Preprints
https://doi.org/10.5194/egusphere-2023-3148
https://doi.org/10.5194/egusphere-2023-3148
16 Jan 2024
 | 16 Jan 2024
Status: this preprint is open for discussion.

Results from a Multi-Laboratory Ocean Metaproteomic Intercomparison: Effects of LC-MS Acquisition and Data Analysis Procedures

Mak A. Saito, Jaclyn K. Saunders, Matthew R. McIlvin, Erin M. Bertrand, John A. Breier, Margaret Mars Brisbin, Sophie M. Colston, Jaimee R. Compton, Tim J. Griffin, W. Judson Hervey, Robert L. Hettich, Pratik D. Jagtap, Michael Janech, Rod Johnson, Rick Keil, Hugo Kleikamp, Dagmar Leary, Lennart Martens, J. Scott P. McCain, Eli Moore, Subina Mehta, Dawn M. Moran, Jaqui Neibauer, Benjamin A. Neely, Michael V. Jakuba, Jim Johnson, Megan Duffy, Gerhard J. Herndl, Richard Giannone, Ryan Mueller, Brook L. Nunn, Martin Pabst, Samantha Peters, Andrew Rajczewski, Elden Rowland, Brian Searle, Tim Van Den Bossche, Gary J. Vora, Jacob R. Waldbauer, Haiyan Zheng, and 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 in the North Atlantic Ocean collected by in situ pumps and the AUV Clio were distributed with a paired metagenome, and one-dimensional liquid chromatographic data dependent acquisition mass spectrometry analyses was stipulated. Analysis of mass spectra from seven laboratories through a common informatic pipeline identified a shared set of 1056 proteins from 1395 shared peptides constituents. Quantitative analyses showed good reproducibility: pairwise regressions of spectral counts between laboratories yielded R2 values ranging from 0.43 to 0.83, and a Sørensen similarity analysis of the top 1,000 proteins revealed 70–80 % similarity between laboratory groups. Taxonomic and functional assignments showed good coherence between technical replicates and different laboratories. An informatic intercomparison study, involving 10 laboratories using 8 software packages successfully identified thousands of peptides within the complex metaproteomic datasets, demonstrating the utility of these software tools for ocean metaproteomic research. 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.

Mak A. Saito, Jaclyn K. Saunders, Matthew R. McIlvin, Erin M. Bertrand, John A. Breier, Margaret Mars Brisbin, Sophie M. Colston, Jaimee R. Compton, Tim J. Griffin, W. Judson Hervey, Robert L. Hettich, Pratik D. Jagtap, Michael Janech, Rod Johnson, Rick Keil, Hugo Kleikamp, Dagmar Leary, Lennart Martens, J. Scott P. McCain, Eli Moore, Subina Mehta, Dawn M. Moran, Jaqui Neibauer, Benjamin A. Neely, Michael V. Jakuba, Jim Johnson, Megan Duffy, Gerhard J. Herndl, Richard Giannone, Ryan Mueller, Brook L. Nunn, Martin Pabst, Samantha Peters, Andrew Rajczewski, Elden Rowland, Brian Searle, Tim Van Den Bossche, Gary J. Vora, Jacob R. Waldbauer, Haiyan Zheng, and Zihao Zhao

Status: open (until 27 Mar 2024)

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  • RC1: 'Comment on egusphere-2023-3148', Anonymous Referee #1, 26 Feb 2024 reply
Mak A. Saito, Jaclyn K. Saunders, Matthew R. McIlvin, Erin M. Bertrand, John A. Breier, Margaret Mars Brisbin, Sophie M. Colston, Jaimee R. Compton, Tim J. Griffin, W. Judson Hervey, Robert L. Hettich, Pratik D. Jagtap, Michael Janech, Rod Johnson, Rick Keil, Hugo Kleikamp, Dagmar Leary, Lennart Martens, J. Scott P. McCain, Eli Moore, Subina Mehta, Dawn M. Moran, Jaqui Neibauer, Benjamin A. Neely, Michael V. Jakuba, Jim Johnson, Megan Duffy, Gerhard J. Herndl, Richard Giannone, Ryan Mueller, Brook L. Nunn, Martin Pabst, Samantha Peters, Andrew Rajczewski, Elden Rowland, Brian Searle, Tim Van Den Bossche, Gary J. Vora, Jacob R. Waldbauer, Haiyan Zheng, and Zihao Zhao

Data sets

Environmental dataset at Biological and Chemical Data Management Office Mak Saito https://www.bco-dmo.org/project/765945

Ocean Metaproteome Intercomparison Consortium: Metagenome Sequencing Reads for Proteome Informatics & Data Analysis Intercomparison Naval Research Laboratory https://www.ncbi.nlm.nih.gov/bioproject/PRJNA932835

Mak A. Saito, Jaclyn K. Saunders, Matthew R. McIlvin, Erin M. Bertrand, John A. Breier, Margaret Mars Brisbin, Sophie M. Colston, Jaimee R. Compton, Tim J. Griffin, W. Judson Hervey, Robert L. Hettich, Pratik D. Jagtap, Michael Janech, Rod Johnson, Rick Keil, Hugo Kleikamp, Dagmar Leary, Lennart Martens, J. Scott P. McCain, Eli Moore, Subina Mehta, Dawn M. Moran, Jaqui Neibauer, Benjamin A. Neely, Michael V. Jakuba, Jim Johnson, Megan Duffy, Gerhard J. Herndl, Richard Giannone, Ryan Mueller, Brook L. Nunn, Martin Pabst, Samantha Peters, Andrew Rajczewski, Elden Rowland, Brian Searle, Tim Van Den Bossche, Gary J. Vora, Jacob R. Waldbauer, Haiyan Zheng, and Zihao Zhao

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Short summary
The ability to assess the functional capabilities of microbes in the environment is of increasing interest. Metaproteomics, the ability to measure proteins across microbial populations, has been increasing in capability and popularity in recent years. Here, an international team of scientists conducted an intercomparison study using samples collected from the North Atlantic Ocean and observed consistency in the peptides and proteins identified, their functions, and taxonomic origins.