Dataset Information

Enrichment strategy for searching missing protein

ABSTRACT: Enrichment strategy for searching missing protein is a project under the guidance of Chromosome-Centric Human Proteome Project (C-HPP). We developed systematical enrichment strategies for revealing the existence of MPs including low molecular weight (LMW), membrane proteins, post-translational modification (PTM), and nucleic acid associated.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Ping Xu

PROVIDER: MSV000083957 | MassIVE | Wed Jun 12 03:31:00 BST 2019

SECONDARY ACCESSION(S): PXD002255

REPOSITORIES: MassIVE

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Publications

Special Enrichment Strategies Greatly Increase the Efficiency of Missing Proteins Identification from Regular Proteome Samples.

Su Na N Zhang Chengpu C Zhang Yao Y Wang Zhiqiang Z Fan Fengxu F Zhao Mingzhi M Wu Feilin F Gao Yuan Y Li Yanchang Y Chen Lingsheng L Tian Miaomiao M Zhang Tao T Wen Bo B Sensang Na N Xiong Zhi Z Wu Songfeng S Liu Siqi S Yang Pengyuan P Zhen Bei B Zhu Yunping Y He Fuchu F Xu Ping P

Journal of proteome research 20150715 9

As part of the Chromosome-Centric Human Proteome Project (C-HPP) mission, laboratories all over the world have tried to map the entire missing proteins (MPs) since 2012. On the basis of the first and second Chinese Chromosome Proteome Database (CCPD 1.0 and 2.0) studies, we developed systematic enrichment strategies to identify MPs that fell into four classes: (1) low molecular weight (LMW) proteins, (2) membrane proteins, (3) proteins that contained various post-translational modifications (PTM ...[more]

PMID: 26144840

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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.

Dataset Information

Enrichment strategy for searching missing protein

Publications

Special Enrichment Strategies Greatly Increase the Efficiency of Missing Proteins Identification from Regular Proteome Samples.

Similar Datasets

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