Novel bacterial taxa in the human microbiome

The human gut harbors thousands of bacterial taxa. A profusion of metagenomic sequence data has been generated from human stool samples in the last few years, raising the question of whether more taxa remain to be identified. We assessed metagenomic data generated by the Human Microbiome Project Consortium to determine if novel taxa remain to be discovered in stool samples from healthy individuals. To do this, we established a rigorous bioinformatics pipeline that uses sequence data from multiple platforms (Illumina GAIIX and Roche 454 FLX Titanium) and approaches (whole-genome shotgun and 16S rDNA amplicons) to validate novel taxa. We applied this approach to stool samples from 11 healthy subjects collected as part of the Human Microbiome Project. We discovered several low-abundance, novel bacterial taxa, which span three major phyla in the bacterial tree of life. We determined that these taxa are present in a larger set of Human Microbiome Project subjects and are found in two sampling sites (Houston and St. Louis). We show that the number of false-positive novel sequences (primarily chimeric sequences) would have been two orders of magnitude higher than the true number of novel taxa without validation using multiple datasets, highlighting the importance of establishing rigorous standards for the identification of novel taxa in metagenomic data. The majority of novel sequences are related to the recently discovered genus Barnesiella, further encouraging efforts to characterize the members of this genus and to study their roles in the microbial communities of the gut. A better understanding of the effects of less-abundant bacteria is important as we seek to understand the complex gut microbiome in healthy individuals and link changes in the microbiome to disease.     

The "most wanted" taxa from the human microbiome for whole genome sequencing

The goal of the Human Microbiome Project (HMP) is to generate a comprehensive catalog of human-associated microorganisms including reference genomes representing the most common species. Toward this goal, the HMP has characterized the microbial communities at 18 body habitats in a cohort of over 200 healthy volunteers using 16S rRNA gene (16S) sequencing and has generated nearly 1,000 reference genomes from human-associated microorganisms. To determine how well current reference genome collections capture the diversity observed among the healthy microbiome and to guide isolation and future sequencing of microbiome members, we compared the HMP's 16S data sets to several reference 16S collections to create a 'most wanted' list of taxa for sequencing. Our analysis revealed that the diversity of commonly occurring taxa within the HMP cohort microbiome is relatively modest, few novel taxa are represented by these OTUs and many common taxa among HMP volunteers recur across different populations of healthy humans. Taken together, these results suggest that it should be possible to perform whole-genome sequencing on a large fraction of the human microbiome, including the 'most wanted', and that these sequences should serve to support microbiome studies across multiple cohorts. Also, in stark contrast to other taxa, the 'most wanted' organisms are poorly represented among culture collections suggesting that novel culture- and single-cell-based methods will be required to isolate these organisms for sequencing.     

微生物组大数据管理与分析

高通量技术的迅猛发展促使微生物生态学研究获得了重大突破,掀起了元基因组学(Metagenomics)研究的热潮。元基因组学通常被定义为对未培养的环境样本中微生物群体的DNA序列分析。随着微生物组学数据的日益剧增,微生物大数据的高效管理与分析越来越受到研究者的关注。如何从海量的微生物组数据中挖掘出具有科研价值的数据信息并应用于实际问题成为当前的研究热点。目前已有很多计算生物学程序工具及数据库用于元基因组数据的分析与管理。本文主要综述了随着高通量测序技术的进步,国际上主要的微生物组计划及微生物组数据平台,如人类微生物组项目(human microbiome project,HMP)、地球微生物组项目(earth microbiome project,EMP)、欧盟的肠道微生物组计划(metagenomics of human intestinal tract,MetaHIT)、MG-RAST、i Microbe、整合微生物组(integration microbial genomes,IMG)以及EBI Metagenomics等;介绍了微生物数据分析的主要流程与工具;提出了建设多源异构的微生物生态数据管理与分析系统的必要性。     

