pmid stringlengths 8 8 | pmcid stringlengths 8 11 ⌀ | source stringclasses 2
values | rank int64 1 9.78k | sections unknown | tokens int64 3 46.7k |
|---|---|---|---|---|---|
32356660 | PMC7243252 | pmc | 6,597 | {
"abstract": "The programmed construction of functional\nsynthetic cells requires\nspatial control over arrays of biomolecules within the cytomimetic\nenvironment. The mimicry of the natural hierarchical assembly of biomolecules\nremains challenging due to the lack of an appropriate molecular toolbox.\nHerein, we report the implementation of DNA-decorated supramolecular\nassemblies as dynamic and responsive nanoscaffolds for the localization\nof arrays of DNA signal cargo within hierarchically assembled complex\ncoacervate protocells. Protocells stabilized with a semipermeable\nmembrane allow trafficking of single-stranded DNA between neighboring\nprotocells. DNA duplex operations demonstrate the responsiveness of\nthe nanoscaffolds to different input DNA strands via the reversible\nrelease of DNA cargo. Moreover, a second population of coacervate\nprotocells with nanoscaffolds featuring a higher affinity for the\nDNA cargo enabled chemically programmed communication between both\nprotocell populations. This combination of supramolecular structure\nand function paves the way for the next generation of protocells imbued\nwith programmable, lifelike behaviors."
} | 286 |
36908533 | PMC9993237 | pmc | 6,598 | {
"abstract": "Catechol-based hydrogels have good adhesion properties; however, since the concentration of catechol is low and it can be easily oxidized to quinone, the adhesion performance of the hydrogels is reduced, which limits their application as self-adhesive flexible wearable sensors. In this work, a dopamine: poly(sodium 4-styrenesulfonate) (DA:PSS)-initiated strategy was proposed to construct adhesive hydrogels, where the semiquinone radicals present in DA:PSS were used to initiate radical polymerization to obtain the DA:PSS/poly(acrylic acid) (DA:PSS/PAA) hydrogel. This hydrogel exhibited good stretchability and adhesion with various substrates. We observed that, even after exposure to air for 21 days under certain relative humidity (76%), the catechol groups hardly oxidized and the DA:PSS/PAA hydrogel presented good adhesion. The DA:PSS/PAA hydrogel also showed good electrical conductivity and fast response ability. Thus, the general strategy of triggering monomer polymerization to form hydrogels based on the semiquinone radical present in DA:PSS offers great potential for their application in flexible electronic devices and wearable sensors.",
"conclusion": "4. Conclusions In summary, we report a polymerization strategy to fabricate catechol-functionalized hydrogel triggered by semiquinone radicals in DA:PSS. The DA:PSS/PAA hydrogel exhibits good stretchability (1249%) due to the existence of the interpenetrating network of PAA and PSS, and the multiple hydrogen bonds induced by DA. In contrast, profiting from the abundant catechol, carboxyl, and sulfonate groups, the conductive hydrogel presented good adhesion with various substrates ( e.g. , PP, alloys, porcine skin, rubbers, iron, glass, and wood). Additionally, the DA:PSS/PAA hydrogel has long-lasting adhesiveness, which may be attributed to the resistance of DA to oxidation due to the acidic environment and the interaction of the amino group of DA and sulfonate group of PSS. The DA:PSS/PAA hydrogel also exhibits strain-responsive conductivities. Attributed to these advantages, the conductive DA:PSS/PAA hydrogel could be applied as skin-like sensors to monitor human movements. To meet the long-term application, it is necessary to improve the moisture retention of the DA:PSS/PAA hydrogel. We are continuing our research to find out how pH affects the activity of semiquinones in DA:PSS, and develop proper methods to improve the moisture retention of the prepared hydrogels. We believe that our work may provide new insights into the development of adhesive hydrogels based on DA and PDA materials.",
"introduction": "1. Introduction Adhesive hydrogels, owing to their excellent electronic properties and the soft nature of the wet tissues in them, are great candidates for use in flexible wearable sensors, human movement detection, soft robotics, and wearable healthcare tracking. 1–3 Recently, inspired by natural mussel adhesion, various catechol-based adhesive hydrogels have been proposed in the synthesis of self-adhesive epidermal sensors. 4–6 So far, several catechol-based adhesive hydrogels have been fabricated using catechol-containing polymers, catechol-functionalized monomers, and other catechol-functionalized materials. 4–14 Dopamine (DA), an important neurotransmitter found in the brain, contains both catechol and amine groups. 15 It is also identified as a small-molecule mimic of mussel foot proteins, which can undergo autooxidation and then self-polymerize under alkaline conditions to generate polydopamine (PDA) materials. 15–22 DA derivatives and PDA-incorporated hydrogels exhibit strong adhesiveness toward various organic and inorganic substrate surfaces, and human skin. 8–12 Radical polymerization using additional initiators is a typical method to prepare mussel-inspired hydrogels. 8–12 However, since the presence of a high concentration of catechol moieties can result in the substantial quenching of free radicals thereby suppressing the formation of hydrogel networks, it is important to ensure that the hydrogels prepared by radical polymerization possess low catechol content, that is, lower than 2 wt% of the monomer. 8–12 However, such a low concentration of catechol undermines the adhesion performance of mussel-inspired hydrogels as well as their application in self-adhesive skin-like sensors. In addition, the catechol in the adhesive hydrogels was usually oxidized to quinone by air during storage and usage, which caused the hydrogels to lose their adhesion ability. 13,14 Furthermore, Zhang and co-workers found that semiquinone radical species generated during the oxidation of DA can trigger the polymerization of acrylate monomers to eliminate the use of additional free-radical initiators. 23 The Zhang group present a DA-triggered gelation to fabricate mussel-inspired conductive hydrogels with high optical transparency and catechol content (up to 50 wt% of the monomer), simultaneously, by taking advantage of intriguing mussel-inspired chemistry to eliminate the use of additional free-radical initiators. 12 Recently, the Liang group found that the sulfonate in poly(sodium 4-styrenesulfonate) (PSS) interacts with the amino group on DA, which inhibits both its cyclization and polymerization; during the process, while more semiquinone radicals are found to be produced, dopaquinone is not detected. 24 Furthermore, PSS could be used as the hard segment to interact with flexible macromolecules such as poly(acrylic acid) (PAA) to form interpenetrating polymer network. 25,26 On the other hand, PAA-based hydrogel is an ionic hydrogel which is widely used as flexible wearable sensors due to its excellent ionic conductivity. 25–29 Here, we prepared an adhesive hydrogel using acrylic acid (AA) as the monomer and N , N′ -methylenebis(acrylamide) (BIS) as the chemical crosslinking agent, initiated by the semiquinone radicals in DA:PSS, where DA:PSS can interact with PAA through hydrogen bond, PSS and PAA could also form interpenetrating network ( Scheme 1 ). The prepared DA:PSS/PAA hydrogel was found to exhibit long-lasting adhesion due to the acidic environment endowed by PAA and the interaction between the amino group of DA and sulfonate of PSS, which prevent the oxidation of DA to dopaquinone. Furthermore, the DA:PSS/PAA hydrogel could be used as flexible wearable sensors. Scheme 1 Schematic of DA:PSS-initiated polymerization-triggered synthesis of PAA adhesive hydrogel. (i) The sulfonate in PSS interacts with the amino group on DA. (ii) Schematic diagram of the internal structure of the hydrogel. (iii) Interactions between the hydrogel and various substrates: (I) hydrogen bond. (II) Coordination bond. (III) Cation–π interaction. (IV) π–π interaction. (V) Covalent linking. (iv) Schematic diagram of interactions of DA, PAA and PSS.",
"discussion": "3. Results and discussion 3.1 Analysis of the chemical structure of DA:PSS The complex of DA and PSS (DA:PSS) was synthesized by directly adding solid DA·HCl into an aqueous solution of PSS, according to the method described in the literature. 24 The structure of DA:PSS is obtained from the 1 H-NMR and 13 C-NMR spectra of DA:PSS and DA·HCl, respectively, as shown in Fig. 1 . The peaks at around 6.5 ppm belonged to the aromatic protons of DA in DA:PSS. Moreover, there were two sharp peaks at 9.0 ppm, which may be ascribed to the phenolic hydroxyl protons of DA in DA:PSS ( Fig. 1a ). The 1 H-NMR spectra of DA·HCl and DA:PSS overlapped almost completely. The signal peaks in the 1 H-NMR spectra of DA:PSS were very clear and were completely different from those in the 1 H-NMR spectra of PDA. 24 The 13 C-NMR spectra of DA:PSS matched well with that of the DA monomer ( Fig. 1b ). The 1 H-NMR and 13 C-NMR spectra showed the structure of DA:PSS similar to that shown in the literature, 24 indicating that no dopaminequinone was generated. These results show that we have successfully synthesized DA:PSS. Fig. 1 (a) 1 H-NMR and (b) 13 C-NMR spectra of DA·HCl and DA:PSS. Electron spin resonance (ESR) was conducted to detect the characteristics of radicals in DA:PSS (Fig. S1 † ). A single-line ESR of DA:PSS with accurate g -factor of 2.0050 (the experimental data amounted to 2.0010) at room temperature was detected, indicating the formation of semiquinone radicals. 24,30 Thus, the semiquinone radicals in DA:PSS could be used to trigger free radical polymerization. 3.2 Mechanical properties of DA:PSS/PAA hydrogel According to previous reports, PAA and PSS chains could form interpenetrating networks in which PAA interacts with DA and PSS via hydrogen bonding. 25,26,31,32 In this work, gelation time experiments were used to explore the appropriate ratio of spontaneous formation of hydrogels by DA:PSS and AA without adding initiators (Fig. S2 and S3 † ). It could be observed that the gelation time decreased with the increase in the dosage of DA:PSS. The weight ratio of DA:PSS to AA was chosen as 1 : 1 for the subsequent experiments. However, the strength of these hydrogels was so low that limited their application. To obtain hydrogels with good mechanical properties, crosslinking agent BIS was induced into the reaction system, which could adjust the crosslinking density of the hydrogels. Composite hydrogels with different mechanical properties were obtained by changing the content of BIS. Fig. 2a shows the stress–strain curves of the DA:PSS/PAA hydrogel with different BIS contents. It could be seen that, as the BIS content increased from 0.001 to 0.016 g, the stress of the composite hydrogels also increased from 28.7 kPa to ∼50.8 kPa and the elongation at break reduced from 1879% to ∼206%. Due to the addition of BIS, the hydrogel forms multi-crosslinking points that increase the rigidity of the hydrogel and reduce the toughness. 33 The DA:PSS/PAA hydrogel exhibits proper mechanical strength (44.9 kPa) and good stretchability (1249%) at the BIS content of 0.002 g mL −1 . The tensile modulus (100–200% strain) and toughness of DA:PSS/PAA hydrogel at the BIS content of 0.002 g mL −1 are 6.61 kPa, 30.479 kJ m −2 , respectively. Considering at strain and tensile strength, 0.002 g mL −1 BIS was used for subsequent experiments. Fig. 2 Mechanical properties of the DA:PSS/PAA hydrogel. (a) Stress–strain curves of the DA:PSS/PAA hydrogel with different BIS contents. (b) Elasticity of the DA:PSS/PAA hydrogel under 70 successive loading–unloading cycles. Interestingly, this DA:PSS-initiated strategy applies equally to other acrylate monomers such as AM and NIPAM as well. However, only in acidic solutions could AM and NIPAM form hydrogels initiated by semiquinones present in DA:PSS (Fig. S4 † ). From these observations, it may be preliminarily concluded that pH affects the activity of semiquinones in DA:PSS as the initiators for radical polymerization. The reasons for this will be studied in future works. Stability is crucial for the practical application of hydrogels. Therefore, we characterized the fatigue properties of the DA:PSS/PAA hydrogel ( Fig. 2b ). As shown in Fig. 2b , DA:PSS/PAA hydrogel had no obvious hysteresis in their stress–strain curves even after 70 cycles of continuous tension recovery test, with a tensile deformation of 300%, indicating that the DA:PSS/PAA hydrogel has good fatigue resistance. These results indicated that DA:PSS/PAA hydrogel had good mechanical properties. Fig. S5 † shows a comparison of the properties of the PSS/PAA hydrogel (using APS as the initiator) and of the DA:PSS/PAA hydrogel. It may be seen that the elongation of the DA:PSS/PAA hydrogel (1249%) is far greater than that of the PSS/PAA hydrogel (618%), which is due to the multiple hydrogen bonds and ionic interaction induced by DA in the DA:PSS/PAA network. 12,34 3.3 Adhesion properties of DA:PSS/PAA hydrogel As shown in Fig. 3a , DA:PSS/PAA hydrogel could adhere to the surface of PP, alloys, porcine skin, rubbers, iron, glass, and wood. The adhesion strength of DA:PSS/PAA hydrogel on different substrates including glass, porcine skin, wood, and steel were found to be 11.7, 22.3, 23.2, and 27.0 kPa, respectively ( Fig. 3b ), which is very comparable with some catechol-based hydrogels. 12,35 In addition, the adhesion strength of the DA:PSS/PAA hydrogel (newly prepared and after 21 days storage) on glass remained almost unchanged even after 20 peel-adhesion cycles, which indicated that the DA:PSS/PAA hydrogel has long-lasting and repeatable good adhesion ( Fig. 3c ). The photographs of the DA:PSS/PAA hydrogel showed that the colour of the hydrogel changed only slightly after 21 days ( Fig. 3d ), indicating that the catechol hardly oxidized in the hydrogel due to the acidic environment and the interaction between the amino group of DA and sulfonate of PSS. 24 Fig. 3 Adhesion ability of the DA:PSS/PAA hydrogel. (a) DA:PSS/PAA hydrogel showed good adhesion to various substrates: alloys, porcine skin, rubbers, iron, PP, glass, and wood. (b) The adhesion strength of the DA:PSS/PAA hydrogel on different substrates. (c) The adhesion strength of the DA:PSS/PAA hydrogel under 20 adhesion-peel cycles (d) Photographs of the appearance and simple stretching of the DA:PSS/PAA hydrogel after 21 days. Furthermore, two DA:PSS/PAA hydrogels was put on the arm crossing the wrist for 5 hours to investigate the effect of the real body and around environment on this hydrogel (Fig. S6 † ). In comparison, one of the DA:PSS/PAA hydrogels was coated with glycerine after adhered to the arm. It was observed that both hydrogels turned thinner, indicating the losing of water happened for both hydrogels due to the body temperature. But it was apparent that the hydrogel coated with glycerine kept more water than that of the bare hydrogel. And the calculation of weight loss supported the observation (65.03% for the bare hydrogel and 54.37% for the hydrogel coated with glycerin). The weight loss changed the mechanical properties as shown in Fig. S7. † To make the prepared hydrogel meet the practical application, the improvement of moisture retention was necessary, and the related work will be carried out later. The adhesion of the DA:PSS/PAA hydrogel may be attributed to the synergistic effect of the carboxyl groups of PAA, sulfonate groups of PSS, and the catechol groups of DA through covalent and noncovalent bonding, as shown in Scheme 1 . The existence of large amounts of hydrogen bonds and electrostatic interactions in this system is of great importance to the adhesive properties. In addition to the interaction between the hydrogen bonds and electrostatic interactions, other physical interactions that are formed between the gel and the substrate, such as π–π stacking, cation–π interaction, and metal coordination, 12,16,19,36–38 are also expected also endow the hydrogel materials with adhesiveness. 3.4 Strain-responsive conductivity properties of DA:PSS/PAA hydrogel The DA:PSS/PAA hydrogel demonstrated good electrical conductivity due to the presence of Na + of PSS in the network, serving as a conductive medium. The circuit was formed by connecting the hydrogel with copper wires, an LED bulb, and a power supply. Upon stretching, the brightness of the LED bulb darkened and the brightness recovered when the strain disappeared. It may be noted that the brightness of the LED bulb changed almost simultaneously with stretching, revealing the fast response of the hydrogel to strain. Fig. 4a shows the change in resistance of the DA:PSS/PAA hydrogel when it is stretched to different lengths. It can be seen in Fig. 4b that, as the hydrogel is stretched continuously, its resistance increases immediately with hardly any hysteresis. We further use the gauge factor (GF, (Δ R / R 0 )/ ε ) to evaluate the strain sensitivity. Within the strain increases to 500%, the GF was found to be 4.02. Therefore, it may be concluded that the DA:PSS/PAA hydrogel has the potential to be used as a skin sensors. Fig. 4 Strain-responsive conductivity properties of the DA:PSS/PAA hydrogel. (a) Change in the LED light with the elongation of the hydrogel. (b) Change in the resistance and GF values of the DA:PSS/PAA hydrogel with increasing strain. 3.5 Flexible wearable sensors based on DA:PSS/PAA hydrogel Given their excellent flexibility, strain sensitivity, and adhesive ability, DA:PSS/PAA hydrogel was able to be applied as a wearable strain sensor to detect the motions of finger. To monitor finger motion, we attached the hydrogel sensor to the finger and recorded the real-time resistance–time curve in finger flexion by the electrochemical workstation. The relative resistance change with the finger flexion is shown in Fig. 5a . By bending the fingers (0°, 35°, 50°, and 95°), the change in the hydrogel resistance at different angles was detected. When the finger bending increased from 35° to 50° to 95°, the resistance was also found to increase gradually. When the finger was bent back to 0°, the original resistance was recovered. The relative resistance of the hydrogel increased as the flexion angle of the finger increased. As the hydrogel was attached to the finger, it readily stretched upon finger flexion, leading to an increase in the resistance. With a stepwise increase in the flexion angle of the finger, the relative resistance also showed a corresponding stepwise increase. The relative resistance changes under finger motion also showed a fast and repeatable response, with response times up to 83 ms ( Fig. 5b and c ). The finger motion monitoring results proved that DA:PSS/PAA hydrogel could be used as flexible wearable sensors to detect human activities due to their high sensitivity. Fig. 5 Electromechanical properties of the DA:PSS/PAA hydrogel. (a) Relative resistance variations of the hydrogel strain sensors adhered onto the finger bending upon different angles (0°, 35°, 50°, and 95°). (b) Stability tests of the hydrogel sensors by repeatedly applying for multiple cycles. (c) The response times were up to 83 ms."
} | 4,484 |
34037542 | null | s2 | 6,599 | {
"abstract": "Hydrogels with tunable properties are highly desirable in tissue engineering applications as they can serve as artificial extracellular matrix to control cellular fate processes, including adhesion, migration, differentiation, and other phenotypic changes via matrix induced mechanotransduction. Poly("
} | 75 |
31965222 | PMC7007895 | pmc | 6,600 | {
"abstract": "As photosynthetic microbes, cyanobacteria are attractive hosts for the production of high-value molecules from CO 2 and light. Strategies for genetic engineering and tightly controlled gene expression are essential for the biotechnological application of these organisms. Numerous heterologous or native promoter systems were used for constitutive and inducible expression, yet many of them suffer either from leakiness or from a low expression output. Anyway, in recent years, existing systems have been improved and new promoters have been discovered or engineered for cyanobacteria. Moreover, alternative tools and strategies for expression control such as riboswitches, riboregulators or genetic circuits have been developed. In this mini-review, we provide a broad overview on the different tools and approaches for the regulation of gene expression in cyanobacteria and explain their advantages and disadvantages.",
"conclusion": "Summary and conclusion While constitutive expression works quite well in cyanobacteria, several heterologous or native, inducible promoter systems suffer either from leakiness or from a low expression output. Anyway, in recent years, existing systems have been improved and new promoters have been discovered or engineered for cyanobacteria. Parameters such as the promoter length, slight variations of the sequence and promoter elements (i.e. the −10 and −35 regions, the interspace between them, operators and the RBS) were identified as crucial factors for the promoter efficiency and hold the potential for further optimisation of expression systems for enhanced applications in cyanobacteria. Moreover, alternative strategies for expression control in cyanobacteria have been established. Riboswitches and riboregulators can be regulated independently of the target promoter and emerged as powerful tools for fine-tuning of expression levels and enhancing induction control. Further sRNA-based approaches and target-specific sRNAs essentially increase the toolset of RNA-based regulatory systems. The technological progress on genome-wide screening and transcriptome analysis will lead to the identification of further promising candidates of native regulatory RNAs. Another upcoming strategy for the regulation of gene expression is the generation of genetic circuits via the combination of different regulatory modules. More work in this field will be necessary to further advance efficient and tightly controlled gene expression in cyanobacteria.",
"introduction": "Introduction Cyanobacteria are a very diverse group of photosynthetic microorganisms. They colonise all light-exposed habitats on Earth, including marine water, freshwater, soil, glaciers, deserts and hot springs (Whitton and Potts 2000 ). The phylum is divided into five subsections and comprises unicellular and filamentous strains (Rippka et al. 1979 ). Some of the latter are capable to differentiate some vegetative cells into specialized cell types (i.e., heterocysts) (Stewart et al. 1969 ). As photosynthetic microorganisms, cyanobacteria are appealing models for studying photosynthetic processes on a single-cell level and aspired hosts for the large-scale production of high-value molecules in industry (Abed et al. 2009 ). Despite their high potential in these fields, strategies for genetic engineering and tightly controlled gene expression still lag behind the tools available for common heterologous hosts. Methods for classical mutagenesis are well established in model cyanobacteria (Grigorieva and Shestakov 1982 ; Marraccini et al. 1993 ) and also the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-technology has successfully been applied in these organisms (Ungerer and Pakrasi 2016 ; Wendt et al. 2016 ). However, the application of these methods is limited by the toxicity of Cas9 (Wendt et al. 2016 ), the high ploidy level of many cyanobacteria (Griese et al. 2011 ) and the varying efficiency in the diverse cyanobacterial strains. Another obstacle in genetic engineering is the lack of regulatory elements and induction systems that can be precisely controlled. Several commonly used heterologous promoters are substantially leaky or perform poorly in cyanobacteria (Guerrero et al. 2012 ; Huang et al. 2010 ). As an example, expression levels obtained from Ptrc (a hybrid of the trp and lac promoters from E. coli ) are nearly equal in the presence or absence of the inducer. Native promoter systems in contrast often allow relatively tight induction control, but usually yield lower expression levels and depend on inducers that regulate and thus interfere with endogenous metabolic processes in cyanobacteria (Guerrero et al. 2012 ; Huang et al. 2010 ). Reasons for the respective technical restrictions are the differences in gene expression control in heterotrophic hosts compared to cyanobacteria and the limited knowledge on the underlying mechanisms in the latter. Anyway, in the last years research in this field has been intensified, some existing promoter systems could be improved and novel promising promoters were engineered for the use in cyanobacteria. Moreover, RNA-based tools such as riboswitches, riboregulators or small RNAs (sRNAs) as well as genetic circuits emerged as highly promising strategies for gene expression control in cyanobacteria (Higo et al. 2017 , 2018b ; Ma et al. 2014 ; Taton et al. 2017 ; Ueno et al. 2018 ). Furthermore, striking improvements of gene expression could be achieved by alteration of regulatory elements such as the ribosome binding site (RBS) (Englund et al. 2016 ; Thiel et al. 2018 ; Wang et al. 2018 ). Different tools for RBS design are available, such as the Ribosome Binding Site Calculator (Salis 2011 ), the RBS Designer (Na and Lee 2010 ) or the UTR Designer (Seo et al. 2013 ). More details on the importance of RBS choice and engineering are provided elsewhere (Immethun and Moon 2018 ; Sun et al. 2018a ). In this mini-review, we focus on promoters, riboswitches, riboregulators and genetic circuits. The knowledge on traditionally used systems is briefly summarised and current findings and novel tools are more accurately discussed. Details on all regulatory tools are provided in Online Resource 1. Abbreviations of the discussed cyanobacterial strains and short information about them are provided in Table 1 . Table 1 Cyanobacterial strains Strain Abbreviation Notes Anabaena sp. PCC 7120 A_7120 Model filamentous, heterocyst-forming cyanobacterium Anabaena variabilis ATCC 29413 Av_29413 Model filamentous, heterocyst-forming cyanobacterium Chroococcidiopsis – Ancient coccoidal cyanobacterium (Imre Friedmann and Ocampo-Friedmann 1995 ) Leptolyngbya sp. strain BL0902 L_BL0902 Filamentous, grows well in outdoor bioreactors Nostoc punctiforme ATCC 29133 Np_29133 Filamentous, heterocyst-forming cyanobacterium Spirulina platensis strain C1 Sp_C1 Planktonic filamentous cyanobacterium Synechocystis sp. PCC 6803 Sy_6803 Model unicellular cyanobacterium Synechocystis sp. strain PCC 6714 Sy_6714 Closely related to Sy_6803 Synechocystis sp. strain ATCC27184 Sy 27184 Glucose-tolerant Sy_6803 Synechocystis sp. strain WHSyn Sy_WHSyn Unicellular cyanobacterium, capable of grow in a wide range of salinities Synechococcus sp. strain PCC 73109 Sc_73109 Closely related to Sce_7002 Synechococcus elongatus PCC 6301 Sce_6301 Freshwater unicellular cyanobacterium Synechococcus elongatus PCC 7942 Sce_7942 Model freshwater unicellular cyanobacterium, formerly named Anacystis nidulans R2 Synechococcus elongatus PCC 7002 Sce_7002 Model marine unicellular cyanobacterium, fast growing Synechococcus elongatus UTEX 2973 Sce_UTEX Unicellular cyanobacterium, rapid autotrophic growth"
} | 1,929 |
34123692 | PMC8164909 | pmc | 6,601 | {
"abstract": "Self-assembled supramolecular structures in living cells and their dynamics underlie various cellular events, such as endocytosis, cell migration, intracellular transport, cell metabolism, and gene expression. Spatiotemporally regulated association/dissociation and generation/degradation of assembly components is one of the remarkable features of biological systems. The significant advancement in DNA nanotechnology over the last few decades has enabled the construction of various-shaped nanostructures via programmed self-assembly of sequence-designed oligonucleotides. These nanostructures can further be assembled into micrometer-sized structures, including ordered lattices, tubular structures, macromolecular droplets, and hydrogels. In addition to being a structural material, DNA is adopted to construct artificial molecular circuits capable of activating/inactivating or producing/decomposing target DNA molecules based on strand displacement or enzymatic reactions. In this review, we provide an overview of recent studies on artificially designed DNA-based self-assembled systems that exhibit dynamic features, such as association/dissociation of components, phase separation, stimulus responsivity, and DNA circuit-regulated structural formation. These biomacromolecule-based, bottom-up approaches for the construction of artificial molecular systems will not only throw light on bio-inspired nano/micro engineering, but also enable us to gain insights into how autonomy and adaptability of living systems can be realized.",
"conclusion": "Conclusion and outlook DNA nanotechnology has enabled the construction of various-shaped nanostructures capable of self-assembling into supramolecular structures. It has also promoted the development of artificial molecular circuits that produce/degrade DNA with a specific sequence. Reversible supramolecular assembly, including re-organization, dynamic structural formation/decomposition, and liquid droplet formation via LLPS of DNA nanostructures, was achieved by designing shape complementarity, adjusting interaction strengths, and regulating the solution temperature. Autonomous molecular self-assembly was realized using an artificial molecular circuit with sequence-designed DNA and enzymes. Although theoretical approaches based on free energy of association and dissociation of assembly components are still desired to be studied, these experimental achievements demonstrate the potential use of DNA nanotechnology in realizing artificial molecular systems that are reminiscent of biological systems mainly composed of protein molecules. In biological systems, information encoded in the genomic DNA is transcribed into an RNA molecule and then translated into a polypeptide chain, which is further folded into a functional 3D structure, the protein. In DNA-based artificial systems, although they are similar to biological systems in that DNA sequences provide blueprint of the systems, DNA molecules themselves are folded into designed structures and exhibit prescribed functions. Functions realized by DNA nanotechnology is not limited to those achieved by natural nucleotides. Artificial nucleic acids and nucleotides with chemical modifications provide means to expand the functionality of DNA nanostructures. One of the limitations in DNA-based artificial systems is that they cannot spontaneously initiate optimization, while the natural systems are optimized through evolution and natural selection. The recent success in machine-leaning-based improvement of protein functions [ 63 ], using in silico approaches, offer powerful means to optimize structural components and reaction networks of artificial systems to enhance their functions. Combining bottom-up molecular designing and top-down micro-device engineering may also provide an alternative approach to realize more sophisticated systems. As described in this review, metabolism-like sequential production and decomposition of structural materials was demonstrated using the DNA-based reaction network with the aid of the microfluidic device. Considering that microfluidic devices are often used to model non-equilibrium cellular systems, such as those of oscillatory gene expression [ 64 ] and molecular transportation [ 65 ], the combination of microfluidics and DNA nanotechnology may lead to the construction of a dynamic artificial molecular system based on energy dissipation. It should be noted that various techniques, such as induction of changes in ionic strength [ 7 ] and/or pH [ 8 ], light–irradiation [ 66 , 67 ], and addition of fuel molecules [ 68 , 69 ], can be employed to trigger self-assembly of DNA nanostructures, enabling the construction of various artificial signal-responsive molecular systems that exhibit deformation [ 67 ], locomotion [ 70 ], swarm behaviors [ 71 ], and production of components of supramolecular structures [ 72 ]. The recent development of reversible mechanical motion of DNA nanostructures [ 73 ] and DNA-based circuits [ 74 ] with modularity would empower DNA nanotechnology to enable designing a molecular system that possesses adaptability to environmental changes [ 75 , 76 ]. We anticipate that a bottom-up approach towards the construction of these artificial molecular systems, such as artificial cells and molecular robots [ 77 – 80 ], will elucidate how autonomy and adaptability of living systems can be realized.",
"introduction": "Introduction Self-assembly is a process by which individual components spontaneously form organized patterns or supramolecular structures. It underlies a variety of cellular events. For instance, endocytosis and subsequent vesicle trafficking are often mediated by proteins with self-assembling properties, represented by clathrin, which assembles into a polyhedral lattice on intracellular membranes to form protein-coated vesicles [ 1 ]. The basis for cell migration [ 2 ] and intracellular transport [ 3 ] is provided by self-assembled cytoskeletal filaments, such as actin filaments and microtubules, comprising of actins and tubulins, respectively. Gene transcription [ 4 ] and stress granule formation [ 5 ] are related to phase separation of proteins and/or nucleic acids, which leads to the formation of molecular condensates. Creating a molecular self-assembling system resembling a biological system will widen our understanding of living cells and accelerate the development of nano/micro technologies inspired by biological systems. One of the noteworthy features of biological self-assemblies is the dynamic association and dissociation of their assembly components. This property aids in finding appropriate assembly pairs through repetitive attachments and detachments of molecular components, thereby facilitating the formation of correctly assembled structures [ 6 ]. Furthermore, it supports the assembly/disassembly of structures in response to environmental changes [ 7 , 8 ]. These implications suggest that designing molecular interactions that allow dynamic association and dissociation is an essential step for the construction of the bio-inspired self-assembly systems using artificially synthesized molecules. In this review, we provide an overview of the recent studies on artificially designed DNA-based self-assembly systems that exhibit dynamic features, such as regulatable association/dissociation of assembly components, fusion/fission of macromolecular droplets formed by phase separation, environment-dependent assembly, and chemical circuit-regulated structural formation. Following a brief introduction on the general approaches for designing DNA nanostructures and molecular circuits, we focus on the strategies used for realizing dynamic molecular systems that comprise of DNA nanostructures and exhibit responsivity to changes in the environment, such as salt concentration and solution temperature. We then describe the advances in DNA self-assembled systems coupled with molecular circuits. Finally, we discuss the potential uses of DNA nanotechnology in the construction of artificial cells and molecular robots."
} | 2,011 |
39917963 | PMC11803306 | pmc | 6,603 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,603 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,603 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,603 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,603 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,604 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,604 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,604 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,604 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,604 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,605 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,605 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,605 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,605 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,605 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,606 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,606 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,606 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,606 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,606 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,607 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,607 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,607 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,607 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39917963 | PMC11803306 | pmc | 6,607 | {
"abstract": "Abstract Reference genomes are key resources in biodiversity conservation. Yet, sequencing efforts are not evenly distributed across the tree of life raising concerns over our ability to enlighten conservation with genomic data. Good-quality reference genomes remain scarce in octocorals while these species are highly relevant targets for conservation. Here, we present the first annotated reference genome in the red coral, Corallium rubrum (Linnaeus, 1758), a habitat-forming octocoral from the Mediterranean and neighboring Atlantic, impacted by overharvesting and anthropogenic warming-induced mass mortality events. Combining long reads from Oxford Nanopore Technologies (ONT), Illumina paired-end reads for improving the base accuracy of the ONT-based genome assembly, and Arima Hi-C contact data to place the sequences into chromosomes, we assembled a genome of 532 Mb (20 chromosomes, 309 scaffolds) with contig and scaffold N50 of 1.6 and 18.5 Mb, respectively. Fifty percent of the sequence (L50) was contained in seven superscaffolds. The consensus quality value of the final assembly was 42, and the single and duplicated gene completeness reported by BUSCO was 86.4% and 1%, respectively (metazoa_odb10 database). We annotated 26,348 protein-coding genes and 34,548 noncoding transcripts. This annotated chromosome-level genome assembly, one of the first in octocorals and the first in Scleralcyonacea order, is currently used in a project based on whole-genome resequencing dedicated to the conservation and management of C. rubrum .",
"introduction": "Introduction Octocorallia is a diverse clade of cnidarian composed of more than 3,500 species (gorgonians and soft corals) shared between two orders: Scleralcyonacea and Malacalocyonacea. This clade is characterized by an interesting phylogenetic position within the class Anthozoa as the sister group of Hexacorallia. Octocorals and hexacorals, in particular stony corals (order Scleractinia), shared various ecological features. For instance, they are characterized by a key ecological role as habitat-forming species in benthic habitats from shallow tropical to deep and polar seas (e.g. Gomez-Gras et al. 2021 ). They are also under strong conservation concerns owing to the impacts of global change, including extreme climatic events (e.g. Estaque et al. 2023 ). In spite of these similarities, genomic resources remain scarce in octocorals compared with stony corals. The few genomes available in octocorals (e.g. Ledoux et al. 2020 ) represent <1% of species diversity (see Ahuja et al. 2024 ) and target exclusively species from the Malacalocyonacea order. Besides this biodiversity genomics gap, the lack of genomic resources limits the integration of genomics and population genetics data into ongoing conservation efforts ( Formenti et al. 2022 ). The red coral, Corallium rubrum , is a habitat-forming octocoral ( Fig. 1 ) with a central structural role in benthic communities from the Mediterranean and the neighboring Atlantic ( Laborel and Vacelet 1961 , Zibrowius et al. 1984 ). This iconic species with high cultural and economic value is critically impacted by two anthropogenic pressures. First, as a “precious coral,” it has been harvested for jewelry since ancient times and owing to its market value (>1,000€/kg), the species has been overharvested and intensively poached ( Ledoux et al. 2016 ). Second, C. rubrum has been recurrently impacted in the last 20 years by mass mortalities, linked to marine heatwaves, across thousands of kilometers of coastal habitats ( Garrabou et al. 2022 ). The species with slow population dynamics ( Montero-Serra et al. 2018 ) and restricted connectivity ( Ledoux et al. 2010 ; Horaud et al. 2024 ) is characterized by a low resilience capacity ( Linares et al. 2012 ). The combination of overharvesting and mass mortality events is driving steep demographic declines, raising concerns over the evolutionary trajectory of the species ( Montero-Serra et al. 2019 ). Fig. 1. a) Coralligenous habitat dominated by the red coral, C. rubrum (picture by J. Garrabou) . b) Phylogenetic relationships among different anthozoans species including five octocorals ( Dendronephthya gigantea , Paramuricea clavata , Phenganax marumi , Xenia sp., and C. rubrum ) and three hexacorals ( Actinia tenebrosa , Plumapathes pennacea , and Acropora palmata ) for which good-quality assemblies are available. The tree is based on 298 single-copy orthologous genes identified with BUSCO. c) BlobToolKit Snailplot showing different assembly metrics. The main plot is divided into 1,000 size-ordered bins around the circumference with each bin representing 0.1% of the 532 Mb assembly. The distribution of scaffold lengths is shown in dark gray with the plot radius scaled to the longest scaffold present in the assembly (115,004,408 bp, shown in red). Orange and pale-orange arcs show the N50 and N90 scaffold lengths (18,521,360 and 2,388,869 bp), respectively. The pale gray spiral shows the cumulative scaffold count on a log scale with white scale lines showing successive orders of magnitude. The blue and pale-blue areas around the outside of the plot show the distribution of GC, AT, and N percentages in the same bins as the inner plot. A summary of complete, fragmented, duplicated, and missing BUSCO genes in the metazoa_odb10 set is shown in the top right. d) Chromatin contact map generated from Arima2 Hi-C data shows the 20 chromosomes (2 n = 40) that represent 89.3% of the assembled C. rubrum genome. In this context, C. rubrum is receiving conservation attention from scientists and biodiversity managers (included in Barcelona Convention, EU Habitat Directive and listed as “endangered” by IUCN [ Otero et al. 2017 ]). Yet, major knowledge gaps in relation to genome diversity, effective population size, and adaptation to the local environment remain and should be filled to improve existing conservation policies. As a part of the Catalan Initiative for the Earth BioGenome Project ( Corominas et al. 2024 ), we assembled and annotated the first chromosome-level reference genome for C. rubrum and for the Scleralcyonacea order. This reference genome will support a conservation genomics project funded by the Biodiversity Genomics Europe ( https://biodiversitygenomics.eu ), which is based on whole-genome resequencing. This project will infer demographic history and contemporary processes shaping the intraspecific genetic patterns with direct applications for red coral conservation and management.",
"discussion": "Results and Discussion Genome Assembly The reference genome of C. rubrum was assembled based on ONT long reads, Illumina paired-end reads, and Arima Hi-C contact data ( supplementary table S1, Supplementary Material online) analyzed with the pipeline CLAWS v2.1 ( Gomez-Garrido 2023 ) following the flowchart shown in supplementary fig. S1, Supplementary Material online. Results obtained with Genomescope2 ( supplementary fig. S2, Supplementary Material online) suggest a genome size of around 500 Mb and 1.2% heterozygosity rate. The base assembly obtained with NextDenovo (ND) v2.4.1 comprised a total assembly span of 568 Mb (876 contigs, Table 1 ). The manual curation following the scaffolding with the Hi-C data resulted in a total of 8 cuts in contigs, 15 breaks at gaps, and 31 joins. The remaining edits corresponded to four unlocalized sequences and one haplotig. A total of 20 autosomes were assembled, and no sex chromosomes were identified. A total of 87 unplaced scaffolds (corresponding to 36 Mb of sequences) belonging to non-Cnidaria phyla were removed from the assembly (see blobplot supplementary fig. S3, Supplementary Material online). The final chromosome-level assembly comprised 532 Mb (20 chromosomes, 309 scaffolds; Table 1 ). The contig and scaffold N50 of the final assembly are 1.6 and 18.5 Mb, respectively, and 50% of the sequence (L50) is placed in seven superscaffolds. Merqury ( Rhie et al. 2020 ) and BUSCO ( Manni et al. 2021 ) were run to estimate the accuracy and completeness of the genome assembly. The consensus Phred-scaled base quality (quality value [QV] = −10log 10 P where P is the probability of an incorrect base) of the final assembly was estimated by Merqury as 42 (>99.99% accurate). The gene completeness reported by BUSCO v5 was 87.4% (86.4% single and 1% duplicated BUSCOs) using the metazoa_odb10 database ( Fig. 1 ; Table 1 ), which is similar to values reported in other octocorals (e.g. 90.1% in Xenia sp.; see Hu et al. 2020 ). Table 1 Statistics of the different versions of the genome assembly Assembly ND ND + hypo ND + hypo + purged jaCorRubr1.2 Contig N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 1,625,182 bp Scaffold N50 1,993,440 bp 1,992,814 bp 2,029,805 bp 18,521,360 bp Scaffold L50 84 84 79 7 Total sequences 876 876 784 309 Assembly span 567,713,602 bp 567,661,090 bp 545,517,441 bp 532,310,562 bp BUSCO a single complete 84.3% 88.1% 88.2% 86.4% BUSCO a duplicated complete 2.3% 2.5% 1.2% 1.0% QV 33 42 42 42 K-mer completeness 83.8% 85.8% 84.9% 83.4% \n a BUSCO v5 metazoa_odb10 database. Genome Annotation Using RNA-seq data produced for this study ( supplementary table S3, Supplementary Material online), we annotated a total of 26,348 protein-coding genes that produce 32,180 transcripts (1.22 transcripts per gene) and encode for 30,774 unique protein products. We were able to assign functional labels to 36% of the annotated proteins. The annotated transcripts contain 7.13 exons on average, with 79% of them being multiexonic ( supplementary table S2, Supplementary Material online). In addition, 35,300 noncoding transcripts were annotated, of which 31,357 and 3,943 are long and short noncoding RNA genes, respectively. A total 64.4% of the assembly was identified as repetitive. The BUSCO single and duplicated completeness on this predicted protein set are 78.9% and 1.3%, respectively (complete: 80.2%, fragmented: 1.9%, missing: 17.9% with n = 954). The reference genome presented here is the backbone of an ongoing population genomics project dedicated to the conservation and management of C. rubrum . This chromosome-level assembly, one of the first in octocorals and the first in Scleralcyonacea order, contributes to reduce the current taxonomic bias in the generation of high-quality genome resources."
} | 2,586 |
39345469 | PMC11429942 | pmc | 6,608 | {
"abstract": "Most of Earth’s iron is mineral-bound, but it is unclear how and to what extent iron-oxidizing microbes can use solid minerals as electron donors. A prime candidate for studying mineral-oxidizing growth and pathways is Sideroxydans lithotrophicus ES-1, a robust, facultative iron oxidizer with multiple possible iron oxidation mechanisms. These include Cyc2 and Mto pathways plus other multiheme cytochromes and cupredoxins, and so we posit that the mechanisms may correspond to different Fe(II) sources. Here, S. lithotrophicus ES-1 was grown on dissolved Fe(II)-citrate and magnetite. S. lithotrophicus ES-1 oxidized all dissolved Fe 2+ released from magnetite, and continued to build biomass when only solid Fe(II) remained, suggesting it can utilize magnetite as a solid electron donor. Quantitative proteomic analyses of S. lithotrophicus ES-1 grown on these substrates revealed global proteome remodeling in response to electron donor and growth state and uncovered potential proteins and metabolic pathways involved in the oxidation of solid magnetite. While the Cyc2 iron oxidases were highly expressed on both dissolved and solid substrates, MtoA was only detected during growth on solid magnetite, suggesting this protein helps catalyze oxidation of solid minerals in S. lithotrophicus ES-1. A set of cupredoxin domain-containing proteins were also specifically expressed during solid iron oxidation. This work demonstrated the iron oxidizer S. lithotrophicus ES-1 utilized additional extracellular electron transfer pathways when growing on solid mineral electron donors compared to dissolved Fe(II).",
"introduction": "Introduction To microbes, minerals provide surfaces to live on, a source of nutrients, and in some cases, a substrate for respiration, e.g. for Fe(III)- and S(0)-reducing organisms. We are increasingly finding that microbes can also oxidize minerals, particularly iron minerals such as magnetite ( 1 – 3 ), green rust ( 4 ), pyrite ( 5 ), biotite ( 6 ), and smectites ( 6 – 8 ), using these as a source of electrons, and therefore energy. To use minerals as electron donors, cells must be able to transfer electrons from outside the cell to the interior. This capability, known as extracellular electron uptake (EEU) has been demonstrated not only in cultures with minerals but also by experiments on cathodes in bioelectrochemical systems, which provide a continuous supply of electrons directly to colonizing cells ( 9 – 13 ). EEU is a capability of iron-oxidizing bacteria (FeOB), which need to keep iron outside of cells to prevent various detrimental reactions from occurring in the periplasm or cytoplasm ( 14 , 15 ). Most work on FeOB has focused on oxidation of dissolved Fe 2+ , but if this EEU capability can be adapted to oxidize solid minerals, it would give an energetic advantage, given that most of Earth’s iron is mineral-bound. However, we do not know how common mineral oxidation is amongst microorganisms. To recognize and track mineral oxidation, we need to unravel the mechanisms, i.e. the genes and proteins involved. This requires an organism that can grow both on dissolved and solid substrates. Among the few reliable chemolithotrophic FeOB isolates, the Gallionellaceae Sideroxydans lithotrophicus ES-1 stands out as having a versatile metabolism, able to grow by oxidizing dissolved Fe 2+ , Fe(II)-smectite clays, as well as thiosulfate ( 7 , 16 – 18 ). Sideroxydans species have been identified in many environments, including a variety of sediments ( 19 , 20 ), brackish, freshwater, or groundwater systems ( 16 , 21 – 30 ), and rice paddies or other wetlands ( 31 – 33 ), suggesting this genus is highly adaptable, likely linked to its metabolic versatility. S. lithotrophicus ES-1 has a closed, sequenced genome that encodes multiple possible enzymatic pathways for iron oxidation ( 17 , 34 , 35 ). The genome encodes three isoforms of the iron oxidase Cyc2, a fused monoheme cytochrome-porin which has been biochemically demonstrated to oxidize dissolved Fe 2+ ( 36 , 37 ). It also encodes MtoAB which is homologous to the iron-oxidizing PioAB complex of the photoferrotroph Rhodopseudomonas palustris TIE-1 ( 38 ) and the iron-reducing complex MtrAB in Shewanella species ( 39 , 40 ). Porin-cytochrome complexes like MtrAB and PioAB form conduits across the outer membrane, so are key in iron-reducer interactions with minerals (MtrAB; ( 41 , 42 )), and in oxidation of a cathode (PioAB; ( 43 )). Given the predicted structural similarity to these other systems, and that heterologously expressed MtoA has been shown to oxidize Fe(II) ( 44 ), MtoAB could also play a role in oxidation of extracellular minerals. The genome of S. lithotrophicus ES-1 also encodes other porin-cytochrome complexes with large multiheme cytochrome subunits and a plethora of heme motif (CXXCH)-containing proteins including probable periplasmic electron carriers ( 34 , 45 ). Thus, S. lithotrophicus ES-1 appears well-endowed with multiple potential iron oxidation and other EEU mechanisms, though it is not certain which ones enable oxidation of minerals. Recent work on S. lithotrophicus ES-1 demonstrated for the first time the ability of this organism to utilize a solid Fe(II) source for growth, and gave us some initial clues to the possible mineral oxidation mechanism ( 7 ). The porin MtoB was detected in cells grown on Fe(II)-smectite clays but not dissolved Fe(II)-citrate. The multiheme cytochrome MtoA was not observed, possibly because multiheme cytochromes can be difficult to detect by mass spectrometry due to the large number of covalently modified cysteines per peptide length. The proteomics was supplemented with RT-qPCR, which confirmed that mtoA was upregulated on smectite compared to Fe(II)-citrate. This led to the hypothesis that in S. lithotrophicus ES-1, the MtoAB complex plays a specific role in oxidation of solid iron minerals, but not aqueous Fe(II)-citrate ( 7 ). However, given that only a limited proportion of proteins (<25% of total proteome) were detected in this study, improvements to enhance proteome coverage for low-input samples are necessary to accurately distinguish proteins expressed on solid substrates. Incomplete proteomes can result from low biomass input, as can often be the case for FeOB, since cultures are challenging. In the smectite study of S. lithotrophicus ES-1, large volumes of cultures were required to obtain enough cells for molecular analyses such as proteomics ( 7 ). Recently, this need for large culture volumes was eliminated with the development of a novel on-filter in-cell (OFIC) processing pipeline for proteomic analyses of low biomass samples ( 46 – 48 ). This single-vessel method avoids cell lysis, which tends to cause significant sample loss particularly for low-input samples and performs all the treatments in the same filter device, thus drastically simplifies sample preparation and improves proteomic sensitivity. In a pilot study, ~76% of the entire S. lithotrophicus ES-1 proteome was identified from just ten milliliters of culture (~1×10 9 cells) ( 46 ). Minerals with high Fe(II) content commonly interfere with molecular extractions, making it difficult to obtain complete ‘omics’ datasets. In the smectite study, clays interfered with downstream analyses ( 7 ), so we investigated the possibility of using magnetite, which can be easily removed from cultures with a magnet. As a mixed-valence iron mineral (Fe II Fe III 2 O 4 ) common in sediments ( 49 ), magnetite could potentially serve as an electron donor to support the growth of Fe(II)-oxidizing bacteria. We hypothesized S. lithotrophicus ES-1 could grow by oxidizing Fe(II) in magnetite, in part because S. lithotrophicus ES-1 grows on other iron minerals, and also based on previous observations of other FeOB that were able to oxidize magnetite. The photoferrotroph Rhodopseudomonas palustris TIE-1 oxidized chemically synthesized magnetite ( 1 , 50 ) while nitrate-reducing Fe(II)-oxidizers including Acidovorax sp. 2AN and the enrichment culture KS have been observed to oxidize biogenic magnetite ( 2 , 3 ). If S. lithotrophicus ES-1 is able to oxidize magnetite, this would give us an optimal system for investigating proteins involved in solid Fe(II) oxidation. Here, we tested S. lithotrophicus ES-1 growth on three batches of abiogenic magnetite (two synthesized in house and one purchased from a commercial vendor) and compared protein expression to cells grown on dissolved Fe 2+ . The substrates differed in particle size, crystallinity, and solubility, which allowed us to evaluate growth and Fe(II) oxidation mechanisms in the presence of different proportions of solid and dissolved Fe 2+ . This work gives further evidence that FeOB can grow by oxidizing mineral-bound Fe(II) along with insight into the mechanisms that enable electron uptake from solids.",
"discussion": "Discussion Most of Earth’s iron is mineral-bound, potentially providing a vast source of energy if microbes can obtain electrons from minerals. Chemolithotrophic iron-oxidizing bacteria could hypothetically grow by mineral oxidation, but to date, there has been scant proof of this ability. Here we show that a well-studied iron oxidizer Sideroxydans lithotrophicus ES-1 can grow by oxidizing magnetite and constrain the likely enzymatic pathway via proteomics. Unraveling iron oxidation mechanisms has been hampered by problems with culturing as well as RNA and protein extractions, but recent advances in on-filter, in-cell digestion proteomics methods now enable the study of proteins in low-yield, difficult to grow organisms like S. lithotrophicus ES-1 ( 46 – 48 ). Previous studies on smectite-grown S. lithotrophicus ES-1 included RT-qPCR and proteomics, but proteomics experiments were plagued with a number of issues including interference from iron and filter extractables, as well as the requirement for large volumes of culture to obtain enough cells ( 7 ). Proteomics (not transcriptomics) was required to unravel the mechanisms of magnetite oxidation by providing information on the presence of functional protein. Compared to previous studies, this study improved the overall protein detection rate (>78%) with fewer cells (~3–4×10 8 cells), and improved detection of multiheme cytochrome proteins, which enables us to better evaluate the mechanisms of iron oxidation. We are optimistic that the proteomics pipeline used here will enable the study of other organisms that are difficult to grow. While it is well-known that iron-oxidizing bacteria like S. lithotrophicus ES-1 can grow by oxidizing dissolved Fe(II), here we established that it could grow on the solid mixed-valence iron mineral magnetite (Fe II Fe III 2 O 4 ). We carefully followed the progression of iron redox in both dissolved and mineral phases and noted that magnetite oxidation occurred even in the presence of dissolved Fe(II), but the magnetite was never fully oxidized (lowest Fe(II):Fe(III) = 0.3; Fig. 4 ). Incomplete oxidation of magnetite was similarly observed in experiments with Rhodopseudomonas palustris TIE-1 and enrichment culture KS ( 1 , 3 ), suggesting some amount of Fe(II) is not available for either biological or chemical oxidation. Partial oxidation may occur due to kinetic limitations in electron or iron atom diffusion through the magnetite structure ( 56 ), resulting in preferential oxidation of the surface as seen for the commercial magnetite ( Fig. 4D ). Another reason may be that the redox potential of magnetite increases with oxidation ( 56 ), causing some of the Fe(II) to be inaccessible due to thermodynamics. Given the various challenges with accessing minerals, it was a surprise that S. lithotrophicus ES-1 uses magnetite even in the presence of some dissolved Fe(II). Our results demonstrate that iron-oxidizing bacteria not only oxidize magnetite and dissolved Fe(II) individually, they can use both solutes and solids simultaneously, opening the question of how common such flexibility may be among other iron oxidizers. The ability to access electrons from both dissolved and solid Fe(II) may require separate mechanisms appropriate for each type of Fe(II). Oxidation of solid electron donors likely involves the multiheme cytochrome-porin complex MtoAB, which could transfer electrons across the outer membrane. The MtoAB pathway seems to be specifically expressed by S. lithotrophicus ES-1 for solid Fe(II) oxidation. In previous studies, when S. lithotrophicus ES-1 was grown on Fe(II)-citrate, mto transcripts were very low ( 7 , 17 ). In that study, which also analyzed incomplete proteomes, as well as in our current more comprehensive proteome work, most of the proteins of the Mto pathway were not detected during growth on dissolved Fe(II)-citrate ( Table 1 and ( 7 )). However, when grown on solid magnetite, MtoA/MtoB/CymA(ImoA)/Slit_2494 was one of the most significantly enriched sets of proteins ( Fig. 6 ; Table S1 ), suggesting these proteins are reserved for oxidation of solid Fe(II) sources. This fits with previous research demonstrating that purified MtoA directly interacted with magnetite and was able to extract reactive Fe(II) from within solid ferrite spinel nanoparticles ( 57 ). The homologous MtrAB system of iron-reducing Shewanella has been shown to be electrochemically reversible and capable of electron uptake ( 58 ). Furthermore, the iron-oxidizing homolog in Rhodopseudomonas palustris TIE-1, PioAB, has been shown to play a role in the oxidation of solid electrodes ( 9 , 43 ), and R. palustris can oxidize magnetite (although the proteins involved were not investigated) ( 1 ). Combined, these findings strongly imply that the MtoAB multiheme cytochrome-porin complex enables S. lithotrophicus to conduct extracellular electron uptake from solid electron donors (magnetite, smectite), and could do so in other organisms as well. Dissolved Fe(II) is likely oxidized by another iron oxidase of S. lithotrophicus ES-1, Cyc2, which is also expressed during growth and oxidation of magnetite. Cyc2 is a monoheme cytochrome fused to a porin, and structural constraints lead to the prediction that Cyc2 must be an oxidase of aqueous Fe 2+ ions ( 36 ). Previous work showed Cyc2, specifically the first isoform of Cyc2 (Slit_0263), is highly expressed in all growth conditions, including dissolved Fe(II)-citrate, solid Fe(II)-smectite clays, and thiosulfate ( 7 , 17 ). That continues to be true during growth on magnetite. We hypothesize that dissolved Fe(II) (i.e. Fe 2+ ) is the preferred electron donor of S. lithotrophicus ES-1 and thus it maintains readiness to oxidize dissolved Fe(II) regardless of its presence by constitutively expressing Cyc2 at high levels. It is also possible that dissolved Fe(II) at concentrations below our detection limit is being shed from the magnetite, and is acting as an electron shuttle, prompting the expression of Cyc2. Another possibility could be that Cyc2 plays a role in iron sensing. In any case, S. lithotrophicus ES-1 appears to express its iron oxidases differently. The smaller monoheme cytochrome Cyc2 is expressed under all conditions, while the larger and more energetically expensive complex MtoAB is only expressed when necessary, i.e. when a solid electron source is present. Magnetite oxidation may also involve copper-containing proteins, cupredoxins. Three uncharacterized copper-containing proteins were significantly more highly expressed in the magnetite cultures than the Fe(II)-citrate cultures ( Fig. 6 ; Table S1 ). Two of these proteins possess typical multicopper oxidase motifs (Slit_1817 and Slit_1818). The third (Slit_1816) does not and is significantly larger, with additional domains similar to adhesions and polysaccharide lyases. These proteins are encoded together in the genome, along with a few smaller proteins, a SCO1/SenC protein, and a hypothetical cytochrome. Similar gene clusters are found in other organisms, mostly other members of the Burkholderiales like Paraburkholderia and Ralstonia but also in Anaeromyxobacter and Steroidobacteraceae ( Fig. S4 ). While the roles of these cupredoxin proteins are not known, they are predicted to be extracellular proteins, which would enable access to magnetite particles. Other copper-containing proteins have been reported with ferroxidase ( 59 ) and Mn(II)-oxidase activity ( 60 , 61 ), and play a role in iron oxidation in acidophilic iron oxidizers ( 62 , 63 ); thus it is plausible that the cupredoxins identified here are playing a role in solid Fe(II) oxidation in S. lithotrophicus ES-1. Given the growing recognition of microbial mineral oxidation, it will be important to increase our understanding of the mechanisms in order to recognize and trace the activities of mineral-oxidizing microbes. The evidence obtained so far suggests that magnetite and Fe(II)-smectite oxidation in S. lithotrophicus ES-1 involves the MtoAB complex, a decaheme cytochrome-porin complex homologous to the Shewanella Fe-reductase MtrAB. In studies of Shewanella, Geobacter, and other FeRB, we have learned that multiheme cytochromes (MHCs) are well-suited for redox interactions with minerals ( 64 , 65 ), and their useful characteristics translate well into advantages for oxidizing minerals: 1) When housed in an outer membrane porin, MHCs can transfer electrons across the membrane to or from a mineral. An outer membrane-embedded MHC could either have direct contact with a mineral or transfer to/from extracellular MHC that contact minerals. 2) Unlike single heme cytochromes, MHCs have wide ranges of redox potentials that overlap with mineral redox potentials, which also span wide ranges and can change as minerals are oxidized and reduced. The multiheme cytochrome MtoA exhibits a range of redox potentials (−400 mV to +100 mV vs. SHE; ( 44 , 66 ) that overlaps with 10–20 nm magnetite (−480 to +50 mV vs. SHE) and smectites (e.g., −600 to +0 mV for SWa-1; −400 to +400 mV for SWy-2; ( 56 , 67 , 68 )). 3) MHCs can act as capacitors to store electrons, enabling microbes to continue making energy if there is an interruption in electron supply. This is more likely for minerals, which may be periodically exhausted of electron supply, in contrast to dissolved substrates that tend to be in more constant supply. So, overall, although MHCs are resource intensive – MtoAB is larger than Cyc2 (1165 vs ~440 amino acids, ten heme cofactors vs one) - the investment in biosynthetic energy and resources would enable access to electrons stored in redox-active sedimentary minerals. The utility of MHCs to FeOB is suggested by the number and diversity of MHCs in known FeOB. More than 60% of the iron-oxidizing Gallionellaceae possess a putative decaheme or larger cytochrome, suggesting many of these iron oxidizers may be able to utilize solid electron donors ( 45 ). Many of the Gallionellaceae possess multiple MHC gene clusters. For instance, S. lithotrophicus ES-1 encodes MtoAB plus at least two other MHC complexes known as PCC3; these other cytochromes could be used by S. lithotrophicus ES-1 to oxidize different solid substrates. It remains to be seen if these are deployed under different conditions individually for distinct substrates or work simultaneously. It will be necessary to further constrain the functional relationships between specific MHCs, minerals, and growth conditions to enable gene- and protein-based tracking of microbial mineral oxidation. Multiheme cytochromes are being increasingly recognized in diverse organisms ( 69 – 74 ), opening the possibility of discovering new mineral-oxidizing organisms and broadening our understanding of the functionality of multiheme cytochromes. Overall, our work expands our understanding of how magnetite can promote microbial growth, which has implications for biogeochemical cycling in sediments, aquifers, and rock-hosted environments. In these systems, magnetite can serve as an electron donor to microbes, but then can be re-reduced by iron/mineral-reducing microbes. Once recharged, the magnetite can be discharged again by FeOB, and so on, cycling back and forth, making magnetite a biogeochemical redox buffer that also supports growth and associated C, N, and P transformations. As we increasingly recognize the metabolic flexibility and adaptability of iron oxidizers like S. lithotrophicus ES-1 to the varied iron sources on Earth, this will help us understand the active role of iron oxidizers in iron mineral biogeochemical cycling throughout the Earth’s environments."
} | 5,153 |
38791573 | PMC11121894 | pmc | 6,609 | {
"abstract": "Synthetic polymers, commonly known as plastics, are currently present in all aspects of our lives. Although they are useful, they present the problem of what to do with them after their lifespan. There are currently mechanical and chemical methods to treat plastics, but these are methods that, among other disadvantages, can be expensive in terms of energy or produce polluting gases. A more environmentally friendly alternative is recycling, although this practice is not widespread. Based on the practice of the so-called circular economy, many studies are focused on the biodegradation of these polymers by enzymes. Using enzymes is a harmless method that can also generate substances with high added value. Novel and enhanced plastic-degrading enzymes have been obtained by modifying the amino acid sequence of existing ones, especially on their active site, using a wide variety of genetic approaches. Currently, many studies focus on the common aim of achieving strains with greater hydrolytic activity toward a different range of plastic polymers. Although in most cases the depolymerization rate is improved, more research is required to develop effective biodegradation strategies for plastic recycling or upcycling. This review focuses on a compilation and discussion of the most important research outcomes carried out on microbial biotechnology to degrade and recycle plastics.",
"conclusion": "4. Conclusions The magnitude of plastic usage and the later production of its waste, which in most cases remains in nature for decades, makes the search for alternative bioplastic materials or other compounds a matter of major importance for today’s society. In addition, the biodegradation of these materials and, where possible, the use of their constitutive monomers as carbon and energy sources for the growth of microorganisms that can produce valuable compounds are important goals to achieve [ 145 ]. Despite the fact that there are a large number of studies based on genetic modifications, most of them were carried out through modifications in the amino acid sequence. New strategies have been recently tested, such as the use of chimeras or fusion proteins, among others, but these approaches are a minority. Further research in the use of genetic techniques, as well as combining different strategies, is necessary to obtain new strains or proteins with a greater degradative capacity of these synthetic polymers. An example of a new research field is the use of transcriptional regulators, such as Garrido et al. [ 146 ] have carried out. This work tested if the FarA transcription factor in Aspergillus oryzae was directly related to the synthesis of CutL1 and HsbA, a cutinase and a hydrophobic surface binding protein that participate in the degradation of poly(butylene succinate- co -adipate) (PBSA), a biodegradable polymer. The deletion of FarA produced a mutant with minimal concentrations of cutL1 and hsbA compared with its native strain and without the ability to degrade PBSA. This study differs from the ones described in the main text, as it consists of the basic research of an organism and its genetic regulation. This does not mean that the other studies ignore the subject of gene expression. In contrast, modifying bacteria to express an enzyme requires careful consideration of the genetic elements necessary for its successful production. The difference relies on studying genetic expression in the native organism, which cannot only help us understand their genetic regulation and metabolism but also give us hints on different approaches to enhance plastic degradation and how to use the native organism instead of relying on a different host organism. It is also relevant to point out that the research tends to focus on enhancing an enzyme’s ability to degrade specific polymers, with almost no studies evaluating how the modifications performed may change specificity toward other polymers. Limiting the analysis to just a few substrates—for which the enzyme is already specific—is comprehensible, but using a wider variety of polymers could indicate if the modifications have a greater effect than expected and may be more useful. In addition, there is little work on the tridimensional structure of the different enzymes—native or modified—that have been mentioned. Deeper research is necessary on this matter in order to better understand why changes happen regarding the affinity for the substrate or the stability, among other characteristics, according to the exchanged residues. Obtaining the structure of enzymes can be achieved not only through X-ray crystallography but also in silico by modeling. This is especially useful when proteins cannot be successfully purified and crystallized, but modeling goes even further. From molecular dynamics to substrate docking, these tools are used in some of the referenced studies to analyze enzymes’ properties and enhance their activities. Similar to plastics themselves, approaches to studying their biodegradation are diverse, and this variety often comes with a lack of consistency between studies. The conditions in which the enzymes are used can differ, and some studies do not calculate enzymatic activity and limit themselves to detecting solid plastic disintegration or monomer liberation, and the works that calculate enzymatic activity can use different units. This can sometimes make it complicated to compare their conclusions. Overall, more research is required to develop effective, i.e., quicker, safer and more efficient, biodegradation strategies for plastics, if possible. This applies not just to the plastics that are briefly addressed in this work but also to all plastics in general. Microbial biotechnology and genetic engineering approaches, together with the current development of artificial intelligence tools that provide a new direction in the study and design of novel of enzymes, can facilitate the generation and optimization of several types of plastic-degrading enzymes and valorization processes. Nowadays, we are getting closer to achieving this aim thanks to the latest advances in DNA sequencing, metagenomics, bioinformatics, genome mining and machine learning tools, in conjunction with new genetic engineering techniques, such as CRISPR-Cas technologies.",
"introduction": "1. Introduction 1.1. Definition and Classification of Plastics Plastics are a type of synthetic polymeric material based on carbon and hydrogen and with high molecular weight [ 1 ]. Industrial-scale plastic production began in the 20th Century, and their use has increased over time [ 2 , 3 ]. Plastics can be classified according to different criteria. For example, depending on the composition of their backbone, they can be homochain polymers (when their backbone is made up exclusively of carbon) or heterochain polymers (if there are other elements, like oxygen and nitrogen, present in their backbone) [ 4 ]. Depending on the monomers that they are made of, they can be classified as homopolymers if they only have one monomer or copolymers if they have two or more different monomers [ 1 ]. Depending on their thermomechanical properties, they can be thermosets if, during their fabrication, covalent bonds are established between polymer chains, giving them high resistance and a shape that cannot be modified thermically; thermoplastics, if no covalent bonds are established between polymer chains so they can be fused and reshaped; or elastomers if they have a high elasticity [ 5 ]. Depending on the presence of benzene rings in their backbone, they can be aromatic if they have benzene rings or aliphatic if they do not have benzene rings [ 6 ]. Depending on the raw material they are made from, they can be petrochemical (the raw material is petroleum) or biobased (the raw material is biomass), and depending on their degradability by organisms, they can be biodegradable or non-biodegradable. 1.2. Advantages and Disadvantages of Plastics In general, plastics are lightweight, long-lasting, inert and cheap and easy to produce. Their diversity is such that there are plastics with the ideal characteristics for almost any application. Furthermore, the use of mixtures and alloys, as well as additives, can change the properties of the material and adjust them as desired [ 1 ]. As plastics are remarkably diverse and can have vastly different properties, their uses are just as varied. They are used to make, among many others, fibers and textiles, toys, packaging, healthcare instruments, such as syringes and implants, and construction materials for insulation, pipes and cable coatings [ 1 ]. Even though plastics are generally cheap and easy to produce and have good mechanical properties, the field of engineering requires especially resistant materials for very specific applications. Though they are more expensive, the so-called “engineering plastics” are used for that purpose as they boast a high performance [ 1 ]. Other plastics, known as commodity plastics, are found in everyday items. The most used commodity plastics are poly(ethylene terephthalate) (PET), high-density polyethylene (HDPE), poly(vinylchloride) (PVC), low-density polyethylene (LDPE), polypropylene (PP) and polystyrene (PS) [ 2 , 7 , 8 ]. Products made with these plastics can be identified according to the ASTM International Resin Identification Coding System (RIC). The “Others” category includes all other plastics, as well as products made with a mixture of two or more plastics [ 9 ]. The global annual production of plastics exceeded 400 million metric tonnes (400 Mt) in 2022, 362.3 of which were new petrochemical plastics. Commodity plastics make up the following percentages (see Figure 1 ): PET 6.2%, HDPE 12.2%, PVC 12.7%, LDPE 14.1%, PP 18.9% and PS 5.2% [ 10 ]. Out of the different uses, most plastic is destined for packaging. In 2019, 142 Mt (31%) of plastics were used in packaging [ 3 , 7 ]. Between 1950 and 2022, more than 10 billion metric tonnes (10.000 Mt) of plastics were produced [ 2 , 10 , 11 ]. Despite their useful properties, the use of plastics has two main disadvantages, which have to do with the beginning and the end of their lifetime: the first one is the fact that most plastics are petrochemical, and the second one is the amount of non-biodegradable waste generated. Regarding their origin, the reserves of petroleum are limited as petroleum is a non-renewable resource, and given the production rate in 2020, it is estimated that reserves will last for 50 years [ 12 ]. For the purposes of this article, the waste generated is the most relevant problem."
} | 2,642 |
36655713 | PMC10086821 | pmc | 6,610 | {
"abstract": "Abstract Biofilms are multicellular, often surface‐associated, communities of autonomous cells. Their formation is the natural mode of growth of up to 80% of microorganisms living on this planet. Biofilms refractory towards antimicrobial agents and the actions of the immune system due to their tolerance against multiple environmental stresses. But how did biofilm formation arise? Here, I argue that the biofilm lifestyle has its foundation already in the fundamental, surface‐triggered chemical reactions and energy preserving mechanisms that enabled the development of life on earth. Subsequently, prototypical biofilm formation has evolved and diversified concomitantly in composition, cell morphology and regulation with the expansion of prokaryotic organisms and their radiation by occupation of diverse ecological niches. This ancient origin of biofilm formation thus mirrors the harnessing environmental conditions that have been the rule rather than the exception in microbial life. The subsequent emergence of the association of microbes, including recent human pathogens, with higher organisms can be considered as the entry into a nutritional and largely stress‐protecting heaven. Nevertheless, basic mechanisms of biofilm formation have surprisingly been conserved and refunctionalized to promote sustained survival in new environments.",
"introduction": "INTRODUCTION Global bacterial infections, such as medieval plague caused by Yersinia pestis , pandemic cholera caused by Vibrio cholerae , whooping cough caused by Bordetella pertussis and tuberculosis caused by Mycobacterium tuberculosis contributed to our anthropocentric view of microbes acting as single‐cell planktonic organisms. Upon closer inspection of the disease process, however, these and other infectious agents and microbes are, rarely, if at all, observed as single planktonic cells. Multicellular biofilm‐forming microbes, which display as surface, interface or self‐attached cell aggregates, consisting of autonomous cells of diverse phylogenetic origin constitute the majority of microbial life. The success of this multicellular mode of growth during earth time is reflected by the fact that up to 80% of human bacterial infections are biofilm‐associated according to the National Institutes of Health (Flemming & Wuertz, 2019 ). Thereby, biofilm formation might be the major virulence factor of otherwise more benign microorganisms or play a role only in a spatially, temporally or functionally restricted part of the infection process. Be it in marine sediments, in the continental subsurface or in association with higher organisms, such as plants, invertebrates and humans, biofilm‐forming organisms are the predominant life form and drive to 100% geochemical processes (Flemming & Wuertz, 2019 ). The formation of biofilms, which were defined by Bill Costerton as ‘microbes adhering to each other and/or to surfaces or interfaces with the aid of a self‐produced (or environmentally based) extracellular matrix’ (Costerton et al., 1995 ), includes initial adherence, the assembly of microcolonies and monolayers of cells on surfaces. These initial structures transition into multicellular assemblies of differentiated self‐autonomous cells with tissue‐like properties by conducting developmental cycle(s) sophisticated genetically and environmentally programmed. The life cycle they enter switches reversibly between multicellularity and the, often motile, single‐cell planktonic state. Directed is this life style transition by the integration of a multitude of environmental and intrinsic signals on various regulatory levels (Asally et al., 2012 ; Chou et al., 2022 ; Palmer & White, 1997 ; Simm et al., 2004 ; Simm et al., 2014 ). Rather the rule than the exception, more than one distinct pathway leading to biofilm formation can be encoded by one microbial genome. Thereby, the genetically programmed biofilm formation which is highly flexible with respect to the contributing components is build up modularly from individual biofilm pathways and biosynthetic entities (Bundalovic‐Torma et al., 2020 ; Erskine et al., 2018 ; Korea et al., 2010 ; Low & Howell, 2018 ; Römling & Galperin, 2015 ; Zapotoczna et al., 2016 ). For example, distinct biofilms can be built by three different exopolysaccharides in Pseudomonas aeruginosa . Considering this flexibility, the genetic plasticity of biofilm genes and their lateral transfer, it might be challenging to develop strategies to tackle biofilm‐associated infections, although commonly acting activators of biofilm formation such as the ubiquitous second messenger cyclic di‐GMP have been identified (Hee et al., 2020 ; Römling et al., 2013 ; Trampari et al., 2021 ). Refractoriness to stress conditions might be founded already in the origin of biofilm formation, which is proposed to be intimately coupled to the origin of life itself. To lay out the fundamentals of ancient metabolisms which are preserved until today even in evolved organisms might also aid in the tackling of chronic infections (Falkowski et al., 2008 ; Greening et al., 2022 ).",
"discussion": "DISCUSSION The early origin of life spanning from the emergence of first organic molecules to fundamental energy and carbon fixation mechanisms in bacteria and archaea has been thoroughly studied. Development of alternative aspects of microbial physiology and metabolism such as the time line of origin, evolution and diversification of surface‐dependent energy conservation processes and the integration of redox‐active minerals into cell physiology has only been analysed at a rudimentary level. Equally, the time line of origin, evolution and diversification of biofilm formation including its task distribution and cell differentiation into, for example, persister cells, has not been performed. Identification of the ancient inventory and the deep phylogeny of biofilm genes including diversification of mechanisms and regulation of biofilm formation in the deepest branching bacterial and archaeal phyla can identify the most ancient processes. Equally addressing in detail the evolution of energy preserving modules with the analysis and integration of ancient energy‐gaining pathways such as anaerobic sulfur respiration (Hedderich et al., 1998 ) can give a first glimpse on these processes. On the other hand, while the presence of biofilm components such as the genetic modules for the production of the poly‐beta‐1,6‐ N ‐acetyl‐glucoseamine and cellulose exopolysaccharide and the contribution of eDNA to the extracellular matrix have been realized to occur in bacteria throughout the phylogenetic tree, its origin has not been defined (Mack et al., 1996 ; Whitfield & Howell, 2021 ; Zogaj et al., 2001 ). Equally, although a Gram‐negative acyl‐homoserine quorum sensing system has also been identified punctually in archaea (Zhang et al., 2012 ), a deep phylogenetic origin of biofilm‐regulating quorum sensing systems remains elusive (Lerat & Moran, 2004 ). However, an early bacterial ancestor has been suggested to have been a flagellated microbe with two membranes (Coleman et al., 2021 ). Extending such analyses about the origin of biofilm and biofilm‐related genes might provide novel insights into the treatment of biofilm infections (Kalia et al., 2019 ; Römling & Balsalobre, 2012 ). In many bacterial species, an agar‐grown biofilm model has been identified (Römling et al., 1998 ; Shapiro, 1998 ). These colony morphotype biofilm models with dense association of individual cells embedded into a honey‐bee comb like extracellular matrix (Branda et al., 2001 ; Morris et al., 1996 ; Rice et al., 1992 ; Römling et al., 1998 ) can be seen in a light rather different than a laboratory curiosity resembling embryonic and tissue development in higher organisms (Asally et al., 2012 ; Chou et al., 2022 ; Futo et al., 2021 ). In fact, the dense association of microbial cells, a readily accessible and genetically screenable biofilm model, might not only be a physiologically and ecologically relevant model for biofilm formation in microbial‐dense environments such as the colon but also serve as a model for ancient environmental biofilms on surfaces (Boomer et al., 2009 ; MacKenzie et al., 2015 ; Ward et al., 1998 ). The subsequent free‐living planktonic life style is considered a temporary condition in the life cycle of most microbes (Futo et al., 2021 ; Henrici, 1933 ), which does, however, not contradict the multiple independent gain of nmulticellularity in eukaryotes (Parfrey & Lahr, 2013 ). The fundamentally ancient process of energy conservation involving solid reversible redox active surfaces has many applications. One of the most prominent applications is the gain of energy in microbial fuel cells (Logan et al., 2006 ; Ucar et al., 2017 ). Another example is the gain of energy by electrosynthesis (Jourdin & Burdyny, 2021 ; Rabaey & Rozendal, 2010 ). In a reverse process, biofilms that protect steel from corrosion can be developed (Dubiel et al., 2002 ). Furthermore, the understanding of these ancient molecular mechanisms of biofilm formation might also aid to modulate biofilm formation (Maeda et al., 2007 ; Perona‐Vico et al., 2019 ) and tackle chronic infections (Nie et al., 2012 ; Soldano et al., 2021 ). Integrating the knowledge on these ancient processes of energy acquisition and its preservation in modern microbes might lead to innovative biofilm treatment strategies and new application processes."
} | 2,372 |
32817760 | PMC7427070 | pmc | 6,612 | {
"abstract": "Background Acid pretreatment is a common strategy used to break down the hemicellulose component of the lignocellulosic biomass to release pentoses, and a subsequent enzymatic hydrolysis step is usually applied to release hexoses from the cellulose. The hydrolysate after pretreatment and enzymatic hydrolysis containing both hexoses and pentoses can then be used as substrates for biochemical production. However, the acid-pretreated liquor can also be directly used as the substrate for microbial fermentation, which has an acidic pH and contains inhibitory compounds generated during pretreatment. Although the natural ethanologenic bacterium Zymomonas mobilis can grow in a broad range of pH 3.5 ~ 7.5, cell growth and ethanol fermentation are still affected under acidic-pH conditions below pH 4.0. Results In this study, adaptive laboratory evolution (ALE) strategy was applied to adapt Z. mobilis under acidic-pH conditions. Two mutant strains named 3.6M and 3.5M with enhanced acidic pH tolerance were selected and confirmed, of which 3.5M grew better than ZM4 but worse than 3.6M in acidic-pH conditions that is served as a reference strain between 3.6M and ZM4 to help unravel the acidic-pH tolerance mechanism. Mutant strains 3.5M and 3.6M exhibited 50 ~ 130% enhancement on growth rate, 4 ~ 9 h reduction on fermentation time to consume glucose, and 20 ~ 63% improvement on ethanol productivity than wild-type ZM4 at pH 3.8. Next-generation sequencing (NGS)-based whole-genome resequencing (WGR) and RNA-Seq technologies were applied to unravel the acidic-pH tolerance mechanism of mutant strains. WGR result indicated that compared to wild-type ZM4, 3.5M and 3.6M have seven and five single nucleotide polymorphisms (SNPs), respectively, among which four are shared in common. Additionally, RNA-Seq result showed that the upregulation of genes involved in glycolysis and the downregulation of flagellar and mobility related genes would help generate and redistribute cellular energy to resist acidic pH while keeping normal biological processes in Z. mobilis . Moreover, genes involved in RND efflux pump, ATP-binding cassette (ABC) transporter, proton consumption, and alkaline metabolite production were significantly upregulated in mutants under the acidic-pH condition compared with ZM4, which could help maintain the pH homeostasis in mutant strains for acidic-pH resistance. Furthermore, our results demonstrated that in mutant 3.6M, genes encoding F 1 F 0 ATPase to pump excess protons out of cells were upregulated under pH 3.8 compared to pH 6.2. This difference might help mutant 3.6M manage acidic conditions better than ZM4 and 3.5M. A few gene targets were then selected for genetics study to explore their role in acidic pH tolerance, and our results demonstrated that the expression of two operons in the shuttle plasmids, ZMO0956–ZMO0958 encoding cytochrome bc1 complex and ZMO1428–ZMO1432 encoding RND efflux pump, could help Z. mobilis tolerate acidic-pH conditions. Conclusion An acidic-pH-tolerant mutant 3.6M obtained through this study can be used for commercial bioethanol production under acidic fermentation conditions. In addition, the molecular mechanism of acidic pH tolerance of Z. mobilis was further proposed, which can facilitate future research on rational design of synthetic microorganisms with enhanced tolerance against acidic-pH conditions. Moreover, the strategy developed in this study combining approaches of ALE, genome resequencing, RNA-Seq, and classical genetics study for mutant evolution and characterization can be applied in other industrial microorganisms.",
"conclusion": "Conclusion Two acidic-pH-tolerant mutants 3.6M and 3.5M of Z. mobilis , which possessed advantages at acidic-pH conditions including high growth rate and ethanol productivity, were obtained from wild-type ZM4 by ALE strategy in this study. Genetic changes and gene expression at acidic and neutral pH conditions were then investigated using NGS-based genome resequencing and RNA-Seq with the underlying mechanism of acidic-pH resistance proposed. Specifically, Z. mobilis altered its metabolic flux through genomic changes affecting gene and gene expression associated with membrane modification, proton transportation, energy conservation and redistribution for acidic-pH resistance. Mutant strains had genes differentially expressed at acidic-pH conditions to help strengthen membrane-associated transporters, and increase proton consumption and alkaline metabolite production to maintain proton permeability and cellular pH homeostasis. In addition, the enhanced F 1 F o ATPase was also upregulated in mutant 3.6M, which could contribute to its advantage in the acidic-pH condition over another mutant 3.5M and wild-type ZM4. Genetic study results demonstrated that the introduction of plasmid constructs containing operons expressing cytochrome bc1 complex or RND efflux pump affected acidic pH tolerance in Z. mobilis . This study obtained and characterized acidic-pH resistant mutant strains of Z. mobilis , which can be used as candidate strains for commercial bioethanol production under acidic fermentation conditions. In addition, the molecular mechanism of acidic pH tolerance of Z. mobilis proposed in this study can also facilitate future research on rational design of synthetic microorganisms with enhanced tolerance against acidic-pH conditions, and the strategy we developed in this study combining ALE, genome resequencing, RNA-Seq, and classical genetic study for mutant evolution and characterization can be applied to other industrial microorganisms.",
"discussion": "Results and discussion Development of acidic-pH-tolerant mutants of Z. mobilis through adaptive laboratory evolution (ALE) Zymomonas mobilis was reported to be able to grow within a broad range of pH 3.5 ~ 7.5 [ 21 ]. In this study, the growth of Z. mobilis in pH range below pH 4.0 was further investigated. The results showed that ZM4 can grow below pH 4.0 (Fig. 1 ), which is consistent with previous reports [ 21 , 43 ]. However, when the pH value decreased from 4.0 to 3.5, a longer lag phase was observed accompanied by a lower biomass production (Fig. 1 ). Cells almost could not grow at pH 3.5 (Fig. 1 ), which might be ascribed to the damage of cell membrane structure and protein configuration at acidic pH [ 44 ]. Therefore, the development of acidic-pH-tolerant strains could directly benefit commercial bioethanol production under acidic fermentation conditions. Fig. 1 Cell growth of wild-type Z. mobilis ZM4 under different pH conditions. ZM4 was cultured in RMG5 using Bioscreen C instrument at a pH range within pH 3.5–4.0. pH 3.5 (red color circle), pH 3.6 (green color square), pH 3.7 (blue color upward triangle), pH 3.8 (purple color downward triangle), pH 3.9 (yellow color diamond), and pH 4.0 (pink color diamond). At least two independent experiments were performed with similar results. Values are the mean of one representative experiment with three technical replicates. Error bars represent standard deviations Subsequently, adaptive laboratory evolution (ALE) was carried out with two parallel experiments in RMG2 medium, which was firstly adapted at pH 4.0 with 30 cultivation cycles and then transferred to pH 3.5 and pH 3.6 for acidic-pH resistance evolution (Fig. 2 a). Finally, after 55 and 75 cultivation cycles at pH 3.5 and pH 3.6, respectively, four evolved mutants, named as 3.5M-1, 3.5M-2, 3.6M-1, and 3.6M-2, with enhanced acidic pH tolerance were obtained. The stability of these four adapted mutants was then analyzed at pH 3.6 with three colonies of each as replicates. The results showed that the growth of replicates from 3.5M-1 and 3.6M-1 was more uniformed than those of 3.5M-2 and 3.6M-2 (Fig. 2 b). The growth of these four mutants was then further compared with wild-type ZM4 under different pH conditions of pH 3.5, pH 3.6, pH 4.0, and pH 6.0 (Fig. 3 ). Fig. 2 The workflow to obtain acidic-pH resistant mutants of Z. mobilis ZM4 through adaptive laboratory evolution (ALE) in RMG2 media ( a ), and the verification and selection of mutants with stable acidic-pH resistance under pH 3.6 culture condition ( b ) Fig. 3 Cell growth of four acidic-pH-tolerant mutants of 3.5M-1, 3.5M-2, 3.6M-1, and 3.6M-2 and wild-type Z. mobilis ZM4 under different pH conditions of pH 3.5 ( a ), pH 3.6 ( b ), pH 4.0 ( c ), and pH 6.0 ( d ) in RMG2. OD values at 600 nm were monitored using Bioscreen C instrument. At least two independent experiments were performed with similar results. Values are the mean of one representative experiment with three technical replicates. Error bars represent standard deviations Under the condition of pH 3.5 (Fig. 3 a), all four mutants had higher growth rates and final OD 600 values than ZM4, among which the mutant 3.6M-1 exhibited the highest OD 600 value of cell growth, followed by 3.6M-2, 3.5M-2 and 3.5M-1 successively. Under pH 3.6 condition, the mutants also had higher growth rates and shorter times reaching stationary phase than ZM4 (Fig. 3 b). The mutants had no obvious disadvantages compared to ZM4 except that 3.5M-1 had a lower final OD 600 value at both pH 4.0 and pH 6.0 (Fig. 3 c, d). These results suggested that although all mutants had enhanced tolerance at acidic-pH conditions, their performance was different. To understand the molecular mechanism of acidic-pH resistance, two mutants 3.5M-1 and 3.6M-1 with growth differences from ZM4 were selected and renamed as 3.5M and 3.6M correspondingly for further studies. 3.6M-1 is the best acidic-pH-tolerant mutant based on its highest final OD 600 values among all mutants and wild-type ZM4 in acidic-pH conditions. Another acidic-pH-tolerant mutant 3.5M-1 was selected because it grew better than ZM4 at pH 3.5 while having the largest difference from 3.6M-1 in various conditions (Fig. 3 ). Evaluation of cell growth, glucose consumption, and ethanol production of mutant strains 3.5M and 3.6M at acidic and neutral pH conditions Since the acidic-pH conditions affect cell growth, glucose consumption, and ethanol production, two mutant strains 3.5M and 3.6M were investigated at acidic and neutral pH conditions of pH 3.8 and pH 6.2, respectively. Both mutants 3.5M and 3.6M exhibited better cell growth and faster ethanol production than wild-type ZM4 at acidic pH 3.8 (Fig. 4 a, b). The growth rates of 3.5M and 3.6M were 0.23 h −1 and 0.35 h −1 , respectively, while that of ZM4 was only 0.14 h −1 (Table 1 ). Consistent with the fast cell growth and glucose consumption, the fermentation time were reduced significantly from 22 h for ZM4 to 18 h and 13 h for 3.5M and 3.6M, respectively, leading to the increase of ethanol productivity by 21.21% and 64.65% correspondingly (Table 1 ; Fig. 4 a, b). Fig. 4 Cell growth, glucose consumption, and ethanol production of Z. mobilis mutants 3.5M and 3.6M compared with wild-type ZM4 at pH 3.8 ( a , b ) and pH 6.2 ( c , d ). At least two independent experiments were performed with similar results. Values are the mean of one representative experiment with three technical replicates. Error bars represent standard deviations Table 1 Fermentation performance of time to consume all glucose (Time), growth rate, as well as ethanol titer, yield, and productivity of the wild-type Z. mobilis ZM4 and mutant strains 3.5M and 3.6M in RMG5 at pH 3.8 and pH 6.2 Condition and Strain Glucose used (g/L) Time (h) Growth rate (h −1 ) Titer (g/L) Yield (%) Productivity (g/L/h) pH 3.8 ZM4 44.95 ± 0.12 22 0.14 ± 0.01 21.74 ± 0.43 94.55 ± 1.89 0.99 ± 0.02 3.5M 44.91 ± 0.01 18 0.23 ± 0.01 21.62 ± 0.14 94.13 ± 0.64 1.20 ± 0.01 3.6M 44.98 ± 0.00 13 0.35 ± 0.01 21.22 ± 0.28 92.24 ± 1.22 1.63 ± 0.02 pH 6.2 ZM4 44.91 ± 0.11 10 0.49 ± 0.007 20.21 ± 1.33 87.99 ± 5.88 2.02 ± 0.13 3.5M 44.97 ± 0.00 12 0.39 ± 0.005 20.05 ± 0.82 87.19 ± 3.56 1.67 ± 0.07 3.6M 44.95 ± 0.00 10 0.49 ± 0.01 20.24 ± 0.36 90.00 ± 1.20 2.02 ± 0.04 At least two independent experiments were performed with similar results. Values are the means and standard deviations of one representative experiment with three technical replicates Under the neutral pH condition of pH 6.2, cell growth, glucose consumption, and ethanol production of 3.6M were similar to those of ZM4, but were better than those of 3.5M (Table 1 ; Fig. 4 c, d). These results suggested that 3.5M and 3.6M possessed relatively fast glucose consumption and ethanol production at the acidic-pH condition, and 3.6M maintained similar capacities as ZM4 at the neutral pH condition. Thus, 3.6M can be used to replace ZM4 as the biocatalyst for bioethanol production fermenting well in both acidic and neutral pH conditions (Table 1 ; Fig. 4 c, d). The underlying mechanism of acidic pH tolerance through NGS-based genome resequencing and RNA-Seq To illustrate the underlying genetic basis responsible for the enhanced acidic pH tolerance, samples of mutant and wild-type strains cultured at acidic pH 3.8 and neutral pH 6.2 were collected for WGR to determine the genetic changes in 3.5M and 3.6M using the genome of parental strain ZM4 (ATCC 31821) as the Ref. [ 45 ]. RNA-Seq was also employed to explore the global transcriptional differences among these strains at acidic and neutral pH conditions. The WGR results identified several SNPs in the mutants, including seven SNPs in 3.5M and five SNPs in 3.6M, which are listed in Table 2 . Among these mutations, four common SNPs were found in both mutants located at the coding sequence (CDS) region of four genes: ZMO0421 (A67T), ZMO0712 (G539D), ZMO1432 (P480L), and ZMO1733 (T7K), respectively (Fig. 5 a). These common mutations may contribute to the enhanced acidic pH tolerance of mutant strains, while other unique mutations that are not shared by these strains may contribute to the unique phenotypic differences of these strains. Table 2 Single-nucleotide polymorphisms (SNPs) in mutant strains 3.5M and 3.6M compared to wild-type ZM4 Locus SNP AA change 3.5M 3.6M Gene Product 424761 C/T A67T 99.76 98.86 ZMO0421 (hisC2) Histidinol-phosphate aminotransferase 711194 G/A G539D 99.24 99.73 ZMO0712 ( ppk ) Polyphosphate kinase 1449594 G/A P480L 100 99.72 ZMO1432 Efflux pump membrane component 1779278 C/A T7K 100 99.71 ZMO1733 ( oxyR ) Transcriptional regulator OxyR 1306151 C/T W485* 99.5 – ZMO1291 Peptidase S10 serine carboxypeptidase 1701191 G/A L77F 99.08 – ZMO1651 ( ptsP ) Signal transduction protein 173653 T/C 100 – Intergenic region Between ZMO0183 and ZMO0184 1451222 A/G – 100 Intergenic region Between ZMO1432 and ZMO1433 The numbers in the columns of 3.5M and 3.6M represent the frequency (%) of the SNP identified in all genome resequencing reads, and “–” indicates the absence of SNP. AA means amino acid. * indicates stop codon Fig. 5 Potential molecular mechanism of acidic-pH-tolerant mutant strains of Z. mobilis . Common mutations identified in two mutants ( a ); potential membrane modification ( b ); upregulation of the central metabolism producing enough ATP and reducing power ( c ); downregulation of flagella and chemotaxis reducing energy consumption ( d ); export of acidic substances by transporters ( e ); translocation of excess proton out of cell by F 1 F o ATPase and electronic transport chain related complex ( f ); alkaline compound generation ( g ); downregulation of macromolecular repair system ( h ). The numbers after the gene locus in shadow represent the log 2 -based fold changes. Red indicates upregulated, blue indicates downregulated. BCAAs: branched-chain amino acids, ADA: adenosine deaminase, NIT: nitrilase Additionally, the differentially expressed genes (DEGs) were identified through analysis of variance (ANOVA) using strains and different pH conditions as variables. A total of 781 genes were identified by comparing any two conditions with P value < 0.05 (Additional file 1 : Table S1). There were 271, 362, and 498 DEGs comparing acidic pH 3.8 with neutral pH 6.2 conditions of 3.5M, 3.6M and wild-type ZM4, respectively (Additional file 2 : Fig. S1A). 246, 199 and 144 DEGs were also identified comparing 3.5M with ZM4, 3.6M with ZM4, and 3.5M with 3.6M at acidic pH 3.8 conditions, respectively (Additional file 2 : Fig. S1B). The DEGs from comparison of the same strain under different pH conditions or different strains under acidic pH 3.8 conditions were then further analyzed. Association of genes with common changes in mutants with enhanced acidic pH tolerance A common mutation was found in gene ZMO0421 , encoding histidinol-phosphate aminotransferase HisC2, which catalyzes the seventh step in the histidine biosynthesis pathway. Previous studies in Z. mobilis showed that HisC2 has broad substrate specificity and participates in transamination reactions for tyrosine and aromatic amino acid (phenylalanine) biosynthesis, which is essential in all studied organisms [ 46 ]. The A67T mutation in ZMO0421 was located in the amino transfer domain (PF00155, 32-357 aa) catalyzing the transamination reaction, which could likely affect enzymatic activity although detailed experiment is needed in the future. Another common mutation was found in ppk gene ( ZMO0712 ), which encodes polyphosphate kinase that transfers the γ-Pi of ATP to form a long chain polyphosphate (polyP) reversibly [ 47 ]. Several biological functions have been identified for cellular polyP including buffering capacities for pH homeostasis, DNA damage repair, cell cycle, motility, and biofilm formation [ 48 – 50 ]. Studies in other bacteria showed that polyP was rapidly accumulated by PPK under environmental stresses including acidic conditions [ 51 – 53 ]. Our transcriptomic data indicated that the expression of ppk in wild-type ZM4 and mutant strains was upregulated at pH 3.8 compared with pH 6.2 (Additional file 3 : Table S2), which is consistent with the conclusion reported above. Considering that the G539D mutation in PPK was located in the C2 domain (PF13090, 503–687), which is highly conserved in the PPK family and essential for the enzymatic activity [ 53 ], the mutation in this enzyme may help improve the activity of PPK resulting in the acceleration of polyP production to respond to the toxic acidic conditions. Additionally, a mutation in gene ZMO1432 encoding the inner membrane protein component of an RND efflux system containing 12 transmembrane domains [ 54 ] was observed in both mutants. The P480L mutation was located at the eleventh transmembrane (TM11) domain, which may play an important role in the process of substrates extrusion from cytoplasm to periplasm by proton motive force (PMF) with the conformational changes of RND system [ 54 ]. According to the prediction by TMHMM Server v. 2.0 [ 55 ], the transmembrane probability of TM11 domain in the mutant protein was improved from 0.7 to 0.95 (Additional file 4 : Fig. S2). Therefore, the P480L mutation in ZMO1432 may increase the stability and rigidity of TM11 and hence indirectly improve the efficiency to resist acidic stress by pumping out toxic substances such as organic acids or anions [ 56 ]. Moreover, a mutation (A to G) was also found in the intergenic region between ZMO1432 and ZMO1433 in mutant 3.6M (Table 2 ), which is in the upstream of the promoter region of ZMO1432 predicted by BPROM [ 57 ]. As shown in the RNA-Seq results, the expression of the whole operon encoding an RND efflux system consisted of ZMO1432 , ZMO1431 , ZMO1430 and ZMO1429 was significantly upregulated at acidic pH 3.8 in two mutant strains compared with ZM4, and 3.6M had the highest expression level among these strains (Additional file 1 : Table S1, Additional file 3 : Table S2). The mutation in the intergenic region in mutant 3.6M could help upregulate the expression of downstream genes, since the expression of these genes was also upregulated under pH 6.2 in 3.6M compared with ZM4 (Additional file 3 : Table S2). Combining these mutations and transcriptomic results, the RND efflux pump may play a crucial role in acidic-pH resistance in mutant strains. The last common mutation shared in both mutant strains was within oxyR gene ( ZMO1733 ). OxyR is a LysR family transcriptional regulator consisting of an N-terminal DNA-binding domain (DBD) and a C-terminal regulatory domain (RD), which controls the OxyR regulon consisting of almost 40 genes that can help protect cells from oxidative stress [ 58 ]. The T7K mutation in OxyR was in the N-terminal of LysR-type helix–turn–helix (HTH) DNA-binding domain (PS50931, 6-63 aa), which likely changes the binding affinity of HTH with its target DNA sequence due to the amino acid change from threonine with short side chain to lysine with long side chain (Table 2 ). Our RNA-Seq results showed that several genes involved in reactive oxygen species (ROS) detoxification possibly regulated by OxyR, such as ZMO0918 (catalase) and ZMO1060 (superoxide dismutase), were significantly upregulated in all strains, especially in ZM4 at pH 3.8 compared to pH 6.2, while ZMO1211 (glutathione reductase) was significantly upregulated at pH 3.8 only in wild-type ZM4 (Additional file 3 : Table S2). Since acidic pH could induce a secondary oxidative stress and the acid tolerance response overlaps with the oxidative stress response [ 59 , 60 ], the mutation in oxyR could contribute to the acidic pH tolerance in mutant strains. Since mutant strains with these mutations exhibited advantages under acidic-pH condition compared with wild-type ZM4, these mutations could be crucial for Z. mobilis to resist the acidic-pH stress although further investigation is needed to help confirm whether or not and how they are necessary for the acidic-pH resistance phenotype. Upregulation of genes associated with membrane components for enhanced acidic pH tolerance The modification of the phospholipids in the inner membrane is a strategy to reduce proton permeability, since the lipid composition of cell membrane could be reconfigured at the acidic-pH condition, which will affect proton permeability directly or indirectly [ 61 ]. In many bacteria, the resistance to acidic pH is associated with the conversion of unsaturated fatty acids (UFAs) into cyclopropane fatty acids (CFAs) through the addition of a methyl group to the double bond of UFA, which is associated with cyclopropane fatty acid synthase (Cfa). The expression of cfa gene is usually upregulated under acidic conditions [ 62 , 63 ], and a similar upregulation was observed for gene ZMO1033 encoding Cfa in ZM4 at acidic pH, suggesting that cfa gene may be associated with outer membrane modification and acidic pH tolerance (Fig. 5 b; Additional file 3 : Table S2). Energy generation through increased glycolysis and energy conservation through decreased cell motility for acidic-pH resistance It is reported that Streptococcus mutans altered its metabolism by increasing the glycolytic activity to produce ATP at acidic-pH conditions [ 64 , 65 ], and ATP utilization was further derived from cell growth for acid tolerance [ 66 ]. Although the Entner–Doudoroff (ED) pathway only produces one mole of ATP per single mole of glucose, it is reported that the ED pathway in Z. mobilis is nearly twice as thermodynamically favorable as the Embden–Meyerhof–Parnas (EMP) pathway in E. coli or S. cerevisiae [ 67 ]. Our RNA-Seq results demonstrated that four genes involved in the glycolysis pathway, ZMO1478 (pgl), ZMO1240 (gpmA), ZMO1596 (adhB), and ZMO1236 (adhA) , were significantly upregulated at the acidic pH 3.8 compared to a neutral pH 6.2 in ZM4 and 3.6M. Another three genes involved in glycolysis pathway, ZMO0997 (eda), ZMO0177 (gap), and ZMO0152 (pyk) , were significantly upregulated at pH 3.8 compared to pH 6.2 only in 3.6M. Since these genes are involved in energy generation and recycling, the upregulation of these genes could help produce more ATP for acidic pH tolerance (Fig. 5 c; Additional file 3 : Table S2). Correspondingly, the final log 2 OD 600 values of three strains at pH 3.8 were lower than those at pH 6.2, which was about 1.90 and 2.34, respectively (Fig. 4 a, c), indicating that more energy was consumed for acidic-pH resistance instead of cell growth. This energy-demanding process might explain the uncoupling between glycolytic and biosynthetic reactions in Z. mobilis [ 68 ] with energy generated from glycolysis being diverted for acidic-pH resistance, which is consistent with previous reports that the upregulation of pyk enhanced tolerance against acid stress in S. mutans [ 65 ]. In addition, the expression of ZMO1754 encoding SsdA that catalyzes the reaction of acetate biosynthesis from acetaldehyde was significantly upregulated in both mutants and especially wild-type ZM4 at pH 3.8 compared to that at pH 6.2, and was significantly downregulated in mutant background compared to ZM4 at pH 3.8 (Fig. 5 c; Additional file 3 : Table S2). The ssdA gene expression was also correlated with acetate production in mutants and wild-type strains (Additional file 5 : Fig. S3). These results indicated that more acetate might be produced at an acidic pH than at the neutral pH condition, and acidic-pH-tolerant mutants produced less protonated acetate than wild-type ZM4 in acidic-pH conditions. Therefore, acidic-pH-tolerant mutants could have a less acidified cytoplasmic environment than wild-type ZM4 and could divert NAD + used for acetate production into glycolysis maintaining a low NADH/NAD + ratio, which was reported to be responsive for acetic acid tolerance in Z. mobilis [ 31 ]. Moreover, a number of genes encoding flagellar structure proteins and chemotaxis-related proteins were significantly downregulated under the acidic pH compared with neutral pH condition in both ZM4 and mutant strains (Fig. 5 d; Additional file 3 : Table S2), which could also help conserve energy from cell motility for survival in conditions of stress such as acidic-pH and ethanol shock [ 69 ]. Upregulation of transporter and efflux pump helped maintain pH homeostasis in acidic conditions The increase of acidic end-products such as acetate in acidic-pH conditions (Additional file 5 : Fig. S3) could lead to an acidic intracellular condition [ 64 ]. Therefore, it is important for cells to export acidic products to maintain intracellular pH homeostasis. ABC transporters transport a wide spectrum of substrates from small inorganic and organic molecules to larger organic compounds, and have been confirmed to contribute to acetic acid tolerance as an efflux pump of acetic acid [ 70 ]. Our results demonstrated that five genes encoding ABC transporters ( ZMO0143, ZMO1017, ZMO0799–ZMO0801 ) were significantly upregulated in both mutant strains compared with ZM4 at pH 3.8 (Fig. 5 e; Additional file 3 : Table S2). Moreover, RND efflux pump is well-known for transporting various compounds including cationic dyes, antibiotics, detergents, and even simple organic solvents with the proton antiport [ 56 , 71 , 72 ]. Our results indicated that an RND efflux pump encoded by ZMO1429–ZMO1432 was also significantly upregulated at acidic pH in both mutant strains compared with ZM4 (Fig. 5 e; Additional file 3 : Table S2). The upregulation of ABC transporters and efflux pumps may suggest an enhanced capability of mutant strains to maintain cytoplasmic pH homeostasis under acidic-pH conditions. In addition, pumping H + out of the cytoplasm is another efficient way to maintain pH homeostasis [ 73 ]. F 1 F o ATP synthase (F 1 F o ATPase) can utilize the proton gradient for ATP synthesis; it can also reverse and hydrolyze ATP to pump H + out to maintain intracellular pH homeostasis [ 74 , 75 ]. For example, genes encoding F 1 F o ATPase in S. mutans were upregulated at acidic pH to help resist acid stress [ 76 ]. Another study indicated that when respiration was impeded, F 1 F o ATPase hydrolyzed ATP to pump protons and contributed to the intracellular neutral condition maintaining the essential mitochondrial membrane potential [ 77 ]. Our results demonstrated that 7 genes encoding F 1 F o ATP synthase ( ZMO0239 , ZMO0240 , ZMO0241 , ZMO0667 , ZMO0668 , ZMO0669 , ZMO0671 ) and another gene encoding F 1 F o ATP synthase assembly protein ( ZMO2005 ) were significantly upregulated at pH 3.8 compared to pH 6.2 for the mutant strain 3.6M (Fig. 5 f; Additional file 3 : Table S2). Since the cellular respiration process was uncoupled with cell growth in Z. mobilis [ 78 ], and the ATP generation was majorly from glycolysis whose activity was increased as discussed above, the upregulation of F 1 F o ATPase genes may possibly help pump H + out from the cytoplasm through consuming ATP. Furthermore, proton translocation was suggested to result in an alkalization of the intracellular medium in Z. mobilis at pH 6.5 during the respiration by transferring the H + out of cytoplasm [ 79 ]. Two genes related to the respiration chain for transferring electrons to oxygen, ZMO0012 and ZMO0568, were downregulated significantly; and six other genes , ZMO0956–ZMO0958, ZMO0961, ZMO1253 and ZMO1255, were reduced more than 1.5 times in ZM4 at pH 3.8 compared with pH 6.2 (Fig. 5 f; Additional file 3 : Table S2). In addition, six genes encoding Rnf complex ( ZMO1809–ZMO1814 ) and an assembly gene ( ZMO1808 ) were also downregulated at pH 3.8 compared with pH 6.2 in ZM4 but not in mutant strains (Fig. 5 f; Additional file 3 : Table S2). The Rnf complex is required for the electron transfer to nitrogenase during nitrogen fixation with proton excretion in Rhodobacter capsulatus [ 80 ]. Furthermore, the gene ZMO0456 encoding the ferredoxin, which is the electron acceptor from NADH and electron donor for nitrogenase, was also downregulated at acidic pH 3.8 compared with neutral pH 6.2 in ZM4 (Fig. 5 f; Additional file 3 : Table S2). The downregulation of genes associated with the electron transfer chain at the acidic-pH condition in wild-type ZM4 could make the excretion of protons against proton gradient from cytoplasm difficult, leading to growth inhibition. In contrast, the expression of these genes in the mutant background was not significantly downregulated at acidic pH 3.8 compared with neutral pH 6.2. Instead, they were upregulated compared with ZM4 at pH 3.8 (Fig. 5 f; Additional file 3 : Table S2). These results indicated that mutants could maintain relatively high proton transportation capacity against acidic-pH conditions. Proton consumption and alkaline compound production for enhanced acidic-pH resistance Biosynthesis of branched-chain amino acids (BCAAs) was reported to reduce H + concentration in the cytoplasm by consuming proton or producing ammonia [ 64 ]. Two genes involved in the conversion of isoleucine from threonine in Z. mobilis ( ZMO0687 and ZMO0115 ) were significantly upregulated in mutants 3.5M and 3.6M compared with ZM4 at pH 3.8 (Fig. 5 G; Additional file 3 : Table S2). In addition, gene ZMO0296 encoding adenosine deaminase (Ada) to convert adenosine into inosine with ammonia production was significantly upregulated at pH 3.8 in 3.6M strains compared with ZM4 (Fig. 5 g; Additional file 3 : Table S2). The expression of ZMO1207 gene encoding nitrilase (Nit, EC 3.5.5.1) that catalyzes the substrate containing cyano group to ammonia was also upregulated at pH 3.8 in mutant strain 3.6M compared with ZM4 (Fig. 5 g; Additional file 3 : Table S2). At acidic pH conditions, ammonia could react with protons to produce the ammonium ion [ 81 ], which indicated that mutant strain 3.6M possessed greater capacity than mutant strain 3.5M and ZM4 to neutralize the intracellular pH by proton-consuming and alkali-producing reactions resulting in enhanced acidic-pH resistance. However, the cytoplasmic pH homeostasis is connected with the proton motive force (PMF), which consists of two components of a transmembrane pH gradient (ΔpH) and a transmembrane electrical potential (Δψ) maintaining intercellular negative relative to outside [ 81 ]. The production of NH 4 + from NH 3 and proton thus will result in excess intracellular positive charges while reducing the ΔpH, which could destroy the PMF and impair cellular functions. To balance the excess intracellular positive charges, exporting NH 3 and NH 4 + by an ammonium transporter would avoid excessive positive charges hyperpolarizing the cell membrane [ 81 ]. Our RNA-Seq results showed that the transcriptional level of ammonium transporter encoded by ZMO0346 was upregulated significantly in both mutant strains compared with ZM4 (Fig. 5 g; Additional file 3 : Table S2), which may help transport NH 3 and NH 4 + outside the cell and ensure normal PMF function on the membrane. Moreover, it was reported that the conversion of CO 2 to HCO 3 − by carbonate anhydrase (CA) also contributed to acid–base equilibrium in H. pylori [ 21 , 81 ]. It is interesting that the transcriptional level of ZMO1133 encoding carbonate anhydrase was significantly upregulated at pH 3.8 compared to that at pH 6.2 in all strains (Fig. 5 g; Additional file 3 : Table S2). Since Z. mobilis can consume sugars and produce CO 2 efficiently [ 82 ], CO 2 /HCO 3 − could also be involved in keeping acid–base equilibrium at acidic-pH conditions. Reduced energy consumption on macromolecular repair for enhanced acidic pH tolerance of mutant strains Cell membrane, proteins, and DNA would be damaged when bacteria are cultured in acidic environments. To reduce the damage, the expression of repair and defense proteins such as DnaK, RecA, UvrA, IrrE, and AP endonuclease could be increased to protect the macromolecules from the damage [ 64 , 75 , 83 ]. Our results showed that the transcription level of ZMO0660 ( dnaK ) together with its co-chaperone ZMO1690 ( dnaJ ) as well as ZMO1588 ( uvrA ) and its subunit ZMO0362 ( uvrB ) were upregulated in ZM4 at acidic pH 3.8 than at neutral pH 6.2. Moreover, the expression level of Clp protease complex, ZMO0405 ( clpA ), ZMO0948 ( clpP ), ZMO0949 ( clpX ) and ZMO1424 ( clpB ) involved in protein remodeling and reactivation [ 64 , 84 ], altered similarly as ZMO0660 (Fig. 5 h; Additional file 3 : Table S2). These results demonstrated that it is necessary to enhance the expression of these proteins in order to protect DNA and protein from damage in acidic cytoplasm. However, the expression level of these genes was down-regulated at pH 3.8 in mutants compared to ZM4, except for gene recA, which had no significant changes at different pH conditions in any strains. In addition, the transcriptional level of ZMO1929 , which encodes GroEL protein and is important during adaptation to acid [ 64 ], was downregulated at pH 3.8 in mutant strains compared to ZM4 (Fig. 5 h; Additional file 3 : Table S2). The deficient in HtrA, a surface protease involved in the degradation of aberrant proteins, reduced the ability of the mutant strain to endure acidic conditions [ 85 ], which demonstrated that this protein is important for cells to defend acid conditions. The phenomenon that the expression of macromolecular repair genes that are indispensable for acid resistance was upregulated at acidic pH only in wild-type ZM4 background indicated that a great demand on these proteins is needed for ZM4 to survive at acidic-pH conditions, while the downregulation of these genes in mutant backgrounds compared with ZM4 suggested that acidic-pH-tolerant mutants may acquire the capability to manage defense responses without triggering abrupt augmented macromolecular repair activities and thus conserve energy for cell growth instead. Genetic confirmation of genes associated with acidic-pH resistance in Z. mobilis ZM4 To evaluate the impact of candidate genes associated with acidic-pH resistance identified through our genomic and transcriptomic studies as discussed above, six plasmids containing candidate operons were constructed based on the shuttle vector pEZ15Asp with P tet as the promoter [ 86 ]. These candidate operons including ZMO0142–ZMO0145 encoding ABC transporter, ZMO0798–ZMO0801 encoding multiple drug efflux, ZMO0956–ZMO0958 encoding cytochrome bc1 complex, ZMO0238 – ZMO0242 encoding ATP synthesis F 1 submits, ZMO1428 – ZMO1432 encoding RND efflux system with a mutation in ZMO1432, and ZMO2005, ZMO0667 – ZMO0671 encoding ATP synthesis F 0 submits were cloned into pEZ15Asp shuttle vector, which were named pEZ-Tc1, pEZ-Tc2, pEZ-Tc3, pEZ-Tc4, pEZ-Tc5(M) and pEZ-Tc6, respectively. These plasmid constructs including the empty vector pEZ15Asp as the control were then introduced into ZM4 separately. These recombinant strains were then investigated under different conditions to examine their impact on cell growth (Fig. 6 , Additional file 6 : Fig. S4). Fig. 6 Cell growth of recombinant and wild-type strains of Z. mobilis containing the control plasmid pEZ15A and plasmid constructs of pET-Tc3 and pET-Tc5 (M) at pH 3.6, 4.0, and 6.0 without tetracycline ( a , c ) and with 0.8 μg/mL tetracycline induction ( b , d ). pEZ-Tc3, plasmid construct expressing operon ZMO0956 – ZMO0958 encoding cytochrome bc1 complex; pEZ-Tc5 (M), plasmid construct expressing operon ZMO1428 – ZMO1432 encoding RND efflux system with a mutation in ZMO1432. At least two independent experiments were performed with similar results. Values are the mean of one representative experiment with three technical replicates. Error bars represent standard deviations With the increase of the tetracycline inducer concentration from 0 to 0.8 μg/mL, the growth advantage of the recombinant strain containing pEZ-Tc3 decreased at pH 3.8 (Fig. 6 a, b). Our previous work demonstrated that the P tet promoter driving the operon expression used in this study is leaky even when tetracycline was not supplemented into the medium [ 86 , 87 ]. Therefore, this result suggested that the cytochrome bc1 complex encoded by the operon ZMO0956–ZMO0958 in the recombinant strain containing pEZ-Tc3 could contribute to the acidic pH tolerance in Z. mobilis at a low expression level, which is consistent with our RNA-Seq result that the reduced expression of genes associated with electron transfer chain impacted the acid resistance of wild-type ZM4 (Fig. 5 f; Additional file 3 : Table S2). In addition, the upregulated expression of cytochrome bc1 complex impacted the growth in neutral pH condition (Fig. 6 b), which may indicate a potential role of low expression of this “dead-end” respiration branch in cell growth, since the function of cytochrome bc1 in electron transport is still unknown in Z. mobilis [ 88 ]. Similarly, with the increase of tetracycline inducer concentration from 0 to 0.8 μg/mL, the growth advantage of recombinant strain containing pEZ-Tc5(M) decreased in acidic-pH condition, but there was still an advantage with 0.8 μg/mL tetracycline (Fig. 6 c, d), which is again consistent with the upregulation of these genes in our RNA-Seq study (Fig. 5 e; Additional file 3 : Table S2). Although further investigation is still needed to understand the association of acidic-pH resistance with the different expression levels of these genes, our result suggested that the mutation in the intergenic region of upstream of ZMO1432 in mutant 3.6M may contribute to the upregulation of the downstream gene, and a higher expression of RND efflux pump is more advantageous for strains to defend against acidic-pH conditions. Recombinant strains containing the other four operons had no advantageous effect on cell growth in acidic-pH conditions both with and without tetracycline induction (Additional file 6 : Fig. S4). Instead, the growth of the recombinant strain containing pEZ-Tc2 was dramatically impeded when induced with 0.8 μg/mL tetracycline (Additional file 6 : Fig. S4C, S4D), and the growth of the recombinant strain containing pEZ-Tc6 was inhibited both with and without the supplementation of tetracycline inducer (Additional file 6 : Fig. S4G, S4H). Since these operons encode the ABC transporter, multiple drug efflux, and ATP synthase submits, which may function with other cellular component coordinately, a delicate balance of these operons with other genes may be needed for acidic-pH resistance similar to a previous report’s findings that the tailored expression of multiple genes simultaneously was essential for enhanced low-pH tolerance in E. coli [ 89 ]. In summary, although our results suggested that the mutation in the intergenic region of upstream of ZMO1432 in mutant 3.6M may contribute to the upregulation of the downstream gene (Table 2 ), and high expressions of RND efflux pump or cytochrome bc1 complex is advantageous for the strain to defend acidic-pH condition (Fig. 6 ), the advantage of these recombinant strains was still not as prominent as the mutant itself. This indicates that one gene/operon is not sufficient to warrant the acidic pH tolerance, and synergetic effects of multiple mutations affecting protein structural changes and expression of multiple genes need to be further investigated to understand the association of acidic-pH resistance phenotype with the genetic difference of mutant strains."
