Doyle V. Ward

Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons

Bacterial diversity among environmental samples is commonly assessed with PCR-amplified 16S rRNA gene (16S) sequences. Perceived diversity, however, can be influenced by sample preparation, primer selection, and formation of chimeric 16S amplification products. Chimeras are hybrid products between multiple parent sequences that can be falsely interpreted as novel organisms, thus inflating apparent diversity. We developed a new chimera detection tool called Chimera Slayer (CS). CS detects chimeras with greater sensitivity than previous methods, performs well on short sequences such as those produced by the 454 Life Sciences (Roche) Genome Sequencer, and can scale to large data sets. By benchmarking CS performance against sequences derived from a controlled DNA mixture of known organisms and a simulated chimera set, we provide insights into the factors that affect chimera formation such as sequence abundance, the extent of similarity between 16S genes, and PCR conditions. Chimeras were found to reproducibly form among independent amplifications and contributed to false perceptions of sample diversity and the false identification of novel taxa, with less-abundant species exhibiting chimera rates exceeding 70%. Shotgun metagenomic sequences of our mock community appear to be devoid of 16S chimeras, supporting a role for shotgun metagenomics in validating novel organisms discovered in targeted sequence surveys.

Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment

BackgroundThe inflammatory bowel diseases (IBD) Crohns disease and ulcerative colitis result from alterations in intestinal microbes and the immune system. However, the precise dysfunctions of microbial metabolism in the gastrointestinal microbiome during IBD remain unclear. We analyzed the microbiota of intestinal biopsies and stool samples from 231 IBD and healthy subjects by 16S gene pyrosequencing and followed up a subset using shotgun metagenomics. Gene and pathway composition were assessed, based on 16S data from phylogenetically-related reference genomes, and associated using sparse multivariate linear modeling with medications, environmental factors, and IBD status.ResultsFirmicutes and Enterobacteriaceae abundances were associated with disease status as expected, but also with treatment and subject characteristics. Microbial function, though, was more consistently perturbed than composition, with 12% of analyzed pathways changed compared with 2% of genera. We identified major shifts in oxidative stress pathways, as well as decreased carbohydrate metabolism and amino acid biosynthesis in favor of nutrient transport and uptake. The microbiome of ileal Crohns disease was notable for increases in virulence and secretion pathways.ConclusionsThis inferred functional metagenomic information provides the first insights into community-wide microbial processes and pathways that underpin IBD pathogenesis.

A catalog of reference genomes from the human microbiome.

News from the Inner Tube of Life A major initiative by the U.S. National Institutes of Health to sequence 900 genomes of microorganisms that live on the surfaces and orifices of the human body has established standardized protocols and methods for such large-scale reference sequencing. By combining previously accumulated data with new data, Nelson et al. (p. 994) present an initial analysis of 178 bacterial genomes. The sampling so far barely scratches the surface of the microbial diversity found on humans, but the work provides an important baseline for future analyses. Standardized protocols and methods are being established for large-scale sequencing of the microorganisms living on humans. The human microbiome refers to the community of microorganisms, including prokaryotes, viruses, and microbial eukaryotes, that populate the human body. The National Institutes of Health launched an initiative that focuses on describing the diversity of microbial species that are associated with health and disease. The first phase of this initiative includes the sequencing of hundreds of microbial reference genomes, coupled to metagenomic sequencing from multiple body sites. Here we present results from an initial reference genome sequencing of 178 microbial genomes. From 547,968 predicted polypeptides that correspond to the gene complement of these strains, previously unidentified (“novel”) polypeptides that had both unmasked sequence length greater than 100 amino acids and no BLASTP match to any nonreference entry in the nonredundant subset were defined. This analysis resulted in a set of 30,867 polypeptides, of which 29,987 (~97%) were unique. In addition, this set of microbial genomes allows for ~40% of random sequences from the microbiome of the gastrointestinal tract to be associated with organisms based on the match criteria used. Insights into pan-genome analysis suggest that we are still far from saturating microbial species genetic data sets. In addition, the associated metrics and standards used by our group for quality assurance are presented.

