Rules of engagement: interspecies interactions that regulate microbial communities

Competition for ammonia influences the structure of chemotrophic communities in geothermal springs

Source waters sampled from Perpetual Spouter hot spring (pH 7.03, 86.4°C), Yellowstone National Park, WY, have low concentrations of total ammonia, nitrite, and nitrate, suggesting nitrogen (N) limitation and/or tight coupling of N cycling processes. Dominant small-subunit rRNA sequences in Perpetual Spouter source sediments are closely affiliated with the ammonia-oxidizing archaeon "Candidatus Nitrosocaldus yellowstonii" and the putatively nitrogen-fixing (diazotrophic) bacterium Thermocrinis albus, respectively, suggesting that these populations may interact at the level of the bioavailable N pool, specifically, ammonia. This hypothesis was evaluated by using a combination of geochemical, physiological, and transcriptomic analyses of sediment microcosms. Amendment of microcosms with allylthiourea, an inhibitor of ammonia oxidation, decreased rates of acetylene reduction (a proxy for N2 fixation) and nitrite production (a proxy for ammonia oxidation) and decreased transcript levels of structural genes involved in both nitrogen fixation (nifH) and ammonia oxidation (amoA). In contrast, amendment of microcosms with ammonia stimulated nitrite production and increased amoA transcript levels while it suppressed rates of acetylene reduction and decreased nifH transcript levels. Sequencing of amplified nifH and amoA transcripts from native sediments, as well as microcosms, at 2 and 4 h postamendment, indicates that the dominant and responsive populations involved in ammonia oxidation and N2 fixation are closely affiliated with Ca. Nitrosocaldus yellowstonii and T. albus, respectively. Collectively, these results suggest that ammonia-oxidizing archaea, such as Ca. Nitrosocaldus yellowstonii, have an apparent affinity for ammonia that is higher than that of the diazotrophs present in this ecosystem. Depletion of the bioavailable N pool through the activity of ammonia-oxidizing archaea likely represents a strong selective pressure for the inclusion of organisms capable of nitrogen fixation in geothermal communities. These observations help to explain the strong pattern in the codistribution of ammonia-oxidizing archaea and diazotrophs in circumneutral-to-alkaline geothermal springs.

Microbial diversity and structure are drivers of the biological barrier effect against Listeria monocytogenes in soil

Understanding the ecology of pathogenic organisms is important in order to monitor their transmission in the environment and the related health hazards. We investigated the relationship between soil microbial diversity and the barrier effect against Listeria monocytogenes invasion. By using a dilution-to-extinction approach, we analysed the consequence of eroding microbial diversity on L. monocytogenes population dynamics under standardised conditions of abiotic parameters and microbial abundance in soil microcosms. We demonstrated that highly diverse soil microbial communities act as a biological barrier against L. monocytogenes invasion and that phylogenetic composition of the community also has to be considered. This suggests that erosion of diversity may have damaging effects regarding circulation of pathogenic microorganisms in the environment.

Resource availability and competition shape the evolution of survival and growth ability in a bacterial community

Resource availability is one of the main factors determining the ecological dynamics of populations or species. Fluctuations in resource availability can increase or decrease the intensity of resource competition. Resource availability and competition can also cause evolutionary changes in life-history traits. We studied how community structure and resource fluctuations affect the evolution of fitness related traits using a two-species bacterial model system. Replicated populations of Serratia marcescens (copiotroph) and Novosphingobium capsulatum (oligotroph) were reared alone or together in environments with intergenerational, pulsed resource renewal. The comparison of ancestral and evolved bacterial clones with 1 or 13 weeks history in pulsed resource environment revealed species-specific changes in life-history traits. Co-evolution with S. marcescens caused N. capsulatum clones to grow faster. The evolved S. marcescens clones had higher survival and slower growth rate then their ancestor. The survival increased in all treatments after one week, and thereafter continued to increase only in the S. marcescens monocultures that experienced large resource pulses. Though adaptive radiation is often reported in evolution studies with bacteria, clonal variation increased only in N. capsulatum growth rate. Our results suggest that S. marcescens adapted to the resource renewal cycle whereas N. capsulatum was more affected by the interspecific competition. Our results exemplify species-specific evolutionary response to both competition and environmental variation.

The genotypic view of social interactions in microbial communities

Dense and diverse microbial communities are found in many environments. Disentangling the social interactions between strains and species is central to understanding microbes and how they respond to perturbations. However, the study of social evolution in microbes tends to focus on single species. Here, we broaden this perspective and review evolutionary and ecological theory relevant to microbial interactions across all phylogenetic scales. Despite increased complexity, we reduce the theory to a simple null model that we call the genotypic view. This states that cooperation will occur when cells are surrounded by identical genotypes at the loci that drive interactions, with genetic identity coming from recent clonal growth or horizontal gene transfer (HGT). In contrast, because cooperation is only expected to evolve between different genotypes under restrictive ecological conditions, different genotypes will typically compete. Competition between two genotypes includes mutual harm but, importantly, also many interactions that are beneficial to one of the two genotypes, such as predation. The literature offers support for the genotypic view with relatively few examples of cooperation between genotypes. However, the study of microbial interactions is still at an early stage. We outline the logic and methods that help to better evaluate our perspective and move us toward rationally engineering microbial communities to our own advantage.