} | 10,320 |
31294165 | PMC6605018 | pmc | 6,613 | {
"abstract": "A thorough understanding of the services provided by microorganisms to the agricultural ecosystem is integral to understanding how management systems can improve or deteriorate soil health and production over the long term. Yet it is hampered by the difficulty in measuring the intersection of plant, microbe, and environment, in no small part because of the situational specificity to some plant-microbial interactions, related to soil moisture, nutrient content, climate, and local diversity. Despite this, perspective on soil microbiota in agricultural settings can inform management practices to improve the sustainability of agricultural production."
} | 163 |
31097723 | PMC6522473 | pmc | 6,614 | {
"abstract": "Pseudomonas aeruginosa biofilms are composed of exopolysaccharides (EPS), exogenous DNA, and proteins that hold these communities together. P. aeruginosa produces lectins LecA and LecB, which possess affinities towards sugars found in matrix EPS and mediate adherence of P. aeruginosa to target host cells. Here, we demonstrate that LecB binds to Psl, a key matrix EPS, and this leads to increased retention of both cells and EPS in a growing biofilm. This interaction is predicted to occur between the lectin and the branched side chains present on Psl. Finally, we show that LecB coordinates Psl localization in the biofilm. This constitutes a unique function for LecB and identifies it as a matrix protein that contributes to biofilm structure through EPS interactions.",
"introduction": "Introduction Biofilms are multicellular aggregates of microbes that are enclosed in a matrix composed of exopolysaccharides (EPS), exogenous DNA (eDNA), and proteins. The extracellular matrix is thought to hold these communities together as well as contribute to bacterial persistence at infection sites by protecting against the host immune system and antimicrobial stresses 1 , 2 . The biofilm matrix produced by non-mucoid Pseudomonas aeruginosa strains primarily contains two EPS, Pel, and Psl, which form a scaffold that maintains biofilm structure 3 – 5 . Pel recently was described as an N -acetyl glucosamine (GlcNAc)- and N -acetyl galactosamine (GalNAc)-rich polysaccharide that is charged under slightly acidic pH and interacts with eDNA in the matrix 6 . Psl is composed of a neutral pentasaccharide subunit that contains mannose, rhamnose, and glucose in a 3:1:1 ratio 4 , 7 . The levels of these polysaccharides within the matrix and their relevance for aggregate structural stability varies across P. aeruginosa strains 5 . Furthermore, these EPS can be found as both cell-associated and secreted forms. Less is known concerning the identity and function of P. aeruginosa biofilm matrix proteins. Proteins that interact with these EPS can contribute to biofilm structural integrity and maintenance. To date, the best described matrix protein is the extracellular adhesin CdrA, which promotes aggregate formation through Psl interactions under planktonic conditions, and helps to stabilize the matrix and maintain aggregate structural integrity 3 . It was recently shown that CdrA can also promote bacterial aggregation in the absence of EPS 8 . Outside of CdrA, no other matrix proteins that play a role in biofilm structural stability have been identified. P. aeruginosa produces two small soluble lectins, LecA and LecB (also named PAI-L and PAII-L, respectively) that interact with specific sugars. Crystal structures have been solved for both, and binding affinity experiments showed that LecA binds to galactose and its derivatives, while LecB binds to fucose, mannose, and mannose-containing oligosaccharides 9 – 12 . In addition, it is important to note that functional LecB is a homotetramer consisting of four 114 amino acid LecB monomers which require two divalent calcium ions and has been shown to be associated with the outer membrane 9 , 10 , 13 . The primary functional roles attributed to these lectins is to mediate attachment to the host during infection. In particular, it was shown that LecA is involved in host cell invasion and cytotoxicity, while LecB reduces ciliary beating of airway epithelium 14 – 16 . Both lectins also are linked to biofilm formation on abiotic surfaces, although the underlying mechanism behind these observations are unknown 13 , 17 . Culturing P. aeruginosa in the presence of the monosaccharides that are the binding partners for these lectins inhibits biofilm maturation 13 , 16 , 18 , 19 . This discovery led to the development of putative therapeutic approaches using glycomimetics that disrupt LecB-sugar interactions 15 , 20 – 23 . Interestingly, Psl contains mannose, a target monosaccharide for LecB. In this study, we demonstrate that LecB binds to Psl. We then show that LecB positions Psl within the matrix and that this interaction is crucial for aggregate formation. We find that, unlike biotic surfaces, LecB is not important for adhesion to abiotic surfaces, but its presence leads to increased retention of cells and EPS in the biofilm. This study identifies LecB as a P. aeruginosa biofilm matrix protein that binds to Psl and promotes cell retention.",
"discussion": "Discussion Lectins are found in all domains of life, and their key function is often to mediate interactions 30 , 31 . In bacteria, lectins are nearly exclusively studied in the context of bacterium interactions with higher Eukaryotes 16 , 18 , 32 – 34 . Indeed, these interactions have critical roles in both disease and symbioses. However, particularly in bacterial species, lectins functioning in the context of microbial communities has not been extensively explored. This is certainly the case for P. aeruginosa , where the roles of its two self-produced lectins are largely attributed to disease-related host interactions 16 , 18 . Our findings suggest that lectin-mediated interactions that stabilize the biofilm matrix represent a distinct function for at least one of these lectins. Biofilm formation usually involves the production of EPS and proteins that lend structural integrity to the matrix 5 , 35 – 38 . One of the better characterized systems demonstrating these principles involves Vibrio cholerae . Three matrix proteins were identified in V. cholerae that contribute to biofilm stability. After the production of the main exopolysaccharide VPS 39 , a protein involved in cell–cell and cell–surface adhesion (RmbA) accumulates at the cell surface 40 – 42 . Next, Bap1 is secreted and is thought to crosslink unknown matrix components and cells to ensure matrix integrity, as well as to contribute to the hydrophobicity of the pellicle 41 – 43 . Last, RbmC accumulates at discrete sites and is crucial for retaining VPS throughout the biofilm 41 , 42 , 44 . These principles appear to be conserved in P. aeruginosa , with Pel and Psl performing the role of VPS and CdrA and LecB emulating RbmA, Bap1, and RbmC functions. Biofilm aggregates likely serve some key functions. For biofilms growing at a liquid–solid interface, aggregates protrude out of the boundary layer found at the surface and into the flow stream overlying bulk liquid. One consequence of this is that cells positioned toward the top of the aggregate have favorable access to the overlying nutrients. Indeed, this point is described in a number of laboratory and computational studies of biofilms 45 – 47 . Aggregates also harbor the most antibiotic tolerant subpopulations of biofilm cells 48 , 49 . Thus, aggregates may represent the most protective structures present in a surface-associated community. Therefore, the ability of biofilm communities to produce aggregates may be critical for obtaining the maximal fitness benefits of this growth state. When CdrA was first described, its function within the biofilm was to maintain the structural integrity of aggregates, in part, by promoting Psl localization to the aggregates periphery 3 . In this study, we show a very similar role for LecB. Both CdrA and LecB are tethered to the outer membrane (CdrA through its outer membrane pore CdrB and LecB is thought to occur at OprF) and bind Psl 3 , 8 , 13 , 50 , 51 . Otherwise, they are quite distinct from one another, with LecB being a much smaller protein with a clearly defined EPS binding site (no clear EPS binding domain is present in CdrA). In addition, we know that a secreted, extracellular form of CdrA is capable of binding to Psl in the matrix and promoting matrix stability. The simplest interpretation may be that having functionally redundant (or partially redundant) matrix proteins ensures that deleterious mutations targeting either of their genes do not impair the production of aggregates. Redundancy for critical functions is certainly a common theme encountered in P. aeruginosa and could partially explain our results. However, our observations in NB medium indicate that it might not be that simple. In a Δ lecB Δ cdrA double mutant strain, bacteria remain as a monolayer of cells that largely fail to retain Psl. Complementation with lecB restores wild-type biofilm formation, with large aggregates and Psl retained at the aggregate periphery of these aggregates. Curiously, complementation of the double mutant strain with cdrA failed to restore production of wild-type aggregates. Psl was retained in the biofilm, but the biofilm was a thick homogenous mat of cells (Fig. 6i, j ). This result suggests that under some instances, simple expression of LecB or CdrA is not sufficient to support aggregate production. Why is it unclear? Perhaps, the two proteins differ in their stability under changing environmental conditions. Finally, we cannot rule out that yet unidentified matrix proteins can also contribute to matrix stability in the absence of either LecB or CdrA. Another point of interest is that two clades of LecB have been proposed, one that groups with PAO1 and another that groups with PA14 23 . Although PA14 cannot synthesize Psl, other members of the PA14 clade can. Whether LecB can serve a similar role in Psl-binding and biofilm structure for other Psl-producing members of the PA14 clade remains to be determined. We propose the following model to explain our experimental observations. Surface attachment is similar for both strains, resulting in the production of matrix components (EPS and CdrA). At this stage, cells proliferate and produce both CdrA (at low levels) and LecB which leads to the retention of Psl at the base of the biofilm. In the wild-type strain, aggregates continue to grow and biofilm biomass begins to extend beyond the boundary layer and into the overlying bulk fluid. At this stage, lecB mutant strains are swept away by the shear stress resulting from fluid flow due to their inability to stabilize the aggregate through Psl interactions. While we are able to determine the consequences of the lack of LecB for biofilm maturation, our data do not explain why LecB and Psl begin to co-localize at the aggregates periphery. Is LecB and/or Psl only produced at the periphery of the aggregates? Does CdrA affect LecB–Psl interactions and vice versa? Our data provide a foundation for the current model, however, there are many questions still left unanswered. Future experimentation will include determining whether lecB and Psl expression are coordinately regulated. However, our current knowledge suggests that Psl is primarily influenced by c-di-GMP signaling, while lecB is quorum sensing controlled. In conclusion, our study demonstrates that LecB can serve as a key structural protein in the biofilm matrix. We also demonstrated that Psl and LecB are binding partners and that this interaction impacts biofilm structure. Our findings also have implications for multi-species systems. P. aeruginosa may use LecB to adhere to mannose/fucose containing EPS or glycosylated proteins present in established biofilms of other species. We also predict that the converse may be true: P. aeruginosa biofilms containing lectins may retain planktonic bacteria of other species that are producing target EPS or capsule. Finally, we predict that lectin production within biofilms may allow P. aeruginosa to incorporate free host EPS/oligosaccharides during disease, which might serve as a way of camouflaging the biofilm aggregates from the immune system."
} | 2,888 |
39696653 | PMC11657226 | pmc | 6,615 | {
"abstract": "Background Biorefineries usually focus on the production of low-value commodities, such as bioethanol, platform chemicals or single cell protein. Shifting production to bioactive compounds, such as antimicrobial peptides, could provide an opportunity to increase the economic viability of biorefineries. Results Recombinant production of the antimicrobial peptide pediocin PA-1 in Corynebacterium glutamicum was transferred from yeast extract-based media to minimal media based on lignocellulosic spent sulfite liquor. Induced batch, fed batch, and extended batch process modes were compared for highest pediocin PA-1 production. Conclusion For pediocin PA-1 production on lignocellulosic residues, extended batch cultivation was identified as the optimal process mode, producing up to \\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}$$\\simeq$$\\end{document} ≃ 104 mg/L active pediocin PA-1. Moreover, the production of pediocin PA-1 on this sustainable second generation resource exceeded its state-of-the-art production on yeast extract-based media \\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}$$\\simeq$$\\end{document} ≃ 1.5-fold. Supplementary Information The online version contains supplementary material available at 10.1186/s13068-024-02587-1.",
"conclusion": "Conclusion \n Fig. 6 Maximum antimicrobial activity against Listeria spp. in biological units per ml cultivation supernatant for different process modes \n Various process modes for the production of the antimicrobial peptide pediocin PA-1 with C. glutamicum on lignocellulosic minimal medium were compared (see Fig. 6 ). Induced batch processes with a single coupled growth and production phase resulted in up to \\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}$$\\simeq$$\\end{document} ≃ 6 mg/mL active pediocin PA-1. Fed batch processes up to \\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}$$\\simeq$$\\end{document} ≃ 90 mg/mL active pediocin PA-1, demonstrating that independently optimized conditions for growth and production result in significantly increased production. Extended batch processes produced up to \\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}$$\\simeq$$\\end{document} ≃ 104 mg/mL active pediocin PA-1, indicating that an unlimited substrate uptake regime during production results in an increase in production while reducing process complexity. In summary, the combination of a substrate uptake unlimited production regime and independently optimized growth and production phases was utilized to boost pediocin PA-1 production on cheap renewable carbon sources, exceeding even the highest previously reported production on yeast extract-based media by \\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}$$\\simeq$$\\end{document} ≃ 1.5 fold.",
"discussion": "Results and discussion Specific challenges in AMP production The state-of-the-art product quantification method for AMP, such as pediocin PA-1, is by measuring growth inhibition (antimicrobial activity) against the target organism [ 18 ], rather than product concentration. This method is preferred due to its high selectivity and sensitivity and results are usually expressed in biological activity per mL sample (BU/mL) instead of mg/L. However, pediocin PA-1 is sensitive to oxidation, resulting in a loss of activity upon oxidation [ 15 ]. The production of active product is desired, but aerobic conditions are required for production. Thus, the antimicrobial activity (A) does not represent the product concentration (P) \\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}$$A~\\ne ~P$$\\end{document} A ≠ P , and the volumetric (r) and specific (q) rates depend on both production and oxidation \\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}$$r_A/q_A~=~r_P/q_P~-~r_{OX}$$\\end{document} r A / q A = r P / q P - r OX where only A is quantified. For comparison to product concentration, as a common performance indicator for other products, a factor of \\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}$$\\simeq$$\\end{document} ≃ 2,050 BU/ml per mg/L purified active pediocin PA-1 was established in literature [ 15 , 19 ] and applied in the present study (verified with a standard of known concentration). However, antimicrobial activity, not product concentration, was quantified for all samples, with concentration equivalents provided only for better comparability with other products. Data regarding the verification that the antimicrobial assay is not impeded by a changing sample matrix environment between media are provided in Additional file 1 for interested readers. Moreover, all matrix-based influences diminish with increased sample activity, as matrix-based effects decrease faster with dilution than the highly specific attack of the pediocin PA-1 on the indicator organism. The primary goal of this study was to gain process knowledge of AMP production on lignocellulosic residues in order to increase the antimicrobial activity obtained. For such purposes, design of experiment (DoE) approaches evaluated by linear regression are commonly used in biotechnology [ 20 ]. However, the used state-of-the-art growth inhibition assay [ 18 ] presents two challenges. The assay is based on a serial twofold dilution of AMP against a constant target organism concentration on 96-well plates (from 1:8 to 1:16,384) (for illustration see Fig. 1 ). The well with the lowest dilution, where less than half of the growth of the indicator organism occurs compared to a blank, is used to determine the antimicrobial activity of the sample. This methodology causes two drawbacks. First, the difference in activity between two successive dilutions doubles with each dilution step (resolution halves), and thus providing less accurate results at higher activities. As a countermeasure, a dose–response curve fit [ 21 ] was used to calculate more accurate results (improved resolution) as suggested for AMP [ 19 ]. Thereby, the optical density of the target organism in each well was used to calculate the inflection point where \\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}$$50\\%$$\\end{document} 50 % growth occurs instead of using just the well with \\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}$$<50\\%$$\\end{document} < 50 % growth. Second, the measurement error per well increases exponentially (low precision), leading to heteroscedasticity (unequal variance over the analyzed measurement range). However, homoscedasticity, which describes a constant variance (measurement error) over the analyzed measurement range, is an assumption of ordinary linear regression [ 22 ]. While more advanced options (weighting, transformation [ 22 ]) and methods (maximum likelihood [ 23 ], Bayesian estimation [ 24 ]) exist to deal with non-homoscedastic data, the curve fit simultaneously limits the heteroscedasticity of the assay. Thus, advanced alternatives are only necessary when the desired goals of gaining process understanding and increasing maximum activity cannot be achieved otherwise. Hence, a combination of process optimization using a DoE linear regression approach based on activity data from a dose–response curve fit was chosen as strategy for this study. Fig. 1 Illustration of the growth inhibition assay ( a ). Calculated antimicrobial activity ( b ) directly from the assay including error bars (black diamonds) and curve fit with unknown error distribution (dotted line). Example of homoscedastic (blue triangles) and heteroscedastic (cyan asterisk) data ( c ). The dose–response curve and the corresponding parameters according to equation 1 for different curvatures are shown in color ( d ), with the relationship between the half growth of the indicator assay and the inflection point shown. Example of samples with increasing activity ( e ) and the resulting calculated dilution at half growth is shown (dashed line) Transferability between media In recent years, the production of pediocin PA-1 by Corynebacterium glutamicum was established by [ 15 ] and improved by [ 19 ] on complex yeast extract-based medium. Here a brief summary of highlights from their studies is provided and the transferability to lignocellulosic minimal medium-based production is discussed. [ 15 ] first established pediocin PA-1 production using Corynebacterium glutamicum CR099 on a yeast extract medium (2TY complex medium + salts and vitamins from CGXII defined media) and achieved a maximum of 20,480 BU/ml \\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}$$\\simeq$$\\end{document} ≃ 10 mg/L active pediocin PA-1 using a fed batch process. Production improvements in bioprocess development were discussed, such as increasing the biomass concentration and adjusting the oxygen supply during production to prevent product oxidation. [ 19 ] further analyzed the optimal \\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}$$dO_2$$\\end{document} d O 2 levels ( \\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}$$dO_2$$\\end{document} d O 2 of 30/10/2.5 %) for pediocin PA-1 production using a complex yeast extract-based medium and found a \\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}$$dO_2$$\\end{document} d O 2 of 2.5 % to be optimal during production. In addition, pediocin PA-1 production was enhanced at acidic pH values (best pH 5.9 \\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}$$-$$\\end{document} - 6.0) and at increased concentrations of bivalent ions such as \\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}$$\\hbox {Ca}^{2+}$$\\end{document} Ca 2 + (best 2 g/L \\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}$$\\hbox {Ca}^{2+}$$\\end{document} Ca 2 + ). As hypothesis, the interaction of the cationic peptide with the negatively charged residues of the cell wall of Corynebacterium glutamicum has been proposed. Thus, both the presence of \\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}$$\\hbox {H}^+$$\\end{document} H + and bivalent \\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}$$\\hbox {Ca}^{2+}$$\\end{document} Ca 2 + ions were hypothesized to reduce the absorption of pediocin PA-1 onto the cell surface. A maximum of 135,700 BU/mL \\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}$$\\simeq$$\\end{document} ≃ 66 mg/L active pediocin PA-1 was obtained using a delayed induced batch (shift from growth to production conditions after 4 h) process mode [ 19 ]. In summary, biomass concentration, \\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}$$dO_2$$\\end{document} d O 2 levels, pH and bivalent ion concentration were highlighted for their impact on production utilizing complex yeast extract-based media. In this study, in contrast to prior studies, no yeast extract was used for bioreactor production and UF-SSL was the only complex component used in the minimal medium. UF-SSL contains significant amounts of lignosulfonates, which are water-soluble anionic polymers resulting from the sulfite pulping process [ 25 ]. Among other applications, lignosulfonates are used industrially for protein/peptide purification by precipitation, with patents filed for both enzyme [ 26 ] and AMP [ 27 ] recovery. A reversible complex formation between the lignosulfonates and the protein/peptide surfaces (complex formed below protein pI and dissolved above protein pI) was proposed as the cause of the precipitation and employed for protein recovery. The reversible complex formation was reproduced using UF-SSL and pediocin PA-1 standard (see Additional file 1), with centrifugation conditions adjusted for all experiments to ensure minimal product loss due to centrifugation for cell removal. The beneficial effects of increased biomass concentration and lower pH on pediocin PA-1 were considered to be transferable from yeast extract to UF-SSL-based medium. However, the UF-SSL used in this study contained 14 g/L \\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}$$\\hbox {Ca}^{2+}$$\\end{document} Ca 2 + , exceeding the recommended optimal \\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}$$\\hbox {Ca}^{2+}$$\\end{document} Ca 2 + concentrations by a factor of 2 (in the 25 % dilution used as part of the minimal medium). Therefore, the adjustment of the bivalent ion concentration in the medium is not one-to-one transferable between media. The concentration of soluble bivalent ions in the UF-SSL minimal medium is influenced by two factors. First, the addition of phosphorus to UF-SSL-based minimal medium results in precipitation of calcium as well as other cations present in UF-SSL [ 17 ]. Second, the amount of precipitation is affected by pH in addition to phosphate concentration. Therefore, pH and the amount of \\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}$$\\hbox {PO}_4$$\\end{document} PO 4 added were used instead of the calcium concentration in the medium to evaluate the effect of bivalent ion concentration on pediocin PA-1 production. Similarly, the transferability of adjusted \\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}$$dO_2$$\\end{document} d O 2 levels on yeast extract-based medium was questioned, with initial screening experiments showing no significant impact of the \\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}$$dO_2$$\\end{document} d O 2 level applied on the maximum antimicrobial activity. Initially, the described attachment of lignosulfonates to protein/peptide surfaces was hypothesized to reduce the accessibility of the oxidation site (L-methionine residue at position 31 [ 19 ]) to dissolved oxygen (similar to the reduced antimicrobial activity in the presence of lignosulfonates at low dilutions). In contrast, pediocin PA-1 oxidation was found to be higher in UF-SSL-based minimal medium than yeast extract-based medium (see Additional file 1), indicating that factors other than oxidation may be more prevalent. However, further research into the exact causes of this discrepancy would be necessary with investigations into the exact metabolic impact in both media but was beyond the scope of this study. Therefore, the \\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}$$dO_2$$\\end{document} d O 2 levels were set to 15% during dedicated production phases to limit oxidation potential while imposing less respiratory constraints (2.5% reported as optimal on yeast extract [ 19 ]) on the more challenging substrate. Induced batch \n Fig. 2 a Mean and standard deviation of CER (orange line), OUR (blue line); b biomass (green squares) and product activity (violet diamonds) of induced batch cultures of C. glutamicum on UF-SSL minimal medium. Minimal medium and growth conditions (except induction) were taken from [ 17 ], for more details regarding the substrate utilization readers are refereed there. Error bars and shading represent biological variation between 2 replicates, not technical replicates of measurements \n An induced batch is the simplest process mode for recombinant production. However, optimal conditions for growth and recombinant production might not overlap. Contrary to optimal production reported on complex medium (pH 5.9 \\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}$$-$$\\end{document} - 6.0, \\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}$$dO_2$$\\end{document} d O 2 2.5% [ 19 ]), optimal batch growth of uninduced C. glutamicum on UF-SSL was reported at pH a of 7.0 compared and a \\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}$$dO_2$$\\end{document} d O 2 of 30% [ 17 ]. Moreover, the shortest doubling times for C. glutamicum were reported to be between pH 6.5 and 8.0 with growth limits at pH 5.5 and 9.5 [ 28 ], placing the reported pH optima for production close to the physiological capabilities of the organism. Since low \\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}$$dO_2$$\\end{document} d O 2 levels impose further respiratory constrains on the cells, process conditions optimized for growth [pH 7.0, \\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}$$dO_2$$\\end{document} d O 2 30 %, C/P ratio 1:30] were chosen to establish the baseline production of pediocin PA-1 in an induced batch (see Fig. 2 ). Since the cells detoxify high concentrations of inhibitory compounds, such as furfural and HMF before proliferation [ 17 ], no biomass growth was observed in the first sample after inoculation/induction (3 h). In contrast, the antimicrobial activity obtained at 3 h decreased thereafter and was only reached at 12 h with \\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}$$\\simeq$$\\end{document} ≃ 6-fold higher biomass concentrations. Towards the end of the process, between samples at 21 h and 24 h, the carbon dioxide evolution rate (CER) and the oxygen uptake rate (OUR) stagnated, indicating that growth rapidly decreased before the final sample. Similar to the low growth coinciding with an uptick in antimicrobial activity between 0–3 h, antimicrobial activity showed the greatest uptick between 21–24 h. Therefore, high biomass growth rates were hypothesized to suppress pediocin PA-1 production. Under these conditions, a maximum antimicrobial activity of 12,357 ± 1,119 BU/mL was achieved after 24 h. While it was promising that pediocin PA-1 could be recombinantly produced on UF-SSL, it was \\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}$$\\simeq$$\\end{document} ≃ tenfold lower than values reported on a yeast extract-based medium in fed batch, highlighting the need for separate growth and production phases to achieve higher production [ 15 ]. Fed batch In order to screen for improved production conditions, a fed batch process consisting of an uninduced batch phase and an induced feeding phase using a design of experiment approach was chosen. The design space (DS) for pH was set based on the reported pH for growth on UF-SSL minimal medium (pH 7.0 [ 17 ]) and the optimal production on complex medium (pH 6.0 [ 19 ]). Varying \\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}$$\\hbox {PO}_4$$\\end{document} PO 4 availability in the feeding phase was done by adjusting the carbon to phosphate (C/P) ratio between the UF-SSL feed and the separate NP feed. \\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}$$dO_2$$\\end{document} d O 2 was decreased from 30 % to 15 % after induction to reduce potential for pediocin PA-1 oxidation, while not imposing respiratory constraints on the cells. Fig. 3 The DS of the DoE was analyzed using an MLR model, with the surface plot ( a ), response terms ( b ) and observed versus predicted values ( c ). Both quadratic response terms [pH*pH and C/P*C/P] as well as the interaction term [pH*C/P] were shown to have a significant influence on the maximum pediocin PA-1 activity To generate a multiple linear regression (MLR) model, the maximum pediocin PA-1 antimicrobial activity obtained was selected as the response. Significant quadratic effects for pH and C/P were detected. Furthermore, the impact of the interaction between pH and C/P on both precipitation and production was ascertained. However, some terms were just above the threshold of significance and the variability of all terms was high. Two potential causes for the high variability of the results were hypothesized. First, while the curve fit used to calculate more accurate results changes the exponential heteroscedasticity stemming from the assay, it may not generate a fully homoscedastic distribution. Thus, the MLR may suffer from unequal error distribution of the single repetition experiments at the edge of the DS ( \\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}$$\\simeq$$\\end{document} ≃ 1:2,048 dilution in the assay results in \\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}$$\\ge$$\\end{document} ≥ 50% growth reduction of the Listeria spp. for the highest samples). Second, similar to the CER and OUR profiles of the induced batch cultures, a stagnation was observed before 24 h (start of feeding). This stall in exponential growth could indicate a decrease in cell viability leading to higher variability between replicates. In summary, despite the high variability (see Figure 3 ), a statistically significant model was generated (coefficient of determination \\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}$$R^2$$\\end{document} R 2 = 0.94; goodness of fit \\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}$$Q^2$$\\end{document} Q 2 = 0.78; detailed statistical data can be found in Additional file 1). Maximum antimicrobial activity was observed at the edge of the DS pH 6.0 and C/P 1:45, representing a \\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}$$\\simeq$$\\end{document} ≃ fourfold increase over the induced batch. Thereby, both primary goals of advancing process understanding and increasing activity using lignocellulosic feedstocks were achieved. To continue, further DoEs were performed to compensate for the hypothesized decrease in viability and to ensure a starting point with a reduced spread for the induced feeding phase. Therefore, induction was performed within the exponential growth phase of the culture [21 h], where no stagnation of the CER and OUR was observed in the previous experiments. Since the observed maximum was found at the edge of the DS, two additional DoEs were performed with the earlier induction. One with exactly the same DS as the 24 h DoE, in order to have a one-to-one comparison, and one where the DS was adjusted based on the results of the 24 h DoE to check whether the optimum was within the DS of the 24 h DoE. Regarding the factor pH, the highest antimicrobial activity was observed around pH 6.0, similar to results reported in literature [ 19 ]. Hence, lower pH values were included in the DS of the second DoE [pH 6.5/6.0/5.5]. Since no growth of C. glutamicum was reported below pH 5.5 [ 28 ], no further reduction below of pH 5.5 was considered. Regarding the factor C/P, it was observed that the most favorable C/P ratio for production shifted to higher \\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}$$\\hbox {PO}_4$$\\end{document} PO 4 concentrations at lower pH values in the 24 h DoE. Consequently, the DS for C/P was adjusted by analyzing higher \\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}$$\\hbox {PO}_4$$\\end{document} PO 4 to match the lower pH values used for the updated DS [C/P 1:30/45/60]. Using the earlier induction and feeding start, maximum activities were increased for all experiments compared to the 24 h DoE. The highest maximum activity was measured with 178,949 ± 16,613 BU/mL at pH 6.0 and C/P 1:45 (see Fig. 4 ). This amounts to a 3.4-fold increase in maximum antimicrobial activity achieved only by shifting the induction time by 3 h. All experiments showed a decrease in activity after the maximum was reached, indicating that product oxidation started to exceed product formation ( \\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}$$r_P/q_P~<~r_{OX}~\\Rightarrow ~-r_A/q_A$$\\end{document} r P / q P < r OX ⇒ - r A / q A ) at later process times. However, no MLR model with significant terms could be generated for both 21 h DoEs. The gradual change in behavior from \\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}$$r_P/q_P~>~r_{OX}$$\\end{document} r P / q P > r OX (21–33 h) to \\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}$$r_P/q_P~<~r_{OX}$$\\end{document} r P / q P < r OX (33–42 h) may have resulted in the peak antimicrobial activity not coinciding with a sample of the fixed sampling interval. Therefore, the MLR was subjected to a higher degree of uncertainty while employing the maximum antimicrobial activity as a response. Higher activities thereby decreased both the accuracy and precision of the assay ( \\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}$$\\simeq$$\\end{document} ≃ 1:8,192 dilution in the assay results in \\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}$$\\ge$$\\end{document} ≥ 50% growth reduction of the Listeria spp. for the highest samples). For example, the standard deviation of the biological triplicates of the 21 h DoE center point (16,613 BU/mL) was greater than the maximum activity of the induced batch (12,357 BU/mL). While a statistical evaluation of the DS was hindered by the analytical variability of the growth inhibition assay, the results obtained exceeded the production on yeast extract-based media \\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}$$\\simeq$$\\end{document} ≃ 1.3-fold. This was achieved using higher \\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}$$dO_2$$\\end{document} d O 2 levels (15% \\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}$$dO_2$$\\end{document} d O 2 compared to 2.5%) which impose less respiratory constraints on the cells. Hence, process understanding was demonstrated, as the obtained maximum match between the 24 h DoE and both 21 h DoEs (pH 6.0; C/P 1:45) and maximum antimicrobial activity was pushed past the literature reference on yeast extract-based media, utilizing cheap lignocellulosic feedstocks instead. Therefore, employing more advanced statistical methods than ordinary linear regression was not deemed necessary and the focus was set on improving the understanding of the effect of the shift to earlier induction. Fig. 4 a Mean and standard deviation of CER (orange line), OUR (blue line), b biomass (green squares) and product activity (violet diamonds) of C. glutamicum on UF-SSL minimal medium from DoE centerpoint cultures using an induced fed batch process started after 21 h of uninduced batch. Error bars and shading represent biological variation between 3 replicates, not technical replicates of measurements In single-substrate cultivations, feeding is typically started upon depletion of the single substrate in the medium. For multi-substrate systems, such as UF-SSL, certain primary substrates, especially glucose, are depleted before other secondary substrates (e.g., mannose) are metabolized, and the substrate with the lowest affinity (e.g., xylose) might take exceedingly long until depletion. In this case, growth stagnation or even cell starvation and partial lysis can occur before depletion of all substrates. Feeding after a pre-determined batch duration will result in an excess of secondary substrate during the early feeding phase until an equilibrium is reached. The more excess secondary substrates are available at the start of feeding, the more similar the conditions are to a batch extension. Since an increase in product activity was observed for more secondary substrate overhang, an extended batch approach was compared to the fed batch approach. Extended batch Extended batch processes are preferable for industrial settings due to their reduced complexity and ease of operation. Hence, the hypothesized benefit of substrate unlimited conditions was tested while applying the process understanding gained from the DoE approach. Cultivation conditions of the fed batch with the highest maximum product activity [uninduced: pH 7.0, \\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}$$dO_2$$\\end{document} d O 2 30%, 21 h; induced: pH 6.0, \\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}$$dO_2$$\\end{document} d O 2 15%] were used, but instead of feeding 1 L UF-SSL minimal medium, using an exponential function, the feed was added completely after 21 h within \\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}$$\\le$$\\end{document} ≤ 90 s. In addition, the NP feed was simplified [C/P 1:45, 200 mL, constant 6 mL/h] to further reduce the complexity of the process and thus promote industrial implementability. Furthermore, for lowering the pH from 7.0 to 6.0 upon induction, the UF-SSL-based feed with pH 4.3 \\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}$$-$$\\end{document} - 4.5 was used to reduce acid consumption. This reduced the potential commercial cost of production both in terms of lower capital costs, due to reduced process complexity, and lower operating costs, due to reduced resource use, beyond what is already contributed by the switch from yeast extract to lignocellulosic production. Fig. 5 a Mean and standard deviation of CER (orange line), OUR (blue line); b biomass (green squares) and product activity (violet diamonds) of C. glutamicum on UF-SSL minimal medium from uninduced batch cultures extended and induced after 21 h. Error bars and shading represent biological variation between 2 replicates, not technical replicates of measurements Maximum antimicrobial activity of 206,978 ± 24,717 BU/mL was achieved for the extended batch process mode (see Fig. 5 ). In contrast to the induced batch, the induction was performed at high cell densities upon batch extension, resulting in an \\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}$$\\simeq$$\\end{document} ≃ 17 fold increase in maximum antimicrobial activity. Compared to the fed batch, the maximum activity was reached at 36 h instead of 33 h, with similar activity at 33 h. This indicates that substrate limitation contributes to the change in behavior from \\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}$$r_P/q_P~>~r_{OX}$$\\end{document} r P / q P > r OX to \\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}$$r_P/q_P~<~r_{OX}$$\\end{document} r P / q P < r OX and should therefore be avoided. Reducing substrate limitation resulted in a further \\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}$$\\simeq$$\\end{document} ≃ 1.2 fold increase in maximum antimicrobial activity over the previous best."
} | 10,554 |
38500586 | PMC10945018 | pmc | 6,616 | {
"abstract": "Soil microorganisms play an important role in regulating and contributing to carbon cycling processes in grassland ecosystems. Soil salinization is one of the major problems causing soil degradation, and its effects on carbon cycle immobilization-related functional genes in soil microorganisms remain unknown. Therefore, we took Songnen salinization grassland as the research object, selected grasslands with different salinization levels, and explored the diversity of soil microorganisms and functional genes related to carbon cycling in Songnen grassland with different salinization levels through metagenomic technology. The results showed that with the increase of salinity, the relative abundance of Ascomycetes increased, while the relative abundance of Proteus and Firmicutes decreased. In addition, the relative abundance of functional genes related to carbon cycling fixation has also decreased. As the degree of soil salinization increases, the relative abundance of glycoside hydrolases (GH)130 family significantly increases, while the relative abundance of soil carbohydrate enzymes belonging to GH3 and GH55 families significantly decreases. Using structural equation modeling (SEM), it was found that soil pH and conductivity (EC) have a significant impact on soil microbial diversity and functional genes related to carbon cycling fixation. The increase in soil pH directly reduces the Shannon diversity of soil microbial diversity and functional genes related to carbon cycling fixation. Therefore, it can be concluded that the intensification of grassland salinization reduces the diversity of bacteria and fungi, and affects the diversity of functional genes related to carbon cycling fixation by reducing the total diversity of bacteria. The increase in salinity has a negative feedback effect on grassland soil carbon cycling. This study provides a theoretical framework for grassland soil carbon sequestration and degradation restoration.",
"conclusion": "5 Conclusion In this study, soil metagenomics revealed the mechanisms of microbial diversity and functional gene diversity, which are the main processes of carbon cycling under soil salinization in different grasslands. We found that the microbial community composition and carbon cycle immobilization-related functional gene composition in saline–alkaline in the Songnen Plain in Northeast China were closely and negatively related to soil pH and salinity. Finally, we found that soil salinization lowered the expression levels of genes and enzyme families involved in the immobilization of carbon-rich polymers. Therefore, we believe that improving the functional gene diversity of microorganisms and carbohydrate-related enzyme activities are the key factors to support the improvement and restoration of soil carbon cycle in saline-alkali grassland.",
"introduction": "1 Introduction Soil salinization has become a global ecological problem, with approximately 3% of the soil resources being salinized worldwide. The total area of saline soils in China is 35 million ha; this includes 29 million ha of grassland saline soils ( Mu et al., 2014 ). Human activities, such as overgrazing and perennial cultivation, remove vegetation, destroy the topsoil structure, increase surface evaporation and further transfer soluble salts from deeper soils, thereby increasing the salinization of grassland soils and severely inhibiting grassland productivity ( Guangqiang et al., 2009 ; Lu et al., 2022 ). As an important part of the ecosystem, soil microorganisms are not only involved in the material cycle and energy transformation process of the ecosystem, but also able to respond rapidly to changes in environmental factors ( Carolan and Fornara, 2016 ; Ma et al., 2017 ). Soil microorganisms can regulate the storage and release of organic carbon in soil by changing the rate of decomposing organic matter. Therefore, the population and metabolic characteristics of microorganisms are important indicators of the response of grassland ecosystems to soil salinization ( Zeng et al., 2018 ). Soil microorganisms play an important role in regulating and promoting the carbon cycle process in grassland ecosystems ( Li et al., 2013 ; Tang et al., 2019 ). Organic matter in soil can provide carbon source to microorganisms, which is absorbed and utilized by microorganisms in decomposition. The CO 2 produced during microbial decomposition and respiration is returned to the atmosphere. Previous studies have shown that increasing soil carbon sequestration is a very important way to actively address and mitigate global climate change ( Dai et al., 2018 ). Among them, microbial residues are an important source of soil organic carbon. It was found that the average contribution of microbial residual carbon to organic carbon in grassland soils (0–20 cm topsoil) was 47% ( Wang B. et al., 2021 ; Wang L. P. et al., 2021 ). Soil carbon export through carbon emissions (soil respiration and methane emission) caused by soil microorganisms and the leaching of dissolved organic carbon are also important determinants of the stability of the soil carbon pool ( Li L. F. et al., 2021 ; Li C. Y. et al., 2021 ; Li B. et al., 2021 ). Various specific carbon processes are responsible for the entire carbon cycle; these processes are regulated by genes involved in catabolism (through decomposition) and anabolism (through biosynthesis) ( Balasubramanian et al., 2020 ). Specific carbon cycle immobilization-related genes (e.g., those associated with the conversion of glucosides, starch, esters, chitin and lignin) and the microorganisms containing them are highly correlated with environmental factors, such as salinity, in grassland soils and play a more important role in soil carbon conversion and the stabilization of carbon pools than unrelated genes ( Wang et al., 2013 ). Furthermore, the mechanisms of potential soil microbes and metabolites in response to the salinization of grassland soils remain unknown ( Fornara et al., 2020 ). To understand the processes involved in the carbon cycle and their association with organic compounds, it is crucial to identify genes involved in these specific processes ( Nelson et al., 2017 ). To date, the impact of grassland salinity on soil carbon cycling has been mainly assessed by measuring the soil microbial biomass and assessing changes in the community structure. More recently, a small number of studies have focused on the effects of grassland salinization on bacterial or fungal composition ( Crowther et al., 2019 ; Xu et al., 2021 ). However, in contrast to studies on soil bacterial or fungal composition, the true impact of soil salinity on microbial functional genes remains unknown. Moreover, little is known about the interrelationships among soil salinity, soil microbial (bacterial and fungal) diversity and potential functional genes ( Duran et al., 2013 ; Taylor et al., 2021 ). In this study, we used soil metagenomics to compare soil microbial genes involved in carbon cycling in different saline grasslands and to examine their response to soil and environmental factors. We chose the saline meadow steppe in the Songnen Plain in Northeast China as the ideal platform for this study because this region has the largest concentration of sodic–saline soils in China, in addition to exhibiting typical saline grassland characteristics and a clear gradient of different saline grasslands. This study aimed to (i) determine the composition of microbial carbon cycle immobilization-related genes and enzymes associated with different levels of salinity and (ii) assess the mechanisms linking the physicochemical properties of soil with microbial species diversity and functional genes involved in carbon cycling in grasslands with different salinity gradients. We hypothesized that (i) soil salinization has a significant effect on the soil carbon cycle and soil microbial genes in grasslands and (ii) an increase in grassland soil salinization decreases the microbial species diversity and carbon cycle immobilization-related functional gene diversity in the soil.",
"discussion": "4 Discussion 4.1 Effects of soil pH and EC on carbon immobilization-related genes Soil salinization leads to a significant increase in soil pH and EC ( Lu et al., 2022 ). In general, elevated soil pH enhances the metabolic and decomposition activities of microorganisms, leading to increased soil carbon loss, lower soil organic carbon content, and reduced genetic diversity associated with carbon cycle fixation ( Tang et al., 2019 ). Therefore, the organic carbon content and gene diversity associated with carbon cycle fixation in severely salinized soils were generally lower than those in mild salinized soils ( Li L. F. et al., 2021 ; Li C. Y. et al., 2021 ; Li B. et al., 2021 ). The negative effects of salinization on soil microbial and carbon cycling-related genes can be explained by the low osmotic potential caused by high concentrations of salt, which can reduce the water supply for microbial activity, lead to soil microbial decomposition, and reduce soil microbial diversity ( Zhou et al., 2021 ). The abundance of microbial carbon fixation genes indicates the carbon sequestration potential of microorganisms, and the higher the gene abundance, the stronger the corresponding carbon sequestration potential, and the greater the contribution to soil carbon sequestration. Decreased genetic diversity associated with carbon cycling sequestration indicates a decrease in the carbon sequestration potential of soil microorganisms ( Xu et al., 2021 ). In our study, soil pH and EC also increased significantly as the salinity gradient increased, and the increase in soil pH reduced the microbial abundance associated with soil carbon cycling and the diversity of functional genes associated with carbon cycling fixation. Redundancy analysis showed that soil Anditalea and serratia were significantly positively correlated with soil SOM and negatively correlated with soil pH, indicating that the abundance of microbial diversity and carbon fixation functional genes were closely related to soil pH and organic matter ( Figure 5 ). Therefore, the microbial abundance of EST soil was significantly lower than that of MIS and MDS soils, which may be due to the lower SOM content and higher pH. At the same time, the low abundance of EST carbon-fixing functional genes may also be related to the inhibition of pH and EC in soil, and these results are consistent with previous studies. In addition, it has also been suggested that the growth of some carbon-sequestration bacteria in high-saline soils is inhibited due to higher oxygen concentrations, resulting in a weak microbial carbon sequestration potential in high-saline soils ( Balasubramanian et al., 2020 ). 4.2 Effects of grassland salinity on carbon cycle immobilization-related genes The main determinants of the rate of carbon cycle immobilization-related processes are the availability and accessibility of substrates and the activity of microorganisms ( Ma et al., 2021 ). Soil salinization directly affects the decomposition process of soil microorganisms, microbial activities and the growth and turnover of microbial communities. Severe salinization leads to gradual substrate depletion ( Li L. F. et al., 2021 ; Li C. Y. et al., 2021 ; Li B. et al., 2021 ). Substrate limitation, low microbial biomass and decreased high-quality specific microbial activity can reduce microbial carbon immobilization, resulting in the loss of carbon from the system; this has a potential positive feedback effect on soil salinization ( Li et al., 2019 ). We observed that the diversity of genes and enzyme families associated with the carbon cycle decreased during soil salinization. However, no significant difference was noted in the diversity between MDS and MIS with low salinity and between ETS and HET with high salinity. However, the diversity in ETS and HET was significantly different from that in MDS and MIS. This observation is consistent with the change in SOM and microbial biomass per unit, which is also associated with a change in grassland salinity ( Jiang et al., 2021 ). Although the measurement of potential enzyme activity is a general indicator, it reflects the activity of a limited group of enzymes under optimal conditions, thereby providing an incomplete understanding of what happens under natural conditions ( Chen et al., 2020 ). Among CAZymes, the abundance of GHs and GTs was higher and decreased with an increase in salinity. This indicated that increased salinity negatively affected the grassland soil carbon cycle, which was consistent the change trend noted in soil organic carbon contents ( Song et al., 2019 ). Moreover, physiological changes, especially the ability to produce and secrete the types of enzymes widely existing in soil microorganisms, were found to be an important reason for grassland soil salinization ( Wang et al., 2020 ). The increase in Gemmatimonas and decrease in Sphingomonas and Streptomyces with an increase in salinity exhibited the genes involved in the degradation of all organic carbon forms, indicating a group-specific response of grassland soil microorganisms to grassland salinization and/or substrate preference ( Lv et al., 2020 ; Liang et al., 2021 ). In this study, we only sampled during the annual grassland growth period, and there was a lack of multi-season samples, which had certain limitations, and some articles showed that there were different differences in microbial diversity and carbon fixation-related functional genes in saline-alkali grassland under different seasons ( Taylor et al., 2021 ), and then we will study the direction of seasonal changes in microbial diversity and carbon fixation-related functional genes in Songnen saline-alkali grassland, which will have a significant impact on the protection and restoration of Songnen saline-alkali grassland. Soil carbon management and other aspects provide a deeper theoretical basis."
} | 3,492 |
39607706 | PMC11662647 | pmc | 6,617 | {
"abstract": "Abstract \n Corynebacterium glutamicum is a key industrial workhorse for producing amino acids and high-value chemicals. Balancing metabolic flow between cell growth and product synthesis is crucial for enhancing production efficiency. Developing dynamic, broadly applicable, and minimally toxic gene regulation tools for C. glutamicum remains challenging, as optogenetic tools ideal for dynamic regulatory strategies have not yet been developed. This study introduces an advanced light-controlled gene expression system using light-controlled RNA-binding proteins (RBP), a first for Corynebacterium glutamicum . We established a gene expression regulation system, ‘LightOn C.glu ’, utilizing the light-controlled RBP to construct light-controlled transcription factors in C. glutamicum . Simultaneously, we developed a high-performance light-controlled gene interference system using CRISPR/Cpf1 tools. The metabolic flow in the synthesis network was designed to enable the production of chitin oligosaccharides (CHOSs) and chondroitin sulphate oligosaccharides A (CSA) for the first time in C. glutamicum . Additionally, a light-controlled bioreactor was constructed, achieving a CHOSs production concentration of 6.2 g/L, the highest titer recorded for CHOSs biosynthesis to date. Herein, we have established a programmable light-responsive genetic circuit in C. glutamicum , advancing the theory of dynamic regulation based on light signaling. This breakthrough has potential applications in optimizing metabolic modules in other chassis cells and synthesizing other compounds.",
"conclusion": "Conclusion In conclusion, we have developed ‘LightOn C.glu ’, the inaugural light-controlled gene expression system for C. glutamicum , characterized by its single-component structure, direct activation, highly tunable induction properties, precise spatiotemporal resolution, and strong adaptability. This system precisely regulates RNA metabolism to control gene circuits, enhancing biomanufacturing efficiency by optimizing artificial metabolic pathways in host cells. By rationally designing light-controlled bioreactors and optimising the fermentation process, we have successfully scaled light-regulatory gene expression systems from laboratory settings to industrial applications.",
"introduction": "Introduction As an industrial model microorganism, Corynebacterium glutamicum is widely used in fields such as the food and medical industries, showing remarkable potential for synthesizing various novel chemicals ( 1 , 2 ). However, target product synthesis in C. glutamicum often encounters difficulties, including organic acid by-product accumulation and noticeable bacterial growth inhibition ( 3 ). The metabolic and regulatory networks in the host cell tend to prioritize resources for cell growth and reproduction, making it challenging to balance cell growth with target product synthesis through static regulation alone ( 4 ). Therefore, achieving an optimal microbial cell factory requires directional and synergistic dynamic regulation of multiple key genes in the metabolic pathway ( 5–7 ). However, at present, effective dynamic control tools remain limited in C. glutamicum . Therefore, developing a more universal and refined dynamic control technology for C. glutamicum is of particular significance ( 8 ). In recent years, researchers have developed precise and effective tools for regulating gene expression within living cells, focussing on both temporal and spatial control ( 9 , 10 ). Chemically induced gene expression systems are well established, offering timely gene regulation with high induction levels and minimal background expression ( 11 , 12 ). However, these chemical molecular inducers face challenges such as physiological toxicity, pleiotropy, poor universality and uncontrollable diffusion ( 13 ), which restrict their removal during fermentation and hinder the system's ability to toggle between active and inactive states. Additionally, although some regulatory elements can activate or repress gene transcription in response to specific metabolites, not all intracellular metabolites have natural biosensors. Current dynamic regulatory strategies mainly focus on identifying and using transcription factor-promoters responsive to metabolites. This approach is not limited in scope but also affects the expression strength of the original promoter. Temperature-controlled gene circuits, which rely on temperature-sensitive transcriptional regulators and their corresponding promoters, often experience regulatory delays that can impact bacterial growth and essential enzyme activities ( 14 ). Conversely, light-induced switches offer several advantages, including high resolution, rapid transmission, good reversibility, controllable intensity and minimal toxicity ( 15 , 16 ). These features have made light-induced switches increasingly popular for developing precise spatiotemporal control technologies in cellular metabolism ( 17 , 18 ). However, current light control systems that utilize photosensitive transcription factors typically require specific promoter DNA-binding motifs ( 10 ). This necessitates fusing the operon sequence for transcription factor recognition with regulatory gene promoters, a process that can diminish promoter activity and universality across various chassis cells and varying gene expression scenarios. Furthermore, there are inherent delays in gene expression, transitioning from DNA to mRNA and subsequently from mRNA to protein. Starting regulation at the post‐RNA transcription stage of metabolism results in shorter delays than those of the previously studied gene expression systems. Therefore, the technology of dynamic gene regulation based on RNA level is highly expected. RNA-binding proteins (RBPs) are crucial in regulating cellular RNA functions, recognizing and binding to specific RNA sequences or structures ( 19 ). By integrating an RBP with a photosensitive structural domain responsive to blue light, the resulting fusion protein can bind specific RNA sequences upon exposure. This enables the photoregulation of RNA functions and metabolism within cells. When combined with various RNA effectors, these fusion proteins can facilitate optogenetic control over RNA localization, splicing, translation and stability ( 20 ). This system holds promise for controlling gene circuits, enhancing artificial metabolic pathway adaptability in host cells and improving biomanufacturing efficiency through precise regulation of RNA metabolism. Therefore, this study aimed to develop an efficient and controllable dynamic gene regulation system by constructing a high-performance, advanced light-controlled gene expression system, ‘LightOn C.glu ’ using a light-controlled RBP in C. glutamicum . This light control system does not require specific promoter DNA-binding motifs and offers good generalizability. Initially, we constructed a synthetic light-switchable activating protein, LicV, which is a fusion protein consisting of the transcription anti-terminator protein LicT and the VVD photosensitive domain. In darkness, LicV remains monomeric and does not bind to mRNA. Concurrently, the ribonucleic acid antiterminator (RAT) adopts a stem-loop structure that inhibits transcription. Upon light exposure, LicV dimerizes and binds to the RNA, altering the RAT structure and allowing transcription to proceed, thereby initiating gene expression. We then developed a mutant library of the linker region between LicV recombinant proteins and the LicV gene RBS sequence, creating multiple light control systems with finely tunable induction characteristics, such as background noise, maximum activation level, activation kinetics and photosensitivity. Further studies indicated that this system could integrate with the CRISPR-dCpf1 system to construct a ‘NOT’ Boolean logic gate and develop a high-performance light-controlled gene interference system. Subsequently, we used the chitin oligosaccharides (CHOSs) and chondroitin sulphate oligosaccharides A (CSA) synthesis pathways as a proof of concept. By strategically designingthe metabolic flows of these synthesis networks through light-controlled gene expression regulation, we induced dynamic gene interference within competing pathways, improving the target product titer. A 5-L light-controlled bioreactor was designed for light culture to validate the adaptability of the light-controlled gene expression system at the microbial reactor scale. Finally, the titer of CHOSs increased to 6.2 g/L, marking the highest microbial synthesis titer of CHOSs to date. Our discoveries offer crucial theoretical and technological guidance for enhancing the use of light-controlled bioreactors in industrial applications. This work provides a novel and effective toolkit for dynamic regulation in C. glutamicum , expanding the scope of control genetics from photosensitive and growth-regulating proteins to dynamically managing metabolic fluxes. By integrating control genetics into dynamic metabolic pathway regulation, we enriched the theory and methodology of light signaling‐based dynamic regulation. The framework developed here for designing and optimizing light-responsive gene circuits based on RBPs may be useful for engineering other microorganisms.",
"discussion": "Discussion Precise regulation of gene expression is crucial for understanding the life activities of organisms. Traditionally, gene regulation methods have relied on chemical molecular inducers. However, this approach faces considerable challenges, including the toxicity of chemical molecules to cells, non-specific gene regulation and the complexities of downstream separation and purification ( 10 , 31 ). These limitations have restricted their industrial applicability. Optogenetics, a promising synthetic biology tool, has emerged as a solution by enabling control over metabolic flux distribution ( 17 , 32 ). It addresses the drawbacks of conventional dynamic regulation tools, such as poor generalizability, limited regulation range, slow response speed, and difficulty in separation and purification ( 33 ). Optogenetics extends the scope of dynamic regulation methods, making it an attractive option in industrial applications. Current methods of light-based gene regulation typically rely on the recognition of target DNA sequences (usually located in the promoter region) using light-controlled transcription factors ( 34 , 35 ). However, the limited options for designing DNA target sequences limit the widespread use of optogenetic tools depending on light-controlled factors. In this study, we introduced ‘LightOn C.glu ,’ the first optogenetic tool for C. glutamicum , to the best of our knowledge. This is the inaugural report of using RNA-based binding proteins in conjunction with photosensitive proteins to regulate gene expression in C. glutamicum . By adjusting the parameters of the expression components, we constructed a series of highly adjustable light-control tools characterized by their regulatory window, activation kinetics and photosensitivity, providing flexibility under various experimental conditions. The gene expression regulation system using light-controlled transcription factors and RBPs exhibits clear advantages over existing light-activated systems. Firstly, it does not rely on specific DNA-binding motifs of promoters and avoids fusing transcription factor operon sequences with regulatory gene promoters. Thus, eliminating interference with promoter activity and enhancing versatility across different chassis cells and gene expression conditions. Secondly, regulating metabolism at the RNA transcription level proves more efficient than at the DNA to mRNA or mRNA to protein stages. Thirdly, the system's design is simple and compact, consisting only of the photosensor component, which simplifies genetic engineering operations. Additionally, its highly tunable induction characteristics—such as window adjustment, activation kinetics and photosensitivity—offer adaptability for various experimental setups. Finally, integrating a light-controlled gene expression system into the fermentation process at the bioreactor scale enhances the design and operation of bioreactors. During this period, the light signal can be applied or removed immediately to control batch or fed-batch fermentation processes. Based on this, we combined the light-controlled gene expression regulation system with the CRISPR/Cpf1 system to develop a high-performance light-controlled gene interference system. This system downregulates metabolic flux in competitive pathways, redirecting it towards the synthetic pathway of the target metabolite. Employing the biosynthesis of CHOSs and CSA as examples, we rationally designed the metabolic flow using a gene expression regulation system based on light-controlled RBP, enabling efficient synthesis of these compounds in C. glutamicum . This study not only fills the gap in light-controlled gene regulation tools for C. glutamicum , but it also shows that the light-controlled RBP gene expression system effectively enhances the synthesis of target chemicals, offering significant practical value in metabolic engineering. However, some work requires further research. In light-controlled bioreactors, the penetration depth of light signals is usually limited. In order to solve this problem, it is necessary to improve the mass transfer and regulation performance from the aspects of optical control system expression elements and bioreactor design. First, for photosensitive proteins, it is necessary to analyze and remodel the protein structure in detail, and develop photosensitive protein variants with higher light sensitivity, so that less light intensity in the bioreactor can achieve stronger regulation effect. Additionally, additional research is needed to clarify how the gene circuit responds to the complex interplay of light patterns and to develop a statistical model that links the light-controlled RBP expression system with target gene expression levels. This model will be instrumental in optimising light-controlled fermentation processes. Moreover, exploring other RNA-binding structural domains and photosensitive proteins that respond to different wavelengths could extend the application spectrum of RBP-based photoregulatory systems in dynamic regulation. Expanding the use of photoconvertible RBPs in biological research would enable the simultaneous regulation of multiple RNAs, enhancing our understanding of complex biological processes. In addition, high-performance computer clusters are necessary for simulating computational fluid dynamics to account for different parameters that react to temporal and spatial dynamic changes in the light and flow fields of light-controlled cells. Implementing an artificial neural network to analyze this dataset could develop a black-box model capable of predicting flow field characteristics under any set of operating conditions within the normal operating range. This model could support real-time process control and fermentation process analysis, guiding the rational design and optimization of light patterns and reactor structures in light-controlled bioreactors, tailored to the metabolic performance of the light-controlled cells."
} | 3,814 |
31750012 | null | s2 | 6,618 | {
"abstract": "Protein-based materials have emerged as a powerful instrument for a new generation of biological materials, with many chemical and mechanical capabilities. Through the manipulation of DNA, researchers can design proteins at the molecular level, engineering a vast array of structural building blocks. However, our capability to rationally design and predict the properties of such materials is limited by the vastness of possible sequence space. Directed evolution has emerged as a powerful tool to improve biological systems through mutation and selection, presenting another avenue to produce novel protein materials. In this prospective review, we discuss the application of directed evolution for protein materials, reviewing current examples and developments that could facilitate the evolution of protein for material applications."
} | 209 |
30742048 | PMC6370833 | pmc | 6,619 | {
"abstract": "Microalga is a promising biomass feedstock to restore the global carbon balance and produce sustainable bioenergy. However, the present biomass productivity of microalgae is not high enough to be marketable mainly because of the inefficient utilization of solar energy. Here, we study optical engineering strategies to lead to a breakthrough in the biomass productivity and photosynthesis efficiency of a microalgae cultivation system. Our innovative optical system modelling reveals the theoretical potential (>100 g m −2 day −1 ) of the biomass productivity and it is used to compare the optical aspects of various photobioreactor designs previously proposed. Based on the optical analysis, the optimized V-shaped configuration experimentally demonstrates an enhancement of biomass productivity from 20.7 m −2 day −1 to 52.0 g m −2 day −1 , under the solar-simulating illumination of 7.2 kWh m −2 day −1 , through the dilution and trapping of incident energy. The importance of quantitative optical study for microalgal photosynthesis is clearly exhibited with practical demonstration of the doubled light utilization efficiencies.",
"conclusion": "Conclusion In this study, the optical inefficiency of microalgal photosynthesis was revealed through advanced system modelling based on both microscopic 3D tomography and macroscopic photosynthesis profile. While the cultivation of microalgae has been mostly studied in the field of bioengineering, we have shown that optical study is a key to further boost the biomass productivity to >100 g m −2 day −1 by making photons penetrate longer distance into the bioreactor. We proposed a V-shaped cultivation as a practical scheme for trapping and diluting sunlight. Our modelling work verified that the V-shaped cultivation can achieve the nearly doubled biomass productivity within the incident angle variation of ±23.5°, compared to the previously proposed photobioreactors of vertically or horizontally installed planar or tubular configurations. Experimentally, we verified that the V-shaped configuration can enhance the biomass productivity from 20.7 g m −2 day −1 to 52.0 g m −2 day −1 under 7.2 kWh m −2 day −1 with an outdoor-simulating environment and such areal productivity was shown to be consistent regardless of the cultivation volume, leading higher volume productivity in shallow reactors.",
"introduction": "Introduction Photosynthesis is the principle process by which life converts solar energy and CO 2 into reduced and functional carbon forms and is the product of billions of years of evolution. The global photosynthetic rate of ~130 TW 1 , 2 secures environmental homeostasis by maintaining the carbon balance between land and atmosphere. However, since the industrial revolution, humans have increasingly rapidly burned carbon chemicals (~16 TW) 3 accumulated over the last 100 million years, causing carbon imbalance and, consequently, increasingly daunting global climate change on Earth. Therefore, renewable energy alternatives must be developed and implemented in a multilateral and unceasing manner 4 – 7 . The depletion of the finite chemical energy resources is another reason to pursue such alternatives, especially because of the necessity of carbon-based liquid fuels for transportation (~4 TW) 8 at least for the near future. Biofuels are generally viewed as a solution: they are produced in a continuous manner and reduce CO 2 in the process. However, this potentially green solution, particularly to become effectively commercialized, has many issues that must be overcome. The most important issue is the requirement for large amounts of arable land: at least 6 more Amazon rainforests 9 – 11 are required to meet the 4 TW demand through the cultivation of terrestrial plants such as grains and trees. One promising alternative to terrestrial biomass feedstock is microalgal biomass. These phototrophic microorganisms achieve a 10- to 50-fold higher photosynthesis rate (PR) than terrestrial plants 12 – 14 ; therefore, they need a far smaller land area for biomass production than their terrestrial counterparts. Nevertheless, there exist plenty of challenges for production of microalgal biomass with monoculture, such as avoiding contamination, enhancing lipid contents, and reducing production cost. In particular, we focus on the fact that the present biomass productivity of 10–20 g m −2 day −1 in open-pond cultivation systems, which are advantageous for scaling up and for mass production, is far from profitable, especially in the form of fuels 12 – 15 . Given that such a low productivity has much do with the exceedingly limited utilization of the incoming light, ingenious optical engineering can offer a breakthrough in tackling this otherwise almost insurmountable challenge. Previous attempts can broadly be classified into two: (i) quantity control for diluting strong incident light energy with light guides 16 – 22 , vertically or obliquely installed reactors 23 – 26 , tubular or spiral design 27 – 33 , or increased surface areas 34 – 37 ; and (ii) quality control for effectively utilizing the solar spectrum with luminescent materials 38 – 46 . Although these efforts are useful in various ways, the comprehension of optical behavior of microalgae in particular is greatly lacking, which fundamentally hampers design innovation able to overcome such limited performance. The present study aims to make the best of the optical engineering for the purpose of maximizing the biological counterpart, namely, microalgal photosynthesis; and in so doing, establishing general and specific design rules encompassing economically viable optical strategies in a way that extracts the full potential of microalgal biomass productivity. Based on a 3D profile analysis for refractive indices of algal cells, a realistic model for photosynthetic systems is proposed to better understand the macroscopic behaviour of the photosynthetic microbes. The theoretical analysis predicts that biomass productivity can reach ~140 g m −2 day −1 by way of light energy redistribution under high illumination. To realize this theoretical potential in a practical sense, which is directly applicable to an open pond, a V-shaped cultivator is chosen. When the light energy is efficiently diluted and trapped by adopting the V-shaped bioreactor under an illumination of 7.2 kWh m −2 day −1 , the biomass productivity is experimentally shown to be improved more than 2.5-fold, from 20.7 g m −2 day −1 to 52.0 g m −2 day −1 .",
"discussion": "Results and Discussion Experimental design For the microalgal research, the large-scale outdoor cultivation and lab-scale indoor evaluation have strong pros and cons of each. The outdoor cultivation provides the same environmental condition as the real world application and it is considered to be more trustworthy in the industry; however, its environmental dependence, uncontrollability, and high installation cost have been a high barrier to entry for scientific investigation and innovative challenges. On the other hand, despite the convenience and controllability, lab-scale indoor experiments have been considered to be rarely reproducible in the real-world. Therefore, this research has focused on the establishment of a rigorous outdoor-simulating cultivation system, which would bring the system design work to the field of academic research. A metal halide lamp with proper spectral filters (K3700, McScience, Korea) was adopted to simulate outdoor conditions. Within the wavelength range of 400–800 nm, the relative portions of the photons in 400–500 nm, 500–600 nm, 600–700 nm and 700–800 nm were 28%, 27%, 29%, and 16%, on average, while those are 26%, 28%, 26%, and 21% in the real sunlight with the spectrum of AM 1.5 G, exhibiting only a reasonable deviation of a few percent in the visible range. The illumination intensities were maintained within 0.55–0.60 sun by using a photodiode detecting 300–800 nm, where 1 sun intensity corresponds to 1000 W m −2 for AM 1.5 G and visible photons of 2000 μmol m −2 s −1 (=2000 μE m −2 s −1 ). A photoperiod of 12 h :12 h (light:dark) was adopted to simulate the daily variation of the solar illumination, but the hourly variation of its intensity was not taken into account here due to technical limitation. Continuous illumination during daytime may overestimate the real-world biomass productivity by reducing the peak intensity and alleviating the difficulties of cells to adjust the photosynthetic machinery to variations in light intensity. Such overestimation would decrease in the light diluting schemes, which will be discussed in this manuscript, and we leave more precise investigation of the effect of such hourly intensity variation as a future work. The illumination of 0.6 sun with this photoperiod corresponds to 7.2 kWh m −2 day −1 . The illumination area of each bioreactor was confined by apertures and the sides of the reactors were covered by metal (aluminium foil or a stainless steel wall), which prevented overestimation caused by undesirable photon influx from the outside and realized the periodic boundary condition, making it possible for a laboratory-scale reactor to simulate a large system. All the bioreactors were entirely covered by the transparent covers with the same transparent material (i.e. polycarbonate) regardless of their geometry, in order to focus on their geometrical effects rather than material characteristics such as UV-cutting effect. The validity of our system design and corresponding scalability of the system will be demonstrated in our experimental results later. Optical study of microalgal photosynthesis Previous optical studies have viewed photosynthesis in a bioreactor as a macroscopic phenomenon 47 – 56 ; therefore, the microscopic optical characteristics of the cells inside the reactor have been rarely studied, and their importance has been scarcely noticed. Here, optical diffraction tomography 57 , 58 was used to investigate the biochemical and morphological properties of microalgal cells. Figures 1a and S1 illustrate the 3D refractive index distribution of individual microalgal cells measured at the wavelength of 532 nm. The measured 3D refractive index tomograms of microalgal cells clearly show that individual cells are composed of highly inhomogeneous refractive index distributions and also have refractive indices of 1.36–1.46, which are higher than that of surrounding media (water, n = 1.33). Thus, significant amounts of light scattering events can be expected, particularly when there exists large number of microalgal cells. This phenomenon can be quantitatively analysed using the finite-difference time-domain (FDTD) method based on the tomogram (refer to supplementary information (SI)) in Fig. 1b . Such light scattering, although nominal (<2°) with a single cell, becomes substantial with a number density of 10 7 –10 8 cells mL −1 (refer to SI (Fig. S2 )). Figure 1 Optical characteristics of microalgal cells. ( a ) 3D profile of the refractive index ( n ) of a Chlorella vulgaris cell. ( b ) Volume distribution of the refractive index in the Chlorella vulgaris cell (above) and the calculated angular distribution of light scattered by a single cell. ( c ) Picture of a top-illuminated bioreactor (first), ray-traced image of custom-made optical simulation (second), and simulated light absorption (in log scale) with depth under red (680 nm), green (530 nm), blue (440 nm), and solar (AM 1.5 G) illumination (third, the background image is for the AM 1.5 G absorption profile on a linear scale). ( d ) Experimentally measured (black) or modelled (red, green, and blue for the models based on Eqs 1 – 3 , respectively) areal biomass productivity for various illumination (inset: action spectrum used for the modelling and optical density (O.D.) measured for Chlorella vulgaris ). Light absorption and scattering of the cells result in the uneven distribution of the light energy inside a bioreactor, as shown in the first image of Fig. 1c . As photons are blocked by the cells near the water’s surface, light energy is mostly concentrated within a few centimetres, as is photosynthetic activity; consequently, a negligible degree of photosynthesis occurs in the remainder of the cultivation volume. Monte Carlo Method can be adopted to investigate and visualize such optical properties 59 – 61 . To mimic the macroscopic behaviour of microalgae, we designed triangular bubbles and used them as cells for a custom-made optical simulation, as shown in the second image (refer to SI (Fig. S3 )). The calculated absorption profiles for red (680 nm), green (530 nm), blue (440 nm), and solar (AM 1.5G) illuminations are shown in the third image of Fig. 1c . Green photons and AM 1.5 G light reach deeper than blue and red photons, which have relatively high extinction coefficients. Such optical characteristics result in a sub-linear productivity with respect to illumination, as shown in Fig. 1d ; consequently, the corresponding photosynthesis efficiency (PE) becomes low under increased illumination. The black dots in Fig. 1d represent the experimentally achieved biomass productivity of microalgae ( Chlorella vulgaris ) under various artificial solar illuminations (AM 1.5G). Modelling of microscopic responses of microalgae will deepen our understanding of their photosynthetic mechanism and the resulting macroscopic behaviours of the photosynthetic system. In previous related studies 47 – 56 , the PR is mostly represented by a single fitting equation with a sole parameter of total illumination, which ignores the aforementioned optical energy distribution. In the present study, the microscopic PR profile is newly expressed as a function of ( x , z ) position modifying the macroscopic models previously proposed. Then, the macroscopic biomass productivity can be obtained by integrating the spatial PR for a whole system. Figure 1d compares such integrated biomass productivities using 3 different models with our experimental results, where the model 1 49 , 50 , 56 , 2 47 , 48 and 3 54 are based on 1 \\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}$$\\begin{array}{rcl}PR(x,\\,z) & = & {C}_{{\\rm{volume}}}\\times {R}_{{\\rm{\\max }}}\\times \\,\\tanh ((\\int {A}_{{\\rm{action}}}(\\lambda )\\times \\#Ph.\\,(\\lambda ,\\,x,\\,z){\\rm{d}}\\lambda )\\\\ & & /({C}_{{\\rm{volume}}}\\times {R}_{{\\rm{\\max }}})\\phantom{\\int }\\,),\\end{array}$$\\end{document} P R ( x , z ) = C volume × R max × tanh ( ( ∫ A action ( λ ) × # P h . ( λ , x , z ) d λ ) / ( C volume × R max ) ∫ ) , 2 \\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}$$\\begin{array}{rcl}PR(x,\\,z) & = & {C}_{{\\rm{volume}}}\\times {R}_{\\max }\\times \\int {A}_{{\\rm{action}}}(\\lambda )\\times \\#Ph.(\\lambda ,x,z){\\rm{d}}\\lambda \\\\ & & /({I}_{half}+\\int {A}_{action}(\\lambda )\\times \\#Ph.(\\lambda ,\\,x,\\,z){\\rm{d}}\\lambda ),\\end{array}$$\\end{document} P R ( x , z ) = C volume × R max × ∫ A action ( λ ) × # P h . ( λ , x , z ) d λ / ( I h a l f + ∫ A a c t i o n ( λ ) × # P h . ( λ , x , z ) d λ ) , 3 \\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}$$\\begin{array}{rcl}PR(x,\\,z) & = & {C}_{{\\rm{volume}}}\\times {R}_{{\\rm{\\max }}}\\times 2\\times {I}_{{\\rm{\\max }}}\\int {A}_{{\\rm{action}}}(\\lambda )\\times \\#Ph.(\\lambda ,\\,x,\\,z){\\rm{d}}\\lambda \\\\ & & /({{I}_{max}}^{2}+{(\\int {A}_{action}(\\lambda )\\times \\#Ph.(\\lambda ,x,z){\\rm{d}}{\\lambda })}^{2}),\\end{array}$$\\end{document} P R ( x , z ) = C volume × R max × 2 × I max ∫ A action ( λ ) × # P h . ( λ , x , z ) d λ / ( I m a x 2 + ( ∫ A a c t i o n ( λ ) × # P h . ( λ , x , z ) d λ ) 2 ) , respectively, where C volume is the cell biomass concentration, assumed to be 1.4 g L −1 , which is the average saturated biomass concentration in our experiments, and #Ph .( λ, x, z ) is the number rate of absorbed photons per volume at a given wavelength and position. R max is a constant for the effective maximum PR per weight, influenced by several biological or environmental parameters (species, nutrient, aeration, etc.). A action ( λ ) is an absorbed-light action spectrum defined as the ratio of photons used for photosynthesis to the total photon absorption at a given wavelength; our chosen species Chlorella vulgaris is assumed to have the same spectrum as Chlorella pyrenoidosa from previous reports, as shown in the inset of Fig. 1d 62 , 63 . A action ( λ ) is relatively low under blue light and becomes ~84 % for the entire visible light spectrum. Because 48 photons in total are consumed to produce one glucose molecule (29.8 eV) during the photosynthesis process, at least 57 visible photons should be absorbed per 29.8 eV bioenergy produced under low illumination (i.e., Δ PR(x, z)/Δ#Ph.(x, z) | #Ph .→0 = 29.8 eV/57 photons = 8.36 × 10 −20 J/ photon ). This value is the same as that experimentally predicted by others 64 , 65 . I half in Eq. 2 indicates the absorbed active photon densities (=∫ A action ( λ ) × #Ph .( λ, x, z ) d λ ) for PR reaching the half maximum value, and I max in Eq. 3 indicates that for the maximum value. Here, as a boundary condition, we assumed that 57 visible incident photons (i.e. ∫ A action ( λ ) × #Ph .( λ ) d λ = 48) are completely consumed to produce one glucose molecule under the extremely low illumination; then, I half and I max become dependent variables equal to C volume × R max × 48/(29.8 eV) and 2 × C volume × R max × 48/(29.8 eV), respectively, and R max is the only parameter to be fitted. Figure 1d reveals that the experimental results for flat bioreactors under various illuminations are well matched with our models assuming R max = 0.30 W g −1 for (1) and R max = 0.40 W g −1 for (2) and (3). It should be noted that we succeeded in fitting our models to the experimental results even without the terms for photoinhibition and weight loss from respiration, which appear in many previous models and should be considered important. The exclusion of those terms made our model very simple, minimizing the unknown variables; and it was validated by the facts that (i) all our experiments were based on closed photobioreactors with plastic covers absorbing harmful ultraviolet light; and (ii) R max fitted to the experimental results can roughly reflect the effect of respiration loss (refer to SI for details). While all the models well represent the optical saturation property of photosynthesis, we chose Eq. 1 for calculating the spatial photosynthesis rates in the rest of this manuscript. Figure 2a shows the volumetric PR (W L −1 ) inside the top-illuminated flat cultivator based on our new system. A biomass productivity of 12.5 g m −2 day −1 is estimated under 1.2 kWh m −2 day −1 , which corresponds to 12 hours of 0.1 sun (visible photons of 200 μmol m −2 s −1 ) illumination, which is a quantitatively similar light intensity to typical light-emitting diodes (LEDs). A combustion heat of 4.2 kcal g −1 is obtained from the experiments. Under this condition, the photosynthetic efficiency (PE) of biomass energy is found to be 5.1%. Under such low illumination, the number of photons works as the most deterministic factor of photosynthesis, and the total productivity almost proportionally increases along with the illumination, as shown in Fig. 1d . Under an illumination of 3.6 kWh m −2 day −1 (12 hours of 0.3 sun ), which corresponds to the annual average outdoor condition of South Korea, the biomass productivity is increased to 18.7 g m −2 day −1 . Compared with the 1.2 kWh m −2 day −1 illumination, as shown in Fig. 2a , photosynthesis occurs more deeply and more intensively; the 50% increase in total productivity, by contrast, is much less than a 3-fold illumination boost; therefore, the PE is reduced to 2.5%. This reduced efficiency occurs because the photon flux is saturated near the surface. Likewise, under a higher illumination of 7.2 kWh m −2 day −1 (12 hours of 0.6 sun ), which corresponds to the daily illumination of the world’s hottest regions (such as the Sahara Desert and the Andes Mountains), the biomass productivity increases to 22.8 g m −2 day −1 ; however, the PE drops to 1.5%, as the excess photons are not efficiently utilized. It should be noted that the areal productivity of 22.8 g m −2 day −1 corresponds to the volume productivity (=areal productivity/reactor depth) of 0.46, 0.23, and 0.08 g L −1 day −1 for the reactors with a depth of 5, 10, and 30 cm, respectively. Such optical inefficiency, unless resolved, thwarts the installation of photosynthetic systems in highly illuminated places. Figure 2 Optical study of microalgal cultivation system. ( a ) Simulated photosynthesis rate profiles and expected biomass productivities under 0.1 sun (first), 0.3 sun (second), and 0.6 sun (third) illuminations. ( b ) Simulated photosynthesis rate profiles under 0.6 sun with an increased light propagation of 2 D prop and 4 D prop . ( c ) Expected biomass productivities of the systems in ( a , b ) and the ideal reactor under various illuminations. ( d ) Concept of cultivation building with multiple stacks. Effective alleviation of the optical inefficiency, particularly under high illumination, is therefore a key to achieving an economically feasible level of biomass productivity. For a biomass concentration of 1.4 g L −1 , which was assumed here, a light propagation depth ( D prop ) of 1/α (α: 2.1 cm −1 ) is only 0.47 cm. As shown in Fig. 2b , hypothetically assuming that photons can propagate twice and 4 times deeper with the same cell concentration, the expected biomass productivity would be increased to 38.7 g m −2 day −1 and 60.3 g m −2 day −1 , respectively, even under the same illumination. Figure 2c presents the expected biomass productivity of those virtual conditions as a function of illumination. The productivity difference increases under higher illumination, whereas the productivity is nearly saturated in the original system. In particular, for an ideal system, which sufficiently dilutes incident light, a PE of 9.7% can be achieved for all illumination conditions, and a biomass productivity of ~140 g m −2 day −1 is achievable under high illuminations of >7.2 kWh m −2 day −1 . While the genetic engineering approach must be continuously sought to increase D prop by reducing the absorption cross-section of each cell 64 , optical approaches with system design would possibly offer an equally effective and/or synergistically better means to it. A futuristic, potentially ideal cultivation system can be constructed as a form of cultivation building by inserting light guides into the deep or multiply stacked bioreactor, as schematically illustrated in Fig. 2d 16 – 22 . In the cultivation building, light energy can be evenly distributed through the guides such as optical fibers; however, this concept has been rarely realized before and there are inevitable limitations associated with it, such as structural complexity, high-cost installation of optical components, and high-cost operation of light tracking, which must be accompanied to fix the focus of concentrated light to the light guide according to the solar movement. As a more practical light dilution approach, planar or tubular type photobioreactors are widely used 23 – 33 , but performance is inferior to the ones in Fig. 2c , as discussed in the next section. Practical configuration for boosting productivity To realize the light dilution in an easily implementable fashion, we modified the configuration of shown in Fig. 2d in such a way that each stack is inclined, as shown in Fig. 3a . As a result, the incident sunlight is evenly distributed among the stacks without requiring high-cost optical components. This scheme converges to a V-shaped array cultivator 25 – 27 , as presented in Fig. 3b , of which concept is simple and easy, but has been less spotlighted and rarely studied scientifically. The inclined surfaces of the V-shaped system receive sunlight over a larger area, and the light intensity is diluted by sin( θ v /2), where θ v is the vertex angle. Hence, the V-shaped configuration is equivalent to the system shown in Fig. 2b with D prop ’= D prop /sin( θ v /2) or the cultivation structure in Fig. 2d with 1/sin( θ v /2) stacks. If the system is aligned along the east-to-west line and properly tilted according to the latitude of the installed location, the incident angle of sunlight at noon can be restricted within only ±23.5° from the normal line for an entire year 66 – 69 . The system can be alternatively realized by implementing a V-shaped cover on top of a raceway pond (inset of Fig. 3b ), which makes the V-shaped system economically more viable compared to previous light propagation enhancement systems that are mostly restricted to photobioreactor types or use high-cost optical components 70 – 72 . The V-shaped scheme is very scalable as well (refer to SI (Fig. S4 )); what is better, the material cost does not depend on the depth of the pond. The cover can be made of various transparent materials and it would increase the installation cost. However, the cost would be compensated for by an enhanced algae productivity of more than 100%. The techno-economic analysis shown in SI (Fig. S6 ) reveals the V-shaped cover has a potential for reducing the microalgal biomass selling price from ~US$540 ton −1 to ~US$280 ton −1 in an open pond with the improved productivity. Moreover, by blocking the interface with air, the implementation of the cover would also be beneficial for reducing the operation cost by minimizing water evaporation, which accounts for up to 67% of the total water use, and CO 2 consumption, which mostly escapes to the air due to a low water solubility and accounts for 15–20% of the total price of the dry biomass 15 . Figure 3 Optical modelling for V-shaped microalgal cultivation. ( a ) Cultivation building modified to the V shape. ( b ) V-shaped cultivation array system. (inset: a raceway pond with a V-shaped cover) ( c ) Simulated absorption (left) and photosynthetic rate (right) profiles of the V-shaped system (inset: those for flat systems) ( d ) Average photosynthesis rate as a function of depth. ( e–g ) Calculated Fresnel reflection loss on the surface of ( e ) the flat system, ( f ) the vertical plate, and ( g ) the V-shaped system for an incident angle change parallel (angle 1) or perpendicular (angle 2) to the cross-section plane. Our optical system modelling of photosynthesis enables the prediction of the photosynthetic performance for non-planar-type cultivation. Figure 3c shows a simulated optical energy distribution in a V-shaped system with θ v = 30°, which is equivalent to the cultivation structure comprising 3.9 stacks. Compared to the flat system (inset), incident light reaches much deeper and the integrated photosynthesis depth profile becomes more uniform, as shown in Fig. 3d . The total biomass productivity is expected to be 49.6 g m −2 day −1 , which is 118% higher than that of the flat system and between those for D prop ’ = 2 D prop and D prop ’ = 4 D prop (Fig. 2b,c ). In fact, the V-shaped configuration was proven to be one of the most efficient light-trapping schemes in a PV study 67 , 73 , 74 . Figure 3e–g present the Fresnel reflection loss on the air/glass/water interfaces of a ground-type reactor, a vertical plate reactor, and a V-shaped reactor, respectively. As the Fresnel reflection increases as the incident angle increases, the reflection loss is considerable, especially in the vertical plate; the loss becomes highest at small angles 1 and 2 (inset of Fig. 3e ), which correspond to summer or noon with high illumination. Therefore, a large amount of loss follows. However, such losses can be almost fully avoided by the V-shaped geometry because the photons escaping from one side can enter the opposite side. Comparative study of various configurations While there have been numerous approaches previously proposed for light dilution, the system modelling designed here makes it possible to quantitatively compare the different geometry and optimize the best architecture. To make a general comparison, we classified and simplified the previously proposed configurations into a few 2D cross-sectional geometries including (i) horizontally placed planar geometry (e.g. open-pond, top-illuminated bioreactors with a flat surface, etc.); (ii) vertically placed planar geometry obliquely receiving sunlight (e.g. vertical plat panel, vertical cylinder, etc.); (iii) horizontally placed circles array (e.g. horizontal tubular bioreactors, etc.); and (iv) vertically placed circles array (e.g. fence tubular, helical tubular, spiral bioreactors, etc.), varying vertex angle of V-shape or radius of circles as shown in Fig. 4 . The illumination was roughly assumed to be 7.2 cos( θ i ) kW m −2 day −1 where θ i indicates the incident angle on the cross-sectional plane of each system shown in Fig. 4b . For the vertical systems, the geometrical fill factor was assumed to be dense enough to absorb the full illumination without optically dead area on the ground. Figure 4 Comparative study for various cultivation systems. ( a ) Calculated areal biomass productivities of V-shaped cultivators ( θ v = 30°, 60°, and 90°, denoted by V30, V60, and V90, respectively) and planar (P) or tubular (T10 for diameter of 10 cm and T4 for diameter of 4 cm) cultivators horizontally or vertically installed on the ground as a function of the incident angle on the cross-sectional plane. ( b ) Photosynthesis rate (PR) profiles inside the systems in ( a ) with the same scale bar, at the incident angle of 0° for the horizontally installed systems and 30° for the vertically installed systems as represented by the arrows. The V-shaped systems with vertex angles of 30° and 60° are shown to much outperform the other systems near the normal incident angle ( θ i = 0°), while that of 90° is similar to the one for tubular reactor with a diameter of 10 cm. The biomass productivity at the normal angle is shown to increase as the vertex angle decreases and the factor of light dilution (=1/sin( θ v /2)) increases. On the other hand, for the larger incident angle ( θ i > 1/sin( θ v /2), the incident light impinges on only one side of the V-shaped bioreactor, and the illuminated area decreases as the angle increases further. As a result, the light dilution effect is reduced and the productivity drops rapidly. Concentrating the light dilution effect near the normal incident angle is an effective strategy since the diluting effect is especially critical for the high illumination with the high altitude of the sun. Aligning the bioreactor can further minimize the cross-sectional angle variation as described in Fig. 3b ; the annual variation of the incident angle at noon can be restricted to ±23.5°. The horizontally installed planar bioreactor has shown the minimum variation of the productivity along the variation of the incident angle, since the factor of light dilution is always 1 regardless of the incident angle. On the other hand, the effect of light dilution was shown to be not significant for the vertically installed planar reactor for all angles, despite a dilution ratio of 1/sin( θ i ). In the vertical systems, the angle between the light and surface becomes shallow as the incident angle decreases, and the corresponding Fresnel reflection increases, as discussed in Fig. 3f ; the productivity becomes particularly very low near the normal incident angle. Moreover, the increased cost for high density installation to prevent the optical loss also plays a negative impact on their economic viability. Tubular reactors may compensate for such limitations of the planar reactors. The circular surface itself has a light dilution effect in manner that increases the surface area by π/2 and reduces the Fresnel reflection loss by geometrically guiding the reflected light. Hence, biomass productivity of the horizontally installed tubular system can be higher than that for the planar system at some angles. For the diameter of 4 cm that is comparable to the optical propagation distance in dimension, the geometrical effect is relatively low and the performance is close to that for planar system. It is this reason that we determined the V-shaped configuration as the most efficient system among the examined candidates, at least in the optical point of view. In addition to this, the V-shaped system is distinctively advantageous in that implementation is easily done by simply placing plastic cover on top of an open-pond, while vertical and/or tubular bioreactors are inherently costly. More precise comparison of non-optical efficiencies such as shaking and aeration, possibly influenced by geometry, remains as a future work. Experimental demonstration Experimentally, we constructed a V-shaped physical bioreactor with θ v = 30°, as shown in Figs 5a and S7 . Under 0.60 sun and 12 h :12 h ( light:dark ) conditions, the growth profiles with different system depths are presented in Fig. 5b–d . Although the volume concentration is saturated more quickly in the shallow system than in the deep system, the total growth rate per given illumination area is shown to be almost similar, 52.0 g m −2 day −1 on average, which is 2.5 times higher than that of the flat bioreactor (20.7 g m −2 day −1 ). The PE was also improved from 1.40% to 3.52%, in accordance with the our modelling results of the system (Figs 2c and 3c ). The consistent productivity even with a small-volume V-shaped bioreactor can be attributed to the light-trapping effect, which makes it possible to compensate for the short optical path length of shallow depth. The final cell concentration tends to be higher for systems with small volumes, yielding a higher economic viability by reducing the cost for product drying, water supply, and nutrient preparation. The enhanced microalgal growth in a V-shaped bioreactor was consistently demonstrated in several repeated experiments with semi-continuous cultivation, varied environmental conditions, and a large-volume cultivation system as shown in SI (Fig. S5 ). Figure 5 Experimental demonstration of V-shaped microalgal cultivation. ( a ) Photograph and diagram of the V-shaped bioreactors used in the experiment. ( b , c ) Measured ( b ) volume and ( c ) area concentration of microalgal cells during growth in the flat and V-shaped systems with various depths. ( d ) Volume and area productivities of microalgal biomass in the V-shaped systems with various depths. The main purpose of this research indeed lies not in proposing a single outstanding scheme per se , though we believe ours is such a one indeed, but rather in applying a quantitative optical engineering approach to microalgae research, which has rarely been done in a systematic way. The V-shaped configuration is a mere example proposed through the optical study by means of comparing and integrating all types of previous attempts. Beyond the academic studies, real-world scale demonstration of the proposed scheme would necessarily be a future step for commercializing microalgae and contributing to recovering global carbon balance. The practical issues such as water circulation affected by V-shaped cover, off-gassing of generated oxygen, and lifetime of plastic components, which have not been deeply investigated here, could be raised for scaling up the schemes. Moreover, analysis of lipid contents of biomass, critical for biofuel extraction, as a function of light input and integration with genetic engineering would bring further benefits for the economic viability of microalgal biomass."
} | 9,089 |
35273183 | PMC8913661 | pmc | 6,620 | {
"abstract": "Electronic skins (e-skins) are devices that can respond to mechanical stimuli and enable robots to perceive their surroundings. A great challenge for existing e-skins is that they may easily fail under extreme mechanical conditions due to their multilayered architecture with mechanical mismatch and weak adhesion between the interlayers. Here we report a flexible pressure sensor with tough interfaces enabled by two strategies: quasi-homogeneous composition that ensures mechanical match of interlayers, and interlinked microconed interface that results in a high interfacial toughness of 390 J·m −2 . The tough interface endows the sensor with exceptional signal stability determined by performing 100,000 cycles of rubbing, and fixing the sensor on a car tread and driving 2.6 km on an asphalt road. The topological interlinks can be further extended to soft robot-sensor integration, enabling a seamless interface between the sensor and robot for highly stable sensing performance during manipulation tasks under complicated mechanical conditions.",
"introduction": "Introduction Robots, prosthetics, and other machines gain sensory functions when equipped with electronic skins (e-skins) or flexible pressure sensors 1 – 6 , which play the role of mechanoreceptors in human skin. Performances of such devices have been significantly improved by introducing new designs such as interfacial microstructures, or doping conductive fillers into the dielectric layer 7 – 15 . For example, the introduction of microstructures in flexible pressure sensors can improve both the sensitivity by enhancing the compressibility of the dielectric and the response speed of the device by rapidly restoring and releasing energy 13 – 17 ; and adding conductive fillers in dielectric can produce a higher and pressure-dependent dielectric constant and thereby improve signal magnitude 13 . A long-standing challenge for e-skins is their poor stability under harsh and complicated mechanical conditions because of the poor interfaces in the devices. Both the human skin and most e-skins possess multilayer structures; however, they exhibit significantly different levels of mechanical stability. The human skin consists of epidermis, dermis, and subcutaneous fat layers that grow together to have tough interfaces (Supplementary Fig. 1a ) 18 , 19 . Such firm interlocking between the layers allows the skin to survive during manipulation tasks that involve complex mechanical modes such as stretching, torsion, shear, and compression (Supplementary Fig. 1b ). By contrast, existing layered e-skins often consist of stacked functional layers (e.g., two electrodes sandwiching a soft dielectric layer) with non-bonded interfaces 16 , 20 , 21 . The mechanical stability of such an interface is further undermined when microstructures and air gaps are introduced to improve the sensitivity of the device 22 – 25 . Another important concern for the weak interfaces in e-skins is the mechanical mismatch between different layers. For example, Young’s moduli of different layers can vary up to five orders of magnitude 16 , 21 , 22 , 26 – 28 . As a result, delamination or separation of layers readily ensues under complex mechanical deformations, impairing to a large extent the performance of the e-skins and thus the sensory functions of the machine employing the e-skins. Although the integration of interlayers with homogenous composition or fully elastic components that exhibit close rigidity has been used to achieve minimized mechanical mismatch and improved stretchability 29 – 31 , microstructures and robust interface are not introduced, and thus desired sensing performance and interfacial stability cannot be achieved. Furthermore, integrating e-skins into soft robots or other machines inevitably introduces additional interfaces 32 , 33 . Such integration likewise suffers from poor interfacial adhesion and mechanical mismatch. It thus remains an urgent necessity to form robust interfaces between different layers for e-skins and for sensor-robot integration. Here we address the challenges by using a quasi-homogeneous composition for all interlayers and introducing interlinked and microstructured interfaces in a multilayered sensor. The quasi-homogeneous composition made by polydimethylsiloxane-carbon nanotubes (PDMS-CNTs) can avoid the mechanical mismatch between the layers, and the strong topological interlinks between different functional layers can lead to tough and strong interfaces. The sensors consist of a microconed electrode (7 wt% CNTs), a dielectric layer (2 wt% CNTs), and a flat electrode layer (7 wt% CNTs). The microstructured interface with topological interlinks has a high interfacial toughness of 390 J·m −2 enabled by two mechanisms: elastic dissipation and discrete rupture of the microstructures. The microcones can be significantly stretched to dissipate energy upon peeling, and the discrete rupture mode stabilizes the interface to prevent catastrophic crack propagation. The CNT doping in the dielectric layer together with the microstructures also boosts the signal intensity of the sensor by a factor of 33. The enhancement of the signal magnitude lies in a composition-structure synergistic effect: the conductive filler enlarges the dielectric constant of the composite upon loading, and the microstructure deformation changes the dielectric-electrode contact area. The tough and strong interface ensures high fidelity of the sensing signal under harsh mechanical conditions: the sensors exhibit adequate signal stability when subjected to repeated rubbing and shear test for at least 10,000 cycles, or when fixated to the tire tread of a running car driven 2.6 km on an asphalt road. The interlinks can also be applied to the soft robot-sensor interface, and we demonstrate the seamless integration of a soft robot and sensors, both made of PDMS-CNTs composites, for pressure and strain sensing during demanding gripping tasks without any interfacial failure or fatigue. The sensor can identify various stages during the gripping process via the decoupled bimodal signals of capacitance for pressure information. We expect this strategy to be extended to other material systems and other types of sensors for attaining robust interfaces and highly stable signals.",
"discussion": "Discussion Traditional e-skins designs have mainly focused on the improvement of sensing performance, while few efforts have taken robust interfaces into considerations. Challenges among interfaces stem either from the interlayer debonding/delamination in the sensors, or from the poor fixation of the sensors on robots. Additive manufacturing is expected to be promising for integrated e-skins and for sensor-soft robot integration achieved by multimaterial printing 50 ; but this technology is still in its infancy and is currently limited to strain sensors with simple device structures. Here we still used the traditional multilayered design for sensors and for sensor-soft robot integration, but simply applied a single-material system with tunable functions, together with the interlinking of the layers. Our design minimizes the mechanical mismatch and achieves strong adhesion between different layers in sensors, and between the sensors and a soft robot, while significantly boosting sensing performances. As expected, the tough and strong interfaces remarkably improve the signal fidelity of the sensor under extreme mechanical conditions. Although our strategy of using a single material-system and introducing interlinks between the layers can provide highly stable signal, the maximum sensitivity is relatively low, which might be due to the low conductivity of the electrodes 17 , 51 , 52 . This problem can possibly be addressed by using other highly conducting fillers such as Ag nanowires, or by using an ionic material to replace the dielectric layer that help form a supercapacitor at the interface. In summary, we have developed all-PDMS-CNTs-based sensors with topologically interlinked interfaces, integrated the sensors on soft robots, and demonstrated stable sensing performance under harsh mechanical conditions. By controlling the concentration of CNTs in PDMS, the function of the composite can be tuned to be a dielectric layer or an electrode, while both exhibit similar mechanical properties. The interlinked interface as well as the doping of CNTs in dielectric remarkably boosts the signal amplitude and sensitivity by tens of times. The interlinked interfaces have a high toughness of >390 J·m −2 , and a shear strength of >88 kPa. As such, the sensor exhibits negligible fatigue when subjected to repeated rubbing and shear test for at least 10,000 cycles, or when attached on a tire tread and run over 2.6 km. The high toughness and strength of the microstructured interfaces stem from the topological interlinks, the elastic dissipation caused by the microcones, and the discrete rupture mode of the cones. The interlinked interface and the all-PDMS-CNTs composition can also be extended to the integration of e-skins on soft robots, and we have shown that e-skins bonded on soft robot grippers exhibit high stability during manipulation tasks under harsh mechanical conditions. Our strategy opens a path for the fabrication of highly robust e-skins with improved sensitivity and response/relaxation speeds, as well as for the integration of sensors and soft robotics."
