Integrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone.

Autor:	Louca S; Institute of Applied Mathematics, University of British Columbia, Vancouver, BC, Canada V6T1Z2., Hawley AK; Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada V6T1Z3., Katsev S; Large Lakes Observatory, University of Minnesota Duluth, Duluth, MN 55812; Department of Physics and Astronomy, University of Minnesota Duluth, Duluth, MN 55812., Torres-Beltran M; Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada V6T1Z3., Bhatia MP; Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada V6T1Z3; Canadian Institute for Advanced Research Program in Integrated Microbial Biodiversity, Canadian Institute for Advanced Research, Toronto, ON, Canada M5G1Z8., Kheirandish S; Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada V6T1Z3., Michiels CC; Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada V6T1Z3., Capelle D; Department of Earth, Ocean, and Atmospheric Sciences, University of British Columbia, Vancouver, BC, Canada V6T1Z4., Lavik G; Biogeochemistry Group, Max Planck Institute for Marine Microbiology, Bremen D-28359, Germany., Doebeli M; Department of Zoology, University of British Columbia, Vancouver, BC, Canada V6T1Z4; Department of Mathematics, University of British Columbia, Vancouver, BC, Canada V6T1Z4., Crowe SA; Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada V6T1Z3; Department of Earth, Ocean, and Atmospheric Sciences, University of British Columbia, Vancouver, BC, Canada V6T1Z4; Ecosystem Services, Commercialization Platforms, and Entrepreneurship (ECOSCOPE) Training Program, University of British Columbia, Vancouver, BC, Canada V6T1Z3; sean.crowe@ubc.ca shallam@mail.ubc.ca., Hallam SJ; Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada V6T1Z3; Canadian Institute for Advanced Research Program in Integrated Microbial Biodiversity, Canadian Institute for Advanced Research, Toronto, ON, Canada M5G1Z8; Ecosystem Services, Commercialization Platforms, and Entrepreneurship (ECOSCOPE) Training Program, University of British Columbia, Vancouver, BC, Canada V6T1Z3; Graduate Program in Bioinformatics, University of British Columbia, Vancouver, BC, Canada V6T1Z3; Peter Wall Institute for Advanced Studies, University of British Columbia, Vancouver, BC, Canada V6T1Z2 sean.crowe@ubc.ca shallam@mail.ubc.ca.
Jazyk:	angličtina
Zdroj:	Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2016 Oct 04; Vol. 113 (40), pp. E5925-E5933. Date of Electronic Publication: 2016 Sep 21.
DOI:	10.1073/pnas.1602897113
Abstrakt:	Microorganisms are the most abundant lifeform on Earth, mediating global fluxes of matter and energy. Over the past decade, high-throughput molecular techniques generating multiomic sequence information (DNA, mRNA, and protein) have transformed our perception of this microcosmos, conceptually linking microorganisms at the individual, population, and community levels to a wide range of ecosystem functions and services. Here, we develop a biogeochemical model that describes metabolic coupling along the redox gradient in Saanich Inlet-a seasonally anoxic fjord with biogeochemistry analogous to oxygen minimum zones (OMZs). The model reproduces measured biogeochemical process rates as well as DNA, mRNA, and protein concentration profiles across the redox gradient. Simulations make predictions about the role of ubiquitous OMZ microorganisms in mediating carbon, nitrogen, and sulfur cycling. For example, nitrite "leakage" during incomplete sulfide-driven denitrification by SUP05 Gammaproteobacteria is predicted to support inorganic carbon fixation and intense nitrogen loss via anaerobic ammonium oxidation. This coupling creates a metabolic niche for nitrous oxide reduction that completes denitrification by currently unidentified community members. These results quantitatively improve previous conceptual models describing microbial metabolic networks in OMZs. Beyond OMZ-specific predictions, model results indicate that geochemical fluxes are robust indicators of microbial community structure and reciprocally, that gene abundances and geochemical conditions largely determine gene expression patterns. The integration of real observational data, including geochemical profiles and process rate measurements as well as metagenomic, metatranscriptomic and metaproteomic sequence data, into a biogeochemical model, as shown here, enables holistic insight into the microbial metabolic network driving nutrient and energy flow at ecosystem scales. Competing Interests: The authors declare no conflict of interest.
Databáze:	MEDLINE
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