Georgia Giannoukos

Genome-wide maps of chromatin state in pluripotent and lineage-committed cells

We report the application of single-molecule-based sequencing technology for high-throughput profiling of histone modifications in mammalian cells. By obtaining over four billion bases of sequence from chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of mouse embryonic stem cells, neural progenitor cells and embryonic fibroblasts. We find that lysine 4 and lysine 27 trimethylation effectively discriminates genes that are expressed, poised for expression, or stably repressed, and therefore reflect cell state and lineage potential. Lysine 36 trimethylation marks primary coding and non-coding transcripts, facilitating gene annotation. Trimethylation of lysine 9 and lysine 20 is detected at satellite, telomeric and active long-terminal repeats, and can spread into proximal unique sequences. Lysine 4 and lysine 9 trimethylation marks imprinting control regions. Finally, we show that chromatin state can be read in an allele-specific manner by using single nucleotide polymorphisms. This study provides a framework for the application of comprehensive chromatin profiling towards characterization of diverse mammalian cell populations.

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.

Quality scores and SNP detection in sequencing-by-synthesis systems

Promising new sequencing technologies, based on sequencing-by-synthesis (SBS), are starting to deliver large amounts of DNA sequence at very low cost. Polymorphism detection is a key application. We describe general methods for improved quality scores and accurate automated polymorphism detection, and apply them to data from the Roche (454) Genome Sequencer 20. We assess our methods using known-truth data sets, which is critical to the validity of the assessments. We developed informative, base-by-base error predictors for this sequencer and used a variant of the phred binning algorithm to combine them into a single empirically derived quality score. These quality scores are more useful than those produced by the system software: They both better predict actual error rates and identify many more high-quality bases. We developed a SNP detection method, with variants for low coverage, high coverage, and PCR amplicon applications, and evaluated it on known-truth data sets. We demonstrate good specificity in single reads, and excellent specificity (no false positives in 215 kb of genome) in high-coverage data.

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.

Relating the metatranscriptome and metagenome of the human gut.

Significance Recent years have seen incredible growth in both the scale and specificity of projects analyzing the microbial organisms living in and on the human body (the human microbiome). Such studies typically require subjects to report to clinics for sample collection, a complicated practice that is impractical for large studies. To address these issues, we developed a protocol that allows subjects to collect microbiome samples at home and ship them to laboratories for multiple different types of molecular analysis. Measurements of microbial species, gene, and gene transcript composition within self-collected samples were consistent across sampling methods. In addition, our subsequent analysis of these samples revealed interesting similarities and differences between the measured functional potential and functional activity of the human microbiome. Although the composition of the human microbiome is now well-studied, the microbiota’s >8 million genes and their regulation remain largely uncharacterized. This knowledge gap is in part because of the difficulty of acquiring large numbers of samples amenable to functional studies of the microbiota. We conducted what is, to our knowledge, one of the first human microbiome studies in a well-phenotyped prospective cohort incorporating taxonomic, metagenomic, and metatranscriptomic profiling at multiple body sites using self-collected samples. Stool and saliva were provided by eight healthy subjects, with the former preserved by three different methods (freezing, ethanol, and RNAlater) to validate self-collection. Within-subject microbial species, gene, and transcript abundances were highly concordant across sampling methods, with only a small fraction of transcripts (<5%) displaying between-method variation. Next, we investigated relationships between the oral and gut microbial communities, identifying a subset of abundant oral microbes that routinely survive transit to the gut, but with minimal transcriptional activity there. Finally, systematic comparison of the gut metagenome and metatranscriptome revealed that a substantial fraction (41%) of microbial transcripts were not differentially regulated relative to their genomic abundances. Of the remainder, consistently underexpressed pathways included sporulation and amino acid biosynthesis, whereas up-regulated pathways included ribosome biogenesis and methanogenesis. Across subjects, metatranscriptional profiles were significantly more individualized than DNA-level functional profiles, but less variable than microbial composition, indicative of subject-specific whole-community regulation. The results thus detail relationships between community genomic potential and gene expression in the gut, and establish the feasibility of metatranscriptomic investigations in subject-collected and shipped samples.

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.

Functional optimization of gene clusters by combinatorial design and assembly

Large microbial gene clusters encode useful functions, including energy utilization and natural product biosynthesis, but genetic manipulation of such systems is slow, difficult and complicated by complex regulation. We exploit the modularity of a refactored Klebsiella oxytoca nitrogen fixation (nif) gene cluster (16 genes, 103 parts) to build genetic permutations that could not be achieved by starting from the wild-type cluster. Constraint-based combinatorial design and DNA assembly are used to build libraries of radically different cluster architectures by varying part choice, gene order, gene orientation and operon occupancy. We construct 84 variants of the nifUSVWZM operon, 145 variants of the nifHDKY operon, 155 variants of the nifHDKYENJ operon and 122 variants of the complete 16-gene pathway. The performance and behavior of these variants are characterized by nitrogenase assay and strand-specific RNA sequencing (RNA-seq), and the results are incorporated into subsequent design cycles. We have produced a fully synthetic cluster that recovers 57% of wild-type activity. Our approach allows the performance of genetic parts to be quantified simultaneously in hundreds of genetic contexts. This parallelized design-build-test-learn cycle, which can access previously unattainable regions of genetic space, should provide a useful, fast tool for genetic optimization and hypothesis testing.

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.

A scalable, fully automated process for construction of sequence-ready barcoded libraries for 454

We present an automated, high throughput library construction process for 454 technology. Sample handling errors and cross-contamination are minimized via end-to-end barcoding of plasticware, along with molecular DNA barcoding of constructs. Automation-friendly magnetic bead-based size selection and cleanup steps have been devised, eliminating major bottlenecks and significant sources of error. Using this methodology, one technician can create 96 sequence-ready 454 libraries in 2 days, a dramatic improvement over the standard method.