Serum dioxin and DNA methylation in the sperm of operation ranch hand veterans exposed to Agent Orange.

BACKGROUND: Exposure to the herbicide Agent Orange during the Vietnam War was widespread and is associated with numerous adverse health outcomes. A continuing concern of veterans is the possibility that exposure to the dioxin-containing herbicide might induce adverse reproductive outcomes. We sought to assess whether exposure to Agent Orange in Vietnam was associated with changes in DNA methylation in sperm in a subset of Vietnam veterans who participated in the Air Force Health Study (AFHS). METHODS: We studied 37 members of the AFHS chosen to have no, low, medium or high exposure to Agent Orange, based upon serum dioxin levels obtained during a series of examinations. DNA from stored semen was extracted and DNA methylation assessed on the Illumina 450 K platform. RESULTS: Initial epigenome-wide analysis returned no loci that survived control for false discovery. However, the TEAD3 gene had four different CpG sites that showed loss of DNA methylation associated with dioxin exposure. Analysis assessing regional DNA methylation changes revealed 36 gene regions, including the region of the imprinted gene H19 to have altered DNA methylation associated with high exposure compared to the low exposure group. Additional comparison of our data with sperm DNA methylation data from Russian boys exposed to dioxin found an additional 5 loci that were altered in both studies and exhibited a consistent direction of association. CONCLUSIONS: Studying a small number of sperm samples from veterans enrolled in the AFHS, we did not find evidence of significant epigenome-wide alterations associated with exposure to Agent Orange. However, additional analysis showed that the H19 gene region is altered in the sperm of Agent Orange-exposed Ranch Hand veterans. Our study also replicated several findings of a prior study of dioxin-exposed Russian boys. These results provide additional candidate loci for further investigation and may have implications for the reproductive health of dioxin-exposed individuals.

Effects of continuous bisphenol A exposure from early gestation on 90 day old rat testes function and sperm molecular profiles: A CLARITY-BPA consortium study.

Bisphenol A (BPA) is a ubiquitous industrial chemical that has been identified as an endocrine disrupting compound (EDC). There is growing concern that early life exposures to EDCs, such as BPA, can adversely affect the male reproductive tract and function. This study was conducted as part of the Consortium Linking Academic and Regulatory Insights on BPA Toxicity (CLARITY-BPA) to further delineate the toxicities associated with continuous exposure to BPA from early gestation, and to comprehensively examine the elicited effects on testes and sperm. NCTR Sprague Dawley rat dams were gavaged from gestational day (GD) 6 until parturition, and their pups were directly gavaged daily from postnatal day (PND) 1 to 90 with BPA (2.5, 25, 250, 2500, 25,000, 250,000 µg/kg/d) or vehicle control. At PND 90, the testes and sperm were collected for evaluation. The testes were histologically evaluated for altered germ cell apoptosis, sperm production, and altered spermiation. RNA and DNA isolated from sperm were assessed for elicited changes in global mRNA transcript abundance and altered DNA methylation. Effects of BPA were observed in changes in body, testis and epididymis weights only at the highest administered dose of BPA of 250,000 µg/kg/d. Genome-wide transcriptomic and epigenomic analyses failed to detect robust alterations in sperm mRNA and DNA methylation levels. These data indicate that prolonged exposure starting in utero to BPA over a wide range of levels has little, if any, impact on the testes and sperm molecular profiles of 90 day old rats as assessed by the histopathologic, morphometric, and molecular endpoints evaluated.

Oligotyping analysis of the human oral microbiome.

The Human Microbiome Project provided a census of bacterial populations in healthy individuals, but an understanding of the biomedical significance of this census has been hindered by limited taxonomic resolution. A high-resolution method termed oligotyping overcomes this limitation by evaluating individual nucleotide positions using Shannon entropy to identify the most information-rich nucleotide positions, which then define oligotypes. We have applied this method to comprehensively analyze the oral microbiome. Using Human Microbiome Project 16S rRNA gene sequence data for the nine sites in the oral cavity, we identified 493 oligotypes from the V1-V3 data and 360 oligotypes from the V3-V5 data. We associated these oligotypes with species-level taxon names by comparison with the Human Oral Microbiome Database. We discovered closely related oligotypes, differing sometimes by as little as a single nucleotide, that showed dramatically different distributions among oral sites and among individuals. We also detected potentially pathogenic taxa in high abundance in individual samples. Numerous oligotypes were preferentially located in plaque, others in keratinized gingiva or buccal mucosa, and some oligotypes were characteristic of habitat groupings such as throat, tonsils, tongue dorsum, hard palate, and saliva. The differing habitat distributions of closely related oligotypes suggest a level of ecological and functional biodiversity not previously recognized. We conclude that the Shannon entropy approach of oligotyping has the capacity to analyze entire microbiomes, discriminate between closely related but distinct taxa and, in combination with habitat analysis, provide deep insight into the microbial communities in health and disease.

