1
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Chen S, Wang X, Yang N, Song Y, Cheng H, Sun Y. p53 exerts anticancer effects by regulating enhancer formation and activity. J Biomed Res 2024; 38:334-347. [PMID: 38808570 PMCID: PMC11300520 DOI: 10.7555/jbr.37.20230206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 02/08/2024] [Accepted: 03/05/2024] [Indexed: 05/30/2024] Open
Abstract
The abnormality of the p53 tumor suppressor is crucial in lung cancer development, because p53 regulates target gene promoters to combat cancer. Recent studies have shown extensive p53 binding to enhancer elements. However, whether p53 exerts a tumor suppressor role by shaping the enhancer landscape remains poorly understood. In the current study, we employed several functional genomics approaches to assess the enhancer activity at p53 binding sites throughout the genome based on our established TP53 knockout (KO) human bronchial epithelial cells (BEAS-2B). A total of 943 active regular enhancers and 370 super-enhancers (SEs) disappeared upon the deletion of p53, indicating that p53 modulates the activity of hundreds of enhancer elements. We found that one p53-dependent SE, located on chromosome 9 and designated as KLF4-SE, regulated the expression of the Krüppel-like factor 4 ( KLF4) gene. Furthermore, the deletion of p53 significantly decreased the KLF4-SE enhancer activity and the KLF4 expression, but increased colony formation ability in the nitrosamines 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone-induced cell transformation model. Subsequently, in TP53 KO cells, the overexpression of KLF4 partially reversed the increased clonogenic capacity caused by p53 deficiency. Consistently, KLF4 expression also decreased in lung cancer tissues and cell lines. It appeared that overexpression of KLF4 significantly suppressed the proliferation and migration of lung cancer cells. Collectively, our results suggest that the regulation of enhancer formation and activity by p53 is an integral component of the p53 tumor suppressor function. Therefore, our findings offer some novel insights into the regulation mechanism of p53 in lung oncogenesis and introduce a new strategy for screening therapeutic targets.
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Affiliation(s)
- Shuhan Chen
- Key Laboratory of Human Functional Genomics of Jiangsu Province, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Department of Cell Biology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Xuchun Wang
- Key Laboratory of Human Functional Genomics of Jiangsu Province, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Department of Cell Biology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Nan Yang
- Key Laboratory of Human Functional Genomics of Jiangsu Province, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yuechi Song
- Department of Cell Biology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - He Cheng
- Key Laboratory of Human Functional Genomics of Jiangsu Province, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Department of Cell Biology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
| | - Yujie Sun
- Key Laboratory of Human Functional Genomics of Jiangsu Province, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Department of Cell Biology, School of Basic Medical Sciences, Nanjing Medical University, Nanjing, Jiangsu 211166, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Personalized Cancer Medicine, Nanjing Medical University, Nanjing, Jiangsu 211166, China
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2
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Wang Y, Chen Y, Zhang Y, Wei W, Li Y, Zhang T, He F, Gao Y, Xu P. Multi-Protease Strategy Identifies Three PE2 Missing Proteins in Human Testis Tissue. J Proteome Res 2017; 16:4352-4363. [PMID: 28959888 DOI: 10.1021/acs.jproteome.7b00340] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Although 5 years of the missing proteins (MPs) study have been completed, searching for MPs remains one of the core missions of the Chromosome-Centric Human Proteome Project (C-HPP). Following the next-50-MPs challenge of the C-HPP, we have focused on the testis-enriched MPs by various strategies since 2015. On the basis of the theoretical analysis of MPs (2017-01, neXtProt) using multiprotease digestion, we found that nonconventional proteases (e.g. LysargiNase, GluC) could improve the peptide diversity and sequence coverage compared with Trypsin. Therefore, a multiprotease strategy was used for searching more MPs in the same human testis tissues separated by 10% SDS-PAGE, followed by high resolution LC-MS/MS system (Q Exactive HF). A total of 7838 proteins were identified. Among them, three PE2 MPs in neXtProt 2017-01 have been identified: beta-defensin 123 ( Q8N688 , chr 20q), cancer/testis antigen family 45 member A10 ( P0DMU9 , chr Xq), and Histone H2A-Bbd type 2/3 ( P0C5Z0 , chr Xq). However, because only one unique peptide of ≥9 AA was identified in beta-defensin 123 and Histone H2A-Bbd type 2/3, respectively, further analysis indicates that each falls under the exceptions clause of the HPP Guidelines v2.1. After a spectrum quality check, isobaric PTM and single amino acid variant (SAAV) filtering, and verification with a synthesized peptide, and based on overlapping peptides from different proteases, these three MPs should be considered as exemplary examples of MPs found by exceptional criteria. Other MPs were considered as candidates but need further validation. All MS data sets have been deposited to the ProteomeXchange with identifier PXD006465.
