Activity and interactions of methane seep microorganisms assessed by parallel transcription and FISH-NanoSIMS analyses

To characterize the activity and interactions of methanotrophic archaea (ANME) and Deltaproteobacteria at a methane-seeping mud volcano, we used two complimentary measures of microbial activity: a community-level analysis of the transcription of four genes (16S rRNA, methyl coenzyme M reductase A (mcrA), adenosine-5′-phosphosulfate reductase α-subunit (aprA), dinitrogenase reductase (nifH)), and a single-cell-level analysis of anabolic activity using fluorescence in situ hybridization coupled to nanoscale secondary ion mass spectrometry (FISH-NanoSIMS). Transcript analysis revealed that members of the deltaproteobacterial groups Desulfosarcina/Desulfococcus (DSS) and Desulfobulbaceae (DSB) exhibit increased rRNA expression in incubations with methane, suggestive of ANME-coupled activity. Direct analysis of anabolic activity in DSS cells in consortia with ANME by FISH-NanoSIMS confirmed their dependence on methanotrophy, with no (15)NH(4)(+) assimilation detected without methane. In contrast, DSS and DSB cells found physically independent of ANME (i.e., single cells) were anabolically active in incubations both with and without methane. These single cells therefore comprise an active ‘free-living' population, and are not dependent on methane or ANME activity. We investigated the possibility of N(2) fixation by seep Deltaproteobacteria and detected nifH transcripts closely related to those of cultured diazotrophic Deltaproteobacteria. However, nifH expression was methane-dependent. (15)N(2) incorporation was not observed in single DSS cells, but was detected in single DSB cells. Interestingly, (15)N(2) incorporation in single DSB cells was methane-dependent, raising the possibility that DSB cells acquired reduced (15)N products from diazotrophic ANME while spatially coupled, and then subsequently dissociated. With this combined data set we address several outstanding questions in methane seep microbial ecosystems and highlight the benefit of measuring microbial activity in the context of spatial associations.