1
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Hanna R, Rozenberg A, Saied L, Ben-Yosef D, Lavy T, Kleifeld O. In-Depth Characterization of Apoptosis N-terminome Reveals a Link Between Caspase-3 Cleavage and Post-Translational N-terminal Acetylation. Mol Cell Proteomics 2023:100584. [PMID: 37236440 PMCID: PMC10362333 DOI: 10.1016/j.mcpro.2023.100584] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/16/2023] [Accepted: 05/22/2023] [Indexed: 05/28/2023] Open
Abstract
The N-termini of proteins contain information about their biochemical properties and functions. These N-termini can be processed by proteases, and can undergo other co- or post-translational modifications. We have developed LATE (LysN Amino Terminal Enrichment), a method that uses selective chemical derivatization of α-amines to isolate the N-terminal peptides, in order to improve N-terminome identification in conjunction with other enrichment strategies. We applied LATE alongside another N-terminomic method to study caspase-3 mediated proteolysis both in vitro and during apoptosis in cells. This has enabled us to identify many unreported caspase-3 cleavages, some of which cannot be identified by other methods. Moreover, we have found direct evidence that neo-N-termini generated by caspase-3 cleavage can be further modified by Nt-acetylation. Some of these neo-Nt-acetylation events occur in the early phase of the apoptotic process and may have a role in translation inhibition. This has provided a comprehensive overview of the caspase-3 degradome and has uncovered previously unrecognized crosstalk between post-translational Nt-acetylation and caspase proteolytic pathways.
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Affiliation(s)
- Rawad Hanna
- Faculty of Biology, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Andrey Rozenberg
- Faculty of Biology, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Layla Saied
- Faculty of Biology, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Daniel Ben-Yosef
- Faculty of Biology, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Tali Lavy
- Faculty of Biology, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Oded Kleifeld
- Faculty of Biology, Technion-Israel Institute of Technology, Technion City, Haifa 3200003, Israel.
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2
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Zong Y, Wang Y, Yang Y, Zhao D, Wang X, Shen C, Qiao L. DeepFLR facilitates false localization rate control in phosphoproteomics. Nat Commun 2023; 14:2269. [PMID: 37080984 PMCID: PMC10119288 DOI: 10.1038/s41467-023-38035-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 04/06/2023] [Indexed: 04/22/2023] Open
Abstract
Protein phosphorylation is a post-translational modification crucial for many cellular processes and protein functions. Accurate identification and quantification of protein phosphosites at the proteome-wide level are challenging, not least because efficient tools for protein phosphosite false localization rate (FLR) control are lacking. Here, we propose DeepFLR, a deep learning-based framework for controlling the FLR in phosphoproteomics. DeepFLR includes a phosphopeptide tandem mass spectrum (MS/MS) prediction module based on deep learning and an FLR assessment module based on a target-decoy approach. DeepFLR improves the accuracy of phosphopeptide MS/MS prediction compared to existing tools. Furthermore, DeepFLR estimates FLR accurately for both synthetic and biological datasets, and localizes more phosphosites than probability-based methods. DeepFLR is compatible with data from different organisms, instruments types, and both data-dependent and data-independent acquisition approaches, thus enabling FLR estimation for a broad range of phosphoproteomics experiments.
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Affiliation(s)
- Yu Zong
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | - Yuxin Wang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
- Department of Computer Science, and Institute of Modern Languages and Linguistics, Fudan University, Shanghai, China
| | - Yi Yang
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | - Dan Zhao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China
| | | | | | - Liang Qiao
- Department of Chemistry, and Shanghai Stomatological Hospital, Fudan University, Shanghai, China.
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3
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Sun B, Liu Z, Liu J, Zhao S, Wang L, Wang F. The utility of proteases in proteomics, from sequence profiling to structure and function analysis. Proteomics 2023; 23:e2200132. [PMID: 36382392 DOI: 10.1002/pmic.202200132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 11/08/2022] [Accepted: 11/08/2022] [Indexed: 11/18/2022]
Abstract
In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.
