Lineage-dependent ecological coherence in bacteria

Linking niche size and phylogenetic signals to predict future soil microbial relative abundances

Bacteria provide ecosystem services (e.g., biogeochemical cycling) that regulate climate, purify water, and produce food and other commodities, yet their distribution and likely responses to change or intervention are difficult to predict. Using bacterial 16S rRNA gene surveys of 1,381 soil samples from the Biomes of Australian Soil Environment (BASE) dataset, we were able to model relative abundances of soil bacterial taxonomic groups and describe bacterial niche space and optima. Hold out sample validated hypothetical causal networks (structural equation models; SEM) were able to predict the relative abundances of bacterial taxa from environmental data and elucidate soil bacterial niche space. By using explanatory SEM properties as indicators of microbial traits, we successfully predicted soil bacterial response, and in turn potential ecosystem service response, to near-term expected changes in the Australian climate. The methods developed enable prediction of continental-scale changes in bacterial relative abundances, and demonstrate their utility in predicting changes in bacterial function and thereby ecosystem services. These capabilities will be strengthened in the future with growing genome-level data.

Abundance-Occupancy Relationships Along Taxonomic Ranks Reveal a Consistency of Niche Differentiation in Marine Bacterioplankton With Distinct Lifestyles

Abundance-occupancy relationships (AORs) are an important determinant of biotic community dynamics and habitat suitability. However, little is known about their role in complex bacterial communities, either within a phylogenetic framework or as a function of niche breadth. Based on data obtained in a field study in the St. Lawrence Estuary, we used 16S rRNA gene sequencing to examine the vertical patterns, strength, and character of AORs for particle-attached and free-living bacterial assemblages. Free-living communities were phylogenetically more diverse than particle-attached communities. The dominant taxa were consistent in terms of their presence/absence but population abundances differed in surface water vs. the cold intermediate layer. Significant, positive AORs characterized all of the surveyed communities across all taxonomic ranks of bacteria, thus demonstrating an ecologically conserved trend for both free-living and particle-attached bacteria. The strength of the AORs was low at the species level but higher at and above the genus level. These results demonstrate that an assessment of the distributions and population densities of finely resolved taxa does not necessarily improve determinations of apparent niche differences in marine bacterioplankton communities at regional scales compared with the information inferred from a broad taxonomic classification.

Quantitatively Partitioning Microbial Genomic Traits among Taxonomic Ranks across the Microbial Tree of Life

Recently, there has been great progress in defining a complete taxonomy of bacteria and archaea, which has been enabled by improvements in DNA sequencing technology and new bioinformatic techniques. A new, algorithmically defined microbial tree of life describes those linkages, relying solely on genetic data, which raises the issue of how microbial traits relate to taxonomy. Here, we adopted cluster of orthologous group functional categories as a scheme to describe the genomic contents of microbes, a method that can be applied to any microbial lineage for which genomes are available. This simple approach allows quantitative comparisons between microbial genomes with different gene compositions from across the microbial tree of life. Our observations demonstrate statistically significant patterns in cluster of orthologous group functional categories at taxonomic levels that span the range from domain to genus.

Widely used microbial taxonomies, such as the NCBI taxonomy, are based on a combination of sequence homology among conserved genes and historically accepted taxonomies, which were developed based on observable traits such as morphology and physiology. A recently proposed alternative taxonomy database, the Genome Taxonomy Database (GTDB), incorporates only sequence homology of conserved genes and attempts to partition taxonomic ranks such that each rank implies the same amount of evolutionary distance, regardless of its position on the phylogenetic tree. This provides the first opportunity to completely separate taxonomy from traits and therefore to quantify how taxonomic rank corresponds to traits across the microbial tree of life. We quantified the relative abundances of clusters of orthologous group functional categories (COG-FCs) as a proxy for traits within the lineages of 13,735 cultured and uncultured microbial lineages from a custom-curated genome database. On average, 41.4% of the variation in COG-FC relative abundance is explained by taxonomic rank, with domain, phylum, class, order, family, and genus explaining, on average, 3.2%, 14.6%, 4.1%, 9.2%, 4.8%, and 5.5% of the variance, respectively (P < 0.001 for all). To our knowledge, this is the first work to quantify the variance in metabolic potential contributed by individual taxonomic ranks. A qualitative comparison between the COG-FC relative abundances and genus-level phylogenies, generated from published concatenated protein sequence alignments, further supports the idea that metabolic potential is taxonomically coherent at higher taxonomic ranks. The quantitative analyses presented here characterize the integral relationship between diversification of microbial lineages and the metabolisms which they host.

