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 language | English |
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Article number | 7305 |
Journal | Nature Communications |
Volume | 12 |
Issue number | 1 |
DOIs | |
State | Published - 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.
Funders | Funder number |
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Collaborative Research Centre 992 Medical Epigenetics | SFB 992/1 2012 |
National Cancer Institute-Informatics Technology for Cancer Research | |
USDA National Institute of Food and Agriculture Hatch project | |
National Science Foundation | OIA 1934844, 1458524, IOS 2003107 |
National Science Foundation | |
National Institutes of Health | R01-DK70977 |
National Institutes of Health | |
Foundation for the National Institutes of Health | |
National Cancer Institute | U24CA199347 |
National Cancer Institute | |
National Institute of Food and Agriculture | 1014212 |
National Institute of Food and Agriculture | |
Horizon 2020 Framework Programme | |
H2020 European Research Council | |
Foundation for Food and Agriculture Research | 593607 |
Foundation for Food and Agriculture Research | |
Federation of European Biochemical Societies | |
Federation of European Microbiological Societies | |
European Research Council | ERC-CoG 863664 |
European Research Council | |
Deutsche Forschungsgemeinschaft | RE3474/2-2, RE3474/5-1 |
Deutsche Forschungsgemeinschaft | |
Agence Nationale de la Recherche | ANR-17-CE18-0023-01 |
Agence Nationale de la Recherche | |
Fonds National de la Recherche Luxembourg | PRIDE/ 11823097, CORE-INTER/13684739 |
Fonds National de la Recherche Luxembourg | |
Bundesministerium für Bildung und Forschung | 031 A538A/A538C RBC, 031L0106 de.STAIR, 031L0103 |
Bundesministerium für Bildung und Forschung | |
Fonds Wetenschappelijk Onderzoek | 1S90918N, 12I5217N, G042518N |
Fonds Wetenschappelijk Onderzoek | |
Vlaams Instituut voor Biotechnologie | |
Horizon 2020 | 823839, H2020-INFRAIA-2018-1 |
Horizon 2020 | |
Novo Nordisk Fonden | NNF20OC0061313 |
Novo Nordisk Fonden |