficiency, the database has been widely adopted for functional classification( Chen et al., 2019a ; Delgado-Baquerizo et al., 2020 ; Liu et al., 2021 ). Subsequently, the actual pathogenicity of the potential fungal pathogen is highly dependent on the context, that is, the presence of other surrounding microbes ( Malik et al., 2016 ; Liu et al., 2023 ) and the environmental changes ( Liu and He, 2019 ; Tannous et al., 2020 ) could lead to variations in the pathogenicity. Future research should focus on how the context dependence could affect the association between fungal pathogen community and the actual pathogenicity, to provide more comprehensive insights into the interaction between forest plants and fungal pathogens. In conclusion, we explored the root-associated fungal pathogen community using high-throughput sequencing technology. Taking abiotic and biotic factors into account, we identified the roles of plant species identity, plant habitat, and plant mycorrhizal type in shaping the fungal pathogen community composition. Furthermore, we quantified the relative importance of different community assembly of the pathogen community at either species or mycorrhizal type level and highlighted the determinant roles of functional traits. Our findings also implied that the relative importance of homogeneous selection and drift could indicate negative density dependence, promoting our understanding of the belowground microbial dynamics that greatly impact forest community structure and ecosystem functioning."
} | 3,916 |
38091992 | PMC10752370 | pmc | 2,257 | {
"abstract": "Summary Microbial communities offer vast potential across numerous sectors but remain challenging to systematically control. We develop a two-stage approach to guide the taxonomic composition of synthetic microbiomes by precisely manipulating media components and initial species abundances. By combining high-throughput experiments and computational modeling, we demonstrate the ability to predict and design the diversity of a 10-member synthetic human gut community. We reveal that critical environmental factors governing monoculture growth can be leveraged to steer microbial communities to desired states. Furthermore, systematically varied initial abundances drive variation in community assembly and enable inference of pairwise inter-species interactions via a dynamic ecological model. These interactions are overall consistent with conditioned media experiments, demonstrating that specific perturbations to a high-richness community can provide rich information for building dynamic ecological models. This model is subsequently used to design low-richness communities that display low or high temporal taxonomic variability over an extended period. A record of this paper’s transparent peer review process is included in the supplemental information .",
"introduction": "Introduction Microbiome engineering holds tremendous potential for applications spanning human health to environmental remediation. 1 A key challenge toward realizing this potential is developing the capability to steer communities toward desired states. 2 Microbial communities are complex and dynamic systems, shaped by nonlinear interactions and feedback. 3 , 4 Control of such nonlinear dynamical systems toward desired states is a fundamental question that lies at the heart of many problems encountered in the field of engineering and is critical to harnessing the functional capabilities of microbiomes for a wide range of potential applications. 5 Precise control of microbiomes requires the ability to elucidate influential control parameters and predict temporal behavior as a function of these different inputs. 6 The ability to control microbial community dynamics could facilitate the development of defined combinations of human-associated intestinal isolates as next-generation bacterial therapeutics. 7 , 8 The beneficial properties of well-characterized mixtures of commensal strains could be optimized while simultaneously avoiding the drawbacks of fecal microbiota transplantation. 9 , 10 A key challenge toward this goal is the economical production of defined, therapeutic communities that span the phylogenetic and functional diversities of the healthy adult microbiome. 11 The current strain culturing process contributes substantially to this challenge, as constituent organisms of a community are typically grown as separate monocultures, and then subsequently mixed to a desired species composition. 12 This “monoculture-then-mix” process is complicated, costly, and scales poorly for communities with large numbers of organisms. 12 Implications of this economic barrier extend beyond commercial-scale profit margins: medical progress is slowed when pilot-scale drug supply bottlenecks clinical trials or global health applications become cost prohibitive. 11 , 12 , 13 Culturing communities in a single-vessel could circumvent high costs associated with the monoculture-then-mix approach but presents new challenges stemming from the fundamental question of community control. Leveraging model-guided approaches to predict community growth as a function of specific control inputs would greatly enhance our ability to manipulate community composition toward a desired state. 14 The Monod equation, and its ecological counterpart MacArthur’s consumer-resource model, is, in theory, well suited to describe the growth and metabolite dynamics likely to govern community assembly. 15 , 16 However, it is not trivial to identify and quantify many unknown metabolites driving constituent community member growth in an experimental system. 17 Even if all key resources were known and measurable, modeling these metabolites in addition to microbial species may lead to an intractable state space for parameter inference from experimental data in larger communities. 18 Finally, the consumer-resource model structure for a given system may not easily generalize to other environmental conditions or communities. Optimal design of experiments (DoE) is an approach that leverages informative experiments and statistical modeling to map key input-output relationships and has been increasingly used to engineer biological systems. 19 For example, DoE has been used to explore regulatory sequence space for modulating protein translation and tuning enzyme expression to optimize production of a target metabolite. 19 , 20 , 21 In addition, DoE was used to formulate a chemically defined media by optimizing microbial growth as a function of various media components. 22 , 23 Statistical modeling, an integral part of the DoE workflow, has been used to predict specific community-level functions from species abundance and community composition as a function of dietary inputs in the murine gut. 24 , 25 , 26 Dynamic ecological models, such as the generalized Lotka-Volterra (gLV) model, have been shown to be predictive of microbial community assembly in a particular media environment. 18 , 27 These studies suggest that statistical and ecological models can be integrated with experimental data to predict and design biological system behaviors. We investigate and exploit control points for microbial community assembly by combining high-throughput experiments and computational modeling. We develop a two-stage, model-guided approach for systematically tuning key media components and initial species densities to maximize the diversity of a 10-member human gut community in batch culture. Based on the hypothesis that monoculture growth kinetics contribute substantially to community assembly, we use a model-guided approach to design a culture medium to promote similarity in the growth responses of single species. This high-throughput, monoculture-based optimization procedure yields a concomitant improvement in community diversity in the designed medium. We then use a design-test-learn (DTL) cycle to systematically modulate individual species’ initial population sizes (i.e., inoculation densities) to further optimize community diversity in the new medium. Finally, we build a dynamic ecological model informed by our DoE-generated dataset that captures pairwise inter-species interactions. We demonstrate that pairwise interactions can be inferred from complex community data and are largely consistent with spent media experiments. This model is used to guide the design of communities with distinct classes of dynamic behaviors. Our generalizable framework provides a foundation for the data-driven control of defined microbial communities toward target compositional states.",
"discussion": "Discussion We currently lack a framework for designing interventions to precisely and predictably control microbial communities. 6 We demonstrate that despite their complexity, synthetic communities respond predictably to model-guided manipulation of media formulation and inoculation densities. Our results demonstrate that both media and inoculation densities are useful and complementary in steering communities to desired compositional states. Media factors determine the availability of metabolic niches, whereas inoculation densities can dictate the ability of species to secure the metabolic niches in a competitive environment either transiently or longer term. Data-driven dynamic and statistical modeling frameworks are developed for tuning these control points to optimize the endpoint Shannon diversity of a representative 10-member synthetic gut community to 91% of its maximum possible value ( Figure 3 F). In each stage of the workflow, we exploit high-throughput, monoculture experiments to first characterize the “parts” of our microbial ecosystem and show that this information is useful for guiding community design. Based on the notion that monoculture growth is an influential variable in community assembly, we demonstrated that maximizing monoculture diversity as a function of media components substantially increased community diversity. The competition-based CSLE model informed by monoculture kinetics made useful predictions of inoculation densities that enabled efficient optimization of Shannon diversity using a DTL cycle ( Figures 1 I and S3 J). Understanding what features of microbial communities can be predicted from monoculture information is a key scientific question in the microbiome field. If monoculture information can forecast specific community-level properties, highly automated approaches for parallelized culturing could be exploited to inform the design of communities with desired functions. For example, synthetic human gut communities of ∼100 members are now being studied in vitro and in vivo . 55 Although we selected a limited number of simple media control points, more complex resources such as fibers, peptones, and mucins have been shown to support high-richness communities from stool sample inocula. These media factors could be manipulated to expand the number of metabolic niches and tune species abundances in larger communities. 56 , 57 Central to our approach was mapping control inputs to outputs without the need for characterizing detailed biochemical mechanisms specific to a particular system (e.g., uptake and production kinetics of specific metabolites mediating interactions). Therefore, our model-guided strategy should generalize to a wide range of synthetic communities and media environments. Furthermore, although we focused on optimizing Shannon diversity as our objective function, our framework could be applied to design communities with tailored compositions or target functions (e.g., production of key health-relevant metabolites). One limitation of our approach is that species with very low fitness in the community may not achieve a target abundance even with a high inoculation density. Future efforts could leverage the gLV model-guided design of multiple inoculation timings as an additional control point for endpoint community composition. For example, a species like BL that does not grow well in certain community contexts due to negative interactions could be given a “head start” by inoculating at an earlier time point. As a proof of concept that inter-species interactions can be leveraged to design temporal behaviors, we used a data-driven gLV model to guide the design of communities with low variability of species composition over time ( Figures 5 B and 5C). Theoretical analyses of the gLV model tend to investigate qualitative long-term behaviors (e.g., exclusion, stable steady states, or limit cycles) to which many different initial conditions converge. 3 By contrast, the measured endpoint community composition of batch culture does not necessarily represent a system’s stable steady state (e.g., a composition that does not change as a function of time in continuous culture or over multiple passages). This endpoint community composition measurement was nonetheless predicted quite accurately by fitting non-equilibrium trajectories of the model to experimental data ( Figure 4 B). Therefore, although our gLV model has constrained steady states that may not match the experimental system, it can still be used to design community compositions in batch culture as a function of initial conditions by exploiting the flexible transients of the model. The merits of different mathematical modeling approaches for microbial communities have aptly garnered much attention. 14 With experimental systems like synthetic communities, a consideration of perhaps equal importance is “what data should be collected to inform the model?” The use of automated liquid handling to array synthetic communities according to optimal experimental designs (DoE) offers a practical approach for efficiently exploring these high-dimensional biological systems. Although the DoE framework has typically been implemented with linear models, this approach may broadly benefit parameter inference for other models used to study microbial communities. Bayesian experimental design approaches could be used in future work to leverage parameter and prediction uncertainty to maximize the information from limited experiments using DTL cycles. 58 Furthermore, machine learning models like recurrent neural networks are flexible to various inputs and outputs and could be used to design community dynamics and functions using initial species abundances and key resources as simultaneous control points. 59 Defined microbial communities hold great promise for many applications including sustainable agriculture, production of valuable compounds from renewable resources, and precision and personalized medicine. 60 Our systematic approaches for community control could be adapted as bioprocess engineering strategies to manufacture defined consortia as therapeutics in a scalable fashion. These methods could also be used to tune community member proportions and optimize key metabolite outputs for industrial bioprocessing in which metabolic pathways are distributed across community members to exploit the benefits of division of labor. 52 , 61 Eventually, the ability to identify and influence analogous control parameters for microbiome composition and function could be used to steer a patient’s dysbiotic microflora toward a healthy state. Similar to media formulation, changes in diet are well documented to shape gut microbiome composition. 62 Dosage (analogous to inoculation density) was a critical factor in the successful redesign of the first phase three clinical trial of a donor-derived live bacterial therapeutic for treating recurrent C. difficile infection. 63 Overall, initial population densities (i.e., dosage), environmental resources, and inter-species interactions should be considered key control parameters for the model-guided design of microbial community dynamics and functions."
