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Turnbaugh, Peter

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Turnbaugh

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Peter

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Turnbaugh, Peter

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2011 - 20134

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Author's Publications: search.filters.isAuthorOfPublication.a3c66208-cdc8-4721-b93a-27c31ba83ea2

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Now showing 1 - 4 of 4
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    High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions
    (Oxford University Press, 2013) Amir, Amnon; Zeisel, Amit; Zuk, Or; Elgart, Michael; Stern, Shay; Shamir, Ohad; Turnbaugh, Peter; Soen, Yoav; Shental, Noam
    The emergence of massively parallel sequencing technology has revolutionized microbial profiling, allowing the unprecedented comparison of microbial diversity across time and space in a wide range of host-associated and environmental ecosystems. Although the high-throughput nature of such methods enables the detection of low-frequency bacteria, these advances come at the cost of sequencing read length, limiting the phylogenetic resolution possible by current methods. Here, we present a generic approach for integrating short reads from large genomic regions, thus enabling phylogenetic resolution far exceeding current methods. The approach is based on a mapping to a statistical model that is later solved as a constrained optimization problem. We demonstrate the utility of this method by analyzing human saliva and Drosophila samples, using Illumina single-end sequencing of a 750 bp amplicon of the 16S rRNA gene. Phylogenetic resolution is significantly extended while reducing the number of falsely detected bacteria, as compared with standard single-region Roche 454 Pyrosequencing. Our approach can be seamlessly applied to simultaneous sequencing of multiple genes providing a higher resolution view of the composition and activity of complex microbial communities.
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    Predicting and Manipulating Cardiac Drug Inactivation by the Human Gut Bacterium Eggerthella lenta
    (American Association for the Advancement of Science (AAAS), 2013) Haiser, Henry J.; Gootenberg, David; Chatman, Kelly; Sirasani, Gopal; Balskus, Emily; Turnbaugh, Peter
    Despite numerous examples of the effects of the human gastrointestinal microbiome on drug efficacy and toxicity, there is often an incomplete understanding of the underlying mechanisms. Here, we dissect the inactivation of the cardiac drug digoxin by the gut Actinobacterium Eggerthella lenta. Transcriptional profiling, comparative genomics, and culture-based assays revealed a cytochrome-encoding operon up-regulated by digoxin, inhibited by arginine, absent in nonmetabolizing E. lenta strains, and predictive of digoxin inactivation by the human gut microbiome. Pharmacokinetic studies using gnotobiotic mice revealed that dietary protein reduces the in vivo microbial metabolism of digoxin, with significant changes to drug concentration in the serum and urine. These results emphasize the importance of viewing pharmacology from the perspective of both our human and microbial genomes.
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    Functional Characterization of Bacteria Isolated from Ancient Arctic Soil Exposes Diverse Resistance Mechanisms to Modern Antibiotics
    (Public Library of Science, 2013-07-02) Perron, Gabriel; Whyte, Lyle; Turnbaugh, Peter; Hanage, William; Dantas, Gautam; Desai, Michael
    Using functional metagenomics to study the resistomes of bacterial communities isolated from different layers of the Canadian high Arctic permafrost, we show that microbial communities harbored diverse resistance mechanisms at least 5,000 years ago. Among bacteria sampled from the ancient layers of a permafrost core, we isolated eight genes conferring clinical levels of resistance against aminoglycoside, \(\beta\)-lactam and tetracycline antibiotics that are naturally produced by microorganisms. Among these resistance genes, four also conferred resistance against amikacin, a modern semi-synthetic antibiotic that does not naturally occur in microorganisms. In bacteria sampled from the overlaying active layer, we isolated ten different genes conferring resistance to all six antibiotics tested in this study, including aminoglycoside, \(\beta\)-lactam and tetracycline variants that are naturally produced by microorganisms as well as semi-synthetic variants produced in the laboratory. On average, we found that resistance genes found in permafrost bacteria conferred lower levels of resistance against clinically relevant antibiotics than resistance genes sampled from the active layer. Our results demonstrate that antibiotic resistance genes were functionally diverse prior to the anthropogenic use of antibiotics, contributing to the evolution of natural reservoirs of resistance genes.
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    Removing Noise From Pyrosequenced Amplicons
    (BioMed Central, 2011) Quince, Christopher; Lanzen, Anders; Davenport, Russell J; Turnbaugh, Peter
    Background: In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs) present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base errors. We also introduce a novel chimera removal program, Perseus, that exploits the sequence abundances associated with pyrosequencing data. We use data sets where samples of known diversity have been amplified and sequenced to quantify the effect of each of the sources of error on OTU inflation and to validate these algorithms. Results: AmpliconNoise outperforms alternative algorithms substantially reducing per base error rates for both the GS FLX and latest Titanium protocol. All three sources of error lead to inflation of diversity estimates. In particular, chimera formation has a hitherto unrealised importance which varies according to amplification protocol. We show that AmpliconNoise allows accurate estimates of OTU number. Just as importantly AmpliconNoise generates the right OTUs even at low sequence differences. We demonstrate that Perseus has very high sensitivity, able to find 99% of chimeras, which is critical when these are present at high frequencies. Conclusions: AmpliconNoise followed by Perseus is a very effective pipeline for the removal of noise. In addition the principles behind the algorithms, the inference of true sequences using Expectation-Maximization (EM), and the treatment of chimera detection as a classification or 'supervised learning' problem, will be equally applicable to new sequencing technologies as they appear.