Advancing medical diagnosis with fully untargeted proteomics-based virus identification

Introduction:

The 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 on unknown pathogens or 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 virus identification, eliminating the need for predefined targets, and permitting detection from multiple matrices of clinical interest.

Methods:

We evaluated our proteotyping method on a range of viruses including SARS-CoV-2, Vaccinia virus, and Monkeypox virus, among others. To demonstrate its clinical relevance, we tested the method using various clinically significant matrices, such as positive saliva and feces samples. Proteins were extracted and digested via microplate-adapted SP3 protocol. The resulting peptides were subjected to a 30 min LC-MS/MS analysis using a Vanquish Neo UHPLC coupled to an Exploris 480 mass spectrometer (ThermoFisher). The resulting spectra were analyzed using an in-house tool, based on a cascade search permitting the taxonomical identification of the sample components using a generalist database.

Results:

Based on the combination of shared and taxa-specific peptides, our method successfully identified all viruses. Additionally, the other Eukaryotic and Prokaryotic organisms present in the sample were identified. Notably, SARS-CoV-2 and Vaccinia virus were detected from saliva, a complex biological matrix, from 106 pfu/ml, a clinically relevant concentration. In addition, rotavirus from gastroenteritis fecal samples was successfully identified, along with the different microorganisms, depicting the full sample microbial pictures in a single query. The entire experimental workflow, including digestion in 96-well plates and short LC-MS/MS analyses is straightforwardly amenable to high throughput. Such detection procedures pave the way for a rapid, accurate, and non-invasive diagnosis.