} | 3,548 |
28820506 | PMC5649172 | pmc | 2,260 | {
"abstract": "Chemosynthetic Fe-oxidizing communities are common at diffuse-flow hydrothermal vents throughout the world’s oceans. The foundational members of these communities are the Zetaproteobacteria, a class of Proteobacteria that is primarily associated with ecosystems fueled by ferrous iron, Fe(II). We report here the discovery of two new isolates of Zetaproteobacteria isolated from the Mid-Atlantic Ridge (TAG-1), and the Mariana back-arc (SV-108), that are unique in that they can utilize either Fe(II) or molecular hydrogen (H 2 ) as sole electron donor and oxygen as terminal electron acceptor for growth. Both strains precipitated Fe-oxyhydroxides as amorphous particulates. The cell doubling time on H 2 vs Fe(II) for TAG-1 was 14.1 vs 21.8 h, and for SV-108 it was 16.3 vs 20 h, and it appeared both strains could use either H 2 or Fe(II) simultaneously. The strains were close relatives, based on genomic analysis, and both possessed genes for the uptake NiFe-hydrogenase required for growth on H 2 . These two strains belong to Zetaproteobacteria operational taxonomic unit 9 (ZetaOTU9). A meta-analysis of public databases found ZetaOTU9 was only associated with Fe(II)-rich habitats, and not in other environments where known H 2 -oxidizers exist. These results expand the metabolic repertoire of the Zetaproteobacteria, yet confirm that Fe(II) metabolism is the primary driver of their physiology and ecology.",
"introduction": "Introduction Ferrous iron is an important driver of chemosynthetic or chemolithoautotrophic microbial ecosystems at both deep and shallow marine hydrothermal vents, and it is now well documented that specialized communities adapted for microaerobic growth on Fe(II) thrive at these vents ( Kato et al. , 2012 ; Hoshino et al. , 2016 ). A number of Fe-oxidizing bacteria (FeOB) produce organo-metallic filamentous Fe-oxides to construct a woven fabric mat that provides enough structural integrity for colonization by other microbes ( Chan et al. , 2016 ). The population structure of active marine iron mats is dominated by members of the Zetaproteobacteria, one of the seven officially recognized classes of Proteobacteria ( Makita et al. , 2016 ). In general, the Proteobacteria are well known for the remarkable breadth of their metabolic diversity, and the different classes of Proteobacteria occupy a wide variety of both oxic and anoxic niches, where they are often conspicuous for their high relative abundances. The Zetaproteobacteria are unique in this sense, as they are only found associated with marine systems, or ancient marine sediments, where Fe(II) is a prevalent electron donor ( McAllister et al. , 2011 ; Scott et al. , 2015 ). Thus, the Zetaproteobacteria are more metabolically specialized than the other classes of Proteobacteria, with the exception of the class Acidithiobacillia, which are obligate iron or sulfur utilizers, but restricted to acidic environments ( Williams and Kelly, 2013 ). Consistent with the Zetaproteobacteria being specialists for Fe(II)-based lithotrophy, thus far all the known isolates are obligate Fe-oxidizers that prefer microaerobic conditions. This makes the Zetaproteobacteria a compelling group of organisms for understanding how aspects of phylogenetic diversity contribute to functional unity. The Fe(II)-rich ecosystems of these FeOB inhabit are almost exclusively associated with lower temperature (<100 °C) diffuse vents. The cumulative contribution of diffuse hydrothermalism to the biogeochemical cycling of elements at the seafloor may be as great, or greater than at high-temperature vents ( Wankel et al. , 2011 ; Resing et al. , 2015 ). Nonetheless, the microbiology and geochemistry of diffuse-flow systems is not as well studied as high temperature, focused flow vents most typified by black smokers. In theory, lower temperature vents offer greater niche-space for colonization by diverse microbial communities. The thermal gradients in diffuse-flow systems are less extreme; therefore, they encompass a spatially larger habitable zone that can include the subsurface ( Orcutt et al. , 2011 ). As a result, they may offer heterogeneous gradients of electron donors and acceptors to support diverse microbial ecosystems. Previous studies have shown that the diversity of Zetaproteobacteria phylotypes is as great, or greater, within a particular vent site than it is between vent sites separated by large geographical distances ( Davis and Moyer, 2008 ; McAllister et al. , 2011 ; Scott et al. , 2015 ). Other recent studies showed that physicochemical differences in temperature, oxygen and Fe(II) concentrations, as well as hydrodynamics played an important role in shaping the community structure of microbial iron mats ( Fullerton et al. , 2017 ; Scott et al. , 2017 ). What is not known is how metabolic differences—specifically the ability to utilize alternative electron donors to iron or for that matter alternative electron-acceptors—drives community diversity, and whether Zetaproteobacteria are all obligate Fe oxidizers. Here, we describe two new isolates of Zetaproteobacteria that come from quite different hydrothermal systems at nearly opposite sides of the Earth. These two strains are close phylogenetically and share many phenotypic attributes including the ability to use H 2 in addition to Fe(II) as their sole electron donor, thus expanding the metabolic repertoire of the Zetaproteobacteria.",
"discussion": "Discussion Previous isolates of marine FeOB have all been obligate Fe-oxidizers, thus TAG-1 and SV-108 are the first Zetaproteobacteria shown to grow microaerobically on H 2 as an alternative substrate. Phylogenetic analysis of conserved genes as well as comparative genomics clearly shows these two strains are not closely related to other isolates belonging to the Zetaproteobacteria. Furthermore, they do not produce any identifiable extracellular organo-metallic structures such as stalks, sheaths or organized filaments that are characteristic of other known marine FeOB. Consistent with a lack of stalk production, TAG-1 and SV-108 do not possess the putative genes for stalk-formation ( xag operon), although these are conserved in the genomes of several Mariprofundus species ( Kato et al. , 2015 ). Presumably these two strains produce a different type of exopolymer that prevents them from becoming encrusted in Fe-oxides, as has been proposed for several, non-stalk forming freshwater FeOB ( Emerson et al. , 2013 ). Despite coming from hydrothermal vents on opposite sides of the world, the two isolates share most of their genes in common and their genomes have substantial regions of synteny. Together these results demonstrate TAG-1 and SV-108 represent a novel genus within the Zetaproteobacteria, and the name ‘ Ghiorsea bivora’ is proposed. Metabolism Thermodynamically H 2 is a better energy source than Fe(II) with a moderately higher free energy, Δ G °=−237 kJ mol −1 (−474 kJ per mol O 2 reduced) for H 2 vs Δ G °=−90 kJ mol −1 for Fe(II) (−360 kJ per mol O 2 reduced) ( Emerson et al. , 2010 ). The doubling times of TAG-1 and SV-108 were 55.0% and 23.2% more rapid for H 2 -grown cells compared to Fe(II)-grown cells, respectively, and cell yields were marginally higher on H 2 compared to Fe(II) ( Figure 2a ). While we could not totally account for auto-oxidation of Fe(II) in the substrate utilization experiments, it appeared both substrates were consumed simultaneously, indicating these organisms are not adapted to preferentially use either Fe(II) or H 2 , despite H 2 being the more energetically favorable electron donor. Both strains share nearly identical suites of genes involved in H 2 metabolism that include the canonical genes for the oxygen-tolerant, membrane-bound H 2 -uptake NiFe-hydrogenase ( Greening et al. , 2016 ). These proteins contain signal sequences and are presumably located in the periplasm where they can initiate H 2 oxidation coupled to energy conservation via the electron transport chain. The phylogenetic analysis of the large subunit of the hydrogenase revealed that two SAG genomes belonging to ZetaOTU9 (SCGC AB-706_B05 and SCGC AD-336-F10) also contain uptake NiFe-hydrogenase ( Figure 5 ). Together these genes from the Zetaproteobacteria fall into a diverse cluster of related genes in the Gammaproteobacteria, with the closest relatives coming from lithotrophic sulfur-oxidizing bacteria ( Figure 6 ). This raises the possibility that H 2 oxidation was acquired through different horizontal gene transfers. Regarding iron oxidation, we still lack definitive evidence as to how FeOB conserve energy from Fe(II) oxidation ( White et al. , 2016 ); however, these two strains illustrate the diversity of specific pathways that are likely involved in this process. Both strains have a gene homolog to Cyc2 PV-1 that a recent proteomic analysis indicated could be an important outer membrane cytochrome that may initiate iron oxidation. The Cyc2 homologs encoded by TAG-1, SV-108 and an SAG belonging to ZetaOTU9 (SCGC AD-336-F10) show high gene homologies ( Supplementary Figure S7 ). Neither strain however, possesses a gene homologous to the Cyc1 PV-1 , a soluble cytochrome that has been suggested to play a role in shuttling electrons across the periplasm in M. ferrooxydans . Both strains have the capacity to produce the different complexes of the electron