} | 2,347 |
40043200 | PMC11931477 | pmc | 6,621 | {
"abstract": "Developing scaffolds\nfor three-dimensional (3D) cell culture and\ntissue regeneration with biopolymers requires the creation of an optimal\nnanobiointerface. This interface must possess suitable surface chemistry,\nbiomechanical properties, and fibrillar morphology across nano- to\nmicroscale levels to support cell attachment and growth, enabling\na biomimetic arrangement. In this study, we developed a hydrogel scaffold\nmade from bacterial nanocellulose (BNC) functionalized with carboxylic\nacid groups (BNC–COOH) through a reactive deep eutectic solvent\n(DES), offering a sustainable approach. The surface properties and\nfibrillar structure of BNC–COOH facilitated the formation of\nhydrogels with significantly enhanced water uptake (1.4-fold) and\nadhesion force (2.3-fold) compared to BNC. These hydrogels also demonstrated\ntissue-like rheological properties in both water with G ′ exceeding G ″, suggesting predominantly\nelastic (solid-like) characteristics and viscosities in the range\nof 8–15 Pa·s. The BNC–COOH hydrogel scaffold demonstrated\nexcellent biocompatibility, supporting significant cell growth and\nanchorage for the 3D growth of mammalian cells and enhancing preadipocyte\ngrowth by up to 7.3 times. Furthermore, the BNC–COOH hydrogel\nfacilitates the maturation of 3T3-L1 preadipocytes into mature adipocytes,\ninducing typical morphology changes, such as decreased filopodia extensions,\nrounded cell shape, and lipid droplet accumulation without any additional\nchemical induction stimulus. Therefore, we demonstrated that a reactive\nDES composed of oxalic acid and choline chloride represents a mild\nreaction medium and a suitable approach for designing biocompatible\n3D hydrogel scaffolds with improved physicochemical properties and\nbiological activities for 3D cell culture.",
"conclusion": "Conclusion In this study, we developed a sustainable\nmethod\nto introduce carboxylic\nmoieties onto bacterial nanocellulose fibers, forming hydrogels through\na nonaqueous deep eutectic solvent. The resulting BNC–COOH\nhydrogel has a high concentration of carboxylic acid functional groups,\nenhancing swelling, viscosity, surface roughness, and adhesion. It\nalso demonstrates greater resistance to deformation, reduced water\nloss, and improved thermal stability compared to native BNC. This\nhydrogel demonstrated biocompatibility with preadipocyte 3T3-L1 cells\nand exhibited exceptional capability in promoting cell growth. Our\nfindings indicate that the biomimetic micronano features on BNC–COOH\nare significantly more effective than those found in native BNC environments,\nproviding an optimal bionanointerface for cell anchorage. As a result,\nthe BNC–COOH hydrogel promotes outstanding cell growth. It\nmediates the maturation of preadipocytes into mature adipocytes, as\nevidenced by a decrease in extended filopodia and a rounded cell morphology,\nalong with increased content of intracellular lipid droplets after\n40 days of culture, as demonstrated by confocal microscopy images.\nThe maturation of 3T3-L1 cells was facilitated by carboxylic acid\nfunctional groups, and the 3D structure was provided by the bacterial\nnanofibers in the hydrogel. This microenvironment promotes cell growth,\nallowing cells to interact in 3D arrangements, which enhances cellular\ncommunication. Thus, we demonstrated that a reactive DES based on\noxalic acid and choline chloride serves as an effective method for\ncreating biocompatible 3D hydrogel scaffolds with enhanced physicochemical\ncharacteristics and improved biological functionality for 3D cell\nculture applications.",
"introduction": "Introduction Bacterial nanocellulose (BNC) is being\nrecognized as a highly promising\nand versatile biobased material that has found diverse applications\nin areas like energy, environment, food and pharmaceutical sciences,\nand biomedicine, among others. Currently, BNC applications in biomedicine\nand hydrogel design have garnered significant attention due to their\nintrinsic attributes, which include 1 excellent\nmechanical properties and biodegradability. 2 Arranged as a tridimensional network of nanofibrils, BNC exhibits\nhigh porosity, shareability, and tissue-like properties, potentially\nimpacting the development of blood-contacting biomedical materials,\nsuch as artificial vascular grafts 3 , 4 and drug delivery\nsystems. 5 Compared with other methods\nfor extracting fibers and fibrils from\nlignocellulosic biomass, the production process for BNC is considerably\nmore straightforward. BNC typically exhibits higher crystallinity,\nwith nanofibril diameters ranging from 20 to 80 nm. 6 A significant advantage of BNC is its high purity when\nobtained by biotechnological approaches that involve acetic acid bacteria,\nas it does not contain lignin or hemicellulose, unlike plant-based\nnanocellulose. This makes BNC particularly well-suited for designing\n3D scaffolds. 6 , 7 BNC consists of d -glucose\nmonomeric units linked by glycosidic bonds to form chains arranged\nin fibrils. The abundance of hydroxyl groups in the chemical structure\nof BNC enables its cross-linking and functionalization with various\npeptides, proteins, polysaccharides, and functional groups, improving\nits chemical and physical properties. 4 Furthermore,\nBNC bundles feature networks that resemble the extracellular matrix\n(ECM) and possess mechanical properties comparable to collagen found\nin native tissue ECM. 1 The 3T3-L1\nmouse fibroblast cell line is one of the most clearly\ndefined in vitro cell culture models for adipocytes,\nundergoing a transformation from preadipocytes into adipocyte-like\ncells under specific conditions typically induced by a hormonal cocktail. 8 This model is crucial for studying adipocyte\nbiology and plays a pivotal role in advancing our understanding of\nadipogenesis, lipid metabolism, and the effects of hormones and xenobiotics\nin adipose tissue. 9 Initial exposure of\n3T3-L1 cells to differentiation media triggers the upregulation of\nadipogenic genes, leading to increased glucose uptake and triglyceride\nsynthesis. 8 , 10 It has been documented that 3T3-L1 cells\nshow clear signs of lipid accumulation after the initial exposure\nto the differentiation medium, and this process may vary between 4\nand 7 days. 11 The 3T3-L1 cells, derived\nfrom Swiss 3T3 cells and initially identified\nby Green et al., 12 have been chosen for\ntheir capability to accumulate lipids, a key feature for studying\nadipocyte function. Maturing these preadipocyte cells into full adipocytes\nrequires various agents that promote differentiation. 13 It has been documented that these cells exhibit a lipid\nprofile characterized by the accumulation of odd-chain-length unbranched\nfatty acids across all major lipid categories, a process that can\nbe attributed to the α-oxidation of fatty acids in peroxisomes.\nAs these preadipocytes differentiate into adipocytes, there is a notable\nincrease in the concentration of these odd-chain fatty acids. 14 Several investigations have proposed different\nBNC-based platforms\nfor cell culture. For instance, Osorio et al. 15 evaluated the short- and long-term in vivo implantation\nresponses of 3D and two-dimensional (2D) porous BNC biomaterials,\nas well as their ex vivo hemocompatibility, including\nhemolysis and clotting time. They found that biomaterials with porosities\nof around 60 μm promoted superior fibrotic tissue distribution,\nhigh cell migration, and excellent collagen and elastin deposition\nwithin the BNC hydrogel. Additionally, Vielreicher et al. 16 studied the efficiency and quality of collagen-I\nformation, considering factors such as cell type, medium composition\n(serum, ascorbic acid), and differences in cell architecture between\n2D and 3D cultures. However, most studies have mainly focused on collagen\nproduction and have not explored the effect of surface functionalization\nof BNCs to enhance cell anchorage and biocompatibility. 7 Deep eutectic solvents (DESs) are an emerging\nclass of designer\nsolvents that have garnered significant attention for their effectiveness\nin processing and valorizing lignocellulosic materials under sustainable\nprotocols 18 , 19 DESs are composed of mixtures of hydrogen\nbond donors (HBDs) and hydrogen bond acceptors (HBAs), which exhibit\nenthalpy-driven negative deviations from thermodynamic ideality. In\ncontrast, the melting point depression observed in eutectic solvents\nresults from ideal liquid-phase behavior. 20 A typical HBA is the quaternary ammonium salt choline chloride (ChCl),\nwhile common HBDs encompass a wide range of compounds, including carboxylic\nacids, polyols, and amides. 21 Notably,\nthe combination of ChCl and oxalic acid (OA) is widely acknowledged\nas a DES, recognized for its good biodegradability, accessibility,\nand low toxicity. 22 These properties make\nit particularly suitable for extracting and valorizing nanocellulose\nand designing materials for biological applications. 19 This study aimed to design a carboxylated BNC hydrogel\n(BNC–COOH)\nfor 3D cell culture, using a nonaqueous and sustainable approach at\n60 °C of functionalization temperature. To this end, a DES composed\nof oxalic acid and choline chloride was employed as a reactive solvent\nfor BNC treatment, which introduced carboxylic acid moieties onto\nthe BNC surface to enhance cell anchorage and overall biocompatibility.\nThe mixture of ChCl and OA offers a sustainable process compared with\nconventional methods that rely on harsh chemicals like TEMPO or strong\nacids. Moreover, cellulose produced by bacterial genera such as Gluconacetobacter is inherently of high purity, eliminating\nthe need for lignin and hemicellulose removal, a step typically required\nfor plant-derived cellulose. 23 The\nBNC–COOH hydrogel (ca. 0.1 wt % BNC–COOH) produced\nin this study was employed as a 3D scaffold for fibroblast cells (3T3-L1).\nWe found that BNC–COOH scaffolds enhanced cell proliferation\nand induced reactive oxygen species (ROS) production due to higher\ncellular metabolic activity. Moreover, the 3D architectural arrangement\nof cells within the BNC–COOH hydrogel scaffold promotes the\ndifferentiation of preadipocyte fibroblast cells into adipocytes (3T3-L1)\nwithout external chemical stimuli at 40 days. This highlights the\nkey role of surface chemistry in cellulosic forming 3D hydrogels,\nwhich can direct the fate of the cell cultured on it. More sustainable\nbiomaterials preparation also represents a step forward in developing\nBNC hydrogels with prospective applications in tissue engineering\nand wound healing.",
"discussion": "Results and Discussion Morphological and Structure\nCharacterization of Functionalized\nBacterial Nanocellulose DESs offer an environmentally friendly\nalternative to traditional and harsh solvents for the chemical modification\nof cellulose. In this study, we extended the results on non-lignocellulosic\nmaterials valorization, where oxalic acid and choline chloride-based\nDES served as an effective reaction medium for the esterification\nof bacterial nanocellulose fibers’ surface. 18 , 24 To explore the optimal time that yielded the maximum carboxylic\nacid content in BNC, the treatment was carried out at different times,\nat a fixed BNC/DES mass ratio of 1:5. 25 Figure 1 A shows the\ncharacteristic bands of BNC recorded by ATR - FTIR\nafter extensively washing out the DES and subsequent drying. The typical\nband due to −OH stretching is found at 3345 cm –1 , while the asymmetrical CH 2 stretching is visible at\n2899 cm –1 . Also, the band at 1054 cm –1 resulted from the combination of CH 2 deformation and\nC–O–C and C–OH stretching. The band at 1646 cm –1 is attributed to the −OH bending of residual\nwater in the BNC. 26 − 28 Figure 1 A shows significant differences in the spectrum of the resulting\nBNC after the DES treatment. For instance, the bands at 1644 and 1737\ncm –1 emerged and intensified as the functionalization\ntime increased from 1 to 3 h. These bands correspond to the −C=O\nand −COOH groups stretching, 18 , 24 respectively. Figure 1 ATR-FTIR\nspectra of BNC and functionalized BNC–COOH scaffolds\nare obtained by DES esterification. The reaction was carried out for\n1, 2, and 3 h to determine an appropriate functionalization time for\nthe preparation of the scaffold. (A) ATR-FTIR spectra of functionalization\nof BNC by oxalic acid and choline chloride-based DES at different\ntimes. (B) Correlation of –COOH group concentration with the\narea under the curve (AUC) for the bands at 1644 and 1737 cm –1 . As a first approach to quantify\nthe degree of functionalization,\nthe area under the curve of the bands at 1644 and 1737 cm –1 in BNC–COOH at different times was correlated with carboxylic\nacid moieties’ abundance. The intensity of carbonyl bands increases\nwith longer functionalization times, confirming the modification of\nthe BNC fibrils, likely occurring at the C-6 in the pyranose ring\nof cellulose using oxalic acid and choline chloride-based DES. 29 , 30 The optimal concentration of −COOH groups was achieved after\nfunctionalization for 3 h, as indicated by the correlation of the\narea under the curve of carboxyl bands ( Figure 1 B). Extended functionalization times resulted\nin fragile BNC hydrogels, unsuitable as scaffolds for cell culture\n( Figures S1 and S2 and Movie S1 ). The morphological analysis of the nanofibrils\nis presented in Figure 2 , which shows the\nlength and diameter histograms of BNC and BNC–COOH obtained\nby SEM analysis processed with ImageJ. The morphology ( Figure 2 A and D) and nanofibril size\n( Figure 2 B and E) of\nthe native BNC and carboxylated BNC remain unchanged following the\nfunctionalization with carboxylic acids using oxalic acid and choline\nchloride-based DES. There is no evidence of fibrils’ rupture,\nthus confirming that the functionalization occurred on the BNC surface. 7 Figure 2 Morphology, size, and crystallinity of native BNC and\nBNC–COOH.\n(A and D) HR-SEM micrography of BNC and BNC–COOH, respectively\n(scale bar = 2 μm). (B and E) The fiber diameter of BNC and\nBNC–COOH was calculated using ImageJ software. (C and F) XRD\npattern and crystallinity index (CI %) calculated of BNC and BNC–COOH. BNC is a biopolymer characterized by higher crystallinity\ncompared\nto wood-based and plant-based cellulose. 31 Unlike plant-derived cellulose, BNC is not associated with other\npolymers, such as lignin and hemicellulose, due to its unique biosynthetic\nprocess. 32 BNC is classified as a subpolymorph\nof Iα cellulose, 31 featuring a triclinic\nunit cell, which is characteristic of most algal and bacterial cellulose. 33 The crystallinity in the structure of BNC confers\nattractive physicochemical properties, such as density, Young’s\nmodulus, and tensile strength, which are analogous to those of collagenous\nfibers in bone tissue and extracellular matrix. Crystallinity is a\nkey aspect involved in promoting cell adhesion, cell proliferation,\nand differentiation in nanocellulosic biomaterials. 17 , 32 The X-ray diffraction (XRD) analysis of both native and functionalized\nnanocellulose assessed the changes in the crystalline structure of\nBNC resulting from the DES treatment. The XRD pattern showed a crystallinity\nindex (CI %) of 99.6 for native BNC and 99.0 for the functionalized\nBNC–COOH, calculated by the Segal method 34 ( Figure 2 C and F). These results suggest that functionalization occurred on\nthe BNC surface, likely on the crystalline plane (001) due to the\nintroduction of carboxylic acids at the C-6 position of the cellulose\nring, as discussed above. Surface functionalization is critical for\nmaintaining the BNC fibrils’ features while enhancing the bionanointerface\nwith cells. Surface functionalization of BNC using the complete ChCl-OA-based\nreactive DES enhanced its surface chemistry while preserving its key\nmechanical and morphological properties. 35 The hydrophilicity of BNC can be enhanced by introducing polar\nand ionizable groups, such as carboxylic acids, 32 through the incorporation of multiple water molecules,\nimproving its dispersibility in water, facilitating water uptake and\nhydrogel formation. Therefore, the surface carboxylation of BNC significantly\ninfluences the water absorption capacity of the hydrogel-forming fibrils,\nmaking it highly suitable for 3D cell culture applications. Not only\nhas surface chemistry been reported to affect cell adhesion and differentiation, 17 but also wettability, surface rugosity, and\nsurface energy play important roles. To gain deeper insights\ninto the surface energy modification of\nBNC following functionalization with carboxylic acids, surface morphology,\nand stress–strain ( F –δ) curves\nwere obtained by using AFM ( Figure 3 ). The surface morphology of BNC displays more fibril\nagglomeration and compaction than BNC–COOH, with a root-mean-square\n(RMS) roughness of 30 ± 0.13 nm for BNC and 34 ± 0.24 nm\nfor BNC–COOH ( Figure 3 A and B). The surface morphology for native BNC without chemical\nmodification is similar to that observed by Jabbour et al. 7 AFM height profiles revealed that BNC–COOH\nshows a high surface roughness ( Figure 3 C), which is induced by surface chemical functionalization.\nThe effect of COOH on the BNC was further evaluated through the adhesion\nforce ( F adh ) determined from the F –δ curves ( Figure 3 D). The adhesion value by AFM has been used\nto determine the number of significant adhesion force events by the\ncells or the substrate and the forces required to break each adhesion\nbond. 36 The F adh ratio for BNC–COOH to BNC was 2.34, indicating a higher force\nto detach the probe from the BNC–COOH surface. To understand\nthe increase in F adh , it is necessary\nto consider that the SiO x covering the\nAFM probe tip contains ∼5 −OH nm –2 terminations at ambient conditions. 37 These groups can form water monolayers, even at low relative humidity\nlevels. Thus, the F adh encloses information\nfrom the tip–sample interaction, which is governed by Van der\nWaals and capillary forces resulting from water condensation. This\nresult is a hydrophilic interaction between the AFM tip and BNC–COOH\ndue to the presence of hydroxyl groups. Thus, the enhanced physical\nand chemical properties measured by the F adh , along with the surface morphology, contribute to the BNC–COOH\nfunctioning as a scaffold for cell proliferation, as will be demonstrated\nin the following sections. 17 , 38 Figure 3 AFM surface morphology\nand force adhesion of native BNC and BNC–COOH.\n(A and B) Morphology of native BNC and BNC–COOH, respectively.\n(C) Horizontal profiles were obtained in the middle of the morphology\nimages. (D) Quantitative distribution of adhesion force data measured\nbetween the AFM-tip and the surface of dried BNC and BNC–COOH;\ninset shows the F –δ curves. Water Uptake of BNC and BNC–COOH Water uptake\nis a crucial characteristic of cellulosic materials, as it reflects\ntheir surface properties and determines their ability to form hydrogels.\nHerein, after thoroughly washing out the DES used to functionalize\nthe BNC, the dry BNC and BNC–COOH were used for further studies. Figure 4 A illustrates the\nwater uptake capacities of BNC and BNC–COOH when in contact\nwith water to form hydrogels at equilibrium. It was found that the\nBNC hydrogels exhibited significant swelling within just 1 h of immersion\nin an excess of water, after which there was a negligible increase\nin water absorption with additional immersion time. At equilibrium,\nthe BNC hydrogels absorbed a maximum of 7,917 ± 242% water, while\nthe BNC–COOH hydrogels demonstrated a significantly higher\nwater uptake of 11,180 ± 353% after functionalization ( p < 0.001). Additionally, the hydrogels exhibited good\noptical transparency and excellent water absorption capabilities ( Figure 4 A). These conditions\nare optimal for cell culture and confocal microscopy analysis. 39 Regarding these findings, Smyth et al. 40 reported the impact of hydration of cellulose\nnanofibril (CNF) thin films on stem cell culture. They reported a\nmaximum water uptake percentage of 13% for the CNF materials. Similarly,\nYang et al. 41 reported a swelling ratio\nof 5.5% for a BNC hydrogel with dimensions of 2 × 2 cm, demonstrating\nthe importance of surface functionalization of cellulose nanofiber\nwith hydrophilic groups. Figure 4 (A) Water uptake of BNC, BNC–COOH, and\nBNC–COOH with\nDMEM 10% CALF hydrogels and viscoelastic properties at 25 °C\nand the images of BNC–COOH hydrogels with deionized water.\n(B) Strain sweep, (C) frequency sweep tests ( G ′,\nrepresented by solid symbols; G ″, by open\nsymbols, plotted against frequency); (D) complex viscosity test (η*),\n(E) temperature sweep. (F) Thermal properties of BNC of BNC–COOH\nhydrogels. All tests were conducted in triplicate. In this research, the water in the BNC–COOH\nhydrogel\nwas\nreplaced with Dulbecco’s Modification of Eagle’s Medium\n(DMEM) culture media containing 10% calf serum, while maintaining\nthe maximum swelling (11,019 ± 164%) observed in the BNC–COOH.\nSimilarly, Rasheed et al. 42 reported that\nnanocellulose fiber scaffolds retained their structure in DMEM cell\nculture media, with maximum swelling achieved after 24 h of immersion.\nAdditionally, cell culture media contain ions, amino acids, and various\nproteins necessary for cell growth, which can enhance swelling and\nsupport the hydrogel structure. Moreover, the ions in cell culture\nmedia may contribute to the hydrogel formation through ionic cross-linking.\nFor instance, Curvello and Garnier 43 designed\na nanocellulose hydrogel and demonstrated that cationic cross-linking\nsupports cell adhesion and intestinal organoid formation. Gao et al. 44 found that DMEM cell culture significantly increased\nthe swelling of a hydrogel based on the self-cross-linking of phenylboronic\nand hyaluronic acid. Basic amino acids also stabilize the hydrogel,\nas they carry a positive charge under physiological conditions (pH\n7.4). Furthermore, Li et al. 45 stated that\nDMEM contains a variety of ions that can promote potential intermolecular\ninteractions, enhancing mechanical resistance. Considering the\nabove results, to further study the feasibility\nand properties of BNC–COOH hydrogels for cell culture, hydrogels\ncomposed of 0.1 wt % of both BNC and BNC–COOH were employed,\nwhich are within the range of stable hydrogels found in the swelling\ntest ( Figure 4 A), i.e. , hydrogels that retained a stable physical form without\nleaking solvent at room temperature for 4 h. Rheological Properties\nof the Hydrogels Hydrogels were\ncharacterized mechanically in the linear viscoelastic region (LVR).\nThe LVR is defined as the deformation range where the elastic and\nloss moduli ( G ′ and G ″,\nrespectively) are independent of deformation (γ%). After a critical\ndeformation (γ%), G ′ and G ″ exhibit a sharp change in their slope, diminishing as a\nfunction of the deformation, which is indicative of the breakdown\nof the hydrogel microstructure. To measure the LVR for hydrogel samples,\nstrain sweeps were performed from 0.01 to 100% at a constant frequency\n( f ) of 1 Hz and a temperature of 25 °C. Figure 4 B shows G ′ and G ″ as a function of deformation\nfor BNC and BNC–COOH hydrogels. Results indicate that both\nhydrogels depict a similar trend with LVR values γ% ≤\n0.2. Figure 4 C shows G ′ and G ″\nas a function of the frequency sweep experiments for BNC and BNC–COOH\nsamples. The applied strain for two hydrogels was 0.05%, which is\nwithin the linear viscoelastic region and at a temperature of 25 °C.\nThe elastic and viscous moduli for both hydrogels slightly augment\nwith increasing frequency, but they are overall relatively constant.\nSuch rheological behavior indicates the presence of permanent junction\npoints as opposed to transient entanglements, leading to a viscoelastic\nplateau. 46 The value of G ′ for the BNC–COOH sample is higher than that for BNC.\nThis may be attributed to the formation of denser internanofiber interactions\nat higher frequencies related to the surface carboxyl moieties in\nBNC–COOH. 47 Besides, the elastic\nmodulus is consistently larger than the loss modulus ( G ″), indicating that the hydrogels behave as gel-like over\nthe frequency range studied. On the other hand, the relative relationship\ntan δ = G ″/ G ′\n(dissipation capacity) is similar for both samples, with tan δ\n= 0.17. Figure 4 D illustrates\nthe relationship between the modulus of the complex viscosity (η*)\nand the angular frequency for the samples. The complex viscosity for\nBNC and BNC–COOH diminishes as frequency increases, as described\nabove, and the BNC–COOH sample shows the highest viscosity,\nwhile the BNC sample is two times less viscous. The BNC–COOH\nincreased viscosity is attributed to the formation of hydrogen bonds\nresulting from the surface functionalization with carboxylic acids. 48 Finally, Figure 4 E shows the temperature dependence of G ′\nand G ″ for BNC hydrogels at a frequency of\n1 Hz. The temperature was increased from 25 to 100 °C at a heating\nrate of 5 °C min –1 . The storage modulus ( G ′), representing the solid component of the rheological\nbehavior, remains constant up to 70 °C for BNC and 77 °C\nfor BNC–COOH, after which it declined for both materials. This\neffect is more pronounced in BNC hydrogels than in BNC–COOH\nhydrogels, demonstrating greater resistance to temperature and water\nloss. These results indicate that the structure of the BNC–COOH\nis physically more stable at higher temperatures compared to previously\nreported nanocellulose hydrogels, which exhibited limited stability\nabove 65 °C. 47 This increased stability\nis attributed to the enhanced interactions among the individual functionalized\nnanofibers. Thermal Properties of BNC and BNC–COOH The thermal\nproperties of BNC and BNC–COOH were assessed through thermogravimetric\nanalysis (TGA) to corroborate the increase in the number of carboxylic\nacid groups after esterification. The sample’s thermal degradation\nbehaviors can be divided into two processes for BNC ( Figure 4 F). The initial mass loss occurs\nin the 30–150 °C range, corresponding to the evaporation\nof residual and unbound water in the BNC. Significant differences\nin the thermal degradation of the two samples (BNC and BNC–COOH)\nwere observed during this weight-loss stage. For BNC, the pyrolysis\nstarted between 300 and 360 °C, with the thermal decomposition\nof shorter chains and amorphous cellulose. 49 During this process, the glycosidic linkages in cellulose were cleaved,\nproducing H 2 O, CO 2 , alkanes, and other hydrocarbon\nderivatives, which contributed to the rapid drop in the TGA curves 50 and resulted in a weight loss of 78%. These\nfindings are consistent with previous reports. 35 , 51 In contrast, the pyrolysis of the BNC–COOH sample continued\nin the range of 200–300 °C, resulting in a 56% weight\nloss, primarily associated with the pyrolysis of cellulosic materials.\nThe weight loss of 17% in BNC–COOH in the range of 300–400\n°C corresponds to the decomposition of hydroxyl and carboxylic\nacid groups. 52 After 400 °C, the cellulose\nthermal degradation was nearly completed, leading to the carbonization\nstage. The final residue of BNC at 700 °C was 22%, while that\nof BNC–COOH remained relatively lower, 18% of the initial mass. Collectively, the composition and morphological and physicochemical\nproperties of the functionalized BNC demonstrate the formation of\nstable hydrogels that can be explored to sustain their use as scaffolds\nfor cell culture ( Movies S2 and S3 ). Besides examining the chemical and physical\nstructural aspects of BNC, this study focused on how mammalian cells\ninteract with the material. Mouse fibroblast cells (3T3-L1) were chosen\nfor their ability to grow in a 3D cell culture, making them particularly\nrelevant for research on materials intended for tissue engineering\napplications. 53 , 54 Preadipocytes (3T3-L1) were cultivated\non BNC and BNC–COOH to assess the biomaterial’s capacity\nto support cell attachment, anchoring, growth, and differentiation. Biocompatibility of Hydrogels Hydrogels are the most\nwidely used 3D matrices for cell culture due to their high biocompatibility\nand fluid-retaining structure. 55 In this\nstudy, we assessed the biocompatibility of BNC and BNC–COOH\nhydrogels for culturing 3T3-L1 fibroblast cells in a 3D arrangement.\nAs shown in Figure 5 A, the BNC hydrogel exhibited low biocompatibility, resulting in\nlimited growth of 3T3-L1 cells over 7, 14, and 21 days. The growth\nof fibroblast 3T3-L1 in a 2D arrangement on a polystyrene Petri dish\nreached\na maximum cell count of 201,079 ± 8,423 cells at 21 days. Beyond\nthis time, saturation of the Petri dish impeded further cell growth,\nunderscoring that 2D platforms are unsuitable as long-term platforms.\nHowever, after 21 days, approximately 38,390 ± 7,316 3T3-L1 fibroblasts\nwere found on the BNC scaffold, whereas around 200,778 ± 1,863\ncells were present on the BNC–COOH hydrogel scaffold. This\nresult indicates that the cell growth on the BNC–COOH scaffold\nwas significantly enhanced, being 7.3 times higher than that on the\nBNC hydrogel. Given the improved cell growth on the BNC–COOH\nhydrogel scaffold, we extended the observation period to 40 days.\nIn this regard, it has been reported that BNC scaffolds effectively\nsupport cell ingrowth and facilitate subsequent cartilage remodeling\nin joints, where BNC hydrogel underwent 3D laser perforation before\ncell culture. 56 Figure 5 Biocompatibility of BNC\nand BNC–COOH hydrogels. (A) Cell\nviability of 3T3-L1 fibroblasts in BNC and BNC–COOH hydrogels\nover 7, 14, and 21 days. (B) Confocal microscopy micrographs of the\n3T3-L1 cells cultured in BNC and BNC–COOH hydrogels at 21 days\n(scale bars represent 40 μm). Cells were stained with resorufin\n(pink color), while bacterial nanofibers were stained with calcofluor\n(blue color). (C) Mean fluorescence intensity of the DCFDA (shown\nin green in D) for quantifying ROS production in cells grown in hydrogels.\n(D) ROS production in 3T3-L1 cells at 21 days. Cells are green in\ncolor due to the fluorescence of DCFDA, and the bacterial nanofibers\nare blue due to the staining with calcofluor (scale bars represent\n20 μm). The bars represent the mean ± standard deviation.\nStatistical significance is as follows: * p < 0.05;\n** p < 0.01; *** p < 0.001. However, upon measuring the number of cells on\nthe scaffolds at\n40 days, we found that the counts were significantly lower in both\ncases compared to measurements taken on day 21. Resazurin perfusion\nwithin the scaffold was likely hindered due to the high cell density,\nas observed in the confocal microscopy micrographs, a phenomenon previously\nreported. 57 , 58 Consequently, we analyzed cell growth using\nconfocal microscopy, as shown in Figure 5 B. The confocal microscopy images in Figure 5 B reveal a significantly\nhigher cell density in the BNC–COOH hydrogel compared with\nthe BNC hydrogel. Additionally, it is possible to observe the long\nand thin filopodia of 3T3-L1 cells, which facilitate anchoring to\nhydrogel nanofibrils, as indicated by the white arrows in Figure 5 B (BNC–COOH).\nThe −COOH functional groups on the BNC scaffold enhance the\nadhesion capacity of 3T3-L1 cells observed in the BNC–COOH\nhydrogel. These results are consistent with findings from mesenchymal\nstem cells cultured on BNC hydrogels, where optimal attachment is\nevident through their distinctive filopodia extensions. 16 Reactive oxygen species (ROS) are byproducts\nof cellular respiration\nand serve as quantifiable parameters related to cell proliferation.\nIn Figure 5 C, ROS production\nat day 21 days of culture is represented as the mean fluorescence\nof DCFDA obtained from the confocal micrographs of 3T3-L1 cells ( Figure 5 D). Fibroblast cells\ncultured in BNC–COOH exhibit higher ROS production compared\nto those in BNC, which display moderate ROS levels. This increased\nROS production is consistent with the increase in the 3T3-L1 cell\nnumber observed after 21 days of growth in the BNC–COOH hydrogel.\nTherefore, moderate ROS production correlates with the proliferation\nof 3T3-L1 cells cultured in the BNC–COOH hydrogel. This proliferation\nmay represent an adaptive response to hypoxia, during which cells\nactivate their antioxidant systems, including antioxidant enzymes\nsuch as superoxide dismutase, catalase, and glutathione-dependent\nmechanisms. 58 These systems help mitigate\nthe toxic effects of elevated ROS levels, enhancing proliferative\ncapacity. 59 Furthermore, it has been reported\nthat the cell cycle is coupled to ROS production oscillations. 60 As shown above, BNC–COOH enhanced\ncellular proliferation\nin a time-dependent manner, proving to be a suitable 3D scaffold.\nThus, as an additional property of the arrangement of the nanocellulose\nfibers, it was interesting to assess whether the 3D architecture of\nthe cells would induce their maturation. In this sense, 3T3-L1 cells\nare an excellent model to test preadipocyte maturation, with a fibroblast-like\nmorphology to mature adipocytes characterized by lipid deposition\nin intracellular droplets. The results presented in Figure 6 A,B indicate that\nthe 3D structure formed by BNC–COOH\nand the supportive hydrogel environment contribute to the differentiation\nof preadipocytes into mature adipose cells at 21 days. Additionally,\nthere is a significant increase of 2.2-fold in lipid droplet production\nin the 3T3-L1 cells at 40 days ( Figure 6 C), accompanied by shortened filopodia and more rounded\nmorphology. Similar findings have been reported in Matrigel with DMEM,\nindicating that the maturation of 3T3-L1 cells can take between 2\nand 5 weeks. 61 During the differentiation\nprocess, 3T3-L1 cells not only change into a more spherical morphology\nbut also begin to accumulate lipids and express specific markers of\nfat differentiation 62 ( Figure S3 ). A key morphological characteristic indicative\nof differentiation is the presence of lipid droplets, which can be\nstained with various fluorophores, such as Nile red. Furthermore,\nit has been shown that 3D cell culture promotes adipogenesis similar\nto that observed in an ex vivo model. 63 In this work, adipogenesis is primarily attributed\nto the carboxyl functional groups on bacterial fibrils and the stiffness\nof the hydrogel formed. Similarly, Rasha et al. 17 reported that an increase in hydroxyl groups on the surface\nof CNF samples promotes osteogenic differentiation and enhances the\nbiological performance of scaffolds for bone tissue regeneration.\nThese findings correlate with the surface characteristics of BNC–COOH,\nwhich has a high content of hydroxyl and carboxyl functional groups\nin its chemical structure, supporting cell proliferation. 38 Additionally, Malandain et al. 1 designed a hydrogel composed of collagen type I and bacterial\nnanocellulose fibers, resulting in a 43% increase in hydrogel stiffness\ndue to the combination of these natural polymers. Figure 6 Differentiation of 3T3-L1\ncells cultured in the BNC–COOH\nhydrogel. Confocal microscopy images of 3T3-L1 cells (red color) stained\nwith Nile red, along with bacterial nanofibers (blue color) stained\nwith white of calcofluor at (A) 21 and (B) 40 days of culture. (C)\nLipid deposition in intracellular droplets measured by mean fluorescence\nintensity from confocal micrographs. Scale bars represent 10 μm.\nThe intense red spots correspond to lipid droplets, which indicate\ncell maturation. Furthermore, studies\nhave reported that culturing 3T3-L1 cells\nin 3D environments, such as hydrogels and spheroids, promotes adipogenesis,\naccompanied by an increased expression of mitochondrial genes, and\nkey metabolic phenotypes associated with adipocyte maturation. This\ncontrasts with preadipocytes grown in a 2D monolayer. 64 Consistent with these findings, our results demonstrate\nthat the 3T3-L1 cells proliferated and matured within the 3D structure\nprovided by the BNC–COOH hydrogel. 65 Its physicochemical and rheological properties support enhanced\ncell proliferation, while the nanofibers within the hydrogel facilitate\ncell anchorage. Additionally, the chemical composition of bacterial\nnanocellulose and its 3D arrangement promote cell maturation, making\ncarboxylated BNC scaffolds an effective platform for 3D cell culture."
} | 9,034 |
35508355 | PMC9121345 | pmc | 6,622 | {
"abstract": "Biocatalysis in flow\nreactor systems is of increasing importance\nfor the transformation of the chemical industry. However, the necessary\nimmobilization of biocatalysts remains a challenge. We here demonstrate\nthat biogenic magnetic nanoparticles, so-called magnetosomes, represent\nan attractive alternative for the development of nanoscale particle\nformulations to enable high and stable conversion rates in biocatalytic\nflow processes. In addition to their intriguing material characteristics,\nsuch as high crystallinity, stable magnetic moments, and narrow particle\nsize distribution, magnetosomes offer the unbeatable advantage over\nchemically synthesized nanoparticles that foreign protein “cargo”\ncan be immobilized on the enveloping membrane via genetic engineering\nand thus, stably presented on the particle surface. To exploit these\nadvantages, we develop a modular connector system in which abundant\nmagnetosome membrane anchors are genetically fused with SpyCatcher\ncoupling groups, allowing efficient covalent coupling with complementary\nSpyTag-functionalized proteins. The versatility of this approach is\ndemonstrated by immobilizing a dimeric phenolic acid decarboxylase\nto SpyCatcher magnetosomes. The functionalized magnetosomes outperform\nsimilarly functionalized commercial particles by exhibiting stable\nsubstrate conversion during a 60 h period, with an average space–time\nyield of 49.2 mmol L –1 h –1 . Overall,\nour results demonstrate that SpyCatcher magnetosomes significantly\nexpand the genetic toolbox for particle surface functionalization\nand increase their application potential as nano-biocatalysts.",
"conclusion": "Conclusion Magnetosomes are a biologically produced alternative to existing\ncommercial, magnetic beads for the immobilization of target proteins,\nsuch as biocatalysts. Genetic engineering provides a highly selective\nand reliable tool for the (multi)functionalization of the magnetosome\nsurface; 29 , 31 , 65 however, its\ntime-demanding nature (i.e., the generation of strains producing functionalized\nmagnetosomes) lowers the throughput, and generated particles are predetermined\nto distinct functionalities. Widely used in vitro approaches such as cross-linking reactions allow for a much more\nrapid functionalization of the particle surface but lack specificity\nand controllability. 30 In our study, we\ncombined the advantages of both in vivo and in vitro functionalization by magnetosome expression of\na covalent MamC–SpyCatcher bioconjugate and subsequent coupling\nof SpyTagged protein cargo. While there are many synthetic strategies\navailable for interconnecting two protein compounds, including split\ninteins, 76 coiled coils, 77 and split proteins, 78 the ST–SC\nsystem provides a strong and irreversible interaction by spontaneous\nreconstitution of an intramolecular isopeptide bond. 43 Immobilization of ST-equipped PAD monomers on the\nSC-magnetosome\nsurface resulted in catalytically highly active nanoparticles that\ncould be applied as nano-biocatalyst in a flow reactor system. Compared\nto likewise functionalized commercial Dynabeads, magnetosomes exhibited\nmore stable conversion rates and an overall increased activity, which\nmight be explained by the smaller magnetosome diameter. Thus, a significantly\nhigher number of functional moieties can be immobilized on the same\namount of carrier material, making magnetosomes well-suited for flow\ncatalysis. The simultaneous fusion of the SC bioconjugate to several\ndifferent magnetosome proteins could further enhance the SC protein\ndensity on the particle surface. In addition, the simultaneous fusion\nof SC moieties to the N- and C-termini of the respective membrane\nanchors, or even as arrays, 37 might drastically\nincrease the binding capacity of the particles, thereby turning the\nmagnetosome membrane into a more flexible multimodal binding platform\nfor functional moieties. The catalytic activity of the functionalized\nmagnetosomes furthermore suggests the correct dimerization of the\nPAD monomers as it has been observed for genetically engineered, enzyme\ndisplaying magnetosomes. 29 , 37 Moreover, an increased\nenzymatic stability of PAD-ST was observed (compared to the soluble\nenzyme), suggesting that the immobilization on the magnetic carrier\nfacilitates and stabilizes folding and dimerization of the enzyme.\nBecause of the flexibility of the ST–SC system, the study performed\nhere opens the door to applications employing many other biocatalytically\nrelevant enzymes. Thereby, the magnetosome system might be especially\nuseful for enzymes, which prefer the presence of membranes for their\nimmobilization. In summary, the display of SC connectors greatly\nenhances the flexibility\nto functionalize the magnetosome surface with foreign protein cargo\nand extends the existing toolkit of magnetosome-adapted coupling groups\n(such as nanobodies or streptavidin 38 , 39 , 79 ). Because the complementary ST-peptide tag can be\neasily fused with the desired protein function, the ST–SC system\ncould enable the functionalization of the magnetosome surface with\nany foreign proteins, thereby greatly facilitating the fabrication\nof multifunctional magnetic nanoparticles with tailored properties.",
"introduction": "Introduction Innovative\nbiocatalytic solutions are becoming increasingly relevant\nin the context of the transformation of the chemical industry. 1 − 5 Crucial for the application of a biocatalyst is the successful development\nof an overall biocatalytic process in a suitable reactor system. In\nthis context, the principle of flow catalysis is being increasingly\nexplored, e.g., through the use of novel reactor concepts such as\nbiomimetic pickering emulsion reactors or self-assembling biocatalytic\nmaterials. 5 − 12 Specifically the use of microreactors, with dimensions ranging from\nmicroliters to milliliters, amplifies the advantages of flow systems\ndue to the increased surface-to-volume ratio within the reactor. This\nallows an even better control of the reaction system and thus, higher\nproduct yields. Furthermore, microfluidics is particularly suitable\nfor the realization of biocatalytic processes, as the frequently delicate\nbiocatalysts are exposed to lower shear forces. In this regard, magnetic\nbiocatalysts in a fluidized bed reactor, which are stabilized by a\nmagnetic field, offer a straightforward approach. To enable the use\nof enzymes in such reactors, their immobilization is essential and\ncan be achieved by noncovalent or covalent binding of the biocatalyst\nto a solid support material. 13 Using genetically\nencoded tags, biocatalysts can be covalently immobilized on such support\nmaterials in a predefined manner. 14 − 16 Thereby, the immobilization\nof enzymes on the surface of (nano)supports usually retains a high\ncatalytic activity while simultaneously increasing the particle density\nin a reactor. 13 , 17 − 20 An attractive alternative\nto the variety of commercially available\nnanoparticles is provided by so-called magnetosomes synthesized by\nmagnetotactic bacteria (MTB). For instance, the alphaproteobacterium Magnetospirillum gyphiswaldense biomineralizes ∼40\nmagnetosomes per cell, consisting of a cuboctahedral core of chemically\npure magnetite (Fe 3 O 4 ) enveloped by the magnetosome\nmembrane, a proteinaceous phospholipid bilayer. 21 − 23 Because of\nthe strictly controlled biomineralization process, magnetosomes exhibit\nextraordinary material characteristics such as a strong magnetization,\na narrow particle size distribution, and high crystallinity, to an\nextent that chemical synthesis can hardly achieve. 23 − 26 Moreover, the enveloping membrane\nprovides sites for the covalent attachment of functional moieties. 27 − 29 Functionalization of the magnetosome surface can be accomplished in vivo by genetic engineering as well as by chemical modification\nof the magnetosome membrane. Although the latter is less time-consuming,\nsuch approaches lack selectivity, often require harsh reaction conditions,\nand are difficult to control. 30 The functionalization\nof the magnetosome membrane by genetic means, on the other hand, enables\nthe specific display of functional moieties at distinct stoichiometries.\nForeign “cargo” proteins are expressed as translational\nfusion to abundant magnetosome membrane (Mam) proteins which serve\nas anchor molecules. Using an optimized genetic system, 31 a variety of functionalities has been displayed\non the magnetosome surface, including artificial peptides, 32 − 34 fluorophores, 35 or enzyme proteins, 29 , 36 , 37 demonstrating that magnetosomes\nhave the potential to yield reusable, highly active nano-biocatalysts. It is important to note that these functionalized particles are\nprearranged to specific activities and require the generation of individual\ngenetic variants for each fusion partner. The display of versatile\nconnectors such as nanobodies (camelid antibody fragments), biotin/streptavidin,\nor protein ligands could partly overcome this limitation and enabled\nthe specific immobilization of foreign protein cargo as well as specific\ncoupling reactions with complementary-tagged structures (such as nucleic\nacids) or even whole cells. 34 , 38 − 41 As such approaches are based on noncovalent interactions, they can\nbe affected by a change in reaction conditions. Therefore, a covalent\nbond formation between the connector and the fusion partner would\nbe desirable. For such approaches, the SpyTag–SpyCatcher system\nhas recently been established. 42 , 43 The system consists\nof a 13 aa peptide tag (SpyTag, ST) and a 116 aa peptide (SpyCatcher,\nSC), which autocatalytically form an intermolecular isopeptide bond\nbetween an aspartate and lysine residue under a wide range of temperatures,\npH values, and buffers 44 and can genetically\nbe fused to the protein of interest. The system has been employed\nfor a large variety of applications ranging from materials science,\nmolecular engineering, live-cell imaging, and protein purification\nto synthetic biology. 7 , 16 , 45 − 59 In our study, we demonstrate the installment of SC units on\nthe\nsurface of bacterial magnetosomes and their further functionalization\nwith ST-modified cargo proteins. In particular, we immobilize a phenolic\nacid decarboxylase (PAD) as an example for a biocatalytically relevant\nenzyme onto the particle surface. By comparing our system with commercially\navailable magnetic particles, also under conditions of continuous\nflow, we illustrate that functionalized SC-magnetosomes can serve\nas highly active, stable nanocatalysts for biocatalytic processes\nin flow reactor systems.",
"discussion": "Results and Discussion Magnetosome Expression\nof SpyCatcher Connectors Generates a\nFlexible Adapter Scaffold For magnetosome display of SC coupling\ngroups, the corresponding spycatcher sequence from S. pyogenes ( 42 , 43 ) was optimized to the\ncodon usage of M. gryphiswaldense to\nensure enhanced expression and obtained in a gene-splicing reaction\n( Figure S1 ). SC moieties were expressed\nas translational fusion to the surface-exposed hydrophilic C-terminus\nof the 12.4 kDa magnetosome protein MamC, with a flexible 17 aa Gly-Ser-Thr\nlinker connecting both sequences. MamC is tightly associated with\nthe magnetosome membrane by its two predicted transmembrane helices 60 − 62 and highly abundant on magnetosome particles (80–210 copies\nper particle). 31 , 37 , 63 However, in magnetosome biosynthesis MamC has only a minor, nonessential\nfunction as shown by the fact that Δ mamC deletion\ncells produce wildtype (WT)-like particle numbers with only slightly\nreduced diameters (∼95% of the WT). 64 Because of these characteristics, MamC has proven to be a suitable\nmembrane anchor for the display of foreign proteins and peptides. 65 The MamC–SpyCatcher fusion protein\nwas expressed under control of the strong constitutive magnetosomal\nP mamDC45 promoter with an optimized ribosome binding site\n(oRBS), 31 as illustrated in Figure 1 . The isogenic Δ mamC mutant strain of M. gryphiswaldense was chosen as recipient for the gene fusion, resulting in strain\nΔ mamC :: mamC-spycatcher . Figure 1 Biogenesis\nof SC-functionalized magnetosomes. Genetic organization\nof the expression cassette for SC display on the magnetosome surface.\nThe spycatcher gene was expressed as fusion to mamC , with a flexible gly-ser-thr linker\nconnecting both sequences. The fusion was set under the control of\nan optimized promoter with an optimized ribosome binding site (oRBS) 31 for constitutive high-level expression. The\ncassette was finally cloned into an insertion plasmid and transferred\nto the isogenic Δ mamC deletion mutant of M. gryphiswaldense . Stable insertion of the target\nsequences into the host genome by transposition enabled the production\nof SC-functionalized magnetosomes, which can subsequently be isolated\nwith an intact membrane (size of particle and proteins not to scale). Magnetosome biosynthesis and cell morphology was\nnot affected by spycatcher expression, and strain\nΔ mamC :: mamC-spycatcher biomineralized\n32 ± 10 particles\nper cell arranged in a chain-like manner at midcell ( Figure 2 ). For isolated SC-displaying\nmagnetosomes (termed SC-magnetosomes) an overall average diameter\nof 41.6 ± 7.3 nm was measured from TEM micrographs, with an electron-light,\norganic shell of ∼5 nm representing the magnetosome membrane\nsurrounding the magnetite cores. Figure 2 Transmission electron microscopy (TEM)\nimages of a representative\ncell of the WT of M. gryphiswaldense and strain Δ mamC :: mamC-spycatcher , as well as micrographs of the respective, isolated magnetosomes.\nThe WT produced 32 ± 14 particles per cell, arranged in a chain-like\nmanner at midcell. Suspensions of isolated particles (overall diameter\n38.4 ± 6.6 nm) were free of contamination and in negatively stained\npreparations, an electron-light organic shell was visible (indicated\nby blue arrows) representing the magnetosome membrane. Genomic insertion\nof a mamC-spycatcher expression cassette into the\nΔ mamC deletion mutant fully complemented the\nWT phenotype. The resulting strain Δ mamC :: mamC - spycatcher biomineralized 32 ±\n10 magnetosomes per cell with an overall diameter of 41.6 ± 7.3\nnm. As in the WT, isolated particles were enveloped by an organic\nshell of ∼5 nm on average in thickness. The presence of MamC–SpyCatcher in the isolated magnetosome\nfraction was confirmed by denaturing PAGE and Western blotting, followed\nby immunochemical detection employing IgG antibodies specific for\nMamC ( Figure S2 ). For WT particles or SC-magnetosomes,\nthe expected protein bands were detected, with electrophoretic mobilities\ncorresponding to molecular masses of ∼13 and ∼30 kDa,\nrespectively (calculated masses: 12.4 kDa for MamC and 26.2 kDa for\nMamC–SpyCatcher). The functionality, i.e., the capability\nto bind complementary ST-equipped\nproteins, as well as the amount of SC molecules displayed on the particle\nsurface was investigated by incubating SC-magnetosomes with different\namounts of recombinantly produced EGFP-ST. Both fluorescence microscopy\nanalysis and Western blotting ( Figure S3 ) indicated saturation of the SC adapter scaffold at ∼60 μg\nof EGFP-ST per mg of iron. Taking into account the molecular mass\nof the EGFP-ST fusion (31.4 kDa) and the mass of a single magnetosome\nparticle, an average copy number of ∼170 EGFP-ST moieties can\nbe calculated to be present on each SC-magnetosome (for details on\nthe calculation see the supplementary discussion to Figure S3 ). This value is in accordance with previous reports,\nin which the average copy number of MamC, and consequently the number\nof functional moieties on the magnetosome surface, was estimated to\nbe within the range from 80 to 210 molecules. 31 , 37 , 63 Our observations therefore clearly show\nthe successful immobilization of functional EGFP-ST (as a foreign\ncargo protein) on the surface of SC-magnetosomes and complete saturation\nof the SC-magnetosome adapter scaffold with all MamC–SpyCatcher\nfusions being covalently linked to EGFP-ST. The isolated SC-magnetosomes\nprovide a versatile carrier material\nfor the selective immobilization of functional cargo. To gain a better\nunderstanding of magnetosome behavior in a magnetic bioreactor, EGFP@Mag\n(i.e., SC-magnetosomes displaying ST-modified EGFP) were loaded into\na linear reactor channel. The thickness of the layer in the channel\nwas analyzed by using a z -stack of EGFP fluorescence\nin a fluorescence microscope ( Figure 3 ). Figure 3 (A) For fluorescence microscopic analysis the SC-magnetosomes\nwere\nfunctionalized with ST-modified EGFP 16 and\nloaded into a Topas chip with straight channels. The channel was closed\nand the chip was mounted on a chip holder with integrated Nd magnets.\nNote that due to the hardware configuration, the magnets of the chip\nholder are at the top of the channel. After placement of the setup\nin a fluorescence microscope (LSM 880 with Airyscan, Zeiss) the EGFP\nfluorescence was analyzed. (B) A z -stack of the channel\nsegment allows a 3D-view of the channel. (C) The layer thickness of\nthe magnetosomes in the channel was determined by measuring the fluorescence\nin the z -view of the image. Representative measurements of the magnetosomes in the channel\nshowed a layer thickness of ∼97 μm, which is in the same\nrange as the previously reported layer thickness of biotin-Atto647-functionalized\nSTV Dynabeads with ∼86 μm. 66 This result suggests that a similar amount of carrier material can\nbe loaded into the reactor channel. However, the size of the carrier\nmaterial has to be considered, as the use of smaller particles leads\nto an increase in the effective reactor surface area and, thus, a\nhigher number of functional units in an equal reactor volume, potentially\nleading to a significant enhancement in reactor efficiency. After\nremoval of the underlying Nd magnets, the EGFP-ST@Mag were readily\nflushed out without visible aggregation. Comparison of PAD-ST Immobilized\non SC-Magnetosomes with PAD\nImmobilized on Dynabead Architectures To benchmark the use\nof magnetosomes as immobilization matrix for flow biocatalysis, we\nchose the previously described dimeric phenolic acid decarboxylase\n(PAD) from Enterbacter sp . as a well-established\nbiocatalyst, which offers a sustainable route to styrene derivatives\nfrom biologically derived phenolic acids. 46 , 67 , 68 Three different particle systems were\ncompared for the immobilization of the PAD in this study ( Figure 4 A), and their performance\nin flow microreactors stabilized by a magnetic field was investigated\n( Figure 4 B). For this\npurpose soluble, heterologously expressed ST-equipped PAD (PAD-ST) 46 was coupled onto the surface of SC-magnetosomes\nto yield PAD-ST@Mag. This approach was compared with the immobilization\nof the enzyme on modified, superparamagnetic Dynabeads with a size\nof 2.8 μm ( Figure 4 A). Dynabeads are commercially available, composite magnetic support\nmaterials with various surface chemical modifications and coatings.\nThey have been shown to provide high mechanical stability and low\nporosity as well as excellent biocompatible properties. 14 , 69 − 71 Dynabeads M-270 Epoxy beads were covalently functionalized\nwith heterologous expressed and purified SC protein as previously\nreported. 14 Subsequently, incubation with\nPAD-ST led to capture of the enzyme and yielded the immobilized biocatalyst\nPAD-ST@Dyn. As an alternative example for a self-immobilizing PAD\nfusion enzyme, the HOB-tag was investigated for its suitability to\nimmobilize the PAD, resulting in PAD-HOB@Dyn. The HOB-tag, a variant\nof the HaloTag, is a self-ligating fusion tag that binds covalently\nto chlorohexyl (CH) suicide ligands 72 , 73 and was genetically\nattached to the PAD at its C-terminus. To employ this fusion enzyme,\nwe used Dynabeads M-280 streptavidin, which were further modified\nwith a biotin–PEG–chlorohexyl linker as previously reported. 14 , 66 A detailed scheme of the synthesis routes for each catalyst can\nbe found in Figure S4 . Figure 4 (A) SC-functionalized magnetosomes can be used as immobilizable\nnano-biocatalysts by coupling ST-equipped monomers of the dimeric\nphenolic acid decarboxylase (PAD-ST) onto the SC-magnetosome surface\n(PAD-ST@Mag). This approach was compared with the immobilization of\nthe PAD on SC-modified, commercially available Dynabeads M270 Epoxy\n(PAD-ST@Dyn) and PAD-HOB fusion protein immobilized via a chlorohexyl–biotin\nlinker on commercially available streptavidin-coated Dynabeads STV\nM280 (PAD-HOB@Dyn) for the conversion of p -coumaric\nacid to p -hydroxystyrene in a magnetic microreactor\nin flow (B). Table 1 Architectures of\nMagnetic Decarboxylase\nBiocatalysts Used in This Study biocatalyst PAD-ST@Mag PAD-ST@Dyn PAD-HOB@Dyn PAD variant PAD-ST PAD-ST PAD-HOB carrier material SC-magnetosomes SC-modified Dynabeads M-270 Epoxy CH-modified Dynabeads M-280 STV particle\nsize 41.6 ± 7.3 nm 2.8 μm 2.8 μm surface properties biogenic,\nmembrane-enveloped magnetite nanoparticles with surface-exposed\nSC, genetically incorporated and immobilized as translational fusion\nwith the magnetosome membrane anchor MamC nonporous,\npH neutral, hydrophilic, epoxy-activated magnetic\nparticles 74 with immobilized SC-protein nonporous, hydrophobic, tosyl-activated magnetic particles\nwith immobilized BSA and STV, 75 further\nfunctionalized with a biotin–chlorohexyl linker There are several relevant\nconsiderations for a valid assessment\nof the efficiency of immobilized biocatalysts in a flow reactor. A\npotentially detrimental influence of the binding tags on the biocatalyst’s\nactivity has to be investigated. However, we found that the fusion\nof PAD with the tags used in this work could be heterologously expressed\nin high purity ( Figure 5 A) with no significant differences in the substrate conversion rate\n( Figure 5 B). Furthermore,\nmaximizing the volumetric activity of flow reactors is a crucial parameter\nfor their efficiency and strongly depends on the effective surface\narea and binding capacity of the support matrix used. Prior to application\nin a flow process, the PAD activity per milligram of carrier material\nwas analyzed via the conversion of p -coumaric acid\n( p CA) to p -hydroxystyrene ( p HS) in a batch assay. PAD-ST@Mag showed a superior activity\nper milligram of carrier material in comparison to PAD-ST@Dyn and\nPAD-HOB@Dyn ( Figure 5 C), which might be due to the higher surface area of the magnetosome\nnano-biocatalyst in comparison to the Dynabeads. Figure 5 Characterization of PAD-fusion\nproteins and immobilized PAD on\ndifferent carrier materials. (A) Denaturing 16% SDS-PAGE analysis\nof 4 μg of each PAD fusion protein after heterologous expression\nin E. coli and purification via\na C-terminal 6×His-tag. The proteins were obtained in purities\n>95% according to grayscale analysis. Lane 1: PAD (20.4 kDa); Lane\n2: PAD-ST (21.8 kDa); Lane 3: PAD-HOB (53.8 kDa); Marker: PageRuler\nprestained protein ladder (Thermo Scientific). Molecular weight of\nto the monomer is given. (B) Enzymatic activity in (μmol p CA μmol PAD –1 min –1 ) of the PAD variants by using 0.1 mM p -coumaric acid ( p CA) as substrate, determined\nby an absorbance-based assay in PAD Buffer (25 mM potassium phosphate\nbuffer, pH 6) at 30 °C. (C) Specific activities per milligram\nof carrier material of PAD-functionalized SC-magnetosomes (PAD-ST@Mag;\nyellow) in a batch reaction in comparison to the alternative magnetically\nimmobilizable biocatalyst systems. The conversion of p CA to p HS through PAD-ST@Mag, PAD-ST immobilized\non SC-Dynabeads (PAD-ST@Dyn; dark blue), or PAD-HOB immobilized on\nCH-Dynabeads (PAD-HOB@Dyn; light blue) was monitored at different\npoints in time by using HPLC analysis. All experiments were performed\nin PAD-Buffer at 30 °C and 600 rpm at least in duplicates by\nusing different batches of magnetosomes or particles. Application of PAD-ST@Mag in a Miniaturized Continuous Flow\nBiocatalysis We next investigated the operational stability\nof the three immobilized PAD biocatalysts in a flow process. For practical\nprocesses it is important that the immobilized enzyme preserves high\ncatalytic activity over a prolonged time. To this end, the different\nmagnetic biocatalysts were loaded into a microreactor and fixed via\nNd magnets incorporated in the reactor holder in a continuous reaction\nformat with automated sampling ( Figure 6 A,B). We chose a flow rate of 1 μL min –1 , leading to a typical residence time of 3.5 min. Similar to the\nexperiments performed in batch mode, the immobilized decarboxylase\nbiocatalysts exhibited excellent activity ( Figure 6 C). Employing 2 mg of PAD-ST@Mag, near-quantitative\nconversion to p HS was achieved during the first 24\nh. PAD-ST@Mag proved to be more durable than the PAD immobilized on\nDynabeads, leading to an average space–time yield (STY) of\n49.2 mmol L –1 h –1 during a run\ntime of 60 h. The use of 2 mg of PAD-ST@Dyn led to a satisfactory\naverage STY of 44.7 mmol L –1 h –1 . In contrast, no full conversion could be obtained when employing\n2 mg of PAD-HOB@Dyn. The activity significantly declined after 14\nh, leading to an average STY of only 30.1 mmol L –1 h –1 in the course of 60 h. The decrease in activity\nin the case of the PAD-HOB@Dyn was expected, since the PAD-HOB is\ncovalently coupled to the chlorohexyl–biotin, but its binding\nto the streptavidin is noncovalent, leading to a constant removal\nof PAD from the reactor bed. Figure 6 Application of the PAD-functionalized SC-magnetosomes\nin continuous\nflow reactors in comparison with the alternative magnetically immobilizable\nbiocatalyst systems (Dynabeads). (A) Fluidics setup used in this study.\nGlass syringes containing the substrate solutions were installed in\nCetoni Nemesys syringe pumps and connected to a Topas chip with four\nstraight channels via PTFE tubing. The chip was mounted on a brass\nchip holder with integrated Nd magnets to retain the magnetic catalyst,\nand the chip holder was connected to a thermostat for temperature\ncontrol. The reactor outflow was automatically fractionated into a\n96-well plate by using a Cetoni rotAXYS positioning system, modified\nfor parallel sampling of up to three samples. (B) Magnetic microfluidic\npacked-bed reactor loaded with PAD-functionalized magnetic particles.\nThe picture shows three channel compartments. The brass chip holder\nis connected to a thermostat to control the temperature and contains\nintegrated rectangular Nd magnets that retain the PAD-functionalized\nmagnetic carriers. The first channel on the left contains the light\nbrown PAD-HOB@Dyn, while the dark brown PAD-ST@Dyn is applied in the\ncenter. The right channel contains the black PAD-ST@Mag. (C) Conversion\nof p CA to p HS over 60 h in flow\nmicroreactors using PAD-ST@Mag (yellow), PAD-HOB@Dyn (light blue),\nand PAD-ST@Dyn (dark blue). All experiments were performed at least\nin duplicates by using different batches of magnetosomes and particles.\nThe reactors were perfused with 1 μL min –1 of a 5 mM p CA substrate solution in PAD buffer\nat 30 °C. Fractions were automatically collected every 90 min,\nand the substrate conversion was determined via HPLC analysis of the\nreactor outflow. The slow decline in reactivity\nof the PAD-ST@Mag could potentially\nbe due to disintegration of the magnetosomes. However, we could not\ndetect obvious changes in magnetosome morphology when comparing particles\nbefore and after application in the flow reactor ( Figure S5 ). On the contrary, the stability of the PAD appears\nto be improved by immobilization. While a flow reactor loaded with\nonly 50 μg of PAD-ST@Mag still showed more than 65% of its initial\nactivity after 96 h, the free PAD-ST in the working stock concentration\nfor the batch assays under comparable conditions (30 °C, PAD\nreaction buffer) lost most of its activity after 96 h with only 7%\nof its initial activity remaining ( Figure S6 ). Therefore, the loss in activity over time might indicate a loss\nof particles. These could, however, be recovered and recirculated\ninto the reactor. In comparison with the available commercial particle\nsystems, the magnetosome-based system developed here provides high\nspace–time yields in flow biocatalytic applications, while\noffering a platform for the modular decoration of magnetic nanoparticles\nrequiring no chemical functionalization reactions."
} | 7,079 |
34099669 | PMC8184982 | pmc | 6,623 | {
"abstract": "Nutrient amendment diminished bacterial functional diversity, consolidating carbon flow through fewer bacterial taxa. Here, we show strong differences in the bacterial taxa responsible for respiration from four ecosystems, indicating the potential for taxon-specific control over soil carbon cycling. Trends in functional diversity, defined as the richness of bacteria contributing to carbon flux and their equitability of carbon use, paralleled trends in taxonomic diversity although functional diversity was lower overall. Among genera common to all ecosystems, Bradyrhizobium , the Acidobacteria genus RB41 , and Streptomyces together composed 45–57% of carbon flow through bacterial productivity and respiration. Bacteria that utilized the most carbon amendment (glucose) were also those that utilized the most native soil carbon, suggesting that the behavior of key soil taxa may influence carbon balance. Mapping carbon flow through different microbial taxa as demonstrated here is crucial in developing taxon-sensitive soil carbon models that may reduce the uncertainty in climate change projections.",
"introduction": "Introduction Global climate projections depend on estimates of soil carbon accumulation and decomposition 1 – 3 , processes driven by microorganisms 3 – 6 . Given the vast diversity of soil microorganisms, different microbial taxa may have individualistic effects on C fluxes in soil 7 , yet testing this idea has been challenging. Soils hold over twice as much organic carbon (C) as terrestrial vegetation, and soil C turns over much more slowly. Soil microbial communities contain thousands of different heterotrophic microbial taxa that, together, influence soil C content, but the quantitative contributions of individual microbial taxa to the processes governing soil C accumulation and loss are not known. While some soil biogeochemical processes are physiologically specialized and dominated by a few phylogenetically specific groups, processes involved in heterotrophic decomposition are broadly distributed across the bacterial tree of life 8 . With many taxa contributing to the same process, the functional evenness of heterotrophic decomposition might be expected to be approximately equivalent to the evenness in abundance of heterotrophic decomposers, with each taxon contributing to decomposition in proportion to its abundance. As bacterial abundances are logarithmically distributed 9 , we might expect that the contributions to soil C may be similarly distributed despite differences in ecosystem or bacterial community composition. We used a combination of measurements and models to evaluate the contributions of individual bacterial taxa to heterotrophic growth and respiration in four soils along a climate gradient in northern Arizona. Taxon-specific growth rates were measured using quantitative stable isotope probing with 18 O-water (qSIP, see “Methods” section) 7 , 10 for soils collected from desert grassland (GL), Piñon-Juniper scrubland (PJ), Ponderosa Pine forest (PP), and mixed conifer forest (MC) sites, as described previously 11 – 13 . Mean annual temperature for all respective sites: 8.5, 7, 5.5, and 4 °C and mean annual precipitation: 230, 380, 660, and 790 mm 12 . To determine how taxon-specific contributions to growth and respiration varied with resource availability, measurements were conducted in the laboratory using unamended soil, soil with supplemental glucose, and soil with glucose plus a nitrogen source accessible to microbes, [NH4] 2 SO4 (carbon+nitrogen). Isotopic signatures of specific 16S sequences were combined with 16S abundances from quantitative PCR to yield quantitative estimates of taxon-specific population size and growth.",
"discussion": "Results and discussion Bacterial efficiency and respiration Taxon-specific productivity (µg C g soil −1 week −1 ) was modeled as a function of per-capita growth rate, taking into account relative abundance, 16S content per unit soil, as well as 16S copy number and genome size (as as per Li et al. 13 ) to estimate taxon-specific cell size and carbon content (see “Methods” section). We estimated taxon-specific bacterial respiration as a function of taxon-specific growth rate and taxon-specific carbon use efficiency (CUE), using several parameterizations of the growth ~ CUE relationship (Supplementary Fig. 1 , see “Methods” section). The relationship between microbial growth and efficiency is complex and difficult to identify based on existing literature 14 . Among models with different parameterizations, a unimodal relationship between growth rate and CUE was selected with the lowest AIC and further discussed in the methods (Table 1 ). Table 1 Comparison of per-taxon carbon use efficiency functions. Relation to community CUE CUE (growth) ΔAIC co2 ΔAIC cue ΔAIC combn Constrained Unimodal 0.5 2.98 5.20 11.17 Linear positive 6.10 0 12.21 Unimodal 0.05 0 14.39 14.39 Linear negative 2.85 19.87 25.56 Exponential decline 4.38 20.33 29.08 Unconstrained Exponential decline 17.43 46.25 81.10 Linear negative 21.96 40.89 84.80 Unimodal 0.05 19.58 47.72 86.89 Linear positive 23.56 50.77 97.89 Unimodal 0.5 23.47 50.99 97.94 Akaike information criterion values expressed as the difference from the model with the lowest error (ΔAIC) returned from regression models under different assumptions of per-taxon carbon use efficiency (CUE) as a function of per-taxon growth rate denoted by the CUE(growth) column. Per-taxon CUE estimates were calculated either constrained by the minimum and maximum observed community-level CUE values or bounded only by 0 and 0.85 (unconstrained). For all regression models, both terms were z-transformed. ΔAIC co2 indicates the fit of summed per-taxon respiration to measured respiration. ΔAIC cue indicates the fit of summed relative abundance-weighted per-taxon CUE to community-level CUE. ΔAIC combn indicates the sum of 2(ΔAIC co2 ) and ΔAIC cue . Subscripts following unimodal function names indicate whether maximum per-taxon CUE was centered over a growth rate of 0.5 or the global median growth rate of 0.05 observed across all taxa. We compared this model to one without taxonomy-informed genome characteristics ( 16S content and genome size estimates) and without taxon-specific growth, in which individual bacterial taxa respired in direct proportion to their 16S abundance per unit soil. This comparison served to demonstrate the extent that 16S abundance data of the bacterial community alone can predict soil carbon flux. Across the four soils and nutrient amendment treatments, modeled respiration of individual bacterial taxa was summed over the bacterial assemblage and was compared with measured total soil respiration. When based on measured per-taxon growth rates, modeled bacterial respiration was positively related to total soil respiration ( R 2 = 0.83, p < 0.001; Fig. 1a ). In contrast, when estimated in proportion to a taxon’s abundance alone, modeled bacterial respiration demonstrated a comparatively poor correlation ( R 2 = 0.02, p = 0.70; Fig. 1b ). Although our methods track the incorporation of 18 O-labeled water into bacterial DNA, and not carbon explicitly, these results indicate that growth of individual bacterial taxa measured through 18 O assimilation can be directly associated with the movement of C through the soil. For all but two soil and treatment combinations, modeled respiration was lower than measured respiration, likely in part owing to non-bacterial contributions to measured total respiration (which were not modeled). When we amended soils with carbon (C) and carbon with nitrogen (C + N) we found elevated soil respiration, patterns which were also observed with modeled bacterial respiration (Fig. 1a ). Nutrient amendments also stimulated taxon-specific bacterial respiration ( F 2,9 = 27.2, p < 0.001) and productivity ( F 2,9 = 6.96, p = 0.01) leading to higher total C use in these treatments (Fig. 2 ). Generally, organisms that produced more biomass also respired more (Supplementary Fig. 2 ). Fig. 1 Fit of modeled respiration scaled from taxon-specific isotopic enrichment against community soil respiration, by mass of carbon (C) per g dry soil per week (wk). a Bacterial respiration is estimated as the sum of modeled taxon-specific respiration and plotted against measured soil respiration. b Bacterial respiration is estimated from the community-level enrichment of all 16S copies present in a sample (per g dry soil). Points show mean respiration values ± standard error (SE) across replicates ( n = 3 experimental replicates) for each ecosystem (symbol MC mixed conifer forest, PP ponderosa pine forest, PJ piñon pine-juniper scrubland, GL desert grassland) and treatment (color control = no amendment, C = glucose, C + N = glucose and [NH 4 ] 2 SO 4 ). Fig. 2 Absolute and relative carbon (C) use of bacterial families, per gram of dry soil per week (wk). Values averaged across replicates for each ecosystem (MC mixed conifer forest, PP ponderosa pine forest, PJ piñon pine-juniper scrubland, GL desert grassland) by treatment (rows: Ctrl = no amendment, C = glucose only, C + N = glucose and [NH 4 ] 2 SO 4 ) combination ( n = 3 experimental replicates). Bar color represents bacterial family (15 shown, accounting for ≥75% of C use, remaining families designated as “Other”). a Total C use (C-CO 2 respired and MBC produced) from each bacterial family. b C use for each bacterial family, relativized by total C use. Distribution and consolidation of bacterial carbon use Soils amended with nutrients had higher productivity and respiration; however, in these soils, carbon use was less evenly distributed across the bacterial community, especially in soils provided with carbon and nitrogen. To compare the extent that taxonomic evenness equated to functional evenness (i.e., the extent that both shared similar abundance distributions), we calculated Pielou’s evenness on the relative abundances of bacterial amplicon sequence variants (ASVs) as well as relativized growth and respiration estimates. Bacterial abundances were more evenly distributed than were estimates of bacterial productivity and respiration (Fig. 3a ). Similarly, cumulative C use was strongly associated by treatment, with greater consolidation of carbon in C + N soils as shown by a lower proportion of the bacterial community responsible for a greater proportion of carbon flux (Fig. 3b ). Fig. 3 Change in bacterial taxonomic and functional evenness across soil nutrient amendments. Color indicates soil treatment (Control = no amendment, C = glucose, C + N = glucose and [NH 4 ] 2 SO 4 ). a Pielou’s evenness of bacteria by relative abundance against Pielou’s evenness by relativized carbon (C) use. Closed circles represent evenness of biomass production, open circles represent evenness respiration. b Cumulative contribution of bacteria to total relativized C use across soil amendment ( n = 12 experimental replicates). Microbial community structure and function are thought to be linked 15 , 16 , but most efforts to relate them rely on aggregate community function measurements correlated against summaries of composition, diversity, or interactions (e.g., Creamer et al. 17 ). Interpretation of relative abundances across communities is a common exercise in contemporary studies of microbial ecology. Averaged across all ecosystems, 36 bacterial genera contributed to >50% of sequenced 16S amplicons. Of genera common to all soils, only six were necessary to obtain >50% contributions to C cycling in control and C amended soils while only three were necessary to obtain >50% C cycling in C + N amended soils. Bradyrhizobium (Alphaproteobacteria, Family: Xanthobacteraceae) , RB41 (Acidobacteria, Family: Pyrinomonadaceae—Subgroup 4), and Streptomyces (Actinobacteria, Family: Streptomycetaceae) were common to all soils and treatments and in the C + N treated soils, these lineages accounted for the majority of C flux (Fig. 4a ; Supplemental Table 1 ). These taxa also represent globally ubiquitous and abundant lineages as determined across the Earth Microbiome Project database 18 . Fig. 4 Comparison of relative abundance and relativized carbon (C) use of soil bacterial genera. Points show relative contributions from individual bacterial genera. Values are averages across soil replicates from four ecosystems (mixed conifer forest, ponderosa pine forest, piñon pine-juniper scrubland, and desert grassland) and amended with either water (Control, labeled with 18 O), glucose (C), or glucose and [NH 4 ] 2 SO 4 (C + N) ( n = 3 experimental replicates). a Comparison of the relative abundance and relativized C use of the top 36 most abundance genera. Colors correspond to bacterial phyla (six phyla accounted for >99% of C flux). Symbols correspond to the metric being compared for each taxon (relative abundance of 16S rRNA gene amplicon sequences, relativized use of soil C, or relativized use of native soil C excluding added glucose). b Comparison of relative abundance and relativized C use across all genera. Trend lines show best fit from a linear mixed model accounting for differences between ecosystems and bacterial genera. Asterisks represent significant differences of slopes from the 1:1 line (two-sided unadjusted t -tests; C:Control t 287 = −0.60 ± 0.06 (std error), p = 0.548, effect-size r = −0.0007; C + N:Control t 489 = 2.42 ± 0.06, p = 0.016, effect-size r = 0.012). c Comparison of relativized glucose use and relativized native soil carbon use across all genera, with variance (var) around trend lines included. Asterisks represent significant differences in variance in C + N soils compared to C soils ( F 22,770 = 3.53, p < 0.001, Cohen’s d = 0.134). Relative C use in the bacterial community was more consolidated within fewer lineages than the overall distribution of relative abundances might suggest. Averaged across all ecosystems and treatments, 75.7% of bacterial genera used less C than their relative abundance would otherwise predict. We assessed the relationship between relative C use and relative abundance in response to nutrient amendments using linear mixed modeling, accounting for random intercepts (and to limit pseudo-replication) across ecosystems and bacterial genera, and including an offset term to assess significant departure from the 1:1 line. In parallel with changing profiles of diversity, the relationship between taxon-specific bacterial C use and abundance was affected by treatment ( F 2, 489.11 = 4.926, p = 0.008). Specifically, we estimated that the slope of the relationship between relative C use and relative abundance was slightly but significantly higher than the 1:1 line in C + N amended soils, but not in control and C amended soils ( p = 0.02) (Fig. 4b, c ). Besides relative abundance, other potential influences on taxon-specific C use estimates were per-capita growth rate and taxon-specific cell mass. Analysis of residual values from the linear mixed model found a significant positive relationship between per-capita growth rate and residual variation in C use ( F 1, 583 = 14.3, p < 0.001), whereas individual cell size (µg C) was not a significant driver, suggesting that the bacterial taxa that used more soil C in C + N soils did so because they grew and divided faster, not because they had larger cells, and that taxa that used less soil C in C + N soils grew more slowly than in other treatments. In addition, relative abundances likely reflect a mixture of both historical activity and activity as a result of the experimental conditions. A similar mixed model was therefore run using initial relative abundance, reflecting the historical activity of microbial taxa, as a predictor of C use during the incubation. Initial relative abundances were a significant model term ( F 1, 375 = 83.3, p < 0.001), suggesting that the historical activities of microorganisms can meaningfully influence the trajectories of microbial communities. Bacterial carbon use and abundance in response to resource stoichiometry In general, the relative contributions of individual bacteria to carbon use strongly resembled patterns of relative abundance, where the most abundant genera also utilized the largest proportion of C in the community (Fig. 4 ). However, while relative abundance was generally predictive of relative C use, it was difficult to predict any individual organism’s contribution to C flux based on relative abundance alone, with differences between abundance and C use estimated to be an order of magnitude or more (Fig. 4b ). One notable example was the genus Sphingomonas (Alphaproteobacteria) which had high 16S abundance but contributed minimally to soil C flux (Fig. 4a ). Sphingomonas could be distinguished from the top C using genera by a smaller cell mass estimate (31st percentile), a function of genome length, which was lower than Bradyrhizobium (73rd percentile), Streptomyces (88th percentile), RB41 (81st percentile) or the Burkholderia-Caballeronia-Paraburkholderia group (95th percentile), even though its growth rate was comparable. In glucose-amended soils, the use of native soil C was closely correlated with the use of glucose across the bacterial community ( r = 0.96, p < 0.001). In C and C + N treated soils, we performed 13 C-glucose amendments in parallel to 18 O-water conditions and used per-taxon 13 C enrichment to estimate the amount of native ( 12 C) and glucose carbon utilized across the bacterial community. Our results indicate that the organisms that utilized the most glucose were also those that utilized the most native soil carbon. Thus, organisms with the capacity to grow quickly in response to easily accessible carbon substrates are important to the cycling and turnover of existing soil C. To determine the extent that the C:N stoichiometry of labile resources may change microbial C use preferences, we used Levene’s test on the variance in the relationship between 13 C use and 12 C use, where higher variance in response to nitrogen is indicative of shifts in the type of carbon preferred across bacterial genera. In C + N treated soils, there was significantly more variation around the trend line ( F 22, \n 770 = 3.53, p < 0.001, Levene’s test; Fig. 4c ), indicating that labile nitrogen addition may disrupt the balance between native soil carbon use and use of a labile carbon substrate. Despite some differences between 16S abundance and soil C use, across soils, differences in composition of the community significantly predicted the C use profiles ( r M = 0.68, p < 0.001, Mantel correlation). The four ecosystems differed in the amount of carbon used by different taxa ( R 2 = 0.69, p < 0.001, PERMANOVA), patterns that mirrored differences in relative abundance ( R 2 = 0.69, p < 0.001; Fig. 5 ). Similarly, bacterial communities changed in response to nutrient amendments, observed both with changes in relative abundance ( R 2 = 0.14, p = 0.03) and C use ( R 2 = 0.13, p = 0.05), though these differences were smaller than ecosystem-level separation of community composition and C use. Fig. 5 Composition of abundance and carbon use. Ordinations generated by principal coordinates analysis (PCoA) of Bray–Curtis dissimilarities. Points represent centroids across replicates for each ecosystem (symbol MC mixed conifer forest, PP ponderosa pine forest, PJ piñon pine-juniper scrubland, GL desert grassland) and treatment (color control no amendment, C = carbon—glucose—only, C + N = carbon and nitrogen—[NH 4 ] 2 SO 4 ) ( n = 3 experimental replicates). Ellipses represent multivariate standard error ranges for ecosystem group position (95% confidence). Percentages along axes represent the percent of multivariate dispersion explained by each PCoA dimension. a Beta diversity of relativized abundances. b Beta diversity of relativized carbon use values (respiration plus biomass production, μg carbon per g soil per week). The strong ecosystem-specific clustering of community composition and C use (Fig. 5 ) is seemingly at odds with the strong treatment-specific patterns of cumulative C use (Fig. 3b ), which suggests that there was a similar response to nutrient addition across all ecosystems regardless of which bacteria were responsible. However, relative abundance and C use were strongly linked (Fig. 4 ), and we observed that the most important contributors to bacterial C use were consistently represented by the same, abundant lineages across all ecosystems and treatments (Supplemental Table 1 ). Taken together, these results demonstrate that changing patterns in carbon use were driven by the consistent and abundant portion of the bacterial community which responded to the C + N amendment. Conversely, the importance of any individual lineage that occurred with low abundance towards soil C flux was difficult to determine. Rare taxa are thought to serve as a reservoir or seed bank of microbial function and diversity 19 . Although rare lineages drove ecosystem-specific patterns in community composition and C use due to the sensitivity of multivariate dissimilarity measures to their high diversity, differences in the composition of rare lineages were negligible, contributing minimally to soil C flux. These non-dominant organisms may be best described as part of the “interchangeable” biosphere, where apart from a few consistent taxa that dominate C flux, the identities of most rare taxa are negligible towards their contributions to C flux. Generally, dominant lineages became more dominant—in terms of abundance as well as C use—in nutrient amended soils compared to native soil conditions, especially in the Actinobacteria. Consolidation of C use increased in C + N soils for most major phyla, where a proportionally smaller number of taxa was associated with a greater share of overall abundance and C flux in C and C + N treatments (Fig. 6 ). Several taxa within the Actinobacteria, mostly Streptomyces (Actinomycetaceae), Arthrobacter (Micrococcaceae), and Kribbella (Nocardioidaceae) spp., produced proportionally more 16S rRNA gene copies than other Actinobacteria during the seven-day incubation in C and C + N soils (Supplementary Fig. 3 ). These taxa were also dominant producers of biomass and CO 2 even after correcting for 16S rRNA gene copy number, cell mass, and growth rate (Supplementary Figs. 4 – 6 ). Across nearly all major bacterial phyla, the addition of labile nutrients tended to promote respiration of some lineages relative to others, increasing dominance, and demonstrating that the release of soil carbon as CO 2 can be concentrated in a few taxa (Figs. 3 and 6 and Supplementary Figs. 3 , 4 – 6 ). These findings complement previous synthesis efforts, which have found key taxa are likely responsible for variability in carbon cycling 20 . Generally, microbial communities are more resilient to pulses, such as our C and C + N amendments, than longer disturbances (also known as press disturbances) 21 . It is possible that nutrient addition over longer periods would elicit a different response from abundant and rare bacteria as well as changes in overall soil productivity and respiration. Fig. 6 Change in functional evenness across soil nutrient amendments and major bacterial phyla. Cumulative contribution of bacteria to total relativized carbon (C) use (the sum of μg C–CO 2 respired and μg MBC produced per taxon relativized by total C use across all taxa, both per g dry soil per week [wk]) across soil amendment. Points represent averages across soil replicates from four ecosystems (mixed conifer forest, ponderosa pine forest, piñon pine-juniper scrubland, and desert grassland) ( n = 3 experimental replicates). Color indicates soil treatment (Control = no amendment, C = carbon—glucose—only, C + N = carbon and nitrogen—[NH 4 ] 2 SO 4 ). Taxa were ranked by individual contribution to C use. In conclusion, we identify the contributions of individual bacterial taxa to soil carbon flux through bacterial production and respiration in their native soil habitats, providing insight into the community dynamics that are missing in microbial carbon models 22 , 23 . Our model identified the growth of a few highly abundant bacterial lineages in response to labile nutrient additions, whose pre-existing high abundance in the community allowed them to assimilate ~50% of carbon consumed by or available to bacteria. The well-known pattern of logarithmic bacterial frequency and abundance distributions, thus parallels the high importance of a relatively small subset of bacterial biodiversity in the carbon cycling of any given soil. Given that this pattern is universal in microbial communities 9 , we expect that such inequality in carbon use is as well. 4 of the 20 most prolific contributors to soil respiration come from poorly understood bacterial groups, one from the Acidobacteria, a phylum often generalized as oligotrophic 24 . However, the abundance of individual bacterial taxa, alone, was not a sufficient predictor of soil C flux. Thus, the ability to measure in situ growth rates provided by techniques like qSIP has considerable potential to resolve the ecological roles of bacterial lineages that are difficult to culture, or whose functions would otherwise require extensive physiological assays. With regard to soil respiration modeling, we propose that because the majority of bacterial carbon flux could be accounted for by 3–6 common genera from ecosystems with different temperature and precipitation regimes, and that these genera were globally abundant and ubiquitous 18 , it is worthwhile to determine both the global ubiquity and consistency in carbon process rates, as well as their determining traits, of such highly abundant bacteria in response to climate change. Doing so may reveal a core group of the soil microbial community that act as dominant carbon processors."
} | 6,501 |
35539725 | PMC9081488 | pmc | 6,625 | {
"abstract": "The profitability of next-generation biorefineries is acutely contingent on the discovery and utilization of biocatalysts that can valorize lignin. To this end, the metabolic catalogues of diverse microbiota have been mined previously using functional metagenomics in order to identify biocatalysts that can selectively degrade lignin into monoaromatic compounds. Herein, we have further improved the valorization factor of biorefining by deploying functional metagenomics toward the identification of a novel transaminase that can selectively functionalize lignin-derived monoaromatics to produce value-added feedstocks for pharmaceutical synthesis. We implemented a high-throughput colorimetric assay using o -xylylenediamine as the amino donor and successfully identified a transaminase that utilizes the canonical cofactor, pyridoxal 5′-phosphate, to aminate as many as 14 monoaromatic aldehydes and ketones. We subsequently identified the optimal conditions for enzyme activity towards the most favoured amino acceptor, benzaldehyde, including temperature, pH and choice of co-solvent. We also evaluated the specificity of the enzyme towards a variety of amino donors, as well as the optimal concentration of the most favoured amino donor. Significantly, the novel enzyme is markedly smaller than typical transaminases, and it is stably expressed in E. coli without any modifications to its amino acid sequence. Finally, we developed and implemented a computational methodology to assess the activity of the novel transaminase. The methodology is generalizable for assessing any transaminase and facilitates in silico screening of enzyme–substrate combinations in order to develop efficient biocatalytic routes to value-added amines. The computational pipeline is an ideal complement to metagenomics and opens new possibilities for biocatalyst discovery.",
"conclusion": "3. Conclusions In summary, we employed a high-throughput colorimetric assay using o -xylylenediamine as the amino donor and PLP to identify a novel TA from a subset of our in-house metagenomic library. This is the first ever study to report the successful use of functional metagenomics toward the discovery of a TA. The enzyme successfully transforms several monoaromatic aldehydes and ketones to their corresponding amines in vivo , although the highest conversions were observed when it is used as a constituent of the cell lysate. We then evaluated the specificity of the enzyme towards a variety of amino donors, as well as optimal concentration of the most favoured amino donor, and also identified the optimal conditions for enzyme activity towards the most favoured amino acceptor, benzaldehyde, including temperature, pH and choice of co-solvent. Finally, we developed and implemented a computational methodology to assess its activity. The methodology is generalizable to other enzymes in its class, which facilitates in silico screening of enzyme–substrate combinations and the development of novel biocatalytic routes for amination of monoaromatic derivatives of lignin for use as pharmaceutical intermediates. Significantly, since the enzyme is active towards products of the degradation of lignin that is catalyzed by other enzymes that we have discovered previously, it can be readily deployed in biorefining operations for one-pot valorization of lignin.",
"introduction": "1. Introduction Biorefining is loosely defined as the separation, isolation and conversion of cellulose, hemicellulose and lignin from lignocellulosic biomass into fuels, chemicals, materials and energy. 1 A number of biocatalytic 2 and thermocatalytic 3 processes have been developed for biorefining. However, regardless of the mode of conversion employed, biomass comprising a higher content of cellulose and hemicellulose is generally preferred as a feedstock compared to biomass with a higher proportion of lignin. 4 The degree to which a resource can be valorized (which we define as the valorization factor) is a function of the ratio of the value of all products that can be manufactured from the resource to the value of the resource. Typically, the greater the number of useful products that can be manufactured from a resource, the greater is its valorization factor; and lignin's poor valorizability can be attributed to its recalcitrance to most biocatalytic or thermocatalytic transformations. 5,6 The inability to efficiently valorize lignin represents a lost opportunity for biorefining, especially since lignin has a higher carbon and lower oxygen content compared to both, cellulose and hemicellulose. 7 In particular, lignin is arguably one of the most attractive feedstocks for the manufacture of aromatic specialty and fine chemicals that are, among other applications, widely used in pharmaceutical synthesis. Although these chemicals are presently derived from petroleum, they can be sourced from lignin at higher atom economies. The development of conversion platforms that can efficiently valorize lignin is highly desired, particularly biocatalytic processes that are greener, emit lesser CO 2 and are more energy efficient than thermocatalytic alternatives. 8–13 To this end, functional metagenomics is poised to be a major driver of the discovery of superior biocatalysts for the valorization of lignin. Functional metagenomics provides reliable and easy access to the entire catalogue of microbial biocatalytic transformations without the need to culture any microorganisms in the laboratory. 14,15 We had previously reported the identification of 147 novel, whole-cell biocatalysts that selectively degrade lignin using functional metagenomics. 16 We employed a whole-cell, GFP-based biosensor to screen 42 520 fosmid clones comprising the environmental DNA of archaea and bacteria from coal beds. Each fosmid ranged between 30- to 50-kilo base pairs in length, and the clones selectively degrade lignin into vanillin and syringaldehyde. Herein, we further improve the valorization factor of lignin use by re-deploying functional metagenomics to discover a novel transaminase that catalyzes the asymmetric synthesis of chiral amines from the monoaromatic degradation products of lignin. It is estimated that roughly 40% of all new chemical entities (NCEs) approved by the US Food & Drug Administration (FDA) contain chiral amines building blocks 17 that are the products of enzymes such as imine reductase, 18 monoamine oxidase, 19 ammonia lyases, 20 amine dehydrogenase, 21 and transaminases. 22,23 Of these, transaminases (TAs) are especially promising for biocatalytic aminations since they can convert monoaromatic aldehydes and ketones into their corresponding amines at high yields and selectivities under mild, aqueous reaction conditions. 24 In fact, several chemo-enzymatic schemes employing TAs for the syntheses of enantiopure ( R )- or ( S )-pharmaceutical intermediates have been reported in recent years. 25–30 Amination by a canonical TA commences with the binding of the cofactor pyridoxal 5′-phosphate (PLP) to a lysine residue within the enzyme's active site, which generates an internal (or enzyme-bound) aldimine. 31,32 The amino donor binds to the internal aldimine thereafter and molecular rearrangements ensue, which sequentially generate an external (or dissociated) aldimine, a quinonoid, a ketamine, and, finally, pyridoxamine phosphate (PMP) and the oxo product. The latter is released from the active site and is replaced with the amino acceptor, which then reacts with PMP to produce the desired amino product and re-generate PLP. A variety of high-throughput, enzyme-coupled assays have been employed previously to identify TAs. 33–37 These assays employ other enzymes in addition to the TA to transform amination intermediates into products that can be detected using rapid analytical procedures such as spectrophotometry. Enzyme-coupled assays are quite sensitive but typically necessitate extensive and expensive optimization before they can be deployed for metagenomic screening. 38 As a consequence, we employed a colorimetric assay utilizing o -xylylenediamine (1) as the amino donor to screen novel TAs expressed by an in-house library of E. coli fosmid clones that exhibit activity towards monoaromatic degradation products of lignin. 22 Each fosmid once again ranged between 30- to 50-kilo base pairs in length. The reaction between o -xylylenediamine and the internal aldimine within the active site of a likely TA generates 1 H -isoindole (2) and PMP. PMP remains in the active site and subsequently reacts with the amino acceptor. However, 1 H -isoindole is released into solution, where it tautomerizes to 2 H -isoindole (3). The latter then rapidly polymerizes to yield a black precipitate ( Scheme 1 ). Scheme 1 Overview of the colorimetric assay for high-throughput screening of TAs.",
"discussion": "2. Results & discussion The E. coli fosmid clones were assessed for desired TA activity in 384-well plates. The microcultures were initially propagated in 55 μL LB medium supplemented with 12.5 μg mL −1 of chloramphenicol and 100 μg mL −1 l -arabinose. Chloramphenicol is the antibiotic selection marker whereas arabinose ensures that a defined number of copies of the fosmid are maintained within the bacteria. All solvents and chemicals used in this study were purchased from Sigma Aldrich, Alfa Aesar and Santa Cruz Biotechnologies. The microcultures were allowed to grow at 37 °C for 24 hours, after which they were fed 2 mM of PLP, 25 mM of o -xylylenediamine and 5 mM of the amino acceptor, benzaldehyde (4), and then incubated at 30 °C for an additional 48 hours. At the end of the 48 hour incubation, the plates were imaged from above and the RGB values of the pixel corresponding to the centre of each well were extracted using MATLAB. Eight 384-well plates totalling 3072 fosmid clones were screened in this manner and we successfully identified three primary hits. Hit verification subsequently winnowed the number of confirmed TAs to a single candidate, S2A24, which translates to a hit rate of 0.03% (on a clonal basis) or 1 per 122.9-mega base pairs. This hit rate is significantly higher than the median rate that is observed for functional metagenomic screening. 39 We later picked the S2A24 clone from the original library and extracted its fosmid using a GeneJET plasmid miniprep kit. Sequencing and annotation of the fosmid confirmed the presence of a novel TA and 37 other unique ORFs. The 371-amino acid sequence of the novel enzyme is roughly 15% shorter than and <30% similar to canonical TAs expressed by Pseudomonas putida , 40 Vibrio fluvialis 41 and Chromobacterium violaceum , 35 as well as another TA, pQR1108, that was discovered recently 24 (the multiple sequence alignment has been summarized in Fig. S3 in the ESI or ESI package † ). Nevertheless, the active site and folds of the novel TA aligns quite well with those of previously discovered candidates ( Fig. 1 ). Fig. 1 Structural alignment between the model of the novel TA (prepared by homology modeling using I-TASSER) and the TAs expressed by Pseudomonas putida (PDB code: 3A8U ), Vibrio fluvialis (PDB code: 3NUI ) and Chromobacterium violaceum (PDB code: 4A6R ). We subsequently synthesized the gene that encodes a version of the novel TA bearing a N-terminal polyhistidine tag. Its codons were optimized for expression in E. coli and the gene was later cloned into a high-copy pET-15b plasmid under the control of a T7 transcriptional promoter. Additional details about the molecular cloning have been provided in the ESI. † The resulting plasmid is labelled as pET-TA. This plasmid was then transformed into E. coli BL21 (DE3) using the heat shock method, which involves temporarily exposing the bacteria to 42 °C to permeabilize their cell walls in order to facilitate the delivery of the plasmid into the cells. 42 The transformed cells were cultured on agar plates supplemented with 100 μg mL −1 of ampicillin, and a single colony was later picked and cultured overnight at 37 °C in 5 mL of LB medium also containing 100 μg mL −1 of ampicillin. This overnight culture was subsequently used as the inoculum for a 10 mL culture in the same ampicillin-supplemented LB medium. The latter culture was propagated at 37 °C until it attained an optical density of 0.6, following which isopropyl β- d -1-thiogalactopyranoside (IPTG) was added to the medium and the incubation temperature was lowered to 25 °C. The concentration of IPTG in the medium was 0.5 mM and the cultures were propagated overnight. The cells were then harvested by centrifugation and lysed, and the TA was purified using Qiagen Ni-NTA spin columns. SDS-PAGE confirmed high expression of the enzyme by cultures of the transformed cells that are induced with IPTG (Fig. S2 in the ESI † ). We repeated the o -xylylenediamine assay for 200 μL cultures and lysates of E. coli cells that have been transformed with pET-TA and the S2A24 fosmid. The reactions were conducted in triplicate in a 96-well plate. The culturing and reaction conditions, with the exception of the concentration of o -xylylenediamine, were identical to those of the 384-well plates described earlier. o -Xylylenediamine was supplied at a concentration of either 5 mM or 25 mM. Cultures of E. coli cells transformed with either an empty pET-15b vector or the pET-TA plasmid, but neither of which were supplied with benzaldehyde, were employed as the controls. We observed that the wells harbouring the cell lysates exhibited significantly darker coloration compared to the other wells ( Fig. 2 ). In fact, the lysates of the E. coli cells that had been transformed with pET-TA produced the darkest colour at the end of the 48 hours. We also detected TA activity when the concentration of o -xylylenediamine was reduced from 25 mM to 5 mM. Moreover, the activity is indistinguishable for lysates of the pET-TA cultures and only slightly higher for lysates of the S2A24 clone. However, amination by whole-cell cultures of E. coli transformed with pET-TA and the S2A24 fosmid exhibit marked differences in response to the concentration of o -xylylenediamine, which can be attributed to resistance to transport of the amino donor to the intracellular reaction milieu. Neither control exhibited any TA activity. Although the colour of these reaction mixtures changed, this shift in coloration is attributable to the formation of PMP. 22,38 We also verified the results of the colorimetric assay using HPLC. We added 500 μL of methanol to each mixture to quench the reaction. The samples were then centrifuged and the supernatant was injected into a Water Atlantis C18 column (5 μm, 4.6 mm × 250 mm). A gradient of 10 mM ammonium acetate and acetonitrile (ACN) was employed to resolve the species. The gradient commences with 60% ammonium acetate and 40% ACN, transitions to 100% ACN after 10 minutes, and finally reverts back to 60% ammonium acetate and 40% ACN 20 minutes into the run. Under these conditions, benzylamine, α-methylbenzylamine, benzaldehyde and acetophenone elute at 3.6, 4.2, 7.7 and 8.1 minutes, respectively, and the concentrations of benzylamine in the samples align well with the readouts of the colorimetric screen. Fig. 2 Readout of the 96-well plate o -xylylenediamine assay for the novel TA. Clone A: E. coli transformed with pET-TA but not fed with benzaldehyde; clone B: E. coli transformed with pET-TA; clone C: cell lysate of E. coli transformed with pET-TA; clone D: E. coli transformed with S2A24 fosmid; clone E: cell lysate of E. coli transformed with S2A24 fosmid. With the exception of clone A, which was not provided with any benzaldehyde, all wells are fed with 5 mM benzaldehyde and 2 mM PLP. The volume of each reaction mixture is 200 μL and the plate is maintained at 30 °C and pH 7.5. For reaction conditions 1–3, 5 mM of o -xylylenediamine was supplied to the well. For reaction conditions 4–6, 25 mM of o -xylylenediamine was supplied to the well. The raw image of the plate is included in the ESI. † We then assessed the propensity of the novel TA to employ alternative amino donors. Each reaction mixture comprised ∼1 mg mL −1 of crude lysate of cultures of E. coli transformed with the pET-TA plasmid, 2 mM of PLP, 25 mM of the amino donor ( Fig. 3 ) and 5 mM of benzaldehyde (dissolved in DMSO) in 200 μL of a buffered solution of 100 mM potassium phosphate at pH 7.5. As before, the reactions were monitored colorimetrically for 48 hours, after which the mixtures were analyzed for their benzylamine content using HPLC by following the same methodology for sample preparation as described earlier. Each reaction was performed and analyzed in triplicate. We observed that the enzyme has a strong preference for o -xylylenediamine. The conversion of benzaldehyde when o -xylylenediamine is employed as the amino donor is 42%. In contrast, the use of ( S )-(−)-1-phenylethylamine (18) results in conversion of 10%, and no benzylamine was formed when ( R )-(+)-1-phenylethylamine (19), l -alanine (20), d -alanine (21) and isopropylamine (22) are used as amino donors. We also assessed the potential of the novel TA to aminate other monoaromatic carbonyl compounds that are typically produced by the breakdown of lignin. We used the same reaction conditions as before, but replaced benzaldehyde with other amino acceptors ( Fig. 3 ). After 48 hours had elapsed, the mixtures were vortexed with an equal volume of ethyl acetate and the organic phases were analyzed using GC-MS to determine conversion and confirm 2 H -isoindole formation. GC-MS analysis was performed using an Agilent J&W HP-5ms column (25 m length, 0.20 μm film thickness, 0.25 mm inner diameter). Injector and column conditions have been elaborated in the ESI. † Fig. 3 Amino donors and acceptors evaluated in this study. The TA successfully converted 42% of benzaldehyde, 27% of acetophenone (9), 17% of 4-hydroxybenzaldehyde (5) and 7.5% of cinnamaldehyde (6) into their corresponding amines ( Fig. 4 ). In contrast, the conversion of 4-hydroxy-3-methoxybenzaldehyde (8), 3,4-dimethoxybenzaldehyde (15), and 4-hydroxy-3-methoxyacetophenone (17) was less than 5%, and the enzyme exhibited negligible activity towards the other amino acceptors. Incidentally, we also monitored the reaction mixtures colorimetrically. Benzaldehyde and acetophenone yielded the most intense colour, which is consistent with the GC-MS results. However, the colorimetric assay was not as reliable for the coloured substrates (species 6, 11–14 and 16). This is a known limitation of the assay that needs improvement in order to make it universally applicable for use in functional metagenomic screening of TAs that can functionalize any monoaromatic degradation product of lignin. Fig. 4 Conversions of the amino acceptors considered in this study by the novel TA. Reaction conditions: 5 mM of the individual amino acceptors, 25 mM of o -xylylenediamine and 2 mM PLP in 100 mM potassium phosphate solution buffered at pH 7.5 and maintained at 30 °C. We evaluated the catalytic mechanism of the enzyme using computational modeling. A homology model of the enzyme was constructed using I-TASSER, 43 and the structures of all molecules that participate in the catalytic cycle were prepared in Marvin. 44 We subsequently docked PLP into the active site of the enzyme using AutoDock Vina. 45 The input to the docking calculation comprises an initial set of atomic coordinates for PLP, and the program outputs as many as 9 putative poses of PLP within the active site. A corresponding Gibbs free energy of binding (Δ G ) is also computed for each pose. In order to identify the pose that yields the global minimum for Δ G , we selected the most stable pose and re-used its coordinates as the initial value for a subsequent docking calculation. We iterated this methodology until an unchanging pose was outputted. The docked pose of PLP ( Fig. 5 , Panel 1) aligns exceedingly well with the relative coordinates of PLP in the crystal structures of TAs expressed by Pseudomonas putida (PDB code: 3A8U ), Vibrio fluvialis (PDB code: 3NUI ) and Chromobacterium violaceum (PDB code: 4A6R ), and is in close proximity to the K183 residue of the enzyme. Additionally, the phosphate moiety of PLP is facing outward. This orientation of the phosphate moiety is an important frame of reference for subsequent molecular events. We then used Maestro 46 to generate an aldimine bond between the K183 residue and PLP, as well as add charges to individual atoms in the product. The energy of the structure was subsequently minimized in Maestro. The coordinates of all atoms with the exception of the lysine side chain and PLP were fixed in the energy minimization ( Fig. 5 , Panel 2). Fig. 5 Computational analysis of the catalytic mechanism of the newly discovered TA. We applied a variety of computational tools to simulate the progression of the reaction within the active site of the enzyme. The Gibbs free energy of binding has also been estimated for each pose. Panel 1: binding of PLP within the active site and the close proximity of the K183 residue; panel 2: reaction between the PLP and the K183 residue to form the internal aldimine; panel 3: docking of o -xylylenediamine within the active site of the aldimine-functionalized TA; panel 4: docking of ( S )-(−)-1-phenylethylamine within the active site of the aldimine-functionalized TA; panel 5: docking of ( R )-(+)-1-phenylethylamine within the active site of the aldimine-functionalized TA and confirmation of non-reactivity due to the large distance between its nitrogen atom and the nitrogen atom in the aldimine bond; panel 6: formation of the ketamine intermediate on account of the reaction between o -xylylenediamine and PLP; panel 7: formation of PMP in the active site; panel 8: docking of benzaldehyde within the active site of the TA alongside PMP; panel 9: docking of acetophenone within the active site of the TA alongside PMP; panel 10: docking of 2,6-dimethyl- p -benzoquinone within the active site of the TA alongside PMP. We subsequently docked all the amino donors that were studied previously into the new active site using the same iterative methodology described earlier. Of these, only o -xylylenediamine, ( S )-(−)-1-phenylethylamine and ( R )-(+)-1-phenylethylamine successfully dock within the active site. Moreover, the distances between the nitrogen atom in the aldimine bond and the nearest nitrogen atom of the amino donor that is a key participant in the sequence of steps that culminates with the formation of PMP and the oxo product are 4.9, 5.2 and 6.1 Å for o -xylylenediamine ( Fig. 5 , Panel 3), ( S )-(−)-1-phenylethylamine ( Fig. 5 , Panel 4) and ( R )-(+)-1-phenylethylamine ( Fig. 5 , Panel 5), respectively. This result aligns well with the observed conversions of 42% and 10% for o -xylylenediamine and ( S )-(−)-1-phenylethylamine, respectively, and confirms the non-reactivity of ( R )-(+)-1-phenylethylamine. We then docked the ketamine intermediate of the reaction between PLP and o -xylylenediamine within the active site of the unmodified TA ( Fig. 5 , Panel 6). The calculation suggests that molecular rearrangements within the intermediate cause it to flip its orientation within the active site in a manner such that its phosphate moiety is now facing inward. This prediction is consistent with the expected behaviour of the molecular in response to steric hindrances within the active site, 31,32 as well as the pose of PMP when it has been docked within the active site ( Fig. 5 , Panel 7). Also, the ΔΔ G between the interaction of o -xylylenediamine with the internal aldimine and the interaction of the enzyme with the ketamine intermediate is higher than the corresponding interactions for ( S )-(−)-1-phenylethylamine, which substantiates observed differences in the conversions of the two amino donors. Finally, we docked benzaldehyde ( Fig. 5 , Panel 8), acetophenone ( Fig. 5 , Panel 9) and 2,6-dimethyl- p -benzoquinone (14 and Fig. 5 , Panel 10) into the active site of the TA with PMP already bound within. Interestingly, the docking calculation does not predict any discernible differences in reactivity of benzaldehyde and acetophenone. In this context, we define reactivity as the distance between the amino moiety of PMP and the carbonyl bond in the amino acceptors. However, the observed conversions of benzaldehyde and acetophenone by the enzyme are 42% and 27%, respectively. Differences in conversion may arise due to an increased resistance to diffusion of acetophenone to the active site compared to benzaldehyde or a higher ΔΔ G between the interaction of the enzyme with PMP and benzaldehyde and the interaction of the enzyme with PLP and benzylamine compared to corresponding interactions for acetophenone. The docking calculation also revealed that the distance between the amino moiety of PMP and either carbonyl bond in 2,6-dimethyl- p -benzoquinone is too high for a reaction to occur, which is confirmed by experiments. This suggests that extensive functionalization of the aromatic ring of the amino acceptors introduces significant steric hindrances that greatly impact conversion. Nevertheless, the congruency between experiments and simulation validates the computational analysis that we have implemented to assess the activity of TAs. The computational pipeline is an ideal complement to metagenomics and could be effectively deployed for large-scale in silico screening of enzyme–substrate combinations in order to develop efficient biocatalytic routes for amination of monoaromatic derivatives of lignin for use as pharmaceutical intermediates. Lastly, we also identified the optimal conditions for activity of the novel TA towards the most favoured amino acceptor, benzaldehyde. o -Xylylenediamine was retained as the amino donor and we quantified the conversion of benzaldehyde to benzylamine as a function of temperature, pH, choice of co-solvent and concentration of the amino donor ( Fig. 6 ). The co-solvent is utilized to dissolve benzaldehyde. All reactions comprised ∼1 mg mL −1 of crude lysate of E. coli transformed with the pET-TA plasmid and 2 mM of PLP in a solution of 100 mM potassium phosphate buffer. Each reaction was undertaken in triplicate for 48 hours and had a final volume of 200 μL; and the benzylamine concentration was quantified using HPLC. In order to assess the influence of temperature on enzymatic activity, we added 5 mM of benzaldehyde dissolved in DMSO and 25 mM of o -xylylenediamine to the reaction mixture and maintained the pH at 7.5. The reactions were then undertaken at five temperatures and we observed that the highest conversion of benzaldehyde was obtained at 30 °C ( Fig. 6 , Panel A). In order to investigate the influence of pH, we added 25 mM of o -xylylenediamine and 5 mM of benzaldehyde dissolved in DMSO to reaction mixtures maintained at 30 °C and varied the pH between 6.5 and 9. We observed that the conversion peaked at pH 7.5 ( Fig. 6 , Panel B). Fig. 6 Optimization of reaction conditions for cell lysates for E. coli transformed with pET-TA. All reactions comprised ∼1 mg mL −1 of crude lysate of E. coli transformed with the pET-TA plasmid and 2 mM of PLP in a solution of 100 mM potassium phosphate. Each reaction was undertaken in triplicate for 48 hours and had a final volume of 200 μL; and the benzylamine concentration was quantified using HPLC. The common reaction mixture was suitably modified to deduce the effect of temperature (panel A), pH (panel B), o -xylylenediamine (panel C) and choice of co-solvent (panel D). The activity of the enzyme exhibits canonical behaviour in response to changes in temperature, pH and concentration of the substrate. Each experiment was performed in triplicate and the shaded region denotes the standard error in the measurements. Likewise, the impact of the concentration of o -xylylenediamine on conversion was measured by varying its levels in reaction mixtures comprising 5 mM of benzaldehyde in DMSO and maintained at pH 7.5 and 30 °C. We observed that conversion of benzaldehyde exhibits a hyperbolic response to the concentration of o -xylylenediamine and plateaus near 25 mM ( Fig. 6 , Panel C). The activity of the enzyme exhibits canonical behaviour in response to changes in temperature, pH and concentration of the substrate. Finally, since lignin-derived monoaromatic compounds are poorly soluble in aqueous solutions, we also evaluated several co-solvents for their ability to enhance conversion by improving solubility of benzaldehyde in the reaction mixture. We prepared 10% (volumetric basis) solutions of benzaldehyde in DMSO, acetonitrile (MeCN), isopropyl alcohol (IPA) and methanol (MeOH), and added them to the reaction mixtures to attain a final benzaldehyde concentration of 5 mM. We also directly added benzaldehyde to the reaction mixture without any co-solvent. To our surprise, we observed that the reaction mixture without any co-solvents attained a higher conversion than the mixture that was supplied with benzaldehyde dissolved in IPA ( Fig. 6 , Panel D). The use of DMSO yielded the highest conversion, followed by MeOH and MeCN."
} | 7,309 |
38132503 | PMC10741702 | pmc | 6,626 | {
"abstract": "This article supports the relevance of modeling new bioinspired properties in rate-coding artificial neurons, focusing on fundamental neural properties rarely implemented thus far in artificial neurons, such as intrinsic plasticity, the metaplasticity of synaptic strength, and the lateral inhibition of neighborhood neurons. All these properties are bioinspired through empirical models developed by neurologists, and this in turn contributes to taking perceptrons to a higher potential level. Metaplasticity and intrinsic plasticity are different levels of plasticity and are believed by neurologists to have fundamental roles in memory and learning and therefore in the performance of neurons. Assuming that information about stimuli is contained in the firing rate of the connections among biological neurons, several models of artificial implementation have been tested. Analyzing their results and comparing them with learning and performance of state-of-the-art models, relevant advances are made in the context of the developing Industrial Revolution 4.0 based on advances in Machine Learning, and they may even initiate a new generation of artificial neural networks. As an example, a single-layer perceptron that includes the proposed advances is successfully trained to perform the XOR function, called the Competitive Perceptron, which is a new bioinspired artificial neuronal model with the potential of non-linear separability, continuous learning, and scalability, which is suitable to build efficient Deep Networks, overcoming the basic limitations of traditional perceptrons that have challenged scientists for half a century.",
"conclusion": "5. Conclusions The incipient industrial revolution requires advances in Machine Learning to allow models to mimic the efficiency of biological learning. For this purpose, new engineering models of artificial neuronal structures and learning are a relevant line of research. This paper shows that bioinspiration from new, relevant biological findings can pave the way to this objective. To illustrate this, the author has reviewed the characteristics and results of Konicortex-Like Neural Networks, models that can be trained in an unsupervised and supervised mode, such as associative memory and vector quantization, and show relevant properties such as continuous learning, scalability, and presumed universality of classification. When engineered to solve real multidisciplinary problems using real data, it has produced machines that compete with or improve the state-of-the-art results. A new kind of ANN, called the Competitive Perceptron NN, is finally presented to illustrate how the proposed bioinspired characteristics may drastically improve MLPs and therefore all MLP applications, from the simplest models to the Deep Networks that are presently leading the improvements in Machine Learning and are where the bioinspired improvements presented in this paper can also be implemented at the artificial neuron level.",
"introduction": "1. Introduction It is thought that we are at the beginning of a new industrial revolution, the so-called Industrial Revolution 4.0, in which Machine Learning will play a fundamental role in the development of new powerful intelligent systems to successfully process huge amounts of available information from different users to improve services and associated businesses [ 1 ]. Developing and optimizing machines capable of improving their operation through learning from information contained in data captured from the environment by electronic sensors are key research issues for the upcoming decades. The very concept of Machine Learning is taken from biological beings that adapt to the changing information provided by their senses. A new generation of machines is addressing the most important unsolved problem with artificial neural networks, that is, how to perform unsupervised learning as effectively as the brain [ 2 ]. This leads us to draw inspiration from biological researchers and transfer it to the artificial world of machines with the aim to produce a new generation of artificial neural networks (ANNs) that are necessary for the real development of the new industrial revolution. Presently, the neuroengineering discipline focuses on modeling and applying artificial neural networks (ANNs) that mimic biological neurons and their interconnections, emulating their learning ability. Models are based on neurology research, a discipline that began about one hundred years ago with the studies of Ramón y Cajal [ 3 ], who pointed out that learning could produce changes in the communication between neurons and that these changes could be the essential mechanisms of memory. This property of neurons is now referred to as brain plasticity or Neuroplasticity, or the ability of the brain to modify its connections to produce changes in its communication. Since then, biological research has accumulated an enormous amount of detailed knowledge about the structure and function of the brain. The elementary processing units in the central nervous system are called neurons and are connected to each other in an intricate pattern. Thus far, ANNs have not even come close to modeling the complexity of the brain, but they have been shown to be efficient at problems that are easy for a human but difficult for a traditional computer, such as image recognition and predictions based on past knowledge. The origin of ANNs can be dated back to 1943, when neurophysiologist Warren McCulloch and mathematician Walter Pitts wrote a paper on how neurons might work [ 4 ]. In order to describe how neurons in the brain might work, they modeled a simple neural network using electrical circuits that are called perceptrons. The perceptron is a mathematical model of a biological neuron. While in actual neurons, the dendrite receives electrical signals (inputs) from the axons (outputs) of other neurons, in the perceptron, these electrical signals are represented by numerical values. At the synapses that connect the dendrites and axons, electrical signals are weighted in various amounts. This weighting is also modeled in the perceptron by multiplying each input value by a value called the weight w . An actual neuron activates and fires an output signal only when the total strength of the weighted input signals exceeds a certain activation threshold. This phenomenon is modeled in a perceptron by calculating the weighted sum of the inputs to represent the total strength of the input signals, and the step function f(.) is applied to the sum as an activation function to determine its output. As in biological neural networks, this output is inputted into other perceptrons. After the McCulloch and Pitts perceptron, the first model of synaptic plasticity evolution was postulated by D.O. Hebb in 1949 and is commonly known as the Hebb rule [ 5 ]: “ When an axon of cell A is near enough to excite a cell B and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that A’s efficiency, as one of the cells firing B, is increased ”. Research on perceptrons, with their learning and applications, was popularized in the 1960s and later in the 1980s, with the connection of perceptrons disposed into layers that are called first- and second-generation ANNs, respectively. In second-generation ANNs, so-called Multilayer Perceptrons (MLPs) or feedforward networks can be considered as the simplest but the most powerful artificial model of the biological “brain”, based on the simple model of neuron interconnection in layers (see Figure 1 ). In its structure, we distinguish an output layer of output neurons that will usually be used to recognize classes; if an output is activated, the ANN recognizes the corresponding class as designed. The layer that feeds the output layer is called a hidden layer, which in turn is fed by another hidden neuron layer and so on till the first layer or input layer, which is fed by the input vector. An MLP is then designed by searching a matrix of weights W through an iterative process called training, the objective of which is minimizing the classification error of the universe of input vectors in such a way that when an input data vector feeds the ANN, it activates the output corresponding to the class of the data or corresponds to a desired output. In this last case, the network is applied for functional approximation; that is, the network is trained to perform an arbitrary nonlinear function Y = F (X) of the input vectors. As illustrated in Figure 1 , an MLP is physically composed of layers of aligned simple perceptrons which are fully connected in a feedforward way from layer to layer. The most relevant limitation, linear separability, is associated with each layer in this structure. This means that if we consider the input vector X as a point on a hyperspace, then each perceptron layer only can perform successfully if points are in convex regions limited by hyperplanes. Note that some logic functions such as the Boolean operators AND, OR and NOT are linearly separable problems, i.e., they can be performed using a single perceptron layer. However, not all logic operators are linearly separable. For instance, the XOR operator is not linearly separable and cannot be achieved by a single perceptron layer, since it is impossible to draw a line to divide the regions containing either 1 or 0. Although, even with this fundamental limitation, the perceptron initially seemed promising, it was quickly proven that a perceptron layer could not be trained to recognize many classes of patterns. This caused the field of ANN research to stagnate for many years, challenging scientists. This limitation was finally palliated with the use of more than one perceptron layer arranged in feedforward net with one hidden layer, considerably raising the system complexity, to form the MLP. The first algorithm to train an MLP was called Backpropagation by Rumelhart, Hinton and Williams [ 6 ] and dates to 1986, although the technique was independently rediscovered several times, and had many predecessors dating back to the 1960s. It is a stochastic gradient descent method whose objective function is minimizing a function error like the Mean Square Error (MSE) between the MLP output during learning and the desired output. Three years later, a Russian mathematician called George Cybenko [ 7 ] demonstrated that an MLP consisting of only one hidden layer and composed of an arbitrary number of artificial neurons was able to perform any nonlinear classification or continuous function approximation if the proper weight matrix W was found. Thus, MLPs have since then been referred to as Universal Approximators. In 1990, Ruck et al. [ 8 ] demonstrated that, when modeled by a sigmoidal activation function in [0, 1], the MLP output provides an inherent network estimation of the a posteriori probabilities of the inputs. Such a Multilayer Perceptron can be considered as an approximator to the Bayes Optimal Discriminant Function. The ANNs referred to so far are called rate-coding artificial networks, as they model only the amount of excitation or the rate of short electrical impulses that biological networks receive and produce. These pulses, called action potentials or spikes, have an amplitude of about 100 mV and typically a duration of 1–2 ms. The form of the pulse does not change as the action potential propagates along the axon. A chain of action potentials emitted by a single neuron is called a spike train—a sequence of stereotypical events which occur at regular or irregular intervals. Since all spikes of a given neuron look alike, the form of the action potential does not carry any information. Rather, it is the number and the timing of spikes which matter. The action potential is the elementary unit of signal transmission. Action potentials in a spike train are usually well separated. Even with a very strong input, it is impossible to excite a second spike during or immediately after the first one. The minimal distance between two spikes defines the absolute refractory period of the neuron. The absolute refractory period is followed by a phase of relative refractoriness where it is difficult, but not impossible, to excite an action potential. The effect of a spike on the postsynaptic neuron can be recorded with an intracellular electrode, which measures the potential difference between the interior of the cell and its surroundings. This potential difference is called the membrane potential. Without any spike input, the neuron is at rest, corresponding to a constant membrane potential. After the arrival of a spike, the potential changes and finally decays back to the resting potential. If the change is positive, the synapse is said to be excitatory. If the change is negative, the synapse is inhibitory. At rest, the cell membrane already has a strong negative polarization of about −65 mV. An input at an excitatory synapse reduces the negative polarization of the membrane and is therefore called depolarizing. An input that increases the negative polarization of the membrane even further is called hyperpolarizing. The spikes train resembles a digital transmission, so the exact timing of spikes should play a role. It is important to remember that there is a physical limit on how fast a neuron can fire. The ANNs that model this behavior, that is, those that consider time in their design, are called Spiking Neural Networks (SNNs) and have at least a similar applicability to static ones, although they are usually more difficult to train, showing generally more efficiency in the applications where time plays an important role. Research on SNNs and their learning was popularized in the 1990s, in what is called the third generation of ANNs. ANN structures can be cascaded to form more complex hybrid networks or Deep Networks. In general, neural networks that are capable of tackling more abstract problems by this interconnection or another method are called Deep Learning Networks. They integrate artificial neural systems that are trained together or separately but work together to perform a more sophisticated global task than a single hidden layer or individual networks. Nevertheless, they are also claimed to be bioinspired, as they are structurally more complex, like biological neural networks. Some authors claim that they correspond to the fourth generation of ANNs, as they introduce the novelty of achieving Deeper Learning by physically Deeper Networks, while others just consider them as part of the second generation. Bioinspired neural network models help to understand autonomous adaptive intelligence [ 9 ], and the author of this paper supports that Deeper learning, that is, a higher level of abstraction, will be achieved not only based on more complex networks, but also based on modeling advances from neurologists in the neuron models. This is called Bioinspired Deep Learning, that is, simulating higher-order characteristics of the biological neurons in the node and weight updates of Machine Learning and so achieving a global higher order level of abstraction in performing information extraction on Big Data training sets. Up to now, introductory concepts and definitions briefly summarizing the fundamental state of the art of biological models already successfully implemented have been presented. The main aim of this work is to support the relevance of bioinspiration for the future of these models and therefore of Machine Learning and so too the incipient associated new industrial revolution by modeling advanced neuronal properties in rate-coding ANNs. The selected properties are intrinsic plasticity, metaplasticity and lateral inhibition that allow for competitive learning and performance. The powerful characteristics that they can provide to current ANNs pave the way to a potential new generation of ANNs characterized by overcoming the fundamental limitations of current basic components like classical perceptrons and linear separability. These ANNS are scalable and able to perform continuous learning for deeper, more efficient, and more powerful Machine Learning. The arrangement for the rest of this article is as follows: In Section 2 , the author describes the bioinspired parameters and properties applied to achieve the results in a way that can be easily implemented. In Section 3 , the most relevant implementation results of the bioinspired improvements so far are presented, ending with a novel proposal: the Competitive Perceptron. In Section 4 , a proper discussion is developed, and the conclusions are finally summarized in Section 5 .",
"discussion": "4. Discussion This paper proposes the artificial implementation of three relevant properties of biological neurons to upgrade the characteristics of present rate-coding ANN models: metaplasticity, intrinsic plasticity, and lateral inhibition. Metaplasticity has been shown to drastically improve the training phase of ANNs [ 13 , 14 , 15 , 16 , 17 , 18 ]. It can be implemented not only in MLPs by Equation (1) but also by applying presynaptic rule learning as stated for the KLN and the CP, or even both, as the concept of learning more from infrequent patterns than frequent ones can be applied to any class of rate-coding ANNs as Self Organization Maps (SOMs), Radial Basis Function Networks, or Convolutional Neural Networks [ 29 , 30 , 31 ]. Many other contributions for the further development of brain-like intelligence models can be found by many other approximations that are currently being researched [ 32 , 33 ]. A thorough comparison would be a matter for an extensive review paper [ 34 ]. Intrinsic plasticity is probably responsible for the possibility of continuous learning shown by the KLN, as it avoids the saturation of neuron activation functions and thus the corresponding stagnation of learning. Implementing the concept of a shift in the activation function according to successful or unsuccessful classification is straightforward to generally apply in ANNs, as long as artificial neurons are provided for the activation function. The competitive dynamics that lateral inhibition introduces by implementing WTA competition among neurons mimic natural classification, simplifying the competition and thus contributing to the scalability of the resulting design. The combination of them also incorporates new emerging capabilities, as illustrated by the case of the CP, where the combination of lateral inhibition and intrinsic plasticity allows the Competitive Perceptron to avoid the limitation of linear separability. All these improvements, if transferred to present ANNs, can pave the way to a new generation of neural networks able to come closer to fulfilling the objective of performing unsupervised learning as effectively as the brain, recognized as the current challenge in ANN research by the scientists most involved in the present industrial revolution like Hinton [ 2 ], or at least contribute to it. This is yet to be tested and proven by the researchers that implement them. To support this hypothesis, the Competitive Perceptron, engineered from KLN implementation, is presented; that is, the CP does not model biological reality but it is inspired by its mechanisms. It is a single-layer perceptron that includes the proposed advances with the potential of non-linear separability, continuous learning, and scalability. Thus, it is suitable to contribute to building efficient Deep Networks, overcoming the basic limitations of traditional perceptrons, such as the inefficient scalability and linear separability problems. Its potential and simplicity in comparison with MLPs, which are probably the most applied ANNs and are presently used as the last stage of many Deep Learning Networks, can allow it to improve countless applications where MLPs are being applied successfully. Although this is not proven to be a definitive solution, it is evident that implementing these bioinspired characteristics can improve present designs at the neuronal level. The limits of its implementation in learning and performance are still to be reported by those scientists that study it."