Tracking insertion mutants within libraries by deep sequencing and a genome-wide screen for Haemophilus genes required in the lung

Rapid genome-wide identification of genes required for infection would expedite studies of bacterial pathogens. We developed genome-scale “negative selection” technology that combines high-density transposon mutagenesis and massively parallel sequencing of transposon/chromosome junctions in a mutant library to identify mutants lost from the library after exposure to a selective condition of interest. This approach was applied to comprehensively identify Haemophilus influenzae genes required to delay bacterial clearance in a murine pulmonary model. Mutations in 136 genes resulted in defects in vivo, and quantitative estimates of fitness generated by this technique were in agreement with independent validation experiments using individual mutant strains. Genes required in the lung included those with characterized functions in other models of H. influenzae pathogenesis and genes not previously implicated in infection. Genes implicated in vivo have reported or potential roles in survival during nutrient limitation, oxidative stress, and exposure to antimicrobial membrane perturbations, suggesting that these conditions are encountered by H. influenzae during pulmonary infection. The results demonstrate an efficient means to identify genes required for bacterial survival in experimental models of pathogenesis, and this approach should function similarly well in selections conducted in vitro and in vivo with any organism amenable to insertional mutagenesis.

Evaluation of 16s rDNA-based community profiling for human microbiome research

The Human Microbiome Project will establish a reference data set for analysis of the microbiome of healthy adults by surveying multiple body sites from 300 people and generating data from over 12,000 samples. To characterize these samples, the participating sequencing centers evaluated and adopted 16S rDNA community profiling protocols for ABI 3730 and 454 FLX Titanium sequencing. In the course of establishing protocols, we examined the performance and error characteristics of each technology, and the relationship of sequence error to the utility of 16S rDNA regions for classification- and OTU-based analysis of community structure. The data production protocols used for this work are those used by the participating centers to produce 16S rDNA sequence for the Human Microbiome Project. Thus, these results can be informative for interpreting the large body of clinical 16S rDNA data produced for this project.

Early microbial and metabolomic signatures predict later onset of necrotizing enterocolitis in preterm infants

BackgroundNecrotizing enterocolitis (NEC) is a devastating intestinal disease that afflicts 10% of extremely preterm infants. The contribution of early intestinal colonization to NEC onset is not understood, and predictive biomarkers to guide prevention are lacking. We analyzed banked stool and urine samples collected prior to disease onset from infants <29 weeks gestational age, including 11 infants who developed NEC and 21 matched controls who survived free of NEC. Stool bacterial communities were profiled by 16S rRNA gene sequencing. Urinary metabolomic profiles were assessed by NMR.ResultsDuring postnatal days 4 to 9, samples from infants who later developed NEC tended towards lower alpha diversity (Chao1 index, P = 0.086) and lacked Propionibacterium (P = 0.009) compared to controls. Furthermore, NEC was preceded by distinct forms of dysbiosis. During days 4 to 9, samples from four NEC cases were dominated by members of the Firmicutes (median relative abundance >99% versus <17% in the remaining NEC and controls, P < 0.001). During postnatal days 10 to 16, samples from the remaining NEC cases were dominated by Proteobacteria, specifically Enterobacteriaceae (median relative abundance >99% versus 38% in the other NEC cases and 84% in controls, P = 0.01). NEC preceded by Firmicutes dysbiosis occurred earlier (onset, days 7 to 21) than NEC preceded by Proteobacteria dysbiosis (onset, days 19 to 39). All NEC cases lacked Propionibacterium and were preceded by either Firmicutes (≥98% relative abundance, days 4 to 9) or Proteobacteria (≥90% relative abundance, days 10 to 16) dysbiosis, while only 25% of controls had this phenotype (predictive value 88%, P = 0.001). Analysis of days 4 to 9 urine samples found no metabolites associated with all NEC cases, but alanine was positively associated with NEC cases that were preceded by Firmicutes dysbiosis (P < 0.001) and histidine was inversely associated with NEC cases preceded by Proteobacteria dysbiosis (P = 0.013). A high urinary alanine:histidine ratio was associated with microbial characteristics (P < 0.001) and provided good prediction of overall NEC (predictive value 78%, P = 0.007).ConclusionsEarly dysbiosis is strongly involved in the pathobiology of NEC. These striking findings require validation in larger studies but indicate that early microbial and metabolomic signatures may provide highly predictive biomarkers of NEC.

