title: Satellite remote sensing data can be used to model marine microbial metabolite turnover.
abstract: Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km(2)) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10(-6)) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ∼3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.
authors: Argonne National Laboratory, Biosciences Division, Argonne, IL, USA.
authors: Peter E
authors: PE
authors: Larsen
authors: Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
authors: Nicole
authors: 0000000301930528
authors: N
authors: Scott
authors: The Josephine Bay Paul Center for Comparative Molecular Biology and Evolution, Marine Biological Laboratory, Woods Hole, MA, USA.
authors: Anton F
authors: AF
authors: Post
authors: NERC Centre for Ecology and Hydrology, Wallingford, UK.
authors: Dawn
authors: D
authors: Field
authors: Department of Chemistry and Biochemistry, BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, USA.
authors: Rob
authors: R
authors: Knight
authors: Argonne National Laboratory, Environmental Science Division, Argonne, IL, USA.
authors: Yuki
authors: Y
authors: Hamada
authors: 1] Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA [2] Argonne National Laboratory, Institute for Genomic and Systems Biology, Argonne, IL, USA.
authors: Jack A
authors: JA
authors: Gilbert
mesh_terms: D001419:Bacteria / Q000235:genetics* / Q000378:metabolism; D004739:England; D004784:Environmental Monitoring / Q000379:methods*; D040362:Geographic Information Systems; D006801:Humans; D008954:Models, Biological; D009792:Oceans and Seas; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D063809:Satellite Imagery; D012623:Seawater / Q000382:microbiology*; D014871:Water Microbiology
chemical_list: D012336:RNA, Ribosomal, 16S