Literature DB >> 24503479

Extracting data from the muck: deriving biological insight from complex microbial communities and non-model organisms with next generation sequencing.

Kevin V Solomon1, Charles H Haitjema1, Dawn A Thompson2, Michelle A O'Malley3.   

Abstract

It is becoming increasingly clear that microbes within microbial communities, for which cultured isolates have not yet been obtained, have an immense, untapped reservoir of enzymes that could help address grand challenges in human health, energy, and sustainability. Despite the obstacles associated with culturing these microbes, recent advances in next-generation sequencing (NGS) have made it possible to explore complex microbial communities in their native context for the first time. Key to extracting meaning from rapidly growing NGS datasets are bioinformatics tools that assemble the sequence data, annotate homologous sequences and interrogate it to reveal regulatory patterns. Complementing this are advances in proteomics that can link NGS data to biological function. This combination of next generation sequencing, proteomics and bioinformatic analysis forms a powerful tool to study non-model microbes, which will transform what we know about these dynamic systems.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 24503479     DOI: 10.1016/j.copbio.2014.01.007

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  7 in total

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2.  Early-branching gut fungi possess a large, comprehensive array of biomass-degrading enzymes.

Authors:  Kevin V Solomon; Charles H Haitjema; John K Henske; Sean P Gilmore; Diego Borges-Rivera; Anna Lipzen; Heather M Brewer; Samuel O Purvine; Aaron T Wright; Michael K Theodorou; Igor V Grigoriev; Aviv Regev; Dawn A Thompson; Michelle A O'Malley
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7.  ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions.

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  7 in total

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