Two-stage microbial community experimental design

Microbial community samples can be efficiently surveyed in high throughput by sequencing markers such as the 16S ribosomal RNA gene. Often, a collection of samples is then selected for subsequent metagenomic, metabolomic or other follow-up. Two-stage study design has long been used in ecology but has not yet been studied in-depth for high-throughput microbial community investigations. To avoid ad hoc sample selection, we developed and validated several purposive sample selection methods for two-stage studies (that is, biological criteria) targeting differing types of microbial communities. These methods select follow-up samples from large community surveys, with criteria including samples typical of the initially surveyed population, targeting specific microbial clades or rare species, maximizing diversity, representing extreme or deviant communities, or identifying communities distinct or discriminating among environment or host phenotypes. The accuracies of each sampling technique and their influences on the characteristics of the resulting selected microbial community were evaluated using both simulated and experimental data. Specifically, all criteria were able to identify samples whose properties were accurately retained in 318 paired 16S amplicon and whole-community metagenomic (follow-up) samples from the Human Microbiome Project. Some selection criteria resulted in follow-up samples that were strongly non-representative of the original survey population; diversity maximization particularly undersampled community configurations. Only selection of intentionally representative samples minimized differences in the selected sample set from the original microbial survey. An implementation is provided as the microPITA (Microbiomes: Picking Interesting Taxa for Analysis) software for two-stage study design of microbial communities.     

The Human Microbiome Project in 2011 and beyond

The human microbiome comprises the genes and genomes of the microbiota that inhabit the body. We highlight Human Microbiome Project (HMP) resources, including 600 microbial reference genomes, 70 million 16S sequences, 700 metagenomes, and 60 million predicted genes from healthy adult microbiomes. Microbiome studies of specific diseases and future research directions are also discussed.     

Worlds within worlds: evolution of the vertebrate gut microbiota

In this Analysis we use published 16S ribosomal RNA gene sequences to compare the bacterial assemblages that are associated with humans and other mammals, metazoa and free-living microbial communities that span a range of environments. The composition of the vertebrate gut microbiota is influenced by diet, host morphology and phylogeny, and in this respect the human gut bacterial community is typical of an omnivorous primate. However, the vertebrate gut microbiota is different from free-living communities that are not associated with animal body habitats. We propose that the recently initiated international Human Microbiome Project should strive to include a broad representation of humans, as well as other mammalian and environmental samples, as comparative analyses of microbiotas and their microbiomes are a powerful way to explore the evolutionary history of the biosphere.     

The Prevalence of Species and Strains in the Human Microbiome: A Resource for Experimental Efforts

Experimental efforts to characterize the human microbiota often use bacterial strains that were chosen for historical rather than biological reasons. Here, we report an analysis of 380 whole-genome shotgun samples from 100 subjects from the NIH Human Microbiome Project. By mapping their reads to 1,751 reference genome sequences and analyzing the resulting relative strain abundance in each sample we present metrics and visualizations that can help identify strains of interest for experimentalists. We also show that approximately 14 strains of 10 species account for 80% of the mapped reads from a typical stool sample, indicating that the function of a community may not be irreducibly complex. Some of these strains account for >20% of the sequence reads in a subset of samples but are absent in others, a dichotomy that could underlie biological differences among subjects. These data should serve as an important strain selection resource for the community of researchers who take experimental approaches to studying the human microbiota.     

Illumina-based analysis of microbial community diversity

Microbes commonly exist in milieus of varying complexity and diversity. Although cultivation-based techniques have been unable to accurately capture the true diversity within microbial communities, these deficiencies have been overcome by applying molecular approaches that target the universally conserved 16S ribosomal RNA gene. The recent application of 454 pyrosequencing to simultaneously sequence thousands of 16S rDNA sequences (pyrotags) has revolutionized the characterization of complex microbial communities. To date, studies based on 454 pyrotags have dominated the field, but sequencing platforms that generate many more sequence reads at much lower costs have been developed. Here, we use the Illumina sequencing platform to design a strategy for 16S amplicon analysis (iTags), and assess its generality, practicality and potential complications. We fabricated and sequenced paired-end libraries of amplified hyper-variable 16S rDNA fragments from sets of samples that varied in their contents, ranging from a single bacterium to highly complex communities. We adopted an approach that allowed us to evaluate several potential sources of errors, including sequencing artifacts, amplification biases, non-corresponding paired-end reads and mistakes in taxonomic classification. By considering each source of error, we delineate ways to make biologically relevant and robust conclusions from the millions of sequencing reads that can be readily generated by this technology.     

