Metaproteomics to understand how microbiota function: The crystal ball predicts a promising future

Abstract

In the medical, environmental, and biotechnological fields, microbial communities have attracted much attention due to their roles and numerous possible applications. The study of these communities is challenging due to their diversity and complexity. Innovative methods are needed to identify the taxonomic components of individual microbiota, their changes over time, and to determine how microoorganisms interact and function. Metaproteomics is based on the identification and quantification of proteins, and can potentially provide this full picture. Due to the wide molecular panorama and functional insights it provides, metaproteomics is gaining momentum in microbiome and holobiont research. Its full potential should be unleashed in the coming years with progress in speed and cost of analyses. In this exploratory crystal ball exercise, I discuss the technical and conceptual advances in metaproteomics that I expect to drive innovative research over the next few years in microbiology. I also debate the concepts of ‘microbial dark matter’ and ‘Metaproteomics‐Assembled Proteomes (MAPs)’ and present some long‐term prospects for metaproteomics in clinical diagnostics and personalized medicine, environmental monitoring, agriculture, and biotechnology.

Taxonomical composition and functional analysis of biofilms sampled from a nuclear storage pool

“…However, due to nucleic acids amplicon amplification or metagenome sequencing and its inherent biases, the presence of contaminants may be exacerbated while no bias is expected for the proteotyping methodology. In addition, the approach based on proteins is significantly faster, as the time to results could be less than 5 h as previously reported (Armengaud, 2023), and hence the workload is significantly reduced.…”

“…This number illustrates the conjunction of two factors: an expected lack of completeness of the generalist database used for the interpretation on the one hand, and a possible decrease in the quality of some MS/MS spectra due to the co-elution of diverse peptide entities on the other hand. As recently pointed out, the diversity of peptides in metaproteomic samples can be huge, as multiple strains of the same species can cohabit ( Armengaud, 2023 ). However, these percentages compared favorably with other proteomics search results on non-model organisms whose genome has not yet been sequenced and appropriately annotated ( Trapp et al, 2016 ; Gouveia et al, 2020 ) or for metaproteomic studies of environmental samples such as soils ( Jouffret et al, 2021 ; Lidbury et al, 2022 ).…”

“…Protein inference is the procedure to assemble identified peptide sequences into the most appropriate set of proteins. This inference is far from trivial when multiple organisms share a large number of proteins with partially similar sequences ( Armengaud, 2023 ). By bypassing the protein inference problem, the peptide-centric approach provides a more direct and unbiased view of the taxonomical units present in the sample, and thus a better estimation of their contributions to the biomass ( Pible et al, 2020 ).…”

“…While metagenomics provides an insight into the potential of the microorganisms present in a sample, metaproteomics is dedicated to the global study of the proteins present in a complex sample comprising numerous different organisms in order to better understand the key pathways and the physiology of the main players, and to study the interactions of a microbial community with its environment ( Wilmes and Bond, 2006 ). Interestingly, the approach based on tandem mass spectrometry of complex peptide mixtures provides per principle two distinct but complementary pieces of information: the taxonomic characterization of the organisms present and the identification and quantification of the proteins in the system, thus describing the functioning of the system ( Armengaud, 2023 ).…”

Editorial: Environmental omics and their biotechnological applications

“…In this regard, Abdelmoneim et al proposed in this Research Topic to replace the classical 16S RNA gene amplicon analysis with a taxon-specific qPCR for increasing the throughput of soil surveys which could also be used as a diagnostic tool for soil health. This study is an excellent illustration of how omics will become valuable diagnostic tools over the next decade, as recently envisioned (Armengaud, 2023).…”