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Affiliation(s)
- Binwen Sun
- Engineering Research Center for New Materials and Precision Treatment Technology of Malignant Tumors Therapy, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 463 Zhongshan Road, Dalian, 116023, China
- Engineering Technology Research Center for Translational Medicine, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Zheyi Liu
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 463 Zhongshan Road, Dalian, 116023, China
| | - Jin Liu
- Engineering Research Center for New Materials and Precision Treatment Technology of Malignant Tumors Therapy, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
- Engineering Technology Research Center for Translational Medicine, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Shan Zhao
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 463 Zhongshan Road, Dalian, 116023, China
| | - Liming Wang
- Engineering Research Center for New Materials and Precision Treatment Technology of Malignant Tumors Therapy, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
- Engineering Technology Research Center for Translational Medicine, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
- Division of Hepatobiliary and Pancreatic Surgery, Department of General Surgery, Second Affiliated Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Fangjun Wang
- CAS Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 463 Zhongshan Road, Dalian, 116023, China
- University of Chinese Academy of Sciences, 19 Yuquan Road, Beijing, 100049, China
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4
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Mirror cutting-assisted orthogonal digestion enabling large-scale and accurate protein complex characterization. Se Pu 2022; 40:224-233. [PMID: 35243832 PMCID: PMC9404107 DOI: 10.3724/sp.j.1123.2021.06010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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5
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Urban J. A review on recent trends in the phosphoproteomics workflow. From sample preparation to data analysis. Anal Chim Acta 2022; 1199:338857. [DOI: 10.1016/j.aca.2021.338857] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 07/14/2021] [Accepted: 07/15/2021] [Indexed: 12/12/2022]
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6
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基于精氨酸酶切的蛋白质C端肽段富集方法的优化及评估. Se Pu 2022; 40:17-27. [PMID: 34985212 PMCID: PMC9404053 DOI: 10.3724/sp.j.1123.2021.03030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
基于聚合物的蛋白质C端反向富集策略是用于研究蛋白质C端最为广泛的策略之一。目前,基于胰蛋白酶(trypsin)切割精氨酸残基C端(ArgC型酶切)的蛋白C端组学方法对蛋白质C端的鉴定深度仍有待提高。为解决这一问题,该研究对此方法进行了优化和评估:建立了基于“V型”过滤装置的“一锅法”富集流程,避免了副反应的干扰,缩短了样本的制备时间;优化了蛋白水平乙酰化反应条件,最大限度地降低了丝氨酸、苏氨酸、酪氨酸残基上的副反应,提高了肽段鉴定的可信性;优化了基于固相萃取枪头膜片过滤柱(StageTip柱)的样品分离过程,使C端肽段的鉴定深度增加至原来的4倍。通过以上优化,按照肽段水平错误发现率(FDR)<0.01、离子分数(ion score)≥20,且C端带有乙醇胺修饰的数据筛选标准,从人HEK 293T细胞中共鉴定出696个蛋白质C端。若仅要求肽段水平FDR<0.01,鉴定数目进一步增加到933个,这是基于聚合物富集策略的蛋白质C端组学方法所得的最大数据集之一。探索了胰蛋白酶镜像酶(LysargiNase)切割精氨酸残基N端(ArgN型酶切)与不同肽段N端衍生化修饰组合对蛋白质C端鉴定数目和种类的影响,“LysargiNase酶切+肽段N端乙酰化”新策略在原有“胰蛋白酶酶切+肽段N端二甲基化”策略的基础上将鉴定蛋白质C端的种类提升了47%。综上,该研究通过对基于Arg型酶切的蛋白C端组学方法的优化,提升了C端肽段的鉴定深度,扩大了C端肽段鉴定的覆盖范围。该方法将有望成为系统性表征蛋白质C端的有力工具。
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7
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Chang CH, Chang HY, Rappsilber J, Ishihama Y. Isolation of Acetylated and Unmodified Protein N-Terminal Peptides by Strong Cation Exchange Chromatographic Separation of TrypN-Digested Peptides. Mol Cell Proteomics 2020; 20:100003. [PMID: 33517145 PMCID: PMC7857546 DOI: 10.1074/mcp.tir120.002148] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 10/22/2020] [Accepted: 11/02/2020] [Indexed: 12/25/2022] Open
Abstract
We developed a simple and rapid method to enrich protein N-terminal peptides, in which the protease TrypN is first employed to generate protein N-terminal peptides without Lys or Arg and internal peptides with two positive charges at their N termini, and then, the N-terminal peptides with or without N-acetylation are separated from the internal peptides by strong cation exchange chromatography according to a retention model based on the charge/orientation of peptides. This approach was applied to 20 μg of human HEK293T cell lysate proteins to profile the N-terminal proteome. On average, 1550 acetylated and 200 unmodified protein N-terminal peptides were successfully identified in a single LC/MS/MS run with less than 3% contamination with internal peptides, even when we accepted only canonical protein N termini registered in the Swiss-Prot database. Because this method involves only two steps, protein digestion and chromatographic separation, without the need for tedious chemical reactions, it should be useful for comprehensive profiling of protein N termini, including proteoforms with neo-N termini.