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Affiliation(s)
- Yihao Wang
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China.,Department of Pharmacology and Toxicology, Beijing Institute of Radiation Medicine , Beijing 100850, China
| | - Yang Chen
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Yao Zhang
- State Key Laboratory of Biocontrol and Guangdong Provincial Key Laboratory of Plant Resources, College of Ecology and Evolution, Sun Yat-Sen University , Guangzhou 510275, China
| | - Wei Wei
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Yanchang Li
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Tao Zhang
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Fuchu He
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China
| | - Yue Gao
- Department of Pharmacology and Toxicology, Beijing Institute of Radiation Medicine , Beijing 100850, China
| | - Ping Xu
- State Key Laboratory of Proteomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine , Beijing 102206, China.,Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education, School of Pharmaceutical Sciences, Wuhan University , Wuhan 430072, China.,Graduate School, Anhui Medical University , Hefei 230032, China.,Tianjin Baodi Hospital , Tianjin 301800, China
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3
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Lee BNR, Son YS, Lee D, Choi YJ, Kwon SM, Chang HK, Kim PH, Cho JY. Hedgehog-Interacting Protein (HIP) Regulates Apoptosis Evasion and Angiogenic Function of Late Endothelial Progenitor Cells. Sci Rep 2017; 7:12449. [PMID: 28963460 PMCID: PMC5622095 DOI: 10.1038/s41598-017-12571-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Accepted: 07/14/2017] [Indexed: 11/16/2022] Open
Abstract
Late endothelial progenitor cells (LEPCs) are derived from mononuclear cells (MNCs) and are thought to directly incorporate into blood vessels and differentiate into mature endothelial cells (ECs). Using transcriptome and proteome analysis, we identified distinctive LEPC profiles and found that Hedgehog-interacting protein (HIP) is strongly expressed in LEPCs. Inhibition of HIP by lentiviral knockdown activated canonical hedgehog signaling in LEPCs, while it activated non-canonical hedgehog signaling in ECs. In LEPCs, HIP knockdown induced much enhanced tube formation and resistance to apoptosis under oxidative stress conditions via canonical hedgehog signaling. Although HIP is strongly expressed in proliferating LEPCs, HIP expression is down-regulated during angiogenesis and under oxidative stress condition. Moreover, when LEPCs are treated with angiogenic triggers such as VEGF and FGF2, HIP expression is reduced. Our findings suggest that HIP blocks LEPC angiogenesis and regulate survival when there is no angiogenic stimulation. HIP inhibition in LEPCs enhanced tube formation and reduced apoptosis, resulting in improved angiogenesis.
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Affiliation(s)
- Bom Nae Rin Lee
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul, 151-742, Korea
| | - Yeon Sung Son
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul, 151-742, Korea
| | - Dabin Lee
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul, 151-742, Korea
| | - Young-Jin Choi
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul, 151-742, Korea
| | - Sang-Mo Kwon
- Laboratory for Vascular Medicine & Stem Cell Biology, Medical Research Institute, Department of Physiology, School of Medicine, Pusan National University, Yangsan, 626-870, Korea
| | - Hyun-Kyung Chang
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul, 151-742, Korea
| | - Pyung-Hwan Kim
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul, 151-742, Korea
- Department of Biomedical Laboratory Science, College of Medical Science, Konyang University, Daejeon, 35-365, Korea
| | - Je-Yoel Cho
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul, 151-742, Korea.
