20 research outputs found

    Thinking Outside the Box: Using Computer Science Skills to Make Sense of the Biology of Life

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    While I liked coding and the logical aspects of computer programming, my gut was telling me I hadn\u27t quite found my niche yet. In what field could my computer science skills make a difference while also providing me with challenging problems to solve? As these questions percolated through my subconscious, I came across a brief article about a field called “bioinformatics.

    Oral microbiota in youth with perinatally acquired HIV infection

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    Background: Microbially mediated oral diseases can signal underlying HIV/AIDS progression in HIV-infected adults. The role of the oral microbiota in HIV-infected youth is not known. The Adolescent Master Protocol of the Pediatric HIV/AIDS Cohort Study is a longitudinal study of perinatally HIV-infected (PHIV) and HIV-exposed, uninfected (PHEU) youth. We compared oral microbiome levels and associations with caries or periodontitis in 154 PHIV and 100 PHEU youth. Results: Species richness and alpha diversity differed little between PHIV and PHEU youth. Group differences in average counts met the significance threshold for six taxa; two Corynebacterium species were lower in PHIV and met thresholds for noteworthiness. Several known periodontitis-associated organisms (Prevotella nigrescens, Tannerella forsythia, Aggregatibacter actinomycetemcomitans, and Filifactor alocis) exhibited expected associations with periodontitis in PHEU youth, associations not observed in PHIV youth. In both groups, odds of caries increased with counts of taxa in four genera, Streptococcus, Scardovia, Bifidobacterium, and Lactobacillus. Conclusions: The microbiomes of PHIV and PHEU youth were similar, although PHIV youth seemed to have fewer “health”-associated taxa such as Corynebacterium species. These results are consistent with the hypothesis that HIV infection, or its treatment, may contribute to oral dysbiosis. Electronic supplementary material The online version of this article (10.1186/s40168-018-0484-6) contains supplementary material, which is available to authorized users

    The COMBREX Project: Design, Methodology, and Initial Results

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    © 2013 Brian P. et al.Prior to the “genomic era,” when the acquisition of DNA sequence involved significant labor and expense, the sequencing of genes was strongly linked to the experimental characterization of their products. Sequencing at that time directly resulted from the need to understand an experimentally determined phenotype or biochemical activity. Now that DNA sequencing has become orders of magnitude faster and less expensive, focus has shifted to sequencing entire genomes. Since biochemistry and genetics have not, by and large, enjoyed the same improvement of scale, public sequence repositories now predominantly contain putative protein sequences for which there is no direct experimental evidence of function. Computational approaches attempt to leverage evidence associated with the ever-smaller fraction of experimentally analyzed proteins to predict function for these putative proteins. Maximizing our understanding of function over the universe of proteins in toto requires not only robust computational methods of inference but also a judicious allocation of experimental resources, focusing on proteins whose experimental characterization will maximize the number and accuracy of follow-on predictions.COMBREX is funded by a GO grant from the National Institute of General Medical Sciences (NIGMS) (1RC2GM092602-01).Peer Reviewe

    Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease

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    The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes
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