pmid stringlengths 8 8 | pmcid stringlengths 8 11 ⌀ | source stringclasses 2
values | rank int64 1 9.78k | sections unknown | tokens int64 3 46.7k |
|---|---|---|---|---|---|
34777326 | PMC8586421 | pmc | 5,368 | {
"abstract": "In the ecosystem, microbiome widely exists in soil, animals, and plants. With the rapid development of computational biology, sequencing technology and omics analysis, the important role of soil beneficial microbial community is being revealed. In this review, we mainly summarized the roles of rhizosphere microbiome, revealing its complex and pervasive nature contributing to the largely invisible interaction with plants. The manipulated beneficial microorganisms function as an indirect layer of the plant immune system by acting as a barrier to pathogen invasion or inducing plant systemic resistance. Specifically, plant could change and recruit beneficial microbial communities through root-type-specific metabolic properties, and positively shape their rhizosphere microorganisms in response to pathogen invasion. Meanwhile, plants and beneficial microbes exhibit the abilities to avoid excessive immune responses for their reciprocal symbiosis. Substantial lines of evidence show pathogens might utilize secreting proteins/effectors to overcome the emerging peripheral barrier for their advantage in turn. Overall, beneficial microbial communities in rhizosphere are involved in plant–pathogen interactions, and its power and potential are being explored and explained with the aim to effectively increase plant growth and productivity.",
"conclusion": "Concluding Remarks High-throughput rhizosphere microbiome profiling, combined with perturbation experiments, has shed light on the ecological importance of recruiting specific rhizosphere microorganism for plants against pathogen invasion. These advances have expanded our understanding of plant–microbe interactions, and further research on this topic will contribute significantly one important consideration, utilizing rhizosphere microbiome in disease resistance. However, several pressing questions remain to be addressed. For example, do plants recruit different microbes in response to different pathogens? How plants recruit beneficial microbes through root exudates following sensing pathogens? What root exudates that affect rhizosphere microorganism are directly related to pathogen infection? Do other pathogens contain effector proteins that target rhizosphere microorganism beyond plants? How plants distinguish the commensal microbes and pathogenic microbes through more PRRs or signal pathway? In addition, how could we get further insight into the triangular relationship of plants, beneficial microorganisms, and pathogens? Recently, one new experimental technique, the holo-omics strategy, that pairs host and microbial datasets was proposed ( Nyholm et al., 2020 ). The experimental designs pair host-centered omic strategies, such as transcriptomics, metabolomics, epigenomics, and proteomics, with the more commonly used microbial-focused techniques, such as amplicon sequencing, shotgun meta-genomic, meta transcriptomics, and exometabolomics ( Xu et al., 2021 ). Such holo-omic studies have the power to resolve the functionality of a plant microbiome ecosystem and provide significant information about microbial approach to improving host health and fitness, which will only increase in the near future.",
"introduction": "Introduction In the engagement with plants, phytopathogens have evolved sophisticated invasion strategies, for their own benefits, to bypass defense system and efficiently infect the hosts. As a counterpart, in order to stay healthy, plants have developed powerful weapons to ward off pathogens, including the well-studied multilayered physical barriers, preformed defenses, and innate immune system ( Zhang et al., 2020 ). Recent accumulating studies demonstrate that some pathogens could be blocked by another line of surveillance system, an emerging defense barrier, the plant microbiome, which could be separated as the phyllosphere microbiome and the rhizosphere microbiome ( Hacquard et al., 2017 ; Gong and Xin, 2021 ). Rhizosphere microbiome, known as the second genome of plants, collectively containing bacteria, fungi, and oomycetes, are closely related to plant growth and health ( Berendsen et al., 2012 ; Mueller and Sachs, 2015 ; Cai et al., 2017 ; Wu et al., 2018 ). The typical functional groups, such as rhizobia, mycorrhizal fungi, and the pathogenic microbes, of rhizosphere microorganisms, affecting plant growth and health, have been well studied in the past few decades ( van der Putten et al., 2007 ; Raaijmakers et al., 2009 ; Dardanelli et al., 2011 ; Mendes et al., 2013 ; Tedersoo et al., 2020 ), while the interaction between plants and other rhizosphere microbial communities is less well-understood ( Berendsen et al., 2012 ; Tedersoo et al., 2020 ). These plant microbial groups show potential functions related to probiotics and plant protection, attracting attention from research community; however, how the rhizosphere microbial communities influence plant growth and resistance remains scarce ( Hacquard et al., 2017 ). Traditional culture-dependent approaches, the developed next-generation sequencing (NGS) and the meta-omics technology have served as a key tool for profiling microbial assemblages. Studies suggest that plants affect and recruit soil beneficial microbial community in response to pathogenic microorganism attack, without activating a strong immune response to support its growth and fitness ( Hacquard et al., 2017 ; Yin et al., 2021 ). Moreover, substantial work has revealed that plants could distinguish pathogenic and beneficial microbes accurately and maintain the dynamic balance between plant growth and defenses ( Hacquard et al., 2017 ; Bozsoki et al., 2020 ; Zhou et al., 2020 ; Buscaill and van der Hoorn, 2021 ; Emonet et al., 2021 ; Ma et al., 2021 ; Zhang et al., 2021 ). Here we review and discuss (i) the current status of rhizosphere microbiome; (ii) emphasizing on its role in the context of plant-pathogen interactions, by acting as a barrier to pathogen invasion; (iii) showing the possibility of engineering disease-suppressive microbes in response to pathogen attack."
} | 1,508 |
36315012 | null | s2 | 5,370 | {
"abstract": "Microbial communities are complex living systems that populate the planet with diverse functions and are increasingly harnessed for practical human needs. To deepen the fundamental understanding of their organization and functioning as well as to facilitate their engineering for applications, mathematical modeling has played an increasingly important role. Agent-based models represent a class of powerful quantitative frameworks for investigating microbial communities because of their individualistic nature in describing cells, mechanistic characterization of molecular and cellular processes, and intrinsic ability to produce emergent system properties. This review presents a comprehensive overview of recent advances in agent-based modeling of microbial communities. It surveys the state-of-the-art algorithms employed to simulate intracellular biomolecular events, single-cell behaviors, intercellular interactions, and interactions between cells and their environments that collectively serve as the driving forces of community behaviors. It also highlights three lines of applications of agent-based modeling, namely, the elucidation of microbial range expansion and colony ecology, the design of synthetic gene circuits and microbial populations for desired behaviors, and the characterization of biofilm formation and dispersal. The review concludes with a discussion of existing challenges, including the computational cost of the modeling, and potential mitigation strategies."
} | 372 |
31551530 | PMC6908701 | pmc | 5,373 | {
"abstract": "Dust is an important iron (Fe) source to the ocean, but its utilization by phytoplankton is constrained by rapid sinking and slow dissolution dust-bound iron (dust-Fe). Colonies of the globally important cyanobacterium, Trichodesmium , overcome these constraints by efficient dust capturing and active dust-Fe dissolution. In this study we examined the ability of Trichodesmium colonies to maximize their Fe supply from dust by selectively collecting Fe-rich particles. Testing for selectivity in particle collection, we supplied ~600 individual colonies, collected on multiple days from the Gulf of Aqaba, with natural dust and silica minerals that were either cleaned of or coated with Fe. Using a stereoscope, we counted the number of particles retained by each colony shortly after addition and following 24 h incubation with particles, and documented translocation of particles to the colony core. We observed a strong preference for Fe-rich particles over Fe-free particles in all tested parameters. Moreover, some colonies discarded the Fe-free particles they initially collected. The preferred collection of Fe-rich particles and disposal of Fe-free particles suggest that Trichodesmium can sense Fe and selectively choose Fe-rich dust particles. This ability assists Trichodesmium obtain Fe from dust and facilitate its growth and subsequent contribution to nutrient cycling and productivity in the ocean.",
"introduction": "Introduction In large parts of the oceans, short supply and restricted availability of iron (Fe) limit phytoplankton growth [ 1 – 3 ]. Wind driven desert dust is a major source of new Fe to remote oceanic regions [ 2 , 4 , 5 ], supplying Fe-bearing minerals to Fe-depleted surface water [ 6 – 8 ]. Mineral-Fe is not directly available to most phytoplankton, which can only internalize soluble Fe [ 9 ]. Hence, dissolution of dust-bound Fe is a prerequisite for its utilization by phytoplankton [ 10 , 11 ]. Desert dust contains a complex matrix of minerals, varying in structure, size, and Fe content. Some dust minerals, such as Fe-oxides and hydroxides, are composed mostly of Fe (50–80%), while other dust components are relatively poor in Fe [ 12 , 13 ]. Fe release rates from dust minerals are influenced by multiple factors in addition to their Fe content, such as size, mineral structure, weathering degree, and reactions that occurred in the atmosphere during transport and in the ocean microlayer upon deposition [ 14 ]. The residence time of dust minerals in the ocean surface can vary from days to months [ 15 , 16 ], during which a variety of processes (biological, photochemical, and chemical) can further transform the minerals and influence their bioavailability [ 17 ]. Trichodesmium is a successful, filamentous, colony-forming cyanobacterium residing in oligotrophic tropical and subtropical oceans. Trichodesmium , a globally important diazotroph (N 2 -fixer), contribute annually 60–80 Tg of new N, almost 40% of global marine N 2 fixation [ 18 ]. Diazotrophy involves Fe-rich apparatus and requires a high inner quota of Fe [ 19 ]. Trichodesmium can exist in the water column as single filaments (trichomes) and as large colonies (~1 mm in diameter) that are visible to the naked eye [ 20 ]. Colonies consist of aggregates of several to several hundred trichomes and form fusiform colonies when aligned in parallel (called “tufts”), or spherical colonies when aligned radially (called “puffs”). Various species of Trichodesmium have been described based on the morphology and structure of colonies [ 21 ] and recently, using genetic tools, were grouped to two clades that probably inhabit different ecological niches [ 22 ]. The low surface area to volume ratio of large Trichodesmium colonies imposes a strong limitation on dissolved Fe acquisition [ 23 ]. Hence, to sustain its high Fe demands Trichodesmium relies on Fe supply from particles, such as air-borne dust deposited on the ocean surface [ 24 – 27 ]. Trichodesmium holds various physiological adaptations that enable it to physically interact and retain dust particles. It can regulate its buoyancy and tends to form dense blooms right at the ocean surface, where air-borne dust settles [ 18 ]. In addition, the large surface area and intricate morphology of Trichodesmium colonies enable effective capture and retention of dust particles compared with single-cell phytoplankton [ 28 ]. In addition to physical associations with particles, natural tufts and puff-shaped colonies were shown to actively move dust particles [ 24 ] and shuttle dust from the periphery to colony core in a coordinated movement of the trichomes [ 25 ]. Intrigued by Trichodesmium ’s unique ability to actively collect dust particles, we set out to explore whether Trichodesmium colonies select the particles they capture and maintain in their core. An ability to sense the presence or absence of Fe on/in particles will enable Trichodesmium colonies to optimize their particle collection activity, maximize Fe supply, and minimize possible costs of carrying non-nutritional particles. Testing for selectivity in particle collection, we conducted detailed microscopic observations on ~600 natural Trichodesmium colonies from the Gulf of Aqaba that were incubated for 24 h with natural dust and silica minerals that were either cleaned of or coated with Fe. Since Fe is present in a wide range of forms and particle sizes in seawater, we also conducted a 57 Fe tracer experiment, incubating natural colonies with submicron 57 Fe hematite, to test whether this small and less soluble form of Fe could also be sensed and centered. To examine the particle size range that could be actively centered at the submicron scale, we then imaged the colonies using NanoSIMS. Last, we studied cultured Trichodemium erythraeum (IMS101), finding that the morphological shift from single filaments to colonies was critical for their associations with dust.",
"discussion": "Discussion To assist data synthesis, we schematically illustrate the interactions with dust we observed for natural and cultured Trichodesmium , highlighting the role of Fe in these interactions (Fig. 6 ). For natural colonies, the presence of Fe within or on minerals was found to influence the ST colony–particle interactions, as significantly lower number of colonies interacted with Fe-free dust or Fe-free silicates, compared with dust or Fe-coated minerals (Figs. 2a, d , 6 ). Throughout the season, the number of colonies that formed positive ST interactions with dust gradually changed (Figs. 3a , 6 ). These seasonal changes may reflect shifts between Trichodesmium species or physiological changes that influence colony adhesiveness. After the initial interaction, colonies were found to further collect, center, and retain dust and Fe-rich particles in their cores, during an overnight incubation (Fig. 2b, c, e ). The LT overnight continuous collection of dust and Fe-rich particles occurred throughout the season (Fig. 3c ), even in days with weak initial interaction (Figs. 3a , 6 ). NanoSIMS analysis revealed that natural colonies contain Fe-rich particles, both those derived from the added 57 Fe-hematite and natural sources ( 56 Fe), that are too small to be detected by light microscopy (Fig. 5 ). Fe-rich particles were found almost exclusively in the colony core, and the peripheral areas were free of particles. These observations indicate that Trichodesmium actively collect and center Fe-particles from their natural environment and can interact with a wide range particle sizes, down to the submicron (Figs. 5 , 6 ). However, the continuous particle collection was selective, and did not occur in all cases. We documented here for the first time that many colonies, in fact, discarded Fe-free particles (Fig. 4a ). By disposing of Fe-free particles, these colonies “cleaned” their surfaces (Fig. 5c ), and possibly got ready to collect new “nutritional” Fe-rich particles. Combined, our findings suggest that Trichodesmium can sense the presence of Fe on/in particles and that it coordinates the selective collection of dust and Fe-rich particles by a combination of physical interactions, centering and selective disposal of Fe-free particles (Fig. 6 ). Fig. 6 Schematic representation of Trichodesmium –dust interactions observed in this study and the role of Fe in these interactions. Fe-rich dust (middle) was preferably collected and concentrated, over Fe-free dust (left). Although the initial interactions with Fe-rich dust varied considerably over the season (middle-top), continuous dust collection during overnight incubation resulted in high particle retention (middle-bottom). Fe-free particles were not only collected to a lesser degree (top-left) but were also frequently removed from the colonies (middle-left), resulting in particle-free colonies (bottom-left). Experimenting with cultured strain IMS101 (right), did not yield any associations between dust and Trichodesmium , as long as the culture grew as single filaments (top-right). When colony formation was induced (at conditions of Fe limitation and high trichome density) the colonies readily interacted with dust (middle-right), but did not center it during an overnight incubation (bottom-right) Trichodesmium –dust interactions of cultured IMS101 did not share much similarity with the natural puff-shaped colonies. As long as the culture was growing as single filaments, it did not form any interactions with dust, regardless of its growth phase or Fe-status (Table S3 , Fig. 6 ). When colony formation was induced (at conditions of Fe limitation and high density) the colonies readily interacted with dust but did not center it during an overnight incubation (Fig. 6 ). Our findings of coupling between colony formation and dust adsorption complement those of Langlois et al. (2012) who grew IMS101 with dust and observed formation of colonies [ 26 ]. Together, these observations suggest that colony formation and physical interactions with dust are strongly related in strain IMS101 and may even be regulated by common pathways. However, these findings are not applicable to many coastal and open ocean ecosystems, where colonies prevail and even dominate the population under non-Fe limiting conditions. Basins receiving high Fe fluxes through sediment transport or aeolian dust deposition such as the Red Sea, North Atlantic, and Arabian Sea are often characterized by high abundance of colonies [ 24 – 28 ]. We hence propose that the ecological drivers and physiological mechanisms leading to colony formation, colony stability, and longevity and/or interactions with dust are complex and can vary among Trichodesmium species and within a single species over time. In particular, extra care should be taken when extrapolating IMS101 data related to metabolic functioning of colonies, drivers for colony formation, and associations with dust to oceanic settings, due to differences we and others documented [ 25 , 42 – 44 ]. Back to the natural colonies, the selection of Fe-rich particles rather than Fe-free particles, suggests that Trichodesmium can sense that the minerals contain Fe. To the best of our knowledge, an Fe-sensing system in Trichodesmium was not described. Studies on sensing of Fe by bacteria such as Pseudomonas report that Fe is sensed in its soluble form, as ions rather than minerals [ 42 ]. Hence, we propose that Trichodesmium relies on soluble Fe released from the mineral to discern if it contains Fe. The NanoSIMS images showing centering of 57 Fe-hematite, a mineral often considered as insoluble in oxygenated high pH seawater, suggests that Trichodesmium ’s sensing system is sensitive to minute levels of soluble Fe. The minerals we coated with Fe were also stabilized by heat, a process that diminished their solubility, but nonetheless selection of these particles occurred, signifying that low concentrations of soluble Fe were sensed. Although we focused here on Fe, another important limiting nutrient for Trichodesmium that may be delivered with dust is phosphorus (P). While removing Fe from dust with acid, P was also removed. Hence it is possible that the preference for natural dust over all other particle type examined (Fig. 2 ), may be due to the presence of P (and possibly other elements). In such a scenario, Trichodesmium should be also able to sense P and selectively collect P-rich particles. Further study on chemical sensing in Trichodesmium is required to fully assess these suggestions. Despite the postulated high sensitivity of Trichodesmium’s sensing system to low levels of soluble Fe, the low solubility of hematite and other Fe-minerals makes them poor suppliers of soluble Fe required for Trichodesmium growth. Since most of the Fe in dust is found as very stable mineral phases, the amount of Fe released from dust is rather minimal, as evident by frequent reports on Fe (and P) limitation in natural Trichodesmium populations in the North Atlantic that receive Saharan dust inputs [ 26 , 27 ]. In recent years we documented a variety of biochemical pathways and physical mechanisms that assist Trichodesmium obtain some Fe from mineral sources. Dust packaging in the colony core is beneficial for uptake, since cell-particle proximity facilitate uptake of Fe that dissolves from dust prior to its loss by diffusion [ 25 , 29 ]. Natural colonies can also enhance dissolution rates of dust-bound Fe [ 25 ] and Fe-oxyhyroxides such as ferrihyrite [ 29 ]. Siderophores, iron-complexing molecules synthesized by many bacteria (but not by Trichodesmium ), were proposed to assist in dust-Fe dissolution [ 45 , 46 ]. Lately we showed that Trichodesmium and its associated bacteria act together to increase availability of dust-bound iron, where bacteria promote dust dissolution by siderophore production and Trichodesmium provides dust and optimal physical settings for dissolution and uptake [ 44 ]. Our intriguing findings on selection of Fe-rich particles, adds to the arsenal of Trichodesmium’s unique adaptations for utilizing dust as an iron source. Extending our findings to additional environments we make a distinction between environments with high and low particle loads. In high particle-load, coastal environments, the newly discovered ability of Trichodesmium to remove particles can be of physiological significance. Collection and centering of large numbers of particles may disturb buoyancy regulation, mask light penetration, and may expose the colonies to heavy metals and toxic elements leaching from these particles [ 30 – 32 ]. These trade-offs can be offset if colonies can control the type and amount of retained particles and fine-tune particle nutritional value with their metabolic requirements. In low particle-load open-ocean, chemical sensing of particle composition and nature can assist in detecting and discarding invading bacteria or toxic particles. Returning to Fe, if Trichodesmium indeed sense dissolved Fe released from minerals, it may then select and retain fast Fe releasing or more soluble particles. Our findings from the Gulf of Aqaba, if shared by other Trichodesmium colonies in various ocean basins, can hence assist Trichodesmium optimize the collection and retention of dust to favor particles that can supply them with scare Fe (and P) and consequnetly contribute to nutrient cycling and productivity in the ocean."
} | 3,864 |
33906693 | PMC8077780 | pmc | 5,375 | {
"abstract": "Synthesis of inorganic nanomaterials such as metal nanoparticles (MNPs) using various biological entities as smart nanofactories has emerged as one of the foremost scientific endeavors in recent years. The biosynthesis process is environmentally friendly, cost-effective and easy to be scaled up, and can also bring neat features to products such as high dispersity and biocompatibility. However, the biomanufacturing of inorganic nanomaterials is still at the trial-and-error stage due to the lack of understanding for underlying mechanism. Dissimilatory metal reduction bacteria, especially Shewanella and Geobacter species, possess peculiar extracellular electron transfer (EET) features, through which the bacteria can pump electrons out of their cells to drive extracellular reduction reactions, and have thus exhibited distinct advantages in controllable and tailorable fabrication of inorganic nanomaterials including MNPs and graphene. Our aim is to present a critical review of recent state-of-the-art advances in inorganic biosynthesis methodologies based on bacterial EET using Shewanella and Geobacter species as typical strains. We begin with a brief introduction about bacterial EET mechanism, followed by reviewing key examples from literatures that exemplify the powerful activities of EET-enabled biosynthesis routes towards the production of a series of inorganic nanomaterials and place a special emphasis on rationally tailoring the structures and properties of products through the fine control of EET pathways. The application prospects of biogenic nanomaterials are then highlighted in multiple fields of (bio-) energy conversion, remediation of organic pollutants and toxic metals, and biomedicine. A summary and outlook are given with discussion on challenges of bio-manufacturing with well-defined controllability.",
"conclusion": "Conclusions and perspectives The potential use of nanosized materials in various areas triggers the increasing need to produce them in stable and tailorable formulations with environmental-friendly processes. There is therefore ongoing research for implementing biotechnological and green synthesis methodologies. Microorganisms, as powerful biological nanofactories, have proven themselves capable of rapidly synthesizing various nano-scale materials, especially MNPs. Shewanella and Geobacter species with specific EET pathways are competitive over other microorganisms in controllable synthesis of MNPs with well-defined sizes and structures, since they can directly synthesize MNPs through extracellular reduction without a need for transporting metal ions into the cells. Furthermore, the extracellular dissimilatory reduction abilities of Shewanella and Geobacter species allow them to produce biological RGO and hybrid materials together with various MNPs. Indeed, both direct EET via membrane-bound c -Cyts (Mtr proteins for Shewanella and Omc proteins for Geobacter ) and indirect EET mediated by self-secreted electron shuttles like flavins have been evidenced to transport intracellular electrons (reducing equivalents) across the cell membrane barriers for the reduction of metal ions ot/and GO outside the cells, thus resulting in the formation of inoganic nanomaterials. Apart from the well-controlled nanostructures and physicochemical properties, the bacterial EET-driven synthesis route has also been illustrated substantially to make nanoproducts more biocompatible than the chemically produced counterparts in general, because such biological methodology adpotes biological constituents (e.g. proteins and bio-active small molecules) instead of chemcial reagents (e.g. reducing, capping and stabilizing agents) that are usually required for the chemical synthesis. The biogenic nanomaterials with non- or low-cytotoxicity are of great promise in biomedical application. It is predictable that the biosynthestic route is competitive economically in view of the low-cost and renewbale bacterial cells acting as nanofabricating biofactories and the fast biosynthesis rate (the time required for biosynthesizing MNPs could be as low as several minutes). What's more, the biological synthesis gives a promise to self-assemble inorgnic/biotic hybrid systems through in-situ formation of inorgnic nanomaterials interfacing with bactterial cells, which not only provides a new platform to study the biotic/abiotic interfacial interaction but also broadens the application range from classical areas (e.g. antibacterial and inorganic catalysis) to some emerging interdisciplinary disciplines such as bioelectrocatalysis and biophotocatalysis. Although achieving great advances in nanobiosynthesis using Shewanella and Geobacter species as cell factories, there is still much to do to accurately tune sizes, nanostructures and properties of the biogenic nanoproducts for designated applications. In-depth elucidation and control of the EET route is beyond all doubt the key to achieve this goal. Over the past decade, studies on mechanisms underlying the bacterial EET of Shewanella and Geobacter species have made substantial progress using solid electrodes electron acceptors, but an understanding regarding how the EET pathways take part in the formation of inorganic nanoparticles is still in its infancy. Clear bioformation on the EET pathways is the foundation of controlling the sizes, shapes, locations and dispersities of nanoproducts, and advanced omics technologies such as differential proteomics combined with genomics will be helpful in identifying the key proteins or/and electron transport routes involved in the nanoparticle biosynthesis for the design and construction of new biological entities under the guidance of synthetic biology strategy to produce custom-tailored nanomaterials. Noteworthily, the artificial construction of biological/inorganic hybrids that tactfully combine functional inorganic nanomaterials with bacterial vitalities are gaining great popularity. Nanobiotechnology is highly interdisciplinary, which requires collaboration between different sciences including biology, nanoscience, materials science, chemistry, etc. We envision that with continuous progresses in the biosynthesis mechanisms and biotic/abiotic techniques, the versatile EET feature of microorganisms will unfold greater success in the biosynthesis of inorganic nanomaterials and their applications. The feasibility for the biological production of MNPs on industrial scales is also a crucial point to be considered, in particular their extracellular production, which is of great significance for product recovery. So far, only a few studies have reported the scale-up production of biogenic MNPs. As a result, how to increase the productivity of extracellular MNPs needs more attention in the future.",
"introduction": "Introduction Nanostructured materials having at least one of their dimension sizes smaller than 100 nm have demonstrated wide applicability in producing industrial products and daily necessities. The fabrication and utilization of nanomaterials have thus sparked widespread interest from both academia and industries. One such important class of nanomaterials that have allured global researchers is metal nanoparticles (MNPs), which have become crucial components in multiple cutting-edge areas including catalysis, sensors, clinical diagnosis, nanomedicine, antimicrobial agents, environmental remediation and agriculture [ 1 – 4 ]. Two categories of nanofabrication technologies are known as top-down and bottom-up approaches [ 5 ]. For the former, nanosized materials are prepared through the rupture of bulk materials to fine particles, and such a process is usually conducted by diverse physical and mechanical techniques like lithography, laser ablation, sputtering, ball milling and arc-discharging [ 6 , 7 ]. These techniques themselves are simple, and nanosized materials can be produced quickly after relatively short technological process, but expensive specialized equipment and high energy consumption are usually inevitable. Meanwhile, a variety of efficient chemical bottom-up methods, where atoms assemble into nuclei and then form nanoparticles, have been intensively studied to synthesize and modulate nanomaterials with specific shape and size [ 8 ]. Indeed, chemical methodologies, including but not limited to, aqueous reaction using chemical reducing agents (e.g. hydrazine hydrate and sodium borohydride), electrochemical deposition, hydrothermal/solvothermal synthesis, sol–gel processing, chemical liquid/vapor deposition, have been developed up to now [ 5 , 6 ]. These approaches can not only produce diverse nanomaterials with fairly high yields, but also endow fine controllability in tailoring nanostructures and properties of the products. Nevertheless, they have been encountering some serious challenges of harsh reaction conditions (e.g. pH and temperature), potential risks in human health and environment, and low cost-effectiveness. Moreover, there are biosafety concerns on products synthesized chemically using hazardous reagents, which restricts their applications in many areas, particularly in medicines and pharmaceuticals [ 9 ]. Impressively, biological methodology is becoming a favourite in nanomaterial synthesis nowadays to address challenges in chemical synthesis. Compared to chemical routes, biosynthesis using natural and biological materials as reducing, stabilizing and capping agents are simple, energy- and cost-effective, mild and environment-friendly, which is termed as “Green Chemistry” [ 2 , 6 ]. More significantly, the biologically synthesized nanomaterials have much better competitiveness in biocompatibility, compared to those chemically derived counterparts. On the one hand, the biogenic nanomaterials are free from toxic contamination of by-products that are usually involved in chemical synthesis process; on the other hand, the biosynthesis do not need additional stabilizing agents because either the used organisms themselves or their constituents can act as capping and stabilizing agents and the attached biological components in turn form biocompatible envelopes on the resultant nanomaterials, leading to actively interact with biological systems [ 2 ]. As one of the most abundant biological resources, some microorganisms have adapted to habitat contaminated with toxic metals, and thus evolved powerful tactics for remediating polluted environment while recycling metal resources [ 7 , 10 ], and some review articles on the biosynthesis of MNPs using diverse microorganisms including bacteria, yeast, fungi, alga, etc. and their applications have been published in recent years [ 1 , 2 , 6 , 7 , 10 ]. Nevertheless, our particular concern is dissimilatory metal-reducing bacteria (DMRB) like Shewanella and Geobacter species that are capable of peculiar extracellular electron transfer (EET). Due to their unique functions on electron exchange with extracellular environments, DMRB have aroused intensive research enthusiasm over the past two decades, not only on uncovering their ecological distributions and functions in nature but also on developing a series of novel technological systems in many interdisciplinary areas such as biogeochemistry, bioelectrochemistry, environmental science & engineering, and nanobiotechnology [ 11 – 14 ]. In absence of electron acceptors that are available intracellularly (e.g. oxygen and soluble molecules with high oxidation states), these bacteria can also anaerobically oxidize organic matters inside cells, and then transfer electrons released across their cell envelope barriers to extracellular redox-active minerals (electron acceptors), such as those that contain iron (Fe 2+ and/or Fe 3+ ) and manganese (Mn 3+ or Mn 4+ ), to drive the biogeochemical cycling of elements [ 15 – 18 ]. They also can use solid electrodes like graphite as terminal electron acceptors, thereby coupling bacterial intracellular energy metabolism with bioelectricity production, and such a system is referred to as microbial fuel cell [ 13 ]. These bacteria possessing EET ability are generally termed as electroactive microorganisms, and G. sulfurreducens and S. oneidensis MR-1 are the two most important model strains [ 19 ]. More impressively, many strains of DMRB have functions on the biosynthesis and bioassembly of nano-sized materials associated with their versatile EET features, especially MNPs. With great advances in elucidating bacterial EET mechanisms over the last decade, many noble metal nanoparticles [ 20 – 24 ], their alloys [ 25 , 26 ], metal oxides [ 27 , 28 ] and chalcogenides [ 29 , 30 ] have been synthesized by Shewanella and Geobacter species. Besides, the bacterial EET pathway that pumps electrons out of the cells enables the extracellular reduction of metal ions to form MNPs in the culture, which is beneficial to their subsequent separation and purification. The biogenic metal nanomaterials are promising in many application fields (Fig. 1 ). Fig. 1 Overview for biogenic nanostructured materials (metal nanoparticles and graphene) and their diverse applications Shewanella and Geobacter species are able to produce graphene through the biological reduction of graphene oxide (GO), a two-dimensional honeycomb-structured single atom layer carbon material with high hydrophilicity and biocompatibility. More interestingly, bacterial EET-driven biosynthesis provokes an interesting tactics of the self-assembling bio-abiotic hybrid composed of bacterial cell and inorganic nanomaterials, which exhibit many novel properties originated from their intimate interractions, leading to broader applications.[ 31 – 34 ] Moreover, with the innovation and development of various biotechnologies represented by synthetic biology, the controllable biosynthesis of nanomaterials with well-defined structures and features by virtue of rationally tailoring the EET pathway becomes feasible. Taking into consideration of an ever-growing research enthusiasm and great achievement, a critical review focusing especially on the biosynthesis of nanomaterials inspired by bacterial EET is needed."
} | 3,533 |
23559243 | null | s2 | 5,377 | {
"abstract": "Living cells communicate and cooperate to produce the emergent properties of tissues. Synthetic mimics of cells, such as liposomes, are typically incapable of cooperation and therefore cannot readily display sophisticated collective behavior. We printed tens of thousands of picoliter aqueous droplets that become joined by single lipid bilayers to form a cohesive material with cooperating compartments. Three-dimensional structures can be built with heterologous droplets in software-defined arrangements. The droplet networks can be functionalized with membrane proteins; for example, to allow rapid electrical communication along a specific path. The networks can also be programmed by osmolarity gradients to fold into otherwise unattainable designed structures. Printed droplet networks might be interfaced with tissues, used as tissue engineering substrates, or developed as mimics of living tissue."
} | 226 |
39435150 | PMC11492093 | pmc | 5,384 | {
"abstract": "Summary Microbes in terrestrial and aquatic ecosystems play crucial roles in driving ecosystem functions, but currently, there is a lack of comparison regarding their taxonomic and functional diversities. Here, we conducted a global analysis to investigate the disparities in microbial taxonomy and microbial-mediated biogeochemical cycles between terrestrial and aquatic ecosystems. Results showed a higher relative abundance of bacteria, especially Actinobacteria and Acidobacteria, in soil than water metagenomes, leading to a greater proportion of genes related to membrane transport, regulatory, and cellular signaling. Moreover, there was a higher abundance of genes associated with carbohydrate, sulfur, and potassium metabolisms in the soil, while those involved in nitrogen and iron metabolisms were more prevalent in the water. Thus, both soil and water microbiomes exhibited unique taxonomic and functional properties associated with biogeochemical processes, providing valuable insights into predicting and understanding the adaptation of microbes in different ecosystems in the face of climate change.",
"introduction": "Introduction Microbes are ubiquitous on Earth and play a vital role in various ecosystems, including deserts, 1 forests, 2 tundra, 3 lakes, 4 and marine environments. 5 Geographic distributions of microorganisms are a long-standing and ongoing inquiry in the field of microbiology, 6 , 7 , 8 which provides a starting point to understand ecosystem functioning, 9 such as the global biogeochemical cycling of carbon (C) and nutrients. 10 The Baas-Becking hypothesis, which posits that “everything is everywhere–the environment selects,” has long been a foundation for evaluating biodiversity patterns across various biomes. Thus, the contrasting conditions of soils and water may result in distinct microbial taxa and functional diversities between aquatic and terrestrial environments. 11 , 12 , 13 Metagenomics in international scenarios has been extensively studied for the soil and aquatic microbial communities and their functions, 14 covering a wide range of geographic regions around the globe. 15 Generally, soil microbial communities show marked temporal and spatial heterogeneity, 16 , 17 while those in the aquatic ecosystems also display considerable variability in their physical and chemical properties. 18 , 19 For instance, analyses of global topsoil samples have demonstrated that microbiomes exhibit distinct niche adaptability and spatial variations in their relative contribution to global C and nutrient cycling, 20 such as the decomposition of organic residues, 21 mineralization of nutrients, and formation of stable soil organic matter. 22 Similarly, microorganisms that play crucial roles in the C and nutrient cycling of aquatic ecosystems 23 also exhibit large-scale horizontal and vertical patterns worldwide, spanning from the ocean surface to the deep seafloor, where water temperature, salinity, and oxygen content have significant impacts on aquatic microbial diversity. 24 Although large-scale metagenomic studies have explored microbial composition and potential functional patterns worldwide, the direct comparison of microorganisms as well as their functions between soil and water ecosystems remains lacking in international scenarios. Comparing species composition and functionality of microbial communities between aquatic and terrestrial habitats can enhance our understanding of microbial diversity, and ecosystem functions, as well as provide strategies for managing and preserving transitional domains. Relationships between microbial diversity and functions remain a topic of debate, 25 although the impact of biodiversity on ecosystem stability, productivity, and resilience toward stress and disturbances 26 has long been postulated. Although microbial diversity has been found to exhibit strong correlations with specialized functions such as C and nutrient cycling, 27 emerging evidence suggests a decoupling between microbial taxonomy and function, suggesting the existence of functional redundancy within microbial communities 28 , 29 , 30 meaning that functional similarities might exist among different microbial taxa. 31 Furthermore, the extent of functional redundancy is contingent upon the environmental conditions 32 and the specific type of functions being considered. 30 , 31 Therefore, it is imperative to investigate the relationship between microbial taxa and functions within diverse functional categories in different environments. Recently, shotgun metagenomics, a robust tool for the comprehensive exploration of microbial taxonomies and functions within terrestrial and aquatic ecosystems, 33 has greatly expanded our understanding of environmental microorganisms. 34 , 35 Numerous studies have elucidated the patterns of microbial community and functional diversity as well as their interrelationships at large scales. 6 , 36 Given that most studies deposited raw data in public gene banks such as MG-RAST, 37 data from these untargeted sequencing approaches encompassing the entire microbial genome offer the capability to conduct a global metagenomic analysis of microbial members in an ecosystem 38 and provide a wealth of data for comprehensive analyses and subsequent comparisons. Here, we hypothesized that soil and aquatic microbial communities display significant taxonomic and functional disparities at the metagenomic level. Particularly, these microbial communities were expected to exhibit distinct characteristics and functional patterns in mediating biogeochemical cycles, such as C and nutrient cycling, within soil and aquatic environments. Based on existing research suggesting a potential decoupling between microbial taxonomy and function, 28 , 29 , 30 we proposed that varying degrees of functional redundancy existed among microorganisms inhabiting soil and aquatic ecosystems. Such redundancy was pivotal in stabilizing and maintaining biogeochemical processes, thereby providing a resilience mechanism that mitigates the impact of environmental changes. To test our hypotheses in this study, we constructed microbial taxonomic and functional datasets based on 933 soil metagenomes and 938 water metagenomes from recent publications in the MG-RAST server. Based on these metagenomes, our objective is to investigate the following aspects: (Ⅰ) Disparities in taxonomic composition and functional attributes between terrestrial and aquatic metagenomes; (Ⅱ) Variations in taxonomic composition and functional profiles of microbiomes involved in biogeochemical cycling across terrestrial and aquatic environments; (Ⅲ) Similarity of microbial taxonomic and functional diversities, as well as their correlations in soil and water microbiomes associated with different biogeochemical cycles.",
"discussion": "Discussion Heterogeneity in taxonomic and functional diversity between soil and water As the most heterogeneous component of the biosphere, 39 soil possesses a vast internal surface area that accommodates a substantial amount of microbial biomass. 40 Among these microbial communities, soil bacteria are widely considered to be by far the most numerous organisms, 8 , 41 surpassing other soil microorganisms such as archaea, eukaryotes, and viruses in terms of their relative abundance as also confirmed in our study ( Figure 2 A). Besides, water has also been acknowledged as a major bacterial habitat, 42 but our findings indicated that the relative abundance of bacteria in water was significantly lower compared to in soil ( p < 0.05), accompanied by an increase in the relative abundance of archaea, eukaryotes, and viruses. It was worth noting that viral metagenomes exhibited the most pronounced disparity between soil and water, with approximately 29 times higher relative abundance observed in water than in soil, a finding similar to a previous report on the earth’s virome, 43 which is possibly attributable to high viral concentration found in the marine. 43 , 44 Based on the metagenomic databases, our analysis revealed significant variations in metagenomic taxonomic compositions between soil and water ( Figure 2 B). The bacterial community was dominated by a diverse group of Proteobacteria, including Alpha-, Beta-, Delta-, and Gamma-proteobacteria, possibly due to their wide range of metabolic diversity, 45 including phototrophs, photoheterotrophs, and chemolithotrophs, which contribute to their widespread distribution and greater abundance in aquatic ecosystems. 46 , 47 Compared to the microbial communities in the watershed, soil microbiomes showed a much higher relative abundance of Acidobacteria and Actinobacteria but harbored relatively lower proportions of Bacteroidetes and Cyanobacteria compared to water microbiomes. Acidobacteria are primarily heterotrophic, with most species being aerobic or microaerophilic. 48 Due to cellular specialization, enzyme stability, and a wide range of nutrient uptake transporters, Acidobacteria communities can thrive in lower pH and stressful soil environments. 49 Although recent studies have confirmed the presence of Actinobacteria populations across different aquatic environments, 50 , 51 Actinobacteria are traditionally known as inhabitants of the soil 52 that decompose complex mixtures of organic matter from dead animals, plants, and microbes. 53 In contrast, the strict anaerobes, such as most species of Bacteroides 54 and Cyanobacteria 55 that benefit from nanomolar concentrations of oxygen in water, were more abundant in the aquatic environments. As for metagenomic reads belonging to Eukaryota, the absolute dominance of Ascomycota in all of our soil samples ( Figure 2 B) aligns with patterns observed in soils elsewhere, 56 which is dictated by their wind dispersal abilities, lifestyles, and functional attributes. 57 Compared to aquatic environments, soil provides a richer source of organic matter 58 with a solid matrix that facilitates the growth and attachment of fungal hyphae for Ascomycota 59 as decomposers or saprophytes. 60 Besides, Streptophyta and Chlorophyta constitute two major lineages of green algae, with the former encompassing land plants, 61 exhibiting contrasting distribution patterns between terrestrial and aquatic ecosystems. Moreover, we found that the differences in virus proportions at the family level between soil and water were also statistically significant ( Figure 2 B), as the groups of Microviridae and Siphoviridae are predominantly present in the soil environment while being less abundant in the aquatic habitats. Microviridae and Siphoviridae are typical DNA bacteriophages and mainly infect enterobacteria, intracellular parasitic bacteria, and spiroplasma, 62 , 63 so the increased relative abundance of bacteria may be the cause for higher relative abundance of these viruses in the soil. Conversely, we showed that Myoviridae and Phycodnaviridae exhibited higher relative abundance in water environments ( p < 0.05). The contractile tails and complex tail structures of Myoviridae may facilitate their movement and survival within environments of dynamic water flows. 64 Additionally, the enrichment of eukaryotic algae, which could be potentially infected by Phycoviridae, may be the reason for their relatively abundant distributions in aquatic ecosystems. 65 The majority of metagenomic functions were found in both terrestrial and aquatic ecosystems, but their relative abundances varied across different biomes ( Figure 2 C), especially for viruses ( Figure 2 D) that are greatly dependent on habitat conditions. 66 Although some functions appeared to be stably shared among Archaea, Bacteria, and Eukaryota, certain genes related to AAD (amino acids and derivatives), MEM (membrane transport), and PRO (protein metabolism) were hyper-variable. 67 For example, genes of MEM were associated with the microbial capability to import or export multiple compounds, facilitating active uptakes of available nutrition from the soil, 68 which may favor their survival in complex terrestrial ecosystems. Meanwhile, dissolved C, N, and P enriched in aquatic ecosystems may support the metabolisms of amino acids and protein for microorganisms, 69 as a study spanning the global ocean microbiomes reported a relatively higher abundance of these metabolic processes as well. 70 Additionally, in accordance with the previous study, 71 we found that specific genes, such as MOT (motility and chemotaxis) in soil and PPT (phages, prophages, transposable elements, and plasmids) in water, were found to be enriched divergently ( Figure 2 A), in particular, with a high percentage of MOT genes in the soil despite viruses being traditionally considered non-motile entities. In contrast, higher relative abundances of PPT in the water may indicate their potential for adaptation to aquatic environments. 72 Distinct taxonomic and functional compositions involved in biogeochemical cycling between soil and water Microbial communities play a crucial role in regulating global biogeochemical cycles depending on habitat types. 36 Specifically, the abundance of CAR (carbohydrates), SUL (sulfur metabolism), and PHO (phosphorus metabolism) genes were enriched in soils, while functions of NIT (nitrogen metabolism) and IRO (iron acquisition and metabolism) were relatively dominant in aquatic environments ( Figure 5 D). Within the CAR function, sub-level functional classifications indicated consistently less related genes in aquatic metagenomes compared to terrestrial ones, which was consistent with our previous work in the intertidal zone of a sea island. 73 Possible reasons might be that C turnover is lower under high salinity, 74 and that anaerobic microbes metabolize C slower than aerobic microbes. 75 The abundance of SUL-related genes in the soil was higher than water because microbial anabolism primarily relies on the assimilation of inorganic sulfate for sulfur (S) acquisition, 76 which was confirmed by the dominance of inorganic S assimilation observed in soil environments based on our analyses. Besides, the soil microbiome exhibited a higher relative abundance of alkanesulfonate assimilation and utilization, potentially benefiting from sulfonate enrichment in terrestrial ecosystems. 77 By contrast, dimethylsulfoniopropionate (DMSP) is a key C and S resource for marine microbial growths, 78 which is synthesized from methionine in algae and bacteria, 79 leading to the prevalence of DMSP breakdown genes in water environments. Likewise, the genes related to POT function, most classified into potassium homeostasis involved in membrane transport at sub-level classification 80 greatly dependent on environmental osmolarity, 81 were found to be more abundant in the soil. 82 However, for the genes involved in NIT, those classified into ammonia assimilation emerge as the predominant N pathway, 36 particularly in the water. In contrast, the presence of genes related to allantoin utilization, nitrate and nitrite ammonification, and nitric oxide synthase was elevated in soil environments. These phenomena were similar to the trend in a study of arid soils 83 showing that habitat conditions are deemed essential environmental variables for the interactive effects between C and N cycling. 36 Fe(II) and Fe(III), which interchange under varying redox conditions prevalent in soil and water environments. 84 Iron’s bioavailability drastically varies between soil and aquatic environments, largely dictated by pH levels, the presence of chelating agents, and redox conditions. 85 In soil, iron often exists in forms that are less bioavailable than in aquatic environments, leading to distinct microbial strategies to acquire and utilize iron, influencing community composition. 86 , 87 Vibrio species have evolved a wide array of Fe transport systems including the secretion and uptake of high-affinity Fe-binding compounds (siderophores), as well as transport systems for Fe bound to host complexes. 88 These mechanisms enable the microbes to compete for this essential element in the freshwater, estuarine, and marine systems. 89 Microbial functional groups can also serve as a partial indicator of disparity between soil and water, thereby complementing functional abundance. Our results revealed a distinct taxonomic composition of microbes involved in biogeochemical cycles between soil and water biomes ( Figures 5 B and 5C). Specifically, Acidobacteria, Actinobacteria, Chloroflexi, Deltaproteobacteria, and Firmicutes had higher relative abundances in the soil compared to water, while Bacteroidetes, Cyanobacteria, and Gammaproteobacteria displayed the opposite trends. These taxonomic groups play significant yet different roles in biogeochemical cycles. For example, Acidobacteria demonstrate the capability to metabolize recalcitrant C substrates, 90 actively participating in diverse carbohydrate breakdown, utilization, and biosynthesis through carbohydrate-active enzymes. 86 , 91 Besides, they possess a comprehensive repertoire of genes for catalyzing the metabolism of both inorganic and organic N sources. 87 Metagenomic analyses also indicate the potential for Acidobacteria to release siderophores to scavenge Fe from soil minerals by the formation of Fe(III) complexes. 48 Actinobacteria are renowned for their proficiency in the degradation of plant residues, 92 contributing to the global C cycle through plant biomass breakdowns. 93 Additionally, Actinobacteria have been found to be proficient in phosphate 94 and potassium solubilization, 95 as well as siderophore production. 96 However, Bacteroidetes are thought to exhibit a specialization in the degradation of algae-derived ocean polysaccharides 97 with a pivotal role in the mineralization of complex organic substrates such as polysaccharides and proteins. 98 Cyanobacteria could fundamentally regulate the cycling of C, N, S, and Fe through their involvements in primary production and oxygen generation, 99 , 100 such as those carrying the genes of assimilatory nitrite to ammonium and N fixation pathways. 36 Therefore, our results further showed the differences ( Figures 5 A and 6 A) and similarities ( Figure 7 A) of the taxonomic composition of microbes associated with C and nutrient cycling between soil and water metagenomes, which was also dependent on the type of biogeochemical cycling. Similar to this study, Pearson’s correlation analysis revealed positive associations between the similarities of function and taxonomy engaged in C and nutrient cycling in both soil 29 and water metagenomes. 101 Despite the heterogeneity and discontinuity of the soil compared to water in aquatic ecosystems, 102 we still revealed that soil metagenomes shared more functional compositions than water ones ( Figure 3 B), suggesting a potentially higher level of functional redundancy among soil than water microbes. Furthermore, the degrees of functional redundancy, indicated by the relationship between pairwise similarities of metagenomic taxonomy and function, were observed to depend on biogeochemical cycles as well ( Figure 4 ). For example, for the taxonomic composition of microbes associated with CAR, NIT, and PHO in the soil and water environments, there were lower correlation coefficients than other biogeochemical cycles, such as IRO and POT, suggesting a divergence of potential functional redundancy between certain functions. As C is essential for the formation of organic molecules in almost all life forms, 103 the microbial groups associated with CAR can exhibit great taxonomic diversity depending on the forms and sources of C present in various environments. 104 While Fe is abundant in the environment, its bioavailable form (such as Fe(II)) is relatively limited, 105 which constrains the diversity of microbial groups involved in the metabolisms of Fe, 63 such as specialized capabilities for Fe utilization and transformation. 106 , 107 Microbial co-occurrence network analysis provides a unique and robust tool for understanding the interactions within microbial communities across different environments. The larger and more complex nature of the soil microbial networks suggests that these communities have to contend with a more diverse array of nutritional sources and ecological niches. 108 In the soil environment, certain functions such as CAR exhibit high modularity, indicating that some microbial communities may have established tight correlations for the collective utilization of resources. These modular networks could prove beneficial for sustaining ecosystem functions and offer better resilience to environmental change. 109 However, compared to aquatic metagenomes, soil microbial networks demonstrate longer average path distances in non-carbon-related functions such as NIT, PHO, and SUL cycling, potentially suggesting more complex pathways for nutrient transformations and functional complementarity among microorganisms. 110 Moreover, the relatively simplified network structures of aquatic microbial communities may reflect moderate nutrient levels and less environmental heterogeneity, allowing for stable and less complex community structures. 111 Limitations of the study The extraction efficiency of DNA from environmental samples might affect the comparability between terrestrial and aquatic metagenomes. But all the studies followed standardized procedures for both DNA extraction and sequencing analysis, so we redeemed the observed variations in results were thus likely to be attributable to the differences in environmental sampling rather than to the DNA extraction methods themselves in this research. Future work should investigate the contribution of DNA extraction efficiency to the differences in their microbial compositions."
} | 5,452 |
38730945 | PMC11085887 | pmc | 5,385 | {
"abstract": "Environmental pollution and energy crises have garnered global attention. The substantial discharge of organic waste into water bodies has led to profound environmental contamination. Photocatalytic fuel cells (PFCs) enabling the simultaneous removal of refractory contaminants and recovery of the chemical energy contained in organic pollutants provides a potential strategy to solve environmental issues and the energy crisis. This review will discuss the fundamentals, working principle, and configuration development of PFCs and photocatalytic microbial fuel cells (PMFCs). We particularly focus on the strategies for improving the wastewater treatment performance of PFCs/PMFCs in terms of coupled advanced oxidation processes, the rational design of high-efficiency electrodes, and the strengthening of the mass transfer process. The significant potential of PFCs/PMFCs in various fields is further discussed in detail. This review is intended to provide some guidance for the better implementation and widespread adoption of PFC wastewater treatment technologies.",
"conclusion": "5. Conclusions In this review, the fundamentals, working principle, and configuration development of PFCs and PMFCs were summarized. The most representative research papers specific to PFCs/PMFCs were highlighted in order to improve wastewater treatment in terms of coupled advanced oxidation technology, the rational design of high-efficiency electrodes, and the strengthening of the mass transfer process. Their applications in various fields such as hydrogen synthesis, carbon dioxide capture, environmental biosensors, wearable energy storage, and power generation devices were also reviewed. The development of new and efficient PFC/PMFC systems will improve the efficiency of wastewater co-removal and reduce energy consumption, which has an important scientific and application value for the treatment and resource recovery of refractory organic pollutants in wastewater.",
"introduction": "1. Introduction Environmental pollution and energy crises represent two formidable challenges confronting the sustainable development of human society [ 1 , 2 , 3 , 4 ]. As societal advancement accelerates, the severity of energy and environmental issues continues to escalate. Given the pressing nature of contemporary water pollution challenges, research and development in water treatment technologies assume paramount importance [ 5 , 6 ]. Water treatment processes are typically categorized into physical, chemical, and biological methods based on their operational principles [ 7 , 8 , 9 ]. Wastewater contains a plethora of organic compounds rich in chemical energy, representing a misallocated resource. However, prevailing conventional water treatment strategies primarily emphasize pollutant removal to achieve regulatory effluent standards [ 10 , 11 ]. The imperative to reduce energy consumption while ensuring efficient wastewater treatment remains an urgent concern [ 12 , 13 , 14 ]. Fuel-cell-based water pollution control systems represent cutting-edge technologies for wastewater resource utilization, providing simultaneous wastewater treatment and electricity generation [ 4 , 15 , 16 , 17 ]. This innovation carries significant implications for tackling water pollution and mitigating energy deficits. Among these technologies, the integration of photocatalytic fuel cells (PFCs) and photocatalytic microbial fuel cells (PMFCs) based on photoelectrochemical and photocatalytic bioelectrochemical processes offers a comprehensive solution characterized by high efficiency, energy conservation, and operational simplicity [ 18 , 19 , 20 ]. These integrated systems present a promising approach for addressing the treatment of stubborn organic wastewater. He et al. [ 2 ] reported the fundamentals and technical advancements of PFCs, with a particular emphasis on novel fuel cell configurations. Meanwhile, the rational design of electrode materials was reviewed, focusing on surface properties, morphology, facet structure, and interface reaction engineering [ 3 ]. Ni et al. [ 21 ] summarized recent progress in the development of photoanode/photocathode materials, cathodic materials, system configurations, and radical reaction processes, giving five key strategies to enhance the dynamics and charge transfer properties of the constructed system. Additionally, the challenges, perspectives, and future studies were extensively discussed for different PFC systems. In this review, the fundamentals, working principle, and configuration development of PFCs and photocatalytic microbial fuel cells (PMFCs) were discussed. The strategies for improving the wastewater treatment performance of PFCs/PMFCs in terms of coupled advanced oxidation processes, rational design of high-efficiency electrodes, and strengthening of mass transfer process are highlighted. The significant potential of PFCs/PMFCs in various fields is further discussed in detail. Clearly improving the strategy of the PFC purification of wastewater will help its future application in practical wastewater treatment."
} | 1,262 |
38327185 | PMC10894034 | pmc | 5,387 | {
"abstract": "Abstract The way strong environmental gradients shape multispecific assemblages has allowed us to examine a suite of ecological and evolutionary hypotheses about structure, regulation and community responses to fluctuating environments. But whether the highly diverse co-occurring microorganisms are shaped in similar ways as macroscopic organisms across the same gradients has yet to be addressed in most ecosystems. Here, we characterize intertidal biofilm bacteria communities, comparing zonation at both the “species” and community levels, as well as network attributes, with co-occurring macroalgae and invertebrates in the same rocky shore system. The results revealed that the desiccation gradient has a more significant impact on smaller communities, while both desiccation and submersion gradients (surge) affect the larger, macroscopic communities. At the community level, we also confirmed the existence of distinct communities within each intertidal zone for microorganisms, similar to what has been previously described for macroorganisms. But our results indicated that dominant microbial organisms along the same environmental gradient exhibited less differentiation across tidal levels than their macroscopic counterparts. However, despite the substantial differences in richness, size and attributes of co-occurrence networks, both macro- and micro-communities respond to stress gradients, leading to the formation of similar zonation patterns in the intertidal rocky shore.",
"conclusion": "Conclusion Microbial ASVs exhibit significantly less variation across tides than the most common macroscopic organisms at the species/ASVs level. However, at the community level, most indicators of community structure across the gradient were similar between microbes and macroorganisms. Still, the resulting co-occurrence patterns of positive associations differ between both networks. This supports that communities of macroorganisms and microorganisms respond in different ways to the same environmental forcing, possibly because of differences in their resiliency to ambient stress, different mediating effects of biotic interactions and dormancy in microbial communities. However, despite the substantial differences in richness, size and attributes of co-occurrence networks, both macro- and micro-communities respond to stress gradients, leading to the formation of similar zonation patterns in the intertidal rocky shore.",
"introduction": "Introduction Understanding the mechanisms and processes responsible for patterns of abundance and distribution of species across environmental gradients is one of the main goals of community ecology (Mittelbach and McGill 2019 ), and one of the most striking patterns is the zonation of dominant organisms that occupy different parts of the environmental gradient. These patterns have served as the basis to test core hypotheses about the organization of communities (e.g. Whittaker 1959 ) and the ecological processes shaping fundamental and realized species’ niches, such as physiological tolerances and species interactions (Connell 1961a , b , Menge and Sutherland 1987 ). For microorganisms, the “everything is everywhere, but the environment selects” hypothesis, set forth by Lourens Baas Becking in the early 1930s, has inspired the microbial biogeographical and ecological research of the past decades (de Wit and Bouvier 2006 , O'Malley 2007 , Fontaneto 2011 , Hanson et al. 2012 ) and suggests that microbial communities are primarily determined by unlimited dispersal and secondarily by environmental selection. Microbial biodiversity is significantly influenced by environmental gradients, particularly factors that impact soil or water pH (Rousk et al. 2010 , Krause et al. 2012 ), temperature (Logares et al. 2020 ) and resource availability (Follows et al. 2007 ). The local environment plays a critical role in selecting which microorganisms are present and, like macroscopic organisms, the patterns of abundance and composition across environmental gradients are shaped by abiotic conditions and interactions among co-occurring microbes (Fontaneto 2011 , Hanson et al. 2012 , Mandakovic et al. 2018 ). While numerous studies have examined the biogeography and macroecology of microorganisms, comparing them with macroorganisms (Astorga et al. 2012 , Barberán 2014 , Shade et al. 2018 , Soininen et al. 2018 , Graco‐Roza et al. 2022 ), there is a limited number of studies that assess how both macroorganisms and microorganisms respond to the same environmental gradient within the same location. However, some questions remain: Are microbial communities structured differently across the same environmental gradients than their co-occurring macroscopic counterparts? If both vary across sharp environmental gradients, do the patterns of community structure resemble those observed in macroscopic organisms at the stressful and benign ends of a gradient? Addressing these questions and similar ones enables us to challenge our ecological models and gain valuable insights into the differences in organization between the microscopic and macroscopic worlds. One of the most extensively studied zonation patterns occurs between the highest and lowest tides along many marine rocky shores worldwide (Barnes and Hughes 1999 , Raffaelli and Hawkins 2012 ). This habitat experiences a rapid transition from entirely aquatic to completely terrestrial conditions within just a few meters (Thompson et al. 2002 , Harley and Helmuth 2003 ). Within their tolerance limits, species consistently exhibit varying levels of abundance at different tidal levels (Stephenson and Stephenson 1949 , Connell 1961a , b ). Co-occurrence network analyses also reveal modules, which are clusters of highly interconnected species, associated with specific zonation bands primarily due to shared environmental preferences (Freilich et al. 2018 ). The intertidal zonation of macroscopic organisms extends beyond the tidal regime, which establishes the stress gradient through submersion events and desiccation gradients (Denny and Paine 1998 , Raffaelli and Hawkins 2012 ) (Fig. 1 ). It arises from various interactive physical factors such as wave exposure and associated mechanical stresses, desiccation (Evans 1947 ), temperature (Wethey 1983 ) and solar radiation (Santelices 1990 ). Additionally, species interactions, including interspecific competition for space (Connell 1961b ), food acquisition (Underwood 1972 ), facilitation (Bertness and Leonard 1997 ) and predation (Connell 1961a , Paine 1966 ), play a significant role in shaping intertidal zonation. Consequently, this zonation results from the combined effects of environmental stressors that affect species differently and the propagation of these effects throughout the community via species interactions. Figure 1. Dominant species of macroalgae and macroinvertebrates typically found in wave-exposed intertidal rocky habitats of central Chile across the high, middle and low tidal zones (adapted from Santelices 1990 ). The figure illustrates the principal variables influencing the stress gradient. In intertidal environments on rocky shores, microbial communities can exist as individual cells or form distinct biofilms that colonize nearly all surfaces (Callow and Callow 2011 , Navarrete et al. 2019 ). These biofilms consist of organisms from all three domains of life and are bound together by extracellular polymeric substances, exhibiting various emergent properties such as hydrophobicity, viscoelasticity and drug resistance (Davey and O'Toole 2000 , Schuster et al. 2019 ). Numerous studies have demonstrated that the abundance and composition of intertidal epilithic biofilms are influenced by environmental factors such as temperature, desiccation, UV radiation and wave action (Thompson et al. 2004 , 2005 ), as well as ion and nutrient concentrations (Decho 2000 , Dang and Lovell 2016 ). Additionally, microbial competition and predation (Dang and Lovell 2016 ), competition with macroscopic sessile species like macroalgae for space (Callow and Callow 2011 ), top-down control by grazing macroinvertebrates (Lubchenco 1978 , Underwood 1984 , Arboleda-Baena et al. 2023 ), non-trophic interactions involving marine grazers that feed on epilithic biofilm communities (Iguchi et al. 1982 , Connor 1986 , Arboleda-Baena et al. 2022 ) and indirect effects induced by disturbances from macroorganisms (e.g. macroalgal loss) (Vadillo Gonzalez et al. 2023 ), all exert significant influence over the abundance and tidal distribution of major microbial biofilm groups. Okamoto et al. ( 2022 ) have provided valuable insights into specific aspects of how abiotic gradients in intertidal sandy environments influence the structure of microscopic communities (Okamoto et al. 2022 ). In their study, they observed distinct differences across intertidal zones, including high intertidal, mid intertidal and low intertidal sandy communities. These variations were found to be correlated with moisture levels, organic carbon content and phosphate content. However, it is worth noting that there may still be unexplored dimensions of this phenomenon within both macrobial and microbial intertidal rocky shore communities at the same locality. These unexplored dimensions could include emergent community properties such as species richness, diversity and co-occurrence network structures. In this study, we compare the patterns of zonation in taxonomic diversity, richness and co-occurrence network structures of microbial intertidal communities found on wave-exposed rocky shores in central Chile with the well-documented patterns observed in co-occurring macroscopic organisms (Castilla 1981 , Santelices 1990 , Kéfi et al. 2015 , Freilich et al. 2018 ). Utilizing the established zonation bands for macroorganisms (Fig. 1 ), we investigate four hypotheses: We seek to determine whether taxonomic richness and diversity exhibit similar trends across the environmental gradient. We explore the presence of exclusive communities within each intertidal zone for both macroorganisms and microorganisms. We examine whether microbial communities demonstrate an equivalent level of differentiation across tidal levels compared with their macroscopic counterparts. Given that co-occurrence networks of macroorganisms typically exhibit modules, essentially distinct groups of species corresponding roughly with zonation bands, we hypothesize that a similar pattern may emerge in microbial networks.",
"discussion": "Discussion Microorganisms are foundational to the function of diverse habitats. Understanding their patterns is crucial, especially when comparing them with macroorganisms. However, we acknowledge the inherent challenge in comparing microbial ASV taxa with macroorganism species, recognizing that these entities operate at different biological scales. The deliberate use of the term “ASV/species” was aimed at navigating this distinction; nevertheless, we acknowledge the importance of discussing how the differing scales of microbial and macroscopic communities may introduce variability in response patterns across environmental gradients. In this section, we will delve deeper into the results of this comparison, considering the nuances associated with the ecological dynamics of both microorganisms and macroorganisms, in the context of our study. Our approach, which combines intertidal surveys and experiments, enabled us to analyze microbial communities and draw meaningful comparisons with macroscopic organisms along one of the world's most extensively studied environmental gradients. This also allowed us to gain insights into the processes that shape the ecological organization of microbial organisms, which may differ significantly from those influencing the co-occurring macroscopic components of these communities. Our findings reinforce the concept that microbes are less influenced by environmental fluctuations compared with macroscopic organisms. We hypothesize that this distinction arises because microbes primarily respond to desiccation, while macroorganisms in the same locality contend with both desiccation and submersion (a highly wave-exposed environment). In the Chilean rocky intertidal shore, the dominant species of macroorganisms found in this study in each zone were similar to those reported in previous studies (Castilla 1981 , Broitman et al. 2001 ). As for microorganisms, widely distributed groups predominantly include Alphaproteobacteria, Gammaproteobacteria, Bacteroidetes, Cyanobacteria, Planctomycetes, Actinobacteria and Verrucomicrobia; these groups were previously described in biofilms of similar systems (Lee et al. 2014 , Taylor et al. 2014 , Tan et al. 2015 , Ding et al. 2018 , Kerfahi et al. 2020 ) and have been widely described on different marine biofilms (Dang and Lovell 2016 ). Additionally, we observed ASVs from Acidobacteria, Chloroflexi, Deltaproteobacteria, Firmicutes, Fusobacteria and Eremiobacterota with extensive distribution across all three intertidal zones in our study. Conversely, some groups described in previous studies within the same system, such as Chloroflexi, Gemmatinomadetes and Chlorobi (Kerfahi et al. 2020 ), Deltaproteobacteria and Firmicutes (Tan et al. 2015 ), were not found to be abundant in our findings. The primary abiotic stressors in the intertidal zone are radiation, desiccation and temperature (Thompson et al. 2004 ). On the rocky coasts of various locations, the abundance of epilithic biofilms follows a temporal and spatial pattern, increasing during winter and decreasing during summer (Aleem 1950 , Castenholz 1961 , Underwood 1984 , Hill and Hawkins 1991 , Jenkins et al. 2001 ). One group of microorganisms with adaptive mechanisms to various stressors, such as changes in salinity, desiccation, light fluctuations, temperature variations, UV rays and full immersion periods, is Cyanobacteria. In our study, this group of microorganisms is widely distributed in Chilean intertidal zones. This observation aligns with findings in similar systems (Díez et al. 2007 , Maggi et al. 2017 , Ding et al. 2018 , Kerfahi et al. 2020 ). However, Cyanobacteria from the Xenococcaceae and Phormidesmiaceae families solely exhibit a higher abundance in the high and middle intertidal zones, respectively. Although we hypothesized that the intertidal community would be dominated by cyanobacteria, as reported in previous studies in similar systems (Díez et al. 2007 , Maggi et al. 2017 , Ding et al. 2018 , Kerfahi et al. 2020 ), we observed that the community was dominated by other photosynthetic groups such as diatoms (personal observations). Therefore, for future studies, both the bacteria/archaea and eukaryotic microorganisms should be investigated to obtain a more comprehensive understanding of the entire microbial community. One of our objectives was to assess whether taxonomic richness and diversity exhibit consistent patterns along the environmental gradient for both macrobial and microbial communities. The results of richness and diversity, quantified using the Shannon index, for macroorganisms align with the predictions of the Intermediate Disturbance Hypothesis (IDH) (Connell 1978 ). In essence, the IDH posits that intermediate levels of environmental disturbance promote greater species coexistence, in contrast to situations with low or high disturbance rates. The high intertidal zone experiences substantial stress due to time exposure to radiation, high temperature, UV light and desiccation. Conversely, the low intertidal zone encounters higher submersion pressure, often accompanied by robust waves or surges. Consequently, we anticipate the middle intertidal zone to harbor the highest richness and diversity, and indeed, this is what we did find in the case of macroorganisms. However, when examining microorganisms, we do not observe the same pattern. Instead, we observe an increase in richness and diversity in tandem with the submersion gradient. This suggests that within this community, the desiccation gradient exerts a more pronounced influence on smaller communities, whereas both desiccation and submersion gradients impact the larger, macroscopic communities. Other studies have corroborated this discovery and reported a greater abundance of epilithic biofilms in the lower intertidal zone compared with the upper zone. This difference is attributed to desiccation and UV light exposure (Aleem 1950 , Castenholz 1963 , Underwood 1984 , Thompson et al. 2004 ). Consequently, the gradients of abiotic factors in the intertidal environment may foster adaptations to these challenging conditions, potentially leading to an increase in habitat specialists (Logares et al. 2013 ). This observation also hints at a marine rather than a terrestrial origin for intertidal microorganisms, mirroring the same patterns seen in rocky shore macroorganisms. Conversely, we have confirmed the presence of distinct communities within each intertidal zone for microorganisms, as previously described for macroorganisms (Santelices 1990 , Broitman et al. 2001 , Thiel et al. 2007 ). It is worth noting that, in the context of the intertidal rocky shore, similar questions have previously only been explored in relation to the microbiome of mollusks and macroalgae (Brodie et al. 2016 , Offret et al. 2020 ). However, our study expands upon this inquiry by encompassing the entire macroscopic community in conjunction with co-occurring epilithic microbial communities. Previous studies have indicated that free-living microbial communities in the high, mid and low intertidal zones were distinguishable and exhibited correlations with moisture, organic carbon and phosphate content (Okamoto et al. 2022 ). This suggests that the distribution of microorganisms is influenced by abiotic gradients in the intertidal environment. However, few taxa at the genus or species level individually contributed to this zonation pattern; rather, a unique combination of multiple microbial taxa was probably responsible (Okamoto et al. 2022 ). This is why we compared the coefficient of variance in the intertidal rocky shore for both macro- and micro-communities at the order and species/ASVs levels. The results indicated that although microbial communities exhibit different communities in the three intertidal zones, they show a lower degree of differentiation across tidal levels when compared with their macroscopic counterparts under the same environmental gradient. The 14 most common microbial ASVs show significantly less variation across tides than the 14 most common macroscopic organisms. This suggests that the microorganisms perceive a more homogeneous environment and/or are more resistant to the associated stress. Additionally, it can be suggested that an important contribution from the species in the water pool may have influenced these results. The commonly proposed explanation for this phenomenon is that the environmental conditions in the intertidal rocky shore, as perceived at the microscopic level, may be less demanding than those perceived by macroscopic organisms. While this is a valid hypothesis, it is also plausible that these microorganisms are inherently more resistant to stress gradients of a similar nature. This aspect can only be thoroughly assessed through experimental manipulation of stress levels. Furthermore, it is essential to investigate to what extent the cage used to exclude macroscopic organisms may have reduced the amplitude of the stress gradient. Regardless of the mechanism responsible for differences in stress-related responses at the “species” level, we observed a significant buffering effect of species richness within higher taxa, such as orders, on the response to the stress gradient when considering both microorganisms and macroorganisms together ( Supplementary Information: Fig. S3 ). Furthermore, this effect appeared to be consistent between these groups, as indicated by the non-significantly different slopes. This suggests that increased species redundancy within a taxon confers resistance to environmental stress, a finding worth further exploration as it implies similarities between the microscopic and macroscopic worlds. However, it is important to exercise caution when interpreting these results, particularly when analyzing microscopic organisms separately, as the linear relationship was marginally non-significant in that context. These findings also emphasize the need for caution when studying microbial communities across space without resolution to the ASV level, as aggregating data at higher taxonomic levels (i.e. order) may ambiguously support the “everything is everywhere” paradigm. Given that co-occurrence networks of macroorganisms typically exhibit modules corresponding roughly with zonation bands, we hypothesized that a similar pattern may emerge in microbial networks, potentially resulting in the formation of zonation-related compartments. Our results showed that co-occurrence networks of macroorganisms and microorganisms displayed similar levels of connectivity and transitivity between clusters, despite the large differences in absolute richness, indicative of non-random clustering within the networks (Röttjers and Faust 2018 ). Consequently, these networks had modules (clusters of species/ASVs highly connected) corresponding roughly with tidal levels. These clusters of species were generally more interconnected than the networks as a whole. Co-occurrence networks of microorganisms have been demonstrated to exhibit structural patterns influenced by environmental factors such as pH, aridity and net primary productivity (Delgado-Baquerizo et al. 2018 ). As a result, our approach of identifying habitat specialist clusters showed a stronger correlation with the environmental gradient. Freilich et al. ( 2018 ) observed that co-occurrence networks might represent niche preferences of component species more than they reflect specific biotic interactions. Therefore, networks constructed from known interactions (i.e. consumption) are not directly comparable with co-occurrence networks. Additionally, co-occurrence networks of microorganisms are structured by environmental heterogeneity, for example, pH, aridity, net primary productivity in soil (Delgado-Baquerizo et al. 2018 ) and depth in a marine system (Cram et al. 2015 ). With this caveat in mind, it is important to note that co-occurrence networks of microorganisms and macroorganisms exhibit several remarkably similar attributes and some important differences across the tidal gradient. Highly positive associations were observed for species restricted to the high intertidal zone (Freilich et al. 2018 ), whereas highly positive correlations were observed for ASVs limited to the low intertidal zone. The low intertidal zone is generally expected to be the benign end of the environmental stress gradient for organisms of marine origin, which include both microorganisms and macroorganisms. Still, the resulting co-occurrence patterns of positive associations differ between both networks. This supports that communities of macroorganisms and microorganisms respond in different ways to the same environmental forces, possibly because of differences in their resiliency to ambient stress, different mediating effects of biotic interactions and dormancy in microbial communities."
} | 5,861 |
36844635 | null | s2 | 5,389 | {
"abstract": "Integrating light-harvesting materials with microbial biochemistry is a viable approach to produce chemicals with high efficiency from the air, water, and sunlight. Yet it remains unclear whether all absorbed photons in the materials can be transferred through the material-biology interface for solar-to-chemical production and whether the presence of materials beneficially affect the microbial metabolism. Here we report a microbe-semiconductor hybrid by interfacing CO"
} | 118 |
30037463 | null | s2 | 5,393 | {
"abstract": "Mechanical stimuli play a critical role in organ development, tissue homeostasis, and disease. Understanding how mechanical signals are processed in multicellular model systems is critical for connecting cellular processes to tissue- and organism-level responses. However, progress in the field that studies these phenomena, mechanobiology, has been limited by lack of appropriate experimental techniques for applying repeatable mechanical stimuli to intact organs and model organisms. Microfluidic platforms, a subgroup of microsystems that use liquid flow for manipulation of objects, are a promising tool for studying mechanobiology of small model organisms due to their size scale and ease of customization. In this work, we describe design considerations involved in developing a microfluidic device for studying mechanobiology. Then, focusing on worms, fruit flies, and zebrafish, we review current microfluidic platforms for mechanobiology of multicellular model organisms and their tissues and highlight research opportunities in this developing field."
} | 265 |
36388969 | PMC9663904 | pmc | 5,394 | {
"abstract": "Summary Energy harvesting technologies that convert fluid energy into usable electrical energy are of great significance, especially in long-distance pipeline systems. Here, in order to avoid the collision of conventional galloping triboelectric nanogenerators (GTENGs), and cause material damage or noise, a freestanding gallop-based triboelectric-piezoelectric hybrid nanogenerator (HG P-TENG) is proposed to reduce material wear and improve the reliability of GTENG. Two piezoelectric sheets are attached to the cantilever beam. The root-mean-square (RMS) and peak output power of the HG P-TENG are 68.9 μW and 1.27 mW, respectively. To improve the harvesting efficiency, the fixed copper electrodes are segmented, and experiments indicate that this way of segmenting electrodes can improve the energy harvesting efficiency. Finer electrodes can effectively increase the charging rate of capacitors. A self-powered thermohygrometer and light-emitting diodes (LEDs) are demonstrated in the wind tunnel. It demonstrates that the proposed hybrid nanogenerator will exhibit great potential in pipeline systems.",
"conclusion": "Conclusions In the paper, a galloping-based triboelectric-piezoelectric hybrid nanogenerator (HG P-TENG) is proposed to harvest gas energy in long-distance pipeline, which can provide continuous energy supply for alarm devices and sensors. The use of galloping for energy harvesting effectively reduces material wear and improves the reliability of GTENG. And through the rational construction design of HG P-TENG, the cut-in wind speed and the wear of TENG material are effectively reduced, thus improving the efficiency and durability of the device. Moreover, with periodic contact, FEP can be recharged, offering the possibility of long-term, efficient energy harvesting. Furthermore, by segmenting the electrodes, the energy harvesting efficiency is greatly improved. The maximum I sc of 2-degrees G-TENG has a 34% improvement rather than 6-degrees. Comparing the capacitor charging time, the charging time of 2-degrees G-TENG and HG P-TENG (2-degrees) is reduced by 33% and 52% compared with that of 6-degrees G-TENG, respectively. Then, at a wind speed of 6.24 m/s, the maximum RMS output power of the 6-degrees, 3-degrees, 2-degrees G-TENG, and G-PENG is 52.2, 38.5, 34.7, and 16.7 μW, respectively. In addition, the feasibility of this HG P-TENG to power a thermohygrometer is also demonstrated. This study uses a piezoelectric-triboelectric hybrid nanogenerator to harvest energy from airflow in pipes, which has great potential in long-distance smart pipeline monitoring systems.",
"introduction": "Introduction With the development of the Internet of Things and the digital Internet, a large number of distributed micro-sensors are required to collect various information. These sensors require low power, some as little as a few microwatts, but still need to be powered by conventional methods such as batteries. Traditional batteries have the disadvantages of large size, environmental pollution, and need to be replaced periodically ( Beeby et al., 2006 ), whereas obtaining energy from the environment through an energy harvester can effectively provide a durable and stable energy supply for the micro-sensor. There are various types of energy in the environment, such as solar energy, wind energy, tidal energy, biomass energy, etc., and wind energy is undoubtedly an inexhaustible and very clean energy. So far, energy harvesting technologies have been extensively developed in several types: triboelectric ( Liu et al., 2021 ; Chen et al., 2018 ; Fan et al., 2012 ; Wang et al., 2017 ; Wang, 2014 ), piezoelectric ( Abdelkefi et al., 2014 ; Alhadidi et al., 2020 ; Wang et al., 2021 ; Hu et al., 2018a ), electrostatic ( Mitcheson et al., 2004 ; Basset et al., 2014 ), pyroelectric ( He et al., 2022b ), and electromagnetic ( Avila Bernal and Linares García, 2012 ; He et al., 2022a ; Vicente-Ludlam et al., 2014 ). Compared to several other energy harvesting techniques, the use of piezoelectric and triboelectric is more suitable for this type of low frequency vibration, and a more systematical comparison is shown in Table S1 . Therefore, providing stable energy for micro-sensors via triboelectric nanogenerator (TENG) and piezoelectric nanogenerator (PENG) is a feasible solution. Since TENG was proposed by Wang ( Fan et al., 2012 ) in 2012, a lot of research work has been done on TENG and it has been widely used in various scenarios, such as wearable electronic devices ( Wang et al., 2013 ; Tee et al., 2012 ; Xu et al., 2021 ), micro-sensors ( Li et al., 2021 ; Yang et al., 2021 ) and energy harvesting ( Park et al., 2019 ; Zhang et al., 2021b ; Wang et al., 2015 , 2021 ), and other related work. Long-distance pipeline contains enormous amounts of energy, so energy harvesting is a feasible way to power pipeline monitoring devices. TENG for gas energy harvesting is a very interesting area of research. There are three main types: fluttering ( Hu et al., 2019 ; Ren et al., 2021 ; Olsen et al., 2019 ; Bae et al., 2014 ; Wang et al., 2020d ; Jiang et al., 2020 ), rotary ( Wen et al., 2015 ; Li et al., 2022 ; Fu et al., 2021 ), and galloping ( Zhang et al., 2020a ; Wang et al., 2020c ). Xia et al. investigated the effects of wind speed, length and thickness of the film, and spacing between the upper and lower of two flat electrodes on the performance of the TENG. The results show that choosing appropriate structural parameters can effectively improve the performance of the energy harvester and reduce the cut-in wind speed ( Xia et al., 2021 ). Lin et al. designed an angle-shaped TENG (AS-TENG) that effectively increased the contact area between fluorinated ethylene-propylene (FEP) film and aluminum electrode. The AS-TENG can be facilely integrated into a 360° radial array, which greatly increased the effective area of the whole system with high level of integration. At the same time, a wedge-shaped wind guide channel is also proposed to reduce the cut-in wind speed, which is more suitable for collecting breezes ( Lin et al., 2019 ). In addition, more and more researchers are using rotary sliding triboelectric nanogenerators (RS-TENGs) to harvest wind energy. Xie et al. first proposed a rotary cup-structured triboelectric nanogenerator (R-TENG) to drive the flexible polytetrafluoroethylene (PTFE) to continuously sweep across an aluminum sheet under the action of breezes in the environment, and the energy was collected through continuous contact separation ( Xie et al., 2013 ). Zhang et al. studied elastic rotary triboelectric nanogenerators (ER-TENGs), which effectively reduced the friction between electrodes through material selection and structural design. Compared with conventional ER-TENGs, the energy harvesting efficiency is doubled and the durability is even quadrupled, greatly improving the practicality of the device ( Zhang et al., 2021a ). Most of the current research is still focused on the exploitation of R-TENG for wind energy harvesting. However, using galloping for energy harvesting has the advantage of a simpler structure and high robustness ( Hu et al., 2018b ). Therefore, a gallop-based TENG is designed. Zhang et al. created a galloping triboelectric nanogenerator (GTENG) based on contact electrification between two flexible beams. It is able to achieve an output voltage of more than 200 V at a low wind speed of 1.4 m/s through the cross-flow galloping vibration of a main beam with a prism and collision with an auxiliary beam ( Zhang et al., 2020a ). Zeng has developed a novel TENG based on the flow-induced vibration (FIV) effect (FIV-TENG) which is packed into a bluff body. It not only reduces the environmental interference, but also avoids the huge rotational resistance and frictional wear faced by ordinary TENGs ( Zeng et al., 2020 ; Ren et al., 2020 ). However, this type of beating can easily cause permanent damage to the structure. The reliability of the GTENG is one of the most important considerations, while durability and robustness are also key issues ( Li et al., 2020 ). It is necessary to develop a structure that can work for a long time without damaging the material. To solve the problems of low reliability and poor durability of current GTENG, in this paper, a gallop-based triboelectric-piezoelectric hybrid nanogenerator (HG P-TENG) is proposed. In order to reduce system damping, most areas of the structure are designed to be non-contact, which also can reduce the cut-in wind speed and at the same time reduce the friction loss of material. Although the charges on the surface of FEP material can be stored for several days, it will dissipate gradually and is not suitable for long-time operation. Therefore, the flexible rabbit fur brushes are designed on the outer side of the both sides of electrode for periodic contact with the FEP film to continuously provide charges to the FEP surface. Furthermore, the electrode layers are segmented and the results show that the 6-degrees G-TENG has higher performance which can generate an RMS and peak power of 52.2 μW and 1.13 mW at a wind speed of 6.24 m/s. Although the 2-degrees G-TENG has only an RMS power of 34.7 μW, it can generate more current cycles in one period, thereby charging the capacitor faster. At the same time, to increase the power output, two piezoelectric sheets are attached to the cantilever beam, and the maximum output power of the piezoelectric sheets is about 16.7 μW when the wind speed is 6.24 m/s. To demonstrate the durability of the HG P-TENG, about 250,000 cycles were tested with only a slight decrease in voltage. This fully illustrates the advantages of hybrid nanogenerator in terms of improving power and durability of energy harvesting. To reveal its great potential in smart pipeline monitoring systems, the feasibility of this HG P-TENG to power thermohygrometer and light-emitting diodes (LEDs) at a wind speed of 6.24 m/s is also investigated.",
"discussion": "Results and discussion Structure design and principle The whole experiment is carried out in a circulating wind tunnel, which can generate a highly uniform incoming flow with a turbulence degree of about 0.5%, and the cross-sectional size of the experimental section is 50 × 50 cm Figure 1 E shows the photograph of HG P-TENG, including G-PENG (Galloping PENG) and G-TENG (Galloping TENG). The structure of HG P-TENG is mainly divided into two parts, the first part is the wind vibration transducer, which uses the galloping vibration for energy harvesting. The cantilever beam is mounted on a bracket, and a foam prism is mounted on top of the cantilever beam. Galloping occurs when the wind flows through the prism ( Vedio S1 ). At the bottom of the prism, there is a curved acrylic plate with an angle of 26°, and the FEP film is adhered to acrylic plate ( Figure S1 ). The second part is a fixed free-standing layer with curved copper electrodes mounted on the acrylic directly below the film. Since the motion of this prism is a circular motion with the length of the cantilever beam as the radius, the electrode layer is also designed to be circular to always remain parallel to the FEP, as shown in Figure 1 A. In order to make the FEP film always move on the copper electrode, the radius of the copper electrode should be slightly larger than that of the FEP film, which can effectively prevent the energy loss caused by the incomplete overlapping of the electrodes due to the installation deviation during the movement of the FEP film. A typical application scenario is shown in Figure 1 F. Figure 1 Structure diagram of triboelectric-piezoelectric hybrid nanogenerator (HG P-TENG) (A) Overall schematic of HG P-TENG. (B) Schematic diagram of dielectric layer. (C) Schematic diagram of 6-degrees of Cu electrodes layer. (D) Schematic diagram for the working principle of G-TENG. (E) Photograph of the FEP dielectric layer and hybrid nanogenerator. (F) Application scenario of HG P-TENG in pipeline. \n Vedio S1. HG P-TENG vibrate in the wind tunnel, related to Figure 4 \n The working principle of HG P-TENG is shown in Figure 1 , which mainly consists of two parts. The first part is the piezoelectric nanogenerator. It consists of two pieces polyvinylidene fluoride for energy harvesting using the piezoelectric effect ( Figure S2 ). Two piezoelectric sheets connected in parallel on two sides of the cantilever beam are bent under the influence of the galloping of the prism, resulting in positive and negative charges on its upper and lower surfaces. The second part is the triboelectric nanogenerator. In Figure 1 DI, the prism vibration moves from left to right, and will form a left-to-right current in the external circuit. The prism continues to move to the right, and the FEP dielectric layer under the prism will contact the rabbit fur brushes in Figure 1 D(ii). The rabbit fur is not only an excellent electropositive material but also has low frictional resistance. According to the list of triboelectric series, the difference in triboelectric series between FEP and rabbit fur is so large. Therefore, when the two are in contact, electrons on the surface of rabbit fur will be transferred to the FEP, which makes the FEP surface negatively charged and the rabbit hair positively charged ( Chen et al., 2021 ; Davies, 1969 ; McCarty and Whitesides, 2008 ; Zhu et al., 2012 ). And the surface charges will be saturated after several such cycles. Due to the high stiffness of the cantilever beam, when the cantilever beam reaches the limit of bending to the right in Figure 1 D(ii), the velocity will decrease to zero and start to accelerate to the left. When the FEP dielectric layer moves from the right side to the left side, a reverse current will be generated in Figure 1 D(iii). The prism will continue to move until it reaches the limit on the left and will move to the right in Figure 1 D(iv). So, when the wind passes through the prism, the HG P-TENG will constantly harvest wind energy. Galloping vibration analysis The paper uses galloping method for energy harvesting, which reduces the complexity of the structure and improves the robustness. There are four vibration modes of objects under the action of fluid force: fluttering, galloping, vortex-induced vibration, and buffeting ( Wang et al., 2020a , 2020b ; Orrego et al., 2017 ; AkaydIn et al., 2010 ). Buffeting and vortex-induced vibration are amplitude-limiting vibrations that occur only in a small range of wind speed and remain stationary at most wind speed. Thus, there is no doubt that using these vibrations to harvest energy results in energy wasted. Conversely, as the wind speed increases, the amplitude of galloping and fluttering increases, allowing maximum use of energy. However, since fluttering is a kind of multi-degree-of-freedom vibration, long-term work can easily cause material wear and even damage, so galloping is a better choice. Galloping is an unstable phenomenon that occurs under the action of aerodynamic force. When the wind speed exceeds the cut-in wind speed, its amplitude will increase continuously with the increase of wind speed. Galloping usually occurs in non-streamlined structures such as squares, rectangles, and triangles. It can be regarded as a single-degree-of-freedom self-excited vibration whose oscillation direction is perpendicular to incoming flow, and the overall galloping system can be expressed as ( Sun et al., 2019 ): (Equation 2.1) m Y ¨ + ζ Y ˙ + k Y = 1 2 ρ V 2 D C y (Equation 2.2) C y ( α ) = ∑ i = 1 n A i ( Y ˙ V ) i (Equation 2.3) U o = 4 ζ m ρ D 2 A 1 where m is the mass per unit length of the prism, ζ and k are the damping ratio and stiffness of the system, respectively, V and ρ are the wind speed and density, respectively, C y is the transverse force coefficient, α is attack angle, D is the characteristic length (perpendicular to the incoming flow), Y is the prism displacement, U o is cut-in wind speed, and A i is the coefficient of Equation 2.2 . It can be seen from Equation 2.3 that the cut-in wind speed increases with increasing damping. Through our experiments, it is found that the FEP dielectric layer should not be in contact with the Cu electrode in the initial stationary stage, otherwise it will greatly increase the cut-in wind speed of TENG. In order to realize the periodic charging of the FEP dielectric layer without increasing the cut-in wind speed, the rabbit fur brushes are designed on the outside of the Cu electrode on both sides, as shown in Figure 1 C. When the vibration amplitude exceeds a certain critical value, the FEP is able to contact with the rabbit fur brushes, as shown in Figure 1 E. These soft-contact dielectric brushes can charge the FEP regularly while avoiding a significant increase in cut-in wind speed due to additional damping caused by the contact ( Han et al., 2022 ). And this FEP does not interfere with the motion of the prism when it is in contact with the rabbit fur brushes, because the rabbit fur brushes are very soft. Therefore, the HG P-TENG can effectively utilize galloping for energy harvesting. Output performance of G-TENG and G-PENG It can be clearly seen from Figure 2 A that the open-circuit voltage ( V oc ) is basically not generated at lower wind speed, because when the wind speed is lower, the whole system cannot overcome the damping and no galloping phenomenon occurs. When the wind speed exceeds 1.80 m/s, the V oc will increase in steps, which indicates that it starts to gallop. As the wind speed continues to increase, it can be observed that the voltage increases significantly at the initial stage. But when the wind speed reaches 2.95 m/s, as the wind speed continues to increase, the voltage increases only slightly. Although theoretically the voltage of TENG is only related to the contact area and the surface charge density, but not to the speed. However, it is observed in this paper that there is a very slight increase in the V oc with the increase of the wind speed, and this increase is due to the increasing amplitude of oscillation with increasing wind speed. Therefore, the FEP dielectric layer is able to sweep a larger area on the bottom Cu electrode, which provides the opportunity to induce more charges, and thus the voltage increases slightly. It can also be observed from Figure S3 that the transfer charge ( Q sc ) has the same trend as the V oc , and the increase in voltage and charge is due to FEP sweeping more area and thus inducing more charge. As shown by the short-circuit current ( I sc ) in Figure 2 D, it can be clearly seen that the I sc basically increases with the wind speed. The short-circuit current ( I sc ) can be expressed as: (Equation 2.4) I s c = d Q s c d t Figure 2 Characteristics of the circuit of 6-degrees, 3-degrees, and 2-degrees HG P-TENG at different wind speeds (A–F) (A–C) Open-circuit voltage ( V oc ), (D–F) Short-circuit current ( I sc ) of 6-degrees, 3-degrees, and 2-degrees G-TENG. (G–I) (G and H) Open-circuit voltage ( V oc ) and short-circuit current ( I sc ) of G-PENG at different wind speeds (I) Variation of G-PENG RMS output power with resistance. There is only a small increase in the transfer charge Q sc as the wind speed increases, and the vibration frequency of the system changes very little ( Shi et al., 2020 ). This means that the time required for one cycle of prism motion is essentially constant, but the amplitude increases with the wind speed. For the cantilever beam, when the prism moves toward the middle of the two Cu electrodes, the speed is the largest, and when it moves to the two sides, the speed decreases until zero, as shown in Figure S4 . And with the increase of the amplitude, the speed of the prism across the two Cu electrodes increases continuously and the crossing time decreases, so the I sc will will keep increasing. According to the principle of TENG, the electron transfer phenomenon occurs only when the FEP dielectric layer moves between two Cu electrodes, so we further segment the 6-degrees electrodes into 3-degrees and 2-degrees which can increase the frequency of charge transfer and the results are shown in Figure S5 . Comparing Figures 2 A–2C, 6-degrees G-TENG has the peak voltage and current of about 140 V and 12.5 μA when the wind speed is 6.24 m/s. With increasing the number of electrodes, the open-circuit voltage gradually decreases while the output current increases ( Pang et al., 2021 ). For the 2-degrees G-TENG, the peak voltage and current is about 74 V and 16.7 μA which have a 34% improvement rather than 6-degrees. Also, more current cycles are observed in one cycle for finer electrodes; the number of current peaks for 6-degrees, 3-degrees, and 2-degrees is 6, 12, and 20, respectively, as shown in Figure S6 . In addition, the transfer charge also decreases with the increasing number of electrodes, which is mainly due to the decrease in the number of triboelectric charge ( Lu et al., 2021 ). Since the same piezoelectric sheet was used throughout the experiment, only the piezoelectric performance of the 6-degrees G-TENG is shown in the paper. The 3-degrees G-TENG and 2-degrees G-TENG have basically the same piezoelectric properties. Figures 2 G and 2H give the voltage and current of the piezoelectric nanogenerator at various wind speeds, and the corresponding optimum resistance is 9 × 10 6 Ω as shown in Figure 2 I, and the current between 1s is shown in Figure S7 . The output power of the piezoelectric nanogenerator is basically the same in these three cases. All of them increase with the wind speed, and the maximum output peak voltage and current is 52.8 V and 5.86 μA when the wind speed is 6.24 m/s. In addition to this, it is observed that the RMS current varies essentially linearly with the wind speed ( Figure S8 ), which implies the ability to work as a wind speed sensor ( Ye et al., 2021 ). Figure S9 shows voltage variation of PENG with attack angle (Here the attack angle refers to the angle between the incoming wind and the cantilever beam at stationary). When the attack angle is less than 12°, the voltage of PENG basically does not change, which also indicates that the galloping is basically not influenced by the change of attack angle. As the attack angle continues to increase, the amplitude will gradually decrease until it reduced to zero. Therefore, when the attack angle is less than ±12°, the HG-PENG is still able to harvest energy normally. And in future research, we will further explore the use of a circular array approach to harvest 360° of wind energy. Therefore, it is feasible that this triboelectric-piezoelectric hybrid nanogenerator can effectively utilize PENG and TENG for energy harvesting. Application of HG P-TENG To demonstrate the practical application capability of the HG P-TENG, this combined G-PENG and G-TENG hybrid nanogenerator device and capacitor connected through a full-bridge rectifier are able to drive a thermohygrometer, as shown in Figure 4 H and Vedio S2 . It is also capable of driving more than about 100 green LEDs to glow brightly, as shown in Figure 4 G. And the circuit diagrams of HG P-TENG in lighting and charging capacitors are shown in Figure S10 . Figure 3 shows the voltage curves of HG P-TENG charged to 10 V at a wind speed of 6.24 m/s for capacitors with capacities of 10, 22, and 47 μF. In the cases of 3 different capacitances, the charging rate of the 2-degrees G-TENG is much higher than that of the 6-degrees G-TENG. For a 47 μF capacitor, it takes only 122 s for the 2-degrees, 137 s for the 3-degrees, and 182 s for the 6-degrees, while the charging time of PENG is 314 s. This shows that no matter which TENG is, its charging efficiency is much higher than that of PENG. The charging time of 2-degrees G-TENG is reduced by 33% compared with that of 6-degrees G-TENG, which greatly improves the performance of G-TENG. Furthermore, the charging time of the HG P-TENG (2-degrees) is only 88 s, which is reduced by 52% compared with 6-degrees G-TENG. The saturation voltages of different capacitors are shown in Figure S11 , and we will conduct more detailed charging studies in future experiments. Moreover, a comparison with other energy harvesters is described in Table S2 which indicates that HG P-TENG has a higher charging efficiency. Figure 3 Performance of HG P-TENG for charging different capacitors (A–C) 10μF, (b)22μF, and (c)47μF capacitors charging curves of 6-degrees, 3-degrees, 2-degrees G-TENG and G-PENG. (D–F) 10μF, (e)22μF, and (f)47μF capacitors charging curves of HG P-TENG. (2-T indicates 2-degrees G-TENG and 2-T + P indicates 2-degrees G-TENG and G-PENG). \n Vedio S2. HG P-TENG for powering a thermohygrometer, related to Figure 4 \n Figures 4 A–4C plot the RMS power of these three types G-TENG at different resistances. As shown in Figure 4 A, it can be seen that its maximum power increases with the increase of wind speed. Although the output power decreases after segmenting the electrodes, it is able to transfer more charge in a single cycle. Moreover, it is also observed that the optimal resistance decreases with increasing wind speed. Figure 4 D illustrates the variation of the RMS power of G-TENG and G-PENG with resistance with three different degrees when the wind speed is 6.24 m/s. It can also be found that the finer the electrodes, the smaller the optimal resistance will be, mainly because finer electrodes will have higher capacitance. Further to understand its output power variation, Figure 4 E also depicts the RMS power with wind speed for three types of G-TENG and G-PENG. According to P = V r m s / R , the amount of the resistance needs to be known when calculating the RMS power; however, the optimal resistance of the G-TENG is changing as the wind speed is constantly varying. Therefore, the optimal resistance at 6.24 m/s wind speed is adopted. For 6-degrees, 3-degrees, and 2-degrees G-TENG, the optimal resistance will use 1×10 7 , 4×10 6 , and 3 × 10 6 Ω, respectively. With the increasing of wind speed, the power of both G-TENG and G-PENG is increasing, the power of G-PENG is still increasing until 6.24 m/s. However, when the wind speed increases to 5.74 m/s, the power of G-TENG will not increase and will even decrease slightly. This is because when the wind speed starts to increase from a low speed, its tribo-surface area will also keep increasing. When the wind speed reaches a critical value, the tribo-surface area has reached the maximum value, and its output voltage remains basically constant, as shown in Figure S12 , hence its power will not continue to increase. When the wind speed is 6.24 m/s, the RMS power of 6-degrees, 3-degrees, and 2-degrees G-TENG is 52.2, 38.5, and 34.7 μW, respectively, while the power of G-PENG is 16.7 μW. The overall RMS power of HG P-TENG is 68.9 μW which its RMS power density is about 22.7 mW/m 2 . The peak power of these three structures is presented in Figure S13 . And the peak power and power density of HG P-TENG is 1.27 mW and 0.4 W/m 2 . Moreover, G-TENG has lower cut-in wind speed, as can be seen from Figure 2 B; when the wind speed is 1.80 m/s, the voltage of 6-degrees G-TENG is about 15 V, while PENG is basically 0 V. Figure 4 Output Performance of the HG P-TENG (A–E) Top panel: RMS power resistance profile of (A) 6-degrees, (B) 3-degrees, and (C) 2-degrees G-TENG at various wind speeds. Middle panel: (D) Comparison of RMS power with resistance for 6-degrees, 3-degrees, 2-degrees G-TENG, and G-PENG at wind speed of 6.24 m/s (E) 6-degrees, 3-degrees, 2-degrees G-TENG, and G-PENG RMS power variation with wind speed. (F) Durability of the G-TENG device for about 250,000 cycles at 6.24 m/s. (G) Photograph of the HG P-TENG lighting up more than 100 LEDs. (I) Photograph of the HG P-TENG as a power source to drive a thermohygrometer. The results of the durability test are shown in Figure 4 F, using 6-degrees G-TENG for the test. It can be observed that after about 250,000 cycles, there is only a slight decrease in output voltage, which demonstrates the excellent durability of the HG P-TENG. And Figure S14 displays the scanning electron microscope images of the FEP material before and after the 250,000 test cycles. The images indicate only a few tiny scratches on the surface of the FEP, and no significant damage occurred. The major reason is that HG P-TENG adopts non-contact electrostatic induction and soft contact with rabbit fur, which greatly reduces the wear on the material, and the rabbit fur can also effectively supplement the charge for the FEP. For long-distance pipeline systems, many sensors are required to monitor parameters such as temperature and pressure of the gas in the pipeline. For this distributed energy supply, traditional batteries and wire methods undoubtedly have many drawbacks, so this hybrid nanogenerator will have great advantages in long-distance intelligent pipeline monitoring. On the one hand, the HG P-TENG can be installed in pipeline to effectively drive the sensors to monitor the temperature, humidity, pressure, etc. of the gas in pipeline. On the other hand, it can drive the signal transmission elements and actuators to feedback abnormal signals and eliminate problems in time to ensure the safe operation of pipeline system. The use of HG P-TENG provides an effective solution for the long-distance intelligent pipeline monitoring systems. Conclusions In the paper, a galloping-based triboelectric-piezoelectric hybrid nanogenerator (HG P-TENG) is proposed to harvest gas energy in long-distance pipeline, which can provide continuous energy supply for alarm devices and sensors. The use of galloping for energy harvesting effectively reduces material wear and improves the reliability of GTENG. And through the rational construction design of HG P-TENG, the cut-in wind speed and the wear of TENG material are effectively reduced, thus improving the efficiency and durability of the device. Moreover, with periodic contact, FEP can be recharged, offering the possibility of long-term, efficient energy harvesting. Furthermore, by segmenting the electrodes, the energy harvesting efficiency is greatly improved. The maximum I sc of 2-degrees G-TENG has a 34% improvement rather than 6-degrees. Comparing the capacitor charging time, the charging time of 2-degrees G-TENG and HG P-TENG (2-degrees) is reduced by 33% and 52% compared with that of 6-degrees G-TENG, respectively. Then, at a wind speed of 6.24 m/s, the maximum RMS output power of the 6-degrees, 3-degrees, 2-degrees G-TENG, and G-PENG is 52.2, 38.5, 34.7, and 16.7 μW, respectively. In addition, the feasibility of this HG P-TENG to power a thermohygrometer is also demonstrated. This study uses a piezoelectric-triboelectric hybrid nanogenerator to harvest energy from airflow in pipes, which has great potential in long-distance smart pipeline monitoring systems. Limitations of the study Although, HG P-TENG has a high energy harvesting efficiency when the direction of incoming flow is determined. Due to the characteristics of the vibration form of galloping, it can only be used to harvest wind energy within a certain angle of attack, and when this angle of attack is exceeded, larger winds can even cause damage to the HG P-TENG. So, a structure that automatically rotates according to the wind direction is to be considered in future solutions."
} | 7,862 |
34467290 | PMC8395679 | pmc | 5,395 | {
"abstract": "Biological\nfunneling of lignin-derived aromatic compounds is a\npromising approach for valorizing its catalytic depolymerization products.\nIndustrial processes for aromatic bioconversion will require efficient\nenzymes for key reactions, including demethylation of O -methoxy-aryl groups, an essential and often rate-limiting step.\nThe recently characterized GcoAB cytochrome P450 system comprises\na coupled monoxygenase (GcoA) and reductase (GcoB) that catalyzes\noxidative demethylation of the O- methoxy-aryl group\nin guaiacol. Here, we evaluate a series of engineered GcoA variants\nfor their ability to demethylate o -and p -vanillin, which are abundant lignin depolymerization products. Two\nrationally designed, single amino acid substitutions, F169S and T296S,\nare required to convert GcoA into an efficient catalyst toward the o - and p -isomers of vanillin, respectively.\nGain-of-function in each case is explained in light of an extensive\nseries of enzyme-ligand structures, kinetic data, and molecular dynamics\nsimulations. Using strains of Pseudomonas putida KT2440\nalready optimized for p -vanillin production from\nferulate, we demonstrate demethylation by the T296S variant in vivo . This work expands the known aromatic O- demethylation capacity of cytochrome P450 enzymes toward important\nlignin-derived aromatic monomers.",
"conclusion": "Conclusions We\nhave demonstrated that GcoAB and its single amino acid variants\ncan catalyze a wide range of aromatic O -demethylations\nthat previously constituted critical bottlenecks to biological funneling\nof lignin. These novel catalysts are robust both in vitro and in synthetic biology/ in vivo systems, bringing\nthis longstanding holy grail of renewable carbon capture ever closer\nto actualization. This work further highlights the extraordinary catalytic\nflexibility of bacterial cytochrome P450 systems, their amenability\nto structure-guided engineering approaches, and their particular applicability\nto the lignin funneling problem. Our efforts have resulted in a set\nof P450s interacting with a common reductase (GcoB) that now permit\ndemethylation of all of the canonical aromatic lignin subunits. Acquisition\nof the full set of catalytic functions required for lignin funneling,\nthrough a combination of enzyme discovery and engineering, serves\nas the necessary starting point from which directed evolution and\npractical synthetic strain development can follow.",
"discussion": "Discussion Biological funneling\nas a means of valorizing lignin will require\nthe concerted action of multiple enzymes to reduce the complexity\nof deconstructed lignin streams to generate value-added products.\nThis study describes two new cytochrome-P450 enzymes that catalyze\nthe oxidative demethylation of o - and p -vanillin, which are aldehydes produced from the catalytic deconstruction\nof lignin. The resulting product catechol aldehydes can be further\noxidized via central metabolic pathways common to many bacteria or\nharvested as valuable products. Notably, the new enzyme functions\nwere generated via rational engineering based on high-resolution structures\nand the biocatalytic and dynamic properties of their natural precursor,\nGcoAB, a two-enzyme oxidoreductase system that specifically demethylates\nguaiacol and has only minimal demethylase activity toward the vanillins. 25 , 28 Here, we observed that two single amino acid substitutions,\neach\nof which minimized steric clashes with and introduced hydrogen bond\ndonors to the aldehyde groups, were sufficient to render GcoAB an\neffective catalyst toward the vanillin isomers. As expected, the o -vanillin binding mode with the F169S variant closely resembled\nthat of the isosteric substrate syringol. This variant moreover efficiently\ncatalyzed demethylation of o -vanillin as well as\nthe less encumbered native substrate, guaiacol. Prior MD simulations\nsuggested that the F169 side chain is highly mobile and may be important\nfor maintaining guaiacol in its productive orientation. 25 , 28 Substitution of smaller residues at this position is required for\nring-substituted guaiacol analogues, like syringol and o -vanillin, to stably achieve analogous productive binding modes. Here, as with syringol, 25 , 28 we observed only small\nshifts in the crystallographic position of p -vanillin\nrelative to the native substrate (guaiacol) bound to WT GcoA ( Figure 4 A–C); however,\nthe stability of the ligand in that position in MD\nsimulations is significantly affected. Substitution of the secondary\nalcohol (T296) for the primary (S296) was sufficient for restoring\na WT-like hydrogen bonding pattern in the vicinity of the vanillin\naldehyde group and, in turn, a dynamically stable binding mode that\nultimately permits catalysis. The dynamic interaction between the\nsubstrate, heme propionate, R298, and a triad of crystallographically\nobserved water molecules is apparently flexible enough to permit substitution\nof the sp 3 -hybridized carbon of vanillyl alcohol, as this\nbiological reduction product of p -vanillin was also\nefficiently demethylated by the T296S variant both in vitro ( Figure 2 , Table S1 ) and in vivo ( Figure 5 ). Interestingly,\ncatalysis by the engineered enzyme variants is not due to enhancements\nin the efficiency of water displacement from the active site by the\naldehydes (represented by v i (NADH)), nor\nto increases in equilibrium binding affinity ( K D ) ( Table S1 ). Rather, catalysis\ncorrelates with a lowering of K M for the\nsuccessful enzyme variant/substrate pairs, indicating an increased\nprobability of forming the productive enzyme–substrate near-attack\nconformation. Structurally, this corresponds to precise orientation\nof the reactive methoxyl group and the adjoining aromatic ring into\na productive configuration defined by the binding mode for the native\nsubstrate, guaiacol. Computationally, we see that retention of the\ndemethylation substrate in the near attack conformation is likely\nmediated by hydrophobic interactions in the case of o -vanillin, and by a network of second-sphere hydrogen bonds linking\nthe substrate and heme to the protein environment for p -vanillin and its cognate alcohol."
} | 1,538 |
38888486 | PMC11184938 | pmc | 5,396 | {
"abstract": "Abstract Butyl butyrate is a short‐chain fatty acid ester (C8) with a fruity aroma. It has broad prospects in the fields of foods, cosmetics and biofuels. At present, butyl butyrate is produced by chemical synthesis in the industry, but it is highly dependent on petroleum‐based products. The growing concerns regarding the future scarcity of fossil fuels have been strongly promoted the transition from traditional fossil fuels and products to renewable bioenergy and biochemicals. Therefore, it is necessary to develop a green biochemical technology to replace traditional petroleum‐based materials. In recent years, microorganisms such as Escherichia coli and Clostridium have been engineered to serve as cell factories for the sustainable one‐pot production of short‐chain fatty acid esters, including butyl butyrate. This opinion highlights the recent development in the use of lipases and alcohol acyltransferases (AATs) for butyl butyrate production in microbial fermentation, as well as future perspectives.",
"conclusion": "CONCLUSIONS AND PERSPECTIVES Although the use of lipase as the catalyst could produce a high concentration of butyl butyrate, this reaction has a relatively low equilibrium constant in the aqueous phase at room temperature, and is not thermodynamically favourable with a positive Gibbs free energy change (∆G), resulting in high substrate concentrations required to drive the reaction forward. Conversely, AAT catalytic reaction has a high equilibrium constant and is thermodynamically favourable which means relatively low substrate concentrations are needed to push the reaction forward (Seo et al., 2020 ). From an economic perspective, the addition of precursors and/or lipase not only increases the cost of substrates and enzymes but also raises downstream separation cost. Therefore, to achieve economical production of butyl butyrate, a de novo synthetic approach should be adopted. The natural butyl butyrate synthetic strain Clostridium sp. strain BOH3 was able to produce 6 g/L target product without the addition of any precursors and lipases (Xin et al., 2016 ). However, when the AAT pathway was adopted, the butyl butyrate produced by C. tyrobutyricum engineered strain was 23 times higher than that of Clostridium sp. strain BOH3 (Guo, Ye, et al., 2024 ). Therefore, when compared to lipase, the AAT‐dependent approach is more promising and attractive for butyl butyrate biosynthesis in microorganisms. Although E. coli is a commonly used strain for natural compounds production, its ability to produce butyl butyrate is much lower than that of Clostridium . Butyryl‐CoA and its derivatives, butyric acid and butanol, are mainly produced by clostridia anaerobically, such as C. tyrobutyricum , which can produce more than 50 g/L butyric acid (Guo et al., 2020 ) or 25 g/L butanol (Zhang et al., 2018 ). Thus, anaerobic Clostridium is the preferred host for butyl butyrate production. C. tyrobutyricum is the most promising Clostridium strain for industrial bio‐based butyl butyrate production, with a yield of 0.28 mol/mol in fermentation. This is nine times higher than that of C. saccharoperbutylacetonicum (Feng et al., 2021 ; Guo, Ye, et al., 2024 ) but still only 56% of the maximum theoretical yield, which is still not comparable to the chemical synthesis. Future work should focus on eliminating by‐products, engineering cofactor and energy, regulating key genes, and optimizing fermentation conditions. On the other hand, almost all of the metabolic engineering strategies were based on previous studies due to the lack of understanding of the metabolic mechanism and metabolic regulatory network or pathway. Therefore, future studies should incorporate transcriptomics, metabolomics and/or proteomics to analyse the key elements, enzymes, and intermediate metabolites in the metabolic pathway. Meanwhile, the genome‐scale model should also be optimized to guide the “wet experiment”. Finally, protein engineering or enzyme‐directed evolution should be performed to enhance the affinity, specificity, and catalytic efficiency towards substrates. This will further improve the titre and selectivity of butyl butyrate, and reduce the downstream separation cost. To reduce production cost, renewable feedstocks, such as lignocellulosic biomass (Cui et al., 2023 ; Feng et al., 2021 ; Lu et al., 2023 ) and cassava starch (Guo, Li, et al., 2024 ) have been used to produce renewable butyl butyrate. However, the titers were lower than those obtained with pure sugar. Therefore, more efforts should be made to increase butyl butyrate production from renewable feedstocks. Finally, to maximize the microbial production capacity, a continuous fermentation mode coupled with in‐situ extraction should be developed for industrial production of bio‐based butyl butyrate.",
"introduction": "Introduction Butyl butyrate, one of the short‐chain fatty acid esters, has broad prospects in the food and chemical industries, as well as in renewable energy as a jet fuel or as an additive for gasoline and diesel to improve their octane rating and combustion efficiency (Guo et al., 2023 ). The demand for esters has been increasing in recent years with the continuous expansion of its application range. The global market demand for esters, including butyl butyrate, is predicted to reach $ 159.36 billion by 2033, with a compound annual growth rate (CAGR) of 5.4% (Future Market Insights, 2023 ). Butyl butyrate is naturally produced by plants, such as flowers and fruits (Xin et al., 2019 ). However, the concentration is relatively low when extracted from plants. Thus, to meet the demand, the industrial production of butyl butyrate is carried out by chemical synthesis, including Fischer esterification process with butyric acid and butanol as substrates. This method has been abandoned due to the awful reaction condition (requires high temperature–200°C and concentrated sulfuric acid), environmental pollution and equipment corrosion (Zhang et al., 2017 ). To overcome such issues in butyl butyrate production, mild reactions, such as Tishchenko reaction and Acetylation are employed at room temperature (Kushwaha et al., 2022 ). Nevertheless, these reactions still rely on the petroleum refining industry. With the increasing depletion of petrochemical resources, the increasing environmental pollution caused by traditional energy consumption and the public's preference for bio‐based chemicals, there is an urgent need to develop biosynthesis of butyl butyrate. Biosynthesis of butyl butyrate mainly includes lipases and alcohol acyltransferases (AATs) dependent pathways (Noh et al., 2019 ). If these pathways are introduced into microorganisms, they can produce butyl butyrate from glucose or other sugars in one pot. At present, microorganisms such as Escherichia coli (Layton and Trinh, 2014 ; Lee and Trinh, 2022 ) and Clostridium (Feng et al., 2021 ; Guo et al., 2023 ; Noh et al., 2018 ) have been engineered to serve as cell factories for butyl butyrate production. In this opinion, the strategies for butyl butyrate production via lipases and AATs pathways are reviewed. In addition, the future perspectives and research directions for high concentration, yield, productivity and low cost of renewable butyl butyrate production are suggested."
} | 1,827 |
27685330 | PMC5042559 | pmc | 5,403 | {
"abstract": "Understanding plant-microbe relationships can be important for developing management strategies for invasive plants, particularly when these relationships interact with underlying variables, such as habitat type and seedbank density, to mediate control efforts. In a field study located in California, USA, we investigated how soil microbial communities differ across the invasion front of Taeniatherum caput-medusae (medusahead), an annual grass that has rapidly invaded most of the western USA. Plots were installed in habitats where medusahead invasion is typically successful (open grassland) and typically not successful (oak woodland). Medusahead was seeded into plots at a range of densities (from 0–50,000 seeds/m 2 ) to simulate different levels of invasion. We found that bacterial and fungal soil community composition were significantly different between oak woodland and open grassland habitats. Specifically, ectomycorrhizal fungi were more abundant in oak woodlands while arbuscular mycorrhizal fungi and plant pathogens were more abundant in open grasslands. We did not find a direct effect of medusahead density on soil microbial communities across the simulated invasion front two seasons after medusahead were seeded into plots. Our results suggest that future medusahead management initiatives might consider plant-microbe interactions.",
"introduction": "Introduction Plant communities are typically composed of a combination of native and non-native species. The majority of these non-native species are benign, demonstrating little to no negative effect on neighboring organisms. However, a small fraction of these non-native plants are characterized as invasive because they are able to profoundly modify local plant and animal communities, nutrient cycling, hydrological regimes and fire frequency [ 1 – 2 ]. Not only do these impacts erode biodiversity and devalue ecosystem services, but they can also enhance further invasion by con- and heterospecific exotics (e.g. [ 3 ]). Soil microbial communities might mediate relationships between invasive plant species and their ecosystem impacts [ 4 – 6 ]. Soil microbial communities, which are typically dominated by fungi and bacteria, can be altered by invasive plants directly through growth facilitation or inhibition near the root zone [ 7 ], and indirectly through changes in abiotic conditions (e.g. pH or nutrient availability) that occur in tandem with weed establishment [ 8 ]. For example, species-specific effects of non-native grasses on soil nutrients have been shown to subsequently modify soil microbial community composition, biomass, and bacterial:fungal ratios [ 9 ]. In addition to being vulnerable to impacts from aboveground plant dynamics, soil microbial communities may also play an important role in mediating the success of plant invasions [ 4 ]. For example, extant soil biota have been shown to enhance invasion success of some of the world’s most noxious invasive plants, such as exotic knotweeds ( Fallopia spp.) [ 10 ]. In general, it has been concluded that invasive species may be differentially affected by soil bacterial or fungal pathogens as compared to native plant species [ 11 , 8 ], but see [ 12 ], which could be important for developing reliable control strategies for invasive plants that demonstrate resistance to current management efforts. The invasive annual winter grass medusahead ( Taeniatherum caput-medusae [L.] Nevski) has invaded much of the western USA and has been shown to decrease soil carbon stocks, reduce native plant diversity, and enhance fire frequency [ 13 ]. A recent meta-analysis of medusahead control outcomes in annual grassland and intermountain regions identified large variance in the effectiveness of conventional approaches for managing medusahead [ 14 ], suggesting that underlying variables, such as habitat type and seedbank density, might mediate control efforts. Despite increasing recognition that bacterial and fungal communities can influence plant invasion dynamics, only two published studies have investigated the direct relationship between medusahead and soil microbial communities [ 15 – 16 ]. These studies have conflicting results, suggesting both that the interaction between medusahead and soil microorganisms might or might not enhance its own invasion. Understanding medusahead effects on the soil microbial community is critical for enhancing predictions of invasion effects and for developing effective management strategies. We investigated how soil microbial communities differ across the invasion front of medusahead in experimental plots in open grassland and oak woodland habitat in the Sierra Foothill region of California, USA. We attempted to understand (1) if medusahead modifies soil microbial communities across the invasion front (simulated by differences in seed density) within systems; and (2) how soil microbial communities differ between areas where medusahead invasion is successful (open grassland habitat) and not successful (oak woodland habitat), and the factors that could be responsible for these differences. We hypothesized that medusahead would modify the soil microbial communities within each habitat. We expected this for two reasons. First, early work on this species [ 15 ], as well as more recent work on other invasive annual grasses with similar invasion dynamics to medusahead, have demonstrated linkages between the soil microbes and invasion success [ 17 ]. Second, plant-soil interactions are common in the savannah/oak woodlands of California [ 18 ], so we would expect strong effects from the extant soil microorganisms. We also hypothesized that soil microbial communities (in particular symbiotic and pathogenic fungi) would differ between areas where medusahead invasion is typically successful (open grasslands) and typically not successful (oak woodlands). In California, invasion of winter annual grasses can be strongly limited within oak canopies [ 19 ], possibly due to the different microbial communities associated with oak trees compared to adjacent open grasslands [ 20 – 21 ]. Through shading, litter input, and hydraulic lift, Mediterranean oak trees can also modify a wide variety of soil edaphic factors, such as pH and organic matter concentrations, which directly influence soil microbial communities (e.g. [ 22 ]). At present, we do not know what role, if any, soil microbial communities play in mediating the likelihood of successful medusahead invasions.",
"discussion": "Discussion Soil biota has been implicated in the facilitation of invasive plant dominance [ 5 , 37 ]. However, not all invasive species support plant-soil microbe feedbacks as a driver of invasion [ 38 – 39 ]. We attempted to identify how relationships between the weedy annual grass medusahead and soil microorganisms might mediate invasion success. Unexpectedly, we did not find evidence for medusahead density effects on the soil microbial communities across a simulated invasion front in either habitat. This supports other studies that have documented instances where soil communities are unresponsive to the presence of invasive weeds in arid grasslands [ 40 ] and in other systems [ 41 ]. However, several aspects of our experiment could hinder our ability to capture an existing relationship between medusahead seed density and soil microbial communities. First, we assessed the relationship between medusahead seed density and bulk soil microbial communities and not rhizosphere communities. Rhizosphere microbial communities are different from bulk soil communities [ 42 ], so the potential effects of medusahead invasion intensity on microbial communities may be observable at smaller spatial scales in the rhizosphere (but see [ 43 ]). Second, although this study was conducted across two growing seasons, there may have been insufficient time for soil microbial communities to respond to different seed densities of medusahead [ 44 ]. Although microbial communities have been shown to respond to changes in aboveground plant communities in as little as a month [ 45 ], these communities could be especially slow to respond to the presence of weeds in environments where soil edaphic factors are slow to change in response to invasion. Moreover, in California grasslands, soil appears to be particularly buffered from aboveground changes [ 40 ]. Third, extracellular microbial DNA and DNA from dead cells can persist in soils for years and thus, obscure DNA-based present estimates of soil microbial composition [ 46 ]. Finally, as this study only assessed the composition of the microbial communities, we cannot eliminate the possibility that medusahead seed density can influence the activity and function of belowground soil communities. Using reciprocal soil transplant experiments, [ 47 ] reported higher medusahead biomass in introduced soil than in native soil, which suggests that medusahead success is partially due to release from native soil pathogens [ 48 – 49 ]. In addition to escaping from soil pathogens, certain plant invasive species have been shown to accumulate local pathogens [ 11 , 49 ]. Although previous studies have reported that medusahead is sensitive to antagonistic fungi [ 50 – 51 ], we observed important differences in bacterial and fungal community composition between open grassland sites where medusahead is typically found in high densities and oak woodland sites where medusahead is typically found in low densities. Specifically, we found significantly higher abundances of fungal pathogens in open grasslands compared to oak woodland habitats. Environmental conditions in the grassland habitat are likely more ideal for both soil and foliar fugal pathogens, which can be important drivers of above ground plant dynamics (e.g. [ 52 ]). Indeed, these pathogens have been documented in grasslands in other studies (e.g. [ 53 ]). These results collectively highlight the potential contribution of microbial mechanisms (e.g., via pathogen accumulation) to medusahead dominance in California grasslands. Because the differences in bacterial and fungal communities exist in the absence of medusahead, it is more likely that favorable grassland soil microbial communities facilitate medusahead establishment instead of resulting from the invasion itself. In addition to negative interactions, a large number of plant species establish symbiotic associations with soil microorganisms (in particular with mycorrhizal fungi and nitrogen-fixing bacteria, [ 6 , 54 ]). In this experiment we detected a higher proportion of ectomycorrhizal fungi in soil samples from oak woodland habitats. This result is expected as ectomycorrhizal fungi are important to oak trees for acquiring nutrients and for increasing root absorptive area [ 18 , 55 ]. Our results also show that oak litter (rather than shade) influence overall soil fungal community composition and richness, but not soil bacterial community composition and richness. Although plant litter inputs can change important environmental conditions for soil bacteria such as pH and base cation content [ 42 ], soil fungi are key decomposers of plant necromass and depend more directly on leaf litter than bacteria [ 56 ]. We also observed a significantly higher proportion of arbuscular mycorrhizal fungi in open grasslands. Given the generally non-specific interactions with arbuscular mycorrhizal fungi, it has been proposed that several invasive plants make use of these fungi to enhance their success [ 57 – 60 ]; but see [ 61 ]. Other invasive plants (for example, the garlic mustard Alliaria petiolata ) inhibit mycorrhizal fungi on which natives depend [ 62 ]. Collectively, this work suggests that biocontrol and management initiatives should consider the potentially beneficial plant-microbe interactions rather than just focusing on antagonistic relationships. The context dependency associated with invasion success and weed management efficiency is well documented for both medusahead as well as other weedy species (e.g. [ 63 ]). The presence and abundance of bacterial and fungal groups potentially underlie this context dependency in several instances. Environmental changes, such as exacerbated drought conditions, might modify suitability of oak woodland habitat and perhaps enhance invasibility of previously resistant systems. Therefore, given the complex relationships between aboveground and belowground biota [ 64 ], understanding the potential mechanisms mediating the association between invasive plant species and soil microorganisms could provide practical information for developing effective management strategies, as well as insight into the ecology of plant-soil food webs and diversity."
} | 3,170 |
31052425 | PMC6571658 | pmc | 5,404 | {
"abstract": "Currently, many meshes, membranes, and fabrics with extreme wettability of superhydrophobicity/superoleophilicity, or superhydrophilicity and underwater superoleophobicity are promising candidates for oil/water mixture separation. Nevertheless, a facile yet effective way to design and fabricate porous mesh still remains challenging. In this work, fused deposition modeling (FDM) 3D printing of Fe/polylactic acid (PLA) composites was employed to fabricate superhydrophilic and underwater superoleophobic mesh (S-USM) with hydrogel coatings via the surface polymerization of Fe(II)-mediated redox reaction. In addition, salt of aluminum chloride was incorporated within the hydrogel coating, which was attributed to strengthening the demulsification of oil-in-water emulsions, resulting in efficient separation of oil-in-water mixtures. The S-USM was efficient for a wide range of oil-in-water mixtures, such as dodecane, diesel, vegetable oil, and even crude oil, with a separation efficiency of up to 85%. In this study, the flexible design and fabrication of 3D printing were used for the facile creation of spherical oil skimmers with hydrogel coatings that were capable of removing the floating oil. Most importantly, this work is expected to promote post-treatment processes using 3D printing as a new manufacturing technology and, in this way, a series of devices of specific shape and function will be expanded to satisfy desired requirements and bring great convenience to personal life.",
"conclusion": "4. Conclusions In conclusion, we have developed an in situ method to fabricate S-USM and investigated its wettability and separation performance using homemade equipment. The salt-containing S-USM was efficient for a wide range of oil-in-water mixtures, such as dodecane, diesel, vegetable oil, and crude oil, with a separation efficiency of up to 85%. During the recycling separation test, the separation efficiency remained at approximately 90%, showing high repeatability. The mechanism of emulsion destabilization by inorganic salt is often considered to be electrostatic repulsions. In this manner, the salt-containing S-USM could even demulsificate oil/water emulsions, with rapid separation. Moreover, a key innovation was utilizing the flexible design and fabrication of 3D printing with subsequent hydrogel-coating treatment. The spherical skimmers with hydrogel coatings were facilely created and capable of removing the floating oil. Various oil/water separators can be realized to meet future requirements and bring great convenience to personal life. In view of its simplicity, this work may pave the way for a new method using 3D printing technology, with more practical applications in the fields of separation, hydrogels, electronics, smart robots, and many others.",
"introduction": "1. Introduction Despite the recent emergence and increasing practical feasibility of conventional techniques involving oil skimmers, centrifuges, coalescers, and flotation technologies, the separation of oil/water mixtures cannot be easily handled when faced with wastewater from metal workshops, textiles, leather, and petrochemicals, as well as frequent oil spill accidents [ 1 , 2 ]. What makes oil/water mixtures difficult to separate is that oil/water mixtures often contain immiscible mixtures and emulsified mixtures in which micro oil/water droplets are under a stable state [ 3 , 4 , 5 , 6 , 7 ]. Herein, the key to achieving a high separation efficiency for emulsified oil-in-water mixtures is to break stable oil-in-water emulsions. Currently, extreme wetting materials, such as superhydrophobic/superoleophilic or superhydrophilic and underwater superoleophobic filters [ 8 , 9 ], oil absorptions [ 10 , 11 , 12 , 13 , 14 , 15 ], and membranes [ 16 , 17 , 18 , 19 ], are promising candidates for separating oil-in-water mixtures. Among these, membranes are deemed to be highly efficient and economical [ 20 ]. Recent progress in the fabrication of highly porous membranes has been enabled by textured metal meshes [ 21 ], assembled nanostructures [ 22 ], as well as electrospinning [ 23 , 24 , 25 , 26 ]. However, membranes with complicated geometries and diversified composites are still difficult to fabricate. Allowing flexible design and freeform in three dimensions, 3D printing is a promising method to construct structurally functional devices with post-chemical modifications, and has drawn intense interest regarding application in tissue engineering [ 27 , 28 , 29 ], microfluidics [ 30 , 31 ], and special wetting surfaces [ 32 , 33 , 34 ]. Hydrogel, a crosslinked network full of water, is an example of typical hydrophilic materials. Owing to their excellent capabilities for absorbing and holding water, hydrogels are promising candidates to be used to increase wettability. The Taubert research group [ 35 ] deposited a hydrogel/calcium phosphate hybrid layer on 3D printed poly(lactic acid) scaffolds for biomaterial fabrication. The Irvine research group [ 36 ] further studied the biomaterial surface made by hydrogels on 3D printed substrates for bioartificial blood vessels. The Bashir research group [ 37 ] demonstrated separation of orthogonal functions enabled by 3D printing within a hydrogel particle. The Jiang research group reported using hydrogel-coated mesh for oil/water separation [ 38 , 39 ]. Furthermore, polyacrylamide (PAM) hydrogel has been broadly researched for wastewater treatment as a coagulator or flocculator [ 40 , 41 , 42 ]. Hence, the combination of 3D printing mesh and PAM hydrogel is promising for oil/water separation. In this work, taking advantage of inherent superhydrophilicity and underwater superoleophobicity of hydrogel, we prepared meshes used for oil/water separation by combining 3D printing with hydrogel-coated modification ( Scheme 1 ). Specially, Fe/PLA composites were extruded into filament and then printed into orthogonal meshes using a fused deposition modeling (FDM) 3D printer. The printed mesh was suspended in acrylic acid (AA) and acrylamide (AM) solution to induce PAA/AM hydrogel coating, bounding, and growing on mesh via the surface polymerization of Fe(II)-mediated redox reaction [ 43 , 44 ]. After being immersed in inorganic salt solution, the inorganic salt was incorporated into hydrogel coating to strengthen demulsification of oil-in-water emulsions. Due to superhydrophilic and underwater superoleophobic properties of hydrogel coating, the underwater oil contact angle of superhydrophilic and underwater superoleophobic mesh (S-USM) was over 150 °C with a low adhesion force. The salt-containing S-USM acted as a selective separation membrane, which allowed water to permeate while repelling oil droplets. In order to investigate the separation capability of salt-containing S-USM, four representative kinds of oil mixtures, namely dodecane-in-water, diesel-in-water, vegetable oil-in-water, and crude oil-in-water, were chosen and examined with simple homemade equipment, which demonstrated that S-USM could separate oil/water mixtures with a separation efficiency up to 85%.",
"discussion": "3. Results and Discussion 3.1. Morphologies of 3D-Printed Mesh The printing process of mesh is shown in Figure 1 a. The mesh was fabricated in two orthogonal layers via FDM 3D printing of Fe/PLA composite filaments ( Figure S1 ). The filaments were extruded using heat extrusion (210 °C) and printed in a layer-by-layer sequence., By controlling the printing parameters shown in Figure 1 b, such as stick diameter (d), spacing distance (L), and motion speed (V), a series of meshes with different spacing widths was formed ( Figure S2 ). In addition, the advantage of FDM 3D printing in feasible designing and free forming was obvious, especially for preparing in the macro millimeter to large scale. The lateral dimensions were kept at 20 mm × 20 mm in Figure 1 c, with a facile to larger size, if needed. In the SEM image ( Figure 1 d), 3D-printed mesh is fixed using two orthogonal layers and without collapsing, which is important for offering support to the growing hydrogel coating. 3.2. Fabrication of Hydrogel Coating Hydrogel coating was prepared via the surface polymerization in an Fe (II)-mediated redox reaction during the process of suspending printed Fe/PLA mesh in AA/AM solution. This one-step method of hydrogel coating on Fe/PLA composite mesh was facile and rapid. The optical images in Figure 2 show the process of the hydrogel coating thickness increasing. In Figure 2 a, a single stick was wrapped by hydrogel coating. It is noted that the initial thickness of the hydrogel layer was smooth and uniform at 15 s, but corrugated when extending polymerization time, especially after 2 min. The maximum thickness of hydrogel coating is approximately 400 μm, resulting in a tight hydrogel layer enclosing over the stick ( Figure S3a,b ), whereas for an orthogonal mesh ( Figure 2 b), holes surrounded by hydrogel walls were generated, and with the increase of hydrogel wall thickness, the diameter of the holes decreased [ 43 ]. Through energy-dispersive spectrometry (EDS) in Figure S3d–f , it is obvious that the C, N, and O elements are distributed on the entire S-USM surface, with the atomic percent of C, N, and O being 43.8%, 29.2%, and 28.0%, respectively. 3.3. Wettability of S-USM As is well known, the membrane separation capacity of oil/water mixtures depends largely on membrane wettability [ 2 ]. In order to investigate the wetting properties of S-USM, we characterized the contact angles and permeating behavior of multi-drops of water or oil, with results in Figure 3 a,b. In air, the water droplets infiltrated the S-USM rapidly with a contact angle of close to zero ( Figure 3 a). While oil droplets also spread on the S-USM at a low contact angle of less 10°, they did not permeate through the S-USM, even when more than ten droplets were added onto the mesh ( Figure 3 b). Similarly, in the process of oil/water separation, water droplets would meet with the S-USM, and permeated through the mesh without hesitation, as well as the residue of oil droplets being blocked above the mesh. This process often takes place in a water-filled environment in most cases of oil/water mixture separation, due to the differentiation density of oil and water. Furthermore, dynamic underwater oil (crude oil) contact was observed, as shown in Figure 3 c, as well as adhesion force ( Figure 3 d). In the process of oil receding, no residual oil droplets were visible on S-USM with an underwater oil adhesion force less than 1 μN. Four kinds of underwater oil contact angles of S-USM were further studied in Figure 3 e. They were all found to be up to 150° with a rolling angle of less than 15°, showing excellent underwater repelling and easy flowing away of the oil. Above all, the results showed the superhydrophilicity and underwater superoleophobicity of S-USM, indicating the potential for oil droplets to easily roll away from the S-USM surface without any residue, which is promising for applications separating oil/water mixtures. 3.4. The Process of Oil/Water Mixture Separation Using Salt-Containing S-USM The simulated oil-in-water mixtures were prepared with 10 mL of dodecane, 70 mL of water, and 0.1 g of surfactant, then stirred for 7 h at room temperature. The surfactants were sodium dodecyl sulfate, triethanolamine, Tween 80, and no-surfactant marked as (a), (b), (c), (d) in Figure S4 . With the addition of 0.10 g PAM, 0.50 g NaCl, 0.94 g CaCl 2 , 0.92 g AlCl 3 into 10 mL of the above mixtures, the flocculation and coalescence were enhanced, clarifying the turbid solution. Generally, the presence of electrolytes, such as inorganic salt, influences the surface charge of emulsions by compressing the electrical double layer around the droplet, thus reducing the electrical repulsions and enhancing the gathering of micro oil droplets [ 45 , 46 ]. In detail, the demulsification by AlCl 3 was observed by optical microscopy at room temperature (RH ~30%) as shown in Figure 4 a–c. Compared with the initial emulsion in Figure 4 a, an increased number of oil droplets were found above the mixtures in Figure 4 b,c, indicating more collisions were happening between the two neighboring emulsions, and that oil droplets aggregated together into larger droplets, until floating up as shown in Figure 4 d. Furthermore, one of the highlights of this work is its use of an in situ demulsification and separation method. On the one hand, demulsification takes place on the nearby surface of salt-containing S-USM. On the other hand, water droplets permeate through the mesh simultaneously, leaving the oil droplets above the mesh ( Figure 4 e). From Figure 4 f,g, oil droplets aggregated and condensed with an increasing area of C, and decreasing area of A and B (A and B represent water fields, C represents oil field). Finally, oil covered the S-USM surface randomly in Figure 4 h. As shown in Figure 4 k, a milky emulsion was present on S-USM, indicating successful separation. The surface chemical composition of AlCl 3 -containing S-USM was confirmed by EDS in Figure S5 . It is obvious that the elemental content of C (60.02%) and O (34.39%) after separation was more than before separation (with C (58.45%) and O (28.0%)), indicating residual oil on the mesh. To further evaluate the separation ability of AlCl 3 -containing S-USM, a series of mixtures, such as dodecane-in-water, diesel-in-water, vegetable oil-in-water, and crude oil-in-water, was tested. The oil-in-water mixtures were poured onto the S-USM, which was fixed between two glass tubes as shown in Figure S6a,b . Owing to the superhydrophilicity and underwater superoleophobicity of the mesh, water droplets immediately permeated through the mesh by gravity, while the oil droplets stayed above the mesh. As shown in Figure 5 a, there was almost no visible oil droplets in the filtrate, while a great amount of oil-in-water emulsions were contained in the as-prepared mixtures before separation ( Figure 5 b), showing the excellent separation purity of S-USM. In addition, the optical transmittance of filtrate water had an obvious increase compared to the original dodecane-in-water mixture ( Figure 5 c). Dynamic light scattering (DLS) was conducted to show the decreasing of droplet sizes between origin oil-in-water mixtures and filtrate ( Figure 5 d). The separation efficiency was calculated according to\n η = (m 1 /m 0 ) × 100, (2) \nwhere m 0 and m 1 are the mass of the water before separation and filtration, respectively. As shown in Figure 5 e, the separation efficiencies for the four kinds of oil-in-water mixtures were all above 80%. The S-USM also has good recycling separation ability. It showed high separation efficiency of dodecane-in-water mixtures, almost 90% in Figure 5 f, indicating that the S-USM is applicable for performing repeated rounds of oil/water mixture separation. The separation flux of filtrate water was calculated by\n (3) Flux = Vol / ( A · t ) , \nwhere Vol is filter water volume, A is the area of mesh, and t is the consumed time. As shown in Figure S6c,d , the S-USM had a high initial separation rate, and with extended time, the hydrogel absorbed a high volume of water and swelled, which would decrease the porous area or even blocked the holes. 3.5. Special Oil Skimmers Made of S-USM Interestingly, the cooperation of salt further contributed to flocculation and coalescence, and the flocculated oil droplets began to float on water. To better remove floating oil from water, we demonstrated two specific devices useful for separation, called a spoon skimmer and a barrel skimmer, created with the help of 3D printing in fabricating complex structures ( Figure 6 ). In the case of imitating collecting floating oil (dodecane dyed in blue), a spoon skimmer was created ( Figure 6 a and Figure S7a ). The spoon skimmer consisted of two main parts: spherical mesh and a straight hilt which could be convenient for the operator. The design of a spoon skimmer was developed from the S-USM with high separation efficiency of oil-in-water mixtures. Due to more pores in its spherical surface, the spoon skimmer had a faster speed of separation, making it efficient at resolving accidental oil spills, as shown in Figure 6 c. Furthermore, a barrel skimmer was successful when applied in another case, to collect floating oil (diesel dyed in green) within deep surroundings. The barrel skimmer was composed of spherical mesh and a curved hilt ( Figure 6 b and Figure S7b ). We demonstrated a collection of floating oil that utilized the barrel skimmer shown in Figure 6 d. Both oil skimmers succeeded in removing oil from water, as shown in Figure S8 and Video S1 . Combining hydrogel-coated treatment with the new manufacturing technology of 3D printing, a series of specific, useful separation devices can be fabricated, bringing great convenience to personal life."
} | 4,226 |
37325624 | PMC10264669 | pmc | 5,405 | {
"introduction": "1 Introduction A leading thinker on inflammation wrote that “inflammation is associated with almost every major human disease” ( 1 ). Inflammation is a defense process of the body against stimuli and a biological response of the immune system to harmful stimuli ( 2 ). Inflammation is usually beneficial, but once the inflammatory reaction is out of balance, it will be harmful to the body ( 3 ). Inflammation has a great impact on human health, which has been paid more and more attention by researchers. As far as 2021 is concerned, 13905 articles identified “inflammation” as the keyword, and 1284 articles included the word “inflammation” in the title ( 4 ). This not only reflects the importance of studying inflammation, but also emphasizes the urgency of inflammation research. Dysregulated inflammatory reaction can lead to infectious, autoimmune, neurological, cardiovascular, renal and tumor diseases ( 5 – 8 ). Although researchers have put a lot of efforts into biological understanding and drug development, and some interventions have been successful in clinical trial ( 4 ), the prevention and monitoring of some inflammation is still a problem. Early monitoring of the prevention and recovery process can effectively reduce the impact of inflammation on people’s health. Although traditional drugs can effectively prevent inflammation, it is always difficult for people to take drugs frequently. Emerging triboelectric nanogenerators (TENG) provides a new prevention and monitoring scheme to address this challenge ( 9 – 11 ). The latest research progress in soft electronics has proposed flexible and stretchable functional sensors ( 12 – 14 ). TENG combines flexible materials and wearable characteristics, and has been successfully applied in the health and medical fields as implantable medical sensors ( 15 – 17 ), biological sensors ( 18 – 21 ), monitoring sensors ( 22 – 24 ), etc. TENG is lightweight, highly flexible and elasticity ( 25 , 26 ), and can directly contact the skin or organ surface for inflammation prevention and monitoring. In this paper, the application of the emerging TENG in the prevention and monitoring of inflammation such as cervical spondylitis, lumbar spondylosis, rheumatoid arthritis has been fully discussed. Flexible medical sensors, biosensors and monitoring sensors made of materials with different characteristics have been successfully applied to the prevention and monitoring of some inflammation and diseases. Additionally, this paper also discusses the advantages of TENG combined with artificial intelligence (AI) in disease prevention and monitoring, and the development of TENG in the medical field promoted by AI. At the end of the article, the challenges of the development of TENG and AI in the field of inflammation are analyzed, and its development prospects are prospected.",
"discussion": "4 Discussion TENG has many advantages, including low cost, high efficiency, softness, wearable, self-powered, and combined with AI algorithm, it has great application prospects in the prevention and monitoring of inflammation, even in the treatment. However, the development of new things always faces many challenges. Here, we divide the challenge into two parts, one is the challenge of AI in TENG: Firstly, most AI technologies cannot reveal the potential relationship between materials, structures and outputs. Secondly, there is a lack of generalized mechanism or understanding of the triboelectric effect. Finally, the over fitting related to AI algorithm, which heavily depends on the quality of input data, is also a challenge. The second is the challenge of AI-TENG in the field of inflammation. First of all, how to analyze the collected data is a problem. Secondly, how to design appropriate algorithms for inflammation research is also a great challenge. Finally, how to evaluate the inflammatory state according to real-time data and AI algorithm. Today, with the rapid development of 5G networks and cloud computing, we have enough opportunities to meet these challenges. The application of TENG and AI technology to the field of inflammation provides a new direction for inflammation research and new hope for some difficult to solve inflammation. On the one hand, TENG has strong sensing and data collection capabilities, and its structure is variable, so it can design different TENG for different inflammation. On the other hand, AI technology involves many algorithms, such as artificial neural network (ANN), decision tree, linear classifier, etc. We can choose different algorithms for different inflammation to achieve accurate prevention, monitoring and treatment. Additionally, the combination of AI and TENG can not only design and optimize the TENG according to the actual demand, but also optimize the AI algorithm subject to the actual situation. The combination of TENG and AI technology has great application prospects in the field of inflammation. They will make the medical service system more real-time, accurate and diverse."
} | 1,250 |
29112720 | PMC5753390 | pmc | 5,408 | {
"abstract": "Abstract Microbial functional diversification is driven by environmental factors, i.e. microorganisms inhabiting the same environmental niche tend to be more functionally similar than those from different environments. In some cases, even closely phylogenetically related microbes differ more across environments than across taxa. While microbial similarities are often reported in terms of taxonomic relationships, no existing databases directly link microbial functions to the environment. We previously developed a method for comparing microbial functional similarities on the basis of proteins translated from their sequenced genomes. Here, we describe fusion DB, a novel database that uses our functional data to represent 1374 taxonomically distinct bacteria annotated with available metadata: habitat/niche, preferred temperature, and oxygen use. Each microbe is encoded as a set of functions represented by its proteome and individual microbes are connected via common functions. Users can search fusion DB via combinations of organism names and metadata. Moreover, the web interface allows mapping new microbial genomes to the functional spectrum of reference bacteria, rendering interactive similarity networks that highlight shared functionality. fusion DB provides a fast means of comparing microbes, identifying potential horizontal gene transfer events, and highlighting key environment-specific functionality.",
"conclusion": "CONCLUSIONS \n fusion DB links microbial functional similarities and environmental preferences. Our analysis reveals environmental factors driving microbial functional diversification. By mapping new organisms to the reference functional space, our database offers a novel, fast, and simple way to detect core-function repertoires, unique functions, as well as traces of HGT. With more microbial genome sequencing and further manual curation of environmental metadata, we expect that fusion DB will become an integral part of microbial functional analysis protocols in the near future.",
"introduction": "INTRODUCTION Microorganisms are capable of carrying out much of molecular functionality relevant to a range of human interests, including health, industrial production, and bioremediation. Experimental study of these microbes to optimize their uses is expensive and time-consuming; e.g. as many as three hundred biochemical/physiological tests only reflect 5–20% of the bacterial functional potential ( 1 ). The recent drastic increase in the number of sequenced microbial genomes has facilitated access to microbial molecular functionality from the gene/protein sequence side, via databases like Pfam ( 2 ), COG ( 3 ), TIGRfam ( 4 ), RAST ( 5 ) and others. Note that the relatively low number of available experimental functional annotations limits the power of these databases in recognizing microbial proteins that provide novel functionality. Additional information about microbial environmental preferences can be found, e.g. in GOLD ( 6 ). While it is well known that environmental factors play an important role in microbial functionality ( 7 ), none of the existing resources directly link environmental data to microbial function. We mapped bacterial proteins to molecular functions and studied the functional relationships between bacteria in the light of their chosen habitats. We previously developed fusion ( 8 ), an organism functional similarity network, which can be used to broadly summarize the environmental factors driving microbial functional diversification. Here, we describe fusion DB – a database relating bacterial fusion functional repertoires to the corresponding environmental niches. fusion DB is explorable via a web-interface by querying for combinations of organism names and environments. Users can also map new organism proteomes to the functional repertoires of the reference organisms in fusion DB; including, notably, matching proteins of yet unannotated function across organisms. The submitted organisms are visualized, and can be further explored, interactively as fusion networks in the context of selected reference genomes. Additionally, the web interface generates fusion + networks, i.e . views that explicitly indicate shared microbial functions. Our overall analyses of the fusion DB data for the first time give quantitative support to the fact that environmental factors drive microbial functional diversification. To demonstrate fusionDB functionality for individual organisms, we mapped a recently sequenced genome of a freshwater Synechococcus bacterium to fusion DB. In line with our previous findings ( 8 ), we demonstrate that this microorganism is more functionally related to other fresh water Cyanobacteria than to the marine Synechococcus . In a case study on Bacillus microbes, we use fusionDB to track organism-unique functions and illustrate the detection of core-function repertoires that capture traces of environmentally driven horizontal gene transfer (HGT). fusionDB is a unique tool that provides an easy way of analysing the, often unannotated, molecular function spectrum of a given microbe. It further places this microbe into a context of other reference organisms and relates the identified microbial function to the preferred environmental conditions. Our approach allows for detection of microbial functional similarities, often mediated via horizontal gene transfer, that are difficult to recover via phylogenetic analysis. We note that, in the near future, fusionDB may also be useful for the analysis of functional potentials encoded in microbiome metagenomes. We expect that fusionDB will facilitate the study of environment-specific microbial molecular functionalities, leading to improved understanding of microbial lifestyles and to an increased number of applied bacterial uses.",
"discussion": "RESULTS AND DISCUSSION Mapping a new Synechococcus genome to fusionDB We downloaded the full genome of Synechococcus sp. PCC 7502 (GCA_000317085.1) as translated protein sequence fasta (.faa file) from the NCBI Genbank ( 9 ) and submitted it to our web interface. This 3,318 protein fresh water Cyanobacteria is isolated from a Sphagnum (peat moss) bog ( 6 ). 86% (2,853) of the bacterial proteins mapped to 2208 fusion DB functions, while 462 (14%) were functional singletons; three proteins exceeded runtime and were excluded (Methods). The whole process from submission to results notification e-mail took under three and a half hours. The mapping indicates that Synechococcus sp. PCC 7502 is most functionally similar (56%) to Synechocystis PCC 6803, a fresh water organism evolutionarily closely related to Synechococcus . It also shares a high functional similarity with a mud Synechococcus ( S.sp . PCC 7002; 53%) and with other fresh water Synechococcus ( S. elongatus PCC 7942 and S. elongatus PCC 6301; 52%). Notably, but not surprisingly, Synechococcus sp. PCC 7502 shares much less functional similarity (40–42%) with the marine Synechococcus bacteria. This relationship is clearly demonstrated by the fusion + networks (Figure 2 ). There are 874 functions shared by all the twelve Synechococcus (SOM Data 1), the core-function repertoire for this genus, and 1128 functions shared among only the fresh water Synechococcus (SOM Data 2). These differential 254 functions (SOM Data 3) are likely important for living in fresh water, as opposed to marine, environment, e.g. low salinity and low osmotic pressure. Figure 2. Screenshot of the fusion+ visualization of all Synechoccocus genomes. The submitted Synechococcus sp. PCC 7502 (query, black) clusters with the fresh water Synechococcus organisms (magenta). Note that Synechococcus sp. PCC 7002 – clustered among fresh water organisms; colored dark blue (marine) – is isolated from marine mud. It is salt tolerant but does not require salt for growth). Environment significantly affects microbial function In our evaluation of the effects of environmental pressures on microbial functionality we found that, in general, same environmental condition (SC) organisms across all environmental factors are more functionally similar than DC organisms (from different environments; Figure 3 ; with some exceptions mentioned below, Kolmogorov-Smirnov test ( 14 ) P -value < 2.5e–6). This finding is intuitive and many studies have demonstrated the presence of horizontal gene transfer (HGT) within environment-specific microbiomes ( 15 – 17 ). Our results, however, for the first time, quantify on a broad scale the environmental impact on microorganism function diversification. Figure 3. Organism pairwise similarity is higher among organisms living in the same environmental conditions. The mean pairwise similarity for same (SC) and different (DC) condition organisms according to ( A ) temperature, ( B ) oxygen and ( C ) habitat preferences. For all points without error bars, the standard errors are vanishingly small. SC-thermophile and SC-psychrophile pairs demonstrate significantly higher similarities when compared to DC pairs (Figure 3A ). Notably, the higher functional similarity between thermophiles than between psychrophiles suggests that protein functional adaptation to low temperature may be less taxing than to high temperature – an interesting finding in itself. When contrasted with the extremophiles, mesophiles seem to have much larger functional diversity; in fact, SC-mesophile similarities are comparable to those of DC pairs (Figure 3A ). Different molecular pathways of aerobic-respiration and anaerobic-respiration/fermentation may explain the high level of dissimilarity between the aerobes and anaerobes (DC-anaerobe-aerobe; Figure 3B ). Interestingly, the SC-anaerobe similarities are higher than the SC-aerobe similarities, likely because the more ancient anaerobic-respiration/fermentation machinery tends to be simpler (fewer reactions) ( 18 ) and more conserved. Different habitat (DC) samples show lower pairwise organism similarity than SC samples as well (Figure 3C ). Interestingly fresh water and marine organism similarity (DC-fresh water-marine) is fairly high, likely due to overlaps in requirements of the aquatic conditions. Note however, that the dissimilarity across fresh water and marine conditions is still high enough to differentiate organisms of the same taxa (e.g. strains of Synechococcus in Figure 2 ). SC-host has the lowest mean organism similarity of the habitat SC samples; we speculate this to be a result of differential adaptations necessary to deal with diverse host defense mechanisms ( 19 ). The soil organisms also share low functional similarity, which is likely due to soil heterogeneity at physical, chemical, and biological levels, from nano- to landscape scale ( 20 ). Case study of a temperature driven HGT event Using the fusion DB explore functionality, we extracted thermophilic, mesophilic, and psychrophilic species representatives (one per species) of the Bacillus genus. We also added two other thermophilic Clostridia, Desulfotomaculum carboxydivorans CO-1-SRB and Sulfobacillus acidophilus TPY, to generate a fusion + network (SOM Table S2; Figure S4A). As expected, note here that overall thermophilic bacteria are further removed from psychrophiles than from mesophiles. Moreover, the thermophilic Bacilli were more closely related to the non- Bacillus thermophiles than to other Bacilli . The three Bacilli thermophiles share 29 functions (SOM Data 4) that are not found in other Bacilli in this organism set, three of which also exist in the two thermophilc Clostridia . One is a likely pyruvate phosphate dikinase (PPDK) that, in extremophiles, works as a primary glycolysis enzyme ( 21 ). The thermophilic Bacilli ’s PPDK proteins are more similar to those in thermophilic Clostridia (sequence identity = 0.65 ± 0.03), than to those in mesophilic/psychrophilic Bacilli (sequence identity = 0.17 ± 0.05). Phylogenetic analysis of the genes with additional thermophilic organisms (SOM Methods) suggests a likely HGT event between the thermophilic organisms (Figure 4B ). The other two shared functions are carried out by proteins translated from mobile genetic elements (MGEs) that mediate the movement of DNA within genomes or between bacteria ( 22 ). Shared closely-related MGEs in distant organisms imply HGT ( 23 ). We thus suggest that fusion DB offers a fast and easy way to trace likely functionally necessary HGT events within niche-specific microbial communities. Figure 4. \n fusion DB reveals an HGT event between thermophilic Bacilli and thermophilic Clostridia . ( A ) fusion + visualization of Bacillus and thermophilc Clostridia. Large organism nodes are connected via small function nodes. The two thermophilic Clostridia are connected to the thermophilic Bacilli via functions that are possibly horizontally transferred; ( B ) phylogenetic analysis of pyruvate, phosphate dikinase (PPDK) gene suggests HGT between thermophilic Bacilli and thermophilic Clostridia . The PPDK genes in thermophilic Bacilli are evolutionarily more related to those in thermophilic Clostridia than those in other Bacilli . In this work, we have highlighted the importance of environmental factors for microbial function, and demonstrated the capability of fusion DB to not only annotate functions, but also directly link function to environment. Although it was developed for mapping new microbial genomes, fusion DB also has the potential for microbiome annotations. By mapping metagenome assemblies to fusion DB, both the functional and taxonomical annotations can be obtained. Moreover, our recent work (Zhu et al. 2017, Functional sequencing read annotation for high precision microbiome analysis, submitted ) suggests that accurate functional annotations can also be obtained without assembly. We thus also expect to make fusion DB useful in this type of analyses in the near future."