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4
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Audain E, Uszkoreit J, Sachsenberg T, Pfeuffer J, Liang X, Hermjakob H, Sanchez A, Eisenacher M, Reinert K, Tabb DL, Kohlbacher O, Perez-Riverol Y. In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics. J Proteomics 2017; 150:170-182. [DOI: 10.1016/j.jprot.2016.08.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 07/30/2016] [Accepted: 08/02/2016] [Indexed: 12/24/2022]
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5
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Kim MS, Zhong J, Pandey A. Common errors in mass spectrometry-based analysis of post-translational modifications. Proteomics 2016; 16:700-14. [PMID: 26667783 DOI: 10.1002/pmic.201500355] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2015] [Revised: 11/05/2015] [Accepted: 12/08/2015] [Indexed: 12/29/2022]
Abstract
Mass spectrometry (MS) is a powerful tool to analyze complex mixtures of proteins in a high-throughput fashion. Proteome analysis has already become a routine task in biomedical research with the emergence of proteomics core facilities in most research institutions. Post-translational modifications (PTMs) represent a mechanism by which complex biological processes are orchestrated dynamically at the systems level. MS is rapidly becoming popular to discover new modifications and novel sites of known PTMs, revolutionizing the current understanding of diverse signaling pathways and biological processes. However, MS-based analysis of PTMs has its own caveats and pitfalls that can lead to erroneous conclusions. Here, we review the most common errors in MS-based PTM analyses with the goal of adopting strategies that maximize correct interpretation in the context of biological questions that are being addressed. Finally, we provide suggestions that should help mass spectrometrists, bioinformaticians and biologists to perform and interpret MS-based PTM analyses more accurately.
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Affiliation(s)
- Min-Sik Kim
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jun Zhong
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akhilesh Pandey
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Departments of Biological Chemistry, Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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6
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Improving GENCODE reference gene annotation using a high-stringency proteogenomics workflow. Nat Commun 2016; 7:11778. [PMID: 27250503 PMCID: PMC4895710 DOI: 10.1038/ncomms11778] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2015] [Accepted: 04/28/2016] [Indexed: 12/16/2022] Open
Abstract
Complete annotation of the human genome is indispensable for medical research. The GENCODE consortium strives to provide this, augmenting computational and experimental evidence with manual annotation. The rapidly developing field of proteogenomics provides evidence for the translation of genes into proteins and can be used to discover and refine gene models. However, for both the proteomics and annotation groups, there is a lack of guidelines for integrating this data. Here we report a stringent workflow for the interpretation of proteogenomic data that could be used by the annotation community to interpret novel proteogenomic evidence. Based on reprocessing of three large-scale publicly available human data sets, we show that a conservative approach, using stringent filtering is required to generate valid identifications. Evidence has been found supporting 16 novel protein-coding genes being added to GENCODE. Despite this many peptide identifications in pseudogenes cannot be annotated due to the absence of orthogonal supporting evidence. Identifying and annotating functional elements in the human genome remains a challenging but important task. Here the authors propose a priority annotation score to rank identifications and suggest how proteogenomics evidence can be interpreted and what additional information substantiates protein-coding potential for annotation.
