Ecological drift and local exposures drive enteric bacterial community differences within species of Galápagos iguanas

Diet strongly influences the intestinal microbial communities through species sorting. Alternatively, these communicates may differ because of chance variation in local microbial exposures or species losses among allopatric host populations (i.e. ecological drift). We investigated how these forces shape enteric communities of Galápagos marine and land iguanas. Geographically proximate populations shared more similar communities within a host ecotype, suggesting a role for ecological drift during host colonization of the islands. Additionally, evidence of taxa sharing between proximate heterospecific host populations suggests that contemporary local exposures also influence the gut community assembly. While selective forces such as host-bacterial interactions or dietary differences are dominant drivers of intestinal community differences among hosts, historical and contemporary processes of ecological drift may lead to differences in bacterial composition within a host species. Whether such differences in community structure translate into geographic variation in benefits derived from these intimate microbial communities remains to be explored.     

Spatial analysis of ectomycorrhizal fungi reveals that root tip communities are structured by competitive interactions

Microbial ecology has made large advances over the last decade, mostly because of improvements in molecular analysis techniques that have enabled the detection and identification of progressively larger numbers of microbial species. However, determining the ecological patterns and processes taking place in communities of microbes remains a significant challenge. Are communities randomly assembled through dispersal and priority effects, or do species interact with each other leading to positive and negative associations? For mycorrhizal fungi, evidence is accumulating that stochastic and competitive interactions between species may both have a role in shaping community structure. Could the methodological approach, which is often incidence based, impact the outcomes detected? Here, we applied an incidence‐based Terminal Restriction Fragment Length Polymorphism (T‐RFLP) database approach to examine species diversity and ecological interactions within a community of ectomycorrhizal (ECM) fungi. Co‐occurrence analysis revealed that the ECM community colonizing root tips was strongly structured by competitive interactions, or ecological processes generating a similar spatial pattern, rather than neutral processes. Analysis of β‐diversity indicated that community structure was significantly more similar (spatially autocorrelated) at distances equal to or <3.41 m. The eight most frequently encountered species in the root tip community of ECM fungi displayed significant competitive interactions with at least one other species, showing that the incidence‐based approach was capable of detecting this sort of ecological information.     

Web of ecological interactions in an experimental gut microbiota

The dynamics of all ecosystems are dictated by intrinsic, density‐dependent mechanisms and by density‐independent environmental forcing. In spite of the importance of the gastrointestinal microbiota in health and disease, the ecology of this system remains largely unknown. Here, we take an ecological approach to gut microbial community analysis, with statistical modelling of time series data from chemostats. This approach removes effects of host forcing, allowing us to describe a network of intrinsic interactions determining the dynamic structure of an experimental gut microbiota. Surprisingly, the main colonization pattern in this simplified model system resembled that of the human infant gut, suggesting a potentially important role of density‐dependent interactions in the early gut microbiota. Knowledge of ecological structures in microbial systems may provide us with a means of controlling such systems by modifying the strength and nature of interactions among microbes and between the microbes and their environment.     

Dynamics of microbial competition,commensalism, and cooperation and its implications for coculture and microbiome engineering

Microbial consortium is a complex adaptive system with higher‐order dynamic characteristics that are not present by individual members. To accurately predict the social interactions, we formulate a set of unstructured kinetic models to quantitatively capture the dynamic interactions of multiple microbial species. By introducing an interaction coefficient, we analytically derived the steady‐state solutions for the interacting species and the substrate‐depleting profile in the chemostat. We analyzed the stability of the possible coexisting states defined by competition, parasitism, amensalism, commensalism, and cooperation. Our model predicts that only parasitism, commensalism, and cooperation could lead to stable coexisting states. We also determined the optimal social interaction criteria of microbial coculture when sequential metabolic reactions are compartmentalized into two distinct species. Coupled with Luedeking–Piret and Michaelis–Menten equations, accumulation of metabolic intermediates in one species and formation of end‐product in another species could be derived and assessed. We discovered that parasitism consortia disfavor the bioconversion of intermediate to final product; and commensalism consortia could efficiently convert metabolic intermediates to final product and maintain metabolic homeostasis with a broad range of operational conditions (i.e., dilution rates); whereas cooperative consortia leads to highly nonlinear pattern of precursor accumulation and end‐product formation. The underlying dynamics and emergent properties of microbial consortia may provide critical knowledge for us to understand ecological coexisting states, engineer efficient bioconversion process, deliver effective gut therapeutics as well as elucidate probiotic‐pathogen or tumor‐host interactions in general.     