transport chain; however, TAG-1 does not have a cytochrome bc1 complex (complex III), although it does have the AC-III, while SV-108 does not have AC-III but does have the cytochrome bc1 complex III. Unlike most of the other FeOB genomes, neither strain has the cytochrome bd complex that encodes a terminal oxidase with high oxygen affinity that can couple directly with the quinone pool. In both strains, complex IV, the terminal oxidase of the electron transport chain, is encoded by a single gene cluster ccb 3 -type cytochrome oxidase. This is in contrast to M. ferrooxydans that has this same gene cluster, but also has a second cluster of genes that encode a ccb 3 -type cytochrome oxidase. Proteomic analysis showed that this second cytochrome oxidase was the most highly expressed in M. ferrooxydans ( Barco et al. , 2015 ). Somewhat surprisingly, TAG-1, but not SV-108, also has a gene cluster that includes the coxA (DM09DRAFT_0178) and coxB (DM09DRAFT_0179) genes encoding an aa3-type terminal cytochrome oxidase with lower affinity for oxygen. Thus far, TAG-1 is only genome from an FeOB isolate that has this cytochrome oxidase, although it is present in SAGs and metagenomes of Zetaproteobacteria ( Fullerton et al. , 2017 ). Based on this genomic analysis, we hypothesize that TAG-1 may exhibit more flexibility regarding its ability to grow and survive under higher or more dynamic oxygen concentrations. A related aspect is the capacity for these organisms to defend against reactive oxygen species such as hydrogen peroxide (H 2 O 2 ) and super-oxides. This is especially relevant given that Fenton chemistry involves the reaction of H 2 O 2 with Fe(II) to produce hydroxyl radicals that are extremely damaging to cellular organic matter ( Imlay, 2008 ). Somewhat surprising then is that in the genome of SV-108, neither catalase or superoxide dismutase was found, while TAG-1 had a catalase-peroxidase gene (DM09DRAFT_0584) but also lacked superoxide dismutase ( Supplementary Table S6 ). Superoxide dismutase is a ubiquitous gene in aerobic organisms, and is even found in many anaerobes ( Hewitt and Morris, 1975 ; Imlay, 2008 ). Thus far, the sequenced genomes of all other FeOB have contained superoxide dismutase ( Mumford et al. , 2016 ). For defense against H 2 O 2 production, both TAG-1 and SV-108 contain two copies of a cytochrome c -peroxidase gene. Cytochrome c -peroxidase is excreted to the periplasm, and may act as a defense mechanism against exogenously produced H 2 O 2 . The most abundant genes involved in reactive oxygen species protection for both strains were peroxiredoxins (TAG-1=4 copies; SV-108=5 copies; Supplementary Table S6 ) that utilize a thiol-based mechanism to react with H 2 O 2 in the cytoplasm. Presumably it is this mechanism that is the primary defense for reactive oxygen species in TAG-1 and SV-108. It should be noted, however, that our results cannot eliminate the possibility of either mis-annotation of functional genes, or that a gene is missing from these near complete, but not finished genomes. Some physiological capabilities of TAG-1 and SV-108, such as oxygen tolerance and utilization of nitrogen-species, still have to be evaluated via further cultivation-based tests. Ecological implications All previous isolates of Zetaproteobacteria have been obligate Fe-oxidizers, so the discovery of these two H 2 -utilizing strains adds a new dimension to the physiology of this group. Because the Zetaproteobacteria are phylogenetically differentiated from other Proteobacteria at the class level, we are able to effectively track individual OTUs within them ( McAllister et al. , 2011 ). TAG-1 and SV-108, as well as the two SAGs that also had uptake hydrogenase genes ( Figure 5 ) belong to ZetaOTU9; however, none of the other genomes of Zetaproteobacteria, either from pure cultures, SAGs, or metagenomes have these hydrogenase genes, suggesting that growth on H 2 may be a trait only found in ZetaOTU9. When analyzed relative to the dominant ZetaOTUs in a variety of chemosynthetic iron communities, the overall abundance of ZetaOTU9 is often at background levels of <0.1% of the community. However, in samples where its abundance is >1%, it is often a dominant phylotype of the Zetaproteobacteria. For example, among vent sites at the MAR, ZetaOTU9 was prevalent in five samples (two from TAG, two from Snakepit, one from Rainbow), accounting for 60–95% of Zetaproteobacteria reads, but made-up less than 5% of the reads in three other samples (one each from TAG, Snakepit and Rainbow; Scott et al. , 2015 ). At the Mariana, as mentioned in the results, ZetaOTU9 was in low abundance at the Snail Vents where SV-108 was isolated. However, in a broader survey of chemosynthetic iron mats along the Mariana Arc and back-arc, ZetaOTU9 accounted for >5% of the Zetaproteobacteria reads in 6 of 21 discrete samples from 5 different sites. At one of these sites ZetaOTU9 accounted for 75% of the total Zetaproteobacteria reads ( Hager et al. , 2017 ). An extensive survey of iron mats at L-ō‘ihi Seamount, found ZetaOTU9 was only present in veil-like mats that are structurally dominated by sheath-forming Zetaproteobacteria ( Scott et al. , 2017 ). In addition to being abundant on fresh basalts ( Henri et al. , 2016 ) as noted above, other sites where ZetaOTU9 is abundant are mild steel coupons incubated in coastal seawater ( McBeth and Emerson, 2016 ), and in the subsurface of the ocean crust ( Kato et al. , 2009 ). These latter habitats are locales where H 2 may be present. On steel, ZVI, given the right conditions, can react with seawater to produce H 2 , and in the subsurface water–rock reactions may generate H 2 . The capacity to use H 2 as a sole electron donor would certainly give strains like TAG-1 and SV-108 a competitive advantage over obligate Fe(II)-oxidizers. Unfortunately, it has not been possible to obtain H 2 measurements from the iron mats where ZetaOTU9 was abundant. It is worth pointing out, however, that samples from the MAR, L-ō‘ihi, and the Mariana were all collected at high (sub-centimeter) spatial resolution, thus the corresponding presence and absence of ZetaOTU9 with specific samples that in some cases were only a few centimeters apart, indicates that there may be chemical (e.g., the presence of H 2 ), mineralogical and/or physical drivers that may be controlling their population dynamics. This underscores the importance of being able to collect relevant physicochemical data at spatial scales that can be co-registered with community analysis, so fundamental drivers of microbial diversity are revealed. The IMNGS meta-analysis included a number of sites where H 2 is likely present as a potential energy source, such as sediments and hydrothermal vent communities, but where the abundance of Fe(II) is insufficient to support Fe(II)-fueled chemosynthesis. This indicates that despite having the metabolic flexibility of being able to use H 2 in addition to Fe(II), TAG-1 and SV-108, and by extension ZetaOTU9, are still limited to Fe(II)-rich habitats. Thus the adaptations required to grow on Fe(II) likely play a stronger role in selection than the capacity to grow on H 2 . There can be appreciable fluxes of H 2 -associated diffuse venting systems, and the dynamics of these fluxes indicate there is significant microbial metabolism of H 2 ( Wankel et al. , 2011 ). The discovery that this particular clade of FeOB that grow as well or better on H 2 than Fe(II) supports this finding, and indicates the Zetaproteobacteria contribute to chemosynthesis in these systems via H 2 utilization in addition to iron oxidation. A similar role has been suggested for chemolithoautotrophic sulfur-oxidizing bacteria like Thiomicrospira ( Hansen and Perner, 2015 ). Taxonomy TAG-1 and SV-108 represent the most unique isolates within the Zetaproteobacteria discovered to date. We propose they form a novel genus and species, thus representing the second genus and third species within this class. Description of Ghiorsea gen. nov. Ghiorsea gen. nov. (Ghi.or.se.a. N. L. fem. n. Ghiorsea, named after contemporary American microbiologist William C Ghiorse, in recognition of his important contributions to the field of geomicrobiology. Gram-negative rod-shaped cells. Growth is obligately lithotrophic, oxygen-dependent, and requires marine salts; habitat, marine microbial iron mats. The type species is: Ghiorsea bivora gen. nov. sp. nov. Description of Ghiorsea bivora sp. nov . G. bivora (bi.vor.a, L. prefix bi two; L. comb. –vora, ones that eat; N.L. n. bivora one that eats two substrates). Displays the following properties in addition to those given by the genus description. The cells are rods, approximately 0.3 × 1.5–2 μm. Motility is often observed. Lithotrophic growth on either ferrous iron or on hydrogen gas under microaerobic conditions. Result of growth on ferrous iron is the precipitation of iron-oxyhydroxides with no determinant structure. No observable growth on organic compounds; elevated concentrations of organics may be bacteriostatic. The optimum growth temperature is 20 °C. The pH range for growth is 6.0–7.0. The G+C content of the DNA is 43.7%. The type strain is TAG-1 T (=DSMZ 103937; =JCM 31637;=NCMA B5; IMG genome identification number 2582580733) isolated from an iron-rich microbial mat associated with diffuse hydrothermal venting at the TAG hydrothermal vent site on the MAR."