} | 5,048 |
34030445 | PMC8193633 | pmc | 6,627 | {
"abstract": "The cell-surface\nglycocalyx serves as a physiological barrier regulating\ncellular accessibility to macromolecules and other cells. Conventional\nglycocalyx characterization has largely been morphological rather\nthan functional. Here, we demonstrated direct glycocalyx anchoring\nof DNA origami nanotiles and performed a comprehensive comparison\nwith traditional origami targeting to the phospholipid bilayer (PLB)\nusing cholesterol. While DNA nanotiles effectively accessed single-stranded\nDNA initiators anchored on the glycocalyx, their accessibility to\nthe underlying PLB was only permitted by extended nanotile-to-initiator\nspacing or by enzymatic glycocalyx degradation using trypsin or pathogenic\nneuraminidase. Thus, the DNA nanotiles, being expelled by the physiologic\nglycocalyx, provide an effective functional measure of the glycocalyx\nbarrier integrity and faithfully predict cell-to-cell accessibility\nduring DNA-guided multicellular assembly. Lastly, the glycocalyx-anchoring\nmechanism enabled enhanced cell-surface stability and cellular uptake\nof nanotiles compared to PLB anchoring. This research lays the foundation\nfor future development of DNA nanodevices to access the cell surface.",
"introduction": "Introduction and Background The\nglycocalyx is a layer of plasma-membrane-associated biopolymers\ncomposed of proteoglycans, glycosaminoglycans, other glycoproteins,\nand glycolipids and can extend hundreds of nanometers from the external\nsurface of the phospholipid bilayer (PLB). 1 − 4 Through mechanisms, such as steric\nhindrance and electrostatic repulsion, the glycocalyx serves as a\nmolecular barrier that effectively limits macromolecules, particles,\nand other cells from directly accessing the PLB. 1 , 3 , 4 For example, the endothelial glycocalyx\nis an essential determinant of vascular permeability by excluding\nblood cells (such as erythrocytes and leukocytes) and plasma macromolecules\nfrom accessing the underlying endothelium. 5 − 9 Similarly, the apical glycocalyx of the lung and\nintestinal epithelium acts as a selective barrier interfacing with\nthe external environment and modulates epithelial interaction with\nforeign particles and microbes. 10 − 12 The glycocalyx is a dynamic\nstructure undergoing constant remodeling\nin response to environmental stimuli. 13 , 14 Aberrant degradation\nof the endothelial glycocalyx leads to compromised vascular barrier\nfunction and contributes to vascular pathogenesis, such as atherosclerosis, 15 , 16 stroke, 17 , 18 hypertension, 19 , 20 sepsis, 7 , 21 and ischemia reperfusion injury. 22 , 23 Moreover,\nshedding of the epithelial glycocalyx is associated with respiratory\nand intestinal infection, injury, and inflammation. 10 , 11 , 24 , 25 Thus, characterization\nof the glycocalyx barrier integrity is of pivotal importance. The glycocalyx is composed of delicate polymer structures at the\nnanometer scale. Accordingly, transmission electron microscopy (TEM)\nhas long served as the gold standard for glycocalyx characterization. 26 − 29 Alternative glycocalyx visualization uses fluorescent labeling or\nstaining of particular glycocalyx components, albeit at a lower resolution\ncompared to TEM. 30 , 31 However, most of these approaches\nfocus on evaluating the glycocalyx morphology rather than its function.\nMethods for specific assessment of the glycocalyx barrier function\nare limited and generally require sophisticated imaging techniques,\nsuch as intravital microscopy. 1 , 7 , 32 Thus, there is a critical need for technologies to expedite direct\nexamination of the glycocalyx barrier in living samples with high\nsensitivity and reproducibility. Here, we explored the possibility\nof using DNA origami nanostructures\nas a functional measure of cell-surface glycocalyx barrier integrity.\nThe DNA origami forms 2D and 3D nanostructures from the self-assembly\nof approximately 200 short single-stranded DNA (ssDNA), referred to\nas “staple strands”, based on a large ssDNA scaffold.\nFormation of the DNA origami allows highly predictable and reproducible\nassembly of biocompatible structures at the nanoscale and offers convenience\nfor the incorporation of probe labeling (fluorescence and non-fluorescence)\nand sequence-selective targeting. 33 − 37 With the capacity to carry a range of functionalities,\nDNA origami becomes a desirable candidate for assessing glycocalyx\nstructures with thicknesses up to a few hundred nanometers. 38 In this study, we assembled 2D DNA origami\nrectangles or “nanotiles” 34 and examined ssDNA-initiator-mediated targeting\nof origami nanotiles to the cell surface. We found that nanotiles\ncan only reach ssDNA initiators anchored on the glycocalyx but not\nthose inserted directly on the PLB. The exclusion of nanotiles from\nthe PLB by the physiologic glycocalyx was rescued either by using\na technique reported previously by extending the spacing between the\nnanotile and PLB using a DNA duplex bridge 33 or by enzymatic degradation of glycocalyx proteins via trypsin or\nneuraminidase, which is involved in type 2 diabetes, 39 atrial stiffening, 40 , 41 and viral infections. 42 , 43 Our results establish DNA nanotiles as a functional measure of the\nglycocalyx barrier integrity.",
"discussion": "Results and Discussion Flattened\nDNA origami nanotiles of 80 nm × 64 nm were prepared\nusing a single-step annealing protocol using the bacteriophage M13mp18\nssDNA scaffold ( Figure 1 a, Supplementary Figure 1 ). The top surface\nof the nanotile was decorated with up to 28 single-stranded DNA (ssDNA-comp)\noverhangs (each was 20 nucleotides (nt’s) in length), which\nis complementary to the cell-surface-immobilized ssDNA initiators\nfor subsequent nanotile targeting to cells. The bottom surface was\ndecorated with 35 biotin tags for nanotile visualization using fluorescence-conjugated\nstreptavidin. Atomic force microscopy (AFM) imaging of both undecorated\nand fully decorated DNA nanotiles demonstrated effective origami assembly\nirrespective of the decoration ( Figure 1 b, Supplementary Figure 2 ). This was confirmed by gel electrophoresis ( Figure 1 c). Our gel electrophoresis studies further\nconfirmed that DNA nanotiles remained stable for 24 h when incubated\nin PBS (with calcium and magnesium) or Endothelial Cell Growth Media\n(EGM2) ( Supplementary Figure 3 ). Figure 1 Targeting DNA\nnanotiles to glycocalyx-anchored ssDNA initiators.\n(a) Diagram showing the design and decoration of the DNA nanotile\nwith ssDNA-comp overhangs and biotin tags. (b) AFM images of assembled\nDNA nanotiles without decoration and with full decorations (28 ssDNA-comp\noverhangs and 35 biotin tags). (c) DNA gel electrophoresis analysis\nof 2-Log DNA ladder, M13 scaffold, undecorated nanotiles, and fully\ndecorated nanotiles. (d) Azide ligands were metabolically incorporated\ninto glycans within the glycocalyx by administering Ac4ManNAz. These\ncell-surface azide ligands were conjugated with azide-reactive 5′DBCO-ssDNA\ninitiators, leading to covalent immobilization of ssDNA initiators\nonto the glycocalyx, which can then recruit DNA nanotiles via hybridization\nwith the complementary ssDNA-comp overhangs on nanotiles. (e–g)\nssDNA initiators, immobilized on the glycocalyx, were detected through\nits hybridization with the fluorescent, complementary 5′FAM-ssDNA-comp\noligos (e). FAM fluorescence intensity was visualized using microscopic\nimaging (f) and quantified using a spectrometer (g). (h, i) DNA nanotiles\nwith 35 biotin tags and 1, 3, 6, 14, or 28 complementary ssDNA-comp\noverhangs were targeted to glycocalyx-anchored ssDNA initiators. Cell-surface\nnanotiles were visualized via biotin detection using a fluorophore-conjugated\nstreptavidin (red) (h), and the fluorescence intensity was quantified\nusing a spectrometer (i). Data represent means ± s.d. from three\nindependent replicates. ** P ≤ 0.01, *** P ≤ 0.001. To anchor DNA nanotiles directly onto the cell-surface glycocalyx,\nusing human umbilical vein endothelial cells (HUVECs) as a model,\nwe investigated DNA nanotile targeting via the hybridization of glycocalyx-anchored\nssDNA initiators with nanotiles bearing complementary ssDNA overhangs.\nTo install the 20-nt ssDNA initiators onto the cell-surface glycocalyx,\nwe employed bioorthogonal glycocalyx labeling with the copper-free\nclick chemistry. 44 − 46 We first incorporated azide ligands covalently onto\nthe glycocalyx through metabolic glycan labeling using an azido monosaccharide, N -azidoacetylmannosamine-tetraacylated (Ac4ManNAz) ( Figure 1 d and Supplementary Figure 4 ). 46 In parallel, we labeled the 5′-end of ssDNA initiators with\ndibenzocyclooctyne (DBCO) to generate 5′DBCO-ssDNA and quantified\nthe labeling efficiency to be over 90% using a click shift assay ( Supplementary Figure 5 ). 47 This assay detects 5′DBCO-ssDNA via its conjugation with\na PEG-azide (10 kDa) and the corresponding increase in molecular weight.\nConjugation between azide ligands on the glycocalyx with 5′DBCO-ssDNA\nled to covalent anchorage of ssDNA initiators onto the glycocalyx\n( Figure 1 d), which\nwas demonstrated by their hybridization with the complementary ssDNA-comp\noligos bearing a 5′FAM fluorescent tag (5′FAM-ssDNA-comp)\n( Figure 1 e–g). We then targeted DNA nanotiles to ssDNA initiators anchored to\nthe cell-surface glycocalyx ( Figure 1 d). Each DNA nanotile contains 35 biotin tags on its\nbottom surface and different numbers (1, 3, 6, 14, and 28) of ssDNA-comp\noverhangs that are evenly spaced across its top surface ( Supplementary Figure 6 and Supplementary Figure 7 ). Biotin decoration of DNA nanotiles\noffers excellent solubility and allows specific detection of cell-surface-immobilized\nnanotiles through the staining of cell-impermeable streptavidin. We\ninvestigated the quantitative relationship between the number of overhangs\nper nanotile and its cell-surface immobilization efficiency reflected\nby the fluorescence intensity of biotin staining using fluorophore-conjugated\nstreptavidin. Gradual increase in the number of ssDNA-comp overhangs\nper nanotile led to an initial enhancement in cell-surface recruitment,\nwhich plateaued when the number of overhangs increased beyond 6 per\nnanotile ( Figure 1 h,i).\nTherefore, DNA nanotiles decorated with 6 ssDNA-comp overhangs were\nused throughout the rest of the study. Cholesterol modification,\ndue to its affinity to the PLB, is commonly\nused for cell-surface targeting of DNA nanostructures. 33 , 48 To investigate how the anchoring mechanisms of ssDNA initiators\nregulate cell-surface targeting of DNA nanotiles, we compared the\nperformance of ssDNA initiators anchored on the glycocalyx versus\nthose anchored on the PLB. We synthesized a 5′-cholesterol-conjugated\nssDNA initiator, referred to as 5′Chol-ssDNA, and verified\nits PLB targeting using 5′FAM-ssDNA-comp ( Figure 2 a–c). We then examined\nif PLB-anchored ssDNA initiators were capable of binding to DNA nanotiles\nbearing complementary ssDNA-comp overhangs. We found that, although\nssDNA initiators on the PLB can effectively recruit free 5′FAM-ssDNA-comp,\nthey failed to recruit DNA nanotiles with ssDNA-comp overhangs ( Figure 2 a–c). This\nsuggests that ssDNA initiators on the glycocalyx ( Figure 1 h,i) but not those on the PLB\ncan effectively recruit DNA nanotiles to the cell surface. We speculate\nthat this was because the glycocalyx functioned as a nanoscale barrier\nthat through steric hindrance excluded nanotiles from reaching the\nunderneath PLB. To examine this possibility, we engineered DNA nanotiles\nwith extended nanotile-to-initiator spacing by inserting a DNA duplex\nbridge between the nanotile and each ssDNA-comp overhang ( Figure 2 d). We examined DNA\nduplex bridges with a length of 40 and 80 base pairs (bp’s)\nand observed length-dependent rescue of nanotile binding to PLB-anchored\ninitiators ( Figure 2 e,f). This implies that DNA nanotiles but not DNA duplexes can be\neffectively expelled by the cell-surface glycocalyx. Furthermore,\nwe assessed glycocalyx- and PLB-oriented nanotile targeting to two\nadditional cell types, the Chinese hamster ovary (CHO) cells and adenocarcinomic\nhuman alveolar basal epithelial (A549) cells, and observed consistent\nresults compared to HUVECs ( Supplementary Figure 8 , Supplementary Figure 9 ), demonstrating\nthe wide applicability of our findings. Figure 2 Targeting DNA nanotiles\nto PLB-anchored ssDNA initiators. (a) 5′Chol-ssDNA\ninitiators were anchored onto the PLB via hydrophobic interaction\nand used to recruit either 5′FAM-ssDNA-comp oligos or DNA nanotiles\nbearing ssDNA-comp overhangs. (b, c) Detection of the recruited 5′FAM-ssDNA-comp\noligos and DNA nanotiles was performed via fluorescence imaging of\nFAM and biotin staining (b) and fluorescence quantification using\na spectrometer (c). (d) Diagram of inserting DNA duplex bridges of\n40 and 80 bp’s between the DNA nanotile and each ssDNA-comp\noverhang. (e, f) Biotin-based imaging (e) and fluorescence quantification\n(f) of DNA nanotile recruitment to PLB-anchored ssDNA initiators in\nthe presence or absence of the bridges. Data represent means ±\ns.d. from three independent replicates. ** P ≤\n0.01, *** P ≤ 0.001. To further verify whether it was the physiologic glycocalyx that\nexpelled DNA nanotiles from binding to PLB-anchored ssDNA initiators,\nwe explored enzymatic degradation of the glycocalyx proteins ( Figure 3 a). To do this, HUVECs\nwere treated with an augmented regimen of 2.5% trypsin to digest cell-surface\nproteins, an essential constituent of the glycocalyx, and thereby\ncompromise the glycocalyx barrier integrity. As a control, cells were\ntreated with mild trypsin (0.05%) that is commonly used for cell dissociation.\nThrough fluorescence-based biotin staining, imaging, and quantification,\nwe observed trypsin-dose-dependent enhancement of nanotile recruitment\nto PLB-anchored ssDNA initiators in the absence of extended nanotile-to-initiator\nspacing ( Figure 3 b,c).\nThis confirms that the glycocalyx acted as a nanoscale cell-surface\nbarrier that excluded DNA nanotiles from reaching the underneath PLB. Figure 3 Targeting\nDNA nanotiles to PLB-anchored ssDNA initiators following\ndegradation of glycocalyx. (a) Diagram showing our hypothesis of permitted\naccess of DNA nanotile to the PLB following enzymatic digestion of\nthe glycocalyx via trypsin. HUVECs were pretreated with high (2.5%)\nor low (0.05%) concentrations of trypsin before the sequential binding\nof 5′Chol-ssDNA initiators and DNA nanotiles. (b, c) Evaluation\nof nanotile binding to PLB-anchored initiators by fluorescent streptavidin\ndetection of biotin (red, b) and fluorescence quantification (c).\n(d, e) HUVECs were pretreated with 1 U/mL neuraminidase for 1 h before\nthe sequential binding of 5′Chol-ssDNA initiators and DNA nanotiles.\nFluorescence detection (d) and quantification (e) of DNA nanotile\nrecruitment to PLB-anchored ssDNA initiators via fluorescent streptavidin\nwith and without neuraminidase treatment. Data represent means ±\ns.d. from three independent replicates. * P ≤\n0.05, ** P ≤ 0.01. Neuraminidase is a glycocalyx-degrading enzyme that cleaves sialic\nacid residues expressed on cell-surface glycoproteins and glycolipids. 42 , 49 Upregulation of neuraminidase plays a vital role in a variety of\npathological conditions, such as atrial stiffening, type 2 diabetes,\nand viral infections. 42 , 50 Here we examined whether our\nDNA-nanotile-based PLB accessibility strategy had sufficient sensitivity\nto detect glycocalyx damage caused by neuraminidase treatment, which\nis conventionally detected using transmission electron microscopy\n( Supplementary Figure 10 ). We targeted\nthe nanotiles to PLB-anchored ssDNA initiators in HUVECs with and\nwithout pretreatment of 1 U/mL neuraminidase (1 h). 51 Nanotiles without DNA duplex bridges were unable to access\nPLB-anchored initiators in healthy HUVECs but were able to effectively\nreach and get immobilized on the surface of HUVECs injured by neuraminidase\n( Figure 3 d,e). Our\nresults confirm that the physiologic glycocalyx acted as a nanoscale\ncell-surface barrier that excluded DNA nanotiles from reaching the\nunderneath PLB and that the DNA nanotiles can successfully predict\nthe disease-related compromise of glycocalyx barrier integrity. From the cellular engineering perspective, it is of particular\ninterest to understand how cell-surface accessibility regulates the\nadhesion and the assembly between two groups of cells with surface\ndecoration of mutually complementary ssDNA and ssDNA-comp oligos. 44 , 52 , 53 As described above, we observed\nthat nanotile recruitment to the cell surface is regulated by ssDNA-initiator-anchoring\nmechanisms. Here, we investigated its correlation with cell-to-cell\naccessibility in DNA-guided multicellular assembly. 44 , 52 We mixed at a 1:100 ratio of two groups of color-coded HUVECs, with\nsurface decoration of ssDNA (red cells) and complementary ssDNA-comp\n(green cells) initiators, respectively, and examined the formation\nof a red-cell-centered multicellular assembly as a readout of cell-to-cell\naccessibility ( Figure 4 ). Consistent with the cell-surface accessibility to DNA nanotiles\n( Figure 1 h,i), glycocalyx-anchored\nssDNA and ssDNA-comp initiators promoted effective assembly of two-colored\ncell clusters with desired organization ( Figure 4 c), while the PLB-anchored initiators could\nnot ( Figure 4 a). We\npreviously demonstrated that the poor PLB-to-nanotile accessibility\ncan be rescued by double-stranded-DNA (dsDNA)-mediated spacing ( Figure 2 d–f). To assess\nwhether such spacing modulates the assembly process, the green cells\nwere decorated with a new ssDNA(bridge) initiator, followed by hybridization\nwith the 80-bp dsDNA bridge bearing ssDNA-comp and ssDNA(bridge)-comp\n(complementary to the ssDNA(bridge) initiator) on both ends, which\neffectively extended the spacing between the PLB and the ssDNA-comp\ninitiator by 80 bp’s. In parallel, the ssDNA initiator of the\nred cells remained directly anchored on the PLB without any further\nspacing. Indeed, the dsDNA-bridge-mediated spacing in the green cells\nenabled effective assembly of cells bearing PLB-anchored initiators\n( Figure 4 b,e). This\nis again consistent with DNA-duplex-bridge-mediated control of nanotile-to-PLB\naccessibility ( Figure 2 d–f). In parallel, the bridge-mediated spacing did not obviously\nalter the assembly process mediated by glycocalyx-anchored initiators\n( Figure 4 d,e). These\nresults imply that the outcome of particular cell-surface initiator\nconfigurations (anchoring mechanism and spacer length) for cell–cell\naccessibility in multicellular assembly mirrors its outcome for nanotile-to-cell\naccessibility. Thus, we envision that DNA nanotiles can be used to\nassess and optimize the overall cell-surface accessibility prior to\nperforming multicellular assembly in complex tissue and cell engineering\napplications. Figure 4 Cell-to-cell accessibility assessed by multicellular assembly\ndriven\nby cell-surface ssDNA and ssDNA-comp. Two groups of color-coded HUVECs\nwith surface decoration of mutually complementary ssDNA and ssDNA-comp\nwere mixed at a ratio of 1:100 (green:red) for DNA-guided multicellular\nassembly. (a, b) Assembly between cell groups with PLB-anchored ssDNA\nand ssDNA-comp initiators in the absence (a) and presence (b) of the\nDNA duplex bridge on the green cells. (c, d) Assembly between cell\ngroups with glycocalyx-anchored ssDNA and ssDNA-comp initiators in\nthe absence (c) and presence (d) of the DNA duplex bridge on the green\ncells. (e) Quantification of the number of peripheral cells per central\ncell in the resulting assemblies. Data represent means ± s.d.\nfrom three independent replicates. *** P ≤\n0.001. The desirable features of DNA\norigami, such as biocompatibility\nand 3D programmability, make DNA origami an emerging platform for\nintracellular drug delivery. 54 − 56 Following demonstrating glycocalyx-\nand PLB-oriented mechanisms for targeting DNA origami nanotiles to\nthe cell surface, next we investigated and compared the stability\nof the resulting cell-surface-immobilized nanotiles. Cells bearing\nssDNA initiators on their surface were incubated with DNA nanotiles\nfor 30 min, 1 h, or 2 h at 37 °C, which generated more robust\nlabeling compared to incubation at 4 °C ( Supplementary Figures 11 and 12 ). Following each incubation\nperiod, cells were fixed, and the nanotiles remaining on the cell\nsurface and those that had been uptaken by cells were visualized sequentially\nusing a two-step, dual-color staining assay using fluorescence-labeled,\ncell-impermeable streptavidin. In the first step, the far-red-colored\nstreptavidin (Alexa 647) was introduced to label the nanotiles bound\nto the external cell surface. In the second step, cells were permeabilized\nwith Triton-X100, and the green-colored streptavidin (Alexa 488) was\nadministered to label intracellular nanotiles that have been uptaken\nand therefore escaped with the first round of streptavidin (Alexa\n647) binding ( Figure 5 a,b). Figure 5 Cellular uptake and stability of cell-surface-anchored DNA nanotiles.\n(a) Strategy for the two-step, dual-color streptavidin staining of\ncell-surface and uptaken nanotiles. (b) Dual-color detection of cell-surface\n(red) and uptaken (green) nanotiles following 30 min, 1 h, or 2 h\nof incubation. Nanotiles were targeted to the cell surface via glycocalyx-\nor PLB-anchored initiators. (c) Original and postprocessed fluorescence\nimages of the uptaken nanotiles. (d, e) Fluorescence quantification\nof the uptaken nanotiles (d) and those remaining on the cell surface\n(e) over time. Cells incubated with nanotiles in the absence of cell-surface\ninitiators served as the control. Data represent means ± s.d.\nfrom three independent replicates. * P ≤ 0.05,\n** P ≤ 0.01, *** P ≤\n0.001. Next, the uptaken DNA nanotiles\nwere quantified by measuring the\nsignal intensity of the intracellular labeling by streptavidin (Alexa\n488). An image processing pipeline was developed to facilitate background\nsubtraction and signal identification ( Figure 5 c). Comparing the two different nanotile-anchoring\nmechanisms, glycocalyx anchoring led to enhanced cellular uptake at\n30 min, which further increased at 1 h and reached a plateau afterward\n( Figure 5 b,d). In contrast,\nPLB anchoring resulted in less cellular uptake at 30 min, which did\nnot further increase over time ( Figure 5 b,d). To investigate the potential mechanism underlying\nthis difference, we quantified the stability of nanotiles located\nat the external cell surface and observed superior stability of those\nanchored on the glycocalyx over the 2 h period of investigation ( Figure 5 b,e). In contrast,\nthe abundance of nanotiles anchored directly on the PLB via cholesterol\ndecreased over time ( Figure 5 b,e). This is likely because the hydrophobic interaction between\nthe PLB and 5′Chol-ssDNA initiator is non-covalent and reversible,\nwhile the glycocalyx-targeted initiator anchoring is covalent in nature. DNA origami has emerged as a powerful nanotechnology platform for\nsensing and modulating cellular activities. 33 , 37 , 38 , 53 , 57 − 60 It is therefore of particular interest to target\nDNA origami nanostructures directly to the cell surface. Cholesterol\nlabeling has been commonly used for achieving such a purpose, 33 , 61 which directs origami nanostructures to the phospholipid bilayer\n(PLB). Although cell-surface glycoconjugates have been widely reported\nand used for oligonucleotide attachment, 44 , 45 it has not been explored for DNA origami targeting. Here we explored\nthis possibility and compared it with the commonly utilized cholesterol-mediated\ncell targeting, finding that DNA nanostructures anchored directly\non the glycocalyx (via the glycoconjugates) exhibited several unique\nfeatures in terms of accessibility to the cell surface, sensitivity\nto steric hindrance from the glycocalyx itself, cell-surface stability,\nand cellular uptake activity. We expect these findings to expand the\ntoolbox for cellular targeting of DNA nanostructures, in particular\nregarding improving cell-surface and intracellular delivery. Barrier formation at the tissue level is an essential mechanism\nthat prevents uncontrolled passage of molecules, particles, cells,\nand microbes across tissue boundaries. 1 , 3 , 4 This is observed in the endothelium lining the vasculature\nand epithelium lining the lung and intestinal lumen. 5 − 12 Barrier-forming cells not only establish paracellular junctions,\nsuch as tight junctions and adherent junctions, but also use selective\ndeposition of glycocalyx at their luminal surface as a critical apparatus\ncontrolling barrier permeability. 1 , 3 , 4 Aberrant shedding of the luminal glycocalyx is involved\nin a broad range of pathological conditions, such as atherosclerosis,\nstroke, hypertension, infection, and inflammation. 10 , 11 , 15 − 20 , 24 , 25 Despite the critical importance of the glycocalyx in maintaining\nbarrier homeostasis, most current approaches for glycocalyx analysis\ncharacterize its morphology rather than its barrier function. 26 − 31 Here we established DNA origami nanotiles as an effective and sensitive\nmeasure of the minimal thickness of the glycocalyx barrier. The PLB\naccessibility of nanotiles is quantitatively regulated by the glycocalyx\nintegrity and by the length of nanotile-to-PLB spacing. The compromised\nglycocalyx barrier integrity linked to neuraminidase-related diseases\nwas well captured by the PLB accessibility assay of nanotiles in our\nwork. Given the desirable features, such as nanoscale resolution,\nmanufacturing reproducibility, and solubility, the DNA origami is\nan ideal candidate for future development of probes to monitor the\nglycocalyx barrier integrity both in vitro and in vivo . Besides its contribution to tissue boundary\nformation, the glycocalyx\ncoating also regulates cell-to-cell adhesion. Cell-surface decoration\nof mutually complementary ssDNA oligos has been widely used to guide\nprogrammed assembly of dissociated cells via DNA hybridization. Both\nglycocalyx- and PLB-anchored ssDNA oligos have been used to guide\nmulticellular assembly with desired cellular composition and spatial\narrangement. 44 , 52 However, there has been a lack\nof experimentally tractable systems to allow mechanistic interpretation\nof the varied assembly efficiency. Here we showed that the binding\nof DNA nanotiles to cell-surface ssDNA initiators faithfully predicted\nthe ability of these ssDNA initiators to mediate cell-to-cell assembly,\nand therefore offered a quantitative means to optimize ssDNA-anchoring\nmechanisms and spacing to fine-tune multicellular assembly. We also\nexpect our finding to be useful for developing cell therapy applications\nwhere cell-to-tissue accessibility is of critical importance. With the wide range of cargo versatility and programmability, DNA\norigami is being actively pursued for intracellular drug delivery. 62 − 64 Cholesterol-based cell-surface targeting has recently been used\nfor promoting cellular uptake of DNA nanostructures. 48 , 65 Here we showed that, compared to the cholesterol-directed mechanism,\nglycocalyx-based DNA nanotile targeting exhibited not only enhanced\ncell-surface stability but also augmented cellular uptake efficiency.\nOur glycocalyx-based DNA origami targeting utilizes metabolic azide\nlabeling of glycoproteins within the glycocalyx followed by installation\nof ssDNA initiators via the click chemistry conjugation. The feasibility\nof such metabolic azide labeling and bioorthogonal conjugation has\nbeen well documented in cell, tissue, and live organism applications. 46 , 47 , 66 Therefore, our finding offers\nan alternative option for cellular targeting of the DNA origami with\npotential applicability both in vitro and in vivo . In conclusion, our results present compelling\nevidence that establishes\nDNA origami nanotiles as a nanoscale functional measure of the glycocalyx\nbarrier integrity. Our study enables future development of DNA-origami-based\nnanosensors to monitor glycocalyx integrity during dynamic pathophysiological\nprocesses. We also offer an expanded toolbox for cell-surface targeting\nusing DNA origami to modulate intercellular and intracellular activities."
} | 7,045 |
23448304 | PMC3598825 | pmc | 6,628 | {
"abstract": "Background Consolidated bioprocessing (CBP) of lignocellulosic biomass to ethanol using thermophilic bacteria provides a promising solution for efficient lignocellulose conversion without the need for additional cellulolytic enzymes. Most studies on the thermophilic CBP concentrate on co-cultivation of the thermophilic cellulolytic bacterium Clostridium thermocellum with non-cellulolytic thermophilic anaerobes at temperatures of 55°C-60°C. Results We have specifically screened for cellulolytic bacteria growing at temperatures >70°C to enable direct conversion of lignocellulosic materials into ethanol. Seven new strains of extremely thermophilic anaerobic cellulolytic bacteria of the genus Caldicellulosiruptor and eight new strains of extremely thermophilic xylanolytic/saccharolytic bacteria of the genus Thermoanaerobacter isolated from environmental samples exhibited fast growth at 72°C, extensive lignocellulose degradation and high yield ethanol production on cellulose and pretreated lignocellulosic biomass. Monocultures of Caldicellulosiruptor strains degraded up to 89-97% of the cellulose and hemicellulose polymers in pretreated biomass and produced up to 72 mM ethanol on cellulose without addition of exogenous enzymes. In dual co-cultures of Caldicellulosiruptor strains with Thermoanaerobacter strains the ethanol concentrations rose 2- to 8.2-fold compared to cellulolytic monocultures. A co-culture of Caldicellulosiruptor DIB 087C and Thermoanaerobacter DIB 097X was particularly effective in the conversion of cellulose to ethanol, ethanol comprising 34.8 mol% of the total organic products. In contrast, a co-culture of Caldicellulosiruptor saccharolyticus DSM 8903 and Thermoanaerobacter mathranii subsp. mathranii DSM 11426 produced only low amounts of ethanol. Conclusions The newly discovered Caldicellulosiruptor sp. strain DIB 004C was capable of producing unexpectedly large amounts of ethanol from lignocellulose in fermentors. The established co-cultures of new Caldicellulosiruptor strains with new Thermoanaerobacter strains underline the importance of using specific strain combinations for high ethanol yields. These co-cultures provide an efficient CBP pathway for ethanol production and represent an ideal starting point for development of a highly integrated commercial ethanol production process.",
"conclusion": "Conclusions Here we have shown for the first time that the developed extremely thermophilic co-cultures of Caldicellulosiruptor and Thermoanaerobacter are capable of efficiently converting C6- and C5-sugars from cellulose and various pretreated lignocellulosic materials into ethanol, lactate and acetate, ethanol being the major fermentation product. No external enzyme additions were required since the appropriate cellulolytic and hemicellulolytic enzymes were provided by cellulolytic/xylanolytic Caldicellulosiruptor sp. bacteria and by non-cellulolytic/xylanolytic Thermoanaerobacter sp. bacteria. Therefore, these co-cultures are promising for direct fermentation of lignocellulosic biomass to ethanol in a CBP process with operating temperatures above 70°C. In particular the newly identified Caldicellulosiruptor strain DIB 004C provides an unmatched combination of efficient hydrolysis of C5- and C6-sugar polymers derived from lignocellulose, high ethanol production levels and conversion of both C5 and C6 sugars. Therefore, the strain represents an ideal basis for the development of a high temperature lignocellulose to ethanol CBP, either with DIB 004C alone or in a co-culture with one of the newly identified Thermoanaerobacter strains.",
"discussion": "Discussion The objective of this study was to isolate extremely thermophilic bacteria suitable for a single-step conversion of lignocellulosic biomass to ethanol at temperatures >70°C. Cellulolytic ethanologenic enrichments growing at 72°C and producing ethanol as the main fermentation product from crystalline cellulose and pretreated poplar wood were obtained from various environmental samples collected in Germany (Additional file 1 : Table S1). From these enrichments seven cellulolytic strains of the genus Caldicellulosiruptor (Figure 1 ) and eight non-cellulolytic strains of the genus Thermoanaerobacter (Figure 2 ) were isolated, capable of growing at 72°C. All Caldicellulosiruptor strains were capable of fermenting crystalline cellulose, xylan, as well as glucose and xylose, making them suitable for the hydrolysis and fermentation of lignocellulosic substrates. All Thermoanaerobacter strains fermented glucose and xylose and five strains fermented xylan. Fermentation products of all Caldicellulosiruptor and Thermoanaerobacter strains included ethanol, lactate, acetate, H 2 and CO 2 . When Caldicellulosiruptor strains were grown in tubes or flasks without pH control on cellulose, cellobiose, glucose, xylan or xylose, 1–5 mM of ethanol was accumulating in the fermentation (Table 1 and Additional file 1 : Table S2). Surprisingly, the strain Caldicellulosiruptor DIB 004C produced 12.5 mM ethanol from Avicel in flasks with MOPS buffer for pH stabilization. Ethanol concentrations of 71.5 mM (3.3 g/l) and 76.2 mM (3.5 g/l) were obtained when Caldicellulosiruptor DIB 004C was grown on Avicel and glucose, respectively, in pH-controlled fermentors, ethanol being the main product in some fermentation runs. In contrast, all know bacteria of the genus Caldicellulosiruptor produced only traces or low concentrations (up to 2 mM) of ethanol in fermentations performed with pH control [ 16 ] or without pH control [ 17 , 18 ]. The high ethanol concentrations reported were obtained with the wild-type strain Caldicellulosiruptor DIB 004C grown on non-optimized medium under non-optimized cultivation conditions. These values are similar to ethanol levels reported for the most of wild-type strains of the thermophilic cellulolytic bacterium C. thermocellum , an extensively researched candidate for thermophilic CBP: strain ATCC 27405 in fermentor, 86.8 mM (4 g/l) ethanol [ 11 ]; strain LQRI in flasks, 31.2 mM (1.4 g/l) ethanol [ 13 ]; strain DSM 1313 in flasks, 28.2 mM (1.3 g/l) ethanol [ 3 , 8 ]. An exception is the ethanol hyper-producing C. thermocellum wild-type strain I-1-B. The strain produced from cellulose 86.8 mM (4 g/l) of ethanol in flasks on optimized medium with 14 g/l yeast extract after 168 hours of fermentation [ 26 ] and 512 mM (23.6 g/l) of ethanol in fermentors on optimized medium under optimized fermentation conditions after 156 h [ 27 ]. Ethanol was the main fermentation product of five isolated Thermoanaerobacter strains grown without pH control on cellobiose, glucose, xylan or xylose. The ethanol concentrations obtained were higher than those with the well known ethanologenic bacterium T. mathranii [ 20 ] which was used as a control (Table 1 and Additional file 1 : Table S2). Up to 164 mM ethanol was accumulated when Thermoanaerobacter sp. DIB 004G was grown on glucose with pH control. In this respect the isolated Thermoanaerobacter sp. strains were comparable to ethanologenic bacteria of the genus Thermoanaerobacter producing ethanol as the main fermentation product, e.g. T. mathranii subsp. mathranii str. A3 (DSM 11426) capable of producing 20 mM ethanol from xylose [ 20 ], T. ethanolicus JW 200 (ATCC 31550) producing 78 mM from glucose [ 28 ] and T. thermohydrosulfuricus strain E100-69 (DSM 567) producing 29 mM from glucose [ 29 ]. Cellulolytic strains DIB 004C and DIB 101C grew well on insoluble carbohydrates (mainly cellulose) contained in washed pretreated lignocellulosic substrates. At low substrate concentrations, strain DIB 004C utilized up to 89.1% of insoluble cellulose and hemicellulose present in washed pretreated poplar (Table 2 ) and up to 97% of insoluble cellulose and hemicellulose present in washed pretreated spruce, corn cobs and corn stalks (Additional file 1 : Table S4). The ability of novel Caldicellulosiruptor strains to utilize all major carbohydrates from lignocellulosic materials can be attributed to the presence of a large set of extracellular glycoside hydrolases, similar to those found in C. saccharolyticus [ 30 , 31 ] and C. bescii [ 32 ]. At high concentrations of Avicel or pretreated lignocellulosic materials the carbohydrate consumption by cellulolytic strains was not complete. In fermentations without pH control this can be attributed to acidification of the media to pH below 5.0. In pH–controlled fermentations osmotic pressure was shown to affect growth of T. thermosaccharolyticum [ 33 ] and C. saccharolyticus [ 34 ]. Similar to C. bescii [ 32 ], the novel Caldicellulosiruptor strains displayed planktonic growth on Avicel and lignocellulosic substrates. Microscopic examinations revealed that most of the cells were not attached to the substrate particles. This is in agreement with formation of extracellular glycoside hydrolases and enabled to follow growth via cell density measurements. High ethanol production from cellulose and pretreated poplar demonstrated for a number of our extremely thermophilic enrichment cultures could be explained by the synergistic functioning of natural co-cultures of cellulolytic ( Caldicellulosiruptor ) and non-cellulolytic ( Thermoanaerobacter ) bacteria isolated from these enrichments. Fermentations using co-cultures of thermophilic cellulolytic and non-cellulolytic bacteria represent a promising approach for CBP technology and have been investigated at 50°C-60°C with co-cultures of thermophilic Clostridium thermocellum and different species of Thermoanaerobacter or Thermoanaerobacterium [ 7 , 8 , 10 - 13 ]. In these co-cultures, faster cellulose degradation and increased ethanol production was observed, explained by removal of free sugars, produced from cellulose by C. thermocellum , by the non-cellulolytic bacteria [ 13 ]. De-novo constructed dual Caldicellulosiruptor - Thermoanaerobacter co-cultures revealed up to 8-fold increased ethanol yields compared to the monocultures of Caldicellulosiruptor strains (Table 2 and Additional file 1 : Table S3). Ethanol production by co-cultures was strongly dependent on their composition. From 11 different compositions of dual co-cultures grown on Avicel in flasks, the highest ethanol production was obtained with a co-culture comprising Caldicellulosiruptor DIB 087C and Thermoanaerobacter DIB 097X: 13.8 mM ethanol and 34.8 mol% of ethanol fraction within the total organic products (Figure 3 ). In a control experiment, the co-culture of C. saccharolyticus DSM 8903 and Thermoanaerobacter mathranii DSM 11426 displayed the lowest ethanol yield from all co-cultures tested: 3.3 mM of ethanol and 14.7 mol% of ethanol fraction within the total organic products (Figure 3 ). The functionality of co-cultures was also confirmed in pH-controlled fermentations. The ethanol concentration on Avicel in the co-culture of DIB 004C+DIB 004G increased more than 2-fold compared to the monoculture of DIB 004C (Figure 4 ). Growth of the same cultures on unwashed pretreated poplar revealed a 1.4-fold increase in ethanol levels for the co-culture (Figure 5 ). Therefore, the established co-cultures operated similar to the original ethanologenic enrichments, a synergistic effect of the bacteria in co-cultures being apparent. Although the amounts of ethanol produced by novel cellulolytic strains and co-cultures are relatively high compared to other Caldicellulosiruptor and Thermoanaerobacter species, we are currently working on the optimization of strain performance to maximize ethanol levels. Product profiles as well as conversion of pretreated lignocellulosic materials are addressed by classical strain improvement approaches, targeted genetic engineering of the organisms and improved pretreatment methods. The feasibility of genetic modifications of the novel Caldicellulosiruptor and Thermoanaerobacter strains is supported by the recent progress in the development of genetic tools for T. saccharolyticum [ 19 ] and C. thermocellum [ 8 ] in the projects to produce high ethanol yields and the success in genetic manipulation of C. bescii [ 35 , 36 ]."
} | 3,053 |
23178000 | null | s2 | 6,629 | {
"abstract": "The formation of biofilms is initiated by bacteria transitioning from the planktonic to the surface-associated mode of growth. Several regulatory systems have been described to govern the initiation and subsequent formation of biofilms. Recent evidence suggests that regulatory networks governing the decision of bacteria whether to attach and form biofilms or remain as planktonic cells are further subject to regulation by small non-coding RNAs (sRNAs). This is accomplished by sRNAs fine-tuning regulatory networks to enable concentration-specific responses by sequestering, antagonizing, or activating regulatory proteins in response to environmental cues, or by directly affecting the synthesis of proteins promoting or disfavoring the formation of biofilms. This review gives an overview of the contribution of sRNAs in regulating the switch from the planktonic to the sessile bacterial lifestyle by highlighting how sRNAs converge with known regulatory systems required for biofilm formation."
} | 249 |
33072494 | null | s2 | 6,632 | {
"abstract": "Thin liquid films (TLF) have fundamental and technological importance ranging from the thermodynamics of cell membranes to the safety of light-water cooled nuclear reactors. The creation of stable water TLFs, however, is very difficult. In this paper, the realization of thin liquid films of water with custom 3D geometries that persist indefinitely in ambient environments is reported. The wetting films are generated using microscale \"mounts\" fed by microfluidic channels with small feature sizes and large aspect ratios. These devices are fabricated with a custom 3D printer and resin, which were developed to print high resolution microfluidic geometries as detailed in Reference 26. By modifying the 3D-printed polymer to be hydrophilic and taking advantage of well-known wetting principles and capillary effects, self-sustaining microscale \"water fountains\" are constructed that continuously replenish water lost to evaporation while relying on surface tension to stabilize their shape. To the authors' knowledge, this is the first demonstration of stable sub-micron thin liquid films (TLFs) of pure water on curved 3D geometries."
} | 284 |
32655350 | PMC7325709 | pmc | 6,633 | {
"abstract": "In this work, we present a neuromorphic architecture for head pose estimation and scene representation for the humanoid iCub robot. The spiking neuronal network is fully realized in Intel's neuromorphic research chip, Loihi, and precisely integrates the issued motor commands to estimate the iCub's head pose in a neuronal path-integration process. The neuromorphic vision system of the iCub is used to correct for drift in the pose estimation. Positions of objects in front of the robot are memorized using on-chip synaptic plasticity. We present real-time robotic experiments using 2 degrees of freedom (DoF) of the robot's head and show precise path integration, visual reset, and object position learning on-chip. We discuss the requirements for integrating the robotic system and neuromorphic hardware with current technologies.",
"introduction": "1. Introduction Neuromorphic hardware implements the non-Von Neumann brain-inspired computing architecture based on known properties of biological neural networks. This computing architecture features event-based asynchronous processing and fine-grained parallelism of a network of spiking neurons (Indiveri et al., 2009 ; Schemmel et al., 2010 ; Furber et al., 2012 ; Merolla et al., 2014 ; Galluppi et al., 2015 ; Qiao et al., 2015 ; Davies et al., 2018 ; Moradi et al., 2018 ). Neuromorphic hardware not only supports parallel processing; it also enables feedback loops, recurrence, and online adaptation—the key properties of biological brains that lead to flexible and robust behavior. Biological neural systems evolved to solve tasks that are highly relevant to robotics: perception, movement control, action planning, or decision making under uncertainty. Thus, robotics is a promising application domain for neuromorphic hardware (Krichmar and Wagatsuma, 2011 ). Autonomous robots require that computing be performed with low latency and low power consumption, and these are the key characteristics of neuromorphic devices. In this work, we contribute to the emerging field of neuromorphic robotics by presenting a number of design patterns—spiking neural network models—to solve one of the key robotic tasks, state estimation. To be used efficiently, neuromorphic hardware requires a radical rethinking of the computing paradigm. In neuromorphic hardware, we cannot run functions, create conditional loops, or have if-then-else statements in the same way as in conventional software. To use the brain-inspired computing substrate—neurons and synapses—efficiently, we need to abandon the notion of addition and multiplication as elementary computing operations. Even the mere representation of values as binary bit-strings becomes obsolete in a neuronal computing framework. Instead, neuromorphic systems represent the measured physical variables and perform computation using events (spikes) spreading in a neuronal network, as brains do. Thus, in our work, we aim to develop the neuronal computing elements that are required to solve different tasks, seeking to derive principles and structures that can be reused in different domains. Moreover, we show how an interface can be established between the sensors and motors of a robot and neuromorphic representations. Neuronal network-based algorithms currently deliver the most impressive results in computer vision and machine learning and are increasingly being deployed in robotics (Chen et al., 2015 ; Mnih et al., 2015 ). Training spiking neuronal networks (SNNs) using methods developed for deep learning (i.e., error backpropagation) is challenging and currently leads to reduced performance compared to conventional, full-precision DNNs (Shrestha and Orchard, 2018 ; Neftci et al., 2019 ). On the other hand, the neuromorphic hardware supports online learning, i.e., the adaptation of synaptic weights after deployment of the system. When designing our SNN models, we do not rely on tabula-rasa data-driven learning. Instead, we leverage the knowledge of neuronal circuits that solve similar tasks in animals, reserving learning only to parts that depend on the environment with which the robot interacts. This learning can happen in a “shallow” network. Findings in neuroscience have inspired a number of neuronal architectures for addressing the problem of simultaneous localization and mapping (SLAM) (Arleo and Gerstner, 2000 ; Cuperlier et al., 2007 ; Barrera and Weitzenfeld, 2008 ; Weikersdorfer et al., 2013 ; Milford and Schulz, 2014 ; Jauffret et al., 2015 ). SLAM is one of the core problems in mobile robotics (Stachniss et al., 2016 ) but can be generalized to any robotic system that requires state estimation of the robot relative to its environment. In this work, we present a spiking neural network (SNN) implemented on Intel's neuromorphic research chip, Loihi, for pose estimation of the robot's head. The pose is estimated in the SNN based on the “efferent copy” of the motor commands. The estimate is corrected by a visual cue when the robot sees an object multiple times during exploration of an environment. The initial pose, under which the object was seen the first time, is learned in plastic synapses on chip and is used for the visual reset. Estimating the pose by integrating the motor commands is referred to as dead reckoning in robotics and as path integration in biology. In robotics, the head-pose estimation amounts to the camera pose estimation problem (e.g., Scaramuzza and Fraundorfer, 2011 ). The camera pose is estimated using on-board sensors to measure an incremental change in pose, e.g., the visual system itself, a built-in inertial measurement unit (IMU), laser range finder, time of flight camera (Engelhard et al., 2011 ) or sonar (Thrun et al., 2007 ). Fusion of information from multiple sensors is performed to provide a more robust estimate of the pose change. Since integration of movement is prone to error accumulation, such systems need frequent recalibration. The global positioning system (GPS) or external cameras, e.g., Vicon system, help to avoid this problem, but in many cases measuring the ground-truth pose directly is not possible, and the problem becomes one of simultaneous localization and mapping (SLAM). The reference relative to which the pose is measured is itself estimated concurrently with the estimate of the pose (Stachniss et al., 2016 ). Animals can also navigate in large environments by combining a set of “on-board” sensors, i.e., the vestibular and vision system (Burak and Fiete, 2009 ; Seelig and Jayaraman, 2015 ; Green et al., 2017 ; Fisher et al., 2019 ). They combine motion commands and internal sensing in their neuronal systems to provide a motion estimate. Even simple animals, such as insects, show complex navigation behaviors. A brain region called the central complex (CX) appears to be their navigation center (Pfeiffer and Homberg, 2014 ; Turner-Evans and Jayaraman, 2016 ; Heinze, 2017 ). Visual landmarks (Seelig and Jayaraman, 2013 ), rotational optic flow, and non-visual angular velocity cues (Green et al., 2017 ; Turner-Evans et al., 2017 ) were shown to mediate direction coding in CX neurons, suggesting that allothetic and idiothetic cues are continuously integrated to generate a robust representation of body orientation (Honkanen et al., 2019 ). The orientation appears to be encoded in the activity bump of neurons arranged in a ring that corresponds to the 360° of possible directions. These computational principles were uncovered in brains with a size of <100K neurons and were shown to fit small-scale neuromorphic platforms (Dalgaty et al., 2018 ). Orientation-selective Head Direction (HD) cells have also been discovered in rodents. Several models propose attractor networks to account for their selective firing behavior (Skaggs et al., 1995 ; Redish et al., 1996 ). Such attractor networks might self-organize to respond best to the observed sensory information (Stringer et al., 2002 ). These models have been mapped onto brain anatomy, explaining which brain regions might be involved in the encoding of angular velocity signals, the current head direction estimate, and the update mechanism (Goodridge and Touretzky, 2000 ). The detailed mapping of the HD neuronal circuits gave rise to a Spiking Neural Network (SNN) model in which persistent activity is realized through cross-inhibition rather than through recurrent excitation, as previously assumed (Song and Wang, 2005 ). The function of the HD network is to act as a neural integrator that is supervised by visual signals (Hahnloser, 2003 ) and supposedly is calibrated through angular velocity signals (Stratton et al., 2010 ). The vestibular information appears to be critical for generating the directional signal, and landmark information is important for updating it (Taube, 2007 ). Inspired by the biological findings regarding navigation systems of insects and mammals, several computing architectures have been developed to estimate the position under uncertainty and re-calibrate it using familiar landmarks (Skaggs et al., 1995 ; Samu et al., 2009 ; Arena et al., 2013 ; Erdem et al., 2015 ; Seelig and Jayaraman, 2015 ; Heinze et al., 2018 ). An early successful attempt of a bio-inspired SLAM was the RatSLAM model—a biologically inspired SLAM system able to map indoor and outdoor environments (Milford et al., 2004 ). Recently, the original RatSLAM model was extended to function in 3D environments (Yu et al., 2019 ). Loop closure detection was realized based on visual template matching (Gu and Yan, 2019 ), and multi-sensor fusion was shown to provide more accurate odometry and precise cognitive mapping (Zhang et al., 2019 ). Neural networks of grid cells have been shown to perform long-range navigation through path integration in the 2-dimensional plane (Edvardsen, 2017 ), and a model that was established through the Neural Engineering Framework confirms the attractor map implementation of path integration and proposes that the head direction signal can be used to modulate allocentric velocity input (Conklin and Eliasmith, 2005 ). These computational approaches are complemented by approaches toward neuromorphic SLAM, which realized neuronal models in neuromorphic hardware. In this line of research, the formation of a 1D-map was demonstrated on a neuromorphic chip that could perform Bayesian inference using path integration and visual estimate (Tang et al., 2019 ). A model of the bat navigational system was realized in a neuromorphic VLSI device (Massoud and Horiuchi, 2012 ). This architecture includes a head direction ring attractor network (Massoud and Horiuchi, 2011a ) and online correction through learned landmarks that are identified using sonar sensory signals (Massoud and Horiuchi, 2011b ). Similarly, our previous work on neuromorphic SLAM, implemented on a miniature autonomous vehicle, incorporates a 1D head direction ring, 2D map formation, and a loop closure detection mechanism (Kreiser et al., 2018b , c , 2019a ) based on vision. A neuromorphic system that can generate angular velocity and linear acceleration using IMU signals can be used as input to an HD network and was implemented on a VLSI chip to model the vestibular system (Corradi et al., 2014 ). More recently an SNN model was proposed for performing angular velocity regression on event-based visual data (Gehrig et al., 2020 ) that could potentially be used as input to an HD network when implemented in neuromorphic hardware. Up until now, current approaches to neuromorphic implementations have been proofs of concept and either have not been deployed in a real-world scenario using a robotic agent or do not address the issue of scaling and performance under disturbances. In this work, we build on previous implementations for orientation estimation and use the biologically inspired head-direction network (Seelig and Jayaraman, 2015 ; Green et al., 2017 ; Fisher et al., 2019 ) to build an SNN model that estimates the pose of the robot's head through path integration using feed-forward commands and visual landmark detection. Compared to previous work on neuronal path integration, this work scales up the system to a higher resolution of pose representation, applies it to a 2D system of the robot's head, and quantitatively assesses the path integration performance. We realize this model directly and fully in neuromorphic hardware—Intel's research chip, Loihi (Davies et al., 2018 ). We explore the model's function with a humanoid robot, the iCub (Metta et al., 2008 ), in the system designed to enable closed-loop experiments, i.e., the network controlling the robot's movement. The network tracks the movement in two degrees of freedom of the robot's neck. In our experiments, the iCub explores a wall with an object (a dotted pattern) on it by moving its head. Here, we do not use proprioceptive sensors (motor encoders or IMU) to estimate the robot's pose in an SNN; we use only the issued motor commands. This is done because we would like to estimate the precision of path integration in an SNN without mixing it with sensor errors in pose measurement. Moreover, sensors directly measuring the state of a joint are often not available in more complex motor systems or are costly (e.g., force sensors of compliant actuators). Such sensors can always be used to improve state estimation, similar to how vision is used in our model. We use an event-based camera and simple visual preprocessing to estimate the position of an object in the field of view. More sophisticated event-based feature extraction could be used instead (Alzugaray and Chli, 2018 ; Gallego et al., 2019 ), but the visual processing was not our focus. When the object falls in the center of the visual field for the first time, the network stores the current pose of the robot's head, estimated in the network. Each time the object is seen in the center again, the stored pose is activated and used to correct the current pose estimate. The stored pose can also be used as long-term memory for object location and can trigger a goal-directed movement toward the memorized object, even if it is not in view. The paper proceeds with a description of the hardware setup and the hardware and algorithmic interfaces between the robot and the neuromorphic chip. We then explain the SNN model and show results for pose estimation through path integration on-chip and vision-driven object-directed pose learning. We evaluate network performance in terms of the precision of state estimation and discuss how the SNN parameters influence it. Finally, we conclude with a discussion and the positioning of this work in state-of-the-art neuromorphic robotics.",
"discussion": "6. Discussion In this work, we applied elements of neuromorphic SLAM—neuronal path integration, visual reset, and map learning—in the new setting of a humanoid robot observing a visual scene. The main results of this work can be summarized as follows: We have shown that even a small population of spiking neurons can perform precise path integration of motor commands to obtain an estimation of the current pose of the robot's head. The error, compared to path integration in software, accumulated over 120 s of the experiment, was at the resolution of value representation, < 1°, for the network with 100 neurons representing 100°. We have shown how error that is accumulated due to imperfections of the robot (motor commands do not perfectly correspond to executed movements) can be corrected with external sensing, i.e., vision. We have demonstrated online learning of the reference pose in a closed behavioral loop, i.e., with the weight adaptation occurring in parallel to the robot's movements and path integration. Plastic weights are updated in timesteps, in which the learning conditions are fulfilled: the respective pre- and post-synaptic spikes co-occur in the same timestep. These updates can lead to one-shot learning (as shown here). The network can also be configured to require several co-activations of pre- and post-synaptic neurons for the updated weight to have a noticeable effect after the learning increment. We have shown how multiple objects can be stored in the network by adding one “label” neuron per object and a set of N plastic synapses, where N is the size of the head direction network layers ( N = 100 here). We have introduced a number of structural motifs that solve computational tasks involved in path integration and map formation, that is, setting, resetting, and shifting connections and boosting and pre-shaping, as well as input and output interfaces between the non-spiking periphery and the neuromorphic chip. When presenting the SNN model, we paid particular attention to the computing modules that realize important computational primitives that can be reused as building blocks in other tasks and on other neuromorphic hardware. Thus, we hope to contribute to building-up a neuromorphic “instruction set” that will allow us to design neuronal models, in particular for robotic tasks. Such neuronal models can be built using known biological neural circuits, creating a complementary approach to data-driven learning, which can be too costly in learning time and data-preparation effort for some applications. In comparison to previous work on neuromorphic head direction estimation, we evaluate system performance in a real-world task to estimate the 2D head pose of a humanoid iCub robot, particularly emphasizing the required interfaces between different hardware components. We have shown that disturbances can be mitigated by using information of different sensory modalities, and we evaluated how the path integration error relates to scaling of the network. The main contributions of this work that we would like to emphasize are: We use “place code” to represent values (e.g., the angles of the head's pose): we represent values by the identity of the most active neuron (or localized region) in a neuronal population (layer). In particular, taking advantage of Loihi's precise nature, we use “one-hot” and “single-spike” encoding here, making every spike matter in our network. We show an example of combining rate code and place code to represent values in an SNN architecture, and we show how non-spiking sensory input can drive a spiking network. We use recurrent self-excitatory connections to create self-sustained activation in a neuron or neuronal population: an active neuron continues spiking to represent the current estimate of the pose in the SNN, even in the absence of input. This models the working memory of biological neural systems. We propose connectivity patterns between neuronal populations that solve different computational tasks: - mapping activity from one population to another one in a one-to-one or shifted manner; - resetting activity by inhibiting the currently active neuron(s) and activating another/others; - boosting the whole population through one-to-all connections; - providing subthreshold localized input ( preshape ) to create a potentiality for activation, i.e., when boosted, such a preshape can lead to fully-fledged activation. We demonstrate the integration of different modalities: input from one modality (motor command) is integrated into the network to produce the pose, and input from another modality (vision) is mapped onto the network through plastic —learned—synapses. Finally, we demonstrate one-shot online learning of the object-centering pose and how it can be used to generate object-directed gaze. To use the learned pose, we introduced an additional layer that can read out the learned pose without triggering a reset. Thus, we explicitly distinguish the “remembered” and the “currently perceived” object-centering pose representation, modeling different “directions of fit” from the theory of intentionality (Searle and Willis, 1983 ). These elements form the basic algorithmic building blocks for pose estimation and SLAM-like systems in neuromorphic technologies. In this work, we realize the SNN to estimate the pose of a robot's head within two degrees of freedom (yaw-pitch). The error of the head-direction network compared to the integrated velocity commands in software remains below “one neuron” (i.e., an angle corresponding to V thr from Equation 1). Plastic synaptic connections between the yaw-pitch motor space and visually-activated object-neurons in our SNN are learned to store the positions of objects autonomously during operation, i.e., showing online learning. These connections can be used to produce goal-directed head-movements toward stored poses, “looking back” at objects. The stored associations are also used to correct the pose, as the path integration process may be subject to drift (as shown in Figure 6 ). This work also highlights the interfaces that we developed between the iCub robot and the Loihi chip. System integration is an important challenge in robotics in general and in neuromorphic robotics in particular. Our solution is still in a prototype stage but already achieves real-time performance (processing loop of <10 ms). Tighter integration of the hardware system will further improve the system's latency. When combined with a more powerful object recognition system, our pose estimation and learning SNN can be used as a component of an interactive scene representation system for robotic and augmented reality applications."
} | 5,354 |
37485366 | PMC10359879 | pmc | 6,634 | {
"abstract": "Summary Ecological engineering of soil formation in tailings is an emerging technology toward sustainable rehabilitation of iron (Fe) ore tailings landscapes worldwide, which requires the formation of well-organized and stable soil aggregates in finely textured tailings. Here, we demonstrate an approach using microbial and rhizosphere processes to progressively drive aggregate formation and development in Fe ore tailings. The aggregates were initially formed through the agglomeration of mineral particles by organic cements derived from microbial decomposition of exogenous organic matter. The aggregate stability was consolidated by colloidal nanosized Fe(III)-Si minerals formed during Fe-bearing primary mineral weathering driven by rhizosphere biogeochemical processes of pioneer plants. From these findings, we proposed a conceptual model for progressive aggregate structure development in the tailings with Fe(III)-Si rich cements as core nuclei. This renewable resource dependent eco-engineering approach opens a sustainable pathway to achieve resilient tailings rehabilitation without resorting to excavating natural soil resources.",
"introduction": "Introduction Billions of tons of mine tailings are generated annually from extracting and processing of metal and mineral ores, 1 , 2 , 3 stockpiled in about 4,800 mine tailings storage facilities (TSFs), 4 occupying >240,000 ha of land worldwide. 4 Iron (Fe) ore tailings are one of the most challenging global tailings liability, 5 with over 1.4 billion tons of tailings generated each year. 6 These tailings are not only detrimental to the local environment, but they also have a significant CO 2 footprint associated with rehabilitation and mine closure. Moreover, the traditional soil cover methods consume non-renewable natural soil resources and destroy the local soil ecosystem because of the reliance on excavating and transporting large volumes of soil from natural landscapes. Although Fe-ore tailings pose little pollution risks of heavy metals (unlike metal mine tailings, such as Pb-Zn tailings), they are not suitable for direct colonization of soil microbes and plants. This is because of their finely textured and highly compacted physical structure, and adverse chemical properties (i.e., alkaline pH, saline conditions, low organic matter and available nutrients). 7 Past efforts to revegetate tailings have largely failed, because the effectiveness of remediation methods were short-lived, without accelerating pedological processes (e.g., mineral weathering and aggregation) for soil structure and hydro-geochemical stability development in the tailings. 8 A sustainable approach is urgently required to carry out ecological rehabilitation of Fe ore tailings storage dams without secondary damages to natural landscapes for soil excavation. Evidence so far has demonstrated that one way forward is to develop tailings into soil-like substrates (termed herein technosol) with soil structures capable of supporting sustainable vegetation cover. 7 , 9 This approach adopts ecological engineering (eco-engineering) using abiotic and biotic inputs (i.e., organic matter, pioneer plants, soil microbes, and irrigation) within the context of soil pedogenesis. 9 The critical step in this eco-engineering process is to initiate and accelerate formation of functional soil aggregates in the finely textured tailings, for diverse plant colonization. 10 Stable and functional aggregates are key physical units underpinning the development of soil structure for regulating water retention, gaseous exchanges, soil organic matter and nutrient dynamics and biology capacity (e.g., root penetration and microbial colonization). 11 , 12 The formation of soil aggregates involves assemblage of soil clay mineral particles with organic matter in natural soil. 11 Previous studies with natural soil aggregates have emphasized the role of transient organic cements rather than mineral cements in the formation and stability of soil aggregates. 13 , 14 In fact, ferric iron (Fe(III))-rich amorphous minerals have been considered as potentially important reagents contributing to aggregation in natural soil formed from Fe-rich parent lithologies. 15 , 16 Microbes and plants play critical roles in stimulating bioweathering of primary minerals, especially ferrous iron (Fe(II))-bearing phyllosilicates and the generation of amorphous Fe(III) rich secondary minerals. 17 , 18 Iron ore tailings can be treated as engineered parent materials rich in Fe bearing phyllosilicates, such as biotite and amphibole, without risks of heavy metal toxicity. 7 These primary minerals can be weathered to secondary and amorphous Fe(III) rich mineral cements 19 , 20 because of microbial and rhizosphere activities. 19 , 21 These amorphous Fe(III) minerals act as core nuclei for cementing together finely textured mineral particles, adsorbing and sequestering organic carbon, and forming water-stable aggregates. As a result, it is critical to resolve how to initiate and accelerate the generation of amorphous Fe(III) mineral cements for aggregating fine mineral particles and sequestering organic matter into Fe ore tailings. In the present study, we demonstrate stable aggregate development in the Fe ore tailings through an eco-engineering procedure initiated with tolerant microbes and pioneer plants. It was found that the aggregate stability increased with more colloidal Fe(III)-silica (Si) rich amorphous minerals in the tailings. The amorphous Fe(III)-Si cement formation could be stimulated through continuous microbial and rhizosphere driven biogeochemical processes. By comparing the newly formed aggregate structure in tailings with those of native Fe rich soils, we then develop a conceptual model for stable aggregate development resulting from continuous generation and accumulation of Fe(III)-Si rich cement during mineral weathering of the Fe ore tailings. We propose that this process is the critical step toward the development of soil structure for ecological rehabilitation.",
"discussion": "Discussion Biological weathering and transformation of minerals are essential processes in natural soil formation. 28 Here, we demonstrated the key drivers including tolerant microbes and pioneer plants in driving eco-engineered soil formation in Fe ore tailings through early and advanced technosol development. By adding a renewable resource, such as plant biomass, into the tailings, heterotrophic microbes can be stimulated to decompose organic matter, leading to organic acid generation that not only neutralizes alkaline pH conditions in the tailings, but also facilitates the initial formation of aggregates. 21 , 29 The functions of tolerance microbial decomposition of exogenous OM stimulated the early pedogenesis, toward forming “early technosol” that is capable of survival of pioneer plants. The colonizing pioneer plants further advanced the development of “early technosol” toward “advanced technosol” ( Figure 1 ) through rhizosphere biogeochemical processes, 19 , 29 , 30 , 31 leading to improved physical and chemical conditions ( Figure 2 , Table S1 ) for various key stone native plant species colonization. Consistent with expected barriers of the compacted tailings, the aggregate stability was the dominant factor differentiating tailings, technosols, and native soil ( Figure 2 ), highlighting the importance of the aggregate development in eco-engineered tailings-soil formation. Microbial generation of organic cements to initial aggregate formation Microstructural and microspectroscopic analysis of the tailings undergoing “early technosol” formation revealed that organic cementing agents played a key role in initiating organo-mineral interactions and aggregation of tailings particles, as the extensive mineral weathering of Fe-bearing minerals had not yet occurred to generate secondary mineral cements ( Figure 3 ). In the tailings admixed with OM and the soil inoculum, various chemoheterotrophic microbes, that belong to the phyla of Proteobacteria and Firmicutes, developed and attributed as key OM decomposers in the tailings 32 , 33 ( Figure 7 ). These tolerant microbes drove the decomposition of added OM even under the extremely alkaline pH conditions in the tailings, producing various organic acids 34 (rich in aromatic, carboxyl, phenolic groups, Figure 3 I). These acids then initiated pH neutralization and mineral weathering and acted as organic cements for organo-mineral association. 35 , 36 These OC was distributed in a heterogeneous pattern, possibly because of their selective adsorption onto the Fe/Al bearing minerals, which were also randomly distributed ( Figure 3 ). The binding of OC compounds onto minerals under circumneutral pH conditions may have been driven by reactions between the OH groups of Fe/Al-rich minerals with carboxyl, aromatic and phenolic groups, forming polar covalent X- O -C bonds (X = Fe, Al, or Si) 37 or via hydrophobic interactions between hydrophobic organic compounds (e.g., those aromatic, and/or aliphatic dominated organics) and minerals. 38 As illustrated by the layer-by-layer model, 39 the initial association of organics with mineral surfaces functions as a nucleation site for the formation of stable aggregates. 13 However, there was no mineral cements in the adjoining spaces that connecting different mineral particles in the tailings ( Figures 3 D and 3F). Therefore, the aggregates were mainly supported by organic cements in the “early technosol”, which we believe are transitional cements that may undergo rapid microbial decomposition, leading to aggregate dispersion. Generation of colloidal Fe(III)-Si rich cements to enhance aggregate stability After extensive physical, chemical and biological improvements, the resultant “early technosols” would have functions to support the growth of tolerant pioneer plants ( Figure 1 ). All pioneer plants grew well in the “early technosol” ( Figure 1 ), except Sorghum spp. that died because of the possible salt stress resulting from the extensive K dissolution; porewater K concentration increased to around 1000 mg L −1 ( Figure S14 ) during initial weathering of primary minerals. The root activities of colonizing plants would subsequently enhance mineral weathering to form secondary mineral cements for the formation of a new class of more stable aggregates in emerging “advanced technosol” ( Figures 2 and 4 ). The microstructure within microaggregates showed that the secondary mineral phases such as irregular Fe-Si rich minerals, were generated. These, in turn, cemented quartz, biotite and FeOx particles in the “advanced technosols” after plant colonization ( Figure 4 ), leading to the elevated stability of aggregates. These mineral cements were probably amorphous Fe(III)-Si short range ordered (SRO) minerals, which were found to be enriched in colloidal fractions within aggregates ( Figure 5 ). It is reported that the colloidal fraction was small in size (below 1 μm) and high in chemical reactivity with other minerals and organics, 40 , 41 acting as an important constituent of mineral cements for forming aggregates. 42 The Fe(III)-Si rich SRO minerals are considered to have resulted from the co-precipitation of dissolved Fe(III) and Si species ( Figure 9 A) generated from the weathering of primary minerals (such as biotite) in the tailings. 19 , 20 Typically, the Fe(II) cations liberated from weathered minerals may be rapidly oxidized to Fe(III) ( Figure S8 ), to form Fe(III) oxyhydroxide minerals (e.g., ferrihydrite) under circumneutral pH conditions through processes like hydrolysis and polymerization. 43 The co-presence of amorphous/soluble silica hinders Fe(III) mineral polymerization, favoring the formation of Fe(III)-Si rich SRO minerals. 44 This may explain why Fe(III)-Si-SRO were so abundant in the colloidal fraction ( Figure 5 A). These nanosized Fe(III)-Si-SRO minerals have a high affinity for organic molecules, 45 forming close association with organics as nuclei sites to agglomerate other mineral particles (i.e., primary mineral biotite and quartz), leading to the formation of stable aggregate structure. The mixed layered minerals (e.g., illite and smectite) in the non-colloidal fractions of microaggregates ( Figure S6 ), possibly resulting from the solid-alteration of biotite minerals in the tailings, 46 may also partially contribute to the aggregate formation. Figure 9 Diagram showing processes and possible mechanisms underlying rhizosphere driven mineral weathering and Fe(III)-Si mineral formation in Fe ore tailings (A) Eh-pH diagram showing the key geochemical evolution pathways during pioneer plant driven secondary Fe-Si mineral (especially Fe-Si rich short range ordered (SRO) minerals) formation coupled with primary mineral weathering in the advanced technosols. (B) Diagram summarizing plant root driven mineral weathering and secondary colloidal Fe(III)-Si-SRO-OM complex formation. The primary minerals (biotite, amphibole, magnetite) were expected to have undergone microdivision by root effects, forming micro- and nano-sized particles in colloids. These small-sized mineral particles are easily to be dissolved under functions of organic groups exuded by roots, causing the release of Fe 2+ , Fe 3+ , silica, and aluminum, as well as salt elements such as K + , Mg 2+ and Ca 2+ . The salt elements were further taken up by halophyte plants, which stimulated further mineral weathering. The Fe 2+ could be oxidized to Fe 3+ , which would co-precipitate together with silica in the presence of organics under rhizosphere modified geochemical conditions, leading to the formation of Fe(III)-Si-SRO-OM complexes. Note: Bt: Biotite; Amp: Amphibole; Mag: Magnetite; Fh: Ferrihydrite; OM: Organic matter; SRO: Short range ordered minerals. Rhizosphere processes enhancing formation of colloidal Fe(III)-Si-SRO like minerals Plant colonization can influence the mineralogical composition in colloidal fraction via alteration of pH, ionic strength, and/or organic groups in the tailing solutions ( Figure 9 ). The circumneutral to slightly alkaline pH conditions ( Figure S12 ) and the organic acid generation ( Figure S13 ) by root activities facilitated the formation of ferrihydrite or Fe(III)-Si-SRO minerals ( Figure 9 A). 20 It is noted that the initial weathering of biotite like minerals and the rapid release of K and Mg into porewater elevated salinity of the tailings ( Figure S14 ), which could hinder the Fe(III)-Si-SRO formation. 47 However, plant uptake of these elements ultimately lowered porewater ionic strength ( Tables S3 and S4 , Figures S12 and S14 ), which, in turn, would have progressively favored Fe(III)-Si-SRO formation ( Figure 9 B) 19 , 20 and diminished sylvite and aphthitalite minerals in colloidal fraction ( Figure S6 ). In addition, the changes of composition and abundance of individual organic acids (e.g., the increase of acetic acid, Figure S13 ) in the rhizosphere would have enhanced mineral weathering and Fe(III)-Si-SRO formation. 48 The organic functional groups such as aromatic and/or carboxyl groups ( Figure 6 ) may complex Fe cations to form Fe-OM complexes, as has previously been demonstrated in numerous natural and man-made environments. 49 These hindered Fe, Si and Al polymerization, 50 and facilitated the formation of SRO mineral-OM complexes ( Figure 9 B). 51 In sum, the association between SRO minerals and organics acts as nucleus underpinning the formation of water stable aggregates and organic matter stabilization, 14 both of which are fundamental and essential processes leading to soil formation in the tailings. Rhizosphere processes may have also accelerated mineral weathering and amorphous mineral formation through stimulating key microbial development in tailings. Particularly, plant colonization increased the percentage of functional microbes involved in mineral weathering, such as Fe phyllosilicate and/or rock associated bacteria Verrucomicrobiaceae (belong to phlum Verrucomicrobia) 24 and endolithic Ellin6075 (belong to phlum Acidobacteria) 25 at family level ( Figure S17 ), as well as Bacillus spp., Helothiobacillus spp., Solibacillus spp., Streptomyces spp., Geobacter spp., and Thiobacillus spp. 18 ( Table S5 ). These ongoing enrichment of diverse mineral associated microbes in rhizosphere further contributed to the progressive weathering of Fe bearing minerals to form increasing amounts of secondary Fe(III)-Si minerals, advancing aggregate structure development in the technosols. Conceptual synthesis of mineral cements generation and aggregate development in tailing-soil formation The study has demonstrated the development of stable aggregate structure in Fe ore tailings through continuous mineral weathering and amorphous Fe(III)-Si mineral formation which was driven by microbes and pioneer plant root activities. The Fe(III)-Si rich mineral cements are critical to soil aggregate stability, which was also revealed through detailed characterization of mineral makeup, distribution and organo-mineral association in native Fe rich soil (Ferralsol) aggregates from the local Fe-ore mine site ( Figure 8 ). The Fe(III)-Si rich mineral cements in soil aggregates mostly consisted of amorphous Fe(III) oxyhydroxides and Fe(III) bearing 1: 1 aluminosilicates (kaolinite, or halloysite) ( Figures 8 and S18–S20 ), which most likely came from the weathering of primary minerals (i.e., biotite, amphibole) with K and/or Ca depletion. 52 The isomorphic substitution of Al 3+ by Fe 3+ in the phyllosilicate structure could then have caused structural disorder and increased surface area and reactivity of kaolinite. 53 , 54 In addition, amorphous Fe(III) oxyhydroxides may have co-precipitated with secondary 1:1 phyllosilicates (e.g., via electrostatic interactions) to form “gel” like Fe(III)-rich mineral cements. 36 , 55 These Fe(III)-Si rich cements in soil aggregates were found to be mostly in the colloidal fraction ( Figure S23 ), which not only confer strong physical stability, but also provide affinitive surfaces for interactions with carboxylic dominated organics ( Figure 8 L), underpinning organo-mineral association and nucleation sites for aggregate structure development. 39 However, it is important to point out that the proportion of colloidal Fe(III)-Si rich cements in aggregates in the “advanced technosol” (0.4–0.8% w/w) remained much lower than those of native soil aggregates (3.5% w/w). This difference may explain the lower stability of the technosol aggregates than that of native soil aggregates. The aggregate structure and stability development in the tailings may be enhanced by increasing the generation of Fe(III)-Si cements during the eco-engineering processes and the technosol development over the time. From the perspective of natural pedogenetic processes, Fe(III)-Si rich mineral cements in soil aggregates should have formed via the long-term primary mineral weathering driven by continuous plant root and microbial activities. 52 A conceptual model has thus been proposed to demonstrate procedures of aggregate development in the tailings ( Figure 10 ). Figure 10 A conceptual model for eco-engineering stable soil aggregate structure in Fe ore tailings The early aggregates (formed in “early technosol”) could be initiated through microbial decomposition of exogenous organic matter and resultant organics cementation. The transition from early aggregates into advanced aggregates could be achieved through the accumulation of Fe(III)-Si rich cements during mineral weathering and geochemical reactions driven by intensive pioneer plant colonization. Mature aggregates can be progressively formed via long-term biotic and abiotic mediated processes of mineral weathering and Fe(III)-Si rich cements generation and accumulation, which collectively maintain the hydrological and geochemical stability of the aggregates. Briefly, the initial aggregates in “early technosol” can be formed through cementing effects of organic materials derived from microbial OM decomposition, which intimately associate with tailing minerals. The aggregates are progressively consolidated by accumulating Fe(III)-Si rich mineral cements generated from the weathering of primary minerals (such as biotite) and the formation of colloidal Fe(III)-Si short range ordered (SRO) minerals, which are stimulated by ongoing rhizosphere activities of tolerant plants in the developing technosol. Those colloidal Fe(III)-Si SRO minerals would be polymerized into ferrihydrite-Si, goethite and even hematite, during long-term aging. These more stable secondary minerals together with Fe(III)-Si SRO minerals would form new Fe(III)-Si rich mineral cements, serving as reactive sites for association with other mineral particles and organics to enhance aggregate stability under the semi-arid climatic conditions ( Figure 10 ). The development of soil aggregate structure in “advanced technosol” subsequently facilitates the colonization of various plant/microbial communities, from pioneer plant species to diverse keystone plant species, in association with key soil microbes such as mycorrhizal fungi. 56 These plant and rhizosphere microbial activities in the tailings would consistently stimulate the long-term soil aggregate development, through enhancing mineral weathering, Fe(III)-Si rich cements formation and organic matter stabilization ( Figure 10 ). This would lead to a quasi-stable soil-like substrate, with strong and mature aggregate structure for supporting long-term resilient revegetation and ecosystem build-up in the tailing sites. It is important to point out that we have emphasized the key role of bioweathering and secondary Fe(III)-Si mineral cements in the formation of stable soil aggregate structure in Fe ore tailings undergoing soil formation. These secondary Fe(III)-Si minerals in the microaggregates significantly increase OC sequestration, because of their high reactivity and specific surface area. 41 These organo-mineral complexes embedded in microaggregates contribute to the long-term retention of OC. 14 The organo-mineral association formed through interactions of these secondary Fe(III)-Si minerals with functional organics are of critical importance to not only soil structure development, but also the development of biogeochemical functions in the technosols for resilient ecological rehabilitation of tailings landscapes. 57 We have demonstrated the approach to harness biological drivers of tolerant microbes and pioneer native plants as the key soil formation factors in accelerating critical processes of bio-generation of mineral cements (i.e., amorphous Fe(III)-Si minerals) and formation of microaggregates. This process is the key to unlock the barrier to soil formation in the mechanically compacted tailings without functional physical structure. Ecological rehabilitation of large areas of Fe-ore tailings landscapes worldwide requires large volumes of natural soils by excavating natural landscapes, which is not a sustainable option. Our findings have opened a cost-effective and sustainable pathway to achieve ecological rehabilitation of Fe-ore tailings without natural soil, potentially solving the big environmental issues of thousands of hectares of mine tailing sites globally. The merits of environmental and economic sustainability lie in the fact that our approach to eco-engineer tailings into functional soil for supporting revegetation does not require the supply of many millions of cubic meters of natural soil at mine sites for rehabilitating hundreds to thousands of ha of tailings landscape. Furthermore, the access to natural soil supply is beyond the reach of many mine sites, regardless of financial capability. Compared to conventional method by relying on excavated topsoil to construct soil cover, the rehabilitation of Fe ore tailings through the proposed eco-engineering pathway has been estimated to save up to 50–70% of the rehabilitation costs. For instance, in Australia, the current price of natural soil supply from offsite ranges is from $30 to 120/m 3 , including handling and transport expenses, which is translated to the cost of $300,000–1,200,000 per ha if using natural soil to create 1 m soil cover across a tailings landscape. As a result, the translation of this eco-engineering approach in field operations would lead to rapid rehabilitation progress and potential savings worth many billions of dollars, if adopted across the thousands ha of Fe ore mine tailings landscapes worldwide. Our work has proved the concept of eco-engineering of Fe ore tailings into soil-like technosol through a pot experiment under glasshouse conditions. Soil aggregate structure were formed and progressively developed in tailings to support soil functionality during eco-engineering processes driven by tolerant microbial community and pioneer plants. The initial aggregates in “early technosol” contained little Fe(III)-Si cements and were mainly held together by organic cements. Later, rhizosphere biogeochemical processes of pioneer plants induced the generation of colloidal Fe(III)-Si SRO minerals, which sequestrated organic carbon and consolidated the aggregate structure and stability. The importance of Fe(III)-Si rich cements in underpinning aggregate structure was confirmed in native Fe rich soil surrounding the investigated tailing site. Based on these findings, we propose a conceptual model for progressive aggregate structure development in the tailings with Fe(III)-Si rich cements as core nuclei. The eco-engineering process proposed here can be tailored for local resource availability and climatic conditions in future scale-up field trials before adoption at remote mine sites. Limitations of the study In this study, we have demonstrated the approach to employ tolerant microbes and pioneer plants as the key drivers in accelerating in situ mineral weathering and secondary mineral cement formation for aggregate development toward eco-engineered soil formation in Fe ore tailings. The concept has been proved under the short-term glasshouse conditions. However, it is essential to scale up the proof of concept into the operational methodology by conducting long-term broadacre field trials at Fe ore tailings landscape, with consideration of climate and parent material variability across spatial distance and different field operators. Furthermore, because this study was only carried out using the magnetite alkaline Fe ore tailings as an example, it is necessary to investigate the suitability of this approach in eco-engineering soil formation in other tailings, such as hematite Fe ore tailings and Cu tailings."
} | 6,689 |
21365734 | null | s2 | 6,635 | {
"abstract": "Bacteria can coordinate group behavior using chemical signals in a process called quorum sensing (QS). The QS system in the opportunistic pathogen Pseudomonas aeruginosa is largely governed by the LasR receptor and its cognate chemical signal, N-(3-oxo)-dodecanoyl L-homoserine lactone (OdDHL). LasR also appears to share this signal with an orphan LuxR-type receptor in P. aeruginosa, termed QscR, which represses LasR activity. Non-native molecules that modulate QscR would represent valuable tools to study the role of this novel QS repressor protein in P. aeruginosa. We performed a critical analysis of previously identified, non-native N-acylated L-homoserine lactone (AHL) activators and inhibitors of QscR to determine a set of structure-activity relationships (SARs). Based on these SAR data, we designed, synthesized, and screened several second-generation libraries of AHLs for new ligands that could target QscR. These studies revealed the most active AHL agonists and antagonists of QscR reported to date, with activities ranging from nanomolar to low micromolar in a QscR bacterial reporter strain. Several of these AHLs were highly selective for QscR over LasR and other LuxR-type receptors. A small subset of the new QscR activators, however, were also found to inhibit LasR; this demonstrates the exciting potential for the synergistic modulation of these integral P. aeruginosa QS receptors by using a single synthetic compound."
} | 361 |
36595705 | PMC9926230 | pmc | 6,636 | {
"abstract": "Significance Antifreeze proteins (AFPs) are essential for the survival of many cold-blooded species in extremely cold environments. These highly potent proteins can lower the freezing point and inhibit ice recrystallization at very low concentrations, making them interesting for many applications. However, currently, the mechanisms for their activity remain unclear because the interactions of these proteins with ice could not be visualized. Here, we develop nanoscopy below zero degrees to visualize how AFPs interact with ice at the single-molecule level. We observe that tight binding of AFPs at the interface is required for freezing point depression but not ice recrystallization inhibition. By correlating the single-molecule dynamics to activity, we thus find that distinct binding modes underlie the differential activity of different types of AFPs.",
"discussion": "Conclusion and Discussion Here, we adopted SMLM at the ice–water interface to visualize individual AFPs with high spatiotemporal resolution. This allowed us to study the interfacial interactions of AFPs with ice at the single-molecule level. By visualizing the IRI- and TH-active QAE isoform of type III AFP, that has previously been shown to bind irreversibly to ice ( 12 , 32 ) , we were able to resolve that it is not merely irreversibly bound but in fact pinned at a fixed position without the ability to “surf” (i.e., in-plane motion) along the surface regardless of concentration. This observation is consistent with the theoretical description of TH activity by the adsorption-inhibition model ( 9 – 11 ) and provides direct evidence for the central assumption that AFPs pin tightly on ice/water interfaces. Surprisingly, upon imaging the QAE(T18N) mutant that only displayed IRI¸ pinning was lost and the molecules interacted in a highly reversible manner with the ice–water interface. Each interaction now lasted no more than a few tens of milliseconds. These results, therefore, show that reversible adsorption is sufficient for IRI activity, but not for the TH activity of QAE AFP, for which irreversible adsorption and/or pinning appears to be an essential condition. To our knowledge, these highly reversible interactions with ice have not been included in current theoretical models for IRI activity. Similar short-lived, reversible binding events may underlie the activity of more ice binders that display potent IRI but little or no TH activity and should therefore be further investigated. For example, our approach might aid to elucidate the interfacial behavior of antifreeze glycoproteins (AFGPs). These have been shown to bind ice irreversibly at very low undercooling ( 13 ), whereas other simulation and experimental studies have suggested weaker ice binding by AFGPs than type III AFPs and the ability of the proteins to walk/surf along the surface ( 15 , 16 ). Additionally, it could now be investigated whether reversible interactions with ice or interfacial surfing might explain why the widely studied, IRI active polymer, polyvinyl alcohol, does not elicit TH activity. Molecular dynamic simulations have already predicted length-dependent, reversible ice-binding kinetics of this polymer ( 33 – 35 ), which can now be tested experimentally at the single-molecule level. Similar to the ice-binding dynamics of QAE(T18N), our sptPALM experiments showed highly reversible ice binding for HaloTagged- wf AFP. As this AFP did not display any notable TH activity nor crystal growth burst during undercooling at the measured concentrations, these findings are consistent with our hypothesis that reversible interactions are sufficient for IRI. However, interestingly, at higher concentrations, previous studies have found that wf AFP can display TH at about half the activity of wild-type QAE ( 30 ). Simultaneously, other studies hypothesized that this TH activity of wf AFP is due to time-dependent protein rearrangement and/or accumulation at the interface ( 20 ) and that plane selectivity of the various AFPs affects TH dynamics ( 25 ). How concentration- and time-dependent interactions with distinct ice planes vary and underlie different activities, could be an interesting avenue for future studies at the single-molecule level. Additionally, it should be noted that even though we could visualize the highly reversible binding events by wf AFP and the QAE(T18N), which lasted tens of milliseconds, our sptPALM experiments could not resolve the exact dynamics during these events. Resolving the exact moment when these and other IRI-active molecules interact with ice, and upon doing so whether they are shortly pinned or diffuse freely along the surface, could provide further exciting insights to elucidate the underlying mechanisms behind their activity. To achieve this, future work could use even faster sptPALM imaging or the more recently developed MINFLUX technique ( 36 ) in order to resolve these interactions at submillisecond timescales. In summary, here, we establish a nanoscopic strategy to visualize single AFP on ice that offers exciting insights into the interfacial dynamics of AFPs at the single-molecule level. We anticipate that this approach will be widely applicable to better understand how adsorption and interfacial dynamics can vary and underlie the differences in activity of the large variety of structurally diverse natural and synthetic ice binders. This will greatly advance our understanding of the antifreeze mechanisms and will facilitate the development of engineered ice binders with activities tailored for optimal performance in complex environments."
} | 1,397 |
40242661 | PMC12002889 | pmc | 6,637 | {
"abstract": "Microbial production of bicyclic monoterpenes is of great interest because their production primarily utilizes non-sustainable resources. Here, we report an engineered Saccharomyces cerevisiae yeast that produces bicyclic monoterpenes, including borneol, camphor, and bornyl acetate. The engineered yeast expresses a bornyl pyrophosphatase synthase from Salvia officinalis fused with mutated farnesyl pyrophosphate synthase from S . cerevisiae and two mevalonate pathway enzymes (an acetoacetyl-CoA thiolase/hydroxymethylglutaryl-CoA [HMG-CoA] reductase and an HMG-CoA synthase) from Enterococcus faecalis . The yeast produced up to 23.0 mg/L of borneol in shake-flask fermentation. By additionally expressing borneol dehydrogenase from Pseudomonas sp. TCU-HL1 or bornyl acetyltransferase from Wurfbainia villosa , the engineered yeast produced 23.5 mg/L of camphor and 21.1 mg/L of bornyl acetate, respectively. This is the first report of heterologous production of camphor and bornyl acetate.",
"conclusion": "4 Conclusions In this study, we established a microbial platform to produce borneol, camphor, and bornyl acetate using the yeast S. cerevisiae . To this end, we engineered yeast strains to express the rate-limiting enzymes ( Ef MvaE and Ef MvaS) and the fusion enzyme of BPPS and Erg20p WW with and without Ps BDH or Wv BAT4. This study is the first report of yeast production of camphor and bornyl acetate. Although the concentration of borneol produced was comparable to that of a previously reported yeast strain ( Ma et al., 2022 ), overlaying IPM onto the medium improved borneol production by 1.7-fold, leading to the highest borneol titer in a shake flask reported for the yeast S . cerevisiae . Nevertheless, the borneol production was 4-fold lower than that reported for E . coli ( Lei et al., 2021 ). Further improvement in production could be achieved by combining the modulation of competitive pathways ( Paddon et al., 2013 ; Hull et al., 2014 ; Peng et al., 2017 ; Broker et al., 2018 ; Zhou et al., 2021 ; Tominaga et al., 2022 ; Wei et al., 2024 ), protein engineering to improve the enzymatic activity of BPPSs ( Lei et al., 2021 ), amplification of the gene copy number of rate-limiting enzymes ( Peng et al., 2022 ), and enzyme compartmentalization ( Cheah et al., 2023 ). Evolutionary engineering for the production of borneol and camphor can be performed using recently developed genetically encoded biosensors that respond to borneol or camphor ( Ikushima et al., 2015 ; Ikushima and Boeke, 2017 ; Tominaga et al., 2021 ; D'oelsnitz et al., 2022 ). Finally, a high-throughput platform could be developed to facilitate mutational analysis of various plant BDHs ( Lin et al., 2023 ) and investigate their properties, such as product specificity ( Hofer et al., 2021 ; Ma et al., 2021 ; Hu et al., 2022 ).",
"introduction": "1 Introduction Bicyclic monoterpenoids, including borneol, camphor, and bornyl acetate, are used in traditional herbal medicine by leveraging their biological activities, which include anti-inflammatory, analgesic, antibacterial, antitumor, and anti-anxiety effects, and they are also used in fragrances and cosmetics ( Ma et al., 2023 ). These monoterpenes are commercially available and can be extracted with high enantioselectivity from natural sources (e.g., Cinnamomum burmanni and Blumea balsamifera for borneol [ Li et al., 2022 ], Cinnamomum camphora for camphor [ Zhou and Yan, 2016 ], and Amomum villosum , Inula graveolens , and Tetraclinis articulata for bornyl acetate [ Zhao et al., 2023 ]). However, the supply chains of these products are unstable due to limited space for plant cultivation and low yield. Although racemic borneol and camphor can be chemically synthesized from α-pinene, a major constituent of turpentine oil ( Ponomarev and Mettee, 2016 ), this process produces a toxic by-product, isoborneol, which may causez1 serious side effects. Furthermore, chemical synthesis of these compounds uses harmful catalysts, such as heavy metals ( Ponomarev and Mettee, 2016 ). Thus, alternative methods to sustainably produce these monoterpenes are needed. Borneol, camphor, and bornyl acetate are naturally biosynthesized in the plants via the isoprenoid pathway, as follows ( Fig. 1 ). Isoprenyl-pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP) are produced via the mevalonate pathway and condensed into geranyl-pyrophosphate (GPP) by farnesyl pyrophosphate synthetase, Erg20p. GPP is then further circularized to bornyl-pyrophosphate (BPP) by BPP synthase (BPPS), and BPP is dephosphorylated into borneol. Borneol dehydrogenase (BDH) and bornyl acetyltransferase (BAT) convert the resultant borneol into camphor and bornyl acetate, respectively. Fig. 1 Biosynthetic pathway of borneol, camphor, and bornyl acetate reconstituted in the yeast S . cerevisiae . Heterologous enzymes are indicated in bold type. Fig. 1 BPPSs are found in a diverse array of plants, including B. balsamifera , C. burmanni , A. villosum , Lavandula angustifolia , Salvia officinalis , and Lippia dulcis ( Despinasse et al., 2017 ; Wang et al., 2018 ; Ma et al., 2022 ). BDHs are found in plants ( C. camphora [ L .] Presl ) ( Ma et al., 2021 ) and bacteria ( Pseudomonas sp. strain TCU-HL1) ( Tsang et al., 2016 ). More recently, a plant BAT was identified for the first time in Wurfbainia villosa (homotypic synonym, A. villosum ) ( Liang et al., 2022 ). Microbial production of borneol by heterologous expression of plant BPPSs has also been reported. An engineered Escherichia coli strain reportedly produced 87.20 mg/L borneol in shake-flask fermentation ( Lei et al., 2021 ), whereas an engineered strain of the yeast Saccharomyces cerevisiae produced 12.68 mg/L and 148.59 mg/L borneol in a shake flask and 5-L bioreactor, respectively ( Ma et al., 2022 ). However, borneol productivity remains far below the level needed for practical use, and microbial production of camphor or bornyl acetate has not been reported to date. To establish a microbial platform to produce borneol, camphor, and bornyl acetate, we metabolically engineered the yeast S . cerevisiae , including engineering the heterologous expression of mevalonate pathway enzymes and a fusion enzyme between BPPS and an Erg20p mutant, with and without BDH or BAT.",
"discussion": "3 Results and discussion To generate a yeast strain that produces borneol, the gene encoding BPPS without the N-terminal plastid-localization sequence (2–49 residues) from S. officinalis ( So BPPS, GenBank: AAC26017.1 ) was codon-optimized for yeast ( Supplementary Table 1 ) and fused to the mutated ERG20 gene from yeast, which encodes mutant Erg20p with high GPP synthesis activity (Erg20p F96W−N127W , Erg20p WW ), thereby enabling the efficient substrate channeling ( Ignea et al., 2014 ) toward BPP. The resulting fusion gene was cloned into the yeast integration vector so that the BPPS gene could be expressed from the strong TDH3 promoter. In addition, the genes encoding acetoacetyl-CoA thiolase/hydroxymethylglutaryl-CoA (HMG-CoA) reductase and HMG-CoA synthase from Enterococcus faecalis ( Ef MvaE and Ef MvaS, respectively), which convert acetyl-CoA into mevalonate to produce more terpenoids in both E . coli ( Tsuruta et al., 2009 ; Yoon et al., 2009 ) and the yeast S . cerevisiae ( Peng et al., 2017 ), were also cloned into plasmid pATP403red ( Tominaga et al., 2021 ). The resulting plasmids were successively integrated into the chromosome of the yeast strain ScKZ014 derived from strain BY4741 ( Brachmann et al., 1998 ), which harbors a borneol-responsive transcription activator and reporter plasmid for the in vivo sensing of borneol ( Supplementary Fig. 1 and Supplementary Note 1), thereby generating yeast strain ScKZ045 ( Supplementary Fig. 2 ). When this strain was incubated in YPD medium, the concentration of borneol in the medium increased after 24 h and peaked at 72 h, reaching 13.6 mg/L before gradually decreasing ( Fig. 2 A and Supplementary Fig. 4 ). Note that the borneol concentration was >3-fold higher than that produced using the strain lacking expression of Ef MvaE and Ef MvaS ( Supplementary Fig. 5 ). To convert borneol into camphor and bornyl acetate, two strains were constructed that additionally express borneol dehydrogenase from Pseudomonas sp. TCU-HL1 ( Ps BDH, GenBank: AOE86728.1) and bornyl acetyltransferase from W. villosa ( Wv BAT4) ( Liang et al., 2022 ). To do so, codon-optimized PsBDH and WvBAT4 ( Supplementary Table 1 ) were additionally cloned into the expression vectors for Ef MvaE and Ef MvaS and integrated into yeast strain ScKZ045, generating strains ScKZ048 and ScKZ046, respectively ( Supplementary Fig. 3 ). These strains successfully produced camphor and bornyl acetate ( Fig. 2 B and C, and Supplementary Fig. 4 ) and exhibited the same time-course for borneol production. The concentrations of camphor and bornyl acetate reached 12.4 and 5.00 mg/L at 72 h, respectively, and then decreased. Borneol, camphor, and bornyl acetate are highly volatile. For instance, >20 % of borneol is lost from the medium after 48 h of incubation ( Lei et al., 2021 ), which may contribute to the observed decrease in monoterpene production after 72 h. To minimize the loss of volatile monoterpenes from the fermentation medium, we performed two-phase fermentation by adding IPM to the medium ( Fig. 2 D–F). IPM was added at a final concentration of 10 % (v/v), and cultivation was carried out by vortexing, followed by removal of an aliquot from the organic phase for analysis. As expected, the maximum concentrations of borneol, camphor, and bornyl acetate increased by 1.7-fold (23.0 mg/L at 96 h, Fig. 2 D), 1.9-fold (23.5 mg/L at 120 h, Fig. 2 E), and 4.2-fold (21.1 mg/L at 120 h, Fig. 2 F), respectively. Note that the growth of all yeast strains was enhanced slightly by the addition of IMP, possibly because the toxic effects of the monoterpenes were reduced by extracting the compounds into the IPM phase ( Brennan et al., 2012 ). Approximately 5 mg/L of borneol remained in the medium when producing bornyl acetate ( Fig. 2 F) but not when producing camphor ( Fig. 2 D), indicating that the enzymatic activity of Wv BAT4 is weaker than that of Ps BDH."
} | 2,571 |
30888185 | null | s2 | 6,638 | {
"abstract": "Three seemingly distinct directions of nanomaterials research, photovoltaics, biofuel production, and biological modulation, have been sequentially developed over the past several decades. In this Mini Review, we discuss how the insights gleaned from nanomaterials-based solar energy conversion can be adapted to biointerface designs. Because of their size- and shape-dependent optical properties and excellent synthetic control, nanomaterials have shown unique technological advantages as the light absorbers or energy transducers. Biocompatible nanomaterials have also been incorporated into biological systems including biomolecules, bacteria, and eukaryotic cells for a large collection of fundamental studies and applications. For the photocatalytic biofuel production, either isolated bacterial enzymes or the entire bacteria have been hybridized with the nanomaterials, where functions from both parts are synergistically integrated. Likewise, interfacing nanomaterials with eukaryotic systems, whether in individual cells or tissues, has enabled optical modulation of cellular behavior and the construction of active cellular materials. Here we survey different approaches in which nanomaterials are used to elicit electrical or mechanical changes in single cells or cellular assemblies via photoelectrochemical or photothermal processes. We end this Mini Review with the discussion of future nongenetic modulation at the intracellular level."
} | 362 |
38470918 | PMC10962991 | pmc | 6,641 | {
"abstract": "Significance In this paper, we describe a very different architecture for complex computations. It is a step in the direction of modeling and experimentally demonstrating a highly interactive system which we think more represents the functioning of our brains. We bring together the properties of superconducting loops linked together with Josephson junctions and the physics of disordered structures. The information is transmitted via superconducting magnetic vortices transmitted between loops through junctions and the delocalized long-range coherence is assured by the superconducting properties. The disorder of the constituent loops offers an exponentially increasing density of configurational states resulting in static and dynamic memory. We have shown both by modeling and experiment that this circuit has intrinsic associated memory: a prerequisite for cognition."
} | 218 |
27142075 | PMC4855977 | pmc | 6,642 | {
"abstract": "Background Given its high surplus and low cost, glycerol has emerged as interesting carbon substrate for the synthesis of value-added chemicals. The soil bacterium Pseudomonas putida KT2440 can use glycerol to synthesize medium-chain-length poly(3-hydroxyalkanoates) (mcl-PHA), a class of biopolymers of industrial interest. Here, glycerol metabolism in P. putida KT2440 was studied on the level of gene expression (transcriptome) and metabolic fluxes (fluxome), using precisely adjusted chemostat cultures, growth kinetics and stoichiometry, to gain a systematic understanding of the underlying metabolic and regulatory network. Results Glycerol-grown P. putida KT2440 has a maintenance energy requirement [0.039 (mmol glycerol (g CDW h) −1 )] that is about sixteen times lower than that of other bacteria, such as Escherichia coli , which provides a great advantage to use this substrate commercially. The shift from carbon (glycerol) to nitrogen (ammonium) limitation drives the modulation of specific genes involved in glycerol metabolism, transport electron chain, sensors to assess the energy level of the cell, and PHA synthesis, as well as changes in flux distribution to increase the precursor availability for PHA synthesis (Entner–Doudoroff pathway and pyruvate metabolism) and to reduce respiration (glyoxylate shunt). Under PHA-producing conditions (N-limitation), a higher PHA yield was achieved at low dilution rate (29.7 wt% of CDW) as compared to a high rate (12.8 wt% of CDW). By-product formation (succinate, malate) was specifically modulated under these regimes. On top of experimental data, elementary flux mode analysis revealed the metabolic potential of P. putida KT2440 to synthesize PHA and identified metabolic engineering targets towards improved production performance on glycerol. Conclusion This study revealed the complex interplay of gene expression levels and metabolic fluxes under PHA- and non-PHA producing conditions using the attractive raw material glycerol as carbon substrate. This knowledge will form the basis for the development of future metabolically engineered hyper-PHA-producing strains derived from the versatile bacterium P. putida KT2440.",
"conclusion": "Conclusion Overall, our results support the view that P. putida KT2440 has evolved to high metabolic versatility by a complex interplay of different molecular layers. This applies not only for the shift from carbon to nitrogen limitation, but also for a given specific growth rate, especially important, when cells are synthesizing PHAs. This study unravels that the Entner–Doudoroff and the glyoxylate pathways, and pyruvate metabolism play a key role when synthesizing mcl-PHA from glycerol as the only carbon and energy source. In addition, P. putida KT2440 modulates the expression of genes responsible for sensing its energetic state of the cell in order to satisfy the ATP requirement under PHA-producing conditions. Predictive metabolic modeling shows that there is still huge potential for improvement of mcl-PHA synthesis, where different metabolic engineering targets are proposed. In this way, genes belonging to the TCA cycle, ED pathway, and the synthesis of de novo fatty acids are identified as promising targets for genetic engineering towards improved PHA synthesis.",
"discussion": "Discussion Low energy requirement of P. putida for maintenance enables versatile metabolic response Impressively, the maintenance requirement of glycerol-grown P. putida KT440 is 16 times lower in comparison to E. coli and 20–25 times lower than that of other important strains grown on glycerol [ 46 , 47 ] (Table 6 ). In addition, the maintenance coefficient was 1.5 times lower than that of P. putida growing on glucose and approximately ten times lower than that of several other glucose-grown industrial strains. As glycerol has a higher degree of reduction than glucose and produces twice as much reducing equivalents, when converted to phosphoenolpyruvate [ 48 ], it seems a straightforward substrate for the production of redox-demanding chemicals through fermentation processes. Moreover, glucose is not the preferred carbon source of strains belonging to the Pseudomonas genus [ 49 , 50 ], making glycerol an attractive raw material for P. putida production processes. Several studies have attempted to reduce the carbon requirement for cell maintenance. Particularly, attention has been poured into industrial strains such as Bacillus subtilis [ 51 ], Corynebacterium glutamicum [ 52 ], and Escherichia coli [ 53 ]. Strains with a low maintenance coefficient can redirect more carbon towards a desired product, which is of utmost importance in white biotechnology as maintenance plays a key role under reduced growth rates [ 54 ]. Moreover, the maintenance requirement varies over time [ 54 ], thus having direct impact on the economics of the industrial process, particularly when operating the preferred fed-batch cultivation mode [ 55 ]. The ED pathway is favored under both carbon and nitrogen limitation As previously reported, nitrogen limitation promotes synthesis of PHA in P. putida [ 1 ]. A similar phenomenon has been observed for metabolically engineered E. coli strains able to accumulate PHB on glucose [ 56 ]. This modulation of the PHA flux has been related to several factors including (i) NADPH supply [ 57 ], (ii) activity of enzymes of the PHA pathway [ 56 ], and (iii) precursor availability [ 15 , 58 ]. In this study, preferential use of the ED pathway and glyoxylate shunt was associated with increased PHA-production (Fig. 2 ). Particularly, recycling of resources through the upper EMP pathway, instead of channeling carbon directly through the lower EMP pathway, was associated with increased cofactor and PHA-precursor availability and thus a higher PHA biosynthetic flux. Conversely, this yielded less ATP, indicating that PHA production is constrained to a greater extent by cofactor and precursor availability than by ATP-deficiency. Additionally, the preferential use of the glyoxylate shunt, instead of the reductive TCA cycle between isocitrate and succinate, decreased the loss of carbon to CO 2 , however less reductive power could be generated. Therefore, it seems that PHA synthesis in P. putida under nitrogen-limitation is mainly constrained by precursor-availability. This also fits nicely with the predicted targets for improved PHA production (Fig. 4 ). The recycling of resources through the upper EMP pathway and ED pathway promotes PHA synthesis, whereas the reductive TCA-cycle is predicted to influence PHA synthesis adversely. In this regard, it is important to make a clear distinction among metabolic routes fueling PHA synthesis, as each of these pathways yields a specific amount of NADPH and PHA precursors. For instance, C. necator and metabolically engineered E. coli strains both possess a complete EMP and PP pathway. Additionally, the former has an active ED pathway, which works in conjunction with the EMP and PP pathway to yield pyruvate and acetyl-CoA. In this case, improved production of PHB has been achieved by re-directing the carbon flux through the PP pathway instead of the EMP pathway [ 59 , 60 ]. As more NADPH is produced by the former strain, an increase in cofactor availability led to an improved synthesis of PHB. As P. putida does not have a complete EMP pathway [ 61 ], we have previously proven that overexpression of genes of the PP pathway does not improve PHA synthesis in P. putida KT2440, when grown on glucose [ 15 ]. On the contrary, our current findings point towards engineering of the ED pathway to improve PHA production capabilities in P. putida . This is also conform with the high natural flux through the ED pathway, when P. putida KT2440 is grown on glucose [ 62 ], and as shown here, also on glycerol (Fig. 2 ). Previous works have also pointed out the ED pathway as the possible main route when synthesizing mcl-PHAs on glycerol. A co-feeding strategy of glycerol and fatty acids was performed to evaluate its activity [ 24 ]. Here we fully confirm the use of the ED pathway by P. putida KT2440 under both carbon- and nitrogen-limiting conditions (Fig. 2 ) and propose its overexpression to improve PHA-productivity. Evaluation of metabolic responses on different organizational levels is vital to understand an organisms’ survival and success in the environment [ 63 ]. Integration of the transcriptome and metabolic fluxes showed that, upon an increased dilution rate under carbon-limiting conditions, P. putida KT2440 exhibits a more active ED pathway and increased flux through the pyruvate node, associated with significant upregulation of pyruvate metabolism (PP0554, acoA ) (Fig. 2 a, b; Table 5 ). Also, catabolism and anabolism appear to be tightly coupled as no by-product (citrate, succinate, or malate) formation is found (Table 2 ). On the other hand, nitrogen-limiting growth drove a major flux of carbon via the hexose-phosphates to the ED pathway when the specific growth rate was increased (Fig. 2 ). Interconnection between transcripts and fluxes deciphers regulatory mechanisms of core carbon metabolism Strong transcriptional regulation of glycerol metabolism The shift from glycerol limitation to glycerol excess reveals unique flux and gene expression patterns in central carbon metabolism (Fig. 5 ). At low growth rate, the transcriptional regulator glpR , which represses genes, involved in the uptake and incorporation of glycerol in P. putida [ 24 ], did not show transcriptional changes, whereas the transporter glpF was transcriptionally attenuated (Table 5 ). It has previously been postulated that the presence of glycerol in the medium modulates the expression of glpF [ 24 ], which is consistent with our findings. Furthermore, at high growth rates the repression of glpR , mitigating the transcription of glpF and the regulator araC (PP1395) (Table 5 ), seems responsible for the decreased uptake rate of glycerol. Furthermore, at the transcript and flux level, a more active ED pathway, pyruvate node (anaplerotic reactions), and TCA cycle were found at a low dilution rate. In addition, pyruvate metabolism seems to be a key node, when glycerol is used as carbon source, as this pathway is transcriptionally modulated by the imposed nutrient limitation, a trait that has not been previously described for cells grown on glycerol under PHA-producing conditions (Table 5 ). Fig. 5 Comparison of fluxes and transcription levels between nitrogen and carbon-limitation under a low dilution rate and b high dilution rate. Significant flux differences are indicated by the color of the arrow , whereas differentially expressed genes are color-coded as gene names next to the respective arrows . Green represents transcription levels or fluxes that are significantly higher under carbon-limiting conditions. Contrastingly, blue indicated values that are increased under nitrogen-limiting conditions. Changes that exceeded a twofold increase or decrease were considered significant when the p value did not exceed 0.05 Complex regulation of isocitrate dehydrogenase mediated flux Isocitrate dehydrogenase ( icd , PP4012) showed no repression at low dilution rate, accompanied by a higher flux through its reaction (Fig. 5 a), whereas at high dilution rate a significant decrease in transcription level was linked to a steady flux. Whilst previous studies have shown that at the mRNA level the gene icd is repressed under nitrogen-limiting conditions [ 9 , 15 ], our findings indicate that regulation of the isocitrate dehydrogenase mediated flux might not be solely transcriptional. In fact, an increased enzymatic activity of Icd under nitrogen-limitation would explain the observed phenomenon. Compelling correlation between PHA synthesis and expression of several genes from the PHA cluster With regard to PHA synthesis, the shift from carbon- to nitrogen-limitation promoted accumulation of the biopolymer, whereby the phaG gene was most strongly up-regulated independently of the set dilution rate (Fig. 5 ). PhaG (transacylase) is the linking enzyme between de novo fatty acid synthesis and PHA biosynthesis in Pseudomonas strains [ 64 , 65 ] and obviously supported enhanced PHA synthesis. In addition, PHA-granule forming enzymes, encoded by phaI and phaF, were up-regulated among the open reading frames of the PHA cluster, however, to a lesser extent (Table 5 ). They are known key elements of the PHA synthesis machinery, since they are involved in the segregation and distribution process of PHA [ 66 – 68 ]. Here, we discovered a direct correlation between strong synthesis of PHA and high expression of the phaF gene (Table 5 ). On the contrary, at a high specific growth rate, mRNA levels of phaF were unaffected, which could explain the observed low PHA production. PHA biosynthetic enzyme identified as potential bottleneck towards improved PHA production in P. putida Transcriptome analysis revealed that pyruvate dehydrogenase (encoded by acoA ) was overexpressed, when comparing cells growing at a high dilution rate against those at low dilution rate under nitrogen limitation (Table 5 ). This also correlates well with a high flux through this particular reaction (Fig. 2 c, d). Nonetheless, when the carbon flux segregates from acetyl-CoA to various pathways (TCA cycle and PHA synthesis), the PHA flux was the same for both conditions (Fig. 2 c, d). This leads to the hypothesis that PHA production in P. putida is restricted at the enzymatic level, probably at some point in the malonyl and/or the synthesis de novo fatty acid pathway. Additionally, the prediction of genetic targets for enhanced PHA synthesis by elementary mode correlation indicated that both the PHA biosynthetic pathways and the recycling of the ED pathway positively influence PHA productivity, as well as the elimination of by-product formation, being malate the target with the highest priority (Fig. 4 )."