Conceptualizing ecosystem tipping points within a physiological framework

Connecting the nonlinear and often counterintuitive physiological effects of multiple environmental drivers to the emergent impacts on ecosystems is a fundamental challenge. Unfortunately, the disconnect between the way “stressors” (e.g., warming) is considered in organismal (physiological) and ecological (community) contexts continues to hamper progress. Environmental drivers typically elicit biphasic physiological responses, where performance declines at levels above and below some optimum. It is also well understood that species exhibit highly variable response surfaces to these changes so that the optimum level of any environmental driver can vary among interacting species. Thus, species interactions are unlikely to go unaltered under environmental change. However, while these nonlinear, species‐specific physiological relationships between environment and performance appear to be general, rarely are they incorporated into predictions of ecological tipping points. Instead, most ecosystem‐level studies focus on varying levels of “stress” and frequently assume that any deviation from “normal” environmental conditions has similar effects, albeit with different magnitudes, on all of the species within a community. We consider a framework that realigns the positive and negative physiological effects of changes in climatic and nonclimatic drivers with indirect ecological responses. Using a series of simple models based on direct physiological responses to temperature and ocean pCO₂, we explore how variation in environment‐performance relationships among primary producers and consumers translates into community‐level effects via trophic interactions. These models show that even in the absence of direct mortality, mismatched responses resulting from often subtle changes in the physical environment can lead to substantial ecosystem‐level change.     

Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries Using Sparse Linear Regression

Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1) a correlation between the abundances of two species does not imply that those species are interacting, 2) the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3) errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called “errors-in-variables”. Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS), that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct “keystone species”, Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in the human gut microbiome.     

Intestinal microbiota in fishes: what's known and what's not

High‐throughput sequencing approaches have enabled characterizations of the community composition of numerous gut microbial communities, which in turn has enhanced interest in their diversity and functional relationships in different groups of vertebrates. Although fishes represent the greatest taxonomic and ecological diversity of vertebrates, our understanding of their gut microbiota and its functional significance has lagged well behind that of terrestrial vertebrates. In order to highlight emerging issues, we provide an overview of research on fish gut microbiotas and the biology of their hosts. We conclude that microbial community composition must be viewed within an informed context of host ecology and physiology, and that this is of particular importance with respect to research planning and sampling design.     

Subspecies in the global human gut microbiome

Population genomics of prokaryotes has been studied in depth in only a small number of primarily pathogenic bacteria, as genome sequences of isolates of diverse origin are lacking for most species. Here, we conducted a large‐scale survey of population structure in prevalent human gut microbial species, sampled from their natural environment, with a culture‐independent metagenomic approach. We examined the variation landscape of 71 species in 2,144 human fecal metagenomes and found that in 44 of these, accounting for 72% of the total assigned microbial abundance, single‐nucleotide variation clearly indicates the existence of sub‐populations (here termed subspecies). A single subspecies (per species) usually dominates within each host, as expected from ecological theory. At the global scale, geographic distributions of subspecies differ between phyla, with Firmicutes subspecies being significantly more geographically restricted. To investigate the functional significance of the delineated subspecies, we identified genes that consistently distinguish them in a manner that is independent of reference genomes. We further associated these subspecies‐specific genes with properties of the microbial community and the host. For example, two of the three Eubacterium rectale subspecies consistently harbor an accessory pro‐inflammatory flagellum operon that is associated with lower gut community diversity, higher host BMI, and higher blood fasting insulin levels. Using an additional 676 human oral samples, we further demonstrate the existence of niche specialized subspecies in the different parts of the oral cavity. Taken together, we provide evidence for subspecies in the majority of abundant gut prokaryotes, leading to a better functional and ecological understanding of the human gut microbiome in conjunction with its host.     

