Project description:In recent years, high-throughput technologies have contributed to development a more precise picture of the human proteome. However, 2,129 proteins remain listed as missing proteins (MPs) in the newest neXtProt release (2019-02). The main reasons for MPs are a low abundance, low-molecular-weight (LMW), unexpected modifications, membrane characteristics, etc. Moreover, more than 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, presents an opportunity to identify these buried MPs in complex samples. Proteins and potential MPs were identified using Open-pFind and three other search engines to compare their performance and efficiency with three large-scale datasets digested by different enzymes. Our results demonstrated that Open-pFind identified 29.9-47.5% more peptide-spectrum matches (PSMs), 48.0-63.9% more peptides sequences (with modifications) and 22.7-38.1% more peptide sequences (regardless of modifications) than those identified by the second-best search engine. As a result, Open-pFind detected 7.5-19.3% more candidate MPs than those by the second-best search engine. In total, 5 (PE2) of the 150 candidate MPs identified by Open-pFind were verified from two unique peptides containing more than 9 amino acids (AA) by using spectrum theoretical prediction with pDeep, and synthesized peptide matching with pBuild, after spectrum quality analysis, isobaric post-translational modification, and single amino acid variant (SAAV) filtering. These five verified MPs can be ranked in the PE1 level. In addition, three other candidate MPs were verified with two unique peptides (one peptide containing more than 9 AA) and the other containing only 8 AA), which were slightly lower than the criteria listed by C-HPP, and required additional verification information. More importantly, unexpected modifications were detected in these MPs. Another 141 MPs were listed as candidates, but required additional verification information.

Project description:Dengue and Zika are two mosquito-borne diseases of great concern, affecting mainly the tropical and subtropical regions worldwide. The arrival of Zika virus (ZIKV) in dengue virus (DENV) endemic areas imposed challenges for differential diagnosis and the development of candidate vaccines. The use of peptides has shown great potential to achieve these goals. We aimed to identify the linear epitope profile recognized by the serum samples of dengue and Zika patients in the E and NS1 proteins of DENV and ZIKV to select peptides with the potential for the development of diagnostic tests and vaccines. Analysis of a peptide microarray platform with serum samples of dengue and Zika patients demonstrated that the epitopes were evenly distributed across the entire viral proteins, showing no preference for particular regions. However, several epitopes were within epitope hot spots constituted by clusters of peptides recognized in more than 30% of the sub-arrays analyzed with individual or pools of serum samples. The serum samples of dengue and Zika patients showed a high level of cross-reaction for epitopes in the DENV and ZIKV proteins. Analysis of an additional peptide microarray platform containing selected peptides based on the results of the first screening showed that three peptides (DENV: TQGEPSLNEEQDKRF and TQTVGPWHLGKLEID; ZIKV: LELDPPFGDSYIVIG), highly specific for their cognate viruses (p<0.05), were within the epitope hot spots; however, these peptides showed low detection rates (32.5, 35.0, and 28.6%, respectively). We also found two peptides (DENV: WEVEDYGFGVFTTNI and LELDFDLCEGTTVVV) in the epitope hot spots detected by both dengue and Zika patients with similarly high rates (arbitrary detection rate cut-off threshold of ≥40%). The epitope hot spots harbor several immunodominant epitopes recognized by a higher number of individuals when compared to the 15 aa sequence peptides. Therefore, the entire epitope hot spots, spanning up to ~30 aa, would have more potential than peptides of only 15 aa to serve as antigens in diagnostic tests and vaccine developments.

Dataset Information

The exploration of Missing Proteins by a combination approach to enrich the low abundance membrane proteins from several cancer cell lines

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Publications

Exploration of Missing Proteins by a Combination Approach to Enrich the Low-Abundance Hydrophobic Proteins from Four Cancer Cell Lines.

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