Establishment and metabolic analysis of a model microbial community for understanding trophic and electron accepting interactions of subsurface anaerobic environments

metaGEM: reconstruction of genome scale metabolic models directly from metagenomes

Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here, we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end pipeline enabling metabolic modeling of multi-species communities directly from metagenomes. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from MAGs to community level flux balance analysis (FBA) simulations. To demonstrate the capabilities of metaGEM, we analyzed 483 samples spanning lab culture, human gut, plant-associated, soil, and ocean metagenomes, reconstructing over 14,000 GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to isolated genomes. We demonstrate that metagenomic GEMs capture intraspecies metabolic diversity and identify potential differences in the progression of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, metaGEM enables FBA-ready metabolic model reconstruction directly from metagenomes, provides a resource of metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses.

Metabolic modelling approaches for describing and engineering microbial communities

Microbes do not live in isolation but in microbial communities. The relevance of microbial communities is increasing due to growing awareness of their influence on a huge number of environmental, health and industrial processes. Hence, being able to control and engineer the output of both natural and synthetic communities would be of great interest. However, most of the available methods and biotechnological applications involving microorganisms, both in vivo and in silico, have been developed in the context of isolated microbes. In vivo microbial consortia development is extremely difficult and costly because it implies replicating suitable environments in the wet-lab. Computational approaches are thus a good, cost-effective alternative to study microbial communities, mainly via descriptive modelling, but also via engineering modelling. In this review we provide a detailed compilation of examples of engineered microbial communities and a comprehensive, historical revision of available computational metabolic modelling methods to better understand, and rationally engineer wild and synthetic microbial communities.

Targeted isolation and cultivation of uncultivated bacteria by reverse genomics

Most microorganisms from all taxonomic levels are uncultured. Single-cell genomes and metagenomes continue to increase the known diversity of Bacteria and Archaea, but while ‘omics can be used to infer physiological or ecological roles for species in a community, most of those hypothetical roles remain unvalidated. Here we report an approach to capture specific microorganisms from complex communities into pure cultures using genome-informed antibody engineering. We apply our reverse genomics approach to isolate and sequence single cells and to cultivate three different species-level lineages of human oral Saccharibacteria/TM7. Using our pure cultures we show that all three saccharibacteria species are epibionts of diverse Actinobacteria. We also isolate and cultivate human oral SR1 bacteria, which are members of a lineage of previously uncultured bacteria. Reverse-genomics-enabled cultivation of microorganisms can be applied to any species from any environment and has the potential to unlock the isolation, cultivation and characterization of species from as-yet-uncultured branches of the microbial tree of life.

Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales

Soils contain a tangle of minerals, water, nutrients, gases, plant roots, decaying organic matter, and microorganisms which work together to cycle nutrients and support terrestrial plant growth. Most soil microorganisms live in periodically interconnected communities closely associated with soil aggregates, i.e., small (<2 mm), strongly bound clusters of minerals and organic carbon that persist through mechanical disruptions and wetting events. Their spatial structure is important for biogeochemical cycling, and we cannot reliably predict soil biological activities and variability by studying bulk soils alone. To fully understand the biogeochemical processes at work in soils, it is necessary to understand the micrometer-scale interactions that occur between soil particles and their microbial inhabitants. Here, we review the current state of knowledge regarding soil aggregate microbial communities and identify areas of opportunity to study soil ecosystems at a scale relevant to individual cells. We present a framework for understanding aggregate communities as "microbial villages" that are periodically connected through wetting events, allowing for the transfer of genetic material, metabolites, and viruses. We describe both top-down (whole community) and bottom-up (reductionist) strategies for studying these communities. Understanding this requires combining "model system" approaches (e.g., developing mock community artificial aggregates), field observations of natural communities, and broader study of community interactions to include understudied community members, like viruses. Initial studies suggest that aggregate-based approaches are a critical next step for developing a predictive understanding of how geochemical and community interactions govern microbial community structure and nutrient cycling in soil.