Towards a predictive systems-level model of the human microbiome: progress, challenges, and opportunities

The human microbiome represents a vastly complex ecosystem that is tightly linked to our development, physiology, and health. Our increased capacity to generate multiple channels of omic data from this system, brought about by recent advances in high throughput molecular technologies, calls for the development of systems-level methods and models that take into account not only the composition of genes and species in a microbiome but also the interactions between these components. Such models should aim to study the microbiome as a community of species whose metabolisms are tightly intertwined with each other and with that of the host, and should be developed with a view towards an integrated, comprehensive, and predictive modeling framework. Here, we review recent work specifically in metabolic modeling of the human microbiome, highlighting both novel methodologies and pressing challenges. We discuss various modeling approaches that lay the foundation for a full-scale predictive model, focusing on models of interactions between microbial species, metagenome-scale models of community-level metabolism, and models of the interaction between the microbiome and the host. Continued development of such models and of their integration into a multi-scale model of the microbiome will lead to a deeper mechanistic understanding of how variation in the microbiome impacts the host, and will promote the discovery of clinically relevant and ecologically relevant insights from the rich trove of data now available.

Functional microbial diversity explains groundwater chemistry in a pristine aquifer

BACKGROUND

The diverse microbial populations that inhabit pristine aquifers are known to catalyze critical in situ biogeochemical reactions, yet little is known about how the structure and diversity of this subsurface community correlates with and impacts upon groundwater chemistry. Herein we examine 8,786 bacterial and 8,166 archaeal 16S rRNA gene sequences from an array of monitoring wells in the Mahomet aquifer of east-central Illinois. Using multivariate statistical analyses we provide a comparative analysis of the relationship between groundwater chemistry and the microbial communities attached to aquifer sediment along with those suspended in groundwater.

RESULTS

Statistical analyses of 16S rRNA gene sequences showed a clear distinction between attached and suspended communities; with iron-reducing bacteria far more abundant in attached samples than suspended, while archaeal clones related to groups associated with anaerobic methane oxidation and deep subsurface gold mines (ANME-2D and SAGMEG-1, respectively) distinguished the suspended community from the attached. Within the attached bacterial community, cloned sequences most closely related to the sulfate-reducing Desulfobacter and Desulfobulbus genera represented 20% of the bacterial community in wells where the concentration of sulfate in groundwater was high (> 0.2 mM), compared to only 3% in wells with less sulfate. Sequences related to the genus Geobacter, a genus containing ferric-iron reducers, were of nearly equal abundance (15%) to the sulfate reducers under high sulfate conditions, however their relative abundance increased to 34% when sulfate concentrations were < 0.03 mM. Also, in areas where sulfate concentrations were <0.03 mM, archaeal 16S rRNA gene sequences similar to those found in methanogens such as Methanosarcina and Methanosaeta comprised 73-80% of the community, and dissolved CH4 ranged between 220 and 1240 μM in these groundwaters. In contrast, methanogens (and their product, CH4) were nearly absent in samples collected from groundwater samples with > 0.2 mM sulfate. In the suspended fraction of wells where the concentration of sulfate was between 0.03 and 0.2 mM, the archaeal community was dominated by sequences most closely related to the ANME-2D, a group of archaea known for anaerobically oxidizing methane. Based on available energy (∆GA) estimations, results varied little for both sulfate reduction and methanogenesis throughout all wells studied, but could favor anaerobic oxidation of methane (AOM) in wells containing minimal sulfate and dihydrogen, suggesting AOM coupled with H2-oxidizing organisms such as sulfate or iron reducers could be an important pathway occurring in the Mahomet aquifer.

CONCLUSIONS

Overall, the results show several distinct factors control the composition of microbial communities in the Mahomet aquifer. Bacteria that respire insoluble substrates such as iron oxides, i.e. Geobacter, comprise a greater abundance of the attached community than the suspended regardless of groundwater chemistry. Differences in community structure driven by the concentration of sulfate point to a clear link between the availability of substrate and the abundance of certain functional groups, particularly iron reducers, sulfate reducers, methanogens, and methanotrophs. Integrating both geochemical and microbiological observations suggest that the relationships between these functional groups could be driven in part by mutualism, especially between ferric-iron and sulfate reducers.