The gut microbiome reflects ancestry despite dietary shifts across a hybrid zone

The microbiome is critical to an organism's phenotype, and its composition is shaped by, and a driver of, eco-evolutionary interactions. We investigated how host ancestry, habitat and diet shape gut microbial composition in a mammalian hybrid zone between Neotoma lepida and N. bryanti that occurs across an ecotone between distinct vegetation communities. We found that habitat is the primary determinant of diet, while host genotype is the primary determinant of the gut microbiome—a finding further supported by intermediate microbiome composition in first-generation hybrids. Despite these distinct primary drivers, microbial richness was correlated with diet richness, and individuals that maintained higher dietary richness had greater gut microbial community stability. Both relationships were stronger in the relative dietary generalist of the two parental species. Our findings show that host ancestry interacts with dietary habits to shape the microbiome, ultimately resulting in the phenotypic plasticity that host–microbial interactions allow.     

Honeybees and bumblebees share similar bacterial symbionts

Associations with symbiotic microorganisms are a major source for evolutionary innovation in eukaryotes. Arthropods have long served as model systems to study such associations, especially since Paul Buchner’s (1965) seminal work that beautifully illustrated the enormous diversity of microorganisms associated with insects. Particularly high taxonomic and functional diversities of microbial symbionts have been found in the guts and gut‐associated organs of insects. These microorganisms play important roles in the digestion, nutrition and defence of the host. However, most studies of gut microorganisms have focused on single host taxa, limiting the ability to draw general conclusions on composition and functional roles of the insect gut microbiota. This is especially true for the diverse and important insect order Hymenoptera that comprises the bees, wasps and ants. Recently, Russell et al. (2009) analysed the bacterial community associated with diverse ant species and found evidence for changes in the microbial gut community coinciding with the evolution of herbivory. In this issue of Molecular Ecology, Martinson et al. (2011) provide the first broad‐scale bacterial survey for bees. Their findings substantiate earlier evidence for a surprisingly simple gut microbiota in honeybees (Apis mellifera) that is composed of only six to ten major phylotypes. Importantly, Martinson et al. demonstrate for the first time that the same bacterial phylotypes are major constituents of other Apis as well as Bombus species, but not of any other bees and wasps outside of the corbiculate bees, a clade of four tribes within the subfamily Apinae. These results indicate that corbiculate bees harbour a specific and possibly co‐evolved bacterial community in their digestive tract. Furthermore, the comparison with other bees and wasps suggests that changes in social lifestyle may have had a stronger effect on the evolution of the gut microbiota than the dietary shift from predatory ancestors to pollen‐feeding (i.e. herbivorous) species. These findings have far‐reaching implications for research on the microbial symbionts of insects as well as on the nutritional physiology of the ecologically and economically important group of corbiculate bees.     

Incorporating phylogenetic metrics to microbial co‐occurrence networks based on amplicon sequences to discern community assembly processes