Enumerating all possible biosynthetic pathways in metabolic networks

Exhaustive identification of all possible alternate pathways that exist in metabolic networks can provide valuable insights into cellular metabolism. With the growing number of metabolic reconstructions, there is a need for an efficient method to enumerate pathways, which can also scale well to large metabolic networks, such as those corresponding to microbial communities. We developed MetQuest, an efficient graph-theoretic algorithm to enumerate all possible pathways of a particular size between a given set of source and target molecules. Our algorithm employs a guided breadth-first search to identify all feasible reactions based on the availability of the precursor molecules, followed by a novel dynamic-programming based enumeration, which assembles these reactions into pathways of a specified size producing the target from the source. We demonstrate several interesting applications of our algorithm, ranging from identifying amino acid biosynthesis pathways to identifying the most diverse pathways involved in degradation of complex molecules. We also illustrate the scalability of our algorithm, by studying large graphs such as those corresponding to microbial communities, and identify several metabolic interactions happening therein. MetQuest is available as a Python package, and the source codes can be found at https://github.com/RamanLab/metquest.

Yeast Creates a Niche for Symbiotic Lactic Acid Bacteria through Nitrogen Overflow

Many microorganisms live in communities and depend on metabolites secreted by fellow community members for survival. Yet our knowledge of interspecies metabolic dependencies is limited to few communities with small number of exchanged metabolites, and even less is known about cellular regulation facilitating metabolic exchange. Here we show how yeast enables growth of lactic acid bacteria through endogenous, multi-component, cross-feeding in a readily established community. In nitrogen-rich environments, Saccharomyces cerevisiae adjusts its metabolism by secreting a pool of metabolites, especially amino acids, and thereby enables survival of Lactobacillus plantarum and Lactococcus lactis. Quantity of the available nitrogen sources and the status of nitrogen catabolite repression pathways jointly modulate this niche creation. We demonstrate how nitrogen overflow by yeast benefits L. plantarum in grape juice, and contributes to emergence of mutualism with L. lactis in a medium with lactose. Our results illustrate how metabolic decisions of an individual species can benefit others.

How mutualisms arise in phytoplankton communities: building eco-evolutionary principles for aquatic microbes

Extensive sampling and metagenomics analyses of plankton communities across all aquatic environments are beginning to provide insights into the ecology of microbial communities. In particular, the importance of metabolic exchanges that provide a foundation for ecological interactions between microorganisms has emerged as a key factor in forging such communities. Here we show how both studies of environmental samples and physiological experimentation in the laboratory with defined microbial co‐cultures are being used to decipher the metabolic and molecular underpinnings of such exchanges. In addition, we explain how metabolic modelling may be used to conduct investigations in reverse, deducing novel molecular exchanges from analysis of large‐scale data sets, which can identify persistently co‐occurring species. Finally, we consider how knowledge of microbial community ecology can be built into evolutionary theories tailored to these species’ unique lifestyles. We propose a novel model for the evolution of metabolic auxotrophy in microorganisms that arises as a result of symbiosis, termed the Foraging‐to‐Farming hypothesis. The model has testable predictions, fits several known examples of mutualism in the aquatic world, and sheds light on how interactions, which cement dependencies within communities of microorganisms, might be initiated.

Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can be used to analyze complex “omics” data and to infer and optimize metabolic processes. Thereby, SMN models are suitable to capitalize on advances in high-throughput molecular and metabolic data generation. SMN models are starting to be applied to describe microbial interactions during wastewater treatment, in-situ bioremediation, microalgae blooms methanogenic fermentation, and bioplastic production. Despite their current challenges, we envisage that SMN models have future potential for the design and development of novel growth media, biochemical pathways and synthetic microbial associations.

Microbial metabolic networks in a complex electrogenic biofilm recovered from a stimulus-induced metatranscriptomics approach

Microorganisms almost always exist as mixed communities in nature. While the significance of microbial community activities is well appreciated, a thorough understanding about how microbial communities respond to environmental perturbations has not yet been achieved. Here we have used a combination of metagenomic, genome binning, and stimulus-induced metatranscriptomic approaches to estimate the metabolic network and stimuli-induced metabolic switches existing in a complex microbial biofilm that was producing electrical current via extracellular electron transfer (EET) to a solid electrode surface. Two stimuli were employed: to increase EET and to stop EET. An analysis of cell activity marker genes after stimuli exposure revealed that only two strains within eleven binned genomes had strong transcriptional responses to increased EET rates, with one responding positively and the other responding negatively. Potential metabolic switches between eleven dominant members were mainly observed for acetate, hydrogen, and ethanol metabolisms. These results have enabled the estimation of a multi-species metabolic network and the associated short-term responses to EET stimuli that induce changes to metabolic flow and cooperative or competitive microbial interactions. This systematic meta-omics approach represents a next step towards understanding complex microbial roles within a community and how community members respond to specific environmental stimuli.