DRISEE overestimates errors in metagenomic sequencing data.

The extremely high error rates reported by Keegan et al. in 'A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE' (PLoS Comput Biol 2012; 8: :e1002541) for many next-generation sequencing datasets prompted us to re-examine their results. Our analysis reveals that the presence of conserved artificial sequences, e.g. Illumina adapters, and other naturally occurring sequence motifs accounts for most of the reported errors. We conclude that DRISEE reports inflated levels of sequencing error, particularly for Illumina data. Tools offered for evaluating large datasets need scrupulous review before they are implemented.

Patterns of gene expression and DNA methylation in human fetal and adult liver.

BACKGROUND: DNA methylation is an important epigenetic control mechanism that has been shown to be associated with gene silencing through the course of development, maturation and aging. However, only limited data are available regarding the relationship between methylation and gene expression in human development. RESULTS: We analyzed the methylome and transcriptome of three human fetal liver samples (gestational age 20-22 weeks) and three adult human liver samples. Genes whose expression differed between fetal and adult numbered 7,673. Adult overexpression was associated with metabolic pathways and, in particular, cytochrome P450 enzymes while fetal overexpression reflected enrichment for DNA replication and repair. Analysis for DNA methylation using the Illumina Infinium 450 K HumanMethylation BeadChip showed that 42% of the quality filtered 426,154 methylation sites differed significantly between adult and fetal tissue (q ≤ 0.05). Differences were small; 69% of the significant sites differed in their mean methylation beta value by ≤0.2. There was a trend among all sites toward higher methylation in the adult samples with the most frequent difference in beta being 0.1. Characterization of the relationship between methylation and expression revealed a clear difference between fetus and adult. Methylation of genes overexpressed in fetal liver showed the same pattern as seen for genes that were similarly expressed in fetal and adult liver. In contrast, adult overexpressed genes showed fetal hypermethylation that differed from the similarly expressed genes. An examination of gene region-specific methylation showed that sites proximal to the transcription start site or within the first exon with a significant fetal-adult difference in beta (>0.2) showed an inverse relationship with gene expression. CONCLUSIONS: Nearly half of the CpGs in human liver show a significant difference in methylation comparing fetal and adult samples. Sites proximal to the transcription start site or within the first exon that show a transition from hypermethylation in the fetus to hypomethylation or intermediate methylation in the adult are associated with inverse changes in gene expression. In contrast, increases in methylation going from fetal to adult are not associated with fetal-to-adult decreased expression. These findings indicate fundamentally different roles for and/or regulation of DNA methylation in human fetal and adult liver.

VAMPS: a website for visualization and analysis of microbial population structures.

BACKGROUND: The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 105-108 reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. RESULTS: We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators' private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. CONCLUSIONS: VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.

A large-scale benchmark study of existing algorithms for taxonomy-independent microbial community analysis.

Recent advances in massively parallel sequencing technology have created new opportunities to probe the hidden world of microbes. Taxonomy-independent clustering of the 16S rRNA gene is usually the first step in analyzing microbial communities. Dozens of algorithms have been developed in the last decade, but a comprehensive benchmark study is lacking. Here, we survey algorithms currently used by microbiologists, and compare seven representative methods in a large-scale benchmark study that addresses several issues of concern. A new experimental protocol was developed that allows different algorithms to be compared using the same platform, and several criteria were introduced to facilitate a quantitative evaluation of the clustering performance of each algorithm. We found that existing methods vary widely in their outputs, and that inappropriate use of distance levels for taxonomic assignments likely resulted in substantial overestimates of biodiversity in many studies. The benchmark study identified our recently developed ESPRIT-Tree, a fast implementation of the average linkage-based hierarchical clustering algorithm, as one of the best algorithms available in terms of computational efficiency and clustering accuracy.

