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.
|Original language||English (US)|
|Journal||Proceedings of the National Academy of Sciences of the United States of America|
|State||Published - Oct 4 2016|
Bibliographical noteFunding Information:
We thank the crew aboard the Marine Science Vessel John Strickland; Phylis Lam for assistance with rate measurements; and Sarah Perez, Aria Hahn, and Natasha Sihota for comments on the manuscript. We also thank the Joint Genome Institute, including Sussanah Tringe, Stephanie Malfatti, and Tijana Glavina del Rio, for technical and project management assistance. This work was performed under the auspices of the US Department of Energy (DOE) Joint Genome Institute, supported by US DOE Office of Science Contract DE-AC02-05CH11231; the G. Unger Vetlesen and Ambrose Monell Foundations; the Tula Foundation-funded Centre for Microbial Diversity and Evolution; the Natural Sciences and Engineering Research Council of Canada (NSERC); Genome British Columbia; the Canada Foundation for Innovation; and grants from the Canadian Institute for Advanced Research (to S.A.C. and S.J.H.). Metaproteomics support came from the intramural research and development program of the W. R. Wiley Environmental Molecular Sciences Laboratory (EMSL). The EMSL is a national scientific user facility sponsored by the US DOE Office of Biological and Environmental Research and located at the Pacific Northwest National Laboratory operated by Battelle for the US DOE. S.L. was supported by the Pacific Institute for the Mathematical Sciences (International Graduate Training Centre for Mathematical Biology), as well as the Department of Mathematics, University of British Columbia. M.P.B. received support from the Canadian Institute for Advanced Research Global Fellowship in the Integrated Microbial Biodiversity Program. S.L., M.P.B., and M.D. also received support from NSERC. G.L. was supported by the Max Planck Society.
© 2016, National Academy of Sciences. All rights reserved.
- Gene-centric model