Metabolic dependencies drive species co-occurrence in diverse microbial communities

Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture.

Nutritional stress induces exchange of cell material and energetic coupling between bacterial species

Knowledge of the behaviour of bacterial communities is crucial for understanding biogeochemical cycles and developing environmental biotechnology. Here we demonstrate the formation of an artificial consortium between two anaerobic bacteria, Clostridium acetobutylicum (Gram-positive) and Desulfovibrio vulgaris Hildenborough (Gram-negative, sulfate-reducing) in which physical interactions between the two partners induce emergent properties. Molecular and cellular approaches show that tight cell-cell interactions are associated with an exchange of molecules, including proteins, which allows the growth of one partner (D. vulgaris) in spite of the shortage of nutrients. This physical interaction induces changes in expression of two genes encoding enzymes at the pyruvate crossroads, with concomitant changes in the distribution of metabolic fluxes, and allows a substantial increase in hydrogen production without requiring genetic engineering. The stress induced by the shortage of nutrients of D. vulgaris appears to trigger the interaction.

Scalable production of microbially mediated zinc sulfide nanoparticles and application to functional thin films

A series of semiconducting zinc sulfide (ZnS) nanoparticles were scalably, reproducibly, controllably and economically synthesized with anaerobic metal-reducing Thermoanaerobacter species. These bacteria reduced partially oxidized sulfur sources to sulfides that extracellularly and thermodynamically incorporated with zinc ions to produce sparingly soluble ZnS nanoparticles with ∼5nm crystallites at yields of ∼5gl(-1)month(-1). A predominant sphalerite formation was facilitated by rapid precipitation kinetics, a low cation/anion ratio and a higher zinc concentration compared to background to produce a naturally occurring hexagonal form at the low temperature, and/or water adsorption in aqueous conditions. The sphalerite ZnS nanoparticles exhibited narrow size distribution, high emission intensity and few native defects. Scale-up and emission tunability using copper doping were confirmed spectroscopically. Surface characterization was determined using Fourier transform infrared and X-ray photoelectron spectroscopies, which confirmed amino acid as proteins and bacterial fermentation end products not only maintaining a nano-dimensional average crystallite size, but also increasing aggregation. The application of ZnS nanoparticle ink to a functional thin film was successfully tested for potential future applications.

Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics

The interspecies exchange of metabolites plays a key role in the spatiotemporal dynamics of microbial communities. This raises the question of whether ecosystem-level behavior of structured communities can be predicted using genome-scale metabolic models for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice and applied it to engineered communities. First, we predicted and experimentally confirmed the species ratio to which a two-species mutualistic consortium converges and the equilibrium composition of a newly engineered three-member community. We next identified a specific spatial arrangement of colonies, which gives rise to what we term the "eclipse dilemma": does a competitor placed between a colony and its cross-feeding partner benefit or hurt growth of the original colony? Our experimentally validated finding that the net outcome is beneficial highlights the complex nature of metabolic interactions in microbial communities while at the same time demonstrating their predictability.

Clostridia initiate heavy metal bioremoval in mixed sulfidogenic cultures

Sulfate reducing bacteria (SRB) are widely used for attenuating heavy metal pollution by means of sulfide generation. Due to their low metal tolerance, several SRB species depend on associated bacteria in mixed cultures to cope with metal-induced stress. Yet the identity of the SRB protecting bacteria is largely unknown. We aimed to identify these associated bacteria and their potential role in two highly metal-resistant mixed SRB cultures by comparing bacterial community composition and SRB activity between these cultures and two sensitive ones. The SRB composition in the resistant and sensitive consortia was similar. However, whereas the SRB in the sensitive cultures were strongly inhibited by a mixture of copper, zinc, and iron, no influence of these metals was detected on SRB growth and activity in the resistant cultures. In the latter, a Gram-positive population mostly assigned to Clostridium spp. initiated heavy metal bioremoval based on sulfide generation from components of the medium (mainly sulfite) but not from sulfate. After metal levels were lowered by the Clostridium spp. populations, SRB started sulfate reduction and raised the pH of the medium. The combination of sulfite reducing Clostridium spp. with SRB may improve green technologies for removal of heavy metals.