The stage-specific testicular germ cell apoptotic response to low-dose radiation and 2,5-hexanedione combined exposure. II: qRT-PCR array analysis reveals dose dependent adaptive alterations in the apoptotic pathway.

Testicular effects of chemical mixtures may differ from those of the individual chemical constituents. This study assessed the co-exposure effects of the model germ cell- and Sertoli cell-specific toxicants, X-irradiation (x-ray), and 2,5-hexanedione (HD), respectively. In high-dose studies, HD has been shown to attenuate x-ray-induced germ cell apoptosis. Adult rats were exposed to different levels of x-ray (0.5 Gy, 1 Gy, and 2 Gy) or HD (0.33%), either alone or in combination. To assess cell type-specific attenuation of x-ray effects with HD co-exposure, we used laser capture microdissection (LCM) to enrich the targeted cell population and examine a panel of apoptosis-related transcripts using PCR arrays. The apoptosis PCR arrays identified significant dose-dependent treatment effects on several genes, with downregulation of death receptor 5 (DR5), Naip2, Sphk2, Casp7, Aven, Birc3, and upregulation of Fas. The greatest difference in transcript response to exposure was seen with 0.5 Gy x-ray exposure, and the attenuation effect seen with the combined high-dose x-ray and HD did not persist into the low-dose range. Examination of protein levels in staged tubules revealed a significant upregulation in DR5, following high-dose co-exposure. These results provide insight into the testis cell-specific apoptotic response to low-dose co-exposures of model testicular toxicants.

The stage-specific testicular germ cell apoptotic response to low-dose X-irradiation and 2,5-hexanedione combined exposure. I: Validation of the laser capture microdissection method for qRT-PCR array application.

Over the past decade, laser capture microdissection (LCM) has grown as a tool for gene expression profiling of small numbers of cells from tumor samples and of specific cell populations in complex tissues. LCM can be used to study toxicant effects on selected cell populations within the testis at different stages of spermatogenesis. There are several LCM-related hurdles to overcome, including issues inherent to the method itself, as well as biases that result from amplifying the LCM-isolated RNA. Many technical issues associated with the LCM method are addressed here, including increasing RNA yield and obtaining more accurate quantification of RNA yields. We optimized the LCM method optimized to generate RNA quantities sufficient for quantitative reverse transcription polymerase chain reaction (qRT-PCR) array analysis without amplification and were able to validate the method through direct comparison of results from unamplified and amplified RNA from individual samples. The addition of an amplification step for gene expression studies using LCM RNA resulted in a bias, especially for low abundance transcripts. Although the amplification bias was consistent across samples, researchers should use caution when comparing results generated from amplified and unamplified LCM RNA. Here, we have validated the use of LCM-derived RNA with the qRT-PCR array, improving our ability to investigate cell-type and stage-specific responses to toxicant exposures.

TaxMan: a server to trim rRNA reference databases and inspect taxonomic coverage.

Amplicon sequencing of the hypervariable regions of the small subunit ribosomal RNA gene is a widely accepted method for identifying the members of complex bacterial communities. Several rRNA gene sequence reference databases can be used to assign taxonomic names to the sequencing reads using BLAST, USEARCH, GAST or the RDP classifier. Next-generation sequencing methods produce ample reads, but they are short, currently ∼100-450 nt (depending on the technology), as compared to the full rRNA gene of ∼1550 nt. It is important, therefore, to select the right rRNA gene region for sequencing. The primers should amplify the species of interest and the hypervariable regions should differentiate their taxonomy. Here, we introduce TaxMan: a web-based tool that trims reference sequences based on user-selected primer pairs and returns an assessment of the primer specificity by taxa. It allows interactive plotting of taxa, both amplified and missed in silico by the primers used. Additionally, using the trimmed sequences improves the speed of sequence matching algorithms. The smaller database greatly improves run times (up to 98%) and memory usage, not only of similarity searching (BLAST), but also of chimera checking (UCHIME) and of clustering the reads (UCLUST). TaxMan is available at http://www.ibi.vu.nl/programs/taxmanwww/.

Maturation of the developing human fetal prostate in a rodent xenograft model.