} | 3,478 |
20026216 | null | s2 | 5,409 | {
"abstract": "Regenerated silkworm silk solutions formed metastable, soft-solid-like materials (e-gels) under weak electric fields, displaying interesting mechanical characteristics such as dynamic adhesion and strain stiffening. Raman spectroscopy, in situ electric field dynamic oscillatory rheology and polarized optical microscopy indicated that silk fibroin electrogelation involved intermolecular self-assembly of silk molecules into amorphous, micron-scale, micellar structures and the formation of relatively long lifetime, intermicellar entanglement crosslinks. Overall, the electrogelation process did not require significant intramolecular beta-strand or intermolecular beta-sheet formation, unlike silk hydrogels. The kinetics of e-gel formation could be tuned by changing the field strength and assembly conditions, such as silk concentration and solution pH, while e-gel stiffness was partially reversible by removal of the applied field. Transient adhesion testing indicated that the adhesive characteristics of e-gels could at least partially be attributed to a local increase in proton concentration around the positive electrode due to the applied field and surface effects. A working model of electrogelation was described en route to understanding the origins of the adhesive characteristics."
} | 324 |
38435806 | PMC10903745 | pmc | 5,410 | {
"abstract": "Resistive switching\ndevices based on the Au/Ti/TiO 2 /Au\nstack were developed. In addition to standard electrical characterization\nby means of I – V curves, scanning\nthermal microscopy was employed to localize the hot spots on the top\ndevice surface (linked to conductive nanofilaments, CNFs) and perform\nin-operando tracking of temperature in such spots. In this way, electrical\nand thermal responses can be simultaneously recorded and related to\neach other. In a complementary way, a model for device simulation\n(based on COMSOL Multiphysics) was implemented in order to link the\nmeasured temperature to simulated device temperature maps. The data\nobtained were employed to calculate the thermal resistance to be used\nin compact models, such as the Stanford model, for circuit simulation.\nThe thermal resistance extraction technique presented in this work\nis based on electrical and thermal measurements instead of being indirectly\nsupported by a single fitting of the electrical response (using just I – V curves), as usual. Besides,\nthe set and reset voltages were calculated from the complete I – V curve resistive switching series\nthrough different automatic numerical methods to assess the device\nvariability. The series resistance was also obtained from experimental\nmeasurements, whose value is also incorporated into a compact model\nenhanced version.",
"conclusion": "6 Conclusions An experimental characterization\nof resistive switching in Au/Ti/TiO 2 /Au devices has been\npresented, including data obtained with\nsurface scanning thermal microscopy. Macroscopic simulations with\nCOMSOL Multiphysics are performed in order to link the electrical\nand thermal measurements. Quantum effects are considered in the simulations\nperformed. The experimental and simulated data are used together to\ncalibrate a compact model (an enhanced version of the widely used\nStanford model). In this way, temperature in-operando measurements\nof hot spots on the top device surface, linked to the position of\nCNFs, and simulations allow us to describe the CNF internal temperature\nfor modeling. A good agreement between simulated and experimental\ndata is achieved, for both the current and CNF temperature. The average\nCNF temperature is employed to extract the device thermal resistance.\nThis parameter is indirectly determined in compact modeling by fitting\nthe electrical characteristics ( I – V curves). On the contrary, the procedure presented in this\nwork permits a direct estimation, linked to thermal measurements.\nThe device characterization is completed by the extraction of set/reset\nvoltages and series resistance from the experimental I – V curves. The latter parameter is also incorporated\nin the compact model.",
"introduction": "1 Introduction Memristors based on resistive\nswitching (RS) are being scrutinized\nat academic and industrial research centers. The potential of these\nelectron devices is outstanding at the commercial level, and different\nniche applications have already been put in the market. 1 Some of these memristors change their internal\nresistance by means of the creation and destruction of a conductive\nnanofilament across an insulator layer (this layer is sandwiched between\ntwo metals, i.e., a metal–insulator–metal, MIM, structure)\nthat shorts the metallic electrodes. These types of devices are known\nas resistive memories, and they are included by several companies\nin their technologies as nonvolatile memories (TSMC for its 40, 2 28, 3 and 22 nm 4 nodes, as well as INTEL for its 22 nm 5 node). When the CNF is formed, the device\nis in the low-resistance state\n(LRS); conversely, when the CNF is broken (after switching from the\nLRS), it is said to be in the high-resistance state (HRS). This digital\noperational viewpoint allows their use in memory circuits; however,\nif the analog perspective is considered in terms of the device conductance\nvariation, new applications come up such as neuromorphic engineering,\nwhere these memristive devices offer in-memory computing capabilities,\nthat lead to new architectures that can overcome the limitations of\nvon Newmann’s bottleneck. 6 The role\nof memristors within this new paradigm 7 − 16 is essential to reduce energy consumption in artificial intelligence\ncomputation, since circuits based on conventional MOS transistors\nto implement artificial neurons and synapses are more power-inefficient.\nIn addition, resistive memories can also be used for hardware cryptography\nas entropy sources to build physical unclonable functions and true\nrandom number generators. 17 − 19 It is known that RS is\ncontrolled by the application of an electric\nfield and also by the device internal temperature that is increased\nby Joule heating. 20 − 24 In fact, the physical mechanisms behind RS are thermally activated;\nhence, thermal effects are key to understanding and controlling the\ndevice operation. Consequently, an accurate description of these effects\nis essential to build compact models for circuit simulations. 21 , 22 , 25 − 27 Here,\nwe study the RS features of devices based on Au/Ti/TiO 2 /Au stacks. We fabricate them and measure I – V curves under the ramped voltage stress\n(RVS) operation regime. An in-depth analysis of the experimental data\nis performed making use of different numerical methods to extract\nRS parameters. In addition, a study of the cycle-to-cycle variability 22 , 28 , 29 is performed to understand the\nexperimental data structure. The information on heat dissipation produced\nby the filament for these devices is provided in ref ( 30 ). An operando scanning\nthermal microscope (SThM) was used to characterize the device surface,\nlocalize the device CNFs, and extract the temperature in the hot\nspots. The results are contrasted with physical simulations by means\nof the COMSOL Multiphysics simulation tool, and the device charge\nconduction and temperature distributions are analyzed. Both experimental\ncurrent and temperature distributions are used to tune the simulator.\nFinally, we go through a compact modeling stage where the Stanford\nmodel 31 − 34 is adapted to fit experimental and simulation data, and essential\nparameters such as thermal resistance are extracted.",
"discussion": "5 Results and Discussion 5.1 Parameter\nExtraction As highlighted\nabove, the set and reset voltage extraction procedures are explained\nin the Supporting Information 1 and Figure S1 . If the set and reset currents are plotted versus the corresponding\nvoltages ( Figure 4 a,b),\nwe see that the reset parameters present less variability, which is\neasily seen in the cumulative distribution functions plotted in Figure S2a–d . Figure 4 (a) Experimental I set vs V set extracted,\nemploying methods MS1, MS2, and MS3. (b)\nExperimental I reset vs V reset extracted, switching voltage parameters, employing\nmethods MR1, MR2, MR3, and MR4. (c) LRS and HRS resistances (read\nat 0.2 V) vs cycle number for all the measured RS series. (d) HRS/LRS\nresistance ratio vs cycle number calculated with data from (c). It is observed that R HRS / R LRS is high enough to let the use of\nthese devices feasible\nfor nonvolatile memory applications, and the values found for R HRS and R LRS are\ncoherent in comparison to other memristive devices. 28 5.2 RS Parameter Statistics We performed\na statistical analysis to untangle the structure of the data obtained\nin previous sections. To do so, we obtained the mean values, standard\ndeviations, and coefficients of variation (CV, calculated as σ/μ,\nwhere σ stands for the standard deviation and μ for the\nmean) for each RS parameter; see Tables 2 and 3 for the set\n(reset) parameters. In general, if the cycle-to-cycle variability\nis low (i.e., CV of V set < 2%), the\ndevices could be used for information storage, 44 computation, 6 or transmission; 45 if the variability is high (CV of V set > 20%), the devices could rather be employed for\ndata\nencryption as entropy source for true random number generators 18 or physical unclonable functions. 46 Table 2 Statistical Study\nof the Extracted\nSet of RS Parameters for the Different Extraction Methodologies a parameter mean (μ) standard deviation (σ) coefficient of variation (σ/μ) V MS1 0.68789 V 0.10654 V 0.15488 V MS2 0.64782\nV 0.11663 V 0.18004 V MS3 0.55103 V 0.08048 V 0.14606 I MS1 3.32701 × 10 –4 A 7.83586 × 10 –5 A 0.23552 I MS2 2.2049 × 10 –4 A 1.0575 × 10 –4 A 0.47961 I MS3 9.95904 × 10 –5 A 3.76061 × 10 –5 A 0.37761 a The minimum CV\nvalues are highlighted. Table 3 Statistical Study of the Reset RS\nParameters for the Different Extraction Methodologies a parameter mean (μ) standard deviation (σ) coefficient of variation (σ/μ) V MR1 0.73267 V 0.08869 V 0.12105 V MR2 0.73084\nV 0.08786 V 0.12022 V MR3 0.6658 V 0.06492 V 0.09751 V MR4 0.68092 V 0.07063 V 0.10373 I MR1 5.08099 × 10 –4 A 5.09536 × 10 –5 A 0.10028 I MR2 5.17962 × 10 –4 A 5.46663 × 10 –5 A 0.10554 I MR3 5.47164\n× 10 –4 A 5.32173 × 10 –5 A 0.09726 I MR4 5.53214 × 10 –4 A 5.09291 × 10 –5 A 0.09206 a The minimum\nCV values are highlighted. As known, a lower CV indicates lower variability.\nThe results demonstrate,\nas expected, that the CV depends on the extraction methodology. This\nis a key result that makes it clear that the extraction numerical\nprocedure should be clarified in the literature. In particular, MS3\npresents the lowest value for V set , whereas\nMS1 is for I set . MR3 marks the minimum\nvariability for V reset , while MR4 is for I reset . In filamentary-based memristive\ndevices, the reset process normally\nexhibits higher variability than the set; 1 , 47 , 48 however, in our devices, the behavior is\ndifferent. Therefore, a different role of thermal and electric field\neffects is expected to lead to the homogenization of the V reset distribution. We have also extracted the series\nresistance of our devices following\na previously published extraction technique; 49 , 50 see Figure 5 a. In\naddition, the reset and set transition voltages were extracted 50 (they stand for the reset and set voltages,\nonce the effects of the series resistance have been extracted from\nthe original current vs voltage curve, what is known as the normalized I – V curve); see Figure 5 b. The CDFs for these parameters\nare listed in Figure 5 c,d. It is observed, as also reported in ref ( 50 ) for the HfO 2 technology, that the absolute values of the reset and set transition\nvoltages are much more similar than the original set and reset voltages.\nHowever, the series resistances extracted are higher than that in\nthe HfO 2 devices analyzed in ref ( 50 ). Figure 5 (a) Series resistance\ncomputed for the complete RS series as a\nfunction of the cycle number for the data analyzed. (b) Set transition\nvoltage ( V TS ) and reset transition voltage\n( V TR ) plotted against the cycle number\nfor the complete RS series of the data under study. Cumulative distribution\nfunctions for the studied parameters in the whole RS series: (c) series\nresistance, (d) transition voltages for the set ( V TS ) and for the reset processes ( V TR ). 5.3 Device\nPhysical Simulation We have\nmade use of the simulation approach described in Section 4 . The reset process was simulated\nby assuming that the CNF is fully formed at the beginning of the simulation.\nWe employ the first part of the reset I – V curve (see Figure 6 a), prior to the reset event, in order to fit the experimental\ncurrent and also the temperature in certain parts of the device. In Figure 6 a, we show the current\nversus voltage (blue data) and temperature increment (black data)\non top of the Al 2 O 3 layer measured with the\nSThM technique (in an in-operando manner). In particular, we simulated\nthe reset curve (highlighted with a red ellipse); in this case, we\nuse a fully formed hourglass-shaped CNF, as shown in Figure 3 . Simulation and in-operando\nexperimental data for the reset process highlighted in Figure 6 a are shown in Figure 6 b showing a reasonably good\nfit, taking into account the complexity of simultaneously reproducing\ntemperature and current data. Figure 6 (a) Experimental current vs voltage (in blue)\nand temperature increment\n(in black, obtained with SThM) on top of the device outer Al 2 O 3 layer vs voltage (the current curve corresponds to\nthe temperature increment curve; i.e., in-operando measurements),\n(b) simulated (straight lines) and experimental data (in dots) for\nthe reset process (the experimental data correspond to the curve highlighted\nin the red ellipse in (a). (c) Simulated (straight lines) and experimental\n(black dots) temperature increment on top of the Al 2 O 3 layer and simulated CNF average temperature along the reset\nprocess I – V curve (this latter\ncurve is needed for the compact modeling process). Once the COMSOL simulation model was tuned, we\ncalculated the average\nCNF temperature. This temperature is employed in compact models since\njust one temperature is usually assumed in the device for each bias\npoint. In this respect, simplified thermal models can be built to\ndescribe the devices in the circuit simulation approach. 25 A closer look at the CNF temperature allows\nus to detail the thermal\ndistribution along its length ( Figure 7 ). See the temperature peaks at the CNF narrowing,\nas it should be since Joule heating increases at this point because\nof the current line concentration. Notice also the fast temperature\ndecrease outside the filament region, mostly at the Au side. Figure 7 Temperature\nat the center of the conductive filament vs z coordinate\n(vertical device coordinate) in our simulation\ndomain for different external voltages. CNF position and the z -axis orientation are seen in the inset. The higher temperature\nis obtained at the CNF narrowing (at the center of the hourglass structure). It is worth also mentioning the good fit obtained\nby comparing\nthe simulated and measured distributions of temperature increase at\nthe device surface ( Figure 8 ). A good result is obtained throughout the simulation domain\ntop surface. These results suggest the correctness of the model proposed. Figure 8 (a) Three-dimensional\nexperimental plot (temperature increase with\nrespect to room temperature) on top of the Al 2 O 3 layer for V = 0.3 V. (b) Corresponding COMSOL simulation\n(after tuning) for the device scheme in Figure 3 and V = 0.3 V. (c) Comparison\nbetween the simulated and measured distributions; (d) panel; (c) zoomed-in\nview. (e) Good fit is obtained for the different cuts in the experimental/simulated\ndistributions at different simulation domain orientations; this one\nis taken along the x- axis. 5.4 Compact Modeling For the compact\nmodeling approach, the Stanford model 31 − 34 is employed. This widely known\nmodel uses an equivalent single RC electrical network, driven by a\ncurrent source, for representing the thermal behavior (thermal resistance\nand capacitance) and the Joule heating, respectively. We were able\nto fit the experimental reset curve highlighted in Figure 6 , as shown in Figure 9 . Figure 9 (a) Current vs voltage\nfor a reset process. Experimental data are\nshown in red symbols, and those obtained with the Stanford model are\nshown in lines. (b) Average temperature in the CNF obtained with the\nCOMSOL simulation tool (green line) and device temperature obtained\nwith the Stanford model (black line). We employed the model parameters described in Table 4 . In particular, for\nthe determination\nof the thermal resistance, we used the COMSOL simulated data of Figure 9 b (average CNF temperature).\nAt this point, we highlight the fact that, when fitting I – V curves in developing memristor models,\nwe usually do not have the information given in Figure 9 b, which is connected to the SThM measurements,\nand therefore, the thermal resistance ( R th ) cannot be accurately determined. In our case (see Table 4 ), the value is 1.2 × 10 6 K/W, which is in line with those reported in refs ( 25 , 31 ). Table 4 Stanford Model Parameters\nUsed in Figure 9 a symbol value symbol value t ox 10 nm E a 1.05 eV I 0 50 mA E m 3.25 eV V 0 0.2 V g max 6.3 nm g 0 0.7 nm g ini 5.2 nm β 10.5 (reset) T 0 300 K v 0 5 × 10 6 m/s T crit 450\nK γ 0 20 R series 220 Ω α 1.1 (reset) R th 1.2 × 10 6 K/W a R series is a series resistance added to the nonlinear\ncurrent source of\nthe Stanford model. 50 The analytical expression to determine\nthe thermal\nresistance is\ngiven in eq 2 . In our\ncase, accounting for the low-frequency RVS operation measurements\nperformed (this implies steady-state operation), the transient part\nof the modified heat equation can be excluded for the usual thermal\ncapacitance values found for resistive memories. 25 2 We also used a series resistance\nin the compact modeling approach, following a previous work, 50 where the inclusion of this parameter and the\neffects on the simulation are described."
} | 4,201 |
26949922 | null | s2 | 5,411 | {
"abstract": "Oscillations between reducing and oxidizing conditions are observed at the interface of anaerobic/oxic and anaerobic/anoxic environments, and are often stimulated by an alternating flux of electron donors (e.g., organic carbon) and electron acceptors (e.g., O2 and NO3(-)). In iron (Fe) rich soils and sediments, these oscillations may stimulate the growth of both Fe-reducing bacteria (FeRB) and Fe-oxidizing bacteria (FeOB), and their metabolism may induce cycling between Fe(II) and Fe(III), promoting the transformation of Fe (hydr)oxide minerals. Here, we examine the mineralogical evolution of lepidocrocite and ferrihydrite, and the adaptation of a natural microbial community to alternating Fe-reducing (anaerobic with addition of glucose) and Fe-oxidizing (with addition of nitrate or air) conditions. The growth of FeRB (e.g., Geobacter) is stimulated under anaerobic conditions in the presence of glucose. However, the abundance of these organisms depends on the availability of Fe(III) (hydr)oxides. Redox cycling with nitrate results in decreased Fe(II) oxidation thereby decreasing the availability of Fe(III) for FeRB. Additionally, magnetite is detected as the main product of both lepidocrocite and ferrihydrite reduction. In contrast, introduction of air results in increased Fe(II) oxidation, increasing the availability of Fe(III) and the abundance of Geobacter. In the lepidocrocite reactors, Fe(II) oxidation by dissolved O2 promotes the formation of ferrihydrite and lepidocrocite, whereas in the ferrihydrite reactors we observe a decrease in magnetite stoichiometry (e.g., oxidation). Understanding Fe (hydr)oxide transformation under environmentally relevant redox cycling conditions provides insight into nutrient availability and transport, contaminant mobility, and microbial metabolism in soils and sediments."
} | 459 |
30881604 | PMC6420082 | pmc | 5,412 | {
"abstract": "With regard to social and environmental sustainability, second-generation biofuel and biogas production from lignocellulosic material provides considerable potential, since lignocellulose represents an inexhaustible, ubiquitous natural resource, and is therefore one important step towards independence from fossil fuel combustion. However, the highly heterogeneous structure and recalcitrant nature of lignocellulose restricts its commercial utilization in biogas plants. Improvements therefore rely on effective pretreatment methods to overcome structural impediments, thus facilitating the accessibility and digestibility of (ligno)cellulosic substrates during anaerobic digestion. While chemical and physical pretreatment strategies exhibit inherent drawbacks including the formation of inhibitory products, biological pretreatment is increasingly being advocated as an environmentally friendly process with low energy input, low disposal costs, and milder operating conditions. Nevertheless, the promising potential of biological pretreatment techniques is not yet fully exploited. Hence, we intended to provide a detailed insight into currently applied pretreatment techniques, with a special focus on biological ones for downstream processing of lignocellulosic biomass in anaerobic digestion.",
"conclusion": "6 Closing Remarks—Conclusions Various pretreatment strategies—physical, chemical, and biological—have been developed to overcome the inherent resistance of lignocellulose to anaerobic degradation. Biological pretreatment strategies, however, outcompete other pretreatments due to the application of milder conditions, and lower by-product formation and corrosiveness. The variety of applied techniques comprises micro-aerobic treatments, ensiling or composting, the separation of digestion stages, and pretreatments using various fungi. Fungal pretreatments have achieved particular success using various white, brown, and soft rot fungi, or a combination of these. Pretreatment processes applying white rot fungi from the genera Ceripoioposis, Phanerochaete, Fusarium, Trametes, Polyporus, and Pleurotus target cellulose as well as lignin, allowing the use of recalcitrant, second-generation substrates for biogas production. Therefore, biological pretreatment strategies offer great potential to improve the digestibility of different biogas substrates; however, detailed investigations of the mode of action, the application of different substrates, full-scale implementation, and possible by-product formation are still needed.",
"introduction": "1 Introduction Although it is known that CO 2 production from fossil fuel combustion is a major contributor to global warming, these energy carriers are still the most important resources for global energy generation [ 1 ]. Great efforts have been devoted to increasing energy production from nonfossil fuels and to replacing climate-change-relevant energy sources by renewable ones. Hydropower, wind, and solar energy are probably the most promising alternative energy resources but can exhibit limitations concerning flexible energy production, storage and/or backup, transportation, and land requirements [ 2 ]. Biogas production from anaerobic digestion (AD) processes is considered as an attractive source for green energy [ 3 , 4 ] and, therefore, endeavors have been made to increase the share of biogas in global energy production. During anaerobic digestion, organic feedstocks are converted into biogas containing methane (CH 4 ) as a valuable end-product. The energy input for biogas production is calculated to be lower than in current ethanol production, leading to a higher energy output-to-input ratio [ 5 ]. However, the expanded production of biogas was often achieved by the utilization of energy crops directly competing with food crop farming (first-generation biofuels). Therefore, the exploration of lignocellulosic materials (second-generation biofuels) for bio-methane production was substantially accelerated during the past years, thus offering ecological as well as economic advantages [ 6 ]. However, lignin resists (complete) degradation under anaerobic conditions, posing a challenge regarding the overall degradability of lignocellulose in AD. In this context, enhancing the substrate conversion to overcome the degradation resistance of lignocellulosic resources is of utmost importance to achieving environmentally friendly and economically feasible processes [ 7 , 8 ]. Hence, effective pretreatment methods are needed, particularly because lignocellulosic biomass has been evaluated as an attractive renewable energy source due to its inexhaustible, ubiquitous character [ 2 , 9 ]. The main objectives of this work are, therefore, (i) to present a short update on the currently available pretreatment strategies for enhanced disintegration of lignocellulosic resources and their application, and (ii) to review biological pretreatments currently applied for enhanced biogas production."
} | 1,237 |
29922245 | PMC5996133 | pmc | 5,414 | {
"abstract": "Trees are crucial for sustaining life on our planet. Forests and land devoted to tree crops do not only supply essential edible products to humans and animals, but also additional goods such as paper or wood. They also prevent soil erosion, support microbial, animal, and plant biodiversity, play key roles in nutrient and water cycling processes, and mitigate the effects of climate change acting as carbon dioxide sinks. Hence, the health of forests and tree cropping systems is of particular significance. In particular, soil/rhizosphere/root-associated microbial communities (known as microbiota) are decisive to sustain the fitness, development, and productivity of trees. These benefits rely on processes aiming to enhance nutrient assimilation efficiency (plant growth promotion) and/or to protect against a number of (a)biotic constraints. Moreover, specific members of the microbial communities associated with perennial tree crops interact with soil invertebrate food webs, underpinning many density regulation mechanisms. This review discusses belowground microbiota interactions influencing the growth of tree crops. The study of tree-(micro)organism interactions taking place at the belowground level is crucial to understand how they contribute to processes like carbon sequestration, regulation of ecosystem functioning, and nutrient cycling. A comprehensive understanding of the relationship between roots and their associate microbiota can also facilitate the design of novel sustainable approaches for the benefit of these relevant agro-ecosystems. Here, we summarize the methodological approaches to unravel the composition and function of belowground microbiota, the factors influencing their interaction with tree crops, their benefits and harms, with a focus on representative examples of Biological Control Agents (BCA) used against relevant biotic constraints of tree crops. Finally, we add some concluding remarks and suggest future perspectives concerning the microbiota-assisted management strategies to sustain tree crops.",
"conclusion": "Concluding remarks: toward microbiota-assisted management strategies Belowground microbial communities associated with tree crops are key factors for their growth, development, and health, particularly under non-favorable soil conditions. They decisively contribute to enhanced productivity, improve accessibility to low-abundant nutrients, cope with a range of (a)biotic stressors that affect their associated hosts, and also play an important role in phyto-assisted biodegradation of toxic compounds present in soils. Until now, how belowground microbiota contribute to the fitness of tree crop agro-ecosystems, remains largely unknown and only now it is starting to be unraveled in detail. The four fundamental questions to better understand these associations are: who are there? what are they doing? who is active out there? and how do activities of these microorganisms relate to ecosystem functions? (Amann, 2000 ; Leveau, 2007 ). The answers to these questions, based on an in-depth knowledge of the structure and functioning of belowground communities, will constitute the pillars to develop holistic management strategies aiming to cope with the range of (a)biotic constraints affecting tree crops (Figure 5 ). The relationship between soil-borne microbes and tree crops is delicate and complex and can have either positive or negative effects on the host. It can be assumed that benefits derived from the interaction of tree crops with beneficial belowground (micro)organisms are expected to yield similar outcomes in aboveground ecosystems than those observed, and more frequently investigated, in herbaceous, short-living species. Moreover, the associations established with trees are expected to be more stable, enduring along time, although variations in composition, structure, and functioning do occur, likely in a cyclic manner. These are subjected to a broad range of genetic, (a)biotic and environmental cues and factors. In this sense, integrated “omic” analyses, combining metagenomics, metatranscriptomics, metaproteomics, and metabolomics, are now providing a more accurate view of the activities and the physiological potential of belowground plant-associated microbiota (Zhang et al., 2010 ; Knief, 2014 ). Figure 5 A strategy to manage biotic constraints affecting tree crops (i.e., pathogens, pests, invasive species) based on the identification, characterisation and harnessing of soil/root microbiota [based on a conceptual framework by Kowalski et al. ( 2015 )]. Studies on tree crop production and diseases have thus far historically relied on single microbe-based formulations or focused on single species (the pathogen), while little attention has been paid to the use of consortia of beneficial microorganisms or to investigate many other microorganisms most likely present in the infection sites. One way to assist tree crop production might be to integrate beneficial plant microbiota or use ad hoc tailored microbiota to target specific deleterious agents (Gopal et al., 2013 ; Kowalski et al., 2015 ; Pinto and Gomes, 2016 ; Berg et al., 2017 ; Figure 5 ). Due to the complexity of tree crop ecosystems—dominated by vegetal species displaying peculiarities such as large biomass, complicated anatomy, large root systems, longevity, and the large spatial domains and timescales over which tree crops are grown –management options such as soil amendments, intercropping and soil processing can be applied by farmers. Once again, the currently-available multi-omic tools, combined with other methodological approaches, will provide a much better knowledge on the complex network of trophic interactions taking place at the soil/root level (Massart et al., 2015 ). A more-in-depth analysis of these interactions could be of crucial importance in designing new and effective microbial consortia for optimizing plant production and developing new strategies for disease control. In conclusion, a more holistic approach to tree crop agriculture is needed. Understanding the microbial diversity, distribution, activity, and function, and linking the microbial community structure with both environmental factors and ecosystem functioning, are major challenges for the soil/plant microbiology science in this century.",
"introduction": "Introduction Tree crops are fundamental for human nutrition and warrant food security and stability of many farms. The surface covered by tree crops showed a growing trend in the last decade, approaching to a global acreage of 10 Mha for main fruit types with an ~20% increase in productivity during the period 2004–2014 (FAOSTAT, http://fenix.fao.org/faostat/beta/en/ ) (Figure 1 ). Plants (like trees) as well as the environment (such as soil) consist of complex and diverse assemblage of myriads of microbial species closely associated with their host, either as epiphytes or as endophytes (Trivedi et al., 2016 ). The association established by a plant and its microbiota (Lederberg, 2006 ) can be either stable, transient or fluctuating, enduring along the host lifetime determines its development, fitness, and health (Kowalski et al., 2015 ). The belowground microbiota is mostly comprised of bacteria and fungi belonging to the second trophic level (i.e., decomposers, mutualists, pathogens, parasites, and root-feeders) of the soil food web (Ingham, 1999 ) (Figure 2 ). Because of their size, nematodes per definition are not part of the soil microbiota, although they can play important roles in shaping its structure, including not only species belonging to the second trophic level (root-feeder nematodes) but also those ones of the third level (i.e., shredders, predators, grazers), particularly nematodes feeding on fungi and bacteria. Despite their parasitic behavior, phytoparasitic nematodes spend a considerable part of their life-cycle in the soil and represent the first group of plant parasites present in the soil. Therefore, the fraction of microorganisms linked to them can be considered as a specific compnent of the plant-associated microbiota (Vandekerckhove et al., 2000 ; Haegeman et al., 2009 ). Figure 1 Total world surface (triangles) and yield/hectar (solid squares) of main tree crops (citrus, fresh and tropical, pome and stone fruits) (source FAOSTAT: http://fenix.fao.org/faostat/beta/en/ ) . Figure 2 A simplified food web describing main soil components and their relationships. The nodes are classified by roles as: primary root (dark green), beneficial soil components, organisms or promoters, including soil factors (blue), decomposers (brown), pathogens (orange) and biocontrol agents or antagonists (pale green). Arrows show negative effects (A) , such as predation, parasitism, pathogenicity or (B) positive links, such as growth promotion, symbiosis or alimentary provision. Indirect factors such as those related to abundance, competition or other density-dependent effects are not included. Node labels and sizes are proportional to their connection level (number of edges). Analysis produced with Gephi (Bastian et al., 2009 ). The study of the belowground microbiota has gained attention during the last years. Many studies have investigated soil belowground microbiota focusing on key issues such as the composition, structure, and functioning of these microbial communities and how they are built up and influenced by a range of factors [e.g., changing environment, varying weather/climatic conditions, (diffuse) pollution, anthropogenic actions, plant genotype, plant signals, etc.] [see, for instance (Doornbos et al., 2012 ; Bakker et al., 2013 ; Bulgarelli et al., 2013 ; Mendes et al., 2013 ; Lakshmanan et al., 2014 ; Fierer, 2017 )]. Structural and functional modifications in the soil/rhizosphere microbiota have a crucial impact on aboveground ecosystems. In the particular case of trees, the trophic interactions established between the host and its associated belowground microbiota could be assumed, at least a priori , as more durable than that occurring in short-living, herbaceous species. Indeed, due to their perennial, long-living nature, it could be envisaged that belowground microbial communities associated with tree crops may be shaped by more persistent changes than those taking place in annual crops. Trees provide, in a more long-lasting way, an energy flow through photosynthesis, mobilizing nutrients as part of a continuous process leading to their recycling via the organic matter accumulation and its eventual decay. Moreover, due to the absence of annual rotation and lack of soil tillage, perennial tree crops also represent a stable food source not only for building up consortia of beneficial microbial communities but also for many root pathogens or parasites. Direct effects, due to deposition of organic matter and nutrients, could be more constant while indirect effects through agricultural inputs (i.e., application of fertilizers, pesticides, etc., irrigation and soil labor) would potentially work in a similar way as in annual crops. Being present on a time scale of years, and having a persistent, deeper root system, the impacts of tree crops (e.g., on nutrients mobilization, organic matter accumulation, parasites, etc.) largely differ from annual crops and thus cannot be considered as comparable. This is well illustrated by the currently-available and powerful metagenomic approaches (Colagiero et al., 2017 ). Overall, the events taking place between a tree crop and its associated whole soil microbiota have not been widely investigated. In this study, we consider a tree crop as a woody, perennial plant with a distinct trunk, such as fruit, nut, and timber trees of economic importance, grown in orchards or in planted forests. Therefore, we exclude from this definition any palm “tree” species ( Arecaceae family) as well as any other herbaceous perennial monocots (e.g., Musa spp., Dracaena spp., Poaceae family representatives, etc.) showing arborescent growth, since from both botanical and anatomical point of view they are not true trees. Tree crop ecosystems are of immense importance since they provide a range of products and ecosystem services. An increased understanding of the links between soil microbiota and trees is certainly helpful for the development of more effective and sustainable tree crop management strategies. Here, we (i) summarize methodological approaches used to unravel belowground microbial communities, with emphasis on tree crops; (ii) review the composition, distribution, and multitrophic networks of soil and root-associated microbiota, including endophytes, and the way they influence aboveground ecosystems in tree crops; (iii) examine the benefits (productivity, development, health and fitness, stress alleviation) and harms (mainly biotic stresses) for tree crops and woody plantations upon interaction with indigenous and introduced soil-borne (micro)organisms; and (iv) recapitulate strategies implemented for tree crop growth promotion."
} | 3,258 |
24812336 | PMC4147887 | pmc | 5,415 | {
"abstract": "Motivation: Genome-scale metabolic reconstructions summarize current knowledge about a target organism in a structured manner and as such highlight missing information. Such gaps can be filled algorithmically. Scalability limitations of available algorithms for gap filling hinder their application to compartmentalized reconstructions. Results: We present fast G ap F ill , a computationally efficient tractable extension to the COBRA toolbox that permits the identification of candidate missing knowledge from a universal biochemical reaction database (e.g. Kyoto Encyclopedia of Genes and Genomes) for a given (compartmentalized) metabolic reconstruction. The stoichiometric consistency of the universal reaction database and of the metabolic reconstruction can be tested for permitting the computation of biologically more relevant solutions. We demonstrate the efficiency and scalability of fast G ap F ill on a range of metabolic reconstructions. Availability and implementation: fast G ap F ill is freely available from http://thielelab.eu . Contact: \n ines.thiele@uni.lu Supplementary information: \n Supplementary data are available at Bioinformatics online.",
"introduction": "1 INTRODUCTION A biomolecular network reconstruction summarizes biochemical, physiological and genomic knowledge in a mathematically structured electronic format ( Palsson, 2006 ). It can be converted into a computational model, and predictions have been used to accelerate biotechnological and biomedical discoveries ( Oberhardt et al. , 2010 ). The predictive capacity and accuracy of a model depend on the comprehensiveness and biochemical fidelity of the reconstruction, with respect to the underlying biochemistry. The comprehensiveness of a genome-scale metabolic reconstruction can be improved by using the model to detect and fill network gaps ( Rolfsson et al. , 2011 ). Similarly, reconstruction fidelity can be improved by using the model to detect reconstruction stoichiometry inconsistent with biochemistry ( Gevorgyan et al. , 2008 ) or reactions inconsistent with steady state flux ( Vlassis et al. , 2014 ). Existing gap-filling algorithms, reviewed by Orth and Palsson (2010) , become intractable in high dimensions. Decompartmentalization of genome-scale compartmentalized metabolic networks reduces their dimension, rendering gap filling tractable ( Rolfsson et al. , 2011 ). However, this approach underestimates the amount of missing information because it connects reactions that would normally not co-occur in the same cellular compartment. We present fast G ap F ill , the first scalable algorithm capable of efficiently detecting and filling network gaps in compartmentalized genome-scale models. fast G ap F ill draws on, and extends, fastcore ( Vlassis et al. , 2014 ), an algorithm to approximate the cardinality function to identify a compact flux consist ent model, in which all reactions carry a non-zero flux in at least one flux distribution. fast G ap F ill allows integrating all three notions of model consistency, namely, gap-filling, flux consistency and stoichiometric consistency in a single tool.",
"discussion": "4 DISCUSSION We applied fast G ap F ill to five metabolic models ( Table 1 ), demonstrating its broad applicability and scalability for various sizes of the gap-filling problem. Alternate gap-filling solutions can be computed by changing weightings on non-core reactions in the preprocessed problem. Note that all candidate metabolic and transport reactions are hypotheses requiring experimental validation ( Rolfsson et al. , 2011 ). Our implementation provides an openCOBRA ( Schellenberger et al. , 2011 ) compatible version of the KEGG reaction database; however, any other universal reaction database could be used with fast G ap F ill , so long as the same input format is maintained and care is taken to correctly identify identical metabolites. fast G ap F ill is the first scalable approach to identify candidate missing knowledge in compartmentalized metabolic reconstructions, and the approach is applicable to any form of biochemical network gap-filling problem.\n Table 1. Gap filling of metabolic reconstructions on a standard desktop computer (Dell, Intel Core i5, 16 GB RAM, 64 bit) Model name Thermotoga maritima Escherichia coli Synechocystis sp. sIEC Recon 2 ( Zhang et al. , 2009 ) ( Feist et al. , 2007 ) ( Nogales et al. , 2012 ) ( Sahoo and Thiele, 2013 ) ( Thiele et al. , 2013 ) S a 418 × 535 1501 × 2232 632 × 731 834 × 1260 3187 × 5837 SUX a 14 020 × 31 566 21 614 × 49 355 28 174 × 62 866 48 970 × 109 522 58 672 × 132 622 Comp b 2 3 4 7 8 B 116 196 132 22 1603 B s 84 159 100 17 490 Number of gap-filling reactions 87 138 172 14 400 t preprocessing (s) c 52 237 344 1003 5552 t fastGapFill (s) 21 238 435 194 1826 a The dimensions are given as metabolites × reactions. b Comp, compartments. c Preprocessing includes computing the flux consistent metabolic model, merging of UX for all compartments of S and adding solvable blocked reactions B s . Note : Equal weighting of all reactions was used. See Supplementary Table S1 for candidate gap-filling solutions. Funding : I.T. was supported by an ATTRACT program grant ( FNR/A12/01 ) from the Luxembourg National Research Fund (FNR) . R.F. was supported by the Interagency Modeling and Analysis Group , Multi-scale Modeling Consortium U01 awards from the National Institute of General Medical Sciences , award GM102098-01 , and U.S. Department of Energy, Office of Science, Biological and Environmental Research Program , award ER65524 . Conflict of Interest : none declared."
} | 1,399 |
36073819 | PMC9602832 | pmc | 5,418 | {
"abstract": "ABSTRACT Forest succession is important for sustainable forest management in terrestrial ecosystems. However, knowledge about the response of soil microbes to forest disease-driven succession is limited. In this study, we investigated the soil fungal biomass, soil enzyme activity, and fungal community structure and function in forests suffering succession processes produced by pine wilt disease from conifer to broadleaved forests using Illumina Miseq sequencing coupled with FUNGuild analysis. The results showed that the broadleaved forest had the highest fungal biomass and soil enzyme activities in C, N, and S cycles, whereas the conifer forest had the highest enzyme activity in the P cycle. Along the succession, the fungal diversity and richness significantly increased ( P < 0.05). The fungal communities were dominated by Ascomycota (42.0%), Basidiomycota (38.0%), and Mortierellomycota (9.5%), among which the abundance of Ascomycota significantly increased ( P < 0.05), whereas that of Basidiomycota and Mortierellomycota decreased ( P < 0.05). The abundance of species Mortierella humilis , Lactarius salmonicolor , and Russula sanguinea decreased, whereas that of Mortierella minutissima increased ( P < 0.05). The forests in different succession stages formed distinct fungal communities and functional structures ( P < 0.05). Functionally, the saprotrophs, symbiotrophs, and pathotrophs were the dominant groups in the conifer, mixed, and broadleaved forests, respectively. Soil pH and soil organic carbon were the key factors influencing the fungal community and functional structures during the succession. These findings provide useful information for better understanding the plant-microbe interaction during forest succession caused by forest disease. IMPORTANCE The studies on soil fungal communities in disease-driven forest succession are rare. This study showed that during the disease-driven forest succession, the soil enzyme activity, soil fungal diversity, and biomass increased along succession. The disease-driven forest succession changed the soil fungal community structure and function, in which the symbiotrophs were the most dominant group along the succession. These findings provide useful information for better understanding the plant-microbe interaction during forest succession caused by forest disease.",
"conclusion": "Conclusion. The forest succession induced by pine wood nematode disease significantly increased the fungal biomass, soil enzyme activity, and fungal diversity. The forests in different stages of succession formed a distinct fungal community and functional structures in which the fungal community shifted from Basidiomycota dominance in the initial conifer forest to a higher abundance of Ascomycota in the eventual broadleaved forest. Moreover, the symbiotrophs were the most dominant group and the abundance of pathotrophs increased during the succession. Functionally, saprotrophs, symbiotrophs, and pathotrophs dominated the fungal community in the initial forest, mixed forest, and eventual forest, respectively. The soil pH and SOC were the most important factors affecting the fungal community and functional structure, indicating the importance of environmental factors in shaping microbial community. These findings provide new insight into the responses of microbes to disease-induced forest succession and also highlight the importance of the linkage between plants and microbes in the forest ecosystem.",
"introduction": "INTRODUCTION Forest succession caused by natural disturbance can affect a wide array of terrestrial ecosystem processes and is important for sustainable forest management ( 1 ). The ecological linkages between aboveground and belowground biota during forest succession have been considered an important mechanism in forest development and succession ( 2 ). For example, wildfire disturbance can change the forest soil chemistry and soil enzyme activity, which reduces the diversity and abundance of mycorrhizal fungi ( 3 ). The plant changes caused by succession can affect the soil microbial community, which, in turn, can regulate the plant growth via moderating the decomposition of soil organic matter (SOM) ( 4 ). Many studies have focused on the effects of forest succession on the aboveground plant community assembly ( 5 ), tree architecture variability ( 6 ), and plant nutrient use strategies ( 7 ), but knowledge on the dynamics of soil microbial communities and their functions during the disease-driven forest succession process is limited. Soil microbes generally have rapid responses and high turnover rates in response to environmental disturbance, which could provide additional information on the forest succession mechanism; for example, plant species can strongly affect the soil microbial community structure and functions through the allocation of plant carbon and other nutrients ( 8 , 9 ). Soil abiotic properties, including pH and nutrient availability, are key regulators that link plant performance with soil microbial communities ( 10 , 11 ). Soil fungi represent an essential functional component of soil as decomposers, symbionts, and pathogens, in which saprophytic soil fungi can decompose soil substrates and increase the soil nutrient cycle, while ectomycorrhizal fungi, such as symbiotrophs, are known to enhance the nutritional condition of plants ( 12 , 13 ). Fungal biomass and microbial enzyme activity are sensitive to changes in soil characteristics ( 14 ). In general, the deciduous forest has significantly higher soil fungal biomass when compared with that of the conifer forest ( 15 ). The extracellular soil enzymes produced by fungi can be involved in soil carbon (C), nitrogen (N), and phosphorus (P) cycles, which have a significant effect on the initial decomposition of plant litter ( 16 , 17 ). Many environmental factors, such as plant species, can influence soil enzyme activities ( 18 , 19 ). Therefore, soil enzyme activities and the fungal biomass are often used as indicators to reflect changes in the ecosystem due to their rapid response to environmental changes. Forest decline has contributed to changes in soil nutrients and properties. The most recent outbreak caused by mountain pine beetle ( Dendroctonus ponderosae ) has affected more than 14 million hectares of forest land and triggered forest decline in western Canada ( 20 ). Compared with undisturbed stands, beetle-killed lodgepole pine ( Pinus contorta var. latifolia Engelm.) stands have caused a decrease in soil phenolic content and increased soil moisture content and available nutrients ( 21 , 22 ). Increased soil phenolics have led to decreased colonization rates in ectomycorrhizal fungi ( 23 ). Soil phenolics belong to a class of carbon-rich plant secondary compounds and are known to affect nutrient availability, especially nitrogen ( 23 , 24 ). A previous study has demonstrated a decreased richness of ectomycorrhizal fungi in beetle-killed pine stands ( 25 ). However, there is a lack of research on the response of soil microbes to forest decline induced by forest disease. Pine wilt disease (PWD) caused by pinewood nematode (PWN) Bursaphelenchus xylophilus is one of the most serious diseases worldwide, affecting several species of pine trees ( Pinus spp.) and resulting in huge economic and environmental losses ( 26 – 28 ). PWD was first discovered on Japanese black pine ( Pinus thunbergii Parl.) in China in 1982 in Purple Mountain Park, Nanjing, China, where the vegetation type is a pure conifer forest established in the late 1970s ( 29 , 30 ). Since then, the disease has rapidly spread in China and continuously killed conifer trees. Currently, the forest in Nanjing Zijin Mountain Park is still undergoing forest succession from conifer of P. thunbergii and Pinus massoniana to deciduous trees of Liquidambar formosana (Sweetgum) and Quercus spp. (Oak) due to the occurrence of PWD. In the current study, we selected three typical forest types representing the entire forest succession process from initial conifer forest to intermediate mixed forest and eventual pure broadleaved forest. The three forests include a pure forest ( P. thunbergii ), a mixed pine and broadleaved forest ( P. thunbergia + L . formosana ), and a pure broadleaved forest ( L . formosana ). The intermediate mixed forest is defined by the equal ratio (1:1) between P. thunbergii and L . formosana trees ( 31 ). The eventual pure broadleaved forest is defined by the last pine tree being recently removed due to PWD. As PWD is the only and continuous driving force for forest decline and subsequent succession, our hypothesis is that the response of soil microbes in such a process might differ from those in which the driving forces are transient, such as fire, storm, or lightning. Therefore, the aims of the study are (i) to elucidate the changes in soil enzyme activity and fungal biomass during PWD-induced forest succession, (ii) to investigate the response of the soil fungal community structure and function, and (iii) to determine the environmental factors contributing to the dynamic changes in the fungal community during forest succession. To our best knowledge, there is no information available on the dynamic responses of soil microbes to forest succession caused by forest disease.",
"discussion": "DISCUSSION Soil fungal biomass, enzyme activity, and fungal α-diversity during forest succession. We observed significant differences in fungal biomass among the three forests. The fungal biomass is a determinant of enzyme activities in forest soil ( 32 ) and contributes to total microbial biomass ( 33 ). Increased fungal biomass could indicate faster litter composition in the soil ( 34 ), affecting fungal biomass ( 35 ). The fungal biomass in the pure L. formosana forest (PLF) was significantly higher than that in the other sites, which is in line with a previous study that suggested that the deciduous forest has a significantly higher soil fungal biomass than that of the conifer forest ( 15 ). The discrepancies in changes in aboveground plants could partly contribute to this observation. The litter input in pure L. formosana forest contains more easily available nutrients for fungi than the pure pine forest. The contents of fungal biomass increased during forest succession, which may indicate the faster decomposition rate due to the shift from conifer to broadleaved trees. The shift in aboveground plant species caused by forest succession can affect the plant residue biochemistry and the amount and stability of the soil C pool via changing the aggregate allocation of carbon ( 36 , 37 ). In this study, the enzyme activities in C, N, and S cycles increased during forest succession. The enzyme involved in the C cycle showed higher activities in the PLF forest than those in the other forests, positively correlated with soil fungal biomass. The PPF forest had a lower soil pH with a low soil organic carbon content than that of the other forests, which may explain the lower enzyme activity in the C cycle in the PPF forest. Different tree types can affect the ratio of soil fungi and bacteria by increasing the biomass of fungi over bacteria, which can alter soil enzyme activities ( 38 ). This might also explain the difference in enzyme activities among the three forests. In our study, the N -acetylglucosaminidase (NAG) and sulfatase activities were significantly higher in the PLF site. NAG is involved in the decomposition of chitin and fungal mycelium ( 39 ), and sulfatase is involved in the hydrolyzation of sulfate esters ( 40 ). Previous studies have indicated that the activities of both enzymes were correlated positively with soil microbial biomass ( 38 , 41 ). The NAG and sulfatase activities being significantly higher in the PLF may result from the increased fungal biomass, which can also explain the significantly increased fungal α-diversity and richness in the PLF site. Moreover, microbes under low P availability might be forced to release phosphatase to meet the demand of P for further growth ( 42 ), which causes the higher PHO activity in the initial pure pine forest. Soil fungal community structure at OTU and taxonomic levels during forest succession. The three forests during the succession formed distinct soil fungal communities in our study. The plant species can strongly affect the soil microbial community structure by allocating plant C and other nutrients ( 8 , 9 ). The variation in tree species in the three forest types could be the key contributor to the observation. The physiochemical properties of soil (e.g., soil pH and nutrient availability) can be altered by tree species ( 41 ), which are important regulators affecting soil microbial communities ( 10 , 11 ). Soil pH and soil C and N content also significantly differed among the three forests during the succession in our study (see Table S1 in the supplemental material). Interestingly, the fungal community structures in the mixed forest between MPF and MLF did not differ. A similar result was observed for the bacterial community in the same sites in our previous study ( 31 ). A previous study has also found that forest type strongly impacts microbial community structure at nutrient-poor sites but less at nutrient-rich sites ( 43 ). Therefore, further studies are necessary to elucidate the possible reasons. Ascomycota, Basidiomycota, and Mortierellomycota were the dominant phyla during forest succession, which is consistent with the results of previous studies where they were the main soil fungal groups ( 44 ). During forest succession, the abundance of Ascomycota increased, whereas that of Basidiomycota decreased with the accumulation of soil nutrients. Following forest vegetation restorations, similar results were obtained due to different land uses on the Loess Plateau ( 45 ). Mortierella and Penicillium were the dominant genera during forest succession, reflecting the changes in the availability of nutrients and competition between species. Penicillium can degrade cellulose in the early stages of decomposition ( 46 ). Mortierella spp. can transform phosphorus from an insoluble to a soluble form for plant uptake ( 47 ). The soil properties as explanatory variables were all correlated with the fungal community structures in the study. Previous studies have shown that SOC, soil pH, and TN are factors influencing the fungal community structure ( 48 , 49 ). Among these, soil pH was one of the essential variables, which showed a positive correlation with Ascomycota fungi ( 50 , 51 ). However, we did not detect a correlation between the abundance of Ascomycota and soil pH. The range of soil pH in our study was small, which may be attributed to fungi being less sensitive to pH changes than bacteria ( 52 ). This could be the reason why it was difficult to ascertain such a correlation. Fungal community structure of predicted function during forest succession. Functionally, the fungal trophic modes (saprotroph, symbiotroph, and pathogen) showed different trends during the succession. The abundance of saprotrophs in the mixed forest (MPF and MLF) was significantly lower than that in the pure forests (PPF and PLF). The abundance of saprophytic fungi can be linked to the plant tree species, most likely due to the difference in the biochemistry of litter input, and the mixed litter may inhibit the degradation process of saprophytic fungi ( 53 ). The abundance of symbiotrophs was higher in the mixed forests than that in the pure forests. The mixed forests in our study had higher abundance of ectomycorrhizal (ECM) fungi and SOC content than other forests, which is in line with a previous finding that soil organic matter has a positive correlation with ECM fungi ( 54 , 55 ). Pathotrophic fungi are suspected of causing diseases or negatively affecting plant performance because they derive nutrient substances by attacking host cells ( 56 ). Despite being less abundant during forest succession, the relative abundance of pathotrophs increased during succession. The weakened tree caused by pine wilt disease could increase the occurrence of needle disease and pathogens ( 57 ). A previous study indicated that the changes in pathogens could indicate a complex interaction between soil and plants, and increased vegetation, for example, has increased the heterogeneity of the litter, which can provide diverse ecological niches for pathogens ( 58 ). Conclusion. The forest succession induced by pine wood nematode disease significantly increased the fungal biomass, soil enzyme activity, and fungal diversity. The forests in different stages of succession formed a distinct fungal community and functional structures in which the fungal community shifted from Basidiomycota dominance in the initial conifer forest to a higher abundance of Ascomycota in the eventual broadleaved forest. Moreover, the symbiotrophs were the most dominant group and the abundance of pathotrophs increased during the succession. Functionally, saprotrophs, symbiotrophs, and pathotrophs dominated the fungal community in the initial forest, mixed forest, and eventual forest, respectively. The soil pH and SOC were the most important factors affecting the fungal community and functional structure, indicating the importance of environmental factors in shaping microbial community. These findings provide new insight into the responses of microbes to disease-induced forest succession and also highlight the importance of the linkage between plants and microbes in the forest ecosystem."
} | 4,395 |
37957743 | PMC10644656 | pmc | 5,422 | {
"abstract": "Background Lignocellulose, the most abundant non-edible feedstock on Earth, holds substantial potential for eco-friendly chemicals, fuels, and pharmaceuticals production. Glucose, xylose, and arabinose are primary components in lignocellulose, and their efficient conversion into high-value products is vital for economic viability. While glucose and xylose have been explored for such purpose, arabinose has been relatively overlooked. Results This study demonstrates a microbial platform for producing 1,2,4-butanetriol (BTO) from arabinose, a versatile compound with diverse applications in military, polymer, rubber and pharmaceutical industries. The screening of the key pathway enzyme, keto acids decarboxylase, facilitated the production of 276.7 mg/L of BTO from arabinose in Escherichia coli . Through protein engineering of the rate-limiting enzyme KivD, which involved reducing the size of the binding pocket to accommodate a smaller substrate, its activity improved threefold, resulting in an increase in the BTO titer to 475.1 mg/L. Additionally, modular optimization was employed to adjust the expression levels of pathway genes, further enhancing BTO production to 705.1 mg/L. Conclusion The present study showcases a promising microbial platform for sustainable BTO production from arabinose. These works widen the spectrum of potential lignocellulosic products and lays the foundation for comprehensive utilization of lignocellulosic components.",
"conclusion": "Conclusions In summary, our study involved the development of an artificial biosynthetic pathway for producing BTO from arabinose in E. coli . Through a combination of screening and protein engineering of the keto acid decarboxylase KivD, we greatly enhanced the production efficiency. Additional improvements were achieved through modular optimization of carbon flux distribution. The best-performing engineered strain produced 705.1 mg/L of BTO from arabinose in shake flask experiments. This research extends the spectrum of products that can be derived from arabinose, making a contribution to the comprehensive utilization of lignocellulosic components.",
"discussion": "Discussion Lignocellulose feedstock represents a large amount and sustainable raw materials for the production of a diverse range of chemicals. Arabinose is the third most abundant sugar in lignocellulose follows glucose and xylose, with its content in lignocellulose ranging from 1 to 18%. However, arabinose has received relatively little attention in terms of its conversion into value-added compounds. In this study, we successfully achieved microbial production of the high value molecule BTO from arabinose, which is of great significance in the pursuit of fully utilizing lignocellulosic components. To construct BTO biosynthetic pathway, we harnessed the inherent arabinose metabolic pathway within B. multivorans. This allowed us to convert arabinose into 2-keto-3-deoxy-arabonate. We then screened ketoacids decarboxylase to facilitate the production of BTO. This methodology can be readily extended to synthesize BTO from other sugars, such as fucose, rhamnose and galacturonate [ 28 ]. In this work, we identified the keto acid decarboxylase KivD as the most efficient enzyme for decarboxylation of 2-keto-3-deoxy-arabonate. To further improve KivD activity, we employed protein engineering through a rational design approach. This involved reducing the size of the binding pocket to accommodate a smaller substrate. The application of this approach led to an improvement in KivD's activity, with the engineered enzyme exhibiting nearly a threefold increase in efficiency compared to the native KivD when catalyzing 2-keto-3-deoxy-arabonate. It is worth noting that the KivD demonstrates much higher catalytic efficiency when acting on 2-keto-3-deoxy-xylonate compared to its performance with 2-keto-3-deoxy-arabonate. For example, we previously reported that an engineered E. coli strain expressing KivD can produce 1.5 g/L BTO when using xylose as the carbon source [ 6 ]. The structural difference between 2-keto-3-deoxy-xylonate and 2-keto-3-deoxy-arabonate is the configuration of the hydroxyl group at the C4 site. Therefore, we believe that analysis and mutation of the amino acids residues that interact with the C4 hydroxyl group hold promise for further improving Kivd activity towards 2-keto-3-deoxy-arabonate. In addition, it has been reported that having a sufficient supply of NADH is beneficial for BTO production when utilizing xylose as the carbon source [ 20 ]. This strategy can also be applied to increase BTO titer in the arabinose-based biosynthetic pathway."
} | 1,153 |
36404932 | PMC9674006 | pmc | 5,424 | {
"abstract": "Fungicides reduce fungal pathogen populations and are essential to food security. Understanding the impacts of fungicides on crop microbiomes is vital to minimizing unintended consequences while maintaining their use for plant protection. However, fungicide disturbance of plant microbiomes has received limited attention, and has not been examined in different agricultural management systems. We used amplicon sequencing of fungi and prokaryotes in maize and soybean microbiomes before and after foliar fungicide application in leaves and roots from plots under long-term no-till and conventional tillage management. We examined fungicide disturbance and resilience, which revealed consistent non-target effects and greater resiliency under no-till management. Fungicides lowered pathogen abundance in maize and soybean and decreased the abundance of Tremellomycetes yeasts, especially Bulleribasidiaceae, including core microbiome members. Fungicide application reduced network complexity in the soybean phyllosphere, which revealed altered co-occurrence patterns between yeast species of Bulleribasidiaceae, and Sphingomonas and Hymenobacter in fungicide treated plots. Results indicate that foliar fungicides lower pathogen and non-target fungal abundance and may impact prokaryotes indirectly. Treatment effects were confined to the phyllosphere and did not impact belowground microbial communities. Overall, these results demonstrate the resilience of no-till management to fungicide disturbance, a potential novel ecosystem service provided by no-till agriculture.",
"introduction": "Introduction Disturbances from chemical applications in agriculture reduce the abundance of pests and pathogens and are common in modern agricultural ecosystems [ 1 – 5 ]. However, applying disturbance concepts to microbial communities can be challenging to assess recovery and analyze the full impacts of crop management. A lack of data on the impacts crop management combined with fungicide disturbances on the plant microbiome hinders developing novel strategies to minimize diversity loss, understand unintended consequences of these applications, and improve crop microbiomes’ resilience. Observing fluctuations in taxa abundance and secondary effects mediated through microbial interactions following fungicide application opens the possibility for novel ecologically motivated strategies that promote microbiome stability or resilience following a fungicide application. Fungicide use has become common in conventional agricultural systems. Yet, concerns remain about direct and indirect effects on non-targeted organisms, consequences (i.e., resistance), and negative impacts on the environment or human health [ 6 – 8 ]. The rapid evolution of fungicide resistance in plant and human pathogenic fungal populations can cause devastating epidemics in agricultural ecosystems, with spill-over effects to public health [ 9 – 12 ]. For example, there is substantial concern about the overuse of azole fungicides that have been linked to the resistance of Aspergillus fumigatus to antifungals in human infections [ 11 , 12 ]. Despite concerns, foliar fungicide applications in maize ( Zea mays L.) and soybean ( Glycine max L. Merr) are often made without pathogen pressure due to perceived or marketed yield benefits [ 13 , 14 ]. A meta-analysis of soybeans demonstrated that foliar fungicide application in the absence of disease increased yield by 2.7%, but applications are less profitable without disease pressure [ 14 ]. While fungicides are necessary for crop protection, minimizing non-target effects and unintended consequences is critical in evaluating the sustainability of agricultural production systems. Studies reporting fungicidal and pesticidal impacts on microbiomes [ 15 , 16 ] have focused on soil and aquatic systems [ 8 ] rather than effects on foliage microbes. The two most popular fungicide classes used in agricultural field crops are the sterol demethylation inhibitors (DMIs), otherwise known as triazoles, and quinone outside inhibitors (QoI), or strobilurins. Foliar fungicides for maize and soybean are primarily applied as single or premixed QoI and DMI active ingredients [ 17 ]. QoI fungicides inhibit fungal respiration by blocking the quinol oxidation site in the cytochrome bc 1 complex in the electron transport chain. DMI fungicides inhibit CYP51 (encoding 14α-demethylase), an important enzyme in the ergosterol biosynthesis pathway of fungi [ 18 ]. Both fungicide classes are highly active against many plant pathogens. From the few studies focused on the plant phyllosphere, a consistent non-target effect is detected against phyllosphere yeasts. One study on grapevine microbiomes reported minimal and transient impacts to the phyllosphere microbiome, including phyllosphere yeast abundance [ 19 ]. Similarly, repeated application of broad-spectrum fungicides has been shown through culture-based and culture-independent methods to decrease phyllosphere yeast richness [ 20 – 23 ]. Yeasts that inhabit the phyllosphere are well suited to oligotrophic and dynamic environmental conditions present on leaf surfaces and consequently have been applied for biocontrol of plant pathogens [ 24 ]. They are known to produce extracellular polysaccharides and surfactants, which may be necessary for creating or maintaining biofilms [ 25 ]. In addition, some phyllosphere yeasts, including species of basidiomycete yeasts in Cryptococcus and Sporidiobolus , produce carotenoid compounds, which have antioxidant properties and may protect the yeasts and other resident microbes from stress in the phyllosphere [ 26 ]. Phyllosphere yeast communities have also been linked to pollinator insects by altering floral nectary chemistry, and fungicides can modify this relationship [ 27 , 28 ]. However, few studies have addressed the links between phyllosphere yeasts and other phyllosphere residing microorganisms. One study, which did analyze the links between phyllosphere yeasts and bacteria, found evidence that phyllosphere yeasts have direct interactions with bacterial members of the microbiome [ 29 ]. While indirect and collective effects of removing single species or groups of species from ecosystems have been proposed in ecological theory since the 1940s and studied in various macro-organism contexts such as conservation biology, disturbance ecology, and food web ecology, such effects are comparatively understudied in microbiome science [ 30 – 32 ]. In microbiomes, network complexity (i.e., linkage density) has been correlated to ecosystem functioning and stability [ 33 , 34 ]. Consequently, co-occurrence patterns may reveal indirect effects, which may not be seen using other analyses. Since the US Dust Bowl of the 1930s, soil conservation efforts have led to the steady adoption of minimum or no-till agriculture management systems [ 35 ]. Cropping management systems have been demonstrated to impact phyllosphere microbiomes [ 36 , 37 ]. Crop management’s effect on the resilience of foliar fungal communities following fungicides has not been explored, but differing impacts of fungicides in different agricultural managements are probable. In one study performed on soil, agricultural management altered the response of microbial communities to the application of the DMI fungicide tetraconazole [ 38 ]. Similarly, a study on wheat demonstrated that crop rotation and wheat variety impacted response to foliar fungicides of various active ingredients, however the crop rotation systems differed between locations, confounding efforts to distinguish fungicide responses in specific rotations from those of location and variety [ 39 ]. Long-term experiments circumvent these confounding effects by applying all treatments at a single location. Here, we characterize effects of foliar fungicides on the maize and soybean leaf and root microbiomes in no-till and conventional plots of the Long-Term Ecological Research (LTER) Main Cropping Systems Experiment at the Kellogg Biological Station (KBS). Our research objectives were three-fold: (1) to determine whether fungicides alter microbial diversity across plant compartments (e.g., leaves or roots), crop species (e.g., maize or soybean), or tillage management (conventional vs. no-till); (2) to identify non-target and indirect effects of fungicide applications, and (3) determine if crop management alters the resiliency of the microbiome. We hypothesized that fungicides would alter both maize and soybean microbial (fungal and prokaryotic) diversity and network complexity. We predicted that this effect would be most pronounced in the leaves. In addition, given that plant microbiomes have been shown to differ under the two tillage management systems [ 37 ], we hypothesize that the response and recovery of plant microbiomes following fungicides would also differ. This LTER site allows for a novel approach by eliminating any differences caused by location bias and assessing the effect of fungicide application under long-term agricultural management. We apply a novel microbiome network analysis approach to determine the impact fungicides have on prokaryote-fungal co-occurrences in the plant microbiome. Finally, we used random forest models to predict prokaryote taxa responsive to altered fungal diversity demonstrating the possible indirect effects of fungicides.",
"discussion": "Discussion To our knowledge, this is the first study to assess the effect of fungicide-imposed disturbance and resiliency under different agricultural management systems. We found that fungicide applications had a substantial effect on target and non-target fungal phyllosphere communities, minor indirect effect on prokaryotic communities in the phyllosphere, and no direct effects on fungal or prokaryotic communities of roots. Soil fungi and prokaryotes were also identified in soybeans, where there was no evidence of fungicidal effects (data not shown). Leveraging the KBS LTER site allowed the direct comparison of long-term crop management impacts to the microbiome without confounding location. Our data demonstrate that the resilience of phyllosphere microbiome depends on the cropping management system, with a greater recovery in the abundance of affected phyllosphere microbiota in long-term no-till compared to annually conventional tilled management. Among the most important results was the commonality in the fungal taxa affected by fungicide treatments. In maize and soybean, fungi in Dothidiomycetes (target) and Tremellomycetes (non-target) decreased in abundance following fungicide applications, raising questions on the role of Tremellomycete yeasts; specifically, the Bulleribasidiaceae in phyllosphere microbiomes, and the effects of fungicide use in the absence of disease pressure. This study observed reductions and local extinctions of yeasts following fungicide application, which may lead to unintended consequences for the host plant. Phyllosphere yeast communities have received less attention in the literature than prokaryote communities [ 52 ]. The three Bulleribasidiaceae genera observed in this study were Hannaella , Dioszengia , and Vishniacozyma . Dioszengia , and Hannaella have been demonstrated to produce the plant growth-promoting hormone indole acetic acid (IAA), similar to many plant growth-promoting phyllosphere prokaryotes [ 53 , 54 ]. In comparison, Vishniacozyma yeasts have remained understudied but have been isolated from maize kernels [ 55 ]. In addition, Dioszegia has been identified as a hub taxon important in maintaining fungal-prokaryote interactions by altering prokaryote diversity in the phyllosphere microbiome of Arabidopsis [ 29 , 53 ]. As observed in this study, in the absence of disease pressure, fungicide applications may affect populations of beneficial microbes. However, adverse impacts would be expected to be outweighed if the fungicide mitigates the disease, which will be tested in future experiments. Here, we show for the first time that fungicidal impacts on crop microbiomes are dependent on management, addressing a knowledge gap that previous studies were unable to address specifically [ 20 , 21 , 39 ]. A higher proportion of fOTUs altered by fungicide application in the no-till management system showed improved resilience within the study period, which may be explained by the differences in microbial communities present in the phyllosphere of each management before fungicide applications, as has been demonstrated previously at the KBS LTER site [ 36 , 37 ]. A previous study from the KBS LTER site demonstrated that aerially dispersed yeasts are enriched in the phyllosphere, but also found in lower abundance in belowground plant organs [ 42 ]. Crop residue from previous seasons can harbor fungi that may act as a source to repopulate the phyllosphere following a disturbance like the phenomenon of pathogens transferring from residues [ 56 ]. Yeasts that inhabit the phyllosphere are primarily known to disperse through ballistosporic aerial dispersal, and the reassembly of leaves following fungicides may rely heavily on this spore dispersal mechanism. However, not all yeast taxa in the Bulleribasidiaceae have been observed to form ballistocondia in culture [ 57 ], leaving arguably less efficient means of dispersal from insects or through wind and rain [ 58 , 59 ]. Locally extinct taxa were not part of the core microbiome regardless of tillage management system or spore dispersal mechanism, demonstrating a tight relationship between abundance-occupancy and disturbance. These results indicate that microbiome resilience is improved in no-till crop management, which informs discussion of managing crops for resilience, and demonstrates a potential ecosystem service provided by no-till agriculture in addition to improved nutrient cycling or preservation of habitats for microorganisms and mesofauna [ 60 ]. Fungicide applications affected soybean and maize phyllosphere communities differently. These differences may be due to crop, planting year, or fungicide regime. The effect of fungicide was likely reduced in the final sampling of maize due to sampling of new leaves that were not directly sprayed with fungicides, indicating that any effect would have been through systemic activity of the fungicide 34 days after. This is unlikely since pyraclostrobin is not easily xylem mobile and mainly works as a translaminar local penetrant [ 61 ]. Another critical difference is that the Delaro ® fungicide applied to soybeans in 2018 has two modes of action. Application of fungicides having two different modes of action has been shown to have a more significant effect on fungal community composition than a single mode of action in cereal crops [ 21 ]. Although the impact of fungicides varied in magnitude between the two crops, the commonality of off-target impacted taxa between crops and fungicides demonstrates that multiple fungicide products on different crops consistently reduce these taxa. This information can be used to inform decisions on the use of fungicides under low pathogen pressure across crops and cropping systems. Recovery of network complexity is one measure of microbiome resilience. We show that network complexity decreased significantly in the soybean phyllosphere following fungicide treatment. Despite similar affected taxa, the effect of fungicides on maize was moderate compared to soybean, which saw a reduction in network complexity and local extinctions of some taxa. Therefore, we focused more on fungicidal effects to soybean rather than maize. Other studies have demonstrated that agricultural management alters network complexity. However, the functional consequences of these changes were not directly assessed [ 62 , 63 ]. In soils, it has been demonstrated that increases in network complexity are positively correlated with various ecosystem functions and increases in the number of unique functions and functional redundancy [ 34 ]. The functional consequences of decreases in network complexity remain unexplored in the phyllosphere microbiome. They may provide the rationale for chemical application decisions or novel microbial-based treatments to replace lost taxa. Notably, fungicide application altered co-occurrences between phyllosphere fungi and prokaryotes, demonstrating the indirect effects of fungicide applications through the loss in the diversity of Bulleribasidiaceae. In support of random forest results, many of the same prokaryotes identified from networks as having changes in cumulative mean edge weight were identified by random forest as predicting Bulleribasidiaceae richness. Disturbance can change cooperation/competition dynamics, and a high level of disturbance can reduce cooperation [ 64 , 65 ]. In our study, the cumulative mean edge weight between most phyllosphere prokaryotes and Bulleribasidiaceae became more positive, indicating fewer negative associations between particular bacteria and the Bulleribasidiaceae. However, there were exceptions where cumulative edge weights, positive before spray, became neutral following fungicide application likely due to the disappearance of some fungal taxa from samples, and therefore the disappearance of any associations. Loss of negative correlations may also be due to reduced competition between phyllosphere prokaryotes and Bulleribasidiaceae as more niche space is available to phyllosphere prokaryotes following fungicide application. Shifts in correlations between Bulleribasidiaceae and phyllosphere prokaryotes are of interest due to the unique physiology of many phyllosphere prokaryotes as it relates to plant health. Methylobacterium spp. have been demonstrated to be abundant in plants’ phyllosphere and have the genes to produce plant growth-promoting auxins and UVA-absorbing compounds [ 66 , 67 ]. Hymenobacter sp., Methylobacterium sp., and Sphingomonas sp. are core phyllosphere members in switchgrass [ 68 ] and are highly abundant in the Arabidopsis phyllosphere [ 69 ]. A comprehensive view of the phyllosphere organisms is needed to understand microbiome functioning and plant health. This research demonstrates that foliar fungicide treatments alter phyllosphere microbiomes in maize and soybean, and non-target Bulleribasidiaceae yeasts were negatively impacted in both crops. Microbiome complexity was altered partially by decreasing co-occurrence between Bulleribasidiaceae yeasts and dominant phyllosphere prokaryote taxa, demonstrating indirect effects of fungicide applications mediated through the presence of these yeasts. Further, these data support our hypothesis that the recovery of the phyllosphere microbiome differed by tilling management. Together, these results improve our understanding of fungicide impacts on crop microbiomes and their recovery in different managements and inform their rational use to maintain efficacy and intended impacts across different cropping systems."
} | 4,740 |
34924911 | null | s2 | 5,425 | {
"abstract": "Progress in the field of soft devices-i.e., haptics, robotics, and human-machine interfaces (HRHMIs)-has its basis in the science of polymeric materials and chemical synthesis. However, in examining the relevant literature, we find that most developments have been enabled by off-the-shelf materials used either alone or as components of physical blends and composites. In this Progress Report, we take the position that a greater awareness of the capabilities of synthetic chemistry will accelerate the capabilities of HRHMIs. Conversely, an awareness of the applications sought by engineers working in this area may spark the development of new molecular designs and synthetic methodologies by chemists. We highlight several applications of active, stimuli-responsive polymers, which have demonstrated or shown potential use in HRHMIs. These materials share the fact that they are products of state-of-the-art synthetic techniques. The Progress Report is thus organized by the chemistry by which the materials were synthesized, including controlled radical polymerization, metal-mediated cross-coupling polymerization, ring-opening polymerization, various strategies for crosslinking, and hybrid approaches. These methods can afford polymers with multiple properties (i.e. conductivity, stimuli-responsiveness, self-healing and degradable abilities, biocompatibility, adhesiveness, and mechanical robustness) that are of great interest to scientists and engineers concerned with soft devices for human interaction."
} | 379 |
30302054 | PMC6158934 | pmc | 5,426 | {
"abstract": "An increase in the number of publications in recent years indicates that besides ammonia-oxidizing bacteria (AOB), ammonia-oxidizing archaea (AOA) may play an important role in nitrogen removal from wastewater, gaining wide attention in the wastewater engineering field. This paper reviews the current knowledge on AOA and AOB involved in wastewater treatment systems and summarises the environmental factors affecting AOA and AOB. Current findings reveal that AOA have stronger environmental adaptability compared with AOB under extreme environmental conditions (such as low temperature and low oxygen level). However, there is still little information on the cooperation and competition relationship between AOA and AOB, and other microbes related to nitrogen removal, which needs further exploration. Furthermore, future studies are proposed to develop novel nitrogen removal processes dominated by AOA by parameter optimization.",
"conclusion": "6. Conclusions The discovery of AOA breaks the traditional view for the past 100 years that ammonia oxidation is only conducted by AOB, improving the knowledge of the global nitrogen cycle. AOA also appear to play an important role in nitrogen removal from wastewater. Hence, the nitrogen cycle in a wastewater treatment system needs reevaluation. The collaborative, competitive, and inhibitive relationships in microbial communities need further exploration in actual wastewater nitrogen removal systems. The ammonia-oxidizing microorganisms are affected by various environmental conditions, and AOA have stronger environmental adaptability than AOB, which provides the possibility for the development of novel nitrogen removal processes with ammonia oxidation dominated by AOA under extreme environmental conditions (such as low temperature and low oxygen level).",
"introduction": "1. Introduction Nitrogen-containing pollutants are considered one of the most common environmental pollutants in various types of wastewater, and they are an important pollution factor that causes eutrophication. The conventional biological system for nitrogen removal from wastewater is usually through the biological oxidation of ammonia and organic nitrogen (nitrification) and the biological reduction of the oxidation products, that is, nitrate (denitrification). From the viewpoint of microbial transformation of nitrogen, the nitrification process includes ammonia oxidation (NH 3 -N → NO 2 − -N) and nitrite oxidation (NO 2 − -N → NO 3 − -N). As the rate-limiting step of the nitrification, ammonia oxidation is the key process for biological nitrogen removal from wastewater, thus attracting wide attention from researchers. In the past 100 years, ammonia-oxidizing bacteria (AOB) were considered as the dominant microorganism in the ammonia oxidation process [ 1 ]. With the development of molecular biology techniques in recent years, it had been found that the amoA gene, a kind of indicative gene of ammonia oxidation, exists in large numbers of archaea distributed in the marine environment, proving that archaea also have the capacity of ammonia oxidation at the physiological metabolic level [ 2 ]. Hereafter, ammonia oxidations conducted by archaea were widely found in hot springs, soils, oceans, sediments, and wetlands and these archaea were formally known as ammonia-oxidizing archaea (AOA) in subsequent studies [ 3 – 5 ]. In addition, a large number of studies have reported that the AOA abundance and the archaeal amoA gene abundance are significantly higher than that of AOB in farmland soils, river sediments, and oceans [ 6 ], indicating that AOA are the main driver of ammonia oxidation in these habitats and play a more important role in the global nitrogen cycle."
} | 923 |
30619411 | PMC6297361 | pmc | 5,428 | {
"abstract": "Nitrogen (N) deposition and precipitation could profoundly influence the structure and function of forest ecosystems. However, conventional studies with understory additions of nitrogen and water largely ignored canopy-associated ecological processes and may have not accurately reflected the natural situations. Additionally, most studies only made sampling at one time point, overlooked temporal dynamics of ecosystem response to environmental changes. Here we carried out a field trial in a mixed deciduous forest of China with canopy addition of N and water for 4 years to investigate the effects of increased N deposition and precipitation on the diversity and community composition of arbuscular mycorrhizal (AM) fungi, the ubiquitous symbiotic fungi for the majority of terrestrial plants. We found that (1) in the 1st year, N addition, water addition and their interactions all exhibited significant influences on AM fungal community composition; (2) in the 2nd year, only water addition significantly reduced AM fungal alpha-diversity (richness and Shannon index); (3) in the next 2 years, both N addition and water addition showed no significant effect on AM fungal community composition or alpha-diversity, with an exception that water addition significantly changed AM fungal community composition in the 4th year; (4) the increment of N or water tended to decrease the abundance and richness of the dominant genus Glomus and favored other AM fungi. (5) soil pH was marginally positively related with AM fungal community composition dissimilarity, soil NH 4 + -N and N/P showed significant/marginal positive correlation with AM fungal alpha-diversity. We concluded that the effect of increased N deposition and precipitation on AM fungal community composition was time-dependent, mediated by soil factors, and possibly related to the sensitivity and resilience of forest ecosystem to environmental changes.",
"conclusion": "Conclusion Increased N deposition and precipitation have significant interactive effect on AM fungal diversity and community composition, while precipitation increment have stronger effect on AM fungal community structure than increased N deposition in the forest ecosystem. The effect of N deposition and precipitation on AM fungal community composition was time-dependent, mediated by soil factors, and possibly related to the sensitivity and resilience of forest ecosystem to global changes. In the future, we will consider finer and broader time scales and take into account the plant data to achieve comprehensive understanding of AM fungal ecology in the forest ecosystem.",
"introduction": "Introduction Arbuscular mycorrhizal (AM) fungi can form mutualistic symbioses with the majority of terrestrial plants ( Smith and Read , 2008 ) and provide vital ecological services such as improving plant mineral nutrition ( Li et al., 2006 ; Subramanian et al., 2006 ), enhancing plant tolerance to biotic ( Elsen et al., 2008 ; Affokpon et al., 2011 ) and abiotic stresses (e.g., flooding, high temperature) ( Fougnies et al., 2007 ; Li et al., 2009 ; Zhu et al., 2011 ; Camprubi et al., 2012 ), altering the composition and diversity of plant communities and influencing the productivity, structure and stability of ecosystems ( van Der Heijden et al., 1998 , 2008 ; Jansa et al., 2008 ), and intensifying the resilience of ecosystem to global climate change ( Martínez-García et al., 2017 ). In view of their ecological significance, investigation on AM fungal diversity and community assemblage has become hot topics in soil ecology in recent years. AM fungal community assembly could be predicted by both niche theory which assumes that the competition among species for limited resources and the differentiation of niche space across species allow species coexistence, emphasizing the importance of determined processes in structuring community assembly ( Leibold and McPeek, 2006 ), and neutral theory which presumes that all species are ecologically equivalent, emphasizing the significance of stochastic processes and dispersal limitation depending on spatial scales ( Hubbell, 2001 ). At global and regional scales, neutral theory weighs more than the ecological niche theory, and AM fungal distribution pattern is mainly shaped by geographical distance and climate factors. However, the ecological niche theory dominates at local scale and small scale, and the effects of host plants and the soil properties on AM fungal community become more important than geographical distance restriction ( Chen et al., 2018 ). In recent decades, global climate change driven by anthropogenic disturbance has been intensified and impacted the structure and function of multiple aquatic and terrestrial ecosystems ( Marino et al., 2017 ). As an important component of global climate change, nitrogen (N) deposition and its ecological consequences have attracted serious concerns. At global scale, it is estimated that the N deposition rate has increased nearly 34 Tg N yr -1 in 1860–100 Tg N yr -1 in 1995 and may increase up to 200 Tg N yr -1 in 2050 ( Galloway et al., 2004 ). Increased N deposition could cause negative effects on terrestrial ecosystems, such as biodiversity loss, soil acidification, productivity decline, nutrient imbalance and forest degradation ( Vitousek et al., 1997 ; Magill et al., 2004 ; Hogberg et al., 2006 ; Bobbink et al., 2010 ; Lu et al., 2014 ). Most previous studies on N deposition are carried out in Europe and North America, while studies on N deposition and its ecological consequences in China are rather limited. As a fact, with the rapid development, China is also experiencing increasing N deposition, especially in its central and southeastern areas ( Jia et al., 2014 ). The mean wet N deposition over China has increased nearly 25% from 1990s to 2000s ( Jia et al., 2014 ), and the N deposition rate in China is predicted to continually increase in the coming decades ( Liu et al., 2013 ). Besides increased N deposition, changes in precipitation patterns is also an important component of global change. According to IPCC report, heavy precipitation events including the frequency and intensity of heavy precipitation over land regions increased markedly in recent years. In many mid-latitude regions, mean precipitation will gradually increase in the 21st century ( Integrated Professional Competency Course [IPCC], 2013 ). Increased precipitation could change species richness and alter the plant community structure and aboveground net primary productivity (ANPP) in arid and semi-arid (water-limited) steppe ecosystems ( Yang et al., 2011 ; Zeppel et al., 2014 ; Ren et al., 2015 ). Intensified precipitation can also elevate the risk of soil nutrient leaching (e.g., N, P) ( Martínez-García et al., 2017 ). Moreover, under natural conditions, multiple global changes may occur simultaneously and interact with each other ( Harpole et al., 2007 ). The impacts of N deposition on the ecosystem structure and function would be substantially altered by precipitation ( Harpole et al., 2007 ; Yang et al., 2011 ; Araya et al., 2013 ). Previous studies showed that precipitation increment could alleviate the negative effects of increased N deposition by increasing the mobility and leaching of soil inorganic N ( Li et al., 2016 ; Sun et al., 2017 ). More extensive studies on the interactive effects of N deposition and precipitation on ecosystems are still expected. Up to date, very limited information is available as for the responses of belowground ecosystem especially for soil microbial communities, to climate changes ( Li et al., 2016 ). Definitely more attention should be paid to the soil microorganisms which play important roles in nutrient cycling, organic matter decomposition, primary production, regulation of greenhouse emissions and other ecosystem functions ( Philippot et al., 2013 ; Wagg et al., 2014 ; Delgado-Baquerizo et al., 2017 ). As an important functional group of soil microbes, AM fungi directly bridge up plant and soil, and are selected as model organism for studying belowground-aboveground interactions. It has been well documented that increased N deposition decreased the abundance ( van Diepen et al., 2007 , 2010 ; Camenzind et al., 2014 , 2016 ), richness ( Camenzind et al., 2014 ; Liu et al., 2014 ; Chen et al., 2017 ) and diversity ( Chen et al., 2017 ), and altered the community composition ( van Diepen et al., 2011 ; Chen et al., 2014 ; Zheng et al., 2014 ; Kim et al., 2015 ) of AM fungi. Precipitation increment can also decrease the abundance and alpha-diversity ( Chen et al., 2017 ), and alter community composition ( Gao et al., 2016 ; Chen et al., 2017 ) of AM fungi in semiarid (water-limited) steppe ecosystem. However, as far as we know, there were only limited reports on the interaction of N deposition and precipitation on AM fungal communities, and they all were carried out in water-limited steppe ecosystems ( Li et al., 2015 ; Chen et al., 2017 ). The interaction could be different in humid forest ecosystem from arid/semi-arid steppe ecosystems. In addition, most previous studies on the ecological impacts of precipitation increment or N deposition on forest ecosystems largely ignored many canopy-associated ecological processes by understory addition of N or water. The canopy-associated processes may include N uptake by leaves, epiphytes and microbes; immobilization in decaying leaves or other dead organic matters; volatilization as water evaporates; and transformation of inorganic N to organic N ( Zhang et al., 2015 ). Undoubtedly, canopy processes are more important in forest than in grassland and should not be neglected. As seen in report, the percentage of retained N from N deposition by forest canopy could vary in different studies from 1∼5% to 10∼25%, depending on forest type and N deposition intensity ( Zhang et al., 2015 ). Furthermore, AM fungal community structure exhibits seasonal dynamics and interannual variability ( Husband et al., 2002 ; Hazard et al., 2014 ). Husband et al. (2002) investigated the diversity and distribution of AM fungi colonizing tree seedling roots for 2 years in the tropical forest on Barro Colorado Island, Republic of Panama. They found that dominant AM fungal types in the first year were nearly entirely replaced by previously rare types in the following year; Hazard et al. (2014) investigated the effects of biosolids on AM fungal communities in grassland and arable agroecosystems and found that the effect of seasonality exceeded that of biosolids application. The AM fungal community compositions (using T-RFLP method) associated with Lolium perenne shifted with seasonality and year, some dominant AM fungi (e.g., T-RFs associated with Rhizophagus irregularis ) were present in roots throughout and between years, others were only present seasonally (e.g., HinfI -HEX 422), and rarer species fluctuated in presence and frequency. However, many studies only made one sampling and overlooked the temporal dynamics of AM fungal community in response to environmental changes. As a result, we conducted a field trial in a mixed forest in China’s climate transition zone from subtropical to warm temperate climate to investigate the impacts of N deposition and precipitation increment on AM fungal community with canopy N and water addition. We carried out field investigation and collected soil samples every year since the experiment establishment in 2013, and analyzed AM fungal diversity and community structure by using the high throughput sequencing technology. We hypothesized that (1) canopy N or water addition would significantly decrease AM fungal richness, Shannon diversity index and change community composition; (2) N and water addition interactively shape AM fungal community; (3) the effects of N and water addition on AM fungal community would be time-dependent. To the best of our knowledge, this study for the first time investigated the interactive effects of increased N deposition and precipitation on AM fungal diversity and community composition in a forest ecosystem and is expected to allow better understanding of the impacts of climate changes on the forest ecosystems.",
"discussion": "Discussion This study investigated the effects of canopy additions of N and water on AM fungal diversity and community composition for consecutive 4 years and the results indicated that canopy N addition significantly changed AM fungal community composition, however, this effect was time-dependent, only occurred in the 1st year. While, the effect of water addition overwhelmed that of N addition, which not only changed the community composition, but also decreased the alpha-diversity of AM fungi, and these consequences were also time-dependent and only occurred in the earlier stages (1st/2nd year). In addition, the increment of N or water tended to decrease the abundance and richness of the most dominant genus Glomus and favored other AM fungi. The effects of N/water addition on AM fungal community composition were potentially mediated by soil properties, such as pH, NH 4 + -N and N/P. Effects of Canopy N and Water Addition on Soil Properties Nitrogen deposition usually leads to soil acidification ( Lu et al., 2014 ; Tian and Niu, 2015 ; Chen et al., 2017 ), our study was not an exception (N addition significantly decreased soil pH in the 1st year), although we differently practiced canopy N addition. Possible reasons for soil acidification resulting from N deposition include: (1) NH 4 + ions are absorbed by plant roots, while H + will be released into soil, causing soil acidification ( Smith and Read, 2008 ); (2) NH 4 + ions are converted into nitrites and further converted into nitrates, producing H + leading to soil acidification ( Azevedo et al., 2013 ); (3) NH 4 + ions displacing base cations (Ca 2+ , Mg 2+ , K + , Na + ) and the increasing loss of metal cations could reduce soil buffering capacity against acidification ( Tian and Niu, 2015 ; Lucas et al., 2016 ). Following soil acidification, soil microbial community composition and activity could be changed ( Wei et al., 2013 ). Soil acidification can also result in the loss of plant species across multiple ecosystems ( Azevedo et al., 2013 ) and the suppression of plant growth and carbon (C) sequestration ( Schulte-Uebbing and de Vries, 2018 ). In the 2nd year, water addition significantly decreased soil NH 4 + -N and AN, which may attributed to significant leaching ( Martínez-García et al., 2017 ) and runoff. The loss of N can cause negative impacts to the environment and human, such as eutrophication of water body and decline of crop productivity, which will likely be aggravated by intensive heavy precipitation events ( Martínez-García et al., 2017 ). On the other hand, N addition significantly increased soil NH 4 + -N, consistent with many previous studies ( Chen et al., 2014 , 2017 ; Zhang et al., 2014 ). The increase of soil NH 4 + -N can increase the productivity of N-limited ecosystems such as grassland and forest in temperate zone ( Aber et al., 1998 ; Bai et al., 2010 ); However, excessive N supply can also lead to the accumulation of reactive nitrogen in soil to a toxic level for plant ( Wei et al., 2013 ) and other soil organisms, such as nematodes and fungi ( Eno et al., 1955 ). In the study of Wei et al. (2013) , NH 4 + concentration showed negative relationships with plant composition; in Eno et al. (1955) , the fungi and nematode numbers were decreased under all N addition levels. Compared to control, only 0.6% of the nematodes and 4.9% of the fungi survived under N addition level of 608 mg kg -1 . Effects of Canopy N and Water Addition on AM Fungal Alpha-Diversity In our study, N addition did not significantly decrease AM fungal richness and Shannon index, which failed to support our first hypothesis, also inconsistent with previous studies in forest ( Camenzind et al., 2014 ), agriculture ( Liu et al., 2014 ) and alpine meadow ecosystems ( Zheng et al., 2014 ). In the study of Camenzind et al. (2014) and Liu et al. (2014) , N addition significantly decreased AM fungal richness, while in the study of Zheng et al. (2014) , N addition had significant positive effect on AM fungal alpha-diversity. How AM fungi respond to N addition is probably influenced by local environmental conditions, plant communities, intensity and frequency of N addition, experimental duration and other unknown factors ( Porras-Alfaro et al., 2007 ; Wang et al., 2018 ). In this study, the ecosystem type is forest, which has higher species diversity and stability (strong resistance) than meadow, and agriculture ecosystems. More importantly, the mode of N application in our study was canopy spraying, different from Camenzind et al. (2014) , in which N was directly added to the soil. As known, many canopy processes could substantially affect the consequences of N addition, however, the extent of the impact has not yet been clarified. In addition, although the total amount of N applied in Camenzind et al. (2014) was the same as this study, but the frequency of N application was different (7 times a year in this study, versus twice a year in Camenzind’s). Low frequency with high rate could very likely over-estimate the effect of N deposition, as Zhang et al. (2014) confirmed the overestimation of plant species loss of N addition at high rates and low frequency in a temperate steppe. In the present study, water addition significantly decreased AM fungal richness and Shannon diversity index in the 2nd year, in support of our first hypothesis, also consistent with Gao et al. (2016) and Chen et al. (2017) in steppe ecosystem. By Pearson correlation analysis, we found that NH 4 + -N and N/P were marginally positively correlated with AM fungal richness and significantly positively correlated with AM fungal Shannon diversity index. Meanwhile, NH 4 + -N and N/P were indeed significantly decreased after water addition, possibly due to run-off and leaching of N from soil ( Martínez-García et al., 2017 ). The decrease of NH 4 + -N may have intensified the competition among species leading to the loss of AM fungal niche, while lost niche could finally lead to decrease of AM fungal diversity ( Dickie, 2007 ; Gao and Guo, 2013 ). Moreover, water addition could affect soil nutrient balance including N/P ratio, which can largely affect AM fungal community composition ( Verbruggen et al., 2015 ). Effects of Canopy N and Water Addition on AM Fungal Composition In the 1st year, N addition significantly changed AM fungal community composition, in support of our first hypothesis, and consistent with van Diepen et al. (2011) and Camenzind et al. (2014) , although the mode of N addition were different. The underlying mechanisms for the N effects on AM fungal community composition could be: (1) N addition increased the availability of soil N and reduced the cost in uptake of N by plant, so the plant dependence on mycorrhizal fungi decreased, and the amount of C allocated to mycorrhiza also decreased, which finally strengthened the competition among AM fungal species, led to changes in AM fungal community composition ( Huang et al., 2014 ). (2) N addition led to soil acidification, which can directly affect spore germination and mycelial development ( Rousk et al., 2010 ). More importantly, different AM fungi prefer different optimum pH, so changes in soil pH may lead to changes in community composition of AM fungi ( An et al., 2008 ). Soil acidification caused by N addition may have stronger direct influence on soil microbial community composition than indirectly through the changes in plant community ( Wei et al., 2013 ). At the same time, AM fungal community composition was also significantly altered by water addition, supported our first hypothesis, and in agreement with Gao et al. (2016) and Chen et al. (2017) although their studies were carried out in water-limited ecosystems. Precipitation increment may directly change soil water status and affect the physiological activity of AM fungi. Furthermore, increased precipitation can indirectly affect AM fungi via influencing the soil characteristics and plant communities. For example, in the study of Chen et al. (2017) , changes in soil pH and plant species richness could shift AM fungal community composition. Gao et al. (2016) found that increased precipitation could alter fungal community composition through influencing soil moisture, NO 3 - -N and root turnover. The significant interactions between N and water addition on AM fungal community composition confirmed our second hypothesis, but inconsistent with Li et al. (2015) who observed no significant interactive effect of N and water increment in a semiarid grassland ecosystem after 8 years of experimental treatment. Chen et al. (2017) found that although there was no significant interactive effect of N and precipitation increment on AM fungal diversity, but significant interactive effect was observed on the relative abundance of some AM fungal OTUs. One possible explanation was experimental duration, as in our study the interaction was only observed after 1 year of treatment. Moreover, we also confirmed that the effect of N and water addition on AM fungal community was time-dependent, in support of our third hypothesis. The results of Yang et al. (2016) demonstrated that under field conditions, AM fungal richness increased and community composition shifted after 15 days waterlogging. However, the time resolution in our study is year-based, therefore, more sampling at finer time scales is expected to test how quickly AM fungi respond to environmental changes. In addition, in a Mediterranean grassland, increased precipitation during rainy seasons significantly altered plant community and soil fungal community structure ( Suttle et al., 2007 ; Hawkes et al., 2011 ), but in the dry season, fungal community did not respond to water addition in a different Mediterranean grassland ( Barnard et al., 2013 ). Koyama et al. (2018) suggested that besides water amounts, timing of water manipulations can also be an important influencing factor, however, the present study did not involve the timing of water addition, which could be addressed in future research. In the meta-analysis by Wang et al. (2018) , they found that N addition didn’t change fungal richness significantly when the experimental duration was within 5 years or longer than 10 years, but had significant influence when the treatment duration was 5 ∼10 years. This study only lasted for 4 years, next we will continue to sample and study the long-term ecological effects of increased N deposition and precipitation. Changes in the composition and structure of plant community may affect the amount and quality of C input to belowground thus affecting soil microbial biomass, activity, and community structure ( Meier and Bowman, 2008 ; Treseder, 2008 ; Liu et al., 2016 ). For instance, in the meta-analysis of Liu et al. (2016) , plant lignin, plant protein and soil lignin were significantly increased by 7.13, 25.94, 7.30%, respectively following N addition. On the one hand, the increase of litter quality could promote microbial growth and biomass accumulation; on the other hand, the increase of recalcitrant C compounds (e.g., lignin) could result in the decrease of C availability to soil microbes, inhibiting microbial growth and activity ( Treseder, 2008 ). Moreover, community composition of some specific microbial groups can change under N additions, for example, the diversity of ectomycorrhizal fungi and the richness of fungal decomposers decreased after N fertilization or deposition ( Treseder, 2008 ). It should be further noted that, as symbiotic fungi, AM fungi have host preference ( Sanders, 2003 ; Croll et al., 2008 ), and their community composition and structure are closely linked to plant community characteristics (Öpik et al., 2010; Kivlin et al., 2011 ; Xu et al., 2016 ). At the regional scale, a significant relationship between AM fungal community composition and plant was observed by Xu et al. (2016) . The results of Li et al. (2015) indicated that the AM fungal abundance and OTU richness were significantly correlated with the 7-year averaged ANPP and aboveground biomass of plant functional groups after 8-years N and water additions. In the study of Chen et al. (2017) , significant correlation between plant species richness and AM fungal taxonomic composition was also recorded. Therefore, further research incorporating plant community data is still needed."
} | 6,159 |
33035481 | PMC7758711 | pmc | 5,429 | {
"abstract": "Summary The eco-evolutionary dynamics of microbial communities are predicted to affect both the tempo and trajectory of evolution in constituent species [ 1 ]. While community composition determines available niche space, species sorting dynamically alters composition, changing over time the distribution of vacant niches to which species adapt [ 2 ], altering evolutionary trajectories [ 3 , 4 ]. Competition for the same niche can limit evolutionary potential if population size and mutation supply are reduced [ 5 , 6 ] but, alternatively, could stimulate evolutionary divergence to exploit vacant niches if character displacement results from the coevolution of competitors [ 7 , 8 ]. Under more complex ecological scenarios, species can create new niches through their exploitation of complex resources, enabling others to adapt to occupy these newly formed niches [ 9 , 10 ]. Disentangling the drivers of natural selection within such communities is extremely challenging, and it is thus unclear how eco-evolutionary dynamics drive the evolution of constituent taxa. We tracked the metabolic evolution of a focal species during adaptation to wheat straw as a resource both in monoculture and in polycultures wherein on-going eco-evolutionary community dynamics were either permitted or prevented. Species interactions accelerated metabolic evolution. Eco-evolutionary dynamics drove increased use of recalcitrant substrates by the focal species, whereas greater exploitation of readily digested substrate niches created by other species evolved if on-going eco-evolutionary dynamics were prevented. Increased use of recalcitrant substrates was associated with parallel evolution of tctE , encoding a carbon metabolism regulator. Species interactions and species sorting set, respectively, the tempo and trajectory of evolutionary divergence among communities, selecting distinct ecological functions in otherwise equivalent ecosystems.",
"discussion": "Results and Discussion Rapid evolution of constituent species has been observed across a range of experimental [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ] and natural [ 17 , 18 , 19 , 20 ] microbial communities, including within the human microbiome [ 21 , 22 ], with implications for understanding how these communities are structured [ 23 ] and how they function [ 24 , 25 ]. Disentangling the drivers of natural selection within such communities is extremely challenging but is essential to enable the manipulation of microbial communities for improved function [ 24 , 25 , 26 , 27 ]. Here, to understand the contribution of eco-evolutionary community dynamics to natural selection, we track metabolic evolution by Stenotrophomonas sp. during adaptation to wheat straw with or without a community of five additional, naturally co-occurring species previously isolated from compost [ 28 ]. Wheat straw is a complex carbon source comprised of secondary plant cell-walls composed of cellulose, hemicellulose, and lignin. This lignocellulosic biomass is difficult to digest, as the cellulose exists as crystalline microfibrils, the hemicellulose is a complex, highly branched and crosslinked polymer, and these polysaccharides are sealed in lignin, a complex polyphenol [ 29 ]. Nevertheless, microbial communities efficiently degrade lignocellulose across a range of natural environments including animal digestive tracts and soils [ 30 ]. Replicate microcosms were serially transferred for sixteen 7-day growth-cycles both in monoculture (MC; n = 12) and in six-species polycultures where either the eco-evolutionary dynamics were reset at each serial transfer (long-term change in the relative abundance of taxa—i.e., species sorting—and evolution of other community members not permitted = reset polyculture; RP; n = 6) or allowed to play out (species sorting and evolution of other community members permitted = dynamic polyculture; DP; n = 6). This equated to approximately 125 generations or 150 generations of Stenotrophomonas evolution in monoculture and polyculture, respectively, due to slightly higher growth rates in polycultures. Metabolic evolution by Stenotrophomonas sp. was measured as respiration by evolved populations on seven components of lignocellulose [ 28 ], including both harder-to-digest recalcitrant substrates (β-glucan, cellulose, lignin) and easier-to-digest labile substrates that are protected from saccharification by the structure of lignocellulose prior to its digestion (xylan, arabinoxylan, galactomannan, pectin) [ 29 ]. Resource use by Stenotrophomonas sp. significantly diverged between treatments over time ( Figure S1 ; linear mixed model, treatment × substrate × time interaction, F 12,777 = 7.8661, p < 2.2 × 10 −16 ). We used phenotypic trajectory analysis [ 31 ] to calculate three properties—length, direction, and shape—of the evolutionary paths taken within this 7-dimensional metabolic phenotype space by our treatments. Evolutionary paths varied significantly between treatments ( Figure 1 ; permutational manova, treatment × time interaction, F = 8.97, p < 0.001). Interspecies interactions accelerated Stenotrophomonas sp. metabolic phenotype evolution, as indicated by a shorter evolutionary path in the MC treatment compared to both polyculture treatments (pairwise absolute differences in path distance, RP:MC Z = 7.04, p = 0.001, DP:MC Z = 8.22, p = 0.001), which themselves evolved similar distances (RP:DP Z = 0.27, p = 0.514). The RP treatment took an evolutionary trajectory whose direction was distinct from either the MC or DP treatments (pairwise differences in path angle, RP:DP Z = 2.028, p = 0.039; RP:MC Z = 1.88, p = 0.034). While the evolutionary trajectory of the DP treatment changed direction more over time than either the MC or RP treatment trajectories (pairwise differences in path shape, DP:MC Z = 2.80, p = 0.005; RP:DP Z = 3.58, p = 0.001; RP:MC Z = 1.03, p = 0.149). This is most clearly shown by the change in direction of the DP trajectory from traversing PC1 to traversing PC2 at around transfer 12 ( Figure 1 A). Overall, whereas the RP treatment evolved to increase use of labile substrates ( Figure 1 , along PC1: xylan, arabinoxylan, and pectin), the DP treatment evolved to increase use of recalcitrant substrates ( Figure 1 , along PC2: β-glucan, cellulose, and lignin). Figure 1 Trajectories of Stenotrophomonas sp. Metabolic Phenotype Evolution Ordination plots from a principal components analysis (PCA) of the Stenotrophomonas sp. metabolic phenotype over time. The first 3 principal components (PC) captured 92% of the variation in substrate use, and thus, these PCs were plotted to visualize the evolutionary trajectories of our treatments. Plots show (A) PC1 (54%) against PC2 (25%) and (B) PC2 against PC3 (14%). The variation in resource use associated with each PC is stated on each axis. Lines show evolutionary trajectories for the Stenotrophomonas sp. metabolic phenotype in the monoculture (MC; green), reset polyculture (RP; red), and dynamic polyculture (DP; blue) treatments; dots show values for each individual replicate over time (denoted by transfer number labels on each line). Use of individual substrates over time are plotted in Figure S1 . Individual replicate trajectories for the DP treatment are plotted in Figure S2 . The raw data is provided in Data S1 . Specialization on labile substrates would allow greater exploitation of the lignocellulose digestion of competing species. Consistent with this, while being in a community always increased the growth of Stenotrophomonas sp. relative to its growth alone, only the RP-evolved Stenotrophomonas sp. populations increased their competitiveness relative to the ancestor against the ancestral polyculture community on wheat straw ( Figure 2 ; two-way anova, treatment × growth-condition interaction, F 3,40 = 12.47, p < 0.0001; pairwise comparison of RP versus ancestor growth in polyculture, p < 0.001). Moreover, in competition against the ancestral polyculture community, the RP-evolved Stenotrophomonas sp. reached a higher final relative abundance than its ancestor or the evolved Stenotrophomonas sp. from the DP or MC treatments (one-way anova, F 3,20 = 22.05 p < 0.0001; pairwise Tukey tests against RP, all p < 0.001). This suggests that the on-going eco-evolutionary dynamics of communities limited the evolution of exploitative metabolic strategies by the focal species. Notably, none of the evolved Stenotrophomonas sp. populations showed faster growth on wheat straw alone than their ancestor (pairwise comparisons of MC, DP, and RP growth rates versus the ancestor all p > 0.05). This suggests that our growth assay may not have been sufficiently sensitive to detect differences in autonomous growth rate. It is probable that direct competition of evolved populations against their ancestor would have been more discriminating as this is the gold standard method for estimating relative fitness. However, we lacked an isogenic labeled strain of this Stenotrophomonas sp. environmental isolate, precluding the use of this superior method. Figure 2 Growth Rates of Ancestral and Evolved Stenotrophomonas sp. Growth on wheat straw when cultured alone or alongside the ancestral polyculture. Dots indicate mean growth rate ± standard error for each of the evolution treatments (monoculture [MC; green triangles], reset polyculture [RP; red squares], dynamic polyculture [DP; blue circles]) and the ancestor (purple triangles) and lines connect values measured while grown alone versus alongside the ancestral polyculture. The raw data is provided in Data S1 . Differences in composition among replicate DP communities emerged over time through species sorting ( Figure 3 ). We observed strengthening covariance of Stenotrophomonas sp. evolved metabolism with community structure over time (community dissimilarity × time interaction; F 1,87 = 6.4, p < 0.05), suggesting that changes in composition selected for different evolved metabolic functions among communities. Higher recalcitrant substrate use by Stenotrophomonas sp. was associated with communities that had higher final relative abundance of Bacillus sp. (linear regression, cellulose R 2 = 0.8625, F 1,4 = 19.06, p = 0.012; lignin R 2 = 0.8625, F 1,4 = 19.53, p = 0.0115). Moreover, the reinvasion of three of the replicate DP communities by Bacillus sp. from low density ( Figure 3 ) coincided with the change in direction of the evolutionary path of Stenotrophomonas sp. toward recalcitrant substrates (from PC2 to PC1: Figures 1 and S2 ). We previously showed that this Bacillus sp. strain is a labile substrate specialist [ 28 ], suggesting it would have competed strongly for labile substrates, potentially driving the observed niche differentiation by Stenotrophomonas sp. toward recalcitrant substrate use. Figure 3 Relative Abundance of Species in Dynamic Polyculture Communities Stacked bars show the relative abundance of species over time in the replicate communities (DP1 to DP6) from the dynamic polyculture treatment. The identity of species is indicated by colors as shown in the graphical key. The raw data is provided in Data S1 . To examine the genetic basis of Stenotrophomonas sp. metabolic evolution, we genome sequenced one randomly chosen clone per replicate population. Evolved clones had acquired between 0 and 4 mutations per clone, with 33 mutations in total, of which 66.6% were non-synonymous. While treatments did not vary in the number of mutations per clone (all mutations: Welch’s anova, F 2,10.97 = 0.03154, p = 0.9690; non-synonymous mutations: Welch’s anova, F 2,12.3 = 0.8878, p = 0.4363), the genetic loci affected by non-synonymous mutations varied among treatments ( Figure 4 ; permutational anova, F 5,570 = 6.304, p = 0.0002). Specifically, the DP and MC treatments became significantly genetically differentiated from the RP treatment (RP:MC t = −3.058 p = 0.002; RP:DP t = −2.216 p = 0.027), but not from one another (MC:DP t = −1.448 p = 0.148). This pattern was principally driven by parallel mutation of tctE , which was mutated in multiple replicates of the DP (3/6 clones) and MC (4/12 clones) treatments, but in only one replicate of the RP treatment ( Figure 4 ; Figure S3 ). TctD/TctE form a two-component signaling system that positively regulates tricarboxylic acid uptake in a range of species [ 32 , 33 , 34 , 35 ]. Furthermore, deletion of tctD/tctE has been shown to cause dysregulation of other signaling systems and altered expression of metabolic genes, leading to substantial alteration of carbon metabolism in P. aeruginosa [ 35 ]. It is probable, therefore, that tctE mutations played a role in the evolution of altered substrate use by Stenotrophomonas sp. The higher frequency of tctE mutations in DP-evolved compared to RP-evolved clones suggests that these mutations could be linked to the observed increase in the use of recalcitrant substrates by DP-evolved Stenotrophomonas populations ( Figure 1 , Figure S1 ). However, caution is required in making such inferences, in part because the single clones sequenced per population are unlikely to represent all of the genetic diversity present in the population samples used in the resource use assays. Figure 4 Parallel Genomic Evolution within and between Treatments Circles represent the Stenotrophomonas sp. Genome; each concentric circle is an independent evolved clone sampled at the end of the experiment. Colors denote the monoculture (MC; green), reset polyculture (RP; red), and dynamic polyculture (DP; blue) treatments. Markers indicate genetic loci where mutations were observed in evolved clones and labels show the predicted functional annotation for these loci where available. The shape of the marker denotes the type of mutation observed: filled circle, non-synonymous SNP; open circle, synonymous SNP; triangle, insertion or deletion; square, intergenic SNP. Markers for parallel evolving loci are connected by a gray line. Figure S3 shows the pairwise genetic similarity among all sequenced clones. A complete table of sequence variants is provided in Data S2 . Rapid evolutionary dynamics of constituent taxa are a feature of both experimental [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ] and natural [ 17 , 18 , 19 , 20 , 21 , 22 ] microbial communities and are likely to affect the structure [ 23 ] and function of microbiomes [ 24 , 25 ]. Unlike previous studies of evolution in multispecies bacterial communities [ 8 , 9 , 10 , 11 , 13 , 14 , 15 ], by resetting community dynamics, we disentangled the effects of interspecies interactions from their eco-evolutionary dynamics upon the evolution of focal species’ metabolism. Our data show that the evolutionary paths taken by constituent taxa depend upon the eco-evolutionary dynamics of communities. Species interactions and species sorting set, respectively, the tempo and trajectory of evolutionary divergence for focal taxa among communities. Selection arising from the eco-evolutionary dynamics of communities can override habitat-specific adaptation [ 18 ] to select for distinct ecological functions in otherwise equivalent ecosystems. Moreover, by constraining the evolution of exploitative strategies, the eco-evolutionary dynamics of microbial communities may help to explain the stability of ecological functions that, like lignocellulose metabolism, require the collective action of multiple species in microbiomes [ 24 , 25 ]."
} | 3,885 |
30839723 | PMC6170577 | pmc | 5,432 | {
"abstract": "Insects from the order Embioptera (webspinners) spin silk fibres which are less than 200 nm in diameter. In this work, we characterized and compared the diameters of single silk fibres from nine species— Antipaluria urichi , Pararhagadochir trinitatis , Saussurembia calypso , Diradius vandykei , Aposthonia ceylonica , Haploembia solieri , H. tarsalis , Oligotoma nigra and O. saundersii . Silk from seven of these species have not been previously quantified. Our studies cover five of the 10 named taxonomic families and represent about one third of the known taxonomic family-level diversity in the order Embioptera. Naturally spun silk varied in diameter from 43.6 ± 1.7 nm for D. vandykei to 122.4 ± 3.2 nm for An. urichi. Mean fibre diameter did not correlate with adult female body length. Fibre diameter is more similar in closely related species than in more distantly related species. Field observations indicated that silk appears shiny and smooth when exposed to rainwater. We therefore measured contact angles to learn more about interactions between silk and water. Higher contact angles were measured for silks with wider fibre diameter and higher quantity of hydrophobic amino acids. High static contact angles (ranging up to 122° ± 3° for An. urichi ) indicated that silken sheets spun by four arboreal, webspinner species were hydrophobic. A second contact angle measurement made on a previously wetted patch of silk resulted in a lower contact angle (average difference was greater than 27°) for all four species. Our studies suggest that silk fibres which had been previously exposed to water exhibited irreversible changes in hydrophobicity and water adhesion properties. Our results are in alignment with the ‘super-pinning’ site hypothesis by Yarger and co-workers to describe the hydrophobic, yet water adhesive, properties exhibited by webspinner silk fibres. The physical and chemical insights gained here may inform the synthesis and development of smaller diameter silk fibres with unique water adhesion properties.",
"conclusion": "4. Conclusion Our study made progress along three avenues of investigation into webspinner silk diversity: (i) developing methods for imaging and quantification, (ii) testing whether fibre diameter differences were correlated with insect size or evolutionary history, and (iii) exploring interactions between naturally spun silk and water, inspired by observations of natural colonies in the field. In this work, we used SEM and contact angle to characterize the physical properties of silk spun by webspinners directly onto graphite rods. Our procedures had two distinct advantages: (i) the silk samples were not disturbed by humans and should more accurately reflect natural diameters and water interaction properties, and (ii) the fibres were securely attached to the conductive graphite substrate, which reduced charging effects, and allowed collection of high quality SEM images without the use of metal coatings. Our access to nine species from five taxonomic families allowed us to test whether body length predicted fibre diameter or if diversity of silk fibres was more related to evolutionary history. The latter hypothesis gained support. Our survey adds significantly to the nanoscale description of webspinner silk, despite the relatively small sample size [ 12 ]. Using SEM, we observed that when silks were wetted with water, a film-like sheet results, which may indicate that proteins in the random coil conformation increase, similar to the structures formed when silks were soaked in methanol [ 5 ]. Previous studies suggested that organic solvent was required to dissolve the lipid coating in order to access the protein core. In this study, we expanded the protein–core model to include a description of how water interacts with the protein core in webspinner silk in the absence of organic solvent and show that exposure to water alone results in a change in macroscopic silk structure and wetting properties. Alternatively, exposure to water may remove metals that stabilize the β-sheet structure, as found in caddisfly silk, and when these metal cations are removed, water can penetrate rigid serine-phosphate regions and solvate the protein structure [ 28 ]. This hypothesis will be probed in future studies. When wetted, webspinner silk transforms into a film and water drops slip off more easily. The biological significance is not currently understood, but we suspect that tropical arboreal webspinners may benefit from their silk's ability to shed water given the almost daily exposure to drenching rains [ 29 ]. From an applied point of view, as webspinner fibres become a film upon wetting, their molecular structures may inspire the design of a material which changes its physical properties when wetted. There is growing interest in studying nature-inspired materials to design new nanoscale surfaces with superhydrophobic properties for biomedical applications [ 30 ]. The principles of ‘pinned’ water droplets onto rough surfaces has previously been used to provide a set of ‘design criteria’ for creating a hydrophobic, yet water-adhering material [ 31 ]. However, more molecular insight from NMR and X-ray crystallography studies about the changes that occur in the three-dimensional structure upon exposure to water is required. We reported fibre diameter for nine species from our laboratory cultures, but were able to quantify silk–water interactions for only four—those species that spin copious silk. Species that produce scant silk, such as D. vandykei and H. solieri , tend to dwell in crevices in bark, leaf litter and/or underground. They may produce silks with different characteristics than those living exposed on bark—such as reflected in the four species investigated herein. Determining how to collect silk from crevice-dwelling webspinners would increase our phylogenetic, as well as lifestyle, diversity and is worth pursuing. This is especially true given that previous work on H. solieri by Collin and co-workers [ 8 ] identified unique qualities in their silk proteins when compared to other webspinners. Finally, embiopterans come in a variety of body lengths beyond the range displayed by our current sample. Field collecting trips to Africa, South America and Southeast Asia would give us access to the largest webspinners (approaching 3 cm), and their silk might show qualities not detected in our more limited sample.",
"introduction": "1. Introduction New technologies are being developed to synthesize artificial fibres with unique physical, mechanical or water-interaction properties based on genetically modified silk proteins from spiders and silkworms [ 1 ]. Naturally spun fibres from these arthropods are of the order of 1 to 10 µm in diameter [ 2 ]. Technological advances warrant an interest in preparing smaller diameter (finer) fibres, which may be used in nanoscale medical or optical devices [ 3 ]. To inform the synthesis of finer silk fibres, developers may take inspiration from insects of the order Embioptera (commonly called webspinners or embiids), which spin nature's ‘finest known insect silk fibres’ [ 4 ]. Physical and chemical properties of webspinner silk for only five species have been published [ 4 – 9 ]. In the current work, we characterize and compare the diameters of single silk fibres from nine species. The species in this study provide a range of evolutionary histories, body sizes and lifestyles, from arboreal to detritivores. We established experimental methods for determining the variability of silk fibre diameter within the order Embioptera and explored interactions between silk and water. Given our unique access to a number of different species, we had the opportunity to test two hypotheses regarding single fibre diameters: (i) larger webspinners yield larger diameter silk (as the ‘finest known silk’ comes from a very small webspinner [ 4 ]); and (ii) silks from evolutionarily closely related webspinners have more similar diameters. 1.1. Natural history of webspinners (class Insecta, order Embioptera) Webspinners are mostly tropical and subtropical in distribution and spin by secreting nanoscale fibres ( figure 1 a ) from silk glands housed in their front feet [ 10 ]. All individuals (male, female, immature and adult) spin by stepping with their front feet against the substrate while releasing multiple strands of silk from enlarged tarsal glands. The webspinners are soft-bodied and flexible, and the females are always wingless as shown in figure 1 b ; these features allow them to easily run backwards and forwards within their tightly spun silken tunnels. With stereotypical stepping patterns [ 11 ], they create protective silken domiciles on trees ( figure 1 c ) in humid climes. In dry regions, they live in leaf litter or in underground burrows, which they line with silk. Species used in this survey were from five of the 10 named taxonomic families in the order Embioptera: Antipaluria urichi (family Clothodidae), Pararhagadochir trinitatis (family Scelembiidae) and Saussurembia calypso (family Anisembiidae), all from Trinidad in the West Indies; Diradius vandykei (family Teratembiidae) from the southern USA; and five species in the family Oligotomidae: Aposthonia ceylonica from India, Haploembia solieri and H. tarsalis (introduced into California from the Mediterranean region) and Oligotoma nigra and O. saundersii (pantropical and introduced throughout warmer regions of the world). Our survey included representatives from about one third of known families of webspinners [ 12 ].\n Figure 1. ( a ) SEM image of Pararhagadochir trinitatis naturally spun silk fibres with aluminium coating—note the difference in diameter of fibre bundles and single fibres. ( b ) Adult female P. trinitatis . ( c ) Pararhagadochir trinitatis silk in its natural environment—note the shiny patches apparently due to interactions with rainwater. 1.2. Measuring silk fibre diameter without a metal coating To quantify silk diameters, previous scanning electron microscopy (SEM) analyses of webspinner silk fibres used metal coatings to prevent sample charging [ 4 , 5 , 12 ]. For a fibre that is 30–100 nm in diameter, a 10–20 nm coating can represent a significant error in size measurements, especially in the context of comparing fibres from different species. We are unaware of any reports of SEM images of webspinner silks in the absence of a metal coating, except for transmission electron microscopy (TEM) images which also changed the fibre diameter through chemical manipulation of the silks (uranyl acetate caused the fibre to swell) [ 5 ]. Additionally, in order to understand how exposure to water changes the morphology or structure of the fibres, depositing metal may obscure what we wish to observe. In this study, webspinners were allowed to spin silk directly onto solid cylindrical graphite rods, which were then used in SEM analyses. The use of graphite rods was inspired by the sample preparation used in a study of spider silk [ 13 ]. Tension in the threads tended to pull them towards the surface thereby improving contact. The sufficient conductivity of the graphite allowed us to make clear images of single fibres, therefore eliminating the need for a metal coating. 1.3. Interactions with water (wetting and adhesion) The shiny patches visible on the silk in figure 1 c aroused our curiosity and led to an exploration of how rain may trigger a transformation of the otherwise fibrous, cloth-like nature of webspinner silk. Four arboreal species from four families ( An. urichi (Clothodidae), P. trinitatis (Scelembiidae), Ap. ceylonica (Oligotomidae) and S. calypso (Anisembiidae)), were chosen because they share similar habitats, which experience heavy tropical rains, a situation that potentially imposes selective pressures on the insects to produce effective silk coverings. A webspinner silk fibre is thought to be composed of a lipid coating surrounding a protein core [ 5 , 6 ]. Without this lipid coating, the silk fibre was observed with TEM to be permeable to water [ 6 ]. Previous NMR studies described how organic solvents (2 : 1 chloroform/methanol) changed the hydrophobicity and permeation of webspinner silks to water [ 5 , 6 ]. In the current study, we evaluate whether in the absence of organic solvents, exposure of webspinner silk to water can also change its water permeability properties and macroscopic structure. A previous study of An. urichi silk included contact angle measurements, which indicated that the silk was superhydrophobic (water drops bead up on it) but also highly water adhesive (water drops do not roll off) [ 6 ]. Silken sheets were composed of sparse, unevenly spaced fibres, which were laid ‘down in layers’ and not uniform in thickness [ 6 ]. High advancing contact angles of 150° ± 2° and low receding contact angles (approaching 0°) were measured [ 6 ]. High contact angle hysteresis and adhesive quality have also been previously quantified for the surfaces of rose petals [ 14 , 15 ]. This ‘rose petal effect’ was attributed to water's inability to penetrate into the uniformly distributed nanoscale features on microscale ‘bumps’ on the surface of a rose petal. Osborn Popp and co-workers suggested that lipid coating on webspinner silk was ‘only mildly hydrophobic’, and that the ‘rose petal effect’, was not relevant to silk fibres, which were ‘loosely woven’ and not uniform [ 6 ]. As the water droplet volume decreased when the receding contact angle was measured, fibres were drawn together, forming an aggregated pinning site, which adhered water to the silk surface (see fig. 6 in [ 6 ]). The hydrophobic and adhesive qualities of webspinner silk were attributed to these ‘super-pinning’ sites. In the current work, we extend these studies to include more species. We measure both static contact angles and tilt angles, motivated by previous studies of water interactions with flower petals and replicas [ 14 ].",
"discussion": "3. Results and discussion 3.1. Scanning electron microscopy images of dry silks 3.1.1. Quantification of fibre diameter using metal-free samples Our motivation for developing a metal-free technique for measuring fibre diameters was to remove the inherent uncertainty of adding thicknesses of the same order of magnitude as the samples. Since both the deposition of these metallic layers and the observation by the SEM are directional, it is unclear exactly how to treat subtracting these added thicknesses in order to derive the correct silk diameter. With respect to the location of the sample, the points of view of the deposition source and the SEM are not easily known, so a reliable method for correcting for the added 10–20 nm of metal is not obvious. This detail is especially challenging when measuring fibres with diameters as low as 30 nm. We had a small set of Al-coated fibre diameters that we compared to uncoated ones. The average fibre diameters measured for An. urichi were 100 ± 33 nm (uncoated) and 160 ± 54 nm (Al-coated). These values are consistent with the 10–20 nm added Al thickness. Furthermore, our results are consistent with previous data [ 5 ], indicating that subtraction of estimated metal thickness can be an acceptable approach for larger diameter samples. However, in undertaking a large survey of silk diameters from nine species using many images, our metal-free approach has the significant advantage of eliminating a source of variability from sample preparation. This improvement is especially important for the smallest diameter fibres. A previous study vacuum dried samples from H. solieri before metallization [ 12 ]. Our measurements for the same species are comparable to or slightly smaller than theirs even though the thickness of their gold coating was not specified. All samples in our studies and in the studies in [ 12 ] were SEM imaged under vacuum. We may assume that placing natural silk under vacuum has no significant effect on fibre diameter because significant swelling in our samples due to additional water would suggest that our samples should be larger (not comparable or smaller) compared to the twice ‘dehydrated’ samples. The narrower or comparable diameters of our metal-free H. solieri samples are consistent with the previously reported diameters of metal-coated silk fibres in [ 12 ]. An SEM image of P. trinitatis fibres as spun on a graphite rod is shown in figure 2 a . Regions of the fibres that are in good electrical contact with the substrate appear with dark centres, whereas poor contact leads to a brighter glow. This image is a good example of those used for determining the diameter data in figure 2 b . 3.1.2. Fibre diameters of naturally spun dry silk vary with phylogenetic relatedness The fibre diameters measured for each of nine webspinner species using metal-free samples are shown in figure 2 b . The species are grouped by phylogenetic tree because a statistically significant phylogenetic signal in fibre diameter between species was observed ( K = 1.18, p = 0.02). In other words, species that were more closely related had generally more similar silk fibre diameters. For example, the two Haploembia species in this analysis are similar in fibre diameter, even though H. solieri is smaller than H. tarsalis as an adult female (electronic supplementary material, figure S1). Adult female body length did not show phylogenetic signal ( K = 0.80, p = 0.20). Moreover, the average adult female body length was not significantly associated with average fibre diameter in an ordinary least-squares linear model (intercept t = 0.47, p = 0.67; slope t = 1.72, p = 0.13); or when accounting for phylogenetic relatedness under models of Brownian Motion (intercept t = 1.28, p = 0.25; slope t = 0.93, p = 0.39) or an Ornstein–Uhlenbeck process (intercept t = 0.75, p = 0.48; slope t = 1.52, p = 0.17). Thus, from our dataset, it appears species relatedness explains more variance in fibre diameter than does average adult female body length of webspinner species. 3.1.3. Scooped versus spun silks Both sets of silk diameters (scooped and naturally spun) show significant differences depending on the species that produced the silk. As shown in electronic supplementary material, figure S2, scooping the silk and wrapping it onto the graphite rod tended to obscure the differences in diameter and resulted in more overlap between fibre diameters for the different species. For example, An. urichi scooped silk was 72.3 ± 8.2 nm (s.e.) on average compared to 122 ± 3.5 nm when naturally spun. Naturally spun silks revealed more variability between species for silk diameter. Scooping the silk had a homogenizing effect on the silk fibres, but the specific effect on the silk was variable (half the samples showed an increase in diameter, the other half a decrease compared to natural silk). One explanation for this variability is that fibres could either be stretched or relaxed in the process of scooping. The fibre diameters determined from naturally spun samples are thought to be more accurate because SEM image quality was higher because the insects had stuck the fibres to the surface, thereby producing both a natural tension and enhanced electrical conduction. For both of these reasons, we present only the as-spun silk results in the main text and include data from scooped samples and the statistical analyses in the electronic supplementary material. 3.1.4. Scanning electron microscopy images of previously wetted, naturally spun silk In order to elucidate the mechanisms for film formation in wetted silk (see figure 1 c for the naturally occurring structures), we obtained SEM images of previously wetted fibres. These images show that previously wetted silk exhibits a film-like quality. Figure 3 a shows a single An. urichi fibre from a previously wetted sample. Although the entire area shown in the image was exposed to water (wetted on a macroscopic scale), only part of the fibre appears to have been affected. The darker region in the centre of the image is identified as the residue from the soluble protein core. This image suggests that water was able to penetrate the lipid coating and dissolve the protein core, but only in a localized section of the fibre. Our confidence in this interpretation comes from observing over one hundred images of dry single fibres on graphite. We can easily discern silk and the small graphite crystallites, and we never observe darkened regions as shown in figure 3 a until we expose the silk to water. Figure 3 a is representative of dozens of previously wetted samples of single fibres. It is important to note that these regions only appear in proximity to the silk fibres, and when they do appear, they appear in abundance. Furthermore, we did comparative imaging of a clean graphite rod before and after the same wetting treatment as used with silk-bearing rods. We observe no difference in the images from identical locations on the surface, and no comparable darkened regions appear. The only reasonable explanation for this darker region is the presence of residue from the silk. This effect has been observed in multiple previously wetted samples. A suspended film of P. trinitatis silk is presented in figure 3 b . It appears that an underlying silk layer forms a scaffold underneath the previously wetted silk. The absence of a metal layer makes it possible to see the underlying lattice presumably formed from the outer lipid layer of the fibres. This image has inferior clarify because the sample is not in good electrical contact with ground (the structure is not adhered to the graphite and there is no metallization). Figure 3 c is an example of a metallized previously wetted P. trinitatis silk film, which has better image quality. In this case it is also possible to see some of the underlying lattice of fibres even with the metallic layer. Our observations of the interaction of water with both the single fibre samples ( figure 3 a ) and larger structures ( figure 3 b,c ) suggest a new model for the structural transformation in the wetted silk samples. The protein core of the silk is apparently dissolved by the water that is adhered to the silk. As this water evaporates, the residual protein exhibits a new morphology as a film suspended between the fibre remnants. The structural transformation accounts for the shiny sheet appearance observed in the field ( figure 1 c ). To further elucidate transformations due to interactions with water, contact and tilt angles were measured. 3.2. Contact and tilt angles 3.2.1. Contact angle hysteresis Initial contact angles varied significantly, but with extensive overlap, between silk samples depending on species ( figure 4 a ; F 5,63 = 5.976; p < 0.0001). An. urichi silk generated statistically higher contact angles on average (122° ± 3° (s.e.)) compared to P. trinitatis silk (112° ± 2°). The contact angles of the other two species were intermediate, overlapping statistically with both An. urichi and P. trinitatis . Water placed on An. urichi silk behaved similarly to water on rose petals; these values approached superhydrophobicity (greater than 150°). Despite the higher average for An. urichi , silks of all four embiopteran species interacted with water in a statistically similar manner to the hydrophobic PDMS. Variability was most likely caused by the natural variation generated by the insects spinning in their laboratory containers (refer to electronic supplementary material, figure S5 as an example) and by our sampling method of scooping silk samples onto the notched Plexiglas holders. Contact angles of paired droplets on treated silk samples were significantly different: previously wetted, air-dried silk became hydrophilic while adjacent dry spots remained hydrophobic, irrespective of the species producing the silk ( figure 4 b ; matched pairs t -test = 7.99; p < 0.0001). Species was not a significant factor in influencing contact angles in this analysis, either for dry silks ( F 3,23 = 1.7998, p = 0.1797) or for previously wetted silks ( F 3,23 = 2.0488, p = 0.139). 3.2.2. Tilt angles The volumes of water droplets that slipped off naturally spun silk samples did not differ between the four embiopteran species (ANOVA, F 3,1 = 0.2476, p = 0.28) nor did they depend on the treatment of the silks (mean for dry silk = 63.8 ± 3.5 µl (s.e.) and for previously wetted = 68.1 ± 3.4 µl; F 3,1 = 0.7241, p = 0.4049). A rose petal sample tested at the same time showed a lack of adhesion compared to the silk samples as reflected in the small droplet size (25 µl) that fell when the rose petal was tilted. TA did not vary as a function of species ( F 3,1 = 1.36, p = 0.28) but, in contrast, the overall average TA for the four species for dry silk (85° ± 2°) was significantly higher than the average TA for previously wetted silk (74° ± 2°) ( F 3,1 = 10.45, p = 0.004). Because the water droplets tended to slip off at a lower TA when placed onto previously wetted silk samples, we conclude that adhesive properties due to the silk fibres' ability to pin water droplets [ 6 ] was partially lost when wetted silk transforms to a dry amorphous film. 3.2.3. Accounting for chemical variations in webspinner silks As shown in figure 4 a , contact angles (shown on the left axis) are highest for silk species with the widest fibre diameters (shown on right axis). For example, An. urichi had highest average contact angle and largest average fibre diameter. The average static contact angles from An. urichi silk were the only results that overlapped with the rose petal. If previously exposed to water and then dried, all silks exhibited similar hydrophilic properties. Fibre diameter and contact angles both increased in the following order (from lowest to highest): P. trinitatis ≅ Ap. ceylonica < S. calypso < An. urichi. These results suggest that fibre diameter roughly correlates with the contact angles reported here. The compositions of the lipid coatings of all four species were assumed to be similar to one another and to the lipid coatings of other arthropods silks, as previously suggested [ 5 , 6 ]. However, we considered possible differences in the hydrophobicity of the protein core material. The primary sequences of webspinner silk proteins contain highly repetitive amino acid units [ 7 ], which resemble those found in silk biopolymers from spiders [ 25 ] and silkworms [ 26 ]. Published amino acid sequences for Ap. ceylonica , An. urichi and S. davisi (a close relative of S. calypso ) indicate that the glycine (Gly) and serine (Ser) content of silk from all three species was nearly identical, but the alanine (Ala) content varied, and was 5%, 10% and 17%, respectively [ 7 ]. As Ala is more hydrophobic than Ser, silks with higher percentage of Ala are predicted to be more hydrophobic. Our findings indicate that higher Ala content may contribute to higher contact angles. The amino acid content for P. trinitatis silk is reported here for the first time (electronic supplementary material, table S1). Ala content in P. trinitatis silk is about 2%, which was lower than the other three species studied. Based on Ala content in the primary sequence, the hydrophobicity of silks would increase in the following order: P. trinitatis < Ap. ceylonica < An. urichi < S. calypso . The measured static contact angles followed this overall trend, except the An. urichi silks had slightly higher contact angles than S. calypso , but they were not significantly different. To ensure that protein secondary structure does not contribute to these observed differences in contact angles, we collected FTIR spectra of silks from all four species (electronic supplementary material, figure S4). The infrared absorbances in these spectra were used to describe the secondary structures, and found to be similar to one another. Regardless of Ala content, the silk from all four species exhibit predominately β-sheet structure [ 5 ]. These results are consistent with previously published studies of webspinner silks from H. solieri , S. davisi , Archembia sp., and An. urichi [ 8 ], which also indicated similarities in protein secondary structures. The differences in Ala content may not impact secondary structure, but may have a subtle effect on how β-sheets align in their three-dimensional structure. Previous studies suggested that Ala residues protruding from β-sheets may interlock into Gly residues from adjacent sheets [ 27 ]. Thus, fibres with higher Ala content may have proteins with molecular geometries that favour tightly locked core structures which exhibit decreased water penetration."
} | 7,195 |
32770001 | PMC7414886 | pmc | 5,433 | {
"abstract": "Microbial production of adipic acid from lignin-derived monomers, such as catechol, is a greener alternative to the petrochemical-based process. Here, we produced adipic acid from catechol using catechol 1,2-dioxygenase (CatA) and a muconic acid reductase (MAR) in Escherichia coli . As the reaction progressed, the pH of the media dropped from 7 to 4-5 and the muconic acid isomerized from the cis,cis (ccMA) to the cis,trans (ctMA) isomer. Feeding experiments suggested that cells preferentially uptook ctMA and that MAR efficiently reduced all muconic isomers to adipic acid. Intrigued by the substrate promiscuity of MAR, we probed its utility to produce branched chiral diacids. Using branched catechols likely found in pretreated lignin, we found that while MAR fully reduced 2-methyl-muconic acid to 2-methyl-adipic acid, MAR reduced only one double bond in 3-substituted muconic acids. In the future, MAR’s substrate promiscuity could be leveraged to produce chiral-branched adipic acid analogs to generate branched, nylon-like polymers with reduced crystallinity.",
"conclusion": "Conclusions The fully biological production of adipic acid from catechol, a pretreated lignin monomer, was achieved by screening CatA from different sources and optimizing its co-expression with MAR in E. coli to produce adipic acid at 1.6 mg/L or a 0.241% molar yield. The muconic acid yields presented in this work were lower than in previous studies, which we attribute to the use of batch fermentation rather than a biocatalysis set up and the use of minimal media rather than rich media, which makes it problematic to calculate yields. A closer study of oxygen sensitivity differences between MAR-BC and MAR-CA may help to engineer a more oxygen tolerant enzyme that will be useful in the production of adipic acid from lignin-derived monomers as oxygen is both a substrate (CatA) and an inhibitor (MAR) of the process. Engineering MAR for oxygen tolerance will help improve catechol to adipic acid yields in the future. A key finding of this work is the use of MAR to produce branched adipic acid analogs. Thus, the CatA-MAR cascade could be used to convert lignin-derived monomers to chiral branched dicarboxylic acids that may give tuneable properties to nylon-6,6 like polymers. Application of the enzyme cascade to a variety of lignin-derived monomers demonstrates increased utility as a lignin valorization approach.",
"introduction": "Introduction Adipic acid is used in the production of nylon 6,6, a polyamide present in carpets, textiles and molded plastics. In 2016, the global production of adipic acid was ~ 3.3 million tons per year, with all adipic acid being produced from petroleum 1 . This process generated nearly 10% of global nitrogen oxide emissions 2 . Renewable production of adipic acid provides a greener alternative, and can be initiated from a variety of feedstocks, including simple sugars and lignin-derived aromatics 1 . Independent of the feedstock used, today, the renewable production of adipic acid is a semi-biological process, combining bioproduction of muconic acid followed by its chemical hydrogenation to adipic acid 3 , 4 . For example, Pseudomonas putida has been engineered to convert pretreated lignin to cis,cis -muconic acid (ccMA) at 100% yield from detectable monomers 5 . Escherichia coli has a maximum theoretical yield of 83% from glucose through the shikimate pathway 1 , but experimentally a top yield of 22% has been achieved 6 . Purification of ccMA from the fermentation broth requires four unit operations to achieve the required purity (99.8%) at 81.4% yield 7 . Reduction of ccMA to adipic acid is performed using platinum, rhodium or palladium catalysts, with catalyst cost around $0.30 per kg of adipic acid 7 – 9 , ~ 19% of the current market value of adipic acid from petroleum 10 . Direct production of adipic acid from glucose through a reverse adipate degradation pathway has been achieved, but has a lower maximum theoretical yield (67%) 11 . The fully biological production of adipic acid would eliminate (1) the need for a chemical reactor, (2) the catalyst cost, and (3) the cost of purifying muconic acid prior to chemical hydrogenation. Indeed, a recent techno-economic analysis (TEA) accounting for both fixed and variable costs concluded that a fully biological route to adipic acid from glucose would result in an adipic acid price point of $1.36/kg, while fully chemical and hybrid biological and chemical routes would result in price points of $1.56/kg and $1.48/kg 10 . A separate TEA showed that switching feedstock from glucose to lignin monomers reduced adipic acid minimum selling price by 50% due to increased productivity and decreased feedstock cost 12 . Taken together, lignin is a more desirable feedstock than sugars for adipic acid production. Lignin depolymerisation results in a number of aromatic compounds, including catechol, a key intermediate in the production of adipic acid from both glucose and lignin-derived aromatics such as ferulic acid and p-coumaric acid 1 . Niu et al . achieved the fully biological production of adipic acid from lignin-derived aromatics in P. putida . Specifically, 4-hydroxybenzoic acid was converted to catechol and subsequently 3-ketoadipoyl-CoA via the β-ketodipate pathway. Using three heterologous enzymes and one endogenous thioesterase, 3-ketoadipoyl-CoA was converted to adipic acid with 17.4% molar yield 13 . Sun et al. developed a shorter pathway in E. coli , where glucose is metabolized to catechol via the shikimate pathway and catechol is converted to adipic acid using catechol-1,2-dioxygenase (CatA) and an enoate reductase previously shown to reduce muconic acid to adipic acid (i.e. muconic acid reductase, MAR) 14 . This pathway achieved 80.6 µg/L/hr of adipic acid 15 . Therefore, a better understanding of the CatA-MAR enzyme cascade can be directly applied to adipic acid production pathways that route through catechol. Here, we optimized the CatA-MAR enzyme cascade in E. coli and discovered that the cascade is capable of converting branched catechols to adipic acid analogs (Fig. 1 a). First, we optimized muconic acid production from catechol by screening and optimizing the expression of CatAs from five different organisms. Next, with the optimal CatA in hand, we maximized adipic acid production by optimizing the co-expression of two known MARs. Interestingly, during muconic acid production, the media acidified leading to the isomerization of ccMA to cis , trans -muconic acid (ctMA). To determine the extent to which MAR reduced ctMA, we fed ccMA and ctMA to cells expressing MAR and observed preference to reduce ctMA over ccMA. However, when we fed ccMA and ctMA to the cell lysate, MAR showed no preference between ccMA and ctMA. This data suggests that ctMA is preferentially transported into the cell over ccMA. Given the promiscuity of MAR, we explored its utility by feeding the CatA-MAR cascade branched catechols likely found in lignin 16 to produce chiral-branched diacids. We found that MAR reduced one double bond in muconic acid analogs with short alkyl chains at the 3-position and both double bonds of 2-methyl-muconic acid to produce 2-methyl-adipic acid. The promiscuity of MAR highlights the potential utility of the CatA-MAR enzyme cascade in lignin valorization, as lignin depolymerisation results in a heterogeneous mixture of aromatics. Figure 1 Muconic acid production from catechol. ( a ) Schematic for the bioproduction of adipic acid analogs. CatA: catechol-1,2-dioxygenase, MAR: muconic acid reductase. ( b ) Catechol to muconic acid conversion using CatA. At low pH, cis,cis -muconic acid (cc-muconic acid) can isomerize to cis,trans -muconic acid (ct-muconic acid) and trans,trans -muconic acid (tt-muconic acid). ( c ) Liquid chromatography/mass spectrometry (LC/MS) chromatogram of E. coli expressing Rhodococcus sp. AN22 CatA fed 1 g/L of catechol after 23 h incubation resulted in ccMA and ctMA. No ttMA was observed. Also shown, standards for catechol (6.8 min), ccMA (9.4 min), ctMA (13.6 min) and ttMA (9.6 min). Sample data for LC/UV absorbance spectra found in Supplementary Fig. S4 . ( d ) Optimization of muconic acid production by screening CatAs from five different sources using three different promoter strengths and in low and medium copy plasmids. Experiments were run in triplicate and error bars represent the standard deviation from the mean.",
"discussion": "Results and discussion Catechol to muconic acid conversion CatAs from Pseudomonas putida, Pseudomonas aeruginosa, Acinetobacter calcoaceticus, Acinetobacter baylyi, and Acinetobacter baylyi ADP1 have been used to produce muconic acid in E. coli 6 , 21 – 23 . We compared the E. coli performance of CatAs from P. putida, Acinetobacter baylyi ADP1 (both dimers with moderate specific activity— P. putida 22.4 µM/min/mg), Candida albicans (dimer with a higher specific activity, 63 µM/min/mg), Rhodococcus sp. AN22 (a monomer) and Rhodococcus opacus (structurally well studied) 8 , 24 – 28 (Supplementary Figs. S2 , S3 ). The CatAs were expressed from three promoters with different strengths in low and medium plasmid copy number (Fig. 1 b–d, Fig. S4). All CatAs performed similarly independent of promoter strength and plasmid copy number, reaching almost 100% catechol to muconic acid conversion after 24 h (Fig. 1 d). Of note, Acinetobacter baylyi ADP1 CatA showed < 10% conversion in half of the tested conditions despite similar protein expression (Supplementary Fig. S5 ). Active site alignment of the ADP1 CatA and P. putida CatA revealed that at position 76 ADP1 CatA codes for a proline, while P. putida CatA codes for an alanine (Supplementary Fig. S6 ). A proline to alanine mutation at this position has been shown to increase ADP1 CatA specific activity 10 fold 27 . Therefore, P76 in ADP1 CatA may lead to the underperformance observed when compared to the other CatA homologs. For all subsequent experiments, we used Rhodococcus sp. AN22 CatA as it performed well and it is a monomer, reducing the metabolic load of the system. E. coli expressing AN22 CatA converts catechol to ccMA as the major product. However, we also detected the thermodynamically stable isomer ctMA, which is likely produced from ccMA after media acidification after 24 h growth, which reaches a pH 4.3 after starting at pH ~ 7 (Fig. 1 b,c). We measured the maximum ccMA to ctMA isomerization rate to be between pH 3–5 (Supplementary Fig. S7 ), with previous literature confirming the maximum at pH 4 17 . No isomerization of ctMA to ttMA was observed, which is consistent with the literature 17 . Muconic acid to adipic acid conversion We compared the E. coli performance of Bacillus coagulans MAR (MAR-BC) and Clostridium acetobutylicum MAR (MAR-CA) 14 expressed from two promoters with different strengths in low, medium and high plasmid copy number (Fig. 2 a–c). MAR-BC achieved a 6.1% conversion of 500 µM ccMA to adipic acid using the pTrc promoter from a medium-copy plasmid after a 24 h anaerobic growth. This is lower than Sun et al . who used batch fermentation to convert 2.8 mM of ccMA to adipic acid (18.0% total conversion) using MAR-CA 15 . We rationalize our lower percent conversion in comparison by the use of minimal M9 media supplemented only with 0.5% glucose rather than a modified M9 medium, which contains 0.5% yeast extract, 0.25% glucose and 1% glycerol that aids in higher protein expression and increased cell density. Adipic acid production from catechol The experimental conditions for the CatA-MAR enzyme cascade required balancing the molecular oxygen requirement of the CatA reaction with the oxygen sensitivity of MAR. Thus, fermentations were run as a two-stage batch process with a 2 h aerobic stage followed by a 22-h anaerobic stage 29 . The CatA-MAR cascade was tested in a two- and one-plasmid system. As Fig. 2 d shows, the one-plasmid system resulted in 1.6 mg/L of adipic acid after 24 h, or a 0.241% molar yield from the fed 1 g/L catechol, an 18-fold improvement over the two-plasmid set up. MAR muconic acid isomer preference At pH < 7, ccMA isomerized to ctMA, and both isomers were present at a roughly equal molar ratio in the fermentation broth (Fig. 2 b). Hypothesizing that MAR may not reduce ctMA as efficiently as ccMA, we fed ccMA, ctMA and, for completion, ttMA to cells expressing MAR and to a cell lysate expressing MAR. In the cell-based experiment, both MARs showed a preference to reduce ctMA over ccMA with MAR-CA showing an eightfold preference. MAR-BC also showed a higher adipic acid yield than MAR-CA; 11.5-fold in the case of ccMA, and twofold in the case of ctMA (Fig. 3 a). In the cell lysate-based experiment, both MARs reduced ccMA and ctMA to the same extent. Interestingly, MAR-CA showed a higher adipic acid yield than MAR-BC (Fig. 3 b). MAR-CA also showed a preference for ttMA, which is consistent with previous literature 14 . Of note, the overall yields in the cell lysate experiment were lower than the cell-based experiment, likely due to enzyme deactivation from cell lysis solution components and the reduced co-factor concentration. Taken together, we rationalize the in vivo MAR substrate preference for ctMA to be the result of increased membrane permeability for ctMA over ccMA. We rationalize the higher in vivo activity of MAR-BC over MAR-CA to the fact that once a muconic acid isoform enters the cell the MAR experiences a higher localized substrate concentration. Previously, it has been suggested that MAR-BC has a lower substrate affinity but higher catalytic activity than MAR-CA 14 . Such MAR-BC enzymatic characteristics would fit the observed results. Figure 3 Muconic acid reductase substrate preference ( a ) Adipic acid production of Escherichia coli expressing Bacillus coagulans muconic acid reductase (MAR) or Clostridium acetobutylicum MAR when feeding 500 µM of cis,cis -muconic acid (cc-muconic acid), cis,trans -muconic acid (ct-muconic acid), trans,trans -muconic acid (tt-muconic acid) isomers. ( b ) Adipic acid production of lysed E. coli expressing B. coagulans MAR and C. acetobutylicum MAR fed 583 µM of muconic acid isomers. All experiments were performed in triplicate and error bars represent the standard deviation from the mean. MAR muconic acid analog preference Given that MAR reduces all muconic acid isomers, we investigated the extent to which the CatA-MAR cascade can produce branched adipic acid analogs from alkyl substituted catechols likely found in pretreated lignin 16 . We confined our analysis to commercially available catechols previously shown to be oxidized by CatA: 3-methyl-catechol (3MC), 4-methyl-catechol (4MC), and 4-ethyl-catechol (4EC) 30 . CatA oxidized 3MC, 4MC and 4EC to 2-methyl-muconic acid, 3-methyl-muconic acid and 3-ethyl-muconic acid, respectively (Fig. 4 a–c). MARs singly reduced 3-methyl-muconic acid and 3-ethyl-muconic acid to 3-methyl-hexenedioic acid and 3-ethyl-hexenedioic acid. Only 2-methyl-muconic was doubly reduced to produce 2-methyl-adipic acid by MAR (Fig. 4 a). While the substrate specificities of MAR-BC and MAR-CA were similar, MAR-BC led to higher yields of the singly and fully reduced muconic acid analogs (Fig. 4 ). Figure 4 Production of muconic acid and adipic acid analogs. Reaction schematic and LC/MS chromatograms of Escherichia coli co-expressing Rhodococcus sp. AN22 CatA and either B. coagulans MAR or C. acetobutylicum MAR and fed 1 mM ( a ) 3-methyl-catechol results in 2-methyl hexenedioic acid and 2-methyl-adipic acid; ( b ) 4-methyl-catechol results in 3-methy hexenedioic acid, and ( c ) 4-ethyl-catechol results in 3-ethyl hexenedioic acid. *: Peaks visible in MS but not in UV channel, thus not muconic acid analog peaks (Supplementary Fig. S8 ). CatA oxidation of 3MC resulted in two 2-methyl-muconic acid peaks. Presumably, cis,cis -2-methyl-muconic acid isomerized to the cis,trans isomer over the course of the reaction (Fig. 4 a, Supplementary Fig. S8 ). Interestingly, CatA oxidation of 4MC or 4EC resulted in a single peak for 3-methyl-muconic acid and 3-ethyl-muconic acid, respectively (Fig. 4 b,c, Supplementary Fig. S8 ). Given the steric crowding between the ketone group and the alkyl chains at position 3 in muconic acid in the cis,cis configuration, we presume that only cis,trans -3-methyl-muconic acid and cis–trans -3-ethyl-muconic acid are present in the media."
} | 4,121 |
25271714 | null | s2 | 5,434 | {
"abstract": "During the early days of molecular biology, cell-free protein synthesis played an essential role in deciphering the genetic code and contributed to our understanding of translation of protein from messenger RNA. Owing to several decades of major and incremental improvements, modern cell-free systems have achieved higher protein synthesis yields at lower production costs. Commercial cell-free systems are now available from a variety of material sources, ranging from \"traditional\" E. coli, rabbit reticulocyte lysate, and wheat germ extracts, to recent insect and human cell extracts, to defined systems reconstituted from purified recombinant components. Although each cell-free system has certain advantages and disadvantages, the diversity of the cell-free systems allows in vitro synthesis of a wide range of proteins for a variety of downstream applications. In the post-genomic era, cell-free protein synthesis has rapidly become the preferred approach for high-throughput functional and structural studies of proteins and a versatile tool for in vitro protein evolution and synthetic biology. This unit provides a brief history of cell-free protein synthesis and describes key advances in modern cell-free systems, practical differences between widely used commercial cell-free systems, and applications of this important technology."
} | 335 |
34945389 | PMC8709429 | pmc | 5,436 | {
"abstract": "Room temperature liquid metal (LM) showcases a great promise in the fields of flexible functional thin film due to its favorable characteristics of flexibility, inherent conductivity, and printability. Current fabrication strategies of liquid metal film are substrate structure specific and sustain from unanticipated smearing effects. Herein, this paper reported a facile fabrication of liquid metal composite film via sequentially regulating oxidation to change the adhesion characteristics, targeting the ability of electrical connection and electrothermal conversion. The composite film was then made of the electrically resistive layer (oxidizing liquid metal) and the insulating Polyimide film (PI film) substrate, which has the advantages of electrical insulation and ultra-wide temperature working range, and its thickness is only 50 μm. The electrical resistance of composite film can maintain constant for 6 h and could work normally. Additionally, the heating film exhibited excellent thermal switching characteristics that can reach temperature equilibrium within 100 s, and recovery to ambient temperature within 50 s. The maximum working temperature of the as-prepared film is 115 °C, which is consistent with the result of the theoretical calculation, demonstrating a good electrothermal conversion capability. Finally, the heating application under extreme low temperature (−196 °C) was achieved. This conceptual study showed the promising value of the prototype strategy to the specific application areas such as the field of smart homes, flexible electronics, wearable thermal management, and high-performance heating systems.",
"conclusion": "5. Conclusions In summary, a stable and facile fabrication of composite film by utilizing liquid metal printing for integrated electronics and electrothermal devices has been proposed and demonstrated. The influence of diverse oxidizing time of liquid metal, and the corresponding change in resistance, were discussed. Benefiting from the adjustable adhesive of liquid metal through oxidizing strategy, the liquid metal was enabled via integration on the soft PI film, exhibiting good electromechanical and electrothermal performance, even working normally under extreme conditions. These properties render PI-LM film with potential applications in the field of flexible electronics, personal thermal management, and soft robotics.",
"introduction": "1. Introduction Gallium-based liquid metals, which own excellent conductivity and rheological properties, can commendably achieve the functions of flexible electronics [ 1 , 2 , 3 , 4 ], energy and power transport [ 5 , 6 ], space exploration [ 7 ], and tumor therapy [ 8 ]. Moreover, the cost-effective preparation strategies, such as printings, are a particular advantage of liquid metal electronics [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ]. The thermal characteristics of metallic material play a vital role in these applications. However, due to the large surface tension of liquid metal (Ga, ~0.7 N/m) [ 6 ], it is a practical bottleneck to perform arbitrary printing processes on the flexible substrate. The universally diverse strategies to increase the adhesion between liquid metal and the substrate are explored, such as mechanical microstructure [ 11 ], surface coating modification [ 12 , 13 ], and additive doping [ 14 , 15 , 16 ]. Oxidation offers a cost-effective avenue for the improvement of the interfacial adhesion and chemical activity of liquid metal [ 17 , 18 , 19 ]. The wettability of the liquid metal on the diverse substrates can be effectively altered by adjusting the thickness and constituent of the oxide layer, and the thickness of the layer will also significantly change the conductive properties of the liquid metal [ 17 , 18 , 19 , 20 , 21 , 22 ]. However, the current attractive attentions are in the self-limiting and chemical properties of the natural oxide layer on the surface of liquid metal, and there are few reports on the adhesion properties after sufficient oxidation [ 23 , 24 ]. The electrothermal effect is an energy conversion process that converts electrical energy into thermal energy, which has many potential applications in aerospace, biomedical, and industrial applications [ 25 , 26 ]. The heating devices prepared by the traditional metal wire have the problems of local overheating and low flexibility. The reduction in the thickness of sensitive components would increase the risk of function failure. In recent years, flexible heating devices incorporating with graphene and carbon nanotube materials have been widely investigated to replace the commercial rigid electrical heating films [ 27 , 28 , 29 , 30 , 31 ]. However, there are also some limitations on the heating voltage, the achievable maximum heating temperature, and cost-efficiency of such emerging materials, compared with commercial metallic wire film. Due to its excellent electrical insulation and high temperature resistance, polyimide films (PI) are widely used as thermal control coatings and flexible expandable substrates [ 32 , 33 , 34 , 35 ]. Additionally, the flexible electrothermal PI film can normally work in extreme environments, such as aerospace heating, in which the existing electric heating materials are mostly copper–nickel (Cu/Ni) foil or wire as electric heating layer [ 33 , 34 , 35 , 36 ]. However, the adhesion between the filament or foil material and the film substrate is connected by a physical squeeze, which is likely to cause local thermal stress or disconnection, thus resulting in a device failure. Herein, a universal and facile approach to fabricate the liquid metal composite circuit was provided through the oxidizing strategy, in which commercial PI film with excellent electrical insulation was used as the substrate [ 34 , 35 ]. We firstly obtained the surface morphology and oxygen content of the liquid metal with different stirring times, as well as the wetting behavior on the diverse flexible substrates. The electrical performance of liquid metal under various bending angles and long-term power-loading conditions were evaluated. Then, the surface morphologies and electromechanical and electrothermal performances of the prepared film were measured. Finally, the proof-of-concept heating device was applied to heat transfer and demonstrated its stable performance after treatment at extreme temperatures (−196 °C). The flexible heating device proposed in this paper provides a new strategy for flexible heating applications and flexible electronics.",
"discussion": "4. Discussion It is one of the dominating features of liquid metal with natural thermal and conductive properties. However, the liquid metal is always in a tendency of droplet shrinkage when printing due to the large surface tension [ 43 ], and it is necessary to achieve a smoother printing process through the methods of the additives or partial oxidation. The full oxidation technology used here can efficiently realize liquid metal printing without the restriction of substrate, significantly reducing the selectivity of liquid metal printing to substrates, which can be easily written and printed on various surfaces, illustrating a brand new avenue for the universal printing of liquid metal. On the other hand, this process has a greater cost advantage compared to the previous adhesion method in which metallic particle additives change the wettability. Traditional metallic particles such as nickel, iron, copper, and silver have high prices and potential risks of phase delamination [ 15 , 44 , 45 , 46 ]. However, in natural environments, the strategy of controlling the agitation time to achieve viscosity adjustment, economizing the cost of the additives, offered a unique path to reduce the cost of liquid metal printing technology. This low-cost oxidation method to solve the gallium-based liquid metal printing substrate selection characteristics could further strengthen the advantages of low melting point alloys in the field of flexible electronic printing, achieving multifunction and potential applications in detection sensing, flexible robotics, and biomedical engineering."