Co‐occurrence network analysis based on amplicon sequences is increasingly used to study microbial communities. Patterns of co‐existence or mutual exclusion between pairs of taxa are often interpreted as reflecting positive or negative biological interactions. However, other assembly processes can underlie these patterns, including species failure to reach distant areas (dispersal limitation) and tolerate local environmental conditions (habitat filtering). We provide a tool to quantify the relative contribution of community assembly processes to microbial co‐occurrence patterns, which we applied to explore soil bacterial communities in two dry ecosystems. First, we sequenced a bacterial phylogenetic marker in soils collected across multiple plots. Second, we inferred co‐occurrence networks to identify pairs of significantly associated taxa, either co‐existing more (aggregated) or less often (segregated) than expected at random. Third, we assigned assembly processes to each pair: patterns explained based on spatial or environmental distance were ascribed to dispersal limitation (2%–4%) or habitat filtering (55%–77%), and the remaining to biological interactions. Finally, we calculated the phylogenetic distance between taxon pairs to test theoretical expectations on the linkages between phylogenetic patterns and assembly processes. Aggregated pairs were more closely related than segregated pairs. Furthermore, habitat‐filtered aggregated pairs were closer relatives than those assigned to positive interactions, consistent with phylogenetic niche conservatism and cooperativism among distantly related taxa. Negative interactions resulted in equivocal phylogenetic signatures, probably because different competitive processes leave opposing signals. We show that microbial co‐occurrence networks mainly reflect environmental tolerances and propose that incorporating measures of phylogenetic relatedness to networks might help elucidate ecologically meaningful patterns.     

Linking microbial co‐occurrences to soil ecological processes across a woodland‐grassland ecotone

Ecotones between distinct ecosystems have been the focus of many studies as they offer valuable insights into key drivers of community structure and ecological processes that underpin function. While previous studies have examined a wide range of above‐ground parameters in ecotones, soil microbial communities have received little attention. Here we investigated spatial patterns, composition, and co‐occurrences of archaea, bacteria, and fungi, and their relationships with soil ecological processes across a woodland‐grassland ecotone. Geostatistical kriging and network analysis revealed that the community structure and spatial patterns of soil microbiota varied considerably between three habitat components across the ecotone. Woodland samples had significantly higher diversity of archaea while the grassland samples had significantly higher diversity of bacteria. Microbial co‐occurrences reflected differences in soil properties and ecological processes. While microbial networks were dominated by bacterial nodes, different ecological processes were linked to specific microbial guilds. For example, soil phosphorus and phosphatase activity formed the largest clusters in their respective networks, and two lignolytic enzymes formed joined clusters. Bacterial ammonia oxidizers were dominant over archaeal oxidizers and showed a significant association (p < 0.001) with potential nitrification (PNR), with the PNR subnetwork being dominated by Betaproteobacteria. The top ten keystone taxa comprised six bacterial and four fungal OTUs, with Random Forest Analysis revealing soil carbon and nitrogen as the determinants of the abundance of keystone taxa. Our results highlight the importance of assessing interkingdom associations in soil microbial networks. Overall, this study shows how ecotones can be used as a model to delineate microbial structural patterns and ecological processes across adjoining land‐uses within a landscape.     

A network approach for inferring species associations from co‐occurrence data

Positive and negative associations between species are a key outcome of community assembly from regional species pools. These associations are difficult to detect and can be caused by a range of processes such as species interactions, local environmental constraints and dispersal. We integrate new ideas around species distribution modeling, covariance matrix estimation, and network analysis to provide an approach to inferring non‐random species associations from local‐ and regional‐scale occurrence data. Specifically, we provide a novel framework for identifying species associations that overcomes three challenges: 1) correcting for indirect effects from other species, 2) avoiding spurious associations driven by regional‐scale distributions, and 3) describing these associations in a multi‐species context. We highlight a range of research questions and analyses that this framework is able to address. We show that the approach is statistically robust using simulated data. In addition, we present an empirical analysis of > 1000 North American tree communities that gives evidence for weak positive associations among small groups of species. Finally, we discuss several possible extensions for identifying drivers of associations, predicting community assembly, and better linking biogeography and community ecology.     