Scalable economic extracellular synthesis of CdS nanostructured particles by a non-pathogenic thermophile

We report microbially facilitated synthesis of cadmium sulfide (CdS) nanostructured particles (NP) using anaerobic, metal-reducing Thermoanaerobacter sp. The extracellular CdS crystallites were &lt;10 nm in size with yields of ~3 g/L of growth medium/month with demonstrated reproducibility and scalability up to 24 L. During synthesis, Thermoanaerobacter cultures reduced thiosulfate and sulfite salts to H2S, which reacted with Cd2+ cations to produce thermodynamically favored NP in a single step at 65 °C with catalytic nucleation on the cell surfaces. Photoluminescence (PL) analysis of dry CdS NP revealed an exciton-dominated PL peak at 440 nm, having a narrow full width at half maximum of 10 nm. A PL spectrum of CdS NP produced by dissimilatory sulfur reducing bacteria was dominated by features associated with radiative exciton relaxation at the surface. High reproducibility of CdS NP PL features important for scale-up conditions was confirmed from test tubes to 24 L batches at a small fraction of the manufacturing cost associated with conventional inorganic NP production processes.

Nitrogen and sulfur requirements for Clostridium thermocellum and Caldicellulosiruptor bescii on cellulosic substrates in minimal nutrient media

Growth media for cellulolytic Clostridium thermocellum ATCC 27405 and Caldicellulosiruptor bescii bacteria usually contain excess nutrients that would increase costs for consolidated bioprocessing for biofuel production and create a waste stream with nitrogen, sulfur and phosphate. C. thermocellum was grown on crystalline cellulose with varying concentrations of nitrogen and sulfur compounds, and growth rate and ethanol production response curves were determined. Both bacteria assimilated sulfate in the presence of ascorbate reductant, increasing the ratio of oxidized to reduced fermentation products. From these results, a low ionic strength, defined minimal nutrient medium with decreased nitrogen, sulfur, phosphate and vitamin supplements was developed for the fermentation of cellobiose, cellulose and acid-pretreated Populus. Carbon and electron balance calculations indicate the unidentified residual fermentation products must include highly reduced molecules. Both bacterial populations were maintained in co-cultures with substrates containing cellulose and xylan in defined medium with sulfate and basal vitamin supplements.

The potential of bacteria isolated from ruminal contents of seaweed-eating North Ronaldsay sheep to hydrolyse seaweed components and produce methane by anaerobic digestion in vitro

The production of methane biofuel from seaweeds is limited by the hydrolysis of polysaccharides. The rumen microbiota of seaweed-eating North Ronaldsay sheep was studied for polysaccharidic bacterial isolates degrading brown-seaweed polysaccharides. Only nine isolates out of 65 utilized > 90% of the polysaccharide they were isolated on. The nine isolates (eight Prevotella spp. and one Clostridium butyricum) utilized whole Laminaria hyperborea extract and a range of seaweed polysaccharides, including alginate (seven out of nine isolates), laminarin and carboxymethylcellulose (eight out of nine isolates); while two out of nine isolates additionally hydrolysed fucoidan to some extent. Crude enzyme extracts from three of the isolates studied further had diverse glycosidases and polysaccharidase activities; particularly against laminarin and alginate (two isolates were shown to have alginate lyase activity) and notably fucoidan and carageenan (one isolate). In serial culture rumen microbiota hydrolysed a range of seaweed polysaccharides (fucoidan to a notably lesser degree) and homogenates of L. hyperborea, mixed Fucus spp. and Ascophyllum nodosum to produce methane and acetate. The rumen microbiota and isolates represent potential adjunct organisms or enzymes which may improve hydrolysis of seaweed components and thus improve the efficiency of seaweed anaerobic digestion for methane biofuel production.