Bacterial diversity and community composition in the chemocline of the meromictic alpine Lake Cadagno as revealed by 16S rDNA analysis

Using different techniques of molecular biology we investigated the bacterial diversity of the chemocline of the meromictic Lake Cadagno. Cloning of a total community 16S rDNA PCR product and subsequent screening with a combination of amplified ribosomal DNA restriction analysis and temporal temperature gradient gel electrophoresis (TTGE) analysis revealed that 30 of 47 randomly selected clones were unique. Partial sequencing and comparative analysis indicated a high bacterial diversity dominated by the gamma-Proteobacteria (33.3%). Most of these rDNA clone sequences were not closely related to any 16S rDNA sequence in the database. In a second approach, the TTGE pattern from an environmental sample was compared with the migration of the cloned 16S rDNA fragments. Four clone types were identified on the environmental pattern by excising and sequencing comigrating bands, three of which were well represented in the library: two Chromatiaceae species and one sequence affiliated with the Desulfobulbus assemblage. Using the fluorescent in situ hybridization technique we essentially confirmed the results of the cloning experiments and the TTGE analysis.     

Analyses of the microbial diversity across the human microbiome

Analysis of human body microbial diversity is fundamental to understanding community structure, biology and ecology. The National Institutes of Health Human Microbiome Project (HMP) has provided an unprecedented opportunity to examine microbial diversity within and across body habitats and individuals through pyrosequencing-based profiling of 16 S rRNA gene sequences (16 S) from habits of the oral, skin, distal gut, and vaginal body regions from over 200 healthy individuals enabling the application of statistical techniques. In this study, two approaches were applied to elucidate the nature and extent of human microbiome diversity. First, bootstrap and parametric curve fitting techniques were evaluated to estimate the maximum number of unique taxa, S(max), and taxa discovery rate for habitats across individuals. Next, our results demonstrated that the variation of diversity within low abundant taxa across habitats and individuals was not sufficiently quantified with standard ecological diversity indices. This impact from low abundant taxa motivated us to introduce a novel rank-based diversity measure, the Tail statistic, ("τ"), based on the standard deviation of the rank abundance curve if made symmetric by reflection around the most abundant taxon. Due to τ's greater sensitivity to low abundant taxa, its application to diversity estimation of taxonomic units using taxonomic dependent and independent methods revealed a greater range of values recovered between individuals versus body habitats, and different patterns of diversity within habitats. The greatest range of τ values within and across individuals was found in stool, which also exhibited the most undiscovered taxa. Oral and skin habitats revealed variable diversity patterns, while vaginal habitats were consistently the least diverse. Collectively, these results demonstrate the importance, and motivate the introduction, of several visualization and analysis methods tuned specifically for next-generation sequence data, further revealing that low abundant taxa serve as an important reservoir of genetic diversity in the human microbiome.     

Mathematical modeling of 16S ribosomal DNA amplification reveals optimal conditions for the interrogation of complex microbial communities with phylogenetic microarrays

MOTIVATION: Many current studies of complex microbial communities rely on the isolation of community genomic DNA, amplification of 16S ribosomal RNA genes (rDNA) and subsequent examination of community structure through interrogation of the amplified 16S rDNA pool by high-throughput sequencing, phylogenetic microarrays or quantitative PCR. RESULTS: Here we describe the development of a mathematical model aimed to simulate multitemplate amplification of 16S ribosomal DNA sample and subsequent detection of these amplified 16S rDNA species by phylogenetic microarray. Using parameters estimated from the experimental results obtained in the analysis of intestinal microbial communities with Microbiota Array, we show that both species detection and the accuracy of species abundance estimates depended heavily on the number of PCR cycles used to amplify 16S rDNA. Both parameters initially improved with each additional PCR cycle and reached optimum between 15 and 20 cycles of amplification. The use of more than 20 cycles of PCR amplification and/or more than 50 ng of starting genomic DNA template was, however, detrimental to both the fraction of detected community members and the accuracy of abundance estimates. Overall, the outcomes of the model simulations matched well available experimental data. Our simulations also showed that species detection and the accuracy of abundance measurements correlated positively with the higher sample-wide PCR amplification rate, lower template-to-template PCR bias and lower number of species in the interrogated community. The developed model can be easily modified to simulate other multitemplate DNA mixtures as well as other microarray designs and PCR amplification protocols.     