} | 3,508 |
38431669 | PMC10908859 | pmc | 6,643 | {
"abstract": "Deep neural networks have revolutionized several domains, including autonomous driving, cancer detection, and drug design, and are the foundation for massive artificial intelligence models. However, hardware neural network reports still mainly focus on shallow networks (2 to 5 layers). Implementing deep neural networks in hardware is challenging due to the layer-by-layer structure, resulting in long training times, signal interference, and low accuracy due to gradient explosion/vanishing. Here, we utilize negative ultraviolet photoconductive light-emitting memristors with intrinsic parallelism and hardware-software co-design to achieve electrical information’s optical cross-layer transmission. We propose a hybrid ultra-deep photoelectric neural network and an ultra-deep super-resolution reconstruction neural network using light-emitting memristors and cross-layer block, expanding the networks to 54 and 135 layers, respectively. Further, two networks enable transfer learning, approaching or surpassing software-designed networks in multi-dataset recognition and high-resolution restoration tasks. These proposed strategies show great potential for high-precision multifunctional hardware neural networks and edge artificial intelligence.",
"introduction": "Introduction Deep neural networks (DNNs) possess the capability to represent more complex nonlinear problems than shallow neural networks, and their distributed data learning method is more effective 1 – 3 . The development of DNNs has greatly advanced the breakthroughs in autonomous driving 4 , cancer detection 5 , drug design 6 , and they serve as the foundation for massive AI models like ChatGPT 7 , PaLM 8 , PanguLM 9 . These advancements are largely attributed to the continuous improvement in computational power, network scale, and available data, which enables the implementation of DNNs with more layers and neurons. However, the execution of DNN models demands substantial computational resources. Currently, mainstream methods involve the use of high-end GPUs, accelerators, or cloud computing, which incur high costs and latency and severely limits the application of DNNs in edge AI scenarios, autonomous driving and robotics 10 . Within this background, neuromorphic devices have been intensively studied in recent years, aiming for implementing hardware neural networks with low power consumption and high speed 11 – 16 . Nonetheless, the current efforts have mainly focused on shallow neural networks with a few layers (typically 2 to 5 layers) 17 – 21 . Meanwhile, achieving high accuracy in multifunctional DNNs using the reported devices and hardware network structures remains huge challenging. The main reason is that the majority of networks rely on backpropagation (BP) for weight updates 22 – 25 , yet the layer-by-layer structure leads to gradient vanishing (exploding), making it difficult to effectively train the network 26 – 29 . Although the most advanced neuromorphic chips have attempted to construct DNNs with cross-layer transmission, they still rely on repeated reading of digital memory and DAC/ADC to achieve parallel output of results 30 – 32 . This greatly limits the throughput of data, as these works construct hardware neural networks through all-electric memristors and traditional software-designed structure instead of designing neural networks based on intrinsic parallel devices. Another issue is that, neuromorphic devices require physical processes for weight modulation 33 , 34 , and more layers and synaptic devices will inevitably increase the training time of DNNs. Therefore, to overcome the limitations of current work in terms of computation and training speed and achieve efficient and versatile hardware DNNs, the key lies in designing innovative fast-modulating intrinsic parallel synapses and building cross-layer modules and neural networks through hardware-software co-design. Here, a strategy utilizing innovative dual-output N-LEM to construct cross-layer block (ClBlock) was proposed to achieve a hybrid ultra-deep photoelectric neural network (UPENN) and an ultra-deep super-resolution reconstruction neural network (USRNN) with transfer learning ability. The N-LEM reducing the reset time of a single device after 50 enhanced pulses to less than 3.52 % of natural decay time, which can effectively accelerate the training of DNNs. Furthermore, the N-LEM array and hardware-software co-design were employed to achieve the equivalent cross-layer transmission of electrical information using optical signals, which was utilized in the construction of the ClBlock. Based on optical cross-layer transmission strategy, the UPENN and USRNN effectively prevented gradient vanishing (exploding), extended DNN to 54 and 134 layers, and shown strong transfer learning ability. The N-LEM and optical cross-layer transmission strategy successfully filled the gap in the construction of efficient, accurate, high-robust and low-power DNN, providing a new scheme for high-precision multifunctional hardware neural network and edge AI.",
"discussion": "Discussion In summary, an innovative dual-output N-LEM with negative photoconductivity for ultraviolet light has been developed, significantly reducing the time required for weight suppression. Through software-hardware co-design, the cross-layer transfer module (ClBlock) of neural networks has been successfully implemented. Furthermore, based on ClBlock, two ultra-deep neural networks for multi-task classification and super-resolution restoration have been constructed, effectively expanding the depth and alleviating the issue of gradient vanishing (exploding). The proposed neural networks demonstrate strong transfer learning capabilities and practicality, with UPENN achieving 305.9 % and 325.9 % higher accuracy than Contrast Net after pre-learning and relearning, respectively, while USRNN’s performance in resolution restoration approaches or even surpasses that of software-designed networks. Thus, the proposed N-LEM and ClBlock provide solutions for the challenges of training speed and network depth in neural networks, offering new possibilities for hardware-based ultra-deep neural networks and edge AI."
} | 1,539 |
19680442 | PMC2717328 | pmc | 6,644 | {
"abstract": "In bacteria, recombination is a rare event, not a part of the reproductive process. Nevertheless, recombination—broadly defined to include the acquisition of genes from external sources, i.e., horizontal gene transfer (HGT)—plays a central role as a source of variation for adaptive evolution in many species of bacteria. Much of niche expansion, resistance to antibiotics and other environmental stresses, virulence, and other characteristics that make bacteria interesting and problematic, is achieved through the expression of genes and genetic elements obtained from other populations of bacteria of the same and different species, as well as from eukaryotes and archaea. While recombination of homologous genes among members of the same species has played a central role in the development of the genetics and molecular biology of bacteria, the contribution of homologous gene recombination (HGR) to bacterial evolution is not at all clear. Also, not so clear are the selective pressures responsible for the evolution and maintenance of transformation, the only bacteria-encoded form of HGR. Using a semi-stochastic simulation of mutation, recombination, and selection within bacterial populations and competition between populations, we explore (1) the contribution of HGR to the rate of adaptive evolution in these populations and (2) the conditions under which HGR will provide a bacterial population a selective advantage over non-recombining or more slowly recombining populations. The results of our simulation indicate that, under broad conditions: (1) HGR occurring at rates in the range anticipated for bacteria like Streptococcus pneumoniae , Escherichia coli , Haemophilus influenzae , and Bacillus subtilis will accelerate the rate at which a population adapts to environmental conditions; (2) once established in a population, selection for this capacity to increase rates of adaptive evolution can maintain bacteria-encoded mechanisms of recombination and prevent invasion of non-recombining populations, even when recombination engenders a modest fitness cost; and (3) because of the density- and frequency-dependent nature of HGR in bacteria, this capacity to increase rates of adaptive evolution is not sufficient as a selective force to provide a recombining population a selective advantage when it is rare. Under realistic conditions, homologous gene recombination will increase the rate of adaptive evolution in bacterial populations and, once established, selection for higher rates of evolution will promote the maintenance of bacteria-encoded mechanisms for HGR. On the other hand, increasing rates of adaptive evolution by HGR is unlikely to be the sole or even a dominant selective pressure responsible for the original evolution of transformation.",
"introduction": "Introduction Recombination in the form of the receipt and incorporation of genes and genetic elements from other strains and species of bacteria [1] as well as archaea and eukaryotes [2] , [3] , [4] , [5] , [6] , [7] plays a prominent role as a source of variation for the adaptive evolution of many species of bacteria [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] . Because of this ability to acquire genes and genetic elements from other organisms, horizontal gene transfer (HGT), the pace of adaptive evolution in bacteria need not be limited by the standing genetic variation within a population or the slow rate by which adaptive genes are generated by recurrent mutation. Through single HGT events bacteria can obtain chromosomal genes and gene clusters (islands) as well as plasmids, transposons and prophage bearing genes that have successfully traversed the gauntlet of natural selection in some other population of their own or other species. In this way, bacteria can expand their ecological niches; colonize new habitats and hosts, metabolize new energy sources, synthesize essential nutrients, survive toxic agents like antibiotics, and alas, increase their virulence to human and other hosts. Less clear are the ecological and evolutionary consequences of more mundane HGT events, such as homologous gene recombination (HGR) among members of the same population. In accord with classical population genetic theory, meiotic recombination of can increase the rate at which populations adapt to new environments by assembling in single organisms combinations of adaptive mutations occurring in different members of their population and by reducing the rate at which populations accumulate deleterious mutations, (“Muller's Ratchet”). For superb reviews of this classical theory and some of its more recent extensions see [19] , [20] , [21] . There are good theoretical reasons to anticipate that recombination among chromosomal genes already present and those generated by mutation within a bacterial population can augment its rate of evolution in a variety of ecological situations [22] . There is also experimental evidence in support of this prediction. Transformation occurs at measurable rates in B. subtilis maintained in a more or less natural setting and the resulting HGR appears to promote adaptive evolution in these populations [23] . Two recent experimental studies comparing rates of evolution among recombining and non-recombining populations provide direct evidence that capacity for F-plasmid mediated recombination in E. coli \n [24] , and transformation-mediated recombination in Helicobacter pylori \n [25] , can increase the rate at which these bacteria adapt to culture conditions. However, there is also evidence from studies with experimental populations of E. coli \n [26] and Acinetobacter baylyi \n [27] indicating that there are conditions where there are no differences in the rates at which recombining and non-recombining populations adapt to environmental conditions. On first consideration, it would seem that if recombination increases the rate at which populations adapt to their environment, the capacity for shuffling homologous genes within a population would provide an advantage to the recombining strain when competing with populations without this capacity. Not so clear are the conditions under which selection will favor recombining populations in this way. When will a recombining population prevail over non- or more slowly- recombining populations, and do so in the face of fitness costs associated with the capacity for recombination? Here, we present the results of a study using computer simulations of mutation, recombination, selection and inter-population competition to explore the conditions under which: i) recombination augments rates of evolution in bacterial populations and, ii) when the capacity for HGR will be favored in competition with non-recombining populations. We demonstrate that under broad conditions, HGR occurring at rates in a range estimated for E. coli , H. influenza , S. pneumoniae ,, and B. subtilis can increase the rate of adaptive evolution in bacterial populations. We show that this capacity for increasing rates of evolution by shuffling chromosomal genes can provide a recombining population a selective advantage in competition with populations without this capacity even when the recombining population has a lower intrinsic fitness. On the other hand, we also demonstrate that because the rate of recombination in bacteria depends on the density of the recombining population, the conditions under which recombination can provide a population a selective advantage in competition with non-recombining populations are restricted to when the recombining population is relatively common and the total population density is high. Even in the absence of a fitness cost, when the recombining population is rare, it will not be favored despite its ability to acquire genes from the dominant non-recombining population. We discuss the implications of these simulation results to the role of recombination in the adaptive evolution of bacteria and the evolution and maintenance of different mechanisms for homologous gene recombination in bacteria.",
"discussion": "Discussion We interpret the results of this computer simulation study as support for the proposition that that there are realistic conditions where homologous gene recombination (HGR) will increase the rate at which bacterial populations adapt to their environment. These results are also consistent with the hypotheses that by increasing rates of adaptive evolution, HGR can provide a population a selective advantage when competing with otherwise identical or even somewhat more fit populations that are unable to shuffle homologous genes or do so at lower rates. Our mixed population simulations, however, also illustrate a major caveat to the hypothesis that homologous gene recombination in bacteria evolved in response to selection for increasing rates of adaptive evolution. Even in the absence of a fitness cost, the recombining population will only have an advantage over a non-recombining population when the recombining population is relatively common; HGR will not be favored when it is rare. Homologous Gene Recombination and Rates of Adaptive Evolution The validity and generality of these predictions are, of course, empirical questions. They are however, questions that can be addressed experimentally. And, as noted in our Introduction, there have been at least four experimental studies testing the hypothesis that recombination increases the rate at which bacterial populations adapt to culture conditions. The results of two of these experiments are consistent with this hypothesis, Cooper's study with F-plasmid-mediated recombination in E. coli B \n [24] and Baltrus and colleagues study of transformation-mediated recombination in Helicobacter pylori \n [25] . The results of the other two reports, Souza and colleague's study of Hfr-mediated recombination in E. coli \n [26] and Bacher and colleagues study of transformation-mediated recombination in Acinetobacter baylyi \n [27] are interpreted to be inconsistent. How well do the results of this simulation study account for the outcomes of these recombination – rates of adaptive evolution experiments? We believe that at least at a qualitative level, the results of the three of these studies for which this model is a reasonable analog [24] , [25] , [27] are consistent with the predictions of these simulations. The format of the experiments by Souza and colleagues [26] were different from that of this model and therefore we do not believe these simulations are appropriate for interpreting their results. In their experiments, two genetically different E. coli strains were used; a Hfr strain of E. coli K-12 and a F- strain of E. coli B. Although the Hfr strain donated genes to the E. coli B, under the conditions of their experiments this donor did not replicate and it was not present throughout the course of the experiment as assumed in our model. Although the details of the [24] , [25] , [27] experiments were different from those specified by this simple model, their basic structure was similar to that of the single population simulations initiated with monoclonal (2,2,2,2,2) populations. In these experiments, which were initiated with single clones of either recombining (Rec+ or Com+) or non-recombining (Rec− or Com−) populations, the bacteria were growing in liquid media and reached densities of 5×10 7 per ml or greater. Although the rate constants of recombination χ were not estimated in these experimental studies, it was clear that recombination was occurring at a substantial rate. The frequency of gene replacement by recombination in the Rec+ E. coli B and Com+ H. pylori experiments exceed that expected by mutation, and in the Cooper study the rate of gene replacement by recombination greater is greater than that of the elevated rate of mutation of a mutS strain. For recombination mediated by HFR, F', F+ plasmid in E. coli , χ , it seems reasonable to conclude that in the Cooper experiments c >10 −13 (Cornejo and Levin, In Preparation- but available, see www.eclf.net ). We would also expect χ>10 −13 for the H. pylori experiments and possibly in the Acinetobacter baylyi study as well. This is certainly the case for the only two experimentally obtained estimates χ we know of for transforming bacteria, H. influenzae \n [30] and B. subtilis \n [31] , both of which are on the order of χ ∼10 −12 . With population densities, mutation and recombination rate constants in the ranges of these experiments, our simulations show that recombining populations evolved more rapidly than those that did not have this capacity for shuffling homologous genes. For any given mutation and recombination rate parameters, the rate and magnitude of increase in mean fitness depended on the fitness function. Cooper's observation that recombination increased the rate of adaptation to culture conditions with a higher mutation rate ∼3 times greater than it did with a lower rate [24] is also consistent with the predictions of this model; mutation and recombination act synergistically to increase rates of adaptive evolution. Although Bacher and colleagues [27] interpret the results of their experiments with A. baylyi to be inconsistent with the hypothesis that HGR increases rates of adaptive evolution, that is not the case for all the results they report. In their higher density experiments not only does the fitness of the population increase to a greater extent than in their low density experiments, but this increase in fitness was considerably as well as significantly greater (p = 0.00012 for a two tailed t-test) for the transformation competent population than the non-competent controls. Does Homologous Gene Recombination Increase Rates of Adaptive Evolution in Natural Populations? While we are unaware of direct experimental evidence for an affirmative answer to this question from natural population studies, based on the predictions of the model we would anticipate a positive answer. Retrospective, multi-locus sequence studies suggest that the rates of gene of replacements by homologous recombination in species like Streptococcus pneumoniae exceed that by mutation by a factor of 10 or so [32] , [33] , [34] , and are even greater for some species, like H. pylori \n [35] , [36] . To put these retrospective estimates of recombination rates into the context of our model and its parameters, consider the following intuitive argument. Assume a 1-hour generation time, a habitat of 1 ml, a population of 10 8 bacteria and a mutation rate of 10 −8 per cell per generation. In the course of an hour in that population, for any given locus, an average of 1 mutant would be produced. If gene replacements by recombination occur at 10 times that rate, there would be 10 recombinants at that locus for a value of χ = 10/(10 8 ×10 8 ) = 10 −15 . As noted in our simulations, even at this low rate and an initially monoclonal population, recombination can increase the rate of adaptive evolution over that which would be anticipated by mutation alone. Moreover, natural populations of many bacteria are likely to be composed of multiple lineages and would be genetically variable at many loci. In accord with our simulations the pace at which recombination increases the rate of adaptive evolution would on average increase with the extent of genetic variability of the population, see Figure 5 . Accelerating Adaptive Evolution as a Selective Force for the Maintenance and Evolution of HGR Processes, like homologous gene recombination, that increase rates of adaptive evolution would be to the advantage of a population and augment its prognosis for surviving the vicissitudes of an ever-changing environment. This is, of course, the most common explanation for ubiquity of HGR among extant species of eukaryotes. Indeed, the presumed lack of recombination, sex to be more provocative, in ancient groups of seemingly successful organisms like the bdelloid rotifers make them intriguing objects for study [37] . Whether accelerating rates of adaptive evolution is the selective force responsible for the evolution and maintenance of recombination in eukaryotes is a subject of some controversy [20] , [38] , a subject that we are pleased to say is beyond the scope of this report. The population and evolutionary dynamics of recombination in bacteria are fundamentally different from that of sexually reproducing eukaryotes. In the bacteria, recombination depends on density and is not a part of the reproductive process. If they wish to procreate, sexually reproducing eukaryotes have no choice but to find mates and generate recombinant progeny, independently of density of their populations. Here, we postulate that once the mechanisms for HGR are established in a bacterial population, the advantage accrued by a more rapid rate of adaptation to environmental conditions can promote their maintenance, even if they engender a modest cost in fitness. The necessary condition for this to obtain is that the adaptive process is continuous. This may be the case when a population enters a new environment and/or is confronted by either physical or biological factors that reduce the rates of survival or reproduction (the fitness) of its members. As long as the population is continually confronted with situations where selection favors new genotypes, as was postulated for evolution of mutator genes [39] , recombination could continue to be favored and be maintained. This would not be the case if recombination engenders a fitness cost and the population is confronted with extensive periods of adaptive stasis. Under these conditions, the frequency of the recombining population will continue to decline. And, because of the frequency- and density- dependent nature of selection for recombination, the recombining population may not be able to recover. In this interpretation, the maintaining mechanisms of horizontal gene transfer by HGR by increasing rates of adaptive evolution is not an equilibrium outcome; on “equilibrium day” [40] , recombination will be lost. Moreover, because HGR accelerating rates would not provide an advantage to a recombining population when it is initially rare, it is even less likely to have been a selective force for the original evolution of mechanisms for HGT than it is for maintaining those mechanisms once they evolved. Models can be used to generate hypotheses and, in a quantitative way, evaluate their plausibility. They cannot be used to test those hypotheses! We are unaware of published empirical studies testing the hypotheses that selection for HGR is frequency- and density- dependent. These are, however, hypotheses that can be tested with experiments similar to the single clone studies testing the hypothesis that HGR increases rates of adaptive evolution [24] , [25] , [27] . The idea would be to follow the changes in frequency of Com+ or Rec+ in competition with Com− or Rec− clones with different initial frequencies of these competitors and in populations of different densities. We postulate that under conditions where they accelerate rates of adaptive evolution in single clone culture and adjusting for intrinsic fitness differences: (1) when introduced at roughly equal frequencies, the recombining population will have an advantage over a non-recombining competitor and, (2) the recombining population will not have that advantage when it is initially rare (in our simulations much less than 1%.). We also postulate that because of a lower rate of production of mutants as well as the lower frequency of recombination (which would be proportional to the square of the density of the recombining population); (3) the rate of adaptive evolution would be less in recombining populations of low density than otherwise identical populations of higher density and, (4) the minimum frequency for a recombining population to have a selective advantage in competition with one that cannot recombine would be inversely proportional to the total density of the recombining population. Using the long-term evolved strains of E. coli B developed by Richard Lenski and colleagues [41] , [42] , [43] it should be possible to experimentally test the hypothesis that HGR will only be favored when there is relatively intense selection for adaptation to culture conditions. Although those experimental E. coli B populations continued to evolve in different ways as time proceeded the largest increase in mean fitness relative to the ancestral occurred within the first 5,000 or so generations. We postulate that if in an experiment similar to that in [24] the F'lac constructs were made with E. coli B taken from later generations, say >20,000, the recombining population will not evolve more rapidly than one that is not recombining. HGR and the Maintenance and Evolution of HGT in Bacteria Two of the three major mechanisms responsible for HGT and HGR in bacteria, conjugation and transduction, are not properties of the bacteria but rather that of their parasites, primarily conjugative plasmids and bacteriophage. One needn't postulate that these processes evolved and are maintained by selection favoring bacteria with the capacity for HGT. The most parsimonious hypothesis for recombination mediated by plasmids and phage is as a coincidental byproduct of the infectious transfer of these elements and the host's recombination repair system [44] , [45] . This would also be the case for recombination resulting from cell fusion [11] or transformation mediated by natural electroporulation or cold shocks. In this interpretation, accelerating the rate of adaptive evolution by HGR mediated by these processes are a lagniappe rather than a product of adaptive evolution. To be sure we can make up and probably construct mathematical models illustrating ways by which bacteria evolve mechanisms to be more receptive to plasmids and phage carrying genes on their behalf, but we see no need to stretch our imaginations in that direction. The third main mechanism for HGT and HGR in bacteria, the uptake and incorporation of exogenous DNA, i.e. competence and transformation, are intrinsic properties of bacteria rather that of their parasites. We postulate that under some conditions HGR accelerating rates of adaptive evolution will promote the maintenance of competence and transformation. HGR accelerating rates of adaptive evolution is, however, only one of at least three non-exclusive mechanisms that operate synergistically to maintain competence for the uptake of exogenous DNA. The other three are; (1) the acquisition of templates for the repair of double stranded breaks in DNA [46] , [47] ; the uptake of nutrients and nucleotides [48] , [49] , [50] , [51] , and (3) episodic selection favoring transiently non-growing subpopulations of competent cells and rare transformants [31] . In accord with these three hypotheses, transformation (recombination) is a coincidental byproduct of competence. As is the case with meiotic recombination in eukaryotes, accounting for the selective pressures responsible for original evolution of competence and transformation is more problematic than explaining their maintenance once they have evolved. Competence is a complex character that requires the coordinated activity of a large number of genes [15] , [52] , [53] , [54] , [55] . What are the selective pressures responsible for the evolution of these genes and coordinating their activity? Because recombination will only be favored when it is common, we postulate that HGR accelerating rates of adaptive evolution cannot account for the original evolution of natural competence and transformation. For the same reasons, we postulate that this is also the case for the episodic selection for competence. The DNA repair and food hypotheses have the virtues of selection operating at the level of an individual bacterium rather than populations and thereby allowing competence to be favored when it is rare, rather than only when it is common. On the other hand, these two hypotheses raise other issues about whether they can account for the original evolution of competence. For a recent critical consideration of these “other issues” we refer the reader to the Discussion in [31] . At this juncture, we accept the selection pressures responsible for the origins of competence and transformation in bacteria as a delicious, but yet-to-be solved evolutionary problem. A Caveat In our simulations we have restricted the theater of evolution to single populations. A long-standing argument for the evolution of recombination is that higher rates of adaptive evolution provide an advantage to the collective, the group, rather than individuals [19] , [29] . Populations that evolve more rapidly are more likely to prevail and survive longer than those with lower rates of adaptive evolution. In theory there are conditions where group- or interpopulation- level selection can lead to the evolution of characters that are at a disadvantage within populations [56] , [57] , [58] , [59] . And, mechanisms of this type have been postulated to play a role in the evolution of recombination in bacteria [60] . While we prefer individual-level selection operating within populations on the grounds of parsimony, we can't rule out the possibility that competence and transformation evolved and is maintained by some form of group- level selection."
} | 6,365 |
26356234 | PMC4565550 | pmc | 6,645 | {
"abstract": "Supergeneralists, defined as species that interact with multiple groups of species in ecological networks, can act as important connectors of otherwise disconnected species subsets. In Brazil, there are two supergeneralist bees: the honeybee Apis mellifera , a non-native species, and Trigona spinipes , a native stingless bee. We compared the role of both species and the effect of geographic and local factors on networks by addressing three questions: 1) Do both species have similar abundance and interaction patterns (degree and strength) in plant-bee networks? 2) Are both species equally influential to the network structure (nestedness, connectance, and plant and bee niche overlap)? 3) How are these species affected by geographic (altitude, temperature, precipitation) and local (natural vs. disturbed habitat) factors? We analyzed 21 plant-bee weighted interaction networks, encompassing most of the main biomes in Brazil. We found no significant difference between both species in abundance, in the number of plant species with which each bee species interacts (degree), and in the sum of their dependencies (strength). Structural equation models revealed the effect of A . mellifera and T . spinipes , respectively, on the interaction network pattern (nestedness) and in the similarity in bee’s interactive partners (bee niche overlap). It is most likely that the recent invasion of A . mellifera resulted in its rapid settlement inside the core of species that retain the largest number of interactions, resulting in a strong influence on nestedness. However, the long-term interaction between native T . spinipes and other bees most likely has a more direct effect on their interactive behavior. Moreover, temperature negatively affected A . mellifera bees, whereas disturbed habitats positively affected T . spinipes . Conversely, precipitation showed no effect. Being positively ( T . spinipes ) or indifferently ( A . mellifera ) affected by disturbed habitats makes these species prone to pollinate plant species in these areas, which are potentially poor in pollinators.",
"introduction": "Introduction Supergeneralist species, defined as species that interact with multiple groups of species, are considered key species in interaction networks because they act as important connectors of species subsets that otherwise would be unconnected [ 1 , 2 , 3 ]. The selective removal of species with large number of interactions enhances the fragility of networks [ 4 ] and, for the specific case of pollinators, it may affect plant diversity [ 5 ]. Thus, it is important to understand the role of these species in interaction networks, especially considering the rapidly changing conditions of their habitats. Global changes, mainly the presence of invasive species, climate changes, and habitat disturbance, exert important influences on interaction networks [ 6 , 7 ]. First, invasive species, even when acting as supergeneralists, can exhibit a different role in interaction networks, presenting a disruptive effect, modifying the strength of interactions, and decreasing the connectivity among native species, with detrimental consequences to their interacting partners [ 8 , 9 , 10 ] (but see exceptions regarding alien plants in [ 11 , 12 , 13 ]). Theoretical studies exploring the drivers behind network invasion showed that large [ 14 ] and more generalist [ 14 , 15 ] species are more successful invaders, whereas webs relatively easy to invade have low connectance and greater number of species [ 15 ]. Second, climate change, with increasing variability in temperature and precipitation, appears to have a more moderate effect on invasive species [ 16 , 17 ] and, in some cases, leads to a homogenization of interaction networks due to the expansion of generalists [ 18 ]. It can also disrupt interactions themselves since partner species may disperse differently when seeking for new habitats [ 19 , 20 , 21 ]. Third, disturbed habitats can be better tolerated by generalist species than specialized ones [ 22 , 23 ] and are more likely to facilitate the settlement of invasive species [ 24 , 25 , 26 , 27 , 28 ], also changing the network structure due to species loss and reorganization of interaction patterns [ 29 ]. Thus, complex abiotic-biotic features appear to drive species interactions. Plant-bee interaction networks represent an important case study because pollination is a key ecosystem service [ 30 , 31 ] and multiple drivers related to rapid global change are affecting pollinators worldwide [ 32 , 33 ]. In Brazil, there are two well-known supergeneralist bee species playing a crucial role in interaction networks [ 34 , 35 , 36 , 37 , 38 ]. One is an invasive bee species, Apis mellifera Linnaeus 1758 (Apidae), introduced in the 1950s and currently scattered in all Brazilian regions [ 39 ]; the other is Trigona spinipes Fabricius 1793 (Apidae), a smaller native social stingless bee ( Fig 1 ). Both were recently quoted as pollinators of some crop species [ 40 ] but their role as actual pollinator of native flora and competitor for resources has to be clarified [ 41 , 42 , 43 ]. 10.1371/journal.pone.0137198.g001 Fig 1 A) Abundance, B) Degree (number of interactions), and C) Strength of Apis mellifera (Am) and Trigona spinipes (Ts) in Brazilian weighted plant-bee networks. There is no significant difference between the variables (t-test; P > 0.05). The horizontal line within each box is the median, and the lower and upper limits of the box define the 25th and 75th percentiles, respectively. The lower and upper whiskers define the 10th and 90th percentiles, respectively. Photo by Adrian Gonzalez and Sheina Koffler. The role of supergeneralist species has being debated, and they are suggested to be key elements of mutualistic networks ([ 44 ] but see [ 45 ]), potentially shaping evolutionary dynamics [ 3 ] and being vulnerable to human impact [ 46 ]. However, the simultaneous presence of one native and one invasive bee species in the same interaction networks arises intriguing questions and, to our knowledge, this is the first attempt to analyze a situation like this. In this work, our aim is to analyze the role of invasive A . mellifera and native T . spinipes in Brazilian plant-bee interaction networks by addressing three main questions: 1) Do both supergeneralist species have similar interaction patterns in pollination networks? 2) Are both species equally influential to the network structure? 3) How are these species affected by geographic (climate) and local (natural vs. disturbed habitats) factors? Answering these questions would represent an additional step in understanding the effect of these supergeneralist bees on interaction networks.",
"discussion": "Discussion Supergeneralist species, which interact with multiple groups of species and act as connectors of otherwise unconnected species, are important for maintaining the robustness of networks. In this study, we show that native and non-native supergeneralist bees, despite their similarities (question 1), exert different effects on interaction networks (question 2) and are affected differently by climate and landscape features (question 3). The significant similarity of both supergeneralist bees, described here as their abundance, degree, and strength, is most likely due to their ability to occupy broad distributional ranges and the relative independence of cavities in which to build their nests. The higher number of interactions of some species may be, in many cases, associated with their abundances. There is a heated debate in the literature on the role abundance plays in structuring ecological networks [ 49 , 69 , 70 ]. In fact, models based on the neutral theory often predict the existence of highly connected species [ 71 ]. Nevertheless, under the assumption of neutrality, the most abundant species at a local scale is the result of ecological drift, which also predicts that most abundant species will vary across different sites. Therefore, it is not expected the same few species to be the dominant components of ecological assemblages in many different sites. In this sense, the dominance of these supergeneralist bees may be a consequence of their traits, which in turn, may also explain their ecological success. In spite of having different body sizes, both bee species present colonies with a very large number of individuals and were once considered \"similar species\" [ 72 ]. However, both species do not have the same effect on network structure since only A . mellifera showed a strong effect on nestedness, whereas T . spinipes was found to present a main effect on the bee niche overlap. The correlation between A . mellifera degree and nestedness was positive, suggesting that the higher the number of interactions of A . mellifera , the higher the nestedness. Nestedness describes a common topology where the most generalist species interact among them generating a core of interactions to which the rest of the species is attached, implying the existence of a relatively small group of highly connected species. In our case, A . mellifera seems to exert a positive effect on this type of topology. As already pointed, this supergeneralist species is fundamental to the maintenance of the whole network, since it participates on most of the links established with plant species. Also, the positive correlation with niche overlap suggests that the similarity of interaction patterns in each trophic level is directly related to the number of interactions showed by A . mellifera with its partners. Finally, it was already pointed by other authors that recent invasive species enter networks, interacting primarily with native generalists, which directly and rapidly increases nestedness [ 73 ]. Moreover, the dependence of plants on the new species may be lower than expected because other native pollinators most likely are more tightly associated with native plants. This could explain the opposite results obtained when analyzing the role of the degree (number of interactions) and strength (dependence of plants) of A . mellifera on nestedness. However, the long-term interactions between T . spinipes and other native bees could have resulted in a higher effect on the adaptation of other bees. Although A . mellifera appears to displace the other bees from plant resources, making them change their phenology [ 42 ], T . spinipes presents a more direct effect on them, since they display an aggressive behavior when interacting with other bees during foraging [ 74 ]. Our data also suggest that high temperature reduces the strength of A . mellifera and increases network nestedness and plant niche overlap, temperature being highly correlated to altitude. This result indicates that the higher the temperature, the lesser is the dependence of A . mellifera and also, the higher is the aggregation of generalist species in a core (nestedness) and the similarity between partner species (niche overlap). It was already demonstrated that the mean annual temperature positively influences A . mellifera nest density only up to values equal to 25°C, whereas higher temperatures produce an inverse effect [ 75 ]. In addition, during seasons with extremely high temperatures, the abundance of A . mellifera decreases locally [ 76 ]. It is likely that local bees are more adapted to severe environmental conditions, playing central roles in these networks and apparently displacing A . mellifera . However, it is important to notice that temperature was negatively correlated to plant richness, what could also be mediating these results. Unlike temperature, precipitation showed no significant effect on either species. However, our dataset did not include networks on the Amazon biome, an area of constant high rainfall in Brazil; thus, the effect of precipitation on the role of these bees remains unclear. Finally, we found no correlation between disturbed habitats and A . mellifera , while this variable was correlated positively with T . spinipes strength. The lack of correlation found on A . mellifera interaction pattern suggests that this invasive species is neither favored nor hindered by habitat degradation whereas the positive correlation between habitat degradation and T . spinipes strength may suggest that this species responds well to disturbances. This emphasizes the potential role of both species as pollinators of local plants in degraded areas, which typically have smaller pollinator diversity [ 77 ]. Our results are a good example of the effect of different habitats inducing different interactions. In short, our results suggest that temperature has an important effect on A . mellifera and disturbance, on T . spinipes . Both species are correlated differently to networks, being A . mellifera more influential on network topology (nestedness and plant niche overlap) and T . spinipes more influential on the interaction patterns of plants and other bees (plant and bee niche overlap). Overall, our results suggest that highly generalist invasive species alter the structure of interaction networks, and act differently from other equally generalist species, but which are not exotic, i.e., those that participate on networks for a long-time period. These species may present different answers to global changes, with consequences for their interaction networks and to the ecosystem services delivered by them. Understanding these relationships more accurately could contribute to the establishment of conservation programs that address management and public policy, aiming to enhance the protection of pollinators."
} | 3,421 |
36910977 | PMC9996761 | pmc | 6,646 | {
"abstract": "Shark skin-inspired riblets have represented the tremendous\npotential\nfor drag reduction (DR) and antifouling in submarine, ship, and so\non. Most studies simplified the complex denticle embedded in the shark\nskin into the single-stage riblet with uniform parameters, ignoring\nthe influence of riblet height gradient and material deformation on\nDR and antifouling. In the present study, flexible multistage gradient\nriblets (MSGRs) with varied heights were proposed, and their DR and\nantifouling effects were investigated by the experiment and numerical\nsimulation. The experimental results showed that the maximum DR rate\nof flexible MSGRs with an elastic modulus of 4.592 MPa could reach\n16.8% at a flow velocity of 0.5 m/s. Moreover, the dynamic adhesion\nmeasurement indicated a reduction by 69.6% of the adhesion area of Chlorella vulgaris on the flexible MSGR surface.\nThe results identified that flexible MSGRs with low surface energy\ncould generate steady high- and low-velocity streaks and alter the\nflow state of the fluid, thus lessening the average velocity gradient\nnear the wall and the adhering selectivity of pollutants in riblet\nand achieving synergistic DR and efficient antifouling. Taken together,\nthe proposed flexible MSGR surface holds promise for reducing surface\nfriction and inhibiting particle attachment in engineering applications.",
"conclusion": "5 Conclusions Flexible MSGRs was proposed\nto improve DR and antifouling ability\nby the optimization of the near-wall velocity distribution. Experimental\nand numerical simulation methods were performed to characterize the\nDR and antifouling effects of the flexible MSGR surface. According\nto the analysis of the circulating water tunnel, flexible MSGRs could\naccomplish greater DR than the classic single-stage riblet with uniform\nparameters and expand the effective DR speed range. In addition, computational\nfluid dynamics was used to analyze the flow on the flexible MSGR surface,\nwhich identified that high- and low-velocity streaks alternated along\nthe span. This regular arrangement of streaky structures could bring\nabout changes in the flow near the wall, velocity gradient reduction\nof the boundary layer, and further DR. Moreover, the elastic modulus\nof the flexible MSGR surface with the best DR effect was 4.592 MPa,\nwhich could produce velocity slip, further reduce the velocity gradient\nof the boundary layer, and absorb pressure fluctuations, thus achieving\na DR rate of 16.8% at a flow rate of 0.5 m/s. Flexible MSGRs, serving\nas an antifouling microstructure, could reduce the adhesion coefficient\nof C. vulgaris by about 69.6% compared\nwith an F surface. The secondary stream and high- and low-velocity\nstreaks were generated in the low surface energy flexible MSGR surface\nwith asymmetric intersection and high- and low-gradient riblet, breaking\nthe isolated rotating vortex in the groove, shortening the residence\ntime of pollutants, reducing the selectivity of pollutants, and enhancing\nthe anti-adhesion property. In summary, flexible MSGRs provide a feasible\nsolution for ship DR and pollution prevention.",
"introduction": "1 Introduction Drag reduction (DR) and\nantifouling have been plaguing various\nindustries. For instance, over 50% of fuel consumption in ships is\nattributed to surface drag. 1 Moreover,\nthe surface fouling on the underwater ships is also severe and inevitable,\nusually intensifying the drag. Generally, as the fouling coverage\nrate was 5%, the ship drag was twice greater than that of the clean\nsurface, and the fuel consumption increased by 10%. Therefore, it\nwas beneficial to design the composite surface with DR and antifouling\nabilities. 2 Natural creatures evolving\nunique structures and excellent surface functions through millions\nof years of natural selection could adapt to the harshest environment. 3 − 9 Inspired by natural creatures, scientists and engineers have obtained\nmany innovative inspirations to address the above technical challenges. 10 − 12 Numerous studies have indicated that many tiny denticles embedded\nin the shark skin and parallel to the streamwise direction played\na decisive role in reducing drag and antifouling. 13 − 16 However, due to the complexity\nof the denticle structure, it was\nintractable to fabricate the real shark skin surface in a large area,\nand thus, scientists generally simplified the denticle into riblet\nstructures with triangular, rectangular, and other cross-sections. 17 − 20 Schumacher et al. 21 prepared a new type\nof environment-friendly ship coating named barnacle-specific Sharklet\nAF based on the micro-topographical characteristics of shark skin.\nDai et al. 22 developed the shark-skin-like\nsurface with a 90° orientation by three-dimensional (3D) printing\nand accessed its DR effect with a rheometer. Qin et al. 23 modified the bionic non-smooth surface by combining\nZIF-67 particles to enhance its DR and antifouling properties. Zhou\net al. 20 , 24 fabricated multilayer hierarchical riblets\nby three-layer hybrid mask lithography, which presented an excellent\nair DR. Additionally, shark skin has an excellent antifouling effect. 20 , 22 , 25 , 26 Chung et al. 27 and Schumacher et al. 21 found that Sharklet AF based on the shark skin\nhad a significant antifouling effect on Staphylococcus\naureus and zoospores of Ulva linza . Choi et al. 28 and Yoo et al. 29 investigated the influence of the spacing dimension\nof the Sharklet structure on membrane biofouling and observed that\nthe 2 μm spaced pattern exhibited the least fouling. Lee et\nal. 30 and Schumacher et al. 31 found that the increasing length gradient of\nthe riblet on the bionic shark skin surface was beneficial in reducing\nthe residence time of pollutant particles on the patterned surface.\nIt can be seen that the application of bionic shark skin structure\nwith changing parameters has been a new trend for DR and antifouling.\nTherefore, it is significant to further study the comprehensive effect\nof bionic shark skin structure with changing heights in response to\nDR and antifouling. In addition, DR and antifouling are a complicated\nsubject related not only to the surface morphology of bionic shark\nskin structure but also to wettability, surface free energy, surface\nroughness, and mechanical properties. 32 , 33 In this\npaper, considering the height gradient of the shark skin\nshield scale structure, five bionic flexible multistage gradient riblet\n(MSGR) surfaces with different mechanical properties were prepared\nby polydimethylsiloxane (PDMS). To analyze the DR and antifouling\neffects of the prepared flexible MSGR surface, it was compared with\nMSGR surfaces and classic single-stage riblet surfaces. Surface drag\nand fouling were determined using a closed water tunnel and Chlorella vulgaris coloring tests, respectively.\nMoreover, numerical evaluation was performed on the flow characteristics\nof the bionic surface; the influence of the bionic surface on the\nnear-wall flow field was analyzed; the pollutant pathway was determined\nby numerical simulation; the effects of wettability on DR and antifouling\nwere evaluated by dynamic and static contact angles (CAs) and surface\nfree energy; and the possible new DR and antifouling mechanisms of\nthe flexible MSGR surface were studied. In addition, in terms of the\nDR and antifouling, the flexible MSGR surface inspired by shark skin\nnot only showed great application potential in underwater vehicles\nbut also enlightened the reasons for other similar flexible gradient\nstructures by exploring its internal mechanism.",
"discussion": "4 Discussion 4.1 Synergistic DR Effect of the Flexible MSGR\nSurface The comparison of the DR results with wettability\nshowed no direct correlation. The MSGR surface showed a low static\nCA in rigid bionic surfaces but a small drag. Therefore, it is important\nto analyze the effect of structure and material deformation on DR. Figure 7 a presents contours\nof constant flow velocity in a wall-parallel plane at a distance of\n0.1δ from the bottom for different rigid bionic surfaces, where\nδ denotes the boundary layer thickness. 40 On the MSGR surface, high- and low-velocity streaks appeared near\nthe low riblet (black arrow) and high riblet (red arrow), respectively.\nSimilar conclusions were obtained from the study of the European bass\nand tuna. 40 − 42 More detailed information on the velocity variation\nin different bionic surfaces is demonstrated in Figure 7 b, which exhibited spanwise velocity profiles\nfor different wall-normal locations at the location y = y o + 3100 μm. Except for that\nof the MSGR surface, the streak amplitude of other surfaces was less\nthan 0.07 of the inlet velocity, and no high- and low-velocity streaks\nwere formed. For the MSGR surface, the high- and low-velocity streaks\nextended through most of the boundary layer at different depths. As\nthe normal distance from the wall was lengthened, the amplitude of\nthe streak decreased monotonically until the outer edge of the boundary\nlayer reached zero amplitude. In order to explore the effect of high-\nand low-velocity streaks on DR, velocity contours of the boundary\nlayer cross-sections of the R, F, and MSGR surfaces were analyzed,\nas shown in Figure 7 c. Note that for each row of rhombus-shaped patterns, the results\nwere periodic in the spanwise direction. A detailed comparison of\ndimensionless velocity profiles in the R surface and the high- and\nlow-velocity regions of the MSGR surface are shown in Figure 7 d. Compared with the velocity\nprofile of the F surface (black line), the velocity gradient near\nthe wall became flatter at points A, B, and C. However, the thickness\nof the boundary layer was almost consistent. This suggested that riblets\nchanged the shape of the velocity profile in the boundary layer area\nbut not the thickness of the boundary layer (despite affecting the\nnear-wall flow). The near-wall flow was modulated by the MSGR surface,\nwith streaks that would affect the wall shear stress (τ w ) distribution compared with flow over a classic single-stage\nriblet surface. In comparison with the velocity profile for an R surface\n(green line), the velocity gradient of the MSGR surface got flatter\nalong the low-velocity area (red line) but steeper along the high-velocity\narea (blue line). The wall shear stress had direct relationship to\nthe velocity gradient; thus, the wall shear stress along the span\nof the MSGR surface was relevant to the low- and high-velocity areas.\nThe integral of the wall shear stress over the entire surface was\nthe total friction drag, which was the synergistic DR effect of streaks. Figure 7 Velocity\ncontours and velocity profiles on different bionic surfaces.\n(a) Velocity contours of R, DCR, EGR, and MSGR surfaces at a distance\nof z = 0.1δ from the bottom in a wall-parallel\nplane. The flow direction is indicated by arrows. Note that the blue\narrows are consistent in length at the inlet, the lengths of the red\nand black arrows at the outlet are different at the MSGR surface,\nand the green arrows are uniform in the other cases. (b) Velocity\nvariation of R, DCR, EGR, and MSGR in the spanwise direction at different\nwall-normal distances in the boundary layer. The black line indicates\na position in the y -direction at a distance of 3100\nμm from the inlet. (c) Velocity contours of MSGR, R, and F surfaces\nin the x – z plane at a distance\nof 3100 μm from the inlet. (d) Velocity profile in the groove\nregion corresponding to (c). In addition, the MSGR surface could be deemed to\nbe distributed\nroughness on an F surface, and the roughness Reynolds number was calculated\nto be 55 based on Re k = ρ u k h /μ, where u k denoted the velocity at the peak roughness height (i.e., riblet\nheight h 1 ). The critical roughness Reynolds\nnumber of induced bypass transition was approximately 250. 40 Therefore, the roughness Reynolds number was\nmuch smaller than the critical value. This suggests that MSGRs, as\nmicro-roughness elements placed within the boundary layer, could generate\nstable low- and high-velocity streaks without causing bypass transitions.\nTaken together, the presented MSGR surface could generate steady low-\nand high-velocity streaks and reduce the velocity gradient in the\nboundary layer, thus achieving DR. To explore why the DR effect\nof the flexible MSGR surface is better\nthan that of the MSGR surface, Figure 8 a shows the velocity contours of both surfaces at the\nsame position. A small velocity was generated in the near-wall region\nof the flexible MSGR surface, while the fluid velocity in the near-wall\nregion of the MSGR surface was almost 0. Velocity slips were produced\nin the flexible MSGR surface, which further reduced the velocity gradient\nin the boundary layer. In addition, the flexible MSGR surface was\nslightly deformed by fluid flow, as shown in Figure 8 b,c. At the inlet velocity of 1 m/s, the\nmaximum deformation of the flexible MSGR surface was 5.64 × 10 –9 m, which was significantly larger than that of the\nMSGR surface and effectively absorbed turbulent pulsation. Therefore,\nthe flexible MSGR surface showed superior DR effects compared with\nthe MSGR surface. However, greater deformation displacement did not\nmean better DR performance of the surface. When the deformation of\nthe flexible riblet in the downstream and spanwise directions gradually\nincreased, the basic shape of the riblet changed, and the DR effect\ndiminished. The elastic modulus was an important factor in maintaining\nthe shape, which explained why the flexible MSGR surface with an elastic\nmodulus of 4.592 MPa had the best DR performance. Figure 8 Velocity and displacement\ncontours on the MSGR surface and the\nflexible MSGR surface. (a) Velocity contours, (b) total displacement,\nand (c) normal displacement on the MSGR surface and the flexible MSGR\nsurface, where the flexible MSGR surface was made of PDMS and curing\nagent in the ratio of 10:1. 4.2 Efficient Antifouling Effect of the Flexible\nMSGR Surface The attachment point theory indicated that organisms\npreferred to attach to shaped surfaces with more contact points, 23 which explained the difference in the attachment\nof organisms on different bionic surfaces in static antifouling experiments.\nHowever, the contact points of organisms on the surface were variable\nin dynamic testing. By predicting the physical pathway of pollutants\nvia analyzing the flow characteristics adjacent to the various bionic\nsurfaces, the possible antifouling performance of bionic surfaces\nwas explained physically. Notably, the flow between protruding riblets\ncould be divided into main and secondary streams, as shown in Figure S5 . For example, in the R and EGR surfaces,\nthe red and blue curves represented the main and secondary streams,\nrespectively. The EGR surface with asymmetric intersections enabled\nthe flow to partially enter or leave the riblet gap to form a secondary\nstream. Figure 9 a illustrates the velocity distributions of a single riblet at 0.1δ\nheight from the bottom of different rigid bionic surfaces. Because\nno geometric factors interfered with the flow, the flow velocity of\nthe main stream was uniform on the R surface. In contrast, the flow\non the DCR surface was affected by small vortices, and thus, the main\nstream was locally decelerated, as shown by the dashed box in Figure 9 a. The small vortex\noriginated from the rotating flow of the riblet gap in the bottom\npattern. In addition, the secondary stream in the EGR and MSGR surfaces\ncaused local flow communication between adjacent grooves. The secondary\nstream weakened the small vortex near the riblet gap, alleviating\nthe main stream deceleration in the groove. It was worth noting that\nthe flow velocity of the main stream on the MSGR surface was much\nmore uniform than that on the EGR surface, which might be because\nalmost no isolated rotating vortex existed in the groove of the MSGR\nsurface, as shown in Figure 9 b. Figure 9 c presents the velocity distributions of the x -component\nat 0.1δ height from the bottom of different rigid bionic surfaces.\nThe flow velocity in the groove was similar, but a slight difference\nwas observed near the riblet gap. The secondary stream was observed\nnear the riblet gap on the MSGR and EGR surfaces but not on the R\nand DCR surfaces. The secondary stream on the MSGR surface was significantly\nstronger than that on the EGR surface, leading to almost no vortex\nnear the riblet gap; the main stream velocity in the groove was more\nuniform. As shown in Figure 9 d, due to the high- and low-velocity streaks in the MSGR surface,\nthe secondary stream was enhanced, and the residence time of pollutants\nwas shortened. In detail, the secondary stream could pass through\nthe riblet gap inward and outward, breaking the isolated rotating\nvortex in the groove and reducing the residence time of pollutants\nat the bottom. In addition, high- and low-velocity streaks on the\nMSGR surface could reduce the selectivity of pollutants, namely, the\nsynergistic antifouling effect of streaks. Figure 9 Velocity contours and\nflow fields on different rigid bionic surfaces.\n(a) Velocity distribution of a single riblet with a height of 0.1δ\nfrom the bottom of different bionic surfaces. (b) Path lines in y – z planes in the groove region\ncorresponding to the dashed box in (a), and the velocity distributions\nof (c) x - and (d) y -components at\na height of 0.1δ from the bottom on different surfaces. Compared with the MSGR surface, the flexible MSGR\nsurface had certain\nhydrophobicity and lower surface energy, which improved its adhesion\nresistance and further enhanced its antifouling performance."
} | 4,394 |
30895699 | null | s2 | 6,647 | {
"abstract": "Syntrophy is essential for the efficient conversion of organic carbon to methane in natural and constructed environments, but little is known about the enzymes involved in syntrophic carbon and electron flow. Syntrophus aciditrophicus strain SB syntrophically degrades benzoate and cyclohexane-1-carboxylate and catalyses the novel synthesis of benzoate and cyclohexane-1-carboxylate from crotonate. We used proteomic, biochemical and metabolomic approaches to determine what enzymes are used for fatty, aromatic and alicyclic acid degradation versus for benzoate and cyclohexane-1-carboxylate synthesis. Enzymes involved in the metabolism of cyclohex-1,5-diene carboxyl-CoA to acetyl-CoA were in high abundance in S. aciditrophicus cells grown in pure culture on crotonate and in coculture with Methanospirillum hungatei on crotonate, benzoate or cyclohexane-1-carboxylate. Incorporation of "
} | 223 |
39128935 | PMC11317521 | pmc | 6,648 | {
"abstract": "Intertidal algae may adapt to environmental challenges by acquiring genes from other organisms and relying on symbiotic microorganisms. Here, we obtained a symbiont-free and chromosome-level genome of Pyropia haitanensis (47.2 Mb), a type of intertidal algae, by using multiple symbiont screening methods. We identified 286 horizontal gene transfer (HGT) genes, 251 of which harbored transposable elements (TEs), reflecting the importance of TEs for facilitating the transfer of genes into P. haitanensis . Notably, the bulked segregant analysis revealed that two HGT genes, sirohydrochlorin ferrochelatase and peptide-methionine (R)-S-oxide reductase, play a significant role in the adaptation of P. haitanensis to heat stress. Besides, we found Pseudomonas, Actinobacteria, and Bacteroidetes are the major taxa among the symbiotic bacteria of P. haitanensis (nearly 50% of the HGT gene donors). Among of them, a heat-tolerant actinobacterial strain ( Saccharothrix sp.) was isolated and revealed to be associated with the heat tolerance of P. haitanensis through its regulatory effects on the genes involved in proline synthesis ( proC ), redox homeostasis ( ggt ), and protein folding ( HSP20 ). These findings contribute to our understanding of the adaptive evolution of intertidal algae, expanding our knowledge of the HGT genes and symbiotic microorganisms to enhance their resilience and survival in challenging intertidal environments.",
"introduction": "Introduction Red algae have thrived on Earth for more than 1.2 billion years, evolving into a unique lineage of photosynthetic eukaryotes 1 that were the first to adapt to intertidal environments 2 . They are characterized by their low evolutionary status, rich diversity, structurally simple yet diverse forms, strong resistance to stress, and economic value 3 , 4 . Moreover, red algae play a dual role as both the first eukaryotic hosts involved in primary endosymbiosis and as the plastid donors involved in secondary endosymbiosis, thereby endowing them with a combination of ancestral land plant-like stress resistance mechanisms and their own distinct adaptations 5 , 6 . Therefore, intertidal red algae are crucial subjects for studies on adaptive evolution. In recent years, global climate changes and associated factors, such as high temperatures, high light intensity, hyposaline, and disease outbreaks, have significantly restricted the sustainable development of seaweed cultivation 7 , 8 . A previous study found that temperature significantly affects seaweed cultivation, leading to a gradual northward shift in the cultivation zones of various red algal species 9 . Thus, elucidating the adaptive evolutionary mechanisms of intertidal red algae can provide new insights into plant evolution and genetic resources for breeding stress-resistant varieties. To adapt to intertidal environments, red algae may have undergone genome reduction 2 , 10 , 11 . However, intertidal red algae remain highly resistant to stress, implying they may have acquired genes related to stress adaptations at critical points during evolution. Horizontal gene transfer (HGT) might promote functional convergence and the adaptability of red algae 11 – 13 . For example, the HGT genes associated with heat stress responses in Cyanidiophyceae ( Galdieria and Cyanidioschyzon ) include homologs of genes encoding heat shock protein 20, thermostable α-xylosidase, thermostable β-xylosidase, thioredoxin oxidoreductase, and a putative glutathione-specific γ-glutamylcyclotransferase 2, which can decrease the damage caused by high-temperature-induced free radicals 14 . Similarly, Pyropia haitanensis , an intertidal seaweed species, acquired unique lipoxygenase genes that mediate complex chemical defenses from bacteria, while also obtaining carbonic anhydrase (CA) genes that enhance survival during the sporophyte stage as well as carbon utilization 13 . Wang et al. 12 identified 51 genes from prokaryotes that were acquired by Pyropia yezoensis through HGT, including genes encoding superoxide dismutase (SOD), CAs, N-acyl- d -glucosamine 2-epimerase, glycine N-methyltransferase, and peroxidase. Thus, in addition to genome simplification, adaptive HGT may have also been a major factor contributing to the evolution of the genomes of red algae. The evolutionary interaction between plants and microorganisms enabled plants to colonize land through the evolution of ancient gene modules and lineage-specific specializations more than 450 million years ago 15 . Wang et al. 16 integrated genome-wide association studies (GWAS), microbiome-wide association studies (MWAS), and microbiome genome-wide association studies (mGWAS) to identify 257 rhizoplane microbial biomarkers associated with six key agronomic traits (e.g., top second leaf width, main stem width, panicle diameter of the main stem) of Setaria italica , and screened four beneficial microorganisms that promote seedling height and root length through selective separation culture medium. Therefore, precise microbiome management facilitated the development of microbial inoculants that can increase crop yield and quality 16 , 17 . Similarly, the seaweed surface harbors highly diverse microbial communities, creating a unique microenvironment known as the “phycosphere” 18 . Phycosphere microorganisms differ significantly from those in the surrounding seawater in terms of composition and function, and the community structure can also undergo significant changes under different developmental or growth conditions 19 – 22 . Kessler et al. 23 found that Ulva is able to cultivate its microbial community by releasing chemical attractants and carbon sources. Among them, the dimethylsulfonopropionate (DMSP) released by Ulva can be perceived and utilized by bacteria with the DMSP demethylase gene (dmdA), contributing to Ulva’s growth and morphogenesis. Deutsch et al. 24 demonstrated that endophytic bacteria ( Bacillus subtilis ) isolated from Ulva sp. can be reintroduced into their original host and influence the biodiversity of associated microbial communities. This interaction may aid in protecting Ulva sp. from pathogens and other opportunistic microorganisms. In summary, highly diverse and taxonomically specific microbial communities may be closely related to the adaptation of seaweeds, and identifying a pathway through microbiota manipulation is also important for improving seaweed aquaculture 25 . However, it is unclear which core phycosphere microorganisms are involved in key HGT events and how they regulate seaweed stress responses. Here, we propose that specific microbial taxa within the phycosphere community may play pivotal roles as potential donors or facilitators of HGT events, thus impacting the abiotic stress tolerance of P. haitanensis . To test this hypothesis, this study constructed a high-quality P. haitanensis genome and identified HGT events and the donors of HGT genes. Furthermore, a bulked segregant analysis (BSA) was performed to identify linked quantitative trait loci and candidate HGT genes associated with the high-temperature tolerance of P. haitanensis . Additionally, we analyzed the changes in the microbial community structure in different P. haitanensis strains that varied regarding temperature tolerance. We also isolated the beneficial bacteria via selective medium culture, enhancing the high-temperature tolerance of P. haitanensis . The study results provide new insights into the stress resistance of intertidal seaweeds as well as genes potentially useful for breeding novel stress-resistant germplasm.",
"discussion": "Discussion In land plants, HGT genes frequently accumulate, replicate, or undergo functional divergence within descendant populations, thereby contributing to diversification and adaptive evolution. Researchers have identified 593 gene families transferred to both charophytes and land plants, with two major HGT events associated with the early evolution of streptophytes (first events) and the origin of land plants (second events), explaining how land plants acquired a large number of genes in their early evolutionary stages 26 . In this study, 55 HGT gene families were identified in Pyropia / Porphyra spp., which is the most HGT family among the 9 red algae genomes that have been reported. Specifically, the HGT genes in Pyropia/Porphyra spp. are mainly related to the metabolism (energy metabolism, lipid metabolism, and amino acid metabolism, etc.), and also participate in the regulation of cellular processes and genetic information processing, such as replication and repair, fold, sorting and degradation, as well as transport and catabolism (Supplementary Fig. 14 ). Moreover, these pathways have been confirmed to participate in the response mechanisms of Pyropia / Porphyra spp. to environmental stressors such as high temperature 27 , hypersaline stress 28 , hyposaline stress 29 , dehydration 30 and high light intensity 31 . This indicated that HGTs enabled Pyropia/Porphyra spp. to acquire crucial genes with diverse functions that facilitated adaptations to intertidal zone environments, especially under genome reduction conditions. Twenty-four HGT gene families are common to the three Pyropia / Porphyra spp. examined in this study. For example, the SOD 32 , methyltransferase 33 , and E3 ubiquitin–protein ligase 34 , 35 gene families are closely related to the abiotic stress resistance of Pyropia / Porphyra spp. Similarly, the HGT genes encoding methionine S-methyltransferase-like proteins are associated with plant salt tolerance 26 , 36 . The HGT genes unique to P. haitanensis (i.e., not in P. yezoensis and P. umbilicalis ), including HSP-encoding genes, autophagy-related genes, and DNA repair-related genes, may have contributed to the adaptation of P. haitanensis to high-temperature conditions at relatively low latitudes 27 , 37 , 38 . Horizontal gene transfer events occur in streptophytes, and they are also a major reason for the functional convergence in intertidal red algae with a unique evolutionary status. Additionally, TEs considered vital components of genomes, often promote HGTs and genome rearrangements while also facilitating the acquisition of genes that confer selective advantages to the host 39 , 40 . In the present study, we determined that of the 286 HGT genes identified in P. haitanensis , 265 (e.g., HSP20 , proC , sirB , MSRB , and rpoD ) are associated with TE insertions (Fig. 1c ). These findings reflect the close association between either TE insertions and HGT events in P. haitanensis . For many multicellular eukaryotes, the number of genes in the symbiotic microbial community exceeds the number of genes in their own genomes, making the associated microbes important sources of genetic diversity and genes mediating adaptive evolution 41 , 42 . Bacteria are typically the primary donors of genes that are horizontally transferred to plants 26 , 43 . In accordance with this earlier finding, in the current study, 98% of the HGT genes in P. haitanensis were derived from bacteria (Fig. 1c , Supplementary Fig. 5 ). A combined analysis of bacterial donors, genome-filtered microbial datasets, and the core microbiota in the phycosphere of P. haitanensis collected from natural coastal regions revealed that the symbiotic bacteria in P. haitanensis are primarily from three taxa ( Pseudomonas , Actinobacteria, and Bacteroidetes), accounting for nearly 50% of the potential HGT gene donors (Supplementary Fig. 5 , Supplementary Fig. 11 ). Lu et al. 22 recently reported that 14 core genera from eight families belonging to the phyla Proteobacteria, Bacteroidota, Verrucomicrobiota, and Actinobacteriota account for an average of 43.5% ( Gelidium sp.), 53.9% ( Grateloupia sp.), 58.3% ( Ulva sp.), and 48.8% ( Saccharina sp.) of all phycosphere bacteria, but only 5.7% and 1.5% of the bacteria in seawater and sediment samples, respectively. Accordingly, there appears to be a close relationship between these core phycosphere bacteria and seaweeds. Therefore, a comprehensive analysis of the key HGT gene donors within the core bacteria in the P. haitanensis phycosphere is critical for further clarifying the interactions between algae and microbes as well as their adaptation to intertidal zones. Further analyses involving amplicon sequencing, isolation, and co-culturing showed that the actinobacterium Saccharothrix sp. significantly enhances the high-temperature tolerance of P. haitanensis (Supplementary Fig. 9 , Supplementary Fig. 10 ). Similarly, Hmani et al. 44 found that inoculating Rathayibacter festucae IH2 (Actinobacteria) and Roseovarius aestuarii G8 (Proteobacteria) at 18 °C promotes Ulva growth but inhibits it at 30 °C. Interestingly, this inhibitory effect is alleviated by additional inoculation of Roseovarius sp. MS2 (Proteobacteria). This indicates a close and complex relationship between seaweeds and their associated microorganisms. The metagenomic analysis of the community composition and functional genes revealed that the Saccharothrix sp. treatment group had the strongest correlation with proC and ggt ( P < 0.01; Fig. 3e ). The proC gene, which was acquired from actinobacteria via HGT, is related to proline synthesis. Under heat stress conditions, treatment with Saccharothrix sp . not only promoted the upregulation of genes related to the proline synthesis pathway but also increased the proline content of P. haitanensis (Supplementary Fig. 10D , Supplementary Fig. 11B ). Proline serves as an osmoprotectant, antioxidant, and signaling molecule that regulates the stress responses of higher plants and Pyropia spp 45 – 47 . Similarly, studies on Ulva 48 , Chlamydomonas reinhardtii 49 and Ectocarpus siliculosus 50 have found that abiotic stress also significantly induces the accumulation of proline in organisms. Earlier research indicated GGT (E.C.2.3.2.2) metabolizes extracellular reduced glutathione, thereby helping to salvage extracellular glutathione, while also potentially contributing to the control of the extracellular redox state 51 . Glutathione levels must increase rapidly during the initial exposure to salt stress for P. yezoensis thalli to mitigate the effects of ROS bursts 52 . Additionally, HSP20 , uvrD , AMY , and fabD were also correlated with the Saccharothrix sp. treatment ( P < 0.05; Fig. 3e ). This finding highlights the importance of certain genes acquired through HGT for regulating the synthesis of critical metabolites, DNA repair, and protein folding during the response of intertidal algae to abiotic stress. Furthermore, the addition of Saccharothrix sp. stabilizes the complex microbial community structure of P. haitanensis under heat-stress conditions. The complexity and stability of microbial networks tend to increase in response to global warming 53 . Hence, appropriately regulating the core microbiota associated with the stability and complexity of symbiotic communities is an important approach. This helps ensure that P. haitanensis can adapt to changes in intertidal environmental conditions. In conclusion, this study suggests how HGT genes from bacteria, especially actinobacteria (e.g., Saccharothrix sp.), can mediate the adaptation of P. haitanensis to heat stress by enhancing proline synthesis and stabilizing the phycosphere microbial community. The present study confirmed the crucial role of key microbiota in the resistance of seaweed to environmental stresses. However, it is based solely on the screening results of specific microbes associated with high-temperature resistant strains. A bacterial strain was isolated using selective culture media, which is currently a common utilization method for rhizosphere or gut microbiota, namely by isolating superior strains to develop microbial fertilizers, microbial pesticides, probiotics, prebiotics, and other bioproducts 54 – 56 . However, how to fully utilize the entire microbiome to enhance the host’s stress resistance at a holistic level and how to transition from applying exogenous beneficial microbes to activating the inherent overall function of the microbiome in situ are core issues that urgently need to be addressed 54 . For the environmentally dominated variable rhizosphere microbiome, developing high-throughput microbial culture-omics technologies to isolate and identify a richer set of beneficial microbes and enhance their application potential is essential. For the host-genetics-determined microbiome, employing mGWAS and gene editing techniques to explore genetic variations and functional genes that dominate the symbiotic microbiome and elucidating the molecular mechanisms and regulatory networks by which hosts recruit beneficial microbes are crucial for harnessing the full function of the entire microbiome in situ 16 , 57 ."
} | 4,225 |
33957955 | PMC8101122 | pmc | 6,650 | {
"abstract": "Plant-biomass-based nanomaterials have attracted great interest recently for their potential to replace petroleum-sourced polymeric materials for sustained economic development. However, challenges associated with sustainable production of lignocellulosic nanoscale polymeric materials (NPMs) need to be addressed. Producing materials from lignocellulosic biomass is a value-added proposition compared with fuel-centric approach. This report focuses on recent progress made in understanding NPMs—specifically lignin nanoparticles (LNPs) and cellulosic nanomaterials (CNMs)—and their sustainable production. Special attention is focused on understanding key issues in nano-level deconstruction of cell walls and utilization of key properties of the resultant NPMs to allow flexibility in production to promote sustainability. Specifically, suitable processes for producing LNPs and their potential for scaled-up production, along with the resultant LNP properties and prospective applications, are discussed. In the case of CNMs, terminologies such as cellulose nanocrystals (CNCs) and cellulose nanofibrils (CNFs) used in the literature are examined. The term cellulose nano-whiskers (CNWs) is used here to describe a class of CNMs that has a morphology similar to CNCs but without specifying its crystallinity, because most applications of CNCs do not need its crystalline characteristic. Additionally, progress in enzymatic processing and drying of NPMs is also summarized. Finally, the report provides some perspective of future research that is likely to result in commercialization of plant-based NPMs.",
"conclusion": "Conclusions and future outlook Economic and sustainable production of plant-based NPMs, especially CNMs, remains one of the main barriers to commercialization of NPM-based products. Exploration of the utility of lignin-based NPMs, such as LNPs, is still at an early stage, in terms of both production and utilization. With continued research, we expect that sustainable and commercially viable LNP production techniques will be developed. Especially interesting are techniques that can be integrated into the plant biomass fractionation process, such as AHF [ 43 , 45 , 66 ], or techniques that could use spent liquors from commercial wood pulping directly without purification and drying in between. Surface functionality of LNPs can further facilitate the development of novel LNP-based products in different new markets for lignin valorization. Examples of these new products are particles for drug delivery [ 62 , 87 ], enzyme immobilization [ 83 ], or sun screen applications [ 56 , 250 ], and their dispersing ability and UV-protective properties make LNPs attractive for paints, coatings, and cosmetics. In many applications, production of LNPs with visually appealing color, unlike the dark brown color of commercial technical lignin, are favorable. Various applications have very different demands for the LNP material, hence future research should also focus on comparing methods and finding the best particle preparation method for different applications. Significant research effort in both production and utilization of cellulose-based NPMs (i.e., CNMs) has been deployed. Production processes using concentrated mineral acid hydrolysis, pure mechanical fibrillation, endoglucanases, and TEMPO-mediated oxidation treatments have been scaled-up for application research. Addressing concerns over environmental impact and production economics due to high energy input and difficulties in chemical recovery associated with these early CNM production processes will be a great challenge. Recent research trends and funding, however, are heavily focused on new CNM-based product development using CNMs from these early production techniques. Although new product development is important, addressing CNM production economics and sustainability is a critical prerequisite for commercialization. Some new research focus is needed toward the novel CNM production processes that can address low-cost and sustainable production. In this progress report, we have provided a few promising process perspectives, such as concentrated dicarboxylic acid hydrolysis for integrated production of CNCs with CNFs, and the use of CNWs to substitute for most CNC applications. Moreover, enzymatic treatment remains highly attractive for CNM production. Post-fibrillation endoglucanase treatment can be effective to break up fibril aggregates for producing CNWs. With the development of novel enzymes, such as new bacterial cellulases and LPMOs, new concepts for utilizing specialty enzymes, such as integrating CNM production into a biorefinery concept as presented in this report, are worthy of consideration. Dewatering is another challenge for transportation, drying, and applications of CNMs in hydrophobic media. Novel drying approaches that can avoid CNM aggregation and improve CNM redispersibility and drying energy efficiency also need to be developed. For large-volume applications, such as for papermaking, on-site production of CNFs or CNMs is recommended for potential savings in production and transportation. Redispersion of LNPs after drying is not a problem, and dewatering is also less of a problem than for CNMs. Finally, future product development should focus on [ 251 ] (1) low-cost products with marginal performance improvement to substitute for existing petroleum-based products (i.e., drop-in market product); (2) novel usages with unique performance properties engineered to display orders of magnitude performance improvement, and (3) low-cost and large-volume applications from the forest management perspective."
} | 1,410 |
36322646 | PMC9629744 | pmc | 6,651 | {
"abstract": "We analyze visual processing capabilities of a large-scale model for area V1 that arguably provides the most comprehensive accumulation of anatomical and neurophysiological data to date. We find that this brain-like neural network model can reproduce a number of characteristic visual processing capabilities of the brain, in particular the capability to solve diverse visual processing tasks, also on temporally dispersed visual information, with remarkable robustness to noise. This V1 model, whose architecture and neurons markedly differ from those of deep neural networks used in current artificial intelligence (AI), such as convolutional neural networks (CNNs), also reproduces a number of characteristic neural coding properties of the brain, which provides explanations for its superior noise robustness. Because visual processing is substantially more energy efficient in the brain compared with CNNs in AI, such brain-like neural networks are likely to have an impact on future technology: as blueprints for visual processing in more energy-efficient neuromorphic hardware.",
"introduction": "INTRODUCTION The comprehensive model ( 1 ) for a patch of cortical area V1 in mouse provides an unprecedented window into the dynamics of this brain area. We show that it also provides a unique tool for studying brain-style visual processing and neural coding. The architecture of V1 exhibits an interesting combination of feedforward and recurrent connectivity: Neurons are distributed over several parallel two-dimensional (2D) sheets ( Fig. 1A ), commonly referred to in neuroscience as layers or laminae. The neurons are recurrently connected, but not randomly or in an all-to-all manner. Rather, synaptic connections exist primarily between nearby neurons, both within a layer and between layers. Connectivity between layers supports a strong feedforward stream of visual information from L4 to L2/3 to L5/6, which is complemented by a host of recurrent loops. The dominance of short connections makes it possible to combine in V1 extensive recurrent connectivity with a really small total wire length, which is essential for its physical realization. Fi g . 1. V1 model of ( 1 ). ( A ) The model consists of four classes of neurons on five layers. It comes together with a model for LGN, which transforms visual inputs into input currents to neurons in the V1 model. The LGN model receives visual input from an oval in the central part of an image ( 1 ). ( B ) The model contains one excitatory and three inhibitory neuron classes. Each dot denotes the position of a neuron. ( C ) The data-based base connection probabilities of ( 1 ) depend on the cell class to which the presynaptic (row labels) and postsynaptic neuron (column labels) belongs. White grid cells denote unknown values. ( D ) The base connection probability from (C) is multiplied according to ( 1 ) for any given pair of neurons by an exponentially decaying factor that depends on the lateral distance between them. Note that the illustrations in (A), (C), and (D) were created by us and derived from the publicly available data provided in ( 1 ). ( E ) Spike outputs of two randomly selected neurons from the V1 model for 10 trials with the same input (a trial of visual change detection task for natural images), using the noise model of ( 1 ). ( F ) Same as in (E) but for the version of the data-driven noise model with s = q = 2 that we used as default-noise model during testing. It causes substantially larger trial-to-trial variability. The model of ( 1 ) also integrates, besides these anatomical details, a host of neurophysiological data about area V1. The point neuron version of this model that we are considering uses generalized leaky integrate-and-fire (LIF) neurons, more precisely GLIF 3 neurons. These have, in addition to the membrane potential, two further hidden variables that model slower processes in biological neurons. The large diversity of neurons in the brain is reflected in the model of ( 1 ) through the use of 111 different types of GLIF 3 neuron models that have each been fitted to experimental data in the Allen Brain Atlas ( 2 ). The original model of ( 1 ) is not able to solve nontrivial computing tasks, because its synaptic weights were chosen on the basis of sparse experimental data about the mean and variance of synaptic weights. In contrast, synaptic weights in the living brain are individually tuned through a host of synaptic plasticity processes, and these processes induce higher-order correlations between weights that are crucial for computing capabilities of the network. At present, we do not have enough data about these plasticity processes to reproduce them in a model. However, we can address the question of what visual processing capabilities are supported by the model if synaptic weights are aligned for visual processing tasks through stochastic gradient descent. We applied this strategy to five different visual processing tasks that have commonly been considered in biological experiments ( 3 – 8 ). Afterward, our model achieved high accuracy simultaneously for all five tasks while working in a biologically realistic sparse firing regime close to criticality ( 9 , 10 ). Unexpectedly, its performance level remained in the same high-performance regime as the brain, even when we subjected the V1 model to noise in the images and in the network that it had not encountered during training. We demonstrate that this out-of-distribution (OOD) generalization capability of the V1 model with regard to new perturbations is far superior to that of convolutional neural networks (CNNs). We provide an explanation for that through an analysis of neural coding properties of these two types of models: Both use high-dimensional neural codes for images. However, the neural representation in the model of ( 1 ) is more robust because it uses, like the brain ( 11 ), a power law for the explained variance in higher principal components analysis (PCA) components that is close to a theoretically optimal compromise between the goal to be sensitive to details of visual inputs and the goal to be robust to noise from the visual input and within the network. In contrast, neural codes in CNNs were shown to have a different power law ( 12 ) that favors the first (coding precision) over the second goal (noise robustness). In addition, we demonstrate that the model of ( 1 ) preferentially uses those dimensions of population activity for coding that are orthogonal to the largest noise dimensions, like the brain does ( 3 ). Together, our results show that the currently available anatomical and neurophysiological data, as compiled in ( 1 ), provide the basis for a new generation of neural network models for visual processing that can solve diverse visual processing capabilities in a highly robust manner. Furthermore, these neural network models provide new paradigms for neuromorphic computing because they combine versatility and robustness to noise with small total wire length and highly energy-efficient sparse activity.",
"discussion": "DISCUSSION We have demonstrated that the V1 model of ( 1 ), which arguably provides the largest currently available accumulation of anatomical and neurophysiological data on area V1 in the mouse brain, provides a window not only into brain dynamics but also into visual processing capabilities and neural coding properties that are entailed by these data. In particular, we found that this V1 model exhibits interesting advantages with regard to learning speed and visual processing performance over models that are closer to common artificial neural network models, such as RSNNs and CNNs. Furthermore, we have isolated concrete anatomical and neurophysiological features of the V1 that are responsible for that. CNNs are currently most commonly used for visual processing in artificial intelligence (AI). They were also inspired by some aspects of visual processing in the brain, especially the existence of simple and complex cells in area V1. However, a closer look shows that they differ from V1 in the brain in almost all other respects: with regard to their computational units (artificial neurons in CNNs versus spiking neurons in the brain), the diversity of their units (very few simple units versus a large diversity of neurons with different temporal dynamics), their large-scale architecture (usually feedforward, versus recurrent with laminar structure), their small-scale architecture (very simple network motifs versus a complex combination of feedforward and recurrent processing in cortical microcircuits), and total wire length (almost quadratic versus just linear growth with the number of processing neurons). V1 in the brain, however, also differs from CNNs with regard to two important visual processing capabilities: The brain is more versatile because it can solve a number of diverse visual tasks with the same synaptic weights, in particular also tasks that require integration of sequentially arriving visual information. In addition, visual processing in the brain is very noise robust, also to new types of noise (OOD generalization). We have shown here that the previously listed fundamental differences between the structure of V1 in the brain and CNNs are causally related to these two superior visual processing capabilities of the brain: The V1 model of ( 1 ), which integrates a large body of experimental data on area V1 in the brain, is able to perform similarly versatile and robust visual processing. Furthermore, we could identify concrete anatomical and neurophysiological features of the V1 model that are responsible for this. Because we can now reproduce these two important functional capabilities of area V1 in a model, we have a new research platform at our disposal for studying how neural coding properties of the brain emerge from its anatomical and neurophysiological features and how they are related to its visual processing capabilities. We have demonstrated here the feasibility of this new research strategy by applying it to the V1 model, an analysis of its neural coding that had already been used successfully for elucidating neural codes for images in area V1 of the brain: We analyzed the eigenspectrum of the explained variance of principal components of its neural codes for images. We found that the listed structural features of V1 in the brain do in fact induce a salient feature of its neural coding strategy: The V1 model exhibits a similar power law for neural codes of images as the brain. In contrast, applying the same training process to CNNs, CNNs exhibit a power law with a substantially slower decay of the eigenspectrum. According to the theoretical analysis of ( 11 ), this implies that neural codes in CNNs are less noise robust. By regularizing CNNs ( 28 ) or training them with different methods ( 24 ), one can move the exponent of their eigenspectra closer to 1 + 2/ d , which can improve the robustness of CNNs. We have also shown that the anatomical and neurophysiological data on V1 that have been integrated into the V1 model suffice to reproduce a further salient aspect of neural coding in area V1 of the brain, where, according to ( 3 ), about 90% of the noise fluctuations in area V1 are constrained to dimensions of the population activity that are orthogonal to noise dimensions. We found that this is an emergent property of the V1 model of ( 1 ). On a more general level, we have shown that the V1 model of ( 1 ) can be seen as the first prototype of a new generation of neural network models for visual processing that capture substantially more features of brain processing than CNNs. Further work is needed to tease apart the functional implications of each of its structural features and to port similar advanced brain-like visual processing capabilities into simpler neural network models. Often one uses, instead of data-based models for neural networks of the brain, randomly connected recurrent networks of strongly simplified neuron models. In our experience, neural coding and computational properties of recurrent neural networks vary substantially in dependence on their connectivity structure and neuron models. This highlights the need to test brain-like features not only in abstract models but also in neural network models that integrate our available knowledge about the actual structure of these neural networks in the brain. Our method can also be applied to investigate more detailed models of V1, e.g., models that include data on the lattice of microcolumns of neurons in L5 ( 29 ) and on short-term plasticity ( 30 ) and functionally salient aspects of dendritic spikes ( 31 ). It also provides a paradigm for elucidating how anatomical and neurophysiological details of interconnected higher and lower brain areas carry out distributed computations, in particular how interaction of neurons in superficial layers of V1 with higher cortical areas enhances visual processing capabilities of V1. Although we have focused here on readout neurons in L5, the sparsely firing pyramidal cells in L2/3 of the trained V1 model contain already most of the information that is needed to solve the computational tasks of the network, and hence, they could potentially transmit this to higher areas: Readouts from these neurons (which might be seen as proxies for neurons in higher cortical areas that receive input from V1) can be trained to solve all five tasks with high accuracy (fig. S18). A substantial body of anatomical and neurophysiological data on higher cortical areas and their connectivity to V1 is currently available for that [see, e.g., ( 6 , 32 , 33 )]. We expect that deficits in visual processing capabilities of the V1 model, such as limited spatial integration of image features and a relatively short working memory time span, will disappear when the V1 model is combined with models of higher brain areas. In addition, neurons on L2/3 of the V1 model will then be placed into a biologically more realistic context, where they send computational results to higher areas and receive inputs from them. The analysis of neural coding in the V1 model has produced a number of predictions for future biological experiments. In particular, we have shown in Fig. 7E that correlated noise reduces the coding fidelity of the network but does not produce an a priori bound for its sensory discrimination capability [this had already been hypothesized by ( 4 )]. A further prediction of our model is that the PCA eigenspectrum of neural codes for inhibitory neurons does not obey a power law for higher dimensions (see Fig. 5H ). Last, the values of excitatory synaptic weights in V1 are predicted to generally shrink through training ( Fig. 3A , left), while inhibitory weights are predicted to become stronger ( Fig. 3A , right). Visual processing in the brain exhibits also with regard to two aspects of physical implementation two attractive features: Most synaptic connections in V1 are between nearby units, which is essential for an efficient physical realization of synaptic connections in neuromorphic hardware. This architectural feature is also likely to support faster learning ( Fig. 4A ). In addition, computations are carried out in V1 through event-based processing with very sparse firing activity. This computing regime not only is very energy efficient but also supports computations on tasks where temporal aspects play an important role, because it allows to let time represent itself in network computations. Since we have shown that both of these features can be reproduced in a corresponding neural network model for visual processing, this V1 model suggests that it will also be possible to recruit them for the design of substantially more energy-efficient neuromorphic implementations of visual processing ( 34 )."
} | 3,953 |
23841714 | null | s2 | 6,652 | {
"abstract": "Biofilms promote attachment of Vibrio cholerae in aquatic ecosystems and aid in transmission. Intracellular c-di-GMP levels that control biofilm development positively correlate with expression of Qrr sRNAs, which are transcribed when quorum sensing (QS) autoinducer levels are low. The Qrr sRNAs base-pair with and repress translation of hapR encoding the QS 'master regulator', hence increased c-di-GMP and biofilm development at low density were believed to be solely a consequence of Qrr/hapR pairing. We show that Qrr sRNAs also base-pair with and activate translation of the mRNA of a diguanylate cyclase (DGC), Vca0939; relieving an inhibitory structure in vca0939 that occludes the ribosome binding site. A nucleotide substitution in vca0939 disrupted sRNA/mRNA base-pairing and prevented vca0939 translation, while a compensating Qrr sRNA substitution restored pairing and Vca0939 levels. Qrr-dependent DGC activation led to c-di-GMP accumulation and biofilm development in V. cholerae. This represents the first description of (1) a DGC post-transcriptionally activated by direct pairing with an Hfq-dependent sRNA, and (2) control of a V. cholerae QS phenotype, independent of HapR. Thus, direct interactions of the same sRNAs with two mRNAs promote c-di-GMP-dependent biofilm formation by complementary mechanisms in V. cholerae; by negatively regulating HapR, and positively regulating the DGC Vca0939."
} | 353 |
35495465 | PMC9052389 | pmc | 6,653 | {
"abstract": "Cr( vi ) laden wastewaters generally comprise a range of multiple heavy metals such as Au( iii ) and Cu( ii ) with great toxicity. In the present study, cooperative cathode modification by biogenic Au nanoparticles (BioAu) reduced from aqueous Au( iii ) and in situ Cu( ii ) co-reduction were investigated for the first time to enhance Cr( vi ) removal in microbial fuel cells (MFCs). With the co-existence of Cu( ii ) in the catholyte, the MFC with carbon cloth modified with nanocomposites of multi-walled carbon nanotubes blended with BioAu (BioAu/MWCNT) obtained the highest Cr( vi ) removal rate (4.07 ± 0.01 mg L −1 h −1 ) and power density (309.34 ± 17.65 mW m −2 ), which were 2.73 and 3.30 times as high as those for the control, respectively. The enhancements were caused by BioAu/MWCNT composites and deposited reduzates of Cu( ii ) on the cathode surface, which increased the adsorption capacity, electronic conductivity and electrocatalytic activity of the cathode. This study provides an alternative approach for efficiently remediating co-contamination of multiple heavy metals and simultaneous bioenergy recovery.",
"conclusion": "4. Conclusions In this study, cooperative cathode modification by biogenic nano-Au reduced from Au( iii ) and in situ Cu( ii ) co-reduction was used to enhance Cr( vi ) removal in MFCs. The highest Cr( vi ) removal rate (4.07 ± 0.01 mg L −1 h −1 ) and power density (309.34 ± 17.65 mW m −2 ) were obtained in the BioAu/MWCNT-CrCu MFC, which were 2.73 and 3.30 times as high as those in the Bare-Cr MFC, respectively. Au( iii ) and Cu( ii ) are frequently detected with Cr( vi ) in wastewaters from electroplating and mining industries, this study shed a light on positive effects of concomitant heavy metals and their reduzates on mitigating the cathode deactivation in Cr( vi )-reducing MFCs.",
"introduction": "1. Introduction Hexavalent chromium (Cr( vi )), typically found in industrial wastewaters such as electroplating and mining wastewaters due to widespread industrial application, is a known extremely toxic heavy metal to living organisms. 1 Microbial fuel cells (MFCs) have recently shown promising results for recovering various heavy metals from wastewaters in addition to simultaneous organic wastewater treatment and bioelectricity generation. 2–4 In particular, the electrochemical reduction of Cr( vi ) in MFCs has been reported in the literature with variable degrees of success through the optimization of operation conditions, reactor architectures and cathode electrodes. 5–10 However, the non-conductive Cr( iii ) deposits reduced from Cr( vi ) on the cathode surface led to severe cathode deactivation, exerting negative effects on the electrochemical behavior of the cathode electrode. 6,10–12 Therefore, it should be put more efforts on ex situ or in situ improving the electronic conductivity and electrocatalytic activity of the cathode electrode for Cr( vi ) reduction. High concentration of Cr( vi ) is usually found together with multiple heavy metal ions ( e.g. Au( iii ), Cu( ii )) in the acidic wastewaters from the electroplating and mining industries. 13 On the other hand, chemical Au nanoparticles as electrode modifiers, especially decorating other nanomaterials such as multi-walled carbon nanotubes (MWCNTs), can significantly improve the electrochemical reduction of Cr( vi ). 1,14 Biogenic Au nanoparticles (BioAu), which can be recovered from wastewaters containing Au( iii ) ions by microorganisms such as Shewanella oneidensis , have been reported to possess higher electronic conductivity and electrocatalytic activity compared to the chemical counterpart. 15,16 Our previous work has demonstrated BioAu/MWCNT modification for the anode remarkably enhanced power output of MFCs. 16 However, the BioAu/MWCNT nanohybrids modified electrode, to our best knowledge, has never been attempted to use as the cathode to reduce Cr( vi ) in MFCs. Consequently, BioAu/MWCNT modification might be an ex situ strategy to improve the electrochemical properties of the cathode for Cr( vi ) reduction, which is certainly warranted further investigations. Regarding to the in situ strategy for improving the Cr( vi )-reducing cathode performance, we hypothesized that some co-existing heavy metals could exert positive effects due to their conductive reduzates deposited on the cathode surface. For example, previous studies have confirmed that the main product of Cu( ii ) reduction in MFC cathode (pH = 2.2–3.4) was pure Cu. 3,17 Since Cu possesses excellent conductivity and electrocatalytic activity, the interaction of cathode materials with in situ deposited Cu from Cu( ii ) reduction becomes crucial for the improved electrochemical properties of electrodes. The in situ deposition of Cu onto the cathode has been demonstrated to efficiently enhance continuous Cu( ii ) reduction, subsequent Cd( ii ) reduction as well as energy recovery. Furthermore, different cathode materials influenced the diversity of shapes and morphology of the deposited Cu, resulting in different active surface areas, and consequently the overall performance of MFCs. 17 Therefore, it would be reasonably expected that the co-existence of Cu( ii ) with Cr( vi ) in catholyte might mitigate the cathode deactivation and thereby facilitate Cr( vi ) reduction in MFCs. These effects have not been systematically investigated in literatures, especially when interacting with the BioAu/MWCNT modified electrode. Besides, the use of reduction products from Au( iii ) and Cu( ii ) to facilitate Cr( vi ) reduction is not trivial since Au( iii ) and Cu( ii ) often co-exist with Cr( vi ) in electroplating and mining wastewaters. This study aimed to promote the efficiency of Cr( vi ) removal in MFCs through ex situ and in situ improving the electrochemical properties of the cathode. The effects of cooperative cathode modification by BioAu/MWCNT nanohybrids and in situ Cu( ii ) co-reduction on Cr( vi ) removal in MFCs were systematically investigated. The performance of MFCs was evaluated in terms of cathodic Cr( vi ) and Cu( ii ) removal, anodic COD removal as well as electricity generation. The precipitations on the cathode surface after operation were defined by scanning electron microscopy with coupled energy dispersive spectroscopy (SEM-EDS) and X-ray photoelectron spectroscopy (XPS). This work reveals a new insight into the way to combat poisonous Cr( vi ) through other poisonous heavy metals co-existing in wastewaters.",
"discussion": "3. Results and discussion 3.1. Effects of BioAu/MWCNT ratio and BioAu loading amount on electrode In order to obtain the suitable BioAu/MWCNT ratio for electrode modification, effects of different BioAu/MWCNT ratios (1 : 0, 1 : 1, 1 : 2) on electrochemical characteristics of the carbon cloth were investigated when the BioAu loading amount was set at 0.83 ± 0.02 mg cm −2 . The electrochemical characteristics of different electrodes before operation were evaluated through measuring CV and EIS ( Fig. 1 ). As shown in Fig. 1A , there were no peaks in the CV curves of all the electrodes since no redox reactions happened in PBS. Whereas, there is a significant increase in current range of each modified electrode compared with that of the bare electrode, suggesting that the modified carbon cloths had a higher faradaic charge capacity and electron transfer efficiency possibly due to the physico-chemical properties of the modifiers. Obviously, the larger proportion of MWCNT powder occupied in the modifier, the higher faradaic current was observed in CV. The highest current range was found in the electrode with the BioAu/MWCNT ratio of 1 : 2, indicating that MWCNTs were favorable supports for BioAu modification because of their unique electrical and structural properties. 21 Anchoring of metal nanoparticles over MWCNTs is an effective strategy in improving the dispersion of nanoparticles, which increases the electrochemically available surface area and electrocatalytic active sites of electrodes. 22 Similar synergistic effects have also been found in other nanocomposite modification studies using MWCNTs blending with metal nanoparticles such as TiO 2 , Fe 3 O 4 , and SnO 2 . 21,23,24 Fig. 1 CV and EIS analysis of electrodes with different BioAu/MWCNT ratios (A and B) and different BioAu loading amounts (C and D) before operation. Furthermore, the interfacial electrochemical properties of modified electrodes were also evaluated by EIS. 25 Fig. 1B shows the Nyquist plots of all the electrodes. The x -intercept of a Nyquist plot represents R s , and the semicircle diameter indicates R ct . There were no distinct differences in R s of all the electrodes, whereas all the electrodes presented significant differences in the observed R ct . The R ct decreased with the increased proportion of MWCNT powder in the modifiers, signifying remarkable enhancements of the catalytic reaction and electron transfer efficiency at the electrodes with the addition of MWCNTs. Accordingly, the electrode with the BioAu/MWCNT ratio of 1 : 2 possessed the smallest R ct . The EIS results were in good agreement with the CV results. As the BioAu/MWCNT ratio was set at 1 : 2, effects of different BioAu loading amounts (0.40 ± 0.01, 0.83 ± 0.02, 1.84 ± 0.01 mg cm −2 ) on the electrochemical characteristics of the carbon cloth were studied as well. Similarly, the larger BioAu loading amount caused the higher faradaic current range of the CV curve ( Fig. 1C ), indicating that BioAu possessed the ability to facilitate electron transfer on the electrode. The largest BioAu loading amount (1.84 ± 0.01 mg cm −2 ) achieved the best electrochemical performance for the electrode. EIS analysis ( Fig. 1D ) further confirmed that the larger BioAu loading amount correspondingly reduced the R ct of the modified electrode. Alatraktchi et al. 26 also proposed that higher Au nanoparticle density led to higher power generation when Au nanoparticle modified carbon papers were applied as anodes in MFCs. Therefore, the BioAu/MWCNT ratio and BioAu loading amount were respectively set at 1 : 2 and 1.84 ± 0.01 mg cm −2 for the electrode modification in the subsequent experiments. The surface morphology of the bare and BioAu/MWCNT electrode was observed using SEM-EDS before operation ( Fig. 2A and E ). Compared with a smooth and clean surface of the bare electrode ( Fig. 2A ), there were substantial deposits with typical MWCNTs evenly attached on the BioAu/MWCNT electrode ( Fig. 2E ), resulting in a rougher and more crosslinked surface. 27 Au element was detected on the BioAu/MWCNT electrode by EDS, implying the successful modification of BioAu/MWCNT composites on the carbon cloth (ESI, Fig. S4 † ). Fig. 2 SEM images of the bare (A–D) and BioAu/MWCNT ((E–H) BioAu/MWCNT ratio: 1 : 2, BioAu loading amount: 1.84 ± 0.01 mg cm −2 ) electrode before and after operation. \n Table 1 presents surface characteristics of the two different electrodes. The SSA value of the BioAu/MWCNT electrode (66.97 ± 0.23 m 2 g −1 ) was 17.72 times as high as that of the bare electrode (3.78 ± 0.34 m 2 g −1 ), further confirming that BioAu/MWCNT composites gave rise to a larger surface area. The large surface area can facilitate rapid mass transfer and increase active reaction sites on materials. 28 Besides, the BioAu/MWCNT electrode (contact angle: 48.2 ± 0.7°) was much more hydrophilic than the bare electrode (contact angle: 110.4 ± 0.6°). This was opposite to the BioPd modification results in another study. 29 The materials with strong hydrophilicity could have faster electrochemical reactions due to the enhanced mass transfer on the solid–liquid interface. 30 In terms of the surface resistance, the BioAu/MWCNT electrode had a lower value than the bare electrode. Surface characteristics of the bare and BioAu/MWCNT (BioAu/MWCNT ratio: 1 : 2, BioAu loading amount: 1.84 ± 0.01 mg cm −2 ) electrode Electrode BET SSA (m 2 g −1 ) Contact angle (°) Resistance (Ω) Bare 3.78 ± 0.34 110.4 ± 0.6 7.5 ± 0.7 BioAu/MWCNT 66.97 ± 0.23 48.2 ± 0.7 6.31 ± 0.9 3.2. Electrode performance in Cr( vi )-reducing MFC \n Fig. 3 shows the performance of the Cr( vi )-reducing MFCs with the bare and BioAu/MWCNT electrode as cathodes. The voltage output ( Fig. 3A ) continuously descended as running time in both MFCs. This was mainly caused by the change of Cr( vi ) concentration and typically happened in Cr( vi )-reducing MFCs. 12,31 The maximum voltage output of the MFC with the BioAu/MWCNT electrode achieved 525.01 mV, which was 1.48 times as high as that of the MFC with the bare electrode (354.30 mV). As shown in Fig. 3B , the MFC with the BioAu/MWCNT electrode accordingly produced a maximum power density of 138.38 ± 6.36 mW m −2 , which was around 1.32 times as high as that of the MFC with the bare electrode (104.99 ± 4.99 mW m −2 ). From Fig. 3C , the lower internal resistance was also observed in the MFC with the BioAu/MWCNT electrode (194.43 ± 25.39 Ω) compared to that in the MFC with the bare electrode (305.05 ± 30.04 Ω). Fig. 3 Voltage outputs (A), power densities (B), polarization curves (C), and dissolved Cr( vi ) concentration changes (D) of Cr( vi )-reducing MFCs with different cathode electrodes. MWCNTs have been widely used to remove aqueous metal ions such as Cr( vi ) due to the excellent adsorption performance. 32 In addition, MWCNTs decorated with chemical Au nanoparticles have also been applied for Cr( vi ) detection because of their good electron transfer ability and electrocatalytic activity. 14 Therefore, in order to define the adsorption and electrochemical reduction functions for Cr( vi ) removal, each Cr( vi )-reducing MFC was operated with and without circuit connected ( Fig. 3D ). After 24 h open-circuit operation, the Cr( vi ) removal rate in the MFC with the BioAu/MWCNT electrode reached 0.66 ± 0.04 mg L −1 h −1 after 24 h, while the MFC with the bare electrode achieved 0.31 ± 0.02 mg L −1 h −1 . The Cr( vi ) removal mechanism under open-circuit condition was mainly the electrode adsorption, indicating that BioAu/MWCNT modification increased the adsorption amounts of aqueous Cr( vi ). Clearly, the Cr( vi ) removal remarkably enhanced during closed-circuit operation in both MFCs: extra Cr( vi ) of 52.93% was further removed in the MFC with the BioAu/MWCNT electrode compared with only 26.50% in the MFC with the bare electrode once the circuit connected, demonstrating that BioAu/MWCNT composites facilitated Cr( vi ) electrochemical reduction. The Cr( vi ) removal rate of the MFC with the BioAu/MWCNT electrode (2.86 ± 0.03 mg L −1 h −1 ) was 2.01 times as high as that in the MFC with the bare electrode (1.42 ± 0.04 mg L −1 h −1 ). Table 2 presents the comparative data of studies on abiotic Cr( vi ) reduction in similar two-chamber MFCs. Gangadharan et al. 5 and Gupta et al. 6 respectively investigated a liquid crystal polaroid glass electrode (LCPGE) and an alumina/nickel nanoparticles-dispersed carbon nanofiber electrode (AA:Ni-ACF/CNF) for Cr( vi ) removal in MFCs, and the Cr( vi ) removal rates in these works were lower than that in the present work ( Table 2 ). The results suggest that the excellent adsorption capacity and electrochemical activity of BioAu/MWCNT composites on the cathode electrode enhanced the power output and Cr( vi ) removal in the MFC. Comparison of studies on abiotic Cr( vi ) reduction in two-chamber MFCs a No. Anode (A)/Cathode (C) material Initial Cr( vi ) (mg L −1 ) and pH Other metals (mg L −1 ) in catholyte Power density (mW m −2 ) Cr( vi ) removal rate (mg L −1 h −1 ) Reference 1 Graphite plate (A/C) 200, 2.0 None 150 1.06 \n 7 \n 2 Graphite plate (A)/rutile-coated graphite plate (C) 26, 2.0 None NA 0.97 \n 8 \n 3 Graphite felt (A)/PPy/AQS-modified graphite felt (C) 20, 7.0 None 299.6 0.43 \n 9 \n 4 LCPGE (A/C) 100, 2.0 None 10 2.08 \n 5 \n 5 AA:Ni-ACF/CNF (A/C) 200, 2.0 None 1540 2.13 \n 6 \n 6 Carbon fiber felt (A/C) 250, 2.0 V( v ), 250 970.2 0.79 \n 10 \n 7 Graphite felt (A)/carbon rod (C) 50, 1.5 Fe( iii ), 150 225 9.4 \n 2 \n 8 Graphite felt (A)/BioAu/MWCNT modified carbon cloth (C) 100, 2.5 Cu( ii ), 400 309.34 4.07 This study a NA: not applicable; PPy: polypyrrole; AQS: 9,10-anthraquinone-2-sulfonic acid sodium salt; LCPGE: liquid crystal polarized glass electrode; AA:Ni-ACF/CNF: alumina/nickel nanoparticles-dispersed carbon nanofiber; BioAu/MWCNT: biogenic Au nanoparticles/multi-walled carbon nanotubes. 3.3. Effects of co-existing Cu( ii ) in catholyte The effects of co-existing Cu( ii ) (400 mg L −1 ) on Cr( vi ) removal in MFCs with different cathode electrodes were studied at an external resistance of 10 Ω ( Fig. 4 ). As shown in Fig. 4A , all the MFCs with the BioAu/MWCNT electrode produced higher voltage outputs than the MFCs with the bare electrode. In particular, the co-existing Cu( ii ) in catholyte further enhanced the electricity generation of MFCs. The maximum voltage (59.33 mV) was observed from the BioAu/MWCNT-CrCu MFC, which was 2.28 times as high as that of the bare-Cr (26.04 mV) MFC. Table 3 displays the maximum power densities, internal resistances and anodic COD removal of all the MFCs. Clearly, the BioAu/MWCNT-CrCu MFC obtained the highest power density of 309.34 ± 17.65 mW m −2 , which was 1.44 and 3.30 times as high as that of the BioAu/MWCNT-Cr (215.39 ± 21.21 mW m −2 ) and bare-Cr (93.82 ± 4.79 mW m −2 ) MFC, respectively, illustrating the role of Cu( ii ) in promoting the Cr( vi )-reducing MFCs performance. The co-existing Fe( iii ) (150 mg L −1 ) has also been reported to have a synergistic effect on Cr( vi ) removal in MFCs, but the current density was only increased by 27.27% compared with that in the absence of Fe( iii ). 2 Accordingly, the BioAu/MWCNT-CrCu MFC possessed the lowest internal resistance (124.42 ± 9.54 Ω), while the bare-Cr MFC had the highest one (259.52 ± 21.65 Ω). The anodic COD removal reached 79.66 ± 4.87% in the BioAu/MWCNT-CrCu MFC, which was increased by 78.69% compared to that in the bare-Cr MFC (44.58 ± 2.57%). Fig. 4 Voltage outputs (A), dissolved Cr( vi ) concentration changes (B), and dissolved Cu( ii ) concentration changes (C) of MFCs with different cathode electrodes for different heavy metals removal. Maximum power densities ( P max ), internal resistances, and anodic COD removal of different MFCs Group \n P \n max (mW m −2 ) Internal resistance (Ω) COD removal (%) Bare-Cr 93.82 ± 4.79 259.52 ± 21.65 44.58 ± 2.57 Bare-Cu 80.03 ± 5.01 239.17 ± 26.745 53.21 ± 1.67 Bare-CrCu 143.60 ± 12.46 202.09 ± 18.64 57.64 ± 3.58 BioAu/MWCNT-Cr 215.39 ± 21.21 197.64 ± 17.55 68.65 ± 2.93 BioAu/MWCNT-Cu 231.38 ± 13.53 162.32 ± 13.86 70.91 ± 1.76 BioAu/MWCNT-CrCu 309.34 ± 17.65 124.42 ± 9.54 79.66 ± 4.87 As seen from Fig. 4B , Cr( vi ) was removed more quickly in the MFCs with co-existing Cu( ii ) than MFCs without co-existing Cu( ii ). The BioAu/MWCNT-CrCu MFC obtained the highest Cr( vi ) removal rate (4.07 ± 0.01 mg L −1 h −1 ), which was 1.36 and 2.73 times as high as that from the BioAu/MWCNT-Cr (3.00 ± 0.02 mg L −1 h −1 ) and bare-Cr (1.49 ± 0.02 mg L −1 h −1 ) MFC, respectively, implying that the presence of Cu( ii ) accelerated the electrochemical reduction of Cr( vi ) in MFCs. In addition, the enhancement exhibited an increasing trend with the increased Cu( ii ) concentrations (from 50 mg L −1 to 400 mg L −1 ) and with the decreased external resistances (from 2000 Ω to 10 Ω), implying more Cu( ii ) ions and electrons were needed to exert synergistic effects of the co-existing Cu( ii ) for Cr( vi ) reduction (ESI, Fig. S2 and S3 † ). According to Table 2 , although it might not be appropriate to directly compare the Cr( vi ) removal efficiency due to different conditions applied in the studies, it still clearly shows that the present study obtained a noticeably higher Cr( vi ) removal rate than other studies, except Wang et al. 's 2 study. In their study, a lower pH (1.5) along with the presence of Fe( iii ), an efficient electron mediator, were used to obtain a higher Cr( vi ) removal rate (9.4 mg L −1 h −1 ) but a lower power density (225 mW m −2 ) than those in our study. 2 As seen in Fig. 4C , Cu( ii ) was simultaneously removed with Cr( vi ) from catholyte in MFCs, although the Cu( ii ) removal was slightly lower than that in MFCs with Cu( ii ) acting as the sole electron acceptor. The Cu( ii ) removals in the BioAu/MWCNT-CrCu and bare-CrCu MFC reached 89.10 ± 0.23% and 66.23 ± 0.98%, respectively, while those in the BioAu/MWCNT-Cu and bare-Cu MFC were 98.54 ± 0.48% and 84.93 ± 0.47%. This indicated that BioAu/MWCNT modification could also facilitate Cu( ii ) removal and the co-existing Cr( vi ) negatively affected Cu( ii ) reduction due to the non-conductive deposits generated from Cr( vi ) reduction on the cathode surface. 10 On the other hand, the deposited products of Cu( ii ) reduction on the cathode appreciably increased the conductivity throughout the cathode electrode, leading to the improved electricity generation and Cr( vi ) removal. 17 The bare and BioAu/MWCNT electrode were observed by SEM after 24 h-operation time ( Fig. 2 ). Compared with the corresponding electrodes before operation, some noticeable precipitates were generated on all of the electrode surfaces. In particular, the largest amount of precipitates was found on the BioAu/MWCNT electrode for Cr( vi ) and Cu( ii ) removal ( Fig. 2H ). This was consistent with the substantial reduction of Cr( vi ) and Cu( ii ) in MFCs ( Fig. 4 ). The BioAu/MWCNT electrode for Cr( vi ) and Cu( ii ) removal was further analyzed by XPS to determine the elemental compositions of precipitates on the surface ( Fig. 5 ). The XPS results showed the presence of Cr, Cu, C, O and Au signals ( Fig. 5A ). Detailed XPS scans of the Cr2p region ( Fig. 5B ) were observed Cr2p 1/2 and Cr2p 3/2 lines at 577.4 and 587.1 eV, respectively, confirming Cr( vi ) was electrochemically reduced to Cr( iii ) and recovered as Cr 2 O 3 . Similarly, Cu2p 3/2 and Cu2p 1/2 lines at 932.7 and 952.5 eV were respectively observed in Cu2p region ( Fig. 5C ), demonstrating that the reduction products of Cu( ii ) were Cu and Cu 2 O. Tao et al. 33 reported the same results about Cu( ii ) reduction products in MFCs. Au4f 7/2 line at 84.3 eV in Au4f region ( Fig. 5D ) together with SEM-EDS results proved the successful modification of BioAu/MWCNT composites on the electrode. Previous studies have found that non-conductive Cr( iii ) deposits on the electrode from Cr( vi ) reduction ( e.g. Cr 2 O 3 ) led to severe cathode deactivation, decreasing electrode conductivity and impeding electron transfer on the cathode. 5,6,10,13 Due to the cathode deactivation, the Cr( vi ) has been demonstrated to negatively affect the co-existing V( v ) reduction in MFCs. 10 This phenomenon was similar with the decreased efficiency of co-existing Cu( ii ) reduction in this study. On the contrary, the deposited products from Cu( ii ) reduction on the electrode surface have been proven to significantly improve the adsorption capacity, electronic conductivity and electrochemical activity of the cathode, which facilitated the subsequent cycles of Cu( ii ) and Cd( ii ) reduction and energy recovery. 3,17 Moreover, Devaraj et al. 34 observed a remarkable enhancement of electrochemical activity for the carbon-based electrode after Cu@Cu 2 O/MWCNT modification. Therefore, BioAu/MWCNT modification coupling with in situ Cu( ii ) co-reduction noticeably enhanced Cr( vi ) removal as well as electricity production in MFCs by improving electrochemical properties of the cathode. Since in practice Cr( vi ) laden wastewaters generally comprise a range of multiple heavy metal ions such as Au( iii ) and Cu( ii ), this study provides a feasible approach through recovering some heavy metals from wastewaters as ex situ or in situ electrode modifiers to accelerate Cr( vi ) removal. It could simultaneously realize the concomitant heavy metals remediation along with bioenergy generation. However, there are a variety of impurities in the real wastewaters, including not only diverse metal ions but also organic contaminants, which might have different effects on the performance of Cr( vi )-reducing MFCs. For example, except Au( iii ) and Cu( ii ), the other co-existing metal ions which might have positive or negative effects on the Cr( vi ) removal still need to further investigate. In addition, the interaction effects of metal ions and organic contaminants in the real wastewaters are another subject deserved to study as well. These should be clarified before the application for the real wastewaters in the future. Fig. 5 XPS analysis for the deposits on the BioAu/MWCNT electrode after Cr( vi ) and Cu( ii ) removal ((A) full survey, (B) Cr2p, (C) Cu2p, (D) Au4f)."