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7
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Locard-Paulet M, Pible O, Gonzalez de Peredo A, Alpha-Bazin B, Almunia C, Burlet-Schiltz O, Armengaud J. Clinical implications of recent advances in proteogenomics. Expert Rev Proteomics 2016; 13:185-99. [DOI: 10.1586/14789450.2016.1132169] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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8
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Zickmann F, Renard BY. MSProGene: integrative proteogenomics beyond six-frames and single nucleotide polymorphisms. Bioinformatics 2015; 31:i106-15. [PMID: 26072472 PMCID: PMC4765881 DOI: 10.1093/bioinformatics/btv236] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Summary: Ongoing advances in high-throughput technologies have facilitated accurate proteomic measurements and provide a wealth of information on genomic and transcript level. In proteogenomics, this multi-omics data is combined to analyze unannotated organisms and to allow more accurate sample-specific predictions. Existing analysis methods still mainly depend on six-frame translations or reference protein databases that are extended by transcriptomic information or known single nucleotide polymorphisms (SNPs). However, six-frames introduce an artificial sixfold increase of the target database and SNP integration requires a suitable database summarizing results from previous experiments. We overcome these limitations by introducing MSProGene, a new method for integrative proteogenomic analysis based on customized RNA-Seq driven transcript databases. MSProGene is independent from existing reference databases or annotated SNPs and avoids large six-frame translated databases by constructing sample-specific transcripts. In addition, it creates a network combining RNA-Seq and peptide information that is optimized by a maximum-flow algorithm. It thereby also allows resolving the ambiguity of shared peptides for protein inference. We applied MSProGene on three datasets and show that it facilitates a database-independent reliable yet accurate prediction on gene and protein level and additionally identifies novel genes. Availability and implementation: MSProGene is written in Java and Python. It is open source and available at http://sourceforge.net/projects/msprogene/. Contact:renardb@rki.de
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Affiliation(s)
- Franziska Zickmann
- Research Group Bioinformatics (NG4), Robert Koch Institute, 13353 Berlin, Germany
| | - Bernhard Y Renard
- Research Group Bioinformatics (NG4), Robert Koch Institute, 13353 Berlin, Germany
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9
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Kim YI, Lee J, Choi YJ, Seo J, Park J, Lee SY, Cho JY. Proteogenomic Study beyond Chromosome 9: New Insight into Expressed Variant Proteome and Transcriptome in Human Lung Adenocarcinoma Tissues. J Proteome Res 2015; 14:5007-16. [PMID: 26584007 DOI: 10.1021/acs.jproteome.5b00544] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
This is a report of a human proteome project (HPP) related to chromosome 9 (Chr 9). To reveal missing proteins and undiscovered features in proteogenomes, both LC-MS/MS analysis and next-generation RNA sequencing (RNA-seq)-based identification and characterization were conducted on five pairs of lung adenocarcinoma tumors and adjacent nontumor tissues. Before our previous Chromosome-Centric Human Proteome Project (C-HPP) special issue, there were 170 remaining missing proteins on Chr 9 (neXtProt 2013.09.26 rel.); 133 remain at present (neXtProt 2015.04.28 rel.). In the proteomics study, we found two missing protein candidates that require follow-up work and one unrevealed protein across all chromosomes. RNA-seq analysis detected RNA expression for four nonsynonymous (NS) single nucleotide polymorphisms (SNPs) (in CDH17, HIST1H1T, SAPCD2, and ZNF695) and three synonymous SNPs (in CDH17, CST1, and HNF1A) in all five tumor tissues but not in any of the adjacent normal tissues. By constructing a cancer patient sample-specific protein database based on individual RNA-seq data and by searching the proteomics data from the same sample, we identified four missense mutations in four genes (LTF, HDLBP, TF, and HBD). Two of these mutations were found in tumor samples but not in paired normal tissues. In summary, our proteogenomic study of human primary lung tumor tissues detected additional and revealed novel missense mutations and synonymous SNP signatures, some of which are specific to lung cancers. Data from mass spectrometry have been deposited in the ProteomeXchange with the identifier PXD002523.