Whole Genome Characterization of the Mechanisms of Daptomycin Resistance in Clinical and Laboratory Derived Isolates of Staphylococcus aureus

Background Daptomycin remains one of our last-line anti-staphylococcal agents. This study aims to characterize the genetic evolution to daptomycin resistance in S. aureus. Methods Whole genome sequencing was performed on a unique collection of isogenic, clinical (21 strains) and laboratory (12 strains) derived strains that had been exposed to daptomycin and developed daptomycin-nonsusceptibility. Electron microscopy (EM) and lipid membrane studies were performed on selected isolates. Results On average, six coding region mutations were observed across the genome in the clinical daptomycin exposed strains, whereas only two mutations on average were seen in the laboratory exposed pairs. All daptomycin-nonsusceptible strains had a mutation in a phospholipid biosynthesis gene. This included mutations in the previously described mprF gene, but also in other phospholipid biosynthesis genes, including cardiolipin synthase (cls2) and CDP-diacylglycerol-glycerol-3-phosphate 3-phosphatidyltransferase (pgsA). EM and lipid membrane composition analyses on two clinical pairs showed that the daptomycin-nonsusceptible strains had a thicker cell wall and an increase in membrane lysyl-phosphatidylglycerol. Conclusion Point mutations in genes coding for membrane phospholipids are associated with the development of reduced susceptibility to daptomycin in S. aureus. Mutations in cls2 and pgsA appear to be new genetic mechanisms affecting daptomycin susceptibility in S. aureus.

Peptide linkage mapping of the Agrobacterium tumefaciens vir-encoded type IV secretion system reveals protein subassemblies

Numerous bacterial pathogens use type IV secretion systems (T4SS) to deliver virulence factors directly to the cytoplasm of plant, animal, and human host cells. Here, evidence for interactions among components of the Agrobacterium tumefaciens vir-encoded T4SS is presented. The results derive from a high-resolution yeast two-hybrid assay, in which a library of small peptide domains of T4SS components was screened for interactions. The use of small peptides overcomes problems associated with assaying for interactions involving membrane-associated proteins. We established interactions between VirB11 (an inner membrane pore-forming protein), VirB9 (a periplasmic protein), and VirB7 (an outer membrane-associated lipoprotein and putative pilus component). We provide evidence for an interaction pathway, among conserved members of a T4SS, spanning the A. tumefaciens envelope and including a potential pore protein. In addition, we have determined interactions between VirB1 (a lytic transglycosylase likely involved in the local remodeling of the peptidoglycan) and primarily VirB8, but also VirB4, VirB10, and VirB11 (proteins likely to assemble the core structure of the T4SS). VirB4 interacts with VirB8, VirB10, and VirB11, also establishing a connection to the core components. The identification of these interactions suggests a model for assembly of the T4SS.

Efficient and robust RNA-seq process for cultured bacteria and complex community transcriptomes.

We have developed a process for transcriptome analysis of bacterial communities that accommodates both intact and fragmented starting RNA and combines efficient rRNA removal with strand-specific RNA-seq. We applied this approach to an RNA mixture derived from three diverse cultured bacterial species and to RNA isolated from clinical stool samples. The resulting expression profiles were highly reproducible, enriched up to 40-fold for non-rRNA transcripts, and correlated well with profiles representing undepleted total RNA.

Non-invasive mapping of the gastrointestinal microbiota identifies children with inflammatory bowel disease.

Background Pediatric inflammatory bowel disease (IBD) is challenging to diagnose because of the non-specificity of symptoms; an unequivocal diagnosis can only be made using colonoscopy, which clinicians are reluctant to recommend for children. Diagnosis of pediatric IBD is therefore frequently delayed, leading to inappropriate treatment plans and poor outcomes. We investigated the use of 16S rRNA sequencing of fecal samples and new analytical methods to assess differences in the microbiota of children with IBD and other gastrointestinal disorders. Methodology/Principal Findings We applied synthetic learning in microbial ecology (SLiME) analysis to 16S sequencing data obtained from i) published surveys of microbiota diversity in IBD and ii) fecal samples from 91 children and young adults who were treated in the gastroenterology program of Children’s Hospital (Boston, USA). The developed method accurately distinguished control samples from those of patients with IBD; the area under the receiver-operating-characteristic curve (AUC) value was 0.83 (corresponding to 80.3% sensitivity and 69.7% specificity at a set threshold). The accuracy was maintained among data sets collected by different sampling and sequencing methods. The method identified taxa associated with disease states and distinguished patients with Crohn’s disease from those with ulcerative colitis with reasonable accuracy. The findings were validated using samples from an additional group of 68 patients; the validation test identified patients with IBD with an AUC value of 0.84 (e.g. 92% sensitivity, 58.5% specificity). Conclusions/Significance Microbiome-based diagnostics can distinguish pediatric patients with IBD from patients with similar symptoms. Although this test can not replace endoscopy and histological examination as diagnostic tools, classification based on microbial diversity is an effective complementary technique for IBD detection in pediatric patients.