} | 6,207 |
21601093 | null | s2 | 6,654 | {
"abstract": "With the expanding interest in cellular responses to dynamic environments, microfluidic devices have become important experimental platforms for biological research. Microfluidic \"microchemostat\" devices enable precise environmental control while capturing high quality, single-cell gene expression data. For studies of population heterogeneity and gene expression noise, these abilities are crucial. Here, we describe the necessary steps for experimental microfluidics using devices created in our lab as examples. First, we discuss the rational design of microchemostats and the tools available to predict their performance. We carefully analyze the critical parts of an example device, focusing on the most important part of any microchemostat: the cell trap. Next, we present a method for generating on-chip dynamic environments using an integrated fluidic junction coupled to linear actuators. Our system relies on the simple modulation of hydrostatic pressure to alter the mixing ratio between two source reservoirs and we detail the software and hardware behind it. To expand the throughput of microchemostat experiments, we describe how to build larger, parallel versions of simpler devices. To analyze the large amounts of data, we discuss methods for automated cell tracking, focusing on the special problems presented by Saccharomyces cerevisiae cells. The manufacturing of microchemostats is described in complete detail: from the photolithographic processing of the wafer to the final bonding of the PDMS chip to glass coverslip. Finally, the procedures for conducting Escherichia coli and S. cerevisiae microchemostat experiments are addressed."
} | 414 |
39915469 | PMC11802859 | pmc | 6,655 | {
"abstract": "Emerging soft systems, including soft robots or wearable devices, actuated by fluidic means facilitate a series of inherent benefits, including safe human-robot interactions, lower costs, and adaptability in geometry for manipulating delicate objects. However, existing fluidic soft systems are facing a critical barrier: how to get rid of traditional rigid, bulky, and redundant fluid power/control components as well as develop their own flexible, portable, and universal fluidic components for implementing fully flexible, multi-circuit, and untethered autonomous systems. Here, we introduce a strategy of flexible electro-hydraulic power chips that enables multi-circuit independent pumping and control of soft systems in simple, compact, and lightweight forms. These electro-hydraulic power chips could be arbitrarily programmed through “line-plane-body” combinations of electro-hydraulic power “diode” or “triode” modules with high output density of 10.77 kPa/g and 2.15 L/min/g, and freely fabricated into the desired shapes and functions via multi-material 3D printing technique. Demonstrations of multi-circuit mass transfer, five-finger selective cooling, bird’s multiple actuation, jellyfish’s fast swimming show electro-hydraulic power chips’ portable, powerful, and multi-circuit independent attributes. The proposed strategy is an important advance towards low-cost, mass-manufactured, and standard universal fluid power components for the next generation of multi-functional, autonomous soft systems.",
"introduction": "Introduction Natural organisms predominantly use soft materials to safely and efficiently interact with the environment and others, which has inspired the development of soft systems 1 – 3 , including soft robotics, wearable devices, and biomedical equipment, etc., to transform the way we interact with machines and environment 1 , 4 . Fluid power has become the most popular power mean for these soft systems due to its inherent flexibility 5 , allowing for a number of unique benefits such as the simplicity of their design, ease of fabrication, and low cost, etc. However, a critical barrier stems from that existing fluidic soft systems mainly rely on traditional rigid components (pumps and valves, etc.) for fluid power generation and control 6 – 10 . These standard universal pumps and valves originally developed for rigid mechatronic systems appear too bulky and redundant for nascent soft systems. Especially more and more rigid pumps or valves are required to achieve multi-circuit actuation and control of soft systems, which greatly increases the weight and volume of soft system and limits their portability. Therefore, how to develop portable, powerful, and standard universal fluid power components for soft systems is a key challenge for their technological advances and widespread applications. To overcome this barrier, scientists and engineers have made a lot of efforts and contributions to develop flexible and portable fluid power components. A series of innovative flexible valves were explored and embedded into soft systems to greatly reduce the need for external rigid control components and simplify the control logic of multiple fluidic circuits, facilitating the versatility and autonomy of soft robotics and wearable devices 7 , 11 – 14 . Despite these advantages, the requirement of external power sources to pressurize and depressurize working fluid remains a critical challenge that should be addressed simultaneously before untethered soft systems are widely practical. To achieve flexibility and portability of fluid power source, various novel pumps responsive to external stimuli (e.g., thermal, combustion, chemical reaction, phase transition, electrostatic force, etc.) have also been developed 15 – 20 . These techniques effectively remove fluidic tether but introduce new challenges like slow response speed, poor controllability, limited output density, etc. Furthermore, existing manufacturing methods of these pumps (e.g., casting and manual assembly, etc.) cannot achieve a trade-off between structural complexity, low cost, labor saving, accuracy repeatability, and mass manufacturing, limiting their generality in soft systems. As is well known, electronic chips achieve high integration and miniaturization of multiple circuits through the combination of many modular transistors, extensively promoting the portability and versatility of electronic products such as mobile phones and computers, etc. Inspired by the modular design concept of electronic chips as well as their great success in portable electronic products, here we apply this modular design concept of electronic chips to develop multi-circuit flexible electro-hydraulic power chips (EPCs), whose shapes and functions can be programmed through different combinations of multiple electro-hydraulic power “transistor” modules. These “transistor” modules can directly convert electrical energy into hydraulic power without any moving parts. Then, flexible materials in combination with multi-material 3D printing techniques are used to freely fabricate the desired flexible EPCs. These 3D-printed flexible EPCs have several distinctive qualities: (i) Chip-integrated design concept and multi-circuit independent control allow soft systems to achieve as much functionality as possible in extremely compact space; (ii) High output density of electro-hydraulic power “transistor” module has been achieved by combining the structural design of non-uniform strong electric field, the selection of lightweight and flexible materials, and the use of near-net 3D printing technique; (iii) Compared with traditional manufacturing method (e.g., casting and manual assembly, etc.), digital 3D printing technique not only dramatically saves labor and time, but also facilitates personalized customization, precision repeatability and standardized mass-manufacture. Successful applications of flexible EPCs in multi-circuit mass transfer, five-finger selective cooling, bird’s multiple actuation, and jellyfish’s fast swimming illustrate their great potential to be popularized in fluidic soft systems. Structure and working principle of electro-hydraulic power transistor It is widely known that transistors are the basic modules of electronic chips. Similarly, we have developed our flexible fluid power transistors—electro-hydraulic power “diode” or “triode” — as the basic elements for EPCs. Figure 1a shows a prototype of flexible electro-hydraulic power “diode”, which consists of a triangular-shaped emitter electrode (Conductive Thermoplastic Polyurethane, TPU), a silt-shaped collector electrode (Conductive TPU), and a channel support shell (Non-conductive TPU). Planar layout and flexible materials allow electro-hydraulic power “diode” to be easily fabricated via multi-material 3D printing (Fig. 1b, c , Supplementary Fig. 1 , Supplementary Table 1 , and Supplementary Movie 1 ). A unidirectional jet could be generated from emitter to collector electrodes in electro-hydraulic power “diode” (Supplementary Fig. 2 and Supplementary Movie 2 ). The smallest electro-hydraulic power “diode” we can print weighs 0.13 g and is about one-third of a thumbnail, exhibits high pressure and flow rate density of 10.77 kPa and 2.15 L/min. Fig. 1 Design, fabrication, and working principle of flexible electro-hydraulic power transistor. a Structure of flexible electro-hydraulic power “diode”. Triangular-shaped emitter electrode and silt-shaped collector electrode are conductive TPU, while the support shell is non-conductive TPU. Define the angle of triangular-shaped emitter electrode as α , the horizontal distance between the tip of the triangular-shaped emitter electrode and the collector electrode as l , and the distance between the two collector electrodes as d . b Conceptual illustration of multi-material 3D printing of electro-hydraulic power “diode” using conductive TPU (black) and non-conductive TPU (white). c Fabrication result of electro-hydraulic power “diode”. d Working principle of electro-hydraulic power “diode”. Strong non-uniform electric field dissociate neutral liquid molecules into free electrons and positive ions. Positive ions move along electric fields to collector electrode, dragging liquid flow. e Structure of flexible electro-hydraulic power “triode”. It is made of two emitter electrodes and a collector electrode. f Demonstration of an electro-hydraulic power “triode” to pump liquid between two tanks, and the pumping direction is reversed. g Demonstration of an electro-hydraulic power “triode” to pump liquid from right to left. h Demonstration of an electro-hydraulic power “triode” to pump liquid from left to right. The working principle of electro-hydraulic power “diode” is given as follows (Fig. 1d ): When the emitter and collector electrodes are respectively connected to high-voltage positive and grounding negative electrodes, a non-uniform strong electric field will be formed between them to cause the dissociation of a small amount of neutral liquid molecules into free electrons with negative charges and positive ions. All free electrons will be absorbed by emitter electrode, while the positive ions will move to collector electrode along the direction of electric field gradient. The rapid and continuous movement of positive ions will directly drag the rest liquid molecules flow to generate a strong jet from emitter to collector electrodes. When the positive ions reach to collector electrode, they will combine with free electrons of collector electrode to reform neutral liquid molecules. As long as applied electric field exists, continuous fluid flow will generate in electro-hydraulic power “diode”. Theoretical results of electro-hydraulic power “diode” are consistent with experimental ones (see Supplementary Materials, Supplementary Fig. 3 , and Supplementary Table 2 ), indicating that the working principle is reasonable and accurate. Two triangular-shaped collector electrodes can be symmetrically distributed on either side of one emitter electrode to form an electro-hydraulic power “triode” (Fig. 1e ). This “triode” can achieve reversibly bidirectional pumping when two opposite emitter electrodes are selectively connected to high-voltage positive electrode. Figure 1f–h , and Supplementary Movie 3 demonstrate the rapid, controllable, and fast-switching bidirectional fluid flow processes of the electro-hydraulic power “triode”. Performances of electro-hydraulic power transistor The output pressure and flow rate of electro-hydraulic power “diode” are determined by a large number of factors, including fluid materials, voltage range, and electrode configuration, and the measurement devices of output pressure and flow rate is shown in Supplementary Fig. 4 . In order to choose electrically responsive fluids, the flow capacities of many electrically responsive fluids are tested. Among them, four fluids with different flow capacities (including the most strongest fluid: Linalyl Acetate) are demonstrated in this work. A Movie comparing the flow capacities of these four fluids is shown in Supplementary Movie 4 . Moreover, the resistance measurement of four electrically responsive fluids is conducted to explain the interface resistance between the conductive TPU and different fluids as well as different flow performance of these four fluids (Supplementary Fig. 5 ). The results show that Linalyl Acetate has a higher current than FC 40, 7100, and 7200 at the same applied voltage, indicating that more electronic motion could pass through the interface between the conductive TPU electrode and fluid, and enter the fluid to produce stronger flow effects. Additionally, we tested the output performances of four different electrically responsive fluids at different voltages (Fig. 2a, b ). It is apparent that the output performances of different fluids show an approximately linear increase with the increase of applied voltage, which offers an effective and precise way to control the output performance of electro-hydraulic power “diode” by adjusting input electrical signal. Fig. 2 Performances of flexible electro-hydraulic power transistor. a Pressure versus voltage for four types of liquids. Liquid 1 : Linalyl Acetate; Liquid 2 : 3 M™ Fluorinert™ FC-40 Electronic Liquid; Liquid 3 : 3 M™ Novec™ 7100 Engineered Fluid 4; Liquid 4 : 3 M™ Novec™ 7200 Engineered Fluid. b Flow rate versus voltage for four types of liquids. c Pressure versus triangle electrode angle α at the voltage of 12 kV and 15 kV. d Flow rate versus triangle electrode angle α at the voltage of 12 kV and 15 kV. e Pressure versus electrode gap l at the voltage of 12 kV and 15 kV. f Flow rate versus electrode gap l at the voltage of 12 kV and 15 kV. g Pressure versus slit width d at the voltage of 12 kV and 15 kV. h Flow rate versus slit width d at the voltage of 12 kV and 15 kV. i Pressure versus voltage for different series integration use of multiple electro-hydraulic power transistors. j Flow rate versus voltage for different parallel integration use of multiple electro-hydraulic power transistors. k Transient response of electro-hydraulic power transistor at the voltage of 15 kV. l Performance comparison between electro-hydraulic power transistor, commercial rigid pumps, and existing flexible pumps. Meanwhile, the electrode configuration (i.e., triangular angle of emitter electrode α , slit width of collector electrode d , and electrode gap between emitter and collector electrodes l ) have a significant influence on the output performances of electro-hydraulic power “diode”, and their influence law should be explored to provide theoretical guidance for optimization design of electro-hydraulic power toransistor. Figure 2c, d show that the flow rate and pressure of electr-hydraulic power “diode” first increase and then decrease as the triangular angle α of emitter electrode increases. Note that the output performances reach the highest values at a triangular angle α of 60° due to the strongest non-uniform electric field intensity being formed at this angle. Additionally, the small electrode gap l (Fig. 2e, f ) and slit width d (Fig. 2g, h ) are beneficial to the enhancement of output pressure and flow rate. These phenomena indicate that the smaller, lighter, and more powerful electro-hydraulic power transistors could be fabricated with the advancement of printing accuracy. Moreover, the output pressure could be linearly raised by series integration use of multiple electro-hydraulic power transistors (Fig. 2i ), while output flow rate could be linearly raised by parallel integration use of multiple ones (Fig. 2j ). To further validate this stacking rule, we have also measured the output pressure and flow rate of an ECP with four transistors in series and five transistors in parallel (Supplementary Fig. 6 ). The results show that its output pressure is four times that of one transistor, while its output flow rate is five times that of one transistor. These results are in accord with the series/parallel rules of EPC performance mentioned above. The response time (peak time) of electro-hydraulic power transistor is ~0.67 s, and the switching response time of bidirectional pumping is ~0.83 s (Fig. 2k ). We also compare the flow rate and pressure density of electro-hydraulic power transistors with other commercial rigid pumps and existing flexible pumps (Fig. 2l ). The special pressure (10.77 kPa/g) and flow rate (2.15 L/min/g) of electro-hydraulic power transistor are far higher than those of commercial rigid pumps 21 – 23 and existing flexible pumps 19 , 20 , 24 – 27 . When an EPC is applied with a voltage of 15 kV, its power consumption of EPC is about 3.24 W and energy conversion efficiency is about 11.91%. (“Power consumption and energy efficiency of EPC” in Supplementary Materials). Continuous operating experiments of EPC under different voltages are conducted, and the temperatures of both fluid and EPC shell (near electrodes) are measured to know the temperature effects on their performance. The results show that the temperatures of fluid and EPC shell are relatively stable during continuous operation, and there is no obvious temperature increase (“Temperature measurement of EPC fluid and shell” in Supplementary Materials and Supplementary Fig. 7 ). Programmable electro-hydraulic power chips Interestingly, diverse EPCs could be programmatically designed to the desired shape, size, and function through reasonable combination and arrangement of electro-hydraulic power transistor modules, and 3D printed to meet different demands of various soft systems. The design of EPCs can be divided into three levels from simplicity to complexity. (i) Linear single channel: the length and width of a single linear channel can be respectively increased through the series and parallel integration of multiple electro-hydraulic power transistors (Fig. 3a, b ), while the height of the channel can be increased directly with the increase of printing height (Fig. 3c ). (ii) Plane multiple channels: multiple channels can be integrated into one plane, including interconnected channels with multiple entrances or exits (Fig. 3d, e ) and multiple independent channels (Fig. 3f ); (iii) Multi-layered layout: the desired shape and size in 3D space can be obtained through multi-layer stacking (Fig. 3g–i , Supplementary Figs. 8 and 9 ). The detailed wiring and control methods of EPCs are described in Supplementary Materials, Supplementary Figs. 10 and 11 , while the interface connection information between interfacing devices and EPCs is also elaborated. Fig. 3 Diverse design of EPCs. a Electro-hydraulic power transistor module, and the length of a single-channel EPC can be increased through series integration of multiple electro-hydraulic power transistors. b The width of a single-channel EPC can be increased through parallel integration of multiple electro-hydraulic power transistors. c The height of a single-channel EPC can be customized directly through 3D printing. d Interconnected-channel EPC with three entrances/exits in one plane. e Interconnected-channel EPC with four entrances/exits in one plane. f EPC with eight independent channels in one plane. g Three-layer stacked EPC with the same shape and size for each layer. h Three-layer stacked EPC with the same shape but different sizes for each layer. i Three-layer stacked EPC with different shapes and sizes for each layer. Although there are some previous works about modular pumps 19 , 20 , 24 , their structures are relatively complex and mainly manufactured via traditional fabrication techniques such as casting and manual assembly, etc. With the increase in module number and combination complexity, it is difficult to achieve their high precision, miniaturization, and easy manufacturing. The proposed EPCs based on electro-hydraulic power transistors have unique merits in the simplicity of their design and ease of fabrication, allowing designers to move toward this level of structural complexity and compact layout, albeit at a larger scale and with fewer materials. Soft system applications of electro-hydraulic power chips Fluidic soft robots or wearable devices always require multiple independent fluidic circuits to achieve their functional operations, such as various crawling behaviors of a quadruped, multimodal grasping of a flexible robotic gripper, wearable tactile feedback of different objects from virtual world, etc. Increasing the number of independently operated fluidic circuits via traditional rigid pumps and valves will greatly increase the burden on soft systems, even exceeding the limits they can withstand. We illustrate the unique merit of flexible EPCs in various multi-circuit soft systems by demonstrating three scenarios of multi-circuit mass transfer, five-finger selective cooling, and bird’s multiple actuation. We design and print a miniatured square EPC (Fig. 4a, b ). There are four fluidic circuits in the EPC, two of which are unidirectional fluidic circuits and the other two are bidirectional fluidic circuits. These four fluidic circuits are independently controllable without interference with each other, and their flow rate and pressure can be adjusted directly by changing input voltage signal. This EPC made of fully flexible materials shows good flexibility and can easily be stretchable and twisted (Fig. 4c ), ensuring the security in human-machine interaction process. The EPC selectively and controllably moves liquids with suspended particles of different colors (Supplementary Movie 5 ) in four independent fluidic circuits (Fig. 4d, g ), two independent fluidic circuits (Fig. 4e, h ), and one single fluidic circuit (Fig. 4f, i ), illustrating their broad potential in wearable drug delivery or screening devices. Fig. 4 Design, fabrication, and performances of a miniatured square EPC. a Schematic diagram of square EPC. The chip consists of four independent fluidic circuits, two of which are unidirectional fluidic circuits and the other two are bidirectional fluidic circuits. b Fabrication result of square EPC. c The square EPC can be stretchable and twisted. d Schematic diagram of four-circuit flow. e Schematic diagram of two-circuit flow. f Schematic diagram of one-circuit flow. g Demonstration of four-circuit flow in square EPC. h Demonstration of two-circuit flow in square EPC. i Demonstration of one-circuit flow in square EPC. We also embed a five-circuit EPC into a wearable glove device to effectively achieve controllable temperature control for selectively cooling different fingers (Fig. 5a ). This wearable device mainly consists of a EPC, some flexible tubes, a cooling source (TES1-4903, Zave), an energy supply system, and high-voltage power converter (Supplementary Fig. 12 ). Five independent flexible tubes are wrapped around five fingers, and connected to a five-circuit EPC (Fig. 5b ), thereby forming five independent fluidic circuits. A cooling source is placed on a wearable bracelet to contact a small section of five independent fluid circuits. When the fluid in one or more fluidic circuits of EPC is driven, the fluid flow will pass through the cooling area and bring low-temperature liquid to cool one or more fingers. Figure 5c shows the temperature information of fingers when the EPC is out of work. The five-circuit EPC selectively and controllably moves low-temperature liquid to reduce the temperature of one finger (Fig. 5d ), two fingers (Fig. 5e ), three fingers (Fig. 5f ), four fingers (Fig. 5g ), and five fingers (Fig. 5h ). These results indicate that the EPC is an advance in promoting the development of wearable devices for human thermal management with lighter weight and higher spatial resolution, illustrating its great potential in future virtual reality applications. Fig. 5 Thermal regulation of five-circuit EPC. a Schematic diagram of a wearable glove device to effectively achieve temperature control for cooling different fingers. The device consists of a five-circuit EPC, some flexible tubes, a cooling source, and an energy supply system. The fluid flow will pass through the cooling area and bring low-temperature liquid to cool one or more fingers. b Fabrication result of a five-circuit EPC. c Temperature information of five fingers when the five-circuit EPC is out of work. d Temperature information of one finger selective cooling state (i.e., little finger). e Temperature information of two fingers selective cooling state (i.e., thumb and forefinger). f Temperature information of three fingers selective cooling state (i.e., thumb, forefinger, and middle finger). g Temperature information of four fingers selective cooling state (i.e., thumb, middle finger, ring finger, and little finger). h Temperature information of all five fingers cooling state. Except for mass and heat transfer functions for fluidic wearable devices, EPCs could also be embedded into soft robots to achieve versatile motions without bulky and redundant fluid power/control components. A four-circuit fluid power actuator driven by a customized EPC is implanted into a soft robotic bird to achieve independent actuation of different organs, including a mouth, two wings, and a tail (Fig. 6a ). The four-circuit fluid power actuators (Fig. 6b and Supplementary Fig. 13 ) are made of four flexible actuators, four liquid tanks, and a three-layered four-circuit integrated EPC (Fig. 6c ). The operating principles of mouth opening and closing motion, wing flapping motion, and tail curling motion are schematically shown in Fig. 6d–f , respectively. The bird’s mouth opens when the corresponding mouth actuator is out of work. As the corresponding mouth actuator is driven by EPC, the fluid flow will cause the soft actuator contract to pull the mouth to close (Fig. 6d and Supplementary Movie 6 ). Two corresponding wing actuators can be independently controlled by EPC to achieve the wing flapping up and down at different frequencies (Fig. 6e ), while the corresponding tail actuator powered by EPC is responsible for the tail curling motion (Fig. 6f ). The independent actuation of opening and closing the mouth, flapping the wings, and curling the tail is respectively demonstrated in Fig. 6g–i , and the simultaneous actuation of all these motions are shown in Fig. 6j . Fig. 6 Structure, operating principle, and experimental results of a soft robotic bird powered by a three-layered four-circuit electro-hydraulic power chip. a Structure of a soft robotic bird. It consists of a mouth, two wings, a tail, an embedded four-circuit fluid power actuator, and a flexible shell. b A four-circuit fluid power actuator. c A three-layered four-circuit integrated electro-hydraulic power chip. d Operating principle of mouth opening and closing motion. e Operating principle of wing flapping motion. f Operating principle of tail curling motion. g Demonstration of mouth opening and closing motion. h Demonstration of wing flapping motion. i Demonstration of tail curling motion. j Demonstration of mouth opening and closing motion, wing flapping motion, tail curling motion at the same time. In addition, we designed and manufactured a jellyfish-like robot propelled by four paddling actuators, of which the paddling actuators are driven by EPCs (Fig. 7a ). Each paddling actuator consists of an EPC sealed by elastic film, electrically responsive fluid, and PET sheet (Fig. 7b ). When the EPC is not applied with voltage, the pre-deformed PET sheet is initially in a bent state. As the EPC is applied with high voltage, the jet generated by the EPC drives the liquid to flow from EPC tank into PET sheet. This process will cause the rapid extension of the initially bent PET sheet, thereby achieving the paddling action of jellyfish robot to propel itself swim forward. Once the voltage is removed, the elastic potential energy of the PET sheet will drive the polymer film to return to its initial bend state accompanied by liquid reflux (Fig. 7c ). By applying periodic high voltage, jellyfish robot can achieve fast swimming (Fig. 7d ). Figure 7e shows the actual swimming process of jellyfish robot (Fig. 7e and Supplementary Movie 7 ), which can reach a swimming speed of ~ 0.87 body lengths per second that is obviously faster than other flexible jellyfish robots 28 – 34 (Fig. 7f ). Fig. 7 Structure, operating principle, and swimming performance of EPC-driven flexible jellyfish robot. a Structure of EPC-driven flexible jellyfish robot. It consists of a flexible shell, EPCs, and PET sheets. b Structure of a paddling actuator. c Operating principle of paddling actuator. The PET sheet is initially in a bent state. As the EPC is applied with high voltage, the jet drives the liquid to flow from EPC tank into PET feet. This process causes the rapid extension of bent PET sheet, achieving the paddling action of jellyfish robot to propel itself swim forward. Once the voltage is removed, the elastic potential energy of the PET sheet will drive the polymer film to return to its initial bend state. d Schematic of 2-cycle swimming of jellyfish robot. e Demonstration of the periodic swimming of jelleyfish robot. f Swimming performance comparison between EPC-driven jellyfish robot and other flexible jellyfish robot 28 – 34 .",
"discussion": "Discussion In summary, we have proposed a strategy of flexible EPCs that can achieve multi-circuit independent pumping and control of fluidic soft systems in an extremely simple and lightweight form that is not possible with existing technologies. The multi-material 3D printing shows great advantages for the monolithic fabrication of complex, multi-circuit EPCs with high repeatability, few materials, and low manual labor requirements, while previous fluid power components have been mainly fabricated in multiple steps using a silicone molding process followed by manual assembly of subsystems. The demonstration of multi-circuit mass transfer, five-finger selective cooling, and bird’s multiple actuation illustrate the great potential of EPCs as mass-manufactured, low-cost, and standard universal fluid power components for fluidic soft systems. Except for stacking method, there are also several methods to further improve the output pressure or flow rate of EPC. Actually, the out pressure or flow rate of EPC is also determined by fluid materials and electrode types, etc. The output pressure or flow rate of EPC could significantly be improved by discovering or developing new electrically responsive fluid materials with stronger flow performance. For example, doping other materials into the electrically responsive fluids is a feasible way to enhance their output pressure or flow rate. Electrode types (including materials and size) can also affect the output pressure or flow rate. Firstly, developing flexible electrode materials with better conductivity could also improve output pressure or flow rate. Secondly, it is found from Fig. 2e–h that the smaller the electrode size and electrode spacing, the higher the output pressure or flow rate. This indicates that the smaller, lighter, and more powerful EPCs could be fabricated with the high printing accuracy. The development of 3D printing techniques with higher printing resolution and accuracy or new printing technologies could reduce the size of EPCs, thereby increasing output pressure or flow rate. Except for unidirectional or bidirectional flow function, developing the devices driven by EPCs to prevent fluid flow is an important and meaningful research direction, which could add more functions to soft systems. Moreover, the EPCs could be fully integrated and printed with soft robots and wearable devices themselves, making these soft systems lighter and more compact, simpler to manufacture, and more reliable in fluidic sealing. In addition, flexible high-voltage circuits should also be developed and integrated with EPCs for printing together. This strategy of EPCs has great potential to be popularized as the standard universal fluid power components for autonomous soft systems."
} | 7,818 |
35529586 | null | s2 | 6,657 | {
"abstract": "Introduction of surface textures has long been used to improve the hydrophobicity of solid materials. This study focusses on understanding the effects of various micro-texture geometries on the hydrophobicity of textured polymer surfaces. Square pillar, cylindrical, hemispherical and conical surface features, both protrusion and cavity, are considered in this study for two polymers. Employing the well-known models, the study shows that introducing textures on polymer surfaces generally increases the contact angle and, therefore, improves the hydrophobicity of polymers. The effect of surface texture on hydrophobicity significantly varies with texture geometry and dimension. The study provides useful guidelines for improving hydrophobicity of polymers by introducing textures on the surface."
} | 199 |
34685099 | PMC8538726 | pmc | 6,658 | {
"abstract": "Recently, the research of distributed sensor networks based on triboelectric technology has attracted extensive attention. Here, we reported a new triboelectric nanogenerator based on sodium chloride powder (S-TENG) to obtain mechanical energy. The polytetrafluoroethylene (PTFE) film and sodium chloride powder layer serve as the triboelectric pair. After testing and calculation, the internal resistance of S-TENG is 30 MΩ, and the output power of S-TENG (size: 6 cm × 6 cm) can arrive at the maximum value (about 403.3 µW). Furthermore, the S-TENG can achieve the open circuit voltage ( V oc ) of 198 V and short-circuit current ( I sc ) of 6.66 µA, respectively. Moreover, owing to the moisture absorption of sodium chloride powder, the S-TENG device also has the function of the humidity sensor. This work proposed a functional TENG device, and it can promote the advancement of self-powered sensors based on the TENG devices.",
"conclusion": "4. Conclusions In conclusion, we propose a novel triboelectric nanogenerator based on sodium chloride powder (S-TENG) to obtain mechanical energy. In addition, the S-TENG serves as the self-powered humidity sensor. It is noteworthy that sodium chloride is a kind of food material, which is non-toxic, pollution-free and rich in reserves. The PTFE film and sodium chloride powder layer form the triboelectric pair. The conductive aluminum tape is used as the conductive electrode, and the glue section is used to paste triboelectric materials. From the results, the output power of S-TENG (size: 6 cm × 6 cm) can arrive at the maximum value (about 403.3 µW). Furthermore, the S-TENG can achieve the V oc of 198 V and I sc of 6.66 µA, respectively. Moreover, the S-TENG device can monitor environmental humidity.",
"introduction": "1. Introduction Recently, owing to the progress needs of the Internet of things (IoT), various sensor technologies show numerous application prospects widely in the domain of the (IoT) [ 1 , 2 , 3 ]. As a significant part of the IoT, distributed sensor network has attracted the attention of academia and industry [ 4 , 5 ]. Often, distributed sensor networks consist of many sensors, but this poses new challenges to energy supply [ 6 ]. It is noteworthy that renewable energy generation is widely concerned, such as solar energy, ocean wave, temperature difference energy, wind and other green energy [ 7 ]. Compared with traditional fossil energy (oil, coal and natural gas), renewable energy has the characteristics of rich reserves, and is inexhaustible, and can reduce environmental pollution [ 8 , 9 ]. Therefore, harvesting technologies based on green renewable energy, such as electromagnetic power generation technology, piezoelectric power generation technology, photoelectric power generation technology and thermoelectric power generation technology, have exploded over the past few years. However, there are still many challenges in energy harvesting efficiency and use environment. In addition, the high preparation cost is also an important reason to hinder its application in distributed sensor networks [ 10 ]. In recent years, with the development of energy storage technology, distributed sensor network nodes usually provide power by electronics. However, the limited service life of the battery has brought a lot of replacement and maintenance work. Furthermore, this has an impact on the development of the Internet of things [ 11 , 12 ]. In addition, there will be environmental pollution problems. Therefore, the development of new power generation technology is necessary and meaningful. In 2012, Professor Wang and his research group reported the triboelectric nanogenerator (TENG). The TENG device can convert low frequency and low amplitude mechanical energy into electrical energy output [ 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. Furthermore, TENG devices exhibit an extensive application prospect in the fields of self-powered sensors, ocean wave energy and high-voltage power sources [ 22 , 23 , 24 , 25 ]. In addition, it has a profound and significant influence on the sustainable development of energy and environmental protection. The triboelectrification phenomenon can occur between most materials, and friction movement is everywhere in life [ 26 , 27 ]. Thus, the TENG devices have a wide range of preparation materials, and this also promotes the rapid development of TENG devices based on different triboelectric material combinations [ 28 , 29 , 30 ]. Up to now, TENG can gain almost all mechanical energy and convert it into electrical energy, such as ocean wave, breeze energy, human motion and other mechanical vibration energy in the form of low frequency [ 31 , 32 , 33 , 34 , 35 ]. In addition, TENG devices can respond to changes in the environment through changes in electrical output signals. Therefore, it is meaningful to develop a TENG device with a sensing function. Here, we propose a novel triboelectric nanogenerator based on sodium chloride powder (S-TENG) to obtain mechanical energy. Furthermore, the S-TENG serves as the self-powered humidity sensor. It is noteworthy that sodium chloride is a kind of food material, which is non-toxic, pollution-free and rich in reserves. In addition, sodium chloride is easily soluble in water, which also creates conditions for material recycling. The polytetrafluoroethylene (PTFE) film and sodium chloride powder layer form the triboelectric pair. The conductive aluminum tape serves as the conductive electrode, and the glue section is used to paste triboelectric materials. From the results, the output power of S-TENG (size: 6 cm × 6 cm) can arrive at the maximum value (about 403.3 µW), and the internal resistance of S-TENG is 30 MΩ. Furthermore, the S-TENG can achieve the V oc of 198 V and I sc of 6.66 µA, respectively. Moreover, the S-TENG device can monitor environmental humidity.",
"discussion": "3. Results and Discussion The S-TENG can work under vertical motion conditions, and the operating mechanism of S-TENG is shown in Figure 2 . Generally, the PTFE film can obtain electrons from other triboelectric materials during the triboelectric process. Thus, when PTFE film contact with the sodium chloride powder layer, the PTFE film surface will obtain electrons, and the sodium chloride powder layer will lose the same amount of electrons due to the contact electrification mechanism, as shown in Figure 2 a. Then, when the surfaces of the PTFE film and sodium chloride powder layer separate ( Figure 2 b), the top electrode of the S-TENG device will generate a positive charge, and the electrode at the bottom of the S-TENG will produce the same amount of negative charge. In addition, this can lead to the generation of pulse current in the external circuit. When the maximum separation distance reaches a certain value, the charge transfer between the two electrodes reaches the saturation state. Furthermore, the circuit will not produce pulse current, as shown in Figure 2 c. when the PTFE film surface is close to the sodium chloride powder layer surface, the negative charge at the top electrode will be transferred to the bottom electrode, and a reverse pulse current will be formed, as shown in Figure 2 d. Moreover, we connect loads with different resistance values to S-TENG and measure the output performance (output voltage and current) of S-TENG, as shown in Figure 3 a. The mechanical vibrator can provide an external force to drive the S-TENG. In addition, the motion parameters (such as vibration frequency and maximum separation distance) are set as 6 Hz and 5 mm, respectively. The size of the S-TENG device is about 6 cm × 6 cm. As is shown in Figure 3 b, when the resistance of the load grows from 1 MΩ to 1 GM, the V oc of S-TENG will rise whereas the I sc of S-TENG will drop, which also indicates that TENG devices usually have high V oc and low I sc . Furthermore, we calculated the output power ( P ) of S-TENG through the relationship P = UI . In addition, Figure 3 c describes the calculation results and relations. From the results, the S-TENG device can realize the maximum output power of 403.3 µW. Meanwhile, the internal resistance of S-TENG is 30 MΩ. Furthermore, the S-TENG can achieve the V oc of 198 V and I sc of 6.66 µA, respectively, as shown in Figure 3 d,e. Figure 3 f illustrates that the charge transfer in the external circuit can reach 25.5 nC. It is worthy to point out that the parameters of external excitation are the factors influencing the output characteristics of S-TENG. Therefore, we explored the influence of motion frequency and maximum separation distance on the electrical output of S-TENG. As shown in Figure 4 a, when the working frequency rises from 2 Hz to 6 Hz, the I sc of S-TENG will grow from 3.33 µA to 6.5 µA. The reason for the increase of S-TENG is that the higher motion frequency is conducive to the rapid transfer of charges. As illustrated in Figure 4 b,c, when the working frequency rises from 2 Hz to 6 Hz, the V oc of S-TENG will remain constant at about 198 V, and the transferred charge of S-TENG will also be unchanged at about 25.5 nC, which also indicates that the superiority of TENG devices in low-frequency motion energy harvesting. Moreover, the maximum separation distance between the PTFE film surface and sodium chloride powder layer surface can also influence the S-TENG electrical output. With the increase of the maximum separation distance (from 1 mm to 5 mm) shown in Figure 4 c–e, the electrical output of S-TENG, such as I sc , V oc and transfer charge, will increase. Moreover, considering the continuous work of S-TENG, we explored the electrical output of S-TENG under continuous operating conditions. Based on the results in Figure 5 a, the S-TENG has good stability. Furthermore, we examine the charging effect of S-TENG with a power management circuit, as shown in Figure 5 b. Here, we developed the relationship of S-TENG charging capacitors under different frequencies. Obviously, the higher the externally provided vibration frequency, the faster the rate of storing electric energy, as shown in Figure 5 c. In addition, we also researched the influence of S-TENG charging different capacitors, as illustrated in Figure 5 d. According to the experimental results, the larger the capacitor, the faster the charging speed. Often, TENG devices can convert moving mechanical energy into electrical energy during the contact and separation movement of triboelectric materials. In addition, the generated electrical signal is closely related to the influence of the working environment. Environmental factors will affect the electrical output signal produced by the TENG device, for example, relative humidity. It is noteworthy that sodium chloride powder has strong moisture absorption. Furthermore, this characteristic can make the S-TENG the self-powered humidity sensor by the electrical output signal change of the S-TENG device, as shown in Figure 6 a,b. Specifically, the relative humidity will have a significant influence on the charge transfer of the TENG device. In this design, the sodium chloride powder plays the role of triboelectric material, and meanwhile, it is sensitive to relative humidity. Specifically, we measured the V oc , I sc and transferred charge of S-TENG under different relative humidity, as present in Figure 6 c–e. According to the results, when the relative humidity rises, the electrical output ( V oc , I sc and transferred charge) of S-TENG can grow, which indicates the S-TENG can monitor humidity changes."
} | 2,884 |
30680281 | PMC6334791 | pmc | 6,659 | {
"abstract": "The adhesiveness of biological micropatterned adhesives primarily relies on their geometry (e.g., feature size, architecture) and material properties (e.g., stiffness). Over the last few decades, researchers have been mimicking the geometry and material properties of biological micropatterned adhesives. The performance of these biomimetic micropatterned adhesives is usually tested on hard substrates. Much less is known about the effect of geometry, feature size, and material properties on the performance of micropatterned adhesives when the substrate is deformable. Here, micropatterned adhesives of two stiffness degrees (Young’s moduli of 280 and 580 kPa) were fabricated from poly(dimethylsiloxane) (PDMS) and tested on soft poly(vinyl alcohol) (PVA) substrates of two stiffness degrees (12 and 18 kPa), and on hard glass substrates as a reference. An out-of-the-cleanroom colloidal lithographic approach was successfully expanded to fabricate adhesives with two geometries, namely dimples with and without a terminal layer. Dimples without a terminal layer were fabricated on two length scales, namely with sub-microscale and microscale dimple diameters. The cross section of samples with a terminal layer showed voids with a spherical shape, separated by hourglass-shaped walls. These voids penetrate the terminal layer, resulting in an array of holes at the surface. We found that on soft substrates, generally, the size of the dimples did not affect pull-off forces. The positive effects of sub-microscale features on pull-off and friction forces, such as defect control and crack trapping, as reported in the literature for hard substrates, seem to disappear on soft substrates. The dimple geometry with a terminal layer generated significantly higher pull-off forces compared to other geometries, presumably due to interlocking of the soft substrate into the holes of the terminal layer. Pull-off from soft substrates increased with the substrate stiffness for all tested geometries. Friction forces on soft substrates were the highest for microscale dimples without a terminal layer, likely due to interlocking of the soft substrate between the dimples.",
"conclusion": "Conclusion We used a facile, out-of-the-cleanroom method to fabricate microstructures with sub-microscale features, and expanded it for microscale features. We fabricated geometries of moderate architectural complexity (extruded patterns with curved surfaces) and of high architectural complexity (overhanging features), at different length scales and different degrees of stiffness. We found that higher pull-off and friction forces on soft substrates were generated with larger feature sizes. On soft substrates, the positive effects of sub-microscale features on pull-off and friction forces, such as defect control and crack trapping, are not present, because the substrate conforms to the micropattern. Instead, interlocking is likely the dominant mechanism of pull-off and friction forces on soft substrates. The effect of the microstructure stiffness was not pronounced, which is not surprising, considering that the microstructures were one order of magnitude stiffer than the soft substrate, meaning that the latter was the main component to deform. We expect that the effect of the microstructure stiffness becomes larger when it is in the same order as the substrate stiffness, in which case both the microstructure and the substrate compete to deform. In conclusion, we found that, on soft substrates, microscale dimples generate higher pull-off and friction forces than sub-microscale dimples. Generation of grip on soft substrate seems to be dominated by different underlying mechanisms than those holding for hard substrates.",
"introduction": "Introduction Pull-off and friction forces of micropatterned adhesives as a function of geometry, feature size, and stiffness Over the last few decades, researchers have been developing micropatterned adhesives mimicking the geometry and material properties of biological dry adhesives [ 1 – 5 ]. Pull-off and friction forces of these biomimetic adhesives rely on the formation of intimate contact with the substrates [ 6 ], enabling physical interactions between the adhesive and the substrate, in the form of intermolecular forces, capillary forces, and suction forces. To achieve intimate contact between the adhesive and the substrate, researchers have been designing micropatterned adhesives with a low effective elastic modulus E eff [ 6 ]. For example, micro- and/or nanoscale fibrillar geometries have been reported [ 7 ], where the flexibility of the individual fibrils leads to a low E eff [ 8 ]. Furthermore, micropatterns with a fibrillar geometry have been shown to have better defect control [ 9 ] and better stress distribution [ 10 ] compared to smooth adhesives. The decreased E eff of a fibrillar geometry also leads to decreased contact stiffness [ 11 ] and higher conformability to substrate roughness [ 12 ]. The abovementioned effects of fibrillary geometries can be further enhanced with altering the pillar geometry. For example, Gorb et al. fabricated micropillars of 100 μm height and a stem diameter of 60 μm, terminated with a thin (2 μm) disc of 40 μm in diameter [ 11 ]. These so-called mushroom-shaped micropillars generated higher pull-off forces than flat-punch micropillars, a phenomenon attributed to a higher adaptability to substrate roughness due to the presence of the terminal thin disc [ 11 ]. Varenberg et al. found that detachment of the terminal disc happens from the inside out, with a peeling line moving from the center of the disc toward its outer edge [ 13 ]. In later work, Varenberg et al. reasoned that, as the terminal disc of mushroom-shaped micropillars detaches via a local thin-film peeling mechanism, multiple peeling fronts are present throughout the micropattern [ 14 ]. This splitting-up of the peeling front in multiple smaller fronts results in a drastic increase in peeling line length, and therefore in high pull-off and friction forces [ 14 – 15 ]. Heepe et al. investigated the significance of suction forces during detachment of mushroom-shaped micropillars [ 16 ], considering that the inside-towards-outside detachment mechanism gives rise to a low-pressure enclosed space in the center of the terminal disc during detachment. These authors empirically showed that suction forces are responsible for about 10% of the pull-off force mushroom micropatterns [ 16 ]. The presence of a terminal layer connecting neighboring micropillars at their tips has also shown to have a favorable effect on pull-off and friction forces on hard substrates. Glassmaker et al., for example, fabricated arrays of micropillars of 14 μm in diameter and 50 μm in height, where neighboring micropillars were connected at their tips with a continuous terminal layer of 4 μm in thickness [ 17 ]. These authors found that pull-off forces increased with increasing spacing between micropillars, and 9-times higher forces were generated compared to flat control samples at a spacing of 87 μm. The authors suggested that the increase in pull-off forces was caused by a crack-trapping mechanism during pulling off [ 17 ]. Bae et al. argued that the presence of a terminal layer leads to an increase of contact area with increasing preloads, resulting in higher pull-off forces under compression as compared to geometries without a terminal layer [ 18 ]. The friction of micropatterned adhesives with a terminal layer has been also investigated. He et al., for example, reported that, for a film-terminated ridge-channel structure, friction forces increased when channel width increased [ 19 ]. It was suggested that the terminal layer stretches during sliding, causing loss of elastic energy, thereby contributing to friction. Besides geometry (i.e., shape), also the size of micropattern features has an effect on the E eff of micropatterned adhesives. Varenberg et al. reasoned that finer micropillars have a lower contact stiffness, resulting in a lower contact reaction force, which might, in turn, result in higher pull-off forces, as long as the formed real contact area of the finer microstructure is not considerably lower than that of coarser microstructure [ 14 ]. Greiner et al. found that with increasing aspect ratio of micropattern features, their compliance increases, resulting in a better conformability to substrate roughness [ 20 ]. Hierarchical geometries, that is, architectures with features on different length scales, conform to substrate roughness on different length scales, increasing pull-off and friction forces [ 21 ]. Besides geometry and feature size, the E eff of adhesive micropatterns also relates to the stiffness of the material the micropattern is made of [ 6 ]. When a soft material is used for the micropattern, the E eff is low, leading to better defect control, stress distribution, and contact stiffness compared to micropatterns made of stiffer materials [ 22 ]. Also, the strength of the contacts formed between the adhesive and the substrate is affected by the material stiffness of the micropatterned adhesive, as this strength depends on the area of contact that is formed, which in turn is determined by the indentation depth of the adhesive into the substrate [ 23 ]. The performance of biomimetic micropatterned adhesives is usually tested on hard substrates, primarily glass and polystyrene. Much less is known about the performance of micropatterned adhesives when the substrate is deformable. Secure grip on soft, deformable substrates can be useful in a range of applications, including soft-tissue manipulation during surgical procedures and pick-and-place of soft biological objects such as grapes and poultry in food processing industries. The role of the geometry, feature size, and material stiffness of a micropattern on its pull-off and friction forces on a soft, deformable substrate can be expected to be different than on a hard substrate, as soft substrates deform under load and may conform to the geometry of the adhesive. For example, for a simplified representation of a discoidal adhesive element of a beetle, Heepe et al. showed that if the substrate is stiffer than the adhesive apparatus, a detachment mechanism similar to that observed for mushroom-shapes micropillars is present, with detachment starting from the center of the disc and moving toward its outer edge. However, if the substrate is softer than the adhesive apparatus, the latter potentially behaves like a flat punch, and detachment starts at the outer edge. Cheung et al. showed that during pulling off a micropattern from a soft substrate, the substrate deforms, and the detachment of neighboring pillars is no longer independent [ 24 ]. Accordingly, the pull-off force of mushroom-pillar micropatterns on a soft elastic substrate (Young’s modulus E = 200 kPa) has been found to be lower than on a rigid glass substrate [ 24 ]. On very soft substrates (Young’s modulus E ≈ 10 kPa), the indentation depth of microscale features is determined by a balance between the elastic properties of the substrate and the substrate–micropattern adhesion effects [ 25 ]. The length scale at which these adhesion effects are present is referred to as the elastocapillary length l , which is defined as l = γ/μ, where γ is the surface tension of the substrate and μ is the elastic shear modulus of the substrate [ 26 ]. If the length scale of the microscale features is in the order of the elastocapillary length, indentation is dominated by surface-tension effects, whereas for larger features, surface-tension effects are balanced by elasticity [ 25 ]. Summarizing, whereas for rigid substrates, adhesive micropatterns have been designed to gain a low E eff , it remains to be investigated whether this design approach should also be followed for adhesive micropatterns used on soft substrates. In order to gain insight into this question, we investigated the pull-off and friction forces of adhesive micropatterns on soft substrates as a function of the geometry and feature size of the micropattern, and the stiffness of both the substrate and the adhesive. Fabrication of micropatterned adhesives with various geometries, feature sizes, and stiffness degrees Fabrication of micropatterned adhesives is most commonly done with molding techniques, in which a curable resin is shaped using a photolithographically fabricated three-dimensional hard template [ 3 , 24 , 27 ]. This fabrication method allows for the fabrication of a wide range of architectures and of features sizes at both nano- and microscale [ 28 ]. A limitation of this molding method is that demolding becomes challenging when the shaped material is soft. Another challenge of this method is that it requires complex instrumentation [ 28 ]. Akerboom et al. recently demonstrated a fast and cost-effective alternative method to fabricate micropatterns, in which a colloidal monolayer acts as a three-dimensional template to shape a curable resin [ 29 – 30 ], resulting in arrays of sub-microscale dimples [ 30 ]. This fabrication method allows for the demolding of resins even if, due to their softness, these adhere to the template, as demolding is done by chemically dissolving the colloidal template. In this work, we used the abovementioned colloidal lithographic approach to fabricate adhesive micropatterns with various stiffness degrees. Moreover, we expanded the fabrication method in order to fabricate two dimple sizes: sub-microscale and microscale. Finally, considering the positive effect of a terminal layer on the adhesion of micropatterns, we expanded the fabrication process in order to also fabricate dimple arrays topped with a thin terminal layer. The pull-off and friction forces of these micropatterns were tested on soft substrates made of poly(vinyl alcohol) (PVA) with two stiffness degrees and compared with the corresponding performance on glass as reference.",
"discussion": "Discussion In this work, we expanded a recently introduced colloidal lithographic approach and showed that it is possible to fabricate micropatterns with microscale dimples that are about one order of magnitude larger than the (sub-)micrometer-sized dimples reported in [ 28 , 30 , 33 – 34 ], with stiffness values down to 280 kPa, which is lower than the typical stiffness in the megapascal-range achieved by soft molding [ 35 ]. This fabrication method showed to be highly repeatable, and provided consistent results in terms of geometrical properties. With this fabrication method, we also demonstrated how to fabricate dimple arrays with and without a terminal layer. The pull-off and friction forces of the fabricated micropatterns were measured on soft substrates as a function of feature size, stiffness degree of the micropattern and of the substrate, and the presence or absence of a terminal layer. Pull-off forces Effect of geometry and stiffness on pull-off forces on soft substrates Pull-off measurements on soft substrates show that micropatterns of sub-microscale and microscale dimples without a terminal layer do not generate significantly higher pull-off forces than flat samples. We assume that, for both dimple sizes, the soft substrate fully conforms to the dimples, and the formation of independent contacts does not happen. Sub-microscale dimples have a depth of around 250 nm. As the elastocapillary length of PVA substrates is in the order of 400 nm, the PVA substrates fully conform to the micropattern based on surface tension effects, without elastic penalty. Microscale dimples have a dimple depth of around 5 μm, which is well above the elastocapillary length of PVA, and conformation to the micropattern is expected to be elastically dominated. As a result of the conformation properties of the substrate, a single larger contact area is formed, and advantageous effects of defect control and crack trapping mechanisms, as reported for rigid substrates [ 30 ], are not present. A microscale dimple geometry with a terminal layer generated higher pull-off forces compared to other tested geometries and flat control samples on the softer PVA substrate (PVA-12). A possible underlying mechanism explaining the positive effect of the terminal layer on pull-off force is that the soft PVA substrate interlocks with the holes of the terminal layer. Deformation of the PVA substrate, resulting in protrusions perforating the terminal layer, is elastically dominated, as the terminal layer thickness is well above the elastocapillary length of PVA of 400 nm. Formation of protrusions is a trade-off between, on the one hand, elastic stresses and, on the other hand, the compressive load on the bulk. On the stiffer PVA-18 substrate, this positive effect of a terminal layer on pull-off forces was not observed. PVA-18 has a higher elasticity, likely resulting in a higher elastic penalty for protrusion formation than in the case of the PVA-12 substrate. Therefore, during pulling off, formed protrusions jump back, and interlocking is lost faster on the PVA-18 substrate compared to the softer PVA-12 substrate. We expect that crack trapping mechanisms, as reported for terminal-layer geometries on hard substrates, are not involved on the tested PDMS-PVA configurations. As Heepe et al. already reasoned for a (simplified) representation of a discoidal adhesive element [ 6 ], the advantageous effect of a thin film micropattern on pull-off force is lost when the substrate is soft compared to the adhesive. Suction forces might also play a role in generating grip with arrays of dimples, both with and without a terminal layer. Air in dimples or, in the presence of a terminal layer, in the sub-surface cavities, will be squeezed out during loading, resulting in suction during detachment. We do not expect that suction is a dominant mechanism in the tested micropatterned adhesives, as there was no significant difference in pull-off forces between sub-microscale and microscale dimples without a terminal layer on soft substrates, despite the fact that sub-microscale dimples have a much lower suction cup volume compared to microscale dimples. Spolenak et al. found that at contact radii smaller than 10 μm, as is the case for our geometries, suction cups rapidly lose their effectiveness [ 36 ]. Force–time plots of pull-off force on soft substrates ( Figure 4 ) show that during pulling off (phase II in Figure 4 ), the drop in force took a few seconds longer compared to pulling off from glass substrates, indicating that contact was lost less abruptly on soft substrates. This gradual contact loss is probably caused by deformation of the soft substrate during pull off, as observed by Cheung et al. [ 24 ]. We did not test whether this deformation has a dissipative or an elastic nature, a question that could be investigated in future works by varying the pull-off speed. Force–time plots on soft substrates also show that the peak force at phase III was wider compared to measurements on glass, indicating that detachment from PVA was slower than from glass. On soft substrates, we did not find a consistent effect of the theoretical contact area of the measured geometries on pull-off force. For example, while microscale dimples without a terminal layer have a higher contact area compared to sub-microscale dimples without a terminal layer, the former did not generate higher pull-off forces compared to the latter on soft substrates. This observation might indicate that the contact formed between micropattern and substrate is not a strong contact. A low strength of the formed contact might be explained by PVA having a low surface energy (ca. 50 mN/m [ 32 ]), and because of the presence of water at the PVA–micropattern interface, which might be squeezed out of the PVA gel during loading. Whereas geometry did not show consistent effects on pull-off force, the substrate stiffness did exhibit a systematic effect on pull-off forces for geometries without a terminal layer and for flat control samples, generating higher pull-off forces on the stiffer PVA-18 substrate compared to the softer PVA-12. This result is logical, because, given that the PVA substrates are much softer than the used microstructures ( G ′ PVA ≈ 10 1 kPa; E PDMS ≈ 10 2 kPa), the substrate is expected to be the main component to deform when stress is applied. Geometry effects, if present, are unlikely to significantly contribute to the generated pull-off forces and friction forces, because the soft substrates likely fully conform to the micropattern. The PVA substrates have some dissipative properties (dissipation factors of PVA-12: tan δ = 0.05; PVA-18: tan δ = 0.07), which might contribute to the resultant pull-off force as well. Given the low value of these dissipation factors, we doubt whether damping plays a significant role in generated pull-off forces. Our measurement data suggest that, when the substrate is softer than the adhesive, the substrate conforms to the features of the adhesive when load is applied, enabling intimate contact [ 37 – 38 ]. The intimate contact has a positive effect on pull-off and friction forces, as long as the elastic penalty of the substrate deformation does not dominate over surface energy effects. Because the formed intimate contact between a micropatterned adhesive and a conformed soft substrate is a singular contact, geometry-induced defect control and stress distribution are not expected to be present on a soft substrate when the adhesive micropattern is stiff compared to the substrate. Effect of geometry on pull-off forces on hard substrates Measurements on glass showed that sub-microscale samples tend to generate higher pull-off forces than flat samples and microscale samples without a terminal layer and flat samples. Crack trapping, as proposed for similar microscale dimple arrays by Akerboom et al. [ 30 ], is likely more dominant in the smaller (sub-microscale) features than in the microscale micropatterns. Furthermore, sub-microscale dimples might form complete contact with the substrate [ 30 ], generating a higher contact area compared to other geometries. Because of the high surface energy of glass (about 1000 mJ/m 2 [ 39 ]), the formed contact points between the micropattern and the substrate are stronger than the contact points between micropattern and PVA substrates, which may partially explain the higher pull-off forces on glass compared to soft substrates. Microscale dimples without a terminal layer did not generate higher pull-off forces compared to flat control samples. We expect that, under the applied load, the elastic penalty for making full contact dominates over the gained pull-off force as a result of formed contact for this geometry. Similar to the results on the soft substrates, microscale dimples with a terminal layer tended to generate higher adhesive forces on glass compared to the same dimples without a terminal layer and flat samples. In line with Glassmaker et al. [ 17 ], we assume that a crack-trapping mechanism plays a role in our terminal-layer geometries. Additionally, crack trapping may be promoted by the presence of microscale voids in the terminal layer, similar to the observations by Hwang et al., who found enhanced pull-off forces by using cuts in the applied materials, thereby introducing compliant regions in stiff adhesive films [ 40 ]. The presence of a terminal layer further enhances pull-off forces because of the deformability of the former, resulting in a higher effective contact area than micropatterns without a terminal layer [ 17 ]. This deformation effect of the terminal layer on pull-off force is supported by the findings by Shahsavan et al., who reported that with thin film-terminated micropillars higher compliance and pull-off forces can be realized when the terminal layer has viscoelastic material properties [ 41 ]. For microstructures of dimples with a terminal layer, deformation of the terminal layer is likely to happen, given that the elastic modulus of PDMS is in the kilopascal-range, and thus elastic, and the thickness of the terminal layer is limited (i.e., conformation to substrate roughness requires only a small volume of material to elastically deform, resulting in a minor elastic penalty for conformation). The result that higher pull-off forces are generated with the softer PDMS-280 microstructures compared to PDMS-580 microstructures supports a deformation effect of the terminal layer. Besides elastic stretching of the terminal layer, the effective modulus of the dimples with terminal layer is likely lower compared to other geometries, because of the presence of sub-surface voids. A suction mechanism, if present, is expected to play a more dominant role on the rigid and impermeable substrate of glass than on PVA substrates [ 33 ]. However, we do not expect that suction forces are the main mechanism generating pull-off forces in the tested geometries, as sub-microscale dimples, despite having much smaller suction cups compared to microscale dimples, outperformed microscale dimples on glass. Friction forces Effect of geometry and stiffness on friction forces on soft substrates On soft substrates, force–time plots of friction force ( Figure 4 ) show that the static friction force (phase V in Figure 4 ) is comparable to the dynamic friction. A minor increase in friction force during sliding was typically observed, presumably caused by the PVA substrate “piling up” at the front line during sliding of the micropattern. On the stiffer PVA (PVA-18) substrate, large dimples without a terminal layer outperformed all other geometries. A similar, albeit less pronounced, effect was also observed on the softer PVA-12 substrate. We assume that with large dimples indent deeply into the PVA substrates, generating mechanical interlocking and a relatively high contact area. The microstructure starts moving when this interlocking is lost due to deformation of the substrate. A low indentation depth, as it is expected for flat samples, sub-microscale dimples and dimples with a terminal layer, requires a smaller volume of substrate to elastically deform to start sliding, resulting in lower friction forces. On the softer substrate of PVA-12, the elastic penalty for deforming is lower compared to PVA-18, which can explain why the superior performance of microscale dimples without a terminal layer on PVA-18 was less pronounced on the softer PVA-12. Dimples with a terminal layer generated higher friction on the softer substrate of PVA-12 compared to the stiffer PVA-18, in line with the findings for pull-off force measurements. It is possible that the same protrusion formation as described for pull-off force measurements also holds for friction measurements, with the substrate protruding into the sub-surface voids of the microstructure. Similar to pull-off experiments, suction forces cannot be ruled out either. Effect of geometry on friction forces on glass On the glass substrate, force–time plots of friction force ( Figure 6 ) show that static friction (peak at phase V in Figure 6 ) is dominant over dynamic friction. Some sort of zigzag was typically visible in the dynamic friction regime, indicating stick-slip-like behavior during sliding for both flat and micropatterned samples. Our results suggest that sub-microscale dimples led to higher friction forces compared to flat samples and to large dimples with or without terminal layer. We expect that under the applied preload, sub-microscale dimples flatten, and a contact area similar to flat samples is formed. Due to stored elastic energy in the micropattern, the formed contact might be better preserved during sliding compared to a flat geometry, resulting in higher friction forces. For a microscale dimple geometry without a terminal layer, friction forces are similar to or even lower than the friction forces of flat control samples on glass. Similar to the pull-off force measurements, we assume that the applied load during sliding is not sufficient to bring the bottom of the dimples into contact with glass, leading to a small contact area and thus low friction forces. Microscale dimples with a terminal layer generate higher friction forces compared to flat control samples. This might be related to the compliance of the terminal layer, due to which the contact during sliding is more efficiently conserved compared to flat samples. Elastic storage by means of stretching of the terminal layer, as suggested by He et al. [ 19 ], might also occur, leading to an increase in friction. Besides, as already noted earlier, because of the presence of spherical voids below the surface, the effective modulus of the terminal-layer micropatterns is likely lower compared to other geometries and flat control samples. Limitations and recommendations for future work In our experimental setup, we performed pull-off and friction measurements in a plate-to-plate configuration. We took extensive measures to assure proper alignment of the sample on the substrate, including visual inspection of the sample–substrate interface prior and during measurements using a magnifying camera, and real-time inspection of the recorded time–force curves. Moreover, the platform on which the substrate was placed was positioned between three sets of springs (flexures), which gave the platform some self-aligning properties. Despite these measures, we suspect that the high variation of the measurement data on glass was caused by misalignment. To counterbalance such issues of misalignment, our experimental design and statistical analysis were conservative: each data point was the average of five consecutive repeats and the measurements of independent samples were done in a randomized order. We also opted for a low α value of 0.001. It should be further noted that the increase in random variance because of misalignment and other side effects was not too large to dilute the strongly significant non-random effects we observed. On soft substrates, the variation of the measurement data was lower, which is logical, because the flexibility of the soft substrate ensures that the sample establishes good contact with the substrate. For follow-up experiments, the use of a (hemi-)spherical probe instead of a plate-to-plate configuration can be considered, to avoid misalignment issues. Due to the limited force range of our measuring setup, some samples could not be measured on glass. Considering the limited amount of data, we refrained from drawing conclusions on the effect of microscale samples with and without a terminal layer on friction. The fabricated sub-microscale dimples had a lower depth than the particle radius. Considering that the time between casting the monolayer with PDMS, degassing and subsequent curing at 68 °C was in the order of 15 min, the uncured PDMS does not fully flow through the colloidal monolayer on this timescale, resulting in a limited dimple depth. A strategy to increase the PDMS penetration into the monolayer would be to cure the PDMS at room temperature for 48 h, in which case PDMS remains in a liquid state for much longer. Indeed, we did observe larger dimples and thinner walls between dimples when curing the sample at room temperature in a post-hoc synthesis, as can be seen in section 3 of Supporting Information File 1 . Given the high pull-off and friction forces of microscale dimples with a terminal layer on both hard and soft substrates, it would be interesting to test the performance of sub-microscale dimples with a terminal layer. However, we were not able to fabricate sub-microscale dimples with a terminal layer, presumably because the walls between dimples are so thin that they break during peeling off from the template, or because the uncured PDMS did not fully penetrate the monolayer. The latter problem could be solved by creating colloidal monolayers with a larger spacing, for example by optimizing the surface chemistry of particles. The mechanism of generating grip on the tested substrates is likely indentation-based, creating mechanical interlocking, and therefore strongly depends on the stiffness of both substrate and adhesive. Consequently, it is not surprising that our results pointed towards higher friction on soft substrates when employing large dimples compared to small dimples. This result suggests that with even larger dimples the friction performance of micropatterns on soft substrates can be improved, even under low (pre)loads, a hypothesis that deems further investigation. In our work, the stiffness of the substrate was much lower than the stiffness of the sample. Future work could be directed towards testing configurations in which the stiffness of adhesive and substrate are of the same order. Our hypothesis is that in this case, contact loss due to substrate deformations is prevented, and effects of geometry, such as increased contact area with a dimples-with-terminal-layer geometry, become visible. Although the use of a much softer micropattern might give rise to geometry effects, it remains to be investigated whether the loss in contact strength accumulatively leads to an increase in pull-off force. While we found a significant effect of the geometry on pull-off and friction forces on soft substrates, it was difficult to clarify the underlying mechanisms that cause these effects, both qualitatively and quantitatively. The hypothesized interlocking effects could be investigated in future studies by quickly freezing microstructure–substrate complexes when under load and studying their cross section with optical microscopy. The importance of deformation mechanisms of the substrate in the pull-off and sliding of our adhesives could be further investigated by varying the pull-off or sliding speed, since the strain rates of both substrate and adhesives are time dependent."
} | 8,458 |
19660930 | null | s2 | 6,660 | {
"abstract": "Lignocellulosic biofuels represent a sustainable, renewable, and the only foreseeable alternative energy source to transportation fossil fuels. However, the recalcitrant nature of lignocellulose poses technical hurdles to an economically viable biorefinery. Low enzymatic hydrolysis efficiency and low productivity, yield, and titer of biofuels are among the top cost contributors. Protein engineering has been used to improve the performance of lignocellulose-degrading enzymes, as well as proteins involved in biofuel synthesis pathways. Unlike its great success seen in other industrial applications, protein engineering has achieved only modest results in improving the lignocellulose-to-biofuels efficiency. This review will discuss the unique challenges that protein engineering faces in the process of converting lignocellulose to biofuels and how they are addressed by recent advances in this field."
} | 226 |
38386509 | PMC10919095 | pmc | 6,661 | {
"abstract": "Biomaterials often\ncontain large quantities of water (50–98%),\nand with the current transition to a more biobased economy, drying\nthese materials will become increasingly important. Contrary to the\nstandard, thermodynamically inefficient chemical and thermal drying\nmethods, dewatering by membrane separation will provide a sustainable\nand efficient alternative. However, biomaterials can easily foul membrane\nsurfaces, which is detrimental to the performance of current membrane\nseparations. Improving the antifouling properties of such membranes\nis a key challenge. Other recent research has been dedicated to enhancing\nthe permeate flux and selectivity. In this review, we present a comprehensive\noverview of the design requirements for and recent advances in dewatering\nof biomaterials using membranes. These recent developments offer a\nviable solution to the challenges of fouling and suboptimal performances.\nWe focus on two emerging development strategies, which are the use\nof electric-field-assisted dewatering and surface functionalizations,\nin particular with hydrogels. Our overview concludes with a critical\nmention of the remaining challenges and possible research directions\nwithin these subfields.",
"introduction": "1 Introduction Within the current transition\nto a biobased economy, many challenges\nmust be resolved. 1 A critical challenge\nis that biobased materials often contain large quantities of water\n(50–98%). 2 − 4 Biomaterials are materials derived from land-based\nand aquatic plants, animals, bacteria, and fungi. 5 Their large moisture content makes transport and processing\ncost- and energy-intensive, making efficient dewatering an essential\nunit operation in biorefineries. 6 , 7 Yet, traditional dewatering\ntechniques based on thermal or chemical drying are thermodynamically\ninefficient and, currently, account for 15% of the energy consumed\nin industry. 2 , 3 , 8 Moreover,\nthese techniques can negatively affect the product quality. 9 , 10 Dewatering through membrane separation will provide an energy-efficient\nalternative and has therefore gained a lot of attention in recent\nyears. 11 − 15 Membranes allow for selective water filtration by means of\nsize\nexclusion, solution diffusion, and solute–membrane affinity, 16 , 17 hereby separating the smaller water molecules from the larger biomaterial\nconstituents. Membrane separations are used for many applications,\nranging from water purification, 18 − 20 gas separations, 21 , 22 oil–water separations, 23 − 25 and fuel cells 26 − 29 to biomedical separations, 30 − 32 and extensive literature can be found on the design and performance\nof these membranes. However, the utilization of membranes in the dewatering\nof biomaterials introduces new requirements and challenges that need\nto be solved. To achieve a satisfactory performance for biomaterial\ndewatering,\nresearchers have been developing suitable membrane separations for\nvarious classes of biomaterials. Extensive literature can be found\non the topic of microalgae harvesting, 13 , 33 , 34 protein concentration, 35 − 37 and polysaccharide removal. 38 All of these dewatering applications require\na high water/biomaterial selectivity and permeate flux, combined with\nminimal fouling ( Figure 1 ). 39 , 40 However, maintaining a high permeate flux\nover time is a major challenge and depends on the antifouling properties\nof the membrane. 41 − 43 Contrary to membrane separations in which the permeate\nis the product, biomaterial dewatering typically yields a retentate\nproduct. In such cases the quality of the retentate needs to be maintained,\ntherewith raising the need for different antifouling strategies. 8 , 44 − 47 Recent studies in this research field aim to improve current membrane\nmaterials by focusing on improving the dewatering performance and\nantifouling properties. 48 − 52 In addition, membrane separations have been performed under applied\nvacuum 13 , 34 , 53 and under\nthe influence of vibrations 54 , 55 and an electric field 56 , 57 to improve the overall performance for biomaterial dewatering. Figure 1 A conceptual\noverview of biomaterial dewatering through membrane\nseparation (left) and the four design requirements for an efficient\nmembrane separation (right). Requirements for membrane dewatering\nfor biomaterials are listed as (1) antifouling properties, (2) membrane\nselectivity, (3) high permeate flux, and (4) scalability. The parameters J H 2 O , C H 2 O , and C bio depict the water\nflux and concentrations of water and biomaterials, respectively. In this review, we will first discuss the major\ndesign requirements\nfor the dewatering of biomaterials using membranes ( section 2 ), followed by the recent\ndevelopments that address the requirements and challenges mentioned\nabove ( section 3 ).\nThese developments have focused on two strategies: ( section 3.1 ) using an electrical driving\nforce to tune the interaction of biomaterials with the membrane interface\nand enhance the selective permeation of water, and ( section 3.2 ) surface functionalization,\nin particular with hydrogels, which are used to counteract fouling\nand increase selectivity and flux. Alongside an overview of the existing\nliterature, we identify future challenges and knowledge gaps within\nthese membrane material developments. Though reviews on membrane dewatering\nof biomaterials have been published, they focus either on specific\nfeeds 2 , 3 , 44 , 58 , 59 or primarily on fouling\nprevention. 48 , 60 − 63 As far as we are aware, we are\nthe first to provide an overview of the design requirements and developments\nof the complete field."
} | 1,401 |
36691727 | PMC9873259 | pmc | 6,665 | {
"abstract": "Unicellular algae, termed phytoplankton, greatly impact the marine environment by serving as the basis of marine food webs and by playing central roles in the biogeochemical cycling of elements. The interactions between phytoplankton and heterotrophic bacteria affect the fitness of both partners. It is becoming increasingly recognized that metabolic exchange determines the nature of such interactions, but the underlying molecular mechanisms remain underexplored. Here, we investigated the molecular and metabolic basis for the bacterial lifestyle switch, from coexistence to pathogenicity, in Sulfitobacter D7 during its interaction with Emiliania huxleyi , a cosmopolitan bloom-forming phytoplankter. To unravel the bacterial lifestyle switch, we analyzed bacterial transcriptomes in response to exudates derived from algae in exponential growth and stationary phase, which supported the Sulfitobacter D7 coexistence and pathogenicity lifestyles, respectively. In pathogenic mode, Sulfitobacter D7 upregulated flagellar motility and diverse transport systems, presumably to maximize assimilation of E. huxleyi -derived metabolites released by algal cells upon cell death. Algal dimethylsulfoniopropionate (DMSP) was a pivotal signaling molecule that mediated the transition between the lifestyles, supporting our previous findings. However, the coexisting and pathogenic lifestyles were evident only in the presence of additional algal metabolites. Specifically, we discovered that algae-produced benzoate promoted the growth of Sulfitobacter D7 and hindered the DMSP-induced lifestyle switch to pathogenicity, demonstrating that benzoate is important for maintaining the coexistence of algae and bacteria. We propose that bacteria can sense the physiological state of the algal host through changes in the metabolic composition, which will determine the bacterial lifestyle during interaction.",
"introduction": "Introduction Half of Earth’s photosynthesis takes place in the marine environment by phytoplankton – photosynthetic single-celled algae ( Field et al., 1998 ). Phytoplankton have great ecological importance by forming the basis of marine food webs and influencing biogeochemical cycles. Therefore, the biotic interactions phytoplankton engage in, and the metabolic exchange that governs them, have immense impacts on large-scale biogeochemical processes. Phytoplankton are a main source of organic matter in the marine environment, thus fueling the growth and functioning of heterotrophic bacteria that interact with them through chemical exchange ( Cirri and Pohnert, 2019 ; Seymour et al., 2017 ). Chemical communication takes place in the phycosphere – the diffusive boundary layer that surrounds algal cells, where molecules can accumulate to high concentrations ( Bell and Mitchell, 1972 ; Seymour et al., 2017 ). Studies on algae-bacteria interactions revealed that the partners often exchange growth substrates ( Landa et al., 2017 ; Segev et al., 2016 ), essential vitamins and nutrients ( Amin et al., 2009 ; Croft et al., 2005 ; Wang et al., 2014 ), and infochemicals (molecules that convey information) ( Amin et al., 2015 ; Barak-Gavish et al., 2018 ; Pohnert et al., 2007 ; Seyedsayamdost et al., 2011 ). Bacteria have developed mechanisms of foraging for phytoplankton cells, such as motility and chemotaxis, and cell-surface attachment mechanisms to maintain close association within the phycosphere ( Fei et al., 2020 ; Furusawa et al., 2003 ; Li et al., 2016 ; Mayali et al., 2008 ; Miller and Belas, 2006 ; Slightom and Buchan, 2009 ; Sonnenschein et al., 2012 ; Stocker and Seymour, 2012 ). Marine bacteria from the Rhodobacteraceae family, often termed the Roseobacter group ( Simon et al., 2017 ), are found to be associated with phytoplankton ( Alavi et al., 2001 ; Amin et al., 2012 ; Behringer et al., 2018 ; Buchan et al., 2014 ; Geng and Belas, 2010 ; González and Moran, 1997 ; Rink et al., 2007 ; Vincent et al., 2021 ). They are metabolically versatile and specialize on algae-derived substrates that promote interactions with phytoplankton ( Newton et al., 2010 ). The organosulfur molecule dimethylsulfoniopropionate (DMSP), produced by many phytoplankton species ( Keller, 1989 ), is especially known to mediate Roseobacter-phytoplankton interactions by serving as a carbon and sulfur source, as a chemotaxis cue, and as an infochemical for the presence of algae ( Amin et al., 2015 ; Barak-Gavish et al., 2018 ; Bürgmann et al., 2007 ; Landa et al., 2017 ; Miller et al., 2004 ; Miller and Belas, 2004 ; Seymour et al., 2010 ; Sule and Belas, 2013 ). In mutualistic interactions, algae provide organic matter such as sugars, amino acids, sulfonates, and polyamines for bacterial growth. In exchange, Roseobacters produce essential B-vitamins and growth promoting factors such as indole-3-acetic acid ( Amin et al., 2015 ; Cooper et al., 2019 ; Durham et al., 2015 ; Landa et al., 2017 ; Wagner-Döbler et al., 2010 ). In recent years, cumulating studies that investigated the interactions of phytoplankton and bacteria in co-cultures revealed that some Roseobacters display a lifestyle switch from mutualism to pathogenicity toward the algae ( Barak-Gavish et al., 2018 ; Bolch et al., 2017 ; Bramucci et al., 2018 ; Mayers et al., 2016 ; Segev et al., 2016 ; Wang et al., 2014 ). This occurs when the algal host reaches stationary phase and is mediated by infochemicals. For example, Roseobacters can produce potent algicidal compounds, termed roseobacticides, in response to p -coumaric acid, an aromatic lignin breakdown product released by aging algae ( Seyedsayamdost et al., 2011 ; Sule and Belas, 2013 ). While this bacterial lifestyle switch, often termed the “Jekyll-and-Hyde” phenotype, seems to be a recurring phenomenon, knowledge about the bacterial behavior in the different modes of interaction and the regulation of such lifestyle switch are still rudimentary. In the current study, we investigated the behavior of the Roseobacter Sulfitobacter D7, during interaction with Emiliania huxleyi , a cosmopolitan bloom-forming phytoplankter. E. huxleyi has a significant role in biogeochemical cycling of carbon and sulfur. It produces the climatically active gas dimethyl sulfide and its precursor DMSP, both function as infochemicals during interactions with E. huxleyi ( Barak-Gavish et al., 2018 ; Shemi et al., 2021 ). Sulfitobacter sp. are associated with E. huxleyi in nature, and Sulfitobacter D7 was isolated from a natural E. huxleyi bloom ( Ankrah et al., 2014 ; Barak-Gavish et al., 2018 ; Ku et al., 2018 ; Vincent et al., 2021 ). Therefore, this ecologically relevant model provides a tractable system to examine how metabolic exchange regulates the nature of interactions between algae and bacteria. Our previous work revealed that Sulfitobacter D7 displays a lifestyle switch, from coexistence to pathogenicity, during its interaction with E. huxleyi ( Barak-Gavish et al., 2018 ). We found that algal DMSP, which usually mediates mutualistic interactions, plays a pivotal role by invoking bacterial pathogenicity ( Barak-Gavish et al., 2018 ). Bacterial genes related to DMSP uptake and catabolism have been investigated in many studies ( Curson et al., 2011 ; Gao et al., 2020 ; Howard et al., 2006 ; Reisch et al., 2011 ; Sun et al., 2012 ; Todd et al., 2007 ), but the regulation of DMSP-responsive genes and their interplay with bacterial lifestyle and behavior during interactions with algae is yet to be explored. We performed a transcriptomics experiment that enabled us to elucidate the bacterial response to algal infochemicals and to characterize DMSP-responsive and pathogenicity-related genes. We revealed the signaling role of DMSP that led to a systemic remodeling of Sulfitobacter D7 gene expression but only in the presence of additional algal metabolites. Overall, we unraveled the transcriptional signature of the switch from coexistence to a pathogenic bacterial lifestyle during interaction with their algal host and provide insights into the ecological context of this mode of interaction.",
"discussion": "Discussion Signaling role of DMSP and other algal metabolites in the lifestyle switch of Sulfitobacter D7 In this study, we aimed to unravel the molecular basis for the lifestyle switch from coexistence to pathogenicity in Sulfitobacter D7 during interaction with the bloom-forming alga E. huxleyi . We substantiated the signaling role of algal DMSP that mediates the shift toward pathogenicity by mapping the transcriptional profiles of Sulfitobacter D7 in response to DMSP and other algal metabolites. However, DMSP signaling in medium that lacked E. huxleyi -derived metabolites (i.e. MM +DMSP) had a different effect on Sulfitobacter D7 transcriptome. We propose that the signaling role of DMSP that mediates the coexistence to pathogenicity lifestyle switch in Sulfitobacter D7 depends on other infochemicals produced by E. huxleyi . DMSP is a ubiquitous infochemical produced by many phytoplankton species as well as some bacteria ( Curson et al., 2017 ), making it a prevalent signaling molecule that mediates microbial interactions in the marine environment. Therefore, it is likely that other algal metabolites are involved in the recognition of the specific phytoplankter host by bacteria, thus ensuring specificity in DMSP signaling during alga-bacteria interactions. In natural environments, where many microbial species are present simultaneously, such a mechanism can ensure that bacteria will invest in altering gene expression and metabolic remodeling only when the right algal partners are present. We revealed that the alga-derived aromatic compound benzoate plays a pivotal role in Sulfitobacter D7- E. huxleyi interaction by maintaining the coexistence, even when DMSP is present at high concentrations ( Figure 6 , Figure 6—figure supplement 1 ). Benzoate also acts as an efficient bacterial growth factor serving as a carbon source ( Figure 4 ). These observations provide a possible explanation for the switch in bacterial behavior from coexistence to pathogenicity. During the interaction, E. huxleyi provides benzoate and other growth substrates to Sulfitobacter D7, which uptakes and consumes them ( Figure 7 ). We propose that as long as Sulfitobacter D7 benefits from the interaction with E. huxleyi by receiving beneficial growth substrates, it will maintain a coexisting lifestyle. When less growth substrates are provided by the alga, the opportunistic pathogen will switch to killing the algal host, which will in turn lead to a surge of intracellular E. huxleyi -derived metabolites that Sulfitobacter D7 can benefit from ( Figure 7 ). Studies on phytoplankton exudation of organic matter demonstrated that algae release more organic matter in stationary phase, but the chemical composition is different from that of exponential growth ( Barofsky et al., 2009 ; Jensen, 1984 ). In nutrient limiting conditions, which often occur in stationary phase, the organic matter exuded by phytoplankton is less favorable for bacterial uptake and consumption for growth ( Obernosterer and Herndl, 1995 ). In such a chemical context, high concentrations of algae-derived infochemicals, for example, DMSP ( Barak-Gavish et al., 2018 ) or p -coumaric acid ( Seyedsayamdost et al., 2011 ), can be perceived by bacteria and signal that the physiological state of the algal host is deteriorating. Namely, by sensing the changes in the metabolic composition of the phycosphere during the interaction, Sulfitobacter D7 executes its pathogenicity against a compromised E. huxleyi population. Therefore, the initial metabolic exchange in the coexistence phase is a prerequisite for the onset of bacterial pathogenicity. Figure 7. Conceptual model of the lifestyle switch of Sulfitobacter D7 in response to Emiliania huxleyi -derived metabolites. During its interactions with E. huxleyi , Sulfitobacter D7 exhibits a lifestyle switch from coexistence to pathogenicity. In the coexistence phase, E. huxleyi secretes to the phycosphere various metabolites such as benzoate, dimethylsulfoniopropionate (DMSP), and other growth substrates, which bacteria can uptake and consume for growth. Based on the observation that benzoate hindered the pathogenicity-inducing effect of DMSP, we hypothesize that such energy-rich metabolic currencies hinder DMSP signaling in Sulfitobacter D7. When the algal physiological state is compromised, for example, stationary phase, the amount of available growth substrates decreases, due to bacterial consumption and less secretion by the alga. In this context, high concentration of algal DMSP acts as a signal that alters the transcriptional profiles of the bacterium and leads to high expression of pathogenicity-related genes, such as flagellar and transport genes, and yet unknown virulence factors that kill E. huxleyi cells. This leads to a surge of alga-derived growth substrates that are taken up efficiently by Sulfitobacter D7. The flagellum can mediate the dispersal of Sulfitobacter D7 and to forage for an alternative host. The ability to utilize benzoate is shared among bacterial strains that are associated with E. huxleyi in the natural environment and in cultures ( Figure 5a ; Green et al., 2015 ; Orata et al., 2016 ; Rosana et al., 2016 ; Vincent et al., 2021 ). Since benzoate can act as an antibacterial compound ( Amin and Abolmaaty, 2020 ; Haque et al., 2005 ), we propose that secretion of benzoate by E. huxleyi can select for bacteria that specialize on this compound and is therefore important for the establishment of a coexistence phase. Similarly, the diatom Asterionellopsis glacialis produces two secondary metabolites that select for specific bacteria and affect their behavioral response ( Shibl et al., 2020 ). Bacterial sensing of general phytoplankton-derived compounds (e.g. DMSP) together with additional more selective compounds (e.g. benzoate) can ensure the recognition of the algal host by the bacteria within the phycosphere. This can increase the specificity of an interaction and ensure fine-tuning of the behavior of microorganisms by regulating gene expression. This is especially relevant for DMSP that has diverse functions in bacteria ( Barak-Gavish et al., 2018 ; Kessler et al., 2018 ; Miller et al., 2004 ; Miller and Belas, 2004 ; Seymour et al., 2010 ). Molecular mechanisms in bacteria that integrate information perceived by various chemical signals include catabolite repression and two-component systems, which can also play a role in regulating bacterial pathogenicity ( Beier and Gross, 2006 ; Görke and Stülke, 2008 ). The lifestyle switch of Sulfitobacter D7 from coexistence to pathogenicity Our experimental setup demonstrated that Sulfitobacter D7 grown in pathogenicity-inducing media are in a different transcriptional state than in coexistence medium, which corresponds to the behavioral switch during co-culturing with E. huxleyi ( Figure 1 ). Many transport systems were DE, mainly upregulated, when Sulfitobacter D7 was in pathogenic state compared to the coexistence state ( Figure 3 ). Since bacteria often exert their pathogenicity as a means to access nutrients released from the host, it is likely that in this mode Sulfitobacter D7 will maximize uptake and assimilation of metabolites released by dying E. huxleyi cells. High expression of transporters for branched-chain amino acids, C4 carbohydrates, DMSP, taurine, and polyamines can facilitate the efficient uptake of these energy-rich metabolites ( Figure 3 , Figure 3—source data 1 ). Upregulation of transport genes for these metabolic currencies in response to DMSP was also demonstrated in R. pomeroyi DSS-3, a Roseobacter often used to study metabolic exchange between bacteria and phytoplankton ( Bürgmann et al., 2007 ; Durham et al., 2015 ; Landa et al., 2017 ). During the pathogenic lifestyle there was upregulation of flagellar genes, which was functionally validated by motility assays ( Figure 2 ). While DMSP is a known chemoattractant and therefore mediates the establishment of bacterial interactions with algae ( Miller et al., 2004 ; Seymour et al., 2010 ), we speculate that this is not the case for Sulfitobacter D7, since its genome does not encode for known chemotaxis genes. We propose that the increased motility in response to DMSP in the pathogenic mode can serve as an ecological strategy to escape from competition with other bacteria in the phycosphere ( Yawata et al., 2014 ). E. huxleyi cell death, induced by Sulfitobacter D7, likely leads to a surge of intracellular metabolites that may attract other bacteria. The upregulation of transport systems together with flagellar motility can enable efficient substrate uptake by Sulfitobacter D7 and swimming away to forage for alternative metabolically active hosts. Such an ‘eat-and-run’ strategy can be ecologically beneficial by facilitating the evasion from competition. Upregulation of flagellar genes was also demonstrated during the mutualistic to pathogenic lifestyle switch of the Roseobacter Dinoroseobacter shibae during interaction with a dinoflagellate algal host ( Wang et al., 2015 ). Even though Sulfitobacter D7 motility was increased in the pathogenic mode ( Figure 2 ), the involvement of the flagellum may be by other functions that mediate bacterial virulence ( Chaban et al., 2015 ); that is, flagella can mediate biofilm formation and attachment to surfaces ( Li et al., 2016 ). Additionally, the flagellar type 3 secretion system, which is found in the basal body and necessary for secretion of the components needed for flagellum assembly, can also be used as an export system for effector proteins in pathogenic bacteria ( Diepold and Armitage, 2015 ). In this manner, pathogenic bacteria may utilize the flagellum for multiple functions important for pathogenicity against their hosts and subsequent dispersal. The mechanism of Sulfitobacter D7 pathogenicity against E. huxleyi remains to be discovered. The genome of Sulfitobacter D7 encodes numerous cellular machineries, such as type 2 secretion system (T2SS), Flp (fimbrial low-molecular-weight protein) pilus, and two type 4 secretion systems, which can potentially mediate cell-cell interactions and possibly bacterial virulence ( Backert and Meyer, 2006 ; Cianciotto and White, 2017 ; Ku et al., 2018 ; Tomich et al., 2007 ). While the Flp pilus and T4SS are common features encoded in Roseobacter genomes, T2SS is less prevalent ( Frank et al., 2015 ; Slightom and Buchan, 2009 ). This may hint for a unique mode of pathogenicity in Sulfitobacter D7 and requires further investigation. Ecological context of bacterial lifestyle switches during algal blooms Bacterial lifestyle switches are evident in several model systems of phytoplankton-bacteria interactions; however, the ecological significance of such modes of interaction in the natural environment is elusive. In this study, we provide a contextual framework for the switch from coexistence to pathogenicity – metabolite depletion in the phycosphere. During a phytoplankton bloom, heterotrophic bacteria can support the growth of the algae and benefit from organic matter released to the phycosphere. As the bloom progresses, various factors, such as nutrient depletion, viral infection, and grazing, can compromise the algal population and its ability to provide essential metabolic currencies for optimal bacterial growth. We propose that bacteria can sense the host's physiological state, by infochemicals secreted from stressed algae, and switch their behavior to pathogenicity. This will result in algal cell death and bacterial proliferation, which could eventually contribute to the bloom demise. Therefore, phytoplankton-associated opportunistic bacterial pathogens constitute an underappreciated component in the regulation of algal blooms dynamics. Investigating the dynamic microscale interactions of such bacteria with phytoplankton and the metabolic crosstalk that mediates them can provide insights into their impact on large scale biogeochemical processes in the marine environment."
} | 5,063 |
28513556 | PMC5487990 | pmc | 6,666 | {
"abstract": "Poly(3-hydroxybutyrate) (PHB) is an interesting biopolymer for replacing petroleum-based plastics, its biological production is performed in natural and engineered microorganisms. Current metabolic engineering approaches rely on high-throughput strain construction and screening. Analytical procedures have to be compatible with the small scale and speed of these approaches. Here, we present a method based on isotope dilution mass spectrometry (IDMS) and propanolysis extraction of poly(3-hydroxybutyrate) from an Escherichia coli strain engineered for PHB production. As internal standard (IS), we applied an uniformly labeled 13 C-cell suspension, of an E. coli PHB producing strain, grown on U- 13 C-glucose as C-source. This internal 13 C-PHB standard enables to quantify low concentrations of PHB (LOD of 0.01 µg/g CDW ) from several micrograms of biomass. With this method, a technical reproducibility of about 1.8% relative standard deviation is achieved. Furthermore, the internal standard is robust towards different sample backgrounds and dilutions. The early addition of the internal standard also enables higher reproducibility and increases sensitivity and throughput by simplified sample preparation steps.",
"conclusion": "5. Conclusions Using a sensitive detection system (GC-MS) together with an appropriate internal standard, a robust, easy to perform PHB quantification method was achieved. The IS- 13 C-PHB suspension not only corrects for matrix effects, but also variations in the sample preparation process that is suitable for low sample amount measurements. A low sample volume can provide flexibility and convenience for the researcher to design experiments. For instance, low volume cultivation experiments using shake flasks, falcon tubes, or even a microtiter plate. The technical reproducibility for sample measurements was 1.9%. Including the sample processing steps, a reproducibility of 2% was observed, supporting that the internal standard can correct for sample processing variability [ 23 ]. While the reported method was focused on PHB, different polymers are produced by microorganisms. The presented approach can be extended to the quantification of PHV, P4HB (poly(4-hydroxybutyrate)), and other polyhydroxyalkanoates.",
"introduction": "1. Introduction Since the discovery of PHB accumulating microorganisms, different approaches have been proposed for a precise and accurate measurement of the PHB content [ 1 , 2 ]. The first method was developed by Lemoigne [ 3 ], which was followed by a series of improvements. Especially, different reagents for extraction like dichloroethane, chloroform [ 4 ], or free chlorinated solvents like propanol or butanol [ 5 ] have been developed. Nowadays, one of the most commonly used methods is propanolysis and GC-based quantification [ 6 , 7 , 8 , 9 ]. The method can be applied to a wide range of microorganisms [ 10 , 11 ]. Next to propanolysis an approach based on derivatization with N -tert-butyldimethylsilyl- N -methyltrifluoroacetamide (MTBSTFA) and GC-MS/MS has been proposed [ 12 ]. A comparison of the described methods including required sample amounts and accuracy can be found in Table 1 . Unfortunately, not all methods were fully documented with respect to detection limits and accuracies—therefore, partly, the lowest calibration point rather than detection limit is reported. In this study, the LOD reported is based on a split 1:500 injection meaning that only 2 nL is injected on the column, the GC-MS/MS method is used in SL (splitless) mode, which means that 0.1 µL is injected. Therefore, there is also the possibility of lowering the LOD at least 100 times. There are two main limitations in the current methods: (1) laborious and time consuming sample preparation and (2) the requirement of several milligrams of biomass [ 1 ]. In view of high-throughput experimentation, a fast and small-scale method is needed. Especially, the cultivation volume will be limited and only small sample volumes can be obtained. Further, a high amount of samples is only feasible with a robust and simple protocol [ 16 , 17 ]. Here, we present an approach that is robust towards the cellular matrix and requires small sample volumes, especially the weighing step of samples and standards for the PHB quantification. The major difference to previous methods is the application of a labeled internal standard [ 18 , 19 ].",
"discussion": "3. Results and Discussion The development of the novel PHB measurement method required a series of experiments to verify the potential use of the proposed IS and the reduction of steps involved in the analytical protocol. Besides establishing calibration lines and the study of a matrix effect, other experiments were performed such as complete assessment of the derivatization time, homogeneity, and simultaneous biomass quantification, which can be found in the Supplementary Materials . 3.1. PHB Determination from Small Sample Volume To test if the extraction and derivatization from small sample volumes would bias the results, the results were compared to the GC-FID based measurement [ 4 ]. The results showed a PHB content of 14.4 ± 1.6% with the new method and 12.7 ± 2.0% with the conventional method. The t -test ( p < 0.05) demonstrate no significant difference between methods. 3.2. Calibration with Labeled PHB as Internal Standard Equal amounts of IS- 13 C-PHB were added to each standard of 3-HB. The peak area ratio was then measured by GC-IDMS. Linear calibration lines were obtained from the ratio between the 12 C-3HB and the IS- 13 C-PHB suspension). The standard deviation of the ratio ( 12 C-PHB/IS- 13 C-PHB) measurements was used to calculate the relative and the absolute error: 0.0053 mmol/L and 3 × 10 −5 respectively. The resulting heteroscedastic error model was used for weighted linear regression. A calibration line, valid over four orders of magnitude was obtained ( Figure 2 )."
} | 1,473 |
38886365 | PMC11183213 | pmc | 6,667 | {
"abstract": "Understanding what makes a community vulnerable to invasion is integral to the successful management of invasive species. Our understanding of how characteristics of resident plant interactions, such as the network architecture of interactions, can affect the invasibility of plant communities is limited. Using a simulation model, we tested how successfully a new plant invader established in communities with different network architectures of species interactions. We also investigated whether species interaction networks lead to relationships between invasibility and other community properties also affected by species interaction networks, such as diversity, species dominance, compositional stability and the productivity of the resident community. We found that higher invasibility strongly related with a lower productivity of the resident community. Plant interaction networks influenced diversity and invasibility in ways that led to complex but clear relationships between the two. Heterospecific interactions that increased diversity tended to decrease invasibility. Negative conspecific interactions always increased diversity and invasibility, but increased invasibility more when they increased diversity less. This study provides new theoretical insights into the effects of plant interaction networks on community invasibility and relationships between diversity and invasibility. Combined with increasing empirical evidence, these insights could have useful implications for the management of invasive plant species.",
"introduction": "Introduction Understanding and predicting invasion in plant communities is a critical question in ecology. Significant progress has been made in identifying traits of invading plants and of resident plant communities that affect invasion success. Invader traits shown to increase invader success (invasiveness) include long-range seed dispersal 1 , the ability to alter growth conditions favoured by resident species 2 – 4 , and rapid evolutionary change that results in increased competitive ability 5 , such as the evolution of novel traits or novel biochemical ‘weapons’ 6 . Resident community traits shown to affect invasion success (invasibility) include niche space availability and the presence of enemies or competitors 7 . While theories suggest that diverse communities may be less invadable due to having fewer available niche spaces and more enemies/competitors 5 , a general relationship between diversity and invasibility is debated 8 – 10 . Plant-plant interactions can affect species coexistence including the coexistence of competitors, through for example, facilitation 11 . Therefore, plant-plant interactions likely also affect community invasibility 11 – 13 . However, few studies have explored how plant interactions that affect community traits such as diversity and the presence of competitors affect community invasibility, as it is empirically challenging to do so. In plant communities, a range of positive and negative interactions between species occur, directly through facilitation or competition, or indirectly through changes to abiotic /biotic conditions. A network approach is increasingly being used in ecology as a framework to explore the complexity of species interactions and their effects on community structure and functioning 14 , 15 . As collecting empirical data on complete ecological interaction networks is challenging, most studies model invasion in simulated communities with defined interaction networks. This allows for the roles of different factors in the invasion process to be disentangled. Such work has led to the identification of several network properties that can affect community invasibility. These include connectivity—the number of interactions among species 16 , interaction symmetry—the differences in the number or strength of interactions among species 17 , and the network architecture type—the arrangement of interactions among species also known as network topology or structure 18 , 19 . From such studies, nested architectures, where a group of highly interactive species interact with many other species, with few to no interactions occurring among the other species, have been found to increase invasibility in trophic communities (negative interactions among species) 18 , but not in plant-pollinator communities (positive interactions among species) 19 . Modularity, where species interact in groups/modules, with relatively few interactions occurring among the different modules, has been found to increase invasibility in both trophic and plant-pollinator networks 18 , 19 . While studies have explored the effect of network architecture on plant community diversity and resilience 20 – 25 , few have considered its effects on invasibility 17 , 21 , 26 . Mack et al. 21 compared the invasibility of plant communities with either intransitive interaction networks or with only negative conspecific interactions, which are both interactions shown to increase species coexistence/diversity 27 . Intransitive interaction networks are where there is no clear “winner” among the competitors. It can be a type of negative ring network architecture where species A negatively affects species B which then negatively affects species C which then negatively affects species A, creating a ring architecture A > B > C > A. Negative conspecific interactions are a type of negative frequency-dependent feedback where individuals of the same species (conspecifics) make conditions less suitable for each other. Mack et al. 21 found that communities with intransitive interaction networks were less susceptible to invasion than communities with negative conspecific interactions. Kinlock & Munch, 26 found that intransitive interaction networks were more invadable that transitive networks, where there is a clear hierarchy among the competitors. However, intransitive communities became the least invadable of the three when species richness was low, suggesting invasibility is affected by a complex interaction between network architecture and diversity. As other network architectures of positive and negative interactions likely exist in plant communities (e.g., modular architectures) and can affect species coexistence and diversity 24 , the effects of other architectures on plant community invasibility should also be explored. It is suggested that how diversity affects invasibility depends critically on the processes regulating diversity in resident communities 12 , 26 , 28 , 29 . The same could be true for other lesser studied emergent properties such as compositional stability and productivity, which like diversity, will also affect the presence/strength of competitors 24 , 26 . As networks of plant interactions can affect emergent community properties, such as diversity and compositional stability, considering their effects on invasibility may help explain relationships between these emergent properties and plant community invasibility. In this study, we explored how nested, modular, and intransitive plant-plant interaction networks with either positive or negative interactions among species, and with/without negative conspecific interactions, affect community invasibility using a stochastic grid-based simulation model of plant community dynamics. Specifically, we aimed to investigate: How different network architectures of heterospecific interactions, with and without negative conspecific interactions, affect a plant community’s vulnerability to invasion; and Whether species interaction networks can lead to and explain relationships between invasibility and other emergent community properties also affected by plant species interaction networks, such as pre-invasion alpha diversity, productivity, and compositional stability.",
"discussion": "Discussion Our results indicate that plant interaction networks can affect a community’s vulnerability to invasion by affecting the average growth rate of the resident community. As a slower average growth rate (productivity) of the resident community equates to a reduced competitive ability, this result is consistent with theory that shows that invasion can occur when the invader has a competitive advantage over resident species 5 , 6 . However, how plant interaction networks affected the average growth rate of the community, and thus invasibility, was not simply due to the presence/absence of negative or positive interactions. Instead, it also depended on the diversity, dominance, composition, and compositional stability of the communities that result from plant interaction networks. Our results showed two main diversity-invasibility and diversity-growth rate relationships. Negative conspecific interactions promoted diversity and increased vulnerability to invasion. However, among our PSFI scenarios with negative conspecific interactions, those with higher diversity were less vulnerable to invasion. These apparently contradictory relationships could be explained by considering the mechanism by which plant interaction networks affected diversity and average growth rate. For example, negative conspecific interactions promoted diversity in our plant communities, but also reduced their average growth rate and thus made them more vulnerable to invasion. However, species have a lower probability of propagating into soil conditioned by a conspecific if there is high diversity. Therefore, resident species with negative conspecific interactions are more likely to grow at a faster rate in a diverse community, making them more competitive, and thus these communities are less vulnerable to invasion. Following this, the PSFI scenarios where the addition of negative conspecific interactions did not greatly increase diversity, e.g. negative nested scenarios, had the highest invasibility. It is not surprising that mechanisms that promote species coexistence can also make the community more vulnerable to invasion, as by definition, stable coexistence requires species to be able to successfully invade an established population of the other species 36 . However, interestingly, our results provide a novel explanation for why the relationship between coexistence, diversity, productivity, and community invasibility can be complex, based on plant species interaction networks alone. Therefore, our results add to a growing body of literature that suggests that how diversity affects invasibility depends critically on the processes regulating diversity in resident communities 5 , 12 , 28 , 29 . Our results are consistent with previous work that suggests that a nested architecture makes a community more vulnerable to invasion when the interactions among species are negative 19 . Negative nested interactions can lead to a stable dominance of the competitive “winners” – those that experience the fewest number of negative interactions, even with the addition of negative conspecific interactions which normally reduce species dominance 24 . Our results suggest that in a negative nested scenario with negative conspecific interactions when a highly interactive species dominates, conspecifics, other highly interactive species, and other less interactive neutral species, all grow at a slower rate in soil conditioned by the dominant highly interactive species. As a slower average growth rate of the resident community equates to a reduced competitive ability, this explains why negative nested communities, especially those with negative conspecific interactions, were our most easily invaded PSFI scenario. Negative modular architectures can lead to one species from each module dominating, resulting in a community with, for example, five non-interacting dominant species for a scenario of five modules 24 . Similarly, negative ring architectures also lead to the dominance of non-interacting species 24 . As the dominant species in these communities were not negatively affecting each other’s growth, the average growth rate of negative ring or modular communities was higher than that of the negative nested communities, thus resulting in ring or modular communities being less invadable. Negative ring communities were slightly more invadable than negative modular communities. This is likely an artefact of the model which meant that more species were negatively affected by soil conditioned by any other species under a ring network architecture compared to a modular network architecture for any given group size (e.g. 20 species under ring scenarios vs 19 species under modular scenarios when group size is 20), thus making the average growth rate lower in the negative ring communities. Invasion was most prevalent in scenarios with negative heterospecific interactions, but sometimes scenarios with positive heterospecific interactions were also invaded. These included scenarios with positive ring heterospecific interactions and negative conspecific interactions, which have previously been found to encourage extreme species dominance at one point in time 24 . We suspect that under this scenario the population of dominant species in the community temporarily crashes as the probability of propagating in conspecific soil becomes high, resulting in a sharp drop in the average growth rate of the resident community. We believe that this rise of dominance through positive interactions, then crash following the effects of negative conspecific interactions, created a window of opportunity for the invader to establish in these communities. Positive nested scenarios and the null scenario also saw the establishment and coexistence of the invader. This is because under positive nested interactions, the highly interactive facilitator species become disadvantaged as they experience a fewer number of positive interactions, the reverse of the effect observed for negative nested interaction scenarios explained above. This eventually results in a community containing mostly non-interactive species that is then functionally equivalent to the null scenario (contains only non-interacting species). In these null and positive nested scenarios, the invader’s positive conspecific interactions are enough to allow it to immigrate, coexist and eventually dominate in these communities, especially (but not only) when negative conspecific interactions slow the average growth of the resident community. Our work is only a first step towards understanding how plant interaction networks can affect the invasibility of communities over time. In many ways our model lacked biological realism. Our approach where species are identical except for differences in species interactions allowed for the effects of plant interaction networks on invasibility to be clearly distinguished, but it also meant that differences among species were relatively subtle which may not be true in nature. Additionally, in nature the invader would likely interact with resident species which could have important implications for invasion as seen in Kinlock & Munch 26 . Moreover, plant interactions resulted in some communities being compositionally unstable over time (Fig. 4 ). Although compositional stability did not directly relate to invasibility, different compositions of a community could result in different levels of productivity. Therefore, the invasibility of a community that is compositionally unstable may vary over time. Dispersal was also not limited in our model. This meant that we could not explore the effects of species interactions on the spatial clustering and segregations of species across the landscape as seen in other studies 26 and in nature 37 . With local dispersal, species may be able to avoid interacting with certain other species in the community through spatially distancing themselves from them. As suggested in Kinlock & Munch 26 , this could have important implications for invasibility if spatial patterns due to plant interactions exist despite/on top of the effects of abiotic drivers. Lastly, our 100 species communities were much larger than those used in comparable studies (3–11 species) 21 , 26 , who found interesting interactions between changes in species number and interaction structure in the effects on invasibility; this also warrants further investigation. Better application to real systems will require further development of empirical and analytical methods for identifying and quantifying plant species interaction networks. Once species interaction networks can be identified, the long-term effects of interaction networks on community dynamics can then be investigated through simulation studies such as this one. These developments will help the ideas of this study to be applied to real systems. In conclusion, our model demonstrated that different plant interaction networks can lead to communities with different levels of invasibility. Resident communities with lower average growth rates (lower productivity) were more invadable. The effect of plant interactions on the average growth rate of the resident species was not simply explained by the presence/absence of negative or positive heterospecific interactions, but also depended on the dominance, composition, and compositional stability of the communities as derived from the plant interactions. We also found that plant interactions can lead to and explain apparently contradictory relationships between diversity and invasibility, with negative conspecific interactions leading to a positive relationship between diversity and invasibility and heterospecific interactions leading to a negative relationship between diversity and invasibility. Overall, our results suggest that understanding the mechanisms driving emergent properties such as species coexistence, diversity, productivity and compositional stability, can be useful for understanding complex relationships between emergent community properties and invasibility, and that network architecture of species interactions could be one of these key mechanisms."
