Session: Parallel session 6 - Proteogenomics and metaproteomics

LC-MS/MS proteotyping hold a bright future as a routine diagnostic tool

Fast and accurate identification of microorganisms is essential for medical diagnosis. Traditional microbiological methods rely on cultivation, which is time-consuming and fails to detect all microorganisms. DNA amplification-based methods, such as PCR, require prior knowledge of the microorganism's genome and allow only the detection of the targeted species. MALDI-TOF only permits the detection of species included in a dedicated spectral library and performs poorly in the presence of host material. In this context, a universal method that does not require prior knowledge of the sample components and is not hindered by host proteins would greatly advance the detection and identification of pathogens. Here, we present a groundbreaking tandem mass spectrometry proteotyping method for rapid and universal microorganisms identification, eliminating the need for predefined targets, and permitting detection from multiple matrices of clinical interest.



We exemplified the use of our proteotyping method on a range of viruses including SARS-CoV-2, Vaccinia virus, and Monkeypox virus, among others, and multiple microorganisms. To demonstrate its clinical relevance, we tested the method using various clinically significant matrices, such as positive saliva, feces samples, and bacterial isolate. Samples were prepared via a shotgun proteomics workflow and analyzed using an in house pipeline permitting the taxonomical identification of the sample components using a generalist database.



Based on the combination of shared and taxa-specific peptides, our method allowed the identification of microorganisms from multiple matrices of clinical relevance. Eukaryotic and Prokaryotic organisms present in the samples were identified, permitting a versatile use of our methodology. The full experimental workflow, including digestion in 96-well plates and short LC-MS/MS analyses is amenable to high throughput, paving the way for a rapid, accurate, and non-invasive diagnosis.