} | 4,714 |
39739802 | PMC11725925 | pmc | 2,261 | {
"abstract": "Significance Symbioses have evolved in all lineages of the tree of life. Among them, the arbuscular mycorrhizal symbiosis (AMS) evolved in the first plants that colonized land 450 million years ago. The mechanisms that have allowed this very ancient symbiosis to evolve and to be maintained remain poorly described. Here, we demonstrate that Marchantia paleacea shares a signaling pathway with flowering plants. This strongly suggests that all extant land plants share this pathway for activating a dedicated genetic program in the presence of the arbuscular mycorrhizal symbiont. Like in flowering plants, deleting this pathway in M. paleacea is sufficient to completely abolish symbiosis. We propose that plants have maintained a signaling pathway to support symbiosis for 450 million years.",
"discussion": "Discussion This work demonstrates that the three main CSP components SYMRK/DMI2, CCaMK/DMI3, and CYCLOPS/IPD3 are essential for AM symbiosis in the liverwort M. paleacea ( Figs. 2 – 4 ), as described over the last two decades for angiosperms. To explain this conserved role, the most parsimonious hypothesis suggests that the most recent common ancestor of the angiosperms and the bryophytes already used the CSP to engage and associate with AM fungi. In other words, together with the recent description of the role played by the fourth CSP gene, DMI1 , in AMS in M. paleacea ( 29 ) our data indicate that land plants have relied on a conserved symbiotic signaling pathway since their most recent common ancestor. From a symbiotic perspective to an evo-devo one, this finding opens up a number of questions. Overexpression of CYCLOPS and CCaMK gain-of-function versions (CYCLOPS-DD and CCaMK-Kin) led to significant, and overlapping, gene induction in M. paleacea ( Fig. 5 ). When comparing the list of DEGs in response to the overexpression of CYCLOPS-DD or CCaMK-Kin with the DEGs during AMS in M. paleacea the overlap differs. Such a difference might come from the more upstream position of CCaMK in the CSP which goes through CYCLOPS but also alternative side pathways to be described. Illustrating these bifurcations in the CSP, two Cyclin-dependent Kinase-Like (CKL1 and CKL2) acting downstream of DMI2/SYMRK and LysM-RLKs, but independently of CCaMK or CYCLOPS, have been described in the angiosperm M. truncatula ( 30 ). In addition to these bifurcations in the CSP, the gain-of-function approach did not lead to the induction of the entire AMS transcriptomic response. It is likely that numerous genes under direct or indirect control of the CSP were not captured by the gain-of-function approach because of missing coregulators, such as the GRAS transcription factors NSP1, NSP2, or DELLA ( 31 , 32 ). In addition, the CSP is under control of feedback loops that likely modulate the expression of the AMS-related genes, such as the phosphate starvation response via PHR1/2 ( 33 , 34 ). Phylogenomic analyses pointed out two directions that remain poorly explored. First, CCaMK, CYCLOPS, and a pro-ortholog of SYMRK are all present in streptophyte algae, thus predating the origin of AMS ( 35 ). Recent coexpression network analyses in the streptophyte alga Zygnema circumcarinatum indicate that the three genes may belong to separate pathways in algae ( 36 ). In that case, they would have assembled in a unified pathway after the divergence between Zygnematophyceae and land plants. Alternatively, the pathway was already formed, although each component was transcriptionally regulated in different ways as seen in extant Zygnematophyceae, and was directly recruited, exapted, as a whole during the evolution of AMS. Besides its origin and the recruitment for AMS, comparative phylogenomics indicated that, subsequently, the CSP may have been co-opted for other intracellular symbioses with diverse fungi and nitrogen-fixing bacteria ( 15 ). Genetics in legumes support this hypothesis for the root-nodule symbiosis ( 6 ). Here, we show that the CYCLOPS response element, CYC-RE pro , previously identified in the promoter of the root-nodule symbiosis-specific gene NIN ( 12 , 19 ) is a reporter of CYCLOPS activation and of intracellular symbiosis outside of the root-nodule symbiosis context. Trait evolution is often mediated by the rewiring of existing gene regulatory networks, rewiring resulting from gene losses/gains, protein neofunctionalization, or gains and losses of cis -regulatory elements ( 37 ). Exploring further the rewiring of cis- regulatory elements downstream CCaMK-CYCLOPS that allowed plant lineages to transition from one symbiotic type to another represents the next challenge to be addressed. Recent evo-devo studies conducted using Marchantia polymorpha by comparison with knowledge in angiosperms demonstrated that plant immunity mechanisms used by extant land plants were likely present in their most recent common ancestor. Indeed, reverse genetic approaches demonstrated that LysM-RLKs confer in both M. polymorpha and angiosperms the ability to perceive fungal chitin, and other microbe-derived polysaccharides, leading to the activation of plant defense responses ( 38 ). Downstream chitin perception, the PBL-RBOH cascade, described in angiosperms, is also essential to trigger defense responses such as ROS bursts in M. polymorpha ( 39 ). With the lack of very ancient fossils, reconstructing the morphology and biology of the first land plants is currently impossible. Despite this gap in our knowledge, the recent discoveries on plant immunity and the work presented here collectively indicate that 450 million years ago the first land plants were already able to regulate the interactions with their microbiota using specific signaling pathways."
} | 1,430 |
28337848 | null | s2 | 2,263 | {
"abstract": "Recombinant protein design allows modular protein domains with different functionalities and responsive behaviors to be easily combined. Inclusion of these protein domains can enable recombinant proteins to have complex responses to their environment (e.g., temperature-triggered aggregation followed by enzyme-mediated cleavage for drug delivery or pH-triggered conformational change and self-assembly leading to structural stabilization by adjacent complementary residues). These \"smart\" behaviors can be tuned by amino acid identity and sequence, chemical modifications, and addition of other components. A wide variety of domains and peptides have smart behavior. This review focuses on protein designs for self-assembly or conformational changes due to stimuli such as shifts in temperature or pH."