Investigating microbial associations from sequencing survey data with co‐correspondence analysis

Microbial communities, which drive major ecosystem functions, consist of a wide range of interacting species. Understanding how microbial communities are structured and the processes underlying this is crucial to interpreting ecosystem responses to global change but is challenging as microbial interactions cannot usually be directly observed. Multiple efforts are currently focused to combine next‐generation sequencing (NGS) techniques with refined statistical analysis (e.g., network analysis, multivariate analysis) to characterize the structures of microbial communities. However, most of these approaches consider a single table of sequencing data measured for several samples. Technological advances now make it possible to collect NGS data on different taxonomic groups simultaneously for the same samples, allowing us to analyse a pair of tables. Here, an analytical framework based on co‐correspondence analysis (CoCA) is proposed to study the distributions, assemblages and interactions between two microbial communities. We show the ability of this approach to highlight the relationships between two microbial communities, using two data sets exhibiting various types of interactions. CoCA identified strong association patterns between autotrophic and heterotrophic microbial eukaryote assemblages, on the one hand, and between microalgae and viruses, on the other. We demonstrate also how CoCA can be used, complementary to network analysis, to reorder co‐occurrence networks and thus investigate the presence of patterns in ecological networks.     

A phylogenetic perspective on species diversity, β‐diversity and biogeography for the microbial world

There is an increasing interest to combine phylogenetic data with distributional and ecological records to assess how natural communities arrange under an evolutionary perspective. In the microbial world, there is also a need to go beyond the problematic species definition to deeply explore ecological patterns using genetic data. We explored links between evolution/phylogeny and community ecology using bacterial 16S rRNA gene information from a high‐altitude lakes district data set. We described phylogenetic community composition, spatial distribution, and β‐diversity and biogeographical patterns applying evolutionary relatedness without relying on any particular operational taxonomic unit definition. High‐altitude lakes districts usually contain a large mosaic of highly diverse small water bodies and conform a fine biogeographical model of spatially close but environmentally heterogeneous ecosystems. We sampled 18 lakes in the Pyrenees with a selection criteria focused on capturing the maximum environmental variation within the smallest geographical area. The results showed highly diverse communities nonrandomly distributed with phylogenetic β‐diversity patterns mainly shaped by the environment and not by the spatial distance. Community similarity based on both bacterial taxonomic composition and phylogenetic β‐diversity shared similar patterns and was primarily structured by similar environmental drivers. We observed a positive relationship between lake area and phylogenetic diversity with a slope consistent with highly dispersive planktonic organisms. The phylogenetic approach incorporated patterns of common ancestry into bacterial community analysis and emerged as a very convenient analytical tool for direct inter‐ and intrabiome biodiversity comparisons and sorting out microbial habitats with potential application in conservation studies.     

土壤动物肠道微生物多样性研究进展

随着分子生物学技术方法的快速发展,动物肠道微生物已成为医学、动物生理学与微生物生态学等研究领域热点。土壤动物种类繁多,分布广泛,其作为陆地生态系统重要组分,是驱动生态系统功能的关键因子。土壤动物体内的微生物由于与宿主长期共存,在与宿主协同进化中形成了丰富多样的群落结构,能够影响土壤动物本身的健康,进而介导土壤动物生态功能的实现。近些年,土壤动物肠道微生物工作方兴未艾,日渐得到重视。总结了四个部分内容：1)首先总结了土壤动物肠道微生物多样性领域的研究现状,该领域年发文量逐年增长,且近十年增长快速。土壤模式生物肠道微生物多样性研究较多且更为深入。土壤动物肠道微生物多样性组成与驱动机制、共存机制及群落构建的理论研究是该领域前沿;2)进而展示了土壤动物肠道微生物多样性组成和研究方法,土壤动物肠道菌群组成以变形菌门、厚壁菌门、放线菌门和拟杆菌门为主。早期工作基于传统分离培养,近年来新一代测序技术推动了该领域发展;3)接着关注了土壤动物肠道微生物的生态学功能,总体上体现在肠道微生物能帮助宿主分解食物基质、参与营养利用、影响寿命和繁殖及提高宿主免疫能力,且其能够影响土壤动物的气体排放及介导其对生态系...     