Colonization resistance and microbial ecophysiology: using gnotobiotic mouse models and single-cell technology to explore the intestinal jungle

The highly diverse intestinal microbiota forms a structured community engaged in constant communication with itself and its host and is characterized by extensive ecological interactions. A key benefit that the microbiota affords its host is its ability to protect against infections in a process termed colonization resistance (CR), which remains insufficiently understood. In this review, we connect basic concepts of CR with new insights from recent years and highlight key technological advances in the field of microbial ecology. We present a selection of statistical and bioinformatics tools used to generate hypotheses about synergistic and antagonistic interactions in microbial ecosystems from metagenomic datasets. We emphasize the importance of experimentally testing these hypotheses and discuss the value of gnotobiotic mouse models for investigating specific aspects related to microbiota-host-pathogen interactions in a well-defined experimental system. We further introduce new developments in the area of single-cell analysis using fluorescence in situ hybridization in combination with metabolic stable isotope labeling technologies for studying the in vivo activities of complex community members. These approaches promise to yield novel insights into the mechanisms of CR and intestinal ecophysiology in general, and give researchers the means to experimentally test hypotheses in vivo at varying levels of biological and ecological complexity.

Microbial competition in polar soils: a review of an understudied but potentially important control on productivity

Intermicrobial competition is known to occur in many natural environments, and can result from direct conflict between organisms, or from differential rates of growth, colonization, and/or nutrient acquisition. It has been difficult to extensively examine intermicrobial competition in situ, but these interactions may play an important role in the regulation of the many biogeochemical processes that are tied to microbial communities in polar soils. A greater understanding of how competition influences productivity will improve projections of gas and nutrient flux as the poles warm, may provide biotechnological opportunities for increasing the degradation of contaminants in polar soil, and will help to predict changes in communities of higher organisms, such as plants.

Competition sensing: the social side of bacterial stress responses

The field of ecology has long recognized two types of competition: exploitative competition, which occurs indirectly through resource consumption, and interference competition, whereby one individual directly harms another. Here, we argue that these two forms of competition have played a dominant role in the evolution of bacterial regulatory networks. In particular, we argue that several of the major bacterial stress responses detect ecological competition by sensing nutrient limitation (exploitative competition) or direct cell damage (interference competition). We call this competition sensing: a physiological response that detects harm caused by other cells and that evolved, at least in part, for that purpose. A key prediction of our hypothesis is that bacteria will counter-attack when they sense ecological competition but not when they sense abiotic stress. In support of this hypothesis, we show that bacteriocins and antibiotics are frequently upregulated by stress responses to nutrient limitation and cell damage but very rarely upregulated by stress responses to heat or osmotic stress, which typically are not competition related. We argue that stress responses, in combination with the various mechanisms that sense secretions, enable bacteria to infer the presence of ecological competition and navigate the 'microbe-kill-microbe' world in which they live.

Microbial life in the phyllosphere

Our knowledge of the microbiology of the phyllosphere, or the aerial parts of plants, has historically lagged behind our knowledge of the microbiology of the rhizosphere, or the below-ground habitat of plants, particularly with respect to fundamental questions such as which microorganisms are present and what they do there. In recent years, however, this has begun to change. Cultivation-independent studies have revealed that a few bacterial phyla predominate in the phyllosphere of different plants and that plant factors are involved in shaping these phyllosphere communities, which feature specific adaptations and exhibit multipartite relationships both with host plants and among community members. Insights into the underlying structural principles of indigenous microbial phyllosphere populations will help us to develop a deeper understanding of the phyllosphere microbiota and will have applications in the promotion of plant growth and plant protection.

The spectral networks paradigm in high throughput mass spectrometry

High-throughput proteomics is made possible by a combination of modern mass spectrometry instruments capable of generating many millions of tandem mass (MS(2)) spectra on a daily basis and the increasingly sophisticated associated software for their automated identification. Despite the growing accumulation of collections of identified spectra and the regular generation of MS(2) data from related peptides, the mainstream approach for peptide identification is still the nearly two decades old approach of matching one MS(2) spectrum at a time against a database of protein sequences. Moreover, database search tools overwhelmingly continue to require that users guess in advance a small set of 4-6 post-translational modifications that may be present in their data in order to avoid incurring substantial false positive and negative rates. The spectral networks paradigm for analysis of MS(2) spectra differs from the mainstream database search paradigm in three fundamental ways. First, spectral networks are based on matching spectra against other spectra instead of against protein sequences. Second, spectral networks find spectra from related peptides even before considering their possible identifications. Third, spectral networks determine consensus identifications from sets of spectra from related peptides instead of separately attempting to identify one spectrum at a time. Even though spectral networks algorithms are still in their infancy, they have already delivered the longest and most accurate de novo sequences to date, revealed a new route for the discovery of unexpected post-translational modifications and highly-modified peptides, enabled automated sequencing of cyclic non-ribosomal peptides with unknown amino acids and are now defining a novel approach for mapping the entire molecular output of biological systems that is suitable for analysis with tandem mass spectrometry. Here we review the current state of spectral networks algorithms and discuss possible future directions for automated interpretation of spectra from any class of molecules.

