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Establishing links between microbial diversity and environmental processes requires resolving the high degree of functional variation among closely related lineages or ecotypes. Here, we implement and validate an improved metagenomic approach that estimates the spatial biogeography and environmental regulation of ecotype-specific replication patterns (RObs) across ocean regions. A total of 719 metagenomes were analyzed from meridional Bio-GO-SHIP sections in the Atlantic and Indian Ocean. Accounting for sequencing bias and anchoring replication estimates in genome structure were critical for identifying physiologically relevant biological signals. For example, ecotypes within the dominant marine cyanobacteria Prochlorococcus exhibited distinct diel cycles in RObs that peaked between 19:00–22:00. Additionally, both Prochlorococcus ecotypes and ecotypes within the highly abundant heterotroph Pelagibacter (SAR11) demonstrated systematic biogeographies in RObs that differed from spatial patterns in relative abundance. Finally, RObs was significantly regulated by nutrient stress and temperature, and explained by differences in the genomic potential for nutrient transport, energy production, cell wall structure, and replication. Our results suggest that our new approach to estimating replication is reflective of gross population growth. Moreover, this work reveals that the interaction between adaptation and environmental change drives systematic variability in replication patterns across ocean basins that is ecotype-specific, adding an activity-based dimension to our understanding of microbial niche space.

 

Historically, our understanding of bacterial ecology in the Indian Ocean has been limited to regional studies that place emphasis on community structure and function within oxygen‐minimum zones. Thus, bacterial community dynamics across the wider Indian Ocean are largely undescribed. As part of Bio‐GO‐SHIP, we sequenced the 16S rRNA gene from 465 samples collected on sections I07N and I09N. We found that (1) there were 23 distinct bioregions within the Indian Ocean, (2) the southeastern gyre had the largest gradient in bacterial alpha‐diversity, (3) the Indian Ocean surface microbiome was primarily composed of a core set of taxa, and (4) bioregions were characterized by transitions in physical and geochemical conditions. Overall, we showed that bacterial community structure spatially delineated the surface Indian Ocean and that these microbially defined regions were reflective of subtle ocean physical and geochemical gradients. Therefore, incorporating metrics of in situ microbial communities into marine ecological regions traditionally defined by remote sensing will improve our ability to delineate warm, oligotrophic regions.

 

Abstract Concentrations and elemental stoichiometry of suspended particulate organic carbon, nitrogen, phosphorus, and oxygen demand for respiration (C:N:P:−O 2 ) play a vital role in characterizing and quantifying marine elemental cycles. Here, we present Version 2 of the Global Ocean Particulate Organic Phosphorus, Carbon, Oxygen for Respiration, and Nitrogen (GO-POPCORN) dataset. Version 1 is a previously published dataset of particulate organic matter from 70 different studies between 1971 and 2010, while Version 2 is comprised of data collected from recent cruises between 2011 and 2020. The combined GO-POPCORN dataset contains 2673 paired surface POC/N/P measurements from 70°S to 73°N across all major ocean basins at high spatial resolution. Version 2 also includes 965 measurements of oxygen demand for organic carbon respiration. This new dataset can help validate and calibrate the next generation of global ocean biogeochemical models with flexible elemental stoichiometry. We expect that incorporating variable C:N:P:-O 2 into models will help improve our estimates of key ocean biogeochemical fluxes such as carbon export, nitrogen fixation, and organic matter remineralization. 

Detailed descriptions of microbial communities have lagged far behind physical and chemical measurements in the marine environment. Here, we present 971 globally distributed surface ocean metagenomes collected at high spatio-temporal resolution. Our low-cost metagenomic sequencing protocol produced 3.65 terabases of data, where the median number of base pairs per sample was 3.41 billion. The median distance between sampling stations was 26 km. The metagenomic libraries described here were collected as a part of a biological initiative for the Global Ocean Ship-based Hydrographic Investigations Program, or “Bio-GO-SHIP.” One of the primary aims of GO-SHIP is to produce high spatial and vertical resolution measurements of key state variables to directly quantify climate change impacts on ocean environments. By similarly collecting marine metagenomes at high spatiotemporal resolution, we expect that this dataset will help answer questions about the link between microbial communities and biogeochemical fluxes in a changing ocean.

 

Nutrient supply regulates the activity of phytoplankton, but the global biogeography of nutrient limitation and co-limitation is poorly understood.Prochlorococcusadapt to local environments by gene gains and losses, and we used genomic changes as an indicator of adaptation to nutrient stress. We collected metagenomes from all major ocean regions as part of the Global Ocean Ship-based Hydrographic Investigations Program (Bio-GO-SHIP) and quantified shifts in genes involved in nitrogen, phosphorus, and iron assimilation. We found regional transitions in stress type and severity as well as widespread co-stress.Prochlorococcusstress genes, bottle experiments, and Earth system model predictions were correlated. We propose that the biogeography of multinutrient stress is stoichiometrically linked by controls on nitrogen fixation. Our omics-based description of phytoplankton resource use provides a nuanced and highly resolved description of nutrient stress in the global ocean.