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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.
The authors present CAMPI, a large-scale multi-lab comparison of diverse metaproteomics workflows. CAMPI provides insights into the robustness of current methods, suggests further improvements to the field, and may pave the way for future community-driven metaproteomics projects.
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1 VIB - UGent Center for Medical Biotechnology, VIB, Ghent, Belgium (GRID:grid.511525.7); Ghent University, Department of Biomolecular Medicine, Faculty of Medicine and Health Sciences, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798)
2 University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Esch-sur-Alzette, Luxembourg (GRID:grid.16008.3f) (ISNI:0000 0001 2295 9843)
3 Bioprocess Engineering, Otto-von-Guericke University Magdeburg, Magdeburg, Germany (GRID:grid.5807.a) (ISNI:0000 0001 1018 4307)
4 Department of Molecular Systems Biology, Helmholtz-Centre for Environmental Research - UFZ GmbH, Leipzig, Germany (GRID:grid.7492.8) (ISNI:0000 0004 0492 3830)
5 Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, USA (GRID:grid.135519.a) (ISNI:0000 0004 0446 2659)
6 Département Médicaments et Technologies pour la Santé (DMTS), Université Paris Saclay, CEA, INRAE, SPI, Bagnols-sur-Cèze, France (GRID:grid.5583.b) (ISNI:0000 0001 2299 8025)
7 Norwegian University of Life Sciences (NMBU), Faculty of Chemistry, Biotechnology and Food Science, Ås, Norway (GRID:grid.19477.3c) (ISNI:0000 0004 0607 975X)
8 INRAE, AgroParisTech, Micalis Institute, Université Paris-Saclay, Jouy-en-Josas, France (GRID:grid.462293.8) (ISNI:0000 0004 0522 0627)
9 Bioprocess Engineering, Otto-von-Guericke University Magdeburg, Magdeburg, Germany (GRID:grid.5807.a) (ISNI:0000 0001 1018 4307); Anhalt University of Applied Sciences, Microbiology, Department of Applied Biosciences and Process Technology, Köthen, Germany (GRID:grid.427932.9) (ISNI:0000 0001 0692 3664); Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany (GRID:grid.419517.f) (ISNI:0000 0004 0491 802X)
10 Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, Berlin, Germany (GRID:grid.13652.33) (ISNI:0000 0001 0940 3744)
11 University of Minnesota, Department of Biochemistry Molecular Biology and Biophysics, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000000419368657)
12 North Carolina State University, Department of Plant & Microbial Biology, Raleigh, USA (GRID:grid.40803.3f) (ISNI:0000 0001 2173 6074)
13 Université Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE – Le Moulon, Gif-sur-Yvette, France (GRID:grid.460789.4) (ISNI:0000 0004 4910 6535)
14 VIB - UGent Center for Medical Biotechnology, VIB, Ghent, Belgium (GRID:grid.511525.7); Ghent University, Department of Applied Mathematics, Computer Science and Statistics, Ghent, Belgium (GRID:grid.5342.0) (ISNI:0000 0001 2069 7798)
15 Bioprocess Engineering, Otto-von-Guericke University Magdeburg, Magdeburg, Germany (GRID:grid.5807.a) (ISNI:0000 0001 1018 4307); Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany (GRID:grid.419517.f) (ISNI:0000 0004 0491 802X)
16 Bioinformatics Unit (MF1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, Berlin, Germany (GRID:grid.13652.33) (ISNI:0000 0001 0940 3744); Data Analytics and Computational Statistics, Hasso-Plattner-Institute, Faculty of Digital Engineering, University of Potsdam, Potsdam, Germany (GRID:grid.500266.7)
17 Bielefeld University, Faculty of Technology, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128)
18 University of Sassari, Department of Biomedical Sciences, Sassari, Italy (GRID:grid.11450.31) (ISNI:0000 0001 2097 9138)
19 University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Esch-sur-Alzette, Luxembourg (GRID:grid.16008.3f) (ISNI:0000 0001 2295 9843); Integrated Biobank of Luxembourg, Luxembourg Institute of Health, Dudelange, Luxembourg (GRID:grid.451012.3) (ISNI:0000 0004 0621 531X)
20 University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Esch-sur-Alzette, Luxembourg (GRID:grid.16008.3f) (ISNI:0000 0001 2295 9843); University of Luxembourg, Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, Belvaux, Luxembourg (GRID:grid.16008.3f) (ISNI:0000 0001 2295 9843)
21 Section eScience (S.3), Federal Institute for Materials Research and Testing, Berlin, Germany (GRID:grid.71566.33) (ISNI:0000 0004 0603 5458)