Advances in the clinical use of metaproteomics

ABSTRACTIntroduction Investigating the taxonomic and functional composition of human microbiomes can aid in the understanding of disease etiologies, diagnosis, and therapy monitoring for several diseases, including inflammatory bowel disease or obesity. One method for microbiome monitoring is metaproteomics, which assesses human and microbial proteins and thus enables the study of host–microbiome interactions. This advantage led to increased interest in metaproteome analyses and significant developments to introduce this method into a clinical context.Areas covered This review summarizes the recent progress from a technical side and an application-related point of view.Expert opinion Numerous publications imply the massive potential of metaproteomics to impact human health care. However, the key challenges of standardization and validation of experimental and bioinformatic workflows and accurate quantification methods must be overcome.KEYWORDS: Bioinformaticsmass spectrometryhuman microbiomeproteomicshost–pathogen interactionsanalytic sample preparation methodsmetaproteome Article highlights This review covers recent developments and findings regarding all elements of the metaproteomic wet-lab workflow, starting with sample handling, through cell lysis, protein extraction, purification, and digestion to LC-MS/MS measurements.Strategies for handling the bioinformatic challenges in metaproteomic studies, e.g. database construction and protein annotation, are acquired from recent literature.The potential for exploring host–microbiome interactions in health and disease is highlighted by a summary of discoveries obtained in clinical metaproteomic studies regarding diseases like inflammatory bowel disease, cancer, or covid-19.We identified the accurate quantification of proteins and agreements on experimental and bioinformatical workflows and metadata standards as key challenges for increased use of metaproteomics in the clinical context.We propose that metaproteomics will have a massive potential for application in diagnostics, investigation of drug–microbiome interactions, and personalized healthcare.Author contributionsAll authors identified relevant literature beyond the search methodology, contributed to defining the concept and scope of this review, and provided expertise for the identification of future research directions and challenges. All authors provided critical feedback, helped structure the manuscript, and identified key messages to highlight. L Knipper identified workflow elements in original research articles for Supplementary Table 1. M Wolf took the lead in writing the manuscript and designed the figures, with input from all authors. R Heyer supervised this project. All authors approved the final version of the manuscript to be published.Declaration of interestThe authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.Reviewer disclosuresPeer reviewers on this manuscript have no relevant financial or other relationships to disclose.Supplemental dataSupplemental data for this article can be accessed online at https://doi.org/10.1080/14789450.2023.2215440.Additional informationFundingThis paper was not funded.