The exploration of Missing Proteins by a combination approach to enrich the low abundance hydrophobic proteins from four cancer cell lines.

The mission of the Chromosome-Centric Human Proteome Project (C-HPP) to discover Missing Proteins (MP) has become increasingly difficult due to the remaining low-abundance, high-hydrophobicity or low-molecular-weight MPs. We have reported two approaches to resolving these identification problems for the low-abundance and high-hydrophobicity MPs. 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 2 non-nested unique peptides with ≥9 amino acids) with 61 unique peptides were identified from 4 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, 2 additional MPs were verified from the same cell line by PRM assay, although the 2 non-nested unique peptides with ≥9 amino acids for each MP were identified from different MS injections or cell lines by DDA. Thus a total of 18 MPs were dig out in this study. The data are available via ProteomeXchange (PXD014058) and PeptideAtlas (PASS01388).

[1]  Huanming Yang,et al.  Improvement of Peptide Separation for Exploring the Missing Proteins Localized on Membranes. , 2018, Journal of proteome research.

[2]  F. He,et al.  Multiproteases Combined with High-pH Reverse-Phase Separation Strategy Verified Fourteen Missing Proteins in Human Testis Tissue. , 2018, Journal of proteome research.

[3]  F. He,et al.  Digging for Missing Proteins Using Low-Molecular-Weight Protein Enrichment and a "Mirror Protease" Strategy. , 2018, Journal of proteome research.

[4]  G. Omenn,et al.  Progress on Identifying and Characterizing the Human Proteome: 2018 Metrics from the HUPO Human Proteome Project. , 2018, Journal of proteome research.

[5]  Eric W Deutsch,et al.  Progress and Future Direction of Chromosome-Centric Human Proteome Project. , 2017, Journal of proteome research.

[6]  Huanming Yang,et al.  Digging More Missing Proteins Using an Enrichment Approach with ProteoMiner. , 2017, Journal of proteome research.

[7]  S. Ranganathan,et al.  Accelerating the search for the missing proteins in the human proteome , 2017, Nature Communications.

[8]  Amos Bairoch,et al.  The neXtProt knowledgebase on human proteins: 2017 update , 2016, Nucleic Acids Res..

[9]  G. Omenn,et al.  Progress in the Chromosome-Centric Human Proteome Project as Highlighted in the Annual Special Issue IV. , 2016, Journal of proteome research.

[10]  Tadashi Yamamoto,et al.  Why are they missing? : Bioinformatics characterization of missing human proteins. , 2016, Journal of proteomics.

[11]  Lydie Lane,et al.  Metrics for the Human Proteome Project 2016: Progress on Identifying and Characterizing the Human Proteome, Including Post-Translational Modifications. , 2016, Journal of proteome research.

[12]  Lennart Martens,et al.  Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 2.1. , 2016, Journal of proteome research.

[13]  A. Bairoch,et al.  Missing Protein Landscape of Human Chromosomes 2 and 14: Progress and Current Status. , 2016, Journal of proteome research.

[14]  Oliver Kohlbacher,et al.  LFQProfiler and RNP(xl): Open-Source Tools for Label-Free Quantification and Protein-RNA Cross-Linking Integrated into Proteome Discoverer. , 2016, Journal of proteome research.

[15]  Hao Jiang,et al.  In-Depth Proteomic Quantification of Cell Secretome in Serum-Containing Conditioned Medium. , 2016, Analytical chemistry.

[16]  Jens Nielsen,et al.  Transcriptomics resources of human tissues and organs , 2016, Molecular systems biology.

[17]  G. Aldini,et al.  An in depth proteomic analysis based on ProteoMiner, affinity chromatography and nano-HPLC-MS/MS to explain the potential health benefits of bovine colostrum. , 2016, Journal of pharmaceutical and biomedical analysis.

[18]  A. Nesvizhskii,et al.  Metrics for the Human Proteome Project 2015: Progress on the Human Proteome and Guidelines for High-Confidence Protein Identification. , 2015, Journal of proteome research.

[19]  J. Hardouin,et al.  Characterization of new outer membrane proteins of Pseudomonas aeruginosa using a combinatorial peptide ligand library , 2015, Analytical and Bioanalytical Chemistry.

[20]  G. Jarvik,et al.  Parallel reaction monitoring (PRM) and selected reaction monitoring (SRM) exhibit comparable linearity, dynamic range and precision for targeted quantitative HDL proteomics. , 2015, Journal of proteomics.

[21]  G. Omenn The strategy, organization, and progress of the HUPO Human Proteome Project. , 2014, Journal of proteomics.

[22]  P. Clegg,et al.  Comprehensive protein profiling of synovial fluid in osteoarthritis following protein equalization , 2014, Osteoarthritis and cartilage.

[23]  Derek J. Bailey,et al.  Parallel Reaction Monitoring for High Resolution and High Mass Accuracy Quantitative, Targeted Proteomics* , 2012, Molecular & Cellular Proteomics.

[24]  S. Hanash,et al.  Standard guidelines for the chromosome-centric human proteome project. , 2012, Journal of proteome research.

[25]  S. Hanash,et al.  The Chromosome-Centric Human Proteome Project for cataloging proteins encoded in the genome , 2012, Nature Biotechnology.

[26]  E. Boschetti,et al.  Contribution of solid-phase hexapeptide ligand libraries to the repertoire of human bile proteins. , 2007, Journal of chromatography. A.

[27]  William Stafford Noble,et al.  Semi-supervised learning for peptide identification from shotgun proteomics datasets , 2007, Nature Methods.

[28]  Juri Rappsilber,et al.  Proteomic analysis of human blood serum using peptide library beads. , 2007, Journal of proteome research.

[29]  Juri Rappsilber,et al.  Exploring the hidden human urinary proteome via ligand library beads. , 2005, Journal of proteome research.

[30]  Liliana Gheorghiu,et al.  Reduction of the concentration difference of proteins in biological liquids using a library of combinatorial ligands , 2005, Electrophoresis.

[31]  J. Yates,et al.  An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database , 1994, Journal of the American Society for Mass Spectrometry.

[32]  Martin von Bergen,et al.  Comparison of targeted peptide quantification assays for reductive dehalogenases by selective reaction monitoring (SRM) and precursor reaction monitoring (PRM) , 2013, Analytical and Bioanalytical Chemistry.