IMPORTANCE Recently, there has been great progress in defining a complete taxonomy of bacteria and archaea, which has been enabled by improvements in DNA sequencing technology and new bioinformatic techniques. A new, algorithmically defined microbial tree of life describes those linkages, relying solely on genetic data, which raises the issue of how microbial traits relate to taxonomy. Here, we adopted cluster of orthologous group functional categories as a scheme to describe the genomic contents of microbes, a method that can be applied to any microbial lineage for which genomes are available. This simple approach allows quantitative comparisons between microbial genomes with different gene compositions from across the microbial tree of life. Our observations demonstrate statistically significant patterns in cluster of orthologous group functional categories at taxonomic levels that span the range from domain to genus.

The human gut pan-microbiome presents a compositional core formed by discrete phylogenetic units

The complex community of microbes living in the human gut plays an important role in host wellbeing. However, defining a ‘healthy’ gut microbiome in terms of composition has remained an elusive task, despite its anticipated medical and scientific importance. In this regard, a central question has been if there is a ‘core’ microbiome consisting of bacterial groups common to all healthy humans. Recent studies have been able to define a compositional core in human gut microbiome datasets in terms of taxonomic assignments. However, the description of the core microbiome in terms of taxonomic assignments may not be adequate when considering subsequent analyses and applications. Through the implementation of a dynamic clustering approach in the meta-analyisis of comprehensive 16S rRNA marker gene datasets, this study found that the human gut pan-microbiome presents a preeminent compositional core comprised of discrete units of varying phylogenetic depth present in all individuals studied. Since both microbial traits and ecological coherence show signs of phylogenetic conservation, this outcome provides a new conceptual framework in the study of the ecosystem, as well as important practical considerations which should be taken into account in future research.

Structure of association networks in food bacterial communities

The structure of microbial association networks was investigated for seventeen studies on food bacterial communities using the CoNet app. The results were compared with those for host and environmental microbiomes. Microbial association networks of food bacterial communities shared several properties with those of host microbiomes, although they were less complex and lacked a scale-free, small world structure that is characteristic of environmental microbial communities. This may depend on both the initial contamination pattern, whose main source is the raw material microbiome, and on the copiotrophic nature of food environments, with lack of well defined, specific niches. The selective factors which are characteristic of fermentation and spoilage drastically simplified microbial association networks and showed the emergence of negative hubs. Co-presence and mutual exclusion networks had a radically different structure, with high clustering coefficient in the first and high heterogeneity in the latter. Node properties (degree, positive degree, betweenness centrality, abundance) can be combined in plots, which allow a rapid identification of hub species. The combined use of three network inference tools (CoNet, SparCC, and SPIEC-EASI) confirmed that microbial association network detection is method specific, but several coherent copresence or mutual exclusion relationships were detected by at least two different methods.

Nutrient and Rainfall Additions Shift Phylogenetically Estimated Traits of Soil Microbial Communities

