Open-pFind Enhances the Identification of Missing Proteins from Human Testis Tissue.

Abstract

In recent years, high-throughput technologies have contributed to the development of a more precise picture of the human proteome. However, 2129 proteins remain listed as missing proteins (MPs) in the newest neXtProt release (2019-02). The main reasons for MPs are a low abundance, a low molecular weight, unexpected modifications, membrane characteristics, and so on. Moreover, >50% of the MS/MS data have not been successfully identified in shotgun proteomics. Open-pFind, an efficient open search engine, recently released by the pFind group in China, might provide an opportunity to identify these buried MPs in complex samples. In this study, proteins and potential MPs were identified using Open-pFind and three other search engines to compare their performance and efficiency with three large-scale data sets digested by three enzymes (Glu-C, Lys-C, and trypsin) with specificity on different amino acid (AA) residues. Our results demonstrated that Open-pFind identified 44.7-93.1% more peptide-spectrum matches and 21.3-61.6% more peptide sequences than the second-best search engine. As a result, Open-pFind detected 53.1% more MP candidates than MaxQuant and 8.8% more candidate MPs than Proteome Discoverer. In total, 5 (PE2) of the 124 MP candidates identified by Open-pFind were verified with 2 or 3 unique peptides containing more than 9 AAs by using a spectrum theoretical prediction with pDeep and synthesized peptide matching with pBuild after spectrum quality analysis, isobaric post-translational modification, and single amino acid variant filtering. These five verified MPs can be saved as PE1 proteins. In addition, three other MP candidates were verified with two unique peptides (one peptide containing more than 9 AAs and the other containing only 8 AAs), which was slightly lower than the criteria listed by C-HPP and required additional verification information. More importantly, unexpected modifications were detected in these MPs. All MS data sets have been deposited into ProteomeXchange with the identifier PXD015759.