Parallel changes in the taxonomical structure of bacterial communities exposed to a similar environmental disturbance

Bacterial communities play a central role in ecosystems, by regulating biogeochemical fluxes. Therefore, understanding how multiple functional interactions between species face environmental perturbations is a major concern in conservation biology. Because bacteria can use several strategies, including horizontal gene transfers (HGT), to cope with rapidly changing environmental conditions, potential decoupling between function and taxonomy makes the use of a given species as a general bioindicator problematic. The present work is a first step to characterize the impact of a recent polymetallic gradient over the taxonomical networks of five lacustrine bacterial communities. Given that evolutionary convergence represents one of the best illustration of natural selection, we focused on a system composed of two pairs of impacted and clean lakes in order to test whether similar perturbation exerts a comparable impact on the taxonomical networks of independent bacterial communities. First, we showed that similar environmental stress drove parallel structural changes at the taxonomic level on two independent bacterial communities. Second, we showed that a long-term exposure to contaminant gradients drove significant taxonomic structure changes within three interconnected bacterial communities. Thus, this model lake system is relevant to characterize the strategies, namely acclimation and/or adaptation, of bacterial communities facing environmental perturbations, such as metal contamination.

OptCom: a multi-level optimization framework for the metabolic modeling and analysis of microbial communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models.

Microbial community succession during lactate amendment and electron acceptor limitation reveals a predominance of metal-reducing Pelosinus spp

The determination of the success of in situ bioremediation strategies is complex. By using controlled laboratory conditions, the influence of individual variables, such as U(VI), Cr(VI), and electron donors and acceptors on community structure, dynamics, and the metal-reducing potential can be studied. Triplicate anaerobic, continuous-flow reactors were inoculated with Cr(VI)-contaminated groundwater from the Hanford, WA, 100-H area, amended with lactate, and incubated for 95 days to obtain stable, enriched communities. The reactors were kept anaerobic with N(2) gas (9 ml/min) flushing the headspace and were fed a defined medium amended with 30 mM lactate and 0.05 mM sulfate with a 48-h generation time. The resultant diversity decreased from 63 genera within 12 phyla to 11 bacterial genera (from 3 phyla) and 2 archaeal genera (from 1 phylum). Final communities were dominated by Pelosinus spp. and to a lesser degree, Acetobacterium spp., with low levels of other organisms, including methanogens. Four new strains of Pelosinus were isolated, with 3 strains being capable of Cr(VI) reduction while one also reduced U(VI). Under limited sulfate, it appeared that the sulfate reducers, including Desulfovibrio spp., were outcompeted. These results suggest that during times of electron acceptor limitation in situ, organisms such as Pelosinus spp. may outcompete the more-well-studied organisms while maintaining overall metal reduction rates and extents. Finally, lab-scale simulations can test new strategies on a smaller scale while facilitating community member isolation, so that a deeper understanding of community metabolism can be revealed.

Systems analysis of microbial adaptations to simultaneous stresses

Microbes live in multi-factorial environments and have evolved under a variety of concurrent stresses including resource scarcity. Their metabolic organization is a reflection of their evolutionary histories and, in spite of decades of research, there is still a need for improved theoretical tools to explain fundamental aspects of microbial physiology. Using ecological and economic concepts, this chapter explores a resource-ratio based theory to elucidate microbial strategies for extracting and channeling mass and energy. The theory assumes cellular fitness is maximized by allocating scarce resources in appropriate proportions to multiple stress responses. Presented case studies deconstruct metabolic networks into a complete set of minimal biochemical pathways known as elementary flux modes. An economic analysis of the elementary flux modes tabulates enzyme atomic synthesis requirements from amino acid sequences and pathway operating costs from catabolic efficiencies, permitting characterization of inherent tradeoffs between resource investment and phenotype. A set of elementary flux modes with competitive tradeoffs properties can be mathematically projected onto experimental fluxomics datasets to decompose measured phenotypes into metabolic adaptations, interpreted as cellular responses proportional to the experienced culturing stresses. The resource-ratio based method describes the experimental phenotypes with greater accuracy than other contemporary approaches and further analysis suggests the results are both statistically and biologically significant. The insight into metabolic network design principles including tradeoffs associated with concurrent stress adaptation provides a foundation for interpreting physiology as well as for rational control and engineering of medically, environmentally, and industrially relevant microbes.

