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Microbial interactions in the anaerobic oxidation of methane: model simulations constrained by process rates and activity patterns.
He, Xiaojia; Chadwick, Grayson; Kempes, Christopher; Shi, Yimeng; McGlynn, Shawn; Orphan, Victoria; Meile, Christof.
Afiliação
  • He X; Department of Marine Sciences, University of Georgia, Athens, GA, USA.
  • Chadwick G; Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA.
  • Kempes C; Santa Fe Institute, Santa Fe, NM, USA.
  • Shi Y; Department of Marine Sciences, University of Georgia, Athens, GA, USA.
  • McGlynn S; Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA.
  • Orphan V; Earth-Life Science Institute, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan.
  • Meile C; Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA.
Environ Microbiol ; 21(2): 631-647, 2019 02.
Article em En | MEDLINE | ID: mdl-30565827
ABSTRACT
Proposed syntrophic interactions between the archaeal and bacterial cells mediating anaerobic oxidation of methane coupled with sulfate reduction include electron transfer through (1) the exchange of H2 or small organic molecules between methane-oxidizing archaea and sulfate-reducing bacteria, (2) the delivery of disulfide from methane-oxidizing archaea to bacteria for disproportionation and (3) direct interspecies electron transfer. Each of these mechanisms was implemented in a reactive transport model. The simulated activities across different arrangements of archaeal and bacterial cells and aggregate sizes were compared to empirical data for AOM rates and intra-aggregate spatial patterns of cell-specific anabolic activity determined by FISH-nanoSIMS. Simulation results showed that rates for chemical diffusion by mechanism (1) were limited by the build-up of metabolites, while mechanisms (2) and (3) yielded cell specific rates and archaeal activity distributions that were consistent with observations from single cell resolved FISH-nanoSIMS analyses. The novel integration of both intra-aggregate and environmental data provided powerful constraints on the model results, but the similarities in model outcomes for mechanisms (2) and (3) highlight the need for additional observational data (e.g. genomic or physiological) on electron transfer and metabolic functioning of these globally important methanotrophic consortia.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article