Critical Assessment of Metaproteome Investigation (CAMPI): A Multi-Lab Comparison of Established Workflows

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 carried out the first community-driven, multi-lab comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluated the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, lab-assembled human intestinal model and a human fecal sample. We observed that variability at the peptide level was predominantly due to wet-lab workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappeared at protein group level. While differences were observed for predicted community composition, similar functional profiles were obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-lab studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Critical Assessment of Metagenome Interpretation - the second round of challenges

“…As the state-of-the-art in methods and data generating techniques progresses, it will be important to continuously reevaluate these questions. In addition, computational methods for other microbiome data modalities 12 and multi-omics data integration could be jointly assessed. Most importantly, CAMI is a community-driven effort, and we encourage everyone with an interest in benchmarking from the field of microbiome research to join us.…”

“…Over the last two decades, advances in metagenomic techniques have vastly increased our knowledge of the microbial world and intensified development of data analysis techniques [1][2][3][4][5] . This created a need for unbiased and comprehensive performance assessment of these methods, to identify best practices as well as open challenges in the field [6][7][8][9][10][11][12][13] . CAMI, the Initiative for the Critical Assessment of Metagenome Interpretation, is a community-driven effort that addresses this need, by offering comprehensive benchmarking challenges and datasets representing common experimental settings, data generation techniques, and environments in microbiome research.…”

Metaproteomics to Decipher CF Host-Microbiota Interactions: Overview, Challenges and Future Perspectives

“…The inferred proteins are then used to determine which taxa are active in the community, their functions, and the relative gene expression levels. Each of the steps in this process can potentially influence the outcome of a metaproteomics analysis, as well as providing its own specific benefits and challenges [71]. Overall, two major challenges still limit the routine application of metaproteomics: (i) sample preparation due to high sample complexity and extensive contamination, and (ii) data analysis due to the computational efforts required to treat large datasets, a lack of appropriate annotated protein sequence databases, and difficulties with protein inference leading to ambiguous protein annotation [72].…”

Evaluation of sample preservation and storage methods for metaproteomics analysis of intestinal microbiomes

“…For example, metaproteomics revealed protein biomarkers of disease in Inflammatory Bowel Disease (IBD) and colorectal cancer and provided insights into the role of the microbiome in such diseases [30,31]. In addition to quantifying differences in protein abundances between samples, metaproteomics can also be used to assess microbial community structure based on proteinaceous biomass [32][33][34][35] and track incorporation of specific substrates using stable isotope content of peptides [36][37][38][39].…”

“…Metaproteomics workflows are complex and variability can be introduced at every step, from sample preparation to data acquisition by LC-MS/MS and data processing [35]. There is no standardized workflow for metaproteomics of intestinal microbiome samples but some of the individual steps have been optimized in the past, such as protein extraction [40], database creation [41], and database searching [42].…”