Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Tim Van Den Bossche, Benoit J. Kunath, Kay Schallert, Stephanie S. Schäpe, Paul E. Abraham, Jean Armengaud, Magnus Arntzen, Ariane Bassignani, Dirk Benndorf, Stephan Fuchs, Richard J. Giannone, Timothy J. Griffin, Live H. Hagen, Rashi Halder, Céline Henry, Robert L. Hettich, Robert Heyer, Pratik Jagtap, Nico Jehmlich, Marlene JensenCatherine Juste, Manuel Kleiner, Olivier Langella, Theresa Lehmann, Emma Leith, Patrick May, Bart Mesuere, Guylaine Miotello, Samantha L. Peters, Olivier Pible, Pedro T. Queiros, Udo Reichl, Bernhard Y. Renard, Henning Schiebenhoefer, Alexander Sczyrba, Alessandro Tanca, Kathrin Trappe, Jean Pierre Trezzi, Sergio Uzzau, Pieter Verschaffelt, Martin von Bergen, Paul Wilmes, Maximilian Wolf, Lennart Martens, Thilo Muth

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Original languageEnglish
Article number7305
JournalNature Communications
Volume12
Issue number1
DOIs
StatePublished - Dec 2021

Funding

This work has benefited from collaborations facilitated by the Metaproteomics Initiative (https://metaproteomics.org/) whose goals are to promote, improve and standardize metaproteomics. Part of the LC–MS/MS measurements were made in the Molecular Education, Technology, and Research Innovation Center (METRIC) at North Carolina State University, the ProGénoMIX platform at CEA-Marcoule supported by the IBISA network. Parts of the bioinformatics analysis were carried out using the high-performance computing facilities of the University of Luxembourg (https://hpc.uni.lu). This work was supported by the Research Foundation - Flanders (FWO) [grant no. 1S90918N (S.B.) to T.V.D.B.; 12I5217N to B.M.; G042518N to L.M.]; by a FEBS Summer Fellowship [to T.V.D.B.]; by the European Union’s Horizon 2020 Program (H2020-INFRAIA-2018-1) [823839 to L.M.]; by the FEMS [R.T.G. to S.S.S.]; by the Norwegian Centennial Chair program [to T.J.G., P.D.J., and M.A.]; the Novo Nordisk Foundation grant NNF20OC0061313 to M.A.; the USDA National Institute of Food and Agriculture Hatch project [1014212 to M.K.]; the U.S. National Science Foundation [OIA 1934844 and IOS 2003107 to M.K.]; the Foundation for Food and Agriculture Research [Grant ID: 593607 to M.K.]; the Agence Nationale de la Recherche [ANR-17-CE18-0023-01 to G.M., O.P., J.A.]; Deutsche Forschungsgemeinschaft (DFG) [RE3474/5-1 and RE3474/2-2 to S.F., T.M., B.Y.R.]. Research by T.J.G., P.D.J, E.L was funded by National Cancer Institute-Informatics Technology for Cancer Research (NCI-ITCR) grant 1U24CA199347 and National Science Foundation (U.S.) grant 1458524 to T.J.G.; and the National Institutes of Health R01-DK70977 to RLH. The European Galaxy server that was used for some calculations is in part funded by Collaborative Research Centre 992 Medical Epigenetics (DFG grant SFB 992/1 2012) and the German Federal Ministry of Education and Research (BMBF grants 031 A538A/A538C RBC, 031L0101B/031L0101C de.NBI-epi, 031L0106 de.STAIR, 031L0103 MetaProtServ (de.NBI)). This work was supported by the Luxembourg National Research Fund (FNR) under grants PRIDE/ 11823097 and CORE-INTER/13684739 to B.J.K., P.M. and P.W, and the European Research Council (ERC-CoG 863664) to P.W.

FundersFunder number
Collaborative Research Centre 992 Medical EpigeneticsSFB 992/1 2012
National Cancer Institute-Informatics Technology for Cancer Research
USDA National Institute of Food and Agriculture Hatch project
National Science FoundationOIA 1934844, 1458524, IOS 2003107
National Science Foundation
National Institutes of HealthR01-DK70977
National Institutes of Health
Foundation for the National Institutes of Health
National Cancer InstituteU24CA199347
National Cancer Institute
National Institute of Food and Agriculture1014212
National Institute of Food and Agriculture
Horizon 2020 Framework Programme
H2020 European Research Council
Foundation for Food and Agriculture Research593607
Foundation for Food and Agriculture Research
Federation of European Biochemical Societies
Federation of European Microbiological Societies
European Research CouncilERC-CoG 863664
European Research Council
Deutsche ForschungsgemeinschaftRE3474/2-2, RE3474/5-1
Deutsche Forschungsgemeinschaft
Agence Nationale de la RechercheANR-17-CE18-0023-01
Agence Nationale de la Recherche
Fonds National de la Recherche LuxembourgPRIDE/ 11823097, CORE-INTER/13684739
Fonds National de la Recherche Luxembourg
Bundesministerium für Bildung und Forschung031 A538A/A538C RBC, 031L0106 de.STAIR, 031L0103
Bundesministerium für Bildung und Forschung
Fonds Wetenschappelijk Onderzoek1S90918N, 12I5217N, G042518N
Fonds Wetenschappelijk Onderzoek
Vlaams Instituut voor Biotechnologie
Horizon 2020823839, H2020-INFRAIA-2018-1
Horizon 2020
Novo Nordisk FondenNNF20OC0061313
Novo Nordisk Fonden

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