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

Yuanliang ZhangZhilong LinYifan TanFanyu BuPiliang HaoKeren ZhangHuanming YangSiqi LiuYan Ren
Published in: Journal of proteome research (2019)
The mission of the Chromosome-Centric Human Proteome Project (C-HPP) to discover missing proteins (MPs) has become increasingly difficult due to the remaining low-abundance, high-hydrophobicity, or low-molecular-weight MPs. We have reported two approaches to resolve these identification problems for the low-abundance and high-hydrophobicity MPs, respectively. In this study, to improve the identification of low-abundance MPs with high hydrophobicity, we combined two approaches and obtained MPs from several different cancer cell lines. Their membrane fractions were isolated by ultracentrifugation, and the low-abundance proteins were enriched at the protein level with the ProteoMiner kit. After that, the peptides from the enriched proteins were separated by high concentrations of organic solvents according to their hydrophobicity as the first dimension of separation at the peptide level, and the second and third dimensions of separation involved a high pH reversed-phase and an acid reversed-phase column, respectively. In total, 16 MPs (at least two non-nested unique peptides with ≥9 amino acids) with 61 unique peptides were identified from four human cancer cell lines, including 2, 8, 2, and 7 MPs from HeLa, HCT116, SNU-1, and HepG2 cells, respectively. Furthermore, all MPs were verified with two non-nested unique peptides through parallel reaction monitoring (PRM) by matching the peptides with their chemically synthesized peptides. Interestingly, two additional MPs were verified from the same cell line by PRM assay, although the two non-nested unique peptides with ≥9 amino acids for each MP were identified from different MS injections or cell lines by data-dependent acquisition (DDA). Thus, a total of 18 MPs were dug out in this study. The data are available via ProteomeXchange (PXD014058) and PeptideAtlas (PASS01388).
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