Community-wide analysis of microbial genome sequence signatures

Background  

Analyses of DNA sequences from cultivated microorganisms have revealed genome-wide, taxa-specific nucleotide compositional characteristics, referred to as genome signatures. These signatures have far-reaching implications for understanding genome evolution and potential application in classification of metagenomic sequence fragments. However, little is known regarding the distribution of genome signatures in natural microbial communities or the extent to which environmental factors shape them.     

磷脂脂肪酸方法在土壤微生物分析中的应用*

磷脂脂肪酸(PLYA)是活体微生物细胞膜的重要组分,不同类群的微生物能通过不同的生化途径合成不同的PLFA,部分PLFA可以作为分析微生物量和微生物群落结构等变化的生物标记。在土壤微生物分析中,越来越多地采用了PLFA方法。主要对PLFA方法在土壤微生物分析中的应用做一综述。     

Infrared Spectroscopic Biosignatures from Hidden Cave,New Mexico: Possible Applications for Remote Life Detection

Subsurface environments are known to support and preserve diverse microbial communities. Giant pool fingers from Hidden Cave, New Mexico consist of mm-scale dark micritic calcite layers alternating with clear dogtooth spar crystals and contain morphological and geochemical evidence of past microbial communities. We used Fourier Transform infrared spectroscopy to identify fatty acids, proteins, PO₂-carrying compounds, and polysaccharides spatially related to morphological fossil filaments throughout the surface micritic laminations and central pool finger regions. These biomolecular signatures are important components that contribute to the biosignature suite under development that identify microbial involvement in carbonate precipitation on Earth and remotely.     

Divergence in gut microbial communities mirrors a social group fission event in a black‐and‐white colobus monkey (Colobus vellerosus)

Host behavior and social factors have increasingly been implicated in structuring the composition of gut microbial communities. In social animals, distinct microbial communities characterize different social groups across a variety of taxa, although little longitudinal research has been conducted that demonstrates how this divergence occurs. Our study addresses this question by characterizing the gut microbial composition of an African Old World monkey, the black‐and‐white colobus (Colobus vellerosus), before and after a social group fission event. Gut microbial taxonomic composition of these monkeys was profiled using the V‐4 hypervariable region of the bacterial 16S ribosomal RNA gene, and pairwise‐relatedness values were calculated for all individuals using 17 short tandem repeat loci and partial pedigree information. The two social groups in this study were found to harbor distinct microbial signatures after the fission event from which they emerged, while these communities were not divergent in the same individuals before this event. Three genera were found to differ in abundance between the two new social groups: Parabacteroides, Coprococcus, and Porphyromonadaceae. Additionally, although this fission happened partially along lines of relatedness, relatedness did not structure the differences that we found. Taken together, this study suggests that distinct gut microbial profiles can emerge in social groups in <1 year and recommends further work into more finely mapping the timescales, causes, and potentially adaptive effects of this recurring trend toward distinct group microbial signatures.     

Deep Sequencing Identifies Ethnicity-Specific Bacterial Signatures in the Oral Microbiome

Oral infections have a strong ethnic predilection; suggesting that ethnicity is a critical determinant of oral microbial colonization. Dental plaque and saliva samples from 192 subjects belonging to four major ethnicities in the United States were analyzed using terminal restriction fragment length polymorphism (t-RFLP) and 16S pyrosequencing. Ethnicity-specific clustering of microbial communities was apparent in saliva and subgingival biofilms, and a machine-learning classifier was capable of identifying an individual’s ethnicity from subgingival microbial signatures. The classifier identified African Americans with a 100% sensitivity and 74% specificity and Caucasians with a 50% sensitivity and 91% specificity. The data demonstrates a significant association between ethnic affiliation and the composition of the oral microbiome; to the extent that these microbial signatures appear to be capable of discriminating between ethnicities.     

