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Gaining new insights into microbial methanogenesis and anaerobic methane oxidation through in vivo nuclear magnetic resonance spectroscopy


EMSL Project ID
51091

Abstract

Methane is a singularly important molecule in the context of the United States' energy and environmental priorities. It represents a substantial energy source and potential feedstock for biofuel production schemes and is a strong greenhouse gas that contributes substantially to anthropogenic warming. Much of Earth's methane production and consumption is performed by anaerobic microorganisms; that said, it is surprising that the precise environmental determinants that primarily govern in situ methanogenic (methane production) and methanotrophic (methane consumption) metabolic rates remain poorly constrained. Clarifying the environmental factors that modulate biological methane production and consumption will help us better understand how microbial methane cycling might respond to natural and/or anthropogenic environmental change, and will also expose potential options for metabolic engineering to enhance methane consumption or develop methane-to-biofuel pathways.

Here we present an experimental and analytical approach to studying microbial methanogenic and methanotrophic responses to environmental dynamics, with an emphasis on substrate availability, pH, total alkalinity, and end-product concentration. Briefly, using pure cultures of metabolically facultative methanogens, methane seep microbial enrichments, as well as native rock-microbial geobiological assemblages, we will track carbon flow through 13C stable isotopically enriched substrates provided during a series of incubations at environmentally-relevant conditions. The near-continuous nature of batch measurement enabled by NMR will confer a degree of realism unmatched by other analytical approaches that require incubations to be stopped at discrete time-points. A wide range of practitioners, including bioengineers, biofuel advocates, climate scientists, oceanographers, and microbiologists will likely derive value from the anticipated data.

Project Details

Project type
Exploratory Research
Start Date
2019-11-26
End Date
2021-09-30
Status
Closed

Team

Principal Investigator

Jeffrey Marlow
Institution
Boston University

Co-Investigator(s)

Peter Girguis
Institution
Harvard University