Development of a Prokaryotic Universal Primer for Simultaneous Analysis of Bacteria and Archaea Using Next-Generation Sequencing

For the analysis of microbial community structure based on 16S rDNA sequence diversity, sensitive and robust PCR amplification of 16S rDNA is a critical step. To obtain accurate microbial composition data, PCR amplification must be free of bias; however, amplifying all 16S rDNA species with equal efficiency from a sample containing a large variety of microorganisms remains challenging. Here, we designed a universal primer based on the V3-V4 hypervariable region of prokaryotic 16S rDNA for the simultaneous detection of Bacteria and Archaea in fecal samples from crossbred pigs (Landrace×Large white×Duroc) using an Illumina MiSeq next-generation sequencer. In-silico analysis showed that the newly designed universal prokaryotic primers matched approximately 98.0% of Bacteria and 94.6% of Archaea rRNA gene sequences in the Ribosomal Database Project database. For each sequencing reaction performed with the prokaryotic universal primer, an average of 69,330 (±20,482) reads were obtained, of which archaeal rRNA genes comprised approximately 1.2% to 3.2% of all prokaryotic reads. In addition, the detection frequency of Bacteria belonging to the phylum Verrucomicrobia, including members of the classes Verrucomicrobiae and Opitutae, was higher in the NGS analysis using the prokaryotic universal primer than that performed with the bacterial universal primer. Importantly, this new prokaryotic universal primer set had markedly lower bias than that of most previously designed universal primers. Our findings demonstrate that the prokaryotic universal primer set designed in the present study will permit the simultaneous detection of Bacteria and Archaea, and will therefore allow for a more comprehensive understanding of microbial community structures in environmental samples.     

A Guide to Enterotypes across the Human Body: Meta-Analysis of Microbial Community Structures in Human Microbiome Datasets

Recent analyses of human-associated bacterial diversity have categorized individuals into ‘enterotypes’ or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes.     

FastGroupII: A web-based bioinformatics platform for analyses of large 16S rDNA libraries

Background  

High-throughput sequencing makes it possible to rapidly obtain thousands of 16S rDNA sequences from environmental samples. Bioinformatic tools for the analyses of large 16S rDNA sequence databases are needed to comprehensively describe and compare these datasets.     

Optimizing read mapping to reference genomes to determine composition and species prevalence in microbial communities

The Human Microbiome Project (HMP) aims to characterize the microbial communities of 18 body sites from healthy individuals. To accomplish this, the HMP generated two types of shotgun data: reference shotgun sequences isolated from different anatomical sites on the human body and shotgun metagenomic sequences from the microbial communities of each site. The alignment strategy for characterizing these metagenomic communities using available reference sequence is important to the success of HMP data analysis. Six next-generation aligners were used to align a community of known composition against a database comprising reference organisms known to be present in that community. All aligners report nearly complete genome coverage (>97%) for strains with over 6X depth of coverage, however they differ in speed, memory requirement and ease of use issues such as database size limitations and supported mapping strategies. The selected aligner was tested across a range of parameters to maximize sensitivity while maintaining a low false positive rate. We found that constraining alignment length had more impact on sensitivity than does constraining similarity in all cases tested. However, when reference species were replaced with phylogenetic neighbors, similarity begins to play a larger role in detection. We also show that choosing the top hit randomly when multiple, equally strong mappings are available increases overall sensitivity at the expense of taxonomic resolution. The results of this study identified a strategy that was used to map over 3 tera-bases of microbial sequence against a database of more than 5,000 reference genomes in just over a month.     