Dynamics of the Microbiota in Response to Host Infection

Longitudinal studies of the microbiota are important for discovering changes in microbial communities that affect the host. The complexity of these ecosystems requires rigorous integrated experimental and computational methods to identify temporal signatures that promote physiologic or pathophysiologic responses in vivo. Employing a murine model of infectious colitis with the pathogen Citrobacter rodentium, we generated a 2-month time-series of 16S rDNA gene profiles, and quantitatively cultured commensals, from multiple intestinal sites in infected and uninfected mice. We developed a computational framework to discover time-varying signatures for individual taxa, and to automatically group signatures to identify microbial sub-communities within the larger gut ecosystem that demonstrate common behaviors. Application of this model to the 16S rDNA dataset revealed dynamic alterations in the microbiota at multiple levels of resolution, from effects on systems-level metrics to changes across anatomic sites for individual taxa and species. These analyses revealed unique, time-dependent microbial signatures associated with host responses at different stages of colitis. Signatures included a Mucispirillum OTU associated with early disruption of the colonic surface mucus layer, prior to the onset of symptomatic colitis, and members of the Clostridiales and Lactobacillales that increased with successful resolution of inflammation, after clearance of the pathogen. Quantitative culture data validated findings for predominant species, further refining and strengthening model predictions. These findings provide new insights into the complex behaviors found within host ecosystems, and define several time-dependent microbial signatures that may be leveraged in studies of other infectious or inflammatory conditions.     

Abrupt burial imparts persistent changes to the bacterial diversity of turbidite‐associated sediment profiles

The emplacement of subaqueous gravity‐driven sediment flows imposes a significant physical and geochemical impact on underlying sediment and microbial communities. Although previous studies have established lasting mineralogical and biological signatures of turbidite deposition, the response of bacteria and archaea within and beneath debris flows remains poorly constrained. Both bacterial cells associated with the underlying sediment and those attached to allochthonous material must respond to substantially altered environmental conditions and selective pressures. As a consequence, turbidites and underlying sediments provide an exceptional opportunity to examine (i) the microbial community response to rapid sedimentation and (ii) the preservation and identification of displaced micro‐organisms. We collected Illumina MiSeq sequence libraries across turbidite boundaries at ~26 cm sediment depth in La Jolla Canyon off the coast of California, and at ~50 cm depth in meromictic Twin Lake, Hennepin County, MN. 16S rRNA gene signatures of relict and active bacterial populations exhibit persistent differences attributable to turbidite deposition. In particular, both the marine and lacustrine turbidite boundaries are sharply demarcated by the abundance and diversity of Chloroflexi, suggesting a characteristic sensitivity to sediment disturbance history or to differences in organic substrates across turbidite profiles. Variations in the abundance of putative dissimilatory sulfate‐reducing Deltaproteobacteria across the buried La Jolla Canyon sediment–water interface reflect turbidite‐induced changes to the geochemical environment. Species‐level distinctions within the Deltaproteobacteria clearly conform to the sedimentological boundary, suggesting a continuing impact of genetic inheritance distinguishable from broader trends attributable to selective pressure. Abrupt, <1‐cm scale changes in bacterial diversity across the Twin Lake turbidite contact are consistent with previous studies showing that relict DNA signatures attributable to sediment transport may be more easily preserved in low‐energy, anoxic environments. This work raises the possibility that deep subsurface microbial communities may inherit variations in microbial diversity from sediment flow and deformation events.     

Metagenomic and stable isotopic analyses of modern freshwater microbialites in Cuatro Ciénegas, Mexico