Marine microbial symbiosis heats up: the phylogenetic and functional response of a sponge holobiont to thermal stress

Large-scale mortality of marine invertebrates is a major global concern for ocean ecosystems and many sessile, reef-building animals, such as sponges and corals, are experiencing significant declines through temperature-induced disease and bleaching. The health and survival of marine invertebrates is often dependent on intimate symbiotic associations with complex microbial communities, yet we have a very limited understanding of the detailed biology and ecology of both the host and the symbiont community in response to environmental stressors, such as elevated seawater temperatures. Here, we use the ecologically important sponge Rhopaloeides odorabile as a model to explore the changes in symbiosis during the development of temperature-induced necrosis. Expression profiling of the sponge host was examined in conjunction with the phylogenetic and functional structure and the expression profile of the symbiont community. Elevated temperature causes an immediate stress response in both the host and symbiont community, including reduced expression of functions that mediate their partnership. Disruption to nutritional interdependence and molecular interactions during early heat stress further destabilizes the holobiont, ultimately leading to the loss of archetypal sponge symbionts and the introduction of new microorganisms that have functional and expression profiles consistent with a scavenging lifestyle, a lack virulence functions and a high growth rate. Previous models have postulated various mechanisms of mortality and disease in marine invertebrates. Our study suggests that interruption of symbiotic interactions is a major determinant for mortality in marine sessile invertebrates. High symbiont specialization and low functional redundancy, thus make these holobionts extremely vulnerable to environmental perturbations, including climate change.

Chapter 12: Human microbiome analysis

Humans are essentially sterile during gestation, but during and after birth, every body surface, including the skin, mouth, and gut, becomes host to an enormous variety of microbes, bacterial, archaeal, fungal, and viral. Under normal circumstances, these microbes help us to digest our food and to maintain our immune systems, but dysfunction of the human microbiota has been linked to conditions ranging from inflammatory bowel disease to antibiotic-resistant infections. Modern high-throughput sequencing and bioinformatic tools provide a powerful means of understanding the contribution of the human microbiome to health and its potential as a target for therapeutic interventions. This chapter will first discuss the historical origins of microbiome studies and methods for determining the ecological diversity of a microbial community. Next, it will introduce shotgun sequencing technologies such as metagenomics and metatranscriptomics, the computational challenges and methods associated with these data, and how they enable microbiome analysis. Finally, it will conclude with examples of the functional genomics of the human microbiome and its influences upon health and disease.

Fundamentals of microbial community resistance and resilience

Microbial communities are at the heart of all ecosystems, and yet microbial community behavior in disturbed environments remains difficult to measure and predict. Understanding the drivers of microbial community stability, including resistance (insensitivity to disturbance) and resilience (the rate of recovery after disturbance) is important for predicting community response to disturbance. Here, we provide an overview of the concepts of stability that are relevant for microbial communities. First, we highlight insights from ecology that are useful for defining and measuring stability. To determine whether general disturbance responses exist for microbial communities, we next examine representative studies from the literature that investigated community responses to press (long-term) and pulse (short-term) disturbances in a variety of habitats. Then we discuss the biological features of individual microorganisms, of microbial populations, and of microbial communities that may govern overall community stability. We conclude with thoughts about the unique insights that systems perspectives – informed by meta-omics data – may provide about microbial community stability.

Microbiota-targeted therapies: an ecological perspective

The connection between disease and the disruption of homeostatic interactions between the host and its microbiota is now well established. Drug developers and clinicians are starting to rely more heavily on therapies that directly target the microbiota and on the ecology of the microbiota to understand the outcomes of these treatments. The effects of those microbiota-targeted therapies that alter community composition range in scale from eliminating individual strains of a single species (for example, with antibacterial conjugate vaccines) to replacing the entire community with a new intact microbiota (for example, by fecal transplantation). Secondary infections linked to antibiotic use provide a cautionary tale of the unintended consequences of perturbing a microbial species network and highlight the need for new narrow-spectrum antibiotics with rapid companion diagnostics. Insights into microbial ecology will also benefit the development of probiotics, whose therapeutic prospects will depend on rigorous clinical testing. Future probiotics may take the form of a consortium of long-term community residents: "a fecal transplant in a capsule." The efficacy of microbiota-targeted therapies will need to be assessed using new diagnostic tools that measure community function rather than composition, including the temporal response of a microbial community to a defined perturbation such as an antibiotic or probiotic.

Competition, not cooperation, dominates interactions among culturable microbial species

Microbial cells secrete numerous enzymes, scavenging molecules, and signals that can promote the growth and survival of other cells around them [1-4]. This observation is consistent with the evolution of cooperation within species [5], and there is now an increasing emphasis on the importance of cooperation between different microbial species [4, 6]. We lack, however, a systematic test of the importance of mutually positive interactions between different species, which is vital for assessing the commonness and importance of cooperative evolution in natural communities. Here, we study the extent of mutually positive interaction among bacterial strains isolated from a common aquatic environment. Using data collected from two independent experiments evaluating community productivity across diversity gradients, we show that (1) in pairwise species combinations, the great majority of interactions are net negative and (2) there is no evidence that strong higher-order positive effects arise when more than two species are mixed together. Our data do not exclude the possibility of positive effects in one direction where one species gains at the expense of another, i.e., predator-prey-like interactions. However, these do not constitute cooperation and our analysis suggests that the typical result of adaptation to other microbial species will be competitive, rather than cooperative, phenotypes.