} | 2,023 |
21304826 | PMC3033426 | pmc | 5,437 | {
"abstract": "The phytoplankton community in the oligotrophic open ocean is numerically dominated by the cyanobacterium Prochlorococcus , accounting for approximately half of all photosynthesis. In the illuminated euphotic zone where Prochlorococcus grows, reactive oxygen species are continuously generated via photochemical reactions with dissolved organic matter. However, Prochlorococcus genomes lack catalase and additional protective mechanisms common in other aerobes, and this genus is highly susceptible to oxidative damage from hydrogen peroxide (HOOH). In this study we showed that the extant microbial community plays a vital, previously unrecognized role in cross-protecting Prochlorococcus from oxidative damage in the surface mixed layer of the oligotrophic ocean. Microbes are the primary HOOH sink in marine systems, and in the absence of the microbial community, surface waters in the Atlantic and Pacific Ocean accumulated HOOH to concentrations that were lethal for Prochlorococcus cultures. In laboratory experiments with the marine heterotroph Alteromonas sp., serving as a proxy for the natural community of HOOH-degrading microbes, bacterial depletion of HOOH from the extracellular milieu prevented oxidative damage to the cell envelope and photosystems of co-cultured Prochlorococcus , and facilitated the growth of Prochlorococcus at ecologically-relevant cell concentrations. Curiously, the more recently evolved lineages of Prochlorococcus that exploit the surface mixed layer niche were also the most sensitive to HOOH. The genomic streamlining of these evolved lineages during adaptation to the high-light exposed upper euphotic zone thus appears to be coincident with an acquired dependency on the extant HOOH-consuming community. These results underscore the importance of (indirect) biotic interactions in establishing niche boundaries, and highlight the impacts that community-level responses to stress may have in the ecological and evolutionary outcomes for co-existing species.",
"introduction": "Introduction The open ocean is the largest biome on the surface of the earth, but due to its distance from coastal and deep ocean sediments, is also one of the most oligotrophic. Nutrient scarcity is especially prevalent in the surface mixed layers of highly stratified systems, with inputs of nutrients often restricted to new production (e.g. nitrogen fixation) or atmospheric (dust) deposition [1] . Microbes dominate biomass in this “wet desert” [2] and the most abundant phytoplankter in the tropics and subtropics (∼40°N to 40°S latitude) is the unicellular cyanobacterium, Prochlorococcus \n [3] . This oligotrophic specialist has the smallest cell size (0.4 to 1.2 µm in diameter) and genome (1.7–2.5×10 6 bp) [4] , [5] of any known photoautotroph. The small cell size results in a superior surface to volume ratio that is believed to provide a key advantage in nutrient scavenging versus larger competitors [6] . The small genome size, together with a reliance on sulfo- rather than phospholipids [7] , greatly diminishes its cellular P quota, providing an additional advantage over larger competitors. As a result of these and other adaptations, Prochlorococcus populations span the entire euphotic zone, often exceeding 10 5 cells mL −1 , and due to this numerical dominance have been credited for roughly half of all photosynthesis in the oceans [8] – [12] . Genetically distinct ecotypes of Prochlorococcus partition the oligotrophic euphotic zone niche with respect to depth and latitude, in response to gradients of light and temperature, respectively. The upper euphotic zone is dominated by two closely-related ecotypes, eMED4 (“e” for ecotype, “MED4” for the type strain of the lineage) and eMIT9312, which are high-light adapted (HL), while the lower euphotic zone is dominated by low-light adapted (LL) ecotypes that include eNATL2A, eMIT9313, and eSS120 [13] – [17] . In seasonally-stratified regions of the subtropics, deep mixing events facilitate an invasion of the surface mixed layer by the LL ecotype eNATL2A [17] , [18] , which in certain instances may lead to numerical dominance of the LL ecotypes in the mixed layer [19] . The high irradiances found near the ocean surface restrict the growth of eNATL2A [17] as well as the other LL ecotypes [16] but eNATL2A appears unique amongst the LL ecotypes in its ability to survive temporary exposures to high light, such as would be experienced during deep vertical mixing events [18] . The two HL ecotypes further partition the upper euphotic zone by latitude: the eMIT9312 ecotype dominates the middle band from 30° N to 30° S latitude, while eMED4 dominates the higher latitudes at the extremes of Prochlorococcus' distribution [20] . This latitudinal niche partitioning is driven primarily by ocean temperature [17] – [21] , and is consistent with the growth properties of cultured ecotype representatives [20] . The pattern of diversification within the Prochlorococcus lineage is consistent with an evolutionary progression from LL ancestors restricted to the deep euphotic zone, towards HL strains able to exploit the high light niche in the surface mixed layer. The eMIT9313 ecotype is the earliest branching lineage from the last common ancestor of Prochlorococcus and Synechococcus , and like all Prochlorococcus contains pigments that optimize the cells for the utilization of the blue light wavelengths that penetrate deepest into the euphotic zone [22] . The LL lineages are polyphyletic, with the eNATL2A ecotype the most recently derived. Based on reconstructions of Prochlorococcus evolution from molecular phylogenies along with ecological observations, the emergence of the eNATL2A lineage coincided with the ability of Prochlorococcus to invade the surface mixed layer, albeit only in instances of deep vertical mixing that minimize the lengths of exposure to high light [17] . Acquisition of a DNA photolyase and an elevated number of high light inducible proteins may have been responsible for this adaptation for high light tolerance [23] . With the emergence of the eMED4 and eMIT9312 “true” high light ecotypes – the most derived lineages – Prochlorococcus gained a sustained presence in the mixed layer, irrespective of mixed layer depth. The HL ecotypes have a common “core” of ∼100 genes not found in the LL ecotypes, and many of these may be responsible for the exploitation of high light near the surface [23] . In addition to the high light and low nutrient stresses associated with the oligotrophic surface mixed layer, the invasion of the mixed layer by Prochlorococcus may have also involved elevated oxidative stress. While hydrogen peroxide (HOOH) is ubiquitous in the ocean, the photooxidation of dissolved organic carbon (DOC) by sunlight [24] , particularly by light in the UV range [25] , results in near-surface HOOH maxima. Along with iron, HOOH is enriched in rainwater [26] – [28] , and the combination of the two may cause periodic oxidative stress in marine organisms via the generation of highly reactive hydroxyl radicals (OH • ) by the Fenton reaction [29] , [30] . HOOH has been shown to inhibit the growth of diverse marine algae, including cyanobacteria, macro- and microscopic chlorophytes, diatoms, and coral-associated zooxanthellae [31] – [36] , albeit at levels higher than those typically measured in pelagic waters. In prior work, we demonstrated that Prochlorococcus was dependent on “helper” heterotrophic bacteria to thrive in dilute laboratory cultures [37] . Many heterotroph strains were capable of helping Prochlorococcus , including members of the α- and γ-Proteobacteria and the Bacteriodetes cluster, suggesting the mechanism(s) are common bacterial activities. In these experiments, the helping phenomenon occurred when Prochlorococcus and heterotrophic bacteria were inoculated at ecologically relevant concentrations, suggesting that the helping mechanism might also play an important role in natural communities. Preliminary evidence suggested the helper phenotype was associated with protection from HOOH, compensating for Prochlorococcus ' conspicuously diminished suite of antioxidant genes (e.g. catalase) compared to other aerobes [4] , [38] . In this study, we were driven by the following questions regarding the heterotroph/ Prochlorococcus interactions: is the removal of HOOH from the medium necessary and sufficient for the helping phenotype? Does this mechanism of protection have relevance to natural communities in the open ocean? How universal is the dependency on helpers for the growth of the Prochlorococcus lineages? Finally, what does the apparent loss of endogenous HOOH-protection mechanisms imply regarding the genomic streamlining of the Prochlorococcus genus?",
"discussion": "Discussion HOOH removal is the primary mechanism responsible for the helper phenotype In this work we have confirmed our initial report [37] that heterotrophic bacteria help dilute Prochlorococcus cultures grow via removal of HOOH from the environment. HOOH diffuses freely across cellular membranes [55] , and hence the heterotrophic HOOH degradation could occur in the cytoplasm, periplasm, or extracellular milieu, perhaps with the same overall effect. Density-dependence of HOOH resistance has also been observed in Escherichia coli , and catalase-positive E. coli has been shown to cross-protect more vulnerable catalase-negative mutants in co-culture [56] . Inter-species cross-protection from oxidative stress has been noted for heterotrophic bacterial communities involved in aromatic degradation [57] and in oral biofilms [58] , as well as in a benthic mat-forming cyanobacterium [59] , but to our knowledge this is the first demonstration that such helping can occur between planktonic microbes of different trophic levels. While HOOH removal is sufficient to explain the helping phenotype of heterotrophic bacteria (at least for the EZ55 strain), other types of interactions may also contribute. For instance, heterotrophs can help eukaryotic algae by improving carbon fixation, either via increasing DIC concentrations [60] or lowering oxygen concentrations (thus diminishing the competing oxygenase reaction of Rubisco [61] ). However, the addition of heterotrophic helpers to the Prochlorococcus cultures either led to no observable difference in bulk bicarbonate, CO 2 , or oxygen, or a change in the opposite direction to that expected for a beneficial role ( Figure S2 ). In other cases heterotrophs help by supplying an essential metabolite (e.g. vitamin B12 [62] or indole acetic acid [63] ) or trace nutrient (e.g., by producing iron-binding siderophores [64] ). While we cannot rule out involvement of such cross-feeding interactions, our results suggest that any nutritional mechanism must play a secondary role relative to oxidative stress reduction, as adding HOOH back to helper treated media was alone sufficient to restore the growth limitation of dilute Prochlorococcus cultures ( Figure 1A ). Other than inorganic C, N, P, and metals, Prochlorococcus has no known nutritional requirements for growth [65] , [66] , and in fact grows better when dense versus dilute, contrary to expectations for an organism with a nutritional deficiency. Additionally, that a dense strain of Prochlorococcus can help a dilute strain ( Figure 1B ) argues against a requirement for a nutrient that Prochlorococcus itself cannot produce from the medium. With the exception of MIT9313, exposure of all axenic cultures of Prochlorococcus to SMC levels of HOOH results in catastrophic loss of cell envelope integrity ( Figure 3B and Figure 4B ). Concomitant with this envelope damage is the loss of photosynthetic efficiency ( Figure 4E,G ), and both of these effects may be consequences of lipid peroxidation. The slow decline of HOOH in sterile, light exposed media ( Figure S1 ) may be the result of the Fenton reaction, where photochemically produced Fe(II) reacts with HOOH to produce highly reactive OH • \n [67] . In turn, OH • can attack polyunsaturated fatty acids such as those found in most biological membranes, producing relatively stable lipid peroxide radicals that can spread via radical propagation if not countered by antioxidant defenses [55] . Both the cytoplasmic and the photosynthetic membranes may be susceptible to lipid peroxidation, and this may account for the coincident loss of cell envelope integrity and photosynthetic capacity we observed. Of note, dependence of HOOH-induced lethality on free Fe(II) could explain the greater resistance of MIT9313 to SMC challenge, as this is the only strain of Prochlorococcus to express the Fe-binding dpsA gene [4] which is linked to oxidative stress tolerance in other organisms [68] . Interestingly, the Synechococcus PCC7942 DpsA has a weak catalase activity [69] and if similar, the DpsA homolog of MIT9313 may be responsible for the cell's ability to eventually deplete the HOOH after 2 weeks under the SMC treatment (data not shown). HOOH may also affect photosynthesis by impinging on the turnover of RCII protein D1. D1 proteins are continuously degraded in illuminated photosynthetic membranes, and cells must repair or replace these proteins to maintain photosynthetic activity [70] . In the freshwater cyanobacteria Synechococcus PCC7942 and Synechocystis PCC6803, exogenous HOOH inhibits protein synthesis by specific inactivation of elongation factor G [71] , leading to net loss of photosystems containing functional D1. Hence, two non-mutually-exclusive mechanisms – lipid peroxidation and interruption of D1 turnover – may be responsible for the HOOH-dependent loss of photosynthetic efficiency in Prochlorococcus , and future studies should be aimed at testing these hypotheses. Impact of helpers on Prochlorococcus ecology Our results suggest that Prochlorococcus depends on the HOOH-degrading members of the microbial community to grow in the surface mixed layer of the open ocean. Opposing photochemical production reactions [24] , [25] and microbial degradation reactions [52] , [53] maintain the HOOH concentration within the permissive range (<0.2 µM) for the three ecotypes of Prochlorococcus that exploit the mixed layer niche. Absent the mixed layer microbial community, photochemical production of HOOH yields concentrations that are lethal to all three ecotypes ( Figure 2B–C ). The surface monoculture (SMC) challenge ( Figure 3 and Figure S6 ) demonstrated that, absent a counteracting microbial community, HOOH in surface seawater from the open ocean climbs to concentrations that ecologically relevant cell concentrations of these ecotypes are unable to survive. Curiously, the one strain that can tolerate the SMC challenge, MIT9313, belongs to an ecotype that is restricted from the mixed layer [17] , probably due to its sensitivity to high light [16] . While the SMC challenge reflects a worst case scenario for un-helped Prochlorococcus (e.g. sustained presence within 5 m of the surface), we note that even modest increases of HOOH above the steady state mixed layer concentrations (e.g. 0.2 µM, Figure 2A ) are enough to significantly impact growth ( Figure 1 , Figure 3A , and Figure 5 ), suggesting that the entire Prochlorococcus mixed layer population, not just cells at the very surface, benefit from the activity of helpers. Hence, an important but previously unrecognized role of the microbial community is to make the surface mixed layer permissive for the growth of Prochlorococcus , and by doing so, facilitate the expansion of its habitat range. Whether this relationship between Prochlorococcus and its HOOH-consuming neighbors is commensal or mutualistic remains to be determined, but as the numerically-dominant primary producer in the surface mixed layer, it is certainly conceivable that the HOOH consumers may benefit indirectly through the release of organic carbon during the growth [72] or lysis of Prochlorococcus . Our study contributes to a growing body of evidence that interspecies interactions can contribute significantly to niche expansion via stress reduction. For instance, land plants in high altitude alpine sites subjected to high abiotic stress (e.g., low moisture, low temperature, strong winds) experience pronounced losses in productivity as well as increased mortality in the absence of other members of the plant community, whereas this helping effect does not occur in otherwise similar communities in less stressful, lower altitude habitats [73] . Likewise, lichenized algae and fungi gain vastly improved resistance to desiccation and oxidative stress in symbiosis, expanding the range of each to include subaerial habitats [74] . Similarly, cnidarians (e.g., corals) and zooxanthellae tolerate temperature and hypoxia extremes together that neither can tolerate separately [75] . Collectively, these studies support the broader “stress-gradient hypothesis” that cooperation should be stronger in more stressful environments [76] , and emphasize the need to assess stress responses at the community level in order to understand their impacts on biological distributions in nature. The microbial community in the surface mixed layer is genetically diverse [2] , and identifying the microbes contributing most significantly to HOOH degradation is a major challenge for future studies. We know that Prochlorococcus degrades HOOH poorly ( Figure S1 ) and thus is not likely to contribute significantly to HOOH decomposition in the ocean. Intriguingly, the same may be true for the most abundant heterotroph in the oligotrophic ocean as well, as the genome of Pelagibacter ubique , the first cultured representative of the SAR11 cluster, also lacks homologs of catalase and other antioxidant defenses and [77] . The lack of robust HOOH scavenging pathways in both the numerically dominant autotroph and heterotroph implies that this critical function may be performed by less abundant “keystone” species in the mixed layer. Given the high catalytic rate of catalase [78] and the efficiency of HOOH removal observed in culture (e.g. Figure S1 ), it is conceivable that a relatively small number of catalase-expressing organisms could protect the entire surface mixed layer community from solar-generated HOOH. We note that many of the confirmed helpers of Prochlorococcus \n [37] are catalase-positive members of the alpha and gamma proteobacteria whose genetic signatures appear at reasonable frequencies in the open ocean mixed layer [2] , [79] , and are thus potential candidates for these keystone microbes. However, there are clearly other biological mechanisms for removing HOOH (e.g., the residual HOOH scavenging abilities of catalase mutants, Table S2 ), any one of which may contribute to the helper phenotype of surface mixed layer communities. Evolutionary implications of the helper- Prochlorococcus interaction Our results present an apparent paradox regarding the evolutionary history of the Prochlorococcus lineage: the eMIT9313 ecotype, which is restricted from the HOOH-enriched mixed layer by its sensitivity to high light, is more resistant to HOOH than the ecotypes found in high abundance in the mixed layer. eMIT9313 is the earliest branching lineage from the last common ancestor of Prochlorococcus and Synechococcus \n [23] , [80] , and although it lacks catalase, may share other ROS defense mechanisms with Synechococcus (e.g. dpsA ). Indirect defense mechanisms may also be involved in eMIT9313. For example the peptidoglycan synthesis genes of MIT9313 are more similar to those of Synechococcus than those of the HL strain MED4, and the MIT9313 cell wall is intermediate in thickness between those of Synechococcus and MED4 [81] . A thicker cell wall may confer enhanced resistance by limiting HOOH diffusion into cells and/or preventing cell lysis (e.g., Figure 4B versus Figure 4D ). It is not clear why eMIT9313 has retained the relatively high resistance to HOOH; perhaps the genes conferring resistance are also involved in other cellular functions that remain under selection. However, what is clear is that for the more recently derived lineages, including the LL ecotype eNATL2A, the net genomic reduction that has occurred relative to eMIT9313 [23] has coincided with a loss of HOOH resistance. Thus, the evolution of the genus leading to tolerance of temporary exposures to high light (eNATL2A) and true high light adaptation (eMED4 and eMIT9312) that allowed this lineage to exploit the surface mixed layer habitat did not coincide with a greater resistance to HOOH; in fact, the opposite occurred. We believe that this paradox is resolved because the HOOH-consuming microbes present at the ocean's surface made the HOOH resistance genes in Prochlorococcus dispensable. Prochlorococcus evolved in the context of an extant HOOH-scavenging community, and thus as it developed tolerance to high light and possibly other environmental stresses in the surface mixed layer, it had no selection pressure to maintain the high level of resistance to HOOH. As the oligotrophic environment imposed pressure to reduce genome size [5] , [22] , [23] , [82] , [83] , genes encoding these resistance mechanisms were amongst the pool of expendable genes, and were eventually lost. Similar mechanisms may have been at play during the genome streamlining of the ocean's most abundant heterotroph, P. ubique \n [84] , although it is unknown as yet whether or not this organism benefits from co-culture with helpers. It is intriguing to note that both Prochlorococcus and P. ubique are conspicuously difficult to cultivate, leading to speculation that other, as-yet-uncultured organisms may be similarly dependant on helpers in nature (e.g., [64] ). Hence, this study emphasizes the importance of community-level stress responses not only for the ecology, but also the evolutionary history of free-living microbes. Finally, we note that while the catalase gene could have been lost from the Prochlorococcus lineage (either prior to or after the divergence from Synechococcus ) as a consequence of neutral genetic drift, it may also have been lost as a selectively favorable event. One reason may be economic: as hypothesized for the reduction of peptidoglycan in the HL strain MED4 [81] and the reduction of phospholipids in favor of sulfolipids throughout the Prochlorococcus lineage [7] , the loss of catalase may have been selected to lower the cell quota for scarce nutrients in the oligotrophic ocean. The catalase-peroxidase found in most cyanobacteria is a large dimeric enzyme (160 kilodaltons) that has 4 iron-containing heme co-factors [78] . If we make certain assumptions about expression levels based on published data (see Methods ), we may estimate that loss of catalase-peroxidase would result in a reduction of cell quotas for Fe, P, and N by 0.2%, 0.14%, and 0.05%, respectively, for Prochlorococcus MED4 ( Table S4 ). As the primary selective pressure implicated in the genomic reductions for this oligotrophic lineage is to lower the cost of such scarce nutrients for cell production [5] , [22] , [23] , [82] , [83] , it is reasonable that such a gene would be lost in the absence of selective pressure for its retention. Additionally, catalases in keratinocytes have been shown to generate an unidentified form of reactive oxygen species when exposed to UV-B [85] . If similar side reactions occur for bacterial catalases, cells in the UV-exposed surface mixed layer may experience a tradeoff, degrading HOOH while also producing another form of activated oxygen; under these conditions the negative consequences may outweigh the positive ones for Prochlorococcus . In the future, development of robust genetic tools for Prochlorococcus should allow us to ectopically express catalase and determine if it indeed has a positive or negative impact under mixed layer conditions."
} | 6,008 |
30180154 | PMC6138402 | pmc | 5,438 | {
"abstract": "Habitat-forming species sustain biodiversity and ecosystem functioning in harsh environments through the amelioration of physical stress. Nonetheless, their role in shaping patterns of species distribution under future climate scenarios is generally overlooked. Focusing on coastal systems, we assess how habitat-forming species can influence the ability of stress-sensitive species to exhibit plastic responses, adapt to novel environmental conditions, or track suitable climates. Here, we argue that habitat-former populations could be managed as a nature-based solution against climate-driven loss of biodiversity. Drawing from different ecological and biological disciplines, we identify a series of actions to sustain the resilience of marine habitat-forming species to climate change, as well as their effectiveness and reliability in rescuing stress-sensitive species from increasingly adverse environmental conditions.",
"conclusion": "Concluding remarks Amelioration of physical stress by habitat-formers sustains species persistence in harsh environments [ 14 , 15 ]. This service might become increasingly important under future climates. The potential of habitat-formers to act as climate rescuers relies on their ability to maintain key individual and population traits in the face of climate changes. Likewise, the strength of rescuing effects depends upon source-sink dynamics and the interplay of stabilizing and destabilizing forces regulating the coexistence between the benefactor and the beneficiaries as well as among beneficiaries. Thus, current ability to ameliorate environmental conditions is not sufficient in itself to make a habitat-former a climate rescuer species. Nonetheless, some habitat-forming species display the right individual and population traits ( Box 3 ). Drawing from different ecological and biological disciplines, a series of management actions can sustain the strength and reliability of their climate-rescuing effects. Within a multidisciplinary framework ( Fig 3 ), understanding how biogenic habitats influence evolutionary adaptation of beneficiary species to changing conditions and their ability to track suitable climates should be considered a priority. Developing the concept of sustaining habitat-former populations as a nature-based solution to climate change will likely depend on our ability and willingness to address ethical issues in modern conservation, such as those related to the use of synthetic biology, non-native species, assisted species evolution, and species relocation. Finally, the general features of one or a few species that reduce climate-driven abiotic stress for other species that we describe in coastal systems are likely to be found also in other types of ecosystems. For example, heat tolerance of freshwater gastropods is lowered in hypoxic conditions [ 97 ] and may be sustained by macrophyte oxygen production. In high-alpine systems, some cushion plants mitigate the effects of warming on native grasses [ 9 ]. Likewise, during drought events, canopy-forming mosses enhance the survival of smaller mosses and hepatics in their understory [ 98 ]. Thus, the broad conclusions we derive for coastal ecosystems under climate change may also apply to other ecosystems. Box 3. Examples of potential climate rescuers Climate rescuer on the sand Sea cucumbers play an important role in coastal environments since they bioturbate sediments and recycle nutrients, sustaining the diversity and functioning of benthic communities [ 99 ]. The sea cucumber Holothuria scabra (the “sandfish,” Fig 1F ) is distributed throughout the Indo-Pacific region, between 30° N and 30° S of latitude. It is an active burrower and enhances sediment oxygenation, buffering negative effects of hypoxia caused by eutrophication and warming [ 33 ]. In addition, it can foster seagrass growth and productivity via remineralization of nutrients and/or their release from sediment pore water [ 99 ], potentially triggering a facilitation cascade. This species is cultured, and it seems able to rapidly adapt to variable environmental conditions (e.g., salinity, temperature) through behavioral and molecular mechanisms [ 100 , 101 ]. For instance, in aquaculture facilities, extreme water temperatures exceeding 31 °C caused no mortality of juveniles and, indeed, fostered their growth [ 102 ]. Finally, the entire mitochondrial genome of this species has been sequenced [ 103 ]. For the reasons above, this species may offer a nature-based solution for alleviating the impact of temperature-driven hypoxia. Climate rescuer on the rocks The brown macroalga Fucus vesiculosus ( Fig 1C ) occupies wide ecological and geographical ranges. Presently, it spans latitudes from above 70° N (Norway) to near 30° N (Morocco), withstanding, at low tide, extreme freezing (e.g., Labrador Sea), extreme heat (e.g., above 40 °C in Iberia), and variable salinities (estuaries, the Baltic Sea). It can function as climate rescuer for taxa beyond the southern limits of most intertidal fucoid seaweeds of the NE Atlantic, which can be vertically compressed and geographically restricted beyond the northwest Iberian climate refugium [ 104 ]. In contrast, F . vesiculosus extends further south, persisting in more extreme conditions. Although it suffered the loss of many populations of a southern genetic lineage [ 105 ], reciprocal transplants showed that populations that persisted from this southern lineage have better adaptive traits for their habitat [ 106 ]. In this species, the costs of thermal stress to cellular metabolism (recorded as molecular heat shock response) can be escaped when high temperatures co-occur with rapid extreme desiccation [ 36 ]. Producing large quantities of recruits of F . vesiculosus is a standard procedure because this species has been widely used for decades as a model in developmental biology, reproductive ecology, and ecophysiology, including in experimental field outplants [ 107 ]. Because the species is easily propagated and the southern populations have the capacity to withstand heat stress and maintain large canopies in areas where few other large intertidal canopies exist, it may offer a nature-based solution for alleviating the impact of multiple stressors on intertidal community diversity and abundance along its warm range limits."
} | 1,580 |
37580316 | PMC10425419 | pmc | 5,439 | {
"abstract": "Microorganisms play essential roles in the health and resilience of cnidarians. Understanding the factors influencing cnidarian microbiomes requires cross study comparisons, yet the plethora of protocols used hampers dataset integration. We unify 16S rRNA gene sequences from cnidarian microbiome studies under a single analysis pipeline. We reprocess 12,010 cnidarian microbiome samples from 186 studies, alongside 3,388 poriferan, 370 seawater samples, and 245 cultured Symbiodiniaceae, unifying ~6.5 billion sequence reads. Samples are partitioned by hypervariable region and sequencing platform to reduce sequencing variability. This systematic review uncovers an incredible diversity of 86 archaeal and bacterial phyla associated with Cnidaria, and highlights key bacteria hosted across host sub-phylum, depth, and microhabitat. Shallow (< 30 m) water Alcyonacea and Actinaria are characterized by highly shared and relatively abundant microbial communities, unlike Scleractinia and most deeper cnidarians. Utilizing the V4 region, we find that cnidarian microbial composition, richness, diversity, and structure are primarily influenced by host phylogeny, sampling depth, and ocean body, followed by microhabitat and sampling date. We identify host and geographical generalist and specific Endozoicomonas clades within Cnidaria and Porifera. This systematic review forms a framework for understanding factors governing cnidarian microbiomes and creates a baseline for assessing stress associated dysbiosis.",
"introduction": "Introduction Cnidarians (e.g., corals, sea anemones, jellyfish) face anthropogenic stressors that are increasing in severity and frequency. Globally, the ecosystem services that corals and other cnidarians provide have fallen by approximately 50% 1 , with further decreases forecasted in the future 2 . Since many organisms reside within and around cnidarians, loss of cnidarian species has resulted in a 63% decline in coral reef associated biodiversity, including macroinvertebrates and fish 1 . In addition to macroorganisms, cnidarians host a multitude of microorganisms, which together constitute their microbiome 3 – 6 . Research on the mutualistic symbiosis between cnidarians and dinoflagellate algae (family Symbiodiniaceae), including the bleaching phenomenon (loss of Symbiodiniaceae and/or their chlorophyll content), overshadows the knowledge on the Archaea, Bacteria, Fungi, microalgae, protists, and viruses of the cnidarian microbiome 7 – 11 . Nevertheless, the non-Symbiodiniaceae members of cnidarian microbiomes play important roles within the holobiont 12 (host and microbiota). To understand cnidarians under current climate conditions, and cnidarian capacity to withstand environmental change, it is imperative to understand the fundamental factors influencing the microbiome composition of cnidarians. The cnidarian microbiome functions in host nutrient cycling (C, N, P, S) (reviewed in 13 – 16 ), homeostasis (reviewed in 17 , 18 ), protection, including antimicrobial production and competitive exclusion (reviewed in 19 – 21 ), development (reviewed within 22 ), health (reviewed in 23 , 24 ), and response to environmental fluctuations (reviewed in 25 , 26 ), in addition to contributing to reef processes (reviewed in 27 , 28 ), and ecosystem resilience (reviewed in 16 , 29 ). These findings were made possible with the increasing access to DNA sequencing and prompted by the increased concern for coral reef health 30 – 32 . The majority of cnidarian microbiome research has utilized 16S rRNA amplicon sequencing of scleractinian coral microbiomes to identify primarily bacterial assemblages. As the main frame builders of coral reefs, scleractinian corals (class Hexacorallia, sub-phylum Anthozoa 33 ), have been the main emphasis of cnidarian microbiome research. This focus has framed our current understanding of cnidarian microbiomes. Research into non-scleractinian cnidarians, however, has identified significantly different structuring of cnidarian microbial symbioses 34 – 36 . Unfortunately, the lack of standardized sampling, storage, processing, and analytical protocols across 16S rRNA gene amplicon studies, hinders the ability to synthesize published data to create a baseline for cnidarian microbiomes 37 – 39 . Thus, the scientific community often relies on literature reviews in lieu of meta-analyses or systematic reviews 37 , 40 , 41 . The methodological variability not only challenges data integration but can lead to different conclusions due to identifying significantly different microbial communities from the same coral sample 42 . In addition to variability resulting from different processing protocols, the majority of cnidarian datasets published to date have been processed by clustering (typically to 97% similarity) their sequences into operational taxonomic units (OTUs), with the remaining datasets denoised to produce amplicon sequence variants (ASVs). Clustering within datasets limits detailed examination of trends across available literature, as OTUs from one study are inherently different from those from another. Further, while both OTU and ASV approaches have their strengths and weaknesses 43 , 44 , the denoising steps in ASV pipelines can increase the precision of measuring environmental specificity 45 and, importantly, allow for direct comparison of sequences across studies. However, the production of ASVs across different denoising pipelines, or different parameters, can also introduce sequence variation. In this study we unify available cnidarian 16S rRNA sequences (Fig. 1 , Supplementary Data 1 ) under a single analysis pipeline, thereby creating a global baseline for cnidarian microbiomes, and elucidating patterns and factors that govern the assemblage of cnidarian microbiomes. Importantly, this database is freely available ( Figshare ) to serve as a community resource for further exploration into cnidarian microbiomes, and to support global conservation strategies. We assemble all available 16S rRNA sequences from nearly 200 studies, each of which preserved, extracted, amplified, processed, and analyzed samples using distinct techniques. Partitioning these samples according to host health, sampling effort, hypervariable region, and sequencing platforms, we reduce the methodological and sequencing variability present for cross-study analyses. We compare the diversity, structure, and richness of scleractinian coral prokaryotic microbial communities to other members of the phylum Cnidaria, to determine how phylogeny, geography, and depth influence cnidarian microbiomes. We investigate the relative abundance of microbiota as a function of depth, and identify the taxonomic ‘core microbiome’ (microbiota present in all samples within a species per site), as this microbial component often serves as a proxy for holobiont health and resilience when facing anthropogenic stressors 20 , 46 . Further, we examine differences in the microbial relative abundance in three different coral microhabitats (tissue, skeleton, and mucus) by using unique sequence and clustering-based techniques. Finally, we document microbial genera (including Endozoicomonas ) that are highly prevalent and abundant within the different microhabitats of cnidarian species, serving as core members across cnidarian classes. Fig. 1 Global distribution of the 12,010 cnidarian microbial (16S rRNA gene) samples included in the systematic review. Regional pie chart diameters indicate sample abundance, with colors representing the relative abundance of five cnidarian orders and an ‘other’ category which includes seven additional cnidarian orders. Smaller circles represent studies with at least one cnidarian microbiome sample, with colors specific to water bodies. Made with QGIS.",
"discussion": "Discussion Cnidarian microbiota diversity This systematic review revealed that cnidarians host an extraordinary array of microbial phyla (12 archaeal and 74 bacterial phyla, 22 and 185 classes, respectively, Fig. 2 ). This substantially expands previous totals of the 42 microbial phyla identified in the Coral Microbial Database and the Coral Microbiome Portal 41 , and the 63 bacterial phyla identified in the Sponge Global microbiome dataset 51 . Remarkably, cnidarian microbial phyla diversity also rivals the 85 phyla identified in the Earth Microbiome Project, which examined 2.2 billion free-living and host-associated 16S rRNA sequences 45 . This incredible diversity suggests that cnidarians are one of Earth’s most diverse microbial reservoirs, supporting substantial prokaryotic metacommunities. Shared Cnidarian microbiota The integration of microbiome data across Cnidaria, which we performed in this systematic review, is critical for a greater understanding of cnidarian-microbiome structure and plasticity, as well as prokaryotic interactions with other coral reef invertebrates. Establishing a microbial baseline will also allow for the assessment of stressor-associated dysbiosis. For example, even with the current sampling bias of scleractinian corals, Alcyonacea and Scleractinia each hosted approximately 30% of all shared cnidarian microbiota, suggesting that both orders may act as reservoirs for other cnidarian species (Fig. 4d ). Conversely, these shared sequences represented <3% of the entire scleractinian microbiome, of which 12.5% was shared within the order, suggesting that scleractinian corals might not only serve as an important reservoir for scleractinians, but they may also play a key role in the reacquisition of microbiota following stressor-associated dysbiosis. Complexity of Cnidarian microbiomes Across Cnidaria, host phylogeny plays a key role in microbial assembly, influencing the structure, complexity, and diversity of cnidarian microbiomes. Our cnidarian-wide comparisons greatly expand previous findings of phylogenetic influence on coral microbiomes 52 – 54 , and are similar to processes identified in poriferan holobionts 55 , 56 . We posit that increased body plan complexity, e.g., the evolution of skeletons in Alcyonacea, Antipatharia, Helioporacea, and Scleractinia, increased the number of internal niches, driving niche partitioning, and facilitating increases in the richness and/or diversity of specific microbial communities (Fig. 3 ). More diverse microbial communities may lead to diversification of the holobiont phenotype, functional capacities, and metabolic capabilities, thereby enabling expansion of the host into novel habitats 57 . This diversification would help explain the significant changes in microbial richness correlated with the radiation of modern scleractinian families 52 . With Cubozoa, Hydrozoa, Scyphozoa, and Octocorallia hosting significantly less complex microbiomes than Hexacorallia, and less diverse microbiomes than Scleractinia, we propose that less complex microbiomes were the ancestral state of Cnidaria, with more complex microbiomes evolving more recently, similar to that of poriferan holobionts 56 . Geographic and phylogenetic influence of Cnidarian microbiomes We found strong clustering by ocean basin of the microbiomes of closely related cnidarians (Supplementary Figs. 11 – 12 ), potentially suggesting that phylosymbiosis (microbial patterns that mirror host phylogeny) may have occurred multiple times in cnidarian holobiont evolution, although this has yet to be tested. While bacterial phylosymbiosis of Scleractinia and Octocorallia has been documented throughout the South-West Pacific 52 – 54 we posit that it may have occurred not only throughout Cnidaria, but repeatedly across geographically distinct ocean basins. Additionally, there are significant community signals of cnidarians residing across shallow and deeper depths, with deeper colonies hosting less diverse microbial assemblages. Further, depth strongly influenced microbial dissimilarity not only in Scleractinia, but across Cnidaria. Relative abundance of Cnidarian microbiota Core communities of microbial genera were repeatedly identified across Cnidaria, with their relative abundance primarily influenced by host phylogeny and depth (Fig. 5a ). Given that the ‘core microbiome’ has been proposed as important for holobiont resilience 20 , 58 , we identified smaller proportions of ‘core microbiota’ in shallow water scleractinian corals, that are often more susceptible to environmental changes, than in shallow water Actinarians and Alcyonaceans, which can be more resilient. Shallow Octocorallia exhibited greater microbial richness and higher core relative abundances when compared to phylogenetically older and deeper lineages, suggesting that these core microbiomes were repeatedly assembled across shallow water lineages 57 , 59 . Surprisingly, tissue core microbiomes (averaged to cnidarian family) consisted of only 0–10 ASVs that were present in all colonies per site (Fig. 5b ). The taxonomic identity of these ASVs was highly conserved, exhibiting depth and cnidarian order fidelity, suggesting potentially important functional roles for these microbial families across Cnidaria (Fig. 5c ). This expands previous findings that scleractinian microbiomes are highly individualistic 60 , 61 , and are dominated by rare sequences 23 , 62 , suggesting that this finding is common for many cnidarians, who potentially exhibit a high degree of functional redundancy across their stable microbial component. Prevalence and specificity of Endozoicomonas Of all microbial families detected across Cnidaria, Endozoicomonas was not only the most prevalent, it was also one of the most ubiquitous globally and consistently present at different depths (Figs. 2 − 5 ). Therefore, Endozoicomonas may play an important role in healthy cnidarian microbiomes. Endozoicomonas are metabolically versatile 63 – 65 and may translocate vitamins to their host 66 . While Endozoicomonas occur in close proximity to Symbiodiniaceae in coral tissue 67 , 21.4% of the Endozoicomonas sequences in our dataset were identified from cnidarian samples that did not host Symbiodiniaceae, with 28.7% of all sequences identified isolated from non-scleractinian samples. Further, comparing the Illumina MiSeq subset of sequences (V4 library), demonstrated that octocorals in the Caribbean, Mediterranean, and Indo-Pacific not only hosted the greatest absolute abundance of Endozoicomonas , but these sequences were shared across more samples, compared to any other cnidarian. Both specialist and generalist strains of Endozoicomonas exist within Anthozoa, suggesting a variable genetic component that has the potential for coevolution with their hosts 41 , 52 – 54 , 62 similar to that of Symbiodiniaceae 68 . We expanded this observation and revealed patterns of switching in host specificity between Anthozoa and non-Anthozoa (including Cubozoa, Hydrozoa, Scyphozoa, and Porifera; Fig. 6a ), as well as within Anthozoa, specifically forming multiple highly conserved associations with Alcyonacea and Rhizostomeae (Fig. 6b ), in addition to fidelity to body compartment and ocean body (Fig. 6c ). Potentially beneficial core microbiota We identified additional common core microbiota across both tissue, skeletal, and mucus samples with potential functional importance. Pseudoalteromonas , a genus well-known as a producer of antimicrobials 17 , exhibits co-phylogeny with Scleractinia, as does Alteromonas 62 . Spirochaetes dominate some octocoral communities and may be involved in nutrient cycling 69 . While these bacteria have been previously identified as being relatively abundant or core members of many scleractinian and octocoral species, here we demonstrate that other cnidarians host these bacteria, hinting at their potential functional importance across Cnidaria. Additionally, we identified other bacteria that may be of functional importance but require further examination. For example, Synechococcus and Prochlorococcus , in the cyanobacterial genus GpIIa, commonly occur in cnidarian microbiomes 60 , as well as being abundant in marine water columns 70 , and therefore may be a sampling artifact. It is also important to experimentally determine whether Propionibacterium is a naturally abundant microbe or a sequencing kit contamination 49 , 50 . Although, by comparing these core microbiota to commonly found methodological contaminants i.e., Propionibacterium , we have increased the confidence that these bacterial genera may not be contaminants. Potentially detrimental core microbiota In this study, we analyzed microbiomes sampled from putatively ʻhealthyʼ cnidarians, focusing on original datasets that did not mention observation of stress or anthropogenic disturbance(s), although this does not discount the possibility that some data may have come from stressed corals or emerging dysbiosis. Many of the bacterial genera that appeared as core members of ‘healthy’ tissue and skeletal microbiomes have been connected to anthropogenic stress, or are potential disease-causing microbes, including Vibrio, Mycoplasma, Sphingomonas , Candidatus Pelagibacter, and Pelomonas 34 , 71 – 74 . The presence of these genera was significantly increased with clustered sequence identification, indicating greater variability in these bacteria between samples. The prevalence and abundance of these microbes could potentially indicate non-virulent symbioses that could become rapidly virulent depending on microbe-microbe competition or fluctuation 74 , 75 , or that many phenotypically ʻhealthyʼ corals are experiencing underlying dysbiosis 76 . Symbiodiniaceae microbiota Few of the microbiota from cultured Symbiodiniaceae also occurred in the cnidarian samples. Pseudomonas , for example, which was identified as a core bacterial genus in cnidarians, also occurred as a core intracellular microbe of Symbiodiniaceae 77 . Pseudomonas co-occurs with Symbiodiniaceae globally 78 , indicating a functional, or conserved symbiosis with both cnidarians and Symbiodiniaceae. This could explain the coculturing benefits of Symbiodiniaceae with Pseudomonas in laboratory studies 79 . Conversely, most other microorganisms that were identified as being part of the core microbiome of cultured Symbiodiniaceae 77 , 80 , 81 were not detected in cnidarian samples. Potentially, the microbiomes of cultured algae differ from those of non-cultured Symbiodiniaceae, or there may be a minimal introduction of novel bacteria through the acquisition of Symbiodiniaceae on coral reefs. This incongruity reiterates the urgency for exploration into Symbiodiniaceae phycospheres and microbiomes 82 , 83 , especially given the critical role of Symbiodiniaceae in the survival of many cnidarians. Summary This study provides important and fundamental insights into our understanding of how cnidarian microbiomes are structured globally. Cnidarian microbiomes are incredibly complex and integrating datasets can potentially enable identifying specific prokaryotic communities to focus future research on their functional role in cnidarian holobionts. The analysis also expanded our knowledge of prokaryotic communities across non-scleractinian cnidarians, which complements our understanding of the role and relevance of microbes within scleractinian corals. Because our data analysis demonstrated that clustering-based sequence pipelines are variable and depend on the cnidarian and microhabitat examined, we recommend that future cnidarian microbiome studies utilize unique sequence analysis. The current review focused primarily on a subset of the available data. Utilizing the entire database requires future investigations into the potential bias in sample storage, sequencing, and processing protocols. Given the current threats posed to cnidarians worldwide, our study provides a global, speciose, microbiome baseline for ‘healthy’ corals. With this baseline, we can begin to elucidate the impacts of stress-associated dysbiosis, in addition to addressing a myriad of ecological questions regarding the structuring of cnidarian microbiomes."
} | 5,006 |
39801293 | PMC11725763 | pmc | 5,440 | {
"abstract": "ABSTRACT Harnessing in situ microbial communities to clean‐up polluted natural environments is a potentially efficient means of bioremediation, but often the necessary genes to breakdown pollutants are missing. Genetic bioaugmentation, whereby the required genes are delivered to resident bacteria via horizontal gene transfer, offers a promising solution to this problem. Here, we engineered a conjugative plasmid previously isolated from soil, pQBR57, to carry a synthetic set of genes allowing bacteria to consume terephthalate, a chemical component of plastics commonly released during their manufacture and breakdown. Our engineered plasmid caused a low fitness cost and was stably maintained in terephthalate‐contaminated soil by the bacterium \n P. putida \n . Plasmid carriers efficiently bioremediated contaminated soil in model soil microcosms, achieving complete breakdown of 3.2 mg/g of terephthalate within 8 days. The engineered plasmid horizontally transferred the synthetic operon to \n P. fluorescens \n in situ, and the resulting transconjugants degraded 10 mM terephthalate during a 180‐h incubation. Our findings show that environmental plasmids carrying synthetic catabolic operons can be useful tools for in situ engineering of microbial communities to perform clean‐up even of complex environments like soil.",
"introduction": "1 Introduction As global plastic production continues to rise, so does the demand of raw materials for plastic manufacture. Polyethylene terephthalate (PET) plastic has an annual global production that surpasses 85 million metric tons, and is ubiquitous in packaging and textile industries (Urbanek, Kosiorowska, and Mirończuk 2021 ). Alongside other polyester‐based plastics such as polybutylene terephthalate (PBT) used as a thermal insulator (De Vos et al. 2021 ), PET is comprised of terephthalate (TPA) monomers, in addition to ethylene glycol (EG). The uses of TPA are not limited to polymer synthesis, as it is also used as an elastomer and plasticiser to enhance material formulation and properties (Pophali et al. 2007 ; Verma, Prasad, and Mishra 2014 ). The chemical production of TPA requires a purification step that yields purified TPA and wastewater, and this wastewater is contaminated with a range of aromatic hydrocarbons, primarily TPA with concentrations as high as 500 mg/L (Lee and Han 2014 ). The release of untreated TPA‐contaminated wastewater into soil ecosystems poses an environmental threat due to its toxicity (Daramola, Aransiola, and Adeogun 2011 ; Ball, McLellan, and Bhat 2012 ). Additionally, TPA release can arise from in situ biodegradation of TPA‐containing polyester plastics by microorganisms (Goel et al. 2014 ; Yoshida et al. 2016 ; Farzi, Dehnad, and Fotouhi 2019 ; Roberts et al. 2020 ). Microbial biodegradation and consumption of TPA offers a promising potential solution to TPA contamination. Bacteria such as Comamonas sp. E6, \n Rhodococcus jostii \n RHA1, or \n Pseudomonas umsongensis \n sp. G016 have all been reported to degrade and consume TPA (Sasoh et al. 2006 ; Hara et al. 2007 ; Narancic et al. 2021 ), and TPA‐degrading operons have been found bioinformatically across diverse bacterial taxa (Salvador et al. 2019 ; Gautom et al. 2021 ). The use of an anaerobic microbial community to treat TPA‐contaminated wastewater have shown effective decontamination (Li et al. 2022 ). However, whether such microbial bioremediation of TPA would work in more complex natural environments, such as soils, remains unclear. The addition of exogenous microorganism(s) to a natural environment, in order to introduce or modify existing community traits, referred to as bioaugmentation, can be effective for a range of applications in soil environments including nitrogen fixation (Brophy et al. 2018 ; Wen et al. 2021 ), phosphorous bioavailability (Vassileva et al. 2010 ; Pang et al. 2024 ) and bioremediation of organic pollutants (Top et al. 1998 ; Mrozik and Piotrowska‐Seget 2010 ; Gao et al. 2015 ; Ren et al. 2018 ), synthetic polyesters (Yip et al. 2024 ) or heavy metals (Pande et al. 2022 ; Atuchin et al. 2023 ). Notably, bioaugmentation for bioremediation can enable clean‐up of already contaminated environments ( in situ bioremediation). Compared with physicochemical methods for pollutant removal (e.g., soil washing, incineration, chemical oxidation), bioaugmentation offers a cheaper and less disruptive alternative (Garbisu et al. 2017 ). Two main types of bioaugmentation for bioremediation exist, cellular and genetic bioaugmentation. The former introduces the bioremediation trait within a focal microorganism that itself then performs the breakdown of the pollutant, while the latter introduces the genes for the bioremediation trait encoded upon a mobile genetic element within a donor microorganism which can both perform breakdown and transfer the bioremediation trait to neighbouring cells (recipients) (Figure 1A ). The resident native microbiota in any given natural environment is likely to be well‐adapted and occupy multiple niches providing high colonisation resistance (Khan et al. 2021 ). As such, introduced exogenous microorganisms frequently experience low survival (Ramos, Duque, and Ramos‐Gonzalez 1991 ; De Rore et al. 1994 ; Top et al. 1998 ; Ronda et al. 2019 ). It has been hypothesised, therefore, that genetic bioaugmentation may be more effective than cellular bioaugmentation in natural communities because it does not rely upon long‐term persistence of the exogenous microbe provided it is resident long enough to transfer the mobile genetic element to resident microorganism(s) (Garbisu et al. 2017 ). Indeed, experimental evidence of stable maintenance of the pollutant‐degrading genes upon a mobile element despite rapid extinction of the donor microorganism has been reported (Dejonghe et al. 2000 ; de Lipthay, Barkay, and Sørensen 2001 ; Inoue et al. 2012 ; French, Zhou, and Terry 2020 ). FIGURE 1 (A) Left panel represents genetic bioaugmentation where upon donor inoculation the plasmid carrying the catabolic genes is horizontally transferred (via conjugation) to the resident members of the community. Upon acquiring the catabolic genes, the resident microbiome transforms the pollutant to biomass thus achieving bioremediation. Right panel represents cellular bioaugmentation where the inoculated bacterium is responsible for the conversion of pollutant into biomass. (B) Top, TPA‐degrading operon architecture; bottom, TPA biodegradation pathway, TPA is imported into the cell via tphK where it is converted to 1,2‐dihydroxy‐3,5‐cyclohexadiene‐1,4‐dicarboxylate (DCD) by tphA \n 1 \n A \n 2 \n A \n 3 and then into protocatechuic acid (PCA) by tphB . PCA enters central metabolism via the Krebs cycle. Image made using Biorender. Genetic bioaugmentation mimics the natural evolutionary process of horizontal gene transfer (HGT), which enables rapid adaptation by microorganisms to environmental fluctuations through acquisition of novel traits from neighbouring cells (Bottery 2022 ), including those for dealing with pollutant accumulation in soil (Springael and Top 2004 ) and catabolic operons (Molbak et al. 2003 ; Shintani et al. 2006 ; Siddavattam, Yakkala, and Samantarrai 2019 ). Like natural HGT, genetic bioaugmentation has taken advantage of diverse mobile genetic elements for transferring traits, including phage transduction and plasmid conjugation. Conjugative plasmids, equipped with the machinery required for conjugation ( tra , mob and oriT ), are particularly attractive tools for genetic bioaugmentation because they can carry large genetic cargos, including multiple entire multigene operons. For instance, the TOL plasmid pWW0 contains the catabolic operon for toluene and xylene utilisation (Kasai, Inoue, and Harayama 2001 ), and the NAH plasmid is equipped with naphthalene‐degrading enzymes (Ono et al. 2007 ). Successful implementation of genetic bioaugmentation using conjugative plasmids has been reported across a range of plasmids, donors, microbial communities and terrestrial environments (Top et al. 1998 ; Jussila et al. 2007 ; Filonov et al. 2010 ; Inoue et al. 2012 ; Gao et al. 2015 ; Yip et al. 2024 ). Engineering natural plasmid backbones isolated from the target environment is likely to have several advantages over using model plasmids typically used in molecular biology. Such advantages include having been previously selected in nature to conjugate efficiently in the environmental substrate which is likely to be more complex than laboratory media (e.g., soils) and having evolved host ranges that are suitable for spreading into common taxa within the resident microbiota. However, the large size of environmental plasmids (on average > 100 kbp Smillie et al. 2010 ]) complicates genetic manipulation (e.g., isolation and transformation). Interestingly, streamlined versions of environmental plasmids with a fraction of their natural size can propagate effectively in complex microbiomes (Brophy et al. 2018 ; Aparicio et al. 2022 ). To promote effective genetic bioaugmentation for in situ pollutant degradation an ideal plasmid vector would have a high conjugation rate, to enable plasmid spread before the donor becomes extinct, and a minimal fitness cost, to prevent lowering the recipients' fitness upon plasmid acquisition in the chosen environmental context, as well as a broad host range, ensuring wide dissemination of the new trait in the native resident community. pQBR57 is a natural mercury resistance encoding megaplasmid (307 kbp) isolated from the sugar beet rhizosphere in Oxfordshire (Lilley et al. 1994 ) and has a broad host range, encompassing Burkholderias , Pseudomonales , Xanthomonadales , Sphingobacteria , Rhizobiales and Paenibacillus (Hall et al. 2020 ). pQBR57 has a high conjugation rate and minimal fitness cost in \n Pseudomonas fluorescens \n , enabling the plasmid to spread within soil communities through interspecies conjugation (Hall et al. 2015 ; Kottara et al. 2021 ). Crucially, pQBR57 is also amenable to genetic manipulation (Hall et al. 2021 ), enabling the insertion of new genetic cargos. Here we explore the potential of the environmental conjugative plasmid pQBR57 to act as a genetic bioaugmentation vector. Firstly, we engineered pQBR57 to encode a synthetic TPA‐degrading operon, tph , and tested its functionality in soil microcosms using \n Pseudomonas putida \n as the donor species. The operon, herein referred to as KAB operon, is composed of a TPA transporter ( tpa K \n ) from Pseudomonas mandelli , and terephthalate dioxygenases ( tph A 2 , tphA3 ), reductase ( tphA1 ) and dehydrogenase ( tph B \n ) from Comamonas sp. E6 (Werner et al. 2021 ; Kincannon et al. 2022 ) (Figure 1B ). We show that \n P. putida \n with pQBR57‐KAB can grow on TPA in both liquid media and soil microcosms and also confirm that this results in the depletion of TPA in situ . Furthermore, we demonstrate conjugative transfer of pQBR57‐KAB in soil microcosms from \n P. putida \n to \n P. fluorescens \n and confirm that a substantial fraction of the plasmid recipients gained the ability to grow on and degrade TPA. In summary, we demonstrate the utility of using an environmental conjugative plasmid encoding synthetic catabolic operon for genetic bioaugmentation in soil.",
"discussion": "4 Discussion TPA is an environmental pollutant associated with PET plastic manufacture and breakdown. Here, we have built a genetic bioaugmentation vector using a synthetic catabolic operon (KAB) and an environmental plasmid (pQBR57), and further demonstrated the bioremediation function, maintenance and interspecies transfer of this plasmid in TPA‐contaminated soil microcosms. Our findings support the utility of genetic bioaugmentation using engineered environmental plasmids for in situ genetic engineering of soil microbiomes to enhance their bioremediation potential. While the use of environmental plasmids for genetic bioaugmentation has been previously reported (Garbisu et al. 2017 ), most studies are limited to the native catabolic operons found naturally in environmental conjugative plasmids (Cycoń, Mrozik, and Piotrowska‐Seget 2017 ). Expanding the function of environmental plasmids with new bioremediation properties via genetic engineering could greatly expand the range of pollutants to target, for instance, Ke et al. ( 2022 ) knocked‐in an amidase leading to expansion the catabolic substrate range of plasmid pDCA‐1. However, integration of a complete catabolic operon to equip an environmental plasmid with bioremediation properties is, to the best of our knowledge, reported for the first time in this study. Genetic bioaugmentation relies on two pillars, (i) transfer and (ii) transconjugant expression of the catabolic payload (Ikuma and Gunsch 2013 ), which were both experimentally validated in this study. The transfer of pQBR57‐KAB from \n P. putida \n to \n P. fluorescens \n was demonstrated in soil (Figure 5A ). \n P. fluorescens \n is a highly proficient plasmid host capable of stably maintaining and transferring conjugative plasmids to indigenous soil communities (Crowley et al. 1996 ; Sarand et al. 2000 ) acting as a hub for HGT. As such, \n P. fluorescens \n could drive higher rates of plasmid spread within complex soil communities via secondary transfer, which has been previously reported for other microbiome engineering plasmids (Ronda et al. 2019 ). Transconjugant expression of the catabolic payload was validated by the ability of \n P. fluorescens \n pQBR57‐KAB to degrade and utilise TPA in minimal media (Figure 5B,C ). Consumption of TPA by \n P. fluorescens \n has not been reported previously, and as such our findings demonstrate that gaining pQBR57‐KAB can convert previously nonbioremediating species into bioremediating ones. Unexpectedly, \n P. fluorescens \n pQBR57‐KAB transconjugants varied markedly in their ability to immediately degrade TPA, but the mechanism for this variation is yet unknown. All tested isolates were confirmed to be carrying the plasmid by PCR (Figure S6 ), suggesting that plasmid loss cannot explain the observed variation. One possibility is that \n P. fluorescens \n pQBR57‐KAB transconjugants required physiological or evolutionary adaptation to enable them to utilise TPA for growth. This hypothesis is potentially supported by the extended lag phase observed in our transconjugant growth assays, which is substantially longer and more variable for \n P. fluorescens \n than for \n P. putida \n (Figure S7 ). It is possible that supplementation of the media with an additional carbon source could have accelerated the gain of TPA degradation, as observed in a previous study focused on toluene degradation by \n P. fluorescens \n (Ikuma and Gunsch 2013 ). The plasmid pQBR57 was isolated from soil (Lilley et al. 1994 ) and is known to have a relatively low fitness cost (Hall et al. 2015 ). Addition of the KAB operon to pQBR57 had no effect on the fitness cost of carrying the plasmid in the absence of TPA (Figure 3B ), suggesting that encoding and expressing this additional genetic material did not comprise a substantial bioenergetic burden for host cells. Crucially, however, the KAB operon conferred a large fitness benefit in the presence of TPA, enabling plasmid carriers to use this carbon source for growth and biomass production, leading to higher total bacterial population densities in TPA‐contaminated soil (Figure 4B ) alongside complete bioremediation of TPA from the contaminated soil substrate (Figure 4C ). Accordingly, the pQBR57‐KAB plasmid was maintained at higher frequencies in TPA‐contaminated soil (Figure 4D ). The combination of no additional fitness cost without TPA and high fitness benefits with TPA suggest that pQBR57‐KAB is a promising genetic bioaugmentation system for use in complex natural environments, such as soil. By contrast, we observed a lower interspecies conjugation rate with the addition of the KAB operon (Figure 3A ), which may indicate barriers to acquisition of plasmids containing the KAB operon that manifest only in \n P. fluorescens \n but not in \n P. putida \n recipients. Nevertheless, this effect was not apparent in soil, where the difference in transconjugants count did not differ between pQBR57 and pQBR57‐KAB (Figure 5A ). The increase in plasmid transfer in the presence of TPA is similar to increased transfer previously reported for other bioaugmentation plasmids across a range of pollutants whose degradation provides plasmid carriers with a ‘privatised’ nutrient (e.g., 2,4‐dichlorophenoxyacetic acid: Top et al. 1998 , toluene; Ikuma and Gunsch 2013 ). Notably, increased transfer with selection is not observed for plasmids that carry resistance traits, such as mercury resistance, due to the selective agent killing potential recipients and thus negating opportunities for conjugation (Stevenson et al. 2017 ). Variants of pQBR57 with higher than wild‐type conjugation rates without higher costs have been experimentally evolved by Kottara et al. ( 2016 ) and could potentially be employed to boost the efficiency of genetic bioaugmentation. Alternatively, further genetical engineering of pQBR57‐KAB to add genes that facilitate cell‐to‐cell contact such as adhesins (Robledo et al. 2022 ) or are involved in biofilm formation (Hausner and Wuertz 1999 ; Ghigo 2001 ) could potentially boost conjugation rate, however closer contacts could promote contact‐dependent killing mechanisms potentially reducing transconjugants (Lin et al. 2022 ). Genetic bioaugmentation vectors must carefully balance their catabolic efficiency against the potential costs of expressing heterologous traits in naïve hosts, which could limit their spread. Here, we used a medium strength constitutive promoter ( Pem7 ) to control the KAB operon on a low copy number plasmid (1–2 copies per cell), which provided appreciable rates of TPA catabolism at a negligible fitness cost in \n P. putida \n . Specifically, \n P. putida \n pQBR57‐KAB achieved complete depletion of 10 mM TPA after 100‐h of incubation in liquid media (Figure 2C ) and 3.2 mg/g TPA after 8 days in soil microcosms (Figure 4C ). More rapid depletion of TPA has been reported with other genetic systems in other studies. Werner et al. ( 2021 ) placed a chromosomal KAB operon under the control of a strong constitutive promoter ( Ptac ) in \n P. putida \n , achieving complete degradation of 45 mM TPA within 36 h in liquid media. In addition, Gonzalez et al. ( 2023 ) used a high‐copy number plasmid encoding the KAB operon regulated by a protocatechuate‐inducible promoter in \n P. putida \n , achieving complete depletion of 10 mM TPA within 24 h in liquid media. Importantly, none of these previous studies assessed the fitness costs of high‐level KAB expression nor tested TPA catabolism in the context of bioremediation in a more complex and relevant environment, as demonstrated here for soil. It is highly likely that high levels of expression of catabolic genes will boost bioremediation at the expense of incurring high fitness costs, which could limit the spread of the function in communities by reducing both donor and transconjugant fitness causing plasmid carriers to be more rapidly outcompeted. At the other end of the spectrum, plasmids with low expression of the catabolic payload (minimal fitness cost) can be stably maintained and result in long‐term bioremediation rates (Gao et al. 2015 ). Genetic bioaugmentation strategies must balance the speed of bioremediation and the fitness cost in diverse natural communities. In nature, catabolic plasmids may preferentially conjugate into and be maintained by slow‐growing microorganisms (Varner et al. 2022 ) which might indicate that low expression constructs could be preferred in the long run. Our study demonstrates the utility of engineering environmental plasmids with synthetic catabolic operons to achieve efficient bioremediation in model soil microcosms. Release of genetically modified strains and plasmids is tightly regulated at present, limiting the use of genetic bioaugmentation approaches reliant upon genetically engineered plasmids, to contained‐use applications. Notably, we observed substantially higher rates of maintenance and interspecies conjugation of pQBR57‐KAB in TPA‐contaminated soil, suggesting that the plasmid's long‐term persistence may be limited once a site is fully bioremediated, although these long‐term dynamics require further study. A potentially promising route to application in the short‐term may be to deploy pQBR57‐KAB for bioremediation in closed systems that ensure biocontainment, such as bioremediation of materials ex situ (i.e., where contaminated material is removed for bioremediation off‐site) or in self‐contained wastewater bioreactors, where the requisite removal of viable GM strains can subsequently be performed. Engineered environmental plasmids could therefore play an important role in reducing pollution by xenobiotics released during manufacturing and waste processing."
} | 5,283 |
39558473 | PMC11949745 | pmc | 5,441 | {
"abstract": "Abstract Field studies of cleaning mutualisms use a variety of methods to quantify behavioral dynamics. Studies in marine systems typically utilize data recorded by human observers on scuba or snorkel or via remote underwater video. The effects of these different methods on cleaner–client behaviors have not been rigorously assessed. We quantified cleaner–client interactions at 13 bluestreak cleaner wrasse ( Labroides dimidiatus ) cleaning stations in Moorea, French Polynesia using hand‐held and remote videos. We found that cleaning, cheating, and client posing rates, cleaning duration, and client species richness were all greater in the remote than in the hand‐held videos, suggesting that human presence disrupts cleaning interactions by inducing antipredator responses among clients. Some metrics, such as the ratio of cleaner chasing to cleaning behavior and the cleaners' benthic feeding rate, were higher for the hand‐held than the remote videos, possibly due to limited access of cleaners to clients in the presence of humans. Other metrics, such as cleaner and client chasing rates, the ratio of cleaning to cheating behaviors, and the duration of cleaner chases, did not differ between video types. Finally, piscivorous clients were far more abundant in the remote than the hand‐held videos, suggesting that piscivores are particularly sensitive to human presence, likely because they are targeted by fishers. Overall, our study suggests that human presence can bias studies of cleaning behavior and cleaner–client interactions, and that remote cameras should be used to conduct behavioral studies. These potential biases should be considered when interpreting existing behavioral data.",
"introduction": "1 INTRODUCTION A variety of methods are used to quantify animal behaviors and to understand their causes and consequences. Each method has its own strengths and weaknesses that can lead to biased interpretations of behavioral dynamics if not properly considered. For example, a study of foraging behavior in white capuchins compared continuous vs. interval focal sampling methods and found that while focal interval sampling was 25% more efficient, it yielded lower estimates of movement rates and foraging success than continuous sampling (Rose, 2000 ). Methodological comparisons can also reveal potential effects of human observers on animal behavior. For example, a study on humbug damselfish ( Dascyllus aruanus L.) found that some of their behaviors were quantified more efficiently by direct diver observation, while other behaviors were more effectively measured with remote video observations (Branconi et al., 2019 ). Understanding how these methodological differences shape estimates of different behavioral metrics is crucial for properly interpreting behavioral data and comparing different studies. In marine cleaning mutualisms a “cleaner” (typically a small fish or shrimp) benefits nutritionally by removing ectoparasites or dead skin from a “client” (typically a larger fish), which benefits from reduced parasite loads (Grutter, 1999 ; Grutter & Lester, 2002 ) and tactile stimulation that lowers its stress levels (Losey & Margules, 1974 ; Soares et al., 2011 ). Cleaning interactions occur worldwide in temperate and tropical marine environments (Grutter, 2002 ) among a wide range of cleaner species. Cleaning interactions are most common in the tropics and usually involve wrasses (fishes in the family Labridae), gobies (fishes in the genus Elacatinus), and decapod shrimps (in the families Palaemonidae and Hippolytidae) (Cote, 2000). Of these cleaning species, the most well‐known and well‐studied is the bluestreak cleaner wrasse Labroides dimidiatus (Valenciennes 1839). \n Labroides dimidiatus are a model system for studying the behavioral ecology of mutualisms (Bshary & Würth, 2001 ; Kuwamura, 1984 ; Potts, 1973 ) and are found throughout the Indo‐Pacific, where they establish cleaning stations in specific locations on coral reefs. Like many mutualisms, cleaning mutualisms can become parasitic (Cheney & Côté, 2005 ) if cleaners cheat by feeding on a client's healthy tissues, which are often more nutritious than dead skin or ectoparasites (Grutter & Bshary, 2003 ). To dissuade cleaners from cheating and encourage mutually positive interactions, clients have evolved control mechanisms such as punishment (chasing the cleaner as retaliation for being cheated) and partner switching (leaving the cleaner after being cheated) (Bshary & Grutter, 2005 ). However, client species vary in their ability to enact these control mechanisms (Bshary & Grutter, 2002 ). For example, piscivorous clients can inflict more severe punishments than non‐piscivorous clients by eating the cleaner rather than just chasing it. Similarly, transient clients (species with large home ranges encompassing multiple cleaning stations) can switch cleaners more easily than can resident clients, whose small home ranges may only cover a single cleaning station. Accordingly, cleaning mutualism dynamics can vary significantly between client species and across different environmental contexts (Bansemer, Grutter & Poulin, 2002 ). Thus, in situ behavioral observations are essential to document this variation and better understand its causes and consequences (Grutter & Poulin, 1998 ; Kuwamura, 1976 ). Researchers have used a variety of methods to quantify the complex behavioral dynamics of cleaning mutualisms in the field. Historically, most observations of cleaners involved a human observer, either on scuba or snorkel, that followed the cleaner around and recorded their interactions with clients (Kuwamura, 1984 ; Potts, 1973 ). However, in recent years, studies have often utilized remote video observations to quantify cleaning dynamics in the absence of an observer (Rose et al., 2020 ; Titus et al., 2017 ). Both methods have potential advantages and disadvantages. Specifically, observations by a mobile observer may yield greater overall coverage of cleaning activities than remote video observations because the observer can follow the cleaner across the reef. However, if potential clients alter their behavior in the presence of humans, this could bias the cleaning dynamics quantified by human observers. Numerous studies have shown that human presence can significantly affect the behavior of marine fish by inducing antipredator responses (Samia et al., 2019 ), yet it is unclear how this might affect cleaner–client interactions. In this study, we quantified interactions between cleaners and clients on 13 cleaning stations in Moorea, French Polynesia using two observational methods: hand‐held and remote videos. We then compared multiple behavioral metrics between the two methods to evaluate how they differ in documenting cleaning mutualisms. Our results suggest that studies that rely on observations by divers or snorkelers may be substantially biased.",
"discussion": "4 DISCUSSION Cleaning, cheating, and client posing rates were greater in the remote videos than in the hand‐held videos. This pattern is probably driven by the presence of a human observer in the hand‐held videos, who likely discouraged clients from interacting with cleaners. Human presence is widely known to induce behavioral changes in fishes, mainly through heightened antipredation responses (Samia et al., 2019 ). If potential clients view a snorkeler (or diver) as a possible threat, they may be less inclined to interact with cleaners since doing so could put them at greater risk of capture. Additionally, transient clients may leave a cleaning station entirely when snorkelers are present, while resident clients may exhibit heightened wariness, both of which would lower cleaner–client interaction rates. This may be especially true for client posing rates, since posing involves a fish altering the position or orientation of its body (e.g., by opening its mouth, flaring its fins/operculum, turning upright/sideways, etc.), which may make the client more vulnerable to predation. This could also explain why client posing rates were almost four times greater in the remote than hand‐held videos, while cleaning and cheating rates were only two times greater. This interpretation that cleaner–client interactions were adversely affected by human presence is further supported by the observation that many piscivorous client species were not recorded at all in the hand‐held videos, and that the relative interaction frequency for piscivores in the remote videos was eight times greater than in the hand‐held videos. Piscivores are especially sensitive to the presence of humans, likely because they are frequently targeted by fishers (Russ & Alcala, 1996 ; Stallings, 2009 ). Indeed, piscivores were relatively rare in the fish surveys, comprising only a small portion of the overall fish community. However, the use of human observers in conducting these fish surveys could itself negatively bias estimates of piscivore abundance so this may be an underestimate of piscivores' actual community composition. Overall, our results strongly suggest that human presence can disrupt cleaning interactions by inducing client fear responses, and that certain species, like piscivores, are especially susceptible. Another important methodological difference between the two video types is that the remote videos had a fixed frame of view while the hand‐held videos had a mobile frame of view. This explains why cleaners were present for an average of 82% of time in the hand‐held videos but only 52% of time in the remote videos. It is noteworthy, however, that the remote videos were recorded facing the section of the cleaning station where we had previously observed the most cleaning activity. This was done to maximize our chance of observing cleaner–client interactions, but by only observing the high‐activity portions of cleaning stations, the behavioral estimates from the hand‐held videos might be biased. The strength of this bias will depend on the spatial variation in cleaner–client interactions (e.g., inside vs. outside the remote frame of view). Although we lack quantitative data on the fine‐scale distribution of cleaning interactions around cleaning stations, our observations suggest that while some areas are clearly preferred, cleaners still often roam throughout their cleaning stations and interact with clients opportunistically. Spatial variation in cleaner behaviors may also explain the observed patterns in benthic feeding. Benthic feeding is relatively rare in Labroides dimidiatus (Côté, 2000 ; Potts, 1973 ). If benthic feeding and cleaning occur on different portions of the reef, then the limited frame of view of the remote camera might have missed most benthic feeding events, leading to artificially low benthic feeding rates in the remote videos. Alternatively, this behavior could be caused by human observers altering client fishes' behavior. Specifically, if the presence of a snorkeler induced fear responses in the clients, then the cleaners may have responded by temporarily shifting to another foraging strategy. This partial abandonment of cleaning mutualisms in favor of benthic feeding has been observed previously in Labroides dimidiatus living in strongly tidal environments where access to clients is limited (Dunkley et al., 2020 ). Unfortunately, we do not have data to discriminate between these two hypotheses, nor are they mutually exclusive (i.e., both may contribute to the pattern). Overall, it is clear that methodological differences between the two video types lead to stark differences in certain behavioral metrics. We gained additional insights into cleaner behavioral dynamics by examining the relationships between different cleaner–client behaviors across the two video types. For example, there was a significant positive correlation between cleaning rates and client posing rates. This is unsurprising, given that clients pose to signal their intent to be cleaned (thus greater posing rates should lead to greater cleaning rates). By contrast, cleaning rates and cleaner chasing rates were not significantly correlated, suggesting that increased chasing by cleaners does not necessarily lead to more cleaning. Together, these results suggest that clients are choosy when interacting with cleaners, preferring to be cleaned on their own terms (i.e., by posing to initiate cleaning) rather than under duress (i.e., after being chased by a cleaner). High levels of choosiness have previously been documented among clients of Labroides dimidiatus and serve as partner control mechanisms to reduce cheating by cleaners (Bshary & Noë, 2003 ). Interestingly, cleaning rates were also positively correlated with cheating rates in our videos, suggesting a constant ratio of cleaning to cheating (e.g., for every two cleans there is one cheat) and that clients may tolerate high cheating rates if cleaning rates are also high. Cleaners that cheat frequently and rarely clean no longer provide a net benefit to their clients and are likely avoided altogether. Altogether, these results suggest that client choosiness plays an important role in shaping overall behavioral dynamics. Our study revealed that remote and hand‐held videos can lead to different interpretations of cleaner–client interactions due to the effects of human observers and differences in the camera's frame of view. Although both factors likely contribute to differences in behavioral metrics, we suspect human presence in the hand‐held videos is the main driver and that the hand‐held videos are substantially biased by this effect. Field‐based behavioral studies of Labroides dimidiatus conducted by human observers on scuba or snorkel are common in the literature (Bshary & Würth, 2001 ; Dunkley et al., 2020 ; Grutter, 1996 ; Kuwamura, 1984 ; Ros et al., 2011 ; Slobodkin & Fishelson, 1974 ). Yet the effects of human presence on cleaning interactions often receive little consideration, typically referenced only when justifying methods intended to reduce disruptions to cleaning, such as maintaining a minimum distance from the cleaner and allowing a short acclimation period. While these measures likely help, they probably do not fully ameliorate the disruptive effects of human presence. Our results suggest that human observers can have a significant impact on behavioral dynamics and should be actively considered when designing behavioral studies and interpreting the resulting data. The magnitude of these biases may also vary among localities, e.g., human‐induced effects (and the associated biases) may be minimal in no‐take marine reserves, where fish perceive little threat from humans, but large in areas open to fishing, where fish perceive greater risk. Indeed, one study found that cleaners in a no‐take marine reserve interacted with more large client fish, including commercially targeted species, than cleaners at a nearby site open to fishing (Silvano et al., 2012 ). Additionally, our study highlights the context‐dependent nature of cleaning mutualisms and the complex behavioral dynamics governing these interactions. We suggest that future studies of cleaning mutualisms should limit the use of human observers, and other studies should examine how variation in predation risk affects the benefits and dynamics of cleaner–client interactions."
} | 3,836 |
25056811 | PMC4108913 | pmc | 5,448 | {
"abstract": "The potential for production of chemicals from microalgal biomass has been considered as an alternative route for CO 2 mitigation and establishment of biorefineries. This study presents the development of consolidated bioprocessing for succinate production from microalgal biomass using engineered Corynebacterium glutamicum . Starch-degrading and succinate-producing C. glutamicum strains produced succinate (0.16 g succinate/g total carbon source) from a mixture of starch and glucose as a model microalgal biomass. Subsequently, the engineered C. glutamicum strains were able to produce succinate (0.28 g succinate/g of total sugars including starch) from pretreated microalgal biomass of CO 2 -grown Chlamydomonas reinhardtii . For the first time, this work shows succinate production from CO 2 via sequential fermentations of CO 2 -grown microalgae and engineered C. glutamicum . Therefore, consolidated bioprocessing based on microalgal biomass could be useful to promote variety of biorefineries.",
"discussion": "Discussion Microalgal biomass of C. reinhardtii is a remarkable carbohydrate feedstock to provide the carbon sources for microbial fermentations. Often separate hydrolysis and fermentation (SHF) or simultaneous saccharification and fermentation (SSF) process have been applied for production for the production of bioethanol 22 23 . However, additional enzyme loading at either SHF or SSF process could be a crucial bottleneck for economically feasible bioprocess to produce value-added chemicals or biofuels 24 . Thus, consolidated bioprocessing was suggested as an alternative strategy that microbial strain is capable of producing enzyme for saccharification and producing the target chemicals such as biofuels from lignocellulosic biomass 25 26 . In this study, we suggested another type of consolidated bioprocessing based on microalgal biomass. A succinate-producing C. glutamicum strain was capable of degrading starch by secreting α-amylase and successfully fermented microalgal biomass and produce succinate without amylase additions. BL-1- pBlAmyS (0.28 g/g) strain and its fermentation of showed remarkable yield of succinate production due to the utilization of soluble starch that C. glutamicum wild type is not able to consume. This consolidated bioprocessing based on microalgal biomass with the best strain BL-1- pBlAmyS does not require additional costs for loading enzymes but produce the high yield of succinate, compared to the succinate producer BL-1. Furthermore, efficient hydrolysis of soluble starch and co-uptake of other carbohydrates and their cooperative sugar metabolisms could be useful to ensure faster cell growth of C. glutamicum and higher production of succinate. Metabolic engineering by optimizing gene expression of AmyS from B. licheniformis could be possible by tuning translation strengths on ribosomal binding site or changing different signal peptides. Additional sugar transporters and hydrolytic enzymes could be necessary to uptake unused carbohydrates in the total sugars because 10% of total sugars in microalgal biomass were not fermentable. In addition to extensive studies on sugar metabolism 27 , pentose-sugar fermentations of engineered C. glutamicum have been well investigated 28 29 . Current synthetic platform (CoryneBrick 29 ) for the gene expression in this study can be easily expanded for additional gene expression of targets. Also, application of cell display system 20 (i.e. the B. subtilis PgsA and C. glutamicum PorC protein as anchor) of target amylases in C. glutamicum could be alternative to increase hydrolysis of soluble starch and production of succinate. Microalgal biomass was shown to serve as an efficient carbon source for the microbial production of succinate, which is considered as a platform chemical, when suitably engineered strains were used which are capable of starch degradation by the secretion of amylases. Ultimately, consolidated bioprocessing based on microalgal biomass offers another options to resolve issues of alternative energy resources, global warming, human health and food security."
} | 1,030 |
32955149 | PMC8359318 | pmc | 5,449 | {
"abstract": "Summary An anaerobic enrichment with CO from sediments of hypersaline soda lakes resulted in a methane‐forming binary culture, whereby CO was utilized by a bacterium and not the methanogenic partner. The bacterial isolate ANCO1 forms a deep‐branching phylogenetic lineage at the level of a new family within the class ‘ Natranaerobiia ’. It is an extreme haloalkaliphilic and moderate thermophilic acetogen utilizing CO, formate, pyruvate and lactate as electron donors and thiosulfate, nitrate (reduced to ammonia) and fumarate as electron acceptors. The genome of ANCO1 encodes a full Wood–Ljungdahl pathway allowing for CO oxidation and acetogenic conversion of pyruvate. A locus encoding Nap nitrate reductase/NrfA ammonifying nitrite reductase is also present. Thiosulfate respiration is encoded by a Phs/Psr‐like operon. The organism obviously relies on Na‐based bioenergetics, since the genome encodes for the Na + ‐Rnf complex, Na + ‐F1F0 ATPase and Na + ‐translocating decarboxylase. Glycine betaine serves as a compatible solute. ANCO1 has an unusual membrane polar lipid composition dominated by diethers, more common among archaea, probably a result of adaptation to multiple extremophilic conditions. Overall, ANCO1 represents a unique example of a triple extremophilic CO‐oxidizing anaerobe and is classified as a novel genus and species Natranaerofaba carboxydovora in a novel family Natranaerofabacea .",
"introduction": "Introduction In view of the possibility of an early soda ocean (created by CO 2 weathering of Na/K‐rich basalt crust of volcanic origin) in the geological history of Earth and Mars and a probability of the same in the current ocean on Europa, there is an interest in astrobiology of the existing haloalkaline environments on Earth, such as terrestrial soda lakes and deep sea serpentinization area (Kempe and Kazmierczak, 2002 ; Herschy et al ., 2014 ; Fox‐Pawel et al ., 2016 ). One of the potential common substrates for extraterrestrial microbes would be CO, which can form by photolysis of CO 2 under strong UV radiation (King, 2015 ). Modern saline‐alkaline soda lakes represent rare examples of stable highly alkaline natural habitats due to the presence of high concentrations of soluble sodium carbonates, which can reach molar concentrations in hypersaline soda lakes. Such lakes are located in arid areas characterized by a hot climate with long periods of evaporative salt concentration (Schagerl, 2016 ). Thus, prokaryotes thriving in soda lakes often exhibit triple extremophilic circumstances, i.e. halo‐alkalo‐thermo‐phily (Mesbah et al . 2007 , 2009 ; Sorokin et al ., 2017 ). Extensive knowledge has been accumulated in the past three decades on the functionally important microbial communities in soda lakes, both by culture‐dependent (Sorokin et al ., 2015 ; Grant and Jones, 2016 ; Sorokin, 2017 ) and culture‐independent molecular approaches (Vauvorakis et al ., 2016 ; 2018 ; Zorz et al ., 2019 ). However, several pieces of the puzzle are still missing. In particular, whether anaerobic carbon monoxide oxidation (carboxydotrophy) is possible under extremely haloalkaline conditions. Aerobic carboxydotrophy has been shown for a group of highly salt‐tolerant soda lake alkaliphiles belonging to two closely related genera Alkalispirillum/Alkalilimnicola of the Gammaproteobacteria (Hoeft et al ., 2007 ; Sorokin et al ., 2010). The only anaerobic isolate reported as capable of CO oxidation at high pH is the acetogenic Alkalibaculum bacchii , a nonhalophilic, alkalitolerant member of the Eubacteriaceae family ( Firmicutes ), isolated from soil (Allen et al ., 2010 ; Liu et al ., 2012 ). Three major types of anaerobic carboxydotrophy have been established: by acetogens via the Wood–Ljungdahl pathway, resulting in CO 2 , acetate and/or ethanol; by methanogens, resulting in methane or acetate; and by hydrogenogens, resulting in H 2 and CO 2 (Diender et al ., 2015 ). Since protons are the final electron acceptors of hydrogenogens, the hydrogenogenic metabolism is highly improbable under soda lake conditions, while both acetogenic and methanogenic CO utilization are possible. There is a fourth (marginal) pathway of anaerobic carboxydotrophy, the direct anaerobic oxidation of CO in presence of a suitable electron acceptor, but it has not yet been well studied, except for sulfate‐reducing conditions, exemplified by Desulfotomaculum species (Parshina et al ., 2010 ) and Archaeoglobus fulgidus (Henstra et al ., 2007 ). Our previous attempts to directly enrich either acetogenic or methanogenic CO‐utilizing haloalkaliphiles from soda lakes at mesophilic conditions and low salinity (0.6 M total Na + , pH 10, 30°C and 0.2 atm CO in the gas phase) resulted in a positive acetogenic enrichment consisting of five clostridia members distantly related to the genera Anaerobranca and Dethiobacter . However, efforts to further enrich the consortium failed and the culture was eventually lost. Recently, another trial was undertaken to find out whether CO could replace formate/H 2 as the electron donor for triple extremophilic methyl‐reducing methanogens of the class Methanonatronarchaeia found in hypersaline soda lakes (Sorokin et al ., 2017 , 2018 ). Methane was indeed formed in such enrichments but not directly by methanogens. Instead, a triple extremophilic anaerobic bacterium capable of utilizing CO as the electron donor was responsible for the initial CO conversion. Its phenotypic, phylogenetic and genomic properties are described in this article.",
"discussion": "Discussion Strain ANCO1 represents the first example of an extremely haloalkaliphilic CO‐utilizing anaerobe. It is a member of a deep‐branching phylogenetic lineage in the phylum Firmicutes , class ‘ Natraanaerobiia ’, which currently consists of only three genera found in soda lakes: the extremely salt‐tolerant genera Natranaerobius and Natronovirga (Mesbah et al ., 2007 ; Mesbah and Wiegel, 2009 ) and a moderately salt‐tolerant genus Natranaerobaculum (Zavarzina et al ., 2013 ). All of them are moderately thermophilic, obligately anaerobic fermentative heterotrophs with potential for anaerobic respiration, and in these the new member of this branch, strain ANCO1, is most similar to Natranaerobius thermophilus , which is also evident from the genome analysis (see Supporting Information Table S1 ). However, the ability to utilize CO as electron donor has not been reported for any of the ANCO1 relatives and the available genomes from the Natranaerobius species lack the respective genetic potential for such metabolism. The CODH/ACS cluster in ANCO1 is similar to that of other thermophilic carboxydotrophs, like Moorella thermoacetica and Carboxydothermus hydrogenoformans (Fig. 5 ). The main product of CO conversion by strain ANCO1 is acetate, similar to what is observed in M. thermoacetica (Drake and Daniel, 2004 ). Thermophilic carboxydotrophs M. thermoacetica and C. hydrogenoformans lack the RnF‐complex and employ energy converting hydrogenases (Ech) in order to generate a cation gradient and produce ATP (Wu et al ., 2005 ; Schuchmann and Müller, 2014 ). Although a CODH‐hydrogenase like gene‐cluster is found in the genome of ANCO1 (Fig. 4 ), the absence of clear hydrogen production suggests it is not employing it. In addition, this cluster does not show the typical Ech structure, indicating that in contrast to other CO‐utilizing thermophiles, ANCO1 uses the Rnf‐complex for its energy metabolism. Despite the presence of soluble hydrogenases encoded in the genome, strain ANCO1 was unable to grow acetogenically on H 2 /CO 2 or use H 2 as electron donor for anoxic respiration. The strain did produce minor amounts of H 2 when grown on pyruvate. This raises the question why strain ANCO1 is able to use CO but not H 2 to drive acetogenesis. A possible reason are the thermodynamic constrains imposed during H 2 ‐dependent acetogenesis – the fact that the standard redox potential of the pair 2H + +2e − /H 2 (≈ −400 mV) is not sufficiently negative to reduce ferredoxin, demands for bifurcation mechanisms to perform CO 2 reduction in the WLP (Schuchmann and Müller, 2012 ; Buckel and Thauer, 2013 ). Utilization of CO (with a substantially lower standard redox potential, i.e. E 0' (CO 2 /CO) ≈ −520 mV) circumvents this bottleneck, and ferredoxin can be directly reduced via CODH. If ANCO1 is unable to link H 2 ‐oxidation to ferredoxin reduction via a bifurcating hydrogenase, this would explain the absence of acetogenic growth with H 2 /CO 2 . The H 2 that is produced during growth on pyruvate might originate from Fe‐only hydrogenases using ferredoxin as donor, and favouring the hydrogen producing reaction direction (Adams 1990 ). As ANCO1 encodes for a HDCR‐like complex (ACONDI 00243‐00246 and 02919‐02924), the WLP appears to be H 2 ‐dependent in this strain. Hydrogen production via Fe‐only hydrogenases with ferredoxin (derived from CO oxidation) might play a role in introducing the reduction equivalents via the HDCR‐like complex into the WLP. Such internal cycling of hydrogen by acetogens has been observed before from organic substrates such as fructose (ref. Wiechmann et al ., 2020 ). To note that activity of HDCR‐like complex in ANCO1 was not confirmed experimentally in this study, it is also possible that formate alternatively originates from bifurcating cytoplasmic enzymes that require NAD(P)H and ferredoxin, similar to what is observed in Clostridium autoethanogenum (Wang et al ., 2013 ). In this case, H 2 would not be required to drive the WLP, allowing operation on CO without intermediate H 2 production. The potential roles for hydrogenases and their role in acetogenesis are depicted in Fig. 4 (dotted red lines). Overall, with current information, we can only speculate on the H 2 metabolism of strain ANCO1 and more biochemical research is required to further elucidate this. Regarding anaerobic respiration, the ability to utilize fumarate and thiosulfate as the electron acceptors is reported for Natranaerobius thermophilus and Natranaerobaculum magadiense , although succinate formation from fumarate was not measured. But the genome of N. thermophilus does contain the genes coding for fumarate reductase and thiosulfate reductase (Nther_2664‐2665 and Nther_0643‐0644, respectively) with the highest similarity to the ones present in ANCO1 genome. What is questionable, however, is the universal ability for the DNRA in the whole ‘Natranaerobiia’ members described previously. The reasons for doubts are the following: (i) formation of ammonia as the final product was not analysed in Natranaerobius truperii and Natronovirga and (ii) genes encoding for respiratory nitrate reductases (Nar/Nap) and the NrfAH‐type multiheme cytochromes c are not present in the genomes of both Natranaerobius species (genomes of Natronovirga and Natranaerobaculum are not available). Therefore, this important mode of anaerobic respiration currently cannot be assumed as a common trait? in this group. It is also questionable that as much as 20 mM nitrate was used in the tests with the ‘ Natranaerobiia ’ members. Our experience with ANCO1 showed that the complete ammonification is inhibited at far lower nitrate concentrations. Furthermore, the inability of ANCO1 to directly utilize nitrite for DNRA is also intriguing, pointing out that there is a problem. The root of this ‘sluggishness’ might lay in the unusual modularity of the DNRA system in this Gram‐positive bacterium. The classical ammonifying nitrite reductase consists of the periplasmic catalytic pentaheme c NrfA and its electron donor tetraheme c NrfH, which is an integral membrane quionol‐dehydrogenase (Simon and Klotz, 2013 ). In ANCO1, only the NrfA subunit is present, which is also a part of a locus containing a truncated Nap nitrate reductase lacking its cytochrome c containing electron donating NapB and NapC. Such deviations from the classical structures might be related to the facts that (i) ANCO1 does not have a periplasm, and (ii) that it does not have the respiratory quinones, which normally serve as the immediate electron donors for the periplasmically located respiratory complexes. Therefore, the only available low‐redox potential electron donors in ANCO1 appears to be produced in the cytoplasm [ferredoxins and NAD(P)H]. This could explain the difficulties with the DNRA growth we observed in ANCO1, particularly that the nitrite reduction was only possible after initiation of growth either by pyruvate fermentation or at fumarate‐reducing conditions. This might have been necessary to build up the required low redox potential electron donor pool for nitrate/nitrite reduction. Regarding the ability for DNRA reported previously in the H 2 /CO‐utilizing acetogens (REFS), it looks like that this is rather complex. At least in two documented cases ( Moorella thermoacetica and Clostridium ljungdahlii ) the ammonification of nitrate/nitrite does happen, however, no evidence for genes encoding multicytochrome c type of ammonifying Nir (NrfA) are present in the genomes. Instead, the cytoplasmic assimilatory NADH‐dependent NirB seems to operate as the electron think rather resembling ‘dump of electrons’ in fermentative prokaryotes (Seifritz et al ., 2003 ; Pierce et al ., 2008 ; Emerson et al ., 2018 ). Therefore, such process is fundamentally different from the respiratory DNRA. Taxonomy Based on the phylogenomic analysis and unique phenotypic properties, we suggest to classify strain ANCO1 into a new genus and species Natranaerofaba carboxydovora , which forms a new family Natranaerofabaceae within the class ‘ Natranaerobiia ’. Natranaerofabaceae fam. nov Natr.an.ae.ro.fa.ba.ce'ae. N.L. fem. n. Natranaerofaba a bacterial genus; − aceae ending to denote a family; N.L. fem. pl. n. Natranaerofabaceae , the family of Natranaerofaba . The family includes obligately anaerobic, acetogenic, extremely haloalkaliphilic bacteria living in hypersaline soda lakes. It is a member of class ‘Natranarobiia’, phylum Firmicutes . The family consists of a single genus and species Natranaerofaba carboxydovora . The type genus is Natranaerofaba . Natranaerofaba gen. nov Natr.an.ae.ro.fa'ba N.L. neut. n. natron , derived from Arabic natrun soda (sodium carbonate); Gr. pref. an‐ , not; Gr. masc. n. aer , air; L. fem. n. faba , bean; N.L. fem. n. Natranaerofaba , bean‐shaped soda loving anaerobe. The genus includes obligately anaerobic acetogenic bacteria with bean‐shaped cells. The polar lipids are dominated by diethers with phosphocholine and phosphoglycerol polar heads. They are extremely halophilic and obligately alkaliphilic moderate thermophiles capable of anaerobic respiration. They can utilize CO and pyruvate during acetogenic growth and formate and lactate in presence of thiosulfate, fumarate or nitrate as electron acceptors. Form a deep‐branching lineage within the class ‘ Natranarobiia ’, phylum Firmicutes . The type species is Natranaerofaba carboxydovora . Family classification: Natranaerofabaceae . Natranaerofaba carboxydovora sp. nov car.bo.xy.do.vo'ra L. pref. carboxydum , carbon monoxide; L. v. voro , to devour, consume; L. fem. adj. carboxydovora , consuming carbon monoxide. Cells possess a Gram‐positive type of cell wall and are bean‐shaped rods, 0.4 × 3–6 μm, motile by peritrichous flagella. Endospore formation is not observed, but the potential is present in the genome. Polar lipids include phosphocholines and phsphoglycerols, with the most common core components being mostly present as ether‐bound C 14:0 and plasmalogen‐derived aiC 17:0 . Respiratory lipoquinones are not present. The species is strictly anaerobic and heterotrophic acetogen capable of anaerobic respiration. Acetogenic growth is possible with pyruvate and CO as the electron donors with production of acetate/lactate and acetate/formate as products respectively. Anaerobic respiration is possible with CO, pyruvate, formate and lactate as donors and fumarate and thiosulfate (2‐electron reduction) as the electron acceptors. Lactate is converted to acetate. Formate also supports anaerobic growth with nitrate as acceptor resulting in formation of ammonia. Yeast extract is utilized as a C‐source. Obligately alkaliphilic with a pH range for growth between 9 and 10.5 and an optimum at pH 9.5–9.7. Extremely salt‐tolerant with a total Na + range for growth from 2.5 to 4.5 M (optimum 3.5–4 M). Moderately thermophilic with a temperature range of 35–56°C and an optimum at 48–50°C. The type strain was obtained from anaerobic sediments of a hypersaline soda lake in Kulunda Steppe (Altai region, Russia). DNA G + C is 35.3 mol% (genome). Type strain is ANCO1 T (DSM 108926). The EMBL/GenBank genome accession number is CP054394. [Correction added on 24 March 2021, after first online publication: The DSM collection number has been corrected in this version for accuracy.]"
} | 4,256 |
35860530 | PMC9290524 | pmc | 5,451 | {
"abstract": "Plants have evolved diverse strategies for foraging, e.g., mycorrhizae, modification of root system architecture, and secretion of phosphatase. Despite extensive molecular/physiological studies on individual strategies under laboratory/greenhouse conditions, there is little information about how plants orchestrate these strategies in the field. We hypothesized that individual strategies are independently driven by corresponding genetic modules in response to deficiency/unbalance in nutrients. Roots colonized by mycorrhizal fungi, leaves, and root-zone soils were collected from 251 maize plants grown across the United States Corn Belt and Japan, which provided a large gradient of soil characteristics/agricultural practice and thus gene expression for foraging. RNA was extracted from the roots, sequenced, and subjected to gene coexpression network analysis. Nineteen genetic modules were defined and functionally characterized, from which three genetic modules, mycorrhiza formation, phosphate starvation response (PSR), and root development, were selected as those directly involved in foraging. The mycorrhizal module consists of genes responsible for mycorrhiza formation and was upregulated by both phosphorus and nitrogen deficiencies. The PSR module that consists of genes encoding phosphate transporter, secreted acid phosphatase, and enzymes involved in internal-phosphate recycling was regulated independent of the mycorrhizal module and strongly upregulated by phosphorus deficiency relative to nitrogen. The root development module that consists of regulatory genes for root development and cellulose biogenesis was upregulated by phosphorus and nitrogen enrichment. The expression of this module was negatively correlated with that of the mycorrhizal module, suggesting that root development is intrinsically an opposite strategy of mycorrhizae. Our approach provides new insights into understanding plant foraging strategies in complex environments at the molecular level.",
"conclusion": "Conclusion Our cross-ecosystem transcriptomics approach provides new insights into understanding gene-environment interactions in plant foraging strategies by defining the three gene coexpression modules for mycorrhiza formation, PSR, and root development. The constancy of the relative expression levels of module member genes among the genotype site combinations suggests that the genetic modules defined by this approach are robustly regulated across ecosystems and that their regulatory systems are conserved at the species level. Our findings have important implications for conservation agriculture. The identification of soil and plant factors that drive the foraging modules would enable us to reduce the environmental impacts of agriculture by manipulating the factors, e.g., by balancing fertilizer input, improving soil physical conditions, and inoculating with AM fungi. Moreover, although the genotypic variation in module expression (i.e., differences in absolute expression levels of the modules) has not been investigated in detail in this study, it is of interest to characterize genotypes based on, e.g., capability of acquiring more nutrients from organic fractions and/or via the mycorrhizal pathway. For this purpose, eigengenes are applicable as a metric to evaluate genotypic performance in field-grown plants, which would contribute to breeding programs in selecting genotypes for low-input food production.",
"introduction": "Introduction Plants have evolved diverse strategies for the acquisition of mineral nutrients, in particular nitrogen (N) and phosphorus (P). Approximately 400 Mya, early plants without a functional root system associated with arbuscular mycorrhizal (AM) fungi to acquire water and nutrients ( Simon et al., 1993 ; Remy et al., 1994 ; Redecker et al., 2000 ; Humphreys et al., 2010 ). This assisted plant terrestrialization and thus is the most ancient strategy of land plants for root foraging. Fungi are associated with more than 70% of modern land plants ( Brundrett and Tedersoo, 2018 ) and construct hyphal networks in soil, facilitating an extensive surface area for water/nutrient acquisition, that is, the mycorrhizal pathway ( Smith and Read, 2008 ). P and N deficiencies trigger the secretion of plant hormone strigolactones into the rhizosphere ( Yoneyama et al., 2012 ), which promotes contact of fungal hyphae with roots by stimulating hyphal branching ( Akiyama et al., 2005 ). After physical contact, fungal hyphae penetrate into the cortex and form highly branched hyphal termini “arbuscules” where nutrient exchange occurs between symbionts. Briefly, inorganic phosphate (Pi), nitrate (NO 3 – ), and ammonium (NH 4 + ) are taken from the soil by extraradical hyphae, delivered to the arbuscules, and released into the arbuscular interface (reviewed in Ezawa and Saito, 2018 ) from which plant cells take nutrients via mycorrhiza-specific transporters for Pi ( Rausch et al., 2001 ; Harrison et al., 2002 ), NO 3 – ( Wang et al., 2020 ), and NH 4 + ( Koegel et al., 2013 ). In return, the host supplies organic carbon as carbon source for fungi (reviewed in Salmeron-Santiago et al., 2022 ). Briefly, lipids ( Bravo et al., 2017 ; Jiang et al., 2017 ; Keymer et al., 2017 ; Luginbuehl et al., 2017 ) and sugars ( Helber et al., 2011 ) are exported via the putative lipid exporter (i.e., a complex of the half-sized ABC transporters STR and STR2) ( Zhang et al., 2010 ) and members of the sugar transporter SWEET gene family ( An et al., 2019 ), respectively. The morphological plasticity of roots is an important part of plant foraging strategies given that roots provide another major pathway for nutrient uptake, that is, the root-direct pathway. NO 3 – - and NH 4 + -enriched patches induce the localized proliferation of lateral roots for efficient capture of nutrients ( Drew, 1975 ), which is triggered by NO 3 – and NH 4 + uptake via the plasma membrane NITRATE TRANSPORTER 1 (NRT1) ( Remans et al., 2006 ; Ho et al., 2009 ) and AMMONIUM TRANSPORTER (AMT) ( Lima et al., 2010 ), respectively. Lateral root formation is, however, inhibited under severe N deficiency, because saving carbon in resource-limited environments is an essential trait for survival ( Araya et al., 2014 ). Pi patches also promote localized proliferation of lateral roots ( Drew, 1975 ). P deficiency generally inhibits primary root growth but increases lateral root growth and density, leading to a shallow root system ( Williamson et al., 2001 ; Gruber et al., 2013 ). Root hairs also play a significant role in Pi uptake by enlarging the contact surface area for the soil solution ( Gahoonia et al., 2001 ). Physiological responses for Pi acquisition under low Pi conditions, known as Pi starvation response (PSR), are also important strategies and have extensively been studied. Pi availability in soil is generally low because a large part of P is present as sparingly soluble inorganic salts and organic P that are unavailable for plants ( Shen et al., 2011 ). Under such conditions, i.e., plants upregulate the high-affinity Pi transporter genes of the Pht1 family to enhance root uptake capability, secrete non-specific acid phosphatase and organic acids to increase the soil Pi pool, and replace phospholipids with sulfo- and galactolipids to accelerate internal Pi recycling, which are typical PSRs (reviewed in Plaxton and Tran, 2011 ). Despite extensive molecular/physiological studies on individual strategies under controlled laboratory/greenhouse conditions, there is little information about how plants orchestrate these strategies in the field, that is, in complex and changing environments. Plants are likely to upregulate the genes responsible for PSR, mycorrhiza formation, and root development in parallel under P-deficient conditions. It is unknown, however, how plants prioritize (i.e., modulate resource allocation to) these strategies to optimize the overall efficiency under various levels of P deficiency. N deficiency would reduce the relative value of P even at low P availability ( Johnson, 2010 ) and thus downregulate genes for PSR and root development. Genes for mycorrhiza formation, however, may not be downregulated by N deficiency, because both P and N could be acquired through the mycorrhizal pathway. Disentangling such complex gene-environment interactions under field conditions is a great challenge but will contribute not only to understanding the regulatory mechanism of plant foraging strategies but also to sustainable intensification of agriculture, e.g., by improving Pi-use efficiency ( Plaxton and Tran, 2011 ) and mycorrhizal function ( Rillig et al., 2016 ). Recently, transcriptomics has been applied to several field studies in plant science: temporal/seasonal changes in the transcriptome ( Nagano et al., 2012 , 2019 ) and responses to fertilizers ( Yu et al., 2018 ) and drought stress ( Varoquaux et al., 2019 ). Particularly, the application of transcriptomics followed by weighted gene-coexpression network analysis (WGCNA) leads to the identification of genetic modules for, e.g., microbial symbioses ( Varoquaux et al., 2019 ; Wu et al., 2019 ) and photosynthesis ( Varoquaux et al., 2019 ). Here, we have established a novel approach, cross-ecosystem transcriptomics; transcriptomes of mycorrhizal roots (i.e., dual transcriptomes of roots naturally colonized by AM fungi) are obtained from plants grown in physically, chemically, and biologically diverse environments and subjected to WGCNA; then, module–environment and module–module interplays are analyzed. This will lead to a comprehensive understanding of plant foraging strategies in the context of plant-microbe-environment interactions at the molecular level. Maize ( Zea mays L.) is one of the most important cereal crops worldwide, serving as staple food, livestock feed, and industrial raw material. Most importantly, this crop establishes a mutualistic association with AM fungi and is grown across a wide range of environments/ecosystems, which led us to employ maize as the first model for this approach. We collected plant and soil samples across the United States Corn Belt and Japan; the former achieves the world’s highest productivity with the typical high-input agricultural system, whereas agricultural practice varies regionally in the latter because of diversity in climate and edaphic properties. It was expected that this sampling strategy would provide broad environmental gradients that cannot be provided by greenhouse/laboratory experiments. The present study addressed the following two hypotheses; (i) root foraging strategies are driven by corresponding genetic modules that are upregulated in response to nutrient deficiency, in which (ii) modules involved in N acquisition are driven solely by N deficiency, while those for P acquisition depend not only on P status/availability but also on N status/availability.",
"discussion": "Results and Discussion Characterization of Field Sites/Plots The sampling plots/sites were characterized by a PCA biplot with the climatic/soil factors ( Figure 1C and Supplementary Tables 1 , 4 ). The United States sites are localized in the first quadrant, whereas the Japanese sites are localized in the other quadrants, between which annual precipitation and soil properties were largely different. Among the Japanese sites, the contents of soil organic matter, base, and clay were highly variable. Notably, there were wide gradients of N and P availability among the sites (e.g., NO 3 -N, 10.5–212 mg kg –1 ; Bray II-P, 5.3–494 mg P kg –1 ), which led us to the expectation that there would also be divergent responses of the plants to nutrient deficiency/excess. RNA Sequencing, Module Definition, and Preliminary Characterization By mRNA-Seq, 8.4 ± 0.25 million reads on average were mapped to exons in each sample ( Supplementary Table 5 ). In a preliminary analysis, we focused on the genes involved in mycorrhiza formation because several plant genes that facilitate AM fungal colonization, particularly those involved in arbuscule development/function, are conserved in the plant kingdom ( Bravo et al., 2016 ). We first identified the orthologs of RAM2 encoding glycerol-3-phosphate acyltransferase, the key enzyme of the mycorrhiza-specific lipid biosynthetic pathway ( Bravo et al., 2017 ), Pht1;6 encoding the mycorrhiza-inducible Pi transporter ( Willmann et al., 2013 ; Sawers et al., 2017 ), and STR2 for primary analysis of expression patterns. The expression levels of STR2 were strongly correlated with those of RAM2 ( r = 0.992) and Pht1;6 ( r = 0.939) ( Supplementary Figure 1 ), indicating that the relative expression of these genes was tightly regulated across the genotypes as well as across the ecosystems/countries. This finding led us to conducting WGCNA. In the WGCNA of the 251 samples, a soft threshold power of 14 provided a scale-free topology of the network ( r 2 = 0.91) ( Supplementary Figure 2 ) and resulted in the definition of 19 coexpression modules named with color codes by the WGCNA program ( Table 1 ). These modules were functionally characterized based on enriched genes and Gene Ontology (GO) analysis ( Table 1 and Supplementary Table 6 ): cell division (black), gene expression/translation (blue), cell cycle regulation (green), stress-associated protein quality control (green–yellow), immune response/N assimilation (gray), antioxidation (gray60), branched-chain amino acid (BCAA) metabolism (light cyan), water uptake and diurnal rhythm (light green), immune response (magenta), lipid biosynthesis (midnight blue), root development (pink), two-component and phosphorelay signal transduction systems (purple), response to hypoxia (royal blue), P-starvation response (PSR) (salmon), trehalose biosynthesis (tan), and mycorrhiza formation (yellow). The functions of cyan, dark green, and dark red modules could not be defined by GO analysis or by enriched genes. In the dark green module, only the GO term oxidoreductase activity was overrepresented in addition to enrichment of several genes encoding the enzymes involved in diterpenoid biosynthesis, which was not enough information to characterize this module. No GO terms were enriched in the cyan and dark red modules. In the cyan module, many of the members encoded unknown proteins, so its function could not be defined. In the dark red module, several genes encoding ribosomal proteins were found, but it was also not sufficient information to characterize this module. It is noteworthy, however, that the dark red module showed rather consistent expression levels across the samples (i.e., across genotypes/sites), suggesting that this module has a housekeeping role. Accordingly, the dark red module was employed as control to analyze genotypic differences in module expression. TABLE 1 Enriched Gene Ontology (GO) terms and putative function of gene coexpression modules. Module (no. of gene) Enriched GO term † Putative function Black (1,574) DNA packaging, cellular component biogenesis, translation, RNA modification, auxin transport Cell division Blue (4,134) RNA splicing, ribonucleoside catabolic process, regulation of translation Gene expression/translation Cyan (86) (No enrichment) (Undefined) Dark green (46) Oxidoreductase activity (Undefined) Dark red (51) (No enrichment) (Undefined) Green (1,257) Mitotic cell cycle, protein localization, organelle organization Cell cycle regulation Green-yellow (139) Protein folding, response to stress, regulation of protein stability Stress-associated protein quality control Gray (8,460) Defense response, cellular amino acid metabolic process, immune response, response to nitrate Immune response and N assimilation Gray60 (77) Antioxidant activity, oxidoreductase activity Antioxidation Light cyan (81) Branched-chain amino acid catabolic process, mitochondrial matrix BCAA metabolism Light green (67) Water transport, rhythmic process Water uptake and diurnal rhythm Magenta (397) Defense response, immune response, response to other organisms Immune response Midnight blue (82) Lipid metabolic process, fatty acid metabolic process Lipid biosynthesis Pink (471) Cell wall biogenesis, lignin metabolic process, root morphogenesis Root development Purple (275) Phosphorelay response regulator activity Two-component and phosphorelay signal transduction systems Royal blue (60) Response to decreased oxygen levels, lactate biosynthetic process Response to hypoxia Salmon (101) Cellular response to phosphate starvation, phosphate ion transport, acid phosphatase activity, galactolipid biosynthetic process P-starvation response Tan (131) Trehalose biosynthetic process Trehalose biosynthesis Yellow (1,023) Lipid biosynthetic process, terpenoid biosynthetic process, chitinase activity Mycorrhiza formation \n † All GO terms enriched in the modules are listed in Supplementary Table 6 . \n In the subsequent analysis, we further characterized the mycorrhizal, PSR, and root development modules, because they are likely to be directly involved in nutrient foraging. We had also realized, however, that a module responsive to N starvation was not clearly defined in this analysis, which is addressed in a later section. Mycorrhizal Module The majority of genes known to participate in arbuscule development and functioning are enriched in this module; e.g., genes encoding the transcription factors RAM1 ( Gobbato et al., 2012 ), RAD1 ( Park et al., 2015 ), and WRI5 ( Jiang et al., 2018 ), Pi transporter Pht1;6, nitrate transporter NPF4.5 ( Wang et al., 2020 ), ammonium transporter AMT3;1 ( Koegel et al., 2013 ), H + -ATPase HA1 ( Krajinski et al., 2014 ; Wang et al., 2014 ), key enzymes for mycorrhiza-specific lipid biosynthesis, RAM2 and FatM ( Bravo et al., 2017 ), putative lipid exporters STR and STR2, and enzymes involved in strigolactone/mycorradicin/blumenol biosynthesis, DXS2 ( Walter et al., 2002 ; Floss et al., 2008 ), PSY2 ( Stauder et al., 2018 ), CCD7, CCD8, D27, and CCD1 ( Al-Babili and Bouwmeester, 2015 ) ( Supplementary Table 7 ). In the WGCNA, the expression levels of the modules are represented by eigengenes (PC1 scores) ( Supplementary Table 8 ), and genes that show a higher correlation coefficient between the eigengenes and their expression levels (i.e., those with higher connectivity) are, in general, considered as those that play a more important role in the module ( Langfelder and Horvath, 2008 ). In this module, STR2 (Zm00001d043722) showed the highest connectivity ( r = 0.977) ( Supplementary Table 7 ). To assess the regulatory robustness of the module across all genotype-site combinations, the module member genes were sorted by connectivity, and the expression levels of the 1st (Zm00001d033915), 50th (Zm00001d033002), and 100th (Zm00001d032267) percentile genes relative to those of STR2 were plotted ( Supplementary Figure 3 ). The levels of the 1st percentile gene were constant across the genotype-site combinations, whereas those of the 50th and 100th percentile genes showed variability in several combinations, suggesting that the relative expression levels of lower-connectivity genes may be finely and differently modulated at least in some genotypes. To address genotypic differences, the absolute expression levels (i.e., eigengenes) of the two genotypes, P2023 and LG2533, grown in the Sapporo site ( Supplementary Tables 4 , 8 ) and those of another pair of genotypes, Canberra 90EX and P2088, grown in the Nagoya site were compared with reference to the dark red module ( Supplementary Figure 4 ). Even in the same sites, the absolute expression levels of the mycorrhizal module were different between the genotypes to some extent, which could be due to the difference in nutrient status ( Supplementary Table 4 ) and/or differentiation in mycorrhizal dependency among the genotypes (e.g., Sawers et al., 2017 ). To characterize this module in relation to AM fungal colonization/functionality, we analyzed the “unmapped sequence reads” (i.e., those that were not mapped to the maize genome) that might contain AM fungal RNA reads. Generally, sequence reads obtained by mRNA-Seq contain a small number of those that originated from rRNA, which led us to the idea that the abundance of AM fungal rRNA reads relative to plant rRNA read number could represent relative fungal biomass in the roots ( Supplementary Table 9 ). It was considered, however, that fungal rRNAs that have A-rich regions were preferentially sequenced in the mRNA-Seq, because polyA-tailed RNA was purified prior to library construction, which might bias fungal rRNA read abundance and composition across the samples. To evaluate the severity of these biases in the mRNA-Seq, we chose randomly 20 samples from the 251 samples and conducted rRNA-Seq, which would provide unbiased rRNA read counts ( Supplementary Table 10 ). The correlation analysis indicated that the rRNA read counts obtained by the mRNA-Seq were highly correlated with those obtained by the rRNA-Seq, with a correlation coefficient of 0.919 ( P < 0.001) ( Supplementary Figure 5 ), indicating that the bias in read abundance is minimum. On the other hand, NMDS showed that OTU compositions in several samples were largely different between those obtained by the two sequencing methods ( Supplementary Figure 6 ), indicating that the bias in read composition is significant in some cases. Accordingly, we employed only the abundance data, but not the compositional data, for subsequent analyses. The unmapped reads were also de novo assembled, and 427,813 out of 2,495,764 non-redundant contigs were predicted as those that originated from AM fungal genes: average length, 461 bp; N50, 525 bp ( Supplementary Figure 7 ). We searched the contigs that showed similarity to the putative Pi exporter SYG1-1 , polyphosphate polymerase VTC4 , vacuolar Pi exporter PHO91 , and aquaglyceroporin AQP3 , which are likely to be involved in Pi delivery in the fungi ( Ezawa and Saito, 2018 ). Then we identified 86, 74, 159, and 105 contigs similar to SYG1-1 , VTC4 , PHO91 , and AQP3 , respectively, mapped the unmapped reads to these contigs, combined read counts within each gene, and normalized on the basis of TPM of the plant ( Supplementary Table 11 ). These expression data were subjected to multiple linear regression analysis together with the AM fungal rRNA read counts using the mycorrhizal module eigengenes as an objective variable. Among them, the read counts of rRNA, SYG1-1 , and PHO91 were significant explanatory variables for the eigengenes with correlation coefficients of 0.875, 0.15, and 0.233, respectively ( R 2 = 0.782, P < 0.001) ( Supplementary Figure 8 ), suggesting that the module eigengenes reflect functional colonization of the fungi. For further functional categorization of the 1,023 genes of this module, k-means clustering analysis was performed using correlation distance as a measure. Clustering the genes into five submodules successfully separated them into different functional groups along the principal component 2 (PC2) axis of the PCA performed using the expression data of all the module member genes ( Figure 2A , Table 2 , and Supplementary Table 12 ). In submodule 1, the majority of the essential components of arbuscule development and nutrient exchange were enriched, e.g., RAM1 , RAD1 , WRI5 , Pht1;6 , NPF4.5 , AMT3;1 , HA1 , RAM2 , FatM , STR / STR2 , and serine/threonine receptor-like kinase ARK1 ( Roth et al., 2018 ), and genes involved in membrane trafficking EXO70I ( Zhang et al., 2015 ) and Vapyrin A ( Pumplin et al., 2010 ) ( Figure 2C and Supplementary Table 7 ). The enrichment of these genes suggests that submodule 1 plays a central role in nutrient exchange across the periarbuscular membrane. In submodule 2, the GO terms fatty acid biosynthetic process and plastid were overrepresented, reflected in the enrichment of genes encoding enzymes involved in de novo biosynthesis of C16:0-fatty acid via acetyl-CoA in plastids. This suggests that submodule 2 has a role in the biosynthesis of an essential component of lipids for the construction of the periarbuscular membrane and/or for export to the fungi. In submodule 3, the GO terms isoprenoid biosynthetic process, carotenoid metabolic process, and hormone metabolic process were overrepresented; genes involved in the biosynthesis of carotenoid derivatives DXS2 , PSY2 , CCD7 , CCD8 , and D27 were enriched. In addition, the GRAS transcription factor NSP2 that regulates strigolactone biosynthesis by modulating D27 expression ( Liu et al., 2011 ) also belongs to this submodule. Therefore, it is likely that submodule 3 regulates the early processes of fungal accommodation by strigolactone production. In submodule, 4 the GO terms senescence-associated vacuole, amino sugar metabolic process, and extracellular space were overrepresented. The enrichment of genes encoding an MYB1-like transcription factor, chitinase, and cysteine protease suggests that this submodule is responsible for arbuscule degeneration/turnover ( Floss et al., 2017 ). Neither GO terms nor known genes involved in fungal accommodation/functioning were enriched in submodule 5; therefore, the biological function of this submodule could not be defined. The average connectivity of submodules 1–5 with mycorrhizal module eigengenes was 0.88, 0.72, 0.77, 0.75, and −0.59, respectively. In addition, most genes in the submodule 1 showed positive PC2 scores, while most of those in submodules 2 and 5 showed negative PC2 scores ( Figure 2B ). These results suggest that the expression of each submodule is finely and adaptively tuned in response to the environment. FIGURE 2 Functional categorization of the 1,023 genes assigned to the mycorrhizal module and into five submodules by k-means clustering analysis using correlation-based distance as a measure. (A) Principal component analysis (PCA) plot of genes in submodules 1–5 and (B) frequency distribution of PC2 score of the genes. (C) Putative function and cellular localization of genes whose orthologs have been functionally characterized in previous studies. The number of the submodule to which the genes belong is indicated in the boxes with same colors in panels (A,B) . No orthologs of the genes in submodule 5 have so far been functionally characterized; thus, they are excluded from this scheme. TABLE 2 Enriched Gene Ontology (GO) terms and putative function of the submodules of the mycorrhizal module. Module (no. of gene) Enriched GO term † Putative function Submodule 1 (332) Peptidase activity, transferase activity Nutrient exchange Submodule 2 (203) Fatty acid biosynthetic process, plastid part Fatty acid biosynthesis Submodule 3 (219) Terpenoid biosynthetic process, carotenoid metabolic process, plastid part Carotenoid biosynthesis Submodule 4 (189) Amino sugar metabolic process, defense response to fungus, extracellular space Arbuscule degeneration Submodule 5 (80) (No enrichment) (Undefined) \n † All GO terms enriched in the modules are listed in Supplementary Table 12 . \n Phosphate-Starvation Response Module This module consists of 101 genes, in which the GO terms involved in PSR, e.g., cellular response to Pi starvation, Pi transport, acid phosphatase activity, and galactolipid biosynthetic process, were overrepresented ( Supplementary Table 6 ). Pht1;3, one of the four Pi transporters in this module, is likely to be responsible for the root-direct pathway ( Glassop et al., 2005 ; Nagy et al., 2006 ) in which the transporter is localized to the root epidermis and mediates Pi uptake independently of the mycorrhizal pathway ( Smith et al., 2011 ). Six genes encoding SPX (SYG1-PHO1-XPR1) domain, a sensor for the inositol polyphosphate-mediated signaling pathway for the maintenance of Pi homeostasis in eukaryotes ( Wild et al., 2016 ), were also enriched in this module; one encodes the Pi exporter PHO1 ( Wege et al., 2016 ) and the other five encode SPX-domain containing proteins. Many acid phosphatase genes, including those encoding purple acid phosphatase, were assigned to this module. Two orthologs of NIGT1 that encode an MYB-type transcription factor belong to this module. NIGT1 was originally identified as a repressor of NO 3 – uptake ( Maeda Y. et al., 2018 ) but was found to be playing a role in PSR by modulating the expression of SPX genes ( Medici et al., 2019 ; Ueda et al., 2019 ; Hu and Chu, 2020 ). It has been well-documented that the transcription factor PHOSPHATE STARVATION RESPONSE (PHR) plays a central role in PSR as a master regulator in Arabidopsis, a non-mycorrhizal plant ( Rubio et al., 2001 ), but recently, one of the orthologs, PHR2, was found to be also involved in the regulation of mycorrhiza formation in rice ( Shi et al., 2021 ; Das et al., 2022 ) and Lotus japonicus ( Das et al., 2022 ). In maize, so far, two orthologs of PHR have been found ( Calderón-Vázquez et al., 2011 ), but both were assigned to the gene expression/translation module in this study ( Supplementary Table 7 ), indicating the complexity of the PHR-mediated regulatory mechanism. In higher plants, including maize, Pi deficiency induces the replacement of membrane phospholipids with non-phosphorous lipids such as galactolipids and sulfolipids ( Tjellström et al., 2008 ). Genes encoding glycerophosphodiester phosphodiesterase (GDPD2) for degradation of phospholipid, monogalactosyldiacylglycerol synthase 2 (MGDG2) for biosynthesis of galactolipids, and sulfoquinovosyl transferase (SQD2) for biosynthesis of sulfolipids were assigned to this module. MGDG2 (Zm00001d031428) showed the highest connectivity, and that of SQD2 , GDPD2 , NIGT1 , and genes encoding SPX-domain containing proteins and purple acid phosphatases was also comparable to the connectivity of MGDG2 ( Supplementary Table 7 ). The expression levels of the 5th (Zm00001d026156), 50th (Zm00001d043681), and 100th (Zm00001d020985) percentile genes relative to MGDG2 expression were generally constant even in the lowest connectivity gene ( Supplementary Figure 9 ), indicating that the relative expression levels of the genes are tightly regulated across the genotypes/sites. Genotypic differences in absolute expression level also seemed minimum in this module ( Supplementary Figure 4 ). Root Development Module This module consists of 471 genes, and GO terms involved in cell wall synthesis and root development were overrepresented; e.g., plant cell wall biogenesis, cellulose synthase, cytoskeleton, root system development, root morphogenesis, and root epidermal cell differentiation ( Supplementary Table 6 ). This indicates that this module is responsible for the development of the root system, accompanying transcriptional activation of a set of genes for cell wall biogenesis. The plant cell wall is composed of the primary cell wall that supports the fundamental growth of cells and the secondary cell wall that supports the primary cell wall mechanically and facilitates water transport. CesA genes encode a cellulose synthase catalytic subunit and form cellulose synthase complexes that consist of 18–24 CesA proteins; CesA1, CesA2, CesA3, CesA5, CesA6, and CesA9 are involved in primary cell wall synthesis, while CesA4, CesA7, and CesA8 are for secondary cell wall synthesis in Arabidopsis ( Taylor et al., 2003 ; Desprez et al., 2007 ; Persson et al., 2007 ). In the maize genome, 20 CesA s have been found ( Penning et al., 2009 ), among which 11 genes, CesA1 , CesA2 , CesA4 , CesA6 , CesA7a , CesA7b , CesA9 , CesA10 , CesA11 , CesA12a , and CesA12b are assigned to this module ( Supplementary Table 7 ). In addition to the CesA s, many genes encoding polysaccharide-biosynthetic/modification enzymes, e.g., glycosyltransferases and glucanases, were also found in this module. There are 15 genes encoding the essential parts of the cytoskeleton, alpha- and beta-tubulins, and a microtubule motor protein in this module. Eighteen transcription factors, e.g., an ethylene-responsive transcription factor (ERF), five NAC-domain transcription factors, and seven MYB-domain transcription factors, are found in this module. ERF035 was expressed in regions related to cell division/differentiation, e.g., lateral roots and central cylinder of primary roots, and upregulate CesA1 in Arabidopsis ( Saelim et al., 2019 ). It has been known that many NAC- and MYB-domain transcription factors are responsible for the regulation of secondary cell wall synthesis ( Yamaguchi et al., 2008 ; Nakano et al., 2015 ) and cell division ( Willemsen et al., 2008 ) during root formation. It is noteworthy that the expression of several genes involved in root hair initiation/elongation, ROOT HAIRLESS 1 ( RTH1 ) ( Wen et al., 2005 ), RESPIRATORY BURST OXIDASE HOMOLOG 1 ( RBOH1 ) ( Mangano et al., 2017 ), and two ROOT HAIR DEFECTIVE 3 ( RDH1 ) ( Schiefelbein and Somerville, 1990 ) that belong to other modules, was also positively correlated with the expression of this module ( P < 0.05) and, interestingly, negatively correlated with that of the mycorrhizal module ( P < 0.001) ( Supplementary Table 7 ). In addition, the expression levels of 40 genes involved in auxin response and transport (e.g., those encoding auxin responsive protein/factor and auxin transporter/carrier), although most of them belong to the modules of immune response and N assimilation and cell division, were positively correlated with the eigengenes of the root development module ( P < 0.05). A gene encoding endoglucanase 2 ( EG2 , Zm00001d021304) showed the highest connectivity in the module ( Supplementary Table 7 ). The expression levels of the 5th (Zm00001d010976), 50th (Zm00001d042276), and 100th (Zm00001d006756) percentile genes relative to EG2 expression were quite constant across the genotypes/sites ( Supplementary Figure 10 ), indicating strict regulation of the module member genes. Genotypic differences in absolute expression levels seemed likely to be minimum, although the expression levels were rather variable among the individuals of the same genotypes ( Supplementary Figure 4 ). Nitrogen Starvation Response Module To explore the N starvation response module, we first searched for genes involved in the initial steps of N assimilation, and six AMT s, three NRT1 s, four NRT2 s, five genes encoding NRT1/PRT family protein (NPF), five nitrate reductase (NR) genes, one nitrite reductase (NIR) gene, six glutamine synthetase (GS) genes, four glutamate synthase (GOGAT) genes, and one glutamate dehydrogenase (GDH) gene were found to be expressed in the roots ( Supplementary Table 13 ). Among the 36 genes, six from the immune response/N assimilation (gray) module and four from the mycorrhizal module showed significant negative correlations with soil NO 3 -N levels ( P < 0.05), implying that the 10 genes were upregulated in response to low NO 3 – levels. The PC1 scores of the ten NO 3 – -responsive genes were calculated based on their expression levels, and genes whose expression levels were correlated with the PC1 scores were extracted from all genes at a criterion of | r | > 0.5 ( P < 1e –17 ) and tentatively grouped as a low-NO 3 – response module ( Supplementary Table 7 ). This module consisted of 1,436 genes, of which 982 were of the mycorrhizal module. The remaining 454 genes were those whose expression levels were highly correlated with the eigengenes of the mycorrhizal module, including two genes encoding GS root isozyme and the transcription factor ROOTLESS WITH UNDETECTABLE MERISTEMS 1 (RUM1) that initiates lateral root formation ( Woll et al., 2005 ). The eigengenes of the low-NO 3 – response module, therefore, showed a strong positive correlation with those of the mycorrhizal module ( r = 0.997). The pairwise correlation analysis between the eigengenes of the low-NO 3 – response module and soil/plant factors ( Supplementary Table 14 ), as well as the PCA biplot constructed with the correlation coefficients of the modules for the soil/plant factors ( Supplementary Figure 11 ), indicated that the response patterns of the low-NO 3 – response module to the factors were quite similar to those of the mycorrhizal module. The analyses strongly suggested that the genetic module that plays a main role in N uptake under low-NO 3 – conditions is the mycorrhizal module; thus, the low-NO 3 – response module was not considered in subsequent analyses. In contrast to NO 3 – , soil NH 4 -N levels were generally low across the plots/sites (<10 mg-N kg –1 ), except for those in the Kasai site ( Supplementary Table 4 ). Accordingly, the range of soil NH 4 -N level was too narrow to explore; thus, a module responsive to low-soil NH 4 + was not considered. Drivers of the Foraging Modules and Module–Module Interplays Pairwise correlation coefficients between module eigengenes and soil/plant factors were calculated ( Supplementary Table 14 ), and a module-factor PCA biplot was constructed based on the coefficients, considering multicollinearity among the factors ( Figure 3 ). Submodules 1–4 of the mycorrhizal module showed positive scores along the PC1 axis that explained 39.6% of the variation and were associated with lower Bray II-P and NO 3 -N in the soil and with lower leaf P and N concentrations, whereas submodule 5 and the root development module showed negative PC1 scores. The PSR module showed a high positive score along the PC2 axis that explained 36.8% of the variation and was associated with higher contents of organic matter and silt and lower leaf P:N ratios. Submodules 1 and 5 and the root development module also showed positive PC2 scores, while submodules 2 and 4 showed negative PC2 scores. To support the PCA biplot, a multiple linear regression analysis of the module eigengenes was also conducted using all factors as explanatory variables, except for one of the two factors that showed a correlation coefficient (| r |) of more than 0.9 ( Supplementary Table 3 ). Bray II-P, NO 3 -N, and clay% were the major negative factors for the mycorrhizal module among the soil factors ( Table 3 ). Bray II-P and exchangeable Ca were negative factors for the PSR module, while organic matter was a major positive factor for the module. For the root development module, clay% was a positive factor, and organic matter and exchangeable Mg were negative factors. As expected from the PCA, leaf P was a strong negative factor for the mycorrhizal module, a positive factor for the root development module, and was not a significant factor for the PSR module. Leaf P:N ratios showed contrasting effects on the mycorrhizal and PSR modules; the ratio was a strong positive driver for the mycorrhizal module but a negative driver for the PSR module. The expression levels of the mycorrhizal and PSR modules were higher in plants with larger stem diameters and in those with slower growth rates, whereas the root development module was downregulated in plants with larger stem diameters. FIGURE 3 PCA biplot of module-factor correlations. The plot was drawn based on the correlation coefficients obtained by pairwise correlation analysis between the soil/plant factors and the module eigengenes ( Supplementary Table 14 ), in which the factors leaf N, P, and P:N, Bray II-P, NO 3 -N, organic matter (OM), and silt% were selected by taking into account multicollinearity. The submodules of the mycorrhizal module were circled with yellow. Module names (functions) and colors are listed in Table 1 , and the mycorrhizal (submodules), PSR, and root development modules were indicated with bold black letters. TABLE 3 Coefficients of the soil and plant factors with the eigengenes of mycorrhizal, phosphate starvation response (PSR), and root development modules in multiple regression analysis. Module Factor Mycorrhiza PSR Root development \n Soil factor \n pH 0.072 0.200 ** 0.078 OM 0.149 * 0.476 *** −0.199 ** Bray II-P −0.198 ** −0.276 *** −0.068 NO 3 -N −0.294 *** 0.021 −0.056 K 0.040 0.276 *** −0.025 Mg −0.102 −0.069 −0.237 *** Ca −0.118 −0.533 *** 0.130 Silt% −0.165 * 0.182 ** 0.092 Clay% −0.487 *** 0.058 0.394 *** \n Plant factor \n Stem diameter 0.469 *** 0.329 ** −0.274 ** Growth rate −0.400 ** −0.676 *** 0.126 Leaf P −0.854 *** −0.153 0.369 ** Leaf N 0.019 0.019 0.207 Leaf P:N 0.641 *** −0.401 ** −0.258 Intercept −4.158 −42.407 *** −16.572 ** \n r \n 2 \n 0.642 *** 0.670 *** 0.441 *** \n Asterisks indicate significant levels (Student’s t-test): *P < 0.05; **P < 0.01; ***P < 0.001. \n To analyze module–module interplays, a gene–eigengene correlation analysis was conducted. Among the 1,023 genes of the mycorrhizal module, 598 genes, most of which belong to submodules 1 and 3, showed positive correlation coefficients with the PSR-module eigengenes ( P < 0.01) ( Figure 4A and Supplementary Table 7 ). Similarly, 51 out of the 101 PSR module genes, including most of the acid phosphatase and Pi transporter (Pht1) genes, also showed positive correlation coefficients with the mycorrhizal module eigengenes ( P < 0.01) ( Figure 4B and Supplementary Table 7 ). However, these correlations were ambiguous in the simple sample-eigengene plot of the two modules probably because of their partial correlations ( Figure 4C ). Clear negative correlations were observed between the mycorrhizal module and the root development module; the expression levels of 873 genes of the mycorrhizal module were negatively correlated with the eigengenes of the root development module, and 414 out of the 471 genes of the root development module showed negative correlation coefficients with the mycorrhizal module eigengenes ( P < 0.01) ( Figures 4D,E and Supplementary Table 7 ). In fact, the correlation coefficient between the eigengenes of the two modules was −0.439 ( P < 0.001), as reflected in the simple sample-eigengene plot ( Figure 4F ). No significant correlations were observed between the PSR and root development modules ( Supplementary Figures 12A–C and Supplementary Table 7 ). FIGURE 4 Interplay of the mycorrhizal (MYC) module with the PSR and root development (RD) modules. (A) Frequency distributions of correlation coefficients of the mycorrhizal submodule genes with PSR module eigengenes, and (B) those of the PSR module genes with mycorrhizal module eigengenes. (C) Scatter plot of the eigengenes of the mycorrhizal and PSR modules of the 251 samples, in which the samples were sorted by the order of mycorrhizal module eigengenes. (D) Frequency distributions of correlation coefficients of the mycorrhizal submodule genes with the root development module eigengenes, and (E) those of the root development module genes with the mycorrhizal module eigengenes. (F) Scatter plot of the eigengenes of the mycorrhizal and root development modules of the 251 samples, in which the samples were sorted by the order of mycorrhizal module eigengenes. The data were extracted from Supplementary Tables 7 , 8 , and all the eigengenes were standardized between –50 (minimum value) and +50 (maximum value) for plotting. The submodule numbers of the mycorrhizal module genes are indicated with the following colors: 1, dark blue; 2, turquoise; 3, purple; 4, red; 5, orange. As proposed by the first hypothesis, three genetic modules, mycorrhiza formation, PSR, and root development that were likely to be directly involved in foraging strategies, were identified. The mycorrhizal module was upregulated by P and N deficiencies in the plants, as well as by low availabilities of P and N in the soil. In contrast, the root development module responded in the opposite direction. The PSR module was mainly driven by P deficiency relative to N (i.e., leaf P:N ratios), supporting the second hypothesis. However, no specialized genetic module for N starvation response could be identified. Although a set of low-NO 3 – responsive genes was identified, most of the genes belonged to the mycorrhizal module in addition to those co-expressed with the mycorrhizal module. These results strongly suggest that, at least under NO 3 – depleted conditions, maize largely relies on mycorrhizae for NO 3 – uptake, as proposed in rice ( Wang et al., 2020 ). We consider that the differential role of mycorrhiza in the uptake of organic P and N differentiates the plant responses to P and N deficiencies. Organic P cannot be taken up directly either by plants or by AM fungi ( Shen et al., 2011 ). Accordingly, plants ( Plaxton and Tran, 2011 ) and AM fungi ( Joner et al., 2000 ; Koide and Kabir, 2000 ; Sato et al., 2019 ) evolved genes encoding phosphatases for direct mineralization and, for indirect mineralization, associated with P-solubilizing bacteria in the rhizosphere and the hyphosphere (e.g., Richardson and Simpson, 2011 ; Zhang et al., 2016 ). In contrast, although both plants and AM fungi are capable of uptaking organic N such as amino acids, the contribution of the root-direct pathway to amino acid uptake seems to be much smaller than that of the mycorrhizal pathway. This assumption is supported by the following two observations. First, amino acids in the rhizosphere turn over so rapidly that they never reach the root surface, whereas extraradical mycelia of the fungi could access amino acids in the bulk soil beyond the rhizosphere ( Jones, 1999 ). Second, amino acid uptake by roots would be primarily for retrieval of amino acids that leaked out of root cells because the efflux of amino acids from roots is not negligible and frequently exceeds their influx ( Nashölm et al., 1998 ; Näsholm et al., 2009 ). Investment in mycorrhizae, therefore, is likely to be a more efficient strategy for N acquisition under inorganic N-limited conditions. Water availability greatly affects the efficiency of nutrient uptake. The Pi taken up by AM fungal hyphae is translocated toward the roots by water flow through the hyphae, which is primarily driven by host transpiration ( Kikuchi et al., 2016 ). NO 3 – is highly mobile in soil, but the mass flow driven by transpiration sustains NO 3 – uptake by roots ( McMurtrie and Näsholm, 2018 ). In this context, it was expected that genes encoding water channels would be enriched in nutrient foraging modules to regulate water uptake. Plasma membrane aquaporins (plasma membrane intrinsic protein, PIP) are mainly responsible for water transport across the plasma membrane ( Kapilan et al., 2018 ), but six out of 13 PIP genes were enriched in the water uptake/diurnal rhythm module that is regulated independently from the nutrient foraging modules ( Figure 3 ). Furthermore, most of the PIP genes were downregulated by mycorrhiza formation ( Supplementary Table 7 ). Instead, four out of seven genes encoding nodulin 26-like membrane intrinsic protein (NIP) were enriched in the mycorrhizal module. NIP was originally identified as a major component of the peribacteroid membrane in soybean root nodules ( Rivers et al., 1997 ) and takes up ammonia from the symbiotic interface ( Niemietz and Tyerman, 2000 ). The NIP family is a group of aquaglyceroporin unique to plants ( Wallace et al., 2006 ), and in normal roots, a NIP is localized in the plasma membrane and transports a variety of uncharged solutes, e.g., arsenite ( Ma et al., 2008 ), silicon ( Ma et al., 2006 ), boron ( Takano et al., 2006 ), and urea ( Yang et al., 2015 ), with low or no water permeability ( Wallace et al., 2006 ). Alteration of the expression pattern of aquaporin genes by mycorrhiza formation has widely been studied in gramineous plants in the context of drought tolerance (e.g., Bárzana et al., 2014 ; Quiroga et al., 2019 ; Symanczik et al., 2020 ), but the upregulation of NIPs seems to be involved in ammonia/ammonium uptake from the arbuscular interface ( Uehlein et al., 2007 ). It is likely that the water uptake capability for nutrient acquisition would be tuned at the posttranslational level rather than at the transcriptional level ( Chaumont and Tyerman, 2014 ). Phosphate-starvation response and mycorrhiza formation are two major strategies for the acquisition of P in plants, but their interplay has attracted interest only recently ( Shi et al., 2021 ; Yaffar et al., 2021 ; Das et al., 2022 ; Han et al., 2022 ). The regulatory role of PHR2, both in PSR and mycorrhiza formation ( Shi et al., 2021 ; Das et al., 2022 ) was partially supported by the coexpression of some PSR genes with mycorrhizal submodules 1 and 3. It is noteworthy, however, that leaf P:N ratios drive the PSR module negatively and the mycorrhizal module positively ( Figure 5 ), suggesting that these two modules are regulated not solely by PHR2 but also at multiple levels. This differential response of the PSR module could be interpreted by the high connectivity to NIGT1 . Although this transcription factor is involved in the signaling cascade of PSR ( Maeda Y. et al., 2018 ; Ueda et al., 2019 ), it is upregulated in a NO 3 – -concentration-dependent manner ( Maeda Y. et al., 2018 ). This implies that increases in soil NO 3 – increase the expression of the PSR module by decreasing leaf P:N ratios, under which the mycorrhizal module is downregulated. The independence of the PSR module from the mycorrhizal module would facilitate an alternative (backup) strategy to cope with P deficiency when P delivery from the mycorrhizal pathway does not meet the demand because of, e.g., low population density of AM fungi, extremely low Pi availability, and presence of excess N in soil ( Shi et al., 2021 ; Das et al., 2022 ). FIGURE 5 Schematic representation of interplay among the mycorrhizal (yellow area), PSR (green area), and root development (purple area) modules with respect to plant nutrient status. Leaf P:N ratios mainly drive the mycorrhizal module positively and the PSR module negatively, although parts of the genes in the two modules are coexpressed. Higher leaf P (and N) concentrations upregulate the root development module and downregulate the mycorrhizal module, but N deficiency under P-sufficient conditions leads to higher P:N ratios and thus upregulates the mycorrhizal module. The present study demonstrated that resource allocation between roots and mycorrhizae is coordinately, rather than independently, regulated according to above-ground nutrient levels at the transcription level. The negative correlation in the expression of the root development module and the mycorrhizal module (as a function of leaf nutrient level) suggests that root development is intrinsically an opposite strategy of mycorrhizae for foraging ( Figure 5 ). It has been well-documented that increases in soil nutrient availability decrease the percent root length colonized by AM fungi by improving plant nutrient status (e.g., Menge et al., 1978 ), representing decreases in AM fungi-to-root biomass ratios. This modulation of relative fungal biomass in response to nutrient availability has traditionally been interpreted as dependency on fungi ( Treseder, 2013 ) but rarely in the context of root-mycorrhiza interplay as foraging strategies. Recently, for categorizing root resource acquisition strategies, a framework of root economic space, which is defined by mycorrhizal dependency (“collaboration gradient,” 1st dimension) and slow/fast resource return on investment (“conservation gradient,” 2nd dimension), has been proposed ( Bergmann et al., 2020 ). Interestingly, maize is located in the middle of the collaboration gradient, suggesting that maize has balanced strategies for resource acquisition via the root-direct and mycorrhizal pathways. The clear shifts between the root development and mycorrhizal modules along the leaf/soil nutrient gradients are likely to reflect the balanced strategies. The impact of mycorrhiza formation on root architecture has extensively been studied, demonstrating that the interactions are quite complex and regulated at multiple levels ( Gutjahr and Paszkowski, 2013 ). Mycorrhiza formation promotes localized proliferation of lateral roots ( Fusconi, 2013 ; Gutjahr and Paszkowski, 2013 ; Gutjahr et al., 2015 ; Yu et al., 2016 ; Chen et al., 2017 ), which is triggered by pre-symbiotic signals released from germinating spores and in response to local increases in nutrients around arbuscules ( Gutjahr and Paszkowski, 2013 ). In this study, we observed that RUM1 , a key regulator of lateral root formation, was coexpressed with the mycorrhizal module, supporting previous observations. Furthermore, RTH1 , RBOH1 , and two RDH1 that regulate root hair formation were found to be downregulated with increasing expression of the mycorrhizal module, adding further complexity to the root morphological/architectural responses to mycorrhiza formation. Modification of root hair development, however, was not examined in this study and needs to be confirmed experimentally. In the Early Devonian, AM symbiosis facilitated the terrestrialization of early plants that only had a poor root system by providing a water/nutrient uptake pathway ( Humphreys et al., 2010 ). During the Middle to Late Devonian, plants evolved a substantial root system not only for taking up water/nutrients but also for anchoring the body to the soil ( Kenrick and Crane, 1997 ). We consider that this dual functionality of the roots drove the development of the fine-tuning system for the mycorrhizal and root-direct pathways. In terms of water/nutrient uptake, these two pathways are functionally redundant. Their roles, however, could be interpreted by the cost-benefit trade-off between the enlargement of surface area for nutrient uptake and the rates (efficiency) of nutrient uptake/translocation ( Smith et al., 2011 ). The mycorrhizal pathway is mediated by fungal hyphae that are much finer than roots and longer than root hairs, which provide a larger surface area per unit carbon investment and thus enable exploration of a larger soil volume beyond the P depletion zone (e.g., Rhodes and Gerdemann, 1975 ). Therefore, under nutrient-depleted conditions where diffusion rates of nutrients toward roots are slow, plants invest more in the mycorrhizal pathway, because hyphal foraging provides more rapid nutrient capture/translocation than the root-direct pathway. In contrast, the root-direct pathway may facilitate more rapid uptake and translocation of nutrients under nutrient-enriched conditions in which the diffusion rates of nutrients are rapid enough to sustain the rapid nutrient uptake by roots. In addition to nutrient uptake, roots play an indispensable role in anchoring the plant body to the ground that mycorrhizae are unable to do, and this role becomes more important when plants grow larger under nutrient-enriched conditions. It has been suggested that gramineous plants have evolved finer roots to obtain a larger surface area per unit carbon investment, that is, toward less dependency to mycorrhizae ( Ma et al., 2018 ). Our findings suggest, however, that maize still maintains balanced strategies, that is, the fine-tuning system of the two nutrient uptake pathways, indicating the importance of the mycorrhizal pathway in foraging, even in the genotypes developed for modern agriculture."
} | 13,796 |
36530181 | null | s2 | 5,452 | {
"abstract": "A simple strategy for generating stimuli-responsive peptide-based hydrogels "
} | 19 |
27004424 | PMC4804515 | pmc | 5,453 | {
"abstract": "Background Biofilm formation is an important survival strategy of Salmonella in all environments. By mutant screening, we showed a knock-out mutant of fabR , encoding a repressor of unsaturated fatty acid biosynthesis (UFA), to have impaired biofilm formation. In order to unravel how this regulator impinges on Salmonella biofilm formation, we aimed at elucidating the S . Typhimurium FabR regulon. Hereto, we applied a combinatorial high-throughput approach, combining ChIP-chip with transcriptomics. Results All the previously identified E. coli FabR transcriptional target genes ( fabA , fabB and yqfA ) were shown to be direct S. Typhimurium FabR targets as well. As we found a fabB overexpressing strain to partly mimic the biofilm defect of the fabR mutant, the effect of FabR on biofilms can be attributed at least partly to FabB, which plays a key role in UFA biosynthesis. Additionally, ChIP-chip identified a number of novel direct FabR targets (the intergenic regions between hpaR / hpaG and ddg / ydfZ ) and yet putative direct targets ( i.a. genes involved in tRNA metabolism, ribosome synthesis and translation). Next to UFA biosynthesis, a number of these direct targets and other indirect targets identified by transcriptomics (e.g. ribosomal genes, ompA , ompC , ompX , osmB , osmC, sseI ), could possibly contribute to the effect of FabR on biofilm formation. Conclusion Overall, our results point at the importance of FabR and UFA biosynthesis in Salmonella biofilm formation and their role as potential targets for biofilm inhibitory strategies. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2387-x) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions In conclusion, we have shown that FabR is involved in Salmonella biofilm formation. In addition, we have illustrated that S. Typhimurium FabR has a limited regulon by combining ChIP-chip analysis with dedicated expression analysis. It directly controls the expression of fabA , fabB and yqfA by direct binding to their promoter regions. This confirms current knowledge generated in E. coli , but is the first evidence for the direct regulation of these genes by FabR in S. Typhimurium. Moreover, novel direct FabR targets were identified. FabB overexpression was shown to partly mimic the biofilm defect of the fabR mutant, indicating that the effect of FabR on biofilm formation can be attributed at least partly to its effect on fabB expression. Exploitation of the expression analysis data, allowed us to put forward some additional putative targets (direct and indirect) through which FabR might impact on biofilm formation. Overall, our results point at the importance of FabR and UFA biosynthesis in Salmonella biofilm formation and their role as potential targets for biofilm inhibitory strategies.",
"discussion": "Discussion In this study, we showed that the unsaturated fatty acid biosynthesis regulator FabR is involved in S. Typhimurium biofilm formation. To unravel how this regulator impinges on Salmonella biofilm formation, a combinatorial high-throughput approach, combining ChIP-chip with transcriptomics, was applied. High-throughput ChIP-chip analysis allowed the identification of in vivo FabR binding sites reflecting potential target genes (Table 2 ). Firstly, all the previously identified E. coli FabR transcriptional target genes ( fabA , fabB and yqfa ) were shown to be direct S. Typhimurium FabR targets as well, validating our approach. Direct binding to the promoter region of fabA , however, was only observed using ChIP-qPCR. The failure to detect FabR binding to this site by the ChIP-chip technique could be due to the sensitivity of the tiling array and/or stringency during the hybridization process [ 68 ] or the failure to randomly amplify this specific genomic region [ 69 , 70 ]. Secondly, ChIP-chip also identified some new, direct FabR targets, i.e. the intergenic regions between hpaR / hpaG and ddg / ydfZ . The latter two genes ( ddg and yfdZ ) are, in contrast to hpaR and hpaG , convergently transcribed, making it unlikely for FabR to exert any direct regulatory function on their expression. Thirdly, our ChIP-chip analysis also identified a number of yet putative FabR target genes (e.g. genes involved in tRNA metabolism, ribosome synthesis and translation). These might also represent real in vivo FabR targets. Together, these data indicate that FabR only has a very limited regulon under the tested conditions. This contrasts to the broad regulon of global transcriptional regulators such as H-NS (ca. 745 direct target genes) [ 43 ] or FNR (ca. 100 direct target genes) [ 71 ] and the larger regulon of more specific regulators such as the invasion regulator HilA (ca. 20 direct target genes) [ 35 ]. Combining the ChIP-chip results with transcriptomics data provided information on the biological relevance of FabR binding for the identified regions. This combinatorial approach provides the first experimental evidence that FabR directly binds to and regulates the expression of yqfA , whereas for E. coli only evidence for binding has been given [ 29 ]. Moreover, we were able to extrapolate the previously observed higher tendency of FabR towards fabB regulation as compared to fabA , from E. coli to S. Typhimurium [ 29 , 31 ]. Although the ChIP-chip and ChIP-qPCR experiments indicated FabR to bind to the hpaR - hpaG intergenic region, none of these genes were significantly upregulated in the fabR mutant. Several possible explanations have been reported before for this observed lack of correlation between ChIP-chip and transcriptomics results (e.g. [ 57 , 58 ]). Some of these might also explain transcription factor binding to the intergenic region between convergently transcribed genes (such as FabR binding between ddg / ydfZ ). In brief, the transcription factors might play other roles than regulating transcription or only have a minor impact on transcription levels. The binding sites may either serve as storage sites buffering the free pool of regulators, or have no physiological role under the given conditions, and/or depend on the presence or absence of other factors. Indeed, occupancy of a promoter region by a transcriptional regulator can be a necessary but not a sufficient condition for its transcriptional activity. In this respect, it was shown that FabR binding to the well-known fabA and fabB targets does not necessarily require unsaturated thioester ligands, but is enhanced in their presence [ 29 , 52 ]. An additional substantiation that the newly identified FabR targets are not just false positives was generated using in silico motif detection. Indeed, the hpaR / hpaG and ddg / yfdZ intergenic regions shared a common consensus motif with the previously identified FabR targets. The degeneracy of the retrieved motif (and the above mentioned ‘gap’), however, probably limit(s) the use of in silico prediction algorithms based on sequence data alone to map the FabR regulon. As we found a fabB overexpressing strain to partly mimic the biofilm defect of the fabR mutant, the effect of FabR on biofilms can be attributed at least partly to the observed enhanced expression of its direct target fabB . FabB plays a key role in UFA synthesis by catalyzing the elongation of the cis-3-decenoyl-ACP produced by FabA. In E. coli FabB overproduction has been shown to increase the synthesis of UFA’s and to enhance the UFA contents of membrane phospholipids [ 29 , 66 ]. The observation that a fabA overexpressing strain does not show this biofilm defect, although FabA and FabB catalyze two subsequent steps in the same pathway, can be explained by the assumption that FabB catalyses the rate limiting step. Indeed, in E. coli FabA overproduction was shown to increase the levels of SFA moieties rather than the levels of UFA’s, an effect that was found to be nullified when both FabA and FabB were overproduced. This indicates that FabB is the limiting step in UFA synthesis and any excess cis-3-decenoyl-ACP produced by FabA would be diverted to the saturated fatty acid synthetic pathway [ 72 ]. Different, yet elusive, links between UFA synthesis and biofilm formation can be inferred. Firstly, the alterations in membrane fatty acid composition potentially impact on surface properties (roughness, cell surface charge, hydrophobicity, exposure of certain proteins, etc. ) and biofilm formation. Membrane fluidity was indeed demonstrated to be essential in controlling swarming, a multicellular behaviour related to biofilm formation [ 73 ], and a biofilm phenotype-specific shift in membrane fatty acid composition has already been reported for S. Enteritidis [ 74 ]. Furthermore, fatty acids were also encountered in the EPS fraction of rdar-expressing S. Enteritidis strains [ 75 ]. Secondly, energy homeostasis, partly dependent on cellular fatty acid metabolism, has also been correlated with the energy-consuming Salmonella biofilm formation process [ 76 ]. Consistent with this, we not only noticed differential regulation of fatty acid-related genes, but also an alteration of the glyoxylate metabolism. Thirdly, as the UFA’s synthesized by FabA and FabB show high similarities with DSFs (diffusible signaling factors), a known class of biofilm dispersing compounds [ 67 ], an alternative potential mechanism through which FabR could impact on biofilm formation is by increasing the levels of free UFA’s acting as biofilm dispersing molecules. However, as we found that exogenous addition of different UFA’s did not affect biofilm formation, this role of FabR in biofilm signaling is unlikely. Next to UFA biosynthesis, a number of other processes regulated by FabR could possibly contribute to the effect of FabR on biofilm formation. ChIP-chip and microarray analysis indicated a direct FabR binding to and upregulation of ribosomal genes. The finding of Boehm et al . that ribosomal stress induces E. coli biofilm formation suggests a possible role for ribosome overexpression in biofilm reduction [ 77 ]. Also, direct links between Salmonella biofilm formation and genes downregulated in a fabR deletion mutant, such as ompA [ 64 ], ompC [ 78 ], ompX [ 79 ], osmB [ 80 ], osmC [ 79 ], sseI [ 78 ], have previously been identified, making them potential targets through which FabR could act on biofilm formation. Several of these repressed genes encode outer membrane proteins ( ompA , ompC , ompX, osmB ). Salmonella mutants in ompA and ompC have been shown to be deficient in biofilm formation on polystyrene and cholesterol-coated surfaces respectively [ 64 , 78 ], whereas the expression of ompX and osmC has been shown to be activated within Salmonella biofilms [ 79 ]. These outer membrane proteins are important for biofilm formation possibly because they mediate electrostatic interactions between salmonellae and the surface, promote overall biofilm health e.g. as nutrient channels, or have regulatory functions within biofilms [ 81 ]."
