ChiMSource improves the accuracy of studies on novel amino acid sequences by predicting alternative sources of mass spectrometry-derived peptides
- 1. Univ Gottingen, Max Planck Inst Multidisciplinary Sci, Clin Neurosci Res Grp, D-37075 Gottingen, Germany
- 2. Oran High Sch Biol Sci ESSBO, Cellular & Mol Biol Dept, Oran 31000, Algeria
- 3. Istanbul Tech Univ, Fac Elect & Elect Engn, TR-34485 Istanbul, Turkiye
- 4. United Arab Emirates Univ, Dept Biol, POB 15551, Al Ain, U Arab Emirates
Description
Mass spectrometry (MS) proteomics is currently the most powerful tool for identifying both annotated proteins and proteins translated from non-canonical open reading frames or unusual genetic events. With this method, numerous novel protein-coding loci have been discovered by searching for short fragments of hypothetical longer peptides and polypeptides. Apart from the validation of translation from mRNA transcripts, MS proteomics has been instrumental for the detection of peptides encoded by non-mRNA transcripts. A special application field of MS proteomics is studies on programmed ribosomal frameshifting (PRF), where the detection of chimeric peptides produced from two different reading frames is vital. Each novel chimeric peptide is thought to originate from a certain genetic locus. However, due to the short length of MS peptides, there is a possibility that MS-validated peptides are produced by additional (alternative) loci via PRF. This scenario evaded due attention because the contribution of non-canonical peptides and proteins to the functional diversity of proteomes is still thought to be minor. Recent studies have challenged this paradigm. To the best of our knowledge, our group was the first to include alternative chimeric sources into the analysis pipeline. This resulted in a much higher certainty about the genomic origin of chimeric peptides, which is crucial for their functional characterization. At the same time, our study revealed an enormous diversity of potential alternative sources for a subset of MS-validated chimeric peptides. Here, we present a highly flexible program that predicts alternative chimeric and non-chimeric sources of peptides detected by MS proteomics.
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