Recent insights into the diversity, frequency and ecological roles of phenazines in fluorescent Pseudomonas spp

Phenazine compounds represent a large class of bacterial metabolites that are produced by some fluorescent Pseudomonas spp. and a few other bacterial genera. Phenazines were first noted in the scientific literature over 100 years ago, but for a long time were considered to be pigments of uncertain function. Following evidence that phenazines act as virulence factors in the opportunistic human and animal pathogen Pseudomonas aeruginosa and are actively involved in the suppression of plant pathogens, interest in these compounds has broadened to include investigations of their genetics, biosynthesis, activity as electron shuttles, and contribution to the ecology and physiology of the cells that produce them. This minireview highlights some recent and exciting insights into the diversity, frequency and ecological roles of phenazines produced by fluorescent Pseudomonas spp.

Computational systems biology and in silico modeling of the human microbiome

The human microbiome is a complex biological system with numerous interacting components across multiple organizational levels. The assembly, ecology and dynamics of the microbiome and its contribution to the development, physiology and nutrition of the host are clearly affected not only by the set of genes or species in the microbiome but also by the way these genes are linked across numerous pathways and by the interactions between the various species. To date, however, most studies of the human microbiome have focused on characterizing the composition of the microbiome and on comparative analyses, whereas significantly less effort has been directed at elucidating, characterizing and modeling these interactions and on studying the microbiome as a complex, interconnected and cohesive system. Here, specifically, I highlight the pressing need for the development of predictive system-level models and for a system-level understanding of the microbiome, and discuss potential computational frameworks for metagenomic-based modeling of the microbiome at the cellular, ecological and supra-organismal level. I review some preliminary attempts at constructing such models and examine the challenges and hurdles that such modeling efforts face. I also discuss possible future applications and research avenues that such metagenomic systems biology and predictive system-level models may facilitate.

Predicting bacterial community assemblages using an artificial neural network approach

Understanding the interactions between the Earth's microbiome and the physical, chemical and biological environment is a fundamental goal of microbial ecology. We describe a bioclimatic modeling approach that leverages artificial neural networks to predict microbial community structure as a function of environmental parameters and microbial interactions. This method was better at predicting observed community structure than were any of several single-species models that do not incorporate biotic interactions. The model was used to interpolate and extrapolate community structure over time with an average Bray-Curtis similarity of 89.7. Additionally, community structure was extrapolated geographically to create the first microbial map derived from single-point observations. This method can be generalized to the many microbial ecosystems for which detailed taxonomic data are currently being generated, providing an observation-based modeling technique for predicting microbial taxonomic structure in ecological studies.

A road map for the development of community systems (CoSy) biology

Microbial interactions are essential for all global geochemical cycles and have an important role in human health and disease. Although we possess general knowledge about the major processes within a microbial community, we are presently unable to decipher what role individual microorganisms have and how their individual actions influence others in the community. We also have limited knowledge with which to predict the effects of microbial interactions and community composition on the environment and vice versa. In this Opinion article, we describe how community systems (CoSy) biology will enable us to decode these complex relationships and will therefore improve our understanding of individual members of the community and the modes of interactions in which they engage.

Accumulation of the antibiotic phenazine-1-carboxylic acid in the rhizosphere of dryland cereals

Natural antibiotics are thought to function in the defense, fitness, competitiveness, biocontrol activity, communication, and gene regulation of microorganisms. However, the scale and quantitative aspects of antibiotic production in natural settings are poorly understood. We addressed these fundamental questions by assessing the geographic distribution of indigenous phenazine-producing (Phz(+)) Pseudomonas spp. and the accumulation of the broad-spectrum antibiotic phenazine-1-carboxylic acid (PCA) in the rhizosphere of wheat grown in the low-precipitation zone (<350 mm) of the Columbia Plateau and in adjacent, higher-precipitation areas. Plants were collected from 61 commercial wheat fields located within an area of about 22,000 km(2). Phz(+) Pseudomonas spp. were detected in all sampled fields, with mean population sizes ranging from log 3.2 to log 7.1 g(-1) (fresh weight) of roots. Linear regression analysis demonstrated a significant inverse relationship between annual precipitation and the proportion of plants colonized by Phz(+) Pseudomonas spp. (r(2) = 0.36, P = 0.0001). PCA was detected at up to nanomolar concentrations in the rhizosphere of plants from 26 of 29 fields that were selected for antibiotic quantitation. There was a direct relationship between the amount of PCA extracted from the rhizosphere and the population density of Phz(+) pseudomonads (r(2) = 0.46, P = 0.0006). This is the first demonstration of accumulation of significant quantities of a natural antibiotic across a terrestrial ecosystem. Our results strongly suggest that natural antibiotics can transiently accumulate in the plant rhizosphere in amounts sufficient not only for inter- and intraspecies signaling but also for the direct inhibition of sensitive organisms.

