Ultra-sensitive metaproteomics (uMetaP) redefines the "dark" metaproteome, enables single-bacterium resolution, and discovers hidden functions in the gut microbiome

The interplay between members of microbial communities (microbiomes) is crucial for planetary health. While genomic methods have greatly expanded the taxonomic characterisation of microbiomes, complementary techniques for directly quantifying biological functions are needed for deeper understanding.

Metaproteomics, which analyzes microbial samples using liquid chromatography-tandem mass spectrometry (LC-MS)-based proteomics, has emerged as a powerful tool for studying host-microbiome interactions. It offers a direct view of functional changes within microbes and their host. However, metaproteomics faces significant challenges compared to single-organism LC-MS. Microbial samples are incredibly complex, containing an estimated 100 million unique peptide species with a vast dynamic range. Consequently, over 80% of bacterial species detected by common genomic methods (e.g., 16S rRNA) remain undetected by metaproteomics, limiting functional characterization. A significant leap in sensitivity, depth, and accuracy is needed to tap into this "dark metaproteome".

We present a novel, ultra-sensitive metaproteomic solution called uMetaP, which leverages cutting-edge technologies for unprecedented sensitivity. Utilizing mouse feces as a model, uMetaP achieves dramatic improvements in key metrics. This includes quantifying unprecedented amounts of protein groups and associated functional pathways for both the host and its microbiome (47925 protein groups and 223 KEGG pathways). Remarkably, uMetaP quantified 220 microbial species, which is comparable to the average amount reached by full-length 16S rRNA, with exceptional reproducibility and quantitative precision in DIA-PASEF runs using low sample amounts (25 ng of peptides). Additionally, uMetaP revealed (i) previously hidden functions, identifying 3252 proteins of unknown function (PUFs), (ii) taxonomic and functional annotation of 2,181 small proteins (sProt), and (iii) 553 proteins gathering predicted antimicrobial peptide sequences (AMPs).

Leveraging uMetaP with a meticulous experimental design utilizing novel SILAC-labelled bacteria, we addressed two longstanding challenges in metaproteomics: 1) the true limit of detection for the so-called "dark metaproteome", and 2) detection at the single-bacterium resolution. We confidently detected 10000 spiked-in bacteria among a theoretical amount of 10 billion, lowering the limit of detection 5000-fold. Moreover, we robustly identified species-specific peptides from a 500 fg two-bacteria peptide mix with remarkable quantification precision and accuracy.

From deciphering the interplay of billions of microorganisms with the host to exploring microbial heterogeneity, uMetaP represents a quantum leap in metaproteomics with the potential to open new avenues for our understanding of the microbial world and its connection to health and disease.