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

TitleIntegrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone
Authors
KeywordsMetaproteomics
Gene-centric model
Biogeochemical
Metatranscriptomics
Metagenomics
Issue Date2016
Citation
Proceedings of the National Academy of Sciences of the United States of America, 2016, v. 113, n. 40, p. E5925-E5933 How to Cite?
Abstract© 2016, National Academy of Sciences. All rights reserved. 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.
Persistent Identifierhttp://hdl.handle.net/10722/269752
ISSN
2023 Impact Factor: 9.4
2023 SCImago Journal Rankings: 3.737
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLouca, Stilianos-
dc.contributor.authorHawley, Alyse K.-
dc.contributor.authorKatsev, Sergei-
dc.contributor.authorTorres-Beltran, Monica-
dc.contributor.authorBhatia, Maya P.-
dc.contributor.authorKheirandish, Sam-
dc.contributor.authorMichiels, Céline C.-
dc.contributor.authorCapelle, David-
dc.contributor.authorLavik, Gaute-
dc.contributor.authorDoebeli, Michael-
dc.contributor.authorCrowe, Sean A.-
dc.contributor.authorHallam, Steven J.-
dc.date.accessioned2019-04-30T01:49:29Z-
dc.date.available2019-04-30T01:49:29Z-
dc.date.issued2016-
dc.identifier.citationProceedings of the National Academy of Sciences of the United States of America, 2016, v. 113, n. 40, p. E5925-E5933-
dc.identifier.issn0027-8424-
dc.identifier.urihttp://hdl.handle.net/10722/269752-
dc.description.abstract© 2016, National Academy of Sciences. All rights reserved. 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.-
dc.languageeng-
dc.relation.ispartofProceedings of the National Academy of Sciences of the United States of America-
dc.subjectMetaproteomics-
dc.subjectGene-centric model-
dc.subjectBiogeochemical-
dc.subjectMetatranscriptomics-
dc.subjectMetagenomics-
dc.titleIntegrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1073/pnas.1602897113-
dc.identifier.pmid27655888-
dc.identifier.scopuseid_2-s2.0-84989833276-
dc.identifier.volume113-
dc.identifier.issue40-
dc.identifier.spageE5925-
dc.identifier.epageE5933-
dc.identifier.eissn1091-6490-
dc.identifier.isiWOS:000384528900019-
dc.identifier.issnl0027-8424-

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