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Affiliation(s)
- Chih-Hsiang Chang
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan
| | - Hsin-Yi Chang
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan; Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei, Taiwan
| | - Juri Rappsilber
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan; Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, Berlin, Germany; Wellcome Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Yasushi Ishihama
- Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan; Laboratory of Clinical and Analytical Chemistry, National Institute of Biomedical Innovation, Health and Nutrition, Ibaraki, Osaka, Japan.
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8
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Mei S, Ayala R, Ramarathinam SH, Illing PT, Faridi P, Song J, Purcell AW, Croft NP. Immunopeptidomic Analysis Reveals That Deamidated HLA-bound Peptides Arise Predominantly from Deglycosylated Precursors. Mol Cell Proteomics 2020; 19:1236-1247. [PMID: 32357974 PMCID: PMC7338083 DOI: 10.1074/mcp.ra119.001846] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 04/20/2020] [Indexed: 12/20/2022] Open
Abstract
The presentation of post-translationally modified (PTM) peptides by cell surface HLA molecules has the potential to increase the diversity of targets for surveilling T cells. Although immunopeptidomics studies routinely identify thousands of HLA-bound peptides from cell lines and tissue samples, in-depth analyses of the proportion and nature of peptides bearing one or more PTMs remains challenging. Here we have analyzed HLA-bound peptides from a variety of allotypes and assessed the distribution of mass spectrometry-detected PTMs, finding deamidation of asparagine or glutamine to be highly prevalent. Given that asparagine deamidation may arise either spontaneously or through enzymatic reaction, we assessed allele-specific and global motifs flanking the modified residues. Notably, we found that the N-linked glycosylation motif NX(S/T) was highly abundant across asparagine-deamidated HLA-bound peptides. This finding, demonstrated previously for a handful of deamidated T cell epitopes, implicates a more global role for the retrograde transport of nascently N-glycosylated polypeptides from the ER and their subsequent degradation within the cytosol to form HLA-ligand precursors. Chemical inhibition of Peptide:N-Glycanase (PNGase), the endoglycosidase responsible for the removal of glycans from misfolded and retrotranslocated glycoproteins, greatly reduced presentation of this subset of deamidated HLA-bound peptides. Importantly, there was no impact of PNGase inhibition on peptides not containing a consensus NX(S/T) motif. This indicates that a large proportion of HLA-I bound asparagine deamidated peptides are generated from formerly glycosylated proteins that have undergone deglycosylation via the ER-associated protein degradation (ERAD) pathway. The information herein will help train deamidation prediction models for HLA-peptide repertoires and aid in the design of novel T cell therapeutic targets derived from glycoprotein antigens.