Ancient biologically mediated sedimentary carbonate deposits, including stromatolites and other microbialites, provide insight into environmental conditions on early Earth. The primary limitation to interpreting these records is our lack of understanding regarding microbial processes and the preservation of geochemical signatures in contemporary microbialite systems. Using a combination of metagenomic sequencing and isotopic analyses, this study describes the identity, metabolic potential and chemical processes of microbial communities from living microbialites from Cuatro Ciénegas, Mexico. Metagenomic sequencing revealed a diverse, redox-dependent microbial community associated with the microbialites. The microbialite community is distinct from other marine and freshwater microbial communities, and demonstrates extensive environmental adaptation. The microbialite metagenomes contain a large number of genes involved in the production of exopolymeric substances and the formation of biofilms, creating a complex, spatially structured environment. In addition to the spatial complexity of the biofilm, microbial activity is tightly controlled by sensory and regulatory systems, which allow for coordination of autotrophic and heterotrophic processes. Isotopic measurements of the intracrystalline organic matter demonstrate the importance of heterotrophic respiration of photoautotrophic biomass in the precipitation of calcium carbonate. The genomic and stable isotopic data presented here significantly enhance our evolving knowledge of contemporary biomineralization processes, and are directly applicable to studies of ancient microbialites.     

Analysis of Factors Affecting the Accuracy, Reproducibility, and Interpretation of Microbial Community Carbon Source Utilization Patterns

We determined factors that affect responses of bacterial isolates and model bacterial communities to the 95 carbon substrates in Biolog microtiter plates. For isolates and communities of three to six bacterial strains, substrate oxidation rates were typically nonlinear and were delayed by dilution of the inoculum. When inoculum density was controlled, patterns of positive and negative responses exhibited by microbial communities to each of the carbon sources were reproducible. Rates and extents of substrate oxidation by the communities were also reproducible but were not simply the sum of those exhibited by community members when tested separately. Replicates of the same model community clustered when analyzed by principal-components analysis (PCA), and model communities with different compositions were clearly separated on the first PCA axis, which accounted for >60% of the dataset variation. PCA discrimination among different model communities depended on the extent to which specific substrates were oxidized. However, the substrates interpreted by PCA to be most significant in distinguishing the communities changed with reading time, reflecting the nonlinearity of substrate oxidation rates. Although whole-community substrate utilization profiles were reproducible signatures for a given community, the extent of oxidation of specific substrates and the numbers or activities of microorganisms using those substrates in a given community were not correlated. Replicate soil samples varied significantly in the rate and extent of oxidation of seven tested substrates, suggesting microscale heterogeneity in composition of the soil microbial community.     

Advanced computational algorithms for microbial community analysis using massive 16S rRNA sequence data

With the aid of next-generation sequencing technology, researchers can now obtain millions of microbial signature sequences for diverse applications ranging from human epidemiological studies to global ocean surveys. The development of advanced computational strategies to maximally extract pertinent information from massive nucleotide data has become a major focus of the bioinformatics community. Here, we describe a novel analytical strategy including discriminant and topology analyses that enables researchers to deeply investigate the hidden world of microbial communities, far beyond basic microbial diversity estimation. We demonstrate the utility of our approach through a computational study performed on a previously published massive human gut 16S rRNA data set. The application of discriminant and topology analyses enabled us to derive quantitative disease-associated microbial signatures and describe microbial community structure in far more detail than previously achievable. Our approach provides rigorous statistical tools for sequence-based studies aimed at elucidating associations between known or unknown organisms and a variety of physiological or environmental conditions.     

The Average Mutual Information Profile as a Genomic Signature

Background  

Occult organizational structures in DNA sequences may hold the key to understanding functional and evolutionary aspects of the DNA molecule. Such structures can also provide the means for identifying and discriminating organisms using genomic data. Species specific genomic signatures are useful in a variety of contexts such as evolutionary analysis, assembly and classification of genomic sequences from large uncultivated microbial communities and a rapid identification system in health hazard situations.     