Accounting for environmental variation in co‐occurrence modelling reveals the importance of positive interactions in root‐associated fungal communities

Understanding the role of interspecific interactions in shaping ecological communities is one of the central goals in community ecology. In fungal communities, measuring interspecific interactions directly is challenging because these communities are composed of large numbers of species, many of which are unculturable. An indirect way of assessing the role of interspecific interactions in determining community structure is to identify the species co‐occurrences that are not constrained by environmental conditions. In this study, we investigated co‐occurrences among root‐associated fungi, asking whether fungi co‐occur more or less strongly than expected based on the environmental conditions and the host plant species examined. We generated molecular data on root‐associated fungi of five plant species evenly sampled along an elevational gradient at a high arctic site. We analysed the data using a joint species distribution modelling approach that allowed us to identify those co‐occurrences that could be explained by the environmental conditions and the host plant species, as well as those co‐occurrences that remained unexplained and thus more probably reflect interactive associations. Our results indicate that not only negative but also positive interactions play an important role in shaping microbial communities in arctic plant roots. In particular, we found that mycorrhizal fungi are especially prone to positively co‐occur with other fungal species. Our results bring new understanding to the structure of arctic interaction networks by suggesting that interactions among root‐associated fungi are predominantly positive.     

Seasonal strengths of the abiotic and biotic drivers of a zooplankton community

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The rate of environmental fluctuations shapes ecological dynamics in a two‐species microbial system

Species interactions change when the external conditions change. How these changes affect microbial community properties is an open question. We address this question using a two‐species consortium in which species interactions change from exploitation to competition depending on the carbon source provided. We built a mathematical model and calibrated it using single‐species growth measurements. This model predicted that low frequencies of change between carbon sources lead to species loss, while intermediate and high frequencies of change maintained both species. We experimentally confirmed these predictions by growing co‐cultures in fluctuating environments. These findings complement more established concepts of a diversity peak at intermediate disturbance frequencies. They also provide a mechanistic understanding for how the dynamics at the community level emerges from single‐species behaviours and interspecific interactions. Our findings suggest that changes in species interactions can profoundly impact the ecological dynamics and properties of microbial systems.     

Drought consistently alters the composition of soil fungal and bacterial communities in grasslands from two continents

The effects of short‐term drought on soil microbial communities remain largely unexplored, particularly at large scales and under field conditions. We used seven experimental sites from two continents (North America and Australia) to evaluate the impacts of imposed extreme drought on the abundance, community composition, richness, and function of soil bacterial and fungal communities. The sites encompassed different grassland ecosystems spanning a wide range of climatic and soil properties. Drought significantly altered the community composition of soil bacteria and, to a lesser extent, fungi in grasslands from two continents. The magnitude of the fungal community change was directly proportional to the precipitation gradient. This greater fungal sensitivity to drought at more mesic sites contrasts with the generally observed pattern of greater drought sensitivity of plant communities in more arid grasslands, suggesting that plant and microbial communities may respond differently along precipitation gradients. Actinobateria, and Chloroflexi, bacterial phyla typically dominant in dry environments, increased their relative abundance in response to drought, whereas Glomeromycetes, a fungal class regarded as widely symbiotic, decreased in relative abundance. The response of Chlamydiae and Tenericutes, two phyla of mostly pathogenic species, decreased and increased along the precipitation gradient, respectively. Soil enzyme activity consistently increased under drought, a response that was attributed to drought‐induced changes in microbial community structure rather than to changes in abundance and diversity. Our results provide evidence that drought has a widespread effect on the assembly of microbial communities, one of the major drivers of soil function in terrestrial ecosystems. Such responses may have important implications for the provision of key ecosystem services, including nutrient cycling, and may result in the weakening of plant–microbial interactions and a greater incidence of certain soil‐borne diseases.