How sulphate-reducing microorganisms cope with stress: lessons from systems biology

Sulphate-reducing microorganisms (SRMs) are a phylogenetically diverse group of anaerobes encompassing distinct physiologies with a broad ecological distribution. As SRMs have important roles in the biogeochemical cycling of carbon, nitrogen, sulphur and various metals, an understanding of how these organisms respond to environmental stresses is of fundamental and practical importance. In this Review, we highlight recent applications of systems biology tools in studying the stress responses of SRMs, particularly Desulfovibrio spp., at the cell, population, community and ecosystem levels. The syntrophic lifestyle of SRMs is also discussed, with a focus on system-level analyses of adaptive mechanisms. Such information is important for understanding the microbiology of the global sulphur cycle and for developing biotechnological applications of SRMs for environmental remediation, energy production, biocorrosion control, wastewater treatment and mineral recovery.

A bacterial consortium isolated from an Icelandic fumarole displays exceptionally high levels of sulfate reduction and metals resistance

The soils of three fumaroles and one mining site, all with high metal content, were surveyed for the presence of metal-resistant sulfate-reducing bacteria and their potential application in the bioremediation of acid mine drainages. By means of selective soil enrichments a bacterial consortium was isolated from an Icelandic fumarole that displayed very high sulfate reduction in the presence of a mixture of 0.75 g/L of Fe, 0.20 g/L of Zn and 0.080 g/L of Cu. Under these conditions the bacterial consortium reduced 91% of the added 3.9 g/L of sulfate after 28 days, precipitating 100% of the Fe, 96% of the Zn and 97% of the Cu during the same time. Both total bacterial numbers and numbers of culturable sulfate-reducing bacteria remained unchanged when grown in media containing metals, suggesting low or absent inhibitory effects of the metals on the bacterial consortium. PCR-DGGE profiles of the sulfate reducing bacterial communities obtained from the Icelandic fumarole sample showed that bacterial diversity decreased significantly after metal addition: from the original 12 ribotypes only two were detected in the metal-tolerant culture. Phylogenetic analysis of 16S ribosomal RNA gene sequences revealed that these two ribotypes were affiliated with the genera Clostridium and Desulfovibrio, with C. subterminale, C. pascui, C. mesophilum and C. peptidovorans and D. desulfuricans identified as their closest relatives.

Geobacter: the microbe electric's physiology, ecology, and practical applications

Geobacter species specialize in making electrical contacts with extracellular electron acceptors and other organisms. This permits Geobacter species to fill important niches in a diversity of anaerobic environments. Geobacter species appear to be the primary agents for coupling the oxidation of organic compounds to the reduction of insoluble Fe(III) and Mn(IV) oxides in many soils and sediments, a process of global biogeochemical significance. Some Geobacter species can anaerobically oxidize aromatic hydrocarbons and play an important role in aromatic hydrocarbon removal from contaminated aquifers. The ability of Geobacter species to reductively precipitate uranium and related contaminants has led to the development of bioremediation strategies for contaminated environments. Geobacter species produce higher current densities than any other known organism in microbial fuel cells and are common colonizers of electrodes harvesting electricity from organic wastes and aquatic sediments. Direct interspecies electron exchange between Geobacter species and syntrophic partners appears to be an important process in anaerobic wastewater digesters. Functional and comparative genomic studies have begun to reveal important aspects of Geobacter physiology and regulation, but much remains unexplored. Quantifying key gene transcripts and proteins of subsurface Geobacter communities has proven to be a powerful approach to diagnose the in situ physiological status of Geobacter species during groundwater bioremediation. The growth and activity of Geobacter species in the subsurface and their biogeochemical impact under different environmental conditions can be predicted with a systems biology approach in which genome-scale metabolic models are coupled with appropriate physical/chemical models. The proficiency of Geobacter species in transferring electrons to insoluble minerals, electrodes, and possibly other microorganisms can be attributed to their unique "microbial nanowires," pili that conduct electrons along their length with metallic-like conductivity. Surprisingly, the abundant c-type cytochromes of Geobacter species do not contribute to this long-range electron transport, but cytochromes are important for making the terminal electrical connections with Fe(III) oxides and electrodes and also function as capacitors, storing charge to permit continued respiration when extracellular electron acceptors are temporarily unavailable. The high conductivity of Geobacter pili and biofilms and the ability of biofilms to function as supercapacitors are novel properties that might contribute to the field of bioelectronics. The study of Geobacter species has revealed a remarkable number of microbial physiological properties that had not previously been described in any microorganism. Further investigation of these environmentally relevant and physiologically unique organisms is warranted.