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Affiliation(s)
- Shutao Mei
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia
| | - Rochelle Ayala
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia
| | - Sri H Ramarathinam
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia
| | - Patricia T Illing
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia
| | - Pouya Faridi
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia
| | - Jiangning Song
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia
| | - Anthony W Purcell
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia.
| | - Nathan P Croft
- Biomedicine Discovery Institute and Department of Biochemistry & Molecular Biology, Monash University, Melbourne, VIC, Australia.
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9
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Xu F, Yu L, Peng X, Zhang J, Li S, Liu S, Yin Y, An Z, Wang F, Fu Y, Xu P. Unambiguous Phosphosite Localization through the Combination of Trypsin and LysargiNase Mirror Spectra in a Large-Scale Phosphoproteome Study. J Proteome Res 2020; 19:2185-2194. [PMID: 32388983 DOI: 10.1021/acs.jproteome.9b00562] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Understanding of the kinase-guided signaling pathways requires the identification and analysis of phosphosites. Mass spectrometry (MS)-based phosphoproteomics is a rapid and highly sensitive approach for high-throughput identification of phosphosites. However, phosphosite determination from MS data with a single protease is more likely to be ambiguous, regardless of the strategy used for phosphopeptide detection. Here, we explored the application of LysargiNase, which was recently reported to mirror trypsin in specificity to cleave arginine and lysine residues exclusively at the N-terminal side. We found that the combination of trypsin and LysargiNase mirror spectra resulted in higher ion coverage in MS2 spectra. The median ion coverage values of b ions in tryptic spectra, LysargiNase spectra, and combined spectra are 8.3, 20.5, and 25.0%, respectively. As for the median ion coverage of y ions, these values are 27.8, 10.0, and 32.3%. Higher ion coverage was helpful to pinpoint the precise phosphosites. Compared to trypsin alone, the combined use of trypsin and LysargiNase mirror spectra enabled 67.1% of mirror spectra with unreliable scores (confidence score <0.75) to become reliable (confidence score ≥ 0.75). Meanwhile, all of the mirror peptide-spectrum matches (PSMs) with multiple potential phosphosites from trypsin and LysargiNase digests could be assigned one precise phosphosite after applying the combination strategy. Besides, the combination strategy could identify more novel phosphosites than the union strategy did. We synthesized three phosphopeptides corresponding to the three novel phosphosites and validated the reliability of the identification. Taken together, our data demonstrated the distinctive potential of the combination strategy presented here for unambiguous phosphosite localization (Project accession PXD011178).
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Affiliation(s)
- Feng Xu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Li Yu
- National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100864, China.,School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xuehui Peng
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Lifeomics, Beijing 102206, China.,Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education, School of Pharmaceutical Sciences, School of Medicine, Wuhan University, Wuhan430072, China
| | - Junling Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Suzhen Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Lifeomics, Beijing 102206, China.,Anhui Medical University, Hefei 230032, China
| | - Shu Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yanan Yin
- Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education, School of Pharmaceutical Sciences, School of Medicine, Wuhan University, Wuhan430072, China
| | - Zhiwu An
- National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100864, China.,School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fuqiang Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yan Fu
- National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100864, China.,School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ping Xu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing Institute of Lifeomics, Beijing 102206, China.,Anhui Medical University, Hefei 230032, China.,Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education, School of Pharmaceutical Sciences, School of Medicine, Wuhan University, Wuhan430072, China
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10
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Wilson JP, Ipsaro JJ, Del Giudice SN, Turna NS, Gauss CM, Dusenbury KH, Marquart K, Rivera KD, Pappin DJ. Tryp-N: A Thermostable Protease for the Production of N-terminal Argininyl and Lysinyl Peptides. J Proteome Res 2020; 19:1459-1469. [PMID: 32141294 DOI: 10.1021/acs.jproteome.9b00713] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Bottom-up proteomics is a mainstay in protein identification and analysis. These studies typically employ proteolytic treatment of biological samples to generate suitably sized peptides for tandem mass spectrometric (MS) analysis. In MS, fragmentation of peptides is largely driven by charge localization. Consequently, peptides with basic centers exclusively on their N-termini produce mainly b-ions. Thus, it was long ago realized that proteases that yield such peptides would be valuable proteomic tools for achieving simplified peptide fragmentation patterns and peptide assignment. Work by several groups has identified such proteases, however, structural analysis of these suggested that enzymatic optimization was possible. We therefore endeavored to find enzymes that could provide enhanced activity and versatility while maintaining specificity. Using these previously described proteases as informatic search templates, we discovered and then characterized a thermophilic metalloprotease with N-terminal specificity for arginine and lysine. This enzyme, dubbed Tryp-N, affords many advantages including improved thermostability, solvent and detergent tolerance, and rapid digestion time.
