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The SARS-CoV-2 pandemic started in the end of 2019 in Wuhan, China, which highlighted the scenario of frequent cross-species transmission events. From the outbreak possibly initiated by viral spill-over into humans from an animal reservoir, now we face the human host moving globally while interacting with domesticated and peridomestic animals. The emergence of a new virus into the ecosystem leads to selecting forces and species-specific adaptations. The adaptation of SARS-CoV-2 to other animals represents a risk to controlling the dissemination of this coronavirus and the emergence of new variants. Since 2020, several mink farms in Europe and the United States have had SARS-CoV-2 outbreaks with human-mink and mink-human transmission, where the mink-selected variants possibly hold evolutionary concerning advantages. Here we investigated the permissibility of mink lung-derived cells using two cell lines, Mv-1-Lu and ENL-R, against several lineages of SARS-CoV-2, including some classified as variants of concern. The viral release rate and the infectious titers indicate that these cells support infections by different SARS-CoV-2 lineages. The viral production occurs in the first few days after infection with the low viral release by these mink cells, which is often absent for the omicron variant for lung cells. The electron microscopy reveals that during the viral replication cycle, the endomembrane system of the mink-host cell undergoes typical changes while the viral particles are produced, especially in the first days of infection. Therefore, even if limited, mink lung cells may represent a selecting source for SARS-CoV-2 variants, impacting their transmissibility and pathogenicity and making it difficult to control this new coronavirus., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Le Bideau, Pires de Souza, Boschi, Baudoin, Penant, Jardot, Fenollar, Colson, Lenk and La Scola.)

In proteomics, peptide information within mass spectrometry (MS) data from a specific organism sample is routinely matched against a protein sequence database that best represent such organism. However, if the species/strain in the sample is unknown or genetically poorly characterized, it becomes challenging to determine a database which can represent such sample. Building customized protein sequence databases merging multiple strains for a given species has become a strategy to overcome such restrictions. However, as more genetic information is publicly available and interesting genetic features such as the existence of pan- and core genes within a species are revealed, we questioned how efficient such merging strategies are to report relevant information. To test this assumption, we constructed databases containing conserved and unique sequences for 10 different species. Features that are relevant for probabilistic-based protein identification by proteomics were then monitored. As expected, increase in database complexity correlates with pangenomic complexity. However, Mycobacterium tuberculosis and Bordetella pertussis generated very complex databases even having low pangenomic complexity. We further tested database performance by using MS data from eight clinical strains from M. tuberculosis , and from two published datasets from Staphylococcus aureus . We show that by using an approach where database size is controlled by removing repeated identical tryptic sequences across strains/species, computational time can be reduced drastically as database complexity increases.

Reversible protein phosphorylation, regulated by protein kinases and phosphatases, mediates a switch between protein activity and cellular pathways that contribute to a large number of cellular processes. The Mycobacterium tuberculosis genome encodes 11 Serine/Threonine kinases (STPKs) which show close homology to eukaryotic kinases. This study aimed to elucidate the phosphoproteomic landscape of a clinical isolate of M. tuberculosis. We performed a high throughput mass spectrometric analysis of proteins extracted from an early-logarithmic phase culture. Whole cell lysate proteins were processed using the filter-aided sample preparation method, followed by phosphopeptide enrichment of tryptic peptides by strong cation exchange (SCX) and Titanium dioxide (TiO2) chromatography. The MaxQuant quantitative proteomics software package was used for protein identification. Our analysis identified 414 serine/threonine/tyrosine phosphorylated sites, with a distribution of S/T/Y sites; 38% on serine, 59% on threonine and 3% on tyrosine; present on 303 unique peptides mapping to 214 M. tuberculosis proteins. Only 45 of the S/T/Y phosphorylated proteins identified in our study had been previously described in the laboratory strain H37Rv, confirming previous reports. The remaining 169 phosphorylated proteins were newly identified in this clinical M. tuberculosis Beijing strain. We identified 5 novel tyrosine phosphorylated proteins. These findings not only expand upon our current understanding of the protein phosphorylation network in clinical M. tuberculosis but the data set also further extends and complements previous knowledge regarding phosphorylated peptides and phosphorylation sites in M. tuberculosis.