Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory 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 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.

Critical Assessment of Metagenome Interpretation: the second round of challenges

“…As the state-of-the-art in methods and data generation progresses, it will be important to continuously re-evaluate these questions. In addition, computational methods for other microbiome data modalities 6 and multi-omics data integration could be jointly assessed. Most importantly, CAMI is a community-driven effort and we encourage everyone interested in benchmarking in microbiome research to join us.…”

Mistle: bringing spectral library predictions to metaproteomics with an efficient search index

“…We evaluate the performance of Mistle on two common mock communities, 9MM (Tanca et al ., 2013) and SIHUMIx (Krause et al ., 2020). For the latter, we follow the recently published CAMPI study (Van Den Bossche et al ., 2021), such that the evaluation is on par with the current metaproteomic benchmarking standard.…”

“…(2013). The two experimental files from the CAMPI study are searched in the SIHUMIx library with 10 ppm precursor tolerance and 0.02 Da fragment tolerance as was done by Van Den Bossche et al . (2021).…”

Considerations for constructing a protein sequence database for metaproteomics

“…We still do not fully understand if distinct construction strategies produce databases that perform differently on biological systems of variable complexity since the most thorough evaluations described in this paper were done only on mice and human gut samples [88] . Community efforts such as the Metaproteomics Initiative [160] , which, for example, recently carried out an interlaboratory comparison of metaproteomic workflows [19] , may represent an excellent mechanism to evaluate the impact of database construction approaches on metaproteomics.…”

“…While the shotgun proteomics approaches described above were originally developed to analyze proteomes of individual organisms, they have been adapted in a very similar form for metaproteomics [1] , [5] , [18] . However, metaproteomics comes with unique challenges not encountered when working with single organisms including (1) the difficulty of obtaining protein sequences from the organisms in the often highly diverse microbial communities and (2) the fact that the presence of homologous sequences from related organisms can make protein inference much more difficult [19] , [20] . Some researchers avoid the protein inference problem by using a peptide-centric approach, which skips the protein inference step and infers taxonomy and function directly from detected peptides by matching the peptide sequences to peptide sequences generated from public protein sequence reference databases [21] , [22] .…”