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Affiliation(s)
- Yong-In Kim
- Department of Biochemistry, BK21 PLUS Program for Creative Veterinary Science Research and Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University , Seoul 08826, South Korea
| | - Jongan Lee
- Department of Laboratory Medicine & Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul 06351, South Korea
| | - Young-Jin Choi
- Department of Biochemistry, BK21 PLUS Program for Creative Veterinary Science Research and Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University , Seoul 08826, South Korea.,ProtAnBio , Seoul 08826, South Korea
| | - Jawon Seo
- Department of Biochemistry, BK21 PLUS Program for Creative Veterinary Science Research and Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University , Seoul 08826, South Korea
| | - Jisook Park
- Samsung Biomedical Research Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul 06351, South Korea
| | - Soo-Youn Lee
- Department of Laboratory Medicine & Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul 06351, South Korea.,Department of Clinical Pharmacology & Therapeutics, Samsung Medical Center, Sungkyunkwan University School of Medicine , Seoul 06351, South Korea
| | - Je-Yoel Cho
- Department of Biochemistry, BK21 PLUS Program for Creative Veterinary Science Research and Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University , Seoul 08826, South Korea
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10
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Hwang H, Park GW, Kim KH, Lee JY, Lee HK, Ji ES, Park SKR, Xu T, Yates JR, Kwon KH, Park YM, Lee HJ, Paik YK, Kim JY, Yoo JS. Chromosome-Based Proteomic Study for Identifying Novel Protein Variants from Human Hippocampal Tissue Using Customized neXtProt and GENCODE Databases. J Proteome Res 2015; 14:5028-37. [DOI: 10.1021/acs.jproteome.5b00472] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Heeyoun Hwang
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
| | - Gun Wook Park
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
- Graduate
School of Analytical Science and Technology, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Kwang Hoe Kim
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
- Graduate
School of Analytical Science and Technology, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Ju Yeon Lee
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
| | - Hyun Kyoung Lee
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
- Graduate
School of Analytical Science and Technology, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Eun Sun Ji
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
| | - Sung-Kyu Robin Park
- Department
of Chemical Physiology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Tao Xu
- Department
of Chemical Physiology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - John R. Yates
- Department
of Chemical Physiology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Kyung-Hoon Kwon
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
| | - Young Mok Park
- Center
for Cognition and Sociality, Institute for Basic Science, Daejeon 34047, Republic of Korea
| | - Hyoung-Joo Lee
- Yonsei
Proteome Research Center and Department of Integrated OMICS for Biomedical
Science, and Department of Biochemistry, College of Life Science and
Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Young-Ki Paik
- Yonsei
Proteome Research Center and Department of Integrated OMICS for Biomedical
Science, and Department of Biochemistry, College of Life Science and
Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
| | - Jin Young Kim
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
| | - Jong Shin Yoo
- Biomedical
Omics Group, Korea Basic Science Institute, Chungbuk 28119, Republic of Korea
- Graduate
School of Analytical Science and Technology, Chungnam National University, Daejeon 34134, Republic of Korea
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11
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Kitata RB, Dimayacyac-Esleta BRT, Choong WK, Tsai CF, Lin TD, Tsou CC, Weng SH, Chen YJ, Yang PC, Arco SD, Nesvizhskii AI, Sung TY, Chen YJ. Mining Missing Membrane Proteins by High-pH Reverse-Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry. J Proteome Res 2015. [PMID: 26202522 DOI: 10.1021/acs.jproteome.5b00477] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Despite significant efforts in the past decade toward complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still "missing proteins". Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using nonsmall cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip prefractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue was incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet, and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring using synthetic peptides, we provided additional evidence of eight missing proteins including seven with transmembrane helix domains. This study demonstrates that mining missing proteins focused on cancer membrane subproteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224.
