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Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing



Mak Saito, Erin Bertrand, Megan Duffy, David Gaylord, Noelle Held, Judson Harvey, Robert Hettich, Pratik Jagtap, Michael G. Janech, Danie Kinkade, Dasha Leary, Matt McIlvin, Eli Moore, Robert Morris, Ben Neely, Brook Nunn, Jaclyn Sanders, Adam Shepherd, Nick Symmonds, David Walsh


Ocean metaproteomics is an emerging field that provides an exciting new datatype with potential to enable discoveries regarding marine microbial communities and their underlying impact on global biogeochemical processes. For example, recent ocean metaproteomic studies have provide new insights into microbial nutrient transport, co-limitation of carbon fixation, the composition of microbial biofilms, and dynamics of carbon flux in marine ecosystems. Future methodological developments should lead to new capabilities such as characterizing large scale ecosystem changes, estimating biogeochemical reaction rates from enzyme concentrations, and conducting in situ stoichiometric measurements. Yet there are continuing challenges to the widespread application of ocean metaproteomics, including aspects of environmental sampling, sample extraction, mass spectrometry, informatic processing, and data intercompatibility and sharing. The inherent biological diversity of ocean metaproteome samples results in the production of mass spectra that appear to be some of the most complex proteomic data observed. While current approaches are successful in generating exciting environmental datasets, it is likely that continued improvements in instrumentation, software algorithms, and genomic and metagenomic sequence availability will contribute to further increases in capturing the diversity of proteins present in metaproteomic samples. Future community efforts to improve data interoperability and metaproteomic intercalibrations would be particularly valuable to enable temporal and spatial comparisons of metabolic features that impact ocean biogeochemical cycling. As ocean metaproteomic data accumulates, we outline proposed best practices for data sharing of ocean metaproteomic datasets, including articulating the data types and associated metadata needed to enable intercomparisons of protein abundance results and for inferring taxonomic and functional attributes as metagenomic datasets gro
ACS Journal of Proteome Research


metaproteomics, data, data sharing


Saito, M. , Bertrand, E. , Duffy, M. , Gaylord, D. , Held, N. , Harvey, J. , Hettich, R. , Jagtap, P. , Janech, M. , Kinkade, D. , Leary, D. , McIlvin, M. , Moore, E. , Morris, R. , Neely, B. , Nunn, B. , Sanders, J. , Shepherd, A. , Symmonds, N. and Walsh, D. (2019), Progress and Challenges in Ocean Metaproteomics and Proposed Best Practices for Data Sharing, ACS Journal of Proteome Research, [online], (Accessed May 27, 2024)


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Created January 30, 2019, Updated October 12, 2021