ArticleCurrent microbiology2026
Identification of new protein-coding potential in Leishmania donovani using a proteogenomics approach.
Article in Current microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Leishmania donovani, the causative agent of visceral leishmaniasis, possesses a highly plastic genome and relies extensively on post-transcriptional regulation, posing challenges for accurate genome annotation. Despite the availability of a high-quality reference genome, many protein-coding genes remain incomplete or misannotated. While proteogenomic workflows have been previously applied to other Leishmania species, their application to the L. donovani CL-SL strain, which exhibits distinct genomic and disease-associated features, remains limited. In this study, we utilised a proteogenomic strategy integrating high-resolution tandem mass spectrometry (MS/MS) data with a custom six-frame translated genome database to re-analyse and refine the strain-specific genome annotation of L. donovani. This study is based on the systematic re-analysis of previously published proteomic datasets originally derived from the L. donovani DD8 strain and cross-mapped to the closely related L. donovani CL-SL reference assembly. By utilising stringent selection criteria, this study enables the extraction of additional, high-confidence annotation-level insights beyond the scope of the original analyses, while remaining cautious of localised, strain-specific sequence variations. Re-analysing published proteomics identified 50 N-terminal extensions and 15 novel coding regions. Many show orthology in related species and contain functional domains linked to metabolism, trafficking, or stress responses. These findings represent structural refinements to existing gene models, awaiting further experimental validation. Collectively, our findings demonstrate that proteogenomic integration significantly improves the accuracy of L. donovani genome annotation by resolving truncated gene models and uncovering hidden coding potential. These findings improve genome annotation and highlight previously unrecognised coding potential supported by peptide evidence in Leishmania donovani.
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