BACKGROUND: Prostate cancer is the most commonly diagnosed nonskin cancer in men. The etiology of prostate cancer is unknown, although both animal and epidemiologic data suggest that early life exposures to various toxicants, may impact DNA methylation status during development, playing an important role. METHODS: We have developed a xenograft model to characterize the growth and differentiation of human fetal prostate implants (gestational age 12-24 weeks) that can provide new data on the potential role of early life stressors on prostate cancer. The expression of key immunohistochemical markers responsible for prostate maturation was evaluated, including p63, cytokeratin 18, α-smooth muscle actin, vimentin, caldesmon, Ki-67, prostate-specific antigen, estrogen receptor-α, and androgen receptor. Xenografts were separated into epithelial and stromal compartments using laser capture microdissection (LCM), and the DNA methylation status was assessed in >480,000 CpG sites throughout the genome. RESULTS: Xenografts demonstrated growth and maturation throughout the 200 days of post-implantation evaluation. DNA methylation profiles of laser capture microdissected tissue demonstrated tissue-specific markers clustered by their location in either the epithelium or stroma of human prostate tissue. Differential methylated promoter region CpG-associated gene analysis revealed significantly more stromal than epithelial DNA methylation in the 30- and 90-day xenografts. Functional classification analysis identified CpG-related gene clusters in methylated epithelial and stromal human xenografts. CONCLUSION: This study of human fetal prostate tissue establishes a xenograft model that demonstrates dynamic growth and maturation, allowing for future mechanistic studies of the developmental origins of later life proliferative prostate disease.

Sewage reflects the distribution of human faecal Lachnospiraceae.

Faecal pollution contains a rich and diverse community of bacteria derived from animals and humans, many of which might serve as alternatives to the traditional enterococci and Escherichia coli faecal indicators. We used massively parallel sequencing (MPS) of the 16S rRNA gene to characterize microbial communities from wastewater treatment plant (WWTP) influent sewage from 12 cities geographically distributed across the USA. We examined members of the Clostridiales, which included the families Clostridiaceae, Lachnospiraceae and Ruminococcaceae for their potential as sewage indicators. Lachnospiraceae was one of the most abundant groups of faecal bacteria in sewage, and several Lachnospiraceae high-abundance sewage pyrotags occurred in at least 46 of 48 human faecal samples. Clone libraries targeting Clostridium coccoides (C. coccoides) in sewage samples demonstrated that Lachnospiraceae-annotated V6 pyrotags encompassed the previously reported C. coccoides group. We used oligotyping to profile the genus Blautia within Lachnospiraceae and found oligotypes comprised of 24 entropy components that showed patterns of host specificity. These findings suggest that indicators based on Blautia might have the capacity to discriminate between different faecal pollution sources. Development of source-specific alternative indicators would enhance water quality assessments, which leads to improved ecosystem health and reduced human health risk due to waterborne disease.

Comparison of the microbial community structures of untreated wastewaters from different geographic locales.

Microbial sewage communities consist of a combination of human fecal microorganisms and nonfecal microorganisms, which may be residents of urban sewer infrastructure or flowthrough originating from gray water or rainwater inputs. Together, these different microorganism sources form an identifiable community structure that may serve as a signature for sewage discharges and as candidates for alternative indicators specific for human fecal pollution. However, the structure and variability of this community across geographic space remains uncharacterized. We used massively parallel 454 pyrosequencing of the V6 region in 16S rRNA genes to profile microbial communities from 13 untreated sewage influent samples collected from a wide range of geographic locations in the United States. We obtained a total of 380,175 high-quality sequences for sequence-based clustering, taxonomic analyses, and profile comparisons. The sewage profile included a discernible core human fecal signature made up of several abundant taxonomic groups within Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria. DNA sequences were also classified into fecal, sewage infrastructure (i.e., nonfecal), and transient groups based on data comparisons with fecal samples. Across all sewage samples, an estimated 12.1% of sequences were fecal in origin, while 81.4% were consistently associated with the sewage infrastructure. The composition of feces-derived operational taxonomic units remained congruent across all sewage samples regardless of geographic locale; however, the sewage infrastructure community composition varied among cities, with city latitude best explaining this variation. Together, these results suggest that untreated sewage microbial communities harbor a core group of fecal bacteria across geographically dispersed wastewater sewage lines and that ambient water quality indicators targeting these select core microorganisms may perform well across the United States.

Distance-decay relationships partially determine diversity patterns of phyllosphere bacteria on Tamarix trees across the Sonoran Desert [corrected].