} | 2,785 |
38673205 | PMC11051187 | pmc | 5,455 | {
"abstract": "The exceptional corrosion resistance and combined physical and chemical self-cleaning capabilities of superhydrophobic photocatalytic coatings have sparked significant interest among researchers. In this paper, we propose an economical and eco-friendly superhydrophobic epoxy resin coating that incorporates SiO 2 @CuO/HDTMS nanoparticles modified with Hexadecyltrimethoxysilane (HDTMS). The application of superhydrophobic coatings effectively reduces the contact area between the metal surface and corrosive media, leading to a decreased corrosion rate. Additionally, the incorporation of nanomaterials, exemplified by SiO 2 @CuO core–shell nanoparticles, improves the adhesion and durability of the coatings on aluminum alloy substrates. Experimental data from Tafel curve analysis and electrochemical impedance spectroscopy (EIS) confirm the superior corrosion resistance of the superhydrophobic modified aluminum alloy surface compared to untreated surfaces. Estimations indicate a significant reduction in corrosion rate after superhydrophobic treatment. Furthermore, an optical absorption spectra analysis of the core–shell nanoparticles demonstrates their suitability for photocatalytic applications, showcasing their potential contribution to enhancing the overall performance of the coated surfaces. This research underscores the promising approach of combining superhydrophobic properties with photocatalytic capabilities to develop advanced surface modification techniques for enhanced corrosion resistance and functional properties in diverse industrial settings.",
"conclusion": "4. Conclusions In summary, SiO 2 @CuO core–shell particles were synthesized using the hydrothermal method. The particles were then functionalized with HDTMS and sprayed onto an aluminum alloy surface, leading to the formation of a superhydrophobic coating with self-cleaning properties and photocatalytic functionalities. Through the application of superhydrophobic coatings, the contact area between the metal surface and corrosive media is minimized, leading to a reduction in the corrosion rate. The incorporation of nanomaterials, such as SiO 2 @CuO core–shell nanoparticles, further improves the adhesion and durability of superhydrophobic coatings on aluminum alloy substrates. Additionally, the utilization of copper oxide (CuO) nanoparticles for photocatalytic degradation of organic compounds demonstrates potential for enhancing the overall performance of the coated surfaces. The Tafel curve and EIS analysis showed a significant decrease in the corrosion rate of the aluminum alloy surface after superhydrophobic treatment, indicating an improved corrosion resistance compared to untreated surfaces. The combination of superhydrophobic coatings and photocatalytic degradation presents a promising approach to enhance the corrosion resistance of metal surfaces, particularly aluminum alloys.",
"introduction": "1. Introduction Corrosion results in economic losses, safety incidents, environmental pollution, and other detrimental effects that require urgent attention in our society [ 1 , 2 ]. Typically, coating the substrates surface to isolate it from the surrounding environment is the most effective corrosion protection method [ 3 , 4 ]. Among various coatings, superhydrophobic materials exhibit a strong repellent effect towards liquids, thereby enabling oil/water separation [ 5 ], microplastics removal [ 6 ], photodegradation of dyes [ 7 ], desalination [ 8 ], heavy metal removal [ 9 ], corrosion resistance [ 10 ], and self-cleaning [ 11 ] capabilities. Generally, the wettability of a surface is influenced by its surface energy and roughness [ 12 , 13 ]. Therefore, exposure of a superhydrophobic surface to harsh environments (acidic or alkaline solutions, organic solvents, abrasion, washing, UV radiation, and high temperatures) can lead to the deterioration of surface roughness (loss of nanoparticles or substrate abrasion) or an increase in surface energy (decomposition of hydrophobic long chains), resulting in the loss of superhydrophobic properties and a significant reduction in the service life of superhydrophobic materials [ 14 , 15 ]. Constructing highly reliable hydrophobic and durable coatings remains a formidable challenge. To enhance the adhesion of superhydrophobic coatings effectively, the concept of “nanoparticles + binder” has been proposed to improve the durability of the coatings [ 16 , 17 , 18 ]. Surface-modified SiO 2 nanoparticles, which are stable and inherently hydrophobic, are utilized in superhydrophobic coatings. Sharma et al. prepared a triethoxyoctylsilane-modified SiO 2 nanoparticle-based superhydrophobic coating by the solution method to prevent the corrosion of mild steel [ 19 ]. Wang et al. reported a robust superhydrophobic SiO 2 /epoxy coating prepared by a one-step spraying method for corrosion protection of aluminum alloy [ 20 ]. Luque et al. constructed a spiky SiO 2 nanoparticle supramolecular polymer superhydrophobic coatings applied to transparent oil–water separating [ 21 ]. Within the adhesive realm, epoxy resin emerges as a standout candidate due to its exceptional chemical stability, robust abrasion resistance, notable water repellency, and strong adhesion to substrates, positioning it as a favored alternative to fluoropolymers for formulating superhydrophobic coatings [ 22 , 23 ]. Despite these advantages, a common issue with many superhydrophobic surfaces is their inherent oleophilic nature, making them susceptible to contamination by organic pollutants and leading to a gradual decline in hydrophobicity and the eventual loss of self-cleaning properties [ 24 , 25 ]. Consequently, the fusion of superhydrophobicity with the photocatalytic decomposition of organic compounds has garnered considerable attention from the research community in recent years [ 26 , 27 , 28 , 29 ]. Semiconductor oxides such as TiO 2 [ 30 ], SnO 2 [ 31 ], ZnO [ 32 ], NiO [ 33 ], Cu 2 O [ 34 ], and CuO [ 35 ] are extensively utilized as photocatalysts in the degradation of various pollutants, encompassing dyes, organic contaminants, natural organic substances, and pharmaceutical compounds. Notably, copper oxide (CuO), featuring a band gap within the range of 1.2~2.1 eV, stands out as a critical p -type semiconductor renowned for its catalytic, optical, antimicrobial, and cost-efficient attributes [ 36 , 37 , 38 ]. Moreover, besides furnishing the requisite roughness for superhydrophobic coatings, SiO 2 can function as a core material for incorporating additional functional elements, facilitating the creation of core–shell architectures. In the realm of photocatalysis, the interplay between distinct components in composite materials enhances the efficiency of separating photo-generated electron–hole pairs, thereby prolonging the lifespan of active electrons, holes, and radicals. Consequently, SiO 2 is extensively employed as a carrier for semiconductor catalytic catalysts to fabricate core–shell configurations [ 39 , 40 , 41 ]. Herein, we present a straightforward approach for the fabrication of flower-shaped SiO 2 @CuO nanoparticles through liquid-phase reduction. A detailed analysis is conducted to elucidate the impact of physical structure and chemical composition on the performance of these nanoparticles. Subsequently, SiO 2 @CuO core–shell particles, surface-modified with HDTMS and dispersed in epoxy resin, were applied via spray coating onto an aluminum alloy substrate. This process aimed to develop long-lasting superhydrophobic coatings with the capability of photocatalytic degradation of organic compounds. The self-cleaning effectiveness and underlying principles of these coatings were thoroughly examined and discussed."
} | 1,926 |
27446004 | PMC4914502 | pmc | 5,456 | {
"abstract": "Strategic enrichment of microcosms derived from wood foragers can facilitate the discovery of key microbes that produce enzymes for the bioconversion of plant fiber (i.e., lignocellulose) into valuable chemicals and energy. In this study, lignocellulose-degrading microorganisms from the digestive systems of Canadian beaver ( Castor canadensis ) and North American moose ( Alces americanus ) were enriched under methanogenic conditions for over 3 years using various wood-derived substrates, including (i) cellulose (C), (ii) cellulose + lignosulphonate (CL), (iii) cellulose + tannic acid (CT), and (iv) poplar hydrolysate (PH). Substantial improvement in the conversion of amended organic substrates into biogas was observed in both beaver dropping and moose rumen enrichment cultures over the enrichment phases (up to 0.36–0.68 ml biogas/mg COD added), except for enrichments amended with tannic acid where conversion was approximately 0.15 ml biogas/mg COD added. Multiplex-pyrosequencing of 16S rRNA genes revealed systematic shifts in the population of Firmicutes , Bacteroidetes , Chlorobi , Spirochaetes , Chloroflexi , and Elusimicrobia in response to the enrichment. These shifts were predominantly substrate driven, not inoculum driven, as revealed by both UPGMA clustering pattern and OTU distribution. Additionally, the relative abundance of multiple OTUs from poorly defined taxonomic lineages increased from less than 1% to 25–50% in microcosms amended with lignocellulosic substrates, including OTUs from classes SJA-28 , Endomicrobia , orders Bacteroidales , OPB54 , and family Lachnospiraceae . This study provides the first direct comparison of shifts in microbial communities that occurred in different environmental samples in response to multiple relevant lignocellulosic carbon sources, and demonstrates the potential of enrichment to increase the abundance of key lignocellulolytic microorganisms and encoded activities.",
"conclusion": "Conclusion Overall, enrichment of BD and MR on multiple lignocellulosic substrates led to the proliferation of recognized cellulolytic bacteria as well as unique lineages that were in low or undetectable abundances in corresponding inocula. These unassigned lineages were grouped in classes SJA-28 , Endomicrobia , orders Bacteroidales , OPB54 and family Lachnospiraceae , and comprised up to half of corresponding communities, warranting future investigation on their potential in lignocellulose degradation. The substrate-based convergence of microbial community compositions originating from BD and MR suggests that resulting communities have specialized to the amended carbon sources, and that corresponding microorganisms may encode distinct CAZymes that are particularly effective toward the given lignocellulosic carbon source. At the same time, microorganisms that were unique to specific enrichment conditions, such as SJA-28 in enrichments amended with CL and bacteria from order OPB54 or Lachnospiraceae family in enrichments amended with CT, may comprise specialized catabolic activities relevant to pretreatment and detoxification of wood hydrolysates ( Lopez et al., 2004 ); metagenomic analyses are now underway to investigate these predictions.",
"introduction": "Introduction Lignocellulose in agricultural and forest residues, as well as energy crops, is considered as an important renewable resource for the production of bioenergy, liquid biofuels, and specialty chemicals. As the main component of plant cell walls, lignocellulose is largely composed of polysaccharides (cellulose, hemicellulose, and pectin) and lignin, with varying chemical compositions and structures depending on plant species, tissue, and cell type ( Harris and Stone, 2009 ). Wood fiber typically contains a higher lignin content and hemicelluloses with chemical structures distinct from those found in grasses. Fungi and bacteria are the dominant organisms responsible for lignocellulose biodegradation and encoded enzymes offer advantages in lignocellulose processing particularly when (i) converting lignocellulose into fermentable intermediates, (ii) synthesizing high-value chemicals from specific lignocellulose components, and (iii) handling residual biomass with high water content, which are less amendable to processing through thermo-chemical options. Metagenomic analysis of microbial communities that degrade lignocellulose has been motivated by decreasing DNA sequencing costs, along with the rich repertoire of CAZymes encoded by gut microflora. Such efforts have included the analysis of metagenomes obtained from foregut of Tammar wallaby ( Pope et al., 2010 ), mid-gut of wood-feeding Asian longhorn beetles ( Scully et al., 2013 ), hindgut of termite ( Warnecke et al., 2007 ), as well as the rumen of ox ( Brulc et al., 2009 ), cow ( Hess et al., 2011 ), yak ( Dai et al., 2012 ), and reindeer ( Pope et al., 2012 ). Corresponding analyses have identified thousands of new genes predicted to encode enzymes relevant to lignocellulose conversion. For instance, metagenomic analysis of the cow rumen alone led to over 27,000 new candidate CAZymes ( Hess et al., 2011 ). In an effort to identify genes likely to encode enzymes optimized for transforming wood fiber, Scully et al. (2013) applied hierarchical cluster analysis of Pfam abundances to compare the gut metagenome of a wood-boring pest, Anoplophora galbripennis , to 19 herbivore-related metagenomes ( Scully et al., 2013 ). Distinct clusters representing different herbivore biome-types were identified, including herbivore gut communities, fungal gallery communities, and communities associated with insects that feed on heartwood. In contrast to grass-fed mammalian herbivores, North American moose ( Alces americanus ) and Canadian beavers ( Castor canadensis ) are iconic Canadian foragers of coniferous and deciduous trees in riparian zones of the boreal mixed-wood forests ( Hood and Bayley, 2009 ). North American moose is the largest browsing ruminant of the deer family Cervidae ( Ishaq and Wright, 2012 ), while Canadian beavers represent one of the largest and ecologically most distinct rodent species with a monogastric digestive system, whose dietary subscription shifted from omnivory to obligate herbivory ( Horn et al., 2011 ). With wood biomass being a significant part of the diet, the microbial communities within the digestive system of these Canadian mammals are likely to include lignocellulose-degrading bacteria. Recent studies report lignocellulose-degrading bacterial lineages among the gut microbes from moose ( Ishaq and Wright, 2014 ), which resemble those residing in the termite hindgut ( Ishaq and Wright, 2012 ). Preliminary data also suggest cellulolytic/xylanolytic activities in the lower gut of beavers ( Gogola et al., 2011 ). Enrichment of microbial communities on selected lignocellulose substrates could augment the fraction of most pertinent lignocellulose degraders and encoded activities. For example, feeding termites with grasses enriched Clostridiales incertae sedis and Spirochaetaceae lineages of Firmicutes in their hindgut populations, whereas feeding with wood fiber proliferated members across several phyla, including Bacteroidetes , Elusimicrobia , Firmicutes , Plantomycetes , Proteobacteria , Spirochaetes , and Verrumicrobia ( Huang et al., 2013 ). Similarly, fecal microbiomes obtained from cattle fed with unprocessed grain were enriched with bacteria belonging to the Ruminococcaceae order, whereas those obtained from cattle fed with forage or processed grain were enriched in bacteria belonging to the Prevotella genus (Order: Bacteroidales; Shanks et al., 2011 ). Notably, specific phyla were enriched in nearly all lignocellulose-degrading gut microflora analyzed to date, including Firmicutes ( Bacilli , Clostridia ), Proteobacteria , Bacteroidetes , Chloroflexi , and Actinobacteria. However, most enrichment studies have been performed in situ , and so are confounded by the presence of additional glycan sources, including mucin glycans produced by the host ( Koropatkin et al., 2012 ; Tailford et al., 2015 ). Alternatively, ex situ enrichment of microbial communities on lignocellulosic carbon sources could uncover microbial lineages that are quintessential to degrading specific biomass components. Here, we directly compared shifts in microbial profiles that result from long-term enrichment (>3 years) of digestive microflora from the Canadian beaver and North American moose, on four lignocellulosic carbon sources: C, CT, CL, and PH. These amendments represented increasingly complex and potentially inhibitory carbon sources. For example, inhibition of methanogenic activity by tannic acids is well known ( Bhatta et al., 2009 ), while PH typically contains mixed-wood extractives, organic acids, furan derivatives, and lignin that can inhibit microbial activity, including methanogenesis ( den Camp et al., 1988 ; Sierra-Alvarez and Lettinga, 1991 ; Mills et al., 2009 ). Aside from monitoring metabolic activities through biogas yield from each enrichment, pyrotag sequencing was performed to characterize shifts in microbial communities that would suggest specialization and expression of distinct lignocellulolytic activities.",
"discussion": "Results and Discussion Establishment of Biogas-Producing Microbial Enrichments Anaerobic enrichments were established and methanogenic activity was sustained over 10 feedings for 3 years on four different lignocellulosic substrate mixes ( Supplementary Table S2 ). Over the enrichment phases, the average volumes of biogas produced per amount of COD added decreased initially and then increased by the ninth growth phase, suggesting acclimatization to each lignocellulosic carbon source by 154–171 weeks of enrichment ( Figure 1 , Supplementary Table S3 ). At the growth phase just prior to DNA extraction (i.e., phase 9), the extent of carbon source conversion for BD enrichments were: C (0.68 ml biogas/mg COD added), PH (0.46 ml biogas/mg COD added), CL (0.36 ml biogas/mg COD added), and CT (0.15 ml biogas/mg COD added). By comparison, the extent of carbon source conversion for MR enrichments was: PH (0.64 ml biogas/mg COD added), C (0.39 ml biogas/mg COD added), CL (0.36 ml biogas/mg COD added), and CT (0.16 ml biogas/mg COD added). Tannic acid consistently inhibited biogas production. The impact of tannic acid is consistent with previous studies, which report that the phenolic hydroxyl groups of tannic acid can complex with proteins, metal ions, amino acids, and polysaccharides ( Makkar, 2003 ), thereby inhibiting enzyme action and uptake of essential carbon sources and metal ions ( Asiegbu et al., 1995 ; Bhatta et al., 2009 ). FIGURE 1 Biogas production profile of microcosms fed with various lignocellulosic carbon sources for over 3 years. The range of stoichiometric maximum biogas yield is shown in the gray band to provide a reference for the conversion extents of the fed substrates in the microcosms [see supplemental methods for the calculation based on Buswell’s formula ( Symons and Buswell, 1933 )]; error bars indicate standard deviation; n = 3. C, cellulose; CL, cellulose + lignosulphonate; CT, cellulose + tannic acid; PH, poplar hydrolysate. Biodiversity Indices in Enrichment Cultures Overall, 179,801 high-quality reads were retained for downstream analyses of community structure, richness, and diversity estimators ( Supplementary Table S5 ). Despite extraction of high-quality DNA and successful PCR amplification, few reads (less than 15) were retrieved for BD cultivations enriched on CT (data not shown), and so this dataset was removed from downstream analyses. In total, recovered sequences were assigned to 5800 unique OTUs at 97% similarity threshold. In the MR enrichments, the decrease in Chao I (richness) and Shannon (diversity) indices compared to the original inoculum were consistent with enrichment of microorganisms best suited to transform amended carbon sources ( Supplementary Figure S1 ). A similar trend was reported recently in soil microbiota following enrichment with wheat straw ( Jimenez et al., 2014 ). In contrast, in the BD enrichments, the comparatively low Chao I index of the inoculum likely reflects the dominance of a soil species as described in the next section. Consistent with this interpretation of Chao I richness, the Simpson’s diversity index was highest for the BD and MR inoculum samples compared to corresponding enrichments. While the time span between defecation and sampling was unclear (as is the case for most fecal studies of wild animals), sample collection from beavers in the wilderness rather than captivity overcomes potential human interference to the gut microbiota. For example, loss in microbial diversity upon captivity has been reported in closely related woodrats ( Kohl et al., 2014 ). With greater loss in microbial diversity in the diet specialist (e.g., Stephens’ woodrat which consumes a diet of 60–95% juniper) than the diet generalist (e.g., white-throated woodrat consumes actus, yucca, juniper, other shrubs and grasses), where the original microbiota could not be restored despite the provision of a natural diet. A high level overview of the amplicon sequencing data revealed that samples from triplicate microcosms for a given enrichment condition clustered most closely, providing confidence in the reproducibility of the analysis ( Figure 2A ). Moreover, the inoculum samples were most divergent from subsequent enrichment cultures, clearly revealing substrate-driven convergence of microbial communities by both UPGMA and Unifrac clustering ( Figures 2A,B ). In the following sections, we first discuss community shifts in the BD samples, and then those in the MR samples, and finally a holistic view of the emergent OTUs that are shared in the enrichment microcosms. FIGURE 2 Substrate-based clustering of lignocellulose-active microbial communities in beaver dropping and moose rumen, and their corresponding enrichment cultures. \n (A) Heatmap with UPGMA clustering and relative abundances of microbial phyla (≥ 1.0% in at least one sample). (B) Three-dimensional Unifrac PCoA plot. BD, beaver dropping; C, cellulose; CL, cellulose + lignosulphonate; CT, cellulose + tannic acid; MR, moose rumen; PH, poplar hydrolysate. Impact of Lignocellulosic Substrates on Microbial Communities Originating from Beaver Droppings Upon enrichment on lignocellulosic substrates under strictly anaerobic methanogenic conditions, we observed a dramatic decrease in the microbes belonging to the Proteobacteria ( Figure 2A ). Specifically, the relative abundance of Proteobacteria diminished from approximately 62% in BD inoculum (sum of all Proteobacteria shown in Figure 3A , Supplementary Data S1 ) to between 1 and 17% in corresponding enrichments ( Figures 3B,C,E ), where highest numbers remained in cultures enriched on PH ( Figure 3E ). Most of the Proteobacteria present in the inoculum belonged to the genus Pseudomonas (approximately 30%; Figure 3A ), which are ubiquitous soil facultative bacteria, and notably also comprise species with ability to detoxify lignocellulosic hydrolysates ( Lopez et al., 2004 ). Although enrichment on PH retained a comparatively high fraction of Proteobacteria , the largest group in that enrichment was assigned to the genus Gammaproteobacteria (14%; Figure 3E ). Notably, Gammaproteobacteria were previously identified in other biomass-degrading communities, including a cellulose-degrading marine biofilm and a wheat straw-degrading microbial consortia ( Edwards et al., 2010 ; Jimenez et al., 2014 ). Similarly, the Fusobacteriaceae family represented 8.5% of the BD inoculum ( Figure 3A ), but were not detected in any of corresponding enrichments ( Figures 3B,C,E ). This family comprises microaerophilic to obligate anaerobes that can ferment carbohydrates and amino acids into various organic acids in anaerobic environments, including oral, gastrointestinal lining of mammals and anaerobic sediments ( Olsen, 2014 ). FIGURE 3 Relative abundances of microbial families (≥ 1.0% in at least one sample) in beaver dropping and moose rumen, and their corresponding enrichment cultures. \n (A) Inocula and microcosms fed with (B) cellulose, (C) cellulose + lignosulphonate, (D) cellulose + tannic acid, and (E) poplar hydrolysate. The distributions of OTUs (≥ 0.5% in at least one sample) are shown in the Venn diagram; shared OTUs are highlighted with red. The impact of microbial enrichment was further illustrated by the detection of microbial phyla in enrichments that were not detected in the BD inoculum given their low abundance. For example, Chlorobi in the C and CT enrichments represented over 10 and 35% of corresponding communities ( Figures 3B,C ), even though this phylum was not detected in the original inoculum. An unassigned member of the uncultured class SJA-28 constituted nearly 10% of C enrichments and 35% CL enrichments ( Figures 3B,C ), while comprising 83% and 95% of the Chlorobi phylum in these respective cultures. Enrichment on lignocellulosic substrates also led to the detection of Spirochaetes and Chloroflexi in enrichments originating from BD. Most notably among the Spirochetaceae , bacteria belonging to the genus Treponema contributed approximately 5% of all enrichments ( Figures 3B,C,E ), whereas the genus W22 from the Cloacamonaceae family comprised over 17% of the microbial community enriched on PH ( Figure 3E ). Treponema acetogens were previously identified in the termite gut microbiome, and were predicted to encode glycoside hydrolases targeting cellulose and xylan ( Warnecke et al., 2007 ). Among the members of Bacteroidetes , family S24-7 made up 4% of the community in the BD inoculum ( Figure 3A ), while an unassigned lineage contributed up to 18% in enrichments established on cellulose ( Figure 3B ), and 11% of enrichments established on PH ( Figure 3E ). Notably, uncultured Bacteroidetes lineages dominate numerous lignocellulose-degrading communities. For example, recent metagenomic studies of microbiomes from human gut and reindeer rumen revealed high abundance of polysaccharide utilization loci-like systems originating from Bacteroidetes ( Martens et al., 2009 ; Pope et al., 2012 ). These gene clusters encode CAZymes as well as transport proteins for glycan hydrolysis and uptake and represent a rich reservoir of new lignocellulolytic activities ( Terrapon et al., 2015 ). Several members of the Firmicutes have been implicated as key cellulose degraders. Consistent with this pattern, enrichment of BD on lignocellulosic substrates led to a four to eightfold increase in the relative abundance of members from this phylum ( Figure 2A ). Most significantly, microbes belonging to the genus Clostridium and Ruminococcus were particularly enriched ( Figures 3B,C,E ), which is consistent with the importance of corresponding species to polysaccharide degradation ( Tracy et al., 2012 ). Moreover, an uncultured lineage in order OPB54 made up to 15% of the BD enrichments amended with cellulose ( Figure 3B ). Notably, OPB54 was previously identified in low abundance in stillage biogas reactors that operated in high temperatures ( Roske et al., 2014 ). Impact of Lignocellulosic Substrates on Microbial Communities Originating from Moose Rumen Similar to the BD enrichments, phyla that were common to all enrichments derived from MR samples included Firmicutes , Bacteroidetes , Chlorobi , Elusimicrobia , and Spirochaetes ( Figure 2A ). In the case of samples from the MR enrichment cultures, all samples had a high relative abundance of Firmicutes , that was comparable between the inoculum (42%; Figure 3A ) and enrichments amended with C (45%) and PH (58%; Figures 3B,E ), but lower in enrichments on CL (13%) and higher in the enrichments on CT (93%) ( Figures 3C,D ). Most dramatically, the fraction of Clostridium species increased from 3% in the inoculum to 33% and 45% in C and PH enrichments, respectively ( Figures 3A,B,E ). By comparison, enrichments amended with CT were distinguished by over 45% of bacteria belonging to the Lachnospiraceae family ( Figure 3D ). The representation of this family decreased from 12% of the inoculum ( Figure 3A ) to less than 5% of other enrichments ( Figures 3B,C,E ). Lachnospiraceae members were previously identified in MR and foreguts of dromedary camels ( Samsudin et al., 2011 ; Meehan and Beiko, 2014 ), but were not reported in reindeer gut ( Pope et al., 2012 ).CT cultivations were further distinguished by an increase in the fraction of uncultured bacteria within the Clostridia class ( Figure 3D ), particularly from order OPB54 as was observed for BD cultures enriched on C (increase from 0.1% in the inoculum to 6.3% in the enrichment) as well as unassigned genera within the Lachnospiraceae family (from 3 to 48% in the enrichment; Figure 3A ). In addition to the Firmicutes , members of the phylum Chlorobi increased from non-detectable levels in the inoculum to 17% and 27% of C and CL cultures ( Figures 3B,C ), respectively. As observed for corresponding enrichments of BD, this increase was mainly attributed to enrichment of bacteria belonging to class SJA-28 . Members of the phylum Elusimicrobia (formerly Termite Group 1 ; TG1 ) were also enriched through growth on CL, from less than 1% in the inoculum to over 17% in the enrichment culture ( Figure 3C ). Notably, growth on other lignocellulosic amendments did not increase levels of Elusimicrobia members. Whereas the relative abundances of Firmicutes , Chlorobi , and Elusimicrobia increased upon various lignocellulosic enrichments, the total fraction and species diversity of Bacteroidetes decreased from 23% in the inoculum to lower levels in the enrichment cultures ( Figure 2A ). Specifically, BS11 (11%) and Prevotella (7%) in the MR sample became non-detectable after the enrichment process ( Figure 3A ), whereas an unassigned lineage under Bacteroidales was maintained after enrichment with C (4%), and increased upon CL (17%) and PH (22%; Figures 3B,C,E ). In contrast, none of the Bacteroidetes species were detected in enrichment cultures amended with CT. Comparative Analysis of All Microbial Enrichments As explained above, an underlying hypothesis of the enrichment study was that the relative abundance of microbes most relevant to lignocellulose conversion would increase by culturing the selected inocula on lignocellulosic substrates. In this way, we could also uncover microbial members that might encode specialized functions, including transformation potential inhibitory substances, such as tannic acid or lignosulphonate. Consistent with our hypothesis, abundances of known lignocellulose degraders increased following amendment with selected lignocellulosic carbon sources and included microbial lineages previously identified in the termite hindgut, such as Firmicutes , Proteobacteria , Bacteroidetes , Spirochaetes , and Elusimicrobia ( Huang et al., 2013 ), or the bovine rumen microbiome, such as Chlorobi , Chloroflexi , and Fusobacteria ( Brulc et al., 2009 ). Moreover, UPGMA clustering of OTU sequences revealed convergence of microbial communities enriched with the same carbon source ( Figure 2A ); convergence of community composition was also revealed through UniFrac analysis ( Figure 2B ). Overall, microbial community compositions could be grouped into three main sub-clusters ( Figure 2A ), namely, (i) original inoculum, (ii) enrichment on C or CL, and (iii) enrichment on PH; the MR enrichment on CT formed a fourth, unique branch. Furthermore, the majority of OTUs present in BD and MR inocula were not detected in the corresponding enrichments ( Figure 4A ), this trend was even more obvious when a threshold of 0.5% abundance is applied ( Figure 4B ). Indeed, the most abundant OTUs in enrichments represented organisms that comprised less than 0.5% of all OTUs in the original inoculum ( Supplementary Data S2 ). This demonstrates strong selection of microbial members for a given lignocellulose amendment, which was underscored by the few overlapping OTUs between enrichments on different lignocellulose amendments ( Figure 4B ). One notable exception was otu6272 (assigned to class Gammaproteobacteria ), which represented nearly 8% of all OTUs in the BD inoculum and 14% of OTUs after enrichment on PH. FIGURE 4 Distribution of (A) all OTUs and (B) OTUs with relative abundances ≥ 0.5% in beaver dropping and moose rumen, and their corresponding enrichment cultures. Abundances of represented OTUs are shown in brackets. Core species were not identified among enrichments originating from the same inoculum ( Figures 4A,B ). Moreover, despite no shared OTUs between BD and MR inocula at a 0.5% abundance cut-off ( Figure 3A ), a high number of overlapping members constituting the shared dominant taxonomic lineages was observed between enrichments fed with the same lignocellulose carbon source ( Figures 3B,C,E ). For example, otu2346 assigned to the Clostridium genus was not detected in BD or MR inocula, but comprised a significant fraction of C enrichments (15–17%), CL enrichments (9%), and PH enrichments (7–49%; Figures 3B,C,E ). Similarly, an OTU assigned to class SJA-28 (otu225) was not observed in either inoculum, but represented 5–15% of both C enrichments and 20–28% of both CL enrichments ( Figures 3B,C ). Finally, otu4036 belonging to the order Bacteroidales was uniquely detected in enrichments established on PH ( Figure 3E ), where it comprised 5–10% of the bacterial community even though it was not detected in either inoculum or any other enrichment condition. Despite the convergence of microbial communities enriched on the same lignocellulosic carbon source, unique lineages were also observed that reflect the impact of starting inocula. After enrichment of BD on Cl and PH, a Ruminococcus OTU (otu2378) represented 6% and 20% of corresponding microbial communities ( Figures 3C,E ). In contrast, otu2378 was not found in any MR enrichments. Similarly, the Gammaproteobacteria OTU (otu6272) and W22 OTU (otu3890) identified in BD ( Figure 3A ) and corresponding enrichments on PH ( Figure 3E ) was not detected in MR samples or any of the derived enrichments. Correlations between microbial membership and lignocellulosic substrate also emerged by identifying key differences between communities resulting from the different amendments. For example, the abundance of class SJA-28 in enrichments amended with CL was double that of enrichments amended with C. In contrast, the abundance of orders OPB54 and Clostridiales consistently decreased upon amendment with CL compared to addition of C alone. Figure 5 summarizes the specific OTUs that were enriched upon lignocellulosic amendment, as well as reported habitats of understudied lineages. In addition to these genera, class Endomicrobia , order Bacteroidales , family Lachnospiraceae , and genus W22 represent additional sources of understudied microorganisms that could comprise unique enzymes and biochemical pathways relevant to lignocellulose conversion. FIGURE 5 Abundant OTUs from enrichment microcosms fed with various lignocellulosic carbon sources. Abundances (≥ 4% in at least one sample) are indicated by the relative length of data bars, which are color coded to represent the inocula (red), and enrichment microcosms fed with cellulose (yellow), cellulose + lignosulphonate (green), cellulose + tannic acid (blue), and poplar hydrolysate (purple)."
} | 6,932 |
25650158 | PMC4312070 | pmc | 5,457 | {
"abstract": "Filamentous cells belonging to the candidate bacterial phylum KSB3 were previously identified as the causative agent of fatal filament overgrowth (bulking) in a high-rate industrial anaerobic wastewater treatment bioreactor. Here, we obtained near complete genomes from two KSB3 populations in the bioreactor, including the dominant bulking filament, using differential coverage binning of metagenomic data. Fluorescence in situ hybridization with 16S rRNA-targeted probes specific for the two populations confirmed that both are filamentous organisms. Genome-based metabolic reconstruction and microscopic observation of the KSB3 filaments in the presence of sugar gradients indicate that both filament types are Gram-negative, strictly anaerobic fermenters capable of non-flagellar based gliding motility, and have a strikingly large number of sensory and response regulator genes. We propose that the KSB3 filaments are highly sensitive to their surroundings and that cellular processes, including those causing bulking, are controlled by external stimuli. The obtained genomes lay the foundation for a more detailed understanding of environmental cues used by KSB3 filaments, which may lead to more robust treatment options to prevent bulking.",
"conclusion": "Conclusions In summary, this study adds novel genomic ‘foliage’ to the tree of life by reporting the near complete genomes of two phylogenetically diverse members of candidate bacterial phylum KSB3 obtained from an industrial UASB system. Genome-based metabolic reconstruction and experimental observations provide clues to the roles of the KSB3 bacteria in the treatment system including their ability to ferment sugars and chemotactically respond to glucose and maltose gradients, laying the foundations for a detailed understanding of their ecophysiology and role in wastewater bulking.",
"introduction": "Introduction Anaerobic digestion is a major type of biological treatment extensively used around the world ( Ahring, 2003a ) that is not only cost effective for treating organic waste and wastewater, but also can frequently produce energy in the form of methane (biogas) ( Angelidaki et al., 2011 ). Over the last thirty years, a set of high rate anaerobic digestion reactor configurations have been developed, of which the upflow anaerobic sludge blanket (UASB) technology is the most successful and commercialized configuration ( Kleerebezem & Macarie, 2003 ; van Lier, 2008 ). Despite the success of this technology, serious performance issues have emerged such as the sudden washout of granular sludge biomass due to overgrowth of filamentous bacteria (bulking), which can lead to complete loss of performance. Bulking of anaerobic digestion systems can be caused by a variety of filamentous microorganisms ( Hulshoff Pol et al., 2004 ; Li et al., 2008 ; Yamada & Sekiguchi, 2009 ) and a phylogenetically novel filament was previously reported to be the cause of bulking in an industrial UASB reactor treating sugar manufacturing wastewater ( Yamada et al., 2007 ; Yamada et al., 2011 ). Small subunit ribosomal RNA (16S rRNA) gene-based analyses of the bulking sludge ( Yamada et al., 2007 ) revealed that the dominant filament type belongs to candidate bacterial phylum KSB3, originally proposed by Tanner et al. (2000) based on an environmental 16S rRNA gene clone sequence obtained from a sulfur-rich marine sediment ( Tanner et al., 2000 ). Fluorescence in situ hybridization (FISH) with KSB3-specific 16S rRNA-directed probes revealed that the KSB3 filaments are localized at the outer layer of healthy granules ( Yamada et al., 2007 ) which become substantially thicker during bulking. The study of filamentous KSB3 bacteria will undoubtedly contribute to our understanding of and ability to prevent bulking in anaerobic wastewater treatment systems, but has been hampered by an inability to obtain a pure culture despite repeated and long term isolation efforts ( Yamada et al., 2011 ). However, culture-independent molecular and imaging methods are beginning to provide clues regarding the ecophysiology of these organisms. This includes their ability to uptake simple carbohydrates, particularly maltose and glucose, under anaerobic conditions and from these observations it was proposed that high carbohydrate loading in the UASB reactor may trigger proliferation of KSB filament populations ( Yamada et al., 2011 ). Here, we obtained near complete genomes from in situ populations of the dominant bulking KSB3 filament type and a second moderately related low abundance KSB3 filament via differential coverage binning ( Albertsen et al., 2013 ) using metagenomic data previously reported from a full-scale UASB reactor ( Soo et al., 2014 ). Differential coverage binning groups together anonymous metagenomic fragments (contigs) belonging to the same population based on the similarity of their sequencing coverage across multiple related metagenomes ( Albertsen et al., 2013 ). These genomes represent the first genomic information for candidate phylum KSB3 and provide insights into the metabolism of KSB3 filaments and their ability to cause bulking.",
"discussion": "Discussion Despite the biotechnological significance of industrial-scale anaerobic digestion, our understanding of the microbial ecology that underpins these processes is still rudimentary because most microorganisms cannot be cultured and such systems are essentially managed as “black boxes” ( Ahring, 2003b ; Rivière et al., 2009 ). Emerging culture-independent molecular techniques such as differential coverage binning of metagenomic data, which allows even low abundance population genomes to be recovered ( Sharon et al., 2013 ; Albertsen et al., 2013 ), are providing new opportunities to understand and optimize system performance ( Vanwonterghem et al., 2014 ). Using this approach, we obtained the first population genomes representing candidate bacterial phylum KSB3 ( Tanner et al., 2000 ; Yamada et al., 2007 ). One of these genomes, UASB14, belongs to a high abundance filament (∼10% of the community; Table 1 ; Fig. 1 ) previously reported to be responsible for bulking in an industrial UASB system treating wastewater from sugar manufacture ( Yamada et al., 2007 ). A second genome from the same habitat, UASB270, represents a low abundance (<0.5%) filament only moderately related to the first, i.e., they represent different classes within the KSB3 phylum ( Fig. 1 ). Metabolic reconstruction indicates that both filaments are primary fermenters of sugar and amino acid-containing compounds in the system ( Fig. 4 ), and both have a high “social IQ” based in part on possession of extensive regulatory networks ( Table 1 ; Tables S8 and S9 ; Fig. S14 ). These findings support the hypothesis that KSB3 filaments are important primary fermenters in healthy sludge granules ( Yamada et al., 2011 ) and further suggest that the filaments are sensitive to their surroundings and that their cellular processes, such as growth, may be controlled by external signals. Whether these features can be extrapolated to the whole KSB3 phylum, or simply reflect the specialized habitat from which the genomes were obtained, remains to be determined. Environmental surveys suggest that the phylum has a shallow ecological footprint, having been identified in mostly anoxic saline habitats ( Fig. 1A ), which may indicate that a fermentative metabolism is universal. The inferred capacity of the filaments to detect physicochemical gradients in their surroundings suggests that they should be motile. Apart from an incomplete gene complement for Type IV pili, no motility mechanism could be identified. However, microscopic observations indicated that the KSB3 filaments are capable of gliding motility in response to applied sugar gradients ( Movie S1 ). Gliding motility is thought to have evolved independently in multiple bacterial lineages, and the molecular mechanisms of gliding are only partially elucidated for a limited number of bacterial taxa ( Jarrell & McBride, 2008 ; Mignot & Kirby, 2008 ). This is the first report of gliding motility of organisms in UASB sludge granules, which have long been considered to have an organization driven by growth and attachment rather than motility of cells ( Liu et al., 2003 ; Hulshoff Pol et al., 2004 ). An enhanced sensory system is also likely the key driver of the bulking phenomenon; that is, changes in the UASB reactor such as increases in glucose or maltose concentration trigger outgrowth of the KSB3 filaments ( Yamada et al., 2011 ). It may also explain why repeated attempts to cultivate KSB3 filaments have failed to date ( Yamada et al., 2011 ), because they require specific and possibly complex environmental cues to stimulate growth in axenic culture. The inference that the KSB3 filaments sense sugars and the observation of a gliding motility response in the presence of a glucose or maltose gradient is consistent with the previous observation of uptake of these sugars by KSB3 filaments ( Yamada et al., 2011 ). Plant operators began monitoring glucose concentration in the UASB reactor influent using a simple urine test strip. No further bulking has occurred to date since keeping influent glucose concentration uniformly low (<200 mg/L) via adjustment of retention times in the acidification pretreatment. A more detailed understanding of environmental stimuli responsible for growth and bulking will be facilitated by the availability of the KSB3 genome sequences which may lead to genome-directed cultivation ( Tyson et al., 2005 ) and other treatment options for bulking. We propose the names ‘ Candidatus Moduliflexus flocculans’ and ‘ Candidatus Vecturithrix granuli’ for the two KSB3 filament types represented by the UASB14 and UASB270 genomes respectively, and the phylum name, Modulibacteria, and intermediate rank names ( Table 1 ; Supplemental Information 1 )."
} | 2,469 |
36445040 | null | s2 | 5,458 | {
"abstract": "Polymer networks built out of dynamic covalent bonds offer the potential to translate the control and tunability of chemical reactions to macroscopic physical properties. Under conditions at which these reactions occur, the topology of covalent adaptable networks (CANs) can rearrange, meaning that they can flow, self-heal, be remolded, and respond to stimuli. Materials with these properties are necessary to fields ranging from sustainability to tissue engineering; thus the conditions and time scale of network rearrangement must be compatible with the intended use. The mechanical properties of CANs are based on the thermodynamics and kinetics of their constituent bonds. Therefore, strategies are needed that connect the molecular and macroscopic worlds. In this Perspective, we analyze structure-reactivity-property relationships for several classes of CANs, illustrating both general design principles and the predictive potential of linear free energy relationships (LFERs) applied to CANs. We discuss opportunities in the field to develop quantitative structure-reactivity-property relationships and open challenges."
} | 281 |
20456942 | null | s2 | 5,459 | {
"abstract": "The past three decades have witnessed steady growth in our ability to harness DNA branched junctions as building blocks for programmable self-assembly of diverse supramolecular architectures. The DNA-origami method, which exploits the availability of long DNA sequences to template sophisticated nanostructures, has played a major role in extending this trend through the past few years. Today, two-dimensional and three-dimensional custom-shaped nanostructures comparable in mass to a small virus can be designed, assembled, and characterized with a prototyping cycle on the order of a couple of weeks."
} | 150 |
36860486 | PMC9969146 | pmc | 5,461 | {
"introduction": "Introduction Francisella tularensis , the causative agent of tularemia, is found in humans, can produce various clinical symptoms ranging from skin lesions (ulcerous lesion), swollen lymph nodes as well as severe pneumonia, depending on the route of infection. Thus, the disease is defined by the following forms: ulcero-glandular or glandular, oropharyngeal, ocular-glandular and respiratory ( Ellis et al., 2002 ; WHO, 2007 ; Maurin and Gyuranecz, 2016 ). F. tularensis can infect a wide range of wild animals ( Ellis et al., 2002 ; WHO, 2007 ). Infections in humans are mostly associated with the highly virulent F. tularensis subsp. ( Ft. ) tularensis and the less virulent subspecies Ft. holarctica ( Fth ) ( Keim et al., 2007 ). However, in individuals with compromised immune systems, opportunistic infections by other Francisella species, such as F. hispaniensis, F. novicida , F. salimarina and F. philomiragia have been reported ( Hollis et al., 1989 ; Clarridge et al., 1996 ; Whipp et al., 2003 ; Frobose et al., 2020 ; Hennebique et al., 2022 ). The family of Francisellaceae exhibits also the genus Allofrancisella , Francisella- like-Endosymbionts of ticks and a new Francisella species ([Allo-] Francisella sp. strain W12-1067), identified in an aquatic habitat in Germany ( Burgdorfer et al., 1973 ; Rydzewski et al., 2014 ; Qu et al., 2016 ; Azagi et al., 2017 ; Challacombe et al., 2017 ; Gerhart et al., 2018 ). So far, it is not known if these species are able to infect humans. In contrast to Ftt , Fth is more frequently associated with aquatic habitats and is widely distributed throughout Eurasia ( Larson et al., 1955 ; Oyston et al., 2004 ; Sjostedt, 2007 ). F. tularensis maintains viability in cold water for long periods of time and it was hypothesized that the aquatic enviroment could serve as a reservoir for F. tularensis ( Parker et al., 1951 ; Forsman et al., 2000 ; Sinclair et al., 2008 ; Telford and Goethert, 2010 ; Gilbert and Rose, 2012 ; Telford and Goethert, 2020 ). The main habitat of F. tularensis in the aquatic reservoir is still unknown and so far it is unclear, if F. tularensis is able to multiply within aquatic (bacteria grazing) protozoa ( Abd et al., 2003 ; Thelaus et al., 2009 ; Buse et al., 2017 ). However, it is well-known that in (aquatic) natural environments, biofilm formation increases the survival of bacteria. The aquatic habitat-associated species F. novicida and F. philomiragia are well-known to form biofilms ( Durham-Colleran et al., 2010 ; Margolis et al., 2010 ; Verhoeven et al., 2010 ; Van Hoek, 2013 ; Hennebique et al., 2019 ; Siebert et al., 2020 ) and recently it was published that Type A and Type B isolates of F. tularensis are also able to form biofilms ( Champion et al., 2019 ; Golovliov et al., 2021 ; Mlynek et al., 2021 ). Biofilm formation is influenced by the pH, by phase variation of LPS and capsule ( Champion et al., 2019 ; Mlynek et al., 2021 ), by stress/ppGpp/relA ( Dean et al., 2009 ; Zogaj et al., 2012 ), by the two-component system qseC/qseB and BfpR ( Durham-Colleran et al., 2010 ; Dean et al., 2020 ) and by chitinases and antibiotic susceptibility ( Chung et al., 2014 ; Dean et al., 2015 ; Biot et al., 2020 ; Dean et al., 2020 ). Furthermore, it has been demonstrated that multi-species biofilms are more resistant against stress compared to single-species biofilms ( Joshi et al., 2021 ; Wicaksono et al., 2022 ) – a property that has not been investigated so far for F. tularensis . Despite of all these attempts, we are still at the beginning to understand the role of Francisella’s biofilm formation in its natural environment. We here could demonstrate that a Fth wild-type (WT) strain, isolated from a beaver deceased from tularemia, is able to form a matrix-associated biofilm. In addition, we can show for the first time that Fth is able to successfully colonize an aquatic multi-species ex vivo biofilm.",
"discussion": "Discussion Many studies about Francisella were performed with the Fth strain LVS, which is a virulence attenuated strain and its laboratory handling is much easier. Although strain LVS is used as a surrogate for F. tularensis , this strain is not fully virulent and may not behave as a Fth WT strain ( Rohmer et al., 2006 ; Biot et al., 2020 ; Mlynek et al., 2021 ). Thus, we used the Fth WT strain A-271, isolated from a carcass of a beaver deceased from tularemia, in our experiments ( Schulze et al., 2016 ; Sundell et al., 2020 ). Here we demonstrated that this strain is a virulent Fth WT strain and able to replicate in macrophage-like cell lines. In addition, in silico analysis of the genome of this strain confirms the presence of all common virulence factors of Fth ( Sundell et al., 2020 ). Furthermore, using this isolate ( Fth A-271), we corroborate earlier findings showing that the culturability of Francisella over time in water is improved at lower (4°C) temperatures rather than at higher ones (RT, 22.5°C). Furthermore, using the amoeba Naegleria gruberi we here can confirm prior publications, demonstrating that Francisella is not able to multiply in amoebae ( Acanthamoeba castellanii , A. polyphaga , Vermamoeba vermiformis ) ( Buse et al., 2017 ; Hennebique et al., 2021 ). However, lower temperatures and the presence of amoeba increased the survival and the long-term culturability of the bacterium ( Abd et al., 2003 ; El-Etr et al., 2009 ; Duodu and Colquhoun, 2010 ; Verhoeven et al., 2010 ; Gilbert and Rose, 2012 ; Ozanic et al., 2016 ; Buse et al., 2017 ; Golovliov et al., 2021 ; Hennebique et al., 2021 ). Therefore, we chose Fth A-271 WT strain to investigate its ability to form biofilms and to colonize and survive in a natural aquatic multi-species biofilm. Biofilm formation Strain Fth A-271 grown on agar plates or in medium T on Thermanox™ coverslips was able to form micro- and macro-colonies, as well as a 3D biofilm structure with a large amount of matrix material, containing strands of eDNA, carbohydrates, proteins and lipids. These results demonstrate the ability of this strain to form its own biofilm ( Figures 1A , C ). Investigating the survival of bacteria in natural water, the experiments demonstrated that the survival of bacteria in biofilms and planktonic bacteria seem to be similar, but the time-span of culturability of biofilm bacteria was increased compared to their corresponding planktonic form ( Figure 2 ). This indicates that bacteria within the biofilm stay culturable for a longer time as also shown for F. novicida and F. philomiragia or for Francisella in co-culture with amoebae ( Verhoeven et al., 2010 ; Ozanic et al., 2016 ; Buse et al., 2017 ; Siebert et al., 2020 ; Hennebique et al., 2021 ; Mlynek et al., 2021 ). The results suggest that biofilm formation may also enhance Francisella persistence within an aquatic habitat. Colonization of a natural aquatic biofilm (microcosm) We mentioned above that Fth WT strain A-271 in our experiment slowly lost its culturability and that they formed cells in a VBNC-like state ( Figure 4 ). VBNC has been described for Francisella , but to our knowledge, the ability to resuscitate these forms has not been published for Francisella so far ( Forsman et al., 2000 ; Thelaus et al., 2009 ; Duodu and Colquhoun, 2010 ; Backman et al., 2015 ). For Legionella pneumophila in contrast, it has been shown that resuscitation of bacteria in the VBNC status is possible in amoebae ( Steinert et al., 1997 ; Epalle et al., 2015 ). However, Francisella is able to survive and persist over long time periods in natural aquatic environments in a temperature-dependent manner ( Parker et al., 1951 ; Forsman et al., 2000 ; Sinclair et al., 2008 ; Berrada and Telford Iii, 2011 ; Broman et al., 2011 ; Gilbert and Rose, 2012 ; Golovliov et al., 2021 ). Furthermore, it was demonstrated that co-cultures of Francisella and amoebae increase the culturability but not the virulence of Francisella , as Francisella is not able to multiply within amoebae ( Abd et al., 2003 ; El-Etr et al., 2009 ; Verhoeven et al., 2010 ; Ozanic et al., 2016 ; Buse et al., 2017 ; Hennebique et al., 2021 ). In addition, microcosm experiments revealed that Francisella did not survive the grazing of the ciliate Tetrahymena pyriformis , while a nanoflagellate was found to favor Fth survival ( Thelaus et al., 2009 ). In addition, F. noatunensis survival was shown to be higher in sterile than in nonsterile microcosms ( Duodu and Colquhoun, 2010 ) and survival seems to be dependent on the number and species of bacterial grazing protozoa ( Mironchuk Iu and Mazepa, 2002 ; Thelaus et al., 2009 ; Duodu and Colquhoun, 2010 ); and own unpublished results). Thus, the survival of Francisella in the aquatic habitat is influenced by a high amount of different biotic and abiotic factors and therefore, we investigated the ability of Fth to colonize a multi-species biofilm. It has been demonstrated that multi-species biofilms are more resistant against stress compared to single-species biofilms ( Joshi et al., 2021 ; Wicaksono et al., 2022 ), but so far this has not been shown for Francisella . As mentioned above, the strain Fth A-271 was isolated from a dead beaver living in an aquatic habitat. Thus we analyzed the ability of this strain to survive and to colonize a natural aquatic multi-species biofilm, in a microcosm-like experiment. The coverslips were incubated for 4 weeks in a natural aquatic habitat at different seasons. We characterized these biofilms as a multi-species biofilm, exhibiting diatoms, Vorticellidae , Rotifera , as well as different amoebae and bacteria. Interestingly, these biofilms could be colonized by our Fth WT strain and we could observe micro- and macro-colonies, as well as mature biofilm-like structures of Fth within the natural biofilm. Furthermore, as demonstrated for the co-culture with amoebae, the presence of the natural biofilm increased the culturability of Fth ; and the effect was found also to be temperature-dependent (4°C > RT). Recently, research started to investigate general interspecies interactions (e.g., an biofilm adapted metabolism) within multi-species biofilms ( Joshi et al., 2021 ; Wicaksono et al., 2022 ) which may be also important for the persistence of Francisella in the environment. In this study, we demonstrated that Fth strains are able to successfully colonize natural-like aquatic multi-species biofilms, a behavior which seems to be important for their observed long-term survival within aquatic habitats. To our knowledge, we are the first to investigate if a Fth WT strain is able to colonize and survive within a natural aquatic multi-species biofilm. We can demonstrate that amoebae, biofilm formation and low temperatures increase the culturability (survival) of Fth in the aquatic environment and that Fth is, indeed, able to successfully colonize a multi-species biofilm. This may have impact on the long-term survival of Francisella in aquatic habitats and should be further investigated."
} | 2,797 |
39433727 | PMC11493965 | pmc | 5,462 | {
"abstract": "The anaerobic oxidation of alkanes is a microbial process that mitigates the flux of hydrocarbon seeps into the oceans. In marine archaea, the process depends on sulphate-reducing bacterial partners to exhaust electrons, and it is generally assumed that the archaeal CO 2 -forming enzymes (CO dehydrogenase and formylmethanofuran dehydrogenase) are coupled to ferredoxin reduction. Here, we study the molecular basis of the CO 2 -generating steps of anaerobic ethane oxidation by characterising native enzymes of the thermophile Candidatus Ethanoperedens thermophilum obtained from microbial enrichment. We perform biochemical assays and solve crystal structures of the CO dehydrogenase and formylmethanofuran dehydrogenase complexes, showing that both enzymes deliver electrons to the F 420 cofactor. Both multi-metalloenzyme harbour electronic bridges connecting CO and formylmethanofuran oxidation centres to a bound flavin-dependent F 420 reductase. Accordingly, both systems exhibit robust coupled F 420 -reductase activities, which are not detected in the cell extract of related methanogens and anaerobic methane oxidisers. Based on the crystal structures, enzymatic activities, and metagenome mining, we propose a model in which the catabolic oxidising steps would wire electron delivery to F 420 in this organism. Via this specific adaptation, the indirect electron transfer from reduced F 420 to the sulphate-reducing partner would fuel energy conservation and represent the driving force of ethanotrophy.",
"introduction": "Introduction Alkanes are the most reduced carbon compounds available in nature that can be used as cellular energy sources for microorganisms in oxic and anoxic environments 1 – 3 . Alkanes naturally perfuse in marine cold seeps and hydrothermal vents, but a biological filter composed of aerobic and anaerobic alkane-oxidising microorganisms prevents the alkanes release into the oceans and atmosphere while sustaining the surrounding chemoautotrophic microorganisms through sulphide generation 4 – 6 . The microorganisms performing the anaerobic oxidation of alkanes and their metabolisms are, however, relatively uncharacterised. The two ethane oxidisers are part of the Methanosarcinales order and were shown to catalyse the complete anaerobic oxidation of ethane, the second most abundant alkane in seeps 7 – 9 . These organisms are closely related and are proposed to be part of the same archaeal genus according to the Genome Taxonomy Data Base 10 . Ethane is activated as an ethyl-thiol adduct on the coenzyme M (CoM) via the ethyl-CoM reductase (ECR), an enzyme specific to these ethane-oxidising archaea 7 , 8 , 11 . It has been suggested that the generated ethyl-CoM is further processed to acetyl-Coenzyme A (acetyl-CoA) based on the knowledge acquired on methanogens belonging to the same order, together and supported by transcriptomics and proteomics data 7 , 8 . Based on the accepted metabolic model, the acetyl-CoA decarbonylase/synthase complex (ACDS) would transform the acetyl-CoA to generate CO 2 concomitantly with a methyl group branched on a tetrahydromethanopterin carrier (CH 3 -H 4 MPT, Fig. 1a ) and CoA. The methyl group would be oxidised through the reverse methanogenesis pathway and released as CO 2 by the formylmethanofuran dehydrogenase complex (Fmd/Fwd for molybdenum/tungsten-dependent enzymes, respectively. Fig. 1a ) 12 – 14 . Therefore, ethane would be ultimately oxidised into two molecules of CO 2, and the CO 2 -releasing enzymes (ACDS and Fwd/Fmd complexes) are expected to reduce ferredoxin, which is employed for energy conservation in methanogens 15 . The electrons released during ethane oxidation are supposed to be indirectly or physically transferred to sulphate-reducing bacteria living in a syntrophic partnership with the archaea 7 , 8 . Fig. 1 Proposed catabolism of Ca . E. thermophilum, and native purification of the CODH component and the Fwd/Fmd complex. a The pathway is based on studies described in Methanosarcinales 7 , 8 , 30 . The assembly of the ACDS (top) and Fwd (bottom) complexes are drawn in compliance with previous studies 17 , 19 , 62 . Arrows are coloured according to the corresponding metabolism, and dashed lines indicate multi-step transformations. White rounded rectangles framed by dotted lines illustrate internal channelling systems in which the substrates diffuse between both catalytic centres. Metallo-cofactor structures displayed in the inserts are derived from the deposited PDB models 1RU3 (acetyl-CoA synthase from Carboxydothermus hydrogenoformans 63 ), 3CF4 (carbonylated ACDS α 2 ε 2 subcomplex from M. barkeri 17 ) and 5T5M (Fwd complex from M. wolfei 19 ) with metals labelled in bold. cLys stands for carboxylysine. b Purification steps of the CODH component of the ACDS on native PAGE (left). (1) soluble extract; (2) anion exchange chromatography; (3, 4) hydrophobic exchange chromatography and (5) size-exclusion chromatography. The purified complex lacks the β, γ and δ subunits and, therefore, does not harbour the A-cluster and B 12 . c Purification steps of the Fwd/Fmd complex on native PAGE (left). (1) soluble extract; (2) anion exchange chromatography; (3) hydrophobic exchange chromatography and (4) size-exclusion chromatography. b , c An asterisk marks the band corresponding to the ECR 11 on the native electrophoresis profile. b , c A denaturing (right) PAGE of the final enriched fractions. The electrophoresis profiles were similar for each purification. Source data are provided as a Source Data file. The ethanotrophs do not contain any known membranous systems that would allow energy conservation from ferredoxin oxidation, questioning if the CO 2 -releasing step operated by ACDS and Fwd/Fmd would be necessarily coupled to ferredoxin reduction, as it is commonly assumed for methanogens and alkanotrophs. To solve this metabolic puzzle, we here characterise the multi-enzymatic ACDS and Fwd/Fmd complexes 16 – 23 by isolating the CODH component of the ACDS and the entire Fwd complex directly from a microbial enrichment of a syntrophic consortium composed of the ethane-oxidising archaeon Candidatus Ethanoperedens thermophilum and the sulphate-reducing bacterium Candidatus Desulfofervidus auxilii. The archaeon represents around 40% of the microbial population in the culture 8 . Purifying enzymes from such a heterogeneous microbial mixture is only feasible for highly abundant enzymes. Published transcriptomic data confirmed that the genes coding for the subunits of the ACDS and Fwd/Fmd complexes are among the 250 most expressed genes in the culture conditions 8 . The biochemical and structural characterisation of both complexes, as well as enzymatic assays, support that the CO 2 -generating steps are coupled to F 420 reduction instead of ferredoxin, suggesting that F 420 reduction is the main driver of this metabolism 24 .",
"discussion": "Discussion This study solved two crucial steps in the catabolic pathway of the ethane-oxidising archaeon Ca . E. thermophilum, deepening our knowledge of the ethanotrophy catabolism performed by the microbial community from deep-sea seeps. The illustrated native crystallisation approach, which could be applied to enrichment cultures of other slow-growing alkanotrophs, unveiled how these atypical archaea optimised their catabolism to derive cellular energy. The structural characterisation of these catabolic complexes illustrates once more how the evolution of microorganisms combines redox modules to cope with metabolic needs. The comparison of the CO 2 -releasing CODH component of the ACDS complex and Fwd with CO 2 -reducing homologues from other organisms shows a high conservation of the active sites. This suggests that metallo-cofactor modifications, coordination, or residue substitution in the active site would not dictate the reaction’s directionality. It will be determined by metabolic fluxes or, in the present case, by the final electron acceptor of the reaction. This concept is particularly important when studying the catabolism of anaerobic alkanotrophs, for which the metabolic pathways still remain to be biochemically characterised. The isolation of native systems from the thermophilic microbial enrichment revealed new pieces of the molecular puzzle of the anaerobic ethane oxidation, and the most intriguing is the key role of F 420 in this process. Relying on F 420 instead of ferredoxin as the final electron acceptor will affect the thermodynamics of the reactions. Considering the standard midpoint redox potentials of the CO-oxidation ( E ° CO/CO 2 = −520 mV 33 ) and formyl-MFR oxidation ( E ° formyl-MFR/MFR + CO 2 = −530 mV 34 ) coupled to F 420 -reduction ( E ° F 420 H 2 /F 420 = −340 mV 24 ), the F 420 -reduction coupled to substrate oxidation catalysed by ACDS and Fwd would be highly exergonic. This could represent the thermodynamic pull of the anaerobic ethane oxidation, preventing the reversal of the pathway in the absence of ethane (i.e. CO 2 conversion to ethane by relying on F 420 H 2 -oxidation would be endergonic under physiological conditions). This might be particularly important in seeps, where concentrations of CO 2 largely exceed those of ethane. In the same line of thought, the exergonic process could counterbalance one or several unfavourable enzymatic reactions occurring during the uncharacterised conversion of ethyl-CoM into acetyl-CoA, explaining why the ζ and FwdI subunits are apparently conserved in the other cultured ethanotroph Ca . A. ethanivorans 7 (Supplementary Figs. 16 , 17 ). Hence, this coupling would be specific to ethanotrophs as the metabolism of other alkanotrophs presents no selective pressure for such a thermodynamically favourable coupling. This agrees with the results presented, indicating that most methanogens and other alkanotrophs probably do not present such an enzymatic coupling (Fig. 4c and Supplementary Figs. 16, 17 ). The F 420 reduction coupled with CO 2 generation also explains the peculiar energy conservation strategy of Ca . E. thermophilum, for which the genome does not encode ferredoxin-dependent cation pumps (i.e. Ech or Rnf complex). In contrast, the Methanosarcina genus uses the reduced ferredoxin pool derived from CO-oxidation or formyl-MFR oxidation to pump H + /Na + by coupling ferredoxin oxidation to methanophenazine reduction or to generate H 2 30 . In the absence of the ferredoxin-dependent pumps, ferredoxin would not represent a viable electron carrier for energy conservation. Therefore, we hypothesise that this catabolism rather relies on the F 420 as a turntable electron carrier to drive ethanotrophy when dependent on a sulphate-reducing partner. In the proposed metabolic model (Fig. 5 ), the highly expressed Fpo complex (Supplementary Table 5 ) is the only energy-conserving system that would allow ion translocations across the membrane to fuel the ATP synthase. The electrons flowing to the extracellular and membrane-bound quinones would be consumed by the thermodynamically favourable sulphate reduction pathway of the bacterial partner. The interspecies transfer would be operated through an elusive path that might imply conductive nanowires 8 . The stoichiometry of the ethane/sulphate oxidoreduction performed by the consortium (4 moles of ethane oxidised for 7 moles of sulphate reduced 8 ) indicates that a total of seven F 420 H 2 could be potentially obtained from the complete oxidation of one ethane molecule. The oxidation of acetyl-CoA by the ACDS and the reactions occurring in reverse methanogenesis (by the Fwd complex and the methylenetetrahydromethanopterin dehydrogenase and reductase) would reduce four out of the seven F 420 . We propose that the missing reduced F 420 s are derived from the two oxidative steps occurring during the metabolic transformation of ethyl-CoM to acetyl-CoA. Despite the uncharted nature of the metabolic pathway, we would expect a generation of one F 420 H 2 and two reduced ferredoxins carrying one electron. The ferredoxins will be oxidised concomitantly with the heterodisulfide CoM-S-S-CoB, produced during ethyl-CoM generation, by the highly expressed putative F 420 -reducing electron-confurcating heterodisulphide reductase to generate two F 420 H 2 (Fig. 5 and Supplementary Table 5 ). The latter step is critical in the regeneration of the coenzyme employed for ethane capture. Since the carbon catabolic and anabolic pathways are expected to be separated, one would expect alternative CO 2 -entry points or carbon sources for carbon assimilation. However, the physiological utilisation of the F 420 H 2 pool could be extended to assimilatory and anabolic pathways, as suggested by the numerous frhB homologues in the genomes of ethanotrophs (Supplementary Fig. 17 ). This unexplored reservoir of reactions coupled to F 420 (H 2 ) oxidoreduction must contain potential unknown metabolic routes and, among them, the reactions behind the ethyl-CoM transformation that remains to be elucidated. Fig. 5 Proposed catabolic metabolism in the Ethane50 consortium. The structurally characterised enzymes are shown as surface representations, coloured as in Figs. 2 , 3 . The catabolic reactions are presented as large arrows coloured in grey, purple, red, and green, corresponding to the C2 part of ethanotrophy, ACDS activity, reverse methanogenesis, and sulphate reduction, respectively. A large dashed arrow indicates the yet uncharacterised ethyl-CoM to acetyl-CoA conversion. Orange arrows indicate F 420 reduction or F 420 H 2 oxidation events. Question marks highlight the uncharacterised reactions that would employ ferredoxin. The ferredoxins are assumed to accept a single electron. The interspecies electron transfer is schematised in a blue dashed line, and the transfer mechanism was omitted in the figure for clarity. The exact number of ions translocated by the Fpo system is not known and is therefore labelled n and hypothesised to be protons. The ion/ATP ratio of the ATP synthase is also not known, and therefore, x ATP is produced, while ions are proposed to be protons. The stoichiometry of sulphate reduction is not respected for clarity."
} | 3,552 |
35131853 | PMC8833168 | pmc | 5,463 | {
"abstract": "Significance Microbial cells organized on solid surfaces are the most ancient form of biological communities. Yet how single cells interact with surfaces and integrate a variety of signals to establish a sessile lifestyle is poorly understood. We developed and used sensitive biosensors to determine the kinetics of second messengers’ responses to surface attachment. This allowed us to examine cell-by-cell variability of the initial signaling events and establish that some of these events depend on flagellar motor function while others do not. Environmentally determined factors, like the energetic status of the cell, can modulate all signaling events. The complex interplay between the surface interaction inputs and external conditions can now be studied using our system.",
"discussion": "Discussion When bacterial cells attach to surfaces, a variety of “surface detectors” generate intracellular signals that inform the altered motility state ( 2 ). c-di-GMP stands out as an initial signal to surface encounter as well as a longer-term surface-sensing signal integrator. Indeed, its concentration increases within minutes of P. aeruginosa and C. crescentus surface attachment ( 6 , 29 , 30 ). In addition, c-di-GMP is essential to both forming and maintaining a biofilm structure in various bacteria ( 4 ). Here, we developed a bright fluorescent protein–based biosensor to determine the kinetics of c-di-GMP concentration changes that follow surface attachment in single E. coli . Our sensing system, which consists of c-di-GMP–responsive and c-di-GMP–unresponsive platforms ( Fig. 1 B ), informs us of changes in intracellular c-di-GMP as well as intracellular pH. We detected an increase in the c-di-GMP concentration within minutes of E. coli attachment to coverslips ( Fig. 2 A ), consistent with reports from other species ( 6 ). In addition, transient pH increases (alkaline spikes) were observed within seconds of the surface encounter. These spikes can be immediately followed by an increase in c-di-GMP ( Fig. 2 D ), which suggests that the alkaline spikes may trigger this increase. Indeed, DgcB, the C. crescentus enzyme responsible for c-di-GMP increase following attachment ( 29 ), has a pH-dependent activity that increases at alkaline pH ( 31 ). However, in our experimental setup, alkaline spikes per se are not sufficient to trigger the c-di-GMP rise, since cells lacking stator units do spike ( SI Appendix , Fig. S10 ), yet they do not increase intracellular c-di-GMP ( Fig. 4 ). As previously suggested ( 29 ), functional flagellar motors may be distinctively required to generate a higher-amplitude, local increase in pH (see next paragraph, SI Appendix , Supplementary Note ) necessary to activate a motor-associated diguanylate cyclase. How are the pH spikes generated? Similar pH transients have been observed in S. cerevisiae , in which they appear to be linked to glycolytic oscillations ( 27 ), in the mitochondrion as “mitoflashes” ( 32 , 33 ), and in plants ( 34 , 35 ). While the mechanism is not well understood, the spikes are thought to be generated by imbalances in the energy metabolism that trigger a pH increase followed by a compensatory mechanism that returns intracellular pH to its homeostatic value ( 36 ). How could surface attachment trigger an increase in intracellular pH? One possibility is that an extracellular pH increase at the attachment interface ( 37 ) triggers an increase in intracellular pH ( 26 ), which is then brought back to the set pH (generating a spike) by the metabolic enzymes involved in pH homeostasis. Such spikes could be generated in both motile and nonmotile cells and would depend on the nature of the attachment surface ( 37 ). An intracellular pH spike could be also generated by stalling the flagellar motor through flagellar interactions with the surface, followed by a similar compensatory mechanism. Indeed, at 100 Hz rotation, a flagellar motor translocates around 50,000 protons per second ( 38 , 39 ). Even though this is a small contributor to the total proton influx ( 38 ), the stall can produce measurable pH spikes, particularly if there is a delay in the proton homeostasis feedback mechanism ( SI Appendix , Supplementary Note ). A spike generated by the second mechanism would require functional flagellar motors and could display a higher amplitude in the vicinity of the motor. We detected only a modest increase in intracellular c-di-GMP concentration for cells attaching in glucose motility buffer ( SI Appendix , Fig. S9 ). Glucose inhibits E. coli biofilm formation ( 40 , 41 ), and this effect is mediated in part by the decreased intracellular cyclic AMP (cAMP) that results from glucose utilization as a carbon source ( 40 , 41 ). Interestingly, for P. aeruginosa , a cAMP increase is thought to precede and trigger the c-di-GMP increase ( 7 , 42 ). P. aeruginosa initial attachment events do occur on a longer timescale than our attachment experiment (hours versus minutes) ( 7 ). However, the same hierarchical second messenger cascade (cAMP, then c-di-GMP) may occur for E. coli surface attachment, too. Alternatively, cAMP may play a permissive, carbon source–informative role in E. coli biofilm formation ( 43 ). The periodic alkaline spikes observed in the glucose motility buffer ( Fig. 3 B ) are striking and reminiscent of the pH oscillations observed in S. cerevisiae during glycolysis ( 27 ). Distinctly, though, E. coli need not be starved to trigger such oscillations, since we immediately transferred the cells from growth media to the buffer containing glucose. Why, then, would the internal pH oscillate upon attachment? Glycolytic enzymes do oscillate together with the internal pH ( 27 , 44 ), and the key enzyme phosphofructokinase is pH sensitive ( 27 ). An initial transient increase in pH following surface attachment could trigger an oscillatory behavior of the glycolytic enzymes and of the internal pH. Both the pH spiking behavior as well as the c-di-GMP increase display a lot of cell-to-cell variability ( Figs. 2 C and D and 3 ). The variability might be due, in part, to the heterogeneity of the E. coli –surface interactions, since some cells approach and interact with the surface over their entire length, while other cells interact closely only at the poles (as seen in our TIRF images, Fig. 2 A ). It would be interesting to establish if this heterogeneity persists to create a low c-di-GMP population and a high c-di-GMP population, as for P. aeruginosa ( 5 )."
} | 1,632 |
27489747 | null | s2 | 5,465 | {
"abstract": "Regeneration of functional polymer surfaces after damage or contamination is an unresolved scientific challenge, and also of practical importance. In this proof-of-concept study, we present a method to regenerate a functional surface property using a polymer multi-layer architecture. This is exemplified using antimicrobially active surfaces. The idea is to shed the top layer of the polymer layer stack, like a reptile shedding its skin. The proof-of-concept stack consists of two antimicrobial layers and a degradable interlayer. Shedding of the top layer is enabled by degrading that interlayer. The shedding process was analyzed by quantitative fluorescence microscopy, ellipsometry, and FTIR spectroscopy. Antimicrobial assays revealed that the functionality of the emerging antimicrobial layer was fully retained after shedding."
} | 208 |
36975684 | PMC10048633 | pmc | 5,466 | {
"abstract": "Polysaccharide-based graft copolymers bearing thermo-responsive grafting chains, exhibiting LCST, have been designed to afford thermo-responsive injectable hydrogels. The good performance of the hydrogel requires control of the critical gelation temperature, T gel . In the present article, we wish to show an alternative method to tune T gel using an alginate-based thermo-responsive gelator bearing two kinds of grafting chains (heterograft copolymer topology) of P(NIPAM 86 - co -NtBAM 14 ) random copolymers and pure PNIPAM, differing in their lower critical solution temperature (LCST) about 10 °C. Interestingly, the T gel of the heterograft copolymer is controlled from the overall hydrophobic content, NtBAM, of both grafts, implying the formation of blended side chains in the crosslinked nanodomains of the formed network. Rheological investigation of the hydrogel showed excellent responsiveness to temperature and shear. Thus, a combination of shear-thinning and thermo-thickening effects provides the hydrogel with injectability and self-healing properties, making it a good candidate for biomedical applications.",
"conclusion": "3. Conclusions A heterograft copolymer constituted of an alginate backbone bearing two kinds of grafting chains, was synthesized and explored as a gelator in aqueous media. The grafting chains are P(NIPAM 86 - co -NtBAM 14 ) random copolymers and pure PNIPAM, differing in their LCST about 10 °C. Due to the thermo-responsive side chains, the ALG/HGC copolymer self-assembles upon heating, exhibiting sol–gel transition, T gel , at 28.9 °C, which lays between the T gels of the corresponding homo-grafted copolymers. Interestingly, the T gel of the heterograft copolymer is controlled from the overall hydrophobic content, NtBAM, of both grafts, implying the formation of blended side chains in the crosslinked nanodomains of the formed network. Rheological investigation of the hydrogel showed excellent responsiveness to temperature and shear. Thus, a combination of shear-thinning and thermo-thickening effects provides the hydrogel with injectability and self-healing properties, making it a good candidate for potential applications such as tissue engineering, and drug delivery. However, specific applications require further evaluation of additional properties such as bioadhesion, biocompatibility/toxicity, payload loading/delivery, hydrogel erosion, etc.",
"introduction": "1. Introduction Three dimensional (3D) networks formed by hydrophilic polymers (gelators), bearing hydrophobic sticky chains and/or specific functionalities, of a large variety of macromolecular topologies (e.g., triblocks, stars, graft copolymers and/or terpolymers) have been designed and explored in aqueous media [ 1 , 2 , 3 , 4 ]. These formulations, also called hydrogels, due to their high water content, have attracted the immense attention of the scientific community thanks to their potential in a vast variety of applications [ 5 , 6 , 7 , 8 ]. As far as biomedical applications are concerned, namely drug delivery, tissue engineering, wound dressing, etc. [ 8 , 9 , 10 , 11 , 12 , 13 , 14 ], a specific design of the gelator is needed to meet the requirements of a given application that is among others, biocompatibility, controlled biodegradability, specific functionality, crosslinking density (porosity), reversibility, suitable mechanical properties, injectability and self-healing [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. Stimuli-responsive water-soluble polymers, are polymers the chain conformation of which is abruptly changed (e.g., coil–globule transition), responding to changes in their environments such as temperature, pH, etc. This functionality has attracted the attention of polymer designers to achieve some of the aforementioned requirements (e.g., injectability) for a tailor-made gelator [ 1 , 4 , 5 ]. For instance, thermo-responsive polymers exhibiting LCST, transforming reversibly from hydrophilic (non-associative) to hydrophobic (associative) upon heating, have been incorporated as sticky building blocks to prepare thermo-responsive gelators [ 18 , 19 , 20 ]. At temperatures below LCST (e.g., room temperature), their aqueous solutions flow easily (sol state) and thus can be effortlessly injected into an environment of a higher temperature than the LCST. At the injection site (e.g., body temperature) the polymer gelator forms a 3D network (gel state), due to the association of the sticky LCST polymer blocks, forming the physical crosslinks. Poly(N-isopropyl acrylamide) (PNIPAM) is one of the most used LCST polymers for the fabrication of thermo-responsive gelators because it exhibits an LCST at about 32 °C which is above the room temperature (20–25 °C) but lower than the physiological temperature (37 °C), making it appropriate for biomedical applications [ 19 , 21 , 22 ]. Concerning the non-associative hydrophilic part of the gelator, forming the bridges between the crosslinks of the network, polysaccharides (very important biopolymers abundantly present in nature) have been widely used to design biocompatible and biodegradable gelators [ 23 ]. From a synthetic point of view, polysaccharides bear suitable functional groups (e.g., COOH, OH, NH 2 , etc.), capable of easy modification and grafting reactions, allowing to fabrication of carbohydrate-based graft copolymer gelators [ 24 , 25 ]. Among others, alginate has been used as the hydrophilic backbone of graft copolymers, bearing carboxyl groups that can be utilized for grafting LCST-type polymers, yielding thermo-responsive hydrogels. Alginate-based copolymers with PNIPAM grafting chains, exhibiting sol–gel transitions in the vicinity of the physiological temperature have been reported previously [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. One of the critical parameters of the hydrogel properties is the sol–gel transition temperature ( T gel ), which affects the entire performance of the hydrogel, namely injectability, in situ gelling, and mechanical suitability at the conditions (pH, temperature, ionic strength) of the targeting site environment (e.g., physiological, tumor, wound). A facile tuning of T gel can be achieved by incorporating hydrophobic monomers into the PNIPAM side chains. As has been shown recently, in alginate-based graft copolymers, T gel decreases linearly with the content of the N-tert-butyl acrylamide (NtBAM) hydrophobic monomer of the P(NIPAM- co -NtBAM) random copolymer side chains which allow fine-tuning of the sol–gel transition. Moreover, the shift of the transition to lower temperatures significantly affects the hydrogel elasticity at the physiological temperature [ 36 ]. Recently, similar conclusions have been deduced from hyaluronan-based thermo-responsive graft copolymers [ 37 ]. In the present article, we wish to show an alternative method to tune T gel using an alginate-based thermo-responsive gelator of heterograft copolymer topology namely, a polymer backbone grafted by two types of different nature polymer chains [ 38 ]. In a two-pot reaction, alginate was grafted sequentially by P(NIPAM 86 - co -NtBAM 14 ) (86/14 molar ratio) random copolymers and PNIPAM homopolymer pendant chains, displaying different LCSTs. The heterograft copolymer gelator exhibited T gel between those of the Alg-g-P(NIPAM 86 - co -NtBAM 14 ) and Alg-g-P(NIPAM). Interestingly, the determining factor regulating T gel is the overall NtBAM content of both grafting chains. The prepared hydrogel exhibits also thermo-/shear- induced injectability and self-healing properties thanks to the excellent shear- and thermo-responsiveness and seems suitable for biomedical potential applications.",
"discussion": "2. Results and Discussion 2.1. Synthesis and Characterization of Heterograft Copolymer A heterograft copolymer constituted of alginate (ALG) backbone grafted by two different LCST-type thermo-responsive polymers, displaying discernible LCSTs, was synthesized according to the grafting onto methodology. Amino-functionalized NH 2 -P(NIPAM 86 - co -NtBAM 14 ) random copolymer and NH 2 -PNIPAM homopolymer with LCST of 22 and 32 °C, respectively, were used as the grafting chains [ 36 ]. The synthesis of the copolymer was conducted In aqueous media using carbodiimide chemistry for the conjugation of the amine end-function of the grafts onto the carboxyl groups of ALG according to standard methods [ 31 , 33 , 34 , 36 ]. Figure 1 depicts schematically the grafting reaction, accomplished in a two-pot reaction. In the first step, the ALG-g-P(NIPAM 86 - co -NtBAM 14 ) graft copolymer was synthesized, isolated, and characterized, as reported previously [ 36 ]. At a second step, the ALG-g-P(NIPAM 86 - co -NtBAM 14 ) graft copolymer was grafted by the NH 2 -PNIPAM homopolymer, yielding the final ALG-[g-P(NIPAM 86 - co -NtBAM 14 )]-g-P(NIPAM) heterograft copolymer (ALG/HGC). 1 H-NMR was used to characterize the ALG/HGC in terms of monomer composition, NtBAM content of the grafts, and grafting density (number of grafts per ALG backbone) ( Figure S1 ). Table 1 shows the molecular characteristics of the ALG/HGC. 2.2. Thermo-Gelling Behavior Aqueous solutions of ALG/HGC, of 5 wt% polymer concentration, were prepared, and their thermo-responsive behavior was explored by using oscillatory shear experiments in the linear viscoelastic region (LVR). The pH of the solutions was adjusted to 7.4 in all cases. The formulation was charged in the rheometer at elevated temperature (gel state) and a successive cooling/heating ramp was applied with a rate of 1 °C/min, setting the frequency at 1 Hz and strain amplitude at 0.1% within the LVR. The data of this experiment, in terms of storage (G’) and loss (G”) modulus versus temperature, are demonstrated in Figure 2 a. At elevated temperatures, the polymer solution behaves as gel since the storage modulus dominates to a loss modulus, whereas at low temperatures the opposite effect (G” > G’) occurs showing a sol state. The moduli follow different paths in the cooling–heating procedure, manifesting a hysteresis, due to the exchange dynamics of the associative side chains of the graft copolymer [ 36 ]. The crossover of G’/G” determines the sol/gel transition defining the T gel . As demonstrated in Figure 2 (photos), at low temperatures (e.g., 10 °C) a transparent solution is formed, which flows relatively easily (sol state). At high temperatures, well above T gel (e.g., 50 °C), a free-standing gel exists, revealing the formation of a 3D network constituted of physically crosslinked nanodomains of the associated thermo-responsive side chain, bridged by the alginate segments existing between the grafting points. The oscillatory data can also be demonstrated by plotting a single parameter (complex viscosity, η * ) as a function of temperature. Figure 2 b shows η * vs. T for the heating procedure. As observed, the viscosity at temperatures below 24 °C (sol state) is of the order of 2 Pa.s, which is about three orders of magnitude higher than the viscosity of the aqueous medium. Provided that the entanglement regime in aqueous polymer solutions is approximately reached at η = 30 η solvent , [ 37 , 39 ] the polymer concentration of 5 wt% is clearly higher than the entanglement concentration, C e , which justifies the observed high viscosity values. More importantly, the viscosity rises above 24 °C, about one order of magnitude up to 35 °C, and continues to rise to 50 °C, but at a slower rate. Above 24 °C (defined as T ass ), the solution becomes turbid (see photo at 25 °C in Figure 2 b inset) revealing the onset of the hydrophobic association of the side thermo-responsive chains of the graft copolymer. Above T ass and up to T gel , the hydrophobic interactions are still very weak, as G” is still lower than G’. Above T gel these interactions are continuously strengthened, leading to the formation of a 3D network. Provided that the graft copolymer bears two kinds of side chains of different critical solution temperatures, the rising question is whether the P(NIPAM 86 - co -NtBAM 14 ) chains, with the lower LCST, will associate first, followed by PNIPAM association at a higher temperature. To answer this question, we have plotted the oscillatory temperature ramp (heating procedure) for the heterografted ALG/HGC and the corresponding ALG-g-P(NIPAM 86 - co -NtBAM 14 ), ALG-g-P(NIPAM) homo grafted copolymers. As can be seen in Figure 3 , the overall behavior of the three copolymers is similar. That is, the moduli increase with temperature passing a single crossover point (G′ = G″, tanδ = 1). The main observation is that the critical temperature T gel of the ALG/HGC has been shifted to a higher temperature with respect to that of the ALG-g-P(NIPAM 86 - co -NtBAM 14 ) precursor. This behavior reminisces the shift of T gel with varying the hydrophilic/hydrophobic content of the grafting chains observed recently [ 36 ]. If we consider that the addition of the PNIPAM side chains decreases the overall NtBAM content of the side chains from 86/14 to 91/9, then the data of the heterograft copolymer should fit with the linear function of T gel versus NtBAM content as observed previously [ 36 ]. Indeed, this is the case as clearly observed in Figure 4 , implying that the different side chains have been blended, exhibiting an intermediate T gel . This seems reasonable since in P(NIPAM 86 - co -NtBAM 14 ) and PNIPAM side chains, NIPAM monomer repeating units are dominating and thus they are compatible, suggesting the formation of mixed crosslinking domains. This also suggests that T gel should be predicted by the formula: T gel (HGC) = w 1 T gel P(NIPAM 86 - co -NtBAM 14 ) + w 2 T gel (PNIPAM) (1) \nwhere w 1 and w 2 (w 1 + w 2 = 1) are the weight fraction of the corresponding side chains on the ALG/HGC. Indeed, applying Equation (1) with w 1 = 0.60, T gel P(NIPAM 86 - co -NtBAM 14 ) = 23.8 °C and w 2 = 0.40, T gel (PNIPAM) = 38 °C, the calculated value, T gel (HGC) = 29,4 °C, is very close to the experimental one of 28.9 °C, verifying mixing of grafting chains in the crosslinked domains. The present results seem to be in very good agreement with those predicting T gel by blending two ABC triblock terpolymers with different C blocks namely: P(NIPAM-r-BA)-b-PDMAAm-b-P(NIPAM-r-BA) and (P(NIPAM-r-BA)-b-PDMAAm-b-PNIPAM) with PDMAAm (Poly(N,N-dimethyl acrylamide, hydrophilic)) and P(NIPAM-r-BA) NIPAM/butyl acrylate random copolymer (BA, hydrophobic) [ 40 ]. Note that the thermo-responsive C blocks are the pure PNIPAM and the random copolymer P(NIPAM-r-BA), where a portion of BA hydrophobic monomer has been incorporated in the PNIPAM block, which is relevant to our case. 2.3. Rheological Properties The mechanical properties of the ALG/HGC formulation were further explored by oscillatory shear experiments at constant temperatures. Figure 5 a demonstrates the G’, G” as a function of angular frequency at selected temperatures. At 28 °C (vicinity of T gel ), tanδ (G″/G’) is close to unity and the frequency dependence power exponent is approximately 0.5, as expected for the sol–gel transition point. At the physiological temperature, 37 °C, G’ dominates G″ in the entire frequency range. The terminal zone is not visible at low frequencies, implying the formation of a 3D network with kinetically “frozen” crosslinked grafting chains, since their exchange dynamics slow down due to the increased hydrophobicity [ 36 , 41 ]. By increasing the temperature to 45 °C, the same behavior is observed with higher values in the moduli, suggesting further strengthening of the network. It is interesting to look at the effect of adding PNIPAM grafts onto the ALG-g-P(NIPAM 86 - co -NtBAM 14 ) precursor on the elasticity of the network. The storage moduli, reflecting the elasticity of the network, for the ALG/HGC and its precursor, are depicted at selected temperatures in Figure 5 b. As can be seen, the storage moduli of the heterograft copolymer are lower than those of its precursor in all temperatures, although the number of grafts (stickers) per alginate backbone increased for the heterograft. This probably could be attributed to the T gel shift to higher temperatures for the ALG/HGC, which moves the gel window too, as has been previously reported [ 36 ]. Provided that the moduli increase with temperature, at a given temperature, the G’ will be lower for the formulation exhibiting higher T gel ( Figure 3 ). To evaluate if this is valid, the G’ values of the ALG/HGC have been shifted in the temperature axis (T-ΔΤ, ΔΤ = 5.1 °C) to coincide with the T gel of its ALG-g-P(NIPAM 86 - co -NtBAM 14 ) precursor. Indeed, the G’ values of the two formulations almost coincide above T gel ( Figure 6 ) confirming the aforementioned hypothesis. Thus, the level of elasticity of the two grafts is almost similar above their critical T gel , implying similar crosslinking density. This is additional indirect evidence that the different side chains are blended in the crosslinking nanodomains of the network. We should mention, however, that in both systems we are in the semi-dilute regime and chain entanglements contribute to elasticity. Provided that the chain backbone in both graft copolymers is the same, we do not expect notable differences in their entanglement number density. 2.4. Injectability and Self-Healing As far as biomedical applications are concerned, injectability is one of the critical properties of hydrogels, as carriers of payloads. For this purpose, shear flow experiments were designed and conducted to evaluate the response of the hydrogel to temperature and shear rate. Figure 7 a demonstrates consecutive shear viscosity time sweep, in time intervals of 60 s, at room (20 or 25 °C) and physiological (37 °C) temperatures. A constant shear rate at 17.25 s −1 was applied, which simulates an injection procedure through a 28-gauge syringe needle [ 41 , 42 ]. The viscosity changes slightly from 20 to 25 °C since the solution is still in the sol state and is of the order of 0.3 Pa.s which is an acceptable value for injection. Upon switching the temperature to 37 °C, the viscosity jumped to 4.2 Pa.s, more than one order of magnitude, due to the thermothickening effect ( Figure 3 ). The viscosity of the solution responds instantly in every stepwise alteration of temperature, with very good reproducibility, showing that the formulation exhibits excellent thermo-responsiveness. Another experiment was designed to evaluate the response of the formulation to simultaneous changes in shear and temperature, as occurs during injection from room to body temperature. Figure 7 b presents the shear viscosity time sweep steps after applying shear rate and/or temperature changes. At 20 °C (room temperature), the viscosity drops instantly by changing the shear rate from 0.01 s −1 (approach of rest) to 17.25 s −1 (injection conditions). This shear thinning effect is due to the disruption of the entanglements since it is in the sol state. The viscosity increases instantly about four orders of magnitude, following the temperature jumps to 37 °C and the shear rate decrease at 0.01 s −1 . This is mainly due to the network formation, induced by the hydrophobic association of the macromolecules at 37 °C (in situ gelling), as shown in Figure 3 . This result clearly demonstrates the excellent response of the formulation to shear and temperature, implying good injectability, provided that the viscosity is low (0.3 Pa) at the injection conditions (i.e., T = 20 °C and shear rate 17.25 s −1 ). Moreover, the viscosity profiles are reproducible, irrespective of the direction of temperature changes (heating or cooling). Importantly, after the disruption of the gel at low temperature and high shear (step 6, Figure 7 b) the hydrogel is instantaneously recovered at 37 °C due to the formation of the hydrophobic junctions (step 7, Figure 7 b), suggesting self-healing capability of the ALG/HGC hydrogel [ 36 , 43 ]. To further evaluate the self-healing of the formulation, an alternative experiment was designed and conducted using stepwise oscillatory tests. Particularly, the hydrogel was subjected to a strain sweep, far beyond the linear regime to disrupt the network, followed by a time sweep, setting the strain amplitude at 1%, within the linear regime at 37 °C. As seen in Figure 8 , in the first step the hydrogel is liquified above 288% strain (G’/G″ crossover). The moduli decreased steadily up to 900% strain with G″ dominating G’, confirming thus the mechanical disruption of the network structure. Upon sudden decrease in the strain from 900 to 0.1%, the hydrogel is recovered instantly since G’ dominates again G″, implying the reformation of the network, confirming therefore the self-healing ability of the hydrogel. Certainly, a large number of polymeric gelators have been designed so far to afford thermo-responsive injectable hydrogels [ 1 , 4 , 9 , 10 , 41 , 44 ]. In most cases, these gelators are segmented macromolecules (block copolymers) bearing associative thermo-responsive blocks in various macromolecular architectures, e.g., triblock copolymers, graft copolymers, stars, etc. The graft copolymer topology, suggested in the present case, offers some advantages with respect to synthetic copolymers (diblocks, triblocks, etc.). Beyond the synthetic simplicity and facility, the possibility to involve natural polymers such as polysaccharides, endowing the gelator with their characteristics such as biocompatibility and biodegradability, makes them compatible with biomedical applications. Particularly, the present work focuses on the issue of tunning T gel , which is critical for the hydrogel performance (e.g., injectability, 3D printability). Moreover, the heterograft type topology adopted in this work seems beneficial since it allows control of T gel and in turn of the hydrogel properties at the required conditions (room and body temperature). Importantly, it allows easy retro design by further grafting and/or adding required functionalities, depending on the specific applications. For instance, for wound healing applications, alginate-based hydrogels have been suggested. In this case, partial oxidation and dopamine functionalization are needed to promote biodegradability and bioadhesion, respectively [ 45 ]."
} | 5,587 |
38107308 | PMC10724560 | pmc | 5,467 | {
"abstract": "Integrating two-dimensional (2D) semiconducting materials into memristor structures has paved the way for emerging 2D materials to be employed in a vast field of memory applications. Bismuth oxyselenide (Bi 2 O 2 Se), a 2D material with high electron mobility, has attracted significant research interest owing to its great potential in various fields of advanced applications. Here, we explore the out-of-plane intrinsic switching behavior of few-layered Bi 2 O 2 Se via a cross point device for application in conductive bridge random access memory (CBRAM) and artificial synapses for neuromorphic computing. Via state-of-the-art methods, CVD-grown Bi 2 O 2 Se nanoplate is applied as a switching material (SM) in an Al/Cu/Bi 2 O 2 Se/Pd CBRAM structure. The device exhibits ∼90 consecutive DC cycles with a tight distribution of the SET/RESET voltages under a compliance current (CC) of 1 mA, a retention of over 10 ks, and multilevel switching characteristics showing four distinct states at Vread values of 0.1, 0.2, 0.25, and 0.3 V. Moreover, an artificial synapse is realized with potentiation and depression by modulating the conductance. The switching mechanism is explained via Cu migration through Bi 2 O 2 Se based on HRTEM analysis. The present structure shows potential for future integrated memory applications.",
"conclusion": "4 Conclusions An Al/Cu/Bi 2 O 2 Se/Pd-based cross point CBRAM device was successfully fabricated. The device exhibits resistive switching at a low voltage level (+1.5 V/-1.5 V) and basic memory functions, including endurance (>90 cycles), cumulative probability (∼99 %), and retention (@ Vread of 0.1 V) over 10 ks (R HRS /R LRS >10). In addition, the device shows multilevel switching behavior via four distinct stable switching states. Artificial synapses are mimicked by conductivity modulation, showing potentiation (35 states) and depression (41 states). The current conduction mechanism encompasses Schottky (during the HRS) and Ohmic (during the LRS) conduction phenomena. Furthermore, the switching mechanism involving Cu migration through Bi 2 O 2 Se has been conceptually explained with the aid of HRTEM imaging. With our findings, Bi 2 O 2 Se-based CBRAM devices can potentially be applied for memory and artificial synapse applications.",
"introduction": "1 Introduction In parallel with the Internet of Things (IoT) and artificial intelligence (AI), devices with a high storage capacity for ease of storage, computing, and transmission are becoming more crucial to deal with the excessive information [ 1 ]. The traditional von Neumann architecture based on physically separated memory and processors adds challenges for the processing speed and energy-efficient data transfer due to bottleneck. Among various technological developments, complementary metal–oxide–semiconductor (CMOS) technology is widely accepted because of its merits, including being favorable in the semiconductor industry in terms of design and fabrication within scaling limits following Moore's law [ 2 ]. The scaling restriction with CMOS technology has revolutionized various emerging memory techniques during the last couple of decades. Foremost are magnetic random access memory (MRAM), phase change memory (PCM), ferroelectric random access memory (FERAM), and resistive random access memory (RRAM) [ 3 , 4 ]. Among them, RRAM is well considered to be the most capable for future data storage technology because of its merits of smaller storage cells, a higher storage density, and faster speeds in write and read processes [ [5] , [6] , [7] , [8] , [9] ]. The fundamental configuration of RRAM is based on a metal–insulator–metal (MIM) structure with a top electrode (TE) and a bottom electrode (BE) separated by at least one dielectric layer or a switching material (SM) [ 10 ]. The key parameters (reported with critical values) for RRAM are as follows: (1) resistance ratio: ratio of the resistances in the HRS and LRS, 10 9 ; (2) endurance: maximum number of recoverable cycles between the HRS and LRS, 10 12 ; (3) retention: time duration for data storage, 10 years; (4) operating voltage: minimum voltage required to alter the resistance states from the LRS to the HRS or from the HRS to the LRS; and (5) switching speed: write voltage pulse width, 10 ns [ [11] , [12] , [13] ]. The switching behavior of RRAM devices has been extensively studied, with their further classification into two major categories, namely, valence change memristors (VCMs) and electrochemical metallization memristors (ECMs). The switching mechanism in VCMs critically depends on ion vacancies or oxygen vacancies in the SM. Although VCMs are fascinating for their well-suited process and steady switching characteristics, they face challenges of a lower dynamic range, a higher off current (excess power feeding), and uncontrolled ion movement. Conductive-bridge random access memories (CBRAMs), also known as ECMs, employ switching behavior based on the formation of conductive filaments between the TE and BE via the redox reaction of the metal. Overcoming the demerits of VCMs, CBRAMs are widely considered to have a higher dynamic range, a lower off current (higher on-off ratio), a higher switching speed, and upgraded scalability [ [14] , [15] , [16] ]. CBRAM, in its primitive structure, comprises a specific switching material (SM) sandwiched between an electrochemically active metal electrode (Cu, Ag) and an electrochemically inert metal electrode (W, Pt, TiN) [ 17 ]. For the switching materials in CBRAM, different classes of materials have been explored, including chalcogenide glasses [ 18 ], oxides [ 19 ], polymers [ 20 ], g-C 3 N 4 and its nanocomposites [ 21 , 22 ]. All these existing SMs have scalability challenges. Two-dimensional materials (2DMs), such as MoS 2 [ 23 , 24 ], h-BN [ 25 ], black phosphorus [ 26 ], and MXene [ 27 ], have been investigated as SMs and electrodes for CBRAM applications. Because of the layered structure containing atomically thin layers, 2DMs facilitate low voltage operation and stable resistive switching characteristics. Since the implementation of 2DMs in CBRAM results in an improvement in performance, exploring new 2DMs for CBRAM remains an open and important research area for realizing CBRAM with optimum performance. Recently, the atomically thin ternary 2DM bismuth oxyselenide (Bi 2 O 2 Se), with a suitable bandgap, has received much attention due to its quasi-2D structure, high electron mobility, and robust air stability [ [28] , [29] , [30] ]. Bi 2 O 2 Se presents a highly symmetric atomic structure with a tetragonal lattice ( I 4/ mmm ; a = b = 3.88 Å, c = 12.16 Å) where eight Bi atoms compose a cube with a Se atom at the body center and with uniform alignment of [Bi 2 O 2 ] n 2n + layers along the c axis. With a key difference from van der Waals layered 2DMs, Bi 2 O 2 Se is recognized as an ionic layered material formed via cation, [Bi 2 O 2 ] n 2n+ , and anion, [Se] n 2n− , stacked layers through weak electrostatic interactions. However, similar to other 2DMs, Bi 2 O 2 Se shows characteristics of layer-number dependent bandgap and optical absorption [ 31 ]. Bi 2 O 2 Se has a low electron effective mass of ∼0.14m 0 , which is lower than that of silicon (∼0.26m 0 ) and MoS 2 (∼0.4m 0 ), revealing a high electron mobility suitable for electronic and optoelectronic applications [ [32] , [33] , [34] ]. Wu et al. reported that the electron Hall mobility of a nonencapsulated Bi 2 O 2 Se flake (∼20.9 nm) was measured to be 28,900 and 150 cm 2 V −1 s −1 at 1.9 K and room temperature, respectively [ 28 ]. The synthesis of Bi 2 O 2 Se is one of the key interests of this research. Different approaches have been reported for the synthesis of Bi 2 O 2 Se, including hydrothermal [ 35 , 36 ], solution-assisted [ 37 ], composite-molten-salt (CMS) [ 38 ], and vapor deposition processes [ 28 , 31 ]. Wu et al. demonstrated the synthesis of 2D Bi 2 O 2 Se single crystals (grain size ∼ 200 μm, thickness down to monolayer ∼ 0.61 nm) on mica substrates via coevaporation of Bi 2 O 3 and Bi 2 Se 3 powders as precursors by the chemical vapor deposition (CVD) method. In the CVD approach for the synthesis of Bi 2 O 2 Se, a mica substrate is widely used because the strong Coulomb interaction between mica and Bi 2 O 2 Se facilitates the lateral growth of Bi 2 O 2 Se for large-scale 2D Bi 2 O 2 Se sheets [ 31 ]. Recently, Khan et al. reported the synthesis of a 2D Bi 2 O 2 Se single crystal with a grain size on the order of millimeters and thickness down to a monolayer by an ambient‐pressure vapor–solid (VS) deposition approach [ 39 ]. The unique structural and physical properties of Bi 2 O 2 Se have been further proven by implementation in devices for novel applications such as thin film transistors [ 40 , 41 ], photodetectors [ 42 , 43 ], artificial synapses [ 44 , 45 ], multifunctional optoelectronics [ 46 ], and optical switches [ 47 ]. Recently, Bi 2 O 2 Se has been employed in memristor structures [ 44 ]. As an example, Liu et al. demonstrated a Bi 2 O 2 Se-based memristor (three terminals) via the application of Bi 2 O 2 Se nanoplates as the bottom electrode (BE). With aid of the similar structure, the function of the “NAND” gate was realized by tuning the electric field polarity of Bi 2 O 2 Se through a metal contact (Pd) [ 48 ]. In another study, Chen et al. demonstrated out-of-plane resistive switching of thick Bi 2 O 2 Se flakes by forming hillocks via the application of a vertical electric field [ 49 ]. Recently, Liu et al. extended the application of the Bi 2 O 2 Se-based memristor (three terminal) structure to security applications by employing the device as a true random number generator [ 50 ]. Moreover, Lai et al. reported advanced impacts of nanotechnology, including recent Bi 2 O 2 Se-based miscellaneous reports [ 51 ]. Although many reports have demonstrated significant efforts for the application of Bi 2 O 2 Se in memristors, the implementation of Bi 2 O 2 Se as a true SM in memristors remains elusive. Motivated by recent reports on the application of Bi 2 O 2 Se in memristor devices, here, we explore the inherent intrinsic switching property of Bi 2 O 2 Se by implementing it as an SM in the CBRAM structure Al/Cu/Bi 2 O 2 Se(SM)/Pd/SiO 2 /Si. The fabricated device exhibits basic switching characteristics at low voltage levels <1.5 V, including endurance (∼90 cycles), cumulative probability (∼99 %), and retention @ Vread of 0.1 V for over 10 ks. With the aid of distinct Vread values of 0.1 V, 0.2 V, 0.25 V and 0.3 V, multilevel switching characteristics are realized. Moreover, artificial synapses are realized by means of potentiation (35 states) and depression (41 states). The switching mechanism is proposed to occur via migration of Cu ions through SM Bi 2 O 2 Se based on HRTEM analysis. Therefore, the presented results show sufficient potential for Bi 2 O 2 Se-based CBRAM for future advanced memory applications enriched with artificial neuromorphic activities.",
"discussion": "3 Results & discussion Fig. 1 a shows a schematic diagram of the layered crystal structure of Bi 2 O 2 Se with integral elements “Bi”, “O”, and “Se” in distinguishable colors green, red, and blue, respectively. The schematic integrates four layers of cation [Bi 2 O 2 ] n 2n+ , and anion [Se] n 2n− , interacting electrostatically in concept [ 31 ]. Fig. 1 b shows an atomic force microscopy (AFM) image of an as-grown Bi 2 O 2 Se nanoplate on a mica substrate. The thickness of the selected Bi 2 O 2 Se nanoplate is observed to be ∼25 nm (∼42 layers: monolayer thickness = 0.608 nm) [ 31 ], with lateral dimensions of ∼40 μm on all sides showing a square shape. The dimensions of the Bi 2 O 2 Se nanoplate are found to be sufficient for its implementation in the device. Fig. 1 c shows the Raman analysis of the transferred Bi 2 O 2 Se nanoplate. The distinctive peak A 1g appears at 162 cm −1 , evidencing the successful synthesis and transfer process (the detailed transfer process is given in the experimental section). The Raman signal also contains other characteristic peaks at ∼95, 355, and 520 cm −1 corresponding to E 1 g (for α-Bi 2 O 3 ), B 1g (for out-of-plane vibrations of “O” atoms), and Si (substrate), respectively [ 30 ]. X-ray photoelectron spectroscopy (XPS) was performed to analyze the chemical bonding states of the constituent elements of Bi 2 O 2 Se, as shown in Fig. 1 d-e-f. As observed, the peaks for Bi are located at approximately 163.2 eV and 157.9 eV, relating to the binding energies of Bi 4f 5/2 and Bi 4f 7/2 , respectively. The peak for O1s is observed at 529.9 eV, corresponding to the oxygen associated with the crystal lattice. The dual-peak resolved spectrum of Se shows peaks at 54.2 eV and 53.3 eV, relating to the binding energies of Se 3d 3/2 and Se 3d 5/2 , respectively. The XPS analysis confirms the synthesized Bi 2 O 2 Se nanoplates are in adequate elemental quality. Fig. 1 Material characterization of a synthesized Bi 2 O 2 Se nanoplate. (a) Schematic view of the layered structure composed of the constituent atoms “Bi” (green), “O” (red), and “Se” (blue). (b) AFM image of a Bi 2 O 2 Se single nanoplate of thickness ∼ 25 nm. (c) Raman signal for Bi 2 O 2 Se transferred onto a Si substrate presenting main peak A 1g at 162 cm −1 . XPS spectrum of the Bi 2 O 2 Se nanoplate (d). The peaks for Bi are located at 163.2 eV and 157.9 eV, corresponding to the binding energies of Bi 4f 5/2 and Bi 4f 7/2 , respectively. (e) The peak for O1s is located at 529.9 eV, representing oxygen associated with the crystal lattice. (f) XPS spectrum of Se showing two peaks at 54.2 eV and 53.3 eV, relating to the binding energies of Se 3d 3/2 and Se 3d 5/2 , respectively. Fig. 1 3.1 Resistive switching characteristics The fabricated Bi 2 O 2 Se-based CBRAM device was first utilized to demonstrate basic bipolar resistive switching characteristics. Fig. 2 a presents the first DC sweep cycle (as measured) with a compliance current (CC) of 1 mA. For the first cycle, the device attains the CC at a sweep voltage of 1.3 V, showing a forming voltage (Vform) of 1.3 V (formation of conductive path between TE and BE through SM), and the RESET voltage for the first cycle is −1 V (rupturing of conductive path formed between TE and BE). Fig. 2 Switching characteristics of Bi 2 O 2 Se-based CBRAM. (a) Voltage sweep for the first cycle (set ∼ 1.3 V, reset ∼ −1 V) as measured with a CC of 1 mA. (b) I–V curves for 90 DC sweep cycles @ a CC of 1 mA. (c) Endurance plot for the HRS/LRS @ a Vread of 0.1 V. (d) Cumulative distribution of the HRS/LRS in DC sweep cycles. (e) Retention characteristics of switching in the HRS/LRS for 10 ks with a multilevel switching property (observed in the LRS) showing four different switching levels at Vread values of 0.1 V, 0.2 V, 0.25 V and 0.3 V. (f) P/E endurance characteristics with an applied pulse width of 100 ns. Fig. 2 The direction of the current with respect to the sweep voltage is indicated by the arrow. Fig. 2 b presents 90 consecutive DC sweep I–V cycles. The SET voltage (Vset) distribution is from 0.6 to 0.8 V (excluding the first cycle), and the RESET voltage (Vreset) distribution is from −0.4 to −1.4 V. In addition, the voltage values for the SET and RESET conditions are presented via the cumulative probability distribution shown in Fig. S3 . The plot displays more variation in Vreset than in Vset. Furthermore, a statistical analysis of the switching voltages under the SET and RESET conditions was performed. The calculated numerical values of the mean, standard deviation, and coefficient of variation (%) are 0.66, 0.09 and 14 for Vset and 0.61, 0.26, and 43 for Vreset (mode), respectively, as presented in Table-ST1 . The endurance plot of DC cycles for the HRS (red color)/LRS (green color) @ Vread ∼ 0.1 V shows in spite of significant variation in HRS values, the separation between the HRS and LRS is higher than 10 ( Fig. 2 c). We believe that the possible reason for lower HRS/LRS ratio is because of conductive nature of Bi 2 O 2 Se which needs further study for more exploration. The cycle-to-cycle cumulative probability for the HRS and LRS is presented in Fig. 2 d which further confirms that HRS and LRS values are separated by least value 10. Next, the device was measured for the retention characteristics. Fig. 2 e shows retention in the HRS and LRS measured at Vread ∼0.1 V with slight deterioration in HRS, and the differentiation between the two states is significantly maintained for over 10 ks. For the HRS, the resistance values at 1 s and 10 ks are measured to be ∼14.15 kΏ and ∼13.18 kΏ, respectively, while for the LRS, the resistance values at 1 s and 10 ks are measured to be ∼706 Ώ and ∼718 Ώ, respectively, with both states HRS/LRS showing ratio R HRS /R LRS >10. To explore multilevel switching characteristics, different values of Vread were applied to the device in the LRS. Four distinct switching levels are observed by applying Vread = 0.1, 0.2, 0.25, and 0.3 V, as depicted in Fig. 2 e. At time t = 1 s, the LRS levels for Vread = 0.1, 0.2, 0.25, and 0.3 V are measured to be 706, 245, 145, and 97 Ώ, respectively, while at t = 10 ks, the LRS levels for Vread = 0.1, 0.2, 0.25, and 0.3 V are measured to be 718, 245, 147, and 102 Ώ, respectively. The four different switching states are quite stable and separated from each other through a time span of 10 ks, proving the device capability to exhibit multilevel resistive switching characteristics. Fig. 2 f represents a quite consistent P/E endurance of 3.6 K cycles under voltage pulse (1 V/−0.8 V) application with a pulse width of 100 ns. 3.2 Current conduction mechanism To deeply understand the current conduction mechanism of the Bi 2 O 2 Se-based CBRAM device, the 7th I–V characteristic curve (out of the 90 presented in Fig. 2 b) was randomly selected, which showed HRS and LRS regions, as presented in Fig. 3 a. Fig. 3 b presents a replot (generated by taking 10 points from 2 to 11 as measured data) of the HRS current under a positive bias in ln(J/T 2 ) versus √E form (where J is the current density. Fig. 3 Analysis of the current conduction mechanism. (a) Typical I–V characteristics of the 7th cycle out of 90 DC sweep cycles with a CC of 1 mA showing the HRS and LRS. (b) Fitting curve for Schottky conduction in the HRS under a positive bias. (c) Fitting curve for Ohmic conduction in the LRS under a positive bias. (d) Fully fitted I–V curve discriminating Schottky and Ohmic conduction regions. Fig. 3 T is the absolute temperature, and E is the electric field), which shows that the HRS includes Schottky conduction. To determine the dynamic dielectric constant (Ԑsch) and Schottky barrier height (φ B ), the following equations were used [ 52 ]. (1) S l o p e = ( √ q 3 4 π ε o ε s c h ( k B T ) 2 ) (2) I n t e r c e p t = q ∅ B k B T in Equations (1) , (2) , q, Ԑ o , and k B represent the electronic charge, permittivity of free space, and Boltzmann's constant, respectively. From the slope and intercept, the calculated values of Ԑsch and φ B are 17.2 and 0.424 eV, respectively. The dielectric constant is high, which is consistent with previous reports for oxygen-rich Bi 2 O 2 Se [ 49 ]. Fig. 3 c presents the replot of the LRS generated by taking 6 consecutive points in ln(I) versus ln(V) form, and the measured value of the slope is ∼1.01. Since the slope is ∼1, the LRS conduction is Ohmic conduction. In linear fitting the Adj. R 2 values for HRS ( Fig. 3 b) and LRS ( Fig. 3 c) are 0.99173 and 0.99991 respectively. Both Schottky (red points) and Ohmic (blue points) conductance regions are clearly revealed in the fully fitted I–V (black) curve, as shown in Fig. 3 d. 3.3 Artificial synapse characteristics Apart from data storage, memory devices have been explored for mimicking other functions that includes synapses [ 21 ], and nociceptors [ 53 ]. The present device was further utilized to mimic basic neuromorphic characteristics such as potentiation and depression. Positive and negative DC sweep voltages were applied to realize potentiation and depression. Fig. 4 a shows the potentiation characteristics. For potentiation, a constant positive DC sweep voltage (0 → 0.3 V) was uninterruptedly applied. The device shows a moderate current increment almost in a linear fashion representing 35 distinct current levels from ∼20 μA (first level due to the first + ve DC sweep) to ∼ 160 μA (35th level in response to the 35th + ve DC sweep), indicating that the average current increment per DC sweep is ∼4 μA. Fig. 4 Mimicking artificial synapse via conductivity modulation. (a) potentiation: 35 states. (b) depression: 41 states. (c) added conductance values for potentiation and depression versus number of DC sweeps. (d) Voltage pulse modulated LTP/LTD characteristics. Fig. 4 In principle, the potentiation exhibits a partial SET condition via the gradual formation of CFs by applying a positive voltage in precisely controlled steps, and hence, the current also gradually increases. Fig. 4 b presents depression characteristics. For depression, a fixed negative DC sweep voltage (0 → −0.6 V) was uninterruptedly applied. The device shows a moderate current decrement representing 41 distinct current levels from ∼320 μA (first level due to the first -ve DC sweep) to ∼ 75 μA (41st level in response to the 41st -ve DC sweep), indicating that the average current decrement per DC sweep is ∼6 μA. Conceptually, depression is tuning the device to the RESET condition via gradual rupturing of the formed CFs by applying a negative voltage in precisely controlled steps, leading to a gradual decrease in the current. For clear visualization of potentiation/depression phenomena, measured values were extracted and replotted as the conductance versus number of DC sweeps, as shown in Fig. 4 c. It is clear that the device conductance gradually increases during potentiation and then gradually decreases during depression. Precisely controlled voltage pulses with a pulse duration of 100 ns were applied to obtain LTP (0.3 V) and LTD (−0.6 V) characteristics presented by the device, as shown in Fig. 4 d. 3.4 Proposed mechanism for resistive switching and artificial synapses The proposed switching mechanism is based on the migration of Cu ions through SM Bi 2 O 2 Se under an appropriate external bias, as schematically explained in Fig. 5 . Fig. 5 -a presents the Bi 2 O 2 Se-based CBRAM structure in its primitive state. Fig. 5 -b shows that the device is tuned to the SET condition by applying a positive voltage sweep on the TE. Under the SET condition, excess Cu ions are generated due to the formation of CuOx (x = 1,2) at the Cu/Bi 2 O 2 Se interface at the time of Cu deposition on Bi 2 O 2 Se following Cu 0 → Cu z+ + ze − (z = 1 or 2). These Cu ions migrate through layered Bi 2 O 2 Se, forming a conductive path (or a conductive filament - CF). Reduction of these Cu ions is expected at the Bi 2 O 2 Se/PdOx interface due to tunneling of electrons from the bottom electrode (BE) Pd through PdOx. PdOx shows less oxygen, indicating metallic-like properties. The work function of PdOx is 4.8 eV, and that of Pd is 4.95 (±0.05) eV. Since the work function difference between PdOx/Pd is low, Ohmic contact facilitates a number of electrons passing through PdOx and reducing the Cu z + ions to Cu 0 . The thicker switching layer of Bi 2 O 2 Se (∼25 nm) can control the migration of Cu ions through it; therefore, the formation of multiple weak CFs can be expected. Additionally, the crystalline nature of Bi 2 O 2 Se can be another potential barrier to Cu ion migration. Fig. 5 -c elucidates the RESET process (by applying a negative voltage sweep at the TE), and the flow of I RESET causes Joule heating.= Fig. 5 Schematic representation of the switching mechanism. (a) Primitive view of the device structure. (b) Device under SET and (c) RESET conditions. (d) STP via formation of smaller CFs by applying a few positive voltage pulses. (e) Strengthening of CFs leading to LTP upon application of pulses in large numbers. (f–g) Weakening of CFs by applying negative voltage pulses in small and large numbers for STD and LTD, respectively. Fig. 5 Owing to the low thermal conductivity of Bi 2 O 2 Se (∼ 1.2 W/mK) [ [54] , [55] ] in comparison with the TE CuO//Cu (33 W/mK//400 W/mK) and PdO//Pd (20 W/mK//71.2 W/mK), maximum thermal heat dissipation occurs at the CuO/Bi 2 O 2 Se interface and Bi 2 O 2 Se/PdO interface through Bi 2 O 2 Se (SM). Therefore, weak CF dissolution occurs in Bi 2 O 2 Se, while residual CFs remain at the CuOx/Bi 2 O 2 Se and Bi 2 O 2 Se/PdOx interfaces, supporting the repeatable switching. Furthermore, these nonlasting residual CFs play a crucial role in endurance and long uniform retention characteristics. Since the Bi 2 O 2 Se-based structure has successfully emulated the synaptic characteristics of LTP and LTD, it is worthwhile to elucidate the mechanism involved in such performance. The proposed mechanism for synaptic emulation is based on the formation and rupture of CFs in a controlled manner via the application of voltage pulses of requisite amplitude and polarity. The device under the RESET condition was used to mimic synaptic characteristics. Fig. 5 -d explains the mechanism of the application of positive voltage pulses on the TE. Cu atoms are oxidized to Cu z + ions, which are reduced to Cu atoms at the BE, and their accumulation forms a CF of low thickness, attaining moderate conductance representing STP. When the positive voltage pulses are increased to an adequate number, the thickness of the CF increases, leading to an enhancement in the conductance, resulting in LTP, as shown in Fig. 5 -e. In synapses, depression is considered the reverse action of potentiation, meaning a reduction in conductance via rupturing of the CF by applying voltage pulses of opposite polarity on the TE. Upon the application of a small number of negative voltage pulses, the CF (of Cu atoms) is supposed to be slightly dissolved, causing the conductance to start decreasing, representing STD, as shown in Fig. 5 -f. By increasing the number of similar negative voltage pulses, the dissolution of the CF becomes crucial for lowering the conductance, emulating LTD, as shown in Fig. 5 -g. Therefore, the Bi 2 O 2 Se-based device can be considered a typical artificial synaptic device because it emulates LTP and LTD behavior via controlled formation and dissolution of CFs, respectively. The performance (memory and artificial synapse) of the Bi 2 O 2 Se-based CBRAM device is compared with that of devices in recent reported references, as presented in Table 1 [ 23 , [56] , [57] , [58] , [59] ]. Table-1 Performance comparison of CBRAM with that of devices in recent reported references. Table-1 Memory Performance Artificial Synapse Device Structure CC (μA) HRS/LRS (ratio) Retention (s) Multilevel RS (levels) P/E (V) P/E pulse width (ns) P/E endurance (#) LTP/LTD states LTP/LTD (V) Ref Al/Cu/Bi 2 O 2 Se/Pd 10 3 >10 10 4 4 1.0/-0.8 100 >3.5 × 10 3 54/105 0.3/-0.6 This work Ag/GeSe/Pt/Ti/SiO 2 5 × 10 3 <10 >10 4 ∼6 0.5/-0.5 3 × 10 3 ∼10 4 ∼50/50 0.3/-0.5 [ 55 ] Al/Cu/TiOx/MoS 2 /TiN 200 10 2 10 4 – 1.2/-0.9 100 2 × 10 9 55/500 0.45/-0.45 [ 54 ] Cu/AlOx/aCOx/TiNxOy/TiN 300–10 3 37 10 4 – 1.2/-0.8 100 1.5 × 10 9 59/101 0.5/-0.4 [ 53 ] Cu/MoS 2 double-layer/Au 2 × 10 3 <10 18 × 10 3 – – – – 20/20 0.6/-0.6 [ 21 ] Cu/MoS 2 /Ni–Mn–In 10 4 300 10 3 – 1.5/-1.5 100 500 – – [ 52 ] The comparison is focused on the major performance parameters, including the compliance current (CC), ON/OFF ratio, retention, P/E endurance, and artificial synaptic activities. The compliance current (CC) for our device is 1 mA, a value in agreement with previous reports [ [56] , [57] , [58] ]. The ON/OFF ratio measured is > 10, an average acceptable value compared with references [ 23 , 59 ]. The device presents retention for over 10 ks, which is a reasonable value [ [56] , [57] , [58] ]. Multilevel switching, an advanced memory function that is not commonly reported [ 59 ], was investigated with the present device via four distinct read levels (Vread = 0.1, 0.2, 0.25, 0.3 V). The P/E endurance measured is > 3.5 × 10 3 with a pulse width of 100 ns and applied voltage levels of 1.0/-0.8 V. The numbers of LTP (54, 0.3 V) and LTD (105, −0.6 V) states are also comparable with those in references crucially reporting artificial synapse activities [ 23 , [57] , [58] , [59] ]. Although the performance of the Bi 2 O 2 Se-based CBRAM device (studied for the first time) shows competitiveness for many parameters, further investigations are needed for performance improvement. 3.5 Cu migration analysis via HRTEM To validate the proposed switching mechanism via well-controlled migration of Cu through the SM Bi 2 O 2 Se, ex situ high-resolution transmission electron microscopy (HRTEM) analysis was performed to achieve a visual view supporting the mechanism of the Bi 2 O 2 Se-based CBRAM device. Before HRTEM analysis, all the measurements were completed with the device kept in the SET condition. Fig. 6 a presents a schematic diagram of the proposed Bi 2 O 2 Se-based CBRAM structure. The successfully fabricated structure is shown in Fig. 6 b. Fig. 6 c shows an HRTEM image of the major portion of the fabricated Cu/Bi 2 O 2 Se(SM)/Pd structure. The TE Cu is partially oxidized and forms CuOx at the Cu/Bi 2 O 2 Se interface, transforming the top layer from Cu to Cu/CuOx. Additionally, the interface of the BE also shows a thin layer of oxidized Pd, which is converted into PdOx/Pd at the Bi 2 O 2 Se/Pd interface. The approximate thicknesses of the CuOx, Bi 2 O 2 Se, and PdOx layers are 4 nm, 25 nm, and 3.5 nm, respectively. The presence of the layered structured Bi 2 O 2 Se can be clearly observed, with a number of layers of ∼42 (corresponding to a total thickness of ∼25 nm) [ 39 ]. Fig. 6 d shows an HRTEM image of an arbitrarily selected region of the SM, which presents the crystalline structure of Bi 2 O 2 Se with a clear view of distinct layers. Some part of the layered crystalline view exhibits black spots owing to the presence of Cu in the SM Bi 2 O 2 Se. To confirm the presence of Cu in the SM, energy dispersive spectroscopy (EDS) was carried out to map the elements. Fig. 6 d (1–4) presents EDS elemental mapping images with differentiating colors for “Bi”, “Se”, “O”, and “Cu”. With the aid of this evidence, it is clear that the switching property of the fabricated device is due to Cu migration via the crystalline layered structure of Bi 2 O 2 Se, which is proposed as the SM in the present memory structure. Fig. 6 High-resolution TEM analysis. (a) Proposed cross point structure. (b) Fabricated Bi 2 O 2 Se-based CBRAM device. (c) HRTEM image of a cross-sectional view of the device. (d) Layered structure of Bi2O2Se used as an SM. EDS elemental mapping of the switching region for “Bi”, “Se”, “O”, and “Cu” (d1-4). Fig. 6"
} | 7,751 |
35915152 | null | s2 | 5,468 | {
"abstract": "The origin of eukaryotic cell size and complexity is often thought to have required an energy excess supplied by mitochondria. Recent observations show energy demands to scale continuously with cell volume, suggesting that eukaryotes do not have higher energetic capacity. However, respiratory membrane area scales superlinearly with the cell surface area. Furthermore, the consequences of the contrasting genomic architectures between prokaryotes and eukaryotes have not been precisely quantified. Here, we investigated (1) the factors that affect the volumes at which prokaryotes become surface area-constrained, (2) the amount of energy divested to DNA due to contrasting genomic architectures and (3) the costs and benefits of respiring symbionts. Our analyses suggest that prokaryotes are not surface area-constrained at volumes of 10"
} | 209 |
37923724 | PMC10624904 | pmc | 5,469 | {
"abstract": "In active matter, particles typically experience mediated interactions, which are not constrained by Newton’s third law and are therefore generically non-reciprocal. Non-reciprocity leads to a rich set of emerging behaviors that are hard to account for starting from the microscopic scale, due to the absence of a generic theoretical framework out of equilibrium. Here we consider bacterial mixtures that interact via mediated, non-reciprocal interactions (NRI) like quorum-sensing and chemotaxis. By explicitly relating microscopic and macroscopic dynamics, we show that, under conditions that we derive explicitly, non-reciprocity may fade upon coarse-graining, leading to large-scale equilibrium descriptions. In turn, this allows us to account quantitatively, and without fitting parameters, for the rich behaviors observed in microscopic simulations including phase separation, demixing, and multi-phase coexistence. We also derive the condition under which non-reciprocity survives coarse-graining, leading to a wealth of dynamical patterns. Again, our analytical approach allows us to predict the phase diagram of the system starting from its microscopic description. All in all, our work demonstrates that the fate of non-reciprocity across scales is a subtle and important question.",
"introduction": "Introduction Our ability to design and engineer new materials largely relies on the possibility to infer their large-scale properties from their microscopic constituents. For equilibrium systems, statistical mechanics allows us to do so by relating the macroscopic free energy to the microscopic partition function and the Boltzmann weight. As a result, the emerging properties of equilibrium systems can be predicted by balancing energy and entropy. This general principle, at the root of so many industrial innovations over the past century, comes with a strong restriction: it only applies to the steady state of systems satisfying detailed balance, thus excluding the vast class of nonequilibrium systems and transient dynamical phenomena. An important challenge is thus to develop theoretical frameworks that would allow us to relate the microscopic description of nonequilibrium systems to their emerging behavior. This is particularly important for active systems, which comprise large assemblies of individual units able to exert non-conservative forces on their environment 1 . From spontaneously flowing matter 2 – 5 to living crystals 6 – 10 , active materials display phases without counterparts in equilibrium physics 11 . This rich phenomenology relies in part on the existence of non-reciprocal interactions (NRI) between active particles, which have attracted a lot of attention recently. From the spontaneous emergence of traveling waves to anomalous mechanics and odd elasticity, NRI have indeed been shown to lead to a wealth of exciting phenomena 12 – 25 . In the simplest case of systems with pairwise forces, NRI correspond to the breakdown of Newton’s third law 12 , 24 , 26 , which states that if particle i exerts a force f i j onto particle j then f j i = − f i j . Such pairwise forces are an idealized limit for most active particles: experimental systems instead typically involve complex mediated N -body interactions like chemotaxis, quorum sensing, or hydrodynamic interactions that need not be reciprocal. In all cases, predicting how such microscopic interactions impact the emerging behavior is a challenging, indeed mostly impossible task (note that, for some passive systems, it has been shown that non-reciprocal interactions may allow for a conservation law of a generalized momentum-like quantity 26 ). An appealing alternative has recently been proposed: to postulate phenomenological theories in which action-reaction is directly broken at the macroscopic scale 16 , 17 . The analysis of the large-scale behavior then amounts to a non-linear dynamics problem for which a wealth of tools are available 16 , 17 , 22 , 23 , 27 – 31 . However, a major limitation is that, in the presence of NRI, there is no generic way to infer which microscopic systems correspond to a given macroscopic description. This not only prevents us from assessing the scope of these theories, but it also deprives us of guiding principles when it comes to engineering microscopic active systems to realize the exciting emerging behaviors observed at the macroscopic scale. In this article, we bridge the gap between microscopic and macroscopic descriptions of active systems with non-reciprocal interactions, which allows us to show that the violation of action-reaction is strongly scale-dependent. To do so, we study active mixtures, which comprise several types of interacting active particles and have attracted a lot of interest recently 12 , 16 , 17 , 21 – 24 , 32 – 44 . We first consider active particles that interact via quorum sensing (QS), i.e., regulate their motility according to the local density of their peers. QS is generic in nature 45 , where it is typically mediated by diffusing signalling molecules. For microorganisms, it plays an important role in regulating diverse biological functions, from bioluminescence 46 – 49 and virulence 50 to biofilm formation 51 and swarming 52 . Furthermore, QS can also be engineered in the lab, for instance using light-controlled self-propelled colloids 53 – 55 . We then close this article by showing that our results generalize to chemotactic interactions and by discussing the case of pairwise forces.",
"discussion": "Discussion In this article we have shown how microscopic and macroscopic scales can be quantitatively bridged for a large class of active mixtures in the presence of mediated non-reciprocal interactions. This revealed a subtle and important property of non-reciprocity: it varies strongly across scales. Based on this insight we derived non-trivial conditions on the microscopic NRI that lead to effective equilibrium at the macroscopic scale. This allowed us to account—accurately and without fit parameters—for the full range of static patterns observed in our simulations. Finally, we derived conditions for NRI to survive coarse-graining, hence leading to positive entropy production rate at the macroscopic scale. When non-reciprocity is strong enough, we showed the emergence of a wealth of dynamical patterns. Again, our micro-to-macro approach allows us to predict the phase diagram from microscopics without fitting parameters. From a biophysical perspective, our study shows how QS and chemotactic interactions lead to a rich phenomenology in complex assemblies of cells. In the context of bacterial colonies, motility-induced patterns will eventually interact with population dynamics 68 , 88 , 89 and genetics 90 . How this interplay will result in diverse co-existing communities is a fascinating research direction for the future indeed. Next, we note that swimming bacteria like E. coli typically grow up to 0.1% volume fraction 91 , so that steric interactions can safely be neglected. It is however possible to design experiments in which bacterial density is much larger, e.g., in swarming conditions 92 . A natural question is then how our results extend to such systems. As shown in the Supplementary Information and in Supplementary Movie 7 , a large part of the phenomenology discussed in this article can be found in mixtures of active particles interacting both via pairwise repulsive forces and QS interactions. Recent theoretical progress places the analytical description of this case within the reach of future work 35 , 93 – 100 . Finally, turning synthetic active-matter systems into smart materials will require quantitative control over complex assemblies of active constituents. Our work demonstrates that one can go up the complexity ladder while retaining an analytical framework to account for the emerging properties of active systems. How these systems can then be optimized to accomplish given tasks is an exciting challenge that appears within reach, given recent progress in automatic differentiation 101 ."
} | 2,008 |
26359181 | PMC4628080 | pmc | 5,470 | {
"abstract": "Haloalkaliphilic microorganisms that grow optimally at high-pH and high-salinity conditions can be found in natural environments such as soda lakes. These globally spread lakes harbour interesting anaerobic microorganisms that have the potential of being applied in existing technologies or create new opportunities. In this review, we discuss the potential application of haloalkaliphilic anaerobic microbial communities in the fermentation of lignocellulosic feedstocks material subjected to an alkaline pre-treatment, methane production and sulfur removal technology. Also, the general advantages of operation at haloalkaline conditions, such as low volatile fatty acid and sulfide toxicity, are addressed. Finally, an outlook into the main challenges like ammonia toxicity and lack of aggregation is provided.",
"conclusion": "Conclusions and future prospects Application of haloalkaliphilic anaerobic microbial communities in the abovementioned processes is an interesting route to consider in specific cases and/or to increase their efficiency. Operation at haloalkaline conditions has several advantages, like low VFA and sulfide toxicity, production of low CO 2 -containing and H 2 S-containing biogas and reduced need for pH control. On the other hand, the challenges of ammonia toxicity and lack of biomass aggregation need to be overcome for application in an industry. In general, more laboratory-scale bioreactor studies focusing on these microorganisms are required. Information on reaction rates, biomass growth and microbial communities during long-term experiments in bioreactors is essential to scale up these technologies. Aknowledgments This work was performed in the TTIW-cooperation framework of Wetsus, European Centre of Excellence for Sustainable Water Technology ( www.wetsus.nl ). Wetsus is funded by the Dutch Ministry of Economic Affairs, the European Union Regional Development Fund, the Province of Fryslân, the City of Leeuwarden and the EZ/Kompas program of the “Samenwerkingsverband Noord-Nederland”. The authors would like to thank the participants of the research theme “Sulfur”, namely Paqell, for fruitful discussions and financial support.",
"introduction": "Introduction The metabolic potential of anaerobic microorganisms has been exploited in a wide range of applications, like volatile fatty acids (VFAs), alcohols, H 2 and methane production. However, information about the application of haloalkaliphilic anaerobes that thrive in high-pH (>8.5) and high-salt conditions (>35 g l −1 ) is very limited. In these extreme environments, microorganisms adapted physiological mechanisms to cope with high pH and salinity. The high salinity of the environment must be compensated to prevent osmotic stress and water leakage from the cell. To cope with high salinity, microorganisms accumulate inorganic or organic compounds that work as osmoregulators, preventing the loss of water inside the cell (Dektova and Boltyanska 2007 ). The high pH, on the other hand, affects the proton balance and transport by the ATPases that are responsible for ATP production. Even though the pH of the environment is alkaline, the cell inside usually operates close to neutral pH. Cells cope with this by having more negatively charged cell walls that generate a layer of more concentrated protons, lower pH, near the cell while repelling anions. These adaptations to alkaline conditions have already been recently reviewed in more detail (Banciu and Muntyan 2015 ; Preiss et al. 2015 ). Various haloalkaline environments, like soda lakes, soda solonchak soil, mining industry waste and leafs of salt secreting trees, have been described (Qvit-Raz et al. 2008 ; Sorokin et al. 2008 ; Sorokin et al. 2014 ; 2015a ; Santini et al. 2015 ). However, only soda lakes and soda solonchak soils have the buffer capacity to maintain a high pH (> 8.5) and high salinity (> 35 g l −1 ). Soda solonchak soils have a higher aeration when compared to soda lakes and favour aerotolerant microorganisms (Sorokin et al. 2008 ). Thus, soda lakes are the most suitable habitats to find anaerobic haloalkaliphilic microorganisms. In these lakes, a high pH and salinity is caused by the evaporative concentration of soluble sodium carbonates as a result of low concentrations of divalent cations such as calcium or magnesium in the ground waters and surrounding minerals. The extremely high pH (between 9 and 11) is stable due to a high alkaline buffering capacity of soluble carbonates and salinity can go from 35 g l −1 up to saturation. Soda lakes harbour highly active and diverse microbial communities involved in the carbon, sulfur and nitrogen cycles. Microbiological studies on soda lakes have been reviewed by Sorokin et al. ( 2014 ; 2015a ) Also, reviews on application of haloalkaliphilic microorganisms on nitrogen cycle, sulfide oxidation, heavy metals removal, biofuel production and enzyme production are available (Horikoshi 1999 ; Zhao et al 2014 ). In this mini-review, research focused on potential application of anaerobic haloalkaliphilic microorganisms in fermentation of lignocellulosic feedstocks, methane production and sulfur removal technology will be reviewed. The advantages of low VFAs and sulfide toxicity and high methane content will be discussed. We will also focus on the main technological challenges, such as ammonia toxicity and lack of microbial aggregation."
} | 1,342 |
34644117 | PMC8514098 | pmc | 5,471 | {
"abstract": "Coral diversity positively affects corals, but these benefits have limits and are threatened by ongoing species loss.",
"introduction": "INTRODUCTION Loss of biodiversity is altering ecosystems worldwide, negatively affecting their ecological function, sustainability, and provision of ecosystem services ( 1 , 2 ). Although biodiversity’s positive influence on ecosystem function has emerged as a general rule in ecosystems ranging from grasslands to forests to seagrass meadows ( 3 , 4 ), we still have a poor understanding of how it affects some of the world’s most biodiverse and vulnerable ecosystems, including tropical reefs. Corals—the foundation species of these ecosystems—are in rapid decline, and coral species loss can trigger negative feedbacks that suppress reef functions and promote further decline ( 5 , 6 ). Despite the critical importance of coral diversity, it is unclear both (i) how the positive effects of diversity change with increasing coral species richness and (ii) what processes generate this effect ( 7 ). Understanding these dynamics may allow better prediction of, adaptation to, and mitigation against global change. Although ecologists often emphasize negative biotic interactions (competition, predation, parasitism, etc.), positive interactions are common and frequently play large roles in regulating community structure and function ( 8 , 9 ). If positive effects of coral biodiversity are typical, then reef resilience and conservation depend not only on recruitment and growth of corals but also on coral biodiversity and how the effects of this vary among different groupings of species. Despite this, few studies have investigated the impacts of coral species diversity for corals themselves ( 10 – 13 ), and manipulative experiments are needed to more directly assess community-level measures of ecosystem performance (e.g., production and invasion resistance) in the wild ( 14 )—especially for small corals at sensitive life stages that are increasingly the focus of restoration efforts ( 15 ). Recent field-based manipulations in Fiji found that lower species richness suppressed coral growth and survivorship in monocultures versus a three-species polyculture ( 14 ), but it is unknown (i) whether this effect occurs for other taxonomic groups or geographic locations, (ii) what mechanisms are involved, and (iii) how this relationship may change across a greater range of species richness.",
"discussion": "RESULTS AND DISCUSSION Corals benefit from biodiversity To address these questions, we conducted a series of manipulative field experiments in Mo’orea, French Polynesia; first by assembling monocultures and polycultures using three coral species ( Acropora hyacinthus , Pocillopora verrucosa , and Porites rus ) that are common in French Polynesia ( Fig. 1A ) and congenerics to species used in previous manipulations in Fiji ( Acropora millepora , Pocillopora damicornis , and Porites cylindrica ). This entailed creating 40 cm by 40 cm experimental plots that contained each of the three species in isolation or combined in random configurations of equal density (12 plots per treatment, 18 corals per plot, 864 corals total; Fig. 1B ) and monitoring coral growth and mortality, as well as macroalgal colonization, for three months within each plot. Coral growth was a significant 33% greater in polycultures than monocultures ( Fig. 1C ), with one of the three species, P. verrucosa , generating much of this effect (+43%, Fig. 1D ). P. verrucosa monocultures also accumulated a greater abundance of macroalgal competitors compared to polycultures or to monocultures of P. rus and A. hyacinthus ( Fig. 1E ). These findings parallel the reduced growth and greater macroalgal colonization—but not tissue mortality—observed among P. damicornis monocultures in Fiji ( 14 ), suggesting that biodiversity effects among corals may be geographically widespread and predictable for certain coral taxa, such as Pocillopora spp. that are common on Indo-Pacific reefs. Pocillopora has been largely responsible for rapid reef recovery in Mo’orea following large-scale mortality events (e.g., crown-of-thorns, bleaching, and cyclones) ( 16 ) and may benefit from diversity at early life stages when mortality is high; if corals escape this critical size category, then survivorship rapidly increases with colony size ( 17 ). Fig. 1. Biodiversity effects in experimental coral polycultures and monocultures. ( A ) Monoculture and polyculture plots at the beginning of the experiment (month 0) and ( B ) a schematic depicting each treatment. ( C ) The combined percent coral growth (means ± SE) at three months for polycultures versus monocultures. ( D ) Percent coral growth (means ± SE) at three months for P. verrucosa , P. rus , and A. hyacinthus in polycultures (Poly.) versus monocultures (Mono.). Total numbers of corals assessed per treatment are indicated below each violin plot in (C) and (D). ( E ) Percent cover of upright macroalgae (means ± SE) at three months for monocultures and polycultures ( n = 12 per treatment). P values are from a permutation-based linear mixed-effects (LME) model. Letters indicate significant groupings via a post hoc permutation test for multiple comparisons. Photo credit: Cody Clements, Georgia Institute of Technology. The mechanisms generating the positive effects of coral biodiversity observed previously ( 14 ) and in this experiment are unknown but may result from a number of nonmutually exclusive processes. More diverse coral communities could (i) reduce intraspecific competition (but see the direct test of this below) ( 18 ), (ii) increase efficiency of resource use (e.g., nutrient uptake) ( 10 ), (iii) enhance the ability of corals to exclude algal competitors ( 19 , 20 ), (iv) reduce disease spread due to dilution effects ( 21 ), (v) reduce predation by coral consumers ( 22 , 23 ), or (vi) facilitate other physical or chemical interactions (effects of hydrodynamics or interactions of separate coral’s chemical defenses, respectively). These possibilities warrant additional research. We did observe elevated macroalgal abundances in P. verrucosa monocultures, and macroalgae predictably suppress coral growth ( 24 ), but identifying specific mechanism(s) responsible for these increases (e.g., reduced herbivory due to coral density or composition) ( 25 ) requires further investigation. In Fiji, negative relationships were observed between coral growth and tissue mortality, and we hypothesized that reduced disease transmission may have contributed to the lesser mortality and greater growth of polycultures in that study ( 14 ); however, we did not observe among treatment differences in tissue mortality in this experiment. Furthermore, evidence for differential predation among treatments was negligible; for example, corallivorous snails (e.g., Drupella spp. and Coralliophila violacea ) were largely absent (only six individuals total) across our 48 plots. The role of intraspecific competition Direct tests of the mechanisms generating positive biodiversity effects remain a challenge in many ecosystems ( 26 , 27 ) and are conspicuously absent for corals. However, an experimentally tractable approach that is grounded in fundamental ecological theory predicts that niche differentiation should reduce competition among species ( 18 ); thus, a reasonable hypothesis is that elevated intraspecific competition may explain why P. verrucosa growth was suppressed in monocultures versus polycultures. To evaluate this hypothesis, we created 60 40 cm by 40 cm experimental plots where we manipulated Pocillopora density and coral community composition. Treatments included the following: (i) six P. verrucosa ; (ii) 12 P. verrucosa ; (iii) 18 P. verrucosa ; (iv) six live P. verrucosa , P. rus , and A. hyacinthus (hereafter “live polyculture”); and (v) six live P. verrucosa with six dead P. rus and six dead A. hyacinthus (hereafter “dead polyculture”) (576 P. verrucosa in total; Fig. 2A ). This tested the effects of intraspecific P. verrucosa density and the physical presence (but not the biology) of other species in the dead polyculture against the live polyculture. Fig. 2. Effects of intraspecific coral density in generating biodiversity effects on P. verrucosa after two months. ( A ) A schematic depicting each treatment. ( B ) Percent P. verrucosa growth (means ± SE) and ( C ) percent cover of upright macroalgae (means ± SE) at two months for plots with either six, 12, or 18 living P. verrucosa , as well as polycultures containing six P. verrucosa and either living or dead heterospecifics (six A. hyacinthus and six P. rus ; n = 12 per treatment). Total numbers of corals assessed per treatment are indicated below each violin plot in (B). P values are from a permutation-based LME model. Letters indicate significant groupings via a post hoc permutation test for multiple comparisons. At two months, P. verrucosa in live polycultures again outperformed (+25%) the growth of monocultures with 18 P. verrucosa . Growth in monocultures with six, 12, or 18 P. verrucosa did not differ significantly among density treatments, and they also did not differ from the dead polycultures ( Fig. 2B ). Macroalgal cover was greater on the P. verrucosa monoculture holding 18 individuals than on all other treatments; cover was greater on the dead polyculture than on the six or 12 P. verrucosa monocultures, but algal cover did not differ between live and dead polycultures ( Fig. 2C ). To evaluate whether this pattern changed with duration, we continued the experiment for five additional months. At seven months, growth was again greater (+29%) in live polycultures than monocultures with 18 corals, but dead polycultures and six or 12 density monocultures did not differ from any other treatments (fig. S1). At this time period, macroalgal cover was absent across all treatments. Nonsignificant trends in P. verrucosa growth with increasing density ( Fig. 2B and fig. S1) suggest that reduced intraspecific competition might contribute slightly to increased growth, but a positive effect of heterospecifics is more consistent with our data because there was never a detectable effect of P. verrucosa density on its growth ( Fig. 2 and fig S1). This indicates that simple niche theory alone cannot account for the enhanced polyculture performance we observed and highlights the potential for positive interactions that overwhelm negative effects of competition ( 8 , 28 ) among these foundation species. As with our initial experiment, lower growth of P. verrucosa at the highest density likely involved competitive suppression by macroalgal colonizers that were most abundant in the P. verrucosa monocultures holding 18 individuals ( Fig. 2C ). Greater community resistance to colonization is a commonly observed benefit of biodiversity in other systems ( 8 , 29 ) and may explain differences in algal abundances we observed among treatments. For example, both coral density and composition (e.g., different coral growth forms) can affect the ease with which herbivores can access and remove macroalgae ( 25 ), and lower density (six and 12 P. verrucosa ) monocultures and live polycultures exhibited the least macroalgae in our manipulations. Do biodiversity effects saturate? As reefs are increasingly threatened, it is critical to determine desirable targets of coral species richness that can maximize ecological functions and slow or avert ecosystem collapse. Our experimental manipulations with three species were representative of richness occurring at similar spatial scales on degraded reefs in Mo’orea (mean = ~two species per 40 cm by 40 cm plot; fig. S2) and elsewhere ( 14 ) but may miss richness optima on less degraded reefs, or in early stages of reef recovery, that could inform management goals. Biodiversity effects on ecosystem function are generally saturating in other ecosystems ( 30 ), but this has not been evaluated for corals. If saturation occurs on coral reefs, biodiversity loss could initially have a weak effect but could accelerate unexpectedly with further loss. Such a relationship might help explain why the species-poor Caribbean has declined faster and more markedly than the species-rich Pacific ( 6 ). To address these issues, we conducted an experiment to assess changes in coral community performance across a greater range of coral species richness; this also lessened the potentially confounding effects of species identity instead of diversity per se. We erected 48 experimental plots supporting equal densities of either one, three, six, or nine coral species, drawn at random for each replicate plot from a pool of nine species: P. rus , Porites lobata , Stylophora pistillata , P. damicornis , P. verrucosa , Pavona cactus , A. hyacinthus , Acropora pulchra , and Acropora cytherea (12 plots per treatment; 864 corals total; Fig. 3A ). These corals are among the most common in lagoons of French Polynesia and span a variety of morphologies (e.g., digitate, branching, massive, and tabular) and reproductive strategies (e.g., brooding, spawning, and fragmentation). Fig. 3. Positive biodiversity effects peak at intermediate coral species richness. ( A ) Plots at the beginning of the experiment (month 0) and a corresponding schematic representing each treatment. ( B ) Percent coral growth (means ± SE) and ( C ) tissue mortality at three months for plots with either one, three, six, or nine coral species. ( D ) Percent coral growth (means ± SE) and ( E ) tissue mortality at seven months for plots with either one, three, six, or nine coral species. Total numbers of corals assessed per treatment are indicated below each violin plot in (B) to (E). P values were obtained from a permutation-based LME model. Letters indicate significant groupings via a post hoc permutation test for multiple comparisons. Photo credit: Cody Clements, Georgia Institute of Technology. At three months, coral growth saturated in plots with three to six species and exceeded growth in monocultures by a significant 62 to 67%. Coral growth in nine-species plots was statistically indistinguishable from plots with one, three, or six species ( Fig. 3B ). Tissue mortality, which exhibited a significant negative relationship with coral growth ( r 2 = 0.298, P < 0.001), was significantly less in plots with three or six species (~19 to 20%) versus monocultures (~45%), while nine species plots did not differ significantly from any other treatment ( Fig. 3C ). Macroalgal cover was absent across all treatments in this experiment. This contrasts with our initial experiment where macroalgal cover, but not tissue mortality, differed among treatments and suggests that multiple, context-dependent mechanisms (e.g., suppression of macroalgal competitors or disease) may be responsible for producing positive biodiversity effects. A follow-up assessment at seven months revealed that growth was still saturating in plots with three to six species; however, differences in tissue mortality among treatments were no longer detectable ( P = 0.183; Fig. 3E ). Growth in three-species plots significantly exceeded (by 53 to 74%) growth in one- or nine-species, but not six-species, plots ( Fig. 3D ). Growth in six-species plots exceeded (by 68%) that in monocultures, but not nine-species plots, which, in turn, were indistinguishable from monocultures ( Fig. 3D ). Hump-shaped relationships between species richness and productivity are commonly observed in nature ( 31 ) and, in this case, may arise from community assembly effects coupled with the traits of the nine species used in our manipulations ( 32 ). We also evaluated species-specific patterns of growth and tissue death at both three and seven months. At three months, growth of three species ( P. verrucosa , P. damicornis , and P. rus ) exhibited significant hump-shaped relationships that peaked in plots with intermediate richness; five of the remaining six species exhibited similar trends, but these were not statistically significant ( Fig. 4A ). At seven months, A. cytherea , P. verrucosa , and P. cactus exhibited significant hump-shaped relationships between richness and coral growth; four of the remaining six species again showed similar but nonsignificant trends ( Fig. 4B ). Tissue mortality of each species was statistically indistinguishable among treatments at both three months ( P = 0.066 to 0.848) and seven months ( P = 0.169 to 0.740). Fig. 4. Positive biodiversity effects are species specific. Percent coral growth (means ± SE) at three ( A ) and seven ( B ) months for each coral species used in plots with either one, three, six, or nine coral species. P values were obtained from a permutation-based LME model. Significant values are denoted in bold font. Letters indicate significant groupings via a post hoc permutation test for multiple comparisons. Our study encompassed three manipulative experiments involving more than 2300 corals and consistently demonstrated the importance of biodiversity for coral productivity, which is critical to reef functions such as CaCO 3 accretion and the creation of reef structure and habitat for other species. Positive biodiversity effects were not generated by a greater impact of intraspecific versus interspecific competition in our three-species experiment; we found no effect of intraspecific density alone ( Fig. 2 ). At the scale of our experiment, biodiversity benefits saturated at intermediate levels of three to six species and appeared to begin a decline above this level ( Fig. 3 ). How biodiversity effects may vary at temporal or spatial scales exceeding those of our manipulations deserves investigation. Our findings suggest that increased coral richness may facilitate corals at early stages of community recovery and may disproportionately benefit certain taxa, such as Pocillipora spp., that can drive reef recovery following disturbance ( 16 ). Harnessing these positive interactions could improve coral conservation and restoration efforts in a similar manner to that observed for foundation species in other marine ecosystems ( 4 , 33 ). Conversely, continued loss of synergies among species could lead to a “biodiversity meltdown” that compromises coral community resilience in ways that further hasten reef decline."
