Niche partitioning of a pathogenic microbiome driven by chemical gradients

dc.contributor.authorQuinn, Robert A.
dc.contributor.authorComstock, William
dc.contributor.authorZhang, Tian-yu
dc.contributor.authorMorton, James T.
dc.contributor.authorda Silva, Ricardo
dc.contributor.authorTran, Alda
dc.contributor.authorAksenov, Alexander
dc.contributor.authorNothias, Louis-Felix
dc.contributor.authorWangpraseurt, Daniel
dc.contributor.authorMelnik, Alexey V.
dc.contributor.authorAckermann, Gail
dc.contributor.authorConrad, Douglas
dc.contributor.authorKlapper, Isaac
dc.contributor.authorKnight, Rob
dc.contributor.authorDorrestein, Pieter C.
dc.date.accessioned2019-04-04T19:16:39Z
dc.date.available2019-04-04T19:16:39Z
dc.date.issued2018-09
dc.description.abstractEnvironmental microbial communities are stratified by chemical gradients that shape the structure and function of these systems. Similar chemical gradients exist in the human body, but how they influence these microbial systems is more poorly understood. Understanding these effects can be particularly important for dysbiotic shifts in microbiome structure that are often associated with disease. We show that pH and oxygen strongly partition the microbial community from a diseased human lung into two mutually exclusive communities of pathogens and anaerobes. Antimicrobial treatment disrupted this chemical partitioning, causing complex death, survival, and resistance outcomes that were highly dependent on the individual microorganism and on community stratification. These effects were mathematically modeled, enabling a predictive understanding of this complex polymicrobial system. Harnessing the power of these chemical gradients could be a drug-free method of shaping microbial communities in the human body from undesirable dysbiotic states.en_US
dc.description.sponsorshipVertex Pharmaceuticals Cystic Fibrosis Research Innovation Award; NSF grant number DGE-1144086, 1516951, and 1517100; NIH/National Institute of Allergy and Infectious Diseases grant number 1 U01 AI124316-01; Bruker Corporationen_US
dc.identifier.citationQuinn, Robert A., William Comstock, Tianyu Zhang, James T. Morton, Ricardo da Silva, Alda Tran, Alexander Aksenov, Louis-Felix Nothias, Daniel Wangpraseurt, Alexey V. Melnik, Gail Ackermann, Douglas Conrad, Isaac Klapper, Rob Knight, and Pieter C. Dorrestein. "Niche partitioning of a pathogenic microbiome driven by chemical gradients." Science Advances 4, no. 9 (September 2018): eaau1908. DOI:10.1126/sciadv.aau1908.en_US
dc.identifier.issn2375-2548
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/15401
dc.language.isoenen_US
dc.rightsCC BY: This license lets you distribute, remix, tweak, and build upon this work, even commercially, as long as you credit the original creator for this work. This is the most accommodating of licenses offered. Recommended for maximum dissemination and useen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/legalcodeen_US
dc.titleNiche partitioning of a pathogenic microbiome driven by chemical gradientsen_US
dc.typeArticleen_US
mus.citation.issue9en_US
mus.citation.journaltitleScience Advancesen_US
mus.citation.volume4en_US
mus.data.thumbpage4en_US
mus.identifier.categoryChemical & Material Sciencesen_US
mus.identifier.categoryHealth & Medical Sciencesen_US
mus.identifier.doi10.1126/sciadv.aau1908en_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentMathematical Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US

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