Cloacal microbial communities of female spotted towhees Pipilo maculatus: microgeographic variation and individual sources of variability

We used Polymerase Chain Reaction (PCR) amplification of 16S rRNA genes and Denaturing Gradient Gel Electrophoresis (DGGE) to describe the microbial communities present in the cloacae of spotted towhees Pipilo maculatus. Our goals were to quantify bacterial diversity of breeding females, describe microgeographic variation of cloacal communities in a network of four urban parks in Portland, OR, and evaluate the degree to which microbial species richness varied with individual female characteristics (age, size, and condition). We detected 57 Operational Taxonomic Units (OTUs) in 46 towhees, but most OTUs showed a relatively low prevalence. Discriminant function analysis correctly classified 69.6% of towhees to their park of origin based on the presence or absence of five OTUs. Parks thus had unique “microbial signatures”. The presence or absence of specific OTUs was not associated with a female's age, but a general linear models analysis established that OTU richness was greatest among females with short tails, narrow bills, and with the exception of one individual, among relatively heavy birds. We speculate that the microgeographic differences in cloacal microbial community structure may exist due to differences in anthropogenic influences among parks. The explanations for the negative relationship between microbial richness and flight feather length, but positive relationship between microbial richness and body condition are unclear, but may reflect the different time frames over which feather growth and body mass are determined.     

Human and Environmental Impacts on River Sediment Microbial Communities

Sediment microbial communities are responsible for a majority of the metabolic activity in river and stream ecosystems. Understanding the dynamics in community structure and function across freshwater environments will help us to predict how these ecosystems will change in response to human land-use practices. Here we present a spatiotemporal study of sediments in the Tongue River (Montana, USA), comprising six sites along 134 km of river sampled in both spring and fall for two years. Sequencing of 16S rRNA amplicons and shotgun metagenomes revealed that these sediments are the richest (∼65,000 microbial ‘species’ identified) and most novel (93% of OTUs do not match known microbial diversity) ecosystems analyzed by the Earth Microbiome Project to date, and display more functional diversity than was detected in a recent review of global soil metagenomes. Community structure and functional potential have been significantly altered by anthropogenic drivers, including increased pathogenicity and antibiotic metabolism markers near towns and metabolic signatures of coal and coalbed methane extraction byproducts. The core (OTUs shared across all samples) and the overall microbial community exhibited highly similar structure, and phylogeny was weakly coupled with functional potential. Together, these results suggest that microbial community structure is shaped by environmental drivers and niche filtering, though stochastic assembly processes likely play a role as well. These results indicate that sediment microbial communities are highly complex and sensitive to changes in land use practices.     

Inferring dynamic signatures of microbes in complex host ecosystems

The human gut microbiota comprise a complex and dynamic ecosystem that profoundly affects host development and physiology. Standard approaches for analyzing time-series data of the microbiota involve computation of measures of ecological community diversity at each time-point, or measures of dissimilarity between pairs of time-points. Although these approaches, which treat data as static snapshots of microbial communities, can identify shifts in overall community structure, they fail to capture the dynamic properties of individual members of the microbiota and their contributions to the underlying time-varying behavior of host ecosystems. To address the limitations of current methods, we present a computational framework that uses continuous-time dynamical models coupled with Bayesian dimensionality adaptation methods to identify time-dependent signatures of individual microbial taxa within a host as well as across multiple hosts. We apply our framework to a publicly available dataset of 16S rRNA gene sequences from stool samples collected over ten months from multiple human subjects, each of whom received repeated courses of oral antibiotics. Using new diversity measures enabled by our framework, we discover groups of both phylogenetically close and distant bacterial taxa that exhibit consensus responses to antibiotic exposure across multiple human subjects. These consensus responses reveal a timeline for equilibration of sub-communities of micro-organisms with distinct physiologies, yielding insights into the successive changes that occur in microbial populations in the human gut after antibiotic treatments. Additionally, our framework leverages microbial signatures shared among human subjects to automatically design optimal experiments to interrogate dynamic properties of the microbiota in new studies. Overall, our approach provides a powerful, general-purpose framework for understanding the dynamic behaviors of complex microbial ecosystems, which we believe will prove instrumental for future studies in this field.     

To What Extent Do Food Preferences Explain the Trophic Position of Heterotrophic and Mixotrophic Microbial Consumers in a Sphagnum Peatland?