Competition between species can stabilize public-goods cooperation within a species

Competition between species is a major ecological force that can drive evolution. Here, we test the effect of this force on the evolution of cooperation within a species. We use sucrose metabolism of budding yeast, Saccharomyces cerevisiae, as a model cooperative system that is subject to social parasitism by cheater strategies. We find that when cocultured with a bacterial competitor, Escherichia coli, the frequency of cooperator phenotypes in yeast populations increases dramatically as compared with isolated yeast populations. Bacterial competition stabilizes cooperation within yeast by limiting the yeast population density and also by depleting the public goods produced by cooperating yeast cells. Both of these changes induced by bacterial competition increase the cooperator frequency because cooperator yeast cells have a small preferential access to the public goods they produce; this preferential access becomes more important when the public good is scarce. Our results indicate that a thorough understanding of species interactions is crucial for explaining the maintenance and evolution of cooperation in nature.

Reverse Ecology: from systems to environments and back

The structure of complex biological systems reflects not only their function but also the environments in which they evolved and are adapted to. Reverse Ecology-an emerging new frontier in Evolutionary Systems Biology-aims to extract this information and to obtain novel insights into an organism's ecology. The Reverse Ecology framework facilitates the translation of high-throughput genomic data into large-scale ecological data, and has the potential to transform ecology into a high-throughput field. In this chapter, we describe some of the pioneering work in Reverse Ecology, demonstrating how system-level analysis of complex biological networks can be used to predict the natural habitats of poorly characterized microbial species, their interactions with other species, and universal patterns governing the adaptation of organisms to their environments. We further present several studies that applied Reverse Ecology to elucidate various aspects of microbial ecology, and lay out exciting future directions and potential future applications in biotechnology, biomedicine, and ecological engineering.

Microbial metabolic exchange--the chemotype-to-phenotype link

The function of microbial interactions is to enable microorganisms to survive by establishing a homeostasis between microbial neighbors and local environments. A microorganism can respond to environmental stimuli using metabolic exchange-the transfer of molecular factors, including small molecules and proteins. Microbial interactions not only influence the survival of the microbes but also have roles in morphological and developmental processes of the organisms themselves and their neighbors. This, in turn, shapes the entire habitat of these organisms. Here we highlight our current understanding of metabolic exchange as well as the emergence of new technologies that are allowing us to eavesdrop on microbial conversations comprising dozens to hundreds of secreted metabolites that control the behavior, survival and differentiation of members of the community. The goal of the rapidly advancing field studying multifactorial metabolic exchange is to devise a microbial 'Rosetta stone' in order to understand the language by which microbial interactions are negotiated and, ultimately, to control the outcome of these conversations.

Beyond the Venn diagram: the hunt for a core microbiome

Discovering a core microbiome is important for understanding the stable, consistent components across complex microbial assemblages. A core is typically defined as the suite of members shared among microbial consortia from similar habitats, and is represented by the overlapping areas of circles in Venn diagrams, in which each circle contains the membership of the sample or habitats being compared. Ecological insight into core microbiomes can be enriched by 'omics approaches that assess gene expression, thereby extending the concept of the core beyond taxonomically defined membership to community function and behaviour. Parameters defined by traditional ecology theory, such as composition, phylogeny, persistence and connectivity, will also create a more complex portrait of the core microbiome and advance understanding of the role of key microorganisms and functions within and across ecosystems.

Coherent dynamics and association networks among lake bacterioplankton taxa

Bacteria have important roles in freshwater food webs and in the cycling of elements in the ecosystem. Yet specific ecological features of individual phylogenetic groups and interactions among these are largely unknown. We used 454 pyrosequencing of 16S rRNA genes to study associations of different bacterioplankton groups to environmental characteristics and their co-occurrence patterns over an annual cycle in a dimictic lake. Clear seasonal succession of the bacterioplankton community was observed. After binning of sequences into previously described and highly resolved phylogenetic groups (tribes), their temporal dynamics revealed extensive synchrony and associations with seasonal events such as ice coverage, ice-off, mixing and phytoplankton blooms. Coupling between closely and distantly related tribes was resolved by time-dependent rank correlations, suggesting ecological coherence that was often dependent on taxonomic relatedness. Association networks with the abundant freshwater Actinobacteria and Proteobacteria in focus revealed complex interdependencies within bacterioplankton communities and contrasting linkages to environmental conditions. Accordingly, unique ecological features can be inferred for each tribe and reveal the natural history of abundant cultured and uncultured freshwater bacteria.

