Transcription Factor Response Elements on Tip: A Sensitive Approach for Large-Scale Endogenous Transcription Factor Quantitative Identification

The ability to map endogenous transcription factors (TFs) DNA binding activity at the proteome scale will greatly enhance our understanding of various biological processes. Here we report a highly sensitive, rapid, and high-throughput approach, transcription factor response elements on tip-mass spectrometry (TOT-MS), that allows for quantitative measurement of endogenous TFs. A total of 150 TFs from 1 μg of nuclear extracts can be quantified with single shot mass spectrometry detection in 1 h of machine time. Up to 755 TFs, which is comparable to the depth of RNA-seq, were identified by TOT coupled with on-tip small size reverse-phase liquid chromatography. We further demonstrated the capability of TOT-MS by interrogating the dynamic change of TFs in the epidermal growth factor (EGF) signaling pathway. This approach should find broad applications in elucidating the TF landscape from limited amounts of biological materials

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

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 (PTMs), and (4) nucleic acid-associated proteins. Of 8845 proteins identified in 7 data sets, 79 proteins were classified as MPs. Among data sets derived from different enrichment strategies, data sets for LMW and PTM yielded the most novel MPs. In addition, we found that some MPs were identified in multiple-data sets, which implied that tandem enrichments methods might improve the ability to identify MPs. Moreover, low expression at the transcription level was the major cause of the “missing” of these MPs; however, MPs with higher expression level also evaded identification, most likely due to other characteristics such as LMW, high hydrophobicity and PTM. By combining a stringent manual check of the MS₂ spectra with peptides synthesis verification, we confirmed 30 MPs (neXtProt PE2 ∼ PE4) and 6 potential MPs (neXtProt PE5) with authentic MS evidence. By integrating our large-scale data sets of CCPD 2.0, the number of identified proteins has increased considerably beyond simulation saturation. Here, we show that special enrichment strategies can break through the data saturation bottleneck, which could increase the efficiency of MP identification in future C-HPP studies. All 7 data sets have been uploaded to ProteomeXchange with the identifier PXD002255

Tissue-Based Proteogenomics Reveals that Human Testis Endows Plentiful Missing Proteins

Investigations of missing proteins (MPs) are being endorsed by many bioanalytical strategies. We proposed that proteogenomics of testis tissue was a feasible approach to identify more MPs because testis tissues have higher gene expression levels. Here we combined proteomics and transcriptomics to survey gene expression in human testis tissues from three post-mortem individuals. Proteins were extracted and separated with glycine- and tricine-SDS-PAGE. A total of 9597 protein groups were identified; of these, 166 protein groups were listed as MPs, including 138 groups (83.1%) with transcriptional evidence. A total of 2948 proteins are designated as MPs, and 5.6% of these were identified in this study. The high incidence of MPs in testis tissue indicates that this is a rich resource for MPs. Functional category analysis revealed that the biological processes that testis MPs are mainly involved in are sexual reproduction and spermatogenesis. Some of the MPs are potentially involved in tumorgenesis in other tissues. Therefore, this proteogenomics analysis of individual testis tissues provides convincing evidence of the discovery of MPs. All mass spectrometry data from this study have been deposited in the ProteomeXchange (data set identifier PXD002179)

First Proteomic Exploration of Protein-Encoding Genes on Chromosome 1 in Human Liver, Stomach, and Colon

The launch of the Chromosome-Centric Human Proteome Project provides an opportunity to gain insight into the human proteome. The Chinese Human Chromosome Proteome Consortium has initiated proteomic exploration of protein-encoding genes on human chromosomes 1, 8, and 20. Collaboration within the consortium has generated a comprehensive proteome data set using normal and carcinomatous tissues from human liver, stomach, and colon and 13 cell lines originating in these organs. We identified 12,101 proteins (59.8% coverage against Swiss-Prot human entries) with a protein false discovery rate of less than 1%. On chromosome 1, 1,252 proteins mapping to 1,227 genes, representing 60.9% of Swiss-Prot entries, were identified; however, 805 proteins remain unidentified, suggesting that analysis of more diverse samples using more advanced proteomic technologies is required. Genes encoding the unidentified proteins were concentrated in seven blocks, located at p36, q12-21, and q42-44, partly consistent with correlation of these blocks with cancers of the liver, stomach, and colon. Combined transcriptome, proteome, and cofunctionality analyses confirmed 23 coexpression clusters containing 165 genes. Biological information, including chromosome structure, GC content, and protein coexpression pattern was analyzed using multilayered, circular visualization and tabular visualization. Details of data analysis and updates are available in the Chinese Chromosome-Centric Human Proteome Database (http://proteomeview.hupo.org.cn/chromosome/)

First Proteomic Exploration of Protein-Encoding Genes on Chromosome 1 in Human Liver, Stomach, and Colon

The launch of the Chromosome-Centric Human Proteome Project provides an opportunity to gain insight into the human proteome. The Chinese Human Chromosome Proteome Consortium has initiated proteomic exploration of protein-encoding genes on human chromosomes 1, 8, and 20. Collaboration within the consortium has generated a comprehensive proteome data set using normal and carcinomatous tissues from human liver, stomach, and colon and 13 cell lines originating in these organs. We identified 12,101 proteins (59.8% coverage against Swiss-Prot human entries) with a protein false discovery rate of less than 1%. On chromosome 1, 1,252 proteins mapping to 1,227 genes, representing 60.9% of Swiss-Prot entries, were identified; however, 805 proteins remain unidentified, suggesting that analysis of more diverse samples using more advanced proteomic technologies is required. Genes encoding the unidentified proteins were concentrated in seven blocks, located at p36, q12-21, and q42-44, partly consistent with correlation of these blocks with cancers of the liver, stomach, and colon. Combined transcriptome, proteome, and cofunctionality analyses confirmed 23 coexpression clusters containing 165 genes. Biological information, including chromosome structure, GC content, and protein coexpression pattern was analyzed using multilayered, circular visualization and tabular visualization. Details of data analysis and updates are available in the Chinese Chromosome-Centric Human Proteome Database (http://proteomeview.hupo.org.cn/chromosome/)