} | 200 |
34753311 | PMC8580440 | pmc | 2,264 | {
"abstract": "Biological collectives, like honeybee colonies, can make intelligent decisions and robustly adapt to changing conditions via intricate systems of excitatory and inhibitory signals. In this study, we explore the role of behavioural plasticity and its relationship to network size by manipulating honeybee colony exposure to an artificial inhibitory signal. As predicted, inhibition was strongest in large colonies and weakest in small colonies. This is ecologically relevant for honeybees, for which reduced inhibitory effects may increase robustness in small colonies that must maintain a minimum level of foraging and food stores. We discuss evidence for size-dependent plasticity in other types of biological networks.",
"introduction": "1 . Introduction Researchers have long noted that colonies of eusocial organisms, like honeybees, behave collectively as part of a superorganism (the colony) similarly to cells within a multicellular organism [ 1 – 4 ]. As in many other biological systems, members of honeybee colonies make contact with only a few others in a given span of time, are distributed across space and are heterogeneous with respect to a number of parameters. Each bee makes decisions based on locally available information in accordance with its unique responsiveness to that information, which is a function of both internal factors, such as genetics and motivational state, and external factors, like the quality of a particular food source. The outcome of decisions is shared via excitatory or inhibitory signals with a few close neighbours [ 4 – 8 ]. Honeybees use the excitatory waggle dance to recruit hivemates to favourable resources, such as food sites [ 9 ]. However, if a forager is attacked at a food source or experiences deteriorating conditions, it returns to the nest and produces weakly inhibitory stop signals directed at dancers advertizing that location [ 10 – 12 ]. Stop signals elicit a brief pause from waggle dancers and reduce the probability that a waggle dancer will continue waggle dancing. Individual stop signals have a low associated probability of completely halting a waggle dance. However, they cumulatively inhibit recruitment [ 12 , 13 ]. The interplay between waggle dances and stop signals allows honeybee colonies to make collective decisions that have intriguing emergent properties [ 14 – 16 ]. For example, when a potential nest site is being advertized, the colony must rapidly coalesce around the correct decision. Dancers for different nest sites compete, with the longest lasting dance performances winning out. However, between dances, the dancers also perform stop signals that target dancers for different nest sites. The resulting cross-inhibition shortens the dancing process, allows the colony to more rapidly choose the best site, and increases the reliability of this system by overcoming deadocks—all without any central director [ 15 ]. Honeybee colonies respond to changing conditions, such as food availability outside and inside the nest. Foraging patterns shift throughout the day and across seasons in response to changes in floral availability and the risk of foraging on these resources. We propose that honeybee colonies can modify their reactions to unfavourable conditions in the environment, depending on multiple factors. We postulate that the mechanism for this threshold is experience-dependent plasticity in the sensitivity of individuals to stop signals. Specifically, we predict that the more stop signals received by an individual, the less responsive it becomes to future signals as a result of behavioural habituation [ 17 ]. The logic underlying this prediction, at the colony level, is that it would not be beneficial for colonies to curtail recruitment to all sites at times when every site is unfavourable to some degree (such as during times of high predator presence at most food resources). At these times, colonies should have a high level of stop signalling. Other arthropods habituate to vibrations [ 18 , 19 ]; although to our knowledge, habituation to an intraspecific vibrational communication signal has not been investigated. Honeybees habituate to other biologically relevant stimuli, such as antennal stimulation with sucrose [ 20 ], and bumblebees habituate to novel visual stimuli after repeated exposure during foraging [ 21 ]. Our preliminary observations suggested that honeybees can become unresponsive to stop signals, perhaps as a result of habituation (see electronic supplementary material). Due to the significant limitation that stop signals need to be identified using both behavioural and acoustic characteristics [ 22 ], it is difficult to estimate, in a typical colony with thousands of individuals, if and how stop signalling levels change over time. Colony-wide automated vibration detection is a useful tool, but noise and the conflating factors of multiple signals sharing similar spectral properties can limit such detection [ 22 , 23 ]. However, Smith & Chen [ 24 ] demonstrated that the overall level of detectable vibrational signalling is inversely related to colony size. We analysed data from a separate colony survey study, and found that colony size and stop signalling were inversely related when we controlled for the level of activity of the colony (see Material and methods). Therefore, manipulating colony size gives us a straightforward, ecologically relevant way to manipulate stop signalling. We hypothesize that honeybee colonies of different sizes are differentially reactive to stop signals because the level of signalling to which each individual bee is exposed—and thus how sensitive each bee is to stop signals—depends on colony size. To test this hypothesis, we measured the effect of artificially generated stop signals on the level of waggle dancing in honeybee colonies of varying sizes. We predicted that waggle dancers in smaller colonies would be less responsive and should, therefore, exhibit less waggle dancing inhibition when compared with waggle dancers from larger colonies, when exposed to the same level of artificial stop signalling.",
"discussion": "4 . Discussion and conclusion Our finding that large colonies were more sensitive to the inhibition provided by stop signalling, when compared with small colonies, is somewhat counterintuitive. However, the specific threat posed by predators or a deteriorating food source to a honeybee colony depends on a number of factors, including how large and well established the colony is. For example, a larger colony might only be marginally affected by curtailing foraging at a dangerous or crowded site that is otherwise profitable, because it has sufficient foragers to cover multiple sites, and enough food stores to buffer against variable rates of resource intake. By contrast, ceasing foraging at a dangerous or deteriorating site might be more costly for a small colony with few foragers available to locate and exploit alternative food sources and less food stores. Although we did not quantify food stores in our colonies and cannot completely rule out this possibility, it is unlikely that the observed changes in waggle dance inhibition were directly driven by the level of stored pollen or nectar. All of our colonies were three-frame observation colonies with little space in which to accumulate food stores. Of the photos we took in which the comb is not totally obscured by bees, no colonies had amassed more than 1/3 frame of pollen or capped honey. In nature, honeybee colonies reproduce by colony fission, with a fraction of the colony, the swarm, leaving to found a new colony [ 30 ]. Colonies thus begin small with essentially no food stores—a relatively perilous state of affairs because small disturbances such as being unable to locate a profitable foraging site on any given day can have major consequences. Small colonies must expand to the point that enough workers are available for all basic tasks (e.g. brood-rearing) before foragers are able to generate the food surpluses that buffer against variable rates of resource intake. In fact, research and modelling demonstrates that colonies need a minimum size to survive [ 30 ]. Our finding that weak or small colonies should resist switching away from foraging at dangerous or crowded locations more than strong colonies aligns with the information primacy hypothesis [ 31 ], and hungry bees have been shown to favour exploitation over exploration [ 32 ]. To protect against the outsized influence of perturbations, individuals in small colonies could become less responsive to signals that inhibit foraging, such as stop signals. For small colonies with little or no food stores, any inhibition on foraging might put the survival of the colony at risk, even if the site is suboptimal, and particularly if the site was initially sufficiently favourable to elicit waggle dancing. As the colony becomes larger and their food stores more established, becoming more sensitive to stop signals may allow the colony to optimize its foraging to take advantage of only the most profitable locations. 4.1 . A widespread phenomenon? All biological systems are capable of adaptation , the capacity to respond to changing conditions. Although much remains unknown, network-level adaptation has been most thoroughly investigated in nervous systems, in which adaptation arises, in part, from plasticity in neural synaptic connections. Multiple synapse types have properties that change in response to increased or decreased frequency of signal transmission between neurons across various timescales, and these changes can result in either increased or decreased synaptic efficacy [ 33 ]. Recent work in statistical mechanics suggests that large, sparsely coupled artificial networks are more robust (less reactive) than small, sparsely coupled networks [ 34 ]. However, there is at least one key difference between these types of networks and biological networks: plasticity in the connections between the nodes. Some neuroscientists have argued that synaptic plasticity, because it represents change, is necessarily distinct from and antithetical to nervous system stability [ 35 ]. However, others have recognized the role of plasticity as a homeostatic mechanism for maintaining network-level stability [ 36 , 37 ]. For example, acquired drug tolerance has been hypothesized to result from nervous system plasticity meant to maintain consistent levels of neurotransmitter system activity but now inappropriately influenced by exogenous ligands [ 38 ]. Although others have described context-dependent plasticity in biological networks, such as socially mediated behavioural plasticity in groups [ 39 – 41 ], to the best of our knowledge, no one has previously considered that network size might drive plasticity in the network elements themselves. Intriguingly, larger bumblebee colonies have been observed to respond more quickly to perturbations of in-hive carbon dioxide levels than smaller colonies, despite a similar proportion of the workforce being dedicated to the effort across all colonies, but no specific mechanism for this difference was suggested [ 42 ]. A re-reading of existing neuroscience literature also provides hints of network size-dependent plasticity in other systems. 4.2 . Evidence for size-dependent plasticity in biological neural networks In both honeybee colonies and nervous systems, robust and adaptive information processing is carried out by distributed networks of heterogeneous components exchanging excitatory and inhibitory signals [ 43 ]. Both also undergo significant changes of size with respect to the number of elements over time. In neuronal networks, these changes occur on multiple timescales, and depend on modifications of the structural and functional connectivity among the constituting neurons [ 44 ]. Moreover, changes of neuronal circuit size and neuronal responsiveness are co-regulated, and are related to the robustness of neuronal network activity to external perturbations. For example, small and immature networks exhibit a stereotypical pattern of oscillatory activity, known to be important for promoting axonal growth and synapse formation during development. The individual neurons in these networks exhibit low responsiveness and make these oscillatory patterns robust to perturbations [ 45 – 47 ]. As these circuits grow in size and connectivity, the responsiveness of their constituting neurons increases, resulting in more variable and complex spatio-temporal patterns of network activity observed in vitro [ 48 ] and in vivo [ 49 ]. Similar co-regulation of network size and neuron responsiveness is observed during sleep and anaesthesia, during which networks become functionally de-coupled [ 50 – 52 ], and in the development of Parkinson's disease, which is characterized by the reduction in the size of networks in some brain regions [ 53 – 55 ]. Thus, our data showing that bees in smaller colonies are less responsive to signals appear to mirror what occurs in small networks of neurons. 4.3 . Implications for artificial network design Although plasticity is ubiquitous in biological networks, it is conspicuously absent in artificial ones (e.g. computer networks). In these systems, distributed robustness is usually achieved by increasing network size in order to introduce redundancy and degeneracy [ 56 ]. We propose that, if size-dependent plasticity is related to maintaining network stability, including size-dependent tuning parameters for connection strength might offer a more efficient solution to the problem of small network instability, and one that is flexible in the face of network expansion. The empirical evidence presented in this paper suggests that honeybee colonies exhibit size-dependent behavioural plasticity with respect to their individual responsiveness to stop signals. Although our findings make sense in the light of the natural ecology of large and small honeybee colonies, we have yet to directly test the functional consequences of this behavioural plasticity on foraging. Additionally, we have cited examples from neuronal networks that suggest size-dependent plasticity with respect to the sensitivity to signals might be a widespread phenomenon in biological systems because it maintains network stability. However, this hypothesis needs to be rigorously tested."