Dispersal limitation in phyllosphere communities was measured on the leaf surfaces of salt-excreting Tamarix trees, which offer unique, discrete habitats for microbial assemblages. We employed 16S rRNA gene pyrosequencing to measure bacterial community dissimilarity on leaves of spatially dispersed Tamarix specimens in sites with uniform climatic conditions across the Sonoran Desert in the Southwestern United States. Our analyses revealed diverse bacterial communities with four dominant phyla that exhibited differential effects of environmental and geographic variables. Geographical distance was the most important parameter that affected community composition, particularly that of betaproteobacteria, which displayed a statistically significant, distance-decay relationship.

Community structures of fecal bacteria in cattle from different animal feeding operations.

The fecal microbiome of cattle plays a critical role not only in animal health and productivity but also in food safety, pathogen shedding, and the performance of fecal pollution detection methods. Unfortunately, most published molecular surveys fail to provide adequate detail about variability in the community structures of fecal bacteria within and across cattle populations. Using massively parallel pyrosequencing of a hypervariable region of the rRNA coding region, we profiled the fecal microbial communities of cattle from six different feeding operations where cattle were subjected to consistent management practices for a minimum of 90 days. We obtained a total of 633,877 high-quality sequences from the fecal samples of 30 adult beef cattle (5 individuals per operation). Sequence-based clustering and taxonomic analyses indicate less variability within a population than between populations. Overall, bacterial community composition correlated significantly with fecal starch concentrations, largely reflected in changes in the Bacteroidetes, Proteobacteria, and Firmicutes populations. In addition, network analysis demonstrated that annotated sequences clustered by management practice and fecal starch concentration, suggesting that the structures of bovine fecal bacterial communities can be dramatically different in different animal feeding operations, even at the phylum and family taxonomic levels, and that the feeding operation is a more important determinant of the cattle microbiome than is the geographic location of the feedlot.

Culture-independent analysis of bacterial fuel contamination provides insight into the level of concordance with the standard industry practice of aerobic cultivation.

Bacterial diversity in contaminated fuels has not been systematically investigated using cultivation-independent methods. The fuel industry relies on phenotypic cultivation-based contaminant identification, which may lack accuracy and neglect difficult-to-culture taxa. By the use of industry practice aerobic cultivation, 16S rRNA gene sequencing, and strain genotyping, a collection of 152 unique contaminant isolates from 54 fuel samples was assembled, and a dominance of Pseudomonas (21%), Burkholderia (7%), and Bacillus (7%) was demonstrated. Denaturing gradient gel electrophoresis (DGGE) of 15 samples revealed Proteobacteria and Firmicutes to be the most abundant phyla. When 16S rRNA V6 gene pyrosequencing of four selected fuel samples (indicated by "JW") was performed, Betaproteobacteria (42.8%) and Gammaproteobacteria (30.6%) formed the largest proportion of reads; the most abundant genera were Marinobacter (15.4%; JW57), Achromobacter (41.6%; JW63), Burkholderia (80.7%; JW76), and Halomonas (66.2%; JW78), all of which were also observed by DGGE. However, the Clostridia (38.5%) and Deltaproteobacteria (11.1%) identified by pyrosequencing in sample JW57 were not observed by DGGE or aerobic culture. Genotyping revealed three instances where identical strains were found: (i) a Pseudomonas sp. strain recovered from 2 different diesel fuel tanks at a single industrial site; (ii) a Mangroveibacter sp. strain isolated from 3 biodiesel tanks at a single refinery site; and (iii) a Burkholderia vietnamiensis strain present in two unrelated automotive diesel samples. Overall, aerobic cultivation of fuel contaminants recovered isolates broadly representative of the phyla and classes present but lacked accuracy by overrepresenting members of certain groups such as Pseudomonas.

Exploring microbial diversity and taxonomy using SSU rRNA hypervariable tag sequencing.