Microbial traits related to ecological responses and functions could provide a common currency facilitating synthesis and prediction; however, such traits are difficult to measure directly for all taxa in environmental samples. Past efforts to estimate trait values based on phylogenetic relationships have not always distinguished between traits with high and low phylogenetic conservatism, limiting reliability, especially in poorly known environments, such as soil. Using updated reference trees and phylogenetic relationships, we estimated two phylogenetically conserved traits hypothesized to be ecologically important from DNA sequences of the 16S rRNA gene from soil bacterial and archaeal communities. We sampled these communities from an environmental change experiment in California grassland applying factorial addition of late-season precipitation and soil nutrients to multiple soil types for 3 years prior to sampling. Estimated traits were rRNA gene copy number, which contributes to how rapidly a microbe can respond to an increase in resources and may be related to its maximum growth rate, and genome size, which suggests the breadth of environmental and substrate conditions in which a microbe can thrive. Nutrient addition increased community-weighted mean estimated rRNA gene copy number and marginally increased estimated genome size, whereas precipitation addition decreased these community means for both estimated traits. The effects of both treatments on both traits were associated with soil properties, such as ammonium, available phosphorus, and pH. Estimated trait responses within several phyla were opposite to the community mean response, indicating that microbial responses, although largely consistent among soil types, were not uniform across the tree of life. Our results show that phylogenetic estimation of microbial traits can provide insight into how microbial ecological strategies interact with environmental changes. The method could easily be applied to any of the thousands of existing 16S rRNA sequence data sets and offers potential to improve our understanding of how microbial communities mediate ecosystem function responses to global changes.

Phenotypic Microdiversity and Phylogenetic Signal Analysis of Traits Related to Social Interaction in Bacillus spp. from Sediment Communities

Understanding the relationship between phylogeny and predicted traits is important to uncover the dimension of the predictive power of a microbial composition approach. Numerous works have addressed the taxonomic composition of bacteria in communities, but little is known about trait heterogeneity in closely related bacteria that co-occur in communities. We evaluated a sample of 467 isolates from the Churince water system of the Cuatro Cienegas Basin (CCB), enriched for Bacillus spp. The 16S rRNA gene revealed a random distribution of taxonomic groups within this genus among 11 sampling sites. A subsample of 141 Bacillus spp. isolates from sediment, with seven well-represented species was chosen to evaluate the heterogeneity and the phylogenetic signal of phenotypic traits that are known to diverge within small clades, such as substrate utilization, and traits that are conserved deep in the lineage, such as prototrophy, swarming and biofilm formation. We were especially interested in evaluating social traits, such as swarming and biofilm formation, for which cooperation is needed to accomplish a multicellular behavior and for which there is little information from natural communities. The phylogenetic distribution of traits, evaluated by the Purvis and Fritz’s D statistics approached a Brownian model of evolution. Analysis of the phylogenetic relatedness of the clusters of members sharing the trait using consenTRAIT algorithm, revealed more clustering and deeper phylogenetic signal for prototrophy, biofilm and swimming compared to the data obtained for substrate utilization. The explanation to the observed Brownian evolution of social traits could be either loss due to complete dispensability or to compensated trait loss due to the availability of public goods. Since many of the evaluated traits can be considered to be collective action traits, such as swarming, motility and biofilm formation, the observed microdiversity within taxonomic groups might be explained by distributed functions in structured communities.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics.

Development, diet and dynamism: longitudinal and cross-sectional predictors of gut microbial communities in wild baboons

Gut bacterial communities play essential roles in host biology, but to date we lack information on the forces that shape gut microbiota between hosts and over time in natural populations. Understanding these forces in wild primates provides a valuable comparative context that enriches scientific perspectives on human gut microbiota. To this end, we tested predictors of gut microbial composition in a well-studied population of wild baboons. Using cross-sectional and longitudinal samples collected over 13 years, we found that baboons harbour gut microbiota typical of other omnivorous primates, albeit with an especially high abundance of Bifidobacterium. Similar to previous work in humans and other primates, we found strong effects of both developmental transitions and diet on gut microbial composition. Strikingly, baboon gut microbiota appeared to be highly dynamic such that samples collected from the same individual only a few days apart were as different from each other as samples collected over 10 years apart. Despite the dynamic nature of baboon gut microbiota, we identified a set of core taxa that is common among primates, supporting the hypothesis that microbiota codiversify with their host species. Our analysis identified two tentative enterotypes in adult baboons that differ from those of humans and chimpanzees.