} | 4,483 |
37513019 | PMC10385058 | pmc | 6,671 | {
"abstract": "The use of biological inputs is an interesting approach to optimize crop production and reduce the use of chemical inputs. Understanding the chemical communication between bacteria and plants is critical to optimizing this approach. Recently, we have shown that Sphingomonas ( S .) sediminicola can improve both nitrogen supply and yield in pea. Here, we used biochemical methods and untargeted metabolomics to investigate the chemical dialog between S. sediminicola and pea. We also evaluated the metabolic capacities of S. sediminicola by metabolic profiling. Our results showed that peas release a wide range of hexoses, organic acids, and amino acids during their development, which can generally recruit and select fast-growing organisms. In the presence of S. sediminicola , a more specific pattern of these molecules took place, gradually adapting to the metabolic capabilities of the bacterium, especially for pentoses and flavonoids. In turn, S. sediminicola is able to produce several compounds involved in cell differentiation, biofilm formation, and quorum sensing to shape its environment, as well as several molecules that stimulate pea growth and plant defense mechanisms.",
"conclusion": "5. Conclusions The chemical dialog underlying plant–microbe interactions are essential to understanding the use of microorganisms in agriculture. We have shown that pea plants employ a strategic mechanism to selectively recruit specific bacteria to their rhizosphere that have the potential to confer benefits to the plants. During its development, the plant modulates its root exudation by first releasing various generalist molecules that allow recruitment focused on fast-growing bacteria. Then, the exudation evolves further by releasing more specific compounds that are tuned to the metabolic potential of the targeted bacterial microbiota, such as Sphingomonas sediminicola . In return, the bacteria provide various services to the plant that allow it to develop better and cope with environmental conditions [ 35 ]. This beneficial interaction between the plant and a bacterium is a step towards understanding the interaction between plants and bacteria. Indeed, the plant in agricultural soil is in relationship with a large variety of organisms, some of which are beneficial, others less so. Therefore, it is important to understand how the plant adapts its recruitment strategies to select the most important partners. It is also important to identify the mechanisms that enable molecular and chemical dialog between partners. Understanding all these strategies is potentially an important lever for implementing more sustainable agriculture.",
"introduction": "1. Introduction Plant growth and productivity are closely associated with rhizospheric bacteria, such as plant growth-promoting rhizobacteria (PGPR), in a reciprocal relationship that benefits both partners [ 1 , 2 ]. These bacteria can live freely in the rhizosphere of plants or be directly associated with plants in a symbiotic relationship. Free PGPR contributes to plant health and development by producing plant growth regulators [ 3 ], increasing the availability of nutrients and water, and reducing the effects of diseases, pests, and environmental stressors. They can also increase the amount of soil organic matter, improve soil texture and structure, and promote micronutrient uptake [ 4 , 5 , 6 ]. Symbiotic PGPR such as those of the order Hyphomicrobiales (= Rhizobiales ) are useful for agriculture because they are able to form nodules on the roots of legumes in which the atmospheric nitrogen (N 2 ) fixed by the bacteria is converted into ammonia for the plant [ 7 ]. The interaction between plants and bacteria requires complex chemical communication, which can be viewed as a conversation between the two parties in which plants and bacteria exchange chemical signals to influence their growth and development [ 8 , 9 ]. First, plants and bacteria can sense each other’s chemical signals through specific receptors [ 10 , 11 ], which usually enables the recruitment of beneficial bacteria by the plant. Plants and bacteria can respond to chemical signals by altering their growth, metabolism, and functions that allow bacteria to colonize plant roots. This also affects the production of chemical signals, forming a feedback loop that leads to an equilibrium beneficial to both organisms [ 12 , 13 ]. PGPRs recruitment by plants requires a significant amount of energy to attract and select bacteria in the rhizosphere [ 14 , 15 , 16 ]. Plant roots release a variable and diverse set of compounds, including carbohydrates, amino acids, organic acids, and secondary metabolites [ 17 , 18 , 19 ]. The compounds released by the roots are an important nutrient source for soil bacteria and have an attractive effect [ 20 ]. In turn, PGPR produces compounds that promote plant growth and health [ 19 , 21 ]. Various studies have shown that the microbial community associated with the root can evolve depending on the chemical composition of the root exudates, which also depends on the plant species and its stage of development [ 11 , 19 , 22 ]. For effective interaction, it is important that the bacteria are metabolically adapted to the chemical signals released by the plant via its root exudates so that they can be recruited and establish themselves in the root system. Agriculture based on the interaction between plants and bacteria promises to limit the use of chemical fertilizers that have negative effects on the environment and health acts [ 23 , 24 ]. Since the last decades, bacterial fertilizers containing free N 2 -fixing PGPR, such as Pseudomonas stutzeri , P. oryzihabitans, or Azospirillum brasilense, have been successfully used in agriculture as a strategy to improve plant growth in a sustainable way [ 6 , 25 , 26 , 27 ]. This aspect is even more pronounced in legumes such as pea, which is normally thought to interact with Rhizobium species [ 28 ]. Therefore, the molecular dialogs during this interaction have been studied in detail [ 29 , 30 ]. These interactions, which depend on the specific characteristics of the pea species and the bacterial species involved, make it possible to predict the effectiveness of the use of this bio-input. Despite the importance of this association, it is important to note that in conventionally plowed soils where peas are rotated, the bacterial community may also be predominantly influenced by other bacterial species, such as Sphingomonas [ 31 , 32 , 33 , 34 ]. Recently, we have shown that Sphingomonas sediminicola is also able to induce the formation of root nodules in peas and increase the production of plant biomass [ 35 ]. This new interaction raises the question of chemical communication between the two partners and offers the possibility of optimizing the effect of bacterial bio-input on a pea plant. Therefore, we examined a wide range of compounds, including carbohydrates, carboxylic acids, amino acids, polyphenols, and flavonoids in hydroponic pea cultures inoculated and non-inoculated with S. sediminicola . We compared these results with the metabolic phenotyping of S. sediminicola based on its ability to degrade various carbon, nitrogen, phosphorus, and sulfur sources. To get an overview of the effect of S. sediminicola on peas, we also analyzed the compounds released by the bacterium.",
"discussion": "4. Discussion Plants release root exudates [ 44 , 45 ] to influence soil bacterial communities and attract certain bacteria to the rhizosphere [ 46 , 47 ]. However, the changes in root exudate composition induced by bacteria involved in plant growth remain poorly understood. During pea development, carbohydrates, particularly hexoses and sucrose, accumulate in the hydroponic solution. Fructose levels notably increase during the transition from leaf emergence to flowering, while sorbitol and xylitol become undetectable. These compounds, being simple sugars, can serve as a carbon and energy source for many bacteria [ 48 ]. Their presence in the hydroponic solution may serve as a chemical communication strategy to recruit bacterial partners capable of utilizing labile carbon. Notably, these molecules have been described to effectively attract bacterial species such as Bacillus , Methylobacterium, or Pseudomonas [ 22 ]. In addition, the abrupt increase in galactose content in pea hydroponic solution at flowering is consistent with Knee et al. [ 49 ] but also with the chemotaxic character of the molecule. Indeed, this compound induces a chemotaxis effect on some PGPR, such as Pseudomonas with legume roots or Bacillus velezensis with cucumber roots [ 49 , 50 ]. In the hydroponic solution of peas inoculated with S. sediminicola , hexose contents followed similar trends until the formation of the second internode. Compared with the non-inoculated peas, higher pentose, and lower galactose contents were observed under the conditions with S. sediminicola . This indicates carbohydrate communication adapted to S. sediminicola , which fits with the more pronounced metabolic preference of the bacterium for pentoses compared to hexoses and the predominant use of these compounds in its culture medium. Pentoses, like hexoses, are labile carbon sources, but their degradation may be more complex than that of hexoses because the enzymes required for their degradation may be less abundant in soil microorganisms [ 51 ]. In addition, pentoses may be incorporated into complex polymers such as cellulose and hemicellulose, which are important components of fresh soil organic matter [ 52 ]. In this case, their degradation may be slower and require the activity of specialized microorganisms such as S. sediminicola [ 32 ]. The hydroponic solution of non-inoculated peas contains high concentrations of organic acids, particularly acetic, citric, lactic, and furamic acids. Acetic and citric acids are generally released by plants to increase nutrient uptake, such as phosphorus [ 53 ], manganese [ 54 ], iron, and zinc [ 55 ]; stimulate biofilm production and motility of some PGPR [ 56 , 57 , 58 ]; induce nitrogen-fixing bacteria [ 59 ], Rhizobium IC3109 [ 58 ] and acid-forming bacteria ( Acetobacter and Gluconacetobacter [ 60 ]); or stimulate bacteria such as Pseudomonas , which is capable of producing plant growth hormones and protecting plants from disease [ 61 ]. Citric acid has also been shown to recruit phosphate-solubilizing bacteria ( Pseudomonas putida [ 62 ]) or symbiotic bacteria ( Burkholderia cepacia and Rhizobium leguminosarum [ 58 , 63 , 64 , 65 ]). Similarly, lactic acid released from the roots of legumes has been shown to attract bacteria such as Lactobacillus and Pediococcus [ 66 , 67 ]. This organic acid is also known for its antimicrobial properties, which can help the plant against pathogens in the rhizosphere [ 68 , 69 ]. Furamic acid was also present in the hydroponic solution. This acid plays an important role in recruiting plant-friendly rhizobacteria, symbiotic nitrogen-fixing bacteria, phosphate-solubilizing bacteria, or bacteria that produce antimicrobial compounds that protect plants from soil pathogens [ 61 , 70 , 71 ]. Therefore, pea releases a wide range of organic acids that serve as a broad-spectrum attractant for rhizosphere bacteria to entice any bacteria capable of perceiving and metabolizing these compounds, potentially including beneficial bacteria that promote plant growth. In the presence of S. sediminicola , the hydroponic solution of peas also contains the same organic acids, except for lactic acid. The presence of these organic acids in the hydroponic solution of peas inoculated with S. sediminicola is consistent with the metabolism of the bacteria, which can utilize acetic and furamic acids but not lactic acid. ( Table S3 ). Other organic acids, such as tartaric acid and butyric acid, which are highly metabolized by S. sediminicola and involved in regulating plant–microorganism communication, could be further quantified [ 63 , 72 ]. In the later growth stages, plants secrete amino acids and polyphenols, which shape bacterial communities [ 18 , 73 ]. Amino acids serve as a nitrogen source for bacteria [ 74 ], leading to competition for nutrient sources among them [ 75 ]. Polyphenols and flavonoids also act as nutrient sources and chemoattractants for bacteria involved in infections or symbiotic relationships, such as Agrobacterium tumefaciens or rhizobia [ 73 , 76 ]. Previous studies have shown that Pseudomonas fluorescens and P. aeruginosa induce the secretion of specific phenolic acids and increase the total content of polyphenols at different plant growth stages, especially in advanced stages of chickpea plants [ 77 ]. Our study indicates that the hydroponic solution of peas inoculated with S. sediminicola is enriched with amino acids and polyphenols from the formation of the second internode to flowering. This suggests that these compounds are a response of the peas to the presence of the bacteria and may affect the bacterial community structure. In addition, bacteria capable of metabolizing a wide range of amino acids from root exudates have a selective advantage in the plant rhizosphere [ 61 , 78 ]. The metabolism of S. sediminicola exhibits a high affinity for amino acid substrates and degrades nearly 80% of all such substrates, which also explains the large number of amino acids used by the bacteria in its culture medium. Flavonoids are plant secondary metabolites released into the rhizosphere, playing a crucial role in chemical communication with rhizosphere bacteria [ 79 ]. They act as chemoattractants for bacteria involved in symbiotic interactions with the plant, such as rhizobia [ 80 ]. Additionally, flavonoids stimulate biofilm production, promoting bacterial colonization of roots, which can lead to better plant growth and health [ 81 ]. Interestingly, the hydroponic solution of peas inoculated with S. sediminicola contained flavonoids, which were not detected in the non-inoculated condition. Moreover, flavonoid content increased with pea development. Some identified flavonoids in the solution corresponded to pisatin, a plant phytoalexin with an antimicrobial activity produced by plants in response to infection or stress [ 82 , 83 , 84 ]. Thus, the induction of pisatin production in the presence of S. sediminicola can be considered a pea defense response. It is noteworthy that S. sediminicola has the ability to form nodules on pea roots during nitrogen stress, aligning with observations in pea- Rhizobium interaction and the regulatory role of isoflavonoids in nodulation [ 35 , 85 , 86 ]. Fragmentation analysis of other peaks from biochemical analysis would help in the identification of other flavonoid compounds. During their growth, rhizospheric bacteria produce various molecules for their own growth, including galactoside [ 87 ]. Galactopinitol b was among the galactosides detected in the culture medium after the growth of S. sediminicola . These galactosides serve as carbon and energy sources for the bacteria, facilitating their growth in the rhizosphere. In addition, certain rhizobia can synthesize galactopinitol b, which may play a role in establishing symbiotic relationships with plants [ 88 , 89 , 90 ]. In the culture medium, we also detected the presence of various components involved in cell differentiation, biofilm formation, and quorum sensing. Thus, the bacterial culture medium was enriched with methyl-4-hydroxy-6-methyl-2-pyrone as well as p-coumaroyl-homoserine lactone (pC-HSL). These compounds are quorum-sensing molecules, facilitating communication and coordination among bacteria to regulate their collective behavior [ 91 , 92 ]. In the same manner, monoglycosyl-N-acylsphingosine, which is involved in biofilm formation, may also regulate plant growth and modulate the plant immune system [ 93 , 94 ]. Interestingly, enrichment of the R2A medium with auxin-associated molecules (indole-3-carboxylic acid, methylimidazoleacetic acid, and indole-3-acetic acid) was also observed. Therefore, S. sediminicola might affect plant growth and development and auxin homeostasis in roots via these molecules [ 95 ]. Thus, it would be interesting to investigate whether the presence of S. sediminicola at the root level affects plant development, root system architecture, plant defense mechanisms, but also the organization of microbial communities in the rhizosphere. Overall, we provide new information on how pea plants modulate the composition of their root exudates to recruit bacteria from which they, and Sphingomonas sediminicola in particular, can benefit. We also describe for the first time the full metabolic and catabolic potential of this bacterium. In future experiments, the inclusion of other rhizobia would provide valuable comparative data on the effects of different bacterial species. Such information would not only improve our understanding of the specific interactions between these bacteria and pea plants but also shed light on the broader context of plant–microbe associations in agricultural systems. It is important to note that our study was conducted under controlled hydroponic conditions that allowed precise control of nutrient availability and environmental factors. However, it would be equally interesting to study the chemical dialog between S. sediminicola and pea plants in an agricultural soil context. Soil conditions have a significant impact on microbial community structure and nutrient dynamics, which could influence the nature and extent of plant–microbe interactions. Future studies in agricultural soil systems would provide a better understanding of the practical implications and transferability of our results to real agricultural conditions."
} | 4,450 |
39811656 | PMC11731282 | pmc | 6,674 | {
"abstract": "Summary Lignin valorization is crucial for achieving economic and sustainable biorefinery processes. However, the enzyme substrate preferences involved in lignin degradation remain poorly understood, and low activity toward specific substrates presents a significant challenge to the efficient utilization of lignin. In this study, we investigated the substrate promiscuity of Th Ado, a key enzyme involved in lignin valorization. Pre-reaction state analysis revealed that a hydrogen bond network is critical in determining substrate selectivity. By performing targeted saturation mutagenesis on residues surrounding the substrate tunnels, we identified the Y205W and Y205Q mutants, which demonstrated 0.73-fold and 0.72-fold enhancements in activity, respectively. Structural analysis indicated that the redirection of the original substrate tunnel may be responsible for the improved activity. Our study provides essential insights into the substrate preference mechanisms of lignin degrading enzymes and suggests that this tunnel-redirection strategy can be extended to other promiscuous enzymes.",
"introduction": "Introduction Lignin represents the most substantial reservoir of renewable aromatic compounds on Earth, and its value-added utilization has emerged as a compelling field driven by urgent demands for energy security and environmental sustainability. 1 , 2 , 3 , 4 , 5 Enzymatic catalysis is crucial for the valorization of lignin; however, the naturally low activity of these enzymes often fails to meet the rigorous standards for industrial applications. 6 , 7 , 8 , 9 , 10 Moreover, the tendency of these enzymes to exhibit substrate promiscuity significantly increases the costs of product separation and purification. 11 , 12 , 13 , 14 , 15 For example, Ado, an aromatic dioxygenase, has a broad substrate range that enables the conversion of lignin derivatives into valuable aromatic building blocks. 16 However, the precise mechanism underlying its substrate preference remains elusive, and modifying its structure to enhance its catalytic efficiency presents significant challenges. 17 , 18 , 19 , 20 , 21 Consequently, there is an urgent need for research on lignin-associated enzymes to enhance the value-added utilization of lignin. 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 To reveal the substrate preference mechanisms of these enzymes, the binding state between the enzyme and substrate has been identified as a crucial factor. Pre-reaction state (PRS) analysis is instrumental in uncovering the details of the enzyme-substrate binding state and plays a pivotal role in clarifying the degree of preference for various substrates. 30 , 31 This approach has been extensively applied to elucidate the reaction mechanisms of non-heme dioxygenases and has contributed significantly to the rational design and optimization of aromatic ring-hydroxylating oxygenases. 32 For enzymes characterized by promiscuity, predicting the precise targets that will enhance activity via a fully rational design is inherently challenging. In the engineering process, PRS analysis can serve as an indispensable guide, allowing for the identification and preservation of key sites that are pivotal for substrate pref. 33 , 34 , 35 , 36 , 37 , 38 Additionally, an alternative strategy involving the modification of the amino acids surrounding the substrate tunnels presents a promising avenue. This approach has the potential to enhance catalytic activity by facilitating the transfer of compounds, without requiring alterations to the catalytic site. In a previous study, the Thal-V82I mutation was integrated into a flavin-dependent halogenase by modifying the intermediate transfer tunnel. This strategic alteration significantly bolstered the catalytic efficiency of the enzyme while preserving its inherent regioselectivity. 39 Nevertheless, the scope of research on the aromatic dioxygenase Ado, which can convert the lignin-derived monomer 4-vinyl guaiacol into the high-value compound vanillin, is currently relatively limited. 16 , 21 In this study, we investigated the substrate preference of Th Ado from Thermothielavioides terrestris to shed light on the molecular mechanisms that dictate its substrate specificity. Our findings indicate that Th Ado exhibits a tiered preference for these substrates in the order of resveratrol, 4-vinyl guaiacol, and piceatannol, with the preference decreasing sequentially. Computational analysis revealed that substrates favored by higher preferences correlated with a more reactive PRS conformation and an enhanced hydrogen bond network. Based on the underlying mechanism, we identified and preserved key sites for modulating substrate preference. Furthermore, we targeted six residues surrounding the substrate tunnel for saturation mutagenesis, resulting in the identification of two promising variants, Y205W and Y205Q, which exhibited 0.73-fold and 0.72-fold enhancements in activity, respectively. Computational analysis suggested that the Y205W and Y205Q mutations resulted in the replacement of the original channel with a novel “redirecting” tunnel that facilitated improved substrate throughput, potentially accounting for the observed increase in activity. This tunnel-redirection strategy, which involves the modification of non-traditional sites, could offer new insights into the semi-rational design of other promiscuous enzymes, broadening the scope of enzyme engineering.",
"discussion": "Discussion Enzymatic catalysis for lignin valorization holds immense promise for sustainable biorefinery practices and the development of green chemistry. However, the promiscuity and low activity of the relevant enzymes greatly limit their potential for the development of enzymatic catalysis for the value-added utilization of lignin. In this study, we conducted a substrate preference analysis for Th Ado, a representative enzyme involved in lignin valorization. Steady-state kinetic experiments and PRS analysis revealed the molecular mechanism of its preference, with sites E400, K157, and Y124 playing key roles in substrate recognition. Based on the underlying mechanism, we identified and preserved key sites for modulating substrate preference. Enzymatic reactions often occur within hidden catalytic sites in the core of proteins, which are linked to the solvent by tunnels, thereby facilitating the movement of substrates and products. 48 The characteristics of these tunnels significantly impact their catalytic properties by regulating the substrate and product exchange rates. Consequently, tunnel engineering has been shown to markedly affect the enzyme performance, including enzyme activity and selectivity. 49 Traditional approaches involve reducing residue size or creating new tunnels. 50 , 51 , 52 In our study, we pursued a unique strategy by conducting saturation mutagenesis around the substrate tunnel, revealing the mutants Y205W and Y205Q, which increased activity by 0.73-fold and 0.72-fold, respectively. The observed increase in activity is likely attributable to the redirection to a more efficient tunnel, offering valuable insights for enhancing lignin-utilizing enzymes and highlighting the potential of a semi-rational design for improving enzyme activity. In summary, our research elucidated the substrate-preference mechanism of lignin-utilizing enzymes and enhanced their catalytic activity through a tunnel-redirection strategy. This provides an improved molecular machine for the biological transformation of lignin and offers guidance for the modification of other enzymes. Our research offers a foundation for continued discovery. With a deeper understanding of the enzyme catalytic mechanism, as well as improvements in the accuracy of protein structure prediction, molecular docking, and substrate tunnel prediction tools, we can more accurately simulate this process in the future, thereby achieving a more precise semi-rational design. This process will accelerate the efficiency of lignin valorization and contribute to the future development of a circular, low-carbon, green economy. Limitations of the study There are several limitations to our study. First, Th Ado currently lacks an experimentally validated crystal structure; its structure was instead predicted using AlphaFold2, introducing potential limitations in the accuracy of the initial conformation and molecular docking results. Consequently, the impact of subsequent analyses based on the predicted structure requires further validation and careful interpretation. Second, although we successfully identified mutants exhibiting improved activity through a tunnel-redirection strategy, the improvement in their catalytic efficiency remains suboptimal. Further investigations should explore the potential of more catalytically efficient mutants, including those combining multiple point mutations, to fulfill the requirements of practical industrial applications."
} | 2,227 |
31624325 | PMC6797708 | pmc | 6,675 | {
"abstract": "Neuromorphic networks are formed by random self-assembly of silver nanowires. Silver nanowires are coated with a polymer layer after synthesis in which junctions between two nanowires act as resistive switches, often compared with neurosynapses. We analyze the role of single junction switching in the dynamical properties of the neuromorphic network. Network transitions to a high-conductance state under the application of a voltage bias higher than a threshold value. The stability and permanence of this state is studied by shifting the voltage bias in order to activate or deactivate the network. A model of the electrical network with atomic switches reproduces the relation between individual nanowire junctions switching events with current pathway formation or destruction. This relation is further manifested in changes in 1/f power-law scaling of the spectral distribution of current. The current fluctuations involved in this scaling shift are considered to arise from an essential equilibrium between formation, stochastic-mediated breakdown of individual nanowire-nanowire junctions and the onset of different current pathways that optimize power dissipation. This emergent dynamics shown by polymer-coated Ag nanowire networks places this system in the class of optimal transport networks, from which new fundamental parallels with neural dynamics and natural computing problem-solving can be drawn.",
"conclusion": "Conclusions We have analyzed the emergent dynamical properties of a neuromorphic system formed by polymer coated silver nanowires that self-assemble into a network with resistive switch electrical junctions. Our electrical measurements, performed with a large interprobe distance across the network, reproduced two important current-voltage properties observed in similar neuromorphic systems: critical activation at a threshold voltage; and evolution towards an optimal conductance state under successive cycles. We devised a new measurement scheme that unveiled even richer and more complex network dynamics arising from multi-scale interactions of the switch junctions, including: (i) a collective memory response in the sub-threshold voltage regime; (ii) distinct low and high network conductance states distinguished by different power-law fluctuation scalings; and (iii) reconfiguration dynamics, similar to synaptic plasticity in the brain, enabling resilience and adaptation. In particular, we found that the emergent temporal correlations arising in the active network under changing voltages exhibit a 1/f power-law spectrum, which is a consequence of fundamental changes in the connectivity map of the network and is primarily mediated by stochastic fluctuations at the individual junction scale that lead to hierarchical collective dynamics, from the scale of junction clusters to the whole-of-network scale. We envisage that by accessing the network’s states through its spectral signatures, we may not only gain a better understanding of its near-criticality dynamics, but may also discover new strategies for controlling training and learning for reservoir computing applications.",
"introduction": "Introduction The human brain is a product of evolution, tuned and reshaped by an ever-changing environment. The brain’s neuronal system is able to achieve the ability to recognize, conceptualize and memorize objects in the physical world. Using environmental information we establish logical associations that ultimately allows us not only to survive, but also to solve highly complex problems 1 .However, in an increasingly connected and interactive world, the volume of information to process has exponentially increased, and in order to extract and synthesize meaningful information, computerized approaches, such as machine learning and its various incarnations have gained tremendous popularity 2 . Typically, Artificial Neural Networks (ANNs) attain this goal by a very delicate and case-selective combination of learning strategies 3 . Data containing complex or contextual associations between objects normally requires an heuristic sampling which limits their ability to synthesize information. Conventional CMOS architectures also restrains the amount of data that is efficiently processed with ANNs due to power consumption bottlenecks. Interest in the creation of synthetic neurons that could increase the processing abilities of ANNs has increased considerably with the discovery of nanomaterials with memristive properties 4 . A memristive device is a non-linear two-terminal device in which the resistance shows resilience to change (i.e. memory), manifested in hysteretic behavior when the energy change is reversed or reduced, also termed as resistive switching. The memristor thus has two important neurosynapse-like properties, plasticity and retention. Traditional integrate-and-fire models, that emulate the electrical behavior of neurons using passive circuit elements, can be simulated exclusively with these elements 5 – 7 . Memristive devices have been successfully embedded into various CMOS architectures, enabling the realization of synthetic neural networks(SNN). SNNs imitate the topology of an ANN in a physical layout, typically stacking memristive terminals in cross-bar configurations 8 , 9 . Using voltage pulses to configure the internal state, or weight , of individual memristors; memorization, learning and classification abilities have been achieved 10 – 13 . However promising, this approach remains reliant upon CMOS technology and inherits some of its limitations: large cost-efficiency ratio, high power consumption, and subpar performance with respect to computerized ANNs. Neuromorphic networks offer a different approach to synthetic neural networks; rather than focusing on the controllability of single synthetic neurons to replicate the learning schemes of ANN, they focus on mimicking the complex network topology of neurons in the brain by creating similarly complex networks comprising nanomaterials such as nanowires or nanoparticles. The contact areas between resistive elements in a neuromorphic network show resistive switching properties similar to those of memristors or atomic switches 14 – 17 . Atomic Switch Networks (ASN) made of Ag 2 S junctions present these properties 18 , 19 . ASNs are created through a combination of bottom-up synthesis and top-down lithographic patterning. A grid of copper posts is used as a seed for decomposition of silver form solution, resulting in the growth of dendritic networks of Ag nanowires whose interconnections, following sulfurization, act as atomic switches. This bottom-up fabrication replicates the high-density and intertwined connectivity of real biological neurons. The exponential increase in neurosynapse-like junctions adds a layer of topological complexity to the network, enhancing its plasticity and adaptability. Demonstrations of natural computing paradigms such as reservoir computing have been reported, using the networks to perform Boolean operations or signal reconstructions 20 – 23 . Alternative approaches to constructing neuromorphic networks relies on bottom-up formation to create random self-assembled networks of nanowire or nanoparticles. Brown and coworkers have created nanoparticle networks by sputtering cluster of different metal oxide nanoparticles, like gold 24 or tin 25 , in a controlled atmosphere. The individual nanoparticle junctions show properties of metal oxide resistive switches, with tunneling and filament formation in the switches, conferring neuromorphic properties to the networks 26 . They also found some evidence of recurrent properties such as critical activation, memorization and stochastic-mediated dynamics 24 , 27 , 28 . Many metallic nanowire or nanoparticle compounds can be synthesized in solution, so the formation of a disperse network is achieved with simpler solution-process techniques, such as drop casting or spray coating 29 . Factors such as density and homogeneity can be tuned by changing solution concentration or droplet size. Ag nanowires are amongst the most widely used to build metallic networks due to their low resistance 30 , low cost and elasticity, which have found several applications as flexible transparent electrodes 29 , 31 . Synthesis of silver nanowires follows a particular reaction process called the polyol process, in which a polyol based solution precludes the oxidation of silver nitrates. Adding polymer species to the solution such as polyvinilpirrolydone (PVP), which selectively attaches to particular facets of silver aggregates, promotes the formation of Ag nanoparticles or nanowires with polymer coated surfaces 32 – 35 . PVP coating is insulating, so disposal of this layer is fundamental to form low resistance networks 30 . Surprisingly, however, PVP-Ag nanowire-nanowire or nanoparticle-nanoparticle junctions show resistive switching properties 36 , 37 . This can be attributed to the growth of metal filaments between the nanowires, possibly facilitated by the ionic transport of silver through the PVP layer after the application of a high-electric field across the polymeric junction between two nanowires. Resistive switching behavior originated by metallic filament growth has also been reported for polymer-based electrolytic atomic switches 38 and in composites of Ag nanowire networks embedded in polymer matrices 39 . In a nanowire network fed by an external current or voltage source, resistive switching in individual junctions produce a dynamic tuning of the effective resistance of the whole network. Formation of low resistance pathways between the probes contacting the networks induces a transition from a low-conductance state(LCS) to a high-conductance state(HCS) at a given voltage threshold. Altering network density and controlling probe spacing can affect this threshold(or activation threshold), but it is routinely found at less than 10 V, even for millimetric space between probes and densities down to 0.08 nanowires/μm 2 40 . In the present work, randomly self-assembled PVP-Ag nanowire networks are created in solution and drop-casted onto a SiO 2 substrate. Activation threshold of these networks and the role of resistive switching of single nanowire-nanowire junctions in the electrical properties has been studied previously 30 , 36 , 40 , 41 . However, spatio-temporal correlations are ubiquitous in ASNs 18 , 42 . This correlations are translated to power-laws in the power spectral distribution (PSD) of signals going through the network. Many dynamical processes showing these power-laws are always present in system in the brink of criticality 43 , such as those found in brain waves 44 . We have inspected this correlational dynamics in PVP-Ag networks. Current-time series are acquired on networks connected by two fixed probes controlled by a bias voltage. Current fluctuation and evolution during the time series is compared with an electrical model of the network. In the model, nanowire-nanowire junctions are considered as filament-like atomic switches. Network activation is inspected under a constant bias voltage high enough to guarantee threshold activation in each case. Current increase as a consequence of network transition to HCS is acquired as a time series. Rather than a continuous transition, we are able to distinguish the activation as a series of discrete current jumps. Comparison with the model shows that resistive switching in vital topological areas of the network produces this effect. When the fixed bias voltage is removed, network memorizes the HCS for varying periods of time. The memory state duration is random and varies between activation cycles. Stochastic dissolution of individual nanowire-nanowire junctions and the formation of multiple conductance pathways during the activation is combined with the model to explain this property. Finally, we devise a novel measuring scheme for the I–V activation cycle, which splits every voltage step change, while tracking the evolution of the network from a very low conductance state, towards activation and subsequent adaptation, leading to a final and very stable high conductance state. Analyzing the 1/f power-law spectrum distribution within these series, we disentangle the dynamical events under witch this optimized current transport state is automatically optimized by the network. This optimal state is nevertheless susceptible to random changes in the sub-threshold regime when vital topological sections of the network are compromised, but the network can quickly recover from such instabilities via an “avalanche-like” remapping of the preferred conductance pathways.",
"discussion": "Discussion It has been shown in previous sections that PVP-Ag nanowire networks evolve towards a definitive state of conductance after becoming fully activated, either by means of repetitive I–V cycles or applying super-threshold voltage over longer times. In the activated network, one or many pathways transport electrical currents. The modelling results (Fig. 2a,d,e ) suggest that the pathway that opens first is the shortest-distance topological path between the electrodes. However, the model assumes a homogeneous initial distribution of junction resistance, which may not be the case in the real system, which has a larger interelectrode distance, as well as non-ideal contact geometry between nanowires and between nanowires and electrodes. Additionally, the self-assembled network may exhibit larger homogeneity variations that are not accounted for in the model. This implies that filament formation at the level of individual junctions might not always lead to an efficient activation sequence. For example if one junction in a less optimized pathway change its resistance state first, it may promote the activation of junctions in its immediate vicinity, thus giving rise to a winner-takes-all phenomenon, as recently observed by Manning and colleagues 41 in a smaller PVP-Ag network. In any case, once a pathway is active, the network will keep further opening parallel pathways in order to optimize the conductance, or else, minimize power consumption, in order to comply with the laws of conservation of electrical current in a resistor network Previous studies 36 have shown the stability of active networks to last extremely long times as long as the energy pumped from a voltage or current source is high enough. Thus, once in the ohmic regime, a network can remain in this state unless, by means of a higher voltage or current injection, other physical phenomena such as joule heating or electro-migration breaks the individual junctions, thereby resetting them 36 , 52 . In our study, we have inspected the dynamics of the active network not only near the threshold voltage, but also in the sub-threshold regime. In this regime, the stability of the networks is still very high, but as the current through individual junctions decreases, the balance between junction formation by means of current injection and junction dissolution triggered by stochastic fluctuations is reduced. Decreasing the voltage in a linear sweep while acquiring time series facilitates the inspection of the dynamical events, signaling network instability by single junction breakdowns. This is assessed by analysis of the PSD power-law exponent (β) distributions in Figs. 5d,e . The β distribution in Fig. 5e shows that most of the magnitudes are centered around 1, with a small tail of values rounding up to a magnitude of 2. Typically, a 1/f power-law spectrum is indicative of a system in which scale-free dynamics is at play. To better understand how the network changes its dynamical behavior, we dissected the downward voltage ramp of the I–V cycle of Fig. 5c and examined the conductance time series at a voltage in which this dynamical balance was evident. Figure 6a shows that the network maintains a very stable (small fluctuations) conductance near 2.6 × 10 −5 S up to approximately 15 s, after which it suddenly becomes unstable, exhibiting sharp and irregular conductance drops interspersed with short plateaus of unequal duration and magnitude, as well as large spikes. This unstable regime last for 3 s, after which the network automatically recovers the previous stable state, only this time with a slightly higher conductance. The level of fluctuations in this new stable regime appears to be slightly lower. Figure 6a also shows β values calculated at every one second interval in the conductance time series. This analysis reveals that when the network is in a dynamical regime that is stable against fluctuations, β values are closer to 1, whereas they approach 2 when the network succumbs to instability. Figure 6b shows PSDs calculated for a stable and unstable region in the conductance time series in Fig. 6a , indicated by the black triangle and pink diamond, respectively. The PSDs clearly distinguish the different dynamical regimes: the PSD is steeper in the unstable regime due to the stronger low-frequency fluctuations. Upon further inspection of Fig. 6a , with reference to the full distribution of sliced time series in Fig. 5c , it is evident that the onset of the unstable regime is not triggered by the negative voltage sweep, nor it is related to changes in the network appearing immediately after one voltage step is performed in the downward ramp, but instead appears randomly and unpredictably, and with an irregular duration. The unstable regime ends when the network recovers a stable conductance state, as signaled by reduced noise fluctuations. Therefore, the network not only adapt its conductive pathways to the nanowire junction topology whenever energy is supplied either from current or voltage sources, but can also adapt dynamically to random changes in the network, reconfiguring the underlying connectivity to find a new optimal pathway. Figure 6 Reconfiguration dynamics in PVP-Ag nanowire networks. ( a ) Conductance time series selected at the 0.31 V step during the downward ramp of the IV cycle, with an overplot of the slope (β) of the power-law fit to the PSD computed for 1 s intervals (blue diamonds). The different spectral distributions of power in the self-organized dynamical regime (indicated by a black triangle) with the unstable regime (indicated by a pink diamond) are compared in ( b ). In each case, a linear fit is overplotted on the PSD. Few nanowire network models have addressed stochasticity in the sub-threshold regime 21 . Our modelling of the activation and deactivation cycles (cf. Figs 2 and 3 ) provides new insights into the process leading to these changes in network. When the applied voltage is much lower than the threshold voltage, the transport hierarchy is revealed through the different irregular decay curves (Fig. 3b ), attributed to stochastic junction breakdown. In reducing the voltage from threshold to sub-threshold level in small steps and long waiting times, we were able to track the transition from the stable state down to the regime in which random fluctuations have a larger influence on the dynamics. Whenever β is close to 1, individual junctions within clusters of high network connectivity are continuously switching off and on, with three different dynamical process (potentiation, inhibition and random breakdown) interacting and evolving in a self-organized way such that the connectivity backbone of the network is not compromised. Therefore, a junction that breaks in a cluster of high connectivity is propagated as a small change in conductance, and, depending on the local topology of these clusters, induces the breakdown of neighboring junctions, as the current in them is instantaneously reduced. But at the same time, when these secondary junctions are broken, the backbone of the network needs to carry more current to maintain conductance, so if a region is locally connectivity-depleted, another region will have to sustain a larger current, and thus, will potentiate the switching-on of junctions over that area. However, the more junctions are switched on, the higher the probability of breaking junctions in these newly connected areas. In this way, self-organized feedback produces the scale-free power-law distribution, as fast individual junction switching leads to changes in conductance for clusters of junctions over a slower time scale, and changes in cluster conductance produce changes in network pathway connectivity on an even slower time scale. This hierarchy is responsible for the characteristic 1/f spectrum in the PSD. From this interpretation, we can infer that the steepening of the power-law spectrum associated with abrupt changes in conductance (cf. Fig. 6a ) occurs when a critical junction (one bridging areas of larger connectivity) breaks down, and splits a network pathway, reducing the total network conductance (by as much as half in the ideal case of two equivalent parallel pathways). Then, self-organized switching is disrupted by larger junction connectivity-depletion, and the connectivity of the network is spontaneously remapped until the broken pathway, or another parallel pathway, is switched back on. This remapping (or reconfiguring) process produces more low-frequency power in the PSD, as clusters of junctions or secondary pathways collectively redistribute connections, which occurs on longer time scales (lower frequencies) than the higher frequency switching fluctuations of individual junctions. When the network transitions back on to a highly conductive state, the conductance is slightly different, implying this complex dynamical process produces long-lasting changes in the backbone connectivity of the network. We can draw a parallel with long-term retention memory in the brain, which requires not only synaptic potentiation in neural connectivity but also persistent structural reconfigurations in connectivity, referred to as plasticity 53 . Further insight into the relation between dynamics and connectivity can be gleaned by encompassing the neuromorphic nanowire network within a broader class of systems, optimal transport networks. In general, these are networks that can be represented by a weighted graph (directed or undirected), with edges representing the conductance (or resistance) between the different parts of the network, and whose solution can be obtained by solving a generalized version of Kirchhoff’s equations, that is, flow and mass conservation. Examples of such systems vary from artificial systems, such as power or water supply networks, to natural systems, e.g. vascular networks in plants or animals 54 . The optimality condition, though not always solvable, is computed by considering that transport is optimized whenever the connectivity map (weight between edges) minimizes power consumption. For example, for a fixed resistor network, current is hierarchically and homogeneously distributed in proportion to the equivalent resistance of the different parallel plus series pathways. In contrast, in vascular systems, which adapt flow to pressure differences 54 , dissipation is minimized by concentrating flow on the edges with larger conductance, thus transport is regulated by the formation of tree-like structures 55 , 56 . Neuromorphic networks clearly show this adaptive behavior, with the system evolving to create few, large connectivity pathways rather than many different pathways, as our activation curve and other recent research shows 41 . However, once the network is connected, parallel pathways, most likely in the form of closed loops or circuits that assist or reinforce the main pathway also appear. This further reduces global power dissipation. Interestingly, research on optimal transport structures suggests that the combination of a fixed unique backbone for transport with different recursively nested loops or cycles is the preferred connectivity map for adaptive networks, and appears once variations in the transport dynamics are introduced in the form of defects or fluctuating currents in the junctions, sources or sinks 55 – 58 . Finally, it is worth considering whether the network dynamics observed in our neuromorphic nanowire system are characteristic of biological neural systems. In particular, we always observe a continuously fluctuating state, as if the system needs to be constantly oscillating, searching the phase space for a solution that guarantees long-term stability. It has been suggested that this edge-of-chaos state could be not only an optimal state of the brain, but a necessary condition for consciousness to exist 43 , 59 . However, although neural dynamics research has tended to focus on wave-like collective oscillations (e.g. in EEG signal acquisitions), other time series analyses continue to be developed 50 , 60 , 61 . Power-law PSD spectra, such as that observed in our nanowire networks, are indeed also observed in neural dynamics (e.g. neuronal avalanche size distribution), although whether these spectra can be interpreted as evidence for the brain operating at or near criticality remains a contentious issue 62 . Changes in power-law slopes, as observed in our nanowire network system, have also been observed in brain measurement data, where a subject performed simple tasks 60 . In our neuromorphic nanowire network, large changes in the power-law dynamics arise as random fluctuations break critical junctions. Introducing a control mechanism to disrupt selected regions of the network could force this remapping mechanism, that ultimately will allow us to harness the natural nonlinear feedback dynamics, thus navigating the large solution space of the network to solving different optimization or recognition tasks."
} | 6,413 |
35755368 | PMC9218975 | pmc | 6,676 | {
"abstract": "Icing and freezing\nphenomena in cold weather cause serious damage\nand economic losses. Thus, the development of a new effective icephobic\nsurface with low ice adhesion strength (τ ice ) that\ncan easily remove ice by wind or gravity force is essentially required.\nIn this study, we propose a silicone oil-infused oleamide–polydimethylsiloxane\n(SiOP) by a facile fabrication method to achieve the effective icephobic\nperformance with enhanced lubrication lifetime. The proposed SiOP\nis composed of a composite containing oleamide and polydimethylsiloxane\n(PDMS) and silicone oil impregnated into the polymeric networks of\nthe composite. Oleamide has been used as a slip agent in industries\nto reduce the skin friction of polymer films. The weight of the oil\nimpregnated in SiOP is approximately three times higher than that\nof silicone oil-infused PDMS (SiPDMS). Different from the SiPDMS surface\non which oil dries easily, a slippery oil layer is stably formed on\nthe SiOP surface. The fabricated SiOP surfaces have very low τ ice values of approximately 1 kPa, which is much smaller than\nthat of the SiPDMS surface. The SiOP with an oleamide content of 5\nwt % exhibits the smallest τ ice value of 0.88 kPa.\nThe fabricated SiOP surfaces maintain their superior icephobicity\nfor more than 30 icing/deicing cycles, demonstrating their enhanced\nlubrication lifetime. In addition, the ice freezing time of a water\ndroplet of 7 μL in volume is significantly delayed on the SiOP\nsurface compared with that on the SiPDMS surface. The present results\ndemonstrate that the proposed SiOP surface can help provide superior\nicephobic performance with the aid of the incorporation of oleamide\ninto the conventional SiPDMS. The developed icephobic SiOP can be\nutilized to satisfactorily resolve the lubricant drought problem of\nconventional icephobic surfaces by empolying oleamide as a complementary\nslip agent.",
"conclusion": "3 Conclusions In this study, a new icephobic SiOP surface with enhanced lubrication\nlifetime was proposed and fabricated by impregnating silicone oil\nas a liquid lubricant into the polymeric networks of OP, and its superior\nicephobic performance was experimentally evaluated. As a result, the\nmaximum oil content in the fabricated SiOPs is approximately three\ntimes higher than that of SiPDMS. The proposed SiOP surfaces form\na stable oil layer unlike SiPDMS. The τ ice values\nof these surfaces are ∼1 kPa, which is approximately eight\ntimes smaller than that of SiPDMS. The SiOP with an oleamide content\nof 5 wt % has the smallest τ ice of 0.88 kPa. This\nexcellent icephobic performance was sustained for more than 30 icing/deicing\ncycles. Several reasons for the superior ice adhesion property of\nSiOP are as follows: first, the oil layer formed on the SiOP surface\nlargely reduces τ ice on its surface. However, after\nnumerous repeated clearing processes, the oil layer on the SiOP surface\neventually dries out. The incorporation of oleamide leads to the increased\nelasticity of the polymer and the slip effect at the interface between\nice and surface, which decreases τ ice on the SiOP\nsurface without the oil layer. In addition, oleamide also delays the\nfreezing of water on the SiOP surface by the decreased thermal conductivity\nof the embedded polymer. The proposed SiOP surface would be effectively\nutilized in various engineering applications, which require superior\nanti-icing and de-icing functions.",
"introduction": "1 Introduction Icing\nand freezing of machines, such as airplanes, ships, turbines,\npower lines, or home appliances, caused by cold weather lead to their\nfailures, inducing serious human casualties and economic losses. 1 − 3 Accordingly, various methods, including mechanical, chemical, and\nthermal treatments, have been used to remove the ice accumulated on\nthe solid surfaces. 4 − 6 However, these methods require a large amount of\ninput energy, and most chemical treatments are not environmentally\nfriendly. 7 Therefore, great efforts have\nbeen made to develop effective icephobic surfaces to passively prevent\nthe formation of ice by using natural wind or gravity force without\nexternal energy consumption. To accomplish the passive removal of\nice, the effective icephobic surfaces should have an extremely low\nice adhesion strength (τ ice ) less than ∼20\nkPa, which is the force capable of removing ice by a strong breeze. 8 , 9 Furthermore, the formation of ice can be inhibited by falling off\nthe water on the surface before it freezes. The superhydrophobic (SHPo)\nsurface, which is one of the typical icephobic surfaces, could easily\nremove the water with the aid of strong water repellency of the surface. 1 , 10 − 12 Given that the SHPo surface with micro/nano structures\nhas a low contact area and low sliding angle for water, the icing\ntime of water on the SHPo surface is delayed, and the water on its\nsurface easily falls off before the freezing. However, these conventional\nicephobic surfaces have a challenging problem in their practical utilization\nat high humidity and pressure conditions under which water or ice\ncan be adhered to their micro/nano structures, thereby eventually\nworsening their icephobic performance compared with a smooth surface. 13 , 14 Recently, a slippery liquid-infused porous surface (SLIPS)\nhas\nbeen receiving great attention as a promising icephobic surface. 15 − 18 The SLIPS inspired by the morphological feature of pitcher plant\nwas fabricated by injecting an immiscible lubricant into micro/nano\nporous structures. 15 , 19 Given that a smooth lubricating\nlayer is formed on the SLIPS, the surface exhibits high water repellency\neven at high humidity conditions. When water is frozen on SLIPS, an\nice–lubricant interface is formed, which can theoretically\nreduce the τ ice to zero. 7 However, the micro/nano structure fabrication process of SLIPS is\nexpensive and complicated, and the injected oil is easily depleted\nby external physical stimuli (e.g., mobile liquid or ice on the surface). 20 , 21 To overcome this shortcomings of SLIPS, a liquid-infused polymer\n(LIP) was developed by integrating silicone oil into the polymeric\nnetwork as a liquid lubricant. 7 , 9 , 22 − 24 Different from SLIPS, in which lubricant is injected\ninto a void space, the polymeric network of LIP holds lubricant oil\ninside itself. LIP can be an economical choice from a practical point\nof view, thanks to its facile fabrication process and scalability.\nHowever, it is difficult for conventional LIP to efficiently utilize\nthe oil stored in its polymeric network, thereby the oil on the surface\ndries up within a short period of time due to migration or evaporation. 7 This implies that the replenishment of oil from\nthe internal polymeric network to the LIP surface is essential to\nextend the lubrication lifetime. 25 , 26 To resolve\nthis limit of LIP, we newly add oleamide to PDMS as\nan additional lubricant. Oleamide, a natural material extracted from\nplants or animals, has been known to weaken the adhesion of biofoulers\nand improve the scratch resistance. 27 − 30 This material has been used as\na slip agent in industries to reduce the skin friction of polymers\nor plastic polyethylene films. Furthermore, oleamide is an economical\nand ecofriendly material. In this study, we propose a silicone\noil-infused oleamide–polydimethylsiloxane\n(SiOP) coating as an effective icephobic surface with enhanced lubrication\nlifetime. SiOP contains more oil than silicone oil-infused polydimethylsiloxane\n(SiPDMS), and the absorbed oil is sustainedly replenished on the surface\nto form a thin lubricating layer. This indicates the effective oil\nstorage and oil management ability of SiOP. Even after the SiOP surface\neventually dries out, it maintains lower τ ice than\nSiPDMS, thanks to its lower elastic modulus and the slip effect of\noleamide. In addition, oleamide slows down the time elapsed for freezing\nwater droplets on the SiOP at low surface temperatures by decreasing\nthe thermal conductivity of the polymer, supporting the potential\nfor water to slide off before freezing.",
"discussion": "2 Results\nand Discussion 2.1 Surface Characteristics The fabrication\nprocess of SiOP is schematically illustrated in Figure 1 . At first, oleamide, the PDMS precursor,\nand the cross-linking agent are well mixed, and this mixture is coated\non a substrate. The mixture coated on the substrate is placed in an\noven to fabricate oleamide–PDMS (OP). The fabricated OP is\nthen immersed in an oil bath. The polymer network is impregnated with\nsilicone oil to fabricate SiOP. The following four test surfaces were\nprepared to investigate the surface characteristics and icephobic\nperformance of SiOP: PDMS, OP, SiPDMS, and SiOP. Water contact angles\n(WCAs) of PDMS and OPs mixed at four different oleamide contents were\ncompared by placing a water droplet of 5 μL on each surface\n( Figure 2 a). The surface\nof pristine PDMS has the highest WCA of 103° among the samples.\nThis notion indicates that pristine PDMS is a hydrophobic surface.\nIn comparison with pristine PDMS, the WCAs of OPs have slightly lower\nvalues due to the presence of the incorporated oleamide. However,\nall OP surfaces are still hydrophobic with WCAs of over 90°. Figure 1 Schematic\nillustration of the fabrication process of SiOP. Figure 2 (a) WCAs\nof PDMS and OPs surfaces before oil impregnation. (b)\nWCAs of SiPDMS and SiOP surfaces after oil impregnation. N = 16. After impregnating silicone oil,\nall SiOP surfaces became hydrophilic\nwith WCAs of less than 90° ( Figure 2 b). Moreover, they have the same WCAs of\n87°, while OPs have different WCAs depending on the oleamide\ncontent. These same WCAs are attributed to the presence of the oil\nlayer on the SiOP surface. A previous study reported that the contact\nangle of a water droplet of 5 μL on the surface of 100 cSt silicone\noil layer is approximately 86.4°, which matched that of SiOP\nimpregnated with 100 cSt silicone oil. 16 Meanwhile, the WCAs of PDMS and SiPDMS are 103°. Specifically,\nthe WCA does not change even after the impregnation of oil into PDMS.\nThis result implies that the SiPDMS surface does not have an oil layer\non its surface, unlike SiOPs. The presence of an oil layer on SiPDMS\nand SiOP was clearly confirmed by placing a blotting paper on the\nsurface ( Figure S1 ). To form an oil\nlayer on a polymer surface, such as like SiOPs,\nthe polymer needs to contain a sufficient amount of oil. 7 , 24 , 26 If the polymer contains more\nthan the critical amount of oil, then the oil molecules infused in\nthe polymer networks are diffused out on the surface to form an oil\nlayer. This notion indicates that the SiOP contains a sufficiently\nlarge amount of silicone oil; thus, the oil layer is sustainably formed\non the surface. In contrast, SiPDMS does not diffuse oil molecules\nin the polymer toward the surface because the oil content is below\nthe critical value. To verify this aspect, we measured the oil\ncontents of SiOP and\nSiPDMS by immersing PDMS and OP in an oil bath ( Figure 3 a). For oil content measurements, PDMS and\nOP were used after stripping from the substrate to accurately characterize\nthe material properties. The peeled PDMS and OP are not bound to the\nsubstrate and thus undergo 3D swelling as the oil is absorbed. Here,\nthe oil content (Φ) is defined as follows 1 where m oil is\nthe weight of the oil infused in the polymer, and m 0 is the initial weight of the polymer without oil impregnation.\nSpecifically, Φ indicates the ratio of the infused oil weight\nto the total weight of the polymer. Figure 3 (a) Impregnation of silicone oil into\nOP to fabricate SiOP. (b)\nTemporal variations in the amount of impregnated silicone oil (0.65\ncSt) in the fabricated PDMS and OPs. (c) Comparison of the maximum\nsilicone oil (100 cSt) contents in PDMS and OPs. Figure 3 b shows\nthe temporal variations in the amount of impregnated silicone oil\n(0.65 cSt) of PDMS and OPs mixed at four different ratios. The incorporation\nof oleamide into PDMS largely increases the absorption of silicone\noil. The Φ value of PDMS reaches the equilibrium state at ∼40\nmin, while those of OPs reach the equilibrium within ∼25 min.\nIn addition, the maximum oil content (Φ max ) of the\nfour OPs with different mixing ratios is ∼0.82, while that\nof PDMS is ∼0.59. In comparison with the amounts of oil absorbed\nper unit initial mass ( m oil / m 0 ), OPs contain approximately 3.3 times more silicone\noil (0.65 cSt) than PDMS. Figure 3 c compares the Φ max values of 100\ncSt silicone oil used in the icephobic performance tests of PDMS and\nOPs. The Φ max values of PDMS and OP are approximately\n0.18 and 0.32, respectively. The maximum content of 100 cSt oil per\nunit initial mass ( m oil / m 0 ) of OP is approximately 2.3 times higher than that of\nPDMS. This result is closely associated with the elastic modulus\nof the\npolymer. The shear modulus ( G ) of a polymer can be\nexpressed as follows 31 , 32 2 where ρ\nis the mass density of the polymer, R is the ideal\ngas constant, T is the absolute\ntemperature, and M C is the average molecular\nweight of the polymer chains between cross-links. According to eq 2 , the chain length between\ncross-links is increased with the decrease in the G of the polymer. This notion implies that more oil is impregnated\nwith the expansion of the polymer network. 32 − 34 In OPs, the\nincorporation of oleamide in PDMS decreases the elastic modulus of\nthe polymer; accordingly, the network expands and contains more silicone\noil. 28 , 29 , 34 The presence\nof the oil layer on SiOPs can be confirmed by checking the increase\nin Φ max value due to low elastic modulus of OP. When\nthe Φ max value exceeds the critical oil content,\nan oil layer is formed on the SiOP surface, unlike SiPDMS. 2.2 Ice Adhesion Strength and Sustainability At a surface\ntemperature of −10 °C, the τ ice values\nof SiPDMS and SiOPs at four different mixing ratios\nwere measured ( Figure 4 a). The τ ice value of SiPDMS is approximately 8\nkPa. Meanwhile, all SiOPs have an τ ice value of approximately\n1 kPa, regardless of the oleamide content. To evaluate the sustainability\nof the icephobic performance, an icing/deicing cycle test was conducted\nto repeatedly measure the τ ice values of SiPDMS and\nSiOP. As shown in Figure 4 b, the τ ice values of SiPDMS do not significantly\nchange. However, the τ ice value of SiOP rapidly increases\nup to approximately 12 cycles and thereafter converges to a value\nof 6.5 kPa. The τ ice values of SiOP are kept lower\nthan those of SiPDMS up to 30 repeated experiments. Figure 4 (a) Comparison of ice\nadhesion strength on SiPDMS and SiOP with\ndifferent oleamide contents. N = 7. (b) Variations\nof ice adhesion strength on SiPDMS and SiOP surfaces according to\nthe number of icing/deicing cycles. N = 7. (c) Variation\nof WCAs on SiPDMS and SiOPs according to oil infusion and icing/deicing\ncycle tests. Figure 4 c compares\nthe WCAs of SiPDMS and SiOP measured at three stages (before and after\nthe oil impregnation and after the icing/deicing cycle test). The\nWCA values of SiOPs (2.5 and 5 wt %) after the icing/deicing cycle\ntest are the same as those before the oil impregnation. This result\nindicates that the oil layer on the SiOP surface disappeared after\nthe icing/deicing cycle test. After the oil impregnation (i.e., before\nthe icing/deicing cycle test), the WCA of both SiOPs is approximately\n87°. This result supports the presence of the oil layer on the\nsurface, as mentioned in Section 2.1 . The oil on the surface gradually disappeared\nwith the repetition\nof the ice removal process because the fabricated SiOP surfaces have\nan oil layer at the beginning of the cycle test. Accordingly, the\nτ ice value of the SiOP surface is rapidly increased.\nWhen the oil layer disappeared from the surface, the τ ice values converged, and the ice column was in full contact with the\nelastomer surface. Several factors may influence the lower τ ice of SiOP than SiPDMS even after the oil disappeared from\nthe surface. One of them is the elastic modulus of the coating material,\nwhich is strongly related to τ ice . 35 − 37 The equation\nfor τ ice of a soft material without oil layer on\nthe surface can be described as follows 38 3 where W a is the\nwork of adhesion between the ice and the surface; and G and t are the shear modulus and thickness of the\ncoating, respectively. According to eq 3 , τ ice on the coating surface decreases\nas G of the coating material decreases. The reasons\nfor the smaller G values of SiOP may be as follows:\n(1) the effect of oleamide incorporation and (2) the effect of oil\ninfusion. In the former case, the incorporation of oleamide into PDMS\ngives rise to a smaller elastic modulus. 29 In addition, the oil impregnation softens the polymer and decreases\nthe elastic modulus. 7 , 34 If the Φ values of SiOPs\nare higher than those of SiPDMS after the oil dried on the surfaces,\nthis would contribute to the low τ ice of SiOPs. Furthermore, fatty acid amides have been known to have a slippery\nfeature that can reduce frictional resistance exerting on solid surfaces. 27 − 29 The incorporation of a fatty acid amide into a polymer increases\nthe yielding contact strain; accordingly, the friction coefficient\nis reduced. Thus, the pressure drop measured in a flow channel coated\nwith OP is smaller than that in a channel coated with pristine PDMS. 29 This slippery property of oleamide may contribute\nto the lower τ ice value of the SiOP surface compared\nwith the SiPDMS surface even after the oil on the surface dries. 2.3 Icing Delay Time The freezing times\nof a water droplet of 7 μL on SiOP and SiPDMS at a surface temperature\nof −10 °C were measured to evaluate the ability to delay\nicing time ( Figure 5 ). The freezing time was determined by monitoring the transparency\nof water droplets. The icing delay time (IDT) of SiOP is approximately\n405 s. The delay is 37 times longer than that of a pure glass and\n1.6 times longer than that of SiPDMS. Figure 5 (a) Photograph of a water droplet on glass,\nSiPDMS, and SiOP before\nand after its freezing. (b) Comparison of IDT on glass, SiPDMS, and\nSiOP. N = 12. This result can be explained by using the following expression\nof IDT Δ t 39 4 where ρ w is the density of\nwater, C p is the specific\nheat capacity, T 0 is the initial temperature\nof the droplet, T 1 is the surface temperature\nof the test sample, and Δ Q is the net heat\nloss per unit time. The experimental conditions of ρ w , C p , and T 0 are the same for all test samples. The surface temperature\nwas measured by installing four thermocouples on the surface of each\nsample during the cooling stage. The temporal variations in the surface\ntemperature of aluminum, SiPDMS, and SiOP (10 wt %) are nearly similar\nwithout significant difference ( Figure S2 ). Therefore, the different IDT values of the test samples are attributed\nto the heat loss (Δ Q ) of the cold solid surface.\nThis notion supports that the incorporation of oleamide might decrease\nthe thermal conductivity. Accordingly, the heat transfer from the\nwater droplets to the SiOP is largely reduced, and the freezing time\nof water droplets is eventually delayed. Therefore, water droplets\ncan be easily removed from the surface by inhibiting the freezing\nof water with prolonged IDT."
} | 4,818 |
25484636 | null | s2 | 6,677 | {
"abstract": "Metagenomic methods provide a powerful means to investigate complex ecological phenomena. Developed originally for study of Bacteria and Archaea, the application of these methods to eukaryotic microorganisms is yet to be fully realized. Most prior environmental molecular studies of eukaryotes have relied heavily on PCR amplification with eukaryote-specific primers. Here we apply high throughput short-read sequencing of poly-A selected RNA to capture the metatranscriptome of an estuarine dinoflagellate bloom. To validate the metatranscriptome assembly process we simulated metatranscriptomic datasets using short-read sequencing data from clonal cultures of four algae of varying phylogenetic distance. We find that the proportion of chimeric transcripts reconstructed from community transcriptome sequencing is low, suggesting that metatranscriptomic sequencing can be used to accurately reconstruct the transcripts expressed by bloom-forming communities of eukaryotes. To further validate the bloom metatransciptome assembly we compared it to a transcriptomic assembly from a cultured, clonal isolate of the dominant bloom-causing alga and found that the two assemblies are highly similar. Eukaryote-wide phylogenetic analyses reveal the taxonomic composition of the bloom community, which is comprised of several dinoflagellates, ciliates, animals, and fungi. The assembled metatranscriptome reveals the functional genomic composition of a metabolically active community. Highlighting the potential power of these methods, we found that relative transcript abundance patterns suggest that the dominant dinoflagellate might be expressing toxin biosynthesis related genes at a higher level in the presence of competitors, predators and prey compared to it growing in monoculture."
} | 446 |
21192828 | PMC3022713 | pmc | 6,679 | {
"abstract": "Background Mixed culture enrichments have been used frequently for biohydrogen production from different feedstock. In spite of the several advantages offered by those cultures, they suffer poor H 2 yield. Constructing defined co-cultures of known H 2 producers may offer a better performance than mixed-population enrichments, while overcoming some of the limitations of pure cultures based on synergies among the microorganisms involved. Results The extreme thermophiles Caldicellulosiruptor saccharolyticus DSM 8903 and C. kristjanssonii DSM 12137 were combined in a co-culture for H 2 production from glucose and xylose in a continuous-flow stirred tank reactor. The co-culture exhibited a remarkable stability over a period of 70 days under carbon-sufficient conditions, with both strains coexisting in the system at steady states of different dilution rates, as revealed by species-specific quantitative PCR assays. The two strains retained their ability to stably coexist in the reactor even when glucose was used as the sole growth-limiting substrate. Furthermore, H 2 yields on glucose exceeded those of either organism alone under the same conditions, alluding to a synergistic effect of the two strains on H 2 production. A maximum H 2 yield of 3.7 mol (mol glucose) -1 was obtained by the co-culture at a dilution rate of 0.06 h -1 ; a higher yield than that reported for any mixed culture to date. A reproducible pattern of population dynamics was observed in the co-culture under both carbon and non-carbon limited conditions, with C. kristjanssonii outgrowing C. saccharolyticus during the batch start-up phase and prevailing at higher dilution rates. A basic continuous culture model assuming the ability of C. saccharolyticus to enhance the growth of C. kristjanssonii could mimic the pattern of population dynamics observed experimentally and provide clues to the nature of interaction between the two strains. As a proof, the cell-free growth supernatant of C. saccharolyticus was found able to enhance the growth of C. kristjanssonii in batch culture through shortening its lag phase and increasing its maximum biomass concentration by ca. 18%. Conclusions This study provides experimental evidence on the stable coexistence of two closely related organisms isolated from geographically-distant habitats under continuous operation conditions, with the production of H 2 at high yields. An interspecies interaction is proposed as the reason behind the remarkable ability of the two Caldicellulosiruptor strains to coexist in the system rather than only competing for the growth-limiting substrate.",
"conclusion": "Conclusions The present study provides essential evidence on the possibility of stable co-existence of two closely related bacteria isolated from distant habitats in a continuous-flow system under steady-state conditions. This augments the suggestion of de novo constructed or 'designer' co-cultures as potential alternatives for several biotechnological applications that are, otherwise, carried out using mixed culture enrichments. Although the increase in H 2 yield by the co-culture constructed in this study was not dramatic, as compared with that of the individual strains, it is still higher than the H 2 yield reported for any mixed culture to date. Generally, benefits of the use of the co-culture other than improving product yield may include enhanced resistance to invasion by other species and increased chance of biofilm formation [ 55 ]; the latter being a desirable feature in several industrial fermentation systems. Extending the range of substrate utilization is another advantage that can be gained by combining C. saccharolyticus and C. kristjanssonii in a co-culture. For example, C. saccharolyticus ferments L-arabinose and L-rhamnose, whereas C. kristjanssonii does not grow on these sugars [ 33 ] and probably the latter would be able to utilize some substrates not readily consumed by the former, which merits further investigation.",
"discussion": "Discussion Hydrogen-producing co-cultures constructed de novo may offer a better performance than mixed-population enrichments, while overcoming some of the limitations of pure cultures based on synergies among the microorganisms involved. In several previous studies on defined co-cultures, it was a common strategy to proceed by isolating the dominant members of a mixed enrichment culture and then recombining the isolates in order to reproduce the stability and function of the original microflora [ 17 , 21 , 29 , 30 ]. Here, we combined two closely-related strains from geographically distant, albeit similar, habitats, i.e., C. saccharolyticus DSM 8903 and C. kristjanssonii DSM 12137. The former bacterium was isolated from a thermal pool in New Zealand [ 31 , 32 ], whereas the latter was isolated from a biomat sample of an Icelandic hot spring [ 33 ]. Both organisms are strictly anaerobic, extreme thermophilic heterotrophs with the ability to degrade complex polysaccharides and ferment both hexose and pentose sugars [ 28 , 31 , 33 , 34 ]. A CSTR seeded with C. saccharolyticus and C. kristjanssonii could be successfully operated over a period of 70 days at different dilution rates with both species coexisting in the system, when glucose and xylose (10 g L -1 ) were used as the main carbon and energy sources. According to steady-state residual sugar analysis, the culture was carbon-sufficient at all dilution rates, indicating that another nutrient must have been limiting the growth. Based on the standard biomass formula, i.e., CH 1.8 O 0.5 N 0.2 [ 35 ], and the maximum biomass concentration obtained by either organism in batch fermentations (ca. 1 gCDW L -1 ), the amount of inorganic nitrogen in the feed, present as NH 4 Cl, is considered to be in excess. A component in yeast extract (YE), e.g., a growth factor, is most likely to be responsible for growth limitation and incomplete sugar utilization by the co-culture, since the YE-to-sugar ratio in the feed was only 1/10. This kind of limitation has been previously suggested for C. saccharolyticus [ 36 ] and for Thermoanaerobacter ethanolicus [ 37 ] during continuous fermentation of glucose and xylose, respectively. In our study, this was verified by increasing the YE-to-sugar ratio in the feed to 1/4, where the co-culture could be carbon limited when grown on a mixture of glucose and xylose (Table 3 ) or glucose only (Table 4 ). In general, the H 2 yields obtained in C. saccharolyticus - C. kristjanssonii co-cultures in this study under both carbon and non-carbon limited conditions are significantly higher than the yields previously reported for defined co-cultures [ 29 , 38 - 40 ] or mixed-culture enrichments [ 3 , 23 , 41 ], regardless of the type of reactor employed. The decrease in H 2 yield with the dilution rate observed in the co-culture fermentations as well as in the pure cultures of C. saccharolyticus and C. kristjanssonii was, in part, a result of increased lactate formation (see Additional file 2 ), which drains some of the electrons required for H 2 production. The highest H 2 yield of the co-culture was 3.7 mol per mol of hexose sugar (i.e., 92.5% of the maximum theoretical H 2 yield that can be achieved via dark fermentation). This yield could only be achieved by limiting the co-culture on glucose at low D (i.e., 0.06 h -1 ) and was higher than that obtained by either organism in pure culture under the same experimental conditions (Table 4 ), alluding to a possible synergistic effect of the two strains on H 2 production. This also indicates that carbon limitation can be a successful strategy for improving the sugar-conversion efficiency and increasing H 2 yield of the co-culture. Although it remains unclear why limiting the cells for glucose leads to what appears to be more efficient substrate utilization and increased H 2 production, Bisaillon et al [ 42 ] suggested the possibility of carbon flow to secondary metabolic pathways, for example, glycogen synthesis, being restricted at low glucose concentrations thereby shunting most of the carbon to the catabolic, H 2 -generating, pathways. In contrast to H 2 yield, the volumetric H 2 production rate of the co-culture constructed in this study increased by increasing the dilution rate, which agrees with data from previous reports on fermentative H 2 production in chemostat cultures [ 36 , 43 ]. The maximum H 2 production rate achieved by the co-culture at the highest D tested in this study (Table 2 ) is equivalent to 0.28 L H2 L culture -1 h -1 , which lies within the upper range of previously reported productivities of mixed culture-fermentations in CSTRs [ 41 , 44 - 46 ]. The optimum balance between yield and productivity was observed under glucose limitation at steady state of the higher D (Table 4 ), implying that both carbon limitation and the dilution rate are critical factors for optimizing H 2 -production efficiency by the co-culture. Under those conditions, the volumetric H 2 production rate of the co-culture was equivalent to that of C. kristjanssonii , which indeed was the predominant organism in the co-culture. H 2 yield, however, was significantly higher than that of C. kristjanssonii , pointing again at a possible synergistic effect of the two strains on H 2 production. An interesting outcome of the present study is the ability of the two closely related Caldicellulosiruptor species to stably coexist over the whole range of conditions tested. Since both species occupy the same trophic level [ 31 , 33 ], they are expected to compete for the same growth-limiting substrate in a chemostat culture. Based on the competitive exclusion principle [ 47 ], this competition should result in one strain in the co-culture completely displacing the other in the development towards a steady state under a given condition. Since YE, which is a complex nutrient, was suspected for growth limitation in the co-culture under carbon-sufficient conditions, the coexistence could be explained in that each species was limited on a different component in YE. However, the stable coexistence of the two strains observed at steady-state conditions with glucose as the sole growth-limiting substrate cannot be explained on that basis. As discussed below, the reproducible pattern of population dynamics observed under different conditions in the present study provides a clue on the occurrence of interspecies interaction in the co-culture, which could be the reason behind the stable coexistence of C. saccharolyticus and C. kristjanssonii . The prevalence of an organism in a batch culture depends on its maximum specific growth rate compared with that of the other organisms capable of growth in the inoculum [ 2 ]. Since C. kristjanssonii exhibits a 40% lower maximum specific growth rate than that of C. saccharolyticus during batch growth on glucose and xylose [ 28 ], the prevalence of the former in their co-culture during the batch start-up phase and at higher dilution rates implies that it acquires a higher specific growth rate in presence of the latter. In addition, the biomass yield of the C. kristjanssonii -dominated co-culture in glucose-limited chemostat cultivations at a D of 0.15 h -1 was significantly higher than that of C. kristjanssonii alone under otherwise the same conditions (Table 4 ), which points to an enhancing effect of C. saccharolyticus on the biomass yield of C. kristjanssonii . Indeed, the fact that none of the strains was completely displaced by the other at any of the steady states evaluated supports the hypothesis of the occurrence of a beneficial sort of interspecies interaction in the co-culture rather than only competition for the same growth-limiting nutrient. The simple mathematical model we developed to describe this proposed interaction, in terms of compound E that has a growth-enhancing effect on C. kristjanssonii , could successfully mimic the stable coexistence and predict the population dynamics in the co-culture, ruling out any other required mechanisms (Figure 5 ). Furthermore, it is the combination of enhancing the growth rate and biomass yield of C. kristjanssonii that creates the condition for stable co-existence as observed in the chemostat-cultivations. This condition only remains valid as long as C. saccharomyces stays in the system to provide the proposed growth-enhancing compound. The reduction in the lag phase and the increase in maximum biomass concentration of C. kristjanssonii in the presence of C. saccharolyticus growth supernatant (Figure 6 ) provided experimental evidence on the presence of such a compound or signaling molecule that can enhance the growth of C. kristjanssonii . Although the maximum specific growth rate was not affected under these conditions, this could be due to the absence of C. saccharolyticus cells in the reactor, thus preventing the continuous supply of the growth-enhancing compound. It cannot also be ruled out that this compound is actually a product of cell lysis rather than a secretory product since C. saccharolyticus cells are prone to lyse significantly [ 48 , 49 ]. In light of the social evolution theory of microorganisms [ 50 ], the ability of C. saccharolyticus to enhance the growth of C. kristjanssonii might be classified as an altruistic cooperation. An explanation for altruistic cooperation between close relatives is best provided by the kin selection theory, where an individual species can still pass on its own genes to the next generation indirectly by helping a closely related species to reproduce. Unraveling the precise mechanism of this interaction or the nature of the involved molecules, however, remains a conceptual and methodological challenge. It is well known that each population or individual detects and responds to the presence of others in a consortium by trading metabolites or by exchanging dedicated molecular signals [ 1 , 51 ]. Growth enhancement as a consequence of interspecies interactions in bacteria may occur in response to some signaling molecules [ 52 ]. Processed oligopeptides are known quorum sensing molecules, or autoinducers, that are used by Gram-positive bacteria for communication [ 53 ]. Nichols et al [ 54 ] presented evidence that short peptides may be essential factors for initiating growth of 'uncultivable' cells. The existence of a peptide-based quorum sensing in hyperthermophilic bacteria was also previously demonstrated in a co-culture of Thermotoga maritima and Methanococcus jannaschii and was responsible for inducing exopolysaccharide production and enhancing biofilm formation by the former organism [ 13 ]. Moreover, it has been recently suggested that the addition of a second microbe, viz. Tm. maritima , to a pure culture of C. saccharolyticus triggers events causing the presence, absence and differential expression of protein species within the system [ 15 ]. Although the genome of C. saccharolyticus has been fully sequenced and annotated [ 34 ], it is difficult to examine for the presence of putative small peptide signaling molecules since signaling peptides are often products of genes encoding proteins less than 100 amino acids in length. In C. saccharolyticus genome, there are 496 of such genes, around 55% of which encode for hypothetical proteins (NCBI Entrez; http://www.ncbi.nlm.nih.gov/sites/entrez ). While genomic information did not prove useful, other approaches, such as microarray-based functional genomics approaches [ 12 , 14 ] or bioassay-directed fractionation and analysis of the growth supernatant [ 54 ], can be adopted for the identification of candidate signaling molecules and understanding the molecular mechanisms behind the interactions in the co-culture. This is, however, beyond the scope of the current study and may become more feasible by the availability of the complete genome sequence of C. kristjanssonii ."
} | 3,994 |
35064088 | PMC8794805 | pmc | 6,680 | {
"abstract": "Significance We develop temperature sensors on the basis of charges accumulated at the electrolyte/dielectric interface and dielectric/electrode interface. The accumulated charges make the temperature sensors self-powered, which simplifies circuit design and enables portable sensing. The sensors are stretchable, but deformation does not affect temperature sensing. The sensors have high sensitivity and fast response. They can be made small and transparent. Such temperature sensors open new possibilities to create human–machine interfaces and soft robots in healthcare and engineering.",
"conclusion": "Conclusion In summary, we have shown that junctions of ionic conductor, electronic conductor, and dielectric can be used to measure temperature. The ionotronic thermometry self-energizes, is highly sensitive, responds rapidly, has a small size, and can be made stretchable and transparent. Such soft, stretchable, transparent thermometry has potential for broad applications in healthcare, engineering, and entertainment.",
"discussion": "Results and Discussion Many designs of ionotronic thermometry are possible, depending on the arrangement of the electrode (electronic conductor), dielectric, and electrolyte (ionic conductor). For brevity, we denote the three substances by e, d, and i, and call the design in Fig. 1 an e-d-i junction. If an electrolyte/electrode interface is ideally polarizable and does not undergo electrochemical reaction, such an interface can enable ionotronic thermometry without the dielectric layer. The temperature sensitivity of electrolyte/electrode interfaces has been used to demonstrate energy harvesting ( 22 , 23 ), but has so far not been developed for temperature sensing. We begin our experiment with a design using two e-i junctions ( Fig. 2 A ). Each junction involves an electronic conductor and an ionic conductor in contact. This design uses no dielectric between the electrolyte and the electrode, and it is assumed that no electrochemical reaction occurs at the electrolyte/electrode interface. One junction serves as a sensing end, and the other junction serves as a reference end. The two ends are connected by an ionic conductor. When temperature at the sensing end differs from that at the reference end, a change in the open-circuit voltage is generated between the two ends and is measured by a voltmeter. The change in voltage depends on the type and concentration of ions, as well as the type of electronic conductor at the sensing end. Fig. 2. Ionotronic thermometry using two e-i junctions. ( A ) Unless otherwise specified, the ionic conductor is polyacrylamide hydrogel containing 0.03 mol/L NaCl, the electronic conductor at the reference end is gold-coated PET, and the temperature at the reference end is at room temperature. ( B ) The voltage is measured as a function of the temperature difference between the two junctions. A silver-plated fabric is used as the sensing-end electrode. Sensitivity depends on ( C ) the concentration of ions and ( D ) the type of electronic conductor at the sensing end. ( E ) Sensitivity is independent of the temperature at the reference end, T ref . Electrodes at both ends are gold-coated PET. ( F ) Two e-i junctions connected by an ionic conductor and the voltage recorded as a function of time. ( Inset ) When a drop of 0.03 mol/L NaCl solution of temperature T drop is released onto one junction, the voltage between the two junctions changes. Electrodes at both ends are gold. Each solid line is a linear fit to the data. To characterize the sensor, we change the temperature at the sensing end, T , keep the temperature at the reference end, T ref , at room temperature, and measure the change in the open-circuit voltage between the two electrodes. We measure the temperatures at the two ends separately using two commercial thermometers ( SI Appendix , Fig. S1 ). For the sensing-end electrode, we choose a commercial silver-plated fabric as a stretchable electronic conductor (MedTex 130) and characterize its electrical and mechanical behavior ( SI Appendix , Fig. S2 ). For the reference-end electrode, we sputter gold (30-nm thickness) on a polyester (PET) film (100-μm thickness; McMaster Carr). For the ionic conductor, we fabricate a stretchable and transparent polyacrylamide (PAAm) hydrogel containing NaCl. The hydrogel is sealed by a stretchable and transparent elastomer (VHB 4905; 3M). We test three samples in which the concentration of ions in the hydrogel is 0.03 mol/L and measure voltage V as a function of temperature difference between the two ends, T − T ref ( Fig. 2 B ). Within a temperature range of tens of degrees, the voltage is linear in temperature and the measured sensitivity is d V / d T = 1.19 mV / ° C . Any type of ions can be used as long as the net interfacial charge σ i + σ e ≠ 0 and the ions cause no electrochemical reactions. Both the net interfacial charge and the Debye length are affected by the type of ions and ionic concentration. We use three concentrations of NaCl to demonstrate the principle. The sensitivity depends on the concentration of ions and reaches a large value at an intermediate concentration of ions ( Fig. 2 C ). When the electrolyte has a high concentration of ions, the Debye length is small, and the capacitance of the junction is weakly sensitive to temperature. When the electrolyte has a low concentration of ions, the Debye length is large, and the capacitance of the junction is temperature-sensitive. In general, σ i varies with concentration, and the concentration dependence of sensitivity is difficult to predict quantitatively. The effect of ion type and ionic concentration on sensitivity deserves a future study. In principle, any electronic conductor can be used, as long as it does not undergo any electrochemical reaction with the ionic conductor. We use three electronic conductors at the sensing end and measure the corresponding voltage–temperature relations ( Fig. 2 D ). In all three cases, gold-coated PET is used as the electronic conductor at the reference end. The sensitivity depends on the type of electronic conductor at the sensing end, which affects the net interfacial charge. The sensitivity does not depend on the type of electronic conductor at the reference end, so long as the temperature at the reference end is unchanged during sensing. This design involves two e-i junctions, one at the sensing end and the other at the reference end. Both e-i junctions are, of course, temperature-sensitive. The two ends are connected with an ionic conductor. As the length of ionic conductor (centimeter) is much larger than the Debye length (nanometer), the two e-i junctions can be considered thermally separated during the time of temperature sensing. The temperature change is much smaller than the absolute temperature. Our model above predicts that the measured open-circuit voltage is linear in the difference in the temperatures of the two ends, T − T ref . To confirm this prediction, we place the two ends on two hot plates and measure the V – T relation at various reference temperatures, T ref . We use gold-coated PET as the electronic conductors at both ends. Our data show that the sensitivity is independent of temperature at the reference end ( Fig. 2 E ). In the design of e-i junctions connected by an ionic conductor, gold (100-μm thickness) is used as the electronic conductor at both ends ( Fig. 2 F ). The sensor is unsealed and placed in open air at room temperature (∼25 °C in this case). Upon releasing a drop of NaCl solution (0.03 mol/L, ∼50 °C) onto one junction, we record a voltage spike within a short time of ∼10 ms. The fast thermal response originates from the small thickness of the electronic conductor. In practice, however, the sensor needs to be sealed. As a result, the thermal response will be affected by the material and thickness of the seal ( SI Appendix , Fig. S3 ). As shown by Eq. 3 , the sensitivity d V e / d T is independent of the area of the e-i junction. However, to ensure accurate measurement, the sensing area should be sufficiently large to produce a measurable electric current through the voltmeter. Thus, the minimum area is determined by the resolution of the voltmeter, as well as the sensitivity ( SI Appendix , Supplementary Note 2 ). Next, we describe several designs of ionotronic thermometry and their properties. Unless otherwise stated, the ionic conductor is PAAm hydrogel containing 0.03 mol/L NaCl, and the electronic conductor is gold-coated PET. In a second design, an e-i junction is formed by a stretchable electronic conductor (silver-plated fabric) and a stretchable ionic conductor (hydrogel) ( Fig. 3 A and SI Appendix , Fig. S4 A ). A dielectric elastomer (VHB 4905; 3M) is used as a seal and an electrical insulator. This design functions as a stretchable thermometer. Its voltage is sensitive to temperature but insensitive to stretch ( Fig. 3 B ). At the interface between stretchable electronic and ionic conductors, e-i junction forms between the individual silver particles and the hydrogel. Because the silver particles are rigid, the electrolyte/electrode interface is unaffected by stretch. Fig. 3. Ionotronic thermometry of several designs. ( A ) An electronic conductor and an ionic conductor are both elastomeric and stretchable. ( B ) At room temperature, stretch of the conductors negligibly affects voltage. A solid line is drawn to guide the eye. ( C ) The two ionic conductors have different ionic concentrations. ( D ) This difference causes a change in voltage when the temperature changes. The solid line is a linear fit to the data. ( E ) An ionic conductor is sandwiched between two dissimilar electronic conductors. The voltage between the two electronic conductors changes with temperature. ( F ) The sensitivity remains nearly constant over days. In a third design, a small piece of electronic conductor connects to two stripes of ionic conductors ( Fig. 3 C ). This design functions as a stretchable and transparent thermometer ( SI Appendix , Fig. S4 B ). It is difficult to identify a stretchable and transparent electronic conductor, but the hydrogel is a stretchable and transparent ionic conductor. The two ionic conductors have different concentrations of ions, so that the two e-i junctions at the sensing end are dissimilar. Outside the sensing end, a transparent dielectric elastomer (VHB) separates the two stripes of ionic conductors. The three-layer structure forms an ionic cable, which serves as a stretchable and transparent interconnect between the sensing end and the reference end. In this design, the voltmeter measures the voltage between the two ionic conductors at the reference end. The two ionic conductors are in contact with two electronic conductors, forming two additional e-i junctions. Consequently, the four e-i junctions are in series. When temperature of the sensing end changes and temperature of the reference end is unchanged, a voltage will be generated. The electronic conductors at the sensing and reference ends are the silver-plated fabric and the gold-coated PET, respectively. The two ionic conductors are PAAm hydrogels containing 0.03 mol/L and 2 mol/L NaCl. When the concentrations of ions in the two ionic conductors are the same, the voltages across the four e-i junctions will cancel out and not respond to temperature ( Fig. 3 D ). Therefore, the asymmetry is crucial for the ionotronic thermometry. Additional analyses and characterizations of this design can be found in SI Appendix , Supplementary Note 3 and Fig. S5 . In a fourth design, an ionic conductor is sandwiched between two different electronic conductors (an aluminum foil and a gold-coated PET) ( Fig. 3 E ). The two interfaces form dissimilar junctions. This design does not require a reference end. When temperature changes over the sandwich, a voltage is generated ( Fig. 3 F ). The sensitivity is stable over days, which indicates negligibly slow electrochemical reactions, if any. This stability is understood as follows. We have used VHB to seal the device, so that the hydrogel loses negligible amount of water during the experiment. Gold is inert in contact with the hydrogel. Aluminum itself is an active metal but forms a thin and stable oxide layer, which serves as a dielectric. The aluminum oxide retards further electrochemical reaction. When the hydrogel loses water to open air, the concentration of ions changes, which affects the sensitivity of a temperature sensor. As we have demonstrated, a sensor sealed by VHB is stable within a week ( Fig. 3 F ). Other elastomers, such as butyl rubbers, have lower water permeability than VHB ( 24 ) and are expected to make a sensor stable over a longer period of time. In addition, ionic liquid has negligible vapor pressure and is expected to make long-lasting sensors. We further note that the sensitivity of this design, ∼ 10 mV / ° C , is about one order of magnitude higher than other designs without using aluminum. The aluminum oxide has hydroxyl groups covalently anchored on the surface ( 25 , 26 ), which possibly increases the ionic charges on the hydrogel/dielectric interface, σ i . Furthermore, dissimilar electronic conductors can anchor ionic charges of opposite signs. The design in Fig. 3 E involves two thermal sensing junctions in series. When the temperature changes, the changes in the voltages of the two junctions can be either additive or subtractive, depending on the two electronic conductors ( SI Appendix , Supplementary Note 4 and Fig. S6 ). These considerations suggest that chemistry greatly affects sensitivity, which we will pursue in a subsequent study. The ionotronic thermometer can be made stretchable, flexible, and transparent ( Fig. 4 A and B ). The stretch insensitivity makes the ionotronic thermometer convenient for sensing temperature for curved surfaces. We use a stretchable and transparent ionotronic thermometer ( Fig. 3 C ) to measure the surface temperature of an egg partly immersed in hot water ( Fig. 4 C ) and compare the ionotronic thermometer with a commercial infrared thermometer (ennoLogic eT650D) ( Fig. 4 D ). Further, we fabricate a pneumatic soft gripper and glue an ionotronic thermometer, in which the silver-plated fabric is used as the electronic conductor at both ends, to one of the four arms. The gripper is used to grip an egg and to measure the temperature ( Fig. 4 E ). The voltage changes negligibly before the gripper touches the egg, rises sharply when the gripper touches the egg, and decreases after the gripper releases the egg ( Fig. 4 F and Movie S1 ). This experiment corroborates that the voltage is sensitive to temperature, but not to stretch. Fig. 4. Stretchable and transparent ionotronic thermometers for curved surfaces. Stretchable and transparent ionotronic thermometer in a stretched state ( A ) and a twisted state ( B ). ( C ) A schematic of experimental setup to monitor temperature on a curved surface. An egg is partly immersed in hot water. ( D ) The ionotronic thermometer is compared with a commercial infrared thermometer. ( E ) The stretchable and transparent ionotronic thermometer integrated with a pneumatic soft gripper to measure surface temperature of a hot egg. ( F ) The voltage changes negligibly before the gripper touches the egg, rises sharply when the gripper holds the egg, and decreases after the gripper releases the egg. We compare a thermocouple and an ionotronic thermometer. The former relies on an irreversible thermodynamic phenomenon and the latter on an equilibrium thermodynamic phenomenon. The junction of two metals in the thermocouple conducts electricity, but the junction of a metal and a hydrogel behaves like a capacitor. A change in temperature causes a steady current in a thermocouple but not in an ionotronic thermometer ( SI Appendix , Fig. S7 ). A thermocouple and an ionotronic thermometer are both self-powered: A change in temperature causes a change in voltage ( SI Appendix , Fig. S8 ). A thermocouple relies on a bulk phenomenon and requires temperature difference between two ends. By contrast, an ionotronic thermometer relies on an interfacial phenomenon and can be used in a design without temperature difference (e.g., the e-i-e junction; Fig. 3 E ). A thermocouple maintains a constant voltage when the temperature difference between two ends is fixed. On the other hand, an e-i junction behaves like a capacitor and discharging the capacitor results in a voltage drop over time. In an open circuit, taking the internal resistance of voltmeter R ∼ 1 GΩ and the capacitance of e-i junction C ∼ 10 − 5 F , we estimate the decay time t RC = R C ∼ 10 4 s . That is to say, the voltage will drop when the sensor is constantly connected to a voltmeter for hours. It is confirmed by experimental measurement ( SI Appendix , Fig. S8 D ). Furthermore, thermocouples are rigid and opaque, but ionotronic thermometers can be stretchable and transparent. We have demonstrated several designs of ionotronic thermometry. In principle, still other designs are possible ( SI Appendix , Fig. S9 ). The detection range of temperature of the ionotronic thermometer is mainly dependent on the ionic conductor. In this work, hydrogel is used as the ionic conductor, so the detection range is within 0 to 100 °C. The detection range can be expanded by using ionogel or organogel as ionic conductors. The ionotronic thermometer can be miniaturized by making arrays of electrolyte/dielectric/electrode interfaces. To make the ionotronic thermometer fully stretchable and transparent, stretchable and transparent electronic conductors are needed, such as those described in refs. 27 and 28 . We also study the electrical response of the ionic cable and show that the electrical response time of the stretchable interconnect is much shorter than the thermal response time ( SI Appendix , Supplementary Note 5 )."
} | 4,489 |
22514077 | null | s2 | 6,681 | {
"abstract": "The development of a new generation of multifunctional biomaterials is a continual goal for the field of materials science. The in vivo functional behaviour of a new fusion protein that combines the mechanical properties of spider silk with the antimicrobial properties of hepcidin was addressed in this study. This new chimeric protein, termed 6mer + hepcidin, fuses spider dragline consensus sequences (6mer) and the antimicrobial peptide hepcidin, as we have recently described, with retention of bactericidal activity and low cytotoxicity. In the present study, mouse subcutaneous implants were studied to access the in vivo biological response to 6mer + hepcidin, which were compared with controls of silk alone (6mer), polylactic-glycolic acid (PLGA) films and empty defects. Along with visual observations, flow cytometry and histology analyses were used to determine the number and type of inflammatory cells at the implantation site. The results show a mild to low inflammatory reaction to the implanted materials and no apparent differences between the 6mer + hepcidin films and the other experimental controls, demonstrating that the new fusion protein has good in vivo biocompatibility, while maintaining antibiotic function."
} | 309 |
22514077 | null | s2 | 6,682 | {
"abstract": "The development of a new generation of multifunctional biomaterials is a continual goal for the field of materials science. The in vivo functional behaviour of a new fusion protein that combines the mechanical properties of spider silk with the antimicrobial properties of hepcidin was addressed in this study. This new chimeric protein, termed 6mer + hepcidin, fuses spider dragline consensus sequences (6mer) and the antimicrobial peptide hepcidin, as we have recently described, with retention of bactericidal activity and low cytotoxicity. In the present study, mouse subcutaneous implants were studied to access the in vivo biological response to 6mer + hepcidin, which were compared with controls of silk alone (6mer), polylactic-glycolic acid (PLGA) films and empty defects. Along with visual observations, flow cytometry and histology analyses were used to determine the number and type of inflammatory cells at the implantation site. The results show a mild to low inflammatory reaction to the implanted materials and no apparent differences between the 6mer + hepcidin films and the other experimental controls, demonstrating that the new fusion protein has good in vivo biocompatibility, while maintaining antibiotic function."
} | 309 |
33557214 | PMC7913968 | pmc | 6,683 | {
"abstract": "This work presents a new approach based on a spiking neural network for sound preprocessing and classification. The proposed approach is biologically inspired by the biological neuron’s characteristic using spiking neurons, and Spike-Timing-Dependent Plasticity (STDP)-based learning rule. We propose a biologically plausible sound classification framework that uses a Spiking Neural Network (SNN) for detecting the embedded frequencies contained within an acoustic signal. This work also demonstrates an efficient hardware implementation of the SNN network based on the low-power Spike Continuous Time Neuron (SCTN). The proposed sound classification framework suggests direct Pulse Density Modulation (PDM) interfacing of the acoustic sensor with the SCTN-based network avoiding the usage of costly digital-to-analog conversions. This paper presents a new connectivity approach applied to Spiking Neuron (SN)-based neural networks. We suggest considering the SCTN neuron as a basic building block in the design of programmable analog electronics circuits. Usually, a neuron is used as a repeated modular element in any neural network structure, and the connectivity between the neurons located at different layers is well defined. Thus, generating a modular Neural Network structure composed of several layers with full or partial connectivity. The proposed approach suggests controlling the behavior of the spiking neurons, and applying smart connectivity to enable the design of simple analog circuits based on SNN. Unlike existing NN-based solutions for which the preprocessing phase is carried out using analog circuits and analog-to-digital conversion, we suggest integrating the preprocessing phase into the network. This approach allows referring to the basic SCTN as an analog module enabling the design of simple analog circuits based on SNN with unique inter-connections between the neurons. The efficiency of the proposed approach is demonstrated by implementing SCTN-based resonators for sound feature extraction and classification. The proposed SCTN-based sound classification approach demonstrates a classification accuracy of 98.73% using the Real-World Computing Partnership (RWCP) database.",
"conclusion": "6. Conclusions This work presents a new approach based on a spiking neural network for sound preprocessing and classification. We propose a biologically plausible sound classification framework that uses an SNN-based network for detecting the embedded frequencies contained within an acoustic signal. A new SCTN digital neuron is used as a basic building block for constructing a spiking neural network. We demonstrate the use of an SCTN-based network as an efficient alternative to the design of programmable analog electronics circuits. The proposed approach is applied to sound signal processing and classification, suggesting direct interfacing of the analog sensor with the SNN network. We present an efficient ultra-low-power implementation of some common analog circuits used for phase and frequency detection, voice feature extraction, and classification. The SCTN is used as the basic building block to implement analog-like circuits, utilizing the unique features of the SCTN neuron and smart inter-connections. Experimental results show high accuracy of 98.73% achieved for sound classification. The benefit of using an SCTN-based network for implementing analog circuits is also reflected by a generic solution and the reuse ability by changing the network weights. The proposed approach can be applied in future work for efficiently extracting the common MFCC coefficients representing a speech signal.",
"introduction": "1. Introduction In recent years, we are witnessing a shift in technological solutions from the traditional algorithmic approach to multipurpose deep neural networks (DNNs) neuromorphic approach. DNN networks are widely applied to sound recognition and image processing [ 1 , 2 ], presenting a new challenge for low-power and efficient implementation in embedded systems. These types of applications attempt to resemble the operation of the human brain by understanding and imitating the process of human sensory perception. The necessity for low-power and high-performance embedded platforms is increasing [ 3 , 4 ]. Many mobile applications such as the Internet of Things (IoT) are penetrating our life rapidly and require energy-efficient processing units [ 5 ], which most of the current NN-based solutions lack. This work presents a new approach based on a spiking neural network for sound preprocessing and classification. The proposed approach is biologically inspired by the biological neuron’s characteristic using spiking neurons, and Spike-Timing-Dependent Plasticity (STDP)-based learning rule. Spiking neural models mimic the biological neurons for information processing purposes [ 6 ]. SNN architectures can be used to solve spatiotemporal problems such as in patterns recognition, optimization, and classification problems [ 7 ]. SNN have been developed with a neurobiologically plausible computational architecture that incorporates both spatial and temporal data into one unifying model and can be applied for pattern recognition [ 8 ]. Recent studies use machine learning methods to integrate the dynamic patterns of spatiotemporal brain data contained in EEG and ERP data. Z. Doborjeh et al. [ 8 ] use SNN for evaluation of concurrent neural patterns generated across space and time from electroencephalographic features representing event-related potential (ERP). Unlike classical neurons, a spiking neuron (SN) uses spikes for communication and computations, and therefore has the potential to consume very low power while enabling efficient implementation in terms of silicon area [ 9 ]. Bensimon et al. [ 10 ] demonstrate that the Spike Continuous Time Neuron (SCTN) model is capable of accurately replicating the behaviors of a biological neuron. A rich diversity of behaviors can be achieved by smart inter-connection of basic neuron blocks. Reordering and connecting blocks of SCTNs into a full SN-based network allow efficient implementation of a large class of cognitive algorithms and voice applications. This work suggests the usage of an innovative energy-efficient hardware-based spiking neuron (SN) presented in [ 11 ] as a basic building block in the design of programmable analog electronics circuits. The proposed SCTN can be considered as a nonlinear device capable of processing an extensive amount of data efficiently. The close resemblance between SN and a biological neuron justifies the evaluation of the substitution of the classical NN model with the SN model. The implementation of SN can be carried out using both analog and digital circuits [ 12 ]. Various kinds of SNN-based models and neuromorphic circuits have been recently proposed to support the processing of vast streams of information in real-time [ 13 , 14 ]. A continuous-time spiking neural network paradigm is presented in [ 15 ]. The spike latency takes into account that the firing of a given neuron occurs after a continuous-time delay. SNN-based classifier consistently outperforms the traditional Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) neural networks in a temporal pattern classification task [ 16 ]. Although RNN and LSTM models capture the temporal transition explicitly, they are hard to train for long sound samples due to the vanishing and exploding gradient problem [ 17 ]. Low-power spiking-based neural networks are highly suitable to replace RNN and LSTM as the computational engine for time-series applications utilizing the high correlation between adjacent frames [ 18 ], especially if the series of data contains strong temporal dependencies like in the case of sound and video applications [ 14 ]. STDP is a biologically plausible learning paradigm inspired by the Hebbian learning principle. STDP is one of the most common activity-driven synaptic weight learning mechanisms [ 19 ]. Following the STDP learning rule, the neuron weights are adjusted considering the time difference between presynaptic and post-synaptic spikes. According to this rule, if the presynaptic neuron fires earlier than the post-synaptic one, the synapse is strengthened. It has been shown that the unsupervised STDP rule can be used for the detection of frequent input spike patterns [ 20 , 21 ]. This work presents a new building block approach and SCTN-based spiking neural network for sound preprocessing and classification. The proposed approach is biologically inspired by the biological neuron’s characteristic using spiking neurons and STDP-based learning rule. We propose a biologically plausible sound classification framework which uses an SCTN-based network for detecting the embedded frequencies contained within an acoustic signal. Throughout the years many voice features extraction techniques have been suggested [ 22 , 23 ]. Voice signal identification systems involve the process of converting analog speech waveform into useful features for further processing and classification. Among the leading voice feature extraction techniques are the Mel Frequency Cepstral Coefficient (MFCC) introduced by Davis et al. [ 24 ], the Linear Prediction Coefficients (LPC), and the Linear Prediction Cepstral Coefficients (LPCC). The Hidden Markov Modeling (HMM) is one of the most common techniques for voice classification [ 25 ] used for automatic speech recognition. J. Wu et al. present a biologically plausible framework for sound event classification [ 16 ]. They propose to use an unsupervised self-organizing maps (SOM) network for representing frequency contents embedded within the acoustic signals and an event-based SNN for pattern classification. R. Xiao et al. propose a feedforward SNN for sound classification using the temporal learning rule [ 26 ]. The classification is based on extracting acoustic features from the time-frequency representation of sound (using FFT). They suggest to convert the representative sound features into a spiking train by a simple mapping rather than using SOM. Then these temporal patterns are classified via SNN using temporal learning rules. Contrarily to the previous SNN-based approaches for sound classification, we propose a framework based on a combined SNN for both preprocessing, feature extraction, and classification. The feature extraction is carried out using an SCTN-based network avoiding the common external preprocessing stage and time-frequency representation of the sound. Moreover, we suggest direct interfacing of the acoustic sensor with the SCTN-based network avoiding the usage of costly analog-to-digital and FFT conversions. This work also demonstrates an efficient hardware implementation of the SNN network based on the low-power digital SCTN neuron presented in [ 10 , 11 ]. The rest of the paper is organized as follows. Section 2 describes in detail the proposed SCTN model and the STDP learning paradigm. Section 3 presents the proposed SCTN building block approach and demonstrates the use of the SCTN to generate a basic frequency detector and a full resonator. Section 4 describes how the SCTN-based SNN is applied to sound features extraction and classification. Section 5 describes the experimental results, and, finally, Section 6 concludes the paper."
} | 2,827 |
33042042 | PMC7527417 | pmc | 6,684 | {
"abstract": "Drought is a critical factor limiting the productivity of legumes worldwide. Legumes can enter into a unique tripartite symbiotic relationship with root-nodulating bacteria of genera Rhizobium , Bradyrhizobium , or Sinorhizobium and colonization by arbuscular mycorrhizal fungi (AMF). Rhizobial symbiosis provides nitrogen necessary for growth. AMF symbiosis enhances uptake of diffusion-limited nutrients such as P, Zn, Cu, etc., and also water from the soil via plant-associated fungal hyphae. Rhizobial and AMF symbioses can act synergistically in promoting plant growth and fitness, resulting in overall yield benefits under drought stress. One of the approaches that rhizobia use to survive under stress is the accumulation of compatible solutes, or osmolytes, such as trehalose. Trehalose is a non-reducing disaccharide and an osmolyte reported to accumulate in a range of organisms. High accumulation of trehalose in bacteroids during nodulation protects cells and proteins from osmotic shock, desiccation, and heat under drought stress. Manipulation of trehalose cell concentrations has been directly correlated with stress response in plants and other organisms, including AMF. However, the role of this compound in the tripartite symbiotic relationship is not fully explored. This review describes the biological importance and the role of trehalose in the tripartite symbiosis between plants, rhizobia, and AMF. In particular, we review the physiological functions and the molecular investigations of trehalose carried out using omics-based approaches. This review will pave the way for future studies investigating possible metabolic engineering of this biomolecule for enhancing abiotic stress tolerance in plants.",
"conclusion": "Conclusion and Future Directions The importance of trehalose in improving stress tolerance, storage properties, and shelf life ( Pereira et al., 2004 ) of microorganisms has been recognized in recent years and is being commercially exploited worldwide ( McIntyre et al., 2007 ). Trehalose-over-producing microorganisms can enhance the tolerance of legume crops to abiotic stresses. However, the specific signaling mechanism behind the microbial trehalose-induced response to abiotic stress in plants requires further efforts. Indeed it is worthwhile to perform a detailed screening of plant varieties and breeding lines for having higher trehalose content in their root nodules during stress. At the same time, it is also promising to use the naturally colonizing native strains of rhizobia and AMF as starter cultures for breeding new lines capable of producing higher trehalose and improving stress tolerance. Increasing evidence indicates that plant trehalose application in plants, either through soil application or microbial inoculants, results in enhanced drought tolerance ( Figure 2 ). However, the question of whether compatible solutes are equally efficient in protecting plants or bacteria from drought under field conditions needs further exploration. To conclude, we present a few critical research areas for enhancing stress tolerance in plants by microbe-mediated trehalose accumulation: FIGURE 2 Diagrammatical representation for developing agro-microbial strategy utilizing arbuscular mycorrhizal fungi and rhizobia for mitigating drought stress in plants. 1. The selection of bacteria and bacterial endophytes capable of overproducing trehalose is very crucial. Exploring such bacteria for developing liquid inoculants with enhanced survival and stability is needed. 2. It is also vital to understand the role of trehalose metabolism in rhizobia through further screening of the trehalose synthase genes (e.g., OtsA gene) in the symbiotic bacteroids at the molecular, biochemical, and physiological levels to increase tolerance and grain yield under stress conditions ( Suárez et al., 2008 ). 3. There is a strong need to carry out detailed investigations on the molecular mechanisms and omics-based approaches involved in AMF colonization during trehalose metabolism to confer tolerance in plants against abiotic stresses.",
"introduction": "Introduction Global climate change is projected to increase average temperatures, change rainfall patterns, and increase water scarcity ( Karl and Trenberth, 2003 ). These effects will be felt especially in the semi-arid tropics, where evaporation and temperature are already high ( Vadez et al., 2012 ). Among all abiotic stresses, drought (water deficit) has been identified as a critical factor limiting crop productivity, with roughly 64% of global land area affected ( Meena et al., 2017 ). Abiotic stresses cause changes in the soil–plant–atmosphere continuum, resulting in crop yield reductions. Prolonged exposure to drought leads to altered metabolism and damage to biomolecules ( Bhagat et al., 2014 ). Legumes deliver several vital environmental, economic, and social services and are a major source of food, nutrition, and feed worldwide, particularly in marginal regions of the global south. They are an essential component of the N cycle, with most species forming symbiotic relationships with diazotrophic bacteria (i.e., rhizobia). Legumes enrich agricultural systems with biologically fixed atmospheric N through the process of biological N fixation (BNF), reducing dependence on chemically produced nitrogenous fertilizers. BNF contributes 40–80% of N worldwide under different agronomic practices ( Herridge et al., 2008 ), where 110–220 kg N/ha/year is fixed by perennial legumes, and 50% of this range is fixed by annual legumes ( Havlin et al., 2005 ). Symbiotic BNF in legumes is highly sensitive to abiotic stresses such as drought and salinity. The protective mechanisms evolved by plants to adapt to stress include the upregulation of compatible solutes, e.g., osmoprotectants, osmolytes, and the activation of both enzymatic and non-enzymatic defense sites. The rhizosphere is the zone of enhanced microbial activity because of the supply of nutrients via host plant root exudates. Plant-growth promoting rhizobacteria, especially rhizobia, colonize plant cells within root nodules, whereas arbuscular mycorrhizal fungi (AMF) form highly branched structures called arbuscules inside the root cortex, which acts as nutrient exchange site between the plant and AMF. The interaction of these two symbiotic entities with the plant helps the host plant with nutrition and protection against soil-borne pathogens ( Vessey, 2003 ; Venant et al., 2013 ). The tripartite symbioses among rhizobia, AMF, and plants demonstrate the complexity of microbial interactions, resulting in enhanced resistance of plants to environmental stresses ( Antunes and Goss, 2005 ; Antunes et al., 2006 ). AMF colonize the roots of 80% of terrestrial plant species and positively influence plant growth by augmenting soil nutrient transport, particularly P, N, Zn, and Cu ( Govindarajulu et al., 2005 ). N-fixing rhizobia nodulate most legumes and enhance plant growth by fixing atmospheric N ( Baral et al., 2016 ). The symbiotic association of leguminous plants with trehalose-producing rhizobia has been reported to impart abiotic stress tolerance to the plants ( Suárez et al., 2008 ; Sugawara et al., 2010 ; Garg and Pandey, 2016 ). Species of rhizobia and host genotype play a key role in the determination of the extent of trehalose accumulation by their symbiotic partner and can result in enhanced BNF. Inoculation of Rhizobium etli strains, characterized by the overexpression of trehalose-6-phosphate synthase into Phaseolus vulgaris , has been shown to enhance both the number of root nodules and N fixation parameters ( Suárez et al., 2008 ). Trehalose acts as a chemical chaperone as well as a metabolite for preventing the protein from acetylation and glycation under desiccation stress. High glucose in bacterial cells leads to acetylated aggregates, vitrification, and advanced glycation end products for cross-link formation of the proteins ( Laskowska and Kuczyñska-Wiśnik, 2019 ). Trehalose accumulation in Rhizobium leguminosarum bv. trifoli strain NZP561 occurs by both otsA and TreYZ pathways during the stationary phase. It has been deemed essential for desiccation tolerance and overcoming stress related to nodule occupancy ( McIntyre et al., 2007 ). Similarly, trehalose biosynthesis in Bradyrhizobium japonicum occurs by OtsA , TreS , and TreY genes playing a role in symbiotic N-fixation and survivability under salinity ( Sugawara et al., 2010 ). Mycorrhizal interaction can also impart benefits to trehalose production. Inoculation of the legume Cajanus cajan with the AMF ( Rhizophagus irregularis ), in combination with rhizobia, improved nodulation, N and phosphorus (P) uptake, and accumulation of higher trehalose in plants under salinity stress. The higher trehalose content was attributed to the increased activity of terpene synthase enzyme and decreased level of trehalase ( Garg and Pandey, 2016 ). Furthermore, combined AMF with silicon inoculation in C. cajan genotypes has been shown to help plants to survive under cadmium and zinc heavy metal stress by improving rhizobial symbiosis competency and regenerating nodules. This was attributed to trehalose synthesis, phytochelatin synthesis, and reactive oxygen species (ROS) scavenging mechanisms ( Garg and Singh, 2018 ). Similarly, the inoculation of AMF and polyamines along with Sinorhizobium fredii strain AR-4 was found to counteract nickel toxicity by increasing nodule functioning and modulating trehalose and ureide metabolism ( Garg and Saroy, 2020 ). Bacteria accumulate osmoprotective solutes, such as trehalose, in response to osmotic or desiccation stress ( Vriezen et al., 2007 ). The survival of trehalose-loaded cells was found to be better than that of non-loaded cells when soybean ( Glycine max ) seeds were coated with cells and subjected to desiccation ( Streeter, 2003 ). Trehalose accumulation in cultured cells and bacteroids by B. japonicum ( Streeter, 1985 ) and subsequent increase due to desiccation stress have been reported ( Cytryn et al., 2007 ), suggesting trehalose’s role as an osmoprotectant. The enhanced survival of B. japonicum in response to desiccation and salinity stress after exogenous addition of trehalose has been reported ( Streeter, 2003 ). Ocón et al. (2007) investigated the role of trehalose in AMF-mediated plants in which they correlated gene expression and the enzymes involved in trehalose metabolism with AMF hyphal biomass. AMF-mediated plants with lower doses of external trehalose application have been shown to induce both biotic and abiotic stress-related genes, mainly promoting downregulated abiotic stress-associated genes ( Schluepmann et al., 2004 ). Additionally, the roles of various bacterial-mediated trehalose biosynthetic pathways, their relationship with physiological responses, and their expression of stress tolerance genes have been studied ( Sugawara et al., 2010 ). However, no systematic studies on trehalose accumulation and mobilization by the tripartite association of plants with rhizobia and AMF have been carried out. In this review, we discuss the significance of tripartite symbiosis of plants, rhizobia, and AMF in trehalose accumulation, metabolism, genomics, and their importance for mitigating abiotic stresses."
} | 2,826 |
39900471 | PMC11837758 | pmc | 6,685 | {
"abstract": "Abstract Aromatic compounds serve pivotal roles in plant physiology and exhibit antioxidative and antimicrobial properties, leading to their widespread application, such as in food preservation and pharmaceuticals. However, direct plant extraction and petrochemical synthesis often struggle to meet current needs due to low yield or facing economic and environmental hurdles. In the past decades, systems metabolic engineering enabled eco-friendly production of various aromatic compounds, with some reaching industrial levels. In this review, we highlight monocyclic aromatic chemicals, which have relatively simple structures and are currently the primary focus of microbial synthesis research. We then discuss systems metabolic engineering at the enzyme, pathway, cellular, and bioprocess levels to improve the production of these chemicals. Finally, we overview the current limitations and potential resolution strategies, aiming to provide reference for future studies on the biosynthesis of aromatic products.",
"introduction": "Introduction Aromatic compounds are ubiquitous in plants and play crucial roles in their physiological processes, such as growth, reproduction, and defense against pathogens and pests. Their inherent antioxidative and antimicrobial properties have led to their extensive utilization as food preservatives and antioxidants. Furthermore, many aromatic compounds exhibit promising potential in supporting human health by potentially mitigating cardiovascular diseases, neurodegenerative disorders, diabetes, and obesity (Noda and Kondo 2017 ). While aromatic compounds can be extracted from plants using methods like distillation, pressing, fractional distillation, and other techniques, their low natural abundance within plants and the typical constraints in raw material supply prevent achieving large-scale production. Presently, the majority of commercially available aromatic compounds are synthesized through petrochemical pathways. However, chemical synthesis of these compounds faces economic and environmental challenges due to intricate reaction pathways, reliance on toxic chemicals, and complex purification processes (Sun et al. 2021 ). As an alternative approach, guided by principles of synthetic biology, the rational modification of microbial cells through genetic engineering, enzyme engineering, metabolic flux regulation, omics technologies, and modeling has facilitated the eco-friendly and sustainable production of numerous aromatic compounds sourced from renewable materials like glucose, plant-derived lignin, and tannate (Huccetogullari et al. 2019 ). This paradigm has spurred significant research advancements in the production of aromatic compounds, scaling up production to an industrial level in some cases (Zhu et al. 2023 ). Key methodologies include enzyme engineering, design of synthetic pathways, adaptive evolution, transporter engineering, and modular engineering, which focused on regulating central metabolic pathways, shikimate pathways, and chorismate pathways (Choi and Lee 2023 ). This review comprehensively summarizes and reviews monocyclic aromatic compounds produced using microorganisms. In addition, systems metabolic engineering strategies in this field are discussed with example cases. These strategies provide critical insights for optimizing industrial fermentation strains and set the stage for the microbial production of innovative and more intricate aromatic compounds in the future.",
"discussion": "Discussion With rapid advancements in synthetic biology, intersecting with artificial intelligence, microbial production of monocyclic aromatic compounds has entered a new era full of opportunities. The overarching objective of synthetic biology is to achieve commercial production of target chemicals, with the key technical indicators for assessing economic feasibility are encapsulated within the Titer-Rate-Yield (T-R-Y) framework (Konzock and Nielsen 2024 ). Titer represents the final product concentration, which directly influences downstream processing costs. Rate reflects production efficiency, closely tied to capital investment. Yield assesses the efficiency of carbon source utilization, which plays a decisive role in raw material costs. Economic feasibility assessments based on T-R-Y can provide valuable guidance for transitioning laboratory-scale research to large-scale production. Two illustrative examples of evaluating economic feasibility using the T-R-Y framework are the production of two bulk chemicals, ethanol and 1,3-propanediol. The production of ethanol exemplifies the inherent trade-off between cellular growth and product formation, whereas the efficient biosynthesis of 1,3-propanediol highlights the critical role of optimized metabolic pathways and bioreactor design. To achieve the commercial production of more monocyclic aromatic chemicals, future research can focus on optimizing fermentation T-R-Y metrics to better accommodate large-scale production requirements. The efficiency of metabolic pathways is the most critical factor affecting the Titer (T) indicator, especially for pathways involving lengthy steps for certain monocyclic aromatic compounds (Li et al. 2021 ). There is still significant room for exploration in the methods based on omics data analysis to uncover new and efficient synthetic routes. It is estimated that plants can synthesize over one million metabolites, only ∼0.1% of biosynthetic pathways have been functionally characterized to date. This limitation primarily stems from the species-specific and time-consuming nature of enzyme function annotation methods based on molecular genetics and analytical biochemistry. With the development of single-cell technologies, high-resolution maps are now available for different cell types, which can improve the efficiency of homologous gene prediction and enzyme function annotation. Moreover, integrating various types of information, including utilizing the three-dimensional protein structures generated by AlphaFold, can further enhance enzyme function prediction, particularly for orphan genes (Zhao and Rhee 2022 ). Building GEMs based on omics data is another key approach for predicting new pathways. Currently, the number of GEMs is still far fewer than the number of sequenced species, which is limited by three main reasons: (i) incomplete annotation algorithms; (ii) GEMs reconstruction requiring substantial manual curation; and (iii) limited understanding of species-specific physiological and biochemical mechanisms. Additionally, GEMs should incorporate simulations of various intracellular interactions (e.g. protein-DNA interactions, protein-protein interactions) and multi-level regulation of pathways (e.g. transcriptional and translational regulation), to provide a comprehensive systems-level understanding of cellular metabolism. This integrative approach will not only improve the prediction accuracy of novel biosynthetic pathways but also enable more precise engineering of metabolic networks, thereby advancing the field of metabolic engineering (Nielsen and Keasling 2016 ). In the economic feasibility assessment of fine chemical production, researchers advocate using the theoretical maximum Yield (Y) as the primary criterion during preliminary feasibility analysis, primarily due to raw material cost considerations (Konzock and Nielsen 2024 ). Despite the unsustainability of petrochemical resources, certain aromatic chemicals continue to face competition from low-cost petrochemical alternatives (Jiang et al. 2023 ). Thus, future research should prioritize the bioconversion of more inexpensive feedstocks. For monocyclic aromatic compounds, the efficient utilization of lignin represents a promising pathway. Lignin, a naturally occurring aromatic polymer, is not only one of the most abundant renewable resources on Earth but also a byproduct of biorefining processes that is often discarded as waste (e.g. through incineration) (Zhang et al. 2021b ). Additionally, with carbon neutrality goals set by China (2060) and the European Union (2050), the use of CO 2 as a substrate for chemical production is increasingly critical (Zhao 2022 ) (Chen et al. 2022a ). The most promising directions for industrialization include the following: (i) developing advanced genetic engineering tools for naturally carbon-fixing microorganisms (e.g. acetogens and cyanobacteria) to enhance their metabolic engineering efficiency and produce monocyclic aromatic compounds solely from CO 2 . (ii) Engineering heterotrophic microorganisms to utilize CO 2 as a co-substrate, thereby significantly reducing production costs (Hu et al. 2021 ). (iii) Creating efficient cell factories to convert one-carbon compounds (e.g. formate and methanol) into monocyclic aromatic compounds and subsequently coupling them with electrochemical CO₂ reduction devices to establish an efficient hybrid conversion system (Clomburg et al. 2017 ). Microbial cell viability is a critical factor influencing the production Rate (R) of monocyclic aromatic compounds, especially given the toxicity that most of these compounds pose to microbial cells. Adaptive evolution strategies for selecting high-tolerance strains are effective but constrained by the high time costs associated with low genetic mutation rates (Liu et al. 2023 ). In recent years, various accelerated evolution systems have been developed to enhance mutation rates (Eom et al. 2022 , Wang et al. 2019 ). Future research could focus on integrating these artificially designed accelerated evolution platforms with biosensors specific to aromatic compounds, enabling the rapid selection of mutant strains with higher production rates in shorter timeframes. Constructing microbial consortia is another cutting-edge strategy to alleviate metabolic burdens and improve cell viability. However, several challenges remain, including ensuring co-culture stability, controlling population dynamics, and optimizing microbial consortia growth (Li et al. 2019 ). Future studies should focus on understanding how environmental factors influence the composition and stability of microbial consortia. For instance, a recently developed toolkit for studying synthetic yeast consortia dynamics and key interactions provides a valuable resource in this regard. Moreover, integrating GEMs to simulate microbial consortia behavior can enhance our understanding of the expression patterns, cellular morphology, and physical interactions among community members. This knowledge could facilitate the design of microbial consortia systems with higher synthetic efficiency (Tarzi et al. 2024 )."