} | 3,583 |
39775870 | PMC11774123 | pmc | 2,265 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
} | 7,774 |
39775870 | PMC11774123 | pmc | 2,265 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
} | 7,774 |
39775870 | PMC11774123 | pmc | 2,265 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
} | 7,774 |
39775870 | PMC11774123 | pmc | 2,266 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
} | 7,774 |
39775870 | PMC11774123 | pmc | 2,266 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
} | 7,774 |
39775870 | PMC11774123 | pmc | 2,266 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
} | 7,774 |
39775870 | PMC11774123 | pmc | 2,267 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
} | 7,774 |
39775870 | PMC11774123 | pmc | 2,267 | {
"abstract": "Abstract Land use and agricultural soil management affect soil fungal communities that ultimately influence soil health. Subsoils harbor nutrient reservoir for plants and can play a significant role in plant growth and soil carbon sequestration. Typically, microbial analyses are restricted to topsoil (0–30 cm) leaving subsoil fungal communities underexplored. To address this knowledge gap, we analyzed fungal communities in the vertical profile of four boreal soil treatments: long-term (24 years) organic and conventional crop rotation, meadow, and forest. Internal transcribed spacer (ITS2) amplicon sequencing revealed soil-layer-specific land use or agricultural soil management effects on fungal communities down to the deepest measured soil layer (40–80 cm). Compared to other treatments, higher proportion of symbiotrophs, saprotrophs, and pathotrophs + plant pathogens were found in forest, meadow and crop rotations, respectively. The proportion of arbuscular mycorrhizal fungi was higher in deeper (>20 cm) soil than in topsoil. Forest soil below 20 cm was dominated by fungal functional groups with proposed interactions with plants or other soil biota, whether symbiotrophic or pathotrophic. Ferrous oxide was an important factor shaping fungal communities throughout the vertical profile of meadow and cropping systems. Our results emphasize the importance of including subsoil in microbial community analyses in differently managed soils.",
"conclusion": "Conclusions Our experimental set-up made it possible to study the long-term impacts of land use and soil management intensity on fungal communities. We showed that the effects of land use and soil management intensity on fungal communities persisted throughout the soil vertical profile down to 40–80 cm. In accordance with our hypothesis, the less intensively managed meadow was more associated with the potentially beneficial fungal groups than the more intensively managed organic and conventional cropping systems by having the highest AMF richness and saprotroph proportion. However, the management intensity differences between organically and conventionally managed soils were not reflected in significant differences in the potentially beneficial fungal groups. Organic and conventional treatments were distinguished by having the highest pathotroph richness and pathotroph and plant pathogen proportion, and forest by having the highest symbiotroph proportion. Similarly, as in forest but on a smaller scale, the mycorrhizal mode of requiring nutrients and energy became proportionally more important in deeper soil layers of meadow, organic, and conventional treatments indicating that subsoil nutrient reservoir could potentially be better utilized and the environmental impacts of farming reduced by optimizing agricultural soil management toward AMF favoring practices. We showed several fungal taxa to be proportionally more prominent in certain soil layers. Topsoil-associated taxa in meadow, organic, and conventional treatments, included the fungal classes Dothideomycetes, Sordariomycetes, and Tremellomycetes. Subsoil-associated taxa included the fungal classes Mortierellomycetes in all treatments and Leotiomycetes in meadow, organic, and conventional treatments. This study showed that the only soil property consistently significantly related to fungal communities throughout the soil vertical profile and with strong positive correlation with AMF richness was Fe-ox, which should be further studied. Additionally, this study indicated that sampling depth should be extended at least to 30 cm deep to better describe the diversity of AMF. Vertical profiles of agricultural soils that deploy more extensive regenerative agricultural practices, such as cover-cropping with deep-rooting plants and minimal-tillage, should in the future be explored for their microbial communities to better understand soil management effects in subsoils.",
"introduction": "Introduction Fungi play a key role in agricultural soil health by affecting soil structure through aggregation, nutrient cycling, plant health, and soil organic carbon (SOC) formation and decomposition (Powell and Rillig 2018 , Toju et al. 2018 , Bhattacharyya et al. 2022 , Xiong and Lu 2022 ). High fungal diversity has been linked to improved soil multifunctionality and crop production (Wagg et al. 2011 , Delgado-Baquerizo et al. 2016 ), and fungal abundance and activity to increased carbon sequestration into soil (Kallenbach et al. 2016 , Bhattacharyya et al. 2022 , Hannula and Morriën 2022 ). Soil management practices that promote diverse fungal communities in agricultural soil can potentially increase stable soil carbon formation and ultimately crop yield (Hannula and Morriën 2022 ), contributing to the UN sustainability goals for sustainable agriculture (United Nations 2015 ). Fungi can be divided into functional groups according to their main mode of acquiring energy and nutrients (Nguyen et al. 2016 ). It has been proposed that, rather than an overall fungal community, certain fungal functional groups would better describe soil ecosystem functioning in agricultural soils (Ferris and Tuomisto 2015 ). Symbiotrophic fungi, especially arbuscular mycorrhizal fungi (AMF), which form interactions with plants and contribute to plant nutrient and water uptake (Smith and Read 2008 ), and saprotrophic fungi, which promote nutrient cycling in soil by decomposing organic material (Deacon et al. 2006 ), are potentially beneficial fungal groups for crop production. AMF have been linked to increased plant phosphorus uptake and ultimately higher plant productivity (van der Heijden et al. 1998 , Fall et al. 2022 ) as well as to pathogen suppression in agricultural soils (Fall et al. 2022 , Hannula and Morriën 2022 ). AMF can increase SOC by promoting plant photosynthate translocation into the soil matrix and by forming hyphal biomass (Jeewani et al. 2020 , Parihar et al. 2020 ). Similarly, saprotrophs have been linked to higher soil fertility (Ning et al. 2021 ) and plant pathogen suppression (van der Wal et al. 2013 ). Saprotrophic fungi have been shown to increase SOC in forest ecosystems (Klink et al. 2022 ), and a similar effect in arable soils was recently proposed (Hannula and Morriën 2022 ). Investigating AMF and saprotrophs, as well as other fungal functional groups such as plant pathogens, that can have harmful effects on crop plant production (Corredor-Moreno and Saunders 2020 ), brings important knowledge on the health and functionality of agricultural soils. Agricultural management intensity, which is a measure of the fertilizer and biocide use, irrigation, and mechanization level (Foley et al. 2011 ), is known to affect soil microbial communities. For instance, high management intensity can decrease fungal biomass and the abundance of both AMF and saprotrophic fungi, likely due to their sensitivity to soil disturbance (Strickland and Rousk 2010 , Thiele-Bruhn et al. 2012 , Hydbom et al. 2017 , Banerjee et al. 2019 ). Long-term organic management, representing a lowered management intensity in which chemical biocides and chemical fertilizers are not used, can promote fungal richness and abundance over more intensive conventional management (Martínez-García et al. 2018 , Peltoniemi et al. 2021 ). Similarly, lowered management intensity in extensively managed grasslands or lands with permanent, predominantly herbaceous plant cover has been shown to promote fungal richness over arable lands (Banerjee et al. 2024 ). Yet, more knowledge of the effects of soil management on fungal communities across the soil vertical profile is needed as studies have mostly focused on topsoil, typically reaching to 20–30 cm depth at maximum (Henneron et al. 2022 ). Agricultural soil carbon is decreasing globally (Lal et al. 2004 ). In Finland, agricultural mineral soils lose carbon at a yearly rate of 0.4% (Heikkinen et al. 2013 ). Globally, several agricultural management practices have been shown to promote SOC, including diverse crop rotation, organic amendments, no-tillage systems in some climate and soil type conditions, and organic farming, although the latter was recently revised to need additional actions, such as cover cropping and enhanced plant residue recycling (Francaviglia et al. 2017 , Yang et al. 2019 , Ogle et al. 2019 , Zhang et al. 2021 , Gaudaré et al. 2023 ). Soil management practices enabling the formation of extensive root systems and deep rooting plants can potentially increase SOC not only in topsoil but also in subsoil layers (below 30 cm), where half of the soil carbon of agricultural fields is stored (Balesdent et al. 2018 , Hirte et al. 2021 , Nguyen 2009 , Paustian et al. 2016 ). In addition to roots, fungal hyphae contribute to the translocation of SOC deeper in the soil (Witzgall et al. 2021 ). The important role of deep soil layers in SOC sequestration (Button et al. 2022 ) and fungi in SOC dynamics further emphasizes the need to investigate fungal communities in the soil vertical profile to better understand the fate of SOC in agricultural soils. Here we used amplicon sequencing of ribosomal RNA gene internal transcribed spacer (ITS2) to study fungal communities in the vertical profile of four soil treatments, organic and conventional cropping systems, unmanaged meadow, and forest, down to 80 cm deep after 24 years of field experiment. The comparison of organic and conventional treatments enables the assessment of the long-term combined effects of fertilizer type and herbicide usage on fungal communities. Organic treatment represents a less intensively managed system compared to conventional treatment, whereas meadow treatment represents the least intensive, natural-grassland-like management, creating a management intensity gradient from least intense to most intense: meadow–organic–conventional. Forest is included as a reference and represents the land use type that prevailed in the experiment area before conversion to agricultural system (Salonen et al. 2023 ), providing insight on how the transition into agricultural or meadow land use changes the fungal community over time. Our overall aim was to study how depth within the land use types (forest, meadow, and organic and conventional cropping systems) and soil management intensity within meadow–organic–conventional soil management intensity gradient influence fungal communities. In addition, we aimed to address which soil properties are the drivers of fungal community differences within the soil vertical profile. We hypothesize that lower soil management intensity in meadow and organic soils increase fungal diversity and promote the potentially beneficial AMF and saprotroph communities compared to more intensively managed conventional soil.",