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Affiliation(s)
- John P Wilson
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Jonathan J Ipsaro
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Samantha N Del Giudice
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Nikita Saha Turna
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Carla M Gauss
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Katharine H Dusenbury
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Krisann Marquart
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Keith D Rivera
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
| | - Darryl J Pappin
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, United States
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11
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Li Q, Zhang Y, Huang J, Wu Z, Tang L, Huang L, Zhang X. Basic Strong Cation Exchange Chromatography, BaSCX, a Highly Efficient Approach for C-Terminomic Studies Using LysargiNase Digestion. Anal Chem 2020; 92:4742-4748. [DOI: 10.1021/acs.analchem.9b05280] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Qingqing Li
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Yang Zhang
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Jingnan Huang
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Zhen Wu
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Langlang Tang
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Lin Huang
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xumin Zhang
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, Shanghai 200438, China
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12
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Xiao W, Zhang J, Wang Y, Liu Z, Wang F, Sun J, Chang L, Xia Z, Li Y, Xu P. Ac-LysargiNase Complements Trypsin for the Identification of Ubiquitinated Sites. Anal Chem 2019; 91:15890-15898. [DOI: 10.1021/acs.analchem.9b04340] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Weidi Xiao
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
| | - Junling Zhang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
| | - Yihao Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
| | - Zijuan Liu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
- School of Basic Medical Science, Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education, School of Pharmaceutical Sciences, Wuhan University, Wuhan 430071, P. R. China
| | - Fuqiang Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
| | - Jinshuai Sun
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
| | - Lei Chang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
| | - Zongping Xia
- Translational Medicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450018, P. R. China
| | - Yanchang Li
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
| | - Ping Xu
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Research Unit of Proteomics & Research and Development of New Drug, Institute of Lifeomics, Beijing 102206, P. R. China
- School of Basic Medical Science, Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education, School of Pharmaceutical Sciences, Wuhan University, Wuhan 430071, P. R. China
- Guizhou University School of Medicine, Guiyang 550025, P.R. China
- Second Clinical Medicine Collage, Guangzhou University Chinese Medicine, Guangzhou 510006, P. R. China
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13
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Hu H, Zhao W, Zhu M, Zhao L, Zhai L, Xu JY, Liu P, Tan M. LysargiNase and Chemical Derivatization Based Strategy for Facilitating In-Depth Profiling of C-Terminome. Anal Chem 2019; 91:14522-14529. [PMID: 31634432 DOI: 10.1021/acs.analchem.9b03543] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Global identification of protein C-termini is highly challenging due to their low abundance in conventional shotgun proteomics. Several enrichment strategies have been developed to facilitate the detection of C-terminal peptides. One major issue of previous approaches is the limited C-terminome coverage. Herein, we integrated LysargiNase digestion, chemical acetylation on neo-N-terminus, and a-ion-aided peptide matching into poly(allylamine)-based C-terminomics (termed as LAACTer). In this strategy, we leveraged LysargiNase, a protease with cleavage specificity N-terminal to Lys and Arg residues, to cover previously unidentifiable C-terminome and employed chemical acetylation and a-ion-aided peptide matching to efficiently boost peptide identifications. Triplicates of LAACTer identified a total of 834 C-termini from proteome of 293T cell, which expanded the coverage by 164% (643 more unique C-termini) compared with the parallel experiments using the original workflow. Compared with the largest human C-terminome data sets (containing 800-900 C-termini), LAACTer not only achieved comparable profiling depth but also yielded 465 previously unidentified C-termini. In a SILAC (stable isotope labeling with amino acids in cell culture)-based quantitative study for identification of GluC-cleaved products, LAACTer quantified 300% more C-terminal peptides than the original workflow. Using LAACTer and the original workflow, we performed global analysis for the C-terminal sequences of 293T cell. The original and processed C-termini displayed distinct sequence patterns, implying the "C-end rules" that regulates protein stability could be more complex than just amino acid motifs. In conclusion, we reason LAACTer could be a powerful proteomic tool for in-depth C-terminomics and would benefit better functional understanding of protein C-termini.