} | 4,602 |
35167265 | PMC8945700 | pmc | 5,472 | {
"abstract": "Machine learning\nand signal processing on the edge are poised to\ninfluence our everyday lives with devices that will learn and infer\nfrom data generated by smart sensors and other devices for the Internet\nof Things. The next leap toward ubiquitous electronics requires increased\nenergy efficiency of processors for specialized data-driven applications.\nHere, we show how an in-memory processor fabricated using a two-dimensional\nmaterials platform can potentially outperform its silicon counterparts\nin both standard and nontraditional Von Neumann architectures for\nartificial neural networks. We have fabricated a flash memory array\nwith a two-dimensional channel using wafer-scale MoS 2 .\nSimulations and experiments show that the device can be scaled down\nto sub-micrometer channel length without any significant impact on\nits memory performance and that in simulation a reasonable memory\nwindow still exists at sub-50 nm channel lengths. Each device conductance\nin our circuit can be tuned with a 4-bit precision by closed-loop\nprogramming. Using our physical circuit, we demonstrate seven-segment\ndigit display classification with a 91.5% accuracy with training performed ex situ and transferred from a host. Further simulations\nproject that at a system level, the large memory arrays can perform\nAlexNet classification with an upper limit of 50 000 TOpS/W, potentially\noutperforming neural network integrated circuits based on double-poly\nCMOS technology.",
"conclusion": "Conclusion We have demonstrated\nfloating-gate memory devices based on monolayer\nMoS 2 with simulations showing no performance degradation\ndown to 100 nm gate length and a useable memory window that persists\nto sub-50 nm channel lengths. The conductance of each memory can be\nfinely tuned with a 4-bit precision using our closed-loop programming\nscheme, being limited only by the speed of the experimental setup.\nCircuits based on the MoS 2 floating-gate devices were used\nto perform in-memory dot-product calculations and inference. We also\nrealize a simple perceptron layer with weights transferred from a\nsimulated model onto the MoS 2 circuit. Our perceptron layer\narchives a maximum of 91.5% experimental accuracy, comparing favorably\nto the modeled 95.5% base accuracy. Finally, we extended our circuit\ntopology to perform ImageNet classification based on the AlexNet architecture.\nOur network shows an upper limit of computation efficiency, excluding\nperipheral circuits, of 50 PetaOps/J, almost 2 orders of magnitude\nhigher than for previously reported accelerators. We believe that\nour findings support the two-dimensional semiconductor material platform\nfor the next generation of in-memory processors where machine learning\nimplementations such as deep neural networks can harness the full\npotential of this architecture.",
"introduction": "Introduction Modern processors perform\nmany functions needed for the operation\nof our electronic devices. This flexibility was initially enabled\nby the separation of processing and memory units in the von Neumann\narchitecture. 1 However, current data-driven\napplications 2 − 6 are imposing energy constraints on edge devices due to intensive\nuse of vector matrix-multiplications and access to memory in deep\nneural networks. 7 The back-and-forth transfer\nof data between the memory and the processor is now counting for one-third\nof all energy used in scientific applications. 8 However, the data transfer bottleneck can be avoided by performing\ncomputation directly in the memories’ physical layer through\nthe combination of Kirchhoff’s and Ohm’s laws. This\ntype of in-memory processing can benefit calculation-intensive applications\nsuch as solving linear system equations, 9 linear and logistic regression, 10 solving\npartial differential equations, 11 image/signal\nprocessing and compression, 12 , 13 as well as in artificial\nneural networks (ANN). 14 , 15 While many material systems\nhave been explored for in-memory computing, 16 the strong electrostatic sensitivity 17 and intrinsic optoelectronic behavior 18 of two-dimensional (2D) materials present a\npromising pathway toward reconfigurable and low-power neuromorphic\nhardware. 19 , 20 In particular, monolayer transition metal\ndichalcogenides (TMDCs), such as MoS 2 have been attracting\ngreat attention due to their potential to extend Moore’s law\nin advanced technological nodes. 21 − 24 Moreover, their use in emerging\nmemory devices has also been widely reported. They are being employed\nfrom standard flash memories 25 − 28 to emerging resistive 29 and ferroelectric memories. 30 Memory\ndevices based on 2D materials have recently been gaining\nattention in the context of in-memory 20 and neuromorphic computing. However, most of previous reports have\nfocused on a single device and extrapolated their behavior to system-level\napplications using models. 31 − 33 Exceptions are reports on vision\nprocessors based on 2D materials 19 , 34 in which arrays\nof photodetectors with programmable conductance were used as artificial\nneural networks capable of optical pattern recognition. These early\nexamples also used in situ training where the training\nfor a neural network was performed directly on the hardware, overcoming\nany hardware imperfections and device-to-device variability. Although\nthis improves system accuracy for a given chip, training is the most\nenergy-consuming part in the use of artificial neural networks, and\nit is not desirable to repeat it for every individual chip. In order\nto conserve energy and time, it would be advantageous to perform training\nonce and transfer it to all the individual processors of the same\ntype. Moreover, a fully electrical processor is preferred for general-purpose\napplications on the edge since it requires only one excitation source. Here, we present an in-memory, general purpose processor fabricated\non a 2D-material based technology platform. Our processor is based\non an array of floating-gate memories with monolayer MoS 2 as an active channel. Simulations predict no significant performance\nloss as the channel and gate lengths are scaled down to below 100\nnm with the scaling trends being experimentally confirmed for devices\nwith gate lengths down to 180 nm, supporting the suitability of 2D\nmaterials for scaled in-memory computing circuits. The conductance\nof the devices can be programmed with a 4-bit precision, allowing\nthem to represent weights for standard dot-product operations needed\nfor in-memory calculations. Finally, we use the memory arrays as artificial\nnetworks for seven-segment digit classification with an experimental\naccuracy of up to 91.5% using transfer of learning from a computer-trained\nmodel. Predictions show that large arrays performing the ImageNet\nclassification could potentially outperform silicon counterparts,\noperating with an upper limit of 50 000 TOpS/W (refs ( 35 and 36 )).",
"discussion": "Results and Discussion Device\nDescription and Characterization Figure 1 a presents the three-dimensional\nschematic and the cross-sectional view of our floating-gate memory\narray, 20 based on a gate stack composed\nof a 40 nm thick platinum (Pt) gate (G), a 30 nm thick hafnium oxide\n(HfO 2 ) blocking oxide layer, 5 nm Pt floating gate, and\n7 nm HfO 2 tunnel oxide, chosen to give a good compromise\nbetween writing speed and retention. Wafer-scale, continuous and large-grain\nmonolayer MoS 2 grown using metal–organic chemical\nvapor deposition (MOCVD) 37 , 38 is transferred on top\nof the gate stack and contacted using titanium–gold (Ti/Au)\ndrain (D) – source (S) electrodes. The devices have a channel\nlength and width of 1 and 12.5 μm, respectively. Individually\naddressable devices are connected in parallel for performing in memory\nthe multiply–accumulate (MAC) operations using Kirchoff laws\nfor summation and Ohm’s law for multiplication ( Figure 1 a inset). Raman spectroscopy\nand high-resolution transmission electron microscopy (HRTEM) is used\nto ascertain the material thickness and quality of the MoS 2 film ( Figures S1 and S3 ). Gate-stack\nand electrode fabrication were carried out in a class 100 clean room\nusing standard wafer-scale fabrication tools (more details in the Methods ). This combination of both wafer-scale material\ngrowth and device fabrication allows scaling toward smaller devices\nand more complex two-dimensional nanocircuits. Figures S1 and S2 show the cross-sectional TEM image of the\nfabricated memory gate stack. The image shows a conformal deposition\nof all layers, including the two-dimensional material. No visible\ndefects and cracks were observed in the material nor in the device,\nalso confirmed by electrical measurements. The optical micrograph\nof a fabricated memory array is shown on Figure 1 b. Figure 1 Device structure and characterization. (a) 3D\nschematic representation\nof the MoS 2 memory device array and the corresponding circuit\nschematic for the multiplication-accumulation operation. (b) Optical\nimage of an array of memories connected in parallel (scale bar: 50\nμm). (c) I DS as a function of V G for constant drain-source voltage, V DS = 50 mV. (d) I DS as a function of V DS for different programming\nvoltages, showing the programmable conductance behavior. The device\nis read using V G (READ) = 0\nV and V DS = 50 mV. The operation of the previously described memory device is based\non charge transfer between the semiconductor channel and the embedded\nmetallic floating gate. The memory is programmed by applying a control\ngate voltage such that it bends the bands of the dielectric stack\nso that direct electron tunnelling can occur through the oxide barrier,\nfrom the MoS 2 channel to the platinum floating gate. The\ncharge Q stored in the floating gate causes a shift\nin the threshold voltage of the MoS 2 transistor Δ V TH = − Q / C CG–FG , where C CG–FG is the capacitance between the control gate and the floating gate. 39 For large gate voltage sweeps, the memory programming\noperation results in a shift of the threshold voltage between the\nforward and the reverse paths, creating a hysteresis cycle. The experimental\nconfirmation of the threshold voltage ( V TH ) shift between the forward and reverse paths are seen in Figure 1 d. This creates a\n11.2 V memory window that can be tuned depending on the programming\nvoltage that is applied to the device gate. At a constant gate voltage\nused for reading the memory state ( V G (READ) = 0 V), different values of V TH result in different conductance ( G ) levels, allowing\nthe memory to be used as a programmable resistor. Figure 1 e shows\nthis programmable conductance feature of the floating-gate memory.\nDifferent slopes of linear I DS versus V DS can be programmed, using different\nprogram and read voltages. Linearity is an important characteristic\nsince the multiplication operation in our in-memory processor is based\non the physical relationship between current and voltage. The different\nconductance states are also stable in a 5 h window without significant\ndegradation. Additional device characteristics are presented in Figure S4 . Device Simulation and Scaling To advance our understanding\nof the device behavior and to analyze its performance in advanced\ntechnological nodes, we have performed device simulations using a\ncommercial CAD software (Sentaurus by Synopsys, Inc.) by fitting the\nexperimental results for the long-channel floating-gate memories. Figure 2 a shows the hysteresis\ncycle of the transfer characteristics for the simulated long channel\ndevice with a channel and gate lengths L = 1 μm.\nThe sweep rate is 3.6 V/min. We obtain a good agreement between the\nsimulated and measured curves for this gate length; see Figure S5 . The longitudinal transport is simulated\nusing a drift-diffusion model with Fermi–Dirac statistics,\nShockley–Read–Hall recombination, and thermionic Schottky\ncontacts. Interface and intrinsic traps are required to reproduce\nthe gradual subthreshold slope of the transfer characteristics. The\ncharge injection into and from the floating gate is responsible for\nthe observed memory window and is modeled using the Wentzel–Kramers–Brillouin\napproximation for the electron tunnelling. Figure 2 Device scaling. (a) Simulated\nhysteresis cycle as the device gate\nlength is scaled from L = 1 μm to L = 50 nm. (b) Calculated threshold voltage shift (for I DS = 10 –10 A·μm –1 ) as a function of programming time t PROG . (c) Calculated threshold voltage shift for different channel lengths\nwith a program time of 1 μs. (d) Experimental hysteresis cycle\n( I DS versus V G with V DS = 500 mV) of devices with 950, 430, and 180\nnm gate length. The curves shown were select as the median behavior\nfrom the experimental data set. (e) Experimental variation of the\nON current for different devices with gate lengths demonstrated in\n(d). Triangle: experimental data. Dot: average value. Error bar: confidence\ninterval with 95% certainty. After having calibrated the model using the experimental data,\nwe have investigated the scalability of the memory device. Figure 2 a shows\nthe simulated hysteresis cycles for gate lengths L down to 50 nm. As the gate length is scaled down, the hysteresis\ncycle is shifted toward lower gate voltages due to electrostatic degradation,\nwhile the peak current increases due to the higher longitudinal electric\nfield in the channel. It is evident from Figure 2 a that the large programming window of the\nlong channel is almost maintained down to L = 50\nnm. In order to investigate the programming speed, we have performed\ntransient simulations of I DS – V G characteristics after the application of a\nprogramming pulse with an amplitude V PROG = 15 V and variable width t PROG . Figure 2 b shows\nthe shift of the threshold voltage, extracted at a constant current\nof 10 –10 A ·μm –1 , for\ndifferent values of t PROG . The results\nshow that a reasonable programming window can be obtained with a program\ntime of 1 μs but also that the programming window is reduced\nas the gate length is scaled down. The threshold voltage roll-off\nis due to the increased semiconductor potential and reduced transverse\nelectric field across the tunnel oxide, which in turn induces a lower\ntunnel injection into the floating gate. Simulations show that a gate\nlength of about 100 nm still maintains most of the long channel memory\nwindow for pulse widths of at least 1 μs. In addition, it is\nimportant to highlight that the memory window measured from pulse\nprogramming is lower than the one extracted from the hysteresis as\ndiscussed in detail in T. Sasaki et al. ( 40 ) In other to verify the simulated scaling\nof our floating-gate memories,\nwe fabricated scaled devices down to 180 nm; see Figure S6 for the microscopy images of our devices. Figure 2 d shows\nthe hysteresis cycle of devices with 950, 430, and 180 nm gate lengths.\nWe show here experimental curves corresponding with the median behavior\nof the devices. In Figure S5 , we show the\nfull data set, indicating the device-to-device variability of the\nscaled devices. From the I DS versus V G curves, we can observe the threshold\nroll-off of the scaled devices as a function of the gate length as\npredicted in the simulations. The electrostatic degradation is more\npronounced at a gate length of 180 nm. To analyze the ON current increase,\nwe show the average behavior of a set of devices in Figure 2 e. As the gate length decreases,\nwe observe an increase in the ON current due to the increased horizontal\nfields, as expected. Closed-Loop Programming Our individual\ndevices show\npromising behavior for advanced scaling. However, inevitable process\nand device-to-device variations will affect the relationship between\nthe device conductance and the programming voltage. In order to reliably\nperform in-memory the MAC operations, we need to be able to accurately\ntune the conductance of each device in the network to a predefined\nconductance value while overcoming device–device variations.\nThe corresponding conductance is then used to map a precise multiplication\ncoefficient used inside filter kernels or as synapse weights in artificial\nneural networks. In our work, we base our programming technique on\npreviously reported pulsed tuning algorithms using depression and\npotentiation pulses with a closed-loop convergence procedure. 41 These consist of providing stimuli on the input\nand probing the device output until it reaches the desired value within\na certain tolerance. First, we map the abstract values (input\nvalue: x , output value: y , multiplication\nfactor: w ) to physical quantities (input voltage: V , output current: I , memory conductance: G ) using a reference voltage, V DS REF and trans-impedance and digital gains, A TI and A DIGITAL . The reference\nvoltage is used to convert the input value x to the\ninput voltage as V = V DS REF · x . For the reminder of the paper,\nwe use V DS REF = −1 V.\nWe have chosen a negative voltage to prevent reprogramming the memory\nelements during their normal use. For scaling the output current I back to the abstract value y , we transform\nthe current into voltage using a trans-impedance amplifier with a\ngain A TI = 2.5 MΩ and rescale the\nobtained voltage with a digital gain A DIGITAL = 10 as y = A DIGITAL · A TI · I . With\nthis mapping, the abstract multiplication coefficient w naturally emerges when we set x = 1, y = w , allowing the conductance value to be indirectly\nprobed. We start the algorithm by resetting the conductance\nvalue to its\nhighest level by applying a long (1 s) negative pulse ( V RESET = −8 V). We successively probe the experimental\nweight value and compare it to the desired one. If the measured weight\nis higher than the desired one, the programming pulses are increased\nto V PULSE + V STEP and applied up to N times. Otherwise, in case that\nthe measured value undershoots the target, a short (10 ms) negative\nreset pulse ( V RESET = −8 V) is\napplied and V STEP is halved. The next\niteration starts until either a maximum of M iterations\nis reached or the algorithm converges to a desired conductance value,\nwithin a tolerance. Our programming tolerance is defined by a discretization\nof the weight range into 2 Nbits values where Nbits is the\nnumber of bits of the desired accuracy. Figure 3 a shows a simplified block diagram of the\npreviously described algorithm, while the extended block diagram is\nshown on Figure S4 . We present in Figure 3 b the evolution of\nweights and applied voltage pulse values V PULSE . During iterative programming and measurement steps, the gate reading\nvoltage is set to a negative value (≈ −5 V) in order\nto stabilize the programming values and prevent unintentional reprogramming\nby operating the device in the subthreshold regime. Figure 3 Closed-loop programming.\n(a) Block diagram explaining the closed-loop\nprogramming procedure. (b) Convergence map for overshoot of the weight\nand progressively decreasing the weight until the correct value has\nbeen reached. Performing the Dot Product\nUsing the In-Memory Circuit By tuning the conductance of\neach memory device, we can define the\nweight vector [ w 1 , w 2 ]. Next, we demonstrate the ability of our devices to perform\nsimple multiplication-accumulation operations. In order to do that,\nwe connect two devices in parallel as shown in Figure 4 a. We test the calculation for different\npairs of x 1 and x 2 with values in the 0–1 range. Parts b–e of Figure 4 show the surface\nplanes representing the results of the dot product operation for different\nweight matrices. The experimental plots are the raw data showing the\nlinearity of the calculation. The overshoot seen in one of the planes\n( Figure 4 c, for x 1 = x 2 = 1) is due\nto the intrinsic error in the programming of weights and read noise. Figure 4 In-memory\ndot product. (a) Realization of the dot-product operation\nusing two memories connected in parallel. (b–d) Data surface\nshowing the equivalent multiplication-sum planes of a dot-product\nwith the following weights: (b) w 1 = 1, w 2 = 0; (c) w 1 =\n0.4, w 2 = 0.6; (d) w 1 = 0, w 2 = 1. Application to a Seven-Segment Display Classification Next,\nas a proof of concept, we demonstrate an artificial neural\nnetwork based on a circuit composed of seven memory devices connected\nin parallel. We perform digit classification of artificially generated\ninputs containing noise, corresponding to a seven-segment LCD display, Figure 5 . We show additional\ndetails related to the physical layout of the memory accelerator in Supporting Section 4 . The seven memory devices\nare reprogrammed to produce up to three different classification outputs\nin a 7 × 3 perceptron layer. Figure 5 a shows the seven-segment display used to\ndefine our figure representation. This display configuration was widely\nused in the past where spurious signal variations cause a noisy representation\nof numbers that standard classification methods have difficulty of\nclassifying. To perform a robust figure classification, we construct\na one-layer perceptron network with a SoftMax activation function\nin the output layer. The dot-product operation is performed in memory\nwhile the nonlinear function is implemented numerically in the acquisition\nsystem, for more information see Supporting Section 4 . Figure 5 b\npresents the schematics of the one-layer network. Figure 5 Classification of a seven-segment\ndigit in memory. (a) Representation\nof a seven-segment display. (b) One-layer perceptron network for seven-segment\nfigure classification. (c) Transfer of learning of the theoretical\nweight matrix to proportional conductance values of individual memories.\n(d) Sample of inference operations after different test signals are\nsent to the input layer and measured in one of the neurons. (e) Effect\nof the signal noise on the classification accuracy. (f) Effect of\nthe programming resolution on the classification accuracy. We choose to train the synaptic weight values to each noise-generated\ndata set ex situ using the standard TensorFlow and\nKeras python libraries and transfer the acquired learning to the physical\nlayer. The computer-trained values give an accuracy of 95.5% for an\ninput signal with added white noise having a standard deviation σ\n= 0.1, which we use as a baseline for comparison with the measured\naccuracy of the circuit. This approach performs training only ex situ , while the trained weights are then transferred\nto different neural network processors. This reduces the energy consumption\nof neuromorphic hardware since training is an extremely power-hungry\nstep in deep neural network algorithms. 42 Figure 5 c shows the\ncomparison between the theoretical weight maps, obtained by backpropagation,\nand the experimental ones after transfer using the previously described\nprogramming algorithm with 4-bit precision. A sample of the acquired\noutput signal after the physical multiplication-accumulation operation\nwithout the SoftMax function and with the digital gain used for scaling\nthe physical values to the abstract numbers of the neural network\nis presented in Figure 5 d. We achieve a maximum accuracy of 91.5%, compared to the 95.5%\naccuracy estimated in the software model, classifying up to 10000\nnumbers/s. This measurement is performed with 4-bit precision programming\nand an input signal with added white noise having a standard deviation\nσ = 0.1. We estimate a resistive power consumption of the memory\nnetwork of ∼74.4 pJ/classification, neglecting the energy expended\nat the input-output interfaces and on charging the line capacitors\n( Supporting Sections 5 and 6 ). To\nfurther analyze the implemented network, we vary both the noise\nin the input signal and the programming resolution to evaluate their\nimpact on the accuracy of in-memory classification. Figure 5 e presents the effect of the\ninput noise on the accuracy of the neural network. We can see that\nboth experimental and computational accuracies follow a linearly decreasing\ntrend as the noise at the input is increased. In addition, the difference\nbetween the average experimental values and the theoretically predicted\naccuracy, as well as the spread of the values, remain similar as the\nnoise standard deviation increases, except for the case of σ\n= 0.5 where the smaller spread is due to the saturation of the output\nanalog-to-digital converters. We expect that the spread in measured\naccuracy is due to variations in each memory weight due to imperfect\nprogramming and system noise. Since both experimental and theoretical\nvalues are following the same trend, we conclude that the expected\nbehavior has been observed. We show in Figure 5 f the effect of the programming resolution\n( N bits ) on the accuracy for a fixed input\nnoise (σ = 0.1). A more relaxed programming resolution is expected\nto decrease the precision since the error between the desired and\nmeasured conductance value is large. Although this effect is seen\nfrom 2-bit to 4-bit data, classification with 1-bit weight programming\nresolution can be as accurate as for 4 bits. Since the rest of the\ndata follows the predicted behavior, we consider the discrepancy of\nthe 1-bit accuracy data to be due to chance. Performance of Larger Neural\nNetworks Encouraged by\nthe promising performance of the demonstrated MoS 2 -based\nartificial neural network accelerator, we evaluate complex neural\nnetworks based on the realized FGFET devices. We consider hardware\nimplementations of deep neural networks in which the most frequent\nlarge building block is an analogue vector-matrix multiplier (VMM). 43 A network of this type is AlexNet, used for\nimage classification of the large ImageNet benchmark database. 44 The considered analogue VMM circuit is\nshown in Figure 6 a,\nwhere each floating gate memory is used as a programmable resistor.\nDuring inference, the control gate voltage is set at V G , and the input vector is encoded in the voltage values\n{ V in,1 , ... , V in,M }. If w ij ( i = 1, ... , M; j = 1, ... , N) is the conductance\nof the floating gate memory, then the output current I out, j is given by the matrix multiplication\nof the voltage vector with the weight matrix as shown in Figure 6 a. Figure 6 System-level analysis.\n(a) Analogue vector-matrix multiplier circuit\nwith floating gate memory devices. (b) Transfer characteristics of\nthe memory cells and of the extracted SPICE models in inversion. (c)\nTransfer characteristics of the memory cells and of the extracted\nSPICE models in the subthreshold. (d) Achievable ENOB of the multiplier\nas a function of the cell voltage bias. (e) Error rate in Imagenet\nclassification for an analogue neural network as a function of the\nsignal-to-noise-and-distortion ratio (SINAD) and of the number of\nbits. To analyze the circuit performance,\nwe have first extracted the\nSPICE model of the floating gate memory in inversion, Figure 6 b, and in the subthreshold\nregion, Figure 6 c.\nWe then evaluate the achievable effective number of bits (ENOB) as\na function of the gate voltage and of the input voltage full scale.\nAs seen in the previous section, a better linearity is obtained with\na lower gate voltage. We find that an ENOB of 5 bits is achieved for\na gate voltage of −3 V, which biases the memory in subthreshold,\nand a maximum input voltage of 50 mV. A system-level simulation of\nan analogue implementation of AlexNet, performed using TensorFlow\nand Keras, shows that for a signal-to-noise-and-distortion ratio of\n32 dB, corresponding to 5 effective bits, an error rate smaller than\n20% can be obtained in ImageNet classification. The difference from\nthe simulated V G (READ) and\nthe experimentally observed one for an effective 4-bit programming\ncan be understood in terms of the variations of the threshold voltage\ndue to variations in the grown material. The latency time can\nbe computed with the optimistic assumption\nthat the slow time constants typically associated with devices based\non 2D materials will be effectively removed as fabrication technology\nreaches the industrial standards and that therefore, transient behavior\ncan be accurately predicted based on quasi-static device models. With\nthis assumption, transient circuit simulations of the analogue VMM\nprovide a latency time of 100 ns and a record-high energy efficiency\nof 50 PetaOps/J, where each single operation is either a scalar multiplication\nor a sum, as is usually assumed. This is a very promising value, considering\nthat the best published estimate is 1.3 PetaOps/J for neural network\nintegrated circuits based on double-poly CMOS technology. 35 We must stress that for estimating the energy\nconsumption we have considered only the analogue VMMs that are the\nmain building blocks, whereas in a full neural network one should\nalso take into account the energy consumption of peripheral circuits,\nsuch as the current-to-voltage converters for each column, digital-to-analog\nand analog-to-digital converters, and interlayer circuitry. While\na full implementation of the peripheral circuits is beyond the scope\nof this work, it would not alter the order of magnitude of the estimated\nenergy efficiency."
} | 7,289 |
22191663 | null | s2 | 5,474 | {
"abstract": "Phytostabilization of mine tailings acts to mitigate both eolian dispersion and water erosion events which can disseminate barren tailings over large distances. This technology uses plants to establish a vegetative cover to permanently immobilize contaminants in the rooting zone, often requiring addition of an amendment to assist plant growth. Here we report the results of a greenhouse study that evaluated the ability of six native plant species to grow in extremely acidic (pH ∼ 2.5) metalliferous (As, Pb, Zn: 2000-3000 mg kg(-1)) mine tailings from Iron King Mine Humboldt Smelter Superfund site when amended with a range of compost concentrations. Results revealed that three of the six plant species tested (buffalo grass, mesquite, and catclaw acacia) are good candidates for phytostabilization at an optimum level of 15% compost (w/w) amendment showing good growth and minimal shoot accumulation of metal(loid)s. A fourth candidate, quailbush, also met all criteria except for exceeding the domestic animal toxicity limit for shoot accumulation of zinc. A key finding of this study was that the plant species that grew most successfully on these tailings significantly influenced key tailings parameters; direct correlations between plant biomass and both increased tailings pH and neutrophilic heterotrophic bacterial counts were observed. We also observed decreased iron oxidizer counts and decreased bioavailability of metal(loid)s mainly as a result of compost amendment. Taken together, these results suggest that the phytostabilization process reduced tailings toxicity as well as the potential for metal(loid) mobilization. This study provides practical information on plant and tailings characteristics that is critically needed for successful implementation of assisted phytostabilization on acidic, metalliferous mine tailings sites."
} | 463 |
22191663 | null | s2 | 5,475 | {
"abstract": "Phytostabilization of mine tailings acts to mitigate both eolian dispersion and water erosion events which can disseminate barren tailings over large distances. This technology uses plants to establish a vegetative cover to permanently immobilize contaminants in the rooting zone, often requiring addition of an amendment to assist plant growth. Here we report the results of a greenhouse study that evaluated the ability of six native plant species to grow in extremely acidic (pH ∼ 2.5) metalliferous (As, Pb, Zn: 2000-3000 mg kg(-1)) mine tailings from Iron King Mine Humboldt Smelter Superfund site when amended with a range of compost concentrations. Results revealed that three of the six plant species tested (buffalo grass, mesquite, and catclaw acacia) are good candidates for phytostabilization at an optimum level of 15% compost (w/w) amendment showing good growth and minimal shoot accumulation of metal(loid)s. A fourth candidate, quailbush, also met all criteria except for exceeding the domestic animal toxicity limit for shoot accumulation of zinc. A key finding of this study was that the plant species that grew most successfully on these tailings significantly influenced key tailings parameters; direct correlations between plant biomass and both increased tailings pH and neutrophilic heterotrophic bacterial counts were observed. We also observed decreased iron oxidizer counts and decreased bioavailability of metal(loid)s mainly as a result of compost amendment. Taken together, these results suggest that the phytostabilization process reduced tailings toxicity as well as the potential for metal(loid) mobilization. This study provides practical information on plant and tailings characteristics that is critically needed for successful implementation of assisted phytostabilization on acidic, metalliferous mine tailings sites."
} | 463 |
33181127 | null | s2 | 5,476 | {
"abstract": "No abstract available"
} | 5 |
22963335 | PMC3443666 | pmc | 5,478 | {
"abstract": "Background Acid Mine Drainages (AMDs) are extreme environments characterized by very acid conditions and heavy metal contaminations. In these ecosystems, the bacterial diversity is considered to be low. Previous culture-independent approaches performed in the AMD of Carnoulès (France) confirmed this low species richness. However, very little is known about the cultured bacteria in this ecosystem. The aims of the study were firstly to apply novel culture methods in order to access to the largest cultured bacterial diversity, and secondly to better define the robustness of the community for 3 important functions: As(III) oxidation, cellulose degradation and cobalamine biosynthesis. Results Despite the oligotrophic and acidic conditions found in AMDs, the newly designed media covered a large range of nutrient concentrations and a pH range from 3.5 to 9.8, in order to target also non-acidophilic bacteria. These approaches generated 49 isolates representing 19 genera belonging to 4 different phyla. Importantly, overall diversity gained 16 extra genera never detected in Carnoulès. Among the 19 genera, 3 were previously uncultured, one of them being novel in databases. This strategy increased the overall diversity in the Carnoulès sediment by 70% when compared with previous culture-independent approaches, as specific phylogenetic groups ( e.g. the subclass Actinobacteridae or the order Rhizobiales ) were only detected by culture. Cobalamin auxotrophy, cellulose degradation and As(III)-oxidation are 3 crucial functions in this ecosystem, and a previous meta- and proteo-genomic work attributed each function to only one taxon. Here, we demonstrate that other members of this community can also assume these functions, thus increasing the overall community robustness. Conclusions This work highlights that bacterial diversity in AMDs is much higher than previously envisaged, thus pointing out that the AMD system is functionally more robust than expected. The isolated bacteria may be part of the rare biosphere which remained previously undetected due to molecular biases. No matter their current ecological relevance, the exploration of the full diversity remains crucial to decipher the function and dynamic of any community. This work also underlines the importance to associate culture-dependent and -independent approaches to gain an integrative view of the community function. Reviewers This paper was reviewed by Sándor Pongor, Eugene V. Koonin and Brett Baker (nominated by Purificacion Lopez-Garcia).",
"conclusion": "Conclusions Our study provided evidences that culture-dependent approaches enable the characterization of a different diversity compared to the one obtained by culture-independent approaches, highlighting the complementarity between the 2 approaches. We also pointed out that the community structure is not as simple as previously established (a 70% increase in overall diversity). Functional experiments showed that important community functions, such as cobalamin biosynthesis, the degradation of cellulose and the oxidation of As(III) are redundant in the ecosystem thus increasing the functional robustness essential for any ecosystem. Additionally, the isolation of neutrophilic or even alkaliphilic strains further highlights the capability carried by the whole community to adapt to in situ conditions changes such as an increase of the pH, thus improving the knowledge of the system resilience. We showed that it remains crucial to associate culture-dependent and culture-independent approaches to gain an integrative view of the community structure and function. However, measuring the exact in situ role of each non-dominant species remains hard to determine, since they are hardly detectable with standard molecular techniques. Specific FISH-probes experiments can be performed more easily after isolation, but the relative abundances remains unknown, since no (or too few) DNA was recovered from the isolated genera. The determination of the full extent of the microbial diversity is therefore still challenging, and considerable efforts in terms of technologies and work have to be undertaken to approach this aim.",
"discussion": "Results and discussion Bacterial diversity in the sediment of Carnoulès by novel culture-dependent approaches The diversity of cultured bacteria was tested in the soft and unstable sediment collected directly under the running water of Carnoulès. The physical and chemical characteristics of the running water were described elsewhere [ 16 ]. For this purpose, 11 media corresponding to commonly used media and newly designed FD media were used. The mineral base of all FD media was identical and was formulated to be as close as possible to the mineral conditions found in Carnoulès, with the exception of the absence of toxic compounds such as arsenic in order to decrease the selective pressure. The importance of the carbon concentration and the pH of the media were tested. All in all, the media used in this study varied from pH 3.5 to 9.8, and from 0.01% CAA as sole carbon source to the LB-rich medium (Table 1 ). Table 1 Strains affiliation, isolating medium characteristics and physiological and genetic properties of the isolated strains Taxonomy Isolation Medium Metabolism and genetic Strains affiliation (isolates) Closest type strain / identity (acc. num.) Name CAA% pH aioA gene amplification arsenite oxidation cellulose degradation Acidobacteria bacterium Acidobacterium capsulatum ATCC 51196 / 94% (NR_043386) (N3B) FD2 0.01 5.5 - - - Bacillus sp. [ Brevibacterium ] frigoritolerans DSM 8801 / 99% (NR_042639) (Q9*) LB - 7 - - - Paenibacillus sp. Paenibacillus taichungensis BCRC 17757 / 99% (NR_044428) (Q8*) LB - 7 - - + Cellulomonas sp. Cellulomonas chitinilytica X.bu-b / 97% (NR_041511) (O1) FD1 0.01 3.5 ( E10 , J12, J13, J14, J16, K13 K5, K6, K8, L7, L8, L9, L11, L14, L15, P2, U3) FD2 0.01 5.5 - - - Streptomyces sp. Streptomyces atratus NRRL B-16927 / 99% (NR_043490) (H7) FD2 0.01 5.5 - - - Propionibacteriaceae Luteococcus peritonei CCUG38120 / 95% (NR_028882) (H7p) FD2 0.01 5.5 - - - Arthrobacter sp. Arthrobacter albidus LC13 / 98% (NR_041403) (J9) FD2 0.01 5.5 - - - Micrococcus sp. Micrococcus yunnanensis YIM / 99% (FJ214355) (Q7*) LB - 7 - - - Rhodococcus sp. Rhodococcus erythropolis N11 / 99% (NR_037024) (U2) FD2 0.01 5.5 - - - Micromonospora sp. Micromonospora coriariae NAR0 / 99% (NR_042314) (X14) 1/100 YPD + 100 mg/l As(V) - 8 + - + Acidocella sp. Acidocella facilis / 99% (NR_025852) (Q3*, Q6*) FD1 0.01 3.5 (I10) FD2 0.01 5.5 - - - (L5, Q1*, Q2*, Q4*, Q5*) FD4 0.1 5.5 Acidisoma sp. Acidisoma tundrae WM1 / 98% (NR_042705) ( K16 , L2) FD1 0.01 3.5 - - + Methylorosula sp. Methylorosula polaris V-22 / 98% (EU586035) (N4) FD2 0.01 5.5 - - - Ancylobacter sp. Ancylobacter dichloromethanicus DM16 / 97% (EU589386) (X1) CDM - 7 - - - Pseudomonas sp. Pseudomonas psychrotolerans C36 / 99% (NR_042191) ( K7 , L10) FD2 0.01 5.5 - - - Rhodanobacter sp. Rhodanobacter ginsengisoli GR17-7 / 99% (NR_044127) ( L12 , N3J, U4, U5, U7) FD2 0.01 5.5 - - - Dyella sp. Dyella japonica XD53 / 97% (NR_040974) ( K4 ) FD2 0.01 5.5 - - - Xanthomonadaceae Dokdonella koreensis DS-123 / 93% (NR_043322) ( X11 ) mm126 - 5 - - - Thiomonas sp. Thiomonas cuprina NBRC 102145 / 98% (NR_041628) (X19) 1/100 YPD + 100 mg/l As(III) - 9.8 + + ND In brackets are the strains code and * indicates the strains isolated via SSMS. In bold are the isolates used for 16S rRNA gene sequencing and physiological experiments. Accession numbers are as follows: N3B (FR874231); Q9 (FR874233); Q8 (FR874235); E10 (FR874226); H7 (FR874234); H7p (FR874241); J9 (FR874236); Q7 (FR874239); U2 (FR874228); X14 (FR874224); I10 (FR874225); K16 (FR874240); N4 (FR874230); X1 (FR874229); K7 (FR874238); L12 (FR874232); K4 (FR874237); X11 (FR874227) and X19 (FR874242). ND: Not determined. The different media and growth conditions allowed the isolation of 49 bacterial strains. All strains were identified by comparison of their nearly complete 16S rRNA gene sequences with the NCBI-nr and RDP databases (Table 1 ). The isolates were assigned to 19 genera belonging to 4 phyla (Figure 1 ). Among the 19 genera detected, 9 (47%) were found within Proteobacteria , 7 (37%) within Actinobacteria , 2 (11%) within Firmicutes and 1 (5%) within the phylum Acidobacteria . Among the Proteobacteria , members of the α- (4 out of 9 genera, 44.5%) and γ-subdivisions (4 out of 9, 44.5%) were well represented, while only one member of the β-subdivision (1 out of 9, 11%) was isolated. Actinobacteria were all found within the order Actinomycetales and were assigned into 5 suborders, namely Micrococcineae (3 genera out of 7, 42.8%), Propionibacterineae (1 out of 7, 14.3%), Corynebacterineae (1 out of 7, 14.3%), Streptomycineae (1 out of 7, 14.3%) and Micromonosporineae (1 out of 7, 14.3%). The 2 Firmicutes were found within the order Bacillales whereas the Acidobacteria was member of the subdivision 1 of this phylum. Figure 1 Phylogenetic tree representing the taxonomic affiliation of the Carnoulès isolates. The 16S rRNA gene sequences of the isolates (in bold) and their closest relatives were aligned with the MEGA 5 implementation of ClustalW algorithm. Neighbor joining tree was performed with this software and tree was drawn up using the website ITOL ( http://itol.embl.de/ ). Interestingly, no growth was detected on FD3, FD5 and FD6 characterized by very low pH (FD3) and/or high CAA concentration (respectively FD5 and FD6). By contrast, FD2, characterized by less acidic pH (5.5) and low carbon concentration (0.01% CAA), allowed the isolation of the largest diversity, with strains belonging to 11 out of the 19 genera. Those genera were found within Proteobacteria (5 genera out of 11, 45%), Actinobacteria (5 genera out of 11, 45%) and Acidobacteria (1 genera out of 11, 9%). It should be noted that FD2 was the most appropriate medium to isolate Actinobacteria , since it allowed the isolation of 5 bacterial strains out of the 7 strains affiliated to phylum Actinobacteria . FD1 medium, differing from FD2 in the pH used (3.5 for FD1) allowed the isolation of representatives of 3 genera, namely Acidisoma, Acidocella and Cellulomonas. The latter two were however also isolated on FD4 and/or FD2 media. Thus, the isolates K16 and L2, both belonging to genus Acidisoma, were the only bacteria that were isolated solely on very acidic medium. These results indicate that the increase of the incubation time and the reduction of the carbon concentration allowed the isolation of the slow-growing bacteria, as previously suggested by Vieira-Silva [ 17 ]. It also shows that the complete mimicking of in situ conditions in terms of pH (3.5) resulted in a poor recovery of genera, since only Acidocella, Acidosoma , and Cellulomonas have been isolated on FD1 (Table 1 ). These results are consistent with those of Hallberg and Johnson [ 18 ] who isolated moderate acidophilic bacteria by increasing the pH of the growth medium compared to the natural environment as well as with data reported by Hao [ 19 ] who detected neutrophilic bacteria in AMD. Another important factor to explain this diversity is the use of gellan gum instead of agar as a solidifying agent. Indeed, when grown on their culturing medium with agar instead of gellan, the growth rate of all strains was slower, except for strains affiliated to the genera Arthrobacter (J9), Acidocella (L5, Q1, Q2, Q3, Q4, Q5, Q6 and I10), and Acidisoma (K16, L2) (data not shown). N3B and H7p, affiliated to the phylum Acidobacteria and the family Propionibacteriaceae , respectively, were even unable to grow on agar plates. These results are consistent with a previous work showing that the cultured microbial diversity was increased with gellan gum when compared with agar [ 20 ]. Direct spreading on modified m126 medium (mm126), CDM and 1/100 YPD media supplemented with 100 mg.l -1 As(III) or As(V) allowed the isolation on each medium of only one bacterial genus, respectively a new genus of the family Xanthomonadaceae (X11), Ancylobacter sp. (X1), Thiomonas sp. (X19) and Micromonospora sp. (X14) (Table 1 ). We showed here that when using a broad range of pH (from 3.5 to 9.8), neutrophilic and even alkaliphilic bacteria could be isolated (Table 1 ). Especially, using a high pH medium (9.8), we succeeded in isolating a strain belonging to the genus Thiomonas sp. (X19). Several bacteria belonging to the group 1 of Thiomonas had been previously isolated from the water of Carnoulès [ 8 , 9 , 11 ]. However, significant differences between the 16S rRNA sequence of X19 and other Thiomonas from group 1 ( e.g. 90% identity between X19 and Thiomonas sp. CB2 (FJ014922) over the full alignment) showed that X19 does not belong to the group 1 of the Thiomonas genus. By contrast, X19 and CARN2 (one of the dominant species detected previously by a culture-independent approach [ 14 ]) differed by only a single nucleotide mismatch over the nearly full length of the 16S rRNA gene. Thus, X19 corresponds to the first representative of the group 2 of the Thiomonas isolated in Carnoulès so far. Members of this genus are routinely grown on m126 medium (pH 5) [ 12 , 13 ] and were not known to grow in alkaline conditions [ 21 ], to the contrary to X19. Nevertheless, spreading X19 on this modified mm126 medium then led to the formation of visible colonies after 10 to 14 days as compared to the 14 to 21 days needed on 1/100 YPD + 100 mg.l -1 As(III) plates. When compared to other Thiomonas bacteria, X19 grew however much slower on mm126 (data not shown) [ 12 , 13 ]. Since the CARN2-like X19 strain adapts in vitro to different conditions such as high pH variation, one can hypothesize about its adaptation potentialities to various in situ physico-chemical conditions. Lastly, a 10 days-incubation of the samples on SSMS [ 15 ] followed by the spreading of the microcolonies on solid media [ 22 ] allowed the culture of isolates belonging to 4 genera. Among them, 3 were detected only on LB plates. Those strains belong to the genera Bacillus (Q9) and Paenibacillus (Q8) from the phylum Firmicutes and Micrococcus (Q7) from the phylum Actinobacteria . The advantage of this strategy was here to avoid fungal contamination compared to direct spreading for which different moulds invaded the LB plates, despite the presence of antifungal agents. Acidocella (Q1 to Q6) were also detected after growth on SSMS and spreading on FD1 media. They shared an identical 16S rRNA gene sequence with strains isolated directly on FD media. Our results indicate that the isolated strains are highly specific to the medium used for primary isolation, since the majority of them were found on only one medium. As previously mentioned, exceptions are found for members of the genus Cellulomonas sp. which were isolated on both FD1 and FD2 media and Acidocella sp. which were found on FD1, FD2 and FD4 media. Isolation of previously uncultured bacteria The culture strategy led here to the isolation of representatives of 3 new genera as defined by Tindall et al . [ 23 ]. Indeed, these 3 isolates shared less than 95% 16S rRNA gene sequence identity with their closest taxonomically characterized species. The first one (N3B) belongs to the phylum Acidobacteria and shared 98% 16S rRNA gene sequence identity with uncultured clone IRON_SNOW_NB_E11 (FR667807) whereas its closest taxonomically characterized species was Acidobacterium capsulatum (CP001472) with 94% identity. Acidobacteria correspond to some of the most abundant microorganisms in the environment but are recalcitrant to cultivate in laboratory [ 24 ]. Only 8 genera from this phylum have been taxonomically isolated so far [ 25 ]. The recent metagenomic investigation of Carnoulès AMD, led to the detection of a strain of Acidobacteria i.e. CARN3 [ 14 ]. However, N3B showed less than 95% 16S identity with CARN3. The second one (X11) belongs to the family Xanthomonadaceae . X11 sequence was closely related to the uncultured γ-Proteobacterium DKE (100% identity, HQ909259) but the closest taxonomically characterized strain was Dokdonella koreensis (AY987368) with less than 94% identity. X11 and its closest related strains are common inhabitants of mines and acidic environments, since BLAST analysis revealed the presence of their 16S rDNA in Carnoulès (clone CG-36 (FN391831) [ 14 ]) as well as in various other acid mine drainages and acidic waters ( e.g. “Rio Tinto” in Spain, “Lower Red Eyes” in Pennsylvania, “Wheal Jane” in England). The third one is H7p, a member of the Propionibacteriaceae family. Its best matching 16S rRNA gene sequence is Luteococcus sp. (AJ132334) found in human peritoneum sharing only 95% identity with H7p. No better identity was found in any database (NCBI-nr and RDP) even with «uncultured bacteria ». The closest taxonomically characterized strain is Luteococcus peritonei (NR_028882) also sharing 95% identity with H7p. It should be noted that the species Propionibacterium acnes , belonging to this family but presenting only 90% sequence identity with H7p, has been previously detected in AMDs [ 18 ]. All these results indicate that H7p belongs to a novel genus that has never been detected previously in AMDs or in any other environment. From the bacterial diversity to the community function Deciphering the biological processes occurring in situ in any environment requires both the knowledge of the overall bacterial diversity and the comprehension of the role of each microorganism in the community function. However, the more diverse is the community, the more difficult it is to understand the role of each taxon in this community. In this sense, acid mine drainages are well-suited models as the bacterial community is considered to harbour a low diversity, with only a few dominant taxa [ 2 - 4 ]. In the AMD of Carnoulès, both culture-dependent and culture-independent approaches were already undertaken to unravel this diversity when using the water body as template [ 3 , 6 - 11 ]. However, only culture-independent approaches were carried out when searching in the soft sediment collected directly under the running water [ 14 , 26 ]. All these experiments highlighted the low bacterial diversity occurring both in the sediment and in the above running water. In the present study, we succeeded in isolating 49 strains belonging to 19 genera. Importantly, 16 of these genera had never been detected previously on this site [ 14 , 26 ], thus increasing the overall bacterial diversity in the sediments by 70% (Figure 2 ). Indeed, only 3 strains, belonging to Rhodanobacter Thiomonas and the new genus belonging to the family Xanthomonadaceae (X11) were found both by our culture-dependent investigations and by culture-independent approaches [ 14 , 26 ]. Moreover, members of 3 phyla were detected only by culture-independent approaches, namely Spirochaetes Nitrospira and the novel phylum represented by CARN1/CARN4 [ 14 ]. On the other hand, phylogenetic groups like the subclass Actinobacteridae or the order Rhizobiales were only detected via the present culture strategy. A phylogenetic tree representing all taxa detected in the sediments of Carnoulès by both methods allowed to highlight the overall microbial diversity and to point out the complementarity between the approaches (Figure 2 ). Figure 2 Phylogenetic tree representing all taxa detected in the sediments of Carnoulès. The 16S rRNA gene sequences of the isolates (filled dark-blue circles), closest relative (filled light-blue circles) and other taxa found in Carnoulès by Bertin et al. , 2011 (filled green circles); Bruneel et al., 2011 (filled yellow circles) were aligned with the MEGA 5 implementation of ClustalW algorithm. Neighbor joining tree and tree representation were performed with this software. The open red circles correspond to phylogenetic groups detected only by culture-dependent approach (this study). To confirm this result, specific primers ( Additional file 1 ) targeting each genus previously undetected by previous culture-independent studies [ 14 , 26 ] were designed and tested by using metagenomic DNA from the Carnoulès sediment as template. Among them, only H7p, member of the new genus within Propionibacteriaceae , had an identical sequence in the metagenomic DNA. This result suggests that only this latter strain could have been detected by the previous molecular techniques, if more clones would have been sequenced. Indeed, no rarefaction curve was presented in the previous studies. More generally, this result suggests that the DNA concentration corresponding to all other cultured strains was too low or even absent to be detected inside the metagenome mixture. Therefore, one could hypothesize that the isolated strains correspond to rare populations [ 27 ] in the sediment of Carnoulès. Indeed, rare bacteria should be considered [ 28 ] since recent studies indicated that even if they are present at a dormant or a spore stage, they may become active and abundant when the in situ conditions change [ 29 , 30 ]. Moreover, it has been shown that rare bacteria eventually not detected by molecular techniques can significantly contribute to the global functioning of any ecosystem [ 31 , 32 ]. It is also recognized that culture may be a powerful strategy to access to this previously undetected rare biosphere [ 33 , 34 ]. Here, the dilutions used (100 μl of the dilutions 10 -1 and 10 -2 were spread on each plate) allowed to estimate the population of each genus by several hundreds to thousands CFU per gram of sediment. Alternatively, they can have been missed out previously because their DNA was inaccessible by the extraction methods used for metagenomic investigations. Indeed, it is already known that Actinobacteria , representing 37% of the genera detected here, are often underestimated by molecular approaches due to poor DNA extraction [ 35 , 36 ]. For instance, it has been proved that Micromonospora species (as X14) are insensitive to most lysis treatments [ 37 ]. More generally, the metagenomic DNA protocol affects importantly the DNA recovered [ 38 ] and thus the bacterial diversity which is detected. No matter the current in situ ecological relevance of the strains, they can play an essential role when the physico-chemical conditions change. In this sense, it remains crucial to approach as far as possible the full bacterial diversity to better understand how a community works and evolves. In addition to the extension of the bacterial diversity, our work also allows to test some physiological characteristics and to provide potential role(s) of the strains for the community function. As such, we decided to screen for functions, which are crucial for the survival of the bacterial community in AMDs but which lack the necessary redundancy, i.e. functions that are carried only once in the previous global metagenomic approach [ 14 ]. The first tested function concerns the biosynthesis of cobalamin (vitamin B12). Interestingly, all FD media were designed without cobalamin and vitamin-free CAA was used. Thus, all bacteria growing on such media are prototroph for cobalamin. Indeed, 12 genera out of the 19 (belonging to Acidobacteria bacterium , Cellulomonas, Streptomyces, Propionibacteriaceae bacterium , Arthrobacter, Rhodococcus, Acidocella, Acidisoma, Methylorosula, Pseudomonas, Rhodanobacter and Dyella , see Table 1 ) were isolated on the newly designed FD media. The cobalamin biosynthesis pathway genes were previously found by metagenomics only in CARN1/CARN4 (both grouped within the uncultured bacterium Candidatus Fodinabacter communificans) whereas the other genomes (such as CARN2 and CARN5) carry the cobalamin transporter btuC gene. Moreover, the photosynthetic microorganism Euglena mutabilis isolated from Carnoulès was recently shown to be auxotroph for cobalamin [ 39 ]. Candidatus Fodinabacter communificans was therefore thought to be essential for the community, at least by providing vitamin B12 for the rest of the community [ 14 ]. It is tempting to hypothesize that some of the isolated strains in the present work are able to produce this vitamin and provide it to the rest of the AMD community. The second function tested was the cellulose degradation. As the AMD of Carnoulès is at least partly oligotroph [ 14 ], any possibility to catabolize unusual nutrients would be advantageous for the corresponding bacterium [ 40 ]. The released by-products can be also useful for the rest of the community as it can allow syntrophic interactions. As such, the metagenomic approach allowed the detection of the genes encoding proteins responsible for the degradation of the cellulose polymers only in the genome of CARN6 [ 14 ]. The ability to degrade the cellulose was tested for one representative of each of the 19 genera (strains code E10, H7, H7p, I10, J9, K4, K7, K16, L12, N3B, N4, Q7, Q8, Q9, U2, X1, X11, X14, X19), using carboxymethylcellulose (CMC) as substrate. A yellow halo was observed for K16 ( Acidisoma sp.), X14 ( Micromonospora sp.) and Q8 ( Paenibacillus sp.), demonstrating their ability to degrade this complex compound (Table 1 ). When used with the strain X19 on mm126 plates, the degradation test resulted in a coagulation of the Congo red dye, which turned violet, making impossible the lecture of the results. This reaction, due to the acidification of the medium, has already been described [ 41 ]. To our knowledge, this is the first time that polymer-degrading activities of bacteria isolated from oligotrophic AMDs were physiologically demonstrated. Q8 was then further studied in details for its numerous polymer-degradation activities under a wide range of stress conditions i.e. for its ecological relevance when ambient environmental conditions change [ 16 ]. The third function is As(III) oxidation, an important function in Carnoulès since it allows the co-precipitation of arsenic and iron and leads to a sharp decrease of the arsenic concentration in the AMD [ 5 ] and to the detoxification of the ecosystem. We tested in laboratory conditions the As(III) oxidation capability for one representative of each genus (strains code E10, H7, H7p, I10, J9, K4, K7, K16, L12, N3B, N4, Q7, Q8, Q9, U2, X1, X11, X14, X19) in their liquid culturing medium supplemented with 100 mg.l -1 As(III). All strains were able to grow but only X19 was able in vitro to oxidize As(III) to As(V) as measured by HPLC-ICP-OES experiments (Table 1 ). The isolation of the CARN2-like X19 strain is of importance, since it allowed to test and measure physiologically its As(III)-oxidizing potentiality previously hypothesized by metagenomic and metaproteomic [ 14 ]. This strategy allowed therefore to confirm one major role for CARN2 in the community function. In accordance to the 16S rRNA gene sequence similarity between X19 and CARN2, the aioA gene sequence (984 bp) of X19 encoding the large subunit of the arsenite oxidase amplified with degenerated primers [ 42 ] shared 98% identity with one copy of the aioA gene from CARN2 (CARN2_1330). It should be noted that we obtained a specific sequence of the aioA gene from X14, belonging to the phylum Actinobacteria . Despite the absence of oxidation measured in laboratory conditions, X14 may therefore be able to also oxidize As(III) in situ as does CARN2. Interestingly, the X14 aioA sequence was 100% identical over its full length (989 bp) to the aioA gene from Thiomonas sp. CB2 (EU339212), belonging to the phylum Proteobacteria and previously isolated from the Carnoulès water [ 8 ]. This observation suggests a recent horizontal gene transfer (HGT) between these 2 bacteria, belonging to very distant phylogenetic groups. The occurrence of HGT for the aioA gene had previously been observed in another study site [ 43 ] but never in Carnoulès, further highlighting the complex interactions between bacteria in situ ."
} | 7,106 |
31340591 | PMC6784372 | pmc | 5,479 | {
"abstract": "The microbial fuel cell (MFC) is a promising environmental biotechnology that has been proposed mainly for power production and wastewater treatment. Though small power output constrains its application for directly operating most electrical devices, great progress in its chemical, electrochemical, and microbiological aspects has expanded the applications of MFCs into other areas such as the generation of chemicals (e.g., formate or methane), bioremediation of contaminated soils, water desalination, and biosensors. In recent decades, MFC-based biosensors have drawn increasing attention because of their simplicity and sustainability, with applications ranging from the monitoring of water quality (e.g., biochemical oxygen demand (BOD), toxicants) to the detection of air quality (e.g., carbon monoxide, formaldehyde). In this review, we summarize the status quo of MFC-based biosensors, putting emphasis on BOD and toxicity detection. Furthermore, this review covers other applications of MFC-based biosensors, such as DO and microbial activity. Further, challenges and prospects of MFC-based biosensors are briefly discussed.",
"conclusion": "6. Conclusions MFC as an analytical tool has been developing very fast over the past two decades. Its application has been expanded from BOD measurement to toxicity detection, DO detection, microbial activity analysis or as a power source for other sensors. It exhibits unique advantages in these applications, such as easy construction, simple operation, low cost and in situ monitoring. Some of the MFC-based biosensors are commercially available. With advances in materials and microbiology, especially electrogenic bacteria, MFC-based biosensors may eventually become approved standard methods.",
"introduction": "1. Introduction Sensors can detect the properties and events occurring around and convert the sensed information into signals [ 1 ]. Nowadays, they are of great significance in many industries, providing quantitative information for counting, sorting, reading, and robotic guidance [ 2 ]. For environmental monitoring, stricter regulations and higher standards have resulted in growing demand for sensors that can detect pollutants quickly and sensitively. Due to the feasibility of portability, of working on-site and determining biological effects, biosensors have been emerging as appropriate analytical tools for environmental monitoring [ 3 ]. Typically, biosensors ( Figure 1 A) consist of biological recognition elements and physical transducers translating the biologic response into an electrical, thermal, or optical signal correlated to the analyte concentration [ 4 ]. According to the type of biorecognition, biosensors can be categorized as immunosensors [ 5 ], enzymatic biosensors [ 6 ], DNA biosensors [ 7 ], cell-based biosensors [ 8 ], and biomimetic biosensors [ 9 ]. Enzymatic biosensors occupy a considerable proportion in biosensors, and they exhibit high selectivity in differentiating the target [ 10 ]. However, they have several main limitations, such as cost-intensive approaches for enzyme purification and immobilization and short half-life time of enzymes compared to chemical catalysts [ 11 ]. These can be overcome by whole-cell based biosensors, and thus they are often considered as future alternatives to enzymatic biosensors [ 12 , 13 ]. As whole-cell based biosensors, microbial fuel cells (MFCs) have been applied for environmental monitoring. MFCs are devices that use microorganisms as catalyst to convert chemical energy directly into electricity [ 14 ]. According to the configuration, they can be classified into two types: single-chamber MFCs and dual-chamber MFCs. Dual-chamber MFCs ( Figure 1 B) consist of anodic and cathodic chambers separated by an ion exchange membrane (IEM), while single-chamber MFCs are mainly composed of anodic chambers and air cathodes [ 15 ]. Electroactive microbes are inoculated into the anodic chamber, where they generate electrons and protons by oxidizing organic compounds. Electrons are captured by the anode and then arrive at the cathode through an external circuit. Meanwhile, protons and other cations (e.g., Na + , K + ) migrate to the cathode through the IEM to keep charge balance [ 16 ]. Finally, when oxygen acts as the electron acceptor, electrons and protons will combine with oxygen to form water [ 17 ]. Despite numerous improvements have been made in MFCs, low power output still constrains their utilization as high-power generators in practice. MFC-based biosensors inherit the common problems of MFCs, such as stability, reproducibility of the signal, long-term operation and substrate-induced metabolic cross-effects. However, MFC-based biosensors focus on the (linear) relationship between the signal output (e.g., voltage, current) and changes in environmental conditions other than high power output [ 18 ]. In an MFC-based biosensor ( Figure 1 C), the developed biofilm in the anodic chamber plays the role of the bioreceptor, while the anode is regarded as the transducer. The response of the anodic biofilm to the disturbance affects the electron flow rate, which is transduced into a measurable signal [ 19 ]. MFC-based biosensor is expected to be one of the most promising applications of MFC-derived technologies, which has been studied to measure various parameters, including biochemical oxygen demand (BOD), chemical oxygen demand (COD), volatile fatty acids (VFAs), dissolved oxygen (DO), toxicants, and microbial activity ( Table 1 ). In this review, we summarize the status quo of MFC-based biosensors, focusing on BOD and toxicity detection. Other applications of MFC-based biosensors, such as DO and microbial activity, are briefly addressed. Finally, the further challenges and prospects of MFC-based biosensors are discussed."
} | 1,443 |
26542393 | PMC4819788 | pmc | 5,480 | {
"abstract": "The closely linked fitness of the Epichloë symbiont and the host grass is presumed to align the coevolution of the species towards specialization and mutually beneficial cooperation. Ecological observations demonstrating that Epichloë -grass symbioses can modulate grassland ecosystems via both above- and belowground ecosystem processes support this. In many cases the detected ecological importance of Epichloë species is directly or indirectly linked to defensive mutualism attributable to alkaloids of fungal-origin. Now, modern genetic and molecular techniques enable the precise studies on evolutionary origin of endophytic Epichloë species, their coevolution with host grasses and identification the genetic variation that explains phenotypic diversity in ecologically relevant characteristics of Epichloë -grass associations. Here we briefly review the most recent findings in these areas of research using the present knowledge of the genetic variation that explains the biosynthetic pathways driving the diversity of alkaloids produced by the endophyte. These findings underscore the importance of genetic interplay between the fungus and the host in shaping their coevolution and ecological role in both natural grass ecosystems, and in the agricultural arena.",
"conclusion": "Conclusions and future perspectives The importance of endophytic Epichloë species to focal ecosystem functions driving both below- and aboveground food webs is well recognized and accepted (Omacini et al. 2001 ; Clay and Schardl 2002 ; Clay et al. 2004 ; Rudgers et al. 2004 ; Saikkonen et al. 2006 , 2010a , 2013a , b , 2015 ; Rudgers et al. 2007 ; Omacini et al. 2012 ). Recent phylogenetic and molecular analyses coupled with accumulating ecological approaches have provided insights into the coevolution of Epichloë -grass symbiosis and how genetic interplay between the partners can have great repercussions also in a ecological time-scale. Reproduction and transmission mode (vertical vs. horizontal) of Epichloë species as well as architecture and lifespan of the host grass are important factors related to the epidemiology, genetic compatibility, specialization and evolution of avirulence in Epichloë species. However, the general questions to be solved in future studies are (a) what is the relative importance of phenotypic plasticity and heritable (genetic and/or epigenetic) variation in ecologically relevant grass traits, (b) how selection operates on the unitary, modular or super organism levels of Epichloë -grass associations, (c) how the phenotypic unit of the symbiotum mediates plant–plant and trophic interactions in grassland communities, and (d) species distribution ranges. Until now the lack of this knowledge has limited the use of full potential of endophytic Epichloë species in sustainable agriculture.",
"introduction": "Introduction Specialization and coevolution have taken the center stage of discussion in evolutionary biology since Darwin emphasized in Origin of Species how species diversity and interactions together shape the evolution of life from individuals to communities (Darwin 1859 ; Thompson 1994 ). Now we know that virtually all species evolve in interactions with other species, interactive species often reciprocally affect each other’s evolution, and reciprocal changes in coevolving species often require and/or produce specialization. Thus, the majority of evolution fundamentally incorporates the elements of coevolutionary processes, and specialization commonly plays a role, especially in tightly linked species interactions such as symbiotic microbial interactions. Interactions between endophytic Epichloë species and their host grasses provide a unique model for ecologists and evolutionary biologists interested in specialization in coevolving species interactions. By definition, fungal endophytes live internally and asymptomatically within organs of their host plant (Wilson 1995 ). These asymptomatic fungal infections are ubiquitous, abundant and taxonomically diverse residents in all terrestrial plants (Saikkonen et al. 1998 ; Rodriguez et al. 2009 ). The majority of endophytes are latent pathogens or dormant saprophytes and other fungal “hitch-hikers” lurking within the plant tissues without causing visible symptoms (Wilson 1995 ; Arnold et al. 2000 ; Saikkonen et al. 2004a , b ; Saikkonen 2007 ; Rodriguez et al. 2009 ; Partida-Martinez and Heil 2011 ; Zabalgogeazcoa et al. 2013 ). In contrast to many other fungal taxa having asymptomatic endophytic periods in their life cycles, the endophytic Epichloë species (Leuchtmann et al. 2014 ) that are symbiotic with cool season grasses form systemic and life-long infections within their hosts. This extension of latency seen with Epichloë species is associated with reduction of virulence, adaptations and specialization that can promote fitness benefits to the host grass (Schardl 1996 ; Kover and Clay 1998 ; Saikkonen et al. 1998 , 2004b , 2006 , 2010a ; Spatafora et al. 2007 ). The symbiosis between Epichloë species and grasses is highly integrated involving the reciprocal use and manipulation of morphology, physiology, and life cycle and history traits of the partners to increase the fitness of the symbiota. First, the fungal hypha grows throughout the above-ground tissues of the host grass including inflorescences. It remains restricted to the intercellular spaces. Such an intimate relationship requires adaptations allowing the fungus to access the host plant interior, perhaps suppressing the recognition and defense responses that normally halt the establishment of harmful fungal infections in the host plant (Hamilton et al. 2012 ; Saikkonen et al. 2013a ). The associated mechanisms are poorly understood but the oxidative balance is suggested to play a role (Hamilton et al. 2012 ). Second, the fitness of the partners is tightly linked, which should favor the evolution of interaction toward reduced antagonism and increased partner fidelity (Thompson 1994 ; Saikkonen et al. 2002 ). Epichloë species are obligate associates of grasses subsisting entirely on the host grass. In addition to nutrient acquisition, grass reproduction provides a distribution avenue for the Epichloë species which are vertically transmitted in seeds from plant to its offspring. For strictly asexual Epichloë species vertical transmission is the only described means for distribution, whilst pleiotropic Epichloë species are capable of both vertical and horizontal transmission with asexual or sexual life cycles (Michalakis et al. 1992 ; Schardl 1996 ; Saikkonen et al. 1998 ; Tadych et al. 2012 ). At the other end of the continuum, truly sexual Epichloë species are horizontally transmitted by ascospores. Thus, the distribution of Epichloë species is largely determined by the fitness of the host particularly in the case of strictly asexual Epichloë species (but see Saikkonen et al. 2002 ). In exchange for hosting the endophyte, the host grass can receive benefits such as competitive superiority compared to uninfected counterparts in a population through increased growth and reproduction, as well as resistance to various abiotic and biotic stresses such as drought, flooding, pathogens and herbivores (Clay 1988 , 2009 ; Saikkonen et al. 2006 , 2010a ; Song et al. 2015 ). Consequently, Epichloë species have the potential to markedly affect host fitness, exert strong selective pressure on grass host traits, and modulate grassland ecosystems (Clay and Holah 1999 ; Saikkonen 2000 ; Clay et al. 2004 ; Rudgers et al. 2004 , 2007 ; Saikkonen et al. 2013a ). Similarly to other biological interactions based on mutual exploitation, benefits to Epichloë species and their host grasses are rarely symmetric. Thus, the symbiosis can range from antagonistic to mutualistic, and conflicting selection forces are likely to destabilize them. For example, when pleiotropic and antagonistic Epichloë species enter their sexual life cycle they produce external stromata surrounding some or all host inflorescences eliminating seed production. The benefits from endophytes appear to be dependent on the fungal and host genotype, and on environmental conditions. Accordingly, the symbioses are commonly regarded either as commensal or mutualistic. The major destabilizing forces in the symbiosis are asymmetry in dependence and genetic compatibility. Accumulating evidence has revealed that the grass does not necessarily depend on the fungus in some environments, many Epichloë strains are host species specific and genetic mismatch between host and symbiont can limit the endophyte-grass combinations (Saikkonen et al. 2004b , 2006 , 2010b ; Gundel et al. 2010 , 2012 , 2013 ). In this paper we first dissect recent research advances and literature on endophytic Epichloë species, covering their evolutionary origin and taxonomical aspects, functional genetics, and coevolution with host grasses, and then examine their ecological roles and potential in novel solutions for sustainable agriculture. Accumulating findings have revealed that Epichloë species can reprogram host metabolism, and modulate photosynthesis, signaling and chemical cross-talk between the partners (Huitu et al. 2014 ; Eaton et al. 2010 , 2015 ; Dupont et al. 2015 ) and thus, directly promote the growth, reproduction and competitive ability of the host grass (Clay and Holah 1999 ; Rudgers et al. 2004 , 2007 ; Saikkonen et al. 2013b ). However, here we focus on functional genetics driving alkaloid production because defense against herbivores is suggested to be the primary driving selective force behind the mutualism (Clay 2009 ; Saikkonen et al. 2010a )."
} | 2,433 |
34947905 | PMC8706314 | pmc | 5,481 | {
"abstract": "Future manned space travel will require efficient recycling of nutrients from organic waste back into food production. Microbial systems are a low-energy, efficient means of nutrient recycling, but their use in a life support system requires predictability and reproducibility in community formation and reactor performance. To assess the reproducibility of microbial community formation in fixed-film reactors, we inoculated replicate anaerobic reactors from two methanogenic inocula: a lab-scale fixed-film, plug-flow anaerobic reactor and an acidic transitional fen. Reactors were operated under identical conditions, and we assessed reactor performance and used 16s rDNA amplicon sequencing to determine microbial community formation. Reactor microbial communities were dominated by similar groups, but differences in community membership persisted in reactors inoculated from different sources. Reactor performance overlapped, suggesting a convergence of both reactor communities and organic matter mineralization. The results of this study suggest an optimized microbial community could be preserved and used to start new, or restart failed, anaerobic reactors in a life support system with predictable reactor performance.",
"introduction": "1. Introduction Future projects for NASA and private space agencies include the establishment of an orbiting Moon base as well as manned travel to Mars. The high costs and size constraints associated with shipping food makes this scenario unlikely to support long-term manned space travel. Therefore, future manned space operations will require efficient recycling of water and nutrients from organic waste for reincorporation back into food production. Currently, on the International Space Station, fecal waste is collected and stabilized for storage prior to shipment back to Earth for disposal [ 1 ]. Urine is collected separately from fecal waste with water recovered by vapor compression distillation and the concomitant production of a nutrient-rich brine [ 1 ]. In both scenarios, valuable nutrients are not reused, but rather collected for disposal. There are currently no waste treatment systems validated for space travel that are able to recover nutrients from food and metabolic wastes for reincorporation into food production. Due to the high water content of urine, feces, and food waste, thermal processes such as combustion, pyrolysis, or gasification would be energy-intensive, and therefore, undesirable for incorporation into life support systems [ 2 ]. Microbial waste treatment is a better option as this is capable of mineralizing a wide variety of wastes while yielding valuable nitrogen and phosphorus nutrients for crop production. Both aerobic and anaerobic microbial treatment systems have been investigated for nutrient recycling in space operations [ 3 , 4 ], although anaerobic systems are preferable as these do not require expensive aeration and produce less microbial biomass. Some studies examining anaerobic waste treatment for space travel have focused on the suppression of methanogenesis to produce a high VFA, high ammonia effluent [ 5 , 6 ]. However, completely preventing methanogenesis is operationally challenging, and methanogenic anaerobic treatment is capable of mineralizing the bulk of organic carbon to CO 2 and methane. The separation of these gases produces a concentrated CO 2 stream that can be used for the growth of algae as a food source [ 7 , 8 ], and the recovered methane can be used for energy production or supplemental food production [ 9 ]. Despite concerns about the use of flammable gases during space travel, methane is currently part of atmosphere regeneration on the ISS [ 10 ], and long-term mission strategies propose to continue this practice for atmosphere regeneration [ 11 ]. The current use of methane gas during the operation of the ISS suggests methane can be safely controlled and utilized in future space missions. Therefore, anaerobic waste treatment is a viable option for recycling nutrients in life support systems. The anaerobic breakdown of organic matter follows sequential steps mediated by a consortium of microbes [ 12 ]. The first step is the hydrolysis of the polymeric substances (polysaccharides, lipids, proteins) into smaller substrates (sugars, fatty acids, amino acids). These are, in turn, utilized during the next stage in the process, termed acidogenesis, in which fermentation produces primarily volatile fatty acids (VFAs) and alcohols, CO 2 , and hydrogen, along with ammonia and sulfide. The final stages, acetogenesis and methanogenesis, overlap. Methane is produced by methanogens through three main pathways. Hydrogenotrophic methanogenesis reduces CO 2 to methane with electrons from H 2 , acetotrophic methanogenesis ferments acetate to CO 2 and methane, and methylotrophic methanogenesis produces methane from methylated substrates such as methanol and methyl sulfides. Acetogenesis converts the fatty acids and alcohols produced during acidogenesis to acetate, H 2 , and CO 2 in syntrophic association with other members of the consortium, often methanogens [ 12 ]. Anaerobic digestion technology has been widely deployed to treat a variety of organic wastes including municipal wastewater sludge, animal manure, agricultural residues, and food waste. Some researchers have attempted to identify a “core microbiome” necessary for anaerobic digestion, yet there is minimal consensus in these findings. Over the course of a year, Calusinka et al. monitored 20 mesophilic, full-scale, continuously stirred tank reactors (CSTRs) treating either municipal wastewater sludge, animal manure, or a combination of the organic fraction of municipal solid waste and agricultural waste [ 13 ]. The microbiomes of individual reactors varied little over the monitoring period. Core members of the Archaea present at all sampling points represented 12.4% of OTUs but 75.3% of sequence abundance. Similarly, core bacteria represented 2.5% of OTUs but accounted for 70.3% of reads, suggesting that microbes representing a rather limited number of OTUs performed the bulk of anaerobic digestion. Thirteen phyla were present in all the samples, including Euryarchaeota , Firmicutes , Bacteroidetes , Cloacimonetes , Proteobacteria , Tenericutes , Spirochaetes , Aminicenantes , Chloroflexi , and Parcubacteria . Hassa et al. examined the microbiomes of 67 CSTRs at 49 different biogas plants differing in operational temperature, retention time, and feedstocks [ 14 ]. A few dominant phyla (e.g., Euryarchaeota , Firmicutes , Bacteroidetes , Cloacimonetes , and Tenericutes ) were similar to those reported by Calusinska et al. [ 13 ]. However, Chloroflexi , Spirochaetes , Aminicenantes , Parcubacteria , and Proteobacteria were not detected in all the reactors. Additionally, the researchers detected the predominance of different phyla, specifically Actinobacteria and Atribacteria [ 14 ], suggesting that these phyla could be considered part of the anaerobic digestion core microbiome. Sundberg et al. determined the microbial communities of 21 full-scale CSTRs, operated at mesophilic or thermophilic conditions, and fed either municipal wastewater sludge, or mixtures of co-digested substrates including slaughterhouse waste, household and restaurant food waste, agricultural residues, and manure [ 15 ]. Sequences belonging to Firmicutes (classes Clostridia , Bacilli , and Erysipelotrichia ) and Bacteroidota (classes Sphingobacteria and Bacteroidetes ) were the only bacterial phyla detected in all the reactors [ 15 ]. These studies suggest a fairly wide diversity of digester microbiomes can function to break down organic matter and recycle nutrients in a life support setting. This functional redundancy is useful in preventing digester upsets; however, it may also cause a lack of predictability in the responsible microbial systems. Ideally, the resultant microbial community and concomitant performance of a digester should be predictable based upon the parameters that can be controlled in the life support system. Development of the microbial community in anaerobic reactors is attributed to both stochastic and deterministic processes. Stochastic processes result from random assembly of the microbial community due, in part, to the potential for functional redundancy in the system. Deterministic processes include the operational control of parameters, such as inoculum, temperature, substrate, organic loading rate, retention time, and reactor configuration. The aforementioned surveys of full-scale CSTRs determined that digester microbiomes are clustered by both temperature [ 14 , 15 ] and substrate [ 13 , 15 ], suggesting performance and microbial communities can be predicted by operational parameters. However, in these studies, reactors were receiving unsterilized waste and so there could be some contribution from the substrate to the microbiome. Han et al. sought to determine the role of the inoculum in the resultant digester microbiome by inoculating CSTRs from full-scale reactors (CSTRs and granular), as well as natural (manure) sources [ 16 ]. Reactors were fed a sterilized basal medium containing cellulose that prohibited reactor colonization from the substrate. The sequencing of reactor communities and inoculum sources showed a clustering of each reactor microbial community with its inoculum source, suggesting a strong influence of the inoculum on the resultant reactor community. Despite developing different communities, the reactors inoculated from different sources demonstrated similar performance, suggesting functional redundancy. However, the triplicate reactors inoculated from a single source demonstrated different performance and different microbial communities, also suggesting stochastic influences in community assembly [ 16 ]. Lemoine et al. inoculated replicate batch reactors from three full-scale digesters, two granular and one CSTR, which were fed pasteurized synthetic dairy wastewater until stable operation was achieved [ 17 ]. Performance was similar for all the reactors, regardless of the inoculum. The sequencing of the microbial communities of these reactors showed only about 25% of OTUs were shared among all the reactors. However, these shared OTUs accounted for over 98% of sequence reads, suggesting similar dominant communities in all the reactors. Similar to the findings of the other studies, the samples in this study clustered by the reactor from which they were taken, and the replicate reactors clustered according to the inoculum source, suggesting persistent and detectable differences in the community structure. Additionally, microbial communities in the lab-scale reactors were more similar to each other than were the communities of the original inocula, suggesting some community convergence in the lab-scale reactor environment [ 17 ]. Community convergence was also detected by Peces et al., who examined the temporal community changes of CSTRs processing cellulose and casein that were inoculated from four full-scale anaerobic reactor sources [ 18 ]. Over time, the reactors converged in both chemical profile and microbial community, with 52% of the identified OTUs shared among all the digesters, representing 72% of the relative abundance. The authors concluded deterministic rather than stochastic processes were important in determining microbial communities [ 18 ]. These studies suggest that although the inoculum source results in detectable differences in the resultant communities, functional redundancy can result in effective and reproducible performance with different communities. These findings are important in the context of a life support system where a reactor may need to be reinoculated from a preserved inoculum, or even from the waste it is treating. Additionally, the choice of reactor type is important for predicting its performance and microbial community. In the previously mentioned studies, reactors were operated as either CSTRs or batch reactors. The small confines of a life support system will require an efficient, high-rate processing of organic waste, which is better suited to a fixed-film reactor. The anaerobic microbial breakdown of organic matter generally proceeds more slowly than aerobic breakdown, as less energy is available from anaerobic processes. However, the use of fixed-film reactors can overcome this limitation by separating the hydraulic retention time of the waste from the solid retention time of the anaerobic microbes, allowing rapid and nearly complete organic matter mineralization with rather compact reactor sizes [ 19 ]. Additionally, fixed-film anaerobic reactors are resistant to changes in the organic loading rate [ 20 ], toxins [ 21 ], high ammonia concentrations [ 20 , 22 ], and even intermittent operation [ 23 ], thereby reducing operational complexity. More recently, developments in anaerobic membrane reactors have shown this technology to be capable of low energy, high-rate organic matter breakdown with the production of a nutrient-rich, microbe-free effluent that can be subsequently used for crop cultivation or further refined to potable water [ 3 , 24 ]. The initial testing of an anaerobic membrane reactor for inclusion in future manned space missions has yielded promising results, including the removal of 99% of volatile solids and resistance to shut-down periods of up to 147 days [ 3 ]. However, few studies have examined the reproducibility of performance and microbial community in fixed-film reactors inoculated from different sources. This is likely due, in part, to the predominance of CSTRs in full-scale digester operations. Cheng et al. examined microbial communities of lab-scale packed-bed membrane reactors and identified core genera present in more than 90% of reactor samples [ 25 ]. These genera represented between 2.4 and 2.9% of sequence reads, and largely belonged to methanogens and their syntrophic fermentative partners. These findings suggest the fixed-film reactor environment selected for a small portion of the community with stochastic assembly describing the bulk of the microbial community [ 25 ]. The most important factors for the deployment of microbial systems in space operations are reliability and predictability. Given the operational efficiency and durability of fixed-film and/or membrane reactors, these are likely candidates for inclusion in a life support system. However, there is a lack of studies examining the reproducibility of microbial community formation in fixed-film reactors, from either naturally occurring or constructed reactor inocula. Therefore, the purpose of the current study was to examine the reproducibility of microbial community development in fixed-film anaerobic digesters inoculated from natural and constructed methanogenic environments and operated under identical conditions. The purpose of this work was to elucidate the influence of both the inoculum and the reactor environment in providing predictable, reproducible microbial communities and performance in replicate reactors inoculated from the same source, as well as the degree to which functional and phylogenetic convergence can occur from diverse microbial inocula.",
"discussion": "4. Discussion This work studied the influence of the inoculum and operational conditions on the establishment of microbial communities in plug-flow, fixed-film reactors. In the current study, a marked decrease in diversity was noted in comparing the lab-scale reactors to the inocula, and this was most dramatic for the Bog-inoculated reactors. Previous studies have demonstrated a similar decrease in community diversity when comparing lab- to full-scale reactors [ 16 , 17 ]. Scaling down the anaerobic digestion process contributes to a loss of microbial community complexity as full-scale reactors are more likely to harbor environmental niches that can support greater microbial diversity. Loss of diversity may lead to a loss in the ability of the microbial community to respond to changes in the reactor, for example, from periodic overloading or a drop of temperature due to a loss of reactor heating. However, high microbial diversity does not necessarily impart an increase in substrate processing, which is the most important function for a digester in a life support system. Venkiteshwaran et al. seeded triplicate reactors from each of 50 full-scale reactors and sequenced the resulting 150 microbial communities [ 48 ]. The researchers found no correlation between the methane production rates and the community indices of diversity or evenness [ 48 ]. Therefore, a highly diverse microbial community does not necessarily predict efficient reactor performance. In general, the diversity of the lab-scale reactor community may result from functional redundancy provided by phylogenetically different microbes. Most studies examining the development of communities in lab-scale reactors inoculated from different sources have found a convergence in both the functioning and community structure [ 16 , 17 , 18 , 49 ], suggesting deterministic processes primarily drive microbial community development. A study by Peces et al. found that lab-scale digester communities demonstrated different metabolic rates for stages of anaerobic digestion (e.g., hydrolysis, acetogenesis, methanogenesis) during the start-up period, but that these rates converged over time for reactors inoculated from different sources [ 18 ]. Microbial community convergence also occurred, yet the differences in community structure and membership based on the inoculum source appeared to be due to minor community members [ 18 ]. Lemoine et al. also saw persistent differences in the community structure based on the inoculum source despite a convergence in the methane production potential for these reactors [ 17 ]. Lemoine et al. suggested that the use of a pre-adapted inoculum, coupled to a slow start-up period, led to the high reproducibility of performance and resultant communities in the replicate reactors in their study [ 17 ]. Indeed, the use of a high diversity or non-adapted inoculum may allow stochastic processes to cause divergences in microbial communities and performance in replicate reactors. Vanwonterghem et al. inoculated triplicate reactors from a mixture of lake sediment, rumen fluid, and anaerobic lagoon material and followed performance and microbial community structure over time. The researchers detected different members of the microbial communities in replicate reactors as responsible for similar processes (e.g., hydrolysis, fermentation, acetogenesis, methanogenesis), leading to different community structures and somewhat different reactor performances [ 50 ]. Other studies examined the development of methanogenesis in lab-scale reactors inoculated from wholly environmental sources. Braun et al. used PAH-contaminated soil, sediment, or wastewater treatment plant sludge as the inoculum for a single lab-scale reactor [ 51 ]. The three reactors possessed different microbial communities and demonstrated vastly different performances, with the reactor receiving an adapted inoculum (wastewater treatment plant sludge) demonstrating high methane production potential and PAH removal [ 51 ]. Perrotta et al. inoculated anaerobic digesters with camel manure, mangrove intertidal sediment, or sludge from a full-scale anaerobic digester [ 52 ]. Despite an enrichment of common OTUs among lab-scale reactors, suggesting some convergence of communities, the reactors retained structurally different communities and demonstrated different performance [ 52 ]. Although it is evident that an environmental inoculum would not be adapted to a constructed reactor environment, thus leading to stochasticity in microbial community formation, it is also important to match the reactor inoculum to the substrate. For example, Moestedt et al. inoculated duplicated reactors from two full-scale anaerobic reactors treating either food and slaughterhouse waste or digesting municipal sludge [ 49 ]. One reactor from each inoculum was then fed food waste as a substrate while the other reactor in the pair was fed digested sludge. The reactors where the inoculum and substrate were matched showed better initial performance, although the performance and reactor communities became similar [ 49 ]. Therefore, the reproducibility and predictability of performance in an anaerobic digester would best be obtained from an inoculum obtained from similar reactor type and operating conditions. In the current study, the replicate Bog reactors had very different community structures and performances from each other than did the replicate AD reactors. The large lab-scale anaerobic reactor was operated for 455 days before serving as an inoculum source for AD 1–4, and therefore, had already selected as a subset of the initial inoculum that could thrive in a lab-scale reactor environment. However, AD 3 had a different community and poorer performance than the other AD reactors. Although there were detectable differences in the microbial communities in the four reactors, these community shifts were smaller and the microbial community development more reproducible than in the Bog-inoculated reactors due to the use of an inoculum that had already been adapted to a reactor environment. It is notable that the reactors inoculated from a highly diverse, acidic bog community could eventually develop communities capable of methanogenesis from ersatz waste, which is quite different from the lignocellulosic material that is the primary substrate in the bog environment [ 27 ]. Although the communities in Bog 1 and Bog 2 differed from each other, they were more similar to AD 1–4 than the original inoculum. Additionally, the methane production from Bog 1 was similar to that of AD 3, suggesting that a community capable of efficiently processing the ersatz waste could be obtained from a wholly environmental inoculum. These results provide a measure of assurance that an anaerobic digester in a life support system could be restarted, in the event of reactor failure, from a preserved inoculum or even a naturally occurring source (e.g., human waste). In this study, deterministic processes, such as operational conditions and choice of substrate, led to a convergence among the small reactor communities inoculated from different sources. However, stochastic processes resulted in somewhat different communities in replicate reactors inoculated from the same source. In this study, clustering analysis of triplicate samples from each small reactor generally grouped according to the reactor from which they were taken as well as by the inoculum source. Despite the clustering analysis, AMOVA detected few statistical differences between the communities in the small reactors, and HOMOVA detected no differences at all. Additionally, the unweighted UniFrac suggested some differences between the small reactor communities, but differences were not detected with the weighted UniFrac. These results suggest minor community members were responsible for the differences in community structure by inoculum source. It is not known if these differences would eventually disappear over longer operational periods as there is generally some stochasticity in community structure during initial reactor operating periods [ 16 , 18 ]. As previously discussed, reactors with somewhat different methanogenic communities can demonstrate a similar performance due to functional redundancy, and different sequencing efforts have resulted in different “core” microbiomes of anaerobic digesters [ 13 , 14 , 15 ]. Given the resolution of the current sequencing methods, it is possible that some of the differences detected in methanogenic communities are insignificant in terms of actual reactor performance, whether due to functional redundancy, normal temporal fluctuations in community membership, or the limitations of reactor sampling for sequencing. Life support systems that utilize microbial communities to carry out specific functions require predictability, reproducibility, and redundancy. The anaerobic rather than aerobic treatment of organic waste is advantageous as the produced methane and CO 2 can be further utilized for energy or food production without oxygen consumption. Extensive research has been devoted to the European Space Agency’s MELiSSA project [ 5 , 6 ], which depends upon microbial systems to accomplish waste treatment and food production, thereby demonstrating how microbial reactor predictability can be accomplished through control of the reactor community and operational conditions. The translation of this work to a methanogenic community may require the formation of an artificially constructed, pathogen-free inoculum composed of community members providing all the necessary metabolic flexibility to process a complex waste stream. Reducing the number of community members would reduce the stochastic nature of microbial community formation, although reducing the diversity could make the reactor more sensitive to process upsets. However, this could be countered by operating multiple reactors in parallel, and maintaining preserved inoculum for restarting reactors, if necessary. Additionally, reactor operation could implement heat pretreatment to sterilize the influent waste that would also hydrolyze lignocellulosic material, thus making it easier to mineralize in the reactor [ 53 ]. Methanogenic reactors would thus serve a vital function in life support systems by facilitating the mineralization and recycling of carbon and nutrients."
} | 6,407 |
30942594 | null | s2 | 5,482 | {
"abstract": "Inspired by this elegant system of cellular adaptivity, we herein report the rational design of a dynamic artificial adaptive system able to sense and respond to environmental stresses in a unique sense-and-respond mode. Utilizing DNA nanotechnology, we constructed an artificial signal feedback network and anchored it to the surface membrane of a model giant membrane vesicle (GMV) protocell. Such a system would need to both senses incoming stimuli and emit a feedback response to eliminate the stimuli. To accomplish this mechanistically, our DNA-based artificial signal system, hereinafter termed DASsys, was equipped with a DNA trigger-induced DNA polymer formation and dissociation machinery. Thus, through a sequential cascade of stimulus-induced DNA strand displacement, DASsys could effectively sense and respond to incoming stimuli. Then, by eliminating the stimulus, the membrane surface would return to its initial state, realizing the formation of a cyclical feedback mechanism. Overall, our strategy opens up a route to the construction of artificial signaling system capable of maintaining homeostasis in the cellular micromilieu, and addresses important emerging challenges in bioinspired engineering."
} | 304 |
35521306 | PMC9066182 | pmc | 5,483 | {
"abstract": "The objective of this study is to assess bioelectricity generation, pollutant removal (COD, ammonium, nitrate) and the bacterial communities on anodes in constructed wetlands coupled with microbial fuel cells (CW-MFCs), through feeding the systems with three different types of synthetic wastewater (system 1: normal wastewater; system 2: ammonium-free wastewater; system 3: nitrate-free wastewater). Three CW-MFCs were operated with different wastewater concentrations and hydraulic retention times (HRTs) over a long time period (6 months). The results indicate that the maximum open circuit voltage (775.63 mV) and maximum power density (0.628 W m −3 ) were observed in system 3 (period 3), and that bioenergy production was inhibited in system 2, when feeding with ammonium-free wastewater continuously. COD removal rates in the three systems were similar during each period and ranged from 82.2 ± 6.8% to 98.3 ± 2.2%. Ammonium removal occurred at the air cathode of the CW-MFCs through nitrification, and a higher level of ammonium removal was found in system 1 (period 3) compared with the others. Meanwhile, denitrification occurred at the anaerobic anode of the CW-MFCs, and a large amount of nitrate was removed effectively. The highest nitrate removal rate was 98.8 ± 0.5% in system 2 (period 3). Additionally, four genera related to electricity generation were detected at the anode: Geothrix ; Desulfovibrio ; Desulfobulbus ; and Geobacter . The relative abundances of Desulfovibrio , Desulfobulbus and Geothrix gradually increased during the three periods in system 3, which might be beneficial for bioelectricity generation. Further investigations are needed to optimize the CW-MFC performance and explain the mechanism behind the pollutant degradation and electron motion in the CW-MFCs.",
"conclusion": "5. Conclusions In this study, the optimal operating conditions for CW-MFCs were investigated through evaluating the bioelectricity generation and pollutant removal performances of CW-MFCs under different operating conditions and periods of time. Further correlational research relating to microbial community structures, electricity generation and decontamination under different conditions was undertaken. In terms of bioelectricity generation, the results indicated that the maximum open circuit voltage (775.63 mV) and the maximum power density (0.628 W m −3 ) were observed in system 3 (period 3), and that bioenergy production was inhibited in system 2. It was verified that electricity generation by CW-MFCs would be inhibited using sewage with high nitrate concentrations in the anodes. In terms of pollutant removal, the COD removal rates of the three systems were similar during each period and ranged from 82.2 ± 6.8% to 98.3 ± 2.2%. Ammonium removal occurred at the air cathodes of the CW-MFCs through nitrification, and a higher ammonium removal efficiency was found in system 1 (period 3) compared with the others. Meanwhile, denitrification occurred in the anaerobic anodes of the CW-MFCs, and a large amount of nitrate was removed effectively. The highest nitrate removal rate was 98.8 ± 0.5% in system 2 (period 3). In the anodic microbial communities, four genera related to electricity generation were detected in the CW-MFCs: Geothrix ; Desulfovibrio ; Desulfobulbus ; and Geobacter . The relative abundances of Desulfovibrio , Desulfobulbus and Geothrix gradually increased during the three periods in system 3. Higher proportions of denitrifying bacteria, including Nitrospira , Thauera and Dechloromonas , were observed at the anode. Further studies of the metabolic pathways of pollutant removal and electron motion are needed.",
"introduction": "1. Introduction The use of systems involving constructed wetlands coupled with microbial fuel cells (CW-MFCs) is a novel development in the field of environmentally friendly wastewater treatment equipment, contributing to bioelectricity generation and the biodegradation of pollutants. 1–3 Recently, CWs have been used to treat livestock wastewater containing high levels of ammonium and nitrate. 4 However, given the limited oxygen transfer rates of traditional CWs and the high residual organic matter and ammonium content in these types of wastewater, treatment efficiency using traditional wetlands is often quite low and requires a large land area. 5 CW-MFCs are a new technology that couples CWs and MFCs. The surface of a vertical flow CW is an aerobic region and the underlying substrate is an anaerobic region, similar to the cathode and anode of a MFC. 3 The performance of a MFC can effectively be improved by using a large number of denitrifying microorganisms and electrogenic microorganisms in the CW. 6 CW-MFCs have the advantages of low cost, easy operation and recyclability, and have been thoroughly studied and widely used in the secondary treatment of domestic sewage, landfill leachate and industrial wastewater. 7 The structure of a CW-MFC mainly consists of four parts: an anaerobic anode chamber, an intermediate filter layer, an air cathode chamber and macrophytes. The chemical transformations (CH 2 O + n CO 2 → n CO 2 + 4 n e − + 4 n H + ) that take place in the anaerobic anode chamber to degrade pollutants and generate electrons involve a multitude of anaerobic microorganisms and facultative anaerobic microorganisms. The intermediate filter layer mainly functions as a medium for protons to move in and to facilitate the simple filtration of sewage. The reaction at the air cathode is 4 n e − + n /2O 2 + 4 n H + → 2 n H 2 O, which completes the whole electrochemical cycle. 8 Macrophytes can absorb small amounts of soluble pollutants and provide oxygen for the air cathode. 9 Furthermore, plant photosynthesis is the main way of promoting bioelectricity generation. At present, environmental pollution and energy shortages have become serious worldwide problems. The main pollutants are made up of sulfides, organic phosphorus, nitrates, nitrites and ammonium. 10 For nitrogenous pollutant removal, previous studies have indicated that nitrate/nitrite can be used as an electron acceptor and be removed at the anoxic-cathode chamber of a MFC. 11 Although nitrate can also be removed at the anode, only weak electricity generation can occur in the presence of nitrate at the anode chamber of a MFC. As a competing electron acceptor, nitrate offers advantages over the anode during the anode reaction, hindering electricity generation. 12 Srinivasan et al. investigated the impact of nitrate at different C/N ratios in mixed-culture chemostats of MFCs. Geobacter can simultaneously degrade nitrate and organic pollutants at the anode, producing carbon dioxide and nitrogen and limiting electron donors at lower C/N ratios. 13 Previous studies have found that the CE is affected by a high C/N ratio, while the maximum voltage output is not significantly affected. MFC bioelectricity generation and nitrate removal functionality are affected by the biofilm thickness of EAB. Sun et al. found that power generation and nitrate removal in a MFC first increase and then decrease along with an increase in biofilm thickness. 14 The removal of nitrates and ammonium under specific conditions has been extensively studied using MFCs. 15–17 However, whether bioelectricity generation performance is affected by nitrate as a competing electron acceptor in the anode reaction of a CW-MFC has seldom been investigated. Additionally, ammonium should first be nitrified before being removed as an electron acceptor through denitrification in the anoxic-cathode chamber. Functional microorganisms play an important role in CW-MFC bioelectricity generation and the biodegradation of pollutants. Meanwhile, the bacterial community composition is associated with the removal of pollutants, such as COD, ammonium and nitrate, and electricity generation, and the effects of the bacterial community composition on CW-MFC performance are yet to be investigated. 18 Since the major oxidation reaction in a CW-MFC occurs at the anaerobic anode, it is particularly important to investigate the microbial community structure of the anode. However, operating conditions such as temperature, HRT, substrate concentration and pH are considered to be important factors that influence the microbial community composition of CW-MFCs. The same utilizable substrate at different concentrations in a MFC might also lead to the bacterial communities developing different structures. 19 Therefore, the influences of different types of wastewater on the microbial community compositions in CW-MFCs should be accounted for in the future. To date, previous studies have reported certain electrochemically active bacteria (EAB), including Desulfuromonas , Pseudomonas , Desulfobulbus , Thermincola , Geothrix , Shewanella , Klebsiella , Enterobacter , Rhodopseudomonas , Citrobacter and Geobacter , 20,21 while most EAB are also nitrobacteria and denitrifying bacteria, such as Shewanella and Geobacter . 22 During the denitrification process, the electrons produced by EAB can be used to convert nitrate into nitrogen gas, which can contribute to nitrate removal in CW-MFCs. 23 In this study, bioelectricity generation, COD removal, ammonium removal, nitrate removal and the bacterial community on the anode were assessed in CW-MFC systems using three different types of synthetic wastewater (system 1: normal wastewater; system 2: ammonium-free wastewater; and system 3: nitrate-free wastewater). The three CW-MFCs operated under continuous influent mode for a long time using different wastewater concentrations and HRTs. We examined and compared the bioelectricity generation performances, wastewater treatment performances and anodic bacterial communities over three periods. The aim of this study was to evaluate the relationships between bioenergy production, pollutant removal efficiency, and microbial community structure in CW-MFCs using different types of synthetic wastewater. Correlations were found between the anode microbial community structure and bioelectricity generation, as well as between the anode microbial community structure and pollutant removal. The effects of the anode microbial community structure on CW-MFC production performance and pollutant removal were also investigated.",
"discussion": "4. Discussion 4.1 Correlation between bioelectricity generation and microbial community composition The bioelectricity generation mechanism of a CW-MFC is as follows. In the anode, glucose from synthetic wastewater can be used as a resource by EAB to generate electrons (e − ) and protons (H + ). Electrons (e − ) are transferred to the cathode along the external circuit and protons (H + ) are transferred to the cathode via flow. In the cathode, oxygen from the air cathode acts as an electron acceptor and oxidizes with protons (H + ) and electrons (e − ) (O 2 + 4H + + 4e − → 2H 2 0). 37–40 This study attempted to explore the effects of different types of synthetic wastewater on the bioelectricity generation mechanism of CW-MFCs. In this study, the bioelectricity generation performances of the three CW-MFCs showed significant differences based on the different types of synthetic wastewater used. A negative bioelectricity generation effect was observed in system 2 (0.04–0.258 W m −3 ), which was supplied with ammonium-free wastewater over the entire operation period. This result can lead to the interpretation that nitrate can act as an electron acceptor and compete for the electrons produced by organic matter (OM) oxidation at the anode when synthetic wastewater containing high concentrations of nitrate flows through the anode of the CW-MFC. 38 The concentration of nitrate in the influent was mostly removed through the anodes of the CW-MFCs. A similar phenomenon has been reported in other studies conducted during the previous year. 26 Nitrate removal in a CW-MFC is mainly based on a pathway of denitrification (NO 3 − + 5e − + 6H + → 0.5N 2 + 3H 2 0 or NO 3 − + 2e − + 2H + → NO 2 − + H 2 O). However, the nitrate in the anode layer may consume more electrons during reduction and less electrons in the cathode half-cell reaction, leading the cathode potential to decrease. Therefore, electricity generation in CW-MFCs will be inhibited when using sewage with a high nitrate concentration in the anode. System 3 showed excellent power generation performance during the entire experiment. This is perhaps attributed to: (1) no nitrate or other electron acceptors flowing through the CW-MFC anode region, resulting in a large amount of electrons (e − ) from EAB-oxidized organic matter enriching the electrode and being passed to the cathode; and (2) the nitrification (NH4 + + 2O 2 → NO 3 − + 2H + + 2H 2 O) of ammonium ions in synthetic wastewater under aerobic conditions in the cathode chamber, where nitrate is formed as an electron acceptor that can promote bioelectricity generation in the CW-MFC. In this study, glucose and sodium acetate acted as carbon sources, and the bioelectricity generation of all CW-MFCs increased along with an increase in the carbon source concentration during the three periods. The value of bioenergy output increased from 0.08 to 0.28 to 0.3 W m −3 from period 1 to period 3 in system 1; from 0.04 to 0.06 to 0.26 W m −3 in system 2; and from 0.13 to 0.31 to 0.63 W m −3 in system 3. This phenomenon indicates that the higher carbon source concentration available during periods 2 and 3 might facilitate the activity and growth of electrochemically active bacteria. It can be speculated that CW-MFCs may show excellent power generation performance at higher carbon source concentrations. The low CEs (lower than 2%) reported in previous studies of CW-MFC systems demonstrate an urgent problem that needs to be solved. A negative impact on the CEs was observed when feeding with higher substrate concentrations in all three systems. Similar results have been previous reported. 23 The main reasons for this are as follows. Firstly, many heterotrophic microorganisms, such as methanogens, are present in the bottom and anode layers of CW-MFCs and they consume large amounts of organic matter, which is converted to methane. During periods 2 and 3, although large COD removal percentages were observed due to biological oxidation, the electrons released were not effectively captured or utilized at the anode. Secondly, in system 1 and system 2, due to high concentrations of nitrates in the anode zone, the electrons used for nitrate removal led to a decrease in the number of electrons available for electricity production, 38 thus resulting in CE decline. EAB play an important role in the CW-MFC bioelectricity generation process. Research has shown that the composition and relative abundance of EAB have a strong influence on CW-MFC electricity generation. 18,26 Seven genera related to electricity generation were identified in the CW-MFCs: Thermomonas ; Geothrix ; Desulfovibrio ; Desulfobulbus ; Pseudomonas ; Geobacter ; and Clostridium . Fig. S4 † shows the relationship between four important EAB and the bioenergy outputs of the CW-MFCs. After the CW-MFCs had been operating for three periods, the relative abundances of Geobacter (0.016% to 0.42%), Desulfovibrio (0.03% to 0.34%), Desulfobulbus (0.02% to 1%) and Geothrix (0.03% to 1.24%) increased with an increase in the substrate concentration and HRT of system 1 (Fig. S4A † ). Meanwhile, Desulfobulbus and Geothrix abundances increased sharply from period 2 to period 3. This phenomenon indicates that a high abundance of EAB can effectively increase the bioelectricity generation abilities of CW-MFCs. As shown in Fig. S4B, † the relative abundances of the genera Desulfobulbus and Geobacter in system 2 decreased rapidly from 0.005% to 0.0009% and from 0.0034 to 0.0004%, respectively, during period 2, suggesting that Desulfobulbus and Geobacter enrichment on the anode is inhibited by a lack of ammonium ions. The abundances of these two genera in system 2 decreased significantly from period 1 to 2, which can be interpreted as resulting in the phenomenon of negative bioelectricity generation in system 2. In system 3, the four EAB returned to higher abundances with an increase in the substrate concentration and HRT. As shown in Fig. S4C, † the relative abundances of Desulfovibrio , Desulfobulbus and Geothrix gradually increased during all three periods, which may be beneficial to bioelectricity generation in system 3. 4.2 Correlation between the degradation of synthetic wastewater and the microbial communities Heterotrophic microorganisms can play a significant role in the process of organic matter removal in CW-MFCs. In this study, high COD removal rates were observed in the anode layers of all three systems. Meanwhile, the COD removal performances of all CW-MFCs gradually decreased as the substrate concentrations and HRTs increased. The COD removal performance of a CW-MFC is inhibited when a higher organic matter load is present in the synthetic wastewater. 26 Illumina Hiseq 16S rRNA gene sequencing showed a large number of heterotrophic microorganisms, including Cytophagaceae, Uliginosibacterium , Propionivibrio , Bacteroidales and Anaerolinaceae, in the anode layer of the CW-MFCs. The order Cytophagaceae possesses the capability to biodegrade refractory organic compounds, including aromatic compounds, through anaerobic biodegradation, which may promote organic matter removal at the anaerobic anode. 39,40 The genus Uliginosibacterium , which possesses the capability to remove nitrogen and/or organic matter from wastewater, 41 was also observed in the CW-MFCs. Bacteroidales and Anaerolinaceae also increased in abundance in the CW-MFCs. These families have been identified as acidogenic fermenting bacteria that possess the ability to remove organic matter from wastewater. 34 Thus, it could be speculated that the COD removal efficiency can be significantly increased with an increased in the abundance of heterotrophic microorganisms in the anode. According to previous studies, denitrification occurs at the anaerobic anode of CW-MFCs, and nitrate is effectively removed. 27 Meanwhile, the process of nitrate removal causes a large amount of electrons to be consumed, which leads to the reduction of the anode potential and decreased bioelectricity generation in CW-MFCs. 38,42 It is very critical that the carbon balance and nitrogen balance are explored for CW-MFCs in relation to wastewater removal. Xu et al. discovered multiple carbon metabolism pathways through studying the carbon balance of CW-MFCs. 25 Therefore, studies of the nitrogen balance in CW-MFCs are urgently needed. Ammonium removal occurs at the air cathode of CW-MFCs through nitrification, 27 and nitrate from the nitrification process can be used as an electron acceptor to promote electricity generation. 38 This result explains the presence of nitrate in the air cathode area ( Table 1 ) and the excellent bioelectricity generation performance of system 3. Therefore, nitrifying and denitrifying bacteria play important roles in the removal of nitrogenous wastewater. At genus level, the relative abundances of nitrifying and denitrifying bacteria, including Planctomyces , Nitrospira , Bacillus , Thauera , Dechloromonas , Pseudomonas , and Thiobacillus , Flavobacterium , were also detected at the anaerobic anode through high-throughput sequencing analysis. Interestingly, we not only found anaerobic denitrifying bacteria in the anaerobic anode region, but also observed some aerobic nitrifying bacteria. This indicates that some small-scale aerobic regions exist in the anaerobic anode region. This result is consistent with the results of a previous study. 18 Higher proportions of denitrifying bacteria, including Nitrospira , Thauera and Dechloromonas , were observed at the anode (Fig. S5 † ). It is clear from Fig. S5 † that the relative abundances of these three microorganisms fluctuate in different systems and during different periods. Nitrospira can play a significant role in nitrifying and denitrifying, and the highest relative abundance of Nitrospira was found in system 3 (period 1). Meanwhile, the relative abundances of Nitrospira gradually reduced from period 1 to period 3 in all systems. Thauera has been identified as a type of autotrophic denitrifying bacteria that is able to biodegrade nitrogen without organic matter. A higher abundance of these bacteria was observed in system 1 (period 1) compared with the other systems. This result demonstrates that system 1 has excellent nitrate removal capacities. In system 2, the relative abundance of Thauera decreased rapidly from period 1 to period 2 (0.04% to 0.015%). The average relative abundances of Dechloromonas , which has been reported to be a type of autotrophic denitrifying bacteria, phosphate-accumulating microorganism and chlorate-reducing bacteria, 43,44 were similar in all three systems (period 3). There were a variety of EAB, such as Geobacter , Desulfovibrio and Pseudomonas , at the anaerobic anode. It has been reported that the nitrate removal efficiency can be significantly increased through using the electrons generated in CW-MFC reactors. Additionally, the change in water quality over the entire experimental period in all systems was attributed to adsorption by activated carbon and other substances. The process of the plant uptake of organic matter, nitrate and ammonium through the rhizosphere was observed, but the removal efficiency of nitrate through plant uptake was apparently lower than when carried out by microbes. 45"
} | 5,423 |
30774711 | PMC6367776 | pmc | 5,484 | {
"abstract": "Background Microbial electrolysis cells (MECs) can be used for energy recovery and sludge reduction in wastewater treatment. Electric current density, which represents the rate of wastewater treatment and H 2 production, is not sufficiently high for practical applications of MECs with real wastewater. Here, a sandwiched electrode-stack design was proposed and examined in a continuous-flow MEC system for more than 100 days to demonstrate enhanced electric current generation with a large number of electrode pairs. Results The current density was boosted up to 190 A/m 3 or 1.4 A/m 2 with 10 electrode pairs stacked in an MEC fed with primary clarifier effluent from a municipal wastewater treatment plant. High organic loading rate (OLR) resulted in high electric current density. The current density increased from 40 to 190 A/m 3 when the OLR increased from 0.5–2 kg-COD/m 3 /day to 8–16 kg-COD/m 3 /day. In continuous-flow operation with two stacked MECs in series, the biochemical oxygen demand (BOD) removal was 90 ± 2% and the chemical oxygen demand (COD) removal was 75 ± 9%. In addition, the sludge production was 0.06 g-volatile suspended solids (VSS)/g-COD removed at a hydraulic retention time of only 0.63 h. The electric energy consumption was low at 0.40 kWh/kg-COD removed (0.058 kWh/m 3 -wastewater treated). Conclusions The MECs with the stacked electrode design successfully enhanced the electric current generation. The high OLR is important to maintain the high electric current. The organics were removed rapidly and the total suspended solids (TSS) and VSS were reduced substantially in the continuous-flow MEC system. Therefore, the MECs with the stacked electrode design can be used for the rapid and low-sludge treatment of domestic wastewater. Electronic supplementary material The online version of this article (10.1186/s13068-019-1368-0) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions and outlook The stacked electrode design demonstrates the excellent wastewater treatability with the minimal biosolids production and consistently low COD in the MEC effluent. Even though the demonstration was achieved in lab-scale experiments, the MEC design is readily applicable in practical applications, as the experiment was conducted with primary clarifier effluent from a local wastewater treatment plant. They demonstrated that MEC design does not need further scale-up for practical applications. Many MEC reactors with 10–20 electrode pairs can be used to receive the primary clarifier effluent in parallel just like a modulated membrane filtration system, where individual membrane modules receive feed water in parallel and operate independently one another. Without further scale-up of the MEC design, the stacked electrode MECs can be used to treat municipal wastewater with stable effluent quality and minimal biosolids’ generation.",
"discussion": "Results and discussion Rapid wastewater treatment with high electric current generation The multi-electrode MEC showed substantially enhanced electric current generation as the maximum current density was 190 A/m 3 or 1.4 A/m 2 in MEC-10 (MEC of 10 electrode pairs) with continuously fed real wastewater (Fig. 1 ). The maximum current density in MEC-1 (MEC of 1 electrode pair) was only ~ 4 A/m 3 or 0.2 A/m 2 , which was much smaller than that in MEC-10. This result indicates that a large number of electrode pairs in the sandwiched design can significantly enhance the rate of wastewater treatment using MECs without any precious metal catalysts on the cathode, such as platinum. The current density in MEC-5 (MEC of 5 electrode pairs) was sensitively affected by the flow rate of wastewater and varied in a wide range up to 92 A/m 3 or 1.2 A/m 2 (Fig. 1 ). Note that the primary clarifier effluent was fed to MEC-10 and the effluent from MEC-10 was introduced to MEC-5 during the continuous MEC operation. The low current density at the low flow rates can be explained by low organic substrate concentration in the effluent from MEC-10. For instance, the measured COD concentration in the MEC-10 effluent (i.e., influent to MEC-5) was 10.4 mg/L, while it was 10.0 mg/L in the MEC-5 effluent at 0.2 mL/min. This negligible COD removal in MEC-5 indicates that the wastewater was sufficiently treated in MEC-10, and thus, MEC-5 did not generate high electric current for 0.2 mL/min (and 0.1 mL/min) due to the low COD concentration. In the previous MEC studies conducted with municipal wastewater, the reported electric current density ranging from 11 to 42 A/m 3 [ 15 – 17 ] is much lower than the current density result in this study. This comparison confirms that the stacked electrode design allowed sufficiently high current generation with primary clarifier effluent. The high current generation can be explained by the significantly high anode surface area (136 m 2 /m 3 for MEC-10,77 m 2 /m 3 for MEC-5), enhancing the rate of the electrode reactions in the small MEC reactors. Fig. 1 Electric current generation in the continuous-flow MEC system fed with primary clarifier effluent It should be emphasized that the mean hydraulic residence time (HRT) in the MEC system was 0.63 h at 2 mL/min. Considering the typical residence time of 6–8 h in aeration tanks of conventional activated sludge systems [ 1 , 2 ], the new MEC stack design can reduce the size of wastewater treatment reactors to approximately 10% of typical aeration tanks in conventional activated sludge for municipal wastewater treatment. Organic loading rate and electric current The current density was governed by the organic loading rate (OLR) rather than the COD concentration as the high OLR resulted in high electric current density (Fig. 2 a). However, the electric current density was not clearly correlated with the COD concentration (Fig. 2 b). This finding is consistent with the previous report that the magnitude of electric current is governed by the OLR rather than other operation factors, such as substrate concentration and conductivity, especially when real wastewater is used as the feed for MEC operation [ 28 ]. Even with significant variations in the influent COD concentration, the OLR was governed by the flow rate, because the influent COD was below 200 mg/L (Fig. 3 ). For the slow flow rates (0.1 and 0.2 mL/min), the OLR was smaller than 2 kg-COD/m 3 /day (0.4–0.5 kg-COD/m 3 /day at 0.1 mL/min and 0.7–1.8 kg-COD/m 3 /day at 0.2 mL/min), resulting in low current densities below 40 A/m 3 (Fig. 2 a). In addition, there was no significant increase in the current densities when the flow rate increased from 0.1 to 0.2 mL/min. However, for the high flow rate of 2 mL/min, the current density increased up to 190 A/m 3 with the relatively high OLR between 8 and 16 kg-COD/m 3 /day (Fig. 2 a). The OLR for the high flow rate was much greater than the typical OLR in conventional activated sludge systems (usually smaller than 2 kg-COD/m 3 /day) [ 2 , 29 ], indicating that the stacked MEC design can treat clarified domestic wastewater more efficiently than conventional activated sludge systems. The relatively short hydraulic residence time in MEC-10 (0.33 h at 2.0 mL/min) did not negatively affect the electric current generation in MEC-10. This finding indicates that exoelectrogenic bacteria can rapidly utilize organic substrates in municipal wastewater, allowing very short hydraulic retention time (i.e., 0.33 h) and thus small MEC reactors for wastewater treatment. Fig. 2 Electric current density in MEC-10 vs. a organic loading rate; b COD \n Fig. 3 COD concentration of the influent and effluent \n It should be noted that a gradual decrease was observed in the electric current of MEC-10 and MEC-5 between 83 and 93 days (Fig. 1 ). This result can be explained by decreased OLR for the MEC operation. From 83 to 93 days, the OLR decreased from 15.4 to 6.6 kg-COD/m 3 /day when the COD concentration of the influent decreased from 214 to 92 mg/L simultaneously (Fig. 3 ). Wastewater treatability on organic removal The rate of organic removal was rapid since 75 ± 9% of COD was removed in MEC-10 and MEC-5 for 2 mL/min or the hydraulic residence time (HRT) of 0.63 h. The COD removal was similar or slightly lower at 64 ± 15% and 59 ± 11% for the longer HRT conditions of 12.5 h (0.1 mL/min) and 6.3 h (0.2 mL/min), respectively (Fig. 4 a). The average current density was 106.4 A/m 3 (MEC-10) and 35.0 A/m 3 (MEC-5) at 2 mL/min, while it was around 23 A/m 3 (MEC-10) and 3 A/m 3 (MEC-5) at low flow rates (0.1 mL/min and 0.2 mL/min) (Fig. 1 ). The electric current in MECs represents the rate of the electrode reactions, which are the organic removal at the anode and hydrogen production at the cathode. Therefore, the higher electric current density contributes to the faster organic removal. In conventional activated sludge systems, the typical HRT in the aeration tank is 6 to 8 h with approximate 80% COD removal [ 2 ]. Considering the rapid COD removal of the examined MEC system (75% COD removal in 0.63 h), the stacked MEC design can be used for effective treatment of municipal wastewater. The BOD removal was high at 90 ± 2% with the effluent BOD of 19.4 ± 4.1 mg/L at 2 mL/min. Note that, for real wastewater without its chemical composition, the BOD-based removal efficiency provides more reliable organic removal treatability for biological wastewater treatment [ 1 ]. Fig. 4 Wastewater treatability of the MEC system: a COD removal; b TSS and VSS removal Wastewater treatability on biosolids reduction TSS (total suspended solids) and VSS (volatile suspended solids) were reduced substantially in the continuous-flow MEC system. Nearly, complete reduction of biosolids (> 94%) for both VSS and TSS was observed regardless of the flow rate conditions (Fig. 4 b). This observed biosolids removal was much higher than 60% of TSS removal reported in single chamber MEC reactors (250 mL) that were fed with domestic wastewater and the MECs were built with only 1 electrode pair [ 27 ]. This comparison indicates that the stacked electrode design is beneficial to minimizing sludge generation. The apparent yield coefficient measured in this study ranged from 0.01 to 0.06 g-VSS/g-COD, which is an order of magnitude smaller than the yield coefficient of the other anaerobic microorganisms (typical 0.1–0.6 g-VSS/g-COD) [ 1 , 30 , 31 ]. In this study, the concentration of biosolids in the effluent was 3.67 ± 1.25 mg-TSS/L or 2.02 ± 1.21 mg-VSS/L at 0.1 mL/min, 2.02 ± 1.21 mg-TSS/L or 1.60 ± 0.90 mg-VSS/L at 0.2 mL/min, and 10.36 ± 8.06 mg-TSS/L or 6.4 ± 2.76 mg-VSS/L at 2 mL/min (Fig. 4 b). These consistently low VSS and TSS concentrations imply that the MEC effluent can be discharged even without secondary clarification. In addition, the enhanced reduction of biosolids clearly indicates that MECs can dramatically reduce the sludge production in wastewater treatment as well as the cost for sludge treatment and disposal. Coulombic efficiency and energy consumption Coulombic efficiency (CE) varied in a wide range (Fig. 5 ). The wide variation of CE can be explained by the use of real wastewater, where its composition, especially the readily biodegradable portion of COD, changes continuously. A certain degree of variations in CE has been commonly found in the previous studies, where the primary clarifier effluent from wastewater treatment plants was fed in bioelectrochemical systems [ 15 , 16 , 32 ]. The CE was 66 ± 27% at 0.1 mL/min, while it dropped to 22 ± 14% at 0.2 mL/min and 20 ± 11% at 2 mL/min (Fig. 5 ). A significant decrease was shown in CE when the flow rate increased from 0.1 to 0.2 mL/min. The significant decrease was due to the increase in ∆COD (Fig. 4 a) and the similar electric current generation at 0.2 mL/min. The CE value was much lower than the CE of our previous study (> 72%), where the reactor was fed with synthetic wastewater [ 21 ]. The low CE results indicate that other biological reactions in the MEC reactors can affect CE. When the MEC reactors were disassembled, thick biofilms were found both on the anode and cathode (Additional file 1 : Figure S1), indicating that there was a substantial amount of microorganisms in the system. The observed biomass on the electrodes did not affect the sludge production during the MEC operation, because the sludge production was consistently low over the course of 3-month operation. The presence of other terminal electron acceptors such as ferric iron and sulfate can contribute to the COD removal without electric current generation in MECs [ 16 ]. In the ICP-OES (inductive coupled plasma-optical emission spectrometry) analysis, the dissolved iron was detected in the feed wastewater, because the local wastewater treatment plant applied ferric sulfate in the preliminary treatment for phosphorus removal. Note that many of the known exoelectrogenic bacteria ( Geobacter and Shewanella spp.) can utilize iron as the terminal electron acceptor [ 33 , 34 ]. In addition, other iron-reducing bacteria are commonly found in domestic sewer systems [ 34 ]. However, the concentration of iron in the influent and effluent decreased from 1.45 to 0.19 mg/L, which only results in the 0.54 mg/L COD removal. Thus, the effects of iron ions were negligible. Sulfate can also contribute to additional COD removal without electric current generation by sulfate reducing bacteria [ 35 ]. Sulfate concentration in the wastewater was consistently high at 82–122 mg/L [ 36 ], which can potentially oxidize up to 81 mg/L of COD assuming H 2 S production. In addition, the methane production in MEC can also result in the low CE. Fig. 5 Coulombic efficiency during the continuous-flow MEC system operation \n The electric energy consumption was as low as 0.40 kWh/kg-COD removed or 0.058 kWh/m 3 wastewater treated (Additional file 2 : Figure S2). The low energy consumption for the MEC operation can be explained by the stacked electrode design with the reduced inter-electrode distance (2.8 mm) and significantly magnified electrode surface area with a total of 15 electrode pairs sandwiched in the small reactors. The short inter-electrode distance contributed to the low inter resistance (229.5 Ω cm 2 based on 1.22 mS/cm and 2.8 mm) and thus resulted in the low-voltage drop between the electrodes (3 to 18 mV). Compared to the energy consumption of conventional activated sludge systems which typically ranged from 0.7 to 2 kWh/kg-COD removed [ 2 ], the energy consumption for MEC operation was much lower. In conclusion, the stacked multi-electrode MECs can replace the activated sludge system because of the great treatability of primary clarifier effluent and low energy consumption. Note that the energy recovered, as H 2 gas production was not included in the energy requirement calculation, because biogas production, including H 2 gas, was very small. The small biogas production can be explained by short hydraulic residence time in the MEC reactor (37.5 min at 2 mL/min). For the short residence time, tiny H 2 gas bubbles from the cathode were flowing with the wastewater rather than separated by gravity in the MEC reactors. In addition, H 2 gas is rapidly converted into CH 4 in MECs without proper inhibition of hydrogenotrophic methanogens. According to the Henry’s law constant (769 atm/M) [ 37 ], the examined highest flow rate can carry more methane (606 mg CH 4 /day) than the maximum amount of methane that can be produced in the MEC (155 mg CH 4 /day; 100% conversion of H 2 into CH 4 ; 100% H 2 production from electric current). Individual electrode performance During the continuous-flow operation, the wastewater flowed through 10 independent electrode pairs serially in MEC-10 and then 5 electrode pairs in MEC-5. The electric current generation was similar among the multiple electrode pairs (Table 1 ), and this result was not consistent with our recent study with synthetic wastewater that is considered to have resulted in a significant variation in the electric current generation among the electrode pairs [ 21 ]. The different performances of the reactor with real wastewater and synthetic wastewater were due to the low readily biodegradable organics concentration of real wastewater. The slow conversion of biodegradable organics to readily biodegradable organics in the reactor contributes to the stable electric current results. In addition, the consistent electric current results indicate that the operation of the MEC stack was reliable even though a single reactor was operated. The location of individual electrode pairs did not affect the current generation except for the first pair from the inlet (electrode pair #1). For instance, there was no significant variation in the electric current for electrode pairs #2 through #10 in MEC-10 (Table 1 ). However, electrode pair #1 generated noticeably lower electric current compared to the other electrode pairs only at the high flow rate of 2 mL/min (Table 1 ). Table 1 Average electric current (mA) for each electrode pair in MEC-10 Electrode pair 0.1 mL/min 0.2 mL/min 2.0 mL/min #1 0.11 ± 0.09 0.08 ± 0.03 0.15 ± 0.08 #2 0.14 ± 0.05 0.09 ± 0.05 0.53 ± 0.19 #3 0.12 ± 0.05 0.10 ± 0.06 0.50 ± 0.15 #4 0.08 ± 0.03 0.10 ± 0.04 0.54 ± 0.17 #5 0.08 ± 0.03 0.09 ± 0.04 0.54 ± 0.18 #6 0.08 ± 0.03 0.09 ± 0.05 0.55 ± 0.20 #7 0.08 ± 0.03 0.11 ± 0.04 0.56 ± 0.20 #8 0.08 ± 0.03 0.09 ± 0.04 0.47 ± 0.17 #9 0.07 ± 0.02 0.09 ± 0.04 0.49 ± 0.18 #10 0.07 ± 0.03 0.08 ± 0.04 0.53 ± 0.22 \n Conclusions and outlook The stacked electrode design demonstrates the excellent wastewater treatability with the minimal biosolids production and consistently low COD in the MEC effluent. Even though the demonstration was achieved in lab-scale experiments, the MEC design is readily applicable in practical applications, as the experiment was conducted with primary clarifier effluent from a local wastewater treatment plant. They demonstrated that MEC design does not need further scale-up for practical applications. Many MEC reactors with 10–20 electrode pairs can be used to receive the primary clarifier effluent in parallel just like a modulated membrane filtration system, where individual membrane modules receive feed water in parallel and operate independently one another. Without further scale-up of the MEC design, the stacked electrode MECs can be used to treat municipal wastewater with stable effluent quality and minimal biosolids’ generation."
} | 4,624 |
35362106 | PMC9324912 | pmc | 5,485 | {
"abstract": "Abstract Seed inoculation with beneficial microorganisms has gained importance as it has been proven to show biostimulant activity in plants, especially in terms of abiotic/biotic stress tolerance and plant growth promotion, representing a sustainable way to ensure yield stability under low input sustainable agriculture. Nevertheless, limited knowledge is available concerning the molecular and physiological processes underlying the root‐inoculant symbiosis or plant response at the root system level. Our work aimed to integrate the interrelationship between agronomic traits, rhizosphere microbial population and metabolic processes in roots, following seed treatment with either arbuscular mycorrhizal fungi (AMF) or Plant Growth‐Promoting Rhizobacteria (PGPR). To this aim, maize was grown under open field conditions with either optimal or reduced nitrogen availability. Both seed treatments increased nitrogen uptake efficiency under reduced nitrogen supply revealed some microbial community changes among treatments at root microbiome level and limited yield increases, while significant changes could be observed at metabolome level. Amino acid, lipid, flavone, lignan, and phenylpropanoid concentrations were mostly modulated. Integrative analysis of multi‐omics datasets (Multiple Co‐Inertia Analysis) highlighted a strong correlation between the metagenomics and the untargeted metabolomics datasets, suggesting a coordinate modulation of root physiological traits.",
"conclusion": "6 CONCLUSIONS Improved yields are required to meet the food demand of an increasing population. Until now, this need has been highly dependent on chemical inputs, and more sustainable approaches are needed. In this framework, beneficial microorganisms are gaining popularity because of the multiple effects they may play several functional roles in plants. Here we show that both the fungal and the PGPR seed treatments were able to increase nitrogen uptake efficiency under low nitrogen availability without compromising yields. This point is of paramount practical importance since it indicates that these biostimulants may support agricultural production in a sustainable manner, under a reduced input farming perspective. Both the biostimulant treatments induced a coordinate modulation of root metabolome and rhizomicrobiome, although with differences between mycorrhiza and PGPR treatments. Nonetheless, such coordinate modulation could be observed several weeks after seeding, supporting the involvement of the biostimulants in the improved maize performance we observed. The effects observed involved the positive modulation of several beneficial rhizosphere microorganisms, possibly involving indirect effects mediated by root exudation patterns. This latter point is of relevance and deserves further ad hoc investigation.",
"introduction": "1 INTRODUCTION The world population is predicted to reach 9.7 billion by 2050 (DeSa, 2015 ) and, consequently, global demand for food and other agricultural products is expected to rise by 50% (FAO, 2017 ), thus requiring a marked increase in agricultural productivity. Cereal production in the world is projected to reach 3054 Mt in 2029, and maize yield is expected to increase the most (+193 Mt) (OECD/FAO, 2021 ). Maize represents the second most important cereal globally in terms of acreage and the first one for production, predominantly cultivated in the USA and used to feed livestock and humans, in addition to bioethanol (FAOSTAT, 2019 ). Agriculture worldwide will need to increase its yields to meet the growing demand also for maize‐based products (OECD/FAO, 2021 ). With this regard, intensive cropping systems will require sustainable approaches to avoid the negative externalities normally linked to the over‐use of chemical inputs, such as biodiversity loss and water/soil degradation (Panfili et al., 2019 ). In this framework, the use of plant biostimulants in agriculture, recently normed by the Regulation (EU) 2019/1009, may represent a sustainable tool to ensure yield stability under low input sustainable agriculture. Recently, positive advances have been found for plant microbial biostimulant application, reflecting advantageous implications for many agronomic and physiological crop traits (Guerrieri et al., 2020 ; Guerrieri et al., 2021 ; Rouphael et al., 2020 ). The most promising microbial biostimulants include arbuscular mycorrhizal fungi (AMF), Trichoderma spp., and plant growth‐promoting rhizobacteria (PGPR) such as Azotobacter ssp., Rhizobium ssp. and Azospirillum ssp. The inoculation of beneficial microorganisms has gained remarkable importance, having been proven to show a biostimulant activity in plants, especially in terms of abiotic/biotic stress alleviation (Sangiorgio et al., 2020 ), growth promotion (Nacoon et al., 2020 ), and improvement of food functional quality (Ganugi et al., 2021a , 2021b ). The putative mechanisms of biostimulation include the provision of enzymatic activities and/or release of small molecules and peptides (in turn affecting nutrients uptake), the release of antimicrobials or quorum‐sensing compounds, and the modulation of plant root architecture (Fiorentino et al., 2018 ; Lucini et al., 2019 ; Raaijmakers & Mazzola, 2012 ; Saia et al., 2020 ). Despite the consensus on their effects, limited knowledge is available to date concerning the molecular and physiological processes underlying plant‐inoculants symbiosis or regarding plant response at root system level under field conditions. The latter information is relevant given the pivotal role played by roots in coping with drought, nutrient deficiencies, toxicants, and soil compaction (Ryan et al., 2016 ). Notwithstanding, the plant dependence on its microbiota across all development stages is also known, with several microbial strains thriving in the rhizosphere that can affect plant health and productivity, as well as resistance to both abiotic and biotic stresses (Colla et al., 2017 ). The interrelationships between root agronomic traits, microbiota and metabolites remain largely unstudied, and the assessment of the metabolomic changes in roots is necessary to fully understand the tripartite interaction between roots, soil and microorganisms underlying the biostimulant activity (Rouphael et al., 2020 ). The lack of information about the interplay mechanisms between roots and beneficial microorganisms can be related to the complex and dynamic processes involved. However, the recent development of new tools, including the integration of multiple omics datasets, has paved the way for a deeper understanding of plant‐microbe interactions. Multivariate approaches such as Multiple Co‐inertia Analysis (MCIA) have been proposed to identify co‐relationships between multiple high dimensional datasets, based on a covariance optimization criterion (Min & Long, 2020 ). Nevertheless, despite the advances in this field, this approach remained limited to human and food studies (Afshari et al., 2020 ; Meng et al., 2014 ). The present study aims at integrating root metabolomics and rhizosphere metagenomics to investigate the interrelationships between agronomic traits, rhizosphere bacterial community and root metabolic processes in maize, following seed treatment with either AMF or PGPR. To this object, MCIA has been used for data integration, combining agronomic trait data, metagenomics analysis, and untargeted metabolomics analyses.",
"discussion": "5 DISCUSSION Bacterial and mycorrhizal biostimulants are known to hold the potential to improve agronomical and physiological traits in crops, especially under stress conditions (Rouphael & Colla, 2020 ). The present study indicated that using the tested bio‐stimulants did not impair the rhizosphere soil bacteria biodiversity in treated plants. This can be attributed to the fact that the microbial treatments accounted for a small portion of the microbial diversity in the rhizo‐microbiome (Nuzzo et al., 2020 ). Nonetheless, it must also be considered that the changes in the microbiome are the consequence of centuries of coevolution and that plants actively seek microbial interactions (Durán et al., 2018 ; Kwak et al., 2018 ). On the other hand, the selection of a functionally positive community at the rhizosphere level can improve plant fitness (Liu et al., 2020 ), a process that typically involves root exudation processes (Carvalhais et al., 2015 ). Indeed, it has been proposed that plant crop species and nutrients were the main drivers of change (Armada et al., 2018 ). In light of these considerations, it is not surprising that our results highlighted moderate differences in root microbiome under the different treatments. Regarding the non‐significant impact of 30% less N fertilization on soil rhizomicrobiome, our results are in accordance with Maris et al., 2021 . The complex dialog between plants and rhizomicrobiome generally paves the way for the active recruitment of specific microorganisms providing benefits to plants, a process that may induce changes in rhizosphere microbial biodiversity (Bandyopadhyay et al., 2017 ). In turn, plant pattern‐recognition receptors (PRRs) at the plasma membrane level are activated by root‐microbe interaction in the rhizosphere and can trigger intracellular processes at the root level (Teixeira et al., 2019 ). Microbe‐associated molecular patterns (MAMPs) are among the most studied molecular processes being elicited in plants following host‐microbiota interaction(s), mostly in the framework of induced systemic resistance or, more generally, plant defense (Pieterse et al., 2014 ). However, plant response to microbial colonization has been proposed to be much wider than defense mechanisms, including direct and indirect effects related to the promotion of plant growth and fitness and tolerance to abiotic stresses (Kumar et al., 2018 ; Oleńska et al., 2020 ). This agrees with our findings, where a broad metabolic reprogramming was observed, with secondary metabolite biosynthesis affected by T2 and T3 treatments. Although limited, the impact of metabolic reprogramming was visible through trends observed in the reprogramming of the microbial communities at soil rhizomicrobiome, hinting at previously cited interlinkages between rhizomicrobiome and metabolites. Statistically insignificant differences at the alpha diversity level were contrasted with the changes in whole community ecology, especially on the community composition level. However, the limited differences in rhizosphere biodiversity between treatments can be attributed to the occurrence of the above‐mentioned interactions directly between plants and specific microorganisms (possibly including microbial dressing treatments), instead of the whole bacterial community of the rhizosphere, in accordance with Dal Cortivo et al., ( 2020 ). Surprisingly, the metabolomics signatures of maize roots differed as a function of the treatment, even though 79 days passed from seed dressing to root sampling and despite trials being carried out in open fields with non‐sterilized agricultural soil. This indicates that the treatments could modify root biochemical processes in a rather persistent manner. The ability of the root microbiome to affect root morphology (Bardgett et al., 2014 ; Pervaiz et al., 2020 ) and exudation patterns (Iannucci et al., 2021 ; Zuluaga et al., 2021 ) (and vice versa) corroborates our findings, where a broad reprogramming of metabolic processes could be observed in maize plant roots. Despite some positive trends could be observed, such modulation was translated into only a limited yield increase, irrespective of the nitrogen availability level. Dal Cortivo et al., ( 2020 ) found similar results, with small grain yield increases (1–4%) when either microbial or fungal consortia were applied to wheat seeds. Nevertheless, it can be interestingly observed that the treatments induced significant changes at the functional level and that root metabolome and rhizosphere population were highly correlated. With this regard, a correlation of 0.84 (as provided by MCIA) under field conditions is indicative of a rather strong link between the two omic profiles. This coordinate modulation of root physiological traits was not translated into yield increase, probably because the concentration of nutrients into the soil was per se relatively high even when the 30% decrease of N‐fertilizer was applied or because root performance was increased following our biostimulant treatments. Nevertheless, our results showed that (1) both biostimulants had higher NUpE with 70% N‐fertilization level, and (2) B. megaterium PGPR led to increased maize root biomass, mostly due to an increase of root development on the crop row. Given these findings and the well‐recognized biostimulant effect of the treatments applied, we can postulate that either more severe nitrogen starvation status or other abiotic stresses such as drought and/or low nutrients (other than N) concentrations and/or high temperatures might have helped in highlighting the beneficial effects of the treatments considered. Notwithstanding, plant response to seed treatment persisted at anthesis, thus paving the way towards a set of beneficial aspects in maize production that go far beyond the direct effects of exogenously applied biostimulant microorganisms. Plant beneficial rhizospheric microorganisms are known to increase nutrient use efficiency (Meena et al., 2017 ). However, we observed the possible mechanisms underlying the coordinate modulation of root metabolome and rhizomicrobiome. It would be aleatory to identify a main player between plants and microorganisms, and the intricate series of interactions occurring at the rhizosphere should be considered instead. In fact, from one side, plant root exudates include chemotaxis compounds and are known to shape the microbial community (Pérez‐Jaramillo et al., 2016 ; van Dam & Bouwmeester, 2016 ), but it is also important to consider that microorganisms produce signaling compounds that are perceived by roots (Mendes et al., 2014 ; Zancarini et al., 2013 ). Together with the exchange of chemical messengers or functional metabolites, the microorganisms perceived by roots are also able to interact with root receptors directly (Poole, 2017 ), thus eliciting specific biochemical responses in the plant cells, and some symbionts are even endophytes. The elucidation of such intricate agroecological crosstalk is very complicated because of technical limitations in sampling and analysis (Escolà Casas & Matamoros, 2021 ) and the need to track temporal and spatial dynamics (van Dam & Bouwmeester, 2016 ). However, it can be noted that under our experimental conditions, the microbial species showing the higher correlation to root metabolome (provided in Table S4 ) are well‐known beneficial rhizobacteria. In particular, Actinobacteria (such as Gemmatimonas , Gaiella , and Solilubrobacter spp.), and some Acidobacteria and Chloroflexi spp. have been reported to provide positive functions at the rhizosphere level, particularly under stress conditions (Akinola et al., 2021 ; Khan et al., 2020 ; Lazcano et al., 2021 ; Yue et al., 2020 ). In particular, some Acidobacteria have been reported to possess the genetic capability to support nitrate, nitrite and nitric oxide reduction and to release serine endopeptidases, hence having the potential to improve nitrogen uptake (Kalam et al., 2020 ). Chloroflexi spp. are beneficial PGPR that have been linked to plant root growth promotion. Similarly, Actinobacteria can promote plant growth under adverse conditions and contribute to fixing atmospheric nitrogen (Yadav et al., 2018 ; Yue et al., 2020 ) and are reported to be increased by AMF (Agnolucci et al., 2019 ). Noteworthy, Gemmatimonadetes and Gaiella spp. play a key role in plant abiotic stress (Khan et al., 2020 ; Yue et al., 2020 ), and both have been specifically linked to the level of N‐nitrate levels in maize (Akinola et al., 2021 ). Among the root metabolites showing the strongest correlation with rhizomicrobiota, flavonoids (sakuranetin and 2′,4,4′,6′‐tetrahydroxychalcone) and isoflavonoids (vestitone and 7,2,4,2′‐tetrahydroxy‐4′,5′‐methylenedioxyisoflav‐3‐ene) were the most represented, followed by the hydroxycinnamic phenolic cinnamoyl‐beta‐D‐glucoside, and the phenolic glycoside salicin. Among non‐phenolics, lipids (a diacylglycerol, a decaprenylbenzoate ubiquinol intermediate and 3‐oxoicosatetraenoyl‐CoA), D‐glucono‐1,5‐lactone, phlormethylbutanophenone (a 2‐acylphloroglucinol) and amino acids intermediates could be found. Plant roots may exudate up to 20% of their photosynthate, in the attempt of shaping the root microbiome (Poole, 2017 ). The molecular processes involved in this chemotaxis are largely unknown, even though literature agrees that root exudation patterns are paramount in the tripartite soil–root–microbiome interaction. Despite no specific pathways for root exudation have been identified to date, our results indicate that the root microbiome may represent an upstream process in the modulation of root exudation. This coordinate modulation of rhizomicrobiome and root metabolomic signature, linked to higher NUpE with reduced N‐fertilization level, implies that biostimulants could be particularly suitable in less suited soils, in arid and semi‐arid regions, with poor soil quality, and where N‐fertilization is a limiting factor (e.g., organic farming). However, since in many temperate areas across the world, the climate is changing rapidly (Zhongming et al., 2021 ) and the European Commission (EU) recently set ambitious goals for reducing fertilizer use significantly at the field level (Schebesta et al., 2020 ), using effective tools to mitigate yield losses by increase nutrient use efficiency will become more important in a greater proportion of arable land across the world."
} | 4,485 |
40268300 | PMC12018069 | pmc | 5,486 | {
"abstract": "ABSTRACT Microbial communities are often complex and highly diverse, typically with dozens of species sharing spatially‐restricted environments. Within these species, genetic and ecological variation often exists at a much finer scale, with closely related strains coexisting and competing. While the coexistence of strains in communities has been heavily explored over the past two decades, we have no self‐consistent theory of how this diversity is maintained. This question challenges our conventional understanding of ecological coexistence, typically framed around species with clear phenotypic and ecological differences. In this review, we synthesise plausible mechanisms underlying strain‐level diversity (termed microdiversity), focusing on niche‐based mechanisms such as nutrient competition, neutral mechanisms such as migration, and evolutionary mechanisms such as horizontal gene transfer. We critically assess the strengths and caveats of these mechanisms, acknowledging key gaps that persist in linking genetic similarity to ecological divergence. Finally, we highlight how the origin and maintenance of microdiversity could pose a major challenge to conventional ecological thinking. We articulate a call‐to‐arms for a dialogue between well‐designed experiments and new theoretical frameworks to address this grand conceptual challenge in understanding microbial biodiversity.",
"conclusion": "5 Conclusion How and why different types of organisms coexist in a shared ecosystem has long been a central question in ecology. There are varied mechanisms by which biodiversity is maintained across taxonomic levels, many of which rely on the occupation of different niches. However, these mechanisms begin to break down when we probe the microbial world, where there is abundant, temporally stable diversity even at the level of individual strains with marginal genetic diversity. Here, we have highlighted some ideas for how closely related strains could coexist via niche‐based mechanisms (metabolic diversity, physiological trade‐offs, anti‐symmetric interactions, and spatiotemporal dynamics), neutral mechanisms (migration and stochasticity) and evolutionary mechanisms (mutation and HGT). We stress that these mechanisms should be considered proposals which are lacking concrete demonstration for strain‐level coexistence in natural or laboratory communities. Experimentally demonstrating these mechanisms as forces behind the coexistence of closely related strains is absolutely critical. Moreover, these mechanisms should be considered collectively to explain coexistence—anyone in isolation is likely insufficient to quantitatively match observation. Doing so opens a variety of fascinating questions: How important are dynamics versus steady states for coexistence? Can communities with population fluctuations due to time‐varying environments or strong community interactions promote strain coexistence when averaged over time? What are the rates of HGT and generation of microdiversity in natural microbial communities, and how do they balance the rates at which diversity is lost? Are there robust generic mechanisms that can make closely related strains effectively neutral? If so, how can they be tested? Answering these questions not only demands novel theory and experiments; it demands their dialogue. At a theoretical level, we must have a pragmatic view of what encompasses coexistence in natural ecosystems, delineating between the ‘hard’ mathematical definition and the ‘soft’ definition which is applicable to realistic conditions. This applies to all ecological subjects—from forests to grasslands to tide pools—but is even more relevant for the microbial world where physiological differences are often small and generation times are short. At a theoretical level, coexistence can be defined as the continual presence of at least two distinguishable organisms across an infinite time span. While mathematically rigorous, this is hardly applicable to reality. For example, say there exists an ecosystem where two strains compete with a vanishingly small, but non‐zero, fitness difference between them. While it may take longer than the age of the universe for one species to outcompete the other (i.e., failing the ‘hard’ definition), we can say that the two strains effectively coexist, at least over the ecologically and evolutionary relevant time scales (i.e., satisfying the ‘soft’ definition) (Louca and Doebeli 2016 ; Martiny et al. 2023 ). Unlike ‘hard’ coexistence, there is no one definition for ‘soft’ coexistence, and the relevant temporal regimes will be highly contextual to the particular ecosystem of study, encompassing the timescales of both the environmental fluctuations and the tempo of evolution in the community. Finding this definition therefore requires a holistic knowledge of the various relevant timescales, knowledge that can only come from direct measurement. On the experimental side, we need targeted observations of strain dynamics at higher temporal and genetic resolution. While current metagenomic snapshots have revealed tremendous diversity, several key experiments could quantitatively test predictions about these coexistence mechanisms. First, introducing known strains (with known or engineered phenotypes) into natural or synthetic communities as ‘tracer particles’ may reveal the relative strength of neutral versus competitive mechanisms in maintaining microdiversity. Doing so may allow us to infer ecological dynamics within specific microbial demographics without requiring high‐cost deep metagenomic sequencing. Second, deep metagenomic long‐read sequencing of natural communities over time would enable estimation of distributions of strain interactions, testing whether observed interactions are more stabilising than predicted by random community assembly. Third, systematic measurements of physiological parameters across strains—including growth rates, half‐saturation constants and yield coefficients—coupled with modern genomic sequencing methods would allow direct comparison with the diversity bounds predicted by resource competition theory. Importantly, this will permit us to construct meaningful maps between genotype and metabolic phenotype, which can be integrated with measurements of environmental contexts to better understand the expected levels of strain‐level coexistence. Fourth, experiments applying controlled environmental perturbations (e.g., temperature shocks, antibiotic pressures, or nutrient fluctuations) could reveal correlations in strain abundances before and after community collapse, helping understand the intricate networks of ecological interactions between strains. Any clustering in such networks would reflect underlying competition, metabolic dependencies or cross‐feeding relationships between strains in communities. Finally, quantification of horizontal gene transfer rates in nature would significantly aid in our understanding of its ecological importance. These experimental advances, combined with theoretical developments in modelling genotype–phenotype relationships, will be essential for understanding the mechanisms enabling the remarkable strain‐level diversity observed in microbial communities.",
"introduction": "1 Introduction Natural ecosystems are remarkably complex, often encompassing organisms spanning the tree of life that directly and indirectly interact through their dynamic environments. The past century of technological and theoretical advancements have allowed us to probe the ‘invisible’ community members–the protists, microbes, and their associated viruses–revealing perplexing ecological phenomena. Studying these phenomena in natural environments has revealed a ‘paradox of the plankton’ (Hutchinson 1961 ). How do hundreds to thousands of species (Hong et al. 2006 ; Tran and Boedicker 2017 ; Hoshino et al. 2020 ; Shu and Huang 2022 ) coexist across long timescales (Goldford et al. 2018 ) despite the comparatively low diversity of available nutrients (tens to hundreds) they use to grow (Figure 1A )? Many studies have since proposed possible resolutions to this paradox (Roy and Chattopadhyay 2007 ; Record et al. 2014 ; Menden‐Deuer and Rowlett 2014 ; Flynn et al. 2022 ). Each of these proposals provide new mechanisms by which species may be able to coexist on a limited pool of nutrients, thereby providing new ecological ‘niches’ that these species can occupy in order to coexist. Although species may coexist by occupying distinct niches, it is reasonable to hypothesise that competition within species (between strains, as defined in Box 1 ) is so intense that only one strain could dominate. How, then, can strains with nearly identical genomes occupy distinct niches? FIGURE 1 Coexistence of organisms across scales. (A) Top row schematizes different levels of taxonomic resolution with hypothesized interactions between community members depicted using sharp‐ and blunted‐arrows. Bottom row diagrams temporal dynamics of community biomass composition at each taxonomic level. (B, left) Observed coexistence of strain clades in an experimental \n Escherichia coli \n community (Good et al. 2017 ) and (B, right) observed coexistence of Pseudomonas strains in a natural community from pitcher plants (Goyal et al. 2022 ). BOX 1 Candidate definitions of a ‘strain’. The taxonomic classification of life has been undeniably useful in piecing together evolutionary history. However, the genomic flexibility of microbes poses unique challenges to these classifications, often making species designations difficult. This problem is even more pronounced for microdiversity—how do we distinguish between microbes of the same species that have distinct traits and ecological behaviour, yet highly similar genomic sequences? In this work, we use the term ‘strain’ to describe such differences, but a more quantitative and concrete definition would be incredibly useful. In our view, there are several ways one could define different strains, each with benefits and caveats. Any two microbes are considered different strains if… \n … they descended from a clonal culture yet exhibit different physiological or ecological behaviours . This definition is particularly useful in ecological contexts, where functional traits determine interactions and fitness. Indeed, grouping microbes into groups with similar traits–termed ecotypes–has allowed for near‐real‐time monitoring of microbial evolution in diverse environments (Good et al. 2017 ; Chase et al. 2018 , 2021 ; Behringer et al. 2022 ). However, the practical limitations are significant as distinct traits or physiological differences are often difficult to quantify, highly context‐dependent, and are not always easily mapped onto genetic variation, which is more easily measurable. Moreover, in natural environments, we rarely have access to complete life histories, making it impossible to verify clonal descent in most (but not all (Good et al. 2017 )) cases. Finally, the stochastic nature of gene expression (Sanchez et al. 2013 ) and epigenetic regulation (Riber and Hansen 2021 ) means that genetically identical individuals can exhibit different phenotypes (e.g., spore formation (Tan and Ramamurthi 2014 ) and antibiotic susceptibility (Akiyama and Kim 2021 )). As a result, this definition, while conceptually appealing, is difficult to operationalise in nature. … a certain percentage of their DNA is identical, averaged across the entire genome . This approach, termed genome‐wide Average Nucleotide Identity (ANI), has been widely adopted for delineating microbial species (< 90% identity) and has been proposed for defining strains at > 99.5% identity (Rodriguez‐R et al. 2023 ). The appeal of this definition lies in its precision and ease of measurement with modern sequencing technologies. However, the choice of a 99.5% threshold is ultimately arbitrary—why not 99.4% or 99.6%? Furthermore, it is unlikely that a single universal threshold applies across all microbial species, as genome divergence rates and recombination frequencies vary widely. This inherent subjectivity means that while ANI provides a useful operational definition, it does not necessarily capture meaningful ecological or functional differences between strains. … they have identical 16S/18S rRNA sequences but differ elsewhere in their genomes . This definition provides a simple and operationally convenient way to distinguish strains from more distantly related taxa, as rRNA sequences are widely used for broad taxonomic classification. However, it is unclear how much genomic divergence is permissible before two organisms should no longer be considered the same strain—differences could range from a single nucleotide polymorphism to substantial genomic rearrangements. \n This is by no means an exhaustive list of definitions, but regardless of which definition one adopts, the framework explored in this review can help assess and contextualise microbial diversity at the strain level. Recent advances in DNA sequencing and genome reconstruction have permitted a deeper understanding of microbial diversity, allowing us to identify and track the dynamics of individual strains within these populations. In both natural and experimental settings, we see diversity at the strain level, where multiple distinct strains not only coexist but also display unique ecological dynamics (Figure 1B ). On a genetic level, coexisting strains differ on the order of hundreds of base pair differences (or less) (Goyal et al. 2022 ; Garud and Pollard 2020 ; Garud et al. 2019 ), raising several key questions that make strain coexistence a qualitatively distinct problem from species coexistence: How can closely related strains coexist even when they are likely competing for the same nutrient sources? How do new strains emerge and compete in this environment? How do strains exhibit impressive physiological diversity when their genetic diversity is minimal? What is the structure of the genotype–phenotype maps in highly similar strains, and is it sufficient to yield the physiological diversity necessary for strains to coexist? Here, we provide a concise overview of the plausible mechanisms that allow for the maintenance of strain‐level diversity (which we refer to as ‘microdiversity’) in microbial communities, emphasising their caveats and open questions (Figures 2 and 3 ), and highlight that we lack a rigorous practical definition of what coexistence means across environmental and evolutionary contexts. We highlight both the potential explanatory power of these mechanisms and their pitfalls, while acknowledging the significant gaps in our understanding that remain. Finally, we issue an interdisciplinary call‐to‐arms for new experiments and theoretical tools to address the simple reality that, the closer we look, the more diversity and coexistence we find. FIGURE 2 Niche‐based mechanisms of strain‐level coexistence. Through schematics, we highlight the four key niche‐based mechanisms that have been suggested to contribute to strain coexistence in microbial communities. For each mechanism, we provide the major takeaway and caveat that may spur future work. FIGURE 3 Neutral and evolutionary mechanisms of strain‐level coexistence. Through schematics, we highlight the two key neutral‐based and two key evolutionary mechanisms that have been suggested to contribute to strain coexistence in microbial communities. For each mechanism, we provide a major open question, takeaway and caveat that may spur future work."
} | 3,887 |
37428910 | PMC10629567 | pmc | 5,487 | {
"abstract": "Significance Weaver ants link their bodies together to form chains over gaps and reach unexplored territories. The decision to join or leave a chain is made by individuals, but has cost implications at the colony level, as longer chains sequester more ants, which cannot perform other tasks. Furthermore, the payoff of a chain remains unknown until it is complete and the new area is explored. We demonstrate that individual ants modulate the time they spend in the chain based on their proximity to the ground and that this local behavioral rule caps the colony-level investment into chains. Our theoretical model offers insights into collective decision-making in the absence of payoff information, and could prove useful in the engineering of multiagent systems.",
"discussion": "Discussion In the current study, we used the chain-building behavior of the weaver ant O. smaragdina as a model system to investigate how animal groups make adaptive decisions under uncertainty, in particular when no information is available about payoff. We combined detailed behavioral analyses with mathematical modeling to describe the behavioral rules underlying chain formation and showed that weaver ants cap their collective investment into chains when the payoff of building is not known. In our experiments, ants consistently formed chains over vertical gaps up to 50 mm in length, but never formed complete chains when this length was increased to 110 mm. Our results are in contrast with a previous model of chain formation ( 27 , 36 ), which predicts that chains should grow indefinitely if the initial population of ants is large enough. We here propose a distance-based model for chain formation in weaver ants, which predicts the emergence of a cost–benefit tradeoff from local decisions of ants without requiring global knowledge, complex cognition, or communication among ants. Informed by our experimental analyses, our model integrates a simple behavioral rule that allows ants to modulate their leaving decisions according to their distance from a platform. We showed that this rule suffices not only to accurately reproduce chain growth within the parameter space of our experiments but also to predict the building decisions of ants when confronted with large gaps. Previous studies on O. smaragdina and its sister species O. longinoda ( 27 , 36 ) reported that the individual-level decisions of ants to join or leave a chain were dependent on the number of individuals already in it. In short, the larger the chain the higher the joining probability of ants arriving at the chain and the lower the leaving probability of ants already in it. However, these studies failed to identify the local stimuli that would allow ants to estimate chain size before joining or leaving. A candidate mechanism is that ants estimate chain size by measuring the distance walked over the chain before joining. Both our current results ( Fig. 2 A ) and previous reports ( 27 ) showed that ants tend to walk down the entire length of the chain before joining, suggesting that ants may be using the length walked as a cue to join chains. Our results, however, showed no impact of chain length on the probability of joining the chain or on the latency to do so. In contrast, we found that the probability of observing an ant joining a chain was independent of the instantaneous conditions of the structure and/or traffic flow. It is, however, unlikely that ants that are already in the chain can assess chain size using local cues. Our experimental analyses revealed that ants tune their leaving decisions according to their distance from the platform, remaining longer in chains when closer to it. It is important to note here that our analyses were restricted to the leaving dynamics at the tip of the chain. Leaving events in other regions of the chain are rare ( Fig. 2 B ), suggesting the existence of a behavioral rule that prevents ants from leaving their positions if other individuals are hanging from them. Anderson et al. ( 28 ) suggested that ants participating in a chain should join and leave only at its extremity because individuals in the middle may be constrained in the structure and unable to leave. Studies on Eciton army ants’ bridges demonstrated that the probability of an ant to leave its position decreases with the number of neighboring individuals and that the traffic passing over the ant further increases its probability to remain motionless ( 50 ). Our behavioral analyses revealed that weaver ants are more likely to remain in chains when the traffic flow arriving at the chain’s tip is high, suggesting that a similar behavioral mechanism may be at play here. This mechanism may also be mediated by the load sustained by ants while in the chain, but further studies are necessary to confirm this hypothesis. A major assumption of the model is that ants are able to perceive and estimate their distance from the platform. Previous research demonstrated that the presence of visual stimuli is necessary for the initiation of chain formation and that chains are never formed when no stimulus is present ( 25 , 27 , 43 ). It is possible therefore that our results could be explained by perceptual constraints, specifically an inability to detect the platform from a distance. This is unlikely, however, as we observed chain initiation in all our experimental conditions and even when the distance from the target was set at 110 mm. O. smaragdina major workers are visual predators and navigators with highly developed eyes that are well-tuned for diurnal light conditions ( 43 , 44 , 51 – 53 ). Although no comprehensive study on the visual capabilities of O. smaragdina workers exists, comparisons of O. smaragdina eye anatomy with that of other ants ( 52 – 54 ) suggest that weaver ants should easily detect the platform stimulus in all of our experimental conditions. Our results also show that ants were more likely to lengthen a chain with their bodies when closer to the platform and that the probability of observing “reaching” behavior also increased with the proximity to the target. Taken together, these results indicate that the modulation of chain building is driven by “voluntary” individual-level decisions of ants rather than by perceptual limitations. Our model also ignores the effect of traffic flow and directionality on the behavior of ants in the chain. This decision is motivated by the relatively small impact of these factors on the leaving decisions of ants ( Fig. 2 D ), and by our effort to maintain model simplicity. Responsiveness to traffic information has been shown to underlie the stability and adaptiveness of the structures built by Eciton army ants ( 35 , 46 , 50 ) and Solenopsis fire ants ( 32 , 55 , 56 ). In these ant genera, individuals within structures use the tactile cues provided by nestmates walking over them to modulate their behavior. Our experimental results suggest that weaver ants may use a similar mechanism during chain formation. Traffic flow descending chains may promote chain stability by keeping ants within the structure motionless during extended foraging periods. On the other hand, ants walking up the chain may signal the presence of danger at the far end of the structure and trigger ants within the structure to leave their position. This may explain the rapid disassembly of chains when a visual stimulus is removed from below the structure ( 27 ). Investigating the impact of traffic cues on chain formation may provide useful insights for comparing the mechanisms governing self-assembly structures in diverse ant genera and shed further light on the local stimuli that regulate decision-making at the individual level. Similar to observations of individual animals ( 1 , 6 , 8 , 9 , 40 , 41 ), O. smaragdina colonies modulate their investment into tasks with unknown payoff. The collective decision of building a chain emerges from the individual-level budgeting decisions of ants already in the chain, without the need to invoke sophisticated communication or complex cognition. Each ant modulates the time spent within a chain in response to locally available information on target distance, and these decisions lead to a collective-level outcome that limits the overall investment into costly chains. While our work focused on the behavioral mechanisms that ants use in the absence of payoff information, future studies should investigate how access to this knowledge modifies the decision-making of maintaining a chain after exploring the new area (i.e., when payoff information becomes available). Payoff information may be encoded in the traffic flow walking over the structure. The weak effect of traffic flow detected in our behavioral analyses during chain formation ( Fig. 2 D ) may have a major effect on maintaining stability in established chains, as it has been observed in the bridges built by Eciton army ants ( 50 ). Our findings also reveal the possibility that noise in the system and/or the motivational state of the ants may regulate chain-building decisions. We observed the initiation of chain formation when the distance from the platform was set at 110 mm, suggesting that some individuals may possess different thresholds for initiating or remaining in chains. Threshold models are common in social insect research ( 15 , 57 – 59 ), and interindividual variation in response thresholds has been shown to enhance group performance in various tasks ( 15 , 57 , 60 – 62 ). Longer than expected chains may also spontaneously emerge in the case of traffic congestions, where ants that are walked over by nestmates may remain locked in position and form small temporary clusters that may seed chain formation. Research on social insect behavior has led to important advances in our understanding of complex systems ( 63 ), and inspired several solutions for the optimization of real-life problems such as traffic formation ( 64 ), protein folding ( 65 ), and DNA sequencing ( 66 ). Our proposed model offers insights for algorithmic solutions to collective decision-making in artificial multiagent systems, especially for cases where information about the outcomes of the decision is unavailable. This is especially relevant for swarm robotics, where scalability, energetic efficiency, and low-cost production are pivotal elements for real-world applications of the swarms ( 67 , 68 ). The behavioral algorithm presented here requires agents to modulate their behavior depending on their energetic or motivational budget, without the need for active communication or sophisticated cognitive abilities. In scenarios such as search and rescue ( 69 ), these behavioral rules may aid robots in navigating unknown environments and make cost-effective decisions without knowledge of the possible outcomes. The current study improves upon the previous model of chain formation ( 27 ) by describing a simple sensory-based mechanism that allows ants to modulate their behavior using only locally available information. The model presented here aligns with the self-organized nature of chain formation, in that a sophisticated group-level behavior can be explained by simple behavioral rules followed by individuals without the need to invoke complex cognition or communication among individuals ( 10 , 14 ). Our study furthers our knowledge of collective decision-making in animal groups and sheds light on the processes that allow groups to deal with uncertainty in real-life scenarios."
