Exploring the microbiome in long COVID patients: a metaproteomic study

Most people infected with COVID-19 recover over time, but a percentage develop what is known as long COVID. Long COVID is the persistence or development of new symptoms with no other explanation 3 months after the SARS COV-2 infection and lasting at least 4 weeks. Previous research has confirmed a relationship between an altered gut microbiota and COVID-19, suggesting that a similar association may exist with long COVID. In this study, our main objective was to investigate changes in microbiota composition and function in patients with long COVID using metaproteomics.

A cohort of 100 patients with long COVID and 34 controls was recruited. Faecal and saliva samples were collected from each patient and control. Faecal samples were processed using differential centrifugation and a combination of bead beating and sonication, whereas saliva samples were processed by sonication only. Peptides were analysed on a timsTOF Pro2 using MSFragger for protein and peptide identification. The Integrated Gene Catalog and the Human Oral Microbiome Database were used for microbial protein identification of gut and oral samples, respectively. Metalab program was used for taxonomic and functional annotation of gut microbiota samples, and for the taxonomic analysis of oral samples. The functional analysis of salivary microbiota was performed using the Unipept Desktop application due to the incompatibility of the database with the functional annotation option of Metalab.

In total, we identified 7.437 protein groups, corresponding to 557 different taxa in the gut microbiota and 1.154 protein groups corresponding to 344 taxa in the oral microbiota in at least 50% of the samples. RStudio was used for visualization and statistical analysis. We observed differences in the relative abundance of different taxa between groups (long COVID and control) in both samples. For example, Akkermansia genus, which is thought to have beneficial effects on host health, was significantly more abundant in control samples. A taxon-symptom correlation analysis was performed to evaluate the importance of these taxa in long COVID condition. We also identified 3497 human proteins in saliva samples. Functional analysis of these proteins revealed interesting results. For example, the String analysis showed a significant cluster associated with fibrinogen proteins. High levels of fibrinogen have been associated with a poor prognosis in COVID-19, and coagulation abnormalities have also been observed in long COVID patients.

In conclusion, our findings highlight the importance of studying the microbiota to understand and potentially manage the complexities of long COVID. This research provides valuable insights into the disease that may improve patient outcomes.