} | 2,657 |
19709625 | null | s2 | 6,686 | {
"abstract": "In this issue of Neuron, Sussillo and Abbott describe a new learning rule that helps harness the computational power of recurrent neural networks."
} | 36 |
34069901 | PMC8157586 | pmc | 6,688 | {
"abstract": "The combined effect of acrylonitrile butadiene styrene (ABS) spherical beads and granular activated carbon (GAC) particles as fluidized media on the performance of anaerobic fluidized bed membrane bioreactor (AFMBR) was investigated. GAC particles and ABS beads were fluidized together in a single AFMBR to investigate membrane fouling and organic removal efficiency as well as energy consumption. The density difference between these two similarly sized media caused the stratified bed layer where ABS beads are fluidized above the GAC along the membrane. Membrane relaxation was effective to reduce the fouling and trans-membrane pressure (TMP) below 0.25 bar could be achieved at 6 h of hydraulic retention time (HRT). More than 90% of soluble chemical oxygen demand (SCOD) was removed after 80 d operation. Biogas consisting of 65% of methane was produced by AFMBR, suggesting that combined use of GAC and ABS beads did not have any adverse effect on methane production during the operational period. Scanning Electron Microscope (SEM) examinations showed the adherence of microbes to both media. However, 16S rRNA results revealed that fewer microbes attached to ABS beads than GAC. There were also compositional differences between the ABS and GAC microbial communities. The abundance of the syntrophs and exoelectrogens population on ABS beads was relatively low compared to that of GAC. Our result implied that syntrophic synergy and possible occurrence of direct interspecies electron transfer (DIET) might be facilitated in AFMBR by GAC, while traditional methanogenic pathways were dominant in ABS beads. The electrical energy required was 0.02 kWh/m 3 , and it was only about 13% of that produced by AFMBR.",
"conclusion": "4. Conclusions Combined media fluidization using GAC particles and ABS plastic beads in single AFMBR exhibited fouling mitigation effectively while limiting the TMP value to less than 0.2 bar at 6 h of HRT. Nevertheless, a high organic removal efficiency (>90%) was achieved with the production of stable methane composition in the biogas as the two solid media were fluidized together. Microbes adhered to both media, but the microbial community was dependent upon the biocarrier material. The number of sequences was similar between GAC and bulk suspension, while fewer sequences were observed for ABS. Additionally, syntrophs and exoelectrogens population were more abundant on the GAC particles than the ABS beads. Therefore, it was more likely that DIET was utilized for methane production in GAC, while the microbes in ABS more heavily relied on traditional methanogenic pathways. The electrical energy required with dual media fluidization was only 0.02 kWh/m 3 , which was 87% lower than the energy produced by AFMBR system.",
"introduction": "1. Introduction Media fluidization is one of the key aspects to determine the performance of AFMBR in the treatment of low strength wastewater such as domestic sewage [ 1 , 2 , 3 ]. The media materials fluidized by bulk recirculation alone through AFMBR provides a surface area for cell growth [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. While AFMBR is widely applied in wastewater treatment along with the production of renewable energy in the form of methane, membrane fouling results in the loss of performance of a membrane due to the deposition of rejected wastewater constituents. GAC particles in AFMBR are often used to provide mechanical cleaning along the membrane surface to reduce membrane fouling [ 6 , 14 ]. While GAC particles can be an excellent tool as fluidizing media [ 15 , 16 , 17 ], the particles can be broken very easily by frequent collisions due to their weak rigidity during long-term reactor operation. This phenomenon should be more pronounced with larger media size, a higher recirculation rate or mixing intensity through the AFMBR reactor [ 18 ]. As a result, GAC particles that are ground into a smaller size can accelerate the membrane fouling because the particles should be deposited on membrane surface or even within membrane pores due to the formation of very dense cake layers easily [ 18 , 19 , 20 , 21 ]. Fluidizing the media accounts for the major portion of the energy in the operation of AFMBR, but it can depend strongly upon their intrinsic properties [ 5 , 22 , 23 ]. For example, higher specific gravity of the media such as GAC than the bulk wastewater present in the reactor, which is often higher than 2.0, requires more energy needed for the media fluidization than smaller ones. Given that the packing ratio of GAC particles is lower, recirculation flowrate through the reactor will be reduced, and thus less GAC particles are expected to be abrased during media fluidization. Nevertheless, membrane fouling is still severe if the upward flowrate is not enough for the GAC particles to cover the whole surface area of the membrane. Significant efforts were made to apply various scouring agents such as zeolite [ 8 , 12 , 13 ] and plastic agent [ 24 , 25 , 26 ] alternatives to the GAC in AFMBR, but only the usage of single media has been considered. Moreover, the use of inorganic particles is still of concern for practical applications because the particles are most likely abrasive in suspension to the membrane. The ABS is a cost-effective, polystyrene-based polymer composite material that has been used widely for various industrial applications [ 27 , 28 , 29 ]. The advantage of ABS can hold excellent mechanical stability and chemical resistance. The ABS-based materials should employ a low deformation rate. As a result, they can maintain intrinsic properties suitable for long-term reactor operation, even under harsh environmental conditions [ 30 ]. Additionally, the ABS beads have lower specific gravity than the GAC, thus requiring low energy consumption for their fluidization. However, the smooth surface of ABS beads provides less surface area for the growth of biofilm than that by GAC [ 31 , 32 , 33 ]. The AFMBR was operated using plastic beads as single fluidized media for domestic wastewater treatment application [ 24 ]. It was reported that bulk volatile suspended solid (VSS) concentration was about 4–5 times higher than those reported with the AFMBR system using the GAC, where most active microorganisms can be grown. The objective of this study was to combine the GAC particles and ABS beads having the different specific gravity and surface properties as fluidized media while having similar sizes to investigate whether their combined usage is complementary and their microbial communities on each media are similar in the AFMBR treating low-strength wastewater. Specifically, this study examined whether combining ABS beads with GAC could have a synergistic impact on the AFMBR performances such as fouling control, organic removal efficiency and methane production. Although the characteristics of GAC as a biocarrier has been widely researched [ 34 ], little is known about the capacity of ABS media to act as a biocarrier and fouling mitigation in the presence of GAC with the AFMBR system. Previous studies have primarily focused on the elimination of biofilm on ABS instead of biofilm development, as ABS is commonly used in medical devices [ 35 , 36 , 37 ]. Thus, we considered that there is a need to study whether ABS can support methane production from a microbial perspective. In addition, the use of plastic beads was applied to reduce the membrane fouling in the membrane bioreactor, but only single media has been used as a scouring agent to clean the membrane [ 38 , 39 ]. Key questions, such as whether ABS beads could harbor the appropriate microbial community for methane production and whether biocarrier materials would also influence such community formation, hold important implications for reactor performance. Therefore, it is necessary to investigate the impact of using combined usage of media on microbial compositions and energy requirements, as well as reactor performance, which is the key to successful AFMBR operation under the dual media fluidization.",
"discussion": "3. Results and Discussion 3.1. Effect of Fluidization of Combined Media on Membrane Fouling Figure 2 shows the change of TMP with the time during the entire operational period of the AFMBR system. During the initial 90 d of operation at 5.3 L/(m 2 h) of permeate flux, which corresponds to 8 h of HRT, the TMP value was maintained at about 0.1 bar. After that, an increase in permeate flux from 5.3 to 7.1 L/(m 2 h) accelerated membrane fouling, showing a rapid increase in TMP to 0.45 bar at 110 d of AFMBR operation. Membrane relaxation was then applied by performing combined media fluidization without producing a membrane permeate for 1 min every 9 min of filtration. After that, the TMP was decreased to the 0.25 bar gradually and then remained during the rest of the operational period. However, further reduction in the TMP value below the 0.25 bar was not observed under the periodic filtration/relaxation at 7.1 L/(m 2 h) of permeate flux. The reduction in membrane fouling due to the scouring effect caused by the fluidization of GAC or plastic beads in AFMBR has been clearly shown in previous studies [ 22 , 24 , 25 , 26 , 38 , 47 , 48 , 49 , 50 , 51 ]. With a flat-tubular ceramic membrane, about 6 L/min of recirculation flow rate was needed in AFMBR for the fluidization of GAC particles at 50 % of the packing ratio. With media fluidization using the same membrane and reactor used previously, due to the lower specific gravity of ABS plastic beads than GAC (1.04 vs. 2.0), the recirculation flow rate needed to be reduced to 3 L/min to avoid the overflow of the ABS beads through the recirculation line. That is, GAC particles could be fluidized along the bottom half of the membrane only, while the above half of the membrane was covered by ABS plastic beads ( Figure 1 ). This fluidized stratification can be expected since the heavier particles require a higher upflow velocity around the particles to cover the whole surface area of the membrane [ 52 ]. In other words, the contact with lighter ABS plastic beads on the membrane could result in a less physical impact to reduce membrane fouling. There is a relationship between the diameter of fluidized media and scouring intensity for the fluidized membrane reactor [ 53 ]. With bigger media, a higher recirculation flow rate was needed and this resulted in an improvement of particle motion, thus enhancing the cleaning efficiency on the membrane. In addition, more energy required to fluidize larger media leads to higher critical flux below which membrane fouling does not occur [ 53 ]. Reduction in the recirculation flow rate to avoid the overflow of ABS plastic beads through the reactor decreased a bulk upflow velocity along the membrane, and thus the fouling mitigation efficiency could be decreased. 3.2. AFMBR Treatment Efficiency Figure 3 shows the variation of SCOD concentration and biogas proportion in permeate and its removal efficiency with time observed during 180 d of AFMBR operation. During the initial 30 d of operation, the SCOD removal efficiency was only 20 to 40% due to the period required for microbial acclimation and the small rejection efficiency of organic components by porous MF membrane as applied in this study. After 40 d of operation, the SCOD removal efficiency started to increase gradually and then was maintained at more than 90%. During the initial 30 days of operation, no biogas was produced from the AFMBR, as shown in Figure 3 b. At day 60, methane composed approximately 45% of the biogas and then increased to about 65% after day 80. In addition, more than 90% of SCOD removal efficiency was achieved and stabilized at this operational period, suggesting that combined media fluidization consisting of GAC particles and ABS plastic beads did not provide any adverse impacts on the organic removal efficiency. The SCOD in bulk suspension and membrane permeate were almost similar, suggesting that most of the dissolved organic compounds should be removed by biodegradation rather than membrane filtration. Table 3 shows the mean value of AFMBR performance for each operational period. As a set-point flux was 5.1 L/(m 2 h), the bulk VSS concentration was maintained as 370.8 mg/L on average under which the TMP value was only about 0.1 bar, probably due to the scouring action of combined media to the clean membrane. Furthermore, it was also found that a higher permeate flux resulted in a lower bulk VSS concentration. As the flux increased to 7.1 L/(m 2 h), the bulk VSS concentration reduced to 60 mg/L, but the TMP jumped to 0.45 bar. A possible explanation for this is the transport of VSS present in reactor bulk toward the membrane surface could be more pronounced at a higher permeate flux, resulting in a higher fouling rate [ 21 , 54 ]. In other words, fluidizing plastic ABS beads and GAC particles together along the membrane surface was not very effective to reduce the fouling rate at 7.1 L/(m 2 h) of permeate flux as applied in this study. After performing the membrane relaxation, bulk VSS concentration was increased significantly to 211.7 mg/L, but TMP was reduced to 0.25 bar. This can support the fact that the media fluidization with GAC and ABS beads on membrane without conducting the permeation is effective to detach the foulant materials from the membrane. The VSS concentration in membrane permeate was near zero during the whole operational period, suggesting that the VSS should be rejected by the membrane almost completely. The EPS concentration in the bulk suspension measured at the end of the operation was 106.4 mg/L. This value was slightly higher than that measured under the fluidization of single GAC [ 55 ], but lower than that measured by plastic bead alone as fluidized media in the AFMBR treating the same synthetic wastewater [ 24 ]. Although a direct comparison is difficult, our observation suggests that more biomass can be grown on the GAC particles, probably due to the higher surface area provided, thereby lowering the concentration of EPS in bulk suspension than when only the plastic bead is used. In the first 30 d of operation, no biogas was produced by the reactor. From the 60 d of operation, however, methane composition in the biogas produced by single AFMBR was increased gradually and approached about 63% at 80 d of operation. After reactor stabilization, the methane composition in biogas was maintained at a rate higher than 55% regardless of the change in bulk VSS concentration under combined media fluidization. 3.3. Microbial Analysis Figure 4 compares SEM images of GAC particles and ABS plastic beads taken from the AFMBR after 180 d of operation. As expected, the surface of bare GAC particles appears to be rougher and more porous than ABS plastic beads ( Figure 4 a,c). Thus, the biofilm may be grown on the GAC particles favorably, as shown in Figure 4 b. Interestingly, there was considerable evidence that the ABS plastic beads provided a surface for the growth of microorganisms with a spherical morphology ( Figure 4 d). The hydrophobic surface of ABS beads may be involved in the adhesion of microorganisms [ 56 , 57 , 58 ]. However, more studies are needed to better understand interactive biofilm formation on polymeric materials such as ABS. To further evaluate the microbial compositions in the combined media, we performed 16S rRNA gene sequencing on bulk liquid, GAC and ABS beads. The samples were collected on day 168, during which the biogas production and methane composition had reached a steady state. Thus, the samples can represent matured microbial communities. Significant differences in the number of clean sequences between GAC (archaeal: 4788; bacterial: 49918) and ABS beads (archaeal: 1681; bacterial: 15033) were observed, while bulk (archaeal: 4817; bacterial: 57211) and GAC were comparable. Considering that the samples were processed using the same protocol, it is most likely that the low sequence count is attributed to the low DNA recovery from the ABS media. Although the SEM images suggested that microbes adhered to the surface of both media, the 16S rRNA gene data suggested that ABS harbored fewer microbes than GAC. The Principal Coordinates Analysis (PCoA) visualized the difference in microbial composition among each sample ( Figure 5 ). The separation among the three samples indicated that their microbial composition was distinctively different. Based on bacterial composition, the fluidized media were more similar than bulk liquid ( Figure 5 a), and this is mainly attributed to the lower abundance of Proteobacteria on both media (28 to 30%) as compared to bulk liquid (50%) ( Table 4 ). Between GAC and ABS beads, compositional differences (2 to 8%) in the phyla Firmicutes, Patescibacteria, Planctomycetes and Spirochaetes further distinguished the two media. In terms of archaeal composition, on the contrary, GAC and bulk liquid shared a more similar profile ( Figure 5 b). In particular, the uncultured Ca. Methanofastidiosales was absent in both bulk liquid and GAC, but was present on ABS (4.4%). These observations collectively suggest that biofilm and bulk communities in AFMBR are distinct from each other, corroborating with previous studies [ 59 , 60 ]. Collectively, biocarrier material is also a determining factor in how the microbial community is shaped. Figure 6 illustrates the distribution of syntrophs, exoelectrogens, and methanogens to focus on how these substrates were consumed in different media. Based on taxonomic classification, the microbial metabolism on GAC and ABS beads were examined and compared. The syntrophs accounted for 9.29% of the bacterial population in the GAC sample, which mostly consisted of propionate-degrading Syntrophobacter (8.46%). It also harbored exoelectrogens such as Desulfobulbus and Geobacter with relative abundances of 3.32% and 2.12%, respectively. The sulfate-reducing Desulfobulbus reportedly utilizes propionate for growth and produces acetate under a sulfate-limiting environment, as is the case with our system [ 61 ]. This taxon was previously observed in an AFMBR system using polyvinylidene fluoride (PVDF) as a scouring agent and biocarrier [ 59 ], but its role in AD metabolism is still unclear. Aceticlastic Methanothrix (28.8%) and an unclassified Methanomicrobia (38%) were dominant methanogens in the GAC; the remaining methanogenic community consisted of hydrogenotrophic methanogens. Since acetate and propionate were used as carbon sources in the synthetic feed, Syntrophobacter was likely to convert propionate into acetate and hydrogen. While the hydrogenotrophic methanogens utilize hydrogen, acetate can then be utilized by Methanothrix for acetoclastic methanogenesis. Moreover, Geobacter can consume acetate and extracellularly release electrons that are used by Methanothrix via direct interspecies electron transfer (DIET) [ 62 ]. Under such circumstances, Methanothrix could utilize CO 2 as the carbon source for methanogenesis, which would otherwise be impossible without its exoelectrongenic partner [ 60 ]. Although bulk liquid also contains Geobacter (1.3%), the currently known mechanisms of DIET requires proximity to function and is unlikely to occur in the suspension of liquid [ 62 ]. In the ABS sample, the relative abundance of Syntrophobacter (2.01%) and Geobacter (0.65%) were lower than in the GAC, suggesting that the syntrophic synergy and occurrence of DIET were relatively limited. While ABS harbored a higher percentage of Methanothrix (38.32%), it is most likely to produce methane via the acetoclastic pathway, as the Geobacter was in low relative abundance (0.65%). Besides, Syntrophobacter only accounted for 2.01% of the bacterial population in ABS beads, and the total syntrophic population is about 3.15%. Such synergy helps to maintain a thermodynamically favorable environment for the degradation of metabolites in the anaerobic digestion system [ 63 ]. While ABS beads could act as a biocarrier to facilitate the development of a syntrophic relationship between syntrophs and methanogens, the syntrophic synergy could be limited. It is plausible that compared to GAC, a more extended enrichment period is required for the development of a syntrophic population on ABS beads, although more studies would be needed to verify this. 3.4. Energy Requirements The energy requirement of the pump for operating AFMBR was estimated using a power requirement equation as follows [ 55 ]: (2) P = Q γ E 1000 \nwhere P is the power requirement of the pump (kW), Q is the recirculation flow rate of bulk suspension (m 3 /s), γ is 9800 N/m 3 , and E represents hydraulic pressure head loss for fluidization (mH 2 O). Table 5 shows the calculation of the energy demand and energy production of AFMBR applied with dual media fluidization in this study. Assuming that the efficiency of the pump is 65%, the total energy requirement is calculated as 2.03 × 10 −2 kWh/m 3 . When converting methane in the generated biogas to electrical energy with an efficiency of 33%, it was calculated as 1.62 × 10 −1 kWh/m 3 and the generated amount compared to the consumed amount was 7.97 times higher than the energy required to operate AFMBR. At 6 L/min of recirculation flow rate, as only GAC particles were applied as fluidized media under 50 % of the packing ratio, the total energy required at this condition was 3.09 × 10 −2 kWh/m 3 [ 55 ]. As mentioned, combined use of GAC and ABS beads requires less energy than that needed by using a single GAC under the same total packing ratio (50%) due to a lower recirculation flow rate required. Therefore, the combined use of both media provides a beneficial effect on reducing the operational costs of AFMBR while the fouling mitigation efficiency may be relatively low."
} | 5,456 |
40118900 | PMC11928476 | pmc | 6,689 | {
"abstract": "Starch is a primary food ingredient and industrial feedstock. Low-carbon microbial manufacturing offers a carbon-neutral/negative arable land-independent strategy for starch production. Here, we reconfigure the oleaginous yeast as a starch-rich micro-grain producer by rewiring the starch biosynthesis and gluconeogenesis pathways and regulating cell morphology. With the CO 2 electro-synthesized acetate as the substrate, the strain accumulates starch 47.18% of dry cell weight. The optimized system renders spatial-temporal starch productivity (243.7 g/m 2 /d) approximately 50-fold higher than crop cultivation and volumetric productivity (160.83 mg/L/h) over other microbial systems by an order of magnitude. We demonstrate tunable starch composition and starch-protein ratios via strain and process engineering. The engineered artificial strains adopt a cellular resources reallocation strategy to ensure high-level starch production in micro-grain and could facilitate a highly efficient straw/cellulose-to-starch conversion. This work elucidates starch biosynthesis machinery and establishes a superior-to-nature platform for customizable starch synthesis, advancing low-carbon nutritional manufacturing.",
"introduction": "Introduction Starch is an essential food ingredient and energy source to meet humans’ nutritional requirements 1 . The annual global demand for starch is above 120 million tons and is projected to grow at a compound annual growth rate of 4–5% as a result of population growth, consumption upgrading, as well as increasing starch demand in industrial applications 2 , 3 . Starch supply through the current production mode, traditional agriculture/crop cultivation, can barely meet the dramatically growing demand due to (i) the limited arable land 4 , 5 , (ii) the rate constraint of natural photosynthesis-based carbon fixation 6 , and (iii) the threat of climate change such as CO 2 emission and global warming 7 . CO 2 -to-starch conversion through low-carbon biomanufacturing is a possible approach to address the challenges and reshape a carbon-negative food supply route via cellular agriculture 8 , 9 . With the consumption of renewable electricity, CO 2 was electro-catalyzed to liquid energy-rich C1/C2 chemicals, such as formate and acetate 10 . These short-chain substrates are then transformed into more complex compounds by enzymatic catalysis 11 or microbial transformation 12 , 13 . The whole process enables an energy efficiency four-fold higher than natural photosynthesis, representing an energy-efficient approach for food ingredient production 14 . In the past several years, there have been continuous breakthroughs in CO 2 electro-conversion to ensure the production of pure acetate at a CO 2 fixation rate dramatically higher than natural photosynthesis 12 , 15 . The subsequent conversion of acetate to starch, however, demands microbes capable of synthesizing and accumulating starch at a superior-to-nature rate and content. The food-safe yeast Yarrowia lipolytica strain 16 , which could naturally assimilate acetate 17 and produce a variety of health-relevant molecules at high levels 18 – 20 , is an excellent chassis strain to develop as an efficient producer of starch-rich micro-grain. Herein, we reconfigure the oleaginous yeast to an efficient workhouse for starch biosynthesis by rewiring the starch biosynthesis and gluconeogenesis pathways, and regulating cell morphology (Fig. 1 ). The engineered strains lay the foundation to understand the natural and remodeled machinery for starch biosynthesis, and facilitate a superior-to-nature high-level production of starch with customized composition. Fig. 1 Design of an artificial yeast cell factory to facilitate the efficient starch synthesis from carbon dioxide. Acetate electro-synthesized from carbon dioxide was used as feedstock for starch synthesis by synthetic yeast Yarrowia lipolytica , which was systematically reprogrammed to accumulate high-level starch. The mechanism supporting the high-level starch biosynthesis was clarified, and the microbial starch production from the natural photosynthesis byproduct, straw, was demonstrated. CO 2 carbon dioxide, Ac-CoA acetyl-CoA, TCA tricarboxylic acid, GNG gluconeogenesis, Glu glucose, FAc-CoA fatty acyl-CoA. [Created in BioRender. Shi, Z. (2025) https://BioRender.com/x81f786 ].",
"discussion": "Discussion Here, we engineered cell metabolism and morphology to transform oleaginous yeast Y. lipolytica cell to starch-rich micro-grain and established an arable land-independent route for the high-level production of customized starch through low-carbon microbial manufacturing. The established process combined engineered yeasts and electricity to convert CO 2 to starch, highlighting the superior efficiency of the hybrid electrochemical-bioconversion approach 26 . The process directly generated starch-rich micro-grain in comparison to the kernel, which is a part of the crop biomass, presenting an ~50 time (243.7 vs. <6.4 g/m 2 /d) higher spatial-temporal productivity and 8.1 time higher energy efficiency than the crop planting: >2.82% vs. solar-to-corn kernel efficiency 0.31% 14 . The high starch content in micro-grain cultivated with short-chain carbon (C1-C4) feedstock, 47.18%, was achieved through a synthetic biology-driven strain customization, which mimicked the crop domestication at a much faster rate (months vs. thousand years). As a supplementary alternative to the traditional reverse genetics approach to understanding natural starch biosynthesis machinery in plants, our work demonstrates a build-to-learn means to dissect the key regulators and molecular mechanisms determining macromolecule synthesis and cell fate. In creating artificial cells accumulating high-level starch via the C2-C3-C6-C6n bioconversion pathway, we highlighted the essentiality of high-level expression of SBP genes and combinatorial manipulation of conserved gluconeogenesis pathway in ensuring efficient starch biosynthesis. In addition, our work dissect that global metabolism remodeling, cellular resource reallocation (together with previous studies 27 – 29 ), and cell size regulation were generally applicable strategies to determine macromolecule accumulation and composition. More importantly, in contrast to the fact that the above-mentioned processes were complicatedly interconnected with seedling growth and controlled by various genes in crops 30 – 32 , those processes can be modulated by manipulation of limited genes, enabling the easiness to allow for a much faster innovation speed for iterative micro-grain improvement. Via the systematic engineering of yeast cells and cultivation condition control, we obtained a variety of micro-grains with different macromolecules (starch-protein-lipid ratio) and starch compositions, which could be readily incorporated into downstream application (Supplementary Discussion 1 ). We prospect that, with the increasingly gained knowledge and development of synthetic biology tools, it will soon be possible to modulate specific features of the micro-grain ingredient (such as starch hardness, stickiness, and gelatinization) and even develop micro-grain to desired full-nutrient food resource, for instance, customized nutritional powder. Additionally, further technological advancements and resource integration are needed to address the high cost of the CO 2 -acetate-starch route at this stage (Supplementary Discussion 2 and 3 , Supplementary Method 1 ) and improve the process efficiency and scalability."
} | 1,880 |
32637739 | PMC7317171 | pmc | 6,690 | {
"abstract": "Nature has achieved materials with properties and mechanisms that go far beyond the current know-how of the engineering-materials industry. The remarkable efficiency of biological materials, such as their exceptional properties that rely on weak constituents, high performance per unit mass, and diverse functionalities in addition to mechanical properties, has been mostly attributed to their hierarchical structure. Key strategies for bioinspired materials include formulating the fundamental understanding of biological materials that act as inspiration, correlating this fundamental understanding to engineering needs/problems, and fabricating hierarchically structured materials with enhanced properties accordingly. The vast, existing literature on biological and bioinspired materials can be discussed in terms of functional and mechanical aspects. Through essential representative properties and materials, the development of bioinspired materials utilizes the design strategies from biological systems to innovatively augment material performance for various practical applications, such as marine, aerospace, medical, and civil engineering. Despite the current challenges, bioinspired materials have become an important part in promoting innovations and breakthroughs in the modern materials industry.",
"introduction": "1 Introduction Biological materials are ingeniously designed and optimized tools that are employed by nature for organisms to survive and thrive within challenging environments [ [1] , [2] , [3] , [4] ]. They represent the elegant strategies that fulfill a variety of not only mechanical but also functional needs [ 2 , 5 , 6 ], as they are generally simple in composition but efficient in performance [ [7] , [8] , [9] ]. This is distinct from most engineering materials that usually depend on complex chemicals or expensive manufacturing, and therefore often confront a tradeoff between properties (e.g., increasing weight to increase strength). Thus, biological materials have been an endless source of inspiration for developing novel materials and structures in recent decades. To actuate this inspiration, the first fundamental step requires revealing structure-property mechanisms and formulating systematic theories, which is known as Biological Materials Science [ 4 , [10] , [11] , [12] ]. This paves the road for the next exciting step of creating new advanced materials by providing essential insights with heretofore unexploited strategies from natural designs. Along with this research rapidly developing to be at the frontier is the ever-expanding understanding and knowledge of biological materials themselves. By utilizing exquisite structures instead of chemical complexity, biological materials surpass their synthetic counterparts in many properties and functions. The key to efficiently secure these outstanding properties lies in their hierarchical structure [ [1] , [2] , [3] , 8 , 13 ]. For mechanical performance, this significantly amplifies the properties of the weak constituents, e.g., the shell nacre has high Young's modulus (70–80 GPa), high tensile strength (70–100 MPa) and high fracture toughness (4–10 MPa m 1/2 ) [ [14] , [15] , [16] ], although it is composed mostly of brittle minerals (at least 95% by volume [ 17 ]) that show a work of fracture that is about 3000 times less than that of the shell [ 16 , 18 ]. Meanwhile, hierarchical structures enable biological materials to achieve substantially higher performance per unit mass, e.g., the spider silk has a tensile strength of 1.1 GPa, which is comparable to that of high-strength steel (1.5 GPa) [ 19 ]; but considering the density (1.3 g/cm 3 versus 7.8 g/cm 3 [ 20 , 21 ]), the spider silk is more than four times stronger per unit mass. These have led to an increasing number of bioinspired high-performance structural materials, e.g., nacre-inspired strong and tough materials [ 22 ] and crustacean-inspired fracture-resistant composites [ 23 ]. In addition to their mechanical performance, biological structures also generate a diversity of interesting functions. For examples, lotus leaves have special surface topographies that allow self-cleaning [ 24 ], gecko feet employ a hierarchical structure that enables them to scale walls through dry adhesion [ 25 ], the beautiful colors of butterflies are realized by their microstructure interacting with light [ 26 ], and the fibrous structure of many plants leads them to self-deform with changes in humidity [ 27 ]. These intriguing functions obtained through the structures of relevant biological materials are reliable, durable, and nontoxic as additional advantages, and thus have been inspiring to functional materials for a variety of practical applications, e.g., high-performance bioinspired anticorrosion coatings [ 28 ], gecko-inspired high adhesion pads [ 29 ], nature-inspired reversible underwater adhesives [ 30 ], and bioinspired self-shaping composites [ 31 ]. In an aim to highlight the rapid, exciting development of this field in a way that is distinct from existing reviews (in which biological and bioinspired designs focusing on certain properties are usually discussed separately), this work addresses bioinspired materials from a vast number of fascinating biological materials in terms of functional and structural categories. Within each category, representative types of functions (superwettability, bioactivity, stimuli-responsiveness) and mechanical properties (light-weight and high-strength, light-weight and high-toughness) are detailed through paradigmatic biological and bioinspired materials. We illustrate the fundamentals for the specific property, then we discuss the insights in structure-property mechanisms from biological materials and their corresponding bioinspired materials that show exceptional functions/properties for relevant applications. We also provide our perspectives on the challenge and prospect of biological and bioinspired designs to further promote the development of advanced functional and structural materials."
} | 1,511 |
31459872 | PMC6648567 | pmc | 6,692 | {
"abstract": "The\npreparation of superhydrophobic textiles with high mechanical\nand chemical durability is challenging. Here, facile and fluorine-free\nmethods, using alkali and plasma-etching treatments, followed by the\naddition of silica nanoparticles and tetraethyl orthosilicate (TEOS),\nwere used to prepare superhydrophobic cotton surfaces. With different\ninput variables and etching techniques, superhydrophobic cotton fabrics\nwith high chemical and mechanical durability were successfully prepared,\nwith contact angles up to 173°. A control of the surface architecture\nat the nanoscale in combination with a homogeneous repellent layer\nof TEOS in the cotton surface was achieved. The repellent properties\nof the as-prepared cotton remain stable under accelerated laundering\nand abrasion test conditions. The etching pretreatment by alkali or\nplasma plays a key role in obtaining superhydrophobic cotton surfaces.",
"conclusion": "3 Conclusions Superhydrophobic cotton fabrics with contact angles up to 173°\nwere successfully prepared using 7 nm silica nanoparticles and a silane-based\nwater-repellent agent, TEOS, in combination with two etching pretreatment\nmethods dealing with alkali and plasma approaches. This exceptionally\nhigh value of contact angle can be explained by several reasons: (i)\nthe alkali and plasma pretreatments lead to a homogeneous rough surface\nthat enhances the hydrophobicity of the cotton fibers and (ii) the\nuse of ultrasmall 7 nm silica nanoparticles leads to the creation\nof a double hierarchical scale on the cotton surface, which confines\nthe contact liquid droplet on the surface without penetration to the\ncellulose substrate. The two etching methods used are equally effective. Our finding shows that the amount of silica nanoparticles and TEOS\nare key parameters that directly affect the superhydrophobility behavior\nof the treated cottons and, thus, display a high resistance to both\nlaundering and abrasion tests. The contact angle remains stable after\n30 cycles of abrasion and 40 h of washing in hot water with a detergent.\nThese cotton fabrics exhibit potential applications in various fields\nsuch as oil/water filtration and functional protective clothing with\nself-cleaning and repellent properties to contaminants such as chemicals\nor aqueous pesticides.",
"introduction": "1 Introduction Superhydrophobic\nsurfaces and coatings have received great attention\nfrom both industrial manufacturers and scientists because of a wide\nrange of applications due to their anticorrosion, 1 − 3 antiwear, 4 , 5 antibacterial, 6 − 11 antifungal, 12 − 14 self-cleaning, 15 − 20 solar-reflective 21 − 23 and photocatalytic properties. 24 − 31 Superhydrophobic textiles 32 , 33 with self-cleaning\nproperties have been generated by making a double structure at two\ndifferent scales, characterized by the surface roughness of their\nmicrostructures and nanostructures, covered by hydrophobic substances\non the top surface. 34 − 36 These approaches have led to the formation\nof surfaces that exhibit\nlarge contact angles (greater than 150°) or low-contact-angle\nhysteresis (lower than 10°) for use in specific applications. 33 , 37 Water drops deposited on superhydrophobic surfaces are not absorbed,\nbut they move on the surface, carrying away residual matters on their\nway, like dust and contaminants. Wenzel 38 and Cassie–Baxter 39 suggested\nthat hydrophobic properties are related to the presence of a microstructure\nat the surface. More specifically, Cassie–Baxter’s law\nconsiders that the water droplets form spheres and reside on the surface\nof the fibrous microstructure, remaining at the top of the asperities,\nforming air pockets between the water droplet and the surface. 40 The incorporation of nanomaterials in\ntextiles can provide new\nand unexpected properties such as antistaining, water repellence,\nwrinkle freeness, static elimination, electrical conductivity, and\nantibacterial characteristics without compromising their comfort and\nflexibility. 41 For water-repellent properties,\nmost recent approaches are mainly based on covering the textile surface\nby nanoparticles 42 − 46 followed by a chemical treatment with water-repellent agents. 47 Rough surfaces have been obtained by introducing\ninorganic nanoparticles such as SiO 2 , 48 TiO 2 , 49 and ZnO 50 by the sol–gel methods. Fluorinated materials\nhave been coated on textile fibers due to their low surface energy\nand repulsive properties to oil and water. 41 , 51 Cotton has often been used in the manufacture of clothing fabrics\ndue to its characteristics including softness, comfort, flexibility,\nhydrophilicity with high absorption capacity, and low cost. 52 Thanks to the large number of hydroxyl groups\non its surface, 53 cotton can be readily\ncolored and modified by physical 54 and\nchemical methods. 55 We report, here,\nfacile and fluorine-free methods to prepare superhydrophobic\ncotton fabrics by a dip-coating technique using chemical and physical\netching treatments of the fiber followed by the deposition of silica\nnanoparticles and tetraethyl orthosilicate (TEOS). By controlling\nthe etching conditions and input variables, superhydrophobic cotton\nfabrics were successfully prepared with contact angle values up to\n173°. These fabrics display excellent resistance to chemical\nand mechanical aggressors due to the covalent bonds formed between\nthe cotton surface and TEOS. The morphology of the as-prepared superhydrophobic\ncottons was revealed by using mainly the scanning electron microscopy–energy-dispersive\nX-ray analysis (SEM–EDXA) technique. These treated cotton fabrics\nexhibit improved performance compared to existing ones where either\ndurability or superhydrophobicity is lacking.",
"discussion": "2 Results\nand Discussion 2.1 Wettability Table 1 describes the conditions\nof the preparation\nof the samples reported in this article, whereas Figure 1 shows the corresponding water\ncontact angles (WCA) measurements. First, SiO 2 (8 wt %)\nand TEOS (10 wt %) one-step dip-coating treatment was applied to a\nfabric that had not been subjected to a chemical or plasma-etching\npretreatment (but they were washed with water and ethanol). As shown\nin Table 1 , line a,\nand Figure 1 a, this\nprocess gives a low WCA of 91°. Figure 1 Contact angles of cotton fabric treated\nin different conditions\nas shown in Table 1 : (a) corresponds to conditions in line a 1 ; (b) corresponds to conditions in line b 1 ; (c) corresponds to conditions in line c 1 ; (d) corresponds to conditions in line d 1 ; (e) corresponds to conditions in line e 1 ; (f) corresponds to conditions in line f 1 and (g) corresponds to conditions in line g 1 . Table 1 Treatment Conditions\nfor Cotton Fabrics\nby One-Step (a) and Two-Step (b–f) Procedures samples pretreatment solution A step 1 solution B step 2 contact angle\n(deg) a water/ethanol SiO 2 (8%) + water (300 mL) + acetic acid (2 mL) TEOS (10%) 91 ± 1 b NaOH (0.5 M) SiO 2 (8%) TEOS (10%) 147 ± 1 c NaOH (0.5 M) SiO 2 (10%) TEOS (10%) 152 ± 1 d NaOH (0.5 M) SiO 2 (12%) TEOS (10%) 160 ± 2 e NaOH (0.5 M) SiO 2 (12%) TEOS (15%) a 173 ±2 f plasma SiO 2 (12%) TEOS (15%) a 173 ± 2 g plasma SiO 2 (12%) 2 wt % of acrylic resin TEOS (15%) a 167 ± 2 a Exceptionally,\nsolution B was prepared\nin benzene instead of toluene. Upon chemical pretreatment with NaOH, followed by dip-coating in\nsolution A with 8 wt % SiO 2 and in solution B with 10 wt\n% of TEOS, Table 1 ,\nline b and Figure 1 b, there is a jump of the WCA to 147°, indicating that etching\nis required to retain sufficient SiO 2 and TEOS on the fiber\nto improve the hydrophobicity. Similar processes with slightly higher\namounts of SiO 2 (10 and 12 wt %) ( Table 1 , lines c and d, and Figure 1 c,d) lead to a slight improvement in WCA\nof 152 and 160°, respectively. Another experiment, Table 1 , line e and Figure 1 e, was developed\nkeeping the SiO 2 concentration\nat 12 wt % but increasing the TEOS concentration to 15 wt %; this\ncontent further improves the values of WCA to a high value of 173°.\nA second set of experiments was developed by etching the fabric by\nplasma treatment, instead of chemicals. When keeping the SiO 2 and TEOS concentrations at the same value as in Figure 1 e, Table 1 , line f and Figure 1 f, a similar value of WCA of 173° is\nobtained, indicating that the chemical and plasma treatments are equally\neffective. Finally, etching again by plasma, keeping the SiO 2 and\nTEOS concentrations at 12 and 15 wt %, respectively, as in the previous\ncase, but adding this time 2 wt % of an acrylic resin to solution\nA, Table 1 , line g\nand Figure 1 g, a small\ndecrease of the contact angle from 173 to 167° is observed. These exceptionally high values of WCA, particularly under conditions\n1e and 1f, can be attributed to the fact that the pretreatment of\nthe fiber surface by etching with NaOH solution or plasma creates\na rough microstructure. Then, a homogeneous distribution of nanoparticles\nat the submicrometer level, covered by a thin layer of TEOS, leads\nto the super repellent properties of the cotton fibers. 2.2 Surface Morphology and Self-Cleaning Properties To\nbetter understand the superhydrophobicity behavior observed\nin the previous section, high-resolution SEM images were obtained\nfrom the fiber surface. Figure 2 shows examples of the SEM images of untreated and treated\ncotton fibers by different methods. It can be seen that untreated\nfibers are smooth ( Figure 2 a). However, the etching pretreatment with sodium hydroxide\nleads to an increase of the rugosity of the cotton fibers ( Figure 2 b) due to the extraction\nof low-molecular-weight materials and lignin present in them. A similar\nrough cotton surface is observed after plasma treatment ( Figure 2 c) due to the electron\nbombardment, also leading to the removal of impurities and low-molecular-weight\nspecies. Figure 2 SEM images of (a) untreated cotton, (b) chemically treated cotton,\nand (c) plasma-treated cotton. The SEM images after the deposition of SiO 2 nanoparticles\nand repellent TEOS are shown in Figure 3 . A SEM image of cotton treated by the one-step procedure\nis used as a reference ( Figure 3 a). It can be seen that this process leads to a large number\nof aggregates of SiO 2 on the cotton surface. These aggregates,\nwith dimensions of the order of several microns, are more clearly\nobserved at the lower-magnification image (red arrows). Figure 3 b presents the SEM image of\ncotton treated with 8 wt % SiO 2 nanoparticles as described\nin Table 1 , line b.\nThe increase of the nanoparticles content in solution A leads to a\nhigher density of nanoparticles on the cotton surface ( Figure 3 c–e). The pretreatment\nwith plasma ( Figure 3 f), followed by nanoparticles and TEOS depositions, also leads to\naggregates having similar density to those obtained with chemical\ntreatment ( Figure 3 e). In all cases, there is a homogeneous distribution of nanoparticles\non the fiber surface. The addition of acrylic leads to homogeneous\nnanoparticles on the cotton fiber surface, and the acrylic resin can\nbe observed from the SEM image ( Figure 3 g). The chemical or plasma pretreatments create a rough\nsurface and, presumably, functional groups to enhance the reaction\nbetween cotton surface and SiO 2 nanoparticles. Figure 3 SEM images\nof treated cotton by the one-step (a) and two-step (b–g)\nprocedures. Details of the treatment conditions are shown in Table 1 , i.e., pictures (a–g)\ncorrespond to lines a–g of Table 1 . Figure (a1) show an example of SiO 2 agglomeration of cotton fiber treated by the one-step approach. The semiquantitative elemental\nanalysis of a plasma-treated cotton\nis shown in Figure 4 . This figure first shows by SEM ( Figure 4 a) a relatively homogeneous distribution\nof silicium nanoparticles on the cotton fiber surfaces, as it was\nfound in Figure 3 a. Figure 4 b, and confirmed\nby elemental analysis, shows the presence of nanoparticles on the\nwhole fiber surface, mainly distributed at the submicrometer scale.\nA separate mapping image for silicium ( Figure 4 c) provides a direct observation of the distribution\nof this element on the treated cotton surface; SiO 2 nanoparticles\nare found on the whole cotton surface, and they are well distributed\nwithout aggregation. In other words, the concentration of nanoparticles\nused is suitable to form a homogeneous layer of SiO 2 on\nthe surface of cotton. Figure 4 NaOH-treated cotton fabric (sample e, Table 1 ): (a) SEM image, (b) elemental\nanalysis\nimage, and (c) silicium mapping of a cotton fiber surface. The repellent behavior of treated cotton fabric\nto different liquids\nthat have lower values of surface tension than pure water, 56 − 58 including coffee, ice tea, diluted ketchup, Coca-Cola, and dyed\nwater, was also investigated. Figure 5 a,b shows the photos of different liquids sitting on\nthe treated cotton surface. They have a spherical form and have not\npenetrated the treated cotton structure, meaning that the cotton exhibits\na superhydrophobility not only for water but also for these liquids.\nThe self-cleaning properties of the cotton were verified with a natural\ncolorant (turmeric nanopowder): 2 g of turmeric powder was deposited\non 2 cm 2 nontreated ( Figure 5 c) and alkali-treated cotton surfaces ( Figure 5 d). They were then wetted by\n2 mL of distilled water drops for 30 s. In the case of untreated cotton,\nthe water drops are rapidly absorbed by the cotton fabric, carrying\nthe colorant inside the fabric structure ( Figure 5 e). However, in the case of the alkali-treated\ncotton, the water droplets were not absorbed by the fabric, and they\ncarry the colorant away from the cotton surface as can be seen in Figure 5 f. Figure 5 Photos of different liquids\ndeposited on a NaOH-treated cotton\nsurface (sample e, Table 1 ): (a) coffee, tea, diluted ketchup, and Coca-Cola; (b) water\n+ dye (5 wt %); (c–f) photos of a natural colorant of turmeric\nnanopowder deposited on an untreated cotton and alkali-treated cotton\n(d). Before adding water drops in (c) and (d), the colorant is seen\nsitting on the fabric; after adding water drops, in (d), it is carried\ninside the fabric, whereas, in (f), it is washed away from the surface\nby the nonabsorbing water. 2.3 Mechanical and Laundering Durability For reuse purposes, treated cottons should be resistant to laundering\nconditions. The laundering of the treated cottons was carried out\nin hot water (60 °C) with and without detergent (2%). The subsequent\nmeasurements of contact angles as a function of laundering times of\ncotton treated with different methods are shown in Figure 6 a. This figure shows that the\ncontact angle decreases slightly after 40 h of treatment from 173°\n(±1) to 165° and from 172° (±1) to 167° with\ndip-coating and plasma-treatment methods, respectively, indicating\nthe stability of the treatment. The sample pretreated with plasma,\nfollowed by an acrylic resin treatment, shows a stable WCA after 40\nh of laundering. Figure 6 (a) Contact angle as a function of laundering times (2\nwt % detergent,\nhot water) and (b) abrasion cycles after different methods of treatments:\nchemical treatment (sample e, Table 1 ); plasma treatment (sample f, Table 1 ); and plasma treatment + acrylic resin coating\n(sample g, Table 1 ). The mechanical durability of the\nsuperhydrophobic coating on the\nfiber surface was investigated with an abrasion test, as described\nin the experimental section: the variation of the contact angle was\nfollowed during the abrasion cycles ranging from 1 to 40 ( Figure 6 b). The cotton shows\na reduction of 10% of WCA after 30 abrasion cycles in the case of\nalkali-treated (blue curve, Figure 6 b) and plasma-treated cotton fabrics (red curve, Figure 6 b). The pretreatment\nof the cotton with plasma, followed by the addition of acrylic resin\n(sample g, Table 1 ),\nleads to a slightly lower WCA, but the cotton exhibits higher resistance\nto abrasion compared to those without resin because their WCA value\nremains unchanged after applying 30 abrasion cycles (green curve, Figure 6 b). 2.4 Discussion The contact state of a\nliquid droplet on a textured surface can be described by Wenzel 38 and Cassie–Baxter 59 theories. In the first case, it is considered that the\nstructure can be wet by the liquid droplets due to their deep penetration\nof the textured surface. In contrast, the Cassie–Baxter model 59 supposes that there are air pockets between\nthe deposited liquids and the material surface, leading to a reduction\nof contact area and an increase in contact angle. Figure 7 shows the high-resolution\nSEM images of the surface of cotton fibers pretreated with alkali\n( Figure 7 a) and plasma\n( Figure 7 b), followed\nby the addition of dip-coated silica nanoparticles and TEOS layers.\nIt can be seen that both pretreatment methods lead to the formation\nof rugosity surface with a large quantity of cavities (holes) ( Figure 7 ). These holes were\nfound on the whole sample surface, with various dimensions ranging\nfrom several ten to a hundred nanometer (red arrows). This structure\nsupports the contacting liquid droplets in the Cassie–Baxter\napproach. Figure 7 High-resolution SEM images at the surface of cotton fibers treated\nby (a) NaOH (sample e, Table 1 ) and (b) plasma (sample f, Table 1 ). Red arrows show the presence of air pockets\non the surface of treated cotton fiber. In nature, lotus leaves are repellent to liquids because\nthey possess\na double hierarchical structure with bumps called papillae, covered\nby hydrophobic tubes at a scale of 100 nm. 60 In the literature, similar artificial superhydrophobic textures\nare usually obtained in two steps: the first step involves an etching\nprocess by chemical or physical methods, followed by the addition\nof layered hydrophobic compounds. In this work, two different\napproaches were used to obtain superhydrophobic\nsurfaces. In the first step (step 1, Figure 8 ), the cotton fibers were etched by chemical\nor physical means. It is well known that the cotton fibers are mainly\ncomposed of cellulose, hemicelluloses, lignin, and some impurities. 61 , 62 The alkali pretreatment partially removes lignin and impurities\non the fiber surface 63 and, thus, enhances\nthe surface rugosity ( Figure 2 b). The plasma etching leads to the removal of impurities\nfrom the fiber surface, resulting in a rough surface, as shown in Figure 2 c. In the second\nstep (step 2, Figure 8 ), a homogeneous deposition of silica nanoparticles by dip-coating,\nfollowed by the addition of a layer of superhydrophobic agent (TEOS),\nleads to a rough surface and water-repellent properties by creating\ncovalent bonds between the silane groups of TEOS and the hydroxyl\ngroups of the silica nanoparticles ( Figure 8 ). Figure 8 Schematic illustration of the preparation of\nsuperhydrophobic cotton\nfabric by alkali or plasma pretreatments. Moreover, the used cotton fabric is formed by a large number\nof\nknitted fibers with dimensions of 10–20 μm ( Figure 3 a–g), which\nare comparable with bumps on a lotus leaf at the scale of 10–20\nμm. 60 The choice of homogeneous and\nsmall nanoparticles (7 nm) and suitable dip-coating conditions (concentration\nof nanoparticles and immersion time) leads to a homogeneous distribution\nof nanoparticles with a double hierarchical scale of textures, as\nproven by SEM images ( Figure 3 e,f). This structure enhances the contact angle of liquid\ndroplets as schematically shown in Figure 9 . In other words, the liquid droplets exhibit\nhigher apparent contact angles on a double hierarchical structure\ncompared with surfaces with a single scale texture 56 (nontreated or treated only with nanoparticles). This is\nbecause air is trapped at a double length scale in a hierarchical\nstructure, whereas it is trapped only at one length scale in the surfaces\nwith a single texture. 56 Figure 9 Schematic illustration\nof liquid droplets deposited on superhydrophobic\ncotton.\n\n2.4 Discussion The contact state of a\nliquid droplet on a textured surface can be described by Wenzel 38 and Cassie–Baxter 59 theories. In the first case, it is considered that the\nstructure can be wet by the liquid droplets due to their deep penetration\nof the textured surface. In contrast, the Cassie–Baxter model 59 supposes that there are air pockets between\nthe deposited liquids and the material surface, leading to a reduction\nof contact area and an increase in contact angle. Figure 7 shows the high-resolution\nSEM images of the surface of cotton fibers pretreated with alkali\n( Figure 7 a) and plasma\n( Figure 7 b), followed\nby the addition of dip-coated silica nanoparticles and TEOS layers.\nIt can be seen that both pretreatment methods lead to the formation\nof rugosity surface with a large quantity of cavities (holes) ( Figure 7 ). These holes were\nfound on the whole sample surface, with various dimensions ranging\nfrom several ten to a hundred nanometer (red arrows). This structure\nsupports the contacting liquid droplets in the Cassie–Baxter\napproach. Figure 7 High-resolution SEM images at the surface of cotton fibers treated\nby (a) NaOH (sample e, Table 1 ) and (b) plasma (sample f, Table 1 ). Red arrows show the presence of air pockets\non the surface of treated cotton fiber. In nature, lotus leaves are repellent to liquids because\nthey possess\na double hierarchical structure with bumps called papillae, covered\nby hydrophobic tubes at a scale of 100 nm. 60 In the literature, similar artificial superhydrophobic textures\nare usually obtained in two steps: the first step involves an etching\nprocess by chemical or physical methods, followed by the addition\nof layered hydrophobic compounds. In this work, two different\napproaches were used to obtain superhydrophobic\nsurfaces. In the first step (step 1, Figure 8 ), the cotton fibers were etched by chemical\nor physical means. It is well known that the cotton fibers are mainly\ncomposed of cellulose, hemicelluloses, lignin, and some impurities. 61 , 62 The alkali pretreatment partially removes lignin and impurities\non the fiber surface 63 and, thus, enhances\nthe surface rugosity ( Figure 2 b). The plasma etching leads to the removal of impurities\nfrom the fiber surface, resulting in a rough surface, as shown in Figure 2 c. In the second\nstep (step 2, Figure 8 ), a homogeneous deposition of silica nanoparticles by dip-coating,\nfollowed by the addition of a layer of superhydrophobic agent (TEOS),\nleads to a rough surface and water-repellent properties by creating\ncovalent bonds between the silane groups of TEOS and the hydroxyl\ngroups of the silica nanoparticles ( Figure 8 ). Figure 8 Schematic illustration of the preparation of\nsuperhydrophobic cotton\nfabric by alkali or plasma pretreatments. Moreover, the used cotton fabric is formed by a large number\nof\nknitted fibers with dimensions of 10–20 μm ( Figure 3 a–g), which\nare comparable with bumps on a lotus leaf at the scale of 10–20\nμm. 60 The choice of homogeneous and\nsmall nanoparticles (7 nm) and suitable dip-coating conditions (concentration\nof nanoparticles and immersion time) leads to a homogeneous distribution\nof nanoparticles with a double hierarchical scale of textures, as\nproven by SEM images ( Figure 3 e,f). This structure enhances the contact angle of liquid\ndroplets as schematically shown in Figure 9 . In other words, the liquid droplets exhibit\nhigher apparent contact angles on a double hierarchical structure\ncompared with surfaces with a single scale texture 56 (nontreated or treated only with nanoparticles). This is\nbecause air is trapped at a double length scale in a hierarchical\nstructure, whereas it is trapped only at one length scale in the surfaces\nwith a single texture. 56 Figure 9 Schematic illustration\nof liquid droplets deposited on superhydrophobic\ncotton."
} | 5,950 |
27322185 | PMC4913940 | pmc | 6,694 | {
"abstract": "Theoretical studies have indicated that nestedness and modularity—non-random structural patterns of ecological networks—influence the stability of ecosystems against perturbations; as such, climate change and human activity, as well as other sources of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks, and found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. Although our findings are preliminary owing to data-analysis limitations, they enhance our understanding of the effects of environmental change on ecological communities.",
"introduction": "Introduction Many species interact with one another via antagonistic (e.g., prey–predator) and mutualistic (e.g., plant–pollinator) relationships, and they compose ecological communities that are often represented as networks [ 1 , 2 ], or ecological networks . Ecological networks are important not only in the context of basic scientific research (e.g., structure–stability relationships [ 1 , 3 – 6 ]), but also in the context of applied ecology (e.g., biodiversity maintenance, environmental assessment [ 1 , 3 , 4 ]); thus, ecological networks have been studied from a complex network perspective for decades, inspired by the development of network science [ 7 , 8 ]. In addition, a significant amount of data on real-world ecological networks have been collected and are available from such sources as GlobalWeb [ 9 ], the Interaction Web DataBase, and the Web-of-Life Database, among others (see also Materials and Methods ). Empirical ecological networks are known to display two non-random structural patterns. One is nested architecture ( nestedness ) [ 10 ], a hierarchical structure in which the interaction pairs of a specialist species are included in those of another (generalist) species. The other is modular structure ( modularity ) [ 11 ], a compartmentalized structure in which a number of dense sub-networks (modules) are weakly interconnected. Modularity is also a significant property of biological systems [ 12 ], such as signaling [ 13 ] and metabolic [ 14 – 16 ] networks. Although these two structural patterns generally correlate with each other, the direction and magnitude of the correlation differ depending on network type and the level of connectedness (connectance or graph density); thus, these structural patterns provide complementary information on how interactions are organized in communities [ 17 ]. The degree of nestedness and modularity vary between antagonistic networks (e.g., food webs) and mutualistic networks (e.g., plant–pollinator networks); the modularity of mutualistic networks is typically lower than that of antagonistic networks, whereas the nestedness of mutualistic networks is generally higher than that of antagonistic networks [ 5 , 10 ]. Furthermore, studies have shown that nestedness and modularity influence ecosystem dynamics; in particular, nestedness plays important roles in increasing mutualistic-network stability [ 18 – 22 ]. Moreover, Thébault and Fontaine [ 5 ] demonstrated that both nestedness and modularity influence ecosystem stability (i.e., persistence and resilience against perturbations). The contributions of nestedness and modularity to ecosystem stability differ between mutualistic and antagonistic networks, in that increasing nestedness and/or decreasing modularity enhance the stability of mutualistic networks but reduce the stability of antagonistic networks (i.e., food webs). In this context, the effects of environmental or external factors on ecological networks are also important. Given that environmental factors can be sources of perturbation (e.g., rainfall, seasonal variation of climate), it would be expected that ecological networks have an optimal structure that maximizes ecosystem stability against such perturbations. Thus, nestedness and modularity change in response to environmental perturbations because they largely determine ecosystem stability [ 5 ]. The importance of environmental factors are often discussed in the context of ecosystem stability [ 23 , 24 ]; many previous studies [ 25 , 26 ] have focused on the association between the environment and ecological network structure, with several focusing specifically on the influence of the environment on nestedness/modularity. Several studies [ 27 – 30 ] have reported the relationship between climatic parameters and nestedness and modularity in mutualistic networks and food webs; for example, nestedness in pollination networks was found to decrease with annual precipitation [ 27 ], whereas modularity in seed-dispersal networks increased with temperature seasonality [ 28 ], and a positive correlation between modularity and precipitation seasonality was observed in food webs [ 29 ]. Previously [ 29 ], we demonstrated that climate seasonality affects ecological networks, and that the type of climatic seasonality influencing network structure differs among ecosystems; for example, network properties in freshwater ecosystems were mainly affected by rainfall seasonality but primarily by temperature seasonality in terrestrial ecosystems. Climate change and human activities are also major sources of environmental perturbations, and given that nestedness and modularity are expected to change in response to environment perturbations, climate change and human impacts are thus also expected to affect ecological network structure. Dalsgaard et al. [ 31 ], for instance, reported that modularity and nestedness in pollination networks correlated with the historical rate of warming, and Sebastián-González et al. [ 32 ] demonstrated that modularity declined and nestedness increased in seed-dispersal networks in response to human impacts (e.g., human population density, land use, infrastructure development, and so forth). Such results imply that mutualistic networks are flexible and can change in response to climate change and human activities in order to improve ecosystem stability. Despite this pioneering research, the impacts of climate change and human activities on ecological networks remain poorly understood, especially with respect to the human impact on pollination networks. Moreover, macro-ecological studies [ 28 , 31 , 32 ] have overwhelmingly focused on the impacts of climate change and human activities on mutualistic networks (i.e., pollination and seed-dispersal networks), and not food webs, for which there has been comparatively little research (e.g., the effect of human activities on prey–predator interactions at a local scale [ 33 ] and over a broader marine region [ 34 ]). We therefore constructed a larger dataset of ecological networks—including food webs, pollination networks, and seed-dispersal networks—and used spatial analysis to investigate the effects of climate change and human activities on these networks.",
"discussion": "Discussion Here, we examined the non-random structural patterns (i.e., nestedness and modularity) of ecological networks based on data collected from several global datasets, and demonstrated that human impacts and climate change affect nestedness and modularity in a range of ecological networks, including food-web, pollination, and seed-dispersal networks. In pollination networks, human impacts were positively correlated with nestedness and negatively correlated with modularity, and modularity declined with temperature-change velocity in seed-dispersal networks. In theory [ 5 ], an increase in nestedness and/or decrease in modularity improves ecosystem stability; thus, these results are an indication that mutualistic networks form in such a way as to enhance ecosystem stability against environmental changes or perturbations. Moreover, nestedness increased and modularity decreased in response to temperature-change velocity in food-web networks. Unlike in mutualistic networks, however, decreasing nestedness and/or increasing modularity enhance ecosystem stability in antagonistic networks (i.e., food webs); as such, our results suggest that food-web stability decreases in response to environmental changes. Additional research is required, however. For example, we estimated climate-change velocities based on the difference between the current and last glacial maximum climate conditions (Materials and Methods), as was done in previous studies [ 28 , 31 , 32 ]. However, the time-scale of these velocities may be too long in terms of ecological-network assemblies; a possible reason was discussed in a previous study [ 31 ], but briefly, this may be because of the most important climatic shift in the Quaternary (past 2.6 million yr). In particular, glacial cold maxima and warm interglacials were periodically repeated during this period, and the most recent, and one of the strongest, climatic shift occurred between last glacial maximum (21,000 yr bp) and the present. This recent shift has been shown to have influenced geographical patterns of species endemism, for example [ 35 ], suggesting that species composition (and ecological-network assemblies, as a result) are more unstable in areas that have experienced larger climatic shifts. However, it is also important to consider short-range climate-change velocity. In this context, a new index [ 36 ] of the velocity of temperature change, derived from spatial gradients and multi-model ensemble forecasts of rates of temperature increase over the 21 st century, may be useful. Alternative hypotheses must also be considered, especially in regard to the relationship between current climate and ecological networks. In food-web networks, for example, modularity increased with precipitation seasonality; given that climate seasonality can be considered as an environmental perturbation [ 29 ], the observed associations suggest that food webs vary to increase ecosystem stability against climate seasonality, consistent with predictions. A number of food-web networks included in this study derived from freshwater and estuarine areas; thus, that precipitation seasonality has an effect on network structure may be a reasonable supposition [ 29 ]. In short, these results imply that ecological networks may be generally adapted to changing environmental conditions. The results presented here are at least somewhat inconsistent with those of previous research on mutualistic networks. For example, one study [ 32 ] reported an association between nestedness/modularity and human impacts in seed-dispersal networks, whereas no relationship was observed here. The results of another study [ 31 ] indicated that nestedness and modularity are associated with temperature-change velocity in pollination networks, but again, no such relationships were observed in this study (Tables 1 and 2 ). These discrepancies may be due to the different datasets used in this study and those used in previous studies; for instance, the dataset on pollination used in our study ( n = 62) is larger than that used in a previous study [ 31 ] ( n = 54); moreover, the similarity of the datasets was low [Jaccard index (JI) of approximately 0.4 (35/81)]. Although the number of seed-dispersal networks is almost similar between this study ( n = 30) and the previous study [ 32 ] ( n = 34), the similarity of the datasets was low [JI ≈ 0.5 (21/43)] because the previous study included unpublished data. In addition, the discrepancy may also be partially attributed to methodological differences. For example, the previous study [ 31 ] did not consider climate seasonality and human impacts, and was based on a unipartite version of modularity despite pollination networks traditionally represented as bipartite networks. Moreover, they did not consider the standardization of nestedness (NODF), although the Z -score (i.e., standardization) allows comparisons of networks with different levels of connectivity (i.e., connectivity or matrix fill strongly affects NODF) [ 37 ]. As pointed out in our earlier study [ 29 ], the conclusions we reached here are limited to binary (i.e., unweighted) networks. However, it is also important to consider weighted network analysis, as a different conclusion may be derived from comparisons between weighted networks and binary networks. For example, nestedness is statistically significant in binary networks, but not in weighted networks [ 38 ], and temperature seasonality was correlated with the weighted version of modularity, but not with the binary version of modularity [ 28 ]. Nevertheless, binary networks were considered in this study because the datasets we used include numerous binary data (Materials and Methods). Moreover, the definition of interaction weight is not uniform throughout the ecological-network datasets. The interaction weight assigned to a given species pair is based on the number of contacts they share; however, the weight need to be corrected (or normalized) for factors such as sampling effort and species abundance. Such normalization methods differ among studies. Therefore, we assumed a binary network approach to represent all ecological networks in order to avoid issues resulting from these variations. Definitions for nestedness and modularity also vary, although here we focused on NODF and M for ease of comparison to previous studies. For nestedness, one previous study [ 38 ] used a spectral graph approach, and proposed the largest eigenvalue of a community matrix (mutualistic networks) for measuring nestedness, instead of using NODF-like nestedness indices. Moreover, the heterogeneity of degree distributions was shown to dominantly determine nestedness [ 39 ], network measures that may be useful as alternative indices for nestedness. The definition of modularity used in this study and in many previous studies is well known to have resolution-limitation problems [ 40 , 41 ]. We avoided this issue as much as possible by using a simulated-annealing algorithm, according to [ 41 ]; however, the conclusions reached in this study regarding network modularity are unavoidably limited. Although network modularity is useful for revealing functional architecture in ecological networks [ 42 ], the modules detected based on network topology may be inconsistent with biologically functional modules because the link weight and overlap of functional modules that are observed in real-world networks were not included in this study. To minimize these restrictions, module detection methods for weighted networks [ 28 ] and overlapping communities (e.g., [ 43 , 44 ]) may be useful because they more accurately predict functional modules. As mentioned in our previous study [ 29 ], our analysis has several limitations, as do many other analyses of ecological networks. For example, we examined antagonistic (i.e., food webs) and mutualistic networks separately despite a mixture of interaction types (i.e., antagonistic interactions and mutualistic interactions) being more representative of real-world ecosystems and thus ecosystem stability [ 3 , 4 ]. Therefore, measurements of network parameters for multiple network types need to be considered in the future in order to evaluate ecological networks under more realistic conditions. In particular, multiple network analysis, which is commonly used in social-network research, can take into consideration many different types of links [ 45 ]. It is possible that sampling effort affects nestedness and modularity when considering the species–area relationship [ 46 ], which states that the number of observed species increases with the observed area. In this study, we could not obtain the relevant information on sampling effort because it is not always clearly delineated in the literature. However, this limitation poses little problem because the effect of species number was removed from the statistical analysis, and earlier work [ 27 ] suggested that nestedness and modularity are mostly independent of sampling effort (observation area and observation time). In addition, we did not consider the effects of phylogenetic signals because species descriptions in the networks are partially unknown or ambiguous. However, the absence of phylogenetic signals is unlikely to have a significant effect, as several studies have reported that phylogenetic signals are weak in ecological networks [ 28 , 47 ]. Moreover, a restricted understanding of interspecific reactions (i.e., missing links) is a more serious limitation. To avoid these limitations, larger-scale and more highly normalized databases should be constructed, and it is especially important that data on weighted networks be expanded. In this context, data sharing [ 48 ] may be important. Although our conclusions must necessarily be considered preliminary due to these limitations, they may enhance our understanding of the effects of environmental change on ecological communities."
} | 4,355 |
37049680 | PMC10095725 | pmc | 6,695 | {
"abstract": "The conjugation of small-molecule semiconductors with self-assembling peptides is a powerful tool for the fabrication of supramolecular soft materials for organic electronics and bioelectronics. Herein, we introduced the benchmark organic semiconductor [1]benzothieno[3,2-b][1]-benzothiophene (BTBT) within the structure of a self-assembling amphipathic peptide. The molecular structure of the conjugate was rationally designed to favour π-π stacking between BTBT cores and π-delocalization within the self-assembled architectures. Hydrogels with fibrillar structure were obtained upon self-assembly. Spectroscopic studies confirmed that both hydrogen bonding between peptide segments and π-π stacking between BTBT chromophores are responsible for the formation of the 3D fibrillar network observed by transmission electron microscopy. The hydrogel was successfully deposited on gold interdigitated electrodes and a conductivity up to 1.6 (±0.1) × 10 −5 S cm −1 was measured.",
"conclusion": "4. Conclusions In summary, we successfully designed and synthesised a hybrid peptide, whose backbone incorporated the [1]benzothieno[3,2-b]benzothiophene (BTBT) small-molecule semiconductor. The hybrid peptide was effectively self-assembled in water to give self-supporting hydrogels upon pH-switching with a fibrillar structure. Spectroscopic studies confirmed the formation of β-sheet assemblies and revealed the presence of strong π-π interactions between BTBT cores, that result in π-delocalization. Such hybrid peptides showed high conductivity values, as high as 5.3 (±0.1) × 10 −7 S cm −1 , corresponding to low operational voltages (i.e., 0 < V < 1 V). Broadening the voltage range ( − 3 V < V < +3 V), we reached a conductivity value equal to 1.6 (±0.1) × 10 −5 S cm −1 . To the best of our knowledge, this conductivity value is one order of magnitude higher than state-of-the-art values reported in the literature related to non-gel BTBT-peptide hybrids. Such promising results pave the way towards interesting applications, where a soft, nanostructured, electrically-active and biocompatible material is required.",
"introduction": "1. Introduction Molecular self-assembly of small π-conjugated molecules (SCM) with optoelectronic properties is a powerful tool for the fabrication of feasible ordered nanoarchitectures for organic electronics [ 1 , 2 ]. In this context, the self-assembly of oligothiophenes [ 3 ] or p-phenylenevinylenes [ 4 ] has been explored extensively in the literature. In a common approach, the functionalization of the SCM with a specific self-assembling unit introduces additional non-covalent interactions and allows control over the supramolecular organisation. This approach leads to a robust and well-ordered supramolecular architecture in which the SCMs have specific positions, which in turn may affect the efficiency of electronic coupling. Due to its biocompatibility and ability to undergo self-assembly, the conjugation of biomolecules to SCM has been suggested as a powerful approach [ 5 ]. Among the various biomolecules capable of self-assembly into ordered supramolecular architectures [ 6 , 7 ], peptides [ 8 ], in particular short peptides [ 9 ], stand out for several reasons. Peptides are known to form well-ordered secondary structures through directional hydrogen bonds, and their self-assembling properties can be tuned by a proper selection of the amino acid sequence. For example, sequences that feature an alternation of hydrophilic and hydrophobic amino acids are known to favour the formation of 1D β-sheet structures [ 10 , 11 ]. Furthermore, peptides can be easily synthesised with a plethora of available natural and non-natural amino acids. In addition, they also offer biocompatibility [ 12 , 13 ] and the possibility of aqueous processing of the material [ 14 ]. In this context, supramolecular peptide hydrogels have been of particular interest in recent years [ 15 , 16 , 17 ]. Peptides self-assemble in water to give a 3D fibrillar network that entraps the solvent, yielding a gel. Thus, hydrogelation is a process that easily allows the fabrication of 1D supramolecular structures and soft materials for organic electronics [ 18 ]. Hydrogelation of peptide conjugates has been used successfully to obtain soft materials incorporating different SCM such as pyrene [ 19 , 20 ], oligothiophenes [ 21 ], naphthalene diimide [ 22 ], oligo-para(phenylenevinylene) [ 23 ], or diketopyrrolopyrrole [ 24 ]. Among SCMs, [1]benzothieno[3,2-b][1]-benzothiophene (BTBT) is a promising small-molecule p-type semiconductor [ 25 , 26 ]. Soluble dialkyl, monoalkyl and aryl derivatives allow for solution processes and combine solubility and high hole mobility featuring good thermal stability [ 27 , 28 , 29 , 30 ]. For example, Yuan et al. reported an impressive thin film transistor hole mobility of 43 cm 2 V −1 s −1 for the 2,7-dioctyl-substituted BTBT (C8-BTBT) [ 31 ]. Despite these important achievements, the development of water-processable and biocompatible BTBT derivatives remains an open challenge. Guler et al. were the first to report two amphiphilic BTBT peptide conjugates, in which BTBT was introduced at the N-terminus separated from the peptide sequence by a flexible linker [ 32 ]. These hybrid molecules self-assembled in water to form nanofibers that showed an average conductivity of 4.2 (±1.8) × 10 −6 S cm −1 and 2.4 (±0.47) × 10 −7 S cm −1 for the BTBT-peptide and the C8-BTBT-peptide, respectively. More recently, we reported the first BTBT-peptide hydrogel [ 33 ]. We functionalised the N-terminus of a β-sheet self-assembling tetrapeptide containing glutamic acid (Glu) and phenylalanine (Phe), namely Glu-Phe-Glu-Phe, with the BTBT core. Furthermore, hydrogels were obtained by tuning both the pH and the ionic strength of the solution. As mentioned above, the type of amino acids and their sequence determine the type of self-assembly, and thus, subtle structural variations might lead to changes in the type and strength of the non-covalent interactions involved, also leading to different supramolecular architectures [ 34 , 35 , 36 ]. For this reason, we aimed to study the effect of introducing the BTBT core in the side chain of the main peptide backbone. To favour a straightforward synthesis of this derivative, the Cu(I)-catalysed azido alkyne cycloaddition (CuAAC) was used to functionalise the amino acid side chain with the BTBT core. An alternating sequence of hydrophilic and hydrophobic amino acids was maintained in order to favour β-sheet formation. Self-supporting transparent hydrogels were obtained upon pH switching. We investigated the solution-based thin film deposition and the electrical properties of this new material.",
"discussion": "2. Results and Discussion 2.1. Design and Synthesis of the BTBT-Peptide Hybrid 1 The molecular architecture of the BTBT-peptide hybrid 1 ( Scheme 1 ) alternates hydrophilic and hydrophobic residues in its structure. This alternation favours the formation of β-sheet structures in which the side chains of adjacent residues point out in opposite directions, generating two distinct faces: a hydrophobic and a hydrophilic one. In aqueous media, two sheets may self-assemble to form a β-sheet bilayer in which hydrophobic residues are buried inside, while the hydrophilic faces are exposed to the solvent. It has been demonstrated that this type of self-assembly can accommodate large aromatic side-chains in the inner shielded region and that increasing the area of the aromatic surface leads to stronger π-π interactions [ 37 ]. Thus, we expected to obtain self-assembled nanostructures with an aromatic core in which strong π-π interactions are established between BTBT chromophores. Concerning the peptide design, two valine residues (Val) were positioned at the N- and C-termini, the hydrophilic lysine residues (Lys) enabled pH-dependent solubility in water, while the central position was occupied by the non-natural amino acid L-propargylglycine (Pra) functionalised with BTBT. The N-acetylated peptide sequence was synthesised following fluorenylmethoxycarbonyl (Fmoc) solid-phase peptide synthesis (SPPS) protocols on a 4-methylbenzhydrylamine (MHBA) Rink amide resin. Couplings were carried out using a mixture of O-benzotriazole-N,N,N′,N′-tetramethyluronium hexafluorophosphate (HBTU), 1-Hydroxybennzotriazole hydrate (HOBt), and N,N-diisopropylethylamine (DIPEA). Fmoc deprotection was achieved by treatment with a 20% solution of 4-methylpiperidine in dimethylformamide (DMF). The BTBT moiety was then introduced through an on-resin CuAAC reaction between the terminal alkyne of the Pra side chain and the azide group of 2-azido-BTBT ( 2 ) in the presence of sodium ascorbate (NaAsc) and CuSO 4 ( Scheme 1 ). Final cleavage was performed using a trifluoroacetic acid (TFA)/triisopropylsilane (TIPS)/water cocktail (See Supporting Information for details). Compounds 1 and 2 were thoroughly characterised by NMR, FT-IR and ESI-MS (See Figures S1–S8 of the Supporting Information ). 2.2. Gelation and Hydrogel Characterization 1 is well soluble in acidic water, where the Lys side chains are protonated. When the pH of the solution was raised above 10 by adding NaOH 0.5 N, a self-supporting hydrogel was formed in a few minutes ( Figure 1 a). The minimum gelation concentration (mgc) was equal to 0.5 wt % and the gel-to-solution transition (Tgel) was observed at 80 °C. The morphology of the self-assembled nanostructures was analysed by transmission electron microscopy (TEM). TEM micrographs of the xerogel revealed the formation of long-range fibres with an average diameter of 10 (±2) nm and a length of up to 500 nm ( Figure 1 b,c). The gel nature of the sample was confirmed via oscillatory rheology. As expected for viscoelastic materials, frequency sweep experiments showed that the elastic modulus (G′) was one order of magnitude higher than the viscous one (G″) within the linear viscoelastic region, and both contributions were frequency-independent within the investigated range ( Figure 2 a). In the strain sweep set-up, the viscous and elastic modulus deviated from linearity above 3% of applied strain, reaching the cross-over point at 25% of strain ( Figure 2 b). Self-assembly was also investigated by UV-Vis absorption and emission spectroscopies and circular dichroism (CD). The UV-Vis absorption spectrum of a 10 −5 M solution of 1 in MilliQ water showed a structured band going from 285 nm to 350 nm originating from the BTBT core ( Figure 3 a) [ 38 ]. The absorption maximum was centred at 315 nm, with a shoulder located at 340 nm. The emission profile was characterised by an asymmetric band centred at 415 nm with a less-pronounced shoulder at 430 nm. Increasing the concentration to 0.5 wt % (5.6 × 10 −3 M), a widening of the absorption band of about 12 nm was observed. The maximum absorption peak remained at 315 nm while the less-pronounced shoulder red-shifted to 352 nm. Even the emission spectroscopy showed a broadening of the profile ( Figure 3 b). The broad emission band showed a maximum at 415 nm, with a shoulder at 440 nm and a long tail up to 620 nm. In an alkaline environment (viz. pH > 10), the gel was formed. The pH-triggered hydrogel showed the broadest UV-Vis absorption spectrum. The main absorption band ranged from 305 nm to 340 nm, while the shoulder increased its intensity and moved to 355 nm. The emission maximum was red-shifted to 445 nm and a tail was observed up to 650 nm. These data suggest the presence of strong π-π interactions between the BTBT chromophores upon gelation. This hypothesis was confirmed by CD investigations ( Figure 3 c). The CD spectrum of a 10 − 5 M solution of 1 in water showed a silent CD in the BTBT absorption region and a negative peak at 200 nm that indicates a random coil conformation of the peptide segment. Upon increasing the concentration, new strong negative CD signals emerge at 228 nm and above 280 nm, in the BTBT absorption region, suggesting the formation of β-sheet structures [ 39 ] and a chiral arrangement of the chromophores within the aggregate. In the hydrogel, the intensity of the CD signal decreased significantly as a consequence of scattering due to the formation of the 3D fibrillar network. Nevertheless, five negative peaks, located at 368 nm, 332 nm, 320 nm, 280 nm, and 220 nm, could be detected. Signals above 280 nm arise from the BTBT moiety, indicating that the chromophore is involved in the formation of a chiral structure. The negative peak at 220 nm is consistent with the formation of a H-bonded β-sheet network [ 39 ]. 2.3. Electrical Characterization In recent years, 2D and 3D conductive hydrogel scaffolds have been extensively studied due to their potential use in tissue engineering applications [ 40 ]. We evaluated the charge-transport behaviour of the designed gelator by performing electrical measurements on drop-casted thin films deposited on gold interdigitated electrodes. The hydrogels were first obtained at the mgc concentration and then diluted with water immediately prior to deposition ( Figure 4 ). Optimization of the deposition process showed that the addition of 1% v / v of N-methyl-2-pyrrolidone (NMP) is necessary to avoid the formation of a “coffee ring” [ 41 ]. The addition of NMP did not affect the spatial organisation of the gelator, and the fibrillar structure was maintained, as confirmed by SEM micrographs ( Figure S9 of the Supporting Information ). Upon drop-casting, the sample was dried at room temperature and then kept under a primary vacuum overnight. Interestingly, we noted that the outcome of the deposition was highly affected by its surrounding. To ensure the reproducibility of the deposition, it was necessary to maintain the NMP-water reservoir close to the BTBT droplets to regulate humidity and allow a control over the drying process. In this context, a few droplets of the 1% NMP solution were placed on the Si/SiO 2 substrates prior to the deposition of BTBT. This specific deposition allowed the control and formation on top of the electrodes of dendrimeric features, as shown in Figure 5 a–c. These particular structures were able to electrically bridge the interdigitated electrodes. These fibrillar structures are physically adsorbed, hence they can be completely removed by rinsing the substrate with water ( Figure 5 c,d). Electrical characterisation was performed by recording the I-V characteristics of the BTBT devices in the air. Figure 6 a,b present the I-V profile obtained when the voltage was swept from 0 V to +1 V, and from −3 V to +3 V, respectively. In Figure 6 a, it is possible to observe a rectifying behaviour due to the p-n diodes composed by the Au electrode and the BTBT film [ 32 ]. This trend is ruled by Equation (1): (1) I = I 0 exp V A − 1 , \nin which I 0 corresponds to the reverse bias current, and A is a linear function of the ideality factor and the thermal voltage. Within this context, the first derivative of current with respect to the applied voltage indicates a diode-limited current that evolves to a resistor-limited current when the applied voltage approaches 1 V. In the resistive region, the linear fit provides a conductivity of 5.3 (±0.1) × 10 −7 S cm −1 , which has the same order of magnitude as that presented in the literature for C8-BTBT-peptide films. Nevertheless, as our device works in a voltage range that is twenty times lower, it opens up the possibility of being applied on low-power devices. We also investigated the electrical response of the BTBT devices in a broader voltage range, as shown in Figure 6 b. In this case, a peak was observed at +1.3 V and −1.2 V. Such a feature has already been reported in the literature for the cyclic voltammetry of BTBT in 1 mM dichloromethane, and it was attributed to reversible redox of the BTBT compounds [ 42 ]. However, as our measurements are performed in the air, we attribute the presence of such redox activity to the presence of trapped water in the BTBT compound, which allows for charge transport. The superposition of these peaks to the diode profile causes a reduction in the measured current in the resistive region according to consecutive scans. The stability of these devices was achieved by leaving the samples in vacuum overnight and by shielding them with a drop-casted PMMA layer. The PMMA layer also prevented the detachment of dendrimeric features from the substrate. Figure S10 of the Supporting Information illustrates the improved performance for six consecutive scans. Under these conditions, the resistive region provides a conductivity of 1.6 (±0.1) × 10 −5 S cm −1 . This value is one order of magnitude higher than the conductivity reported previously for other non-gelled assemblies of BTBT-peptide hybrids [ 32 ]."
} | 4,193 |
30202434 | PMC6123915 | pmc | 6,697 | {
"abstract": "Background The microbial production of fatty acids has received great attention in the last few years as feedstock for the production of renewable energy. The main advantage of using cyanobacteria over other organisms is their ability to capture energy from sunlight and to transform CO 2 into products of interest by photosynthesis, such as fatty acids. Fatty acid synthesis is a ubiquitous and well-characterized pathway in most bacteria. However, the activity of the enzymes involved in this pathway in cyanobacteria remains poorly explored. Results To characterize the function of some enzymes involved in the saturated fatty acid synthesis in cyanobacteria, we genetically engineered Synechococcus elongatus PCC 7942 by overexpressing or deleting genes encoding enzymes of the fatty acid synthase system and tested the lipid profile of the mutants. These modifications were in turn used to improve alpha-linolenic acid production in this cyanobacterium. The mutant resulting from fabF overexpression and fadD deletion, combined with the overexpression of desA and desB desaturase genes from Synechococcus sp. PCC 7002, produced the highest levels of this omega-3 fatty acid. Conclusions The fatty acid composition of S. elongatus PCC 7942 can be significantly modified by genetically engineering the expression of genes coding for the enzymes involved in the first reactions of fatty acid synthesis pathway. Variations in fatty acid composition of S. elongatus PCC 7942 mutants did not follow the pattern observed in Escherichia coli derivatives. Some of these modifications can be used to improve omega-3 fatty acid production. This work provides new insights into the saturated fatty acid synthesis pathway and new strategies that might be used to manipulate the fatty acid content of cyanobacteria. Electronic supplementary material The online version of this article (10.1186/s13068-018-1243-4) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusion In this study, the activity of the enzymes involved in the first reactions of FA synthesis pathway in Se7942 was examined by deleting or overexpressing their respective coding genes and analyzing the resulting FA profiles. In general, the mutant strains showed changes in their FA composition, regarding both the wt Se7942 strain and E. coli mutants. In addition, the modifications that improved the synthesis of C16:0 and C18:0 (overexpression of fabF and deletion of fadD ) used in combination with the expression of Ss7002 desAB desaturase genes was revealed as a feasible strategy to engineer Se7942 for ALA production. To the best of our knowledge, this is the first report on increased ALA production in cyanobacteria using modifications in the expression of the genes belonging to the FAS system. The combination of fadD deletion and fabF overexpression is a strategy that may be evaluated in omega-3 natural producers to raise ALA yield.",
"discussion": "Discussion Se7942 is a model cyanobacterium because of its small genome size and simple metabolism, making it ideal for the study of lipid biosynthesis in photoautotrophic bacteria. To gain a detailed understanding of the FA synthesis pathway in Se7942, a deeper knowledge on the activity of the enzymes involved was needed. To fulfill this aim, we engineered several modifications in the production of these enzymes in Se7942. Our results showed important differences in the activity of some enzymes involved in FA synthesis in Se7942 regarding those in E. coli , despite their amino acid sequence homology (ranging from 42 to 52% identity). Whereas fabD overexpression altered the FA composition of E. coli [ 23 ], this modification did not have a remarkable effect in the Se7942 FA profile. On the other hand, the E. coli fabH mutant is viable and exhibits a small-colony phenotype [ 25 ], suggesting the implication of another condensing enzyme performing less efficiently this reaction in the initiation cycle of the FA biosynthesis. In Se7942, the fabH deletion was lethal, when assayed by random barcode transposon site sequencing (RB-TnSeq) [ 29 ]. Neither was this gene removed from all chromosomal copies of Ss7002 [ 27 ]. Our attempts to delete fabH in Se7942 also resulted in merodiploid mutants, an indication of the indispensability of this gene, and that no other Se7942 KAS enzyme (e.g., FabF) can act as a functional replacement for FabH. Overexpression of fabH led to increase in MCFA production, specifically lauric (C12:0) and myristic (C14:0) acids. Notably, C12:0 is not naturally present in Se7942. Increased levels of MCFAs were reported in an engineered Ss7002 strain in which fabH was replaced by Chaetoceros GSL56 KASIII gene [ 27 ]. MCFAs are appreciated in the fuel industry, which makes fabH overexpression in cyanobacteria potentially useful. These results suggest that in cyanobacteria FabH may have more affinity toward short-chain FAs, a feature described previously in other bacteria [ 47 ]. Regarding the two other KAS, FabB and FabF, relevant differences to E. coli were found. In E. coli , FabB plays an important role in controlling the unsaturation degree of FAs [ 33 ]. It is noteworthy that FabB is absent in Se7942 and most cyanobacteria, but present in Ss7002, where it is dispensable in unsaturated FA synthesis [ 17 ]. In cyanobacteria, unsaturated FA synthesis is controlled downstream of the FA synthases, because their synthesis is performed by desaturases, which act on FAS products [ 40 ]. The growth temperature of cyanobacteria is responsible for the up- or downregulation of the desaturase gene expression [ 48 ]. Overproduction of FabB from Ss7002 in Se7942 did not increase C18:1 yield, contrary to the E. coli case [ 33 ], suggesting that FabB did not play a role in the cyanobacterial unsaturated FA synthesis. Kuo and Khosla speculated that FabB could have an additional role, still unknown [ 17 ]. Overexpression of fabF was lethal in E. coli , likely due to the fact that high levels of FabF block the access of FabB to the product generated by FabD [ 34 ]. This lethality was not observed when the endogenous fabF gene was overexpressed in Se7942, ruled out any FabB blockage by FabF since FabB is absent in Se7942. Taking all these results together, we suggest that the enzymes involved in FA synthesis in Se7942 play a different role from that observed in E. coli . Moreover, it also suggests that these enzymes could be regulated in a different way in both bacteria. Even though the biochemistry of FA synthesis in E. coli is well known and documented, its genetic regulation still remains unclear. In E. coli , the key regulators are the long-chain acyl-ACP end products, which exert a negative regulatory feedback on key enzymes of the synthesis pathway [ 49 ]. Moreover, this pathway is also controlled by transcription factors, mainly FabR (TetR family) and FadR (GntR family), among others [ 49 ]. FabR and FadR also control the expression of FA degradation genes involved in the β-oxidation cycle [ 50 ]. As mentioned above, it appears that cyanobacteria lack the major FA degradative metabolic pathway β-oxidation, generally thought to be universal. In several Gram-positive bacteria, there are other families of regulators that control the expression of fab genes. In Bacillus subtilis , FapR is a global negative regulator of genes involved in FA and phospholipid biosynthesis [ 51 ]. This regulator, a member of the DeoR family, is common to other species of the Bacillus genus, as well as Listeria , Clostridium and Staphylococcus [ 51 ] and senses malonyl-CoA, which releases its transcriptional repression [ 52 , 53 ]. In Streptococcus pneumoniae , a different FA synthesis regulator was identified, FabT, which belongs to the MarR family [ 54 ]. FabT homologs were also located in other groups of Gram‐positive bacteria, such as Enterococcus , Clostridium and Lactococcus [ 54 ]. Little is known about the regulation of the gene expression of FA synthesis in cyanobacteria. In most bacteria, fab genes are organized into operons, and this organization enables the identification of cognate transcription factors based on shared synteny [ 55 ]. In cyanobacteria [ 56 ], fab genes are scattered throughout the genome. Moreover, due to the fact that cyanobacteria do not code for a FA degradation pathway, some authors suggested that the regulatory of mechanisms for FA metabolism may be largely different from those of heterotrophic bacteria [ 56 , 57 ]. There is scarce information on the transcriptional regulation of FA biosynthesis in cyanobacteria. Deletion of a cyanobacteria-specific transcriptional regulator gene, cyAbrB2 , was found to enhance the production of free FAs in engineered strains of Ss6803 [ 58 ]. Besides, the LexA transcription factor was described as a regulator of FA synthesis also in Ss6803, and more specifically as a repressor of genes involved in the initiation step of FA synthesis ( fabD , fabH and fabF ) and the first reductive step in the elongation cycle ( fabG ) [ 56 ]. Gene lexA deletion largely increased the production of FAs in an engineered Ss6803 strain [ 56 ]. No LexA homolog was found in Se7942 [ 59 ]. The information related to FA synthesis regulation in Se7942 focuses on the signal transduction protein P II . The P II mutant strain of Se7942 showed a decreased intracellular acetyl-CoA content and enhanced activity of the acetyl-CoA–carboxylase complex through transcriptional activation of the accABCD genes [ 60 ]. However, P II does not regulate the enzymes involved in the FAS system. These and our results may suggest that the regulation of FA synthesis enzymes in cyanobacteria is independent of FA degradation by the β-oxidation cycle and could involve a global regulator, which has yet to be found. Omega-3 FAs are naturally produced in some cyanobacteria, members of the groups 3α and 4 [ 10 ], which encode Δ12 and Δ15 desaturase genes. Such is the case of Ss6803 [ 61 ], Synechococcus sp. NKBG 15041c [ 62 ] and Ss7002 [ 43 ]. The first two produced high levels of ALA (23 and 50% of total FA, respectively) when engineered to overexpress, respectively, Δ6 + Δ15 and Δ6 FA desaturase genes [ 63 , 64 ]. On the other hand, Ss7002 produced the highest ALA levels (19% of total FA) in a cyanobacterial wt strain when grown at high light intensity either at 22 °C or at 38 °C and shifted to 22 °C for 12 h [ 43 ]. The introduction of the Δ12 desaturase gene desA from Ss6803 into Se7942 caused a modification of its FA composition: dienoic FA C16:2Δ 9,12 and C18:2Δ 9,12 emerged at significant levels at the expense of C16:1Δ 9 and C18:1Δ 9 [ 65 ]. This modification led to an enhancing in chilling tolerance [ 65 ] and protection against photoinhibition [ 66 ]. When transformed with Ss6803 Δ12 and Δ15 desaturase genes, desA and desB , Se7942 was able to desaturase FA at Δ9, Δ12 and Δ15 positions [ 67 ]. ALA production by the transformant strain at 34 °C was low (1% of total lipids) but significantly increased (up to 5%) when incubated at 22 °C. Taking advantage of the high similarity in codon usage between Se7942 and Ss7002, the Δ12 and Δ15 desaturase genes of the latter, desA and desB , were chosen to produce transgenically ALA in Se7942, which lacks these two essential enzymes of the desaturation pathway. The desB gene of Ss7002 is transcribed only at low temperatures (22 °C) [ 44 , 45 ]. Thus, an inducible promoter was chosen to drive the desAB expression at 22 °C once enough biomass was achieved at 30 °C, because Se7942 growth is impaired at low temperature [ 39 ]. The resulting strain, MSM26, produced ALA at the same level of Ss7002 (Fig. 7 b), at the expense of C18 and C16:1 FAs. Se7942 mutants either overexpressing fabF or lacking fadD exhibited a FA profile enriched in C18 and thus these mutations were evaluated in combination with desAB expression. This strategy resulted in a significant improvement in the yield of this omega-3 FA in relation to the available data for Ss7002 [ 43 , 45 , 68 , 69 ], and comparable to the engineered Se6803 [ 63 ]."
} | 3,043 |
39888293 | PMC11948153 | pmc | 6,698 | {
"abstract": "Abstract The coordination of public and private goods production is essential for bacterial adaptation to environmental changes. Quorum sensing (QS) regulates this balance by mediating the trade‐off between the communal benefits of “public goods,” such as siderophores and antibiotics, and the individual metabolic needs fulfilled by “private goods,” such as intracellular metabolites utilized for growth and survival. Pseudomonas fluorescens 2P24 harbors a LasI/LasR‐type QS system, MupI/MupR, which regulates mupirocin production through signaling molecules. This study explores how QS coordinates carbon and nitrogen metabolism to optimize the production of key secondary metabolites, including 2,4‐diacetylphloroglucinol (2,4‐DAPG), mupirocin, and siderophores, which serve as public goods. Loss of QS disrupts this balance by enhancing the Krebs cycle, denitrification, pyruvate anaplerosis, and ammonium assimilation, lead to halted 2,4‐DAPG and mupirocin synthesis and increased siderophore production. In the absence of QS, elevated siderophore production compensates for iron acquisition, ensuring rapid cellular growth. Under nutrient‐limited or high cell density conditions, MupR regulates carbon and nitrogen fluxes to sustain public goods production. These findings highlight QS as a key environmental sensor that fine‐tunes resource allocation, bacterial fitness, and adaptation to ecological and nutritional conditions, suggesting the potential for QS‐targeted approaches to enhance antibiotic production and agricultural sustainability.",
"conclusion": "3 Conclusion Bacterial collective sensing, often mediated through QS, enables individual bacteria to produce and detect signaling molecules, thereby synchronizing its behavior across the community. QS systems differ among bacterial species, reflecting evolutionary adaptations to specific ecological niches. In P. aeruginosa , a complex QS network organized into multiple interconnected systems that utilize both AHLs and quinolone signals, with the Las system primarily controlling virulence factors via the LasR receptor, the Rhl system regulating biofilm formation and motility through the RhlR receptor, and the PQS system functioning independently to influence iron acquisition and antibiotic resistance. [ \n \n 52 \n \n ] In contrast, P. fluorescens utilizes the simpler PcoI/PcoR system, [ \n \n 53 \n \n ] primarily involved in biocontrol, while B. glumae employs the TofI/TofR system and additional regulatory genes like qsmR, expanding its QS network beyond AHL signaling to include virulence factors. [ \n \n 54 \n \n ] The evolutionary origin and maintenance of QS are controversial. While some propose that QS evolved as a form of social communication to enhance collective behavior and fitness, [ \n \n 2 \n , \n 55 \n \n ] others suggest it serves as a sensor system that allows bacteria to monitor and respond to a complex array of environmental signals, thereby enabling adaptive responses that are critical for survival, competition, and cooperation within ecological niches. [ \n \n 56 \n , \n 57 \n , \n 58 \n \n ] \n QS is fundamentally about sensing cell density, enabling bacteria to coordinate behaviors based on the population density [ \n \n 2 \n \n ] However, it functions not merely as an ON‐OFF switch but as a sophisticated tuning mechanism, enhancing their response to varying physical environments. [ \n \n 58 \n \n ] QS can finely tune various metabolic pathways related to nutrient acquisition and utilization. [ \n \n 18 \n \n ] QS in B. glumae acts as a metabolic brake, slowing down primary metabolism in crowded conditions to ensure homeostasis. [ \n \n 20 \n \n ] This involves the coordinated regulation of glucose uptake, energy production, and nucleotide biosynthesis, preventing metabolic imbalances and ensuring efficient resource utilization. In P. aeruginosa , QS leads to significant metabolic alterations, including TCA cycle changes and amino acid and fatty acid metabolism. [ \n \n 59 \n \n ] QS inhibitors like resveratrol can significantly alter the metabolome of P. aeruginosa , affecting pathways related to oxidative stress and energy metabolism. [ \n \n 60 \n \n ] Histidine metabolic imbalance impacts the expression of type III secretion genes through QS pathways in P. aeruginosa , linking nitrogen metabolism to virulence factor production. [ \n \n 61 \n \n ] The integration of AI‐2‐based QS with metabolic cues in Escherichia coli influences the expression of genes related to amino acid uptake and catabolism, ensuring efficient utilization of environmental amino acids. [ \n \n 62 \n \n ] Similarly, QS in Vibrio harveyi controls the expression of genes involved in nutrient uptake, including those related to sugar transport and the biosynthesis of methionine and thiamine. [ \n \n 63 \n \n ] Thus, QS can finely tune bacterial metabolism to optimize nutrient acquisition and utilization, ensuring that the bacterial community can adapt to changing environmental conditions and maintain optimal growth and survival. The mechanisms of QS‐regulated cooperation in the production of public goods, particularly in the context of the metabolism involved in synthesizing carbon‐ and nitrogen‐based secondary metabolites, have yet to be fully demonstrated in bacterial communities. We demonstrate that the QS system in P. fluorescens 2P24 imposes metabolic restrictions by regulating the expression of genes and metabolites, thereby maintaining the production of secondary metabolites within a cooperative carbon and nitrogen metabolism (Figure 5B ). We integrated transcriptome, metabolome, and ChIP‐seq data to dissect the QS‐regulated metabolic network for secondary metabolites production in P. fluorescens 2P24. MupR decreases the levels of G6P, G3P and d ‐sedoheptulose 7‐phosphate, which are associated with glycerol metabolism and pentose phosphate pathway, were significantly higher in Δ mupR mutant. Similarly, concentrations of UDP‐ d ‐galactose, glutaric acid, l ‐2‐hydroxyglutaric acid, 3‐oxo‐dodecanoic acid, as well as fatty acid metabolites such as (S)‐3‐hydroxyoctanoic acid, 10‐hydroxy capric acid, 3s‐hydroxy‐dodecanoic acid were significantly decreased in Δ mupR mutant. Meanwhile, the concentration of S‐adenosylmethionine (SAM) and 5′‐methylthioadenosine (5′‐MTA) that related to AHLs biosynthesis were substantially decreased in Δ mupR mutant (Figure 5A ). When QS is active, MupR represses transcriptional levels of aceE , gltA , pycA , acnB , sucA , and sdhC genes which encode the key enzymes from the TCA cycle. MupR reduces the level of glutarate, which can be converted to glutaryl‐CoA and succinate by succinyl‐CoA transferase, with the resulting succinate being fed into the TCA cycle for energy production. MupR downregulates malonyl CoA‐acyl carrier protein transacylase fabD for reducing the fatty acid synthesis and keeps phospholipids PE at a low level while increasing PG, PC, PS, and PA. PE is the major phospholipid in Gram‐negative bacteria. [ \n \n 64 \n \n ] This implies that acetyl‐CoA and malonyl‐CoA can be accumulated, facilitating the QS system to synthesize polyketide antibiotics such as 2,4‐DAPG and mupirocin. These results indicate that QS allows bacteria to restrict the TCA cycle and enhance the biosynthesis of lipids and amino acids, as these pathways are interconnected with central carbon metabolism. MupR repressed the gene transcriptional level of sucA gene, which encoded the 2‐oxoglutarate dehydrogenase E1 subunit responsible for converting 2OG to succinyl‐CoA. [ \n \n 65 \n \n ] However, MupR does not affect isocitrate dehydrogenase, which is involved in the oxidative decarboxylation of isocitrate to 2OG. This indicates that these two steps of the TCA cycle work together to accumulate and increase 2OG levels. Indeed, metabolomic analysis showed that the levels of the key metabolite 2OG in the TCA cycle and Glu, were increased under the QS system. 2OG acts as a signaling molecule of nitrogen limitation, and regulates the activity of enzymes involved in nitrogen assimilation. [ \n \n 66 \n \n ] MupR represses the genes glnA1 and gltB in GS‐GOGAT pathway for ammonium assimilation and amino acid synthesis. The GS‐GOGAT pathway in bacteria is critical for assimilating ammonium into glutamine and glutamate, linking nitrogen metabolism with central carbon metabolism. [ \n \n 67 \n , \n 68 \n \n ] The accumulation levels of 2‐OG reflect the cellular nitrogen/carbon status. This downregulation of ammonium assimilation genes ensures a balanced metabolic flow, supporting the synthesis of both carbon‐ and nitrogen‐based public goods, thereby maintaining metabolic homeostasis. MupR also downregulates genes involved in the denitrification pathway, including nitrate reductase‐related narH , nitrite reductases‐related nirQS , nitric oxide reductase ( norBC ), and a Crp/Fnr family transcriptional regulator downregulated by MupR. Additionally, MupR downregulates ytfE , which is associated with the bacterial response to oxidative and nitrosative stress, [ \n \n 49 \n \n ] and hmpA , which plays a role in nitric oxide detoxification under aerobic conditions. [ \n \n 50 \n \n ] These downregulated genes from the denitrification pathway imply a metabolic shift from energy‐intensive metabolism for cell growth toward energy‐efficient metabolism for the production of public goods. We also find that the QS system maintains a low ratio of NADH/NAD+, indicating sufficient electron transport chain and leading to energy production. These findings indicate that MupR slows down the TCA cycle or limits denitrification pathways to maintain homeostasis and functions as a metabolic brake to regulate energy production for cellular metabolism. Specifically, the downregulation of ammonium assimilation and amino acid synthesis may limit the availability of nitrogen precursors for siderophore synthesis. Concurrently, carbohydrate and fatty acid metabolism alterations shift central carbon intermediates toward the biosynthesis of key secondary metabolites such as 2,4‐DAPG and mupirocin, while decelerating energy production via the TCA cycle. MupR plays a key role in regulating the balance between central metabolism and secondary metabolite production in P. fluorescens 2P24. By inhibiting respiration through the TCA cycle and denitrification pathways, MupR conserves energy and resources while promoting the synthesis of key carbon‐based secondary metabolites, including AHLs, 2,4‐DAPG and mupirocin. In contrast, the production of nitrogen‐based secondary metabolites, such as siderophores, is suppressed under nutrient‐limited conditions, reflecting a shift in metabolic priorities. This metabolic reorganization helps to balance cellular energy demands, ensuring optimal survival in fluctuating environments. Our findings demonstrate that QS functions as a multifaceted regulatory mechanism, enabling facultative cooperation and acting as a sophisticated sensor system that allows bacteria to monitor their intracellular carbon and nitrogen status. By coordinating carbon and nitrogen metabolic fluxes, QS helps maintain a balanced homeostasis of energy and nutrients, optimizing public goods in response to environmental changes, thereby supporting long‐term bacterial adaptation. While the evolutionary origin of the QS system is debated, it is evident that the production of QS signal molecules, such as AHLs, is closely linked to intracellular carbon metabolism pathways. By modifying bacterial metabolic activities, the QS system mimics the effects of caloric restriction and induces the production of carbon‐based secondary metabolites and AHL signals. The metabolic feedback loops mediated by QS benefit individual bacterial cells and the microbial community by imposing stricter control over nutrient utilization and cellular energy consumption under high cell density conditions. In summary, the QS system may evolve from metabolic byproducts to an environmental sensor that ensures the homeostasis of carbon/nitrogen metabolism in individual cells under crowded conditions, making it a cooperative activity. By shedding light on the balance between private and public goods, our findings offer new insights into how QS coordinates metabolic fluxes in response to changing environmental conditions. This work addresses fundamental questions regarding the coexistence of cooperation and competition in microbial evolution and opens new avenues for exploring the dynamics of bacterial cell‐cell communication and its implications for microbial community behavior.",
"introduction": "1 Introduction Quorum sensing (QS) is a pivotal mechanism of bacterial cell‐to‐cell communication, relying on bacterial population density and coordination of social behavior. [ \n \n 1 \n \n ] It involves the production of extracellular signaling molecules called autoinducers, which accumulate as cell‐population density increases. [ \n \n 2 \n \n ] Bacteria use the QS system to regulate the expression of genes associated with the production of public goods, orchestrating a range of microbial behaviors such as bioluminescence, biofilm formation, mobility, virulence factor production, antibiotic synthesis, siderophore production, and diverse protease secretion. [ \n \n 3 \n , \n 4 \n \n ] However, producing these public goods imposes a metabolic burden on microbial communities, affecting the balance between communal benefits and individual costs in sophisticated environments. [ \n \n 5 \n , \n 6 \n \n ] Strains that do not produce public goods, often referred to as “cheaters,” tend to produce private goods, benefiting from the public goods produced by others without bearing the cost of production. [ \n \n 7 \n \n ] Cheaters can be controlled by cooperator cells through various policing mechanisms, yet in some cases, nonproducing strains are not penalized and continue to participate in community cooperation. [ \n \n 8 \n , \n 9 \n \n ] This behavior is elucidated by the Black Queen Hypothesis, which provides a cost‐benefit selection framework suggesting that the loss of costly functional genes can improve growth efficiency within a microbial community. [ \n \n 10 \n , \n 11 \n , \n 12 \n \n ] \n The function of QS and its role in enhancing cooperative behavior remains a topic of debate. While QS is conventionally perceived as a cell density‐dependent mechanism that facilitates the production and sharing of public goods among bacterial communities, recent studies posit QS as a sensor for individual bacteria cells to monitor signal levels and adapt to their physical environment. [ \n \n 13 \n , \n 14 \n \n ] In this context, individual cells produce and monitor signal levels to infer their local physical constraints. In crowded conditions, QS may help maintain homeostatic primary metabolism, balancing the production of public goods and private goods and addressing trade‐offs inherent in microbial communities. The acyl‐homoserine lactone (AHL) system has been extensively studied in the QS system from Gram‐negative bacteria. [ \n \n 15 \n , \n 16 \n \n ] It involves LuxI ‐type enzymes that synthesize autoinducers like AHLs by catalyzing the transfer of an acyl group, bound to acyl carrier protein (ACP) from fatty acid biosynthesis, to S‐adenosylmethionine, enabling the formation of AHLs that interact with LuxR‐type transcriptional regulators to modulate QS target genes. [ \n \n 17 \n \n ] AHLs are small lipid‐based signaling molecules in the QS systems of Gram‐negative bacteria, consisting of a homoserine lactone ring covalently linked to an acyl side chain, with the acyl group typically ranging from C4 to C18 carbons, either saturated or unsaturated, and these structural variations influence the specificity of AHLs for their corresponding LuxR‐type receptors, thereby affecting the sensitivity and functionality of the QS signaling cascade. [ \n \n 16 \n \n ] AHLs are closely intertwined with the metabolism of bacterial substances, influencing both anabolism and catabolism. This metabolic interplay, primarily involving carbon, nitrogen, and sulfur metabolism, enables bacteria to rapidly adapt to harsh environments, such as nutrient scarcity and extreme survival conditions. [ \n \n 18 \n \n ] \n For instance, in the rice pathogen Burkholderia glumae , the QS system TofI/R activates the expression of the transcription factor QsmR to downregulate pstI expression and slow glucose uptake. Simultaneously, the QsmR from B. glumae negatively regulates pathways, such as glycolysis, amino acids and nucleic acids biosynthesis, energy metabolism, and nitrogen metabolism. In addition, the QsmR upregulated the Krebs cycle in B. glumae . [ \n \n 19 \n , \n 20 \n \n ] Similarly, Yersinia pestis expresses a typical QS system for downregulating the glucose and nucleic acid metabolism while upregulating the Krebs cycle. [ \n \n 21 \n \n ] The opportunistic human pathogen Pseudomonas aeruginosa uses LasI/R and RhlI/R to positively regulate the Krebs cycle, amino acids and nucleic acid metabolism, and negatively regulate denitrification. [ \n \n 22 \n , \n 23 \n \n ] These observations highlight that cell density, often linked to nutrient‐limited conditions, plays a pivotal role in QS‐regulated metabolic adjustments. The role of QS in regulating metabolic responses under environmental stress is indeed complex and how it intricately coordinates primary and secondary metabolism pathways to ensure survival in various sophisticated growth conditions remains uncertain. The heterogeneity in QS among bacteria like Pseudomonas , Vibrio , and Xanthomonas emphasizes a “division of labor” that allows for performing distinct tasks and shared resource utilization, ultimately benefiting overall community fitness. [ \n \n 12 \n , \n 24 \n , \n 25 \n \n ] Still, questions persist about how QS manages homeostatic metabolism to balance the trade‐offs between primary metabolism and secondary metabolism, adapting to nutritional dynamics within microbial communities. The study of QS‐mediated coordination of bacterial metabolism and social behaviors is important for understanding how this cooperative communication system adapts to enhance fitness. Pseudomonas fluorescens 2P24, isolated from the wheat rhizosphere, produces various secondary metabolites, including 2,4‐diacetylphloroglucinol (2,4‐DAPG), known for its potent inhibitory effects against a broad spectrum of soil‐borne pathogens. [ \n \n 26 \n \n ] In addition to 2,4‐DAPG, the genome of P. fluorescens 2P24 also contains gene clusters for mupirocin, siderophore pyoverdine, and hydrogen cyanide biosynthetic gene clusters, highlighting the significant role of these secondary metabolites in determining bacterial fitness. Notably, P. fluorescens 2P24 harbors a LasI/LasR acyl homoserine lactone‐dependent QS system within the mupirocin biosynthesis gene cluster, designated as MupI/MupR. In P. fluorescens NCIMB 10586, the LasI homolog MupI synthesizes a signaling molecule that activates MupR, modulating the expression of genes responsible for mupirocin biosynthesis, thereby adding an additional layer of complexity to bacterial communication and regulation of secondary metabolite production. [ \n \n 27 \n \n ] Here, we examined the role of QS‐mediated regulation of secondary metabolites production in P. fluorescens 2P24 by modulating the metabolic capabilities of microbial communities. By integrating the transcriptome, metabolome, and ChIP‐seq analysis, we investigated impact of QS on the metabolic flux and gene transcription involved in secondary metabolite production in P. fluorescens 2P24. The loss of the QS function drastically alters the expression of genes involved in the Krebs cycle, fatty acid, amino acid metabolism, and denitrification, decreases the key Krebs cycle intermediate 2‐oxoglutarate (2‐OG), completely inhibit the production of carbon‐based secondary metabolites like AHL, 2,4‐DAPG, and mupirocin, while increase nitrogen‐based pyoverdine production. In conditions of high cell density, MupR acts as a metabolic brake, restricting the Krebs cycle and adjusting metabolic flux from carbon to nitrogen metabolism, resulting in higher level of 2‐OG compared to the loss of QS function mutant, which indicate QS as environmental sensor for orchestrating the balance between the primary metabolism and secondary metabolism. In the absence of QS control, increased pyoverdine production serves as a complementary system for bacterial growth, ensuring sufficient iron acquisition which is vital for cellular processes and overall fitness. The ecological and nutritional environment profoundly influences the spectrum of secondary metabolites produced by bacteria, with QS regulation markedly enhancing this diversity. By understanding how MupR‐mediated metabolic regulation governs the production of these metabolites, this study will bridge fundamental QS function with its practical applications, highlighting the potential of QS‐targeted approaches to optimize microbial metabolism for antibiotic production or promote sustainability in agricultural ecosystems."
} | 5,253 |
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