} | 2,877 |
26457194 | PMC4599204 | pmc | 5,488 | {
"abstract": "Background Filamentous fungi are well known for their ability to degrade lignocellulosic biomass and have a natural ability to convert certain products of biomass degradation, for example glucose, into various organic acids. Organic acids are suggested to give a competitive advantage to filamentous fungi over other organisms by decreasing the ambient pH. They also have an impact on the ecosystem by enhancing weathering and metal detoxification. Commercially, organic acids can be used as chemical intermediates or as synthons for the production of biodegradable polymers which could replace petroleum-based or synthetic chemicals. One of the advantages of filamentous fungi as biotechnological production platforms for synthetic biology is their ability to degrade vegetal biomass, which is a promising feedstock for the biotechnological production of organic acids. The Fungal Culture Collection of the International Centre of Microbial Resources (CIRM-CF), curated by our laboratory, contains more than 1600 strains of filamentous fungi, mainly Basidiomycetes and Ascomycetes . The natural biodiversity found in this collection is wide, with strains collected from around the world in different climatic conditions. This collection is mainly studied to unravel the arsenal of secreted lignocellulolytic enzymes available to the fungi in order to enhance biomass degradation. While the fungal biodiversity is a tremendous reservoir for “green” molecules production, its potentiality for organic acids production is not completely known. Results In this study, we screened 40 strains of Ascomycota and 26 strains of Basidiomycota, representing the distribution of fungal diversity of the CIRM-CF collection, in order to evaluate their potential for organic acid and ethanol production, in a glucose liquid medium. We observed that most of the filamentous fungi are able to grow and acidify the medium. We were also able to discriminate two groups of filamentous fungi considering their organic acid production at day 6 of incubation. This first group represented fungi co-producing a wide variety of organic acids and ethanol at concentrations up to 4 g.L −1 and was composed of all the Aspergilli and only 3 other Ascomycota . The second group was composed of the remaining Ascomycota and all the Basidiomycota which produced mainly ethanol. Among the Basidiomycota, two strains produced oxalic acid and one strain produced gluconic and formic acid. Six strains of Aspergillus producing high concentrations of oxalic, citric and gluconic acids, and ethanol were selected for metabolism analysis. Conclusion These results illustrate the versatility in metabolites production among the fungal kingdom. Moreover, we found that some of the studied strains have good predispositions to produce valuable molecules. These strains could be of great interest in the study of metabolism and may represent new models for synthetic biology or consolidated bioprocessing of biomass. Electronic supplementary material The online version of this article (doi:10.1186/s40694-014-0001-z) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusion The potentiality of a wide panel of fungus for organic acids production has been studied in glucose based liquid media at acidic pH to take into account industrial up- and down-stream technical and economical issues. Strains were sorted in two clusters considering their organic acid and ethanol production at day 6 of incubation, showing that some strains, even from the same species, seem to have particular predispositions for some metabolites. Among 26 Basidiomycota tested, only two: Postia stiptica (brown-rot) and Ganoderma weberianum (white-rot) produced oxalic acid. Ethanol is the common metabolite in the fungal kingdom, regardless the geographic origin of the strains, but with different extent depending on the strain. Although yeasts have very competitive ethanol productivity on simple sugars, our best ethanol producers may be good candidates for consolidated bioprocessing (CBP) of cellulosic biomass for second generation ethanol production. Among the Ascomycota, Aspergilli clearly make a distinct cluster for their various and high concentration organic acid production; this illustrates the relevance of organic acids in the chemotaxonomy of Aspergilli . Some of these strains showed particular ability to produce malic, oxalic, gluconic and citric acids or ethanol at low pH. This production could be further improved by genetic modifications. The high intra-specific variability in metabolite production stresses the importance of screenings for a good choice of studied strains. This study provides a better knowledge of the capability of filamentous fungi to produce organic acids which should allow a greater exploitation of filamentous fungi in synthetic biology, metabolic studies and industrial exploitation of organic acids.",
"discussion": "Results and discussion Growth of the selected strains and pH of the medium All the Ascomycota were able to grow in the liquid medium at an initial pH of 5.5. However, 4 strains of Basidiomycota : Ischoderma benzoinum (BRFM1133), Grifola frondosa (BRFM1162), Panellus serotinus (BRFM1284), and Polyporus squamosus (BRFM1531), did not grow to a sufficient level and did not acidify the medium. These strains were not considered for the following steps. The pH of the medium was acidified for most of the cultures but to different extents. An extreme acidification, to pH below or equal to 2, was observed for 33 Ascomycota strains, representing 80% of the strains from this phylum. In particular, all the Aspergilli tested (22 strains) acidified the medium below pH 2 (Figure 1 ). Five strains of Ascomycota acidified the medium to pH between 2 and 4 and only two strains did not or slightly acidify the medium. To the contrary, only two Basidiomycota highly acidified the medium to pH below or equal to 2, namely Phanerochaete chrysosporium (BRFM413) and Trametes menziesii (BRFM1281). Eight strains acidified the medium between 2 and 4, and 12 strains did not or slightly acidified the medium (Figure 1 ). For the strains acidifying the medium, the acidification started within 24 hours of growth and the final pH was already observed after 3 days of growth. Figure 1 \n Repartition of \n Ascomycota \n and \n Basidiomycota \n strains according to the final pH of growth medium after 6 days of incubation. (orange square) Ascomycota , (sky blue square) Basidiomycota . \n Organic acid and ethanol production HPLC analysis of the supernatants obtained at day 3 of incubation contained only oxalic, malic, propionic and citric acids, found mostly in the supernatants of Aspergillus species. The samples taken at day 6 of incubation showed a better view of the potentiality of the strains tested for organic acid production and allowed the detection of 15 different carboxylic acids at concentration between 0.1 and 3.7 g.L −1 : acetic, ascorbic, butyric, citric, fumaric, formic, oxalic, gluconic, itaconic, isobutyric, lactic, malic, propionic, succinic, and tartaric acids (Figure 2 ). Ethanol was the main neutral metabolite. Figure 2 \n Hierarchical clustering of organic acids and/or ethanol producing strains. Concentration were determined by HPLC-UV or RI analysis and expressed as a percentage of the maximum concentration observed for each metabolite and represented by a color scale with different intensity of blue. Concentration of butyric, tartaric, oxalic, malic, citric, gluconic, succinic acids and ethanol were used to build distance tree. The figure was edited using the Multiexperiment Viewer software [ 20 ]. \n Hierarchical clustering was used to classify the strains producing detectable amounts of organic acids and/or ethanol at day 6 of incubation. The clustering was based on production levels of the most widely detected compounds: butyric, citric, gluconic, malic, oxalic, succinic, tartaric acids and ethanol (Figure 2 ). Two main groups appeared in this clustering: one group of organic acid and ethanol producers and one group producing mainly ethanol. In the first group, which was mainly composed of Aspergilli , all the compounds analyzed in our assays were detected. This first group represented fungi co-producing a wide variety of organic acids at relatively high concentrations. Two sub-groups could be observed. The first one was composed of various Aspergilli and Nectria species, with only three A. niger species. The second one was composed mostly of A. niger species, with the exception of A. terreus (BRFM111). These results show that A. niger is clearly an exception in the fungal kingdom concerning organic acid production. Organic acid production may also be used along with secondary metabolites in the chemotaxonomy of Aspergilli \n[ 21 ]. The second group was composed of the remaining Ascomycota and Basidiomycota producing mainly ethanol. The metabolite concentrations obtained were lower than for the first group and the variety was narrower since only 6 different organic acids out of 15 were detected (Figure 2 ). In this second group, two subgroups were observed with strains producing only ethanol and strains producing ethanol and/or other organic acids. Ethanol was detected in 33 strains out of 40 regardless their phylum and species. Although this ethanol production is surprising for organisms traditionally considered as non-fermentative, there are previous records of ethanol production by filamentous fungi. Recent literature shows an increasing interest in ethanol production by filamentous fungi, in particular Flammulina velutipes \n[ 22 ],[ 23 ]. Some species belonging to Fusarium , Mucor and Paecilomyces were also found to efficiently convert xylose to ethanol with high yields [ 24 ]-[ 26 ]. Concerning the relation between pH acidification (section Growth of the selected strains and pH of the medium) and organic acid production, as expected most of the highly acidifying strains were good organic acid producers, from the Ascomycota phylum. However, the pH obtained in the Ascomycota growth media was below 2, which is far below the pKa of organic acids (between 3 and 5). Moreover, some strains for example Phanerochaete chrysosporium (BRFM413) and Cosmospora vilior (BRFM1198) acidified the medium below 3 but did not produce detectable amounts of organic acids. Therefore, the decrease in pH in our experiments cannot be explained by the sole release of large amount of organic acids. The acidification of the medium is probably mainly due to the removal of the ammonium from ammonium sulfate salt, used as nitrogen source, or excretion of H + ions from the assimilation of NH 4 \n + . Organic acid and ethanol production in the Basidiomycota phylum In the Basidiomycota phylum, only 6 strains out of 20 produced organic acids or ethanol. Pycnoporus coccineus (BRFM1396) was the only Basidiomycota producing several metabolites with 0.6 g.L −1 of gluconic acid, 0.2 g.L −1 of formic acid and 0.2 g.L −1 of ethanol (Figure 2 ). Stereum hirsutum (BRFM889), Tinctoporellus epimiltinus (BRFM1229) and Fomitiporia mediterranea (BRFM1315) produced only ethanol at concentrations between 0.12 and 0.19 g.L −1 . Two strains: Postia stiptica (brown-rot, BRFM1148) and Ganoderma weberianum (white-rot, BRFM1548) produced only oxalic acid at 0.06 and 0.08 g.L −1 , respectively. Generally, oxalic acid is accumulated in large quantities by brown-rot fungi and detected in lower amounts in white-rot fungi [ 8 ],[ 10 ]. This difference was attributed to the inability of brown-rot fungi to undertake an active regulation of oxalic acid concentration [ 10 ]. The other brown-rot tested, Gloeophyllum sepiarium , produced neither organic acids nor ethanol. Interestingly, P. coccineus (white-rot) produced 0.2 g.L −1 of formic acid. Formic acid production by this strain might be the result of oxalate decarboxylation, as described previously for white-rots [ 11 ]. Organic acid and ethanol production in the Ascomycota phylum Out of the 40 strains, 6 strains of Ascomycota produced neither organic acids nor ethanol at detectable level: Cosmospora vilior (BRFM982 and BRFM1198), Nectria pseudocinnabarina (BRFM1288), Xylaria schweinitzii (BRFM1447), Hypomyces luteovirens (BRFM1580), and Cordyceps militaris (BRFM1581). Ascorbic, fumaric and itaconic acids were detected in only a few supernatants, all from Aspergilli, and at concentrations below the limit of quantification (0.05 g.L −1 ). The maximal metabolite concentrations were all observed in Aspergilli culture media and ranged from 0.1 g.L −1 for lactic and tartaric acids to more than 2 g.L −1 for citric, formic, gluconic acids and ethanol (Table 1 ). Indeed, among the fungal kingdom, Aspergilli are well known for their ability to accumulate large amounts of organic acids [ 2 ],[ 18 ]. In our culture conditions the concentration obtained were low compared to the literature where the conversion of glucose into organic acid is described to approach 100% for some Aspergilli in optimized conditions [ 2 ]\n . This can be explained by the fact that accumulation of organic acid is strongly influenced by the medium composition [ 2 ],[ 18 ]. These results show that, in the Aspergillus genus, the major metabolite secreted is different depending on the strain. Table 1 \n Highest concentrations of LMWOA and ethanol obtained at day 6 of incubation, for each compound and the corresponding producing strains \n Compound Fungal strain g.L\n −1 \n \n Ascomycota \n \n Ethanol \n \n A. niger (BRFM421) 4.1 \n Gluconic acid \n \n A. niger (BRFM431) 3.7 \n Formic acid \n \n A. flavipes (BRFM456) 3.3 \n Citric acid \n \n A. niger (BRFM422) 2.2 \n Succinic acid \n \n A. flavipes (BRFM456) 1.8 \n Oxalic acid \n \n A. niger (BRFM420) 1.6 \n Malic acid \n \n A. niger (BRFM103) 0.6 \n Acetic acid \n \n A. niger (BRFM428) 0.4 \n Propionic acid \n \n A. niger (BRFM422) 0.2 \n Butyric acid \n \n A. flavus (BRFM821) 0.2 \n Isobutyric acid \n \n A. niger (BRFM432) 0.2 \n Tartaric acid \n \n A. niger (BRFM420) 0.1 \n Lactic acid \n \n A. niger (BRFM428) 0.1 \n Ascorbic acid \n \n A. niger (BRFM280) <0.05* \n Fumaric acid \n \n A. niger (BRFM438) <0.05* \n Itaconic acid \n \n A. terreus (BRFM111) <0.05* \n Basidiomycota \n \n Ethanol \n \n S. hirsutum BRFM889) 0.2 \n Gluconic acid \n \n P. coccineus (BRFM1396) 0.6 \n Formic acid \n \n P. coccineus (BRFM1396) 0.2 \n Oxalic acid \n \n G. weberianum (BRFM1548) 0.1 *limit of quantification. \n Six strains of Aspergillus (BRFM103, BRFM420, BRFM421, BRFM422, BRFM431 and BRFM434) have been selected for further studies due to their high organic acids or ethanol production, and to the variety of organic acids produced. A. brasiliensis BRFM103, A. niger BRFM421, and A. niger BRFM434 were selected for their ability to produce ethanol, 3.6, 4.1, and 2.5 g.L −1 , respectively. A. niger BRFM420 was selected for its production of oxalic acid (1.6 g.L −1 ). A. niger BRFM422 was selected for its production of citric acid (2.2 g.L −1 ) and A. niger BRFM431 was selected for its production of citric (2.1 g.L −1 ) and gluconic acids (3.7 g.L −1 ). At day 6 of incubation 14.2 to 22.9 g.L −1 of glucose remained in the medium and these strains converted 8 to 15% of the glucose consumed to the main organic acid or ethanol (Table 2 ). Table 2 \n Concentrations and conversion yields for the 6 best organic acid producers \n Concentration (g.L\n −1 \n) Mean Y\n P/S \n(%) \n Aspergillus brasiliensis \n (BRFM103) \n Oxalic acid 0.4 ± 0.1 1.2 Citric acid 0.5 ± 0.1 1.5 Malic acid 0.7 ± 0.2 2.0 \n Ethanol \n 3.9 ± 1.0 10.8 Residual glucose 14.2 ± 1.7 \n Aspergillus niger \n (BRFM420) \n \n Oxalic acid \n 2.0 ± 0.4 7.0 Citric acid 0.5 ± 0.1 1.9 Residual glucose 21.6 ± 3.8 \n Aspergillus niger \n (BRFM421) \n Oxalic acid 0.4 ± 0.1 1.4 \n Gluconic acid \n 2.6 ± 0.5 9.5 Malic acid 0.4 ± 0.1 1.6 \n Ethanol \n 4.0 ± 0.7 14.5 Residual glucose 22.9 ± 1.1 \n Aspergillus niger \n (BRFM422) \n Oxalic acid 0.4 ± 0.1 1.3 \n Citric acid \n 2.5 ± 0.6 7.7 Tartaric acid 0.2 ± 0.1 0.6 \n Gluconic acid \n 3.4 ± 0.1 10.4 Succinic acid 0.8 ± 0.1 2.3 Fumaric acid 0.7 ± 0.2 2.3 Residual glucose 17.6 ± 1.3 \n Aspergillus niger \n (BRFM431) \n Oxalic acid 0.9 ± 0.1 3 \n Citric acid \n 2.4 ± 0.4 8.2 \n Gluconic acid \n 4.7 ± 0.6 15.6 Malic acid 0.4 ± 0.1 1.5 Succinic acid 0.7 ± 0.1 2.2 Residual glucose 20.4 ± 1.6 \n Aspergillus niger \n (BRFM434) \n Oxalic acid 0.6 ± 0.1 2.2 Citric acid 0.4 ± 0.1 1.4 \n Gluconic acid \n 2.4 ± 0.8 8.5 \n Ethanol \n 2.1 ± 0.5 7.4 Residual glucose 21.9 ± 1.7 Yields are expressed in g of product per g of glucose consumed. (± SD), n = 3. \n In order to confirm the identity of organic acids of applied interest observed by HPLC-UV (i.e. citric, lactic, malic, and oxalic acid), supernatants from fresh cultures of A. brasiliensis BRFM103, A. niger BRFM422 and A. niger BRFM428 were analyzed by GC-MS. These 4 organic acids were detected in all the supernatants. With HPLC-UV, malic acid was not detected in the supernatants of strains BRFM422 and BRFM428, and lactic acid was detected only in BRFM428. This result suggests that these three strains are able to produce citric, lactic, malic and oxalic acid. However, only BRFM103 produced malic acid and BRFM422 produced lactic acid at amounts detectable by HPLC-UV. Besides, we confirm the high ethanol production by BRFM103 and found smaller amounts of ethanol in BRFM422 and BRFM428 as well. This ethanol production was also found by HPLC-RI (data not shown) showing a biological variability compared to the first cultures. As expected the two main organic acids produced by the 6 Aspergilli strains were citric acid and gluconic acid [ 2 ],[ 18 ]. Interestingly, all these strains also produced oxalic acid. For most of them the production of oxalic acid was low and ranged from 0.4 to 0.9 g.L −1 . This is consistent with the literature since oxalic acid production has been shown to be inhibited at pH below 3 by A. niger \n[ 27 ] and by ammonium and excess of substrate [ 1 ],[ 28 ]. One exception is A. niger BRFM420 which produced 2 g.L −1 of oxalic and with a conversion yield of 7 g oxalic acid/100 g of glucose consumed. For this strain, the only other organic acid detected was citric acid at 0.5 g.L −1 . Even if this conversion yield is low compared to yields obtained in optimum conditions [ 29 ], this strain is particularly interesting since it seems more disposed than other Aspergilli to produce oxalic acid, even when grown in conditions not promoting the production of this organic acid. Regarding ethanol production, the best yield, 14.5%, was observed with A.niger (BRFM421). A. oryzae and Rhizopus oryzae have been shown to convert 51.8% of glucose into ethanol [ 30 ]. However, a complex medium was used in this study, therefore glucose was not the sole carbon source. As a comparison, Saccharomyces cerevisiae , the fermentative organism used for industrial ethanol production, has a maximum theorical yield on glucose of 51.1%, and industry processes are considered economically relevant above 90% of this yield [ 31 ]. The main drawback of ethanol production from biomass using Saccharomyces is that the naturally occurring yeast cannot metabolize xylose, a product of biomass degradation [ 32 ]. These findings could be of interest for the production of 2nd generation ethanol from hemicelluloses and consolidated bioprocessing of biomass to ethanol [ 33 ]."
} | 4,878 |
33323417 | PMC7771537 | pmc | 5,489 | {
"abstract": "Arbuscular mycorrhizal (AM) fungi form tight symbiotic relationships with the majority of terrestrial plants and play critical roles in plant P acquisition, adding a further dimension of complexity. The plant-AM fungus-bacterium system is considered a continuum, with the bacteria colonizing not only the plant roots, but also the associated mycorrhizal hyphal network, known as the hyphosphere microbiome. Plant roots are usually colonized by different AM fungal species which form an independent phosphorus uptake pathway from the root pathway, i.e., the mycorrhizal pathway.",
"conclusion": "Outlook and conclusion. The soil microbiome is critical to the functioning of the plant-AM fungi-bacteria-soil particle continuum and therefore to growing food sustainably with minimal environmental impact and protecting against pathogens and disease while also providing important ecological services such as nutrient turnover and transformation and bioavailability. Understanding the structure of the microbiome is essential for using the native microbiome efficiently ( 41 ). In recent years, mycorrhizal genome sequencing studies have found that mycorrhizal fungi have lost many saprophytic genes in the long-term coevolution process with plants ( 17 ). Cooperating with functional microbiomes, such as phosphatase-releasing bacteria ( 6 , 42 ), is considered an important strategy for AM fungi to compensate for their lack of ability to utilize organic P, for example. We find for the first time that different living AM fungus species colonizing a single plant root system recruit active microbiomes which are distinct from each other. The research not only provides direct evidence for understanding the biophysical process by which AM fungal hypha exudates drive the formation of soil bacteria diversity heterogeneity, but also reveals that the potential division of labor may exist in the plant-AM fungus-bacterium system that still remains to be understood fully. More knowledge of these key interactions in the hyphosphere has the potential to allow effective management of resources in agricultural systems and help us improve future agricultural sustainability.",
"introduction": "INTRODUCTION Plant-arbuscular mycorrhizal (AM) fungal symbiosis has existed for over 460 million years ( 1 ). Consequently, over 80% of terrestrial plants form a symbiosis with arbuscular mycorrhizal (AM) fungi for efficient nutrient uptake or to confer resistance to stress ( 2 ). Exploitation of these symbioses is of high environmental and economic value ( 3 ). Like plant roots, AM fungi produce large networks of extraradical hyphae in the soil, release carbon, and recruit free-living soil microbes to colonize the hyphae ( 4 – 8 ). In recent years, an intimate cooperative relationship between AM fungal hyphae and bacteria has been observed, supported by multiple lines of evidence, including both microscopic observations ( 9 ) and molecular analyses ( 5 ). Bacteria associated with AM fungi (hyphosphere) have been identified as the third component of plant-AM fungal symbiosis because of the critical role they play in mycorrhizal function ( 3 , 6 , 10 , 11 ). Revealing the secrets of hyphosphere microbiomes is essential for a better understanding of the belowground ecosystem. Many soil factors, such as pH and spatial structure, have been identified to influence the bacterial community associated with plant roots, while AM fungi were also identified as a major determining factor ( 12 ). In natural and agricultural systems, the root system of a mycorrhizal plant is usually simultaneously colonized by diverse AM fungal species ( 13 ). The cocolonizing AM fungi have different morphological, physiological, and genetic characteristics ( 14 – 19 ). The coexisting AM fungal species show different contributions to the growth and P uptake of the host plant ( 16 ). For example, Glomus intraradices can rapidly colonize available P patches beyond the root surface and transport significant amounts of P toward the roots, while Glomus margarita has been shown to provide P benefits to the plants by forming dense mycelium networks close to the roots where remaining soil P was less available ( 16 ). In addition, recent decoding of the whole-genome sequences of AM fungi suggest that there is large variation in the genetic control of functions ( 17 ), e.g., Glomus rosea contains a much larger secretome size and more secreted proteins (SSP) than Rhizophagus spp. ( 17 ). Collectively, the above-described morphological, physiological, and genetic differences indicate that the hyphal exudates of AM fungal species are likely to be different, which in turn, is likely to lead to differences in the hyphosphere microbial community structure and function. However, at present, no direct evidence exists that shows the difference between fungal species cocolonizing on a single plant root system. Therefore, to uncover such a difference is fundamental for understanding the central question in fungus-bacterium interaction research: how bacteria and mycorrhizal fungi associate and become mutually beneficial neighbors ( 3 ). Several factors may affect the results of hyphosphere microbial community composition in the plant-AM fungi-soil system. First, plant root exudates are an important factor in the recruitment of the soil microbial community. In order to get direct evidence of the effect of hyphal exudates on hyphosphere microbiome characteristics, it is essential to separate their influence from that of the root exudates. Second, the vitality of AM fungal hyphae is important. Previous studies have shown that soil bacteria differ in their ability to colonize vital and nonvital hyphae and that this can also be influenced by the arbuscular mycorrhizal fungal species involved ( 20 ). Therefore, a method that can test the vital and nonvital hyphae is necessary to identify the hyphosphere microbiome. Third, the feedback effects of plants on the growth of AM fungi due to changes in plant physiology induced by the fungi ( 21 , 22 ) are critical. In the past, split-root methods were used to quantify C allocation to different AM fungal species cocolonizing on a single root system of a plant ( 23 ) in order to assess this factor. In this study, we hypothesized that the different AM fungal species that colonized on a single root system would recruit distinct microbiomes. To test our hypothesis, we developed a new integrated approach where we grew cotton ( Gossypium hirsutum L.) plants in a split-root and compartmented rhizobox in which a buffer zone was set to prevent root exudates from diffusing into the hyphal compartment and to avoid feedback effects. Two independent experiments (experiment 1 [Exp 2] and experiment 2 [Exp 2]) were performed. In Exp 1, we inoculated two different AM fungal species, Funneliformis mossea and Gigaspora margarita , to two separate root compartments, while in Exp 2, Rhizophagus intraradices and Gigaspora margarita were inoculated to the two root compartments. We used 13 CO 2 to pulse-label the plant-AM fungus-hypha-associated bacteria during the last week before harvest and tested active hypha-associated microbiomes by 13 C-DNA-SIP (stable isotopic probing) methods and MiSeq high-throughput sequencing.",
"discussion": "DISCUSSION Validation of a novel method for separating out the impact of AM fungi on the soil microbiome. Traditionally, mycorrhizal colonization is measured by staining and microscopic observation methods ( 25 ). In contrast, in this study we used qPCR to quantify the DNA copy number to indicate mycorrhizal fungus colonizing status with species-specific 18S rRNA primers. There is a background threshold of 100 copies in the AM fungus DNA qPCR process that dictates the presence or absence of AM fungi ( 19 ). Our results suggest that all inoculated treatments have many orders of magnitude more DNA copies than those of control treatments ( Fig. 1a ). In addition, no other nontargeted AM fungus was found in any sample through PCR using AM fungal species-specific primers. Such results suggest that all inoculated AM fungi were well colonized in the split-root system of cotton without contamination. In this study, we compared the bacterial community that associated with the hyphae (representing the hyphosphere microbiome) with the bacterial community in the soil collected from HCs of nonmycorrhizal treatments (representing the bulk soil). As the diameter of AM fungal hyphae is so small that it is difficult to separate soil particles from the hyphae, we quantified the bacteria that were tightly colonizing on the hyphal surface to indicate the status of the hyphosphere bacterial community. To avoid any influence of root exudates on the measurements, we set a 1-cm-wide buffer zone in which we added a sterilized mixture of glass beads and fine clay soil which was sieved through 30-μm nylon mesh. Our results showed that δ 13 C of the HC soils of the control treatments was the same as the background, suggesting no direct influence from root exudates on the microbial community in HCs. Therefore, all differences between hyphosphere and bulk soil or between the different AM fungal species can be attributed to the effects of hyphal exudation. As the turnover rate of AM extraradical hyphae is fast ( 26 ), both vital and nonvital hyphae exist simultaneously; importantly, it is thought that the bacterial communities associated with these two types of hyphae may differ ( 20 ). To avoid these influences, we used a 7-day 13 CO 2 pulse-labeling approach in the last week before harvesting, which ensured that all the 13 C-labeled extraradical mycelia were vital, because the potential turnover time of AM fungal hyphae is 5 to 6 days ( 26 ). We assume nonvital hyphae will not consume the 13 C-labeled carbohydrates because the senescent hyphae form septa to cease protoplasm flow in hyphae. Therefore, the atom percentage of 13 C of the samples in HCs indicated the allocation of photosynthetic products to vital extraradical hyphae and hyphae associated with soil particles and bacteria, and the 13 C-DNA-SIP identified in the hyphosphere microbiome were active hypha exudate consumers. The influence of AM extraradical hyphal exudates on biophysical distribution of the soil microbial community and biodiversity. Arbuscular mycorrhizal fungi produce a large network of extraradical hyphae in soil and provide a carbon-rich habitat for soil microbes ( 5 , 6 ), which induces colonization of diverse groups of bacteria forming the hyphosphere ( 7 , 27 , 28 ). Our current study not only further supports those previous findings, but also provides novel findings. First, the differences in qPCR ( Fig. 1a ) and plant biomass ( Table 1 ) results between F. mosseae and G. margarita and NM in Exp 1 or R. intraradices and G. margarita and NM in Exp 2 indicated that all AM fungal species colonized roots of cotton and played a role in promoting plant growth. Second, we successfully separated the active bacteria that consumed hyphal exudates by 13 C-DNA-SIP plus MiSeq sequencing methods ( Fig. S1 ). Compared to bulk soil, we found that only part of the soil microbiome was 13 C-labeled on the hyphae of the AM fungi, which we defined as the active hyphosphere microbiome ( Fig. S3 ). Third, the cocolonizing AM fungi all formed a unique bacterial community around the extraradical mycelium ( Fig. S2 and S3 ). Our observations help us understand the biophysical mechanisms which dictate the heterogeneous distribution of the microbiome in soil at the microscale ( 29 – 31 ). Our current findings provide new and direct evidence that AM fungal hyphae, most likely through their exudates, are one of the major driving forces for formation of the bacteria mosaic at the micrometer scale in soil. As AM fungi use up to 20% of plant photosynthesis products and form several meters to tens of meters of hyphae in 1 g of soil ( 32 ), an understanding of such mechanisms has significance within the context of the global soil microbial biodiversity and its function. 10.1128/mSystems.00929-20.5 FIG S3 The principal-component analysis (PCA) of 16S rRNA genes from all 30 samples. The three different AM fungal inocula were Rhizophagus intraradices ( R.i ) (EY108), Funneliformis mosseae ( F.m ) (MD118), and Gigaspora margarita ( G.m ) (JA101A). All samples are shown in this part. Download FIG S3, TIF file, 0.1 MB . Copyright © 2020 Zhou et al. 2020 Zhou et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Cocolonizing AM fungal species recruit different active hyphosphere microbial communities. Previous studies have shown that a range of AM fungal species, which are different in morphological structure, hyphal distribution pattern, and metabolic traits, can simultaneously colonize a single root system ( 16 , 33 , 34 ). Whether or not these fungi recruit different microbiomes is still an open question. We hypothesized that any difference in microbial community structures between the two HCs in Exp 1 and Exp 2 can be attributed to the differences in traits of excretion of exudates between the two AM fungal species. Our 13 C-DNA-SIP plus pyrosequencing results supported the hypothesis. First, different AM fungal species produced differing amounts of hyphae in HCs ( Fig. 1b ). Compared to G. margarita , the HCs of both F. mosseae and R. intraradices contained a greater 13 C abundance. Second, there were more OTUs in the microbiome of the F. mosseae and R. intraradices hyphosphere than in that of G. margarita in Exp 1 and Exp 2, respectively. More importantly, the abundance and structure of over half of the bacteria, at both the phylum and genus levels, showed a significant difference between F. mosseae and G. margarita in Exp 1 and between R. intraradices and G. margarita in Exp 2 ( Fig. 2 to 5 ). All these results suggest that the microbiomes associated with the three AM fungal species were distinct. Previous studies have indicated that the hyphosphere microbiome is directly involved in soil organic N, P, and C mineralization ( 7 , 28 , 32 , 35 , 36 ). For example, Pseudomonas and Bacillus are reported to have abilities to mobilize sparingly soluble P in soil ( Table S1 ) ( 5 , 7 ). In the current study, G. margarita harbored a greater abundance of Pseudomonas , but fewer Bacillus , than F. mosseae or R. intraradices . In addition, some soil bacteria, called mycorrhiza helper bacteria (MHB), can help AM fungi colonize the root more effectively or cause them to branch more ( 10 ). Such MHB belong to many taxa, including Proteobacteria ( Agrobacterium , Azospirillum , Azotobacter , Burkholderia , Bradyrhizobium , Enterobacter , Pseudomonas , Klebsiella , and Rhizobium ), Firmicutes ( Bacillus , Brevibacillus , and Paenibacillus ), Actinomycetes ( Rhodococcus , Streptomyces , and Arthrobacter ), and some unculturable bacterial taxa such as Acidobacteria ( Acidobacterium ) ( 37 ) ( Table S2 ). However, MHB are often AM fungal species specific, which means they can stimulate mycorrhizal formation and extraradical hypha production for some AM fungi but inhibit these traits for the others ( 38 ). For example, Streptomyces spp. enhanced the colonization of R. intraradices (formerly named Glomus intraradices ) but inhibited the growth of Hebeloma cylindrosporum ( 39 , 40 ). Here, we found that the abundance of Streptomyces and Bacillus was much greater in the hyphosphere of R. intraradices and F. mosseae than in that of G. margarita , while G. margarita contained the largest abundance of Pseudomonas . These observations suggest that different AM fungal species might cooperate with different functional bacteria and have different impacts on the function of the hyphosphere. The COG functional prediction also supported this assertion, indicating that distinct microbiomes recruited by different AM fungi contained different abundances of inorganic P mobilization abilities or other functions ( Fig. 6 ). Further studies are needed to investigate the functions of the hyphosphere microbiome in specific nutrition cycling. 10.1128/mSystems.00929-20.7 TABLE S1 The relative abundance (%) of phosphate-solubilizing bacteria (PSB) referred to in previous studies. Download Table S1, DOCX file, 0.01 MB . Copyright © 2020 Zhou et al. 2020 Zhou et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . 10.1128/mSystems.00929-20.8 TABLE S2 The relative abundance (%) of mycorrhizal helper bacteria (MHB) referred to in previous studies. Download Table S2, DOCX file, 0.02 MB . Copyright © 2020 Zhou et al. 2020 Zhou et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Outlook and conclusion. The soil microbiome is critical to the functioning of the plant-AM fungi-bacteria-soil particle continuum and therefore to growing food sustainably with minimal environmental impact and protecting against pathogens and disease while also providing important ecological services such as nutrient turnover and transformation and bioavailability. Understanding the structure of the microbiome is essential for using the native microbiome efficiently ( 41 ). In recent years, mycorrhizal genome sequencing studies have found that mycorrhizal fungi have lost many saprophytic genes in the long-term coevolution process with plants ( 17 ). Cooperating with functional microbiomes, such as phosphatase-releasing bacteria ( 6 , 42 ), is considered an important strategy for AM fungi to compensate for their lack of ability to utilize organic P, for example. We find for the first time that different living AM fungus species colonizing a single plant root system recruit active microbiomes which are distinct from each other. The research not only provides direct evidence for understanding the biophysical process by which AM fungal hypha exudates drive the formation of soil bacteria diversity heterogeneity, but also reveals that the potential division of labor may exist in the plant-AM fungus-bacterium system that still remains to be understood fully. More knowledge of these key interactions in the hyphosphere has the potential to allow effective management of resources in agricultural systems and help us improve future agricultural sustainability."
} | 4,610 |
38739531 | PMC11472818 | pmc | 5,491 | {
"abstract": "Bacteria have evolved various strategies to combat heavy\nmetal\nstress, including the secretion of small molecules, known as metallophores.\nThese molecules hold a potential role in the mitigation of toxic metal\ncontamination from the environment (bioremediation). Herein, we employed\ncombined comparative metabolomic and genomic analyses to study the\nmetallophores excreted by Delftia lacustris DSM 21246.\nLCMS-metabolomic analysis of this bacterium cultured under iron limitation\nled to a suite of lipophilic metallophores exclusively secreted in\nresponse to iron starvation. Additionally, we conducted genome sequencing\nof the DSM 21246 strain using nanopore sequencing technology and employed\nantiSMASH to mine the genome, leading to the identification of a biosynthetic\ngene cluster (BGC) matching the known BGC responsible for delftibactin\nA production. The isolated suite of amphiphilic metallophores, termed\ndelftibactins C–F ( 1 – 4 ), was\ncharacterized using various chromatographic, spectroscopic, and bioinformatic\ntechniques. The planar structure of these compounds was elucidated\nthrough 1D and 2D NMR analyses, as well as LCMS/MS-based fragmentation\nstudies. Notably, their structures differed from previously known\ndelftibactins due to the presence of a lipid tail. Marfey’s\nand bioinformatic analyses were employed to determine the absolute\nconfiguration of the peptide scaffold. Delftibactin A, a previously\nidentified metallophore, has exhibited a gold biomineralizing property;\ncompound 1 was tested for and also demonstrated this\nproperty.",
"discussion": "Results and Discussion Comparative Metabolomic Profiling of Delftia lacustris under Iron Limitation To investigate the secretion of siderophores\nby D. lacustris , we followed a methodology we developed\nusing comparative metabolomics with and without excess iron. 24 In essence, we cultivated the bacteria in an\niron-limiting medium with and without iron supplementation. We then\nprocessed the culture supernatants by RP-SPE with C18 and tested the\nmiddle polarity fractions (50% aqueous MeCN) using LCMS to identify\nthe unique metabolites under each circumstance. LCMS revealed four\nmajor eluting ions corresponding to four compounds ( 1 – 4 ) that are produced only under iron limitation;\nthese ions had m / z values of 1213.6414\n[M + H] + , 1215.6579 [M + H] + , 1241.6730 [M +\nH] + , and 1243.6892 [M + H] + (Figure S1, see Supporting Information ). MS data were further\nanalyzed using the GNPS platform 25 and\nvisualized with Cytoscape 26 to see if these\nmasses clustered together. Molecular networking showed these four\nprecursor ions clustered together with many masses unique to the iron-limited\ncondition ( Figure 1 ). The results warranted further investigation of the MS/MS fragmentation\npatterns to assign putative structures associated with this cluster. Figure 1 Metabolomic\nanalysis of D. lacustris culture supernatants\nunder low and high iron conditions using molecular networking. This\nanalysis revealed clusters of putative delftibactin analogs (e.g.,\ndelftibactin C: [M + H] + at 1241 m / z boxed in black, [M – 2H + Fe] + at 1294 m / z boxed in brown). Nodes are colored\nby the culture conditions in which they were observed: blue = low\niron, red = high iron, and yellow = both. Thicker lines indicate higher\ncosine scores. MS/MS Fragmentation Spectra Annotation to Identify Putative\nStructures of Delftibactin A Analogs Based on the antiSMASH 27 genome mining of our D. lacustris genome, which identified the delftibactin A biosynthetic gene cluster\nin this organism (see below), we hypothesized that the unique cluster\nobserved solely under the low iron-limited condition was analogs of\ndelftibactin A (a known metallophore). 11 To test this hypothesis, we used the delftibactin A fragmentation\npattern as a template and investigated the MS/MS fragmentation spectra\nfor the main ions discussed above. Not surprisingly, fragments derived\nfrom delftibactin A (such as fragments with m / z values of 904.4119, 773.3900, 672.3424, 615.3209, 532.2838,\nand 374.2152) were observed in the fragmentation spectra of those\nfour major metabolites ( 1 – 4 , see SI Figures S3, S4, S11, S12, S17, S18, S25, and\nS26). Nevertheless, compounds 1 – 4 exhibited distinct precursor ions with m / z values of 1213.6414 [M + H] + , 1215.6579 [M\n+ H] + , 1241.6730 [M + H] + , and 1243.6892 [M\n+ H] + . The comparison of the precursor ions for compounds 1 and 3 , as well as compounds 2 and 4 , revealed a mass difference of 28 Da. Meanwhile, a 2 Da\ndifference separated compounds 1 and 2 ,\nas well as compounds 3 and 4 . These findings\nled us to formulate the hypothesis that these compounds ( 1 – 4 ) share a delftibactin A-derived peptide backbone\ndistinguished by the length and degree of saturation of an attached\nlipid tail. Careful annotation of the fragmentation mass spectrum\nfor each compound revealed unique fragments bearing a lipid tail.\nWe identified the lipid tails by calculating the mass differences\nbetween delftibactin A (calcd 1033.4914, [M + H] + ) and\nour observed precursor masses. The observed mass differences of 208.1816\nand 210.1978 Da suggested the presence of a 14-carbon fatty acid tail\n(a tetradecanoyl moiety) with and without a double bond for compounds 1 and 2 , respectively. Additionally, compounds 3 and 4 exhibited a 28 Da smaller lipid component\n(180.1499 and 182.1665 Da difference) when compared to those of compounds 1 and 2 . Consequently, it was postulated that\ncompounds 3 and 4 possessed 12-carbon fatty\nacid tails (a dodecanoyl moiety) with or without a double bond, respectively.\nPrior studies have also reported amphiphilic siderophores with similar\nlipid tails. 28 , 29 Our detailed analysis of the\nunique fragments in the MS/MS spectra of 1 – 4 was consistent with the biosynthetic incorporation of the\nlipid tail at the terminal NH 2 of the 4-amino-3-hydroxy-2-methylpentanoic\nacid (Ahmpa) moiety (see Figures S3, S4, S11, S12, S17, S18, S25, and S26 for a comprehensive annotation\nof MS/MS fragments for 1 – 4 ). Isolation and Structural Characterization of Delftibactins C–F Isolation Bacteria were grown in a defined medium for\nsiderophores (DMS) extracted with Diaion HP20 resin and subjected\nto purification using RP-SPE cartridges followed by two routes of\nRP-HPLC to obtain pure compounds 1 (30 mg), 2 (11 mg), 3 (3 mg), and 4 (7 mg). Planar Structure Elucidation After conducting the initial\nMS/MS fragmentation analysis, we postulated that the isolated metabolites\n( 1 – 4 ) were analogs of delftibactin\nA. To test this, we performed 1D- and 2D-NMR analysis and compared\nthe obtained data to previously reported data of delftibactin A. 11 , 30 Delftibactin C ( 1 ) was obtained as a yellowish white\npowder, and its molecular formula was determined as C 54 H 92 N 14 O 19 based on positive HRESIMS m / z 1241.6730 [M + H] + (calculated\n1241.6736, – 0.5 ppm), indicating 17 degrees of unsaturation.\nAnalysis of 1 H NMR and 13 C NMR (DEPT-Q) spectra\nof 1 ( Table 1 ) showed the presence of 10 carbonyl signals, comprising 10\namide carbons at δ C 166.9, 173.8, 172.9, 175.2, 167.8,\n172.6, 174.0, 172.4, 178.2, and 175.3 and one carboxylic acid carbonyl\nat 175.3. Furthermore, an imine carbon at 158.5 ppm, along with a\nformyl singlet for each rotamer at δ H 8.30 and 7.96\n(δ C 164.1 and 159.7), was also detected. Through\nexamination of cross peaks in TOCSY, it was determined that compound 1 has nine distinct spin systems. Although the 1D and 2D NMR\ndata exhibited a strong agreement with those of delftibactin A, there\nwere also unique peaks detected within the NMR data of 1 ( Figures S5–S9 ). In agreement\nwith our MS/MS annotation of compound 1 ( Figures S3 and S4 ), the lipid backbone showed\n10 methylene signals at δ C 37.4 (δ H 2.19, t, J = 7.5), 27.0 (1.62, m), 29.9 (1.32,\nm), 30.0 (1.33, m), 28.0 (2.06, m), 28.1 (2.04, m), 30.8 (1.35, m),\n30.6 (1.33, m), 32.9 (1.30, m), and 23.7 (1.32, m). Additionally,\ntwo olefinic signals were observed at 130.6 (5.35, m) and 131.0 (5.35,\nm) along with a methyl signal at 14.5 (0.90, t, 7.0) ( Table 1 ). The attachment of the lipid\ntail to the delftibactin backbone was established based on the observed\nHMBC cross peaks between the methine proton (H-39) of the Ahmpa moiety\nat δ H 3.96 and the fatty acid carbonyl (C-41, δ C 175.3) ( Figures S8 and S30 ). The\nlocation of the double bond in the lipid tail was established as being\nbetween the seventh and eighth carbon atoms of the lipid (C-47 and\nC-48), based on the HMBC data ( Figures S8 and S30 ). Notably, HMBC cross peaks were observed from the methylene\nprotons (H-42, δ H 2.19) to the carbonyl (C-41, δ C 175.3) and to two methylene carbons (C-43, δ C 27.0 and C-44, δ C 29.9); from methylene protons\n(H-43, δ H 1.62) to two methylene carbons, C-44 (δ C 29.9) and C-45 (δ C 30.0); and from H-46\n(δ H 2.06) to both methylene C-45 and double bond\nC-48 (δ C 130.6). This information, combined with\nthe tandem mass spectrometry assignments, led to the identification\nof compound 1 as a 7-tetradecenoic acid analogue of delftibactin\nA. Table 1 1 H (500 MHz) and 13 C (125 MHz) NMR Chemical Shifts of 1 – 4 in CD 3 OD 1 2 3 4 residue position δ C, type δ H ( J in Hz) δ C, type δ H ( J in Hz) δ C, type δ H ( J in Hz) δ C, type δ H ( J in Hz) Cyclic, N–OH-Orn 1 166.9, C 166.9, C 167.0, C 166.9, C 2 52.6, CH 2 3.67, m, 3.62, m 52.6, CH 2 3.65, m, 3.61, m 52.6, CH 2 3.66, m, 3.61, m 52.6, CH 2 3.67, m, 3.62, m 3 21.6, CH 2 2.08, m, 1.97, m 21.6, CH 2 2.09, m, 1.97, m 21.6, CH 2 2.09, m, 1.97, m 21.6, CH 2 2.09, m, 1.97, m 4 28.5, CH 2 2.04, m, 1.86, m 28.5, CH 2 2.02, m, 1.88, m 28.5, CH 2 2.06, m, 1.88, m 28.5, CH 2 2.04, m, 1.87, m 5 51.3, CH 4.51,\nm 51.3, CH 4.51, m 51.3, CH 4.51, m 51.3, CH 4.52, m Arg 6 173.8, C 173.8, C 173.8, C 173.8, C 7 54.8 4.37, m 54.9 4.35, m 54.9 4.35, m 54.9 4.36, m 8 29.6, CH 2 1.98, m, 1.76, m 29.6, CH 2 1.95, m, 1.75, m 29.6, CH 2 1.96, m, 1.75, m 29.6, CH 2 1.95, m, 1.75, m 9 26.2, CH 2 1.63, m 26.2, CH 2 1.63, m 26.2, CH 2 1.66, m 26.2, CH 2 1.63, m 10 41.9, CH 2 3.17, m 42.0, CH 2 3.16, m 42.0, CH 2 3.16, m 42.0, CH 2 3.17, m 11 158.5 158.6 158.6 158.6 Ser 12 172.9, C 173.0, C 173.0, C 173.0, C 13 57.9, CH 4.40,\nm 58.0, CH 4.38, m 57.9, CH 4.38, m 58.0, CH 4.38, m 14 62.6, CH 2 3.93, m, 3.86, m 62.6, CH 2 3.91, m, 3.85, m 62.6, CH 2 3.93, m, 3.86, m 62.6, CH 2 3.93, m, 3.86, m N δ -OH- N δ -formyl-Orn 15 175.2, C 175.4, C 175.2, C 175.3, C 16 56.3, 56.2, CH 4.33, m 56.4, 56.3, CH 4.31, m 56.3, 56.5, CH 4.30, m 56.3, 56.2, CH 4.30, m 17 29.6, 28.9, CH 2 1.95, m, 1.76, m 29.6, 28.9, CH 2 1.98, m 29.6, CH 2 1.95, m, 1.75, m 29.6, 28.8, CH 2 1.95, m, 1.75, m 18 24.8, 24.3, CH 2 1.84, m, 1.75, m 24.8, 24.4, CH 2 1.78, m 24.8, 24.1, CH 2 1.86, m, 1.75, m 24.8, 24.4, CH 2 1.78, m, 1.75, m 19 47.0, 50.8, CH 2 3.62, m, 3.57, m 47.0, 50.8, CH 2 3.62, 3.56, m 47.0, 50.8, CH 2 3.62, m 47.0, 50.8, CH 2 3.63, m 20 164.1, 159.7, CH 8.30, s, 7.96, s 164.2, 159.7, CH 8.30, s, 7.96, s 164.2, 159.7, CH 8.30, s, 7.96, s 164.2, 159.7, CH 8.31, s, 7.97, s Dhb 21 167.8, C 167.9, C 167.9, C 167.7, C 22 131.9, C 130.9, C 130.9, C 130.9, C 23 132.3, CH 6.56, m 132.3, CH 6.56, m 132.4, CH 6.56, m 132.4, CH 6.57, m 24 13.3, CH 3 1.79, m 13.2, CH 3 1.79, m 13.2, CH 3 1.80, m 13.2, CH 3 1.80, m Gly 25 172.6, C 172.5, C 172.6, C 172.7, C 26 44.0, CH 2 4.06, m, 4.00, m 44.2, CH 2 4.05, m, 4.01, m 44.0, CH 2 4.05, m, 4.00, m 44.2, CH 2 4.05, m, 4.01, m Thr 27 174.0, C 174.2, C 174.0, C 174.2, C 28 60.9, CH 4.30,\nm 60.9, CH 4.29, m 60.9, CH 4.30, m 60.8, CH 4.29, m 29 67.8, CH 4.41,\nm 67.8, CH 4.42, m 67.8, CH 4.42, m 67.9, CH 4.42, m 30 20.5, CH 3 1.24, d (6.4) 20.5,\nCH 3 1.25,\nd (6.5) 20.5, CH 3 1.25, d\n(6.6) 20.5, CH 3 1.25, d\n(6.6) l - erythro -β-OH-Asp 31 172.4, C 172.5, C 172.9, C 172.5, C 32 57.9, CH 4.89,\nm 58.0, CH 4.87, m 58.0, CH 4.89, m 58.1, CH 4.87, m 33 74.2, CH 4.34,\nm 74.2, CH 4.32, m 74.3, CH 4.33, m 74.2, CH 4.33, m 34 175.3, C 175.3, C 174.8, C 174.8, C Ahmpa 35 178.2, C 178.3, C 178.2, C 178.2, C 36 44.3, CH 2.59,\nm 44.3, CH 2.58, m 44.3, CH 2.56, m 44.5, CH 2.58, m 37 12.5 1.20, d (6.9) 12.5 1.20, d (6.9) 12.5 1.20, d (6.8) 12.5 1.20, d (6.7) 38 75.9, CH 3.71, m 75.9, CH 3.71, m 75.9, CH 3.72, m 76.0, CH 3.71, m 39 48.2, CH 3.96,\nm 48.2, CH 3.97, m 48.3, CH 3.97, m 48.2, CH 3.97, m 40 16.7, CH 3 1.17, d (6.6) 16.7,\nCH 3 1.18,\nd (6.6) 16.8, CH 3 1.18, d\n(6.8) 16.8, CH 3 1.18, d\n(6.6) fatty acid\ntail 41 175.3, C 175.4, C 175.3, C 175.4, C 42 37.2, CH 2 2.19, t (7.5) 37.3,\nCH 2 2.18,\nt (7.5) 36.8, CH 2 2.20, t\n(7.5) 37.3, CH 2 2.19, t\n(7.5) 43 27.0, CH 2 1.62, m 27.1, CH 2 1.61, m 27.1, CH 2 1.65, m 27.1, CH 2 1.62, m 44 29.9, CH 2 1.32, m 30.3, CH 2 1.29–1.32, m 27.8, CH 2 2.08, m 30.1, CH 2 1.29–1.32, m 45 30.0, CH 2 1.33, m 30.5, CH 2 1.29–1.32, m 129.8, CH 5.36,\nm 30.5, CH 2 1.29–1.32, m 46 28.0, CH 2 2.06, m 30.7 a , CH 2 1.29–1.32, m 131.8, CH 5.40,\nm 30.7 a , CH 2 1.29–1.32, m 47 130.6, CH 5.35,\nm 30.7 a , CH 2 1.29–1.32, m 28.2, CH 2 2.04, m 30.7 a , CH 2 1.29–1.32, m 48 131.0, CH 5.35, m 30.8 b , CH 2 1.29–1.32, m 30.8, CH 2 1.33, m 30.7 a , CH 2 1.29–1.32, m 49 28.1, CH 2 2.04, m 30.8 b , CH 2 1.29–1.32, m 30.1, CH 2 1.32, m 30.3, CH 2 1.29–1.32, m 50 30.8, CH 2 1.35, m 30.8 b , CH 2 1.29–1.32, m 32.9, CH 2 1.30, m 33.1, CH 2 1.29, m 51 30.6, CH 2 1.33, m 30.5, CH 2 1.29–1.32, m 23.7, CH 2 1.31, m 23.7, CH 2 1.33, m 52 32.9, CH 2 1.30, m 33.1, CH 2 1.27, m 14.4, CH 3 0.90, t (6.9) 14.4, CH 3 0.90, t (6.9) 53 23.7, CH 2 1.32, m 23.7, CH 2 1.33, m 54 14.5, CH 3 0.90, t (7.0) 14.4, CH 3 0.90, t (7.0) a,b Unresolved carbon chemical shifts\nat δ C 30.6(5), 30.7(4), 30.7(6), 30.7(7), and 30.8(0)\nfor 2 and at δ C 30.6(5) and 30.7(4)\nfor 4 . The molecular formula of delftibactin D ( 2 ) was determined\nto be C 54 H 94 N 14 O 19 based\non positive HRESIMS m / z 1243.6892\n[M + H] + (calculated 1243.6892, 0.0 ppm), presenting 16\ndegrees of unsaturation. Thorough examination of the 1D and 2D NMR\ndata for compound 2 unveiled a close resemblance to the\nspectra of compound 1 , except for the absence of a double\nbond in the lipid tail for compound 2 . This was confirmed\nthrough the lack of olefinic signals evident in both the 1 H NMR and 13 C NMR spectra of compound 2 ,\nas well as the presence of two additional methylene signals at δ C 30.7 and 30.8 in the DEPT-Q NMR spectrum ( Table 1 and Figures S13–S15 ). Moreover, tandem mass spectrometry demonstrated\nthat each fragment containing the lipid tail in compound 2 exhibited an increase of 2 Da when compared to the equivalent fragment\nof compound 1 ( Figures S11 and S12 ). Based on these findings, compound 2 was determined\nto be a tetradecanoic acid analogue of delftibactin A. Delftibactin\nE ( 3 ) was obtained as a white powder\nand proved to have a molecular formula of C 52 H 88 N 14 O 19 which was confirmed through positive\nHRESIMS m / z 1213.6414 [M + H] + (calculated 1213.6423, −0.7 ppm), indicating 17 degrees\nof unsaturation. A thorough examination of the NMR data for compound 3 confirmed its resemblance to that of compound 1 . The sole disparity between compounds 3 and 1 lies in the length of the lipid tail, with compound 3 having a lipid tail two carbons shorter than that of compound 1 . This variation was corroborated through analysis of the\nHSQC cross peaks of the methylene groups in compound 3 ( Figure S21 ). Moreover, the DEPT-Q NMR\nspectrum of compound 3 revealed 12 carbon signals for\nits lipid tail, indicating a variance of two carbon atoms when compared\nwith the spectrum of compound 1 , which featured 14 carbon\nsignals ( Table 1 and Figure S20 ). Further support for this assignment\nis derived from the existence of lipid tail fragments in the MS/MS\ndata for compound 3 , which are each 28 Da smaller than\nthose in compound 1 ( Figures S17 and S18 ). The double bond’s position was assigned through\nthe observed HMBC correlations as with 1 . Cross peaks\nwere detected from the methylene protons (H-42, δ H 2.20) to the carbonyl (C-41, δ C 175.3) and to two\nmethylene carbons (C-43, δ C 27.1 and C-44, δ C 27.8) and from methylene protons (H-44, δ H 2.08) to carbons C-43 (δ C 27.1), C-42 (δ C 36.8), and C-45 (δ C 129.8) ( Figures S22 and S30 ). Based on these findings,\ncompound 3 was determined to be a 5-dodecenoic acid analog\nof delftibactin A. The molecular formula of delftibactin F ( 4 ) was proved\nto be C 52 H 90 N 14 O 19 through\npositive HRESIMS m / z 1215.6579 [M\n+ H] + (calculated 1215.6579, 0.0 ppm), implying 16 degrees\nof unsaturation. Thorough analysis of the 1 H NMR, 13 C NMR, and HSQC spectra of compound 4 (see Table 1 and Figures S27–S29 ) indicated high similarity to those\nof compound 2 . Nevertheless, a meticulous examination\nof the methylene groups in compound 4 revealed two fewer\ncarbons in comparison to compound 2 . Additional supporting\nevidence was obtained from the observed lipid tail fragments in which\nthe m / z values exhibited a reduction\nof 28 Da in compound 4 compared to those of compound 2 ( Figures S25 and S26 ). Based\non these findings, compound 4 was determined to be a\ndodecanoic acid analogue of delftibactin A. We attempted to\ndeduce the double-bond configuration of 1 and 3 through the J value of olefinic\nprotons. Unfortunately, overlapping chemical shifts render it challenging\nto accurately measure the coupling constants. Nevertheless, the cis double-bond configuration was unequivocally ascertained\nfrom the δ C values below 30 ppm (28.0 and 28.1 for 1 and 27.8 and 28.2 for 3 ) of the allylic carbons\nadjoining the double bond ( Table 1 ). 31 Gunstone and colleagues\ndemonstrated that the 13 C NMR chemical shift can be used\nto distinguish between cis and trans configurations of alkenoic fatty acids. 31 Following their rationale, we confidently identified the fatty acids\nin compounds 1 and 3 as ( Z )-tetradec-7-enoic acid and ( Z )-dodec-5-enoic acid,\nrespectively. Identification of Delftibactin C–F BGC A complete\ngenome of D. lacustris was obtained by sequencing\nusing a Nanopore MinION sequencer. Analysis of the D. lacustris genome using antiSMASH 27 revealed a hybrid\nPKS-NRPS pathway on the chromosome which the tool assessed as 100%\nsimilar to the previously reported delftibactin A BGC. In this proposal\nwe relied on the homology with the previously reported BGC that was\ninvestigated for its impact on the absolute configuration (e.g., to\nshow the role and functionality of the standalone Asp β-hydroxylase\nDelD 32 ). As we did not observe any products\nlacking the N -hydroxy or formyl groups, we hypothesize\nthat the N -hydroxylase DelL and hydroxyornithine\nformyltransferase DelP act on the tethered peptide chain. However,\nfurther work is needed to confirm this. We also propose that the condensation\ndomain of module six is a member of the dehydrating condensation domain\n(C modAA ) class reported by Patteson and co-workers, 33 here responsible for converting l -threonine\ninto the dehydrobutyrine (Dhb) residue. However, further enzyme or\nbioinformatic analyses will be required to confirm this proposal. Absolute Configuration We performed Marfey’s\nanalysis to determine the amino acid configurations in compound 1 . 35 , 36 Compound 1 was subjected\nto hydrolysis with 55% HI and subsequently treated with l -FDAA, following the methodology described in a prior study. 32 The resulting hydrolysate was compared with l -FDAA-derivatized amino acid standards with known configurations.\nThis analysis revealed the configurations of the residues within 1 as follows: both an l -ornithine and a d -ornithine, d -arginine, d -serine, and l -threonine ( Figures S31–S34 ). Regrettably,\nwe were unable to detect the hydroxyaspartic acid isomer in our Marfey’s\nreaction product. For delftibactin A, the configuration of this amino\nacid ( l - erythro isomer) was previously assigned\nby Reitz and co-workers based on a bioinformatic analysis of the responsible\nβ-hydroxylase (DelD), which we hypothesized would be the same\nin our compounds. 32 To validate this assignment,\nwe examined our genome’s delftibactin BGC from the antiSMASH\nanalysis. It has been reported that the β-hydroxylase ( delD ) gene in the delftibactin A BGC is responsible for\nthe incorporation of the l - erythro -OH-Asp\nstereoisomer by hydroxylation of the loaded aspartic acid during the\nbiosynthesis as a standalone enzyme. 32 An\nequivalent gene was observed in our BGC by antiSMASH; 32 alignment of this protein sequence with the original DelD\nshowed only one amino acid difference (a >99% pairwise identity,\nsee Table S1 ) in our D. lacustris genome. Based on this near-perfect homology, we propose that the\nconfiguration is conserved and l - erythro β-OH-Asp is also present in compound 1 . For the\nassignment of ornithine residues, our Marfey’s analysis indicated\nthe presence of both configurations, confounding the assignment of\nconfiguration for these residues. In tackling this ambiguity, we undertook\nfurther genomic investigations. Initially, we explored the delftibactins’\nBGC for epimerases. Regrettably, the only epimerase our annotation\nanalysis recognized was on module 9, where its presence and the presence\nof a “GGDSI” motif in the peptidyl carrier protein (a\nPCP E domain, the specialized version of this domain followed\nby epimerase domains 34 ) were consistent\nwith the epimerization of the serine residue to d -serine\n( SI Figure S35 ). No epimerase was identified\nthat could explain the d -ornithine. To delve deeper into\nour genomic data, we performed a multiple sequence alignment of the\namino acids between each pair of condensation domains in our detected\ndelftibactin BGC and the previously reported dual condensation (C Dual ) domains ( Figure S36 ). 29 , 37 , 38 We discovered four C Dual domains in our BGC; the first, on module 5, was predicted to act\non glycine, so it would not impact the absolute configuration. The\nsecond, on module 7, resolves the ambiguity of the ornithine moieties\nrevealed in the Marfey’s analysis and indicated that the d -configuration of ornithine belongs to the internal moiety\nrather than the terminal one (the ornithine that becomes cyclized).\nThe remaining C Dual domains, on modules 8 and 9, affirmed\nthe assignments of d -serine and d -arginine from\nour Marfey’s analysis, though we note that the serine could\nbe acted on by either the C Dual domain or the epimerase\ndomain, discussed above, as both enzymes are predicted to convert\nthe incorporated serine to d -serine. Based on this analysis\nand the homology with the previously reported BGC discussed earlier,\nwe proposed a biosynthetic analysis for delftibactins C–F ( Figure 2 ). Figure 2 Proposed biosynthetic\npathway of delftibactins C–F. Based\non homology to the previously reported BGC and the absence of observed\nprecursors, we propose the tailoring enzyme DelD (a standalone Asp\nβ-hydroxylase) acts on the tethered chain, as previously reported. 32 Based on the same reasoning, we also hypothesize\nthat the N- hydroxylase DelL and the hydroxyornithine\nformyltransferase DelP also act on the tethered chain, but further\nwork is needed to support this hypothesis. DelL and DelP could act\nafter the completion of the linear scaffold. Note, arrows representing\nopen reading frames are not drawn to scale. Domain notation: FAAL,\nfatty acid acyl ligase; ACP, acyl carrier protein; C, condensation;\nA, adenylation; PCP, peptidyl carrier protein (PCP E , specialized\nversion of this domain followed by epimerase domains containing the\n“GGDSI” motif, 34 also observed\nin the interaction with DelD 32 ); KS, ketosynthase;\nAT, acyl transferase; DHt, dehydratase; KR, ketoreductase; C Dual , dual condensation; E, epimerase; and TE, thioesterase. Delftibactin C–Metal Interaction To test the\ninteraction of delftibactin C ( 1 ) with metals, aliquots\nof 1 were treated with various metal salts, including\nAuCl 3 , CuCl 2 , and FeCl 3 , and then\nanalyzed by LCMS. A stable complex of the compound–iron adduct\nwas formed in FeCl 3 -treated samples, which was confirmed\nby the complete loss of protonated delftibactin C at m / z 1241.6736 [M + H] + and the formation\nof a new ion at m / z 1294.5855 [M\n– 2H + Fe(III)] + , which was consistent with the\nmolecular formula of the ferric–compound complex (C 54 H 91 FeN 14 O 19 + , calcd 1294.5851,\n0.3 ppm) ( Figures S37 and S38 ). Complete\nconversion of the apo form to the iron adduct when mixing a 1:1 molar\nratio of both compounds 1 and FeCl 3 is consistent\nwith the strong affinity of this molecule for iron predicted by its\nproposed role as a siderophore. 11 The formation\nof an iron adduct with 1 was further verified by the\nobserved maximum absorption at λ max of 441 nm absent\nin apo-delftibactin C. 39 , 40 Upon treatment of 1 with AuCl 3 , a series of unidentified ions emerged. We\nexamined these new ions, for example, a new mass at m / z 1099.5980, but were unable to convincingly annotate\nthese presumed oxidative degradation products of delftibactin C ( Figures S39 and S40 ). Furthermore, treatment\nof compound 1 with soluble ionic gold led to the formation\nof a gold precipitate (observed upon centrifugation of the sample\nprior to LCMS screening), a phenomenon previously associated with\ndelftibactin A ( Figures S37 and S39 ). This\nshows that compound 1 possesses a gold biomineralization\ncapability akin to that of delftibactin A, likely due to the presence\nof common structural features between the two compounds ( Figure S39 ). 11 Additionally,\nthe interaction of compound 1 with CuCl 2 revealed\nthe loss of this compound (at m / z 1241.6736) and the emergence of a series of small unidentified ions\nsuggestive of a potential for distinct chemistry with this metal ( Figure S37 ). A screen using the Mass Query Language\nsearch tool (MassQL) 41 revealed many copper\nadducts among these small ions ( Table S2 ). However, we again encountered difficulty in annotating these ions,\npotentially due to oxidative–reductive chemistry interactions\nbetween the metal center and fragments of compound 1 that\nmask the original structure. In summary, our thorough investigation\ninto the metabolomics and genomics of Delftia lacustris DSM 21246 has resulted in the identification and structural characterization\nof four new amphiphilic metallophores, which we name delftibactins\nC–F ( 1 – 4 ). These compounds\nexhibit an integration of either saturated or unsaturated fatty acid\ncomponents onto the delftibactin A peptide scaffold. The determination\nof their chemical structures was accomplished through NMR and MS/MS\nfragmentation techniques, while the absolute configuration of the\npeptide backbone was assigned using Marfey’s and bioinformatic\nanalyses. Additionally, compound 1 was tested for its\nstability in the presence of different metal salts, including iron,\ngold, and copper. These evaluations revealed the formation of an iron\nadduct of 1 . In the case of gold, the color change along\nwith gold precipitate formation indicated that this lipid-bearing\nanalog of delftibactin A retains the previously reported gold-biomineralizing\nability. 11 However, with copper, a series\nof unidentified small Cu-binding product ions were detected, hinting\nat different chemistry. In sum, compound 1 forms distinct\nproducts when reacted with different metal salts, which raises our\ninterest in this selectivity and its potential use in the bioremediation\nof heavy metals. Further investigation will be required to determine\nthe nature of these compounds’ chemistry with copper and measure\nthe capacity of these compounds for remediation of heavy metals in\npolluted environments."
} | 6,986 |
40095431 | PMC12019922 | pmc | 5,492 | {
"abstract": "Abstract Advances in tactile and haptic intelligence are driven by development of advanced funtional materials capable of translating subtle physical interactions into precise electrical signals. This study presents an innovative approach to enhancing touch sensitivity by incorporating 3D Zinc Oxide (ZnO) tetrapods into a piezoelectric polymer matrix. The distinctive 3D architecture of the ZnO tetrapods significantly improves the mechanical‐to‐electrical conversion efficiency, thereby amplifying the material's ability to detect fine tactile forces. We optimized the loading of ZnO tetrapods within a Polyvinylidene fluoride (PVDF) matrix, resulting in a highly responsive composite material for tactile sensing. It exhibited exceptional performance in detecting minute pressure variations, with just 4 wt.% tetrapods in the polymer matrix. Output voltage and current of the composite matrix increased from 4 V, 0.5µA to 19 V, 2.5µA respectively when the concentration of the ZnO tetrapods is gradually increased from 0–4 wt.% and decreased with further increase in tetrapod concentration. Comprehensive analysis and applications of this piezoelectrical materialconfirmed its robustness across a range of pressure conditions. The amplification of touch sensitivity and signal responsiveness underscores the potential of 3D ZnO tetrapods for tactile and haptic technologies.",
"conclusion": "4 Conclusion The ZnOtetrapod: PVDF piezoelectric nanogenerator (PENG) reported is robust, biocompatible, and multifunctional, capable of independently and simultaneously detecting external stimuli such as pressure under different conditions of mechanical loading, movements, and touch. It benefits from a simple yet very efficient fabrication process, critical for rapid prototyping and integration for capturing human‐machine interactions of physical nature. Coupled with quick responsiveness, mechanical flexibility and durability, it is suitable for a wide range of application domains. These applications include real‐time, continuious monitoring for long‐term data capture, with high‐precision, and reliable monitoring of human physical performance as well as applications in elderly age care and health management. Integration of such sensors in bionic devices is higly topical and it is suited to benefit people with bionic limbs or experiencing plantar issues. The combination of versatility and robustness highlights its potential in advanced wearable electronics, soft robotics, movement neuroscience and biomedical devices.",
"introduction": "1 Introduction In theera of digital revolution underlined by the internet of things (IoTs) and artificial intelligence, technologies that capture human‐machine interaction or machine to machine interaction are becoming prominent. [ \n \n 1 \n \n ] The rapid rise of wearable electronics in application domains such as e‐skins, soft robotics, intelligent clothing, healthcare devices, energy harvesting, and storage systems is defining technological prowess of advanced sensors in almost every aspect of modern technology. [ \n \n 2 \n \n ] For instance, e‐skins can be used in human‐robot interaction for tactile perception, which then expands to assistive devices and rehabilitation training systems. [ \n \n 3 \n \n ] Moreover, in pixelated form such devices can differentiate multiple stimuli simultaneously for tactile perception. Their mechanical flexibility, biocompatibility, and energy harvesting ability make them a perfect core of future electronics innovations [ \n \n 4 \n \n ] However, mechanical flexibility if not optimised for function, makes them prone to local material delamination or cracking under repeated tension and strain, compromising their reliability and longevity. [ \n \n 5 \n \n ] Additionally, the miniaturized and thin form factor of wearable electronics often puts desing limits on free space required for housing sizeable batteries. Such constraints on battery capacity necessitates frequent recharging, which significantly hampers its core function and overall user experience. [ \n \n 6 \n \n ] To address these issues, one can either enhance the battery performance by designing low‐power consuming devices or create a self‐powered mode by energy harvesting on the fly. [ \n \n 7 \n \n ] To address these constraints, self‐powered sensory systems, capable of harnessing energy from mechanical stimuli to power electronic devices while simultaneously responding to various external stimuli, has garnered significant attention, and are particularly desired for IoTs designed to meet Industry 5.0 goals. [ \n \n 6 \n , \n 8 \n \n ] \n Among others, the piezoelectric nanogenerators (PENGs) are promising candidates for converting mechanical movements such as tactile stimuli, [ \n \n 9 \n \n ] wind, [ \n \n 10 \n \n ] drops, [ \n \n 11 \n \n ] ocean waves, [ \n \n 12 \n \n ] into electrical energy by surface charging (triboelectric) mechanism. [ \n \n 6 \n \n ] The PENGs have unique advantages to be self‐powered and responsive to dynamic stress with high sensitivity, high accuracy, at enhanced piezoelectric coefficient. [ \n \n 13 \n \n ] Material‐based PENG investigations have undergone a lot of progress in gases, pressure, and temperature sensing. The state of art piezoelectric sensors are built out of conductive materials, substrates, polymers, and circuits. Over the past few years, many piezoelectric sensors have been reported with energy harvesting applications such as barium titanate (BaTiO 3 ), [ \n \n 14 \n \n ] aluminum nitride (AlN) [ \n \n 15 \n \n ] and lead zirconate titanate (PZT) [ \n \n 16 \n \n ] including many others. For advanced functional outreach of such devices, individual materials cannot satisfy the desired needs. Often the required functionalities are achieved by designing the multicomponent material by combining two or more materials in composite form. For example, the polymer nanocomposites out of fibrous BaTiO 3 reinforced in poly(vinylidene fluoride) (PVDF) nanocomposite is reported as a capable material for transducer applications. [ \n \n 17 \n \n ] The poly(dimethyl‐siloxane) impregnated with multiwalled carbon tubes nanocomposite has been utilized as flexible pressure sensors. [ \n \n 18 \n \n ] The conventionally used PZT based sensors lack the desired softness and flexibility and additionally, PZT is toxic in nature which is a big environmental concern. As an alternative, the zinc oxide (ZnO) nanostructures incorporated cellulose fiber‐based polymer nanocomposite material is reported as a good candidate for strain sensing. [ \n \n 19 \n \n ] In the same line of thought, the electrospun piezoelectric nanocomposite fibers fabricated from ZnO nanorods and PVDF polymer have demonstrated a great strain sensing ability and are already being used for real‐time sensing of internal micro pressure in arteries. [ \n \n 20 \n \n ] \n As an inorganic material, ZnOis a very versatile candidate for nanostructuring because of its hexagonal‐wurtzite crystal structure ( c ‐axis as fastest growth axis). The non‐centrosymmetric crystal structure in wurtzite nicely facilitates the ZnO nano‐microstructures with piezoelectric properties. The Zn 2+ and O 2− terminated polar surfaces along the c ‐axis make the surface of ZnO nanostructures to be functionally very active which is relevant for many sensing applications. [ \n \n 21 \n \n ] ZnO exhibits a wide bandgap of 3.37 eV with an exciton binding energy of 60meV and almost any imaginary nanostructure can be grown easily which gives rise to various applications. [ \n \n 22 \n \n ] With their high surface‐to‐volume (S/V) ratio, typical n‐type conductivity, UV‐sensitive bandgap, and terminated polar surfaces, the ZnO micro and nanostructures offer significant promises for nanoelectronics and sensor development. Their active surface offers significant interaction area with polymers and hence these micro and nanostructures have been used as novel filler candidates in the polymers. [ \n \n 23 \n \n ] The ZnO micro and nanostructures with various ZnO morphologies have been synthesized and used as novel inorganic fillers in polymers to fabricate advanced piezoelectric nanocomposites. [ \n \n 24 \n \n ] The ZnO morphologies include nanoparticles, nanorods, nanowires, nanotubes, nanopillars, nanoflowers, etc. in the polymer as piezoelectric nanocomposites. [ \n \n 25 \n , \n 26 \n \n ] The 1D morphology, i.e., nanorod and nanowire of ZnO is the most explored system with respect to piezoelectric performance [ \n \n 25 \n \n ] and they have been used as filler component to enhance the overall piezoelectric response of nanocomposites. [ \n \n 27 \n \n ] While using 1D ZnO nanostructures as fillers in the polymers, uniform dispersion and alignments of fillers inside the composite is a big challenge. In a non‐homogeneous filler distributed composite, they align differently which impacts the overall piezoelectric performance of the composite. The role of appropriate filler becomes very crucial for improving the piezoelectric performance of the composite. [ \n \n 28 \n \n ] There exists a novel 3D geometry of ZnO micro‐and nanostructure, in the form of tetrapod which offers excellent avenues to upgrade the piezoelectric performance of the composites, if used as filler. The ZNO tetrapods are built out of four 1D wurtzite micro‐nanorods in the form of 3D morphology where all the arms are interconnected via a central crystalline core at an angle of ≈110° with respect to each other. [ \n \n 29 \n \n ] The tetrapod geometry offers unique advantage in the sense, that irrespective of how they are handled, they enquivocally form a self‐assembled highly porous 3D architecture. Their arms prohibit their agglomerations in the polymers and hence a well‐dispersed composite system can be designed. Due to this feature, these ZnO tetrapods have already been utilized in many composite engineering applications. [ \n \n 24 \n \n ] Since ZnO tetrapods are built out of four wurtzite arms, they exhibit interesting piezoelectric responses under the impact of pressure/force. The force on one arm bends the other three arms in other directions accumulating an overall piezoelectric response. [ \n \n 30 \n \n ] Additionally, under pressure, the strained central core improves the carrier density, thereby improving the electrical conductivity. [ \n \n 31 \n \n ] These tetrapods can be novel piezoelectric filler components to improve the overall piezoelectric performance of a composite by embedding them in the appropriate polymer matrix. These ZnO tetrapods are extremely eco‐friendly/biocompatible and also can be produced in large quantities by very simple methods. In short, ZnO tetrapods are unique and special due to their 3D morphology and have four needle or rod‐shaped wurtzite‐structured legs or arms. [ \n \n 29 \n \n ] \n While PVDF, a semi‐crystalline polymeric‐based piezoelectric material, has gained lots of interest for practical piezoelectric applications due to its good flexibility and biocompatibility. [ \n \n 32 \n \n ] Although, PVDF exhibits five different crystalline polymorphs based on the polymer chain structure: α, β, γ, δ, and ε. The polar β phase was reported to exhibit the highest piezoelectricity due to the very large dipole moment in the structure. [ \n \n 33 \n \n ] Inspired by the significant abilities of PVDF polymer, we aimed to use it as the host matrix material for ZnO tetrapods. In this work, we present the design, fabrication and performance of a highly sensitive and flexible electronic skin (e‐skin) leveraging piezoelectricity through compositional engineering of PVDF and ZnO tetrapods. By employing a straightforward and cost‐effective solution casting technique, we have significantly enhanced the piezoelectric properties by achieving performance levels nearly comparable to those of the more commonly used piezoelectric materials. This enhancement is attributed to the optimal ratio and compositional engineering with inorganic ZnO tetrapods fillers, which effectively induce spontaneous polarization in PVDF. Our work offers a low‐cost, high‐performance piezoelectric nanogenerator (PENG) that serves as a highly flexible and intelligent e‐skin, with potential applications in advanced healthcare and other cutting‐edge technologies.",
"discussion": "3 Results and Discussion 3.1 Structural Studies The distribution of ZnO tetrapods in PVDF matrix was determined by SEM results. Figure 1a represents bare ZnO tetrapods and Figure \n \n 2 a–f is its comparison with ZnO tetrapod doped films in the PVDF polymer matrix. From the SEM results, we can conclude that pure PVDF films without any impregnated ZnO tetrapod sample have an amorphous polymeric structure with a randomly distributed polymer chain cluster. Adding 0.5% tetrapods in the PVDF matrix results in tetrapods scarcely distributed in the PVDF matrix. When the tetrapod concentration was increased to 1% and 2%, the higher concentration of ZnO tetrapods was seen in the polymer matrix and still it appeared to be distributed uniformly. When the concentration was increased to 4%, we can see agglomeration of particles started to dominate as shown in Figure 2e . At a concentration higher than this which is 6% (Figure 2f ) ZnO tetrapods dominate the matrix while also decreasing the piezoelectric performance as per the output voltage measurement, which will be discussed in the section on energy harvesting studies. The ZnO‐ tetrpod/PVDF composite films are shown in the photographs (Figure 2f ). A slight variation in film thickness was observed as ZnO tetrapod doping increased. However, the thickness does not affect piezo performance as it is driven by surface charges and it is in good agreement with literature. [ \n \n 36 \n \n ] \n Figure 2 a–f) Top‐down surface SEM images of pure PVDF with 150 µm scale a) and comparison with ZnO‐Ts embedded within the PVDF matrix of the same scale. The addition of ZnO‐Ts to pure PVDF results in changes in the polymer matrix leading to the distribution of tetrapods in the matrix ranging from b) 0.5%, c),1% d) 2%, e) 4%, f) 6%. Inset the photographs of fabricated composite films. 3.2 Discussion of Piezoelectric Properties The piezoelectric properties of PVDF are closely tied to its crystalline phases, particularly the β‐phase, which is known for its high piezoelectric activity due to the alignment of molecular dipoles. The processing conditions used in this study are consistent with those known to promote the formation of the β‐phase in PVDF. [ \n \n 37 \n \n ] Based on these prior studies, [ \n \n 38 \n \n ] it is reasonable to infer that the β‐phase is predominant in our PVDF films, contributing to the observed piezoelectric performance. [ \n \n 39 \n \n ] The inclusion of ZnO tetrapods in the composite films further enhances piezoelectricity, likely due to their unique tetrapodal structure, which has been shown to improve mechanical stress distribution and augment the overall piezoelectric response. [ \n \n 40 \n \n ] This observation is in good agreement with literature precedences that have demonstrated that 3DZnO tetrapods can significantly boost the piezoelectric properties when incorporated into polymer matrices. [ \n \n 24 \n \n ] \n The observed piezoelectric output voltage of the bare PVDF aligns well with the expected performance of β‐phase PVDF films. [ \n \n 41 \n \n ] The enhanced piezoelectric response can be attributed to mechanisms well‐documented in the literature, wherein the β‐phase of PVDF and the unique structure of ZnO tetrapods play pivotal roles. [ \n \n 42 \n \n ] Our findings suggest that the processing conditions likely facilitated the formation of the β‐phase in PVDF, while the zinc oxide tetrapods contributed significantly to the overall piezoelectric effect. [ \n \n 31 \n \n ] . 3.3 Intrinsic Mechanism of Piezoelectricity in ZnO Tetrapods ZnO tetrapods are known for their inherent piezoelectricity due to their non‐centrosymmetric wurtzite structure. [ \n \n 24 \n \n ] When embedded in a piezoelectric polymer, the high dielectric constant of ZnO can enhance the alignment of dipoles in the polymer matrix during poling. [ \n \n 43 \n \n ] This improved alignment leads to stronger polarization and higher piezoelectric coefficients in the composite. These are also active fillers that contribute to the overall piezoelectric output by generating an electric charge when subjected to mechanical deformation. [ \n \n 23 \n \n ] Effective load transfer enhances the deformation‐induced charge generation in the ZnO, which contributes to the composite's overall piezoelectric performance. ZnO tetrapods can act as charge traps and facilitate the redistribution of charges within the composite. [ \n \n 44 \n \n ] Their unique tetrapodal structure provides a multidirectional response and enhances the overall electromechanical properties of the composite, making it suitable for high‐performance piezoelectric applications. [ \n \n 30 \n \n ] \n 3.4 PENG Energy Harvesting Studies The PENG studies of Zn‐T doped PVDF samples reveal the energy harvesting potential of composite films. The packaged device with electrodes and the PDMS is depicted in the above Figure \n 3 a . The electrical connections were made by copper wires to make a complete PENG device. The scheme shows the working principle of PENG. When external force is applied, it leads to a change in symmetry of charges which in turn leads to consequent flow of electrons to the external circuit. In summary, the output voltage is just a reflection of the external force applied to the PENG device. This forms the foundation of PENG based sensors. The composite films can be bent to any angle and hence are very sensitive to any physical deformation. We used a linear motor to apply a mechanical force, following which a potential is generated between the two electrodes in the PENG device, as evidenced by generation of positive and negative potentials. When an external load is available, the electrons flow through this path and are measured via an electrometer. The complete stoppage of electrons occurs when the applied force is released as a result piezoelectric potential vanishes and electrons flow in opposite directions (Figure 3b ). Figure 3 PENG device measurement results. a)The device structure of the piezoelectric nanogenerator. b) Schematic diagram of the measuring mode used for sensing and photograph of fabricated nanogenerator device. The P denotes pressure applied with different frequencies via a linear motor. c) Output circuit voltage variation as a function of the ZnO‐Ts concentration in the PVDF matrix. The highest output voltage was obtained for 4% ZnO‐Ts‐doped samples. d) Comparison of voltage output of pristine PVDF and 4% ZnO‐Ts device. e) Short circuit current output as a function of different concentrations of ZnO‐Ts‐doped PVDF composite films. f) Output voltage obtained from 4% ZnO‐Ts device at different frequencies. Initially, we optimized the concentration of ZnOtetrapodsby varying it from 0.5% to 6%. The PENGs were fabricated using the scheme shown above and subjected to interactions with a linear motor operating at at 4Hz. The open‐circuit output voltage/short‐circuit current of the PENGs exhibited an increase from 4V/0.3 to ≈20V/ 2µA with an increase in ZnO tetrapod intake up to 4 wt.% (Figure 3c,e ). However, the output characteristics decreased substantially to 14V/1.5 µA with increased tetrapod concentration at 6% wt. The enhancement in output characteristics with increased tetrapod concentration correlates with the higher concentration of piezoelectric ZnO in the PVDF matrix. The 4% ZnO‐ tetrapod device when compared with pristine PVDF shows 450% increase in output voltage which can be used in real‐time energy harvesting applications (Figure 3d ). The possible explanation for increased piezo response with an increase in small ZnO tetrapod concentration is due to a change in the number of attractive atomic interactions between PVDF‐ZnO. [ \n \n 44 \n \n ] The decline in output performance beyond 4 wt.% is attributed to Maxwell–Wagner interfacial polarization due to the presence of PVDF and ZnO as two different phases in the composite. [ \n \n 43 \n \n ] The higher concentration of ZnO tetrapods within the polymer matrix leads to an increased number of interfaces with PVDF matrix, promoting Maxwell–Wagner interfacial polarization, consequently enhancing the overall dielectric constant of the composite. [ \n \n 45 \n \n ] Another reason for decreased output voltage with increased concentration can be due to the agglomeration of tetrapods reflected in the SEM studies. The output voltage on the 4% wt. PENG device was tested under different frequencies (2 Hz, 3 Hz, 4 Hz, 5 Hz, 6 Hz). Under fixed frequency of 5Hz gave the highest output voltage of 17V (Figure 3f ). The frequency‐based voltage output showed a decrease in output voltage after 5Hz due to a reduction of dipolar contribution at high frequency. The results given by the 4 wt.% device show the best energy harvesting results and have been used for further applications in this work. The mechanical behavior of 4% ZnO tetrapod composite film was calculated and gave a Young's modulus of 3.60 MPa and stretched up to 12.94% of its original length before it broke even ( Figure \n \n 4 \n ). The initial linear portion represents the elastic deformation, while the subsequent curve shows plastic deformation up to the failure point. The modulus of both the bare and 4% ZnO tetrapod films show that the inclusion of the tetrapods in the matrix enhances the flexibility and toughness and pushes the films into the plastic region rather than snapping at the front. The photograph inset shows that the films can be bent to any angle, demonstrating optimum flexibility and toughness. As demonstrated in Figure 4b , the output characteristics of the fabricated PENG were evaluated over again after 1 month. The results indicated that there was no significant change in the output characteristics. These robust properties make the films suitable for capturing physical interactions of different kinds. such as. Additionally, a switching polarity test was conducted on a PENG fabricated with 4 wt.% ZnO tetrapods in PVDF composite film. The results, illustrated in Figure 4c show that reversing the connection yielded outputs with identical amplitudes but opposite signs. This confirms that the output is attributable to the piezoelectric effect rather than any instrumental artifacts or triboelectric contributions. [ \n \n 46 \n \n ] The comparison table shown below outlines the fabricated PENG device produces remarkably high performance with an optimal quantity of ZnOtetrapods ( Table \n \n 1 \n ). Figure 4 The stress‐strain curve illustrates the mechanical behavior of the 4% ZnO tetrapod‐PVDF film in comparison with pristine PVDF films. The Young's modulus of 3.60 MPa indicating its relative flexibility whereas the bare PVDF material gives a modulus of 12.78 MPa. The photograph embedded shows the stretching, bending, and twisting of these composite films. b) Device stability test showing open circuit voltage stable after 1 month without any considerable change. c) Switching polarity test gives an open‐circuit output voltage of PENG with 4 wt.% of ZnO tetrapod in PVDF with Forward connection d) Reverse connection. Table 1 Comparison with previously reported zinc oxide‐based piezoelectric nanogenerator. Various works reported on PENG Fabrication technique Reported voltages Refs. Flexible Pressure Sensor Based on Tetrapod‐Shaped ZnO‐PDMS Spin coating 0.4 V [ 47 ] PVDF–ZnO seeds composite fibers membranes Electrospinning 1.12 V [ 48 ] PVDF/ZnO (15 wt.%)/CNT Solution casting 1.32 V [ 49 ] Electrospun PVDF‐HFP/Co‐ZnO Nanofibers Electrospinning 2.8 V [ 50 ] PVDF–20% ZnO nanorods Electrospinning 3.6 V [ 51 ] ZnO (nanoflower)/PVDF/PDMS Solution casting 3.16 V [ 52 ] Zinc oxide Nanoflower‐PDMS Solution casting 4.2 V [ 53 ] Piezoelectric properties of zinc oxide/iron oxide filled PVDF fibers Electrospinning 5.9 V [ 54 ] ZnO nanorods in PVDF matrix Solution casting 14.6 V [ 46 ] ZnO NWs @chopped short carbon fiber (CF)/PVDF composite piezoelectric film Drop casting followed by annealing 14.9 V [ 55 ] Flexible ZnO microrods/PVDF composite films Casting followed by phase inversion 15.2 V [ 56 ] PVDF‐MWCNT (0.1 wt.%)‐ZnO (15 wt.%) Drop casting followed by annealing 22 V [ 57 ] Zinc oxide Tetrapods (4 wt.%)/PVDF composite films Solution casting 19 V This work John Wiley & Sons, Ltd. 3.5 Energy Harvesting Applications The circuit diagram for the connection of PENG device to drive a portable calculator by charging a capacitor is shown below ( Figure \n \n 5 a ). The output voltage of PENG was rectified using a bridge rectifier to charge the capacitor. Here, the rectified voltage of ≈22 V was obtained from the proposed PENG device (Figure 5b ). The ZnO tetrapod loaded PENG device was suitable to charge a capacitor of 2.2 µF. It was observed that the device can easily charge the capacitor to drive low‐power consuming electronic devices. The charging and discharging curve of 2.2µF (Figure 5c ) can easily charge the capacitor up to 3V in 25 s. The image of calculator being directly driven by this PENG device is shown in Figure 5d . A live recording of self‐powered calculation via PENG deice is also shown in Supplementary Video S1 (Supporting Information). Figure 5 Waveform of electrical responses from self‐powered nanofibrous PENG. a) The circuit diagram for connecting PENG with a bridge rectifier and with 2.2 µF capacitor. b) The rectifying voltage with 4% ZnO‐ tetrapod devices. c) The capacitor charging and discharging of the PENG device. d) Photograph of self‐powered calculator driven by the PENG device. 3.6 Piezoelectric Sensing Applications In the previous sections, it was observed that the fabricated PENG with 4% wt. ZnO‐tetrapod:PVDF showed the best output characteristics. Such piezoelectric devices are suitable for applications in tactile and force sensing. The piezoelectric composites have been a relatively new technology. It can serve as haptic sensor technology, where energy would be harvested from simple body movements and sensations. [ \n \n 58 \n \n ] The ability to simultaneously detect static and dynamic responses is crucial for effective human motion detection and recognition. [ \n \n 46 \n \n ] Human motion can bring about energy from mechanical stimuli. [ \n \n 59 \n \n ] We used it to measure output generated from finger tapping that generated different voltage responses to matchr single to multi finger interactions ( Figure \n \n 6 a ). Each finger pressed upon the device gives a typical voltage response for that particular load on the PENG device. As the number of fingers pressed on the device is increased, the output voltage also scales high. This confirms that surface area is also a parameter that can contribute to the voltage readings. The waveforms are observed for their signal duration, intensity, and pattern. Typical waveform responses generated upon pressure are shown in Figure 6b , which carried out a fast response time of 20 ms and an average recovery time of 30 ms. The PENG exhibits excellent stability and sensitivity, accurately reflecting both the frequency and magnitude of external stimuli. In Figure 6c , the calibration curve with a 1kg load cell shows a linear relationship between force applied and voltage generated. The output voltage is directly proportional to the force applied. The speed of the load cell for this calibration was 280mm s −1 while the surface area of the probe was 1cm 2 (Video S2 , Supporting Information). The previous experiments had a surface area of 6 cm 2 with speed of 0.4 m s −1 . A larger surface area allows higher cumulative dipole alignment, leading to a more substantial voltage output. This increased surface engagement enhances the device's overall sensitivity, enabling more efficient conversion of mechanical stress into electrical energy. At higher speeds, the mechanical deformation of the PENG is more rapid, increasing the rate of dipole alignment within the piezoelectric material. The sensitivity of the device is 0.13 V/N considering the surface area and the speed of the load cell as a crucial parameter. Thus this device shows exceptional sensitivity in low‐pressure ranges allowing it to detect even the slightest deformations. In summary, tactile sensing can be effectively achieved by using the proposed PENG. Figure 6 Motion detection and pressure sensing via PENG based on a) finger pressing to detect varied responses with a number of fingers. b) The response recorded of the PENG device was 20ms and the recovery time was 30ms. c) The calibration curve of the piezoelectric nanogenerator via force sensor.\n\n3.2 Discussion of Piezoelectric Properties The piezoelectric properties of PVDF are closely tied to its crystalline phases, particularly the β‐phase, which is known for its high piezoelectric activity due to the alignment of molecular dipoles. The processing conditions used in this study are consistent with those known to promote the formation of the β‐phase in PVDF. [ \n \n 37 \n \n ] Based on these prior studies, [ \n \n 38 \n \n ] it is reasonable to infer that the β‐phase is predominant in our PVDF films, contributing to the observed piezoelectric performance. [ \n \n 39 \n \n ] The inclusion of ZnO tetrapods in the composite films further enhances piezoelectricity, likely due to their unique tetrapodal structure, which has been shown to improve mechanical stress distribution and augment the overall piezoelectric response. [ \n \n 40 \n \n ] This observation is in good agreement with literature precedences that have demonstrated that 3DZnO tetrapods can significantly boost the piezoelectric properties when incorporated into polymer matrices. [ \n \n 24 \n \n ] \n The observed piezoelectric output voltage of the bare PVDF aligns well with the expected performance of β‐phase PVDF films. [ \n \n 41 \n \n ] The enhanced piezoelectric response can be attributed to mechanisms well‐documented in the literature, wherein the β‐phase of PVDF and the unique structure of ZnO tetrapods play pivotal roles. [ \n \n 42 \n \n ] Our findings suggest that the processing conditions likely facilitated the formation of the β‐phase in PVDF, while the zinc oxide tetrapods contributed significantly to the overall piezoelectric effect. [ \n \n 31 \n \n ] ."
} | 7,557 |
22967216 | PMC3495685 | pmc | 5,494 | {
"abstract": "Background A new strain of Geobacter sulfurreducens , strain KN400, produces more electrical current in microbial fuel cells and reduces insoluble Fe(III) oxides much faster than the wildtype strain, PCA. The genome of KN400 was compared to wildtype with the goal of discovering how the network for extracellular electron transfer has changed and how these two strains evolved. Results Both genomes were re-annotated, resulting in 14 fewer genes (net) in the PCA genome; 28 fewer (net) in the KN400 genome; and ca. 400 gene start and stop sites moved. 96% of genes in KN400 had clear orthologs with conserved synteny in PCA. Most of the remaining genes were in regions of genomic mobility and were strain-specific or conserved in other Geobacteraceae , indicating that the changes occurred post-divergence. There were 27,270 single nucleotide polymorphisms (SNP) between the genomes. There was significant enrichment for SNP locations in non-coding or synonymous amino acid sites, indicating significant selective pressure since the divergence. 25% of orthologs had sequence differences, and this set was enriched in phosphorylation and ATP-dependent enzymes. Substantial sequence differences (at least 12 non-synonymous SNP/kb) were found in 3.6% of the orthologs, and this set was enriched in cytochromes and integral membrane proteins. Genes known to be involved in electron transport, those used in the metabolic cell model, and those that exhibit changes in expression during growth in microbial fuel cells were examined in detail. Conclusions The improvement in external electron transfer in the KN400 strain does not appear to be due to novel gene acquisition, but rather to changes in the common metabolic network. The increase in electron transfer rate and yield in KN400 may be due to changes in carbon flux towards oxidation pathways and to changes in ATP metabolism, both of which indicate that the overall energy state of the cell may be different. The electrically conductive pili appear to be unchanged, but cytochrome folding, localization, and redox potentials may all be affected, which would alter the electrical connection between the cell and the substrate.",
"conclusion": "Conclusions The KN400 strain of G. sulfurreducens was isolated from a fuel cell that was run for several months poised at increasingly lower potentials. Its 16S rRNA genes are identical to those in the well-studied PCA strain, but the quantity of nucleotide polymorphisms and their strong enrichment at silent sites, as well as the diversity and distribution of genes that lack orthologs between the genomes all suggest the strains have been subject to substantial selective pressure since their divergence. Further study of strain variation in G. sulfurreducens – these two are the only strains that have been sequenced – and the analysis of more closely related genomes would help to reconstruct a detailed evolutionary history, particularly of the genomic mobility seen in this species. The KN400 strain has a number of favorable characteristics that make it the preferred strain to grow in a microbial fuel cell. The first is speed of electron transfer: KN400 oxidizes the donor and transfers the resulting electrons to the electrode faster than PCA [ 5 ]. Analysis of the differences between the two genomes suggests (and eliminates) several explanations for this phenotype. KN400 does not contain additional genes that PCA lacks which are predicted to be involved in donor oxidation, nor does it contain any large sequence changes to the enzymes for acetate oxidation via the TCA cycle. However, there are significant changes to two anaplerotic enzymes that could shift the carbon flux in the KN400 strain from biomass production towards more rapid oxidation of acetyl-CoA. If these two enzymes have lower activity in KN400, the TCA cycle may complete full turns more often, and this would increase the fraction of acetate that is oxidized for respiration. Interestingly, the increased respiration rate does not lead to increased cell growth in the KN400 strain [ 5 ], indicating that there may be important changes in ATP synthesis or availability. Previously, a PCA strain engineered with an unproductive ATP sink exhibited a similar phenotype [ 31 ]. In the KN400 genome, a very broad range of ATP-dependent enzymes were more likely to have sequence changes, and the phosphate sensor, transporter and several phosphate regulators were all also changed. Thus, the phosphate levels, the ATP:ADP ratio, and the energy state of the cell may be different in the KN400 strain relative to the PCA strain, which could result in broad metabolic differences. The second favorable characteristic of KN400 when grown in a microbial fuel cell is its highly conductive biofilms [ 6 ] from which low-potential electrons can be harvested. Analysis of the differences between the two genomes also suggests (and eliminates) factors that may contribute to this phenotype. Though pili are the conductive material in KN400 biofilms, there are no differences in the pilin subunit, biogenesis genes, nor the PilR transcriptional regulator between the strains. However the cell-electrode connection is also mediated by c -type cytochromes, and there are substantial differences between the strains in these proteins. The sequences of both cytochromes and of the channel proteins that affect their localization have substantial changes, most notably in the OmcS cytochrome that is physically associated with the pili. In addition, there are changes to several clusters of exopolysaccharide biosynthesis genes in KN400 which may further affect cytochrome localization and general conductivity. Excellent conservation of heme-binding sites despite sequence changes indicates that cytochrome redox potential changes also warrant further investigation in the KN400 strain. Finally, sensing and response to global redox potential and metal homeostasis may have significant differences in KN400 due to changes in proteins involved in the transport and metabolism of copper, of sulfur, and of metals generally. These types of changes would have a broad impact on electron transport in the species.",
"discussion": "Results and discussion Reannotation of the G. sulfurreducens strains KN400 and PCA genomes As published, the G. sulfurreducens strain PCA genome was 3.8 Mb with 3466 open reading frames (ORFs) [ 8 ] and the G. sulfurreducens strain KN400 genome was 3.7 Mb with 3356 ORFs [ 7 ]. Because the two genomes were sequenced and annotated several years apart using different methods, we re-annotated both genomes, making several types of corrections in order to assure that comparisons between the two were valid. ORF predictions, start and stop sites of the genes, and functional predictions were compared and reconciled using identical methods on both genomes (Additional file 1 : Table S1 and Additional file 1 : Table S2). After the re-annotations, the strain KN400 genome had 3328 ORFs (Additional file 1 : Table S1), and the strain PCA genome had 3432 ORFs (Additional file 1 : Table S2). These re-annotations were deposited in the National Center for Biotechnology Information genome database under the accession numbers of AE017180.2 for PCA and NC_017454 for KN400. A summary of the basic characteristics of the genomes is given in Table 1 . Table 1 Characteristics of the re-annotated G. sulfurreducens genomes strain KN400 strain PCA genome size (bp) 3714272 3814128 open reading frames 3328 3432 G + C content (%) 61.3 60.94 rRNA operons 2 2 plasmids 0 0 Whole-genome comparison of strain KN400 to strain PCA Orthologs, proteins predicted to have the same function in both genomes, were identified using a combination of whole-genome alignment and all-versus-all protein sequence alignments. A whole-genome nucleotide alignment of the PCA and KN400 genomes showed that they were syntenic, with no large-scale rearrangements or inversions (Additional file 2 : Figure S1). Orthologs were identified for 3180 of the 3328 protein-coding genes in the KN400 genome (Additional file 1 : Table S1). A whole-proteome comparison identified orthologs for 3194 genes (Additional file 1 : Table S1). The two methods agreed for 3166 (99.6%) of the pairs, with the genome method identifying 14 orthologs with identical sequences: eight transposases, two cytochromes, and a translation elongation factor, as well as three orthologs under 100 amino acids in length (Additional file 1 : Table S1).The proteome method identified 28 orthologs with low sequence similarity or alignment over a short region of the sequence (Additional file 1 : Table S1). For the analysis of polymorphisms between orthologs presented below, we included orthologs identified by only one method if they aligned over at least 50% of the length of the longer protein, and had a sequence identity of at least 30%. In total, 3192 of the 3328 ORFs in the KN400 strain genome (96%) have orthologs in the PCA strain genome (Additional file 1 : Table S1 and Additional file 1 : Table S2). The relative locations of the conserved genes are largely preserved between the genomes (Additional file 2 : Figure S1). Genes unique to the KN400 strain There were no orthologs in the PCA strain for 126 of the ORFs (3.8%) in the KN400 strain genome (Figure 1 , Additional file 1 : Table S3). In order to better to describe these genes and their evolutionary history, their locations and characteristics were mapped and their sequences were compared to proteins from the 10,291 organisms in the Reference Sequence database from the National Center for Biotechnology Information [ 9 ]. Figure 1 G. sulfurreducens strain KN400 genome differences compared to strain PCA. Inner ring: the number of non-synonymous (those that affect protein sequence) single nucleotide polymorphisms (SNP) per gene. Line scale = 25 SNP Center ring: the total number of SNP per gene. Line scale = 25 SNP. Outer ring: Gene-scale differences in orthologs. Genes with only silent mutations are green, those that have less than 12 non-synonymous SNP per kb (within two standard deviations of the mean) are light red, and those with at least 12 non-synonymous SNP are dark red. Identical genes are grey. Those genes that lack orthologs entirely are black Seventeen of these 126 ORFs had no significant similarity to any gene in another organism, six were most similar to proteins in the PCA strain, and 37 had highest similarity to proteins in Geobacteraceae species other than PCA (Additional file 1 : Table S3). The remaining ORFs were most similar to genes from a variety of phylogenetically diverse organisms including Desulfovibrio , Syntrophobacter , Pseudomonas , and Vibrio species (Additional file 1 : Table S3), suggesting that there are diverse evolutionary histories for these genes. The 126 genes are spread throughout the KN400 genome, the majority in clusters together (Additional file 2 : Figure S1). In total, there are 18 regions in the KN400 genome where at least two consecutive genes have no ortholog in the PCA genome (Additional file 1 : Table S4). Eight are bordered by or contain transposase or integrase genes, three are bordered by tRNA genes, and one is bordered by a conserved repeated nucleic acid sequence (Additional file 1 : Table S4) – indicating that these regions may be or once were mobile genetic elements [ 10 ]. One strain-specific region, found at 466250–483475 in the KN400 genome (genes KN400_0440-KN400_0451), is inserted relative to PCA just downstream of a tRNA gene, between the orthologs to GSU0465 and GSU0466 (Additional file 1 : Table S1). This region encodes a phage integrase and replisome organizer as well as a restriction/modification system. The two genes for the restriction/modification system (KN400_0449 and KN400_0451) are similar to genes from Meiothermus ruber , and are not found in any other Geobacteraceae , suggesting that this region may have been acquired by lateral gene transfer. Another KN400 strain-specific region is found between 3479100–3485200. Here, KN400_3199-KN400_3206 are found between the orthologs to GSU3265 and GSU3267 (Additional file 1 : Table S1). The genes include five conserved hypothetical proteins and three proteins involved in metal transport and usage: a metal-transporting ATPase, a metal-dependent phosphohydrolase, and a hybrid iron transport/cell signaling protein. All of these genes are most similar to those found in other Geobacteraceae and Deltaproteobacteria (Additional file 1 : Table S1), suggesting that they might have been lost in the PCA strain genome. In addition to regions of relative insertion in KN400, there are others where, between regions of excellent conservation between the two genomes, there is a stretch of sequence for which there is little or no similarity. For example, KN400_1871 and GSU1849 are orthologs, and KN400_1883 and GSU1857 are orthologs, but the region between them has low sequence similarity (Additional file 2 : Figure S2, Additional file 1 : Table S1). However, in both strains, the genes encode products involved in exopolysaccharide biosynthesis (Additional file 1 : Table S1; Additional file 1 : Table S2). This may be a region where mutation accumulation was relatively unconstrained, and these genes are attractive targets for studies of differences in the biofilms formed by strains PCA and KN400. A few of the genes found in the KN400 genome but not the PCA genome are isolated, not in the 18 clusters described above. One of these that may have a substantial effect on metabolism is the catalase. The KN400_2748 gene encodes a KatE catalase [ 11 ], while the catalase of G. sulfurreducens strain PCA, GSU2100, encodes a KatG-type [ 11 ] of no sequence similarity. While each strain encodes only one of the two catalases, there is evidence that each once encoded the other. KN400 has a region with nucleic acid similarity to the katG gene (2278624–2280808 KN400), but a single-base deletion results in a frameshift halfway through it. In the PCA genome, the region 3089478–3089600 aligns with the 5’ end and the 3’ end of the katE gene in KN400, though 90% of the gene has been deleted. Both KatE and KatG detoxify reactive oxygen species, but their mechanism and expression are different [ 11 ]. Response to oxidative stress is especially important in Fe(III)-reducing, obligate anaerobes like Geobacter sulfurreducens – reactive oxygen species cause DNA damage and disable many respiratory enzymes, and the presence of ferrous iron can create more of these compounds [ 12 ]. A difference in response to oxidative stress between the strains could affect many aspects of growth. Genes unique to the PCA strain 249 ORFs in the PCA genome (7.2%) did not have orthologs in the KN400 genome (Additional file 1 : Table S5). Gene ontology analysis showed that three types of genes were very highly enriched in this group relative to the whole genome: those involved in DNA transposition, DNA integration, and RNA-dependent DNA replication (Additional file 1 : Table S6). As with strain KN400, these ORFs were mostly found in clusters within the PCA genome (Additional file 2 : Figure S1). There are 18 regions in the PCA genome in which at least two consecutive genes have no orthologs in the KN400 genome, (Additional file 1 : Table S7). Twelve of these are bordered by (or contain) transposases, three by a tRNA gene(s), and two by conserved nucleic acid sequences. Compared to the KN400 strain, there are more transposases and more diverse types of transposases associated with these regions. Several of these non-orthologous regions in the PCA genome are much larger than any of those found in the KN400 genome (Additional file 2 : Figure S1). In the KN400 genome, 4 of the non-orthologous regions have at least ten genes, and the largest has 22 genes. In the PCA genome, 10 regions have at least ten genes, and the largest has 89 genes (Additional file 1 : Table S4 and Additional file 1 : Table S7). The largest region of non-orthology to KN400 is between 2316300–2393600 in the PCA genome (Additional file 1 : Table S7). This region of 89 ORFs (GSU2105-GSU2183) is inserted relative to the KN400 genome between KN400_3465 and a tRNA gene at 2285100. Two-thirds of the proteins encoded in this region are proteins of unknown function or transposases. Other proteins encoded include five putative transcriptional regulators and two efflux pumps (Additional file 1 : Table S5). The second largest region unique to the PCA genome is between 49500–81300 (Additional file 1 : Table S7). This region of 26 ORFs (GSU3471-GSU0064) is inserted relative to strain KN400 between a tRNA gene and KN400_0040. The majority of the proteins encoded here are also transposases and proteins of unknown function. However, this region also encompasses the CRISPR1 locus, six CRISPR-associated genes and a toxin/antitoxin pair, genes involved in resistance to exogenous DNA and potentially in gene regulation [ 13 , 14 ]. In total, the KN400 genome is ca. 100 kb smaller than the PCA genome, with the difference due to the ca. 100 genes in KN400 with no ortholog in PCA and ca. 200 genes in PCA with no ortholog in KN400. These genes have a variety of different apparent histories – some are not found in any other organism, some are syntenic between the genomes but lack sequence homology, some appear to have been lost entirely in one of the strains, and some may have arisen from lateral gene transfer from unrelated species. Strain-specific genes of potential interest include a number for membrane transport and polysaccharide metabolism; a restriction/modification system; catalases; a disulfide bond formation operon unique to KN400; and a CRISPR locus unique to PCA. The evolutionary history of the mobile genetic elements that are enriched in these regions also warrants further investigation. Single nucleotide polymorphisms (SNP) between the PCA and KN400 genomes Using an alignment of the two whole genomes, 27,270 single nucleotide polymorphism sites and small insertions or deletions between the two strains were identified (Figure 1 , Additional file 1 : Table S8). Of these, 23,773 (87%) were intragenic in the PCA strain, with a rate of 6.8 SNP/kb in coding regions and 10.5 SNP/kb in non-coding regions. Within the 3192 genes that had orthologs in both genomes, there were 17,964 SNP and 182 small-scale insertions or deletions (Figure 1 , Table 2 ). The large majority (72%) of the sequence differences between the KN400 and the PCA orthologs were silent, meaning that the SNP caused no changes to translation, and that the protein sequences of the orthologs were identical. The remaining 5109 SNP (28%) were non-synonymous – they caused a difference in amino acid sequence during translation (Figure 1 , Table 2 ). Table 2 Summary of the number and types of SNP in different classes of genes PCA Total KN400 orthologs % with orthologs Total SNP Total NS SNP % NS SNP genes with SNP % Genes w.SNP Genes with NS SNP % genes w.NS SNP SNP/ gene NS SNP/ gene SNP/ SNPed gene NS SNP/ SNPed gene # genes ≥1.2% NS SNP % genes ≥1.2% NS SNP genes 3432 3192 92.6 18146 5109 28.2 1160 36.3 786 24.6 5.6 1.6 15.5 4.4 114 3.6 central metabolism 85 85 100.0 180 37 20.6 34 40.0 17 20.0 2.1 0.4 5.3 1.1 1 1.2 cytochromes 95 94 98.9 1156 365 31.6 48 51.1 36 38.3 12.3 3.9 24.1 7.6 7 7.4 increased expression 93 85 91.4 1518 388 25.6 43 50.6 33 38.8 17.9 4.6 35.3 9.0 6 7.1 One-third of genes had a change of sequence between the strains − 1160 of the 3192 orthologs had at least one SNP, with an average of 5.6 per gene (15.5 per gene in genes that had at least one SNP) (Figure 1 , Table 2 ). A rate of 34 SNP/kb was two standard deviations above average. One-quarter of proteins had a change of sequence between the strains – 786 of the 3192 orthologs had at least one non-synonymous SNP, with an average of 1.6 per ortholog (4.4 per gene with at least one SNP) (Figure 1 , Table 2 ). The set of genes that had at least one non-synonymous SNP was significantly enriched in genes for: c -type cytochromes, integral membrane proteins, phosphorus and phosphate metabolism, cofactor biosynthesis, and ATP-dependent enzymes with a wide variety of functions including: transporters and exporters, helicases, mismatch repair proteins, excinucleases, proteases, and many sensor histidine kinases (Additional file 1 : Table S6). Proteins were considered heavily mutated if the corresponding gene had at least 12 non-synonymous SNP/kb, which was two standard deviations above average (Table 2 ). 125 of the orthologs (3.6%) were heavily mutated (Table 3 , Additional file 1 : Table S9). The set of heavily mutated proteins was significantly enriched in c -type cytochromes and in membrane-bound transport proteins (Table 3 , Additional file 1 : Table S6). Table 3 Orthologous genes in the KN400 and PCA strains that have the highest level of protein-changing single nucleotide polymorphisms per kb (proteins of unknown function not shown) Gene Annotation PCA ortholog Non-synonymous SNP per 1000 bases Total SNP KN400_0176 quinoline oxidoreductase, small subunit protein GSU0200 17.0 25 KN400_0177 quinoline oxidoreductase, large subunit protein GSU0201 21.6 174 KN400_0192 FMN-cofactor binding protein GSU0217 12.4 20 KN400_0193 cytochrome c oxidase synthesis (SCO) factor GSU0218 14.4 32 KN400_0196 cytochrome c oxidase, subunit IV GSU0221 13.8 11 KN400_0197 cytochrome c oxidase, subunit II GSU0222 12.0 44 KN400_0198 cytochrome c oxidase assembly factor GSU0223 18.5 43 KN400_0202 DNA methyltransferase GSU0227 19.6 53 KN400_0225 sensor histidine kinase GSU0253 20.1 118 KN400_0281 DnaJ domain protein GSU0313 15.6 21 KN400_0418 ribonuclease D GSU0443 20.1 64 KN400_0545 DNA-3-methyladenine glycosylase I GSU0567 19.1 28 KN400_0547 nicotinamidase-related cysteine hydrolase GSU0569 21.9 29 KN400_0597 cytochrome c (OmcE) GSU0618 25.8 44 KN400_0681 cytochrome c biogenesis, ResB GSU0704 12.8 36 KN400_0803 sensor histidine kinase GSU0822 13.7 68 KN400_0811 efflux pump, RND family, membrane fusion protein GSU0829 40.2 116 KN400_0818 response regulator GSU0837 12.2 8 KN400_0880 3-oxoalanine-generating family protein GSU0897 17.1 55 KN400_0883 SAM-dependent methyltransferase GSU0900 19.1 40 KN400_0885 response receiver GSU3516 12.8 17 KN400_0887 sensor histidine kinase GSU3518 16.8 68 KN400_0892 pyranopterin cofactor biosynthesis, MoeB GSU0907 34.3 44 KN400_0893 pyranopterin cofactor biosynthesis, MoaD GSU0908 32.0 22 KN400_0899 ATP-dependent RNA helicase RhlE GSU0914 17.9 105 KN400_0908 ABC transporter, ATP-binding protein GSU0922 12.4 75 KN400_0914 zinc-dependent peptidase, M16 family GSU0928 16.0 77 KN400_0950 protease GSU0969 16.3 73 KN400_0995 OmpA family outer membrane lipoprotein GSU1013 15.0 37 KN400_0996 smr domain protein GSU1014 26.4 40 KN400_1013 methyl-accepting chemotaxis sensory transducer GSU3523 19.6 153 KN400_1014 methyl-accepting chemotaxis sensory transducer GSU1035 15.2 107 KN400_1117 methyl-accepting chemotaxis sensory transducer GSU1141 14.5 72 KN400_1307 cytochrome c GSU1334 16.7 81 KN400_1319 sulfate ABC transporter, periplasmic sulfate-binding GSU1346 20.7 58 KN400_1320 sulfate ABC transporter, membrane protein CysU GSU1347 16.8 31 KN400_1510 transcriptional regulator, MarR family GSU1483 49.0 59 KN400_1862 membrane-associated phosphatase, PAP2_like_5 family GSU1840 12.2 15 KN400_1865 RNA exonuclease GSU1843 18.2 58 KN400_1866 IPT/TIG domain protein GSU1844 12.5 107 KN400_1884 IPT/TIG domain protein GSU1858 25.1 173 KN400_2002 exopolysaccharide synthesis exosortase GSU1979 12.6 38 KN400_2006 protein tyrosine kinase GSU1983 14.0 27 KN400_2106 D-glycero-D-mannoheptose-1,7-bisphosphate phosphatase GSU2084 12.2 20 KN400_2110 glycosyltransferase, group 2 family protein GSU2088 57.0 139 KN400_2282 trehalose-6-phosphatase GSU2336 26.6 41 KN400_2284 sodium/proton antiporter complex Mrp, protein G GSU2338 43.8 52 KN400_2286 sodium/proton antiporter complex Mrp, protein E GSU2340 40.2 62 KN400_2287 sodium/proton antiporter complex Mrp, protein D GSU2341 16.5 106 KN400_2288 sodium/proton antiporter complex Mrp, protein C GSU2342 46.6 18 KN400_2382 ATP-dependent protease, putative GSU2433 12.2 77 KN400_2399 peptide methionine sulfoxide reductase GSU2451 14.5 19 KN400_2420 TPR domain protein GSU2476 17.6 74 KN400_2445 YVTN family beta-propeller domain protein GSU3586 16.6 59 KN400_2449 cytochrome c (OmcS) GSU2504 15.4 51 KN400_2452 sensor histidine kinase GSU2507 13.9 70 KN400_2454 TPR domain protein GSU2508 24.5 96 KN400_2457 sensor diguanylate cyclase/phosphoesterase GSU2511 17.6 142 KN400_2460 cytochrome c GSU2513 31.8 27 KN400_2624 2-dehydropantoate 2-reductase GSU2683 38.5 104 KN400_2644 transcriptional regulator, TetR family GSU2698 13.9 33 KN400_2649 molybdopterin-molybdenum ligase GSU2703 12.3 59 KN400_2658 fibronectin type III domain protein GSU2715 48.7 294 KN400_2660 hydrogenase, bidirectional NAD-reducing, protease GSU2717 30.8 35 KN400_2668 cytochrome c GSU2725 25.4 31 KN400_2716 transcriptional regulator, MerR family GSU2779 18.0 30 KN400_2747 transcriptional regulator, Fur family GSU2809 30.6 35 KN400_2750 glutaredoxin family protein GSU2812 89.8 60 KN400_2997 NADPH ferredoxin oxidoreductase (FNOR) beta subunit GSU3058 15.6 32 KN400_3000 squalene cyclase domain protein GSU3061 12.3 107 KN400_3006 UDP-N-acetylenolpyruvylglucosamine reductase GSU3067 21.1 58 KN400_3214 cytochrome c GSU3274 28.8 32 KN400_3301 sensor histidine kinase GSU3357 22.2 146 KN400_3348 OmpJ-related porin GSU3403 29.9 97 KN400_3368 dihydrolipoamide dehydrogenase-related protein GSU3424 16.4 86 Some genes had only silent SNP, or sequence changes that did not affect the resulting protein sequence, indicating that changes to their sequence may be under negative selective pressure. Solely silent changes were present in 373 of the orthologs (12%) (Additional file 1 : Table S1). This set of genes was significantly enriched in genes involved in flagellum biogenesis and amino acid biosynthesis (Additional file 1 : Table S6). The KN400 strain, unlike the PCA strain, produces flagella and is motile [ 5 ]. The most notable silent-mutation-rich region of the genome was cluster GSU1095-GSU1102, which encodes a phosphate transporter and phosphate-dependent regulatory genes (Additional file 1 : Table S2). In order to better understand the phenotypic effects of the nucleotide polymorphisms between the strains, several metabolic networks involved in electron transfer out of the cell were examined in more detail. Sequence differences in central energy metabolism G. sulfurreducens primarily grows by coupling the oxidation of acetate to the reduction of extracellular electron acceptors. Acetate is oxidized by the TCA cycle, with the products used to generate a proton gradient for ATP synthesis [ 1 , 15 ]. The electrons that remain from this process are transferred out of the cell to Fe(III) or to electrodes. In total, 65 genes in strain PCA encode the proteins involved in acetate oxidation, and the KN400 strain has orthologs to each of these (Additional file 1 : Table S10). Ten of the 65 contain a protein sequence change, with fewer per gene than the genome as a whole (0.4 versus 1.6 non-synonymous SNP per gene) (Table 2 ). None are highly mutated. Separately from energy generation, a portion of acetate is shunted to a different pathway and used as the sole source for biomass synthesis via the gluconeogenic and fatty acid pathways [ 15 , 16 ]. 20 genes are involved in this other fate of acetate and the KN400 strain has orthologs to each of these (Additional file 1 : Table S10). However, two reactions from this pathway show higher sequence changes between the strains – phosphate acetyltransferase and acetate kinase (PAT - GSU2706, AK - GSU2707). In KN400 the acetyltransferase has 38 SNP (8 non-synonymous) and the kinase has 45 SNP (7 non-synonymous), with a 27-fold higher non-synonymous SNP/kb ratio than the other enzymes of central energy metabolism (Table 2 , Additional file 1 : Table S10). The sequence differences in PAT and AK stand out as the most pronounced in the otherwise very well-conserved enzymes of central energy metabolism. It has previously been shown that strain PCA cannot grow on acetate alone if either PAT or AK is knocked out [ 16 ]. This phenotype arises because the CoA-transferase that activates acetate for oxidation in the TCA cycle requires CoA derived from the TCA cycle itself. Therefore, additional pathways are needed to produce acetyl-CoA for biosynthetic pathways. With acetate as the sole growth substrate, this anaplerotic function is performed by AK and PAT. Differences in these two enzymes could have a substantial effect on the flux between acetate oxidation and reduction, and thereby on electron transport rates out of the cell and on biomass production. A lower flux through AK/PAT relative to the TCA cycle would translate to a decreased biomass yield per molecule of acetate oxidized and a higher ratio of electrons transferred to the electrode per cell – the phenotype seen in the KN400 strain [ 5 ]. Sequence differences in extra-cytoplasmic electron transfer proteins G. sulfurreducens grows by using Fe(III) oxide or energy-harvesting electrodes as the terminal electron acceptor [ 2 , 17 ]. Cytochromes, pili, and exopolysaccharides have all been shown to be important for growth using these extracellular electron acceptors [ 1 ]. For both the PCA and KN400 strains, the whole proteomes were scanned for the heme-binding motif of c -type cytochromes [ 18 ] (Additional file 1 : Table S11). In each strain, 135 genes encode proteins with this C-X-X-C-H motif (Additional file 1 : Table S11). Since this definition of cytochrome is minimal, proteins were excluded as cytochromes if they had a predicted function or cellular localization that indicated that they were not involved in electron transport outside the cell; most were proteins with iron-sulfur-binding domains (Additional file 1 : Table S11). In total, 107 genes in the PCA and 106 in the KN400 strain were predicted to encode c -type cytochromes (Additional file 1 : Table S11). Only one of the PCA cytochromes lacked an ortholog in KN400: GSU2515, a monoheme cytochrome that has not been shown to be involved in electron transport. Fifty-four of the 106 c -type cytochromes contain at least one SNP in KN400 relative to PCA (51%), compared to 36% of genes in the whole genome (Table 2 ). There were more than two-fold more SNP per cytochrome compared to the genome as a whole: 12.3 vs 5.6 SNP/gene, and almost twice as many of the encoded proteins were heavily mutated: 7.4% vs 3.6% (Table 2 ). However, all 106 of the orthologous cytochromes had the same number of predicted heme-binding sites, with up to 27 motifs in a single protein (Additional file 1 : Table S11). So, while the cytochromes have more than the average number of changes to nucleotide and protein sequences, these changes do not result in a change to the number of hemes predicted to be bound to each cytochrome. This indicates that the proteins’ electron carrying capacity may still function, though perhaps with a changed redox potential due to structural differences [ 19 ]. Most of the cytochromes previously shown to be required for growth with Fe(III) or for optimal current production [ 1 ] are identical in KN400 and PCA, including PpcA, MacA, OmcB, OmcC, OmcF, and OmcZ (Additional file 1 : Table S11). However, two cytochromes are among the most heavily mutated genes in the genomes and are required for extracellular electron transfer – OmcE and OmcS (GSU0618, GSU2504) (Table 3 , Additional file 1 : Table S11). The omcS gene is found in a region (2743500–2775500 in PCA) that has one of the highest SNP rates in the genome: 36 SNP/kb. Of the 22 genes encoded, 8 are heavily mutated, one is frameshifted, and three lack orthologs in the KN400 strain (Additional file 1 : Table S2). This region also encodes six other c -type cytochromes: GSU2494, GSU2495, GSU2501, GSU2503 ( omcT ), GSU2513 and GSU2515. Finding significant changes to OmcS in particular is especially relevant in the KN400 strain because this cytochrome has been shown to be localized outside of the cell along the length of the pili [ 20 ] where it may facilitate electron transfer from pili to the terminal electron acceptor [ 6 , 21 ]. Changes to the electron-carrying protein at this key position for electrical contact could have a substantial effect on phenotype. Pili are also required for the reduction of extracellular electron acceptors by G. sulfurreducens [ 21 , 22 ]. They are believed to provide a conduit for electron transfer through biofilms and to the cytochromes responsible for Fe(III) oxide reduction [ 6 ]. There are 24 genes involved in biogenesis and assembly of pili (GSU0146, GSU0230, GSU0436, GSU1063-GSU1066, GSU1491-GSU1496, GSU2028-GSU2038, GSU3548, GSU2043). All 24 genes have orthologs in the KN400 strain (Additional file 1 : Table S1), and they are all well conserved – 20 of the genes are identical at the nucleotide level between the strains, and only one has a single non-synonymous mutation, a PilT homolog (GSU0436). Extracellular polysaccharides are also required for electrode reduction; they are involved in anchoring the c -type cytochromes that provide the electrical conduit between the cell and the electrode surface [ 23 ]. Five of the genes in the extracellular anchoring polysaccharide gene cluster (GSU1498 to GSU1508) have non-synonymous SNP (Additional file 1 : Table S2), including one in the an ABC transporter ATPase subunit required for polysaccharide production [ 23 ]. Finally, OmpB and OmpC are putative copper-binding oxidoreductases required for insoluble Fe(III) reduction in G. sulfurreducens [ 24 , 25 ]. The ompB gene (GSU1394) is identical between the two strains, and ompC (GSU2657) has a single synonymous mutation. Thus between the KN400 and the PCA strains there is both conservation and divergence among the extra-cytoplasmic proteins involved in transferring electrons out of the cell. Most previously known to be required in vivo did not have large sequence differences, including six cytochromes, two copper proteins, and the pilin. However, cytochromes considered as a class were much more likely to contain non-synonymous SNP, and two important cytochromes, OmcS and OmcE, have especially large differences. Notably though, not a single heme-binding site was lost due to the changes. These data support previous analyses showing that a diversity of cytochromes are characteristic of Geobacter species, but individual cytochromes tend to be poorly conserved [ 26 ]. This kind of cytochrome diversity and adaptability may be especially important for the use of terminal electron acceptors with a wide variety of redox potentials. Sequence differences in the genes with increased expression during growth on an electrode Two previous studies have analyzed changes in gene expression in the PCA strain during growth on an energy-harvesting electrode. Given the improvements in electron transfer to electrodes in the KN400 strain relative to PCA, any sequence changes in these genes are of particular interest. The first study looked at gene expression in the early stages of anode biofilm formation, and showed that 93 genes had an increase in transcript abundance compared to growth by Fe(III) reduction [ 27 ]. The second looked at expression changes in established, high-current-density biofilms, and showed that 13 genes had an increase in transcript abundance compared to growth with fumarate as an electron acceptor [ 22 ]. Only one of the 13 genes with increased expression on the high-current electrode had substantial changes between the KN400 and the PCA strain. OmpJ is an outer-membrane channel protein known to influence the quantity and localization of cytochromes in G. sulfurreducens [ 28 ], so changes to its sequence could influence electron transfer very broadly. OmpJ (GSU3403) has 3-fold higher expression during growth on the electrode, and it was among the most highly mutated genes between the two strains, with 30 non-synonymous changes per kb (Additional file 1 : Table S9). Twenty-four genes have increased expression during early-stage growth on the electrode and also had either no ortholog or large sequence differences in the KN400 strain (Table 4 ). The omcS cytochrome gene is the most highly up-regulated of all genes and it was among the proteins with the largest sequence difference between the KN400 and PCA strains (discussed above). A third copper-binding oxidoreductase has increased expression during growth on the electrode [ 27 ], and the cluster encoding this multicopper oxidase, as well as a cytochrome d and two copper chaperone proteins (GSU1251-GSU1257) had large sequence differences (Additional file 1 : Table S2). Unlike OmpB and OmpC (mentioned above), the role of these proteins in electron transfer has not been studied, though interestingly the most similar complex is found in the Fe(II)-oxidizing Leptothrix species [ 29 ]. Table 4 Genes in strain PCA that have increased expression during growth with an electrode as the electron acceptor and that lack orthologs or have a high level of protein-changing single nucleotide polymorphisms per kb PCA gene Annotation KN400 ortholog Non-synonymous SNPs per 1000 bases electrode increase expression (fold-change) GSU0062 TraD protein none 1.34 GSU0618 cytochrome c (OmcE) KN400_0597 25.8 1.98 GSU0829 efflux pump, membrane fusion protein KN400_0811 40.2 1.69 GSU0955 RNA-directed DNA polymerase none 1.76 GSU1253 cytochrome d KN400_1227 13.7 1.65 GSU1844 IPT/TIG domain protein KN400_1866 12.5 1.55 GSU2113 transcriptional regulator none 1.4 GSU2129 conserved hypothetical protein none 1.38 GSU2133 lipoprotein none 1.62 GSU2135 metal efflux pump, inner membrane protein none 1.73 GSU2136 metal efflux pump, membrane fusion protein none 1.88 GSU2137 metal efflux pump, outer membrane protein none 1.94 GSU2139 transposase none 1.28 GSU2143 conserved hypothetical protein none 3.82 GSU2471 RNA-directed DNA polymerase none 1.56 GSU2476 TPR domain protein KN400_2420 17.6 1.49 GSU2497 lipoprotein KN400_2442 23.8 1.32 GSU2504 cytochrome c (OmcS) KN400_2449 15.4 19.46 GSU2507 sensor histidine kinase KN400_2452 13.9 1.41 GSU2508 TPR domain protein KN400_2454 24.5 1.37 GSU2690 VacJ family lipoprotein KN400_2637 36.6 1.35 GSU2773 conserved domain protein none 1.62 GSU2779 transcriptional regulator KN400_2716 18.0 3.77 GSU3067 UDP-N-acetylenolpyruvylglucosamine reductase KN400_3006 21.1 1.32 GSU3403* OmpJ porin KN400_3348 29.9 2.76 In addition to these copper proteins, a transcriptional regulator (GSU2779) with homology to CueR, a copper-responsive transcriptional activator [ 30 ], has a four-fold increase in expression on the electrode and was heavily mutated in the KN400 strain (Table 4 ). The CueR protein is broadly involved in metal homeostasis, and three general metal efflux pumps also have increased expression on the electrode and sequence changes in KN400. The first pump (GSU2135-GSU2137) was one of the few proteins in PCA that lacked orthologs in KN400 (Table 4 ), and two others have non-synonymous SNPs (GSU0829-GSU0830 and GSU1338-GSU1341). Immediately downstream of one of the metal pumps, a fourth important transporter has large differences between the KN400 and PCA strains: the only sulfate transporter in the genome (GSU1350-GSU1352) was heavily mutated in KN400 (Table 3 ). This is upstream of three additional genes for sulfur metabolism: a sulfite reductase, a sulfur carrier protein, and a thiocarboxylate synthase (GSU1350-GSU1352), which are among the few in PCA that lack orthologs entirely in KN400 (Additional file 1 : Table S5). These changes indicate that KN400 may have a significant difference in its usage of sulfur, copper, and perhaps other metals, which could have far-reaching impact on the types of redox proteins active in the KN400 strain."
} | 10,024 |
31266970 | PMC6606572 | pmc | 5,495 | {
"abstract": "Synthetic fertilizer production is associated with a high environmental footprint, as compounds typically dissolve rapidly leaching emissions to the atmosphere or surface waters. We tested two recovered nutrients with slower release patterns, as promising alternatives for synthetic fertilizers: struvite and a commercially available organic fertilizer. Using these fertilizers as nitrogen source, we conducted a rhizotron experiment to test their effect on plant performance and nutrient recovery in juvenile tomato plants. Plant performance was significantly improved when organic fertilizer was provided, promoting higher shoot biomass. Since the microbial community influences plant nitrogen availability, we characterized the root-associated microbial community structure and functionality. Analyses revealed distinct root microbial community structure when different fertilizers were supplied. However, plant presence significantly increased the similarity of the microbial community over time, regardless of fertilization. Additionally, the presence of the plant significantly reduced the potential ammonia oxidation rates, implying a possible role of the rhizosheath microbiome or nitrification inhibition by the plant. Our results indicate that nitrifying community members are impacted by the type of fertilizer used, while tomato plants influenced the potential ammonia-oxidizing activity of nitrogen-related rhizospheric microbial communities. These novel insights on interactions between recovered fertilizers, plant and associated microbes can contribute to develop sustainable crop production systems.",
"conclusion": "Conclusion Our results shed light on how roots and microorganisms orchestrate, coexist and benefit from each other especially at juvenile plant growing stage, although they depend on the same nutrients and strongly compete for them, particularly in the rhizosphere. Tomato plants seem to influence or even modulate the nitrification activity in the rhizosphere and the highest relative AOB abundance was found with the organic fertilizer. This was confirmed by the increase over time in the community evenness, indicating that plants rather than fertilizers are shaping microbial community composition. Furthermore, the effect of the plant on the microbial community is observed in the activity of the N-related bacteria. As the ammonia oxidation rate was reduced in the rhizosheath, the plant may be impacting the activity of the ammonia oxidizing bacteria to compete for the N sources. Based on our results, ammonium seems to be the key N form for successful nitrogen competition in soilless culture systems. The paramount reason for efficacious nitrogen acquisition from N hotspots in soilless culture systems is spatiotemporal and plant-mediated differences in nitrogen availability and in overall and specific microbial community distributions. There is no doubt that generating a detailed understanding of rhizosheath-rhizosphere related microbial community, their assembly over time and activity will be essential to manipulate root-soil interactions and to ensure sustainable fertilizer use-efficiency and soilless crop production in the future.",
"introduction": "Introduction About 95% of greenhouse vegetables, and especially tomatoes in Europe, U.S.A., and Canada are produced in soil-less culture systems 1 using artificial growing media that provide plants with necessary nutrients. Intensive horticulture, as well as intensive agriculture heavily rely on the input of inorganic and organic fertilizers to sustain food production 2 . The synthetic fertilizer production is associated with high environmental footprint. Therefore, it is meaningful to move towards a sustainable crop production via recovery/reuse of the nutrients in form of alternative fertilizers 3 . The heavy environmental impact of mineral fertilizers in traditional agriculture is aggravated by high nitrogen leaching, as compounds are typically rapidly dissolved 4 . Timing, ratio, and quantity of nutrients are fundamental for optimal plant growth, because the nutrient demand of the plant may not be concomitant with the release from the fertilizers 5 , 6 . Tomatoes can take up nitrogen in the form of ammonium or nitrate 7 . The N contained in organic fertilizers is converted into NH 4 + and NO 3 − by microorganisms to be plant-available. However, plants are capable of taking other organic N sources like simple amino acids 7 . One major process in nitrogen cycling is the conversion of ammonium (NH 4 + ) or ammonia (NH 3 ) to nitrite (NO 2 − ), which is called ‘ammonia oxidation’ or ‘nitritation’. The further transformation of nitrite (NO 2 − ), into nitrate (NO 3 − ), is called ‘nitrite-oxidation’ or ‘nitratation’. Ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) oxidize ammonia to nitrite. AOA and AOB cohabit the vast majority of terrestrial ecosystems 8 , but they may occupy different ecological niches 9 . Nitrite-oxidizing bacteria (NOB) can utilize nitrite as energy source and carbon dioxide as the main carbon source 10 and they convert nitrite (NO 2 − ) to nitrate 11 . The demand for organically grown products has increased during recent years 12 . Thus, organic fertilizers represent a sustainable alternative to mineral fertilizers and can be produced on-farm (e.g. slurries, poultry manures digestate) or off-farm (e.g. as residues from food industry) 13 . Additionally, recycled sources of inorganic nutrients are increasingly becoming available, recovering N from wastewater, sludge or manure through nitrification (e.g. stabilized urine) 14 , stripping/absorption (e.g. (NH 4 ) 2 SO 4 )) or crystallization with magnesium and phosphorus, yielding struvite (MgNH 4 PO 4 .6H 2 O), which is applicable as slow-release fertilizer 15 – 17 . Little research has been conducted on how to efficiently apply recycled nutrients, and how plants and their environment react to them 18 . A key factor that might impact nutrient-use efficiency from these fertilizers in the organic growing media is the root-associated microbial community and its effects on nutrient mobilization, immobilization, and conversion 19 . Plants can impact not only the growing media physically adhered to the roots (rhizosheath), but the effect can reach up to the entire rhizosphere through root exudates 20 . Hence, microbial community structure and activity, nutrient cycling, pH and consequently plant growth will be impacted 21 . We defined rhizosheath (Fig. 1 ) as the soil that physically adheres to the roots system (in the range of less than 1 mm distant from a root), while rhizosphere refers to the soil influenced by the root (within a region of 1 cm distant from the root), as suggested by Pang et al . 20 . “Bulk” was defined as the growing medium within a rhizotron without tomato plants growing. Rhizosheath microbial communities during early plant development are different to those in the rhizosphere, indicating an active plant-shaping effect on the community at the beginning of the life cycle and a slowdown of this effect as plant ages 22 . Changes in the microbial community composition in the rhizosphere might be driven by the plant-microbe competition for nutrients in the growing medium, such as phosphorous and nitrogen 23 , 24 , or by the form of the nitrogen as ammonium or as nitrate 25 . Indeed nitrogen can change the abundance of ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) in the soils 26 , 27 and shift their activities 26 . Many studies have analysed the impact of different N fertilizers on the microbial community. However, we focused on portraying a connection that is yet to be explored: how different ammonium sources (e.g. struvite and organic-N) and the associated nitrogen transformation processes influence the rhizosheath and the rhizosphere microbial community in growing media. Ammonia oxidation is a major process in nitrogen cycling, as it is the first limiting reaction for overall rate of nitrate production. Ammonium is one of the principal plant absorbable N forms. Thus, nitritation and its control by plants may play a central role in the outcome of competition for nitrate and ammonium between plants and microbial communities 28 . Figure 1 Rhizotron design indicating the removable side of the transparent polycarbonate plate that allows the visualization of the roots, and the location of the planar pH-optodes. The planar optode set-up consisted of a foil containing the sensor fixed to the transparent inner side of the rhizotron surface, which comes into contact with roots. The figure also indicates the places where substrate samples were taken at two distances to the root: rhizosphere at approx. 10 mm from the root and rhizosheath samples taken directly at the root (less than 1 mm distance to a root). The aim of this study was to determine the effect of two recovered nutrients used as nitrogen sources, namely struvite and organic fertilizer, on tomato plant performance, nitrogen dynamics in the growing medium, microbial community associated with the rhizosheath and rhizosphere over time, and abundance and functionality of nitrogen turnover-associated microbes, such as AOB and NOB. We hypothesized that (a) the availability of the nutrients from the struvite will rely mainly on the chemical release rate (i.e. dissolution changing because of pH, time, water content), while organic fertilizer will require microbes to become available; that (b) the overall microbial community will be affected by the presence of a plant in comparison to bulk soil, and by the fertilizer treatment, due to root processes related to nutrient uptake that may influence microbial community structure and activity; and that (c) the fertilizer effects are significant for nitrogen-related bacteria, as we would expect larger impact from organic fertilizer (boosting heterotrophs and nitrifiers) vs. struvite (boosting only nitrifiers).",
"discussion": "Discussion We hypothesized that the availability of struvite will rely mainly on the chemical release rate, while organic fertilizer will require microbes to convert the organically bound nitrogen to ammonium and to make it available for the plant. Our results show that both struvite and organic are suitable fertilizers as they can deliver plant available nutrients. However, the use of struvite resulted in decreased leaf area, fresh weight, and dry weight compared to the organic fertilizer. We found that the ammonium from the struvite seemed to be released faster than that from the organic fertilizer. However, the ammonium concentration decreased in the growing medium with organic fertilizer, indicating that most of the ammonium was either used by the plant or was mineralized. Higher biomass production is normally obtained by a combined presence of both ammonium and nitrate 29 . Indeed, the organic fertilizer treatment showed a combined presence of ammonium and nitrate and the highest growth rates and plant yields. In contrast, no nitrate was detected with the struvite treatment, indicating that ammonium was not transformed to nitrate or was immediately taken up by the plant. The availability of nitrogen from struvite is a combination of a chemically and biologically driven process 30 . Struvite has slow-release properties 31 determined by the dissolution rate and solubility 32 . The small increase in the concentration of nitrate observed when struvite was applied to the medium without plants can be explained by the presence of bacteria, altering the dissolution rate of ammonium from struvite 33 . This rate may ultimately impact the physicochemical characteristics of the growing medium and/or microbial community, and therefore plant performance 34 , 35 . The increase of rhizosphere pH observed with the optodes indicated plant nitrate uptake only with the organic fertilizer. It is possible that pH changes were not visualized in other treatments and replicates because pH was not continuously monitored but only every second day. However, these preliminary results agree with the nutrient turnover analyses, indicating that the tomato plant was more effective in taking up nitrogen from organic fertilizer than from struvite. Struvite supply resulted in a steadily net increase of the ammonium concentration over time, most likely due to higher dissolution rates compared to ammonia oxidation rates 34 , 36 . This might result in high or even toxic ammonium concentrations and subsequently decreased plant performance 34 . We found evidence that bacterial abundance between samples of the rhizosphere of tomato and bulk without plant were significantly different, as expected. When plants start rooting, they immediately encounter the microbial community associated with the growing medium, resulting in the establishment of a rhizosphere community closely interacting with the plants and distinct from the bulk growing medium 37 , 38 . In our study, the community composition in the rhizosphere and bulk growing medium without a plant was distinctly different indicating that plants can influence the microbial community composition even at a distance of more than 10 mm in organic growing media. In addition, we found significant differences between microbial community structure and activity in the rhizosphere and rhizosheath. Indeed, the total number of species (richness), the relative abundances of each of these species (evenness) and the pool of species (diversity) at each time point/on each fertilizer/with or without plant was the same in the rhizosphere and rhizosheath. However, differences in community composition and species composition between the rhizosphere and rhizosheath indicated that not all the same species were present in all environments (Tables S3 and S4 ). Thus, the number of species may be equal but turnover between species may be high and the way they are distributed within time points, within plants, and within fertilizers may be different. The colonization of the rhizosphere is the result of a complex exchange of signals between the microorganisms and the plant, which can be beneficial to plants 39 . Indeed, microorganisms can affect plant-nutrient acquisition processes by influencing nutrient availability in the rhizosphere and/or functionality of the biochemical mechanisms underlying the nutritional process 39 . We found significantly increased relative abundance of Asticcacaulis , Opitutus , Sphingomonas and Uncultured Fibrobacter in the rhizosphere, which could be linked to the organic fertilizer treatment. Ambrosini, et al . 40 showed plant growth promoting characteristics of putatively diazotrophic bacteria from the rhizosphere and Asticcacaulis was associated with the rhizosphere. Sphingobacteriales are copiotrophic bacteria with high cellulose degradation activity towards a wide range of carbon sources and are present in soils or growing media with high organic carbon content 41 . The carbon sources are likely to come from the growing medium as it contained high organic matter (34.9% of the dry matter is cellulose) 42 . Similar to our findings, tomato plants inoculated with endophytic Sphingomonas sp. LK11 (Sphingobacteriales) showed significantly increased plant growth, and shoot dry weight compared to the control 43 (Table S1 ). Moreover, as Sphingobacteriales require oxygenated environments for carbon degradation, the decreased relative abundance of Sphingobacteriales in the struvite treatment might indicate a lack of oxygen, explaining decreased nitrification rates when struvite was supplied. Relative abundance of Acidothermus , a genus belonging to Acidobacteria, was higher when struvite was provided. This group of bacteria is mostly considered oligotrophic (K-strategist) and decline with increasing N concentrations 44 . We found the opposite probably because Acidobacteria cannot use the unavailable crystalized NH 4 + present as struvite. Azospirillum , Bdellovibrio , Rhizomicrobium and Uncultured Planctomycetaceae had significant higher relative abundance when no fertilizer was applied. This can be explained since Azospirillum induces changes in plant root architecture, promoting the development of lateral and adventious roots and root hairs 39 . Moreover, Bdellovibrio spp. is a bacterial genus known for unique predatory behaviour, as they attack other Gram negatives, penetrate their periplasm, multiply in their cytoplasm, and finally burst their cell envelopes to start anew, resulting in a release of plant-available nutrients 45 . Differences in the microbial community structure of the rhizosphere were mainly a result of time (Fig. 5 ), which has been described for maize 46 . Plant root exudates are differentially produced at distinct development stages, orchestrating rhizosphere microbiome assemblage 47 and exudation rate increases during the juvenile growing stage as the plant grows 22 , 46 , 48 , 49 . Consequently, spatiotemporal differences are important factors influencing rhizosphere microbial community composition. Bacterial communities in the rhizosheath were significantly different as a result of fertilizer supplementation, which was not observed in the rhizosphere. MFA showed that the microbial community in the rhizosheath becomes stable over time, as indicated by the decreased variations in the bacterial relative abundances over time. Consequently, differences in rhizosheath microbial community composition compared to the rhizosphere are mainly influenced by plant presence and time, i.e. plant age or developmental stage. Absence of fertilizer treatment resulted in higher species richness (total species), diversity (Shannon, Fisher’s alpha, Simpson and Inverse Simpson indices), and evenness (Fig. S2 ). Many dominant bacterial groups might be dormant under particular rhizosphere conditions, but their presence would still be detected by DNA-based analyses. Under P and N deficient conditions plant shoot and root biomass are decreased compared with optimal conditions and consequently, root exudation and influence on rhizosphere microbial community composition may be decreased. Plants produce a root exudate zone adjacent to and just behind root tip meristems 50 , thus altering numbers and diversity of microbes on root surfaces and in the rhizosheath and rhizosphere 51 . Exudates produced in nutrient-limited media (i.e. without fertilizer/struvite) are increased, probably leading to increased microbial activity around roots and increased nutrient ‘microbial mining’ 52 . Through the secretion of root exudates, plants may be considered to be gardening microorganisms 51 . Plant roots activate mineralization of organic nitrogen 53 leading to increased ammonium fluxes in the rhizosphere 8 . The uptake of ammonium 29 , 34 by the roots suggests a direct competition for ammonium with the AOB in the rhizosphere. The nitrogen originating from the organic fertilizer is supplemented as organic nitrogen, while the nitrogen coming from the struvite is supplemented as ammonium. These results indicate organic nitrogen mineralization activity as a result of the organic fertilizer supplementation and higher nitrification activity in comparison to that in struvite. Nitrate was produced only when organic fertilizer was supplied, but its absence in the struvite treatment may indicate inhibition of the nitrification activity. Nitrate accumulates in the growing medium either under high nitrification rates and/or low nitrate reduction rates, i.e. low microbial immobilization, denitrification or dissimilative nitrate reduction to ammonium (DNRA) 44 . The heterotrophic microbial community regulates whether nitrogen is lost or retained in the growing medium 54 – 56 , thus organic nitrogen mineralization relies directly on the microbial nitrogen conversion and results in a release of ammonia, which is subsequently oxidized by NOB into nitrate. The growing medium supplemented with the organic fertilizer showed decreased pH values compared to the growing medium blended with struvite, indicating increased acidotolerant nitrification activity through heterotrophic nitrification 57 , but also through autotrophs 58 . In addition, the organic nitrogen mineralisation results not only in a release of ammonia, but also of CO 2 59 an indispensable carbon source for the autotrophs. AOB abundance was not affected by location but by fertilizer used. Indeed, we found a higher biodiversity in the organic fertilizer compared to the struvite, while no differences were found in the log number of amoA AOB copies per g of dry growing medium between the organic fertilizer and struvite. Lower AOB numbers were observed when no fertilizer was applied, suggesting that AOB benefit from the increased N supply by the fertilizers and not from the increased N supply from roots, efficiently competing for the ammonia with other microorganisms and/or with the tomato plant 8 . Competition relies on the ammonium availability and diffusion of the different N fertilizers in the growing medium and we found significant differences in nitrogen dynamics between treatments. Ammonium availability impacts both the nitrification rates and the nitrifier population size 60 . Hence, affinity for ammonium might be a key characteristic in the rhizosheath. Microorganisms with high affinity for ammonium have low growth rates and are classified as K-strategists. On the contrary, microorganisms with a low affinity have in general a high growth rate and are classified as r-strategists 61 . The results from Table 3 might indicate that the rhizosheath is mainly colonized by K-strategists able to compete with the plants. The rhizosphere, on the contrary, might be more colonized by r-strategists due to the decreased competition with the plant and showing a higher growth rate and maximum ammonia oxidation activity. Higher microbial activity in the rhizosphere, including organic nitrogen mineralization, may stimulate ammonia oxidizing bacteria (AOB) and archaea (AOA). Ammonia uptake by plants may favour AOA, considered to prefer lower ammonia concentrations, while high ammonia concentrations may favour AOB 8 . In general, microorganisms are superior to plants with respect to the competition for nitrogen 62 . Our results suggest that AOB are better competitors for ammonia/ammonium than plants under fertilized conditions (100 mg N L −1 growing medium), but plants are the better competitors under N deficient conditions. Within the NOB community in the organic growing medium, Nitrobacter seems to be a key player in absolute and relative numbers compared to Nitrospira . Nitrobacter is a superior competitor when resources are abundant, while Nitrospira thrives under conditions of resource scarcity 63 . We found no shifts in the relative Nitrobacter/Nitrospira ratio associated with location and fertilizer treatment, indicating interactions between ammonia oxidizers and nitrite oxidizers 64 . Functionality tests revealed that the potential ammonia oxidation activity was significantly higher ( P < 0.05) in the rhizosphere in comparison with the rhizosheath, indicating inhibition of the ammonia oxidation in the rhizosheath or even stimulation of ammonia oxidation in the rhizosphere. Non-invasive pH measurements with the planar optodes showed an increase of the rhizosphere pH and the presence of nitrate with the organic fertilizer. Indeed, uptake of nitrate results in excess uptake of anions over cations, net uptake of protons and thus an increase in the rhizosheath/rhizosphere pH 29 . We found increased pH values in the rhizosheath/rhizosphere indicating that nitrification rates were not inhibited by acidification 65 , 66 . Plant roots can release compounds to suppress nitrification (biological nitrification inhibition) 67 . Inhibition of nitrification is likely to be part of an adaptation mechanism to conserve and use N efficiently in natural systems that are N limiting 68 , 69 . However, this was not shown in soilless culture systems with organic growing medium and tomato plants. In addition, nitrification inhibition is stimulated in the presence of ammonium 67 and we found higher ammonium concentrations in the struvite treatment."
