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Abstract
Horizontal gene transfer (HGT) is a powerful mechanism that allows bacteria to directly transfer long stretches of genomic sequence from one individual to another. The transfer of antimicrobial resistance genes is a prominent example of HGT events in the context of multi-resistant bacteria which pose a high risk to human health. While several approaches for HGT detection exist on the genomic level, to the best of our knowledge, HGT events have not been investigated in a detailed mass spectrometry (MS)-based proteomic study. However, the mere presence of a gene does not necessarily correlate with its expression at the protein level. Consequently, to draw conclusions with respect to the expression of HGT-mediated genes, MS-based proteomics can be employed. We developed a first computational approach - called Hortense - for automated HGT detection directly from shotgun proteomics experiments. We extend the standard database search by a critical cross-validation to unravel potential HGT proteins. A proteogenomic extension gives information about the genomic origin and enables an integration with existing genome-based methods. We successfully validated our approach on simulated data, and further evaluated it on real data from a transgenic organism and a negative control from an organism not harboring a transferred gene. Our results indicate that our method facilitates MS-based analysis for proteomic evidence of HGT events. Especially as an orthogonal approach to genome-based HGT detection methods, our proposed workflow is a first step toward a systematic and large scale analysis of HGT events in, e.g., antimicrobial resistance context. Hortense is publicly available at https://gitlab.com/rki_bioinformatics/.
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