Massively parallel pyrosequencing of hypervariable regions from small subunit ribosomal RNA (SSU rRNA) genes can sample a microbial community two or three orders of magnitude more deeply per dollar and per hour than capillary sequencing of full-length SSU rRNA. As with full-length rRNA surveys, each sequence read is a tag surrogate for a single microbe. However, rather than assigning taxonomy by creating gene trees de novo that include all experimental sequences and certain reference taxa, we compare the hypervariable region tags to an extensive database of rRNA sequences and assign taxonomy based on the best match in a Global Alignment for Sequence Taxonomy (GAST) process. The resulting taxonomic census provides information on both composition and diversity of the microbial community. To determine the effectiveness of using only hypervariable region tags for assessing microbial community membership, we compared the taxonomy assigned to the V3 and V6 hypervariable regions with the taxonomy assigned to full-length SSU rRNA sequences isolated from both the human gut and a deep-sea hydrothermal vent. The hypervariable region tags and full-length rRNA sequences provided equivalent taxonomy and measures of relative abundance of microbial communities, even for tags up to 15% divergent from their nearest reference match. The greater sampling depth per dollar afforded by massively parallel pyrosequencing reveals many more members of the "rare biosphere" than does capillary sequencing of the full-length gene. In addition, tag sequencing eliminates cloning bias and the sequences are short enough to be completely sequenced in a single read, maximizing the number of organisms sampled in a run while minimizing chimera formation. This technique allows the cost-effective exploration of changes in microbial community structure, including the rare biosphere, over space and time and can be applied immediately to initiatives, such as the Human Microbiome Project.

Ironing out the wrinkles in the rare biosphere through improved OTU clustering.

Deep sequencing of PCR amplicon libraries facilitates the detection of low-abundance populations in environmental DNA surveys of complex microbial communities. At the same time, deep sequencing can lead to overestimates of microbial diversity through the generation of low-frequency, error-prone reads. Even with sequencing error rates below 0.005 per nucleotide position, the common method of generating operational taxonomic units (OTUs) by multiple sequence alignment and complete-linkage clustering significantly increases the number of predicted OTUs and inflates richness estimates. We show that a 2% single-linkage preclustering methodology followed by an average-linkage clustering based on pairwise alignments more accurately predicts expected OTUs in both single and pooled template preparations of known taxonomic composition. This new clustering method can reduce the OTU richness in environmental samples by as much as 30-60% but does not reduce the fraction of OTUs in long-tailed rank abundance curves that defines the rare biosphere.

Reproducible community dynamics of the gastrointestinal microbiota following antibiotic perturbation.

Shifts in microbial communities are implicated in the pathogenesis of a number of gastrointestinal diseases, but we have limited understanding of the mechanisms that lead to altered community structures. One difficulty with studying these mechanisms in human subjects is the inherent baseline variability of the microbiota in different individuals. In an effort to overcome this baseline variability, we employed a mouse model to control the host genotype, diet, and other possible influences on the microbiota. This allowed us to determine whether the indigenous microbiota in such mice had a stable baseline community structure and whether this community exhibited a consistent response following antibiotic administration. We employed a tag-sequencing strategy targeting the V6 hypervariable region of the bacterial small-subunit (16S) rRNA combined with massively parallel sequencing to determine the community structure of the gut microbiota. Inbred mice in a controlled environment harbored a reproducible baseline community that was significantly impacted by antibiotic administration. The ability of the gut microbial community to recover to baseline following the cessation of antibiotic administration differed according to the antibiotic regimen administered. Severe antibiotic pressure resulted in reproducible, long-lasting alterations in the gut microbial community, including a decrease in overall diversity. The finding of stereotypic responses of the indigenous microbiota to ecologic stress suggests that a better understanding of the factors that govern community structure could lead to strategies for the intentional manipulation of this ecosystem so as to preserve or restore a healthy microbiota.

Effect of PCR amplicon size on assessments of clone library microbial diversity and community structure.

PCR-based surveys of microbial communities commonly use regions of the small-subunit ribosomal RNA (SSU rRNA) gene to determine taxonomic membership and estimate total diversity. Here we show that the length of the target amplicon has a significant effect on assessments of microbial richness and community membership. Using operational taxonomic unit (OTU)- and taxonomy-based tools, we compared the V6 hypervariable region of the bacterial SSU rRNA gene of three amplicon libraries of c. 100, 400 and 1000 base pairs (bp) from each of two hydrothermal vent fluid samples. We found that the smallest amplicon libraries contained more unique sequences, higher diversity estimates and a different community structure than the other two libraries from each sample. We hypothesize that a combination of polymerase dissociation, cloning bias and mispriming due to secondary structure accounts for the differences. While this relationship is not linear, it is clear that the smallest amplicon libraries contained more different types of sequences, and accordingly, more diverse members of the community. Because divergent and lower abundant taxa can be more readily detected with smaller amplicons, they may provide better assessments of total community diversity and taxonomic membership than longer amplicons in molecular studies of microbial communities.