} | 6,049 |
34276250 | PMC8256426 | pmc | 5,496 | {
"abstract": "Poly(ethylene terephthalate) (PET) is an abundant and extremely useful material, with widespread applications across society. However, there is an urgent need to develop technologies to valorise post-consumer PET waste to tackle plastic pollution and move towards a circular economy. Whilst PET degradation and recycling technologies have been reported, examples focus on repurposing the resultant monomers to produce more PET or other second-generation materials. Herein, we report a novel pathway in engineered Escherichia coli for the direct upcycling of PET derived monomer terephthalic acid into the value-added small molecule vanillin, a flavour compound ubiquitous in the food and cosmetic industries, and an important bulk chemical. After process optimisation, 79% conversion to vanillin from TA was achieved, a 157-fold improvement over our initial conditions. Parameters such as temperature, cell permeabilisation and in situ product removal were key to maximising vanillin titres. Finally, we demonstrate the conversion of post-consumer PET from a plastic bottle into vanillin by coupling the pathway with enzyme-catalysed PET hydrolysis. This work demonstrates the first biological upcycling of post-consumer plastic waste into vanillin using an engineered microorganism.",
"conclusion": "Conclusions Low cost and low intensity technologies to valorise post-consumer plastic waste are urgently required to tackle the plastic waste crisis and enable a circular economy. We have addressed this by engineering a novel biosynthetic pathway in the laboratory bacterium E. coli to convert plastic derived monomer terephthalic acid directly into the value-added molecule vanillin using a single engineered microorganism. The reaction is mild, uses a whole-cell catalyst produced from renewable feedstocks and occurs under ambient conditions (room temperature, pH5.5–7), in aqueous media, requires no additional cofactors or reagents and generates no hazardous waste. Maximum vanillin titres of 785 μM (119 mg L −1 , 79% conversion) were achieved after extensive process optimisation studies, a 157-fold improvement over titres from pre-optimisation experiments. Key to this high conversion was biotransformation temperature, cell permeabilisation and use of ISPR to increase flux towards vanillin. Moreover, we have demonstrated that this pathway can utilise TA derived directly from post-consumer plastic waste in a one-pot bioprocess – the first example of biological upcycling of waste PET into a single value-added small molecule. Future studies will focus on intensifying this process through further strain engineering, process optimisation and extension of the pathway to other metabolites. Fundamentally, this work substantiates the philosophy that post-consumer plastic may be viewed not as a waste product, but rather as a carbon resource and feedstock to produce high value and industrially relevant materials and small molecules.",
"discussion": "Results and discussion Construction of a novel enzymatic pathway for vanillin production from TA Our initial focus was on developing a novel in vivo enzymatic pathway for the conversion of TA to the target compound vanillin. Due to the inherent ability of E. coli to reduce aldehydes to the corresponding alcohol, 37 we chose E. coli MG1655 RARE (reduced aromatic aldehyde reduction) as the host microorganism, which has previously been used for the biosynthesis of vanillin from glucose. 38 Inspired by the biodegradation and metabolism of PET via PC by Ideonella sakaiensis , 14 we hypothesised that TA could be converted into vanillin by a de novo pathway comprising: (i) terephthalate 1,2-dioxygenase (TPADO), (ii) dihydroxy-3,5-cyclohexadiene-1,4-dicarboxylic acid dehydrogenase (DCDDH), (iii) carboxylic acid reductase (CAR) and (iv), catechol O -methyltransferase (COMT) ( Fig. 2a ). It is noteworthy that CARs 39 and O -MTs 40 have both been reported to accept PC, dihydroxybenzaldehyde (DHBAl) and vanillic acid (VA) as substrates, such that the pathway may proceed by two possible intermediates (VA or DHBAl) to produce vanillin. Fig. 2 (a) Proposed enzymatic pathway for the conversion of PET to value added product vanillin. LCC: Leaf-branch compost cutinase; TPADO: terephthalate 1,2-dioxygenase; DCDDH: 1,4-dicarboxylic acid dehydrogenase; O -MT: O -methyltransferase; CAR: carboxylic acid reductase; FAD: flavin adenine dinucleotide; NAD(P)H: reduced nicotinamide adenine dinucleotide (phosphate); SAM: S -adenosyl- l -methionine (b) design of pathway enzyme expression constructs pVan1 and pVan2. (c) HPLC traces showing proof of concept for the pathway. Vanillin was only detected when TA was added to cells expressing pVan1, pVan2 and pSfp. The pathway enzymes were assembled onto two plasmids, named pVan1 and pVan2. pVan1 encodes TPADO from Comamonas sp., a heterotrimer comprising subunits TphA1, TphA2 and TphB2, and DCDDH, also from Comamonas sp., which together catalyse the conversion of TA to PC using atmospheric oxygen as the terminal oxidant. Both enzymes have previously been shown to express in E. coli and show activity towards TA and DCD, respectively. 41–44 pVan2 encodes a carboxylic acid reductase from Nocardia iowensis (NiCAR) and a single point mutant of the soluble form of catechol O -methyltransferase (S-COMT Y200L), from Rattus norvegicus ( Fig. 2b and Fig. S1 † ). 39,40 This mutant was chosen for its high stereoselectivity for methylation at the meta -position of PC and DHBAl. 40 NiCAR was selected for the reduction step as it has previously been demonstrated to efficiently reduce both PC and VA to the corresponding aldehydes. 39 Additionally, cells were co-transformed with a third plasmid encoding the phosphopantetheinyl transferase (pSfp) from Bacillus subtilis , which is necessary for post-translational modification of NiCAR. 45 For proof of concept, resuspended E. coli RARE cells expressing pVan1, pVan2 and pSfp ( E. coli RARE_pVanX) were used in a screening scale biotransformation reaction for the conversion of TA to vanillin. Whilst no vanillin was detected from cells expressing only pVan1 or experiments lacking TA substrate, cells expressing all three plasmids with added TA (5 mM) gave a detectable amount of the target compound vanillin (5 μM, <1% conversion) ( Fig. 2c and Fig. S3–S5 † ), with intermediates PC, DHBAl and vanillic acid also being detected at concentrations of 18 μM, 10 μM and 2 μM, respectively (Fig. S5 † ). Process optimisation for maximum vanillin titres Encouraged by these initial data, we sought to maximise vanillin yields by optimisation of protein expression and whole cell reaction conditions. A screen of protein expression media showed M9 minimal media supplemented with casamino acids (M9-CA) to give the highest combined levels of conversion to vanillin and key intermediate PC (Fig. S5 † ). Resuspending whole cells in fresh M9 media proved superior to adding TA to expression cultures during the exponential growth phase, giving a 4-fold increase in vanillin titres (77 μM ± 11 μM, Fig. 3a ). This was hypothesised to be due to the higher cell density and therefore biocatalyst loading of resuspended cells (OD 600(ferm.) = 0.6–2; OD 600(resusp.) = 20). Examination of standard expression parameters such as induction OD, inducer concentration, time and temperature did not lead to significant improvement in vanillin yields. Likewise, sulfur and iron containing expression medium additives such as cysteine, ferrous sulfate and ferric ammonium citrate, which were hypothesised to increase expression levels of [2Fe–2S] containing TPADO, did not give a significant increase in TA conversion levels (Fig. S6 † ). 43,46 However, the addition of trace elements to the growth media led to a 1.5-fold increase in PC titres ( Fig. 3c ). This was hypothesised to improve TPADO and DCDDH activity, which are Fe 2+ and Zn 2+ dependent, respectively. 41,43,44 Interestingly, the addition of benzyl alcohol (BnOH) to the expression culture prior to induction led to a 2-fold increase in PC levels even in the absence of trace elements. Benzyl alcohol is an osmolyte that has been reported to induce expression of endogenous chaperones in E. coli , leading to increased soluble expression of heterologous genes. 47 Accordingly, analysis of protein expression by SDS-PAGE showed more soluble protein expression in the presence of BnOH or trace metals, whilst adding both BnOH and trace metals to the expression culture did not give further increase in either soluble protein expression or vanillin yields ( Fig. 3c and Fig. S7 † ). Fig. 3 Optimisation of vanillin pathway expression and biotransformation conditions. (a) Comparison between fermentation and resuspended whole cells (conditions: 5 mM TA added to 10 mL fermentation reactions at time of induction, incubated at 30 °C for 24 hours). (b) Effect of cell membrane permeabilisation (conditions: 5 mM TA, 30 °C, 24 hours). (c) Effect of addition of trace elements and benzyl alcohol (BnOH) to expression medium (conditions: 5 mM TA, 30 °C, 24 hours). (e) Effect of in situ product removal (ISPR) (conditions: 1 mM TA, 22 °C, 24 hours). (e) Effect of biotransformation temperature (conditions: 5 mM TA, 24 hours). (f) Time course of TA conversion under optimised conditions (1 mM TA, 22 °C, 20%v/v oleyl alcohol (OA)). GTB: Glycerol tributyrate; TPGS: dl -α-tocopherol methoxypolyethylene glycol succinate; β-CD: β-cyclodextrin; PS-EDA: ethylenediamine, polymer bound, 1% cross-linked (1%w/v loading); DVB-MEA: mercaptoethylamine, polymer bound, 1% cross-linked with divinylbenzene (1%w/v loading). * P < 0.05, ** P < 0.005, *** P < 0.0005 (Welch's T -test). Next, we investigated the effect of the whole cell biotransformation conditions on conversion of TA to vanillin and pathway intermediates. As TPADO is O 2 dependant, we hypothesised that increasing reaction headspace would increase conversion of TA to PC. This was confirmed by observing a 65-fold improvement in vanillin titres (5 μM ± 3 μM to 327 μM ± 15 μM) when the headspace to reaction volume ratio was increased from 1 : 5 to 1 : 99 (Fig. S8 † ). Further improvement in TA conversion was accomplished by increasing E. coli cell membrane permeability to TA. Whilst an influx transporter for TA in Pseudomonas sp. has been reported, 48 E. coli is not known to express a transporter capable of importing TA to the cytosol. Therefore, cell membrane permeabilization strategies were investigated. In particular, n -butanol ( n -BuOH) has been shown to improve cell membrane permeability towards small molecules 49,50 and was therefore hypothesised to improve TA conversion by increasing substrate concentration in the cell interior. Whilst 0.1%v/v had little effect on conversion, the addition of 1%v/v n -BuOH to the biotransformation buffer resulted in a 3-fold increase in cumulative conversion of TA to vanillin and pathway intermediates ( Fig. 3b ). Conversely, attempts to improve membrane permeability through freeze/thaw cycles or the addition of lysozyme to the reaction buffer did not lead to increased vanillin concentrations. Experiments using lysed E. coli RARE_pVanX cells and experiments using co-cultures of E. coli RARE_pVan1 and E. coli RARE_pVan2_pSfp gave negligible (<1%) levels of vanillin, indicating that co-localisation of the pathway enzymes within a single cell is advantageous in this system. Finally, the addition of l -Met (10 mM) resulted in a 2-fold increase in vanillin titres (Fig. S9 † ). This aligns with previous reports of in vivo pathways employing S -adenosylmethionine (SAM) dependant methyltransferases (MTs), which note supplementation of reaction buffer with l -Met as being vital to achieve maximum product titres. 51 The doubly charged nature of terephthalate at neutral pH was also theorised to impede diffusion of TA across the cell membrane and hence the effect of biotransformation buffer pH was investigated. As predicted, a sharp decrease in TA to PC conversion from pH6 to 8 was observed. Upon screening conditions <pH7, pH5.5 was found to be optimum to balance maximum TA diffusion into the cell whilst minimising acid induced stress to the cell (Fig. S10 † ). Cell density of resuspended E. coli RARE_pVanX was also studied. Whilst there was minimal effect on product titres and distribution between OD 600 = 10–60, a significant increase in vanillin concentration (350 μM ± 62 μM to 480 μM ± 36 μM) was obtained at OD 600 = 80, with a switch from PC to vanillin being the predominant product (Fig. S11 † ). Biotransformation temperature also had a dramatic effect on vanillin yields ( Fig. 3e ). Decreasing the reaction temperature from 30 °C to 22 °C gave a 5-fold improvement in vanillin yields (577 μM ± 22 μM compared to 117 μM ± 40 μM at 30 °C). Interestingly, the ratio of pathway intermediates formed also changed upon lowering the reaction temperature. Vanillic acid (VA) was produced at 30 °C (20 μM ± 8 μM), whereas VA titres from lower temperature reactions were negligible. This indicates that at biotransformation temperatures of 22 °C and lower, the pathway proceeds via NiCAR mediated reduction of PC followed by S-COMT mediated methylation to give vanillin, whereas at 30 °C the alternative pathway via vanillic acid also operates. Decreasing the temperature to 16 °C gave no further improvement in product conversion. Finally, we hypothesised that in situ product removal (ISPR) could improve vanillin yields through mitigating the toxicity of vanillin to E. coli (Fig. S12 † ) and increasing flux towards vanillin, the most hydrophobic molecule in the pathway (log P vanillin = 1.2). 52 Three ISPR strategies were investigated: (i) organic solvent overlays, 53 (ii) product entrapment in biocompatible micelles 54 or β-cyclodextrin 55 and (iii) product trapping via reversible nucleophilic addition to the aldehyde moiety of DHBAl and vanillin. 56,57 Whilst the product trapping reagents did not improve product titres, all the solvent overlays and product entrapment ISPR reagents increased vanillin yields relative to the control experiment ( Fig. 3d ). Out of these, oleyl alcohol (OA) and vitamin E derived biocompatible micelles TPGS-750-M were selected for further study based on initial data showing the highest vanillin concentrations and lowest levels of the intermediate DHBAl. The biotransformation of TA to vanillin in the presence of no ISPR reagent, 20%v/v OA, or 2%w/v TPGS-750-M was carried out with varying TA concentrations to investigate whether ISPR enabled higher vanillin titres. These data showed OA to be the superior ISPR reagent, giving maximum vanillin titres of 744 μM ± 100 μM from 1 mM TA. The presence of OA also led to increased conversion of PC to DHBAl, however there was no significant increase in vanillin titres with increased TA concentration, indicating the bottleneck in the pathway to be the final COMT mediated methylation step (Fig. S13 † ). Strategies to alleviate this bottleneck, such as screening a library of alternative O -MTs and upregulating expression of SAH degradation enzymes, 58,59 will be the focus of further study and development of this pathway. Finally, a time course experiment under the optimised conditions with an oleyl alcohol overlay showed maximum vanillin titres to be obtained after 16 hours, with sequential formation and consumption of PC and DHBAl also being observed ( Fig. 3f ). This led to the final optimised biotransformation conditions for TA to vanillin conversion: namely E. coli RARE_pVanX cells resuspended in M9-glucose supplemented with l -Met and n BuOH, pH 5.5, incubated with TA for 24 hours at room temperature with an oleyl alcohol overlay. Product formation under the optimised conditions was confirmed upon scaling up the biotransformation to 40 mL scale and analysing the reaction products by NMR spectroscopy (Fig. S14 † ). Upcycling of post-consumer PET waste into vanillin Finally, we set out to demonstrate the application of the TA to vanillin pathway in valorisation of post-consumer plastic waste. We selected the thermostable enzyme LCC WCCG 15 (hereafter referred to as LCC) as a biocatalyst to aid hydrolysis of PET into TA. Unlike PETase from Ideonella sakaiensis , LCC releases TA directly and does not require an additional enzyme to hydrolyse mono-2-hydroxyethyl terephthalate (MHET) for release of TA. PET from a post-consumer plastic bottle was treated with semi-purified LCC at 72 °C ( Fig. 4a ). The reaction was cooled to room temperature and freshly prepared E. coli RARE_pVanX and a biotransformation buffer concentrate were added, and reactions were analysed after 24 hours. Gratifyingly, without any process optimisation, vanillin was detected when all pathway components were present (68 μM, Fig. 4b ). Vanillin was not detected in control experiments lacking PET or cells expressing the pathway enzymes. Low levels of vanillin were detected in experiments lacking LCC, which is hypothesised to be due to background PET hydrolysis in LCC reaction buffer (pH10) in the absence of LCC (Fig. S15 † ). The addition of an oleyl alcohol overlay did not lead to a significant increase in vanillin titres, which was hypothesised to be due to the lower TA concentrations from PET degradation (300–400 μM). Fig. 4 Conversion of a post-consumer PET bottle into vanillin. (a) Overview of the one-pot, two-step process to convert PET into value-added product vanillin. E. coli RARE_pVanX refers to E. coli RARE expressing plasmids pVan1, pVan2 and pSfp. (b) Data showing production of vanillin only in the presence of cells expressing the vanillin pathway enzymes and the feedstock PET."
} | 4,429 |
36259916 | PMC9828261 | pmc | 5,497 | {
"abstract": "Abstract Control phenomena in biology usually refer to changes in gene expression and protein translation and modification. In this paper, another mode of regulation is highlighted; we propose that photosynthetic organisms can harness the interplay between localization and delocalization of energy transfer by utilizing small conformational changes in the structure of light‐harvesting complexes. We examine the mechanism of energy transfer in photosynthetic pigment‐protein complexes, first through the scope of theoretical work and then by in vitro studies of these complexes. Next, the biological relevance to evolutionary fitness of this localization‐delocalization switch is explored by in vivo experiments on desert crust and marine cyanobacteria, which are both exposed to rapidly changing environmental conditions. These examples demonstrate the flexibility and low energy cost of this mechanism, making it a competitive survival strategy.",
"conclusion": "3 CONCLUSION In this review, we examined delocalization in biological systems fulfilling a new role—control of light harvesting efficiency. Interaction between small coherent domains enables flexibility and quick conversion between energy transfer and dissipation. In analogy to allosteric changes in a protein, small changes enable loss or regeneration of delocalization in larger domains, quickly and reversibly channeling energy transfer in the system. Minute changes at low energy cost to the organism can result in large effects, making the process both efficient, reversible, and flexible (Figure 3A ). Moreover, both lab and field examples show that this mechanism can indeed enhance adaptation and confer an evolutionary advantage to photosynthetic organisms exposed to extreme changes in environmental conditions. FIGURE 3 (A) In biology, both efficiency (associated with order) and flexibility (associated with disorder) are important for survival. Thus, the optimal range for biological processes lies in between maximum disorder and maximum order. (B) Two examples of LH structures in photosynthetic organisms, PBS and LHCII. Presented are the whole antenna structure (I), magnification of a single subunit (II), and the pigments alone (III). Each LH structure exhibits different mechanisms that are optimal for each organism's environment (IV). Phycobilisome (PBS) is a LH complex found in cyanobacteria and red algae, which need flexibility to adapt to unpredictable and rapid changes in conditions. Light harvesting complex II (LHCII) is a LH complex found in land plants and green algae. It exhibits more efficient energy transfer but lacks flexibility. These two structures represent two different options in the range of energetic coupling observed in photosynthetic organisms—note the differences in typical distances between the two structures. Our thanks to Emma‐Joy Dodson for creating these structural images. As mentioned, there is great variability in the structural composition and arrangement of photosystems in nature (Figure 3B ) (Qian et al., 2021 ). For instance, the antennae of Acharyochloris marina are composed of long, straight rods of PC, which assist in preferential harvesting of far‐red light (Rast et al., 2019 ). Purple bacteria, for their part, use chromatophores, which are pseudo‐organelles that contain pigment‐protein complexes for light harvesting and RCs (Chandler et al., 2014 ). Land plants have thylakoid membranes which integrate specific protein‐pigment complexes at significantly different locations, allowing for step‐wise control of the photosynthetic process (Johnson et al., 2014 ; Walker et al., 2020 ). All the above can potentially use the switch from localized to delocalized EET in a myriad of interesting and yet unknown ways. In contrast, green sulfur bacteria that live in the deep ocean and are exposed to minimal amounts of light, have crystalline‐like structures of pigments called chlorosomes, which are inherently inflexible (Pšenčík et al., 2009 ). However, since the changes in conditions and light intensity are minimal and far less drastic than for the other organisms discussed here, this would not be a major limitation. This highlights the difference between extreme static conditions and extreme dynamic conditions. An intriguing new front to explore in this sense would be photosynthetic organisms exposed to extreme temperature changes, where flexibility and rapid adaptation would be key components in an organism's success and proliferation.",
"introduction": "1 INTRODUCTION The biological realm is rarely associated with truly quantum or coherent effects, as these are deemed too sensitive to manifest in the relatively high temperatures and larger scales associated with biology. There is, however, growing evidence that certain quantum effects play a role in some biological processes. One example is the radical pair mechanism (RPM) suggested to be involved in magnetic field sensing for bird navigation; another is the exciton energy transfer (EET) in photosynthetic light‐harvesting systems (Lambert et al., 2012 ; Rodgers & Hore, 2009 ). Such examples are still controversial, for instance, alternative hypotheses to the RPM have been proposed for bird navigation (Natan & Vortman, 2017 ; Werber et al., 2022 ). Photosynthesis is the backbone of life as we know it; it is the engine converting solar energy into chemical energy stored in sugars that organisms use to grow and multiply. Absorbed solar energy is a double‐edged sword: without it, photosynthesis is nonexistent and life grinds to a halt, but on the other hand, an excess of energy can be highly destructive (Taiz et al., 2015 ). Unregulated absorption of solar energy can give rise to harmful oxidative radicals, which damage membranes and proteins or even the DNA of an organism. As such, the regulation of solar absorption and dissipation is key in maintaining homeostasis in photosynthetic (Cruz et al., 2004 ; Taiz et al., 2015 ). In certain conditions, the quantum yield of photosynthesis can be extremely high, up to 0.8 for the initial reaction (Barber, 2007 ; Nelson & Yocum, 2006 ). The quantum yield is a measure of efficiency, the number of photons successfully converted to chemical energy divided by the number of photons absorbed. Even so, the efficiencies measured in natural environments are normally much lower (Barber, 2007 ). This can be puzzling at first glance. However, it is reasonable to assume that efficiency is sacrificed in favor of increased stability and robustness. The mechanisms dictating energy transfer efficiencies are under intense study but are far from being fully understood, classical models, for instance, predict even lower efficiencies than experimentally observed values (Chenu et al., 2017 ). Light harvesting complexes, though ranging in size and composition, exist in the realm where both quantum and classical energy transfer is feasible. This review explores the possibility that rapid switching between different organization regimes is employed as a means of energy transfer regulation. The switching between coupling domains provides control over light harvesting efficiency that can be achieved just by small conformational changes. Several experimental results support the existence of coherent effects in light harvesting complexes (coherent: Box 1 ‐ Baumgratz et al., 2014 ; Young, 1804 ) (experimental results: Engel et al., 2007 ; Herek et al., 2002 ; Hildner et al., 2013 ; Rathbone et al., 2020 ; Romero et al., 2017 ; Schlau‐Cohen et al., 2013 , 2015 ), but there is still an ongoing debate over whether they are indeed fully quantum or not (Keren & Paltiel, 2018 ). For example, although 2D electron spectroscopy of a photosynthetic pigment‐protein complex exhibited picosecond time scale beats (Engel et al., 2007 ), these can be interpreted in two ways. Either they represent electronic coherence from the quantum properties of the wave packet, or they are a result of the coupling of the excitation to mechanical vibrations of the pigment in the protein matrix (Cao et al., 2020 ; Keren & Paltiel, 2018 ; O'Reilly & Olaya‐Castro, 2014 ; Runeson et al., 2022 ; Thyrhaug et al., 2018 ). These discussions often boil down to a question of scale—what frequency would be relevant to a quantum effect versus a classical one? This review does not attempt to distinguish between the two, rather, it aims to show how changes in coupling and, therefore, coherence can be utilized to shift between quenching and harvesting of solar energy. This is similar to coupling control, as seen in waveguides and light propagation, where enhanced coupling leads to delocalization of the wave packet (Gilead & Silberberg, 2017 ). The inherent disorder of the system and the intermediate coupling between pigments makes it possible to swap between localized and delocalized energy states. BOX 1 \nWhat do we mean by “coherent”?\n In physics, coherence describes a constant difference between the phases (angles) of waves that have the same frequency. Coherent sources can create interference patterns, while incoherent sources, which have a changing relation between their phases, cannot. The easiest way to create two coherent sources is to split a single source of coherent light, similarly to the famous double‐slit experiment which showed the dual nature of light. \n Coherence can refer to a completely classical phenomenon of wave interference, but it can also be used in a quantum sense to differentiate between “pure” and “mixed” states. The laser, superconductivity and superfluidity are all macroscopic phenomena that arise from a highly coherent state in certain quantum systems. Coherent control of quantum systems has recently been formulated as a resource theory by Romero et al. ( 2017 ) showing that the relevant resources of entanglement and coherence are found to be equivalent and closely related to a measure of discord. Many different definitions are used for the terms “coherent” or “delocalized”; we will adhere to the definition of Chenu and Scholes ( 2015 ) who define coherent EET as the regime between the Förster and Redfield limits (Novoderezhkin et al., 2004 ) (Box 2 ; Schneckenburger, 2020 ; Seibt & Mančal, 2017 ). This is relevant because photosynthetic light harvesting occurs mostly in this regime (Schneckenburger, 2020 ). To use an excellent explanation attributed to Prof. Rienk van Grondelle (Figure 1A ), we can imagine the energetic landscape of the photosystem as a football field with holes the size of ping pong balls. Localized states will be the size of marbles and easily get stuck in one of the holes. Footballs, on the other hand, will pass over the holes and move freely around the field—these will be delocalized states. Furthermore, delocalized states will not be associated with phase coherence, rather, they will define an electronic excited state comprised of a superposition of excitations at different molecular sites. Another useful definition for this article is the photosynthetic unit (Mauzerall & Greenbaum, 1989 ), defined as the sum total of pigments that contribute excitation to a single reaction center. A reaction center (RC) is the location of the photochemical charge separation reaction in the photosystem, which is the culmination of EET between the pigments, and the driving force behind the conversion of light energy to chemical energy. BOX 2 \nTwo regimes of energy transfer: FRET vs Redfield\n Förster resonance energy transfer (FRET) is based on the theory of non‐radiative energy transfer presented by Theodor Förster in 1948. It describes resonant energy transfer by dipole–dipole interaction from a donor to an acceptor molecule. Due to the R −6 dependence on molecular distances for dipole–dipole interactions, FRET is considered relevant in distances of around 5 nm . Redfield theory is derived from the Redfield Equation, which describes the decay of excitations in a quantum system due to external fluctuations, in a model with weak system‐bath interaction. The relevant distances for Redfield energy transfer are sub‐nanometer , as befit a quantum theory. Since Redfield transfer is influenced by energy gaps, for small enough gaps the Redfield rates are higher than the Förster rates. FIGURE 1 (A) Graphical representation of the “football field” explanation for localized versus delocalized states. The marbles fall into the holes and are localized, while the footballs pass over them and are thus delocalized over the whole field. (B) In many of the systems studied, order generates stronger coupling between subunits, leading to delocalization effects. On the other hand, disorder leads to weaker coupling and localization in the system. The x axes in each of the graphs represent the 1D reduction of 3D space. The y axes represent the wavefunction of the exciton, i.e., the probability density in location space. Thus, delocalization is represented by a disseminated wavefunction in space, while localization is represented by a noticeably higher probability density in a specific location. To date, numerous examples have exhibited delocalization effects in photosynthesis. Such examples provide us with the scale over which we can expect to see such effects. In 2007, Engel et al. ( 2007 ) showed quantum beats in the 2D spectra of the Fenna–Matthews–Olson (FMO) protein‐bacteriochlorophyll complex. This complex is found in green sulfur bacteria and consists of three subunits with eight bacteriochlorophylls (BChl, a type of pigment) each (Ben‐Shem et al., 2004 ; Camara‐Artigas et al., 2003 ; Fenna & Matthews, 1975 ; Li et al., 1997 ). Further research using 2D echo spectroscopy has provided evidence for quantum coherent sharing of electronic excitation in isolated antenna complexes from marine cryptophytes (Collini et al., 2010 ). A subsequent study demonstrated the relation between protein‐pigment complex structure and the coherent coupling between pigments in that structure by comparing the “open” and “closed” configuration of phycobiliprotein antennae in related cryptophyte species— Rhodomonas , Chroomonas , and Hemiselmis (Harrop et al., 2014 ). Another important finding is the ability of single light harvesting (LH) complexes to “blink” between energy‐transferring and energy‐quenching states (Chmeliov et al., 2013 ; Schlau‐Cohen et al., 2013 , 2015 ). Two types of LH complexes were found to exhibit this behavior. These are the LH2 complex, which has a ring‐like structure composed of nine subunits with three BChl and one carotenoid each, and the LHCII complex, which contains three subunits with 14 chlorophyll and four carotenoids each. Additionally, long‐lived coherences of at least 400 femtoseconds were observed by Hildner et al., 2013 on single LH2 complexes, following previous work on quantum coherent control in this system (Herek et al., 2002 ). All examples given are remarkable but refer to complexes much smaller than a whole photosynthetic unit. We can therefore assume that the energy transfer of a whole photosynthetic unit will exhibit more complex behavior (Romero et al., 2017 ). An important point to address is the dimensionality of the energy transfer path. Anderson localization dictates that in 1D, localization will inevitably occur due to the weak interaction between neighboring points in a lattice (Anderson, 1958 ) (Box 3 ). If we assume that energy transfer takes place along a given 1D path, this will prescribe localization and quenching. So, to achieve large enough delocalization, one can either enhance coupling or add another degree of freedom to the energy transfer path. BOX 3 \nWhat is Anderson localization?\n In 1958, P.W. Anderson published a paper showing that even a small amount of disorder can lead to localization in a system with low dimensionality . The paper presented a simple model for processes such as spin diffusion or impurity band conduction. In these processes, transport occurs by quantum‐mechanical “jumps” between neighboring points in a random lattice. It was shown that at sufficiently low densities, transport does not take place at all, and the exact wave functions are localized in a small region of space. In the model, 𝑉 is the interaction matrix element between neighboring sites in a 3D lattice. The higher the disorder in a system, the weaker the interaction between the sites . If V falls off faster than 1/𝑟 3 and the average value is smaller than a certain critical value 𝑉 0 , then there can be no diffusion. Therefore, when applying the theory to 1D, it can be shown that localization must occur, no matter how small the disorder is. Though the mechanism of energy transfer is a fascinating subject in and of itself, from a biological perspective, an even more relevant issue should be addressed. As put forth by Chenu and Scholes ( 2015 ), the main question in this discussion is whether long‐lived delocalization in photosystems confers an evolutionary advantage to these organisms. It is possible that the biological world has harnessed a toolkit of rapid swapping between localization and delocalization that increases fitness. There are many different structures of pigment‐protein complexes in nature, and even within the same organism, these structures can change depending on external stimuli (A.W.D. Larkum, 2003 ; Rathbone et al., 2020 ; Torres et al., 2014 ). The importance of this diversity may be in creating the possibility for operating at specific energy transfer regimes that will best suit a given set of environmental conditions. This paper will attempt to answer this central question by reviewing data from organisms, cyanobacteria, in particular, subjected to fast‐changing conditions, who appear to utilize the localized–delocalized switch to adapt to these changes swiftly and efficiently."
} | 4,451 |
37512813 | PMC10384328 | pmc | 5,498 | {
"abstract": "In this paper, sediments from the Santiago River were characterized to look for an alternative source of inoculum for biogas production. A proteomic analysis of methane-processing archaea present in these sediments was carried out. The Euryarchaeota superkingdom of archaea is responsible for methane production and methane assimilation in the environment. The Santiago River is a major river in México with great pollution and exceeded recovery capacity. Its sediments could contain nutrients and the anaerobic conditions for optimal growth of Euryarchaeota consortia. Batch bioreactor experiments were performed, and a proteomic analysis was conducted with current database information. The maximum biogas production was 266 NmL·L −1 ·g VS −1 , with 33.34% of methane, and for proteomics, 3206 proteins were detected from 303 species of 69 genera. Most of them are metabolically versatile members of the genera Methanosarcina and Methanosarcinales , both with 934 and 260 proteins, respectively. These results showed a diverse euryarcheotic species with high potential to methane production. Although related proteins were found and could be feeding this metabolism through the methanol and acetyl-CoA pathways, the quality obtained from the biogas suggests that this metabolism is not the main one in carbon use, possibly the sum of several conditions including growth conditions and the pollution present in these sediments",
"conclusion": "5. Conclusions The low methane concentration in the biogas of the first experiment indicated that the performance of SRS as an inoculum to produce methane is not good enough. However, the subsequent proteomic analysis suggests that in SRS, there are diverse euryarcheotic species with a high potential for methane production. The abundance of members of the order Methanosarcinales could be important to improve methane production; enrichment of these species in the inoculum using culture medium directed to favor the growth of these organisms could be a first approach. On the other hand, some proteins were identified by a relatively large number of peptides, although their abundance in terms of mass was not the greatest. This suggests that peptide digestion is efficient for these proteins, which could be used as an identification marker for these species (i.e., MtaB to identify Methanosarcina mazei WWM610). Besides that, the abundance of certain proteins in SRS suggests that some metabolisms are established and correspond to nutrients in the culture medium and growth conditions. The stress imposed by the change in the environment of the SRS and the relative abundance of carbon sources promote its use with the consequent processing of ATP and DNA. In SRS, some species are relevant not only because of their capacity to produce methane. For example, the genus Methanobrevibacter and its abundant adhesin-like proteins could be advantageous for the formation of a physical structure for consortia, and syntrophic relations between not only archaea, but also bacteria. In addition, in bioreactors it is desirable to have granular consortia; this facilitates the treatment of wastewater and the subsequent separation of treated water and granular sludge. The diversity of metabolisms found in SRS gave us insight into the complex interactions between archaeal species. Something relevant was the presence of methanotrophic archaea. Perhaps their presence in bioreactors for biogas production is not desirable; however, in nature, they can alleviate part of the problem of uncontrolled methane generation. These uncultured methanotrophs and the presence of little more than 8% of expressed uncharacterized proteins in SRS show a potential research area. It is necessary to say that the Santiago River is a natural resource that requires an urgent intervention to recover its natural conditions to support a healthy ecosystem.",
"introduction": "1. Introduction The Río Grande de Santiago (Santiago River) is part of the Lerma–Chapala–Santiago Basin (LCS), and belongs to rivers with eastern slope, descending roughly 1700 m, from Jalisco State to the Pacific Ocean coast in Nayarit State ( Figure 1 ). The Santiago River is eroding the Neo volcanic belt above the North America plate, flowing for 562 km. It rises between the Zula River and Chapala Lake (20°20′41.0″ N 102°46′44.1″ W), bordering the Metropolitan Area of Guadalajara (AMG; from its name in Spanish) across Santiago’s Canyon flowing from north to west over the Sierra Madre Occidental. The Santiago River is in Nayarit through La Yesca, feeds the hydroelectric power plant El Cajón, and finally discharges close to San Blas in the Pacific Ocean (21°38′20.9″ N 105°26′41.5″ W). Chapala Lake is the central water body of LCS, can store 8126 billion liters of water, and its main tributary is the Lerma River. That and the Santiago River are two of the most polluted rivers in México [ 1 , 2 ]. Both rivers flow around the main urban areas in México: the Lerma River bordering the metropolitan area of the Mexican Valley (ZMVM) with 19.38 million habitants, and the Santiago River bordering the AMG with 5.26 million habitants [ 3 ]. These rivers receive not only municipal wastewater, but also industrial discharge, making treatment of water difficult and contributing to the increasing prevalence of diseases [ 4 , 5 ], social inequities [ 6 ], and visible environmental degradation. These anthropogenically imposed water conditions change the natural transfer of oxygen, stimulate the degradation of anaerobic organic matter, generate water toxic to most pluricellular organisms, and promote the proliferation of vectors such as the mosquito. This imbalance in water conducted across the Santiago River contributes to thriving bacterial and archaeal consortia. The sewer smell, disrupting organoleptic characteristics, the absence of fish and native birds, and mosquito swarms are the obvious indicators of environmental degradation in the Santiago River. Not only is water quality affected by pollution in the Santiago River, but the organic matter load is also converted by anaerobic archaea into methane, a less persistent greenhouse gas, but more powerful than CO 2 . Methane is a reactive gas with chemical activity in the troposphere, mostly modifying hydroxyl concentrations [ 7 ]. Anthropogenic methane emissions rose 355,801 kilotons (kt) in 2022, agriculture being the primary source with 37% (141,954 kt), followed by energy (133,351 kt) and waste (70,759 kt) [ 8 ]. Besides that, with wetlands and oceans, sediments (lakes and rivers) produce 371,000 kt by natural processes [ 9 ]. Additionally to this, current archaeal genetic information has shown the diversity and global relevance of this root of the tree of life [ 10 ]. Research on archaea has gained interest because of the application of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology in genetic engineering [ 11 ], the acquisition of thermostable enzymes [ 12 ], sustainable energetics because of their ability to produce methane [ 13 ], and other recent biotechnological applications [ 14 ]. In the environment, these microorganisms are relevant in the biogeochemical cycles of elements [ 15 , 16 ], such as carbon for methane production and consumption [ 17 ] as well as nitrogen [ 18 , 19 ]. In addition, the metabolic pathways of the archaea domain are diverse in the use of carbon sources [ 20 , 21 ], processing of membranes [ 22 , 23 ], nucleic acids [ 24 , 25 ], protein activity, processing [ 26 , 27 ], electron transport [ 20 , 28 , 29 ], and, recently, the identification of a putative nucleolus structure in the crenarchaeon Saccharolobus solfataricus related to ribosome biogenesis [ 30 ]. Given the importance of study of the archaea, the present research aimed to characterize biogas production and determine the proteins present in the sediments of the Santiago River related to methane-processing metabolisms. The sediments of the Santiago River could be used as alternative inoculums in an anaerobic digestion system. For this, experiments were carried out to evaluate the volumetric yield of biogas per gram of microorganisms as volatile solids from the ratio of methane in biogas. Using a handmade euryarcheotic protein database and mass spectrometry, it was possible to determine the main species and metabolisms present in the sediment of the Santiago River; using this information, the pathways of methane production will be discussed.",
"discussion": "4. Discussion The preferred composition of biogas is a high content of hydrogen or methane, perhaps both. This ensures rapid oxidation of the biogas, releasing high heat energy that can be coupled to various anthropic processes. The establishment of control states that favor biological growth in bioreactors is on its way to a steady state. For our initial growth conditions, this state for biogas production is reached and changed in a reconciling mathematical curve ( Figure 2 ). Although the pattern found in our best-represented proteins suggests that the metabolism of methanol, formate, and acetyl-CoA are established and phosphorylation by V-ATP synthase is also present ( Figure 3 ), the low biogas quality showed that methane metabolism is not privileged in SRS. The above could be attributed to a different condition in this first experiment: the consortia in SRS are not accustomed to these initial experimental conditions [ 66 ]. The change from an oligotrophic site in nature to a controlled system with a complete growth medium, including thermal and osmotic shock, substrate/cofactor/inoculum ratios, and mechanical agitation to ensure homogeneity [ 42 ], as well as a sufficient abundance of organisms that preferentially produce hydrogen or methane, but not H 2 S and CO 2 [ 67 ], among others. In the case of the present study, perhaps in addition, the adaptability of the archaeal consortia in high-arsenic sediments and methanotrophic species could be of importance. Interestingly, the archaeal machinery of arsenic metabolism has not been detected [ 68 ]. The water quality of the Santiago River is monitored by the State Water Commission of the State of Jalisco México [ 69 ]. They report 52 physicochemical and biological parameters, including heavy metals. This information is contained in a database that begins in 2003 and continues to the present. During this period, five water bodies in Jalisco were monitored monthly at different sites, including the Rio Santiago. For the sediment-sampling site ( Figure 1 ), a maximum of 19.9 μg/L arsenic was recorded on July 1, 2021. This suggests that although the inorganic fraction in the sediment contains a significant concentration of arsenic, the water found in the interface contains a relatively high concentration [ 70 ]. This environment does not promote an expression of protective metabolism for arsenic in SRS and could not be the reason for the low-quality biogas produced [ 71 ], but some proteins, such as thermosome subunits and DnaK proteins ( Figure 5 ), have been found in similar conditions [ 72 ]. In SRS, methanotrophic archaea represented only 5.6% of all species found, and their proteins represented 7.7% of the total proteins ( Figure 5 ). However, only three methanotrophic Mcr proteins were detected, suggesting that methane oxidation is not an abundant biological process in SRS and its contribution to low biogas quality is minimal. Interestingly, the three species with the most detected proteins ( Figure 11 ) have a similar number of proteins related to phosphorylation, but only the first and second have the same number of proteins related to methanogenesis, and the third has only one protein related to the one-carbon metabolic process. This suggests that under our conditions not all species are significant methanogens. For the third, the most identified BP was the regulation of DNA template transcription. Factors such as completeness of annotation and amount of information affect the bioinformatic analysis of proteomes. In this work, 464 proteins without annotation were found. This represents 14.4% of the total detected proteins. This type of work requires greater integration of the data and graphical forms of representation, although the molecular process is known. The biological function to which it belongs, and its cellular location allows us to have a global view of the metabolic pathways established in the growth of SRS, it is necessary to have the support of a curated database to reduce the bias of the information. It could be assumed as obvious that the dominant MF in archaeal cells is related to the bioenergetics of ATP, in this study we found that ATP binding is the most detected MF, three times more than the second function, DNA binding ( Figure 8 ). For BP, as expected, methanogenesis is the most annotated, with some authors even describing exactly what type of methanogenesis it is (methanol, acetate, etc.). However, the lack of information starts to become relevant as only 57% of the detected proteins have an annotation ( Figure 9 ). In SRS, the cellular distribution of the detected proteins is balanced between cytoplasm and membrane, as in the previous case, the lack of annotations is relevant with more than 63% of the proteins without annotations ( Figure 10 ). Further proteomic studies are needed to analyze the results obtained so far and to make comparisons of the dominant state of the functions, processes and components involved in the homeostasis of microbial consortia."
} | 3,371 |
34429124 | PMC8385953 | pmc | 5,499 | {
"conclusion": "Conclusions We report that Bd21-3 and Si form a mutualistic symbiosis with a promoting effect on plant yield and development, accompanied by changes in gene expression in both organisms, including putative protein Si effectors and RNAi-related genes. sRNA profiles of both organisms also changed, indicating that this model system will provide important insights into the multiple layers of regulation and interaction between beneficial fungi and cereal hosts. Within the broader scope of plant-mutualist interactions, we show that detection of putative RNAi-involved sRNAs in an interaction highly benefits from simultaneous transcriptome analysis and indicate an involvement of sRNA-based regulation in defense responses, nutritional reprogramming, and colonization maintenance. Alongside other experimental approaches in plant-microbe interactions (eg. sRNA uptake studies [ 83 ]), developing a deeper understanding of the communication mechanisms that modulate mutualistic interactions is highly relevant for establishing robust growth promotion and protection strategies in crops.",
"discussion": "Discussion We established and studied the interaction between Brachypodium distachyon —a model Pooideae plant with shared synteny to major cereal crops—and Serendipita indica —a beneficial endophyte with an exceptionally large host range. This particular combination of traits adorning the Bd-Si interaction has great translational value towards filling in the gaps in knowledge about plant symbioses, especially their transcriptomic and sRNA expression profiles and the significance of RNAi. We show that Si colonizes Bd , resulting in shoot growth promotion, earlier flowering, and improved grain development. In comparison, earlier studies characterizing the interaction between Si and barley have demonstrated that fungal hyphae establish an interface with the root cell plasma membrane at an early colonization stage, followed by expansion of an extracellular hyphal network, intercellular growth, and intracellular penetration of cortical and rhizodermal cells [ 26 ]. Around 3 to 5 DPI, Si starts the switch from a biotrophic to a saprophytic lifestyle [ 26 , 27 ]. Although this change involves intracellular hyphae extensively colonizing dead host cells and gradual digestion of cortical cell walls, the plant still benefits from the fungal presence. Consistent with these findings, our microscopic analyses confirmed proliferation of Si chlamydospores and both inter- and intracellular colonization of Bd21-3 cells in the root differentiation zone from 4 to 14 DPI. Detection of proliferating hyphae that were not wrapped in plasma membrane further suggests that Si is colonizing dead surface plant root cells at 4 DPI [ 25 , 26 ]. Transcriptional changes detected during the Bd-Si interaction To investigate colonization of Bd21-3 by Si , we analyzed Si DEGs in colonized vs. axenic mycelium samples. Gene ontology analysis indicated enrichment in genes involved in various metabolic and catalytic processes. DEGs with the greatest changes in expression play roles in plant cell wall degradation, carbohydrate metabolism and nutrient acquisition. These changes in nutritional reprogramming are to be expected, considering the different nutritional content that Si has accessible in planta vs. axenic CM plates and a more detailed look into the roles of the changed genes unveils a typical switch of fungal lifestyle. Examples of upregulated Si genes involved in cell wall degradation include a probable Pectate lyase , Endo-1,4-beta-xylanases , Cellulose 1,4-beta-cellobiosidase , and Rhamnogalacturonan acetylesterase . The genes encoding these hydrolytic enzymes, which have undergone expansion in the Si genome [ 49 ], are similar to those upregulated in Si during saprophytic growth on autoclaved barley roots at 3 DPI and 5 DPI [ 22 ]. PiAMT1 , encoding a high affinity ammonium transporter also was upregulated (logFC = 3.35; padj < 0.0001). Other upregulated genes encode enzymes involved in carbohydrate metabolism, including probable glucosidases, glucanase, and galactosidase. These proteins may modulate glucose concentration, which then regulates expression of some cell-wall degrading enzymes [ 22 , 50 ]. Some of the 174 putative effector protein-encoding genes also are differentially expressed during Si colonization of barley and Arabidopsis [ 22 , 27 ]. Six of these proteins (Additional file 2 : Table S4) contain the Si -specific DELD domain, which suggests that Si utilizes a common protein effector arsenal to colonize various hosts. Considering highly downregulated Si DEGs, several encoded proteins are associated with adaption to nutrient availability ( Accumulation of dyads protein 2 , ADY2 ; Succinate-fumarate transporter ) and nutrient acquisition ( Acyl-CoA dehydrogenase ; Carnitine acetyltransferase , CRAT ; Phenylalanine ammonia-lyase , PAL [ 51 , 52 ];). Their reduced expression suggests ample nutrient availability at 4 DPI. Given the similarities in the Si transcriptome during colonization of Bd and barley, we propose that these fungal-plant interactions follow a pattern, and that by 4 DPI, a network of plant-endophyte communication cues has initiated a tightly controlled transcriptional program, leading to a shift from biotrophic to saprophytic growth. Roots of Bd21-3 plants also displayed substantial transcriptional reprogramming following Si colonization. Gene ontology term analysis indicated enrichment in genes involved in catalytic and oxidoreduction-associated processes. Bd21-3 DEGs exhibiting the greatest changes in expression between colonized and non-colonized plants are related to stress-response, defense, and plant development. Of the downregulated Bd21-3 genes, several encode proteins commonly associated with stress responses, including a peroxidase, a wound-induced protein , and a putative protein kinase . Additionally, members of the Heat-shock protein gene family [ 53 ] are commonly induced in Bd during abiotic stress and members of the Abscisic acid/water deficit stress (ABA/WDS)-induced protein and the Rare cold inducible (RCI2) gene families enhance abiotic stress tolerance in various plant species [ 54 , 55 ]. Circadian clock and flowering regulation genes such as Pseudo-response regulator 7 ( PRR7 ), Cold regulated protein 27 and Constans-like protein ( CO8 ), also are downregulated during Si colonization. While members of the PRR and CO protein families work together to control flowering time [ 56 , 57 ], any influence on early flowering in Si -colonized Bd21-3 is unclear. Circadian clock-associated genes also regulate lateral root development in Arabidopsis [ 58 ]; whether Si -induced changes in their expression influence root growth is unknown. Other downregulated development-associated DEGs include Fantastic four meristem regulator ( FAF ), which regulates shoot and root development [ 59 ], and putative Sulfoquinovosyltransferase ( SQD2 ), which modulates seed setting and tiller development in rice [ 60 ]. Finally, several downregulated DEGs encode transcription factors, including MYB-related, GRAS, and bZIP. In comparison, many of the upregulated Bd21-3 DEGs are associated with immune responses. Examples include genes encoding leucine-rich repeat (LRR) protein, a WRKY transcription factor, and thaumatin family protein. Increased expression of the defense gene Pathogenesis-related protein 1 ( PR1 ) was similarly and transiently reported in Si -colonized Arabidopsis roots [ 61 ]. Upregulation of G lutathione S-transferase ( GST ) is consistent with the increased antioxidant capacity of Si -colonized plants, which provides protection against attack by necrotrophic pathogens [ 21 , 62 ]. The upregulation of genes in other hormonal networks ( PGP-like Phosphoglycoprotein auxin transporter ) and redox processes ( Multicopper oxidase ) further suggests that Si colonization affects a range of signaling pathways. Bd miRNAs detected in the Bd-Si sample The role of miRNAs as regulators of gene expression in the Sebacinalean symbiosis is largely unexplored. One report showed that Si induces growth promotion-associated miRNAs in Oncidium orchid roots [ 63 ]. Analysis of putative endogenous Bd21-3 sRNAs expressed during Si colonization identified 16 miRNAs. Some of them have known targets in transcription factors associated with plant growth and development. For example, the bdi-MIR166 family targets mRNAs encoding Homeobox domain-leucine zipper transcription factors [ 64 ]. In Arabidopsis, repression of these transcription factors by the miR165/166 family modulates root growth, maintenance of the shoot apical meristem, and development of leaf polarity [ 65 ]. Plant-specific transcription factors encoded by Squamosa promoter-binding protein-like ( SPL ) genes are the presumed targets of bdi-MIR156 and bdi-MIR529 [ 66 ]. In Arabidopsis, miR156-mediated downregulation of SPLs modulates developmental timing, lateral root development, branching, and leaf morphology [ 65 ]. Members of the MYB superfamily of transcription factors, which regulate many aspects of development, are the predicted targets of bdi-MIR159 [ 34 ]. Interestingly, miRNAs belonging to the miR159 and miR166 families in cotton are known ck-sRNAs that target virulence genes in Verticillium dahliae [ 13 ]. Other miRNAs identified in Bd21-3 include bdi-MIR168, predicted to target AGO1 [ 64 ], and two miRNAs that regulate nutrition: bdi-MIR399, which is upregulated in Bd by phosphate starvation [ 64 , 67 ], whereas bdi-MIR408 influences copper levels [ 34 , 68 ]. Additionally, bdi-MIR408 ( Bd sRNA 10) has predicted ck targets in three Si transcripts: CCA72944, CCA72668 , and CCA74115 . Since various targets were predicted for bdi-MIR167 [ 34 , 68 ] and no target was predicted for bdi-MIR9481, their endogenous functions in Bd are unclear. Interestingly, the miRNA families identified in our analysis, except bdi-MIR9481, also were detected in Si -colonized Oncidium [ 63 ]. Thus, this group of miRNAs may play an important role in reprogramming plant cells during Sebacinalean symbiosis establishment. Putative Si and Bd21-3 ck-sRNAs and their predicted targets To date, cross-kingdom RNAi has been demonstrated in pathogenic plant-fungal interactions [ 12 , 13 , 69 ], and while there are promising indications for its presence during plant-mycorrhiza interactions [ 36 ], whether it occurs in Si -plant associations is unknown. To investigate this possibility, we predicted targets for 21 nt putative ck-sRNAs from Si and Bd21-3 and confirmed their downregulation during colonization. This analysis uncovered 358 downregulated Si transcripts that are the predicted targets of 228 unique Bd21-3 sRNAs. Cross-kingdom RNAi-mediated downregulation of these targets might allow Bd21-3 to modulate Si growth during colonization. For example, PAL , Acetyl-CoA synthetase, C arnitine acetyl transferase , Isocitrate lyase , and Acyl-CoA dehydrogenase , which are targeted by Bd sRNA 1, Bd sRNA 2, Bd sRNA 3, Bd sRNA 6, and Bd sRNA 16 (Table 5 ), are involved in fungal nutrient acquisition [ 22 , 55 , 70 , 71 ]. Genes with important homologs in pathogenic fungi also are predicted targets, including S ubtilisin-like serine protease ( Bd sRNA 18) [ 72 ], Alcohol dehydrogenase 1 ( Bd sRNA 7) [ 73 ], and Phosphoprotein phosphatase 2C ( Bd sRNA 9) [ 74 ]. Targeting of Hyphal anastomosis-2 ( HAM-2 ) by Bd sRNA 8 and Bd sRNA 4 may provide another mechanism for controlling fungal growth, as HAM-2 is required for hyphal fusion in N. crassa [ 75 ]. Similarly, targeting of C hitinase ( Bd sRNA 14) may help control Si growth. Concurrently, we identified 49 downregulated Bd21-3 mRNAs that are the predicted targets of 63 unique Si -generated ck-sRNAs. Downregulation of these target genes via cross-kingdom RNAi might facilitate Si growth during colonization. For example, Mannose-binding lectin (targeted by Sis RNA 18) belongs to a family of defense-related genes whose products trigger immune responses following pathogen recognition [ 76 ]. Si sRNA 8 and Si sRNA 15 target a protein kinase domain/LRR gene ( BdiBd21-3.4G0303000.1 ) that may belong to the LRR receptor kinase family, which regulates defense and developmental-related processes [ 77 ]. Transcripts encoding serine-carboxypeptidase-like (SCPL) proteins BdiBd21-3.2G0440200.1 and BdiBd21-3.1G0411900.1 (targeted by Sis RNA 1 and Sis RNA 15) are associated with defense against (a)biotic stresses in monocots [ 78 ]. Members of various transcription factors families also were identified as predicted targets ( MYB by Si sRNA 16, bZIP by Si sRNA 2, and GRAS by Si sRNA 10). These families are associated with (a)biotic stress responses, as well as plant growth and development [ 79 – 81 ]. Lastly, transcripts for proteins involved in circadian clock and flowering regulation ( BdiBd21-3.1G0887100.1 and BdiBd21-3.3G0264400.1 [ 56 ];) are the presumed targets of Si sRNA 1 and S isRNA 19. Together, these findings suggest that Si -derived ck-sRNAs may promote fungal colonization by targeting signaling processes associated with plant development and responses to (a)biotic stresses. In combination with earlier studies on Bd RNAi proteins [ 35 ] and Bd interaction with the pathogen Magnaporthe oryzae [ 82 ], the in silico analyses presented here suggest that Si and Bd contain functional RNAi components and that both organisms generate ck-sRNAs, which potentially modulate this mutualistic interaction. However, further studies are necessary to validate cross-kingdom RNAi in a Sebacinalean symbiosis. Namely, degradome analysis is needed to confirm target degradation and evidence that Bd21-3 and Si AGOs associate with sRNAs expressed by the interacting organism is necessary for confirmation of cross-kingdom RNAi."
} | 3,496 |
37704397 | PMC10521942 | pmc | 5,501 | {
"abstract": "Abstract The biotechnological production of methyl ketones is a sustainable alternative to fossil-derived chemical production. To date, the best host for microbial production of methyl ketones is a genetically engineered Pseudomonas taiwanensis VLB120 ∆6 pProd strain, achieving yields of 101 mgg −1 on glucose in batch cultivations. For competitiveness with the petrochemical production pathway, however, higher yields are necessary. Co-feeding can improve the yield by fitting the carbon-to-energy ratio to the organism and the target product. In this work, we developed co-feeding strategies for P. taiwanensis VLB120 ∆6 pProd by combined metabolic modeling and experimental work. In a first step, we conducted flux balance analysis with an expanded genome-scale metabolic model of i JN1463 and found ethanol as the most promising among five cosubstrates. Next, we performed cultivations with ethanol and found the highest reported yield in batch production of methyl ketones with P. taiwanensis VLB120 to date, namely, 154 mg g −1 methyl ketones. However, ethanol is toxic to the cell, which reflects in a lower substrate consumption and lower product concentrations when compared to production on glucose. Hence, we propose cofeeding ethanol with glucose and find that, indeed, higher concentrations than in ethanol-fed cultivation (0.84 g L aq −1 with glucose and ethanol as opposed to 0.48 g L aq −1 with only ethanol) were achieved, with a yield of 85 mg g −1 . In a last step, comparing experimental with computational results suggested the potential for improving the methyl ketone yield by fed-batch cultivation, in which cell growth and methyl ketone production are separated into two phases employing optimal ethanol to glucose ratios. One-Sentence Summary By combining computational and experimental work, we demonstrate that feeding ethanol in addition to glucose improves the yield of biotechnologically produced methyl ketones.",
"conclusion": "Conclusion We investigated a co-feeding strategy for the production of methyl ketones with P. taiwanensis VLB120 ∆6 pProd. We presented an updated GEM, namely, i JN1463_MK, for metabolic modeling of P. taiwanensis VLB120 and performed FBA for five different co-substrates. Together with information on the DoR of the substrate as well as the uptake metabolism of each substrate from literature, ethanol was ranked highest. Ethanol has the additional advantage that it is a low-cost, high-volume product of many industrial processes. Sustainable industrial-scale production is enabled by the conversion of side and waste streams such as lignocellulosic biomass or biogas (Broda et al., 2022 ). Finetuning of the GEM, that is, revising the uptake metabolism of the co-substrates, might further increase its predictive potential. In batch cultivation, methyl ketone yields were highest on ethanol as sole carbon source. However, high concentrations of ethanol are toxic to the cell (Heipieper & Bont, 1994 ). Consequently, co-feeding with glucose has achieved higher product concentrations, while no diauxic metabolism was observed. In order to further increase the product concentrations, the cellular tolerance to ethanol should be increased by adaptive laboratory evolution (ALE) approaches. Moreover, fed-batch fermentation can help exploiting the full potential. A first growth phase makes the cells more robust to high ethanol concentrations, which makes it possible to increase the concentration of the carbon source. Alternatively, methyl ketone production in resting cells may be attractive, thereby uncoupling growth and product synthesis. Furthermore, the optimal ethanol-to-glucose ratio should be investigated next. When comparing the experimental with computational results, we have observed that there is still potential for improvement in the product yield because many of the carbon atoms are still metabolized to biomass. Genetic modification might further increase the yield. Again, a combined approach of metabolic modeling and experimental data is helpful. Gene knockouts can be predicted in silico by suitable bilevel optimization formulations (Burgard et al., 2003 ; Tepper and Shlomi, 2010 ) and can reduce the effort of subsequent in vitro experiments.",
"introduction": "Introduction Methyl ketones are a versatile class of platform chemicals that are currently produced by the oxidation of hydrocarbons. Aliphatic, medium-chain-length methyl ketones are used in the flavor and fragrance industry (Goh et al., 2012 ). In the last decade, applications for sustainable production of lubricants (Balakrishnan et al., 2016 ) and diesel fuel replacements (Harrison & Harvey, 2018 ) have been discussed. In order to provide a sustainable route for methyl ketone production, extensive research has been carried out to enable microbial production from renewable resources. A first recombinant pathway for the production of medium-chain-length methyl ketones (C12–C15), as diesel replacement, was introduced by Goh et al. ( 2012 ) in Escherichia coli strain DH1. The genetic engineering efforts that particularly involved altering the fatty acid metabolism led to the overproduction of saturated and monounsaturated methyl ketones with a chain length of C11–C15 at a titer of 0.38 g L −1 . Since then, methyl ketone production has been achieved in various Gram-negative microorganisms such as Cupriavidus necator and Pseudomonas putida by means of genetic engineering (Dong et al., 2019 ; Müller et al., 2013 ). Gram-negative Pseudomonas taiwanensis VLB120 has many characteristics that make it interesting for industrial application in bioprocesses. They are nonpathogenic, show high tolerance to organic solvents, can utilize a broad variety of substrates, and are easily genetically engineered. Additionally, P. taiwanensis VLB120 shows a high tolerance to lignin-derived aromatic compounds that have an inhibitory effect on many other microorganisms (Lenzen et al., 2019 ; Wordofa & Kristensen, 2018 ). Nies et al. ( 2020 ) engineered P. taiwanensis VLB120 for the production of medium-chain-length methyl ketones. They established the truncated β -oxidation pathway from Goh et al. ( 2012 ) to Goh et al. ( 2014 ). The strain P. taiwanensis VLB120 ∆6 pProd additionally had deletions of fadA2, tesB , and the pha operon. In a fed-batch bioprocess with glucose as a carbon source, a product titer of 9.8 g L aq −1 at 53% of the theoretical maximum yield was achieved. This is the highest recombinantly produced methyl ketone yield to date (Nies et al., 2020 ). Independent of the microorganism, strategies for methyl ketone production aim for increased availability of fatty acid precursors malonyl-CoA and acetyl-CoA (AcCoA) or the improvement of the conversion rate of fatty acids in the beta-oxidation pathway. Increased availability of ATP and NAD(P)H was shown to have a positive impact as well, since the fatty acid metabolism in general has a high demand for energy carriers and redox cofactors (Hollinshead et al., 2014 ). In order to be competitive with the petrochemical industry, high methyl ketone yields are required when applying microbial production hosts. Similarly, to other fatty acid-derived products, the main challenge is the high demand for ATP along with a complex redox balancing. Herein, the difficulty lies in a net NADH consumption and a net NADPH production (Goh et al., 2018 ; Hollinshead et al., 2014 ). Often, these challenges are tackled by means of genetic engineering; however, redox balancing can be cumbersome (Zu et al., 2021 ). An alternative strategy to improve product formation is the choice of substrate. The utilized carbon source is a lever to rearrange the metabolic fluxes and improve product yields independent of genetic engineering. Different substrates are metabolized by different metabolic pathways, resulting in specific carbon-to-energy ratios. The application of multiple carbon sources in a co-feeding approach has been shown to be advantageous in several applications (Dong et al., 2019 ; Ullmann et al., 2021 ). Especially for the production of highly reduced products such as methyl ketones, co-feeding was beneficial (Park et al., 2019 ). Also, from an ecological perspective, the use of additional, alternative carbon sources can be beneficial. For example, ethanol can be produced from greenhouse gases in syngas fermentations and from formate by electrochemical reduction of CO 2 (Bengelsdorf & Dürre, 2017 ; Cotton et al., 2020 ). Pseudomonas spp. are described as being able to metabolize a broad variety of carbon sources, including pentose and hexose sugars, carboxylic acids, and aromatic compounds (Lang et al., 2014 ; Sivapuratharasan et al., 2022 ; Sudarsan et al., 2014 ; Wordofa & Kristensen, 2018 ). We have preselected five different potential carbon sources as a potential cofeeding compound. Glycerol, ethylene glycol, ethanol, acetate, and formate were chosen because it was previously demonstrated that these substances can have a positive impact on a bioprocess when they are used as a (co-)substrate. Additionally, all applied co-substrates can either be derived from industrial side streams (glycerol, ethylene glycol) or from sustainable resources such as lignocellulosic biomass or CO 2 (ethanol, acetate, and formate) (Li et al., 2019 ; Nikel & de Lorenzo, 2014 ; Sun et al., 2020 ; Ullmann et al., 2021 ; Xu et al., 2021 ). When evaluating co-substrates, metabolic modeling is a powerful tool to support and reduce the effort of laboratory experiments. Metabolic modeling is based on genome-scale metabolic models (GEMs), which are reconstructions of metabolic networks, that is, of all reaction pathways existing in an organism. GEMs contain the stoichiometry of the reactions as well as their associated genes. GEMs serve to predict the phenotypical response of an organism to different environmental conditions, for example, when co-feeding, as well as to predict the inner-cellular fluxes by applying metabolic modeling formulations, such as flux balance analysis (FBA) (Orth et al., 2010 ; Varma & Palsson, 1994 ). With the assumption of steady-state, FBA defines a cellular objective and additional constraints on the reaction fluxes and calculates the resulting flux distribution by means of linear programming. Herein, we applied FBA to preassess which co-substrate is the most promising candidate to improve the yield of methyl ketones. Next, we conducted growth experiments with P. taiwanensis VLB120 ∆6 pProd on the most promising substrate to measure the product titer and yield under different cofeeding conditions. With these experimental results, we redid the FBA prediction with the experimental uptake rates as input to furnish consistent results and compute potentials for further improvement of the methyl ketone yield. To conclude, we used metabolic modeling to reduce laboratory work to develop the co-feeding strategies for improved methyl ketone yield.",
"discussion": "Results and Discussion Case Study: Metabolic Modeling Detects Ethanol as the Most Promising Co-Substrate To represent co-feeding, different uptake fluxes were set as inputs to the FBA. Within a range of 0 C-mmol / g CDW / hr to 18 C-mmol / g CDW / hr, the substrate was varied as glucose plus each denominated co-substrate. The 18 C-mmol / g CDW / hr corresponds to 3 mmol g CDW −1 hr −1 glucose, in alignment with the experimentally measured uptake rate by Nies et al. ( 2020 ). Each input square was covered by 20 times 20 FBA predictions. The methyl ketone exchange reaction flux was maximized to calculate the maximal theoretical methyl ketone production. The resulting ranking of substrates indicates the performance of the substrates, implicitly assuming that the actual production is proportional to the maximal theoretical production. Each FBA is subject to 10% of the maximal theoretical biomass at the respective point, representing the standard growth maintenance. In this parametric linear optimization program, the input space can be seen as a square and the results form planes, as seen in Fig. 1 . No kinks are visible, which means that the optimal basis does not change but rather the active reaction pathways within the metabolic network stay the same. Fig. 1. Evaluation of five co-substrates using flux balance analysis as a function of glucose and co-substrate carbon uptake. The methyl ketone exchange reaction flux was set as objective function. This exchange reaction is normalized for 2-pentadecanone. A threshold on biomass of 10% of the maximal theoretical growth at each point was imposed. Figure 1 shows that the highest methyl ketone flux of 0.026 mmol g CDW −1 hr −1 is reached with the co-substrate ethanol and at maximal glucose and ethanol input. The second-best-performing co-substrate is glycerol, followed by acetate and ethylene glycol. With the co-substrate formate, the maximum reachable methyl ketone flux is 0.015 mmol g CDW −1 hr −1 . The slope of the planes corresponds to the yield of methyl ketones. When only varying glucose, the yield stays constant at 0.67 mmol C-mol −1 for all co-substrates, which was to be expected. When varying the co-substrate, the steepest descent is visible with ethanol, which achieves a yield of 0.85 mmol C-mol −1 , which is higher than the yield on glucose. In other words, more carbon atoms are required with glucose as a carbon source to form the same amount of methyl ketones than on ethanol. Similarly, glycerol exhibits a higher yield than pure glucose, whereas the other co-substrates have a lower yield than pure glucose. The results from Fig. 1 were compared to the DoR of glucose and the five co-substrates. Table 1 displays the DoR calculated with Equation ( 1 ). Table 1. Degree of Reduction (DoR) for Glucose and Five Co-Substrates, Calculated Using Equation ( 1 ) Name Chemical formula DoR Ethanol C 2 H 6 O 6 Ethylene glycol C 2 H 6 O 2 5 Glycerol C 3 H 8 O 3 4.67 Glucose C 6 H 12 O 6 4 Acetate C 2 H 4 O 2 4 Formate CH 2 O 2 2 The DoR is a first estimation of how many electrons the microorganism can derive from a certain substrate. The higher the DoR, the more energy the substrate carries. Interestingly, the DoR displays a different order compared to the aforementioned FBA results. Namely, the DoR suggests that ethylene glycol should perform better than it did in the FBA. Moreover, the DoR indicates that acetate should perform as good as pure glucose. To further understand the differences, the metabolism of the different substrates was investigated in the literature. Figure 2 shows the main metabolization pathways of glucose and the five co-substrates in a metabolic map. Fig. 2. Simplified central carbon metabolism of P. taiwanensis VLB120 with focus on the utilization pathways of glucose, glycerol, ethylene glycol, ethanol, acetate, and formate, as suggested by Li et al. ( 2019 ), Tiso et al. ( 2021 ), Yang et al. ( 2019 ), Poblete-Castro et al. ( 2020 ), and Zobel et al. ( 2017 ). The map was created with ChemDraw 21.0.0. G6P = glucose 6-phosphate; 6PG = 6-phospho gluconate; 2KDPG = 2-keto-3-desoxyphosphogluconate; F6P = fructose 6-phosphate; FBP = fructose 1,6-bisphosphate; G3P = glycerinaldehyde 3-phosphate; DHAP = dihydroxyacetone phosphate; E4P = erythrose 4-phosphate; P5P = 5-phosphate pentoses; S7P = seduheptolose 7-phosphate; 2PG = 2-phospho glycerate; PYR = pyruvate; GLX = glyoxylate; AcCoA = acetyl-CoA; ACAH = acetaldehyde; MalCoA = malonyl-CoA; OAA = oxalacetate; CIT = citrate; ICIT = isocitrate; SUC = succinate; MAL = malate. The metabolization of glucose to glucose 6-phosphate goes along with the investment of one ATP molecule. Glycerol is converted to dihydroxyacetone phosphate (DHAP; Poblete-Castro et al., 2020 ), which further goes into the Embden–Meyerhof–Parnas pathway. Ethylene glycol is transformed into glyoxylate (GLX). GLX can further be transformed via the GLX shunt, producing 2CO 2 and redox cofactors. Alternatively, GLX can be converted to tatronate semialdehyde and CO 2 , and further to pyruvate. Hence, in this pathway, a lot of carbon is lost. The first option makes ethylene glycol an energy carrier rather than a carbon source, while in the second option, it is an inefficient carbon source ( Li et al., 2019 ; Tiso et al., 2021 ). Ethanol is metabolized via acetaldehyde (ACAH) and acetate to AcCoA without carbon losses, that is, CO 2 production (Bator et al., 2020 ). Acetate can directly be converted to AcCoA by acetyl-CoA synthetase with ATP as a co-factor (Bator et al., 2020 ). Formate is not a carbon source as such for the microorganism. Instead, its metabolization into CO 2 produces NADH and, thus, can balance the energy demand of the cell (Zobel et al., 2017 ). Methyl ketones are synthesized in the fatty acid metabolism, and the main precursor for this pathway is AcCoA. Hence, generally, the closer one substrate is in the map to the metabolite AcCoA, the easier the conversion to methyl ketones. In other words, less conversion steps with potential carbon or energy losses are necessary to form methyl ketones. Following this rule of thumb, ethanol and especially acetate are the most promising co-substrates. The FBA and the DoR results, however, ranked acetate lower. For ethylene glycol, despite its high DoR, the metabolic map supports the FBA results by showing that ethylene glycol can enter the GLX shunt instead of producing AcCoA. We conclude that co-feeding can contribute to improving the yield of methyl ketones. Therein, ethanol is the most promising co-substrate, followed by glycerol. Ethylene glycol was shown to improve the methyl ketone yield less than expected from its high DoR. To finally evaluate the performance of acetate, laboratory experiments are necessary. Ethanol Achieves the Highest Reported Yield in Shake Flask Cultivation Prior to more detailed shake flask cultivations, the growth behavior of P. taiwanensis ∆6 pProd with the different co-fed carbon sources was investigated in vivo by online measurement of biomass formation in BioLector experiments. This cultivation showed substrate inhibition in the case of formate and acetate as a co-substrate ( Supplementary Fig. A1 ). According to the FBA-based assessment of the co-substrates, ethanol was considered to be the most promising candidate for further evaluation in shake flask cultivations. The applied MSM media was developed to support cultivations with 10 g L −1 of glucose as a carbon source in shake flasks. To have the co-fed cultivations comparable to that, the same total molar amount of carbon was applied. A carbon ratio of two C-mol ethanol (2.4 g L −1 ) to one C-mol glucose (8 g L −1 ) was tested, and biomass growth, carbon source uptake, and methyl ketone formation was measured. Note that P. taiwanensis VLB120 produces minor amounts of gluconate as the only by-product. After glucose depletion, it also takes up gluconate. Accordingly, there are no side products to be taken into account for the overall assessment of these cultivations. Figure 3 shows the result of the shake flask cultivation. Fig. 3. Concentration of biomass, ethanol, glucose, and methyl ketones in a co-fed shake flask cultivation with P. taiwanensis ∆6 pProd. The C-molar ratios were one part glucose to two parts ethanol. The results are shown as the average of three experiments, and the error bar represents the standard deviation from these biological replicates. Glucose and ethanol were taken up simultaneously, while the rate of glucose uptake occurred to be 1.44 ± 0.13 mmol g CDW −1 hr −1 , higher than the rate of ethanol uptake of 1.05 ± 0.02 mmol g CDW −1 hr −1 . After complete carbon source depletion after 24 hr, 0.84 ± 0.004 g L aq −1 of methyl ketones were produced, corresponding to a yield of 84 mg MK g substrate −1 . Opposed to that, cultivations under the same conditions with only glucose as a carbon source had an average yield of 58 mg MK g substrate −1 . These cultivations show that glucose and ethanol are co-consumed without any diauxic behavior, with a higher uptake rate for ethanol. This indicates that, regarding biomass growth, glucose is the preferred substrate of the production host. However, by applying ethanol as a co-substrate, increased product concentrations and yields compared to glucose as a single substrate can be achieved. Biomass concentration increases exponentially and appears to stop after around 10 hr, which might, however, be due to nonoptimal sampling time points. Presumably, the strain was still in the exponential phase after 10 hr and grew around 1 or 2 hr more. According to our experimental experience, after reaching the stationary phase, the biomass decreases slightly. Presumably, the biomass concentration was higher than 3.6 g L −1 in the time when no sample was taken from the shake flask. The majority of product formation happened in the second half of the cultivation, presumably after substrate depletion. This was also observed earlier in cultivations with P. taiwanensis ∆6 pProd for methyl ketone production. This can occur due to the rate-limiting spontaneous decarboxylation observed before (Goh et al., 2014 ; Nies et al., 2020 ). Potentially, the product concentration could have increased further after the 24 hr that were investigated. After confirming the simultaneous consumption of ethanol and glucose using P. taiwanensis ∆6 pProd as a production host, different combinations of glucose and ethanol were tested and compared regarding product yield and final product titer (Fig. 4 ). Fig. 4. Methyl ketone yield of (co-fed) shake flask cultivation after 24 hr and corresponding concentration of the carbon source. Glucose and ethanol were added in C-molar ratios of two parts glucose to one part ethanol (downward facing triangle) and one part glucose to two parts ethanol (upward facing triangle). Data are shown as the average and standard deviation of three biological replicates. All samples were taken 24.0 or 25.5 hr after inoculation, presumably not corresponding to the highest product yield since product concentrations were still increasing at that time point. The highest yield was obtained by using pure ethanol as a substrate. In the cultivation with ethanol as the only substrate, 2.82 g L −1 of ethanol were converted to methyl ketones with a product yield of 115 mg MK g substrate −1 . By applying ethanol and glucose in C-molar ratios of 2:1 and 1:2, yields of 84.56 and 74 mg MK g substrate −1 were observed. When only glucose was used, the yield varied between 54 and 66 mg MK g substrate −1 . Presumably, these variations derive from slightly different sampling time points. The higher the supplied amount of ethanol, the higher the yield of methyl ketones. This suits the findings of the FBA study. After 48 hr of cultivation, a methyl ketone yield of 154 mg MK g substrate −1 was observed in a shake flask cultivation with single-fed ethanol ( Supplementary Fig. A2 ). To our knowledge, this is the highest reported yield of methyl ketones in batch cultivations with P. taiwanensis VLB120 to date. Using genetically engineered P. putida KT2440, a methyl ketone yield of 169 mg MK g substrate −1 was observed in batch cultivations with glucose and high-value amino acids as co-substrates (Dong et al., 2019 ). On glucose as a single carbon source, P. taiwanensis VLB120 ∆6 pProd was able to produce 101 ± 2 mg L −1 in batch cultivations (Nies et al., 2020 ). Approaches to produce methyl ketones from carbon sources other than glucose and glycerol (Yan et al., 2020 ) are, to the best of our knowledge, not published. However, ethanol conversion takes place at a reduced rate compared to glucose, and no high ethanol concentrations can be applied due to product toxicity. Thus, the final product concentration of 0.48 g L aq −1 in the cultivation with ethanol is also lower than 0.84 g L aq −1 that was achieved with glucose and ethanol. The Comparison of Experimental Data and Simulations Furnishes Consistent Results We compared the experimental results from the shake flask cultivation with FBA results. From the experiments, we concluded that FBA with the assumption of simultaneous metabolization of the substrates is a valid tool, as no diauxic growth was visible during cultivation. The aim of this comparison was threefold. First, the validity of the GEM i JN1463_MK ∆6 pProd should be investigated. Second, the laboratory analysis of biomass should be analyzed. Third, we wanted to see whether there was potential for further improvement of the methyl ketone yield. In order to compare the results, experimental values were transformed into fluxes. The input to the FBA was set to the uptakes that were measured in the experiments. In a first step, we conducted an FBA, where we set an input of 2.77 mmol g CDW −1 hr −1 glucose, corresponding to the measured value. In the corresponding batch cultivation experiment, no methyl ketone production was induced. Hence, in the FBA, biomass production was set as objective function. The FBA returns a production of 0.27 hr −1 , which fits the measured value of 0.28 hr −1 . We conclude that the GEM i JN1463_MK ∆6 pProd is able to simulate the biomass production. In a second step, we compared the results from the best performing methyl ketone production cultivation, as presented in Fig. 3 , to FBA results. In the FBA, the uptake of ethanol was set to 1.05 mmol g CDW −1 hr −1 and the uptake of glucose was set to 1.44 mmol g CDW −1 hr −1 . We set the methyl ketone exchange reaction as objective function, with the following stoichiometry: \n \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n\\begin{eqnarray*}\n&&1.00{\\mathrm{ }}\\cdot{\\mathrm{ }}2\\text{-}{\\mathrm{pentadecanone\\_e}} + 9.18{\\mathrm{ }}\\cdot{\\mathrm{ }}8\\text{-}{\\mathrm{ pentadecen}} \\text{-}2 \\text{-}{\\mathrm{one\\_e}}\\\\\n&&\\quad + {\\mathrm{ }}1.25{\\mathrm{ }}\\cdot{\\mathrm{ }}10\\text{-}{\\mathrm{heptadecen}} \\text{-}2\\text{-}{\\mathrm{one\\_e}} + 7.80{\\mathrm{ }}\\cdot{\\mathrm{ }}2\\text{-}{\\mathrm{tridecanone\\_e}}\\\\\n&&\\quad + {\\mathrm{ }}6.43{\\mathrm{ }}\\cdot{\\mathrm{ }}6\\text{-}{\\mathrm{ tridecen}} \\text{-} 2\\text{-}{\\mathrm{one\\_e}} + 5.66{\\mathrm{ }}\\cdot{\\mathrm{ }}2\\text{-}{\\mathrm{ undecanone\\_e}} \\to\n\\end{eqnarray*}\\end{document} \n that was determined from the measured ratio of congeners. The experimental methyl ketone production rate is 0.041 ± 0.004 mmol g CDW −1 hr −1 . This value corresponds to 7.48% of the theoretical flux of methyl ketones when no threshold on biomass is set in the FBA. Next, in four different FBAs, we constrained biomass formation to find out which simulation fits the measured results. Figure 5 shows the comparison. Fig. 5. Comparison of experimental biomass production and methyl ketone production with flux balance analysis (FBA) results. FBA conditions: The methyl ketone exchange reaction was set as objective function. The biomass threshold was varied from 85% to 100% of the maximal theoretical biomass production, that is, the flux of the biomass reaction v Biomass . Glucose uptake was set to 1.44 mmol g CDW −1 hr −1 , ethanol uptake was set to 1.05 mmol g CDW −1 hr −1 . Cultivation conditions: 1 part C-mol glucose, 2 parts C-mol ethanol, n = 300 min −1 ; T = 30°C; V l , aq = 50 mL; V l , org = 12.5 mL; t = 24 hr; N = 3; c carbon = 0.33 C-mol. Errors were calculated with the jackknife method by Harris ( 1998 ). The methyl ketone production rate is a sum of all congener reaction fluxes. The experimental biomass growth is 0.208 ± 0.008 hr −1 . The simulated growth ranges from 0.162 hr −1 to 0.190 hr −1 , which corresponds to 85% to 100% of the theoretical biomass production. Hence, even the maximal theoretical biomass production does not reach the measured level of biomass. With the validation of the GEM beforehand, we conclude an experimental measurement error. When producing methyl ketones, the biomass was measured in a second, parallel flask, as the added organic solvent for in situ product extraction made simultaneous measurement of biomass and products in the same shake flask infeasible. We conclude that this laboratory analysis procedure needs to be revised. When setting a threshold of 85% of the maximal theoretical biomass production, the simulated methyl ketone production is 0.082 mmol g CDW −1 hr −1 . The production declines to zero when only biomass is produced at 100% of the theoretical biomass production. The intersection point with the experimental value is at 92.5% biomass threshold. In other words, the FBA predicts the same methyl ketone production as the experimental value when setting a threshold on biomass of 92.5% of the maximal theoretical biomass production. The threshold corresponds to a growth rate of 0.18 hr −1 . We conclude from the comparative study that the FBA with the GEM i JN1463_MK ∆6 pProd was able to correctly predict the biomass production. Moreover, we found the potential to improve the laboratory analysis of biomass measurement during methyl ketone production as the measured value was too high. Lastly, we conclude from the high threshold of 92.5% of the maximal biomass production that there is still room for improvement in the methyl ketone production. More carbon atoms could be used for methyl ketone production instead of being incorporated into biomass formation."
} | 7,386 |
35907631 | PMC10173193 | pmc | 5,502 | {
"abstract": "Graphical abstract",
"conclusion": "Conclusion Our study has important implications for understanding how soil bacterial communities induced by organic fertilization respond to climate extremes. The results reveal that organic amendments could maintain high bacterial diversity during drought and increase compositional resilience under rewetting. Moreover, these features can be furtherly contributed to enhance pathogen-inhibiting function at the late recovery stage compared to chemical fertilization. We also demonstrate that a stable community tends to possess a strategy-balancing community in the yield-resource acquire-stress tolerator (Y-A-S) model. We highlight that these conclusions can provide the necessary understanding of microbiome manipulation strategies to enhance soil ecosystem stability and maintain soil functions. \n Compliance with Ethics Requirements \n \n This article does not contain any studies with human or animal subjects.",
"introduction": "Introduction Soils are crucial for human wellbeing by providing food, feed and medicine [1] . The highly diverse soil microbiome is underlying those functions, as well as determining biogeochemical cycling, plant productivity and the performance of soil-borne diseases [2] , [3] . But human practices, such as the overuse of chemical fertilizers [4] , have led to large-scale soil degradation including reductions in the microbiome [5] , [6] . Thus, alternative management forms that aim at enhancing ecosystem multifunctionality including those based on enhancing the soil microbiome were introduced, such as organic and conservation agriculture [7] , [8] , [9] . However, soil microbiome functions are not constant over time and change depending on external conditions, such as being influenced by the increasing incidences of extreme events in the ongoing climate change [10] . Climate extremes impact soil microbial communities and their functioning constantly, such as increased incidences of drought [11] , [12] , [13] , extreme precipitation events and resulting floodings [14] . Under these stresses, microorganisms and their functions are depending on distinct taxon- and community-specific differences in resistance and resilience. Resistance is commonly defined as the ability of a system to withstand a stress, while resilience is the speed of system’s recovery towards its pre-disturbance state or a new stable state [15] , [16] . Among the soil microbiome, bacteria seem more responsive to changes than fungi [17] . But there are differences among bacterial taxa to changing conditions as taxa exist that can be sensitive, tolerant or opportunistic to extreme stress [18] , [19] , [20] . Sensitive microorganisms are damaged during drought stress and can hardly recover [21] , [22] ; some microbes that can remain active during water limitation are tolerators, and opportunistic microorganisms can colonize empty environmental niches first and influence the chronology of the ensuing microbial species to rebound [23] , [24] . Stress, as induced by drought, can also interactively impact microorganisms with additional external factors like agricultural practices, such as chemical and organic fertilization regimes. However, it remains unknown how management might impact the resistance and resilience of soil microbial communities and their functions. Another issue is that most contemporary studies focused on only one component, resistance or resilience, also neglecting, complex multi-step process of recovery that can differ between biotic taxa and communities [25] , rendering our understanding of ecological stability impossible [26] . In this study, we evaluated the impact of different fertilizer practices and the potential positive impact of organic inputs on bacterial communities and their function under drought to evaluate resistance, and rewetting to study resilience. For that, we established a series of experiments to track different responses of bacterial microbiomes and their multidimensional ecosystem stability in organic vs chemical fertilizer input soils under extreme drought stress and rewetting. We hypothesized that long-term organic inputs establish a distinct microbiota compared with conventional inputs, which possess (1) higher bacterial diversity and resistance to drought stress; (2) higher resilience and recovery under rewetting; (3) increased microbial functions after recovery from extreme drought.",
"discussion": "Discussion In this study, we observed that organic fertilization (NOF) established a bacterial community that possesses higher bacterial Faith’s PD index during drought and higher resilience of composition during rewetting compared with conventional fertilizers (NCF). The recovery of bacterial community further enhanced the pathogen-inhibiting function recovery of soil ecosystems in NOF compared to NCF. Generally, drought induced shifts in bacterial diversity and composition. Our results support part of our first hypothesis that NOF supports a higher bacterial diversity under drought than NCF, which is in line with previous studies [53] , [54] . Higher diversity is assumed to be beneficial to cope with extreme stress due to higher metabolic capacities of the entire community [55] . Our results revealed that the relative abundances of Gram-negative bacterial phyla, such as Proteobacteria and Bacteroides , were reduced by drought, while relative abundances of Gram-positive, oligotrophic Actinomyces and Firmicutes were increased. Actinomyces that are plant beneficial under drought [56] , [57] were additionally enhanced in NOF, showing the positive impact induced by organic fertilizers. However, no significant difference of the reactivity and resistance of community composition between NOF and NCF were observed, which contradicts our first hypothesis. On short time scales, the resistance of microorganisms to this dramatic alteration in environmental conditions is determined by specific “response traits” that protect against desiccation [58] , such as a thick peptidoglycan cell wall, osmolyte production, sporulation, and dormancy. On long time scales in our experiment, we speculated that the exhausting of microorganisms’ energy for adapting the 80 days drought affect the resistance of microorganisms in NOF. Our results are consistent with the second hypothesis that higher resilience and recovery of bacterial communities prevail in NOF than in NCF. Interestingly, we observed a sudden decline of bacterial diversity after rewetting the NOF treatment for two days with compositional recovery to the initial community composition only taking place in the late recovery period (from R40 to R170). This finding can be linked to sudden increases in microbial activity after rewetting a dry soil found in a previous study [17] , a phenomenon called the Birch effect [59] . This Birch effect and the findings in our study might be explained by a burst of opportunistic bacteria after reconnecting the aqueous habitat in rewetted soils that result in a diversity decrease of the community [60] . The enrichment of Group 7 indicators in NOF further explained this result at the population level. The dynamics of late recovery in NOF can be explained by the fact that the input of organic fertilizer can increase K-strategist populations, which possess a relatively slow growth rate and plays an important role in moderating the recovery patterns of the soil microbial community [61] . We believe that these microorganisms were promoted among the resident soil microbiome by NOF and not introduced by fertilizers, as most invading microorganisms do not survive in soils for longer periods [62] . The recovery patterns of the NOF community in this study ( Fig. 6 ) further confirmed that ecosystem recovery is a complex and multi-step process that has been found in the secondary succession of forests and guts [63] , [64] . Fig. 6 Conceptual scheme illustrating the response of soil bacterial community to drought stress in different fertilization regimes. The purple and orange lines display the variation trends of community dissimilarity. Different shapes and colour icons represent different community compositions in soil. In early recovery stage, the ‘primary species’ (fast-growing gram-negative bacterial phyla) colonize the nutrient niche space quickly, and the other species below detection limit in the bacterial seed bank remain hidden. In the late recovery stage, a diverse set of the ‘secondary or tertiary species’ (e.g., slow-growing gram-positive bacterial phyla) bloom and increase to pre-stress abundance. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Recovery differences in soil pathogen inhibition capability between NCF and NOF were observed, supporting the third hypothesis. Fusarium oxysporum is a common soil-borne pathogen that cause Fusarium wilt in a wide range of hosts, such as tomato, banana, and pepper [38] , [65] . In plant-based pathogen inhibition assays, the low Fusarium abundance in the rhizosphere indicates high inhibition ability. We first observed that pathogen inhibition ability in NOF was enhanced at the late recovery stage but not in NCF. Enhancement of potential anti- Fusarium species might underlie this phenomenon and supports previous findings [48] . Results showed that the soil respiration rate increased following prolonged time after rewetting because soil respiration was always limited by moisture when affected by several drying events [66] . We also found that bacterial community biomass in both NCF and NOF was increased during early recovery, which is consistent with recent reports [67] , [68] . During the late recovery stage, lower microbial abundance with higher pathogen inhibition ability was present in NOF compared to NCF. This finding could be explained by an increase in abundant and functionally important phylotypes that drive variation in broad functions (respiration, biomass), while rarer phylotypes, such as those that are known to produce anti-microbial compounds (REFS-pseudomonas [27] , bacillus [69] things), drive narrower functions such as pathogen inhibition. [70] . This result further demonstrates the unique components of complex communities that are associated with different types of ecosystem functioning. The trait-based microbial strategy and yield-resource acquisition-stress tolerator (Y-A-S) model has been modified to adapt broad situations [71] . The NOF community was more strategy-balancing than the NCF community. The NCF community showed higher stress tolerance that was linked to lower yield and resource acquisition ability, indicating difficulties to maintain multiple functions under stress. During drought, any drought tolerance strategy involves physiological costs [72] . Here, low physiological costs to cope with drought further revealed that the resistance in NOF was higher than in NCF, which confirms our first hypothesis. During rewetting, the high resource acquisition and yield strategies in NOF indicated a high maximum reproductive rate [73] and carbon source utilization ability, laying the foundation for a high resilience. These results provide a new perspective to evaluate the stabilities of microbial communities, but deeper studies to link trait-based microbial strategies with ecosystem processes are needed."
} | 2,846 |
27117415 | PMC4858559 | pmc | 5,506 | {
"abstract": "Summary Type VI secretion systems (T6SSs) are nanomachines used for interbacterial killing and intoxication of eukaryotes. Although Vibrio cholerae is a model organism for structural studies on T6SSs, the underlying regulatory network is less understood. A recent study showed that the T6SS is part of the natural competence regulon in V. cholerae and is activated by the regulator TfoX. Here, we identify the TfoX homolog TfoY as a second activator of the T6SS. Importantly, despite inducing the same T6SS core machinery, the overall regulons differ significantly for TfoX and TfoY. We show that TfoY does not contribute to competence induction. Instead, TfoY drives the production of T6SS-dependent and T6SS-independent toxins, together with an increased motility phenotype. Hence, we conclude that V. cholerae uses its sole T6SS in response to diverse cues and for distinctive outcomes: either to kill for the prey’s DNA, leading to horizontal gene transfer, or as part of a defensive escape reaction.",
"introduction": "Introduction Vibrio cholerae is a common resident of aquatic habitats and is often found in association with chitinous surfaces ( Lipp et al., 2002 ). Upon growth on chitinous surfaces, V. cholerae enters a state of natural competence for transformation ( Meibom et al., 2005 ), which enables the bacterium to take up free DNA through its DNA-uptake machinery ( Seitz and Blokesch, 2013 , Seitz et al., 2014 ). Competence regulation in V. cholerae involves a complex regulatory network ( Metzger and Blokesch, 2016 ). Briefly, upon growth to high-cell density (HCD; measured by quorum sensing [QS] and the QS regulator HapR; reviewed by Rutherford and Bassler, 2012 ) on chitin, V. cholerae produces the competence activators TfoX and QstR ( Lo Scrudato and Blokesch, 2013 , Meibom et al., 2005 ), both of which positively regulate the essential parts of the DNA-uptake machinery ( Lo Scrudato and Blokesch, 2012 , Lo Scrudato and Blokesch, 2013 , Seitz and Blokesch, 2013 ). We recently demonstrated that the type VI secretion systems (T6SSs) of pandemic V. cholerae strains (i.e., the current seventh cholera pandemic) is part of this chitin-induced and TfoX-driven natural competence regulon and leads to the lysis of neighboring non-immune bacteria, followed by the uptake of their genetic material ( Borgeaud et al., 2015 ). The T6SS therefore enhances horizontal gene transfer, as it frees genomic DNA from prey cells ( Borgeaud et al., 2015 ). T6SSs are present in ∼25% of all Gram-negative bacteria. These systems are molecular killing devices used for bacterial warfare and for the intoxication of eukaryotic cells ( Ho et al., 2014 , Russell et al., 2014 ). The T6SS consists of two main parts: a membrane-spanning part and a phage-like baseplate structure, to which a tail complex is attached ( Costa et al., 2015 ). The latter is composed of an inner tube made of hemolysin-coregulated (Hcp) proteins, decorated on the outside with a contractile sheath structure (made of VipA and VipB proteins for V. cholerae ). Upon contraction of the sheath, the Hcp tube and its tip proteins are propelled into neighboring cells ( Basler, 2015 , Ho et al., 2014 ). The concomitant delivery of effector toxins leads to the killing of neighboring bacteria or eukaryotic cells. Kin discrimination occurs via the production of effector-compatible immunity proteins that prevent self-destruction ( Durand et al., 2014 , Russell et al., 2014 ). Most studies on the function and structure of the T6SS of V. cholerae have been performed in two non-pandemic isolates (V52 and 2740-80) that are constitutively operational with respect to T6SS activity. The rationale behind utilizing these specific strains was that current pandemic V. cholerae strains were considered T6SS silent under laboratory conditions ( Ho et al., 2014 ). Indeed, until we reported chitin as an environmental inducer of the system (involving the competence regulator TfoX; Borgeaud et al., 2015 ), the major trigger that significantly activates T6SS in pandemic strains remained largely unknown ( Ho et al., 2014 ). Interestingly, V. cholerae and other members of the genus Vibrio contain an additional TfoX-like protein, designated TfoY ( Pollack-Berti et al., 2010 ) (former name TfoX GEMM ; Weinberg et al., 2007 ). Pollack-Berti et al. (2010) showed that both proteins, TfoX and TfoY, contribute to efficient natural transformation in the symbiotic bacterium Vibrio fischeri without being functionally identical. Moreover, these authors suggested differential regulation patterns for tfoX and tfoY of V. fischeri , as their transcriptional activation appeared sequential upon colonization of the light organ of the symbiotic partner (the squid) ( Pollack-Berti et al., 2010 , Wier et al., 2010 ). However, regulation of tfoY and any TfoY-driven transformation-independent phenotypes was not addressed. TfoX-like proteins are commonly annotated as competence/transformation regulators. Notably, in this study we demonstrate that TfoY of V. cholerae does not contribute to natural competence for transformation. Instead, we identified TfoY as a second master regulator of T6SS in V. cholerae. T6SS activation by TfoY occurs independently of TfoX, as well as in a chitin- and QS-independent manner. Importantly, we provide evidence that TfoY is not only responsible for T6SS regulation in the most prevalent V. cholerae pandemic strains but also for constitutive T6SS activity in the non-pandemic strain V52. Based on comparison between the TfoX and TfoY regulons and the different phenotypes associated with them, we conclude that these two T6SS regulators initiate distinctive cell fates.",
"discussion": "Discussion The regulatory network that drives T6SS expression in the well-studied seventh pandemic V. cholerae isolates has been sorely neglected in the past. Here, we addressed this lack of knowledge and demonstrated that the two regulatory proteins TfoX and TfoY significantly induce the T6SS, leading to highly efficient interbacterial killing, comparable to the killing observed in the non-pandemic constitutively T6SS-active strain V52. It was known that TfoX is produced upon growth on chitin ( Meibom et al., 2005 ), but the production and function of TfoY remained unknown for V. cholerae . Based on a riboswitch associated with tfoY ( Sudarsan et al., 2008 ), we tested the contribution of the secondary messenger c-di-GMP to the production of TfoY. Our data showed that decreased c-di-GMP levels enforce the production of the TfoY protein and associated phenotypes (e.g., T6SS-mediated killing). Notably, as we only observed a small but significant effect on T6SS-mediated killing ( Figure S4 ), we hypothesize that additional signals are required for full TfoY production in nature. Indeed, a combination of transcriptional and translational control for TfoY production, similar to what has been described for TfoX (reviewed by Metzger and Blokesch, 2016 ), seems likely and will be addressed in future work. This impact of c-di-GMP on T6SS activity in V. cholerae was unexpected and opposite of that described for Pseudomonas aeruginosa. Indeed, in P. aeruginosa the H1-T6SS is produced at high c-di-GMP levels, concomitant with enhanced biofilm formation ( Moscoso et al., 2011 ). With respect to the expression of the T6SS genes, Ho et al. (2014) speculated “that RpoN and VasH control only the hcp operons and not the main cluster suggests a two-tiered regulatory cascade. Environmental signals first need to trigger the transcription of the major cluster so that vasH is expressed, which subsequently activates the transcription of the hcp operons by RpoN.” Here, we provide evidence regarding the initial input into this two-tiered regulatory cascade. TfoX and TfoY are produced, respectively, upon reaching HCD on chitinous surfaces and through the reduction of intracellular c-di-GMP levels ( Figure 4 ). These two regulators both initiate expression of the large T6SS cluster, including vasH . VasH production subsequently leads to expression of the auxiliary clusters 1 and 2 ( Figure 2 A). An important exception to this general regulation occurred, however: in the absence of VasH, the effector/immunity encoding genes of the auxiliary clusters 1 and 2 were still induced in a TfoY-dependent manner ( Figure 2 ) that was not observed upon TfoX induction. We hypothesize that this superior activation by TfoY might be explained by the biological function of these two encoded effector proteins. TseL and VasX possess lipase and pore-forming activity ( Dong et al., 2013 , Miyata et al., 2013 , Russell et al., 2013 ), respectively, both of which are not only functional against prokaryotes but importantly also against eukaryotes. Indeed, it has been previously shown that TseL and VasX are required to fight predation by D. discoideum in the T6SS-hyperactive strain V52 ( Dong et al., 2013 ). Thus, we hypothesize that the TfoY-mediated response aims at targeting eukaryotic predators. Consistent with this idea, we demonstrated that V. cholerae strain V52 is severely impaired for amoebal killing in the absence of tfoY. In addition, a TfoY-mediated defense reaction is supported by the changed expression of several other genes, as elucidated by RNA-seq. For instance, TfoY represses the “flagellum-regulated hemagglutinin A” gene ( frhA ; 3.5-fold repression), a bacterial adhesin required for attachment ( Syed et al., 2009 ). This detachment phenotype accompanies the enhanced motility observed upon TfoY induction ( Figure 1 ). Moreover, TfoY led to a strong induction of hemolysin ( hlyA ; Alm et al., 1988 ; 8.4-fold induction) and of a lecithinase ( lec ; Fiore et al., 1997 ; also known as thermolabile hemolysin, tlh ; 10-fold induction), both of which also target eukaryotic cells. Accordingly, the corresponding activities were strongly reduced in a tfoY mutant compared to the WT ( Figure S4 ). In summary, we conclude that V. cholerae uses two independent regulatory pathways to induce its single T6SS: first, to kill for DNA as part of its natural competence program ( Borgeaud et al., 2015 ), and second, to kill as part of a defensive escape reaction ( Figure 4 ). These two responses are driven by TfoX and TfoY, respectively, and provide the bacterium with the unique ability to use the same T6SS for different purposes. Further studies will show whether potential danger sensing ( LeRoux et al., 2015b ) contributes to full TfoY production and whether the TfoY-mediated phenotypes described in this study aim at fighting a potential threat, as previously suggested for P. aeruginosa ( LeRoux et al., 2015a )."
} | 2,674 |
37416906 | PMC10320358 | pmc | 5,507 | {
"abstract": "Lignin has long been a trait of interest, especially in bioenergy feedstocks such as Populus . While the stem lignin of Populus is well studied, foliar lignin has received significantly less consideration. To this end, leaves from 11 field grown, natural variant Populus trichocarpa genotypes were investigated by NMR, FTIR, and GC-MS. Five of these genotypes were sufficiently irrigated, and the other six genotypes were irrigated at a reduced rate (59% of the potential evapotranspiration for the site) to induce drought treatment. Analysis by HSQC NMR revealed highly variable lignin structure among the samples, especially for the syringyl/guaiacyl (S/G) ratio, which ranged from 0.52–11.9. Appreciable levels of a condensed syringyl lignin structure were observed in most samples. The same genotype subjected to different treatments exhibited similar levels of condensed syringyl lignin, suggesting this was not a response to stress. A cross peak of δ C / δ H 74.6/5.03, consistent with the erythro form of the β-O-4 linkage, was observed in genotypes where significant syringyl units were present. Principle component analysis revealed that FTIR absorbances associated with syringyl units (830 cm −1 , 1317 cm −1 ) greatly contributed to variability between samples. Additionally, the ratio of 830/1230 cm −1 peak intensities were reasonably correlated ( p -value < 0.05) with the S/G ratio determined by NMR. Analysis by GC-MS revealed significant variability of secondary metabolites such as tremuloidin, trichocarpin, and salicortin. Additionally, salicin derivatives were found to be well correlated with NMR results, which has been previously hypothesized. These results highlight previously unexplored nuance and variability associated with foliage tissue of poplar.",
"discussion": "Results and discussion HSQC NMR Heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) was utilized to characterize the isolated lignin structure from the leaf tissue. Specifically, the aromatic region ( δ C / δ H 100–140/6.0–8.0) of the spectra was examined for monolignol content, and the aliphatic region ( δ C / δ H 100–60/6.0–4.0) was examined for interunit linkage content. Samples were observed to have appreciable S units as indicated by the S 2/6 peak ( δ C / δ H 103.7/6.71). All samples exhibited a signal at ( δ C / δ H 110.7/6.98), indicating the presence of G units. The S/G ratio ranged from 0.41 to 11.9, which is a surprisingly high degree of variability ( Fig. 2 ). For all samples, the β-O-4 aryl ether linkage was the most abundant, as indicated by the signal at ( δ C / δ H 71.8/4.86). The β-O-4 linkage is usually positively correlated with the S/G ratio. However, this relationship was not observed here. However, setting aside the two high S/G samples (856-S and 1031-N), β-O-4 levels were correlated with uncondensed S units with a correlation coefficient (CC) = 0.57. A similar observation has been made in a previous study, where β-O-4 was correlated with S but not the S/G ratio. 23 It could be that condensed S units, at least partly, influenced the stereochemistry of linkage formation. This is supported by an observed negative correlation between condensed S units and β-O-4 levels (CC = −0.46). β-5 and β–β linkages were observed at ( δ C / δ H 86.8/5.47) and ( δ C / δ H 84.8/4.64), respectively, but at levels significantly lower than β-O-4 linkages. Most samples also contained condensed S units as indicated by the signal around δ C / δ H 6.32/106.4. However, condensed G units were not observed, suggesting that S units are selectively condensed. In a previous study, the presence of condensed monolignols was observed through decreased thioacidolysis yields. 16 However, thioacidolysis works by cleaving the liable β-O-4 ether bond, and therefore highly condensed lignin structures may bias results. Indeed, Cabané et al. 16 reported that the proportion of S units decreased as condensed units increased ( i.e. , thioacidolysis yield decreased). While the referenced study introduced ozone stress which induced condensed lignin, it would be interesting to evaluate whether only condensed S units were present, or if all monolignols exhibited condensed structures. This observation highlights a unique beneficial utility offered by HSQC NMR. Initially, there appears to be an abundance of H units as indicated by the signal at ( δ C / δ H 127.9/7.19). However, upon closer inspection, this instead resembles characteristic amino acid contamination that has been described in HSQC NMR spectra. 24 To avoid erroneous quantification of H units due to contamination, this signal was not included in the semi-quantitative evaluation of lignin structure. One amino acid that appears prominently in the aromatic region is phenylalanine (Phe). Phenylalanine is a precursor to many secondary metabolites and has been identified as a response to drought stress. 25,26 Though it did not interfere with lignin signals, tryptophan (Trp) was also observed in the spectra. Increased levels of tryptophan helps regulate osmotic balance in response to drought stress. 27 Tyrosine (Tyr) has also been shown to be associated with drought stress tolerance. 28 Strong phenylalanine, tryptophan, and tyrosine signals were present in all samples. These amino acids also play a variety of other roles in plant growth and development. The prominence of amino acid signals in these leaf spectra also illustrate the difference in tissue type, as stem tissue typically registers very low or zero amino acid levels. HSQC NMR revealed tremendous variability among the 11 samples. Perhaps the most striking observation is the degree of variability exhibited in the S/G ratio. While the actual S/G level may vary by analytical method, the S/G ratio of Populus stem lignin is generally reported in the range of 1.5–2.5. 5 These 11 foliage tissue samples exhibited a significantly wider range of S/G ratios, ranging from 0.33 to 9.79. It should be noted that leaf lignin and stem lignin (especially mature wood lignin) are expected to have different properties and should not be directly compared. The authors offer this comparison to illustrate the relatively good agreement of analyses associated with the well-studied stem lignin. S units especially exhibited a high degree of variability. From Fig. 1 , the S 2/6 signal of sample 9860 (S/G = 0.73) is distinguishable at only slightly higher than background levels. However, in sample 1031 (S/G = 9.79), the S 2/6 signal is very prominent and clearly more abundant than the G 5 signal. As HSQC NMR is a semi-quantitative technique, these absolute differences are difficult to distinguish here. However, Cabané et al. quantified foliar lignin S/G ratio of Populus tremula x alba to be approximately 0.6 by thioacidolysis, 16 which compares well with approximately half of the samples analyzed in this study. The β-O-4 linkages also exhibited striking variability across these foliage samples. In stem lignin the β-O-4 bond is the most abundant linkage, with reported values typically in the range of 60–65%. The foliage samples here exhibited β-O-4 content as low as 26.1% and as high as 73.9%, with only two samples (LILC-26-4-S and 9591-S) exceeding 60%. This is consistent with the findings of Cabané et al. , 16 who hypothesized the decreased β-O-4 linkage content was due to the lower S/G ratio. Typically, the β-O-4 linkage content is observed to be positively corrected with the S/G ratio. 29 However, a negative trend between these two phenotypes is observed here. It is unclear what factors may be contributing to this observed variability of these natural variant, field-grown samples. Similar variability was observed in both the south (drought) and north (control) sample sets, so treatment is likely not a contributing factor. One potential explanation may be that lignin structure varies by leaf anatomy. It is well documented that lignin can vary by tissue type ( i.e. , leaf vs. stem). In this case, petiole and/or midrib of the leaf may have a lignin structure different from the lamina ( i.e. , higher S/G ratio), and varying ratios of petiole : midrib : lamina could explain some of the observed variability. Fig. 1 Select HSQC NMR spectra of two lignin samples highlighting the significant variability observed, primarily in the aromatic region. Sample 9860-N (left) was measured to have an S/G ratio of 0.73, whereas sample 1031-N (right) was measured to have a substantially higher S/G ratio of 9.27. The aromatic region of the spectra of both samples displayed signals characteristic of phenylalanine (Phe), tryptophan (Trp), and tyrosine (Tyr) associated with amino acids found in cellulase. In the aliphatic region, the β-O-4 linkage signal was the most prominent, with β-5 and β–β signals typically present near background levels (1031-N) or just above background (9860-N). Fig. 2 HSQC spectra of leaves from the same genotype (1121 and 9591) subjected to different treatments. The genotypes from the north end (1121-N, 9291-N) were irrigated. The genotypes from the south end (1121-S, 9291-S) were subjected to drought treatment. Genotype 1121 exhibited condensed S units, regardless of treatment. Conversely, genotype 9591 exhibited minimal condensed S units ( i.e. , present at approximately background levels), regardless of treatment. One surprising observation is that some samples exhibited differential positions of the C α –H α shift in the β-O-4 linkage structure. The C α –H α shift of the β-O-4 substructures can vary depending on several factors. For instance, a difference in C α –H α chemical shifts has been overserved between G-unit linked β-O-4 substructures and S-unit linked β-O-4 substructures. 30 However, the genotype with the lowest S/G ratio (425-N) exhibited a cross peak consistent with the typical β-O-4 assignment in Populus ( δ C / δ H 71.6/4.79). By contrast, the genotype with the highest S/G ratio (1031-N) exhibited a β-O-4 cross peak around ( δ C / δ H 74.6/5.03). Therefore, differences in shifts due to G-linked and S-linked β-O-4 substructures seems unlikely. Differences in C α –H α chemical shifts associated with erythro and thero conformations of the β-O-4 linkage have also been reported. 31 It has been observed that the erythro form of the β-O-4 dominates in angiosperms, whereas a 50 : 50 mixture of erythro and threo forms are typically present in gymnosperms. 32 This is due, at least in part, to the S/G ratio since S units preferentially form the erythro form of the β-O-4 linkage. However, once again examining the genotype 1031-N spectra, the contribution of S units is almost exclusively from condensed S units. Indeed, it was observed that genotypes which exhibited primarily condensed S units also exhibited β-O-4 cross peaks in the δ C / δ H 74.6/5.03 region. By contrast, genotypes with non-condensed S units exhibited β-O-4 cross peaks in the δ C / δ H 71.6/4.79 region. Therefore, the observed differences in the chemical shifts of the β-O-4 cross peaks are attributed to the erythro and threo forms of the substructure. Similar findings of unexpected lignin structures in leaves and differences in erythro / thero ratios has also been reported in ginkgo leaf. 33 This finding could offer an opportunity for understanding additional factors influencing the erythro / thero ratio of the β-O-4 linkages, which has been shown to impact delignification. 34 While these samples consist of enzyme lignin, another commonly utilized strategy for HSQC NMR analysis is whole cell wall (WCW) analysis, wherein the whole cell wall (after extraction and ball milling) is directly dissolved in the NMR solvent, therefore bypassing the enzymatic hydrolysis step. Sample 856-S was selected for whole cell wall WCW NMR analysis as a comparison to the isolated enzyme lignin (ESI Fig. S1 † ). The typical S 2/6 and G 2 signals were noticeably absent from the WCW spectra but were observed to be well resolved in the enzyme lignin spectra. It is expected that these results are influenced by the low lignin content associated with leaf tissue, which has been measured to be approximately 10%. 8 The enzymatic hydrolysis procedure allows a more lignin rich residue to be analyzed which improves the corresponding signals. Samples were also subjected to two step acid hydrolysis to determine Klason lignin content. However, this procedure produced suspect results, and similar difficulties with Klason lignin measurement of foliage tissue has been previously documented. 35 FTIR Fourier-transform infrared (FTIR) spectroscopy is an analytical tool widely used to identify the functional groups of many compounds, including lignin. Care must be taken when interpreting FTIR spectra of biomass, as bands can be attributed to multiple biomass components. Fig. 3 displays the FTIR spectra of the toleuene : ethanol extracted samples, which will contain cell wall components besides lignin ( i.e. , sugars). Prominent bands in the FTIR spectra are summarized in Table 2 and were assigned based on comparison with existing published literature. All samples exhibited a wide band centered around 3290 cm −1 , which is associated with O–H stretching. Peaks were also observed at 2920 and 2850 cm −1 , corresponding to C–H vibration of CH 2 and CH 3 functional groups. Fig. 3 displays the absorbance spectra of the fingerprint region of 1800–800 cm −1 , as this region typically provides the most information regarding cell wall structure. The peak at approximately 1735 cm −1 represent is typically associated with xylan and has also been associated with stretching vibration of nonconjugated and conjugated ketones. The peak at 1440 cm −1 corresponds to asymmetric O–H deformations in cellulose. The 1515 cm −1 peak is attributed to lignin aromatic skeletal vibrations. Fig. 3 FTIR spectra of all 11 samples are displayed for the fingerprint region of 800–1800 cm −1 . All spectra were baseline corrected and normalized between [0,1]. Specific wavenumbers of interest are indicated on the x -axis, such as 830 cm −1 for syringyl units (827–833 cm −1 ) and 910 cm −1 for guaiacyl units (908–913 cm −1 ). The FTIR spectra were further analyzed by principal component analysis (PCA). PCA is a useful mathematical procedure for analyzing data. The goal of applying PCA to FTIR is to transform a large data set ( i.e. , thousands of data points from FTIR spectra) into a few key parameters called principal components (PCs). The resulting PCs are typically characterized by the amount of variation they represent, with PC1 accounting for the most variation, PC2 accounting for the second most variation, and so forth. Additionally, PC scores are assigned to each sample, and samples that have similar spectra will be scored similarly. The final result is that PCA reduces the FTIR spectra of many samples down to two dimensions (typically PC1 and PC2), which can then be conveniently represented on a familiar X–Y plot. Samples with similar PC scores will be plotted in close proximity, revealing cluster patterns and allowing differentiation between different groups. The resulting PC1 and PC2 scores from each sample are presented in the score plot in Fig. 4 . All spectra were baseline corrected, normalized from [0, 1], and the second derivative of the spectra were taken. Data in the fingerprint region of 1800–800 cm −1 were considered for PCA. PC1 and PC2 accounted for 23.3% and 14.0% of the variability, respectively. The remaining PCs accounted for less than 12% (each) of the variability. No obvious spatial clustering patterns were observed. Specifically, samples from the south (S; drought treatment) and north (N; irrigated treatment) sets are not readily distinguished by PCA at the 95% confidence interval, indicating that treatment was not a significant contributor to the observed variability. Examining the loadings of each PC provides insight as to which structural features (as determined by wavenumbers) contribute most significantly to the observed variation. PC1 is driven primarily by the band around 1317 cm −1 , which is typically associated with the C–O stretching of the S unit ring. This aligns with the (semi-quantitative) observation from the NMR spectra, where the S unit signal is more variable than the G unit signal. Wavenumbers that contributed to PC2 include the peak between 1620–1630 cm −1 , which is associated with C \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n C aromatic skeletal vibrations. The peak around 830 cm −1 , associated with C–H bending of syringyl units, also contributed to PC2. Another contributor to PC2 includes wavenumber 1081 cm −1 , which is a shoulder of the peak centered around 1035 cm −1 peak associated with C–O stretching of primary alcohols in lignin and polysaccharides. The peak around 1685 cm −1 , associated with conjugate carbonate of carboxylic acid and ketone groups, was common to both PC1 and PC2. Fig. 4 Score plot for PCA analysis of FTIR spectral data. Various peaks in the FTIR spectrum have been associated with lignin structure, such as syringyl and guaiacyl units. The peak around 1317 cm −1 is associated with C O stretching of syringyl units. The peak at 1230 cm −1 associated with C–O, C–C, and C O stretching of guaiacyl units. The ratio of intensities at the 1317 cm −1 peak (syringyl) and 1230 cm −1 peak (guaiacyl) are often used to estimate the S/G ratio of biomass. 42 However, the ratio of these two peaks was not well correlated with the S/G ratio. This is likely due to the influence of polysaccharide bands in the FTIR spectra. For instance, a typical lignin peak at around 1594 cm −1 , associated with aromatic skeletal vibrations and C O stretching in lignin, was not present. However, the ratio between the 830 cm −1 peak (associated with syringyl units) and the 1230 cm −1 peak (associated with G units) was observed to be well correlated (CC = 0.58, p -value = 0.03) with the S/G ratio determined by NMR. These observations support the S/G measurement obtained by NMR, but also illustrate benefit of utilizing HSQC NMR for analyzing lignin structure. Metabolite profiling In addition to FTIR and NMR analyses, the 11 foliage samples were subjected to metabolite profiling. Samples were extracted with 80% ethanol, dried under nitrogen, and silylated to generate trimethylsilyl (TMS) derivatives prior to analysis by gas chromatography-mass spectrometry (GC-MS). Sorbitol was used as the internal standard. A summary of some of the most abundant metabolites are reported in Table 3 on the basis of μg metabolite per g dry weight (DW) in sorbitol equivalents. A full list of quantified metabolites is available in the ESI. † Sucrose was by far the most abundant metabolite – approximately 3.5 times more abundant than the second most abundant metabolite (tremuloidin). Other highly abundant metabolites include salicortin, salicin, myo-inositol, quinic acid, glucose, and trichocarpin. Although tremuloidin was the second most abundant metabolite on average, two samples (1025-N, 1031-N) observed to be lacking any measurable tremuloidin, which is a reason these two genotypes were selected for this study. Additionally, sample 1031-N was observed to have low levels of salicin, trichocarpin, catechol, and tremulacin, which were highly abundant in most other samples. This is illustrated in the overlaid total ion chromatograms (TICs) of sample 1031-N and LILC-26-4-S displayed in Fig. 6 . From this figure it can be observed that sample LILC-26-4-S had prominent signals at a retention time (RT) of 16.887 and 17.011 corresponding to trichocarpin and salicortin, respectively. However, these peaks were barely discernible in the 1031-N TIC. A similar phenomenon was observed with the signal at RT = 16.224 associated with tremuloidin. As the samples from the north side of the field (denoted with “-N” in the sample name) were irrigated and samples from the south side of the field (denoted with “-S” in the sample name) were subjugated to drought conditions, one may expect to observed established differences in metabolites associated with drought stress. However, this was not necessarily the case. For instance, malic acid has previously been found to increase in response to drought stress, 43 though these drought samples has lower malic acid levels (3290 μg g −1 DW) compared to irrigated samples (8751 μg g −1 DW). High variability was observed in levels of tremulacin and salicortin among the samples. On average tremulacin levels were higher in the irrigated samples and salicortin levels were higher in the drought samples. These phenolic glycosides have been linked to roles in herbivore and/or pathogen defense, 44 suggesting there may be biotic stressors impacting these samples. PCA was also utilized to distinguish samples based on the variability of metabolite profiles, with results plotted in Fig. 5 . To avoid biasing the results based on the differences in magnitudes of the metabolite concentrations, data were standardized by the standard deviation. PC1 and PC2 accounted for 42.0% and 19.8% of the variability, respectively. Other PCs accounted for less than 14% (each) of the variability. Like the FTIR PCA, 6–7 samples are clustered closer together in (or just outside) quadrant I, whereas 4–5 samples are more dispersed. Loadings for PC2 indicate that it is highly driven by shikimic acid, fructose, glucose, galactose, and raffinose. Loadings for PC1 are less differentiable, but are highly influenced by salicylic acid, catechol, caffeic acid, stearic acid, and maleic acid. PCA did not distinguish samples by treatment at the 95% confidence interval, again indicating that this was not a major contributor to metabolite variability. Fig. 5 GC/MS chromatogram of two selected samples: LILC-26-4-S (black) and 1031-N (blue). The retention time periods of approximately 11–12 minutes and 16–17 minutes have been enlarged to detail differences in metabolites such as quinic acid, glucose, tremuloidin, trichocarpin, and salicortin. Fig. 6 Score plot for PCA analysis considering metabolite profiling results determined by GC-MS. The metabolite profiles were also correlated with the lignin traits elucidated by NMR to explore potential relationships between metabolites and lignin structure in leaves. The resulting Pearson correlation coefficients are tabulated in Table 1 . One of the ways Populus adapts to a water deficit is through drought tolerance. Drought tolerance mechanisms aim to maintain biological function under stress conditions. For instance, the transcription factor PtoMYB170 was shown to influence drought tolerance and lignin deposition. 45 Overexpression of PtroMYB170 induced expression of many lignin biosynthesis genes compared to wild type, including PAL, C4H2, 4Cl5, HCT1, C3H3, CCOAOMOT1, F5H2, CCR2, COMT2, and CAD1. F5H and COMT are responsible for the hydroxylation and methylation, respectively, of coniferyl alcohol and coniferaldehyde, and therefore would be expected to impact the S/G ratio. PtoMYB170 was found to be highly expressed in stem in young leaf tissue, but had low expression in roots, petioles, and mature leaves. In this study, several metabolites were found to be correlated with various lignin traits. Among these correlated metabolites were the salicyloids, salicin and salicylic acid. Specifically, both metabolites were negatively correlated with the S/G ratio. Additional salicin derivatives such as benzyl-salicylic acid-2- O -glucoside, salicyl-coumaroyl-glucoside, and salicyl alcohol also exhibited strong correlations to lignin S/G ratio. Results from integration of signals from the HSQC NMRM spectra. All results are reported on an S + G basis and represent abundance per 100 lignin aromatic units Sample S S, cond. S, total G S/G β-O-4 β-5 β–β 9589-S 1.11 59.8 60.9 39.1 1.56 22.1 4.24 1.97 1181-S 2.33 71.5 73.9 26.1 2.83 50.3 2.75 1.19 1121-S 7.82 60.1 67.9 32.1 2.12 17.9 2.47 1.73 856-S 4.01 85.8 89.8 10.2 8.83 83.2 13.1 4.18 LILC-26-4-S 31.7 5.61 37.3 62.7 0.59 63.3 5.53 2.92 9591-S 37.4 2.2 39.6 60.4 0.70 63.6 2.9 3.5 9860-N 23.1 11.5 34.5 65.5 0.53 26.6 5.17 1.88 1031-N 0.38 91.9 92.3 7.74 11.9 17.8 1.93 0.62 9953-N 33.8 4.08 37.8 62.2 0.61 43.5 6.15 2.87 1025-N 26.5 20.2 46.7 53.3 0.88 74.5 10.3 2.96 425-N 33.0 1.22 34.2 65.8 0.52 43.5 4.28 3.67 Peak of interest identified on the FTIR spectral plot of Fig. 4 Observed Peak (cm −1 ) Peak assignment Reference 1735 C O stretching in lignin and hemicellulose \n 36 \n 1620 C O stretching \n 37 \n 1515 Aromatic C C skeletal vibrations in lignin \n 36 and 38–40 1440 O–H in-place deformation in cellulose \n 37 \n 1318 C O stretching of syringyl units \n 36 , 38 and 40–42 1230 C–C, C–O, and C O stretching of guaiacyl unit \n 36 , 40 and 41 1035 C–O stretching \n 36 , 38 and 42 890 C–H deformation vibration of cellulose \n 42 \n 830 C–H bending of syringyl units \n 42 \n Abundance of each metabolite determine by GC-MS Abundance (μg g −1 DW in sorbitol equivalents) Metabolite 1121-S 1181-S 9589-S 9860-N 9953-N 1031-N 9591-S 1025-N LILC-26-4-S 856-S 425-N Sucrose 189 837 260 895 271 979 222 162 457 405 146 732 145 955 426 783 378 962 224 151 407 349 Tremuloidin 70 907 57 741 95 449 81 725 209 857 0 21 878 0 139 440 39 062 176 411 Salicin 37 348 51 195 63 689 45 474 97 508 103 24 818 25 613 101 144 44 351 94 061 Myo-inositol 19 369 37 636 30 932 23 191 28 732 18 209 20 249 40 563 33 033 33 720 41 203 Quinic acid 59 883 57 465 62 693 29 131 28 392 55 523 31 092 143 311 24 148 29 405 8004 Glucose 41 119 18 283 20 227 8872 21 190 13 444 28 488 129 027 22 380 8564 7702 Trichocarpin 2921 14 313 19 400 8845 20 102 64 3822 2127 15 094 6280 32 742 Malic acid 2976 1542 4371 5919 18 463 3062 2409 11 002 7676 767 5311 Shikimic acid 4641 5524 7534 5404 24 291 6718 8727 31 191 16 158 5627 4326 Citric acid 2755 391 5849 3718 5051 1248 1349 4973 4779 626 4186 2-Phenethyl-glucoside 2608 4131 6153 3666 12 858 4114 1798 7280 13 685 7653 9432 Catechol 1932 1565 1997 1816 5674 18 472 1499 4326 2057 7035 Fructose 5528 3976 4749 2477 4357 4766 7720 25 158 6884 2640 1814 1,2-Cyclohexanediol glucoside 2993 1768 1268 1763 6040 222 634 1965 6951 5473 8631 5-Oxo-proline 675 1797 1427 1111 3301 982 975 2276 2996 895 2070 Catechin 1028 2323 1369 907 883 1013 1619 5670 433 3135 1702 α-Linolenic acid 1136 1693 1293 457 3071 472 2120 1339 8016 1657 2222 Digalactosylglycerol 1855 3009 1509 1413 2828 524 3743 2656 7403 2496 2164 Tremulacin 870 3474 3377 800 880 0 310 0 1412 12 667 30 895 Threonic acid 632 717 1060 1159 3383 1360 874 3809 1885 550 1050 Galactose 2253 952 690 550 2277 1597 2430 16 068 1239 560 526 Salicortin 215 4188 3441 6307 5513 164 1497 622 12 591 50 949 31 845 Monogalactosylglycerol 1788 2005 1124 725 3481 188 2786 1045 8974 1545 1888 Phosphate 881 1011 1492 311 2912 1050 1557 3434 1434 546 475 Glyceric acid 810 763 797 494 3092 920 508 3009 1391 583 369 In Populus sp., salicin biosynthesis has a benzoic acid route, 46 which can be derived through the shikimate/chorismite pathway 47 or the phenylalanine/cinnamate route. 48 Current research indicates that the production pathways of salicyloids and lignin are not competitive processes, though tradeoffs between the two processes have been hypothesized. 49 The correlation between salicyloids and the lignin S/G ratio would provide weight to this hypothesis, as increased salicyloid content is correlated with increased ratio of guaiacyl units. Although no p -hydroxybenzoate (PB) units were observed in the lignin of these leaf tissues, stem tissue of Populus usually contains ∼5% PB units. While p -bydroxybenzoate has been found to almost exclusive acylate the S unit of lignin, PB has been observed to exhibit a negative correlation with the S units. 29 A future study examining salicyloids and benzoate incorporation of lignin may shed additional light on potential trade-offs. Another metabolite found to be correlated with lignin structure was quinic acid ( Table 4 ). Quinic acid can be a precursor of monolignol synthesis. 50 However, its incorporation is associated with the phenylpropanoid pathway product p -coumaroyl CoA, which represents a major branchpoint in the pathway and can be directed to various pathways to produce flavonoids, monolignols, or a number of other compounds. 51 The flavonoid quercetin, which was also observed to be associated with lignin S/G ratio, is derived by converting p -coumaryl CoA to chalcone, though malonyl CoA is also a substrate. 52 A similar relationship has been reported previously, as N -acetylserotonin methyltransferase (MsASMT1) was shown to impact both lignin S/G ratio and glycosides of quercetin when overexpressed in alfalfa. 53 Multiple enzymes catalyze reactions of p -coumaroyl CoA. hydroxycinnamoyl CoA: shikimate hydroxycinnamoyl transferase (HCT) has higher specificity toward shikimic acid and is associated with lignin biosynthesis [reviewed in ref. 51 ]. Hydroxycinnamoyl CoA: quinate hydroxycinnamoyl transferase (HQT) utilizes quinic acid more efficiently, and is more closely associated with the production of chlorogenic acids [reviewed in ref. 51 ]. Correlation coefficients (CC) between metabolite abundance measured by GC-MS and lignin traits measured by HSQC NMR Metabolite S G S/G β-O-4 β-5 β–β Sucrose −0.35 0.35 −0.45 0.15 0.33 0.26 Tremuloidin −0.59 0.59 −0.48 0.48 0.53 0.55 Salicin −0.69 0.69 −0.64 0.55 0.57 0.56 Myo-inositol −0.23 0.23 −0.49 0.07 0.03 0.17 Quinic acid 0.65 −0.65 0.38 −0.77 −0.55 −0.70 Glucose 0.39 −0.39 0.17 −0.51 −0.25 −0.41 Trichocarpin −0.54 0.54 −0.56 0.41 0.35 0.54 α-Linolenic acid −0.57 0.57 −0.41 0.64 0.60 0.35 Quercetin −0.55 0.55 −0.59 0.46 0.51 0.41 Salicylic acid −0.62 0.62 −0.54 0.51 0.39 0.66 Salicyl-salicylic acid-2- O -glucoside −0.64 0.64 −0.49 0.65 0.62 0.39 Salicyl-coumaroyl-glucoside −0.66 0.66 −0.55 0.57 0.42 0.52 Caffeic acid −0.55 0.55 −0.63 0.40 0.38 0.55 Gallocatechin 0.72 −0.72 0.54 −0.74 −0.62 −0.70 In summary, these results provide an extensive characterization of lignin structure and metabolite abundance in Populus foliage tissue, of which there is currently limited knowledge. A surprisingly high degree of variability was observed in the cell wall structure, especially lignin, through HSQC NMR and FTIR. Specifically, condensed syringyl structures were observed in most samples, and these levels appears to be independent of treatment. A high degree of variability of metabolite abundance was also observed by GC-MS analysis, especially in tremuloidin, trichocarpin, and salicortin. These results demonstrate differences between foliage and more well-studied stem tissue, and also highlight previously unexplored nuance and variability associated with foliage tissue of poplar."
} | 7,815 |
37424707 | PMC10328015 | pmc | 5,508 | {
"abstract": "The ecological deterioration caused by the continuous and excessive use of synthetic\ninputs in agriculture has prompted the search for environmentally favorable resources for\ncrop production. Many have advocated for the use of soils from termite mounds to improve\nsoil and plant health; therefore, the purpose of this study was to characterize the\nmicrobiome multifunctionalities that are important for plant health and growth in termite\nmound soil. The metagenomics of soil from termite mounds revealed taxonomic groups with\nfunctional potentials associated with promoting the growth and health of plants in\nnutrient-poor, virtually dry environments. Analysis of microorganisms revealed that\n Proteobacteria dominated the soil of termite colonies, while\n Actinobacteria ranked second. The predominance of\n Proteobacteria and Actinobacteria , the well-known\nantibiotic-producing populations, indicates that the termite mound soil microbiome\npossesses metabolic resistance to biotic stresses. Functions recognized for diverse\nproteins and genes unveiled that a multi-functional microbiome carry out numerous\nmetabolic functions including virulence, disease, defense, aromatic compound and iron\nmetabolism, secondary metabolite synthesis, and stress response. The abundance of genes in\ntermite mound soils associated with these prominent functions could unquestionably\nvalidate the enhancement of plants in abiotic and biotically stressed environments. This\nstudy reveals opportunities to revisit the multifunctionalities of termite mound soils in\norder to establish a connection between taxonomic diversity, targeted functions, and genes\nthat could improve plant yield and health in unfavorable soil conditions.",
"conclusion": "Conclusion Insight on how diverse microbial populations in termite mound soils impact plant\nperformance and production via metagenomics unlocks innovative prospects for developing\necologically friendly means to maximizing the benefits of microbe-mediated agricultural\ntechnologies. Shotgun sequencing of termite mound soils shows high taxonomic richness, with\n Proteobacteria and Actinobacteria dominating the mound\nsoils. Exploration of our data set revealed the functional abilities of the microbiome\nconnected with the termite mound soils. It also revealed that our metagenome housed a high\namount of gene related to secondary metabolism, stress and defense response, iron\nacquisition, xenobiotic breakdown, normal physiological pathways, and biological\nremediation. Therefore, the microbiomes are hypothetical to aid development, survival, and\ngrowth of the crop in harsh ecological soil conditions. With this knowledge, both innovative\nculturable approaches should be developed to isolate these microbial strains that can\nexhibit strong features in hostile circumstances, or we can manipulate organisms with these\ngenes to get new functional benefits.",
"introduction": "Introduction Termites are highly diverse and are mainly found in Africa, Asia, and other continents\nexcept Antarctica. \n 1 \n There are over 2 600 well-known termite species, and approximately 20% of them have\ndetrimental effects on agricultural produce. \n 2 \n Through the excavation of materials from parent soils, mound-building termites\ncontribute significantly to ecological services when building their mounds. \n 3 \n Termites play significant roles in enhancing the physical and chemical properties of\nsoil (eg, nitrogen, phosphorus, potassium, clay) and breaking down organic matter into forms\nutilizable by plants. \n 4 \n Termites as “soil engineers” influence the distribution of nutrients and minerals to\ntheir adjacent soil. \n 5 \n Termites construct structures called mounds which have been reviewed by several\nauthors to be rich in microbial diversity as influenced by a lot of nutrients accumulated in\nsoil from termite mound. 6 , 7 Recently, soils from termite mound have been presented to farmers in central Côte d’Ivoire, \n 8 \n Sierra Leone, \n 9 \n Zimbabwe \n 10 \n , and Uganda \n 11 \n to grow vegetables and other crops on top of mounds, whereas agronomists in southern\nZambia excavate and amass soil from termite mounds and use it as an alternative to increase\ntheir soil fertility at their local farms. \n 12 \n This idea will reduce the total reliance on chemical fertilizers or pesticides by\nfarmers and then reduce the negative impact of excessive and prolonged use of chemical\nfertilizers on the environment. \n 13 \n In accordance with this recommendation, we chose to investigate the effects of\ntermite bioturbation on the termite mound soil microbiome and determine their role in\npromoting plant development, health, and disease resistance through adaptation to abiotic\nand biotic stresses, xenobiotic degradation, stress responses, and iron acquisition. This\nresearch will assist in understanding how diverse microorganism communities in termite mound\nsoils may impact plant performance and productivity (as reported by local subsistence\nfarmers). 14 , 15 To achieve this aim and\nsurmount the limitations of the culture-dependent approach, a shotgun sequencing approach\nwas used to completely characterize the microbial communities and functional genes in\ntermite mound soils. 16 , 17 This\nmetagenomic approach may unleash novel opportunities for developing environmentally friendly\ntechniques to generate profits from microbe-assisted farming machinery. With this in mind,\nit was hypothesized that soil from termite mounds contains a large gene pool for (a)\ndetoxification of xenobiotic compounds and metals, (b) resistance against diverse\nantimicrobial compounds, (c) iron-acquisition functions that enhance iron bioavailability,\nand (d) numerous secondary metabolite pathways associated with the production of\nantibacterial peptides or bacteriocins.",
"discussion": "Discussion Functional characterization of the microbiome in soil from termite mounds is essential for\nunderstanding the microbial role in supporting plant development in abiotically stressed,\ndisease-prone, and nutrient-deficient circumstances. \n 27 \n This study revealed why plants grown on termite mound soils tend to do well as\nreported by many local famers. 11 , 12 , 28 Apart from the fact that\ntermite mound soil contains high soil nutrients as revealed by Ehrle et al \n 29 \n and supported by our soil analysis ( Supplemental\nTable S1 ), it also housed a lot of microbial diversities that are of\nenvironmental importance ( Figure 1 ). \n 7 \n The dominance of Proteobacteria and Actinobacteria \nin termite mound soils from this study supported this fact as some strains\n( Bacillus, Pseudomonas and Streptomyces species) from\n Proteobacteria and Actinobacteria are recognized to\nsynthesize almost 80% of the total metabolites identified nowadays. 30 , 31 It has also been established that\nwell-known antimicrobial compounds like streptothricin, actinomycin, and streptomycin, which\nare of agricultural significance, are produced by some species of the\n Actinobacteria , \n 32 \n which was very abundant in termite mound soils from this study. Identified protein function via KEGG, NOG, COG, and subsystem ( Figure 2 ) revealed community-associated metabolic\nabilities and useful roles of the termite mound soil microbiome. The communities could\nfunction as valued biological sources of novel secondary metabolites with multiple roles\nlike anti-infection, antagonism, antibiotics, and anticancer. Metatranscriptomics research\nsupported the presence of cellular processes, protein families, and particular genes in\ndifferent environments like soil. \n 33 \n Our study revealed a lot of pathways and genes that code for secondary metabolism\n( Figure 3 and Supplemental\nTable S3 ), a unique characteristic of microorganisms to synthesize a variety of\nmetabolites that are significant for self-defense. \n 32 \n They also play huge function in microbe–microbe, host–microbe, and\nmicrobe–environment collaborations. \n 34 \n The presence of genes linked to auxin biosynthesis (a growth regulator influencing\nthe cell elongation and division in plants) in our study shows that termite mound soil\nhoused auxin-producing and auxin-secreting microbiome. Genes that code for cinnamic acid\nbiosynthesis were also identified from our study. This connotes that the microbes in termite\nmound soil can produce allelochemical phenolic—a chemical that affects metabolic processes,\nstimulate plant root growth, and promote seed germination. \n 35 \n Genes that help in iron acquisition and metabolism were reported from this study\n( Figure 6 ). These genes enable\nmicroorganisms to utilize iron for stimulating metabolic enzymes/pathways. \n 36 \n For instance, high-affinity iron transport systems (siderophores) linked with\nbiosynthetic chelates aid plants, bacteria, archaea, and fungi to withstand iron stress. \n 37 \n While microorganisms acquire iron (as siderophores), which is very competitive with\nthe aid of transport systems, plants can also benefit from this acquired iron through\nmicrobe–root communication under diverse soil circumstances. \n 36 \n Furthermore, our study also revealed the occurrences of several stress-mitigated\ngenes ( Figure 4 ). This means that\nthe microorganisms in soil from the termite mound could have employed them as a survival\nstrategy and environmental performances. For example, glycine betaine (reported from this\nstudy) is a key organic osmolyte in bacteria, archaea, and fungi that mitigates diverse\nenvironmental stresses such as heavy metals, salinity, high temperature, drought, and\nultraviolet radiation. \n 38 \n Also, glutathione is a stress-response pathway that militates against oxidative\nstress and gives fortification against toxic xenobiotics in our environment. \n 39 \n The microbial capability to use an aromatic composite by breaking down xenobiotic chemicals\nis necessary for decontamination of natural environments. \n 40 \n The identification of gene sequences linked with pathways for breaking down of\nchlorobenzoate, chloroaromatic, biphenyl, gentisare, benzoate, quinate, phenylpropanoid\ncompound, naphthalene and anthracene, p-hydroxybenzoate, n-phenylalkanoic acid, toluene, and\nsalicylate ester in termite mound soils ( Figure 4 ) suggests the possibility that the microbial communities in termite mound\nsoil could serve as a useful and promising candidate for biological remediation of soils\ncontaminated by the aromatic compounds. 41 , 42 Our study also witnesses high amount of gene sequences connected to virulence, disease, and\ndefense such as bacteriocins and adhesion ( Figure 5 ). These features allow bacterial communities to shield themselves with\nribosomally synthesized antibacterial peptides or bacteriocins. \n 43 \n The occurrence of adhesion in soil from termite mounds is indicative of a function in\nenhancing colonization by bacterial societies residing in termite mounds. The occurrence of\ngene resistance to mercury, arsenic, chromium, vancomycin, cadmium, cobalt–zinc–cadmium, and\nzinc in our study suggests the capability of microbes from termite mound soil in\nbioremediation. 44 - 47"
} | 2,753 |
33014998 | PMC7513618 | pmc | 5,509 | {
"abstract": "Over the past decades, enormous progress has been achieved with regard to research on environmentally friendly polymers. One of the most prominent families of such biopolymers are bacterially synthesized polyhydroxyalkanoates (PHAs) that have been known since the 1920s. However, only as recent as the 1990s have extensive studies sprung out exponentially in this matter. Since then, different areas of exploration of these intriguing materials have been uncovered. However, no systematic review of undertaken efforts has been conducted so far. Therefore, we have performed an unbiased search of up-to-date literature to reveal trending topics in the research of PHAs over the past three decades by data mining of 2,227 publications. This allowed us to identify eight past and current trends in this area. Our study provides a comprehensive review of these trends and speculates where PHA research is heading.",
"conclusion": "Concluding Remarks and Future Perspective The approach proposed in the study, which was based on the analysis of the full texts of articles, allowed to overcome the limitations of the traditional method based only on a systematic review of literature. The sample selected for analysis was divided into groups containing articles published in 5-years overlapping periods beginning in 1988 and ending in 2019. The analysis allowed to identify eight main areas in PHA research that governed the 31 years of discoveries. It should be noted that the indicated research groups do not exhaust all the conducted studies in the analyzed period. However, they present the research with the highest empowerment in identifiable scientific articles. The most important outcome of the data-mining process was the identification of these research areas that are still trending in the scientific community and are of high probability to continue. Firstly, scientists try to understand genetics and biochemistry behind PHA synthesis. This leads to the identification of key enzymes responsible for PHA synthesis, thus to the creation of better production strains. Moreover, insight into PHA accumulation from a genetic perspective opens new routes for obtaining multipurpose bioactive granules. Secondly, it is visible from identified trends that a lot of work is being conducted on processing and modifications of PHA, leading to smart composites. These processes and products will lead directly to providing solutions to substitute petrochemical polymers and provide markets with a range of smart materials. Such an approach is also backed up by studies leading to the sustainable production of these biopolymers from renewable and cheap substrates, which directly can reduce their so far high production costs. It needs to be emphasized that the indicated trends are to serve as a supportive tool for seeking further research directions, which should allow scientists to revise their research areas, improve the research process, and avoid duplication in studies, thereby increasing the efficiency of scientific work. Furthermore, it is vital to remember the given definition of a “trend.” Trends were discovered with restricting criterion of at least 10 papers published in each 5-years period. The criterion was adopted to allow the presentation of the most popular trends. That does not mean that other trends are less important. Moreover, those less popular trends may become leading ones in the future. As cited here, some works, both original or reviews, were published post the trend apogee. They presented either a summary of a specific research area or further narrowed and specialized research continuing from a particular trend. It is also not a foregone conclusion that some of the presented trends will reemerge or new ones will manifest from this broad research on microbial polyesters.",
"introduction": "Introduction Polyhydroxyalkanoates (PHAs) have been researched since their discovery in 1920. An exponential burst of scientific publications started in the early 1990s. Since then, yearly, more and more scientific documents are appearing, increasing our knowledge in this realm of biopolymers. A systematic literature review is an important method of understanding the field of study. However, due to high labor intensity, it is usually limited to narrow subjects. They are, in most cases, narrative and qualitative (Tranfield et al., 2003 ). To study the whole field, it is necessary to adopt text-mining toolset and quantitative methods. It is relatively easy to perform analysis based on metadata related to publications, mostly titles, keywords, and abstracts. The required software is readily available. Unfortunately, research by Blake ( 2010 ) revealed that authors report <8% of scientific claims in abstracts. Moreover, keywords used in publications are in many cases limited or modified by publishers. Therefore, studies based on metadata cannot be treated as fully reliable. The following limitation of most text-mining studies is predefinition of themes, clusters, or categories. This can prevent the discovery of new topics that were not predefined by researchers. Additionally, in the case of qualitative methods, the risk of researcher bias grows significantly. The approach offered in this study was designed to overcome such limitations. The analysis was performed using full texts of publications, and categories were discovered in data, not predefined. The well-known quantitative approach to text-mining was supplemented with new and original tools (for a full description, please see the Materials and Methods section). This allowed authors to identify not only categories but also trends. A diagram of the proposed approach compared with systematic literature review steps is presented in Figure 1 . The procedure is consistent with general rules for systematic literature reviews (Ananiadou et al., 2009 ). In this article, we have sampled scientific publications from Web of Science Core Collection that were firmly related to PHA research and performed an in silico analysis of the most frequently appearing words within the main text. We have omitted on purpose reviews that are not original per se , thus focusing only on scientific publications concerning the generation of new data in areas related to PHAs at the time of their publications. This allowed us to identify scientifically relevant keywords that enabled us to group the publications into clusters, groups, and then trends that have been emerging since the late 1980s. Figure 1 Diagram of the method and steps of systematic literature review (SLR). HDBSCAN, Hierarchical Density-Based Spatial Clustering of Applications with Noise; TF-IDF, term frequency–inverted document frequency."
} | 1,668 |
40235654 | PMC11997550 | pmc | 5,510 | {
"abstract": "Abstract Marine heatwaves occurring against the backdrop of rising global sea surface temperatures have triggered mass coral bleaching and mortality. Irradiance is critical to coral growth but is also an implicating factor in photodamage, leading to the expulsion of symbiotic algae under increased temperatures. Numerical modelling is a valuable tool that can provide insight into the state of the symbiont photochemistry during coral bleaching events. However, very few numerical physiological models combine the influence of light and temperature for simulating coral bleaching. The coral bleaching model used was derived from the coral bleaching representation in the eReefs configuration of the CSIRO Environmental Modelling Suite, with the most significant change being the equation for the rate of detoxification of reactive oxygen species. Simulated physiological bleaching outcomes from the model were compared to photochemical bleaching proxies measured during an ex situ moderate degree-heating week (up to 4.4) experiment. The bleaching response of Acropora divaricata was assessed in an unshaded and 30% shade treatment. The model-simulated timing for the onset of bleaching under elevated temperatures closely corresponded with an initial photochemical decline as observed in the experiment. Increased bleaching severity under elevated temperature and unshaded light was also simulated by the model, an outcome confirmed in the experiment. This is the first experimental validation of a temperature-mediated, light-driven model of coral bleaching from the perspective of the symbiont. When forced by realistic environmental conditions, process-based mechanistic modelling could improve accuracy in predicting heterogeneous bleaching outcomes during contemporary marine heatwave events and future climate change scenarios. Mechanistic modelling will be invaluable in evaluating management interventions for deployment in coral reef environments.",
"conclusion": "Conclusions This study validates the model representation of the photophysiological processes of the coral–symbiont relationship and temperature-mediated, light-driven bleaching impacts. The model captured the observed coral bleaching under heat stress conditions in the unshaded treatment. The model-simulated timing for the onset of bleaching closely corresponded (within a few days) with a significant photochemical decline in the experiment. For the heat stressed but shaded experimental treatment, the model simulated reduced stress that did not exceed the bleaching threshold, whilst in the experiment this treatment experienced reduced and delayed photochemical decline relative to the unshaded heat stressed treatment. This indicates that the model simulated greater protection from bleaching impacts under reduced light levels than in the experiment. Likewise, increased temperatures may have negated some benefits of shade in the experiment. Further validation of the CBM should be conducted in various environmental scenarios and scaled up from a short-duration heat stress experiment to a more realistic representation of an MHW event. Future model evaluation could also consider comparing model-simulated symbiont cell expulsion to observed symbiont cell expulsion and model-simulated photochemistry to observed photochemistry. Alternatively, quantifying the activity of antioxidant enzymes in corals may provide a more suitable comparison to the model’s simulation of ROS-induced bleaching. Changes to the model configuration could consider representing lower nutrient levels typical of most coral reef environments and replacing empirical-based formulations with more mechanistic process descriptions. From this initial model evaluation, we demonstrate the utility of numerical modelling in predicting bleaching outcomes under the multiple stressors of heat and light. We anticipate that process-based mechanistic modelling can provide a much needed assessment of reef interventions, management strategies and predictions of coral bleaching under various climate scenarios. Thus, the CBM has many potential applications, and we envision this study as a foundation for its continued development.",
"introduction": "Introduction Climate change is increasing the frequency and intensity of marine heatwaves (MHWs), which impact coral reefs globally. Anomalously high seawater temperatures associated with thermal stress events have resulted in a global decline in coral cover of >20% during this (21st) century ( Berkelmans et al. , 2004 ; Hughes et al. , 2017 ; Hughes et al. , 2018 ). Thermal anomalies can lead to the breakdown of the mutualism between the coral host and their endosymbiotic algae ( Glynn, 1993 ). Coral bleaching is characterised by a loss of pigmentation of algae from the family Symbiodiniaceae, an expulsion of Symbiodiniaceae via exocytosis from the coral host or the shedding of in hospite Symbiodiniaceae - containing host cells to the water column ( Gates et al. , 1992 ). Recent mass coral bleaching events on the Great Barrier Reef (GBR) have led to regional-scale changes in coral reef assemblages ( Hughes et al. , 2018 ). The widespread events of 2016, 2017 and 2020 were more severe than those in preceding decades, with estimated coral loss across the entire GBR from these events ranging from 30 ( Bozec et al. , 2022 ) to 50% in shallow waters after the 2016 event alone ( Hughes et al. , 2017 ). Aerial surveys confirmed a fourth and fifth mass coral bleaching event impacted the GBR in 2022 and 2024 ( Cantin et al. , 2024 ). During the last decade, the frequency of MHWs has increased by >50% ( Oliver et al. , 2018 ; Méndez et al. , 2023 ). Using a 1982–2005 baseline, >50% of the world’s oceans are projected to be in a permanent MHW state by the end of the 21st century ( Oliver et al. , 2019 ). Annual mass bleaching is predicted on >90% of coral reefs worldwide by the end of this century ( Frieler et al. , 2013 ; van Hooidonk et al. , 2013 ). A variety of modelling systems have been developed for projecting broadscale patterns of mass bleaching on decadal scales, incorporating various levels of complexity ( Donner et al. , 2009 ). In a relatively simplistic approach, general circulation models (GCMs) forced by the IPCC IS92a emission scenario have been used to estimate the frequency of coral bleaching events using future predictions of sea surface temperatures (SSTs) combined with thermal thresholds ( Hoegh-Guldberg, 1999 ). Bleaching severity at a broad scale is well correlated with the degree-heating week (DHW) stress metric ( Sheppard, 1999 ; Spencer et al. , 2000 ). The DHW metric integrates anonymously high temperatures during the most recent 12-week period by summing any temperature anomaly at least 1°C above the maximum monthly mean (MMM) ( Liu et al. , 2013 ). Several stressors are now recognised to influence coral bleaching ( Welle et al. , 2017 ). For instance, high irradiance increases the impacts of high temperatures on coral bleaching ( Gleason and Wellington, 1993 ). The Light Stress Damage algorithm was developed to combine satellite-derived SST data and satellite-derived solar insolation data into a single measure of stress ( Skirving et al. , 2017 ). Satellite algorithms do not consider bleaching factors that cannot be remotely sensed ( Cantin et al. , 2021 ), namely dissolved nutrients ( D’Angelo and Wiedenmann, 2014 ), ocean acidification, biological interactions and microbial communities. Modelling can overcome the limitations of satellite algorithms and better represent the variance in coral bleaching response under a range of dynamic environmental conditions. Process-based models of the coral–symbiont relationship were developed to increase our understanding of climate change impacts on coral bleaching severity. Perhaps the most ambitious application of a coral physiological model to date is the coral bleaching model (CBM). Using extensions from previous models, the CBM was developed for a mechanistic description of the coral–symbiont relationship ( Baird et al. , 2018 ). The CBM includes models for the coral polyp ( Gustafsson et al. , 2013 ), photosystem bleaching ( Gustafsson et al. , 2014 ), photoadaptation ( Baird et al. , 2013 ) and multiple nutrient limitations of microalgae ( Baird et al. , 2016 ). The CBM has been incorporated into the CSIRO Environmental Modelling Suite ( Baird et al. , 2020b ) and implemented in a ∼1-km resolution coupled hydrodynamic–biogeochemical model (a product of the eReefs Project; Steven et al. , 2019 ) that encompasses the entire length of the GBR ( Baird et al. , 2020b ). The CBM in the eReefs model has been calibrated against broadscale aerial bleaching surveys ( Baird et al. , 2018 ; Baird et al. , 2021 ) and has captured the distribution and intensity of bleaching during the summers of 2016 ( Baird et al. , 2018 ), 2017 and 2020 ( Cantin et al. , 2021 ). The CBM applied in realistic environmental conditions has the potential to provide more detailed bleaching predictions than those available from satellite-based coral bleaching parameters ( Steven et al. , 2019 ). The eReefs marine biogeochemical (BGC) model simulates the environmental conditions of the GBR and is used in its management. Previous applications include assessing the impacts of catchment run-off on reef health ( Baird et al. , 2017 ; Brodie et al. , 2017a ; Brodie et al. , 2017b ), evaluating crown-of-thorns starfish outbreaks ( Hock et al. , 2014 ), assessing coral bleaching in the 2016 bleaching event ( Baird et al. , 2018 ) and vulnerability to ocean acidification ( Mongin et al. , 2016 ). The eReefs marine BGC model has also been used to analyse the feasibility of environmental interventions for delaying coral bleaching onset and reducing resulting coral mortality ( Baird et al. , 2020a ; Harrison, 2024 ; Scofield et al. , 2024 ). Solar radiation management techniques are proposed for reducing downwelling irradiance and atmospheric options for cooling and shading reefs include fogging and marine cloud brightening ( Harrison et al. , 2019 ; Harrison, 2024 ). Preliminary modelling of cooling and shading interventions indicated an average reduction in incoming solar shortwave radiation of ~6.8% could have reduced bleaching stress by ~50% in the 2015–16 bleaching event and ~65% in the 2016–17 bleaching event, based on a small number of sample reefs modelled in high resolution ( Harrison et al. , 2019 ). As reef interventions transition from laboratory and field testing to deployment in the natural environment, numerical modelling will be required to extrapolate performance estimates, optimise deployment strategies and quantify potential risks ( Harrison, 2024 ). The CBM within the eReefs marine BGC model is a valuable tool for assessing management strategies on the GBR. To widen the number of applications and facilitate model assessment against laboratory experiments, we developed a single-polyp version of the CBM. This single-polyp version can be compared to experiments with varying temperatures, light levels and coral types to assess model skill and determine parameter values such as maximum symbiont growth rates representing different coral species’ temperature ranges and light tolerances. For the present study, the CBM was configured to simulate a moderate-duration heat (0–4.4 DHW) and light stress laboratory experiment, which is described in Ellis et al. (2024) . The model configuration was altered to improve the representation of coral species. The time-varying environmental inputs measured in the experiment (irradiance, temperature and nutrient concentrations) were used to force the model. Repeat measurements of experimental photochemical parameters of coral health (maximum quantum yield ( F v /F m ), the minimum saturating irradiance ( E k ), the maximum photosynthetic capacity ( r ETR MAX ) and the rise of the curve in the light-limited region ( \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n$\\mathrm{\\alpha}$\\end{document} )) were evaluated against model state variables. Specifically, we aimed to assess the skill of the process-based representation in the CBM for simulating experimental bleaching outcomes.",
"discussion": "Discussion Comparing experimental to model-simulated coral bleaching In the unshaded treatment, the model captured the observed coral bleaching under heat stress conditions. This suggests that the photophysiological processes represented by the model, including photoadaptation, xanthophyll cycle dynamics and reaction centre state transitions, were influential in representing the observed coral bleaching under these environmental conditions. Furthermore, the model-simulated onset of bleaching matched closely with an initial photochemical decline as observed in the experiment. This is significant as the model not only simulated the observed pattern of bleaching under heat stress conditions, in the unshaded treatment, but it also captured the timing and progression of the bleaching process, which further supports the model’s mechanistic processes. The model simulated that high light coupled with increased temperature leads to inhibited reaction centres and accumulated ROS. The model-simulated changes in ROS concentration aligned with experimental photochemical measurements. This provides a powerful validation of the temperature-mediated, light-driven mechanism of bleaching used by the model. The model’s ability to capture bleaching in the treatment of the greatest environmental stress and its relationship to underlying physiological processes observed ex situ emphasises the potential of this modelling tool for predicting reef futures. The model simulated reduced health but no symbiont cell expulsion for the shaded treatment at heat stress temperature. Model-simulated photochemical changes in the shaded treatment at heat stress temperature were insufficient to cause bleaching; ROS concentration gradually increased up to the threshold by the end of the experiment but never exceeded it. Symbiont cell expulsion was simulated by the model only in the unshaded treatment at heat stress temperature. In the experiment, shade alleviated experimental photochemical stress under heat stress; F v /F m did not decrease to zero and the decline in E k , r ETR MAX and alpha was slowed, as opposed to the unshaded treatment. Previous research has demonstrated that shading reduces coral bleaching risk ( Butcherine et al. , 2023 ), which supports using shade-based management interventions to reduce coral bleaching stress and coral mortality ( Harrison, 2018 ). However, even with the application of shade, a significant decline in coral health was observed in our experiment due to the accumulation of heat stress. The temperature treatments may have played a larger role in the experimental bleaching than could be simulated by the model due to unaccounted factors, for instance, pre-experimental stress, acclimatisation or symbiont shuffling. Evaluating model improvements The decision to remove the coefficient for ROS diffusion, increase the initial concentration of ROS within a cell and reduce the number of photons per ROS in this configuration of the model would have further increased the model-simulated ROS concentration. Other changes to initial conditions are not discussed as the model’s photochemistry was shown to adjust within 2 days. An increased ROS concentration increased the symbiont cell expulsion rate. Experimental evidence of ROS movement from the symbiont to the coral host would confirm the relevance of using a ROS diffusion term in the CBM. Further model validation would be required to match simulated changes in photochemistry to observed photochemical proxies. Revising a parameter that influences the sensitivity to light may determine the degree of bleaching simulated by the model. The build-up of ROS simulated by the model is both temperature-mediated and light-driven. The number of photons that lead to the generation of one ROS was reduced to represent the heat-sensitive reef-building coral of the experimental study— A. divaricata . If the number of photons per ROS was not reduced, the model would simulate less ROS concentration in the shaded treatment at heat stress temperature and a reduced symbiont cell expulsion rate in the unshaded treatment at heat stress temperature. Further reducing the number of photons per ROS would increase the bleaching stress simulated by the model in the shaded treatment at heat stress temperature. The stoichiometric nature of the parameter for the number of photons per ROS suggests it might be common across symbiont species. The improvements made to the model contributed to the fit between the model-simulated and observed bleaching. This improved match was due to the model’s more accurate representation of the mechanism through which temperature-mediated light-driven oxidative stress leads to ROS concentration build-up, and consequently symbiont cell expulsion. The model changes outlined above increased the bleaching stress and subsequent bleaching simulated by the model. An increased ROS concentration from the model changes meant that the onset of symbiont cell expulsion under heat stress conditions, in the unshaded treatment, closely corresponded to the observed photochemical decline in A. divaricata . Specifically, the model-simulated bleaching commenced 0.5 days after E k and alpha, 2.5 days after r ETR MAX and 5.5 days after F v /F m , as observed in the experiment. Without these model improvements, we would not expect such a strong degree of model fit to the observed bleaching. Model configuration limitations Nutrient oversupply had no impact on the model outputs. The model simulated a nutrient-replete system with high normalised internal reserves of nitrogen and phosphorous, independent of temperature or shade treatment. The nutrient-replete system simulated by the model and forced by the experimental environmental data may not fully represent the natural coral environment. Many coral reefs are in oligotrophic tropical waters with undetectable levels of DIN (<1 μmol l −1 ) and DIP (<0.1 μmol l −1 ) ( Tanaka et al. , 2007 ). The averaged experimental DIN (1.68 μmol l −1 ) was outside this range, and the averaged experimental DIP (0.19 μmol l −1 ) was also higher but was less than what is considered intermediate nutrient concentrations (DIP < 0.35 μmol l −1 ) found in upwelling regions or coastal areas impacted by riverine and groundwater discharge ( Tanaka et al. , 2007 ). Chronic nutrient exposure increases the prevalence of disease and severity of coral bleaching ( Vega Thurber et al. , 2014 ). An increased susceptibility to temperature- and light-induced bleaching has been linked with increased levels of DIN in combination with limited phosphate concentrations ( Wiedenmann et al. , 2013 ). Specifically, nutrient exposure may increase symbiont abundance ( Marubini and Davies, 1996 ), thus increasing coral bleaching susceptibility during heat stress ( Wooldridge, 2009 ; Cunning and Baker, 2013 ; Wiedenmann et al. , 2013 ). In the model, symbiont cells are expelled due to symbiont ROS levels. However, increased activities of CAT and SOD in response to increased concentrations of the ROS H 2 O 2 at elevated seawater temperature have been found in both coral tissue and zooxanthellae ( Higuchi et al. , 2008 ). This is most likely since H 2 O 2 is a diffusive ROS molecule that readily diffuses across biological membranes and so is not restricted to its point of synthesis ( Lesser, 2006 ; Baird et al. , 2009 ). The potential impact of host–ROS concentration is not currently included in the model. As the model could not incorporate nutrient oversupply into predictions, this may have caused a mismatch between the observed and model-simulated coral bleaching. Considering the above-mentioned impacts linked with increased nitrogen levels, we could expect the model to simulate increased bleaching stress if nutrient oversupply was introduced. With increased bleaching stress, an earlier onset of bleaching may have been simulated by the model, and perhaps increased rates of symbiont cell expulsion. Demonstrating the effects of nutrient oversupply involves representing complex interactions and processes in the coral reef environment. The current simplification of formulations used by the model allows a comprehensive set of processes to be represented, from nutrient and photochemical interactions to coral symbiosis ( Baird et al. , 2018 ). Further tweaking of the model configuration may be required to best represent dynamics at the lower nutrient levels typical of most coral reef environments; this is yet to be tested. In addition to elevated light and heat stress, corals bleach in response to any stressor that disrupts photochemical quenching, namely high levels of dissolved carbon dioxide, salinity extremes, environmental contaminants, low light and cold stress. Dissolved oxygen, pH and salinity are commonly monitored environmental variables in a coral bleaching study and were measured during the experiment to ensure their variation did not confound bleaching results. In the model, these variables do not drive growth rate or photosystem efficiency. Including these variables in growth equations and as input forcings, thus representing them as potential stressors, may provide a more accurate projection of coral bleaching. This would enable the representation of different bleaching events, for instance capturing the localised freshwater bleaching that occurred in 2008–09 and 2010–11 from high freshwater discharges ( Lough et al. , 2015 ). As acknowledged in Baird et al. (2018) , not all processes in the CBM are mechanistic. The inactivation of RuBisCO-mediated carbon fixation, the repair rate of inhibited reaction centres and the detoxification rate of ROS are temperature-dependent empirical formulations. The equation for ROS detoxification is an empirical formulation based on observation rather than mechanistic understanding. ROS detoxification is directly proportional to the maximum growth rate of the symbiont as a simplification—if healthier, faster growing cells have more resources for detoxification. A quantitative understanding of the underlying biochemical reactions is necessary to formulate more mechanistic process descriptions in the CBM. The model simplifies the carbon fixation process and does not fully capture how excess energy is managed by the symbiont when carbon reserves are full. The model assumes that when carbon reserves are full or the RuBisCO enzyme is inactive, photons are not used in carbon fixation. Instead, they lead to the reduction of an oxidised reaction centre. This simplification prioritises simulating reaction centre dynamics and ROS production as drivers of coral bleaching. Whilst the model does not directly simulate the release of carbon, if the host cannot use translocated photosynthate from the symbiont, the model assumes it is released as mucus. The model does not explicitly represent the storage of fixed carbon as starch, instead, it uses generic ‘reserves of carbon’. Future iterations of the model should aim to incorporate more detailed mechanisms of carbon storage and release in symbiotic algae. Future model advancement Future CBM evaluation should compare model-simulated symbiont cell expulsion to observed symbiont cell expulsion and model-simulated photochemistry to observed photochemistry. In this paper, we compared photochemical decline to symbiont cell expulsion rate. The build-up of ROS in Symbiodiniaceae is a physiological response to environmental stress. Comparing the model-simulated physiological response to the observed physiological response would be the most suitable way to validate the mechanism of ROS-induced bleaching used by the model. Comparing the model-simulated photochemical response to the observed photochemical response would validate the photosystem represented by the model. This represents an avenue for future model evaluation. Further information is required to resolve the role of ROS within the coral holobiont and to determine the sequence of events that lead to coral bleaching. This will determine whether a model based on ROS-induced bleaching is the best way to represent the coral bleaching process. Previous studies have detected decreased photosynthetic efficiency and increased oxidative stress in thermally stressed corals ( Lesser, 1997 ; Downs et al. , 2002 ; Saragosti et al. , 2010 ). Increased concentrations of ROS during acute thermal stress are a product of photochemical stress rather than a proximate cause of stress. Thus, coral bleaching may be driven by ROS-independent mechanisms ( Morris et al. , 2019 ; Rädecker et al. , 2021 ; Rädecker et al. , 2023 ). Further coral bleaching studies are required to isolate the mechanisms of bleaching. ROS levels associated with coral bleaching could be inferred through other proxies. Due to the difficulty with measuring ROS concentration (it is often measured as a fluorescent signal rather than a mass per unit volume) and the limitations presented with current methodologies ( Murphy et al. , 2022 ), there is no precise value for ROS toxicity in the literature ( Scofield et al. , 2024 ). An indirect comparison to model-simulated ROS levels could be made with antioxidant enzyme analysis. Components of the antioxidant system, namely superoxide dismutase, catalase and glutathione peroxidase enzymes, are responsible for converting intracellular accumulations of ROS into water before levels supersede a concentration threshold, thus avoiding significant oxidative damage ( Baird et al. , 2009 ). Elevated antioxidant enzyme activity indicates increased levels of ROS ( Lesser et al. , 1990 ). Future evaluation of the CBM could consider using antioxidant enzyme analysis to infer ROS-induced levels of stress in coral species."