"discussion": "Discussion In a recent meta-analysis, it was shown that in the deeper soil layers, there are on average 47% of soil organic C stocks of agricultural fields (Balesdent et al. 2018 ). Similarly in the forest soils, it has been shown that the total soil C stock under 20 cm may be up to 50% of the total (Jobbágy and Jackson 2000 ) and up to 75% of SOM can be found in subsoil (B and C horizons) (Rumpel et al. 2002 ). Considering deeper soil layers as reservoirs for C, different agricultural management practices can have a significant role both as enhancing fresh C input into deeper layers (Lessmann et al. 2022 , Gaudaré et al. 2023 ), as well as modifying the microbial communities responsible for SOC decomposition and plant nutrient uptake (Morugan-Coronado et al. 2022 ). However, we still lack a comprehensive view of how land use or soil management influences microbial communities in the soil vertical profile and how this ultimately affects the fate of SOC. Depth together with land use and agricultural soil management affected fungal community composition The analysis of the vertical soil profile of the four treatments showed that fungal communities were affected by soil layer and treatment and the treatment effect varied between the studied five soil layers. Overall, we found soil layer to have a bigger effect on fungal community differences compared to treatment. Fungal community composition and diversity have previously been shown to be influenced by depth in cropping systems (Schlatter et al. 2018 , Yin et al. 2021 ) and forest (Baldrian et al. 2012 ). Similarly, there are numerous studies showing how agricultural soil management intensity shapes fungal communities in topsoil (Sun et al. 2016 , Gottshall et al. 2017 , Vahter et al. 2022 , Wu et al. 2022 ). However, previously the comparison of organic and conventional treatment effects on the fungal community has been done down to 30 cm, but we lack studies where below 30 cm layers are analysed (Epp Schmidt et al. 2022 ). Here, we show that the treatment effect between organic and conventional cropping systems can be seen down to the deepest measured soil layer 40–80 cm ( Table S4B–F ). Conventional and organic plots had the same 5-year crop rotation and three different crops growing during the sampling year, indicating that agricultural management affects fungal communities regardless of the crop. Fungal richness was not negatively associated with soil management intensity In line with a previous study by Schlatter et al. ( 2018 ), our results on fungal richness showed a consistent decrease in relation to depth in soil layers between 10–80 cm in all treatments. Fungal richness in meadow, organic, and conventional treatments differed in topsoil (0–10 cm) where organic and conventional had more diverse fungal community compared to meadow and in the deepest soil layer (40–80 cm) where organic treatment had more diverse fungal community compared to conventional. Interestingly, contrary to what we hypothesized and what has been found in multiple previous studies (Martínez-García et al. 2018 , Peltoniemi et al. 2021 , Banerjee et al. 2024 ), low management intensity did not promote higher fungal richness in topsoil. This, however, follows the somewhat surprising fungal diversity pattern found in a Europe-wide study across land-use intensity gradients (woodland–grassland–cropland), where higher land use intensity correlated with higher fungal diversity (Labouyrie et al. 2023 ). Similarly, in grasslands, the intensification of land management practices has been found to have either neutral or positive effects on belowground fungal diversity (Allan et al. 2014 , Gossner et al. 2016 ). In diverse environments such as the meadow, organic, and conventional soils in our study, the common understanding in ecology that a higher species richness contributes to higher ecosystem functioning (Loreau et al. 2001 ) has been disputed (Nielsen et al. 2011 ). Ecosystem functions have rather been linked to succession of fungal communities than to high OTU richness (Hoppe et al. 2016 ). We do not have data for temporal succession in our soils, but we know that fungal communities were more specialized vertically in meadow ( Table S4G ), probably due to higher litter input and the lack of interruption by periodic ploughing. This spatial specialization in meadow could possibly lower fungal diversity in individual soil layers. In addition, the lower topsoil pH in the 0–10 cm soil layer of meadow compared to organic treatment and marginally compared to conventional management may have attributed to the lower fungal diversity in meadow (Zheng et al. 2019 ). The over two-fold higher DOC in the 0–10 cm soil layer of meadow, most probably caused by the high litter input, may also have lowered topsoil fungal richness in meadow similarly as in a previous study where higher arable soil DOC and lower fungal richness were found in straw mulch soil compared to soil without mulch (Huang et al. 2019 ). We did not find difference in fungal richness between organic and conventional in the first four soil layers (0–40 cm). Similarly, in a study with organically fertilized (pig manure) and chemically fertilized crop field, and in long-term organic and conventional cereal crop systems, no significant differences in fungal Shannon diversity (Suleiman et al. 2019 ) or OTU richness (Peltoniemi et al. 2021 ) between the management types were found, but rather in the fungal ITS2 copy numbers (Peltoniemi et al. 2021 ), indicating that management effect on fungal diversity could be more subtle compared to fungal abundance, which was not measured in this study. However, our study provides only a single time point view of fungal diversity which can change during the growing season and between years (Degrune et al. 2017 ). Considering our findings and the literature, the overall effect of management intensity on fungal richness remains somewhat unclear. Management intensity affected AMF richness below the surface soil Previously, it has been shown that rather than the overall fungal community, specialized microbial groups are linked to soil ecosystem functioning and may better describe the effects of land use or soil management intensity (Wang et al. 2022 ). Symbiotrophic fungi in general and specifically AMF can benefit plant productivity and soil fertility (van der Heijden et al. 1998 , Smith and Read 2008 et al. 2008 , Jeewani et al. 2020 , Parihar et al. 2020 , Fall et al. 2022 , Hannula and Morriën 2022 ). Although lower agricultural soil management intensity is shown to positively affect AMF (Hydbom et al. 2017 , Banerjee et al. 2019 ), we did not find a significant effect of treatment on AMF or symbiotroph proportion between meadow, organic, and conventional treatments. AMF richness, however, differed between the low-intensity meadow and the highest intensity conventional treatment in the 20–30 and 30–40 cm soil layers. Organic soil which represents a lowered management intensity fell between the intensity extremes and could not be statistically differentiated from either. The management intensity effect on AMF richness can be attributed to different management practices. For instance, AMF are shown to be negatively affected by fertilization overall (Hannula et al. 2021 , Luo et al. 2021 ), and the use of mineral fertilization over manure can further suppress AMF (Wang et al. 2018 ), which could explain higher AMF richness in unfertilized meadow compared to mineral-fertilized conventional treatment. The differences in root biomass between treatments which followed the management intensity gradient (higher root biomass in lower management intensity; Fig. S5 ; Table S8 ) and the lack of disturbance related to tillage operations in meadow may have promoted higher AMF richness in meadow (Hiiesalu et al. 2014 , Schmidt et al. 2019 ). Plant diversity was not measured from the treatment plots in the sampling year (2019), so we cannot fully assess the effect of plant diversity on fungal communities. However, plant richness and Shannon diversity were recorded 7 and 8 years before the experiment (in 2011 and 2012) ( Fig. S5 ) and showed no differences between meadow and the cropping systems (organic and conventional treatments) but higher plant richness in organic compared to conventional treatment in 2012 ( Fig. S5 ). Plant diversity has previously been positively linked to AMF diversity (Hiiesalu et al. 2014 ), indicating that high plant richness in organic treatment might partly explain why organic treatment did not differ from meadow in AMF richness whereas conventional treatment did. Higher plant richness in organic treatment is most probably a consequence of the lack of herbicide usage and is thus part of the management intensity effect. Organic and conventional treatment in this study already had a moderately diversified cropping system with 5-year rotation which included grass and crop mixtures (Salonen et al. 2023 ). However, decreasing management intensity by incorporating reduced tillage and increasing plant diversity by, for instance, cover-cropping, where noncommercial plants are grown together or after the main crop, could potentially further promote AMF richness in organic and conventional treatments (Thapa et al. 2021 ). Arbuscular mycorrhizal fungal communities were affected by treatment and depth, but no treatment-specific taxa were found We took a closer look at the AMF communities since the beneficial functions associated with AMF, such as induced nutrient uptake and protection against pathogens, can differ between AMF taxa (Sikes et