Non-random assembly of bacterioplankton communities in the subtropical north pacific ocean

The exploration of bacterial diversity in the global ocean has revealed new taxa and previously unrecognized metabolic potential; however, our understanding of what regulates this diversity is limited. Using terminal restriction fragment length polymorphism (T-RFLP) data from bacterial small-subunit ribosomal RNA genes we show that, independent of depth and time, a large fraction of bacterioplankton co-occurrence patterns are non-random in the oligotrophic North Pacific subtropical gyre (NPSG). Pair-wise correlations of all identified operational taxonomic units (OTUs) revealed a high degree of significance, with 6.6% of the pair-wise co-occurrences being negatively correlated and 20.7% of them being positive. The most abundant OTUs, putatively identified as Prochlorococcus, SAR11, and SAR116 bacteria, were among the most correlated OTUs. As expected, bacterial community composition lacked statistically significant patterns of seasonality in the mostly stratified water column except in a few depth horizons of the sunlit surface waters, with higher frequency variations in community structure apparently related to populations associated with the deep chlorophyll maximum. Communities were structured vertically into epipelagic, mesopelagic, and bathypelagic populations. Permutation-based statistical analyses of T-RFLP data and their corresponding metadata revealed a broad range of putative environmental drivers controlling bacterioplankton community composition in the NPSG, including concentrations of inorganic nutrients and phytoplankton pigments. Together, our results suggest that deterministic forces such as environmental filtering and interactions among taxa determine bacterioplankton community patterns, and consequently affect ecosystem functions in the NPSG.

Social evolution in multispecies biofilms

Microbial ecology is revealing the vast diversity of strains and species that coexist in many environments, ranging from free-living communities to the symbionts that compose the human microbiome. In parallel, there is growing evidence of the importance of cooperative phenotypes for the growth and behavior of microbial groups. Here we ask: How does the presence of multiple species affect the evolution of cooperative secretions? We use a computer simulation of spatially structured cellular groups that captures key features of their biology and physical environment. When nutrient competition is strong, we find that the addition of new species can inhibit cooperation by eradicating secreting strains before they can become established. When nutrients are abundant and many species mix in one environment, however, our model predicts that secretor strains of any one species will be surrounded by other species. This "social insulation" protects secretors from competition with nonsecretors of the same species and can improve the prospects of within-species cooperation. We also observe constraints on the evolution of mutualistic interactions among species, because it is difficult to find conditions that simultaneously favor both within- and among-species cooperation. Although relatively simple, our model reveals the richness of interactions between the ecology and social evolution of multispecies microbial groups, which can be critical for the evolution of cooperation.

Skin microbiota: microbial community structure and its potential association with health and disease

Skin, the largest human organ, is a complex and dynamic ecosystem inhabited by a multitude of microorganisms. Host demographics and genetics, human behavior, local and regional environmental characteristics, and transmission events may all potentially drive human skin microbiota variability, resulting in an alteration of microbial community structure. This alteration may have important consequences regarding health and disease outcomes among individuals. More specifically, certain diversity patterns of human microbiota may be predictive or diagnostic of disease. The purpose of this review is to briefly describe the skin microbiota, outline the potential determining factors driving its variability, posit the likelihood of an association between the resulting microbial community structure on the skin with disease outcomes among individuals, and finally, to present some challenges and implications for studying the skin microbiota.

How mathematical modelling elucidates signalling in Bacillus subtilis

Appropriate stimulus perception, signal processing and transduction ensure optimal adaptation of bacteria to environmental challenges. In the Gram-positive model bacterium Bacillus subtilis signalling networks and molecular interactions therein are well-studied, making this species a suitable candidate for the application of mathematical modelling. Here, we review systems biology approaches, focusing on chemotaxis, sporulation, σ(B) -dependent general stress response and competence. Processes like chemotaxis and Z-ring assembly depend critically on the subcellular localization of proteins. Environmental response strategies, including sporulation and competence, are characterized by phenotypic heterogeneity in isogenic cultures. The examples of mathematical modelling also include investigations that have demonstrated how operon structure and signalling dynamics are intricately interwoven to establish optimal responses. Our review illustrates that these interdisciplinary approaches offer new insights into the response of B. subtilis to environmental challenges. These case studies reveal modelling as a tool to increase the understanding of complex systems, to help formulating hypotheses and to guide the design of more directed experiments that test predictions.

A coevolutionary framework for managing disease-suppressive soils

This review explores a coevolutionary framework for the study and management of disease-suppressive soil microbial communities. Because antagonistic microbial interactions are especially important to disease suppression, conceptual, theoretical, and empirical work on antagonistic coevolution and its relevance to disease suppression is reviewed. In addition, principles of coevolution are used to develop specific predictions regarding the drivers of disease-suppressive potential in soil microbial communities and to highlight important areas for future research. This approach brings an evolutionary perspective to microbial community management and emphasizes the role of species interactions among indigenous nonpathogenic microbes in developing and maintaining disease-suppressive activities in soil.