} | 6,535 |
30038664 | PMC6052697 | pmc | 5,512 | {
"abstract": "Background The production of ethanol through the biochemical conversion of syngas, a mixture of H 2 , CO and CO 2 , has been typically studied using pure cultures. However, mixed microbial consortia may offer a series of benefits such as higher resilience and adaptive capacity, and non-sterile operation, all of which contribute to reducing the utility consumption when compared to pure culture-based processes. This work focuses on the study of strategies for the enrichment of mixed microbial consortia with high ethanologenic potential, investigating the effect of the operational conditions (pH and yeast extract addition) on both the ethanol yield and evolution of the microbial community along the enrichment process. The pH was selected as the main driver of the enrichment as it was expected to be a crucial parameter for the selection of carboxydotrophic bacteria with high ethanologenic potential. Additionally, a thermodynamic analysis of the network of biochemical reactions carried out by syngas-converting microbial consortia was performed and the potential of using thermodynamics as a basis for the selection of operational parameters favoring a specific microbial activity was evaluated. Results All enriched consortia were dominated by the genus Clostridium with variable microbial diversity and species composition as a function of the enrichment conditions. The ethanologenic potential of the enriched consortia was observed to increase as the initial pH was lowered, achieving an ethanol yield of 59.2 ± 0.2% of the theoretical maximum in the enrichment at pH 5. On the other hand, yeast extract addition did not affect the ethanol yield, but triggered the production of medium-chain fatty acids and alcohols. The thermodynamic analysis of the occurring biochemical reactions allowed a qualitative prediction of the activity of microbial consortia, thus enabling a more rational design of the enrichment strategies targeting specific activities. Using this approach, an improvement of 22.5% over the maximum ethanol yield previously obtained was achieved, reaching an ethanol yield of 72.4 ± 2.1% of the theoretical maximum by increasing the initial acetate concentration in the fermentation broth. Conclusions This study demonstrated high product selectivity towards ethanol using mixed microbial consortia. The thermodynamic analysis carried out proved to be a valuable tool for interpreting the metabolic network of microbial consortia-driven processes and designing microbial-enrichment strategies targeting specific biotransformations. Electronic supplementary material The online version of this article (10.1186/s13068-018-1189-6) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions The enrichment strategies studied resulted in the successful selection of acetogenic bacteria from both untreated and heat-shock-treated anaerobic sludge, obtaining a number of enriched mixed microbial consortia with variable ethanologenic potential and microbial diversity as a function of the enrichment conditions applied. The composition of the microbial community was shown to shift rapidly along the enrichments, reaching a stable microbial composition dominated by the genus Clostridium in all cases, with a single dominant species in most of the enrichments. Both pH and nutrient supplements (YE) were found to be determinant operational parameters affecting the specific composition of the consortia and their microbial diversity. The ethanologenic potential of the enriched consortia was strongly dependent on the pH conditions applied, where an ethanol yield of 59.15 ± 0.18% of the stoichiometric maximum was achieved in pH-based enrichments at the lowest pH tested (pH 5). On the other hand, the addition of YE triggered the production of C4 compounds, opening the way for the production of MCFAs and higher alcohols. The thermodynamic approach used for the analysis of the metabolic network of reactions carried out by syngas-converting microbial consortia proved to be highly useful for assisting the design and interpretation of enrichment strategies. Based on the qualitative predictions of the thermodynamic analysis, it was possible to improve the product selectivity and enhance the maximum ethanol yield obtained in pH-based enrichments by 22.5% (72.44 ± 2.11% of the stoichiometric maximum) through an increase of the initial acetate concentration (enrichment HT5YE-Ac). Thus, this work demonstrated that a highly selective microbial activity towards the production of ethanol is possible using open-mixed microbial consortia. However, given the experimental observations made here, the ethanol yield obtained in enrichment HT5YE-Ac in batch mode cannot be extrapolated to processes in continuous mode as the long-term exposure of the enriched consortium to elevated ethanol and acetate concentrations would likely promote a high chain-elongating activity, lowering the product selectivity towards ethanol. Further work in this area is still needed to develop operational strategies able to control the chain-elongation reaction in syngas-converting microbial consortia.",
"discussion": "Results and discussion Enrichment of syngas-converting microbial consortia based on pH Ethanologenic potential of enriched consortia A number of enrichment strategies using the pH as the main selective driver were designed to study the evolution of the ethanologenic activity during the enrichment of microbial consortia at different initial conditions. Different initial pH conditions were tested using a heat-shock-treated inoculum (pH 6, 5.5 and 5) and a non-treated inoculum (pH 5). All enrichment strategies successfully suppressed the methanogenic activity of the anaerobic sludge as methane was not detected in any transfer of the enrichments. This was expected in the enrichments using a heat-shock-treated inoculum, since spore-forming bacteria should be predominant in the anaerobic sludge as a result of the heat treatment [ 45 ]. In turn, small amounts of methane were expected when using the non-treated inoculum due to the abundance of methanogenic archaea in the anaerobic sludge, as observed by Steinbusch et al. [ 46 ]. However, in this study, the low initial pH (pH 5) of experiments using the non-treated inoculum inhibited both methanogenic and acetogenic growth when YE was not added to the growth medium, whereas experiments with YE addition presented exclusively acetogenic growth. This indicates that the methanogenic activity of the sludge was inhibited by the combination of low pH and toxicity of CO. Thus, open-mixed cultures could be used in syngas fermentation processes with no need of heat treatment or methanogenic inhibitors, just by operating at harsh conditions for methanogenic archaea. All enrichment conditions presented a very low ethanol production in the first transfer, with the product spectrum being initially dominated by acetate (Fig. 2 ). However, as the enrichments progressed, the distribution of products rapidly shifted following different trends depending on the operating conditions and seemed to be relatively stable after two to three transfers in most of the enrichments. The enrichment with initial pH 6 (HT6) resulted in the narrowest product spectrum with acetate as the main end product, and small amounts of ethanol and butyrate produced irregularly during the enrichment (Fig. 2 a). As expected, decreasing the initial pH to 5.5 (HT5.5) improved the production of ethanol, which increased gradually along the enrichment reaching a maximum ethanol yield of 0.025 mol/e-mol (30.4% of the stoichiometric maximum) and an average of duplicates of 0.020 ± 0.005 mol/e-mol at transfer T5 (Fig. 2 b). Nevertheless, the lower initial pH of this enrichment negatively affected the growth of the microbial consortium as the enrichment advanced until transfer T5, at which the culture could not be reactivated anymore. The enrichment with initial pH 5 (HT5) did not present any growth (data not shown); indicating that the microbial activity of the inoculum used was inhibited by the low initial pH of this enrichment. Consequently, enrichments with initial pH 5.5 and 5 were restarted and supplemented with YE to favor a better microbial growth. The addition of YE to the enrichment with initial pH 5.5 (HT5.5YE) indeed allowed a much better microbial growth as the lag phase of the culture was significantly reduced (Additional file 1 : Figures S1–S4), and did not have any effect on the final ethanol yield when compared to enrichment HT5.5 (Fig. 2 b, c). Further decreasing the initial pH to 5 significantly enhanced the solventogenic activity in enrichment HT5YE, with ethanol becoming the main end product and obtaining a maximum ethanol yield of 0.050 mol/e-mol (59.5% of the stoichiometric maximum) and an average of 0.045 ± 0.005 mol/e-mol at transfer T7 (Fig. 2 d). Fig. 2 Product yields (mol/e-mol) obtained in each transfer for all enrichment conditions and final pH at the moment of the transfer. The columns show the values for the fermentation transferred and the error bars indicate the corresponding values of the duplicate experiment. Additional information on substrate consumption and apparent biomass yields can be found in Additional file 1 : Figure S5. a Enrichment HT6 at an initial pH of 6; b enrichment HT5.5 at an initial pH of 5.5; c enrichment HT5.5YE at an initial pH of 5.5 with YE (0.5 g/l); d enrichment HT5YE at an initial pH of 5 with YE (0.5 g/l); e enrichment NT5YE at an initial pH of 5 with YE (0.5 g/l) \n The enrichment with initial pH 5 using the non-treated inoculum (NT5YE) presented a similar trend with enrichment HT5YE, as the solventogenic activity was rapidly boosted along the successive transfers (Fig. 2 e). However, the maximum ethanol yield obtained in enrichment NT5YE at transfer T6, namely, 0.033 mol/e-mol and 39.7% of the stoichiometric maximum (average of 0.032 ± 0.002 mol/e-mol), was not as high as that of enrichment HT5YE. An explanation for this difference in the product yields could be based on the heat treatment of the inoculum, as the enrichment HT5YE presented a more abrupt response upon exposure to the enrichment conditions (from T0 to T1) compared to enrichment NT5YE, where changes in the product profile took place gradually (from T0 to T2). Thus, it is possible that the higher degree of sporulation derived from the heat treatment of the initial inoculum favored a faster microbial selection process ultimately resulting in a different ethanologenic activity in these two enriched consortia. Besides the quantitative difference in the final ethanol yield, the high similarity in the behavioral traits of these microbial consortia is also supported by their common response upon reactivation of the cultures. As shown in Fig. 2 d, e, a noticeable decrease of solventogenic activity was observed in both enrichments after stopping them for 2 months at transfer T4 (HT5YE) and T2 (NT5YE). Additionally, a very similar or even higher solventogenic activity was recovered after two transfers upon resuming the enrichments in both microbial consortia. The apparent biomass yield was observed to be affected by both the initial pH of the enrichments and the addition of YE. Generally, the average biomass yield along the enrichments varied between 1.7 and 2.8 mg VSS/e-mol, with enrichment HT5.5 presenting the lowest biomass yield and enrichments HT5YE and NT5YE exhibiting the highest biomass yields (Additional file 1 : Figure S5). No statistically significant differences were found between the average biomass yield of the enrichments at different pH, with P values above 0.05 in all cases when comparing HT6 to the rest of the enrichments (Additional file 1 : Figure S5 and Table S1). However, the fact that the enrichment HT5.5 could not be reactivated at transfer T6 and that enrichment HT5 did not present any growth indicates a clear negative effect of the pH on microbial growth. In turn, the addition of YE was observed to improve the biomass yield of the enrichment cultures as statistically significant differences with P values below 0.05 were found between enrichment HT5.5 and all enrichments with YE addition, namely, HT5.5YE, HT5YE and NT5YE (Additional file 1 : Table S1). A low pH is commonly applied in syngas fermentation studies [ 47 , 48 ] based on the hypothesis that the higher diffusion of VFAs through the cell membrane at acidic pH triggers solventogenesis as a means of preventing a further intracellular pH drop [ 49 , 50 ]. The observations made in this study are in agreement with this hypothesis as (i) the highest ethanol yields were obtained in the enrichments at the lowest initial pH tested, and (ii) the final pH of the fermentations oscillated around 4.3–4.6 in most enrichment conditions and seemed not to be related to the initial pH conditions (Fig. 2 c, d). Thus, it is likely that intracellular pH homeostasis may have driven a higher ethanol production by the enriched consortia. The addition of YE appeared to have no effect on the final yield of ethanol in enrichments at an initial pH of 5.5 (Fig. 2 b, c), but triggered the production of butyrate, butanol and small amounts of caproate leading to a broader product spectrum in all YE-supplemented enrichments (Fig. 2 c–e). The production of butyrate and butanol was observed to take place in a two-step reaction, which indicates that they were produced through chain elongation and reduction of VFAs (Additional file 1 : Figures S6, S7). The potential of microbial consortia for producing medium-chain fatty acids (MCFAs) through chain elongation has been shown in a number of studies [ 18 , 51 ]. However, when it comes to ethanol production, the chain elongation process is often regarded as a major drawback as it reduces the selectivity of the mixed culture towards ethanol due to the conversion of ethanol and VFAs into MCFAs, as found in El-gammal et al. [ 52 ]. In this study, a significant chain-elongating activity appeared to be prevented by the low pH of the fermentations (generally ranging between 4.3 and 4.6 at the end of the experiments), since both acetate and ethanol remained as the major end products at all enrichment conditions. Ganigué et al. [ 21 ] reached similar conclusions in a study targeting the production of higher alcohols, in which low pH was found to affect negatively the chain elongation process. Nevertheless, the reduced chain-elongating activity found in the present study allowed achieving high ethanol yield in enrichments at pH 5. A maximum ethanol yield of 0.050 mol/e-mol (59.5% of e-mol recovery) and an ethanol-to-acetate ratio of 1.58 g/g was achieved in enrichment HT5YE. The maximum ethanol-to-acetate ratio obtained was significantly higher than those often reported in other batch experiments using pure cultures such as C. ragsdalei (1.30 g/g) [ 10 ], C. autoethanogenum (0.39 g/g) [ 8 ] and C. ljungdahlii (0.70 g/g) [ 53 ], and in other mixed-culture studies with ratios below 0.4 g/g [ 20 , 52 ]. Yet, higher ethanol-to-acetate ratios were reported by Singla et al. (2014) using the enriched culture TERI-SA1 (2.46 g/g). The analysis of the production efficiency on fermentations carried out by the enriched consortia showed that both the pH and YE had a significant effect on the performance of the cultures. Table 3 shows the production efficiencies, calculated on a Cmol and e-mol recovery basis, for all enriched consortia. The calculated Cmol and e-mol recoveries were in relatively good agreement, with a maximum deviation of 10% corresponding to the enriched consortium HT6. Generally, the efficiency of the fermentations remained at a high levels for all enriched consortia and was consistent with previously reported e-mol recoveries [ 54 ]. Nonetheless, differences can be observed in Table 3 , where the production efficiency of the enriched consortium HT5.5 resulted to be much lower than that of the consortia HT6 and HT5.5YE. A statistically significant difference was found when comparing the Cmol recovery of the enriched cultures HT5.5 and HT5.5YE ( P value of 0.0003), indicating that the addition of YE had a positive effect on the production efficiency. On the other hand, the decrease in pH had an adverse effect on the production efficiency since a statistically significant difference ( P value of 0.017 and 0.012 for Cmol and e-mol recovery, respectively) was found between the product recovery of the consortia enriched at pH 5.5 (HT5.5) and at pH 6 (HT6). However, the negative effects of reducing the initial pH were not significant as long as YE was added to the medium (Additional file 1 : Table S2). These effects of pH and YE on the production efficiency were in fact anticipated as increasing both pH (in the range tested) and YE has been previously reported to favor biomass growth [ 8 ], which in turn reduces the maintenance requirements for cell metabolism and allows a higher production efficiency. Interestingly, the product distribution had no effect on the production efficiency of the fermentations, indicating that the latter was strictly dependent on the growth conditions. Table 3 Efficiency calculated in terms of e-mol and Cmol recovery and product yields for all enriched microbial consortia HT6 HT5.5 a HT5.5YE HT5YE NT5YE Recovery (%) b e-mol 92.92 ± 0.54 85.83 ± 2.46 89.84 ± 1.80 88.57 ± 1.77 95.01 ± 3.29 Cmol 83.16 ± 0.70 77.33 ± 2.31 93.18 ± 1.69 80.29 ± 0.83 91.60 ± 6.41 Product yield (% e-mol/e-mol) Acetate 83.32 ± 0.81 61.15 ± 7.41 41.38 ± 1.75 29.29 ± 0.63 27.68 ± 1.67 Propionate 0.00 ± 0.00 0.11 ± 0.20 0.01 ± 0.08 2.11 ± 0.38 0.26 ± 0.04 Iso-butyrate 1.55 ± 0.09 0.00 ± 0.00 1.82 ± 0.78 0.00 ± 0.00 1.17 ± 0.31 Butyrate 0.00 ± 0.00 0.00 ± 0.00 11.59 ± 4.82 2.05 ± 0.74 16.51 ± 1.07 Ethanol 8.16 ± 0.49 25.20 ± 5.32 29.40 ± 5.36 59.15 ± 0.18 34.81 ± 2.27 Butanol 0.00 ± 0.00 0.00 ± 0.00 15.37 ± 1.55 3.50 ± 0.64 21.82 ± 1.45 Caproate 0.00 ± 0.00 0.00 ± 0.00 1.39 ± 0.03 3.33 ± 0.20 1.09 ± 0.09 Biomass yield (g VSS/e-mol) 2.10 ± 0.11 1.83 ± 0.42 3.21 ± 0.51 3.13 ± 0.20 2.85 ± 1.06 a The efficiency and product yields of HT5.5 were calculated using the results for transfers T4 and T5 of the enrichment b Additional information on the production of control experiments is provided in Additional file 1 : Table S3 \n Microbial characterization of enrichment cultures A total of 49,736,621 sequences were obtained from all investigated samples after quality checking and data filtering, with an average of 956,473 reads per sample (range 309.337–8,985,816 reads per sample). Replication, error correction, denoising with unoise algorithm and filtering of OTU table resulted in 6183 OTUs with all but one OTUs belonging to bacteria domain. Considering all sequences retrieved in the present study, Firmicutes accounted for the largest fraction (78% of the total), mainly represented by the classes Clostridia , Tissierella and Bacilli . The analysis of the microbial composition of the enrichment samples at genus level revealed significant differences between the initial inocula and the different enrichment cultures. The untreated (NT) and heat-shock-treated (HT) inocula were initially dominated by the genera Sedimentibacter (32.8% and 22.5% of reads mapping to corresponding OTUs for NT and HT, respectively) and Butyricicoccus (34.9 and 10.6% for NT and HT, respectively), while other genera like Clostridium represented only a minor fraction (below 1% in both cases) (Additional file 2 : Table S1). However, upon exposure to the different operating conditions, the composition of all enrichment cultures rapidly shifted with a clear and stable dominance of the genus Clostridium from transfer T3. As shown in Fig. 3 , the degree of dominance of the genus Clostridium was variable across the different enrichment conditions. Samples from enrichments HT6 and HT5.5YE presented the highest diversity in terms of genera, with the genus Clostridium representing an average of 41.5 ± 3.3% and 37.1 ± 6.3% of the total reads mapped, respectively. In turn, samples from enrichments HT5.5, HT5YE and NT5YE exhibited a lower diversity at genus level with a much larger representation of the reads mapping to OTUs corresponding to Clostridium with an average of 94.7 ± 4.7%, 73.4 ± 10.0% and 90.2 ± 3.3%, respectively. These results show that Clostridium was among the most resilient genera found in the microbial consortia since its dominance increased with harsher enrichment conditions, i.e., decreasing pH or absence of YE. Fig. 3 Relative taxonomic abundance of the analyzed microbial consortia in pH-based enrichments at genus level. The label of the samples is encoded according to the enrichment name, transfer number and growth phase at the moment of the sampling. ME and SP stand for mid-exponential and stationary growth phase, respectively. The label NA corresponds to the sum of all genera with a relative abundance below 1% \n Despite the clear dominance of OTUs belonging to the genus Clostridium in all enrichments, the abundance of individual OTUs found in the enrichment samples varied depending on the enrichment conditions (Additional file 2 : Table S3). The mean relative frequencies between the OTU abundances were compared across all samples with and without addition of YE. It was found that representative sequences of abundant OTUs identified solely in enrichments without addition of YE (HT6 and HT5.5), aligned with high identity (98.4–100%) to 16S rRNA genes from Clostridium autoethanogenum and Clostridium ljungdahlii. Abundances of these OTUs (2;1302;1233;1249;1983) were 81.5% and 41.4% in samples HT5.5T5SP and HT6T6SP, respectively (Additional file 2 : Table S3). In turn, reads mapping to these OTUs were negligible in YE-supplemented enrichments. Moreover, identified OTUs exclusively present in YE-supplemented enrichments and their representative sequences exhibited the best alignment (97–100% identity) with 16S rRNA sequences of Clostridium drakei and C lostridium carboxidivorans. Abundance of these OTUs (1;337;434;359) was up to 87.5% in sample NT5YET6SP (Additional file 2 : Table S3). These differences indicate that the addition of YE, besides promoting better growth conditions for the entire microbial consortium, also played a determining role as a selection factor in addition to the pH conditions and the substrate composition. The range of metabolites found in each of the enrichment series was in agreement with the product portfolio of the putative dominant species identified in the enrichment samples. As mentioned above, acetate and ethanol were the main metabolites in enrichments HT6 and HT5.5 where the putative dominant species were C. autoethanogenum and C. ljungdahlii , while longer carbon chain products such as butyrate and butanol were also found in YE-supplemented enrichments (HT5.5YE, HT5YE and NT5YE) with C. drakei and C. carboxidivorans as putative dominant species. Both C. autoethanogenum and C. ljungdahlii have been reported to produce only acetate and ethanol when fermenting syngas in batch cultures [ 55 , 56 ]. In turn, C. drakei and C. carboxidivorans present a broader product spectrum including butyrate, butanol, and even caproate and hexanol in the case of C. carboxidivorans [ 57 , 58 ], which are produced through re-assimilation, chain elongation and reduction of the primary metabolites [ 59 ]. Additionally, the optimum growth conditions for all these species vary between a pH of 5.5 and 6.2 and temperatures around 37 °C, which explains the dominance of these species during the enrichments. Therefore, most likely the dominant species identified were the major contributors to the formation of products observed during the enrichments. The ethanol yield seemed to be independent of the microbial composition of the enrichment cultures at genus level. Enrichments HT6 and HT5.5YE resulted in a similar microbial composition (Fig. 3 ) and presented a maximum ethanol yield along the enrichment of 0.015 and 0.028 mol/e-mol, respectively (Fig. 2 ). Similarly, enrichments HT5.5, HT5YE and NT5YE also presented similar microbial composition with a clear dominance of the genus Clostridium (Fig. 3 ) and resulted in a maximum ethanol yield of 0.025 mol/e-mol, 0.050 mol/e-mol and 0.034 mol/e-mol, respectively (Fig. 2 ). On the contrary, enrichments at similar operating conditions and different microbial composition (HT5.5 and HT5.5YE) resulted in similar maximum ethanol yields. Thus, despite the clear effect of the pH on the microbial composition of the enriched consortia, it can be concluded that the shift towards ethanol observed in the enrichment experiments was probably the result of the metabolic response to the different initial pH conditions and not so dependent on the microbial composition of the enrichment cultures. A direct comparison with the literature is not possible since the only quantitative analysis of the composition of a syngas-converting microbial consortium using a 16S rRNA amplicon-based sequencing method was performed under higher pH conditions (pH 7.5), and thus, resulted in significantly different microbial composition [ 54 ]. However, the species identified in other studies carried out at a comparable pH range (pH 6.2–6.0) which were entirely consistent with the results found here [ 21 , 24 ]. Ganigué et al. (2016) studied the composition of a microbial consortium during the conversion of syngas into higher alcohols using PCR-DGGE analysis and identified both of the putative dominant species reported here ( C. autoethanogenum / C. ljungdahlii and C. drakei / C. carboxidivorans ). In their study, C. autoethanogenum/C. ljungdahlii were found to be the main species carrying out the carbon fixation. In turn, Singla et al. [ 60 ] found that C. drakei and C. scatalogenes were either the main or possibly the only members of the enriched microbial consortium TERI-SA1. Interestingly, YE was not added in the medium used by Ganigué et al. [ 21 ] during the enrichment, while Singla et al. [ 60 ] added 1 g/l of YE to the medium. Taking this into consideration, the findings reported in the literature and the results reported here follow the same trend, with the putative dominant species of the enrichment cultures being C. autoethanogenum / C. ljungdahlii when YE was absent in the growth medium and C. drakei / C. carboxidivorans when YE was added to the medium. Thermodynamic analysis of the metabolic network of the enriched consortia The enriched consortia developed through pH-based enrichments were observed to produce ethanol with relatively high selectivity. However, the production of ethanol took place during the exponential phase of the fermentations, and thus, it was not possible to distinguish between direct production of ethanol and reduction of acetic acid to ethanol. Therefore, a thermodynamic analysis of the metabolic network of net biochemical reactions taking place during the activity of the enriched consortia was performed to identify possible bioenergetic drivers of the metabolic shift observed under different enrichment conditions. Based on experimental observations, the reactions considered for evaluating the ∆ r G ′ 310 K and the thermodynamic potential factor ( F T ) under changing process conditions were the production of ethanol and acetic acid from H 2 /CO 2 and CO, the production of butyric acid through chain elongation, and the reduction of both acetic and butyric acid into their corresponding alcohols using either H 2 or CO as electron donor. Analyzing the ∆ r G ′ 310 K of the metabolic network of the enriched microbial consortia revealed that several reactions could be affected upon changing the initial pH conditions. As shown in Fig. 4 a, the production of acetate would be favored over ethanol when considering the direct conversion of either H 2 /CO 2 or CO, as the ∆ r G ′ 310 K of acetate-producing reactions are always below that of ethanol regardless the pH conditions. However, acetate-producing reactions from both substrates become less exergonic as the pH decreases, while the analogous ethanol-producing reactions remain unaffected by pH changes. The chain elongation to butyrate follows a similar trend with acetate production, becoming thermodynamically less favorable upon decreasing the pH. In turn, the reduction of acetic and butyric acid using either H 2 or CO as electron donor is significantly boosted by the pH decrease until the ∆ r G ′ 310 K stabilizes at around pH 3.5–4. Overall, besides the fact that acid-producing reactions are negatively affected by the lower pH, it seems that the only reactions clearly favored upon decreasing the initial pH conditions are the reduction of VFAs into their corresponding alcohols. However, the analysis of the thermodynamic potential factor ( F T ) shows that not all reactions are equally affected by the changes in ∆ r G ′ 310 K liberated. The F T of both acetate- and ethanol-producing reactions from H 2 /CO 2 and CO approach 1 at all pH conditions, indicating that these reactions would provide enough thermodynamic driving force to proceed forward regardless of the pH conditions considered and would not be significantly affected by the changes in ∆ r G ′ 310 K (Fig. 4 ). Therefore, rather than being thermodynamically controlled, the rates of direct production of either acetate or ethanol would be ultimately controlled by the specific enzyme kinetics of each metabolic pathway, which in turn would be dependent on the concentration of intermediate metabolites and reduced cofactors during the fermentation. On the other hand, the evaluation of the F T for the reduction of VFAs into their corresponding alcohols, using either H 2 or CO, and the chain elongation reaction resulted in values between 0 and 1 depending on the pH conditions considered (Fig. 4 b). This implies that the energy generated through these reactions is close to their energy conservation requirements, and as a result, the thermodynamic drive for these reactions to proceed forward is limited and pH-dependent. As opposed to direct acetate- and ethanol-producing reactions, the feasibility and the rate of VFA-reducing and chain elongation reactions are very sensitive to the changes in ∆ r G ′ 310 K obtained at different pH conditions (Fig. 4 a). Fig. 4 a Calculated ∆ r G ′ 310 K for the metabolic network of microbial consortia as a function of pH, normalized for e-mol transferred per reaction. Process conditions considered were: temperature of 310.15 K, ionic strength of 0.08 M, P H2 of 1.05 atm, P CO2 of 0.6 atm, P CO of 0.45 atm and concentration of metabolites of 0.001 M. b Thermodynamic potential factor calculated for all reactions as a function of pH. Solid lines represent F T calculated using a ∆ G p of 57.5 kJ/mol of ATP. Dashed lines represent the upper and lower boundary of F T when using a ∆ G p of 45 and 70 kJ/mol of ATP, respectively. The upper and lower boundaries are shown only for acetate-reducing reactions and the chain-elongation reaction According to the thermodynamic analysis, the direct conversion of H 2 /CO 2 and CO into either acetate or ethanol is not expected to be thermodynamically controlled until these substrates become severely depleted. However, the higher thermodynamic driving force (lower ∆ r G ′ 310 K ) and ATP yield per mol of substrate for acetate-producing reactions suggest that these would prevail over direct ethanol-producing reactions under kinetic control. Besides, calculations carried out by Bertsch and Müller [ 40 ] for the model organism Acetobacterium woodii indicate that the production of ethanol from H 2 /CO 2 might not be possible, as this reaction would require a net input of 0.1 mol of ATP per mol of ethanol. As opposed to direct conversion route from H 2 /CO 2 and CO to liquid products, VFA-reducing reactions are subject to thermodynamic control under the operating conditions considered and are clearly favored upon decreasing the pH. The F T values for all VFA-reducing reactions show that changes in ∆ r G ′ 310 K at the pH range studied have a strong effect on the rates of these reactions, which could explain the higher ethanol yield obtained in the enrichment experiments at an initial pH of 5. As illustrated in Fig. 4 b, a high pH in the fermentation broth renders the reduction of acetate with H 2 unfeasible (negative F T values). However, the boundaries of feasibility for this reaction cannot be accurately delimited due to the high sensitivity of F T to the values of ATP yield and Gibbs free energy of phosphorylation (∆ G p ) used in the calculations. Considering an ATP yield of 0.33 mol per reaction and a ∆ G p of 45 kJ/mol of ATP, the reduction of acetate would be feasible below a pH of 5.6, whereas using a ∆ G p of 70 kJ/mol of ATP would render this reaction unfeasible at any pH resulting in a maximum F T of − 0.23 at pH 3. Thus, detailed conclusions on whether this reaction is possible as a function of pH cannot be drawn, although it is obvious that this reaction is more likely to occur at the lower range of pH studied. On the other hand, using CO as electron donor for the reduction of acetate provides a much lower ∆ r G ′ 310 K , reducing the uncertainties on the activity of this reaction. In this case, the use of CO as electron donor is possible at all conditions regardless of the ∆ G p considered (Fig. 4 b). Furthermore, decreasing the pH from 6 to 5 causes the F T of this reaction to increase from 0.68 to 0.79 (Fig. 4 b), indicating that the acetate-reducing activity is significantly boosted as the pH decreases. Thus, it can be concluded that acetate-reducing reactions played an important role on the solventogenic activity observed in the enrichment experiments. Additionally, based on the F T for these reactions, the acetate-reducing activity using CO rather than H 2 as electron donor was probably more significant during the enrichments. This is in line with the observations made by Hu et al. [ 61 ] while studying the thermodynamics of the oxidation of CO and H 2 , where it was concluded that the use of CO as a source of electrons is thermodynamically more favorable than H 2 at all conditions. In “ Ethanologenic potential of enriched consortia ”, it was hypothesized that the chain elongation reaction was inhibited by the decrease of pH during the fermentation, as both acetate and ethanol remained as the main products of the fermentation and were only partially converted into butyrate (Additional file 1 : Figures S6, S7). However, the results of the F T for this reaction at different pH conditions show that the chain elongating activity is negatively affected by the decrease of pH when considering a ∆ G p of 70 kJ/mol, with F T values corresponding to 0.98, 0.86 and 0.68 at pH 6, 5 and 4, respectively (Fig. 4 b). Therefore, the inhibition due to pH drop observed experimentally could be grounded on a limitation in the thermodynamic driving force for this reaction to proceed forward. The thermodynamic analysis carried out here suggests that a significant amount of ethanol was produced via a two-step reaction, where direct production of acetic acid was initially favored followed by its reduction into ethanol in a second step. This is consistent with the distinction between acidogenic and solventogenic growth phases commonly applied in syngas fermentation processes [ 48 , 62 ]. Furthermore, the limited thermodynamic drive for chain-elongating activity found when decreasing the pH could explain the high selectivity towards ethanol observed in enrichments at pH 5. Thus, the methodological approach used here proved to be useful for a qualitative interpretation of how the metabolic network of mixed microbial consortia responds when changing operational conditions. Of course, microbial growth inhibition phenomena due to high VFAs/solvents concentration are not taken into account in this method and need to be considered from a microbiological perspective; however, the enrichment experiments took place at low substrate and product concentration and were not expected to present such inhibition phenomena. This method presented low accuracy when attempting to draw definite boundaries on the feasibility of the acetate reduction with H 2 due to the broad range of ∆ G p used in the calculations. Other limitations identified were the fact that the energy conservation requirements, determined by the ATP yield and the ∆ G p , were assumed to be constant regardless of the reaction and operating conditions considered. The stoichiometry of ATP synthesis was also assumed to have a fixed ratio of 3 ions translocated per mol of ATP. Nevertheless, both the ∆ G p and the stoichiometry of ATP synthesis have been shown to be subject to variation depending on several factors such as intracellular ATP/ADP ratio, electrochemical membrane potential, electron donors and acceptors considered, or even the species carrying out the reaction [ 44 ]. Despite the limitations outlined above, the thermodynamic analysis allowed for interpretation of the effects of operating conditions on the network of biochemical reactions prevailing in mixed microbial consortia. Thus, this method could be used for the selection of operational conditions with the aim of boosting specific reactions. To test the validity of this method for predicting changes in the microbial activity of enriched consortia and improving further the ethanol yield obtained previously, an additional experiment series was performed. Enrichment strategies based on thermodynamics of the metabolic network Thermodynamic predictions of the microbial activity From a thermodynamic perspective, the metabolic network of microbial consortia can be affected by several operating parameters such as the partial pressure of gases, the concentration of products or the pH. Several of these parameters could potentially enhance the production of ethanol due to their distinct effect on different reactions such as the pH already discussed, the partial pressure of CO 2 given the distinct stoichiometric CO 2 formation in acetate- and ethanol-producing reactions, the partial pressure of H 2 and CO affecting acetate-reducing reactions, and the initial concentration of acetate and ethanol affecting the whole metabolic network. In this case, given the effect of the pH on the acetate-reducing activity discussed in “ Thermodynamic analysis of the metabolic network of the enriched consortia ”, it was decided to study the effect of the initial acetate concentration in the medium to boost these reactions even further. However, this can be regarded as a proof-of-concept since this method could be used to evaluate the effect of the abovementioned parameters on any reactions taking place under thermodynamic control, e.g., in systems operating in continuous mode under substrate-limiting conditions. The analysis of the ∆ r G ′ 310 K indicated that the results obtained at pH 5 could be further improved by changing the initial concentration of acetate as several reactions would be significantly affected. As shown in Fig. 5 a, the ∆ r G′ 310 K of ethanol-producing reactions from H 2 /CO 2 and CO would be neither positively nor negatively affected by the initial concentration of acetate. In turn, all reactions involving the use of acetate as product or substrate present significant variations in the ∆ r G′ 310 K upon changes in acetate concentration. While acetate-producing reactions are negatively affected by the increase of acetate, the reactions consuming acetate become thermodynamically favored. However, based on the F T obtained for each reaction, only acetate-reducing reactions and the chain elongation could be thermodynamically controlled upon changing the initial acetate concentration (Fig. 5 b). The production of acetate from both H 2 /CO 2 and CO would not be sensitive to changes in ∆ r G ′ 310 K , as the free energy liberated would be high enough to drive these reactions forward independently of the concentration of acetate (Fig. 5 b). Fig. 5 a Calculated ∆r G ′ 310 K for the metabolic network of microbial consortia as a function of acetate concentration, normalized for e-mol transferred per reaction. Process conditions considered were: temperature of 310.15 K, ionic strength of 0.08 M, P H2 of 1.05 atm, P CO2 of 0.6 atm, P CO of 0.45 atm, concentration of other metabolites of 0.001 M and pH 5. b Thermodynamic potential factor calculated for all reactions as a function of pH. Solid lines represent F T calculated using a ∆ G p of 57.5 kJ/mol of ATP. Dashed lines represent the upper and lower boundary of F T when using a ∆ G p of 45 and 70 kJ/mol of ATP, respectively. The upper and lower boundaries are shown only for acetate-reducing reactions and the chain elongation reaction Comparing the effect of the pH and the initial acetate concentration on acetate-reducing reactions, the analysis of the changes in ∆ r G ′ 310 K and F T shows that the concentration of acetate has a stronger effect on the activity rates of these reactions. An increase in acetate concentration from 1 mM to 20 mM would significantly boost the acetate-reducing activity as the F T would increase from 0.79 to 0.88 when using CO as electron donor, and from − 0.13 to 0.45 when using H 2 . In this case, at an initial acetate concentration of 20 mM, both reactions would be clearly feasible regardless of the ∆ G p considered, even when using the more conservative ∆ G p of 70 kJ/mol of ATP (Fig. 5 b). Thus, according to these calculations, an enrichment at pH 5 and 20 mM of initial concentration of acetate would be expected to boost the ethanologenic potential of the microbial consortium by increasing its acetate-reducing activity. As opposed to lowering the pH, increasing the initial concentration of acetate would favor the chain-elongating activity. In this case, the F T for chain elongation would remain constant at values approaching 1 by increasing the initial concentration of acetate from 1 mM to 20 mM when using a ∆ G p of 57.5 kJ/mol of ATP (Fig. 5 b). Considering the most conservative ∆ G p of 70 kJ/mol of ATP, the F T would increase from 0.86 to approx. 1. Therefore, the rate of this reaction would be clearly boosted by the increase of initial acetate concentration in the fermentation broth. This would theoretically decrease the ethanologenic potential of the microbial consortium, as also shown experimentally by El-gammal et al. [ 52 ]. However, as the pH was anticipated to decrease during the course of the fermentation, the inhibition of the chain-elongating activity due to the low pH observed in this and other studies [ 21 ] was expected to play an important role in such enrichment conditions by preventing a significant activity. Enrichment with acetate addition: ethanol yield and microbial community The results of the enrichment showed that the production of ethanol was enhanced by the addition of acetate. The higher ethanologenic potential of the microbial consortium at these enrichment conditions was evident as, at the first transfer, ethanol was already the main product of the fermentation and the ethanol yield was significantly higher than that of enrichment HT5YE without acetate addition (Fig. 6 ). As the enrichment proceeded, the ethanol production rapidly improved reaching an ethanol yield of 0.055 mol/e-mol (65.58% of the stoichiometric maximum) at transfer T2. Nevertheless, from transfer T0, both acetate and ethanol started to be used as substrates for the chain elongation reaction, resulting in increasing amounts of butyrate produced from transfer T0 to T3. Figure 6 shows the product yields obtained along the enrichment for the two replicates, where a high disparity between replicates and a high tendency for chain elongation can be observed, with butyrate even becoming the main product in one of the replicates at transfer T3. The large variations observed in transfer T3 derive from the fact that butyrate was produced through a two-step reaction, thus causing high deviations depending upon when the chain-elongation reaction started during the fermentation (fermentation profiles of transfer T3 can be found in Additional file 1 : Figures S9 and S10). Although it was possible to perform the transfers while ethanol was still the main product of the fermentation in at least one of the replicates, at transfer T2 it was obvious that the chain-elongating microbial group was being enriched in the microbial consortium. Therefore, the enrichment strategy was modified from transfer T2 in an attempt to wash out the chain-elongating microbial group by transferring the cultures as soon as consumption of both CO and H 2 started. This strategy was expected to select exclusively for carboxydotrophic microorganisms as these would be the only microbial group able to reach exponential growth phase at the moment of the transfer, favoring a gradual wash out of the chain-elongating microbial group. As expected, changing the enrichment strategy allowed reducing the chain-elongating activity of the microbial consortium, yet a complete wash out of this microbial group was not achieved since a residual amount of butyrate was still produced by the end of the enrichment. However, the decline in chain-elongating activity enabled increasing further the ethanol yields obtained during the enrichment, reaching a maximum of 0.059 mol/e-mol (70.24% of stoichiometric maximum) at transfer T6. Fig. 6 Product yields (mol/e-mol), net consumption/production of acetate (mol/e-mol of syngas consumed) and final pH for each fermentation in enrichment at pH 5 with addition of acetate (20 mM). The maximum theoretical net consumption of acetate corresponds to 0.25 mol acetate consumed/e-mol of syngas consumed. The columns show the values for the fermentation transferred and the error bars indicate the corresponding values of the duplicate experiment. Additional information on substrate consumption can be found in the Additional file 1 : Figure S8 The thermodynamic analysis predicted a much higher acetate-reducing and chain-elongating activity in the microbial consortium enriched with acetate (HT5YE-Ac) when compared to the enrichment at pH 5 (HT5YE). The higher acetate-reducing activity could be clearly observed in the fermentation profile shown in Fig. 7 , where the consumption of H 2 , CO and acetate with concomitant ethanol production was apparent. This emphasizes the bioenergetic component of the metabolic shift towards ethanol, as increasing the initial acetate concentration clearly boosted the activity of acetate-reducing reactions. On the other hand, the chain elongation was expected to be inhibited by the decrease of pH along the fermentations even though this reaction would be thermodynamically favored by the addition of acetate. Nevertheless, during the course of the fermentations, the pH of the fermentation broth increased significantly as a result of the acetate conversion into ethanol (Fig. 7 ), which probably favored the fact that the pH inhibition of the chain-elongating activity did not operate during the enrichment. Thus, it seems that an automated pH control would be necessary to successfully prevent the chain-elongating activity through pH inhibition under these enrichment conditions. The results obtained here differed significantly from those reported by El-gammal et al. [ 52 ] since, in their study, acetate-reducing reactions were not enhanced upon addition of acetate, resulting in net acetate production at all times. However, in their study a pH of 6 and an initial acetate concentration of 13 mM was used, which reduced the effect on the ∆ r G ′ 310 K for acetate-reducing reactions. In this study, the fermentation carried out by the enriched consortium HT5YE-Ac (Fig. 7 ) resulted in a net consumption of 0.021 ± 0.004 mol of acetate/e-mol of syngas and an ethanol yield of 0.060 ± 0.002 mol/e-mol (72.44 ± 2.11% of the stoichiometric maximum), increasing the ethanol yield obtained with the enriched consortium HT5YE by 22.49%. Similar yields, corresponding to 58.6 ± 7.4% of the stoichiometric maximum, were reported by Steinbusch et al. [ 22 ] while studying the reduction of acetate into ethanol with H 2 as electron donor using a heat-shock-treated anaerobic sludge as inoculum. Additionally, a high chain-elongating activity was also reported in their study, where ethanol was produced in the first stage of the fermentation and was subsequently converted into butyrate. Fig. 7 Fermentation profile of the enriched consortium HT5YE-Ac. a Gas composition of the headspace (mmol). b Concentration of products in the fermentation broth (mM). c Microbial growth and pH of the fermentation broth \n The analysis of the microbial composition revealed strong similarities with the pH-based enrichment samples analyzed. In this case, the samples were withdrawn at transfers T1 and T3, which allowed evaluating the evolution of the microbial composition at an earlier stage in the enrichment. Interestingly, the results showed that the composition of the microbial community at genus level had already changed drastically at transfer T1 and remained stable until transfer T3 (Fig. 8 ). As in the pH-based enrichments, all enrichment samples were clearly dominated by the genus Clostridium with an average abundance of 63.2 ± 5.4%. However, it was not possible to identify the dominant species. There was a significant proportion of diverse OTUs (between 79.9 and 85.9% in all samples) that could not be reliably classified at this level (bootstrap value of 80% using SINTAX) (Additional file 2 : Table S2). SINTAX-classified OTUs with relatively high abundance were classified as C. nitrophenolicum and C. kluyveri and were present in the enrichment samples within a range of 10.6–18.4% and 0–2.8%, respectively. This magnitude of abundances suggests a possible role during the fermentations. C. nitrophenolicum has never been described to consume neither CO nor H 2 . The only mention of C. nitrophenolicum in gas fermentation-related literature corresponds to a study on bio-H 2 -mediated production of commodity chemicals using bioelectrochemical systems, where this species had a relative abundance between 2.7% and 3.6% in the cathode biofilm [ 63 ]. In turn, C. kluyveri is generally referred to as the model organism for the chain elongation process in several studies using both co- and mixed cultures [ 51 , 64 ]. Additionally, C. kluyveri was identified in an enrichment study aiming at the conversion of syngas into higher alcohols, in which this species was found to participate in the chain elongation of acetate and ethanol [ 21 ]. In this study, the relative abundance of selected OTUs corresponding to C. kluyveri increased from transfer T1 to T3 during the enrichment, where butyrate was observed to be produced through chain elongation (Additional file 1 : Figures S9 and S10). It can be thus concluded that this species clearly contributed to the increasing chain-elongating activity observed during the early stage of this enrichment. Fig. 8 Relative taxonomic abundance of the analyzed microbial consortia in enrichment HT5YE-Ac at genus level. The label of the samples is encoded according to the enrichment name, transfer number and growth phase at the moment of the sampling. ME and SP stand for mid-exponential and stationary growth phase Effect of enrichment conditions on microbial diversity Comparing the microbial diversity of all enrichment samples revealed important differences across enrichment conditions. Figure 9 a shows the alpha diversity calculated for all samples sorted by initial pH conditions. The results show that both inocula used presented among the highest alpha diversity, which gradually decreased with harsher enrichment conditions. The comparison across enrichment conditions shows a clear decreasing trend in alpha diversity as the pH decreases. Although the addition of YE contributed to a higher diversity, as it can be seen by comparing the two enrichments at pH 5.5 (HT5.5 and HT5.5YE), further decreasing the pH to 5 resulted in a drastic drop in diversity despite YE addition. Thus, the pH seems to be the major factor driving the reduction of complexity observed in the enrichment cultures. Similar trends were observed when studying the microbial diversity during a hydrogenotrophic enrichment at different pH conditions using cow manure as inoculum, where it was shown that pH 5 and pH 7 sustained the lowest and the highest microbial diversity among all conditions studied [ 65 ]. Fig. 9 a Dependence of alpha diversity (measured as number of unique OTUs) on pH for all enrichment samples. NA corresponds to samples from the starting inocula. b Non-metric multidimensional scaling (nMDS) unconstrained ordination. The arrows represent the direction and strength of the correlation between the variables and the unconstrained ordination of samples. The label of the samples is encoded according to the enrichment series name and transfer number The non-metric multidimensional scaling (nMDS) analysis (Fig. 9 b) illustrates the degree of microbial composition similarity between enrichment samples based on their relative distance. The results show that the samples from each enrichment are grouped together as a result of their higher similarity, which indicates that the enrichment cultures had reached a stable microbial composition at transfer T3. Comparing across enrichment conditions, it can be seen that enrichments HT6 and HT5.5YE, on one hand, and enrichments HT5YE, NT5YE and HT5YE-Ac on the other, developed closely related microbial communities, although a more widespread distribution can be observed in the latter group (Fig. 9 b). In turn, the microbial consortium from enrichment HT5.5 was less related to other enrichments, probably due to the drastic drop in alpha diversity as compared to HT5.5YE. A statistically significant correlation was found between the initial pH conditions of each enrichment series and their microbial composition with a R 2 corresponding to 0.90 ( P value < 0.001), which indicates that the microbial composition found in the enrichment cultures was pH-dependent (Fig. 9 b). Similarly, the ethanol and acetate yields were also found to be correlated with the ordination of the samples (with a R 2 of 0.73 and 0.65, respectively, P value < 0.001) and followed a similar gradient direction with the pH (Fig. 9 b). Thus, these results show that both the microbial composition and the yield of the main products were affected by the pH conditions of each enrichment series."
} | 13,704 |
35542188 | PMC9080261 | pmc | 5,516 | {
"abstract": "Dielectric materials typically demonstrate poor thermal conductivity, which limits their application in emerging technologies in integrated circuits, computer chips, light-emitting diode lamps, and other electronic packaging areas. Using liquid metal microdroplets as inclusions to develop thermal interface materials has been shown to effectively improve thermal pathways, but this type of material may become electroconductive with the application of a concentrated compressive stress. In this study, an isotropic nano-liquid metal thermally-conductive and electrically-insulating material (nLM-THEM) is developed by combining a modified polymer and well-dispersed nanoparticles, achieving an ∼50× increase in thermal conductivity over the base polymer. In addition, the thermal conductivity of nLM-THEMs exhibits no significant change with varying humidity and a stable anti-corrosion effect even in direct contact with aluminum. More importantly, nLM-THEMs demonstrate a stable electrical insulating property upon compressive stress, while conventional micro-LM-THEMs exude liquid metal. This exceptional combination of thermal and electrical insulation properties is enabled by the interconnection of uniform and spherical liquid metal nanoparticles to create more thermally-conductive pathways, and surfactant modified nanoparticles ensure excellent electric insulation. Moreover, this material can achieve passive heat exchange through rapid heat dissipation, which demonstrates its great application potential in the electronic packaging area.",
"conclusion": "4 Conclusions It is found that the nLM-THEMs can solve the stability problem exhibited by conventional micro-LM-THEMs, as well as prevent electricity leakage and corrosion. These results greatly recommend LM-based THEMs for further practical applications. It is shown that the use of ultrasonic dispersion and surfactant control can effectively achieve a uniform nanoscale LM in base materials. The maximum thermal conductivity of then LM-THEMs reaches 6.73 ± 0.04 W m −1 K −1 with filling ratios of 85.7% (v/v) while the volume resistivity is 2.09 × 10 9 Ω m at 220 V, which ensures a high thermal conductivity and electric insulation. It is shown that the isotropic nLM-THEMs exhibit excellent cooling effects for the heating source. We anticipate that this nLM-THEM will be appropriate for a wide array of future applications in electronic packaging.",
"introduction": "1 Introduction With electronic products advancing to applications in artificial intelligence and miniaturization, a high degree of integration and power density is necessary for these devices. Heat dissipation in these devices has a great impact on their performance and reliability, where a rise of 2 °C in the electrical components will reduce the device reliability by 10%. 1–4 Therefore, heat dissipation is key to developing high-performance electronic products of the future. The development of thermally-conductive and electrically-insulating materials (THEMs) is an effective way to solve the problem. 5 The thermal conductivity of conventional THEMs is mainly based on an organic silica gel incorporating metal oxide and/or metal nitride fillers such as alumina, zinc oxide, magnesium oxide, bismuth oxide, silicon nitride, boron nitride, aluminum nitride and silicon carbide, which operate as conductive inclusions. The thermal conductivity of these THEMs ranges from 0.5 to 5 W m −1 °C −1 , 6–18 but the heat conduction of these types of THEMs is limited owing in part to the ease with which the THEMs absorb moisture and deteriorate in the open air. To improve the thermal capacity of THEMs, solid particle fillers of gold, silver, copper, aluminum, magnesium and other metals have been investigated. 19–22 For polymer-based THEMs, the contact area between the thermally-conductive fillers and the polymer increases as the proportion of the inclusions increases. Consequently, the filling particles disperse in the matrix and form a relatively stable and efficient heat transfer path owing to their direct contact with the polymer, where the path is called a thermally-conductive mesh chain. 23–30 These excellent heat transfer paths effectively improve the thermal conductivity of the composite material, but it is not feasible to continuously increase the composite thermal conductivity with the unrestricted addition of thermally-conductive fillers. For example, the most common thermal filler is a solid powder and when the filling ratio reaches a threshold value the composite material is easily dried. Further, composite materials that use metal powders as fillers exhibit a significant reduction in its electrical resistance. 31 Unlike the traditional solid filler, a room-temperature liquid metal (LM) has a broad applicability for thermal management, and especially the gallium indium eutectic alloy (EGaIn) with a higher thermal conductivity and volume heat capacity. In 2013, Liu et al. developed a thermal interface material (TIM) with a thermal conductivity of 13.07 W m −1 K −1 based on liquid gallium-based materials and oxidation processes. 32 However, this kind of LM-TIM also possesses high electrical conductivity and has a serious corrosion effect on aluminum alloys, and is therefore not applicable for electronic devices. In 2014, Mei et al. prepared a composite thermal grease comprising a gallium alloy as a thermal filler and methyl silicone oil as a matrix, whose maximum thermal conductivity was 5.27 W m −1 K −1 . 33 But the risk of leakage still exists. In addition, LM microdroplets instead of solid metal particles can provide the liquid filler for high-performance THEMs. For example, Bartlett et al. have used LM droplets as fillers in a silicone elastomer to obtain a flexible composite material whose thermal conductivity was 4.7 ± 0.2 W m −1 K −1 under stress-free conditions and 9.8 ± 0.8 W m −1 K −1 at 400% strain, 34 and that is to say the high thermal conductivity of the composite material is not isotropic, it is only along the direction of the elongated droplets. These LM-based THEMs dramatically enhanced the thermal management in electronic packaging applications. Currently, most LM-based THEMs consist of microscale LM droplets as inclusions, but it has been found that this type of LM-filled composite thermal material runs the risk of electrical leakage. Specifically, when the thickness of the coating layer is reduced the LM will precipitate under a light pressure load. In addition, silicone oil leakage may occur during storage after a period of time. These problems restrict the further development and application of LM-based THEMs, and thus it is particularly urgent and necessary to solve the problem of the THEM stability. Here, we propose the use of a modified polymer subjected to ultrasonic dispersion to improve the surface treatment of the LM. A high-stability THEM based on a nano-liquid metal (nLM) was prepared, where the THEMs exhibited high thermal conductivity and insulation characteristics in all directions ( i.e. isotropic) as well as excellent stability. This method solves the stability problem of the binary dispersion system as well as the silicone oil exudation problem. Furthermore, it prevents the risk of electrical leakage or corrosion risk brought about by the metal precipitation. Highly-stable nLM-THEMs exhibit great potential in electronic cooling systems.",
"discussion": "3 Results and discussion 3.1 Formation of nLM particles The EGaIn comprising 75.5% (w/v) gallium and 24.5% (w/v) indium is a nLM at room temperature, and has excellent thermal conductivity suitable for making high-thermal-conductivity THEMs. In the experiment, a nLM-THEM was prepared using EGaIn as the thermally-conductive filler and 201-methyl silicone oil as the matrix material, which were combined via ultrasonic mixing and the addition of Span 85. The preparation process is shown in Scheme 1 . Scheme 1 Schematic diagram of the nLM-THEM fabrication process. It is worth noting that the important parameters affecting the size of nLM are sonication time and sonication power. 35 To determine the appropriate time and power of sonication, a batch of experiments is performed and the results is shown in Fig. S1(a) and (b), † respectively. With the increase of sonication power (sonication time is 25 min), the average size of liquid metal nanoparticles decreased first, then increased, and finally stabilized (Fig. S1(a) † ). When the sonication power is 300 W, the average size of nanoparticles reaches the minimum (259.1 nm); Fig. S1(b) † shows the average size change with sonication time under certain power ( P = 280 W), the size of liquid metal nanoparticles first descends, then increases, and gradually stabilizes. When the sonication time is 40 min, the average particle size reaches a minimum of 248.1 nm. Based on the experimental results, 300 W and 40 min is chosen to make liquid metal nanoparticles, dynamic light scattering (DLS) measurement of the nanoparticles is shown in Fig. S1(c). † The average size of nLM is 232.5 nm. The smaller the size of nLM, more contact with 201-methyl silicone oil will be achieved with the same weight of nLM as filler. Therefore, 300 W and 40 min is chosen for the nLM-THEMs preparation and the next experiments. Four kinds of nLM-THEMs with different filling ratios were prepared by the above process, where the volume proportions of the LM ( V LM ) and that of methyl silicone oil ( V MSO ) were V LM : V MSO = 3 : 1, 4 : 1, 5 : 1, 6 : 1 (volume fractions of LM is 75.0%, 80.0%, 83.3% and 85.7%, respectively). The microstructures of these four variations of nLM-THEMs are shown in Fig. S2 † and a typical example of the nLM-THEM ( V LM : V MSO = 6 : 1) is shown in Fig. 1(a) and (b) . According to the SEM images, the nLM-THEMs are a dense array of smooth spherical particles mostly ranging from 100–800 nm in diameter at 22 °C (Fig. S3 † ), which is consistent with DLS data (Fig. S1(c) † ). The reason why the uniformity is not ideal is that all the products after LM sonication are collected, if gravity settling and stratified centrifugation of nLM sample can be properly conducted, the uniformity of nLM-THEMs will be further improved. Even though, compared to the microstructure of a micro-LM-TIM prepared by the conventional process (see Fig. 1(c) and (d) ), it demonstrates that the droplet diameter of micro-LM THEMs is between 10–200 μm, and the shape of the LM droplets is irregular and nonspherical, showing worse uniformity. Fig. 1 SEM images of the THEMs. Microscopic morphology of the (a) and (b) nLM-THEMs and (c) and (d) micro-LM THEMs. 3.2 High thermal conductivity and electrical insulation with nLM-based material Thermal conductivity is the most important physical parameter for measuring the heat dissipation effect of the THEMs. The thermal conductivities of the nLM-THEMs with different volume fractions 75.0%, 80.0%, 83.3% and 85.7% are measured as 4.03 ± 0.01, 4.40 ± 0.02, 4.92 ± 0.01 and 6.73 ± 0.04 W m −1 K −1 , respectively, as shown in Fig. 2(a) . As the LM volume fraction in the TIM increases, the thermal conductivity of the TIM also increases, though it does not exhibit a linear trend with the LM filling ratio. An increasing proportion of LM nanoparticles will form more thermal conduction paths because of more frequent contact among these particles. It is worth noting that thermal conductivity cannot increase in an unlimited fashion by increasing the LM volume fraction because the modified LM nanoparticles will reach a saturated state in the silicone oil when the LM fraction is greater than 87.5%. This saturated state leads to the propensity of the TIMs to dry and a significant reduction in the electrical insulation. Fig. 2 Physical characterization of the nLM-THEMs. (a) Thermal conductivities of the nLM-THEMs containing varying LM volume fractions showing well consistency with MG model prediction. (b) Specific heat capacities of the nLM-THEMs varying LM volume fractions showing no significant difference. (c) Thermal conductivities of the nLM-THEMs at varying humidity levels. (d) Electrical resistivity of the nLM-THEMs. The thermal conductivity of the binary composites can be predicted using the theoretical Maxwell-Garnett's (MG) model, 36 which is quite commonly used as an effective medium theory to predict the thermal conductivity of binary mixtures. The MG model can be given as follows: 1 where, k eff is the effective thermal conductivity of the nLM-THEMs, k p is the thermal conductivity of the liquid silicone oil, k lm is the thermal conductivity of the liquid metal, ϕ is the volume fraction of the liquid metal. The silicone oil's thermal conductivity is rather small (about 0.7 W m −1 K −1 ), while the EGaIn is tested about 26.62 ± 0.01 W m −1 K −1 . The results obtained from MG model are compared with the experimental data. As shown in Fig. 2(a) , the thermal conductivity increases nonlinearly with the volume fraction of LM. It is clear that the experimental measurement agrees well with the calculated value. The specific heat capacity represents the ability of an object to absorb or dissipate heat. At the same heat absorption, the temperature of an object with a higher specific heat capacity will be lower. Thus, the size of the heat capacity can also reflect the intensity of the THEM thermal conductivity. The specific heat capacity of the nLM-THEMs with different LM volume fractions 75.0%, 80.0%, 83.3% and 85.7% are measured as 2.20 ± 0.05, 2.24 ± 0.03, 2.20 ± 0.08 and 2.42 ± 0.08 MJ m −3 K −1 , respectively, as shown in Fig. 2(b) . From these experimental results it is clear that, though nLM-THEMs have a high specific heat capacity, increasing of the volume fraction of LM does not significantly change the specific heat capacity. Many types of THEMs degenerate quickly when exposed to the open air, wherein the relative humidity of the air has a great impact on the material properties. Under conditions that were otherwise identical, the thermal conductivity of the nLM-THEM (LM fraction is 85.7%) was tested at different humidity levels. Fig. 2(c) shows the results of the thermal conductivities of the nLM-THEMs of 6.69 ± 0.02, 6.72 ± 0.02, 6.73 ± 0.04, 6.71 ± 0.01 and 6.73 ± 0.03 W m −1 K −1 for relative humidity levels of 35, 45, 55, 65 and 75%, respectively. It is demonstrated that the thermal conductivity of the nLM-THEMs remained essentially unchanged with varying relative humidity. This demonstrates that the heat dissipation effect of the nLM-THEMs is nearly unaffected in different indoor environments, which further proves the high stability of nLM-THEMs. To verify the insulation properties of the nLM-THEMs, we measured their volume resistivity at different voltages in the range of 5–220 V, as shown in Fig. 2(d) . It can be seen that the volume resistivity–voltage curve is approximately a straight line, indicating that the volume resistivity of the nLM-THEMs is closely related to the applied electric field. With the increase of the measured voltage, the resistivity of the TIM also increases. The volume resistivity is 9.8 × 10 7 Ω m when the measured voltage is 5 V, and the volume resistivity is 2.09 × 10 9 Ω m when the measured voltage is 220 V. As shown in Fig. 2(a)–(d) , we can see that the nLM-THEM has excellent thermal conductivity and electrical insulating properties. 3.3 Enhanced stability of nLM-THEMs compared to micro-LM THEMs To further test the stability of nLM-THEMs, a series of experiments were conducted. First, nLM-THEMs were placed at room temperature for a month. As shown in Fig. 3(a) , the morphology of the nLM-THEMs stored in a glass bottle is stable with no apparent change. For comparison, the same proportion of micro-type THEMs (micro-LM-THEMs) was prepared according to the traditional process, 33 and the results are shown in Fig. 3(b) . It can be seen that the upper surface of the conventional micro-LM-THEMs in the glass bottle gradually exudes silicone oil with time, and the accumulation of a silicone oil top layer is obvious after a month. Fig. 3 Stability of nLM-THEMs. (a) and (b) Changing state of (a) nLM-THEMs and (b) conventional micro-LM-THEMs after resting for various durations at room temperature. (c) Microscopic morphology of nLM-THEMs showing no apparent difference from day 0 to day 20. (d) Thermal conductivity of nLM-THEMs showing no significant difference along the exposing time. (e) Electric resistivity of nLM-THEMs showing no significant difference along the exposing time. Further SEM characterization of nLM-THEMs was conducted after preparation for different days. As shown in Fig. 3(c) , the diameter of liquid metal particles was about several hundred nanometers after preparation. The observation was conducted on day 0, day 5, day 10 and day 20, respectively. It was demonstrated that the size and distribution of liquid metal particles in the same nLM-THEMs sample was almost indistinguishable with time, and no aggregation formed in the sample. In addition, the changes in thermal conductivity and electric resistivity of the nLM-THEMs were also measured every 5 days after the material fabrication, the results were shown in Fig. 3(d) and (e) . It was found that the thermal conductivity and electrical resistivity of the materials showed no significant difference with time. Both the thermal and electric characterization together with morphology show that the nLM-THEMs is remarkably stable along the exposing time. To demonstrate the contact stability of the nLM-THEMs with various substrates, three different material plates of glass, plastic and copper were used for nLM-THEM-coating experiments. The thickness of the coating in the experiment is about 0.1 mm, which is similar to the thickness of ordinary A4 paper, and is shown in Fig. 4(a) . The coating surface appears gray and delicate, and exhibits no LM precipitation. After one month, no significant changes were observed on the coating surface or at the edge of the coating material (see Fig. 4(b) ). In contrast, when a conventional LM-TIM was coated on cardboard with a similar coating thickness, LM precipitation could be observed, as shown in Fig. 4(c) . This demonstrates that the nLM-THEM is more stable and coats the substrate easier, which exhibits superior practical application advantages compared to conventional LM THEMs. Fig. 4 nLM-THEMs showing high adhesivity and stability to various substrates. (a) and (b) State of a thin layer of nLM-THEMs on surfaces composed of (from left to right) glass, plastic and copper plates (a) directly after being coated and (b) a month after being coated. (c) Cardboard coated with a thin layer of micro-LM-THEMs exhibiting LM microdroplets that have fused into macrodroplets. (d) Rheological properties of the nLM-THEM. (e) Viscoelastic plots of nLM-THEM. The reason why nLM-THEMs showing high adhesivity and stability to various substrates was further conducted. We measured the rheological properties of the nLM-THEMs, using the rotational rheometer (Haake RS6000, Thermo Fisher Scientific Inc., MA, USA). From the relation among shear rate, dynamic viscosity and shear stress ( Fig. 4(d) ), the nLM-THEMs should belong to non-Newtonian fluid, thus shear thinning occurs. And its rheological properties seem to be the same as that of power law fluid, because of the linear γ – τ relationship with logarithmic coordinates. Moreover, the dynamic viscosity of nLM-THEMs is limited between 100 Pa s to 100 000 Pa s with shear rate ranging from 0.1 s −1 to 100 s −1 , therefore, it could be easily coated on the various surface of heat source easily, which is consistent with the above experiments ( Fig. 4(a) and (b) ). During the study of the rheological properties of nLM-THEM, to ensure that nLM-THEM materials are within the range of linear viscoelasticity, stress scan of nLM-THEM was performed. nLM-THEM exhibits linear viscoelasticity under stress range from 8 Pa to 100 Pa ( Fig. 4(e) ). According to the results, the elastic modulus of nLM-THEM is much larger than the loss modulus, demonstrating that nLM-THEM mainly undergoes elastic deformation under stress. 3.4 Anticorrosion effect of nLM-THEMs As we know, THEMs are used widely in chip cooling systems and are in close contact with the chips packaging material which usually is made of aluminium silicon alloy, signifying that corrosion resistance of aluminium is critical to ensure the safety of the chips. When aluminum reacts with oxygen, an oxide film is generated on the surface that impedes further reaction of the aluminum with oxygen. However, gallium-based alloys cause the aluminum atoms to react with oxygen molecules in the air by atomic migration, which generates much alumina and causes aluminum plate corrosion. 37 To demonstrate the anticorrosion characteristics of the nLM-THEMs, EGaIn and nLM-THEMs were designed to corrode a piece of aluminum. Two pieces of aluminum (40 mm × 40 mm × 20 mm) were polished to remove the surface oxide layer, and EGaIn and EGaIn nLM-THEMs were subsequently applied uniformly on the surface of the aluminum in separate areas. Images were recorded daily for nine days, and the results are shown in Fig. 5(a) and 4(i) . Fig. 5 Corrosion test results. (a)–(i) Corrosion of aluminum surface as a function of time. (j) Energy-dispersive spectra of the clean aluminum blocks. (k)–(l) Energy-dispersive spectra of aluminum blocks after nine days of contact with (k) micro-LM-THEMs and (l) nLM-THEMs. (m) FEG-SEM image of the clean aluminum surface. (n) and (o) FEG-SEM image of the aluminum surface after nine days of contact with (n) micro-LM-THEMs and (o) nLM-THEMs. It can be seen that aluminum coated with EGaIn corrodes completely, while aluminum coated with the nLM-THEMs remains as bright and clean as the original surface. The FEG-SEM images and EDX spectra further demonstrate the anticorrosive effect of the nLM-THEMs. According to the EDX spectrum analysis, the ratio of oxygen and gallium increases and the aluminum is relatively reduced when the aluminum block is in contact with EGaIn ( Fig. 5(k) ) compared to the clean aluminum ( Fig. 5(j) ) and the elemental composition of the aluminum in contact with nLM-THEM ( Fig. 5(l) ) does not change during the corrosion test. After the aluminum is in contact with EGaIn, the aluminum surface becomes porous and uneven ( Fig. 5(n) ). In contrast, the structure of aluminum in contact with nLM-THEM exhibits a regular and close arrangement with no corrosion ( Fig. 5(o) ) as well as the clean aluminum ( Fig. 5(m) ). Before the XRD/EDS analysis, the nLM-THEMs was removed by plastic scraper, then the aluminum plate was gently wiped cleanly with dust-free paper. In order to test whether there is corrosion existed in the nLM-THEMs sample, we further analyzed the scraped nLM-THEMs from the aluminum plate by energy spectrum, and the result is shown in Fig. S4. † From the element content table and the spectrum analysis, it is found elements containing C, O, In, Ga and Si, except Al. Hence, it is strongly proved that the aluminum corrosion hasn't been occurred when contact with nLM-THEMs. The LM nanoparticles in the nLM-THEM form an effective protective layer after modification to prevent direct contact between the LM and the aluminum surface, thus avoiding further corrosion by blocking the migration of gallium atoms. In addition, the nLM-THEM demonstrates no obvious corrosion response to the glass, plastic or copper plates, as shown in Fig. 4(c) and (d) . In summary, the nLM-THEMs have excellent thermal insulation properties and stability, as well as good corrosion resistance. 3.5 Enhanced cooling effect of nLM-THEMs To demonstrate the actual heat dissipation effect of the nLM-THEMs, 201-methyl silicone oil, Deepcool®Z9 thermal conductive grease with thermal conductivity > 4.0 W m −1 K −1 , and nLM-THEMs with a volume fraction of LM of 85.7% (v/v) are used to do a parallel test of the cooling effect. Fig. 6(a) shows a schematic diagram of the experimental device. The stability of the thermal distribution is shown in Fig. 6(b) , where it can be seen that the average temperature of the device with the silicone oil as the interface material is highest, the average temperature with Deepcool Z9 is lower, and the average temperature with nLM-THEMs is lowest. Fig. 6 Actual cooling effect comparison of methyl silicone oil, thermal conductive paste and nLM-THEMs. (a) Experimental device diagram of the actual cooling effect of the three THEMs. (b) Temperature distribution thermal image of the test. (c) Core temperature of the euthermic chips as a function of time. The core temperature of the chips using silicone oil as the interface material stabilized at ∼90 °C and its average temperature rise rate is the highest at 0.66 (°C s −1 ) in the beginning, that with Deepcool Z9 thermal paste stabilized at ∼70 °C and its rate at 0.51 (°C s −1 ), and that with nLM-THEMs stabilized at ∼60 °C having the lowest average temperature rise rate at 0.3 (°C s −1 ) in the beginning (see Fig. 6(c) ). This experimental result shows that the thermal diffusivity and thermal conductivity of then LM-THEMs are superior to that of commercial THEMs under the same heating conditions. 3.6 Young–Laplace equation reveals the higher stability of nLM-THEMs than micro-LM-THEMs Here, we report a LM-based thermal interface composite with high thermal conductivity. The maximum thermal conductivity of the nLM-THEMs is up to 6.73 ± 0.04 W m −1 K −1 (∼50 times more than the base polymer) and the volume resistivity is 2.09 × 10 9 Ω m at 220 V. The ability of these high-thermal nLM-THEMs achieves superior thermal conductivity compared to conventional micro-LM-THEMs. The reason may be owing to the fact that the surfactants change the surface properties of the LM particles, in particular by reducing the surface tension of the LM. 38 Unlike conventional LM-TIMs exhibiting a microstructure, the nLM-THEMs exhibit a dense array of smooth spherical particles that largely range from 100–800 nm in diameter at 22 °C. After sonication, Span 85 molecules are coated on the surface of the LM droplets, which prevents the LM droplets from merging immediately with each other when they come in contact. Span 85 is a hydrophobic surfactant with a HLB (hydrophile and lipophile balance) value of 1.8, which is well combined with methyl silicone oil. This can improve the LM dispersion effect in the THEMs, so a “sphere–sphere” combination can be seen in the structural state of the nLM-THEM microstructure. As shown in Fig. 1(a) and (b) , each sphere is in direct contact with the surrounding spheres, but cannot be fused to form larger LM spheres because the surfaces area combination of surfactant and silicone oil. The “sphere–sphere” stable structure not only ensures an effective heat transfer path to improve the thermal conductivity of the material, but also achieves a uniform and stable nLM-THEMs. In the micro-LM-THEMs with no modification, the droplet structure is seen to be discontinuous with many “ditch back” features, with an appearance similar to the human brain. The structure of the “sphere–liquid–sphere” is extremely unstable. The liquid inclusion in the middle of the droplet will be “squeezed out” under external force, and these discontinuous droplets will re-contact and fuse into larger spheres. The LM in conventional micro-LM-THEMs continuously and gradually precipitates with time ( Fig. 3(b) ), whereupon the silicone oil is separated from the materials and accumulates on the surface ( Fig. 3(b) ). According to a previous study, a surface pressure of 1.7 MPa can cause a permanent change in a thin sheet (0.5 mm thick) of poly(dimethylsiloxane) embedded with inclusions of LM (gallium–indium–tin) microdroplets (2–30 μm in diameter), whereupon the film becomes electrically conductive with the concentrated stress. 39 For EGaIn nanoparticles 100 nm in diameter it was found that the necessary sintering pressure is ∼10 MPa, 40 while <1 MPa of pressure was required to sinter particles with diameters > 1 μm. 41 According to Young–Laplace equation, when external force satisfies the following condition, there is possibility to trigger the liquid metal droplet deformation, if external force satisfies: F > P > 2 γ / R where, F is external force, P is internal pressure of liquid metal, γ is surface tension, R is radius of liquid metal droplet. Take EGaIn as example, the surface tension of EGaIn is 0.624 N m −1 . 42 For a LM droplet with radius equal to 100 μm, external forces greater than 1.248 × 10 4 N can trigger the spherical deformation of LM droplet. As to droplet with radium of 100 nm, external force is as high as 1.248 × 10 7 to trigger the deformation. Our results are consistent with the trend found in previous experiment and Young–Laplace equation, which may help to explain the increased stability of nLM-THEMs compared to that of micro-LM-THEMs as shown in Fig. 7 . It is worth noting that the LM nanoparticles are further coated with polymer based surfactant, which means that LM nanoparticles may require more concentrated pressure to fuse. The inclusion of stable LM nanoparticles solves the problem of silicone oil exudation as well as preventing the corrosion risk brought by metal precipitation. Fig. 7 Schematic illustration showing the stability comparison between nLM-THEMs and micro-LM-THEMs. According to Young–Laplace equation, only when external force greater than 2 γ /R 2 , it is possibility to trigger deformation of LM droplet. When 2γ/ R 2 < F < 2γ/ R 1 , nLM-THEMs show high stability while micro-LM-THEMs have been merged with each other. The combination of high thermal conductivity and stability is especially critical for rapid heat dissipation in electrical packaging applications, such as chip cooling, in integrated circuits. The nLM-THEMs demonstrate excellent heat dissipation capabilities compared to commercial silicone oil and grease."
} | 7,501 |
34694768 | null | s2 | 5,517 | {
"abstract": "Biofilms are ubiquitous in nature, yet strategies to direct biofilm behavior without genetic manipulation are limited. Due to the small selection of materials that have been used to successfully grow biofilms, the availability of functional materials that are able to support growth and program microbial functions remains a critical bottleneck in the design and deployment of functional yet safe microbes. Here, we report the design of insoluble pyridine-rich polymer surfaces synthesized using initiated chemical vapor deposition, which led to modulated biofilm growth and virulence in "
} | 147 |
38410171 | PMC10895711 | pmc | 5,519 | {
"abstract": "Context Anthropogenic and natural disturbances may interact synergistically, magnifying their individual effects on biodiversity. However, few studies have measured responses of ecological communities to multiple stressors at landscape scales. Objectives We use a long-term dataset to test for synergistic effects of anthropogenic and natural disturbance on plant community diversity and composition in a large protected area. Methods We quantified changes in plant communities over two decades in 98 plots in Waterton Lakes National Park, Canada. Fifty-three plots burned in a wildfire in the interim. We modeled the effects of wildfire, proximity to trails or roads, and their interaction on changes in species richness, community composition, relative abundance of disturbance-associated species, and colonization by exotic species. Results Interactions between wildfire and proximity to roads and trails affected all metrics except species richness. Only one interaction was synergistic: the relative abundance of disturbance-associated species following wildfire was magnified closer to recreational corridors. The other community metrics showed unexpected patterns. For example, plots with no exotic species in the baseline survey that burned in the wildfire were more likely to gain exotic species than unburned plots only when they were distant from recreational corridors. Conclusions Our study demonstrates interactive effects of natural and anthropogenic disturbance at landscape scales within a protected area. Plant community response to wildfire was influenced by proximity to recreational corridors, sometimes in surprising ways. As the frequency and severity of anthropogenic and natural disturbances both continue to rise, documenting the prevalence and magnitude of interactions between them is key to predicting long-term effects and designing mitigation strategies. Supplementary Information The online version contains supplementary material available at 10.1007/s10980-024-01844-w.",
"conclusion": "Conclusions The potential for synergies between stressors is a popular topic of study (Côté et al. 2016 ; Orr et al. 2020 ), yet very little research has tested for synergistic effects of natural and anthropogenic stressors on community composition over large spatial and temporal scales. Using an extensive dataset covering a wide range of vegetation types within a large protected area, we found clear interactions between wildfire and proximity to recreational corridors on metrics of change in plant communities. However, there was no significant interaction effect on species richness, highlighting the importance of tracking other metrics that capture changes in community composition. Importantly, the nature of the interactive effects of wildfire and recreational disturbance were often surprising, and depended on the starting conditions of the community. Our work offers a baseline against which to compare the effects of interactions between natural and anthropogenic disturbance on communities at landscape scales in other regions and biomes. More large-scale studies investigating the response of communities to concurrent anthropogenic and natural disturbances will help us to predict the long-term effects of these interactions.",
"introduction": "Introduction A fundamental goal of ecology is to understand how ecological communities respond to disturbance. The trajectory of change following the destruction of many or most living individuals in a community by events like wildfires, storms, insect outbreaks, or volcanic eruptions has been a preoccupation of ecologists from the earliest days of the discipline (McIntosh 1985 ; Meiners et al. 2015 ). More recently, ecologists have realized that natural disturbances are affecting ecological communities in a context of increasing human domination of the biosphere. Human activities can alter natural disturbance regimes—by suppressing wildfires, for example (Nowacki and Abrams 2008 ). In addition, disturbance or stressors caused by human activities can change the trajectory of recovery following natural disturbances, or even reduce the resilience of ecological communities to natural disturbances (i.e. their ability to return to their former state; Folke et al. 2004 ). A key challenge for ecology is to understand how anthropogenic and natural disturbances interact to influence the resilience of ecological communities (Paine et al. 1998 ; Turner 2010 ; Smart et al. 2014 ; Côté et al. 2016 ). Many studies have examined the effects of multiple stressors on populations and communities. Effects can be additive, whereby each stressor is independent of the other (Côté et al. 2016 ). Alternatively, the two stressors can interact. If the interaction is synergistic, the magnitude of the effect of one stressor is amplified by the other (Côté et al. 2016 ), potentially leading to ‘ecological surprises’ (Paine et al. 1998 ). Meta-analyses of multi-stressor studies show that synergistic interactions are quite common when the response is measured at the population level, but rare at the community level (Crain et al. 2008 ; Côté et al. 2016 ). However, most studies at the community level examined changes in biomass or species richness (Orr et al. 2020 ). These metrics may be less responsive to disturbance because of complementarity: species that are sensitive to a disturbance or combination of disturbances decline or disappear, but those that are less sensitive increase or colonize, minimizing changes in species richness and biomass (Breitburg et al. 1998 ). Also, most multi-stressor studies are done at small spatial and temporal scales in the lab (e.g. most aquatic studies: Crain et al. 2008 ), warming chambers or mesocosms (e.g. Dieleman et al. 2012 ), or with small-scale experimental manipulations in nature (e.g. Micheli et al. 2016 ). Few multi-stressor studies have examined the response of community composition to anthropogenic and natural stressors at large spatial and temporal scales. In this study, we use data from 98 vegetation plots to test for interactions between natural and anthropogenic disturbance on changes in plant community diversity and composition in Waterton Lakes National Park in Alberta, Canada. The plots were surveyed in the early 1990s and resurveyed in 2019/2020, after about half of them were burned by a severe wildfire in 2017. We use the proximity of recreational roads and trails as a proxy for the degree of anthropogenic disturbance from recreation. We quantify changes in species richness, shifts in community composition, changes in the relative abundance of disturbance-associated species, and colonization by exotic species in each plot. We evaluate two possibilities for the effects of wildfire and recreation on these community metrics. If effects are additive, we predict that the magnitude of change in species richness and community composition will be highest in burned plots, and increase with proximity to roads or trails, but that these two drivers will not interact (Fig. 1 a). If these two stressors interact synergistically, we predict that close proximity to trails or roads will magnify the effect of the wildfire on the plant community (Fig. 1 b). Fig. 1 The predicted relationship between changes in plant community diversity or composition, burn status, and distance from recreational trails if wildfire and recreation are a additive, or b interact synergistically. In a , wildfire increases the magnitude of change in ecological communities over time relative to unburned communities consistently, regardless of the distance from a trail. In b , wildfire increases the magnitude of change in ecological communities over time relative to unburned communities more in areas near trails than in areas far from trails",
"discussion": "Discussion Landscape-scale studies are necessary to determine how interactions between anthropogenic and natural disturbances may influence the resilience of ecological communities (Breitburg et al. 1998 ; Orr et al. 2020 ). Previous landscape-scale studies have shown that when natural vegetation is fragmented, openings in these fragments created by natural disturbance are more likely to be colonized by generalist, disturbance-associated species, altering the trajectory of recovery (Catterall et al. 2008 ; Laurance and Curran 2008 ; Smart et al. 2014 ; Lloren et al. 2020 ). However, the degree to which recreation within protected areas influences the response of ecological communities to natural disturbance is largely unknown. While these areas are protected from habitat conversion, networks of roads and trails allow hiking and other recreational activities, and the intensity and extent of these activities are increasing due to rapidly increasing numbers of visitors (Monz et al. 2021 ). Trail networks are well-known conduits for disturbance-associated native and exotic species (Mount and Pickering 2009 ; Yang et al. 2021 ), and—in combination with natural disturbances that remove competition and increase nutrient levels—could facilitate colonization of these species beyond trail edges, leading to novel communities. At WLNP, communities that burned in the wildfire had greater shifts in composition than those that did not burn. This is not surprising: the fire killed nearly all trees, and there was a dramatic increase of common fire followers, such as Chamerion angustifolium (fireweed). We expected that shifts in composition caused by the fire would be magnified near recreational trails, but this was not the case. Shifts in community composition were driven largely by losses of species, rather than gains (Fig. S5 ). Therefore, although plots closer to recreational corridors saw increases in the relative abundance of disturbance-associated species after the fire, this was not enough to magnify the large shifts in composition already caused by losses of formerly dominant species. Even unburned plots saw a great deal of turnover between 1994 and 2019, with a mean Bray–Curtis dissimilarity of 0.55. Interestingly, unburned plots had greater shifts in composition farther from trails—perhaps indicating a role for recreational corridors in maintaining shade-intolerant species. Forest expansion and densification in this region has been ongoing since at least the late 1800s (Stockdale et al. 2019 ), and we know this trend has continued from 1994 to 2019 in the unburned plots based on significant increases in the relative abundance of woody plants over this timeframe (Lloren 2021 ). The change in relative abundance of disturbance-associated species matched our prediction for a synergistic response, although there was no effect of trail proximity without wildfire. In burned plots the increase in the relative abundance of disturbance-associated species was magnified in plots closer to trails or roads. This is consistent with the hypothesis that recreational trails increase the availability of propagules of disturbance-associated species (e.g. Wells et al. 2012 ; Wedegärtner et al. 2022 ), which are therefore able to quickly colonize burned areas near trails. Unburned plots saw relatively little change in the relative abundance of disturbance-associated species regardless of their proximity to trails or roads. This suggests that the near doubling of visitor levels in the Park over the past 25 years has not caused substantial increases in the abundance of disturbance-associated species—at least, not yet. Exotic plant species tend to be more abundant near trails (e.g. Rew and Johnson 2010 ; Romme et al. 2011 ; Wells et al. 2012 ). We expected, therefore, to find a higher likelihood of colonization by exotic species in both burned and unburned plots that were closer to trails or roads, and highest where the wildfire removed the canopy and reduced competition. Instead, we found that wildfire increased the likelihood of colonization by exotics, but only in plots that did not already have at least one exotic species, and this facilitation of exotic colonization by the fire was greater in plots farther from trails or roads. Perhaps plots near trails with no exotics at the time of the first survey had some unmeasured property making them less favourable to exotic species, such as low productivity (e.g. Brodie et al. 2021 ), and therefore even after fire the probability of colonization by exotics was low. In contrast, plots farther from trails with no exotics in 1994 may have lacked them simply due to competition from established native species, and the fire removed competitors and released nutrients, allowing exotics to colonize. Plots that already had exotic species in 1994 were more likely to gain new exotics if they were closer to trails. However, this effect was reduced in burned plots, an antagonistic rather than a synergistic interaction. It is possible that many burned plots near trails were colonized by new exotic species at some point since 1994, but that in some cases these colonizers were killed by the fire—thereby lowering the probability of our surveys detecting the colonization. The unexpected nature of the interaction between wildfire and trail proximity on exotic species colonization highlights the possibility for ‘ecological surprises’ (Paine et al. 1998 ). The way that the interaction depends on baseline conditions shows that the nature of the response of an ecological community to multiple stressors can be contingent on other factors, including abiotic conditions that influence a community’s susceptibility to change. We do not know whether the interactions we observed will affect the resilience of these communities: that is, their ability to return to their pre-fire state. Drivers of succession include: site conditions and history, species availability, and species performance (Meiners et al. 2015 ). Here, we show evidence for interactions between a natural ‘pulse’ disturbance—wildfire, which has altered site conditions—and an anthropogenic ‘press’ disturbance—recreational roads and trails, which primarily alter species availability (Smart et al. 2014 ). As Meiners et al. ( 2015 ) note, species availability is likely to be most important in transitional phases of succession, as is the case here, just two to three growing seasons after the wildfire. The effect of trail proximity may diminish over time. The early stages of post-wildfire succession in the Rocky Mountains tend to be unpredictable, whereas later succession proceeds predictably towards a coniferous canopy with an understory of shrubs and shade-tolerant herbs (Lyon and Stickney 1976 ). Over the long term, communities tend to be dominated by species that were present in the community before the fire (Doyle et al. 1998 ; Romme et al. 2011 ; Abella and Fornwalt 2015 ). However, some exotic species can maintain their presence over the long term (Lyon and Stickney 1976 ; Doyle et al. 1998 ). Continued monitoring of these plots will allow us to determine whether communities closer to roads or trails are less likely to return to their pre-fire composition. We did not survey the plots immediately prior to the 2017 wildfire. Therefore, the changes we measured in the burned plots are the sum of changes that occurred since 1994 in addition to the effects of the fire, rather than changes due to the fire alone. However, the changes we observed in the unburned plots—specifically, shifts towards taller, woody species (Lloren 2021 )—suggest that our estimates of the magnitude of the fire effect are likely more conservative than if we had compared post-fire communities to the immediate pre-fire state. We also acknowledge that the magnitude of the effect of distance from trails or roads likely varies with the intensity of trail or road use. Wider trails and roads with frequent vehicle traffic often support larger populations of disturbance-associated and exotic species, which may extend farther from the trail edge (e.g. Potito and Beatty 2005 ; Downing 2020 ; Chisholm and McCune 2024 ). We were not able to include a measure of trail use intensity in addition to trail proximity as a covariate in our models due to lack of quantitative data on usage frequency or intensity. However, we note that the intensity of trail use in WLNP in general tends to decline with increasing elevation, and we did not find interactions between proximity to trails and elevation for any of our response metrics. Managers of protected areas that allow public access have to balance outdoor recreation with the protection of ecological communities. Recreational disturbance has well-documented ecological impacts (e.g. Wells et al. 2012 ; Monz et al. 2021 ; Wedegärtner et al. 2022 ). In addition, our study shows that it can interact with natural disturbance. Whether these interactions are a concern depends on management goals. While the number of species in a community did not show a synergistic response, the relative abundance of disturbance-associated species did. Documenting the prevalence of interactions between anthropogenic and natural disturbances globally, and measuring their longevity, is necessary to predict long-term effects and inform potential management strategies to minimize undesired outcomes."
} | 4,300 |
32525284 | PMC8085915 | pmc | 5,520 | {
"abstract": "Summary Anaerobic digesters produce biogas, a mixture of predominantly CH 4 and CO 2 , which is typically incinerated to recover electrical and/or thermal energy. In a context of circular economy, the CH 4 and CO 2 could be used as chemical feedstock in combination with ammonium from the digestate. Their combination into protein‐rich bacterial, used as animal feed additive, could contribute to the ever growing global demand for nutritive protein sources and improve the overall nitrogen efficiency of the current agro‐ feed/food chain. In this concept, renewable CH 4 and H 2 can serve as carbon‐neutral energy sources for the production of protein‐rich cellular biomass, while assimilating and upgrading recovered ammonia from the digestate. This study evaluated the potential of producing sustainable high‐quality protein additives in a decentralized way through coupling anaerobic digestion and microbial protein production using methanotrophic and hydrogenotrophic bacteria in an on‐farm bioreactor. We show that a practical case digester handling liquid piggery manure, of which the energy content is supplemented for 30% with co‐substrates, provides sufficient biogas to allow the subsequent microbial protein as feed production for about 37% of the number of pigs from which the manure was derived. Overall, producing microbial protein on the farm from available methane and ammonia liberated by anaerobic digesters treating manure appears economically and technically feasible within the current range of market prices existing for high‐quality protein. The case of producing biomethane for grid injection and upgrading the CO 2 with electrolytic hydrogen to microbial protein by means of hydrogen‐oxidizing bacteria was also examined but found less attractive at the current production prices of renewable hydrogen. Our calculations show that this route is only of commercial interest if the protein value equals the value of high‐value protein additives like fishmeal and if the avoided costs for nutrient removal from the digestate are taken into consideration.",
"conclusion": "Conclusion To ensure that both products of anaerobic digestion, that is biogas and digestate, are utilized to their full potential as renewable sources of raw materials, new valorization pipelines need to be implemented into the current AD process schemes. At present, products deriving from digestate achieve a low market value and recovery costs cannot be offset by the revenues. Nutrient recovery processes like ammonia stripping or struvite production, however, might represent the starting point of an entire new biorefinery concept in which microorganisms grow on renewable carbon sources and recovered reactive nitrogen while producing protein‐rich microbial biomass (known as microbial proteins). The already well‐established methane‐oxidizing bacteria represent a promising technology to upgrade low‐value methane and nitrogen to a product than can be used as an alternative high‐quality food/feed protein source, surpassing the conventional agro‐based protein generation. The technology for microbial protein production in the framework of an anaerobic digester facility that turns its self‐produced methane with recovered ammonia into proteins is of micro‐economic interest, as this pipeline offers a better return on investment than burning biogas and the use of digestate products for land application. The MP revenues can turn a manure processing facility in a cost neutral (or even profit gaining) installation. For the NH 3 ‐H 2 case, calculations show that this route is of interest if the protein value equals the value of high‐quality agro‐based proteins like fishmeal and if the avoided costs for N removal are taken into consideration. As hydrogen production costs are expected to decrease further, the process will be of higher economic relevance in the future and will, thus, enable maximal utilization of carbon processed through anaerobic digesters. Overall, this study presents an interesting approach to partially shortcut the nitrogen cycle at the scale of a digester facility by direct introduction of MP as feed for animals.",
"introduction": "Introduction Anaerobic digestion (AD) is a mature and energy‐efficient technology, able to convert a broad variety of organic (waste) streams into biogas, a renewable source of methane (CH 4 ), and digestate, a nutrient‐rich organic residue (Appels et al ., 2011 ). The AD process has successfully been put forward as the first commercial ‘waste‐to‐energy’ bioreactor technology dealing with low‐value carbon‐rich waste streams, like manure, and is often envisaged as one of the key low‐carbon technologies in the decarbonized energy mix of the future (Kampman et al ., 2016 ). Today, 70 % of the more than 17 000 AD plants in the European Union are running on agricultural streams, with in many cases manure as the primary feedstock, and often a second substrate, for example grass or corn (typical on‐farm feedstock), or various off‐site feedstock, such as slaughterhouse waste, fats and organic household waste, to increase the biogas production and operational stability of the process (EBA, 2017 ). Biogas is typically valorized (and incentivized) through the production of electricity in a combined heat and power (CHP) unit, but recently, a study pointed out that the inherently low value of methane as energy carrier can be bypassed if the methane is considered as a renewable C 1 feedstock for the production of bio‐based chemicals from industrial waste CO 2 and grid‐injected biomethane (Verbeeck et al ., 2018 ). The conceptual idea to couple anaerobic digesters to centralized chemical industries via the existing natural gas grid, valorizing renewable methane as a green carbon source in production processes, has opened new utilization options for the biogas industry, potentially even without being reliant on legal support schemes to guarantee a profitable investment (Verbeeck et al ., 2018 ). In addition to the conversion of biomass to biogas, anaerobic digesters are excellent liberators of ammonia and phosphates from the complex feedstock. Manure represents an exquisite mining resource, with typical concentrations ranging between 2.1–6.7 g N L −1 and 0.2–1.6 g P L −1 in piggery waste (Pintucci et al ., 2017 ). At a yearly mass flow of 1.3–1.8 billion tons of livestock manure in the EU alone (Foged et al ., 2012 ), manure represents one of the largest secondary flow of nutrients through agricultural supply chains. Historically, digestate produced from the process has been applied to land as an organic fertilizer or soil conditioner, enabling local nutrient cycling. The application to agricultural land is today often limited, due to legislative restrictions on nutrient application of digestate for agricultural purposes in areas with nutrient surpluses (Coppens et al ., 2016 ). Due to a growing awareness of the economic and environmental costs incurred with the inefficient use of mineral fertilizers in current agricultural plant and meat production, technologies to recover nitrogen and phosphorus from used water have gained more attention in recent years, preventing excessive losses of phosphates and reactive nitrogen species (NH 4 \n + , NO 2 \n − , NO 3 \n − ) into our biosphere (Verstraete et al ., 2016 ). Approaches such as ammonia stripping (Pedizzi et al ., 2017 ), electrochemical ammonium extraction (Desloover et al ., 2012 ; Desloover et al ., 2015 ) and struvite precipitation (Le Corre et al ., 2009 ) are some of the key systems to directly refine and recover nutrients from anaerobic digestate, and produce a marketable product. However, the fertilizer products typically derived from digestate (like (NH 4 ) 2 SO 4 , NH 4 OH and struvite) achieve, at present, a market value not higher than 20% of their intrinsic value, because they are endowed with an irregular composition, limited supply quantities and a poor physical condition. Revenues can only slightly compensate the investment and running costs incurred with the transportation, treatment or upgrading efforts (De Vrieze et al ., 2019 ). Today, ammonia–nitrogen in digestate streams is, thus, mainly destroyed through biological nitrogen removal processes (nitrification–denitrification or partial nitritation–annamox), rather than recovered and reused (Matassa et al ., 2015 ). To ensure more secure and sustainable markets for recovered nutrients, with a lower dependence on land application, novel and higher‐value products need to be created. The integration of technologies to upgrade low‐value raw recovered nutrients to high‐value end‐products will be a key feature of next‐generation AD installations. Recently, innovative approaches implementing bacteria to produce microbial protein (MP), also known as single‐cell protein (SCP), within an AD context have been proposed (Matassa et al ., 2015 ). This MP is a more resource‐efficient and high‐rate protein that is put forward as a viable alternative for the conventional agricultural‐based protein production chain, which is rather inefficient when it comes to the use of reactive nitrogen, and which causes serious environmental damages (Galloway et al ., 2014 ; Steffen et al ., 2015 ). Interestingly, MP can be aerobically produced from renewable raw materials, like NH 3 , CH 4 , CO 2 and H 2, generating a sustainable protein‐rich biomass that can be used as a fertilizer, feed or food additive (Pikaar et al ., 2018a ). Anaerobic digesters are providers of the most important building blocks for MP biosynthesis: carbon, energy (chemical or electrical) and NH 3 are available at considerably large amounts. The idea to utilize biogas as a local source of CH 4 for MP production by methane‐oxidizing (methanotrophic) bacteria (MOB) has gained renewed interest (Pieja et al ., 2017 ; Steinberg et al ., 2017 ), mainly due to the pressing need to find new business models for AD biorefinery concepts, and the successful market entry of two natural gas based MP production facilities using MOB (UniBio A/S and Calysta) (Ritala et al ., 2017 ). Methanotrophs grow on methane as their sole carbon and energy source, directly converting methane into bacterial biomass, while assimilating mineral nitrogen ( i.e . ammonium) into high‐quality protein. The end‐products of this MP production technology have been approved as protein‐rich feed additive, having an amino acid profile close to high‐quality animal protein (Øverland et al ., 2010 ). As an alternative to MOB, autotrophic hydrogen‐oxidizing bacteria have recently received attention as potential production strains, due to their unique metabolic ability to fix CO 2 into new cellular material, using H 2 and O 2 as electron donor and electron acceptor respectively. The HOB can contain up to 75% crude protein (12% N) based on cell dry weight (CDW), which is much higher than the 50, 46 and 15% protein content in yeast, soybean and wheat grain respectively (Matassa et al ., 2016b ). The fact that HOB can be grown on recovered CO 2 , electrolytically produced H 2 and O 2 , and recovered NH 3 can potentially create effective niches for novel application in the context of resource recycling and upgrade, mainly because HOB can exploit the potential of renewable energy generation to capture CO 2 from point sources (Pikaar et al ., 2017 ). Carbon feedstocks under consideration for MP production in an AD context include CH 4 from biogas, CO 2 collected from the process of upgrading biogas to biomethane, or the CO 2 emissions coming from the biogas combustion in an on‐site cogeneration unit. The concept that through solar power, coupled to electrolytic H 2 production, reactive nitrogen in the form of ammonia present in anaerobic digestate can be upgraded to valuable feed protein, thereby shortcutting current protein production processes, opens new options for anaerobic digestion as important driver of an entirely new decentralized economy for sustainable on‐site feed production. The main challenge in this context is the selection of the most cost‐effective MP production pipeline. We determined to which extent different scenarios for on‐site up‐cycling of biogas carbon and recovered mineral nitrogen to microbial protein are economically suitable to be implemented in combination with existing or new AD facilities. To evaluate which MP application could potentially find effective niches for useful application in the AD process, the actual economic performance was calculated, accounting for costs and revenues related to the various production approaches. A model agricultural biogas plant was used as the basis of the calculations. Operational expenditure (OPEX), capital expenditure (CAPEX), potential savings and the revenues from the marketing of the resulting products were determined for the integration of two different MP production routes in a model European AD facility: (i) MOB cultivation on biogas methane and (ii) HOB cultivation on H 2 with CO 2 from biogas upgrading or CO 2 in the flue gases from biogas combustion (Fig. 1 ). Our evaluation presents the features and economic potential of MP production through valorization of the different building block chemicals available at a digester facility, and could enable the selection of the most appropriate technology for decentralized carbon and nutrient recovery from organic feedstocks through MP. Fig. 1 Schematic representation of the two microbial protein production approaches in an anaerobic digestion context. The coloured arrows represent the flows of carbon (C), nitrogen (N), phosphorus (P) and energy (e ‐ ) between the different unit technologies (anaerobic digestion, biogas upgrading, biogas combustion in a combined heat and power unit, and microbial protein via methane‐oxidizing and hydrogen‐oxidizing bacteria).",
"discussion": "Results and discussion The key concern to push towards nutrient recovery rather than removal from digestate is the economic viability of the proposed recovery scenario. This viability is determined by the total production cost of the product and the market value of the final product(s). Estimations of the costs and revenues associated with the different options for biogas and ammonia upgrading to microbial protein are presented here. Biogas as feedstock for microbial protein production by MOB The base case production cost of microbial protein obtained from MOB cultivation is estimated at 1544 € per ton crude protein (expressed in 100% dry weight), with 920 € ton protein −1 as the minimum and 2531 € ton protein −1 as the maximum production costs calculated. A cost breakdown analysis of the total MP production cost is represented in Figure 2 . Costs associated with the production/recovery of the building blocks for MOB growth represent 71% of the total base case MP production cost, with 46% for biogas methane, 20% for recovered ammonia and 5% for O 2 , while 19 % can be attributed to CAPEX and OPEX of the MP production unit (293 € ton MP –1 ) and 10 % to dewatering and drying of the wet product (160 € ton MP −1 ). Considering a market price for feed proteins that typically ranges between 1000 € ton −1 protein for soybean meal (as the reference vegetable protein for livestock, expressed as protein active substance) and 2000 € ton −1 protein for fishmeal (as the reference high‐quality animal protein, expressed as protein active substance), MP can be produced from recovered resources at competitive prices. At present, much still depends on factors relating to the quality demands posed on both the input raw materials (degree of refining) and final product (purity of the product), as well as the downstream processing that is required. The amino acid profile and overall nutritive value of a bacterial meal obtained from MOB growth appeared to be comparable to fishmeal and overall better than soybean meal (Øverland et al ., 2010 ) and, it is likely that the produced microbial protein has a market value higher than or at least equal to fishmeal. Market values of protein sources are variable and highly depend on the macroeconomic variables, such as the global demand for livestock protein and the natural gas price for Haber–Bosch ammonia synthesis. As both the global protein demand and pristine ammonia price are expected to increase in the near future (FAO, 2019 ), MP can become a cost competitive route to produce a substitute for soy and fishmeal for animal feed. Figure 3 shows the impact of a change in MP market price on the profitability of this pathway considering the average MP production cost as well as the minimum and maximum values. The base case, using average‐priced methane and ammonia, suggests that at a protein market price of 1750 € ton −1 , MP can be produced through the CH 4 :NH 3 route with a profit around 200 € ton −1 MP, corresponding with ∼ 33 € ton −1 biogas. Taking into account, the savings from the avoidance of the treatment of the mineral nitrogen present in digestate makes this case much stronger. As the dissipation of reactive nitrogen back to the atmosphere as N 2 by means of nitrification–denitrification comes at a cost of about 3–4 € per kg NH 3 ‐N (Van Hulle et al ., 2010 ) and 200 kg NH 3 ‐N/ton MP is assimilated during MOB cultivation, some 600–800 € per ton MP can be saved on reactive N removal, as a result of the reduced need for nitrogen removal in the digestate. If MP production is evaluated in the context of local nutrient up‐cycling from digestate, almost for the entire range of protein market prices profit can be made (Fig. 3B ). The economic viability of an AD facility that turns its self‐produced methane with recovered ammonia into proteins, thus, seems to be guaranteed, at present costs and revenues, without any legal support. The MP revenues can turn a manure processing facility in a cost neutral (or even profit gaining) installation. With an avoided net cost of 10.95–31.61 € per ton manure processed (De Vrieze et al ., 2019 ) (equal to about 548–1581 € ton −1 protein produced), MP production seems to be a prime candidate technology to offset the costs associated with manure processing. The reason for this economically justified implementation of MP production technology is twofold. First, MP production could strongly increase the value chain of recovered nitrogen from around 1 € kg −1 N for (NH 4 ) 2 SO 4 up to 16.7 € kg −1 N for microbial protein. Second, MP production bypasses the low inherent value of methane when energetically valorized on‐site (in a CHP unit) or off‐site (as biomethane in a power plant or car engine), generating more value per ton biogas. As discussed in our previous study, most biogas projects that produce and sell heat and power can only be economically viable with effective and long‐term financial incentives, compensating for the high production costs of biogas/biomethane compared to their market value (Verbeeck et al ., 2018 ). For the manure digester under study, governments should give a subsidy of at least 40 € per MWh produced electrical power (equal to 145 € per ton biogas) to realize break‐even operation, considering an electricity wholesale price of 40 € MWh e \n −1 . Protein production by using methanotrophic bacteria growing on biogas methane would, thus, offer a new business case for AD plants, without dependency on often unstable financial incentives from governments. Our results clearly indicate that through upgrading of low‐value methane and ammonia to protein‐rich microbial biomass, the economic potential of the otherwise often unprofitable exploitation of an AD plant can be strengthened. Fig. 2 Averaged, minimum and maximum protein production costs using MOB, broken down into components (biogas production, ammonia recovery, oxygen production, dewatering and drying, and the total MP production). Fig. 3 Economic analysis for MP production with CH 4 as sole carbon and energy source. Profit generated (in € ton −1 MP) as a function of the protein market price, not including any financial incentive, for the estimated MP production cost (minimum, average and maximum) without (A) and with avoided costs (B) for nitrogen removal from digestate. The shaded vertical (blue) region represents the variation in current wholesale agro‐based protein price. It should be mentioned that our economic evaluation does not consider savings on externalized costs of MP production, such as a decreased water consumption, a lower land occupation and decreased nitrogen pollution and greenhouse gas emissions. Some of the key global impacts of MP production were recently discussed by Pikaar and co‐workers ( 2018b ). The same trends were observed in a study that evaluated the environmental impact of FeedKind™ protein, a MP produced from natural gas at commercial scale. The report shows that the water foot print of MP is about 20–140 times lower than fishmeal and soybean meal, respectively, and land use is > 100 times lower compared to soy proteins (Cumberlege et al ., 2016 ). Including the externalized environmental costs of the current agro‐production system in the price of protein would result in an allocation of resources that is more efficient for all of society as the MP route is a more rational alternative, able to offer immediate advantages in terms of water and land use (Matassa et al ., 2016a ). As raw materials represent 66 % of the total cost, the major cost decrease can theoretically be achieved at the level of the digester and the ammonia recovery unit. However, both technologies are already very mature, and the cost decreases that could be expected are limited and more related to scale effects, rather than technological advances. In fact biogas represents, at present, already a relatively inexpensive source of renewable methane for on‐site production, as the consumer price of natural gas for industrial end users is around 440 € ton −1 (EU‐28 average price in 2015) (EC, 2016), compared to 326 € ton −1 calculated for the base case in this study. This is mainly due to the high transmission and distribution costs of natural gas (see Chapter 2). In contrast, realizing that the gate cost for pristine ammonia is approximately 575 € ton −1 NH 3 ‐N (Schnitkey, 2018 ), and the use of recovered nitrogen is, at present, 2–6 times more expensive compared to Haber–Bosch derived NH 3 . As 1 ton proteins can be produced at a cost of 1359 € ton −1 protein with freshly synthesized reactive nitrogen (data not shown), nutrient recovery costs, together with avoided removal costs, will be decisive to guarantee the economics of future MP production pipelines. It needs to be recognized that the costs of nitrogen removal via stripping/absorption from highly ammonia‐loaded used water streams (> 4 g l −1 ) are in our base case estimated a factor 2 lower than conventional nitrogen dissipation via nitrification–denitrification. Above 2 g NH 3 –N L −1 , commercial stripping installations are able to recover NH 3 at a cost down to 1000–3000 € ton N –1 (Menkveld and Broeders, 2018 ), while treatment costs of the nitrification–denitrification process are estimated at 3400–4000 € ton −1 NH 3 ‐N (Van Hulle et al ., 2010 ; van Eekert et al ., 2012 ). Considering that stripping could remove up to 90 % of the NH 3 in the liquid fraction, the nitrogen input at the wastewater treatment facility is drastically reduced, and a substantial reduction in costs at these facilities can be achieved. Furthermore, the release of free ammonia by the digester microbiome is so intensive that already in some lab‐scale AD reactors an ammonia stripping unit is directly coupled to the digester as a side loop process to avoid inhibition of the methanogens, due to free NH 3 toxicity. Next to resource recovery, ammonia stripping could, thus, also allow higher biogas production rates (Siegrist et al ., 2005 ; Pedizzi et al ., 2017 ). Partial self‐supply of feed on farm scale Assuming that the full methane flow of 5.16 ton CH 4 per day is converted to microbial biomass at a biomass yield of 0.76 g CDW g −1 CH 4 (60 % crude protein content) (Matassa et al ., 2015 ), this accounts up to a daily protein production potential of 2.4 ton (or 3.9 ton if expressed as cell dry weight). If the microbial biomass is used as additional feed source, and considering that the total protein demand for 1 pig is approximately 45 kg (NRM, 2017 ), yearly, about 19 500 pigs can be raised with the proteins produced from the carbon and nitrogen contained in manure and liberated by anaerobic digestion. Based on an average cycle time of 166 days, a farm of about 8 864 pigs can be supplied with the MP from the resources generated at the digester that is treating manure from about 24 000 pigs (assuming a daily manure production of 5 kg fresh material per pig per day). The use of on‐site generated methane to locally produce bacterial biomass, thus, offers the farmer the opportunity of partial self‐supply of feed (37 % in this specific case), replacing crop‐based protein in animal feed by MP. As the yield of soybean is on average 3.11 tons DM per hectare per year (Langemeier and Lunik, 2015 ), an estimated land footprint of 612 hectares would be required to produce the same amount that can be produced via MP in a very compact engineered bioreactor environment, that is 204 m 3 for the case under study. Assuming a bioreactor height of 30 metres, this comes down to a reactor footprint of just 6.8 m 2 . Besides having a much higher efficiency in land and nutrient use, MP do use water very efficiently, up to 99% reduction in water footprint compared to agricultural‐based production (Cumberlege et al ., 2016 ). Implementing a circular approach at digester scale, with the basic components recovered from waste and upgraded into new valuable microbial biomass rich in proteins, thus, offers the opportunity to process manure in a cost‐efficient way, still generating a product that generates profit. Manure requires co‐digestion to achieve the ideal C/N ratio for MP production For a complete valorization of the ammonia–nitrogen recovered on‐site, methane should be available at a CH 4 :N ratio of 11 kg CH 4 per kg N [(0.76 ton CDW ton −1 CH 4 x 0.12 ton N ton −1 CDW) −1 ]. Considering that for manure the methane yield relative to available nitrogen is limited, that is typically only in the range of 12 to 18 Nm 3 methane per ton FM, while nitrogen content can reach> 6 g N L −1 , the CH 4 :N ratio of manure is too low to allow for a full valorization of the nitrogen present in the digestate. For the digester under study, the defined substrate mixture has a N content of 5.1 kg TKN‐N per ton FM. Accounting for a 75% conversion efficiency of Kjeldahl‐N to NH 4 \n + ‐N, a NH 4 \n + recovery in the liquid digestate of 80% and a 90% NH 3 stripping efficiency, 2.75 kg NH 4 \n + ‐N per ton wet substrate (or 54% of the incoming N load) is extracted from the biomass and, thus, made available for MP production. For the optimal CH 4 :N ratio of 11, this requires a substrate mixture with a methane yield of at least 42 Nm 3 CH 4 ton –1 FM, highlighting the need to amend manure with co‐substrates to improve the biogas production and obtain a CH 4 :N ratio sufficient for MP production with complete N valorization. For manure, maximum MP production without co‐substrate addition is only possible if an additional electron donor is supplied, either by dosing fossil methane from the natural gas grid or by supply of hydrogen gas to achieve nitrogen assimilation via the HOB pathway. The amount of co‐substrate that needs to be mixed with manure is determined by the N content and methane yield of the different substrates. For example, when readily available high strength organic waste streams, like fats or greases with a methane yield up to 800 Nm 3 per ton FM, are used as co‐substrate (Weiland, 2010 ), 6 weight % would suffice to achieve the optimal C:N ratio. Opposite, digesters that are limited in nitrogen will need to blend in high N feedstocks or purchase Haber–Bosch NH 3 to upgrade all available methane Fig. 4 Averaged, minimum and maximum protein production costs using HOB, broken down into components (ammonia recovery, hydrogen production via water electrolysis dewatering and drying, and the total MP production). Resource mining from manure: potential to be import free Coupling renewable methane generation with the full‐scale production of MP using pure or mixed cultures of methane‐oxidizing bacteria might be the most straightforward approach for MP production in the context of nitrogen and carbon valorization from anaerobic digestion, since MOB cultivation on fossil methane is already well established with several industrial demonstration plants in operation (e.g. Feedkind™ by Calysta and UniProtein™ by UniBio A/S). The large amounts of renewable carbon and recovered nitrogen make manure digesters prime candidate facilities to shortcut the current unbalanced nitrogen cycle. Considering that livestock manure accounts for a nitrogen flow through the EU economy of about 6–9 Mton per year (Foged et al ., 2012 ), nitrogen upgrading from anaerobic digestate through MP production processes could produce some 27–40 Mton of microbial biomass, representing 16.2–24.0 Mton crude protein. Currently, the EU imports 20 Mton soybean per year (equal to approximately 9 Mton crude protein) (Schreuder and De Visser, 2015 ). This means that if we could upgrade 38–56% of the nitrogen from livestock manure to protein, the EU can already be import free, highlighting MP are the prime candidate alternative protein source, surpassing soy and animal meat proteins. CO 2 as carbon feedstock for protein production using HOB For the H 2 ‐CO 2 route, the profitability of the biogas utilization scenarios, that is power generation or biomethane injection, is not influenced by the production of MP, and CO 2 is envisaged as an unavoidable product of biogas upgrading/combustion that is fully allocated to the production cost of green electricity or methane (no CO 2 cost was taken into account for MP production). Although CO 2 fixating HOB could yield a potential revenue of ~ 160 € per ton protein in carbon credits (at a carbon allowance price of 50 € ton −1 CO 2 ), no savings are taken into account as CO 2 emissions from a biogas plant are considered CO 2 neutral due to their biogenic origin. The HOB fermenter can be considered as a biogas upgrading unit itself, due to its capacity to fix CO 2 from the biogas. This would eliminate the need for additional technologies, making the biomethane production cheaper. However, these savings are not considered in this assessment as the upgrading potential of a bioreactor is limited. CO 2 from upgrading biogas to biomethane With the daily flow of 9.6 ton CO 2 in the tail gas stream from the upgrading unit, about 2.9 ton crude protein DM can be produced (or 3.9 ton of dry microbial‐based biomass with a crude protein content of 75%), provided that H 2 is supplied at the required feeding ratio. Production costs of protein by HOB are estimated based on the costs to produce hydrogen gas (and oxygen gas) via water electrolysis, recover NH 3 \n via ammonia stripping, operate the fermenter and dewater/dry the final product. The total base case production cost of 1 ton HOB biomass is estimated at 2289 € ton −1 (expressed as dry crude protein) (Fig. 4 ). Minimum and maximum costs are estimated at 1589 and 3781 € ton MP −1 , respectively, under the assumptions for extremes made (Table S2 ). The cost breakdown clearly indicates that hydrogen gas production will be cost decisive. The hydrogen production costs by means of water electrolysis comprise about 67% of the total production costs for H 2 ‐based microbial MP. This estimated base case MP production cost was based on a predicted levelized cost of hydrogen of 2.4 € per kg through water electrolysis using renewable energy at a unit price of 44 € per MWh. As recent bids for electricity produced with large‐scale solar photovoltaics have reached prices as low as 30 $ per MWh generated (Haegel et al ., 2017 ), it is not unthinkable that these costs will further decrease down to < 2 € per kg H 2 . Considering a mean avoided cost of 3.5 € kg −1 N when implementing ammonia recovery instead of nitrogen removal via nitrification–denitrification, each ton MP produced saves about 560 € on wastewater treatment costs, making the economics look differently (break‐even point at 1729 € ton −1 MP, Fig. 5B ). Fig. 5 Economic analysis for MP production with H 2 as energy donor. Profit generated (in € ton −1 MP) as a function of the protein market price, not including any financial incentive, for the estimated MP production cost (minimum, average and maximum) without (A) and with avoided costs (B) for nitrogen removal from digestate. The shaded vertical (blue) region represents the variation in current wholesale agro‐based protein price. Per kg protein produced, cells assimilate about 0.16 kg NH 3 ‐N, leading to a gross daily uptake of 463 kg N, equal to 97.5% of the nitrogen that could be extracted from the liquid digestate via stripping. The C:N of the feedstock mixture is, thus, sufficient for a full conversion of CO 2 ‐C and NH 3 ‐N. Current practice for N recovery is mainly air or steam stripping, which is energy intensive, that is 3.9 to 28.2 kWh kg N −1 depending on the scale of the plant (Gulyas et al ., 2014 ), and requires caustic and acid dosage for stripping and scrubbing respectively. Recently, a proof of concept for NH 3 extraction from urine through electrochemical stripping was put forward as an energy‐efficient way to produce a gas mix that was used for microbial protein production by HOB at less than 10 kWh kg −1 N when H 2 energy is considered. This process, which can be fully driven by renewable power, brings the 4 key building blocks for growth of HOB from 1 process: H 2 and NH 3 from the cathode and O 2 and CO 2 (originating from the urea hydrolysis product HCO 3 \n − ) from the anode (Christiaens et al ., 2017 ). Moreover, via the introduction of a membrane to assist the electrochemical stripping, the risks for cross‐over of microorganisms and trace contaminants into the nitrogen product flow was minimized (Christiaens et al ., 2019 ). It needs to be recognized that due to the lower growth rate of HOB relative to MOB and the lower solubility of H 2 over CH 4 , more effort is needed to achieve a high intensive H 2 based protein production. The low solubility of H 2 and CH 4 is typically overcome by engineering bioreactor systems that are designed with the specific purpose to achieve very high volumetric gas–liquid mass transfer rates through a combination of increased head space pressure, intense mixing and fine bubble sparging. Full‐scale bioreactor systems that rely on CH 4 , CO and H 2 as carbon and/or energy source are currently realized by several companies active in MP (UniBio, Calysta) as well as ethanol production (LanzaTech). CO 2 from CHP unit For the biogas plant under study, combustion of the daily biogas flow generates 23.7 ton of CO 2 . Without limitations on the availability of the other building blocks for HOB growth, about 7.2 ton protein per day can be produced fixing the CO 2 in the combustion gases and assimilating about 1.15 ton NH 3 ‐N per day. With this production capacity, some 26 000 pigs can be fed daily. However, realizing that nitrogen is the limiting factor in this scenario, that is only 475 kg recovered NH 3 ‐N available, a maximum of 3.0 ton protein can be produced daily with the nutrients available on‐site. Additional imports of nitrogen of the order of 675 kg per day are, thus, necessary if all available carbon on‐site is targeted for MP production. The overall viability of the biogas plant was evaluated for this case as well, taking into account costs and revenues associated with CHP production. Total cost following this CHP‐MP route is estimated at 605 € ton −1 biogas. Revenues from selling both electricity at 40 € MWh e \n −1 and protein‐rich biomass at 1750 € ton −1 MP are around 500 € ton −1 biogas, while avoided costs for N removal are about 109 € ton −1 biogas. Revenues and savings from MP could, thus, compensate the financial losses from CHP production, enabling a cost‐efficient treatment of manure and organic waste through anaerobic digestion and MP production. In conclusion, the MP production via the NH 3 ‐H 2 route is only economically viable when production costs are assumed to be minimal and savings through nitrogen upgrading are taken into account. Further technological advances to bring down the cost might offer perspectives to increase the cost competitiveness. Future perspectives Complementary hydrogen and methane platforms More than being self‐excluding, the methane and the hydrogen gas platforms can be seen as complementary, depending on the availability of each resource on‐site and the value/cost of renewable energy. The MP production from a mixture of methane and hydrogen opens the potential to consider a system that can valorize all gaseous carbon available at a biogas plant. This would imply the collaboration of two aerobic populations, MOB and HOB, in one engineered bioreactor environment. For the case in the study, 5.3 ton MP per day can be produced from the total carbon flow if an additional 460 kg N per day is purchased. The fact that MOB are well‐studied microorganisms that have been implemented in full‐scale production reactors is a strong asset of this technology platform. When compared with hydrogen‐oxidizing bacteria, methanotrophs offer the benefit that they can be set to work directly on renewable methane without the need for additional energy input. However, relative to HOB, they possess a lower biomass yield, lower growth rates and lower protein levels (Matassa et al ., 2016b ). There is even a potential for MP production from waste organics, such as carboxylic acids that are generated upon fast anaerobic treatment of organic streams, like slaughterhouse wastewater, although this entails that more attention will be needed for avoiding waste materials crossing over into the product. Emerging as microbial protein are the purple non‐sulfur bacteria that require infrared light and an organic substrate to grow (Hülsen et al ., 2014 ), although these come with the evident drawback of needing a photo‐bioreactor. Recently, the use of protein‐rich biomass as slow‐release organic nitrogen fertilizer has been put forward as a novel outcome of MP. Key benefit of producing fertilizer over the MP‐based production of human food and animal feed lies in the fact that processes conditions for non‐food applications are less strict in terms of hygienization, sterilization, composition and dry solid content of the final product (Pikaar et al ., 2018a ). In this perspective, one could look into the option to directly grow MP in the (liquid) digestate, taking up residual carbon and mineral nitrogen from the medium without the need to recover the nutrients prior to MP cultivation. Realizing that stripping and assimilation are both not 100% efficient, there is still an amount of NH 3 ‐N that ends up in wastewater treatment plant. To be able to operate in a full recovery mode (without polishing in a nitrification–denitrification step), the production of MP for fertilizer applications through the assimilation of the residual reactive nitrogen is an interesting approach. What is needed to drive implementation of MP at biogas plants? The strong incentives decarbonization and renewable energy targets drive the valorization of biogas as a local and renewable energy source, either for on‐site CHP production, or via injection of upgraded biomethane in the natural gas grid. As long as these ‘green’ feed‐in premiums generate positive business cases for biogas projects, it will be hard to convince AD owners to valorize the methane in a different way, and particularly to consider making major capital investments. However, there is a second carbon feedstock available at the facility that is, at present, in many cases not valorized: CO 2 . Either the CO 2 produced by upgrading of biogas to biomethane, or the CO 2 emissions from the combustion of biogas can be exploited as carbon feedstock for protein production using H 2 ‐oxidizing bacteria. It remains questionable whether farmers are willing to up‐cycle carbon and nutrients into edible MP products and replace a part of their crop‐based animal feed protein demand by self‐produced MP. A successful and widespread adoption of the MP biotech platform at biogas facilities is, even under a proven economic profitable plant operation taken into account the revenue from the avoidance of the treatment of the mineral nitrogen, prone to cultural factors in farm management, a lacking official legal recognition and the widespread public acceptance of microbial‐derived products as feed and food additive. Labels that clearly indicate to consumers that meats are produced with a lower environmental footprint could assist in market uptake, similar to labels such as 'organic'. It could even be considered that legislators put a cap on acceptable GHG and mineral nutrient emissions per unit meat protein to stimulate alternative sourcing. In this way, the high externalized environmental costs of the current conventional agricultural‐based supply routes for animal‐based proteins would be made clear to the public, playing in favour of establishing a mindset more open to acceptance of alternative protein sources with a lower environmental impact. However, the market entrance of MP as main protein additive in livestock production and aquaculture is probably less a concern compared to the direct consumption as human food as the product quality and taste of the meat will not be affected, and consumers are not directly in touch with the microbial‐based product. Obviously, safety and quality of the edible MP products must be guaranteed in order to allow a successful adoption of microbial‐based products, for sure when produced from carbon and nutrients recovered from organic waste such as livestock manure. In this light, it is essential to sterilize the MP product and to provide safety barriers between the waste stream and the final product to avoid cross‐over of potential opportunistic pathogens or harmful contaminants to the final product ( e.g . membranes)."
} | 10,633 |
27942435 | PMC5120057 | pmc | 5,521 | {
"abstract": "Background Rice bran is a by-product of the rice milling process and mostly discarded in Japan. Although many studies have shown that microbial fuel cells (MFCs) are able to generate electricity from organic wastes, limited studies have examined MFCs for generating electricity from rice bran. Findings Laboratory-scale single-chamber MFCs were inoculated with paddy field soil and supplied with rice bran for examining electricity generation. Power outputs and microbiome compositions were compared between MFCs containing pure water as the liquid phase (MFC-W) and those containing mineral solution (MFC-M). Polarization analyses showed that both MFCs successfully generated electricity with the maximum power densities of 360 and 520 mW m −2 (based on the projected area of anode) for MFC-W and MFC-M, respectively. Amplicon-sequencing analyses revealed that Trichococcus and Geobacter specifically occurred in anode biofilms in MFC-W and MFC-M, respectively. Conclusions The results suggest that rice bran is a feasible fuel by itself for generating electricity in MFCs."
} | 269 |
37603734 | PMC10469513 | pmc | 5,522 | {
"abstract": "Significance Multispecies microbial communities play an essential role in the health of ecosystems ranging from the ocean to the human gut. A major challenge in microbial ecology is to understand and predict which species can coexist within a community. While a simple empirical rule utilizing only pairwise outcomes successfully predicts multispecies laboratory communities, its mechanistic origin has remained unexplained. Here, we find that the observed simplicity can emerge from competition for resources. Using a generic consumer-resource model, we demonstrate that community assembly of highly complex ecosystems is nevertheless well predicted by pairwise competitions. Our results argue that community assembly can be surprisingly simple despite the potential complexity associated with competition and cross-feeding of many different resources by many different species.",
"discussion": "Discussion In this study, we demonstrated that competition for resources may lead to the experimentally observed simplicity in community assembly. Trio assembly is always predictable from pairwise competitions if a species grows better than another species on every supplied resource. Otherwise, resource competition may violate the assembly rule, but only via two rare and specific scenarios. This predictability holds for communities with large number of species and resources and in the presence of cross-feeding. The simplicity that emerges from our resource competition model is at odds with the model’s complexity. Compared to the Lotka–Volterra model with 6 pairwise interactions for a trio, our resource competition model for multiple resources has more parameters and allows for higher-order interactions in which a third species affects pairwise competition between others. Yet resource competition leads to a more constrained set of outcomes than the Lotka–Volterra model. This is because in the resource competition model, species modify the environment but not traits of competitors, e.g., each species’ ZNGI stays the same regardless of whom it competes against. This invariance of the traits of individual species, such as per-capita per-resource growth rates, over different competitions enables a simple emergent mapping despite the underlying complexity. Geometric analysis provides insights on the simple community assembly. The relative ordering between ZNGIs determines a competitive hierarchy between species, and simple arrangement of ZNGIs leads to simple community assembly. Specifically, when a ZNGI does not cross with another ZNGI, then the trio community always follows the assembly rule. This competitive hierarchy also explains why resource competitions are often transitive and rock-paper-scissors pairwise outcome is impossible. In addition, geometric principles impose a hierarchy between coexistences such that the coexistence of many species requires the coexistence of all pairs between them: A, B, and C coexist as a trio community only if A-B, A-C, and B-C pairs all coexist, but not vice versa ‡ . These geometric hierarchies provide a way to understand the agreement between bottom-up assembly rule prediction and resource competition. Like in laboratory experiments, community assembly under resource competition sometimes deviates from the bottom–up assembly rule prediction. Strikingly, such violations may strengthen the connection between experimentally observed community assembly and resource competition. For example, we find that the most frequently observed violation in the experiment is the most frequently observed violation in simulations ( 34 ). Our resource model analysis also clarifies conditions for the bottom–up prediction’s failure in terms of growth rates and resource supply. Trio community assembly may violate the assembly rule only when all three ZNGI pairs cross. This also implies that metabolic tradeoffs may lead to frequent violations of the assembly rule, and indeed, some cases of metabolic tradeoff result in more violations in our simulation ( SI Appendix, Appendix I.2 ). Relatedly, experiments have found that coevolution or history of coexistence may lead to more frequent violations ( 42 , 58 ). Beyond trio communities, assembly rule failure increases with the number of species, especially when dozens of resources are supplied ( Fig. 4 ). Experiments aided with metabolomics may verify the criteria and further improve the predictive power ( 61 ). While we focused on a simple linear consumption model, there are many other models for ecological interactions ( 62 ). For example, the Lotka–Volterra model allows more community assembly outcomes from the pairwise competitions compared to our resource competition model. While our resource competition model and the assembly rule successfully describe laboratory microcosms, further work will be necessary to determine the rules of community assembly in other systems that may involve various interactions such as toxicity or cross-protection ( 18 , 63 ). In addition, our assumption of uniform relative biomass yields means that all communities in our model have a single stable equilibrium. How our results hold in the presence of alternative stable states and dynamical phases such as limit cycles is a question that remains to be answered ( 64 – 70 ). Interestingly, we find that the assembly rule prediction also works well for trio communities with bistable pairs under three resources ( SI Appendix , Appendix V ). Finally, we acknowledge that linear resource consumption is not the only possible mechanism for resource competition, and different models such as the Monod model, Liebig’s law of the Minimum model, or a diauxic model may be more appropriate in some systems. Interestingly, we found that the Monod model, Liebig’s law of the Minimum model, and the diauxic model all lead to community assembly that is often predicted by the same assembly rule ( 71 ) ( SI Appendix , Fig. S4 and Appendix I ). In addition, different assumptions for resource competition such as fluctuating environment, community under oscillation or chaos instead of a single fixed point, or species directly modifying other competitors’ traits may lead to different bottom–up mappings between pairwise outcomes and community assembly. On the other hand, while we have focused on resource competition, there may be other ecological models that also lead to the experimentally observed bottom-up assembly rule. Future work is required to explore the extent of possible mechanistic origins behind the simplicity of community assembly. Our approach highlights that even when one uses mechanistic models, direct measurement of microscopic parameters is not always necessary for predictive power. This is a significant advantage of the empirical approach that has attracted many ecologists ( 30 , 67 , 72 – 76 ). In the case of resource competition, fully characterizing the metabolism of each microbial species is a formidable experimental challenge due to many complications such as cross-feeding, diauxie, and coutilization of resources. Our results illustrate how mechanistic insights can guide simple experimental predictions while circumventing the full microscopic complexity."
} | 1,795 |
26137472 | PMC4468278 | pmc | 5,524 | {
"abstract": "Biofuels from renewable plant biomass are gaining momentum due to climate change related to atmospheric CO 2 increase. However, the production cost of enzymes required for cellulosic biomass saccharification is a major limiting step in this process. Low-cost production of large amounts of recombinant enzymes by transgenic plants was proposed as an alternative to the conventional microbial based fermentation. A number of studies have shown that chloroplast-based gene expression offers several advantages over nuclear transformation due to efficient transcription and translation systems and high copy number of the transgene. In this study, we expressed in tobacco chloroplasts microbial genes encoding five cellulases and a polygalacturonase. Leaf extracts containing the recombinant enzymes showed the ability to degrade various cell-wall components under different conditions, singly and in combinations. In addition, our group also tested a previously described thermostable xylanase in combination with a cellulase and a polygalacturonase to study the cumulative effect on the depolymerization of a complex plant substrate. Our results demonstrate the feasibility of using transplastomic tobacco leaf extracts to convert cell-wall polysaccharides into reducing sugars, fulfilling a major prerequisite of large scale availability of a variety of cell-wall degrading enzymes for biofuel industry.",
"introduction": "1. Introduction Biofuels are currently obtained from edible vegetable products (sucrose, starch, and triglycerides), but ethical considerations as well as problems of economic sustainability have stimulated the development of second and third generation biofuels derived from nonedible cellulosic biomass and lipogenic unicellular algae [ 1 , 2 ]. The conversion of plant biomass and cultivation waste (Agri-Waste) into bioethanol is considered a sustainable process as it (1) reduces the dependency on fossil fuels like coal- and petroleum-based products, (2) reduces the negative impact on the environment being a carbon-neutral cycle, (3) allows us to obtain secondary byproducts with application in pharmaceutical and biotechnological industries from the residual biomass. The plant cell wall is a complex structure consisting of a mixture of cellulose, hemicelluloses, and lignin, varying from plant to plant. Cellulose is the most diffuse source of reduced carbon in the world, ranking second only to fossil carbon [ 3 ]. In order to convert plant biomass into biofuels, cell-wall macromolecules must be depolymerized to sugar monomers that can be fermented to ethanol or other alcohols with a higher number of carbons through the action of yeast or bacterial strains. Alternatively they can be used as growth substrate for lipogenic microorganisms to obtain lipid to be later transformed in biofuel by different treatments. The current technology adopted to degrade cellulose uses high energy-consuming approaches in order to destroy its stable paracrystalline portion. Several fungi and bacteria synthesize all the enzymes required to degrade cell-wall polysaccharides to simple sugars or oligosaccharides from which they obtain the energy to support their growth. Some of these microorganisms are thermotolerant and possess enzymes active at medium-high temperatures (60°C), reviewed in [ 4 , 5 ]. A particularly important need is the availability of large amounts of suitable enzyme cocktails for the saccharification of huge amounts of cellulosic residues and wastes. Current estimates suggest that about 225 M tons of cellulosic biomass/year are available in EU alone [ 6 ]. The cost of enzymes used for saccharification is one of the three crucial parameters for the economical sustainability of biofuel production [ 7 , 8 ]. A number of bacterial and fungal strains able to depolymerize plant cell walls have been described and characterized [ 9 , 10 ]. However, the expression level of these enzymes by wild-type strains is generally low. The recombinant DNA technology in combination with improved bioreactors has been shown to increase significantly the production of microbial enzymes. Prokaryotic and eukaryotic expression systems based on recombinant DNA approaches have been employed for the production of proteins/enzymes of commercial interest and their advantages and disadvantages evaluated [ 5 , 11 – 14 ]. Enzymes used for industrial applications, among which biofuel production is found, are currently produced via microbial fermentation even if the process requires high investment, production, and maintenance costs. Several studies show that protein/enzyme production by plant molecular farming might offer some advantages over microorganisms, as plants have both eukaryotic (nuclear) and prokaryotic (chloroplast) expression systems [ 15 – 18 ] that can be used singly or in combination. Transgenic plants were shown to be a valuable system for the production of a variety of antibodies, proteins/enzymes, and vaccines [ 19 ]. A large number of genetically modified crops expressing genes encoding insecticidal proteins and enzymes conferring resistance to herbicides are grown all over the world [ 20 ]. However, the production of recombinant proteins/enzymes based on nuclear transformation remained a major limitation as the level of recombinant proteins accumulation is generally low. Conversely, a chloroplast-based expression system offers several advantages with respect to the molecular farming notion. Plastid genome (plastome), being prokaryotic in origin, uses operons for the expression of multiple foreign genes under a single promoter. As the integration of transgene constructs takes place through homologous recombination, there is a unique transformation event without any positional effects, contrary to what is observed in the case of nuclear transformation due to random integration of foreign genes into the nuclear genome. Due to independent plastidial transcription, translation, and protein folding machineries, recombinant genes were generally shown to be expressed in chloroplasts at levels higher than that achieved with nuclear-based expression systems [ 21 ]. In most plant species, among which Nicotiana tabacum , the plastome is inherited maternally thus avoiding transgene dispersion by pollen. Moreover, tobacco, being a nonfood and nonfeed plant, is ideal as a recombinant protein expression system since it does not mix with the food chain, a major issue for regulatory clearances for commercial activities [ 22 ]. The low cultivation cost and ease of up-scale production of transplastomic plants (plants with transformed plastid genome) by simply increasing the cultivation area provide additional advantages. More than a decade ago, Leelavathi et al. [ 15 ] were the first to demonstrate the feasibility of accumulating a bacterial thermostable xylanase, which has several industrial applications including the biofuel industry, using a chloroplast genetic engineering approach. Later, this approach has been used to express a large number of cellulolytic enzymes [ 16 , 23 – 26 ]. Besides pointing to chloroplast transformation as a promising technology for the large scale production of recombinant enzymes, the study of Leelavathi et al. [ 15 ] also showed that the plant produced recombinant xylanase retained all biochemical functions, similarly to the native bacterial one. It is also noteworthy that thermostability of recombinant enzymes is a crucial feature since it allows us to partially overlap the cellulose pretreatment process with its digestion. In the present work we expressed in tobacco chloroplasts five cellulase genes isolated from different microbial organisms and a polygalacturonase gene from Aspergillus niger . Leaf extracts containing the recombinant enzymes were tested for their ability to degrade various cell-wall components under different conditions, singly and in combinations. Also the previously described thermostable xylanase [ 15 ] was used in combination with cellulases and a polygalacturonase to study the cumulative effect on the depolymerization of complex plant biomass. Our results demonstrate the feasibility of converting cell-wall polysaccharides into reducing sugars using a combination of tobacco cell extracts containing enzymes with compatible temperature and pH optima.",
"discussion": "4. Discussion Expression of cell-wall degrading enzymes in plants using a nuclear-based transformation approach is a major challenge as the cellulolytic enzyme(s) can interact with the plant cell wall and thereby interfere with cell growth and plant development [ 31 ]. To prevent potentially harmful consequences caused by recombinant cell-wall degrading enzymes, a number of strategies were evaluated among which targeting to subcellular compartments [ 32 ], rhizosecretion into hydroponic culture medium [ 33 ], and accumulation of a fusion storage proteins in seed oil bodies [ 34 ]. However, all these approaches are characterized by a low expression of recombinant enzymes generally associated with nuclear transformation and expression system. Thus, chloroplast transformation was deemed more suitable to obtain a high level of accumulation of recombinant proteins. Although chloroplast transformation offers the possibility of polycistronic transcription, we chose to express a single enzyme per transplastomic plant for two main reasons. First, single cell-wall degrading enzymes find large industrial application. For instance, cellulases are used in the textile industry (stone-washing), [ 35 ], while xylanases are used for pulp whitening and animal feed processing [ 36 ]. Moreover, the availability of a repertoire of single enzymes allows a better formulation of the most suitable cocktail optimal for each lignocellulosic biomass available (woody biomass, grasses, wastepaper, etc.). Secondly, whenever an enzyme cocktail is required, the availability of single enzymes offers the possibility to plan the timely addition of different enzymes. For instance, the efficiency at which cell-wall cellulose can be digested will be improved if the biomass is pretreated with a polygalacturonidase before the addition of cellulases. In fact, a combination of CelK1 and PGA2 enzymes showed an additive effect on the release of reducing sugars from poplar wood ( Figure 6(b) ). Interestingly, when both CelK1 and PGA2 were used together the amount of reducing sugars released increased by more than twofold those suggesting that the removal of pectin by PGA2 is making cellulose more accessible to CelK1. A third important reason to avoid a simultaneous multiple expression of several genes refers to a possible incompatibility of accumulation of a given protein with chloroplast physiology. In fact, it was observed that plants singly expressing bgl1C , cel6B , cel9A , and xeg74 genes from T. fusca showed severe pleiotropic effects [ 25 ]. Therefore, the interference of a single protein with chloroplast biogenesis and/or stability of the photosynthetic apparatus might hamper the expression of the remaining ones. In the biorefinery process for the production of bioethanol, a pretreatment of plant biomass is required to make cell-wall polymers more accessible to the enzymes required for their deconstruction [ 37 ]. Although energy-consuming, such pretreatment, is necessary to reduce the amount of enzymes, which represent the most relevant cost of the entire process [ 38 ]. It is tempting to speculate that plant molecular farming, due to the ease of large scale production of recombinant enzymes, might effectively contribute to reduce the saccharification cost. In conclusion, this study proves that a combination of three enzymes targeting different components of the plant cell wall but having compatible temperature and pH optima not only improves the saccharification of cellulose present in a complex plant biomass but also reduces the number of steps involved in the downstream processing. Our future endeavor would include identification of factors involved in the low or lack of expression/accumulation of beta-glycosidase ( Bgl ) and also identify Bgl genes from other sources having suitable biochemical properties, in order to improve further the cellulosic biomass saccharification."
} | 3,056 |
39921902 | PMC11842047 | pmc | 5,525 | {
"abstract": "Abstract Summary Constraint-based metabolic models offer a scalable framework to investigate biological systems using optimality principles. Construction and simulation of detailed models that utilize multiple kinds of constraint systems pose a significant coding overhead, complicating implementation of new types of analyses. We present an improved version of the constraint-based metabolic modeling package COBREXA, which utilizes a hierarchical model construction framework that decouples the implemented analysis algorithms into independent, yet re-combinable, building blocks. By removing the need to re-implement modeling components, assembly of complex metabolic models is simplified, which we demonstrate on use-cases of resource-balanced models, and enzyme-constrained flux balance models of interacting bacterial communities. Notably, these models show improved predictive capabilities in both monoculture and community settings. In perspective, the re-usable model-building components in COBREXA 2 provide a sustainable way to handle increasingly complex models in constraint-based modeling. Availability and Implementation COBREXA 2 is available from https://github.com/COBREXA/COBREXA.jl , and from Julia package repositories. COBREXA 2 works on all major operating systems and computer architectures. Documentation is available at https://cobrexa.github.io/COBREXA.jl/ .",
"discussion": "4 Discussion Resource allocation constraints are increasingly used in metabolic modeling, due to their ability to mechanistically describe complex metabolic phenomena. We showcased that even a simplified RBA model recapitulates the experimental findings of E. coli metabolism better compared to an enzyme-constrained model: building on theoretical developments, we included both membrane and cytosolic protein capacity constraints to model the onset of overflow metabolism ( Zhuang et al. 2011 , De Groot et al. 2020 ). Interestingly, both the ec-FBA and sRBA models asserted higher sensitivity of the onset to membrane capacity limitations ( Supplementary Section S2.1 ). In the community setting, our results suggest that enzyme capacity plays an important role in determining steady-state community abundances. However, simulations of a 4-member community of E. coli mutants still showed a substantial compositional variability of near-optimal growth rates ( Supplementary Fig. S5 ), which is contradicted by experimental results ( Mee et al. 2014 ), suggesting existence of additional significant driving forces behind the community dynamics. We expect that substantially more complex models will be required to provide sufficient predictive power for such communities. We demonstrated that COBREXA 2 and the constraint trees framework enable rapid implementation of advanced modeling approaches, like community-scale resource-constrained models. In the future, we hope that the model construction approach introduced by COBREXA 2 will aid further refinement of such models with new kinds of constraint systems, enabling further improvements of the model predictive abilities and thus deeper investigation of the biological mechanisms at the root of complex metabolic phenomena."
} | 794 |
39921902 | PMC11842047 | pmc | 5,525 | {
"abstract": "Abstract Summary Constraint-based metabolic models offer a scalable framework to investigate biological systems using optimality principles. Construction and simulation of detailed models that utilize multiple kinds of constraint systems pose a significant coding overhead, complicating implementation of new types of analyses. We present an improved version of the constraint-based metabolic modeling package COBREXA, which utilizes a hierarchical model construction framework that decouples the implemented analysis algorithms into independent, yet re-combinable, building blocks. By removing the need to re-implement modeling components, assembly of complex metabolic models is simplified, which we demonstrate on use-cases of resource-balanced models, and enzyme-constrained flux balance models of interacting bacterial communities. Notably, these models show improved predictive capabilities in both monoculture and community settings. In perspective, the re-usable model-building components in COBREXA 2 provide a sustainable way to handle increasingly complex models in constraint-based modeling. Availability and Implementation COBREXA 2 is available from https://github.com/COBREXA/COBREXA.jl , and from Julia package repositories. COBREXA 2 works on all major operating systems and computer architectures. Documentation is available at https://cobrexa.github.io/COBREXA.jl/ .",
"discussion": "4 Discussion Resource allocation constraints are increasingly used in metabolic modeling, due to their ability to mechanistically describe complex metabolic phenomena. We showcased that even a simplified RBA model recapitulates the experimental findings of E. coli metabolism better compared to an enzyme-constrained model: building on theoretical developments, we included both membrane and cytosolic protein capacity constraints to model the onset of overflow metabolism ( Zhuang et al. 2011 , De Groot et al. 2020 ). Interestingly, both the ec-FBA and sRBA models asserted higher sensitivity of the onset to membrane capacity limitations ( Supplementary Section S2.1 ). In the community setting, our results suggest that enzyme capacity plays an important role in determining steady-state community abundances. However, simulations of a 4-member community of E. coli mutants still showed a substantial compositional variability of near-optimal growth rates ( Supplementary Fig. S5 ), which is contradicted by experimental results ( Mee et al. 2014 ), suggesting existence of additional significant driving forces behind the community dynamics. We expect that substantially more complex models will be required to provide sufficient predictive power for such communities. We demonstrated that COBREXA 2 and the constraint trees framework enable rapid implementation of advanced modeling approaches, like community-scale resource-constrained models. In the future, we hope that the model construction approach introduced by COBREXA 2 will aid further refinement of such models with new kinds of constraint systems, enabling further improvements of the model predictive abilities and thus deeper investigation of the biological mechanisms at the root of complex metabolic phenomena."
} | 794 |
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