Although microorganisms are the primary drivers of biogeochemical cycles, the structure and functioning of microbial food webs are poorly studied. This is the case in Sphagnum peatlands, where microbial communities play a key role in the global carbon cycle. Here, we explored the structure of the microbial food web from a Sphagnum peatland by analyzing (1) the density and biomass of different microbial functional groups, (2) the natural stable isotope (δ ¹³C and δ ¹⁵N) signatures of key microbial consumers (testate amoebae), and (3) the digestive vacuole contents of Hyalosphenia papilio, the dominant testate amoeba species in our system. Our results showed that the feeding type of testate amoeba species (bacterivory, algivory, or both) translates into their trophic position as assessed by isotopic signatures. Our study further demonstrates, for H. papilio, the energetic benefits of mixotrophy when the density of its preferential prey is low. Overall, our results show that testate amoebae occupy different trophic levels within the microbial food web, depending on their feeding behavior, the density of their food resources, and their metabolism (i.e., mixotrophy vs. heterotrophy). Combined analyses of predation, community structure, and stable isotopes now allow the structure of microbial food webs to be more completely described, which should lead to improved models of microbial community function.     

Sequential bioavailability of sedimentary organic matter to heterotrophic bacteria

Aquatic sediments harbour diverse microbial communities that mediate organic matter degradation and influence biogeochemical cycles. The pool of bioavailable carbon continuously changes as a result of abiotic processes and microbial activity. It remains unclear how microbial communities respond to heterogeneous organic matrices and how this ultimately affects heterotrophic respiration. To explore the relationships between the degradation of mixed carbon substrates and microbial activity, we incubated batches of organic‐rich sediments in a novel bioreactor (IsoCaRB) that permitted continuous observations of CO₂ production rates, as well as sequential sampling of isotopic signatures (δ¹³C, Δ¹⁴C), microbial community structure and diversity, and extracellular enzyme activity. Our results indicated that lower molecular weight (MW), labile, phytoplankton‐derived compounds were degraded first, followed by petroleum‐derived exogenous pollutants, and finally by higher MW polymeric plant material. This shift in utilization coincided with a community succession and increased extracellular enzyme activities. Thus, sequential utilization of different carbon pools induced changes at both the community and cellular level, shifting community composition, enzyme activity, respiration rates, and residual organic matter reactivity. Our results provide novel insight into the accessibility of sedimentary organic matter and demonstrate how bioavailability of natural organic substrates may affect the function and composition of heterotrophic bacterial populations.     

Microbial community structure of surface sediments from a tropical estuarine environment using next generation sequencing

Microbial community structure was analyzed from tropical monsoon influenced Mandovi-Zuari (Ma-Zu) estuarine sediment by means of Next Gen Sequencing (NGS) approach using Ion Torrent PGM™. The sequencing generated 80,282 raw sequence reads. Barcoding with Ion Tags allowed multiplex analysis of microbial community and helped in identifying shifts in microbial community structure. Analysis of sequence data revealed that sediment at both the stations in the Mandovi estuary was dominated by Archaeal group, Euryarchaeota (53.1% and 64.01%). Among Euryarchaeota, Methanomicrobia was dominant. Methanococci was present only at the mouth and Methanopyri was detected at the mid-estuarine station. Whereas, both the stations of Zuari estuary were dominated by Bacteria, Proteobacteria, mainly Gammaproteobacteria (97.67% and 54.41%). A clear influence of mangrove ecosystem on the bacterial diversity was evident in the Zuari estuary. These results suggest that the two estuaries have a very distinct microbial community structure. Characterization of microbial communities in this study area using NGS for the first time points out that even within geographically close habitats, the microbial population structure is significantly influenced by localized interactions. The signatures obtained from sediments can thus be used to reconstruct habitat characteristics and serve as biomarkers. Future studies should focus on the functional gene profiling of different microbial communities and the influence of seasons and tide in such monsoon influenced estuaries.     