Microbiomes in light of traits: A phylogenetic perspective

A focus on the phenotypic characteristics of microorganisms-their traits-offers a path for interpreting the growing amount of microbiome data. We review key aspects of microbial traits, as well as approaches used to assay their phylogenetic distribution. Recent studies reveal that microbial traits are differentially conserved across the tree of life and appear to be conserved in a hierarchical fashion, possibly linked to their biochemical complexity. These results suggest a predictive framework whereby the genetic (or taxonomic) resolution of microbiome variation among samples provides information about the traits under selection. The organizational parallels seen among human and free-living microbiomes seem to support this idea. Developments in this framework may offer predictions not only for how microbial composition responds to changing environmental conditions, but also for how these changes may alter the health or functioning in human, engineered, and environmental systems.

Weak Coherence in Abundance Patterns Between Bacterial Classes and Their Constituent OTUs Along a Regulated River

Deductions about the ecology of high taxonomic bacterial ranks (i.e., phylum, class, order) are often based on their abundance patterns, yet few studies have quantified how accurately variations in abundance of these bacterial groups represent the dynamics of the taxa within them. Using 454-pyrosequencing of the 16S rRNA gene, we investigated whether the changes in abundance of six dominant bacterial classes (Actinobacteria, Beta-/Alpha-/Gamma-proteobacteria, Flavobacteria, and Sphingobacteria) along a large dam-regulated river are reflected by those of their constituent Operational Taxonomic Units (OTUs; 97% similarity level). The environmental impact generated by the reservoirs promoted clear compositional shifts in all bacterial classes that resulted from changes in the abundance of individual OTUs rather than from the appearance of new taxa along the river. Abundance patterns at the class level represented the dynamics of only a small but variable proportion of their constituting OTUs, which were not necessarily the most abundant ones. Within most classes, we detected sub-groups of OTUs showing contrasting responses to reservoir-induced environmental changes. Overall, we show that the patterns observed at the class level fail to capture the dynamics of a significant fraction of their constituent members, calling for caution when the ecological attributes of high-ranks are to be interpreted.

Phylogenetic congruence and ecological coherence in terrestrial Thaumarchaeota

Thaumarchaeota form a ubiquitously distributed archaeal phylum, comprising both the ammonia-oxidising archaea (AOA) and other archaeal groups in which ammonia oxidation has not been demonstrated (including Group 1.1c and Group 1.3). The ecology of AOA in terrestrial environments has been extensively studied using either a functional gene, encoding ammonia monooxygenase subunit A (amoA) or 16S ribosomal RNA (rRNA) genes, which show phylogenetic coherence with respect to soil pH. To test phylogenetic congruence between these two markers and to determine ecological coherence in all Thaumarchaeota, we performed high-throughput sequencing of 16S rRNA and amoA genes in 46 UK soils presenting 29 available contextual soil characteristics. Adaptation to pH and organic matter content reflected strong ecological coherence at various levels of taxonomic resolution for Thaumarchaeota (AOA and non-AOA), whereas nitrogen, total mineralisable nitrogen and zinc concentration were also important factors associated with AOA thaumarchaeotal community distribution. Other significant associations with environmental factors were also detected for amoA and 16S rRNA genes, reflecting different diversity characteristics between these two markers. Nonetheless, there was significant statistical congruence between the markers at fine phylogenetic resolution, supporting the hypothesis of low horizontal gene transfer between Thaumarchaeota. Group 1.1c Thaumarchaeota were also widely distributed, with two clusters predominating, particularly in environments with higher moisture content and organic matter, whereas a similar ecological pattern was observed for Group 1.3 Thaumarchaeota. The ecological and phylogenetic congruence identified is fundamental to understand better the life strategies, evolutionary history and ecosystem function of the Thaumarchaeota.

