Saito, M.
, Saunders, J.
, McIlvin, M.
, Bertrand, E.
, Breier, J.
, Brisbin, M.
, Colston, S.
, Compton, J.
, Griffin, T.
, Harvey, J.
, Hettich, R.
, Jagtap, P.
, Janech, M.
, Johnson, R.
, Keil, R.
, Kleikamp, H.
, Leary, D.
, McCain, S.
, Moore, E.
, Mehta, S.
, Moran, D.
, Neibauer, J.
, Neely, B.
, Jakuba, M.
, Johnson, J.
, Duffy, M.
, Herndl, G.
, Giannone, R.
, Mueller, R.
, Nunn, B.
, Pabst, M.
, Peters, S.
, Rajczewski, A.
, Rowland, E.
, Searle, B.
, Van Den Bossche, T.
, Vora, G.
, Waldbauer, J.
, Zheng, H.
and Zhao, Z.
(2024),
Results from a multi-laboratory ocean metaproteomic intercomparison: effects of LC-MS acquisition and data analysis procedures, Biogeosciences, [online], https://doi.org/10.5194/bg-21-4889-2024, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934928
(Accessed November 20, 2024)
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Results from a multi-laboratory ocean metaproteomic intercomparison: effects of LC-MS acquisition and data analysis procedures
Published
Author(s)
Mak Saito, Jaclyn Saunders, Matthew McIlvin, Erin Bertrand, John Breier, Margaret Brisbin, Sophie Colston, Jaimee Compton, Tim Griffin, Judson Harvey, Robert Hettich, Pratik Jagtap, Michael Janech, Rod Johnson, Rick Keil, Hugo Kleikamp, Dasha Leary, Scott McCain, Eli Moore, Subina Mehta, Dawn Moran, Jacqui Neibauer, , Michael Jakuba, Jim Johnson, Megan Duffy, Gerhard Herndl, Richard Giannone, Ryan Mueller, Brook Nunn, Martin Pabst, Samantha Peters, Andrew Rajczewski, Elden Rowland, Brian Searle, Tim Van Den Bossche, Gary Vora, Jacob Waldbauer, Haiyan Zheng, Zihao Zhao
Abstract
Metaproteomics is an increasingly popular methodology that provides information regarding the metabolic functions of specific microbial taxa and has potential for contributing to ocean ecology and biogeochemical studies. A blinded multi-laboratory intercomparison was conducted to assess comparability and reproducibility of taxonomic and functional results and their sensitivity to methodological variables. Euphotic zone samples from the Bermuda Atlantic Time-series Study (BATS) in the North Atlantic Ocean collected by in situ pumps and the autonomous underwater vehicle (AUV) Clio were distributed with a paired metagenome, and one-dimensional (1D) liquid chromatographic data-dependent acquisition mass spectrometry analysis was stipulated. Analysis of mass spectra from seven laboratories through a common bioinformatic pipeline identified a shared set of 1056 proteins from 1395 shared peptide constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R2 values averaged 0.62±0.11, and a Sørensen similarity analysis of the top 1000 proteins revealed 70 %–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. A bioinformatic intercomparison study, involving 10 laboratories using eight software packages, successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. Lessons learned and potential improvements in methods were described. Future efforts could examine reproducibility in deeper metaproteomes, examine accuracy in targeted absolute quantitation analyses, and develop standards for data output formats to improve data interoperability. Together, these results demonstrate the reproducibility of metaproteomic analyses and their suitability for microbial oceanography research, including integration into global-scale ocean surveys and ocean biogeochemical models.Citation
Biogeosciences
Volume
21
Issue
21
Pub Type
Journals
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Keywords
metaproteomics, biogeochemistry
Citation
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Created November 8, 2024