Microbiome Profiles in Periodontitis in Relation to Host and Disease Characteristics

Periodontitis is an inflammatory condition that affects the supporting tissues surrounding teeth. The occurrence of periodontitis is associated with shifts in the structure of the communities that inhabit the gingival sulcus. Although great inter-subject variability in the subgingival microbiome has been observed in subjects with periodontitis, it is unclear whether distinct community types exist and if differences in microbial signatures correlate with host characteristics or with the variable clinical presentations of periodontitis. Therefore, in this study we explored the existence of different community types in periodontitis and their relationship with host demographic, medical and disease-related clinical characteristics. Clustering analyses of microbial abundance profiles suggested two types of communities (A and B) existed in the 34 subjects with periodontitis evaluated. Type B communities harbored greater proportions of certain periodontitis-associated taxa, including species historically associated with the disease, such as Porphyromonas gingivalis, Tannerella forsythia and Treponema denticola, and taxa recently linked to periodontitis. In contrast, subjects with type A communities had increased proportions of different periodontitis-associated species, and were also enriched for health-associated species and core taxa (those equally prevalent in health and periodontitis). Periodontitis subgingival clusters were not associated with demographic, medical or disease-specific clinical parameters other than periodontitis extent (proportion of sites affected), which positively correlated with the total proportion of cluster B signature taxa. In conclusion, two types of microbial communities were detected in subjects with periodontitis. Host demographics and underlying medical conditions did not correlate with these profiles, which instead appeared to be related to periodontitis extent, with type B communities present in more widespread disease cases. The two identified periodontitis profiles may represent distinct dysbiotic processes potentially requiring community-tailored therapeutic interventions.     

Microbes in high arctic snow and implications for the cold biosphere

We applied molecular, microscopic, and culture techniques to characterize the microbial communities in snow and air at remote sites in the Canadian High Arctic (Ward Hunt Island, Ellesmere Island, and Cornwallis Island, latitudes 74 to 83(o)N). Members of the Bacteria and Eukarya were prevalent in the snow, and their small subunit (SSU) rRNA gene signatures indicated strong local aerial transport within the region over the preceding 8 months of winter snowpack accumulation. Many of the operational taxonomic units (OTUs) were similar to previously reported SSU rRNA gene sequences from the Arctic Ocean, suggesting the importance of local aerial transport processes for marine microbiota. More than 47% of the cyanobacterial OTUs in the snow have been previously found in microbial mats in the region, indicating that this group was also substantially derived from local sources. Viable cyanobacteria isolated from the snow indicated free exchange between the snow and adjacent mat communities. Other sequences were most similar to those found outside the Canadian Arctic but were from snow, lake and sea ice, glaciers and permafrost, alpine regions, Antarctica, and other regions of the Arctic, supporting the concept of global distribution of microbial ecotypes throughout the cold biosphere.     

The Microbial Community Structure in Petroleum-Contaminated Sediments Corresponds to Geophysical Signatures

The interdependence between geoelectrical signatures at underground petroleum plumes and the structures of subsurface microbial communities was investigated. For sediments contaminated with light non-aqueous-phase liquids, anomalous high conductivity values have been observed. Vertical changes in the geoelectrical properties of the sediments were concomitant with significant changes in the microbial community structures as determined by the construction and evaluation of 16S rRNA gene libraries. DNA sequencing of clones from four 16S rRNA gene libraries from different depths of a contaminated field site and two libraries from an uncontaminated background site revealed spatial heterogeneity in the microbial community structures. Correspondence analysis showed that the presence of distinct microbial populations, including the various hydrocarbon-degrading, syntrophic, sulfate-reducing, and dissimilatory-iron-reducing populations, was a contributing factor to the elevated geoelectrical measurements. Thus, through their growth and metabolic activities, microbial populations that have adapted to the use of petroleum as a carbon source can strongly influence their geophysical surroundings. Since changes in the geophysical properties of contaminated sediments parallel changes in the microbial community compositions, it is suggested that geoelectrical measurements can be a cost-efficient tool to guide microbiological sampling for microbial ecology studies during the monitoring of natural or engineered bioremediation processes.