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Title: Elucidation of complexity and prediction of interactions in microbial communities

Microorganisms engage in complex interactions with other members of the microbial community, higher organisms as well as their environment. However, determining the exact nature of these interactions can be challenging due to the large number of members in these communities and the manifold of interactions they can engage in. Various omic data, such as 16S rRNA gene sequencing, shotgun metagenomics, metatranscriptomics, metaproteomics and metabolomics, have been deployed to unravel the community structure, interactions and resulting community dynamics in situ. Interpretation of these multi-omic data often requires advanced computational methods. Modelling approaches are powerful tools to integrate, contextualize and interpret experimental data, thus shedding light on the underlying processes shaping the microbiome. As a result, we review current methods and approaches, both experimental and computational, to elucidate interactions in microbial communities and to predict their responses to perturbations.
Authors:
 [1] ;  [1] ;  [1]
  1. Univ. of California, San Diego, La Jolla CA (United States)
Publication Date:
Grant/Contract Number:
SC0012658; SC0012586
Type:
Published Article
Journal Name:
Microbial Biotechnology (Online)
Additional Journal Information:
Journal Name: Microbial Biotechnology (Online); Journal Volume: 10; Journal Issue: 6; Journal ID: ISSN 1751-7915
Publisher:
Wiley
Research Org:
Johns Hopkins Univ., Baltimore, MD (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES
OSTI Identifier:
1392703
Alternate Identifier(s):
OSTI ID: 1392704; OSTI ID: 1485598

Zuñiga, Cristal, Zaramela, Livia, and Zengler, Karsten. Elucidation of complexity and prediction of interactions in microbial communities. United States: N. p., Web. doi:10.1111/1751-7915.12855.
Zuñiga, Cristal, Zaramela, Livia, & Zengler, Karsten. Elucidation of complexity and prediction of interactions in microbial communities. United States. doi:10.1111/1751-7915.12855.
Zuñiga, Cristal, Zaramela, Livia, and Zengler, Karsten. 2017. "Elucidation of complexity and prediction of interactions in microbial communities". United States. doi:10.1111/1751-7915.12855.
@article{osti_1392703,
title = {Elucidation of complexity and prediction of interactions in microbial communities},
author = {Zuñiga, Cristal and Zaramela, Livia and Zengler, Karsten},
abstractNote = {Microorganisms engage in complex interactions with other members of the microbial community, higher organisms as well as their environment. However, determining the exact nature of these interactions can be challenging due to the large number of members in these communities and the manifold of interactions they can engage in. Various omic data, such as 16S rRNA gene sequencing, shotgun metagenomics, metatranscriptomics, metaproteomics and metabolomics, have been deployed to unravel the community structure, interactions and resulting community dynamics in situ. Interpretation of these multi-omic data often requires advanced computational methods. Modelling approaches are powerful tools to integrate, contextualize and interpret experimental data, thus shedding light on the underlying processes shaping the microbiome. As a result, we review current methods and approaches, both experimental and computational, to elucidate interactions in microbial communities and to predict their responses to perturbations.},
doi = {10.1111/1751-7915.12855},
journal = {Microbial Biotechnology (Online)},
number = 6,
volume = 10,
place = {United States},
year = {2017},
month = {9}
}