MOOMZ_Brx
MOOMZ Bioreactor Study
Sequencing of microbial community RNA (metatranscriptome) is a useful approach for   assessing gene expression in microorganisms from the natural environment.  This method has   revealed transcriptional patterns in situ, but can also be used to detect transcriptional cascades in   microcosms following experimental perturbation.  Unambiguously identifying differential   transcription between control and experimental treatments requires constraining effects that are   simply due to sampling and bottle enclosure.  These effects remain largely uncharacterized for   “challenging” microbial samples, such as those from anoxic regions that require special handling   to maintain in situ conditions.  Here, we demonstrate substantial changes in microbial   transcription induced by sample collection and incubation in experimental bioreactors.    Microbial communities were sampled from the water column of a marine oxygen minimum zone   by a pump system that introduced minimal oxygen contamination and subsequently incubated in   bioreactors under near in situ oxygen and temperature conditions.  Relative to the source water,   experimental samples became dominated by transcripts suggestive of cell stress, including   chaperone, protease, and RNA degradation genes from diverse taxa, with strong representation   from SAR11-like alphaproteobacteria.  In tandem, transcripts matching facultative anaerobic    gammaproteobacteria of the Alteromonadales (e.g., Colwellia) increased 4-13 fold up to 43% of   coding transcripts, and encoded a diverse gene set suggestive of protein synthesis and cell   growth.     We interpret these patterns as taxon-specific responses to combined environmental   changes in the bioreactors, including shifts in substrate or oxygen availability, and minor   temperature and pressure changes during sampling with the pump system.  Whether such   changes confound analysis of transcriptional patterns may vary based on the design of the   experiment, the taxonomic composition of the source community, and on the metabolic linkages   between community members.  These data highlight the impressive capacity for transcriptional   changes within complex microbial communities, underscoring the need for caution when   inferring in situ metabolism based on transcript abundances in experimental incubations.