Environments that induce synthetic microbial ecosystems

Interactions between microbial species are sometimes mediated by the exchange of small molecules, secreted by one species and metabolized by another. Both one-way (commensal) and two-way (mutualistic) interactions may contribute to complex networks of interdependencies. Understanding these interactions constitutes an open challenge in microbial ecology, with applications ranging from the human microbiome to environmental sustainability. In parallel to natural communities, it is possible to explore interactions in artificial microbial ecosystems, e.g. pairs of genetically engineered mutualistic strains. Here we computationally generate artificial microbial ecosystems without re-engineering the microbes themselves, but rather by predicting their growth on appropriately designed media. We use genome-scale stoichiometric models of metabolism to identify media that can sustain growth for a pair of species, but fail to do so for one or both individual species, thereby inducing putative symbiotic interactions. We first tested our approach on two previously studied mutualistic pairs, and on a pair of highly curated model organisms, showing that our algorithms successfully recapitulate known interactions, robustly predict new ones, and provide novel insight on exchanged molecules. We then applied our method to all possible pairs of seven microbial species, and found that it is always possible to identify putative media that induce commensalism or mutualism. Our analysis also suggests that symbiotic interactions may arise more readily through environmental fluctuations than genetic modifications. We envision that our approach will help generate microbe-microbe interaction maps useful for understanding microbial consortia dynamics and evolution, and for exploring the full potential of natural metabolic pathways for metabolic engineering applications.

From structure to function: the ecology of host-associated microbial communities

In the past several years, we have witnessed an increased interest in understanding the structure and function of the indigenous microbiota that inhabits the human body. It is hoped that this will yield novel insight into the role of these complex microbial communities in human health and disease. What is less appreciated is that this recent activity owes a great deal to the pioneering efforts of microbial ecologists who have been studying communities in non-host-associated environments. Interactions between environmental microbiologists and human microbiota researchers have already contributed to advances in our understanding of the human microbiome. We review the work that has led to these recent advances and illustrate some of the possible future directions for continued collaboration between these groups of researchers. We discuss how the application of ecological theory to the human-associated microbiota can lead us past descriptions of community structure and toward an understanding of the functions of the human microbiota. Such an approach may lead to a shift in the prevention and treatment of human diseases that involves conservation or restoration of the normal community structure and function of the host-associated microbiota.

Ecological distribution and population physiology defined by proteomics in a natural microbial community

An important challenge in microbial ecology is developing methods that simultaneously examine the physiology of organisms at the molecular level and their ecosystem level interactions in complex natural systems. We integrated extensive proteomic, geochemical, and biological information from 28 microbial communities collected from an acid mine drainage environment and representing a range of biofilm development stages and geochemical conditions to evaluate how the physiologies of the dominant and less abundant organisms change along environmental gradients. The initial colonist dominates across all environments, but its proteome changes between two stable states as communities diversify, implying that interspecies interactions affect this organism's metabolism. Its overall physiology is robust to abiotic environmental factors, but strong correlations exist between these factors and certain subsets of proteins, possibly accounting for its wide environmental distribution. Lower abundance populations are patchier in their distribution, and proteomic data indicate that their environmental niches may be constrained by specific sets of abiotic environmental factors. This research establishes an effective strategy to investigate ecological relationships between microbial physiology and the environment for whole communities in situ.

Evolution: spatial scaling of microbial interactions

Intraspecific incompatibility in the soil bacterium Myxococcus xanthus demonstrates that the social life of microbes is antagonistic on local and global scales. Antagonistic interactions and non-self recognition are likely to promote microbial diversity in local populations.

Developmental microbial ecology of the crop of the folivorous hoatzin

The hoatzin (Opisthocomus hoazin) is a South American strict folivorous bird, with a crop microbial ecosystem that ferments dietary plants. Chicks progressively become independent from the adult-fed regurgitated crop liquids, and we hypothesized that the crop bacterial ecosystem develops through ecological succession mechanisms, as they grow into adults. The aim of this work was to compare the crop bacterial community in hoatzins from three age groups: newly hatched chicks, juveniles and adults by sequencing 16S rRNA genes and using the G2 PhyloChip. Cloning yielded a total of 2123 nearly full-length sequences binned into 294 operational taxonomic units (OTUs) (with <97% homology) belonging to 7 phyla, with 91% of novel OTUs. The microarray identified a diverse bacterial community dominated by Firmicutes and Bacteroidetes, with approximately 1400 taxa grouped in 40 phyla that included those detected by cloning. In comparison with the adult, the hoatzin chick crop had a greater abundance of Flavobacteriaceae, Clostridiaceae and Lachnospiraceae but lacked phyla DSS1, Deferribacteres and Termite group 1, which were mostly present in adults. The overall community structure of the crop of the hoatzin changes with age in a complex manner, probably responding to new niches made available through dietary changes related to the transition from dependent to independent feeding.