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Extensive and expanding oxygen minimum zones (OMZs) exist at variable depths in coastal and open ocean waters. As oxygen levels decline, nutrients and energy are increasingly diverted away from higher trophic levels into microbial community metabolism, resulting in fixed nitrogen loss and production of climate active trace gases including nitrous oxide and methane. While ocean deoxygenation has been reported on a global scale, our understanding of OMZ biology and geochemistry is limited by a lack of time-resolved data sets. Here, we present a historical dataset of oxygen concentrations spanning fifty years and nine years of monthly geochemical time series observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique geochemical framework for evaluating long-term trends in biogeochemical cycling in OMZ waters.

Today in Scientific Data, two compendia of geochemical and multi-omic sequence information (DNA, RNA, protein) generated over almost a decade of time series monitoring in a seasonally anoxic coastal marine setting are presented to the scientific community. These data descriptors introduce a model ecosystem for the study of microbial responses to ocean deoxygenation, a phenotype that is currently expanding due to climate change. Public access to this time series information is intended to promote scientific collaborations and the generation of new hypotheses relevant to microbial ecology, biogeochemistry and global change issues.

Extensive and expanding oxygen minimum zones (OMZs) exist at variable depths in coastal and open ocean waters. As oxygen levels decline, nutrients and energy are increasingly diverted away from higher trophic levels into microbial community metabolism, resulting in fixed nitrogen loss and production of climate active trace gases including nitrous oxide and methane. While ocean deoxygenation has been reported on a global scale, our understanding of OMZ biology and geochemistry is limited by a lack of time-resolved data sets. Here, we present a historical dataset of oxygen concentrations spanning fifty years and nine years of monthly geochemical time series observations in Saanich Inlet, a seasonally anoxic fjord on the coast of Vancouver Island, British Columbia, Canada that undergoes recurring changes in water column oxygenation status. This compendium provides a unique geochemical framework for evaluating long-term trends in biogeochemical cycling in OMZ waters. Machine-accessible metadata file describing the reported data (ISA-Tab format)

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools., Alexander Graham Bell Canada (Graduate Scholarships-Doctoral Program (CGS D)), Tula Foundation, University of British Columbia. Faculty of Graduate and Postdoctoral Studies, Stanford University. School of Medicine (Dean's Funds), National Institutes of Health (U.S.) (Biotechnology Training Grant, grant number 5T32 GM008412), King Abdullah University of Science and Technology (research grant under the KAUST Stanford Academic Excellence Alliance program), National Institutes of Health (U.S.) (NIH/NIGMS 5R01GM099534), Thomas C. and Joan M. Merigan Endowment