Use of Subtractive Hybridization To Design Habitat-Based Oligonucleotide Probes for Investigation of Natural Bacterial Communities

We describe a rapid oligonucleotide probe design strategy based on subtractive hybridization which yields probes for 16S rRNA or rRNA genes of individual members of microbial communities that are specific within the context of those communities. This strategy circumvents the need to sequence many similar or identical clones of dominant members of a community. Radioactively labeled subfragments of a cloned 16S rRNA gene sequence for which a probe is required (target) were hybridized with biotinylated total 16S ribosomal DNA (rDNA) amplified from the microbial community, and the hybrids formed were subsequently discarded. The remaining enriched fragments were used to screen a library consisting of cloned subfragments of the target sequence by colony hybridization in order to identify the variable regions of the 16S rRNA gene with the required specificity. The sequencing of random clones in one 16S rDNA library demonstrated that only those clones with 100% sequence identity with the probe fragment were detected by it. Moreover, sequencing of other, randomly selected, probe-positive clones revealed 100% sequence identity with the probe. Probes developed in this way tended to correspond to more variable regions of the 16S rRNA if the target sequences were similar to the sequences of other clones in the library and to less variable regions if the target sequences were phylogenetically isolated within the clone library. Although the absolute specificity of the latter probes, as assessed by comparison with available database sequences, was lower than the absolute specificity of the probes from the more variable regions, they were specific within the context of the environmental samples from which they were derived.     

A metagenomic approach to characterization of the vaginal microbiome signature in pregnancy

While current major national research efforts (i.e., the NIH Human Microbiome Project) will enable comprehensive metagenomic characterization of the adult human microbiota, how and when these diverse microbial communities take up residence in the host and during reproductive life are unexplored at a population level. Because microbial abundance and diversity might differ in pregnancy, we sought to generate comparative metagenomic signatures across gestational age strata. DNA was isolated from the vagina (introitus, posterior fornix, midvagina) and the V5V3 region of bacterial 16S rRNA genes were sequenced (454FLX Titanium platform). Sixty-eight samples from 24 healthy gravidae (18 to 40 confirmed weeks) were compared with 301 non-pregnant controls (60 subjects). Generated sequence data were quality filtered, taxonomically binned, normalized, and organized by phylogeny and into operational taxonomic units (OTU); principal coordinates analysis (PCoA) of the resultant beta diversity measures were used for visualization and analysis in association with sample clinical metadata. Altogether, 1.4 gigabytes of data containing >2.5 million reads (averaging 6,837 sequences/sample of 493 nt in length) were generated for computational analyses. Although gravidae were not excluded by virtue of a posterior fornix pH >4.5 at the time of screening, unique vaginal microbiome signature encompassing several specific OTUs and higher-level clades was nevertheless observed and confirmed using a combination of phylogenetic, non-phylogenetic, supervised, and unsupervised approaches. Both overall diversity and richness were reduced in pregnancy, with dominance of Lactobacillus species (L. iners crispatus, jensenii and johnsonii, and the orders Lactobacillales (and Lactobacillaceae family), Clostridiales, Bacteroidales, and Actinomycetales. This intergroup comparison using rigorous standardized sampling protocols and analytical methodologies provides robust initial evidence that the vaginal microbial 16S rRNA gene catalogue uniquely differs in pregnancy, with variance of taxa across vaginal subsite and gestational age.     

Community assembly of the native C. elegans microbiome is influenced by time,substrate and individual bacterial taxa

Microbiome communities are complex assemblages of bacteria. The dissection of their assembly dynamics is challenging because it requires repeated sampling of both host and source communities. We used the nematode Caenorhabditis elegans as a model to study these dynamics. We characterized microbiome variation from natural worm populations and their substrates for two consecutive years using 16S rDNA amplicon sequencing. We found conservation in microbiome composition across time at the genus, but not amplicon sequencing variant (ASV) level. Only three ASVs were consistently present across worm samples (Comamonas ASV10859, Pseudomonas ASV7162 and Cellvibrio ASV9073). ASVs were more diverse in worms from different rather than the same substrates, indicating an influence of the source community on microbiome assembly. Surprisingly, almost 50% of worm-associated ASVs were absent in corresponding substrates, potentially due to environmental filtering. Ecological network analysis revealed strong effects of bacteria–bacteria interactions on community composition: While a dominant Erwinia strain correlated with decreased alpha-diversity, predatory bacteria of the Bdellovibrio and like organisms associated with increased alpha-diversity. High alpha-diversity was further linked to high worm population growth, especially on species-poor substrates. Our results highlight that microbiomes are individually shaped and sensitive to dramatic community shifts in response to particular competitive species.