Demonstrating microbial co-occurrence pattern analyses within and between ecosystems

Co-occurrence patterns are used in ecology to explore interactions between organisms and environmental effects on coexistence within biological communities. Analysis of co-occurrence patterns among microbial communities has ranged from simple pairwise comparisons between all community members to direct hypothesis testing between focal species. However, co-occurrence patterns are rarely studied across multiple ecosystems or multiple scales of biological organization within the same study. Here we outline an approach to produce co-occurrence analyses that are focused at three different scales: co-occurrence patterns between ecosystems at the community scale, modules of co-occurring microorganisms within communities, and co-occurring pairs within modules that are nested within microbial communities. To demonstrate our co-occurrence analysis approach, we gathered publicly available 16S rRNA amplicon datasets to compare and contrast microbial co-occurrence at different taxonomic levels across different ecosystems. We found differences in community composition and co-occurrence that reflect environmental filtering at the community scale and consistent pairwise occurrences that may be used to infer ecological traits about poorly understood microbial taxa. However, we also found that conclusions derived from applying network statistics to microbial relationships can vary depending on the taxonomic level chosen and criteria used to build co-occurrence networks. We present our statistical analysis and code for public use in analysis of co-occurrence patterns across microbial communities.

Ecological consistency of SSU rRNA-based operational taxonomic units at a global scale

Operational Taxonomic Units (OTUs), usually defined as clusters of similar 16S/18S rRNA sequences, are the most widely used basic diversity units in large-scale characterizations of microbial communities. However, it remains unclear how well the various proposed OTU clustering algorithms approximate ‘true’ microbial taxa. Here, we explore the ecological consistency of OTUs – based on the assumption that, like true microbial taxa, they should show measurable habitat preferences (niche conservatism). In a global and comprehensive survey of available microbial sequence data, we systematically parse sequence annotations to obtain broad ecological descriptions of sampling sites. Based on these, we observe that sequence-based microbial OTUs generally show high levels of ecological consistency. However, different OTU clustering methods result in marked differences in the strength of this signal. Assuming that ecological consistency can serve as an objective external benchmark for cluster quality, we conclude that hierarchical complete linkage clustering, which provided the most ecologically consistent partitions, should be the default choice for OTU clustering. To our knowledge, this is the first approach to assess cluster quality using an external, biologically meaningful parameter as a benchmark, on a global scale.

To characterize the composition of microbial communities, researchers often sequence and quantify specific marker genes, particularly the SSU (‘small subunit’) ribosomal RNA gene. One crucial step in such studies is the clustering of sequences into Operational Taxonomic Units (OTUs) of closely related organisms. However, this practice has repeatedly been called into question, arguing that the use of OTUs is not backed by microbial speciation theory. Here, we explore whether OTUs group ecologically similar organisms and show that indeed, OTUs are generally ecologically consistent. Moreover, we show how ecological consistency can be used as a measure of OTU ‘quality’ and compare different widely used OTU clustering methods. Our findings should help in the design and interpretation of SSU-based microbial ecology studies, in a research field that is only beginning to unfold its full potential to help understand life at the smallest scales.

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.

Surprisingly extensive mixed phylogenetic and ecological signals among bacterial Operational Taxonomic Units

The lack of a consensus bacterial species concept greatly hampers our ability to understand and organize bacterial diversity. Operational taxonomic units (OTUs), which are clustered on the basis of DNA sequence identity alone, are the most commonly used microbial diversity unit. Although it is understood that OTUs can be phylogenetically incoherent, the degree and the extent of the phylogenetic inconsistency have not been explicitly studied. Here, we tested the phylogenetic signal of OTUs in a broad range of bacterial genera from various phyla. Strikingly, we found that very few OTUs were monophyletic, and many showed evidence of multiple independent origins. Using previously established bacterial habitats as benchmarks, we showed that OTUs frequently spanned multiple ecological habitats. We demonstrated that ecological heterogeneity within OTUs is caused by their phylogenetic inconsistency, and not merely due to 'lumping' of taxa resulting from using relaxed identity cut-offs. We argue that ecotypes, as described by the Stable Ecotype Model, are phylogenetically and ecologically more consistent than OTUs and therefore could serve as an alternative unit for bacterial diversity studies. In addition, we introduce QuickES, a new wrapper program for the Ecotype Simulation algorithm, which is capable of demarcating ecotypes in data sets with tens of thousands of sequences.