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Affiliation(s)
- Reta Birhanu Kitata
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Department of Chemistry, National Tsing Hua University , 101, Sec 2, Kuang-Fu Road, Hsinchu 30013, Taiwan.,Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica , No. 1, Roosevelt Road, Sec. 4, Taipei 10617, Taiwan
| | - Baby Rorielyn T Dimayacyac-Esleta
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Institute of Chemistry, University of the Philippines , Diliman Quezon City, Philippines
| | - Wai-Kok Choong
- Institute of Information Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan
| | - Chia-Feng Tsai
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan
| | - Tai-Du Lin
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Department of Biochemical Sciences, National Taiwan University , 1 Roosevelt Road, Sec. 4, Taipei 106, Taiwan
| | - Chih-Chiang Tsou
- Department of Computational Medicine and Bioinformatics and Department of Pathology, University of Michigan Medical School , 1301 Catherine, Ann Arbor, Michigan 48109, United States
| | - Shao-Hsing Weng
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Genome and Systems Biology Degree Program, National Taiwan University , 1, Roosevelt Road, Section 4, Taipei 10617, Taiwan
| | - Yi-Ju Chen
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan
| | - Pan-Chyr Yang
- Department of Internal Medicine, National Taiwan University Hospital , 1 Jen-Ai Road, Section 1, Taipei 10051, Taiwan.,National Taiwan University College of Medicine , No. 1, Section 1, Ren'ai Road, Taipei 100, Taiwan.,Institute of Biomedical Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan
| | - Susan D Arco
- Institute of Chemistry, University of the Philippines , Diliman Quezon City, Philippines
| | - Alexey I Nesvizhskii
- Department of Computational Medicine and Bioinformatics and Department of Pathology, University of Michigan Medical School , 1301 Catherine, Ann Arbor, Michigan 48109, United States
| | - Ting-Yi Sung
- Institute of Information Science, Academia Sinica , 128 Academia Road, Section 2, Taipei 115, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica , No. 128, Academia Road Sec. 2, Taipei 115, Taiwan.,Department of Chemistry, National Tsing Hua University , 101, Sec 2, Kuang-Fu Road, Hsinchu 30013, Taiwan.,Molecular Science and Technology Program, Taiwan International Graduate Program, Academia Sinica , No. 1, Roosevelt Road, Sec. 4, Taipei 10617, Taiwan
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12
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Chen Y, Li Y, Zhong J, Zhang J, Chen Z, Yang L, Cao X, He QY, Zhang G, Wang T. Identification of Missing Proteins Defined by Chromosome-Centric Proteome Project in the Cytoplasmic Detergent-Insoluble Proteins. J Proteome Res 2015; 14:3693-709. [DOI: 10.1021/pr501103r] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Yang Chen
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Yaxing Li
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Jiayong Zhong
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Jing Zhang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Zhipeng Chen
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Lijuan Yang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Xin Cao
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Qing-Yu He
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Gong Zhang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
| | - Tong Wang
- Key Laboratory of Functional
Protein Research of Guangdong Higher Education Institutes, Institute
of Life and Health Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China
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Foster MW, Thompson JW, Ledford JG, Dubois LG, Hollingsworth JW, Francisco D, Tanyaratsrisakul S, Voelker DR, Kraft M, Moseley MA, Foster WM. Identification and Quantitation of Coding Variants and Isoforms of Pulmonary Surfactant Protein A. J Proteome Res 2014; 13:3722-32. [PMID: 25025725 PMCID: PMC4123939 DOI: 10.1021/pr500307f] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Pulmonary surfactant protein A (SP-A), a heterooligomer of SP-A1 and SP-A2, is an important regulator of innate immunity of the lung. Nonsynonymous single nucleotide variants of SP-A have been linked to respiratory diseases, but the expressed repertoire of SP-A protein in human airway has not been investigated. Here, we used parallel trypsin and Glu-C digestion, followed by LC-MS/MS, to obtain sequence coverage of common SP-A variants and isoform-determining peptides. We further developed a SDS-PAGE-based, multiple reaction monitoring (GeLC-MRM) assay for enrichment and targeted quantitation of total SP-A, the SP-A2 isoform, and the Gln223 and Lys223 variants of SP-A, from as little as one milliliter of bronchoalveolar lavage fluid. This assay identified individuals with the three genotypes at the 223 position of SP-A2: homozygous major (Gln223/Gln223), homozygous minor (Lys223/Lys223), or heterozygous (Gln223/Lys223). More generally, our studies demonstrate the challenges inherent in distinguishing highly homologous, copurifying protein isoforms by MS and show the applicability of MRM mass spectrometry for identification and quantitation of nonsynonymous single nucleotide variants and other proteoforms in airway lining fluid.
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Affiliation(s)
| | | | | | | | | | | | | | - Dennis R Voelker
- ‡Department of Medicine, National Jewish Health, Denver, Colorado 80206, United States
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