al. 2010 ). We found AMF communities to be affected by treatment and depth but AMF taxa-specific differences between meadow, organic, and conventional treatments were not found. Based on patterns of fungal biomass allocation, AMF taxa can be grouped into rhizophilic guild, that have high biomass in roots and may protect host plants from pathogen colonization, edaphophilic guild, that have high extradical hyphae biomass and improve plant nutrient uptake (Weber et al. 2019 ), and ancestral guild, that produce low biomass both within and outside the root (Treseder et al. 2018 , Phillips et al. 2019 ). In our study, the rhizophilic AMF guild was most pronounced, followed by the ancestral AMF guild. High proportion of rhizophilic AMF guild indicates an improved protection over plant pathogens. Edaphophilic guild was the least represented AMF guild in the studied soils, although the only edaphophilic genus, Diversispora , was found in all treatments. The abundance of many edaphophilic AMF taxa, but not Diversispora , has been linked to a higher C-N-ratio than what was present in our soils (Treseder et al. 2018 , Fig. S4 ). Yet, the presence of a plant-nutrient-uptake improving AMF taxa such as Diversispora in organic and conventional treatment is an encouraging finding as it could benefit crop plants by scavenging large volume of soil, including deep soil, for nutrients. In addition to depth, fungal trophic modes were affected by land use and agricultural management In all soil treatments, the proportion of symbiotrophic fungi increased toward deeper soil layers, and in meadow, organic, and conventional treatment this was shown as an increase of AMF proportion in subsoil in comparison to topsoil. Since AMF benefit plant nutrient uptake (Smith and Smith 2011 ), and subsoil can harbour more than two-thirds of the nutrients in arable fields (Kautz et al. 2013 ), this subsoil association of AMF could indicate an important role of subsoil as a nutrient pool in the studied meadow, organic, and conventional treatments. Regarding forest treatment, our results support the previously proposed hypothesis that symbiotrophic mycorrhizal fungi in boreal forests are more competitive than saprotrophs in deeper layers where litter is more decomposed and C:N ratio is lower (Lindahl et al. 2007 , van der Wal et al. 2013 , Santalahti et al. 2016 , Carteron et al. 2021 ), as both the highest symbiotrophic proportion and the lowest C:N ratios coincided in the same deep forest soil layers (30–40 cm and 40–80 cm) (Fig. 3 ; Fig. S4 ). Our results further suggest that the direct fungal interactions with plants, whether symbiotrophic or pathotrophic, are emphasized in deep forest soil (40–80 cm), where symbiotroph and pathotroph-saprotroph fungi represented the majority (75% and 18%) of fungal functional community and pure saprotrophs only a marginal (2%) (Fig. 3C ). This indicates that the role of aboveground vegetation in shaping fungal communities in subsoil of boreal forest may be substantial. Pathotrophic fungi were affected by treatment and depth. Out of all fungal functional groups, pathotrophic fungi correlated most strongly and negatively with depth (Fig. 3 ; Table S5 ), which may be explained by lower host interactions due to lower plant input and the typically lower richness of protist and soil animals in deeper soil layers (Du et al. 2022 , Islam et al. 2022 ). Yet, contrary results were previously observed in a study with wheat-cropping system, where pathotrophic fungi were either unaffected or positively affected by depth (Schlatter et al. 2018 ). Among the pathotrophic fungi, plant pathogens were strongly influenced by treatment. We found organic and conventional treatments to increase plant pathogen proportion compared to forest and meadow ( Table S6 ). Our results do not agree with a previous study where plant pathogen richness and proportion were shown to increase according to SOC (Du et al. 2022 ). Rather, our results are in line with the plant pathogen-inducing effect of arable soils over grasslands (French et al. 2017 ). Saprotrophic fungi have been gaining attention as a potentially beneficial fungal group in agricultural soils contributing to nutrient cycling, soil fertility, plant pathogen suppression and SOC (Deacon et al. 2006 , van der Wal et al. 2013 , Ning et al. 2021 , Hannula and Morriën 2022 ). We found the proportion of saprotrophic fungi to be more associated with low-intensity meadow treatment than with the cropping systems, organic and conventional treatments. Although the decomposing function of saprotrophic fungi can increase soil respiration and loss of carbon from soil in some cases (Newsham et al. 2018 ), a positive link between saprotroph biomass and SOC is frequently observed in agricultural soil (Six et al. 2006 ). In our study, higher SOC (Salonen et al. 2023 ) and higher saprotroph proportion coincided in meadow ( Tables S6 and S8 ), further supporting the role of saprotrophs in SOC accrual. Fe-ox were positively related to fungal communities down to 40–80 cm soil layer with strong correlation with arbuscular mycorrhizal fungal richness Several soil properties contributed to fungal communities in meadow, organic and conventional treatment (Fig. 2 ; Tables 1 and 2 ). Fungal community differences (Bray–Curtis) were influenced by soil properties commonly observed in previous studies, C, N, DOC, C/N, P-tot, and pH (Francioli et al. 2016 , Khan et al. 2016 , Muneer et al. 2021 , Rousk et al. 2010 , 2011 , Tedersoo et al. 2014 , 2020 , Zheng et al. 2019 ), as well as by root biomass, P-org, and Fe-ox, and less by P-inorg and P-H 2 O. Our results confirm the less commonly reported role of root biomass along the soil vertical profile in shaping fungal communities as well as the positive correlation of root biomass with fungal and AMF richness (Broeckling et al. 2008 , Eisenhauer et al. 2017 , López-Angulo et al. 2020 ). Previously, the role of P in shaping fungal communities has been emphasized, especially in agricultural soil (Francioli et al. 2016 , He et al. 2016 , Wu et al. 2022 ). Here, we consistently found P-org out of the different P forms (P-org, P-tot, P-inorg and P-H 2 O) to best explain variations in fungal community differences and fungal richness. Additionally, P-org explained fungal community differences better than any other soil property when the whole soil profile was considered. Total and available P has been shown to correlate negatively with fungal diversity (Wu et al. 2022 ), and in general, soil P is believed to negatively affect fungal richness (Tedersoo et al. 2014 ). In contrast, we did not find a negative link between fungal richness and any P form measured, and only a weak negative link with P-inorg and AMF richness was observed. Although the negative effects of soil P on AMF richness and abundance are well documented (Abbott et al. 1984 , Camenzind et al. 2014 , Chen et al. 2014 , Jasper et al. 1979 , Mosse 1973 , Olsson et al. 1997 ), recently opposing effects of P in topsoil (negative) compared to subsoil (positive) were found (Luo et al. 2021 ), indicating the effects of P on AMF richness to vary within the soil vertical profile. This could explain why we did not find a negative link with most P forms and AMF richness when assessing the whole soil profile. However, our results do support the strong adverse role of different P forms on AMF proportion (Table 2 ) and suggest that AMF diversity and proportions may be differently affected by P in the soil vertical profile. The strong role of Fe-ox in fungal communities is not commonly reported, making it a novel and interesting finding (Brandt et al. 2024 , Jeewani et al. 2020 ). Fe-ox was the only soil property that associated with fungal communities consistently throughout the soil vertical profile (0–80 cm) and additionally correlated strongly with fungal and AMF richness (Tables 1 , 2 ). This is supported by a previous study, where AMF were reported to preferentially associate with iron oxide surfaces in rhizosphere soil (Whitman et al. 2018 ). Fe-ox is important in soil aggregate formation and is associated with SOC (Jeewani et al. 2020 , Pronk et al. 2011 , Salonen et al. 2023 ), which can at least partly explain the role of Fe-ox as both soil aggregates and SOC are known to shape fungal communities (Fan and Wu 2021 , Upton et al. 2019 ; Yang et al. 2019 ). Additionally, soil P availability is negatively affected by Fe-ox, as well as by Al-ox, which adsorb phosphate ions through ligand exchange reaction (Hingston et al. 1967 ). Thus, Fe-ox may have affected fungal communities by controlling the amount of available P. Further studies are needed to better understand the role and function of Fe-ox in shaping fungal, especially AMF, communities. Meadow treatment had the most distinct soil properties among meadow–organic–conventional soil management intensity gradient As such, pH influences fungal community structure (Hannula et al. 2021 , Tedersoo et al. 2020 ) and it was overall higher in the cropping systems (organic and conventional treatment) compared to meadow ( Table S8 ). Lower pH may also have led to higher Fe-ox content in meadow (Thompson et al. 2006 ). In addition to differences in pH and Fe-ox, meadow treatment was associated with higher C, N, C/N, DOC, Al-ox and root biomass in most soil layers, and higher P-org in the topsoil (0–10 cm) compared to the cropping systems, indicating their role in fungal community differences between meadow and conventional/organic treatment. Root biomass, C, N, P-org, and P-H2O were the only soil properties that significantly differed between organic and conventional treatments at least in some of the soil layers, indicating a link between these soil properties and variations in the fungal communities ( Table S8 ). In deep soil, the role of root biomass may have been important as it was the only significantly different soil property between organic and conventional treatments in 30–40 cm and 40–80 cm soil layers. As Fe-ox differed significantly only between meadow and the cropping systems (organic and conventional), its role in the fungal community differences between organic and conventional treatments remains unclear. However, soil layer and treatment alone better explained the observed fungal community differences than all the measured soil properties together (PERMANOVA; R2 = 0.41 vs. R2 = 0.34). This indicates that soil management and depth may influence fungal communities beyond these commonly measured soil properties."
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