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Affiliation(s)
- Hao Hu
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China
| | - Wensi Zhao
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China.,University of Chinese Academy of Sciences , Beijing 100049 , China
| | - Mengdi Zhu
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China.,University of Chinese Academy of Sciences , Beijing 100049 , China
| | - Lei Zhao
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China
| | - Linhui Zhai
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China
| | - Jun-Yu Xu
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China
| | - Ping Liu
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China
| | - Minjia Tan
- State Key Laboratory of Drug Research , Shanghai Institute of Materia Medica, Chinese Academy of Sciences , 555 Zuchongzhi Road , Shanghai , 201203 , China.,University of Chinese Academy of Sciences , Beijing 100049 , China
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14
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Zhou M, Duong DM, Johnson ECB, Dai J, Lah JJ, Levey AI, Seyfried NT. Mass Spectrometry-Based Quantification of Tau in Human Cerebrospinal Fluid Using a Complementary Tryptic Peptide Standard. J Proteome Res 2019; 18:2422-2432. [PMID: 30983353 DOI: 10.1021/acs.jproteome.8b00920] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Here, we report a method for the generation of complementary tryptic (CompTryp) isotope-labeled peptide standards for the relative and absolute quantification of proteins by mass spectrometry (MS). These standards can be digested in parallel with either trypsin (Tryp-C) or trypsin-N (Tryp-N), to generate peptides that significantly overlap in primary sequence having C- and N-terminal arginine and lysine residues, respectively. As a proof of concept, an isotope-labeled CompTryp standard was synthesized for Tau, a well-established biomarker in Alzheimer's disease (AD), which included both N- and C-terminal heavy isotope-labeled (15N and 13C) arginine residues and flanking amino acid sequences to monitor proteolytic digestion. Despite having the exact same mass, the N- and C-terminal heavy Tau peptides are distinguishable by retention time and MS/MS fragmentation profiles. The isotope-labeled Tau CompTryp standard was added to human cerebrospinal fluid (CSF) followed by parallel digestion with Tryp-N and Tryp-C. The native and isotope-labeled peptide pairs were quantified by parallel reaction monitoring (PRM) in a single assay. Notably, both tryptic peptides were effective at quantifying Tau in human CSF, and both showed a significant difference in CSF Tau levels between AD and controls. Treating these CompTryp Tau peptide measurements as independent replicates also improved the coefficient of variation and correlation with Tau immunoassays. More broadly, we propose that CompTryp standards can be generated for any protein of interest, providing an efficient method to improve the robustness and reproducibility for MS analysis of clinical and research samples.
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Affiliation(s)
| | | | | | - Jingting Dai
- Department of Neurology, Second Xiangya Hospital , Central South University , Changsha , Hunan 410078 , China
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15
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Yang H, Li YC, Zhao MZ, Wu FL, Wang X, Xiao WD, Wang YH, Zhang JL, Wang FQ, Xu F, Zeng WF, Overall CM, He SM, Chi H, Xu P. Precision De Novo Peptide Sequencing Using Mirror Proteases of Ac-LysargiNase and Trypsin for Large-scale Proteomics. Mol Cell Proteomics 2019; 18:773-785. [PMID: 30622160 PMCID: PMC6442358 DOI: 10.1074/mcp.tir118.000918] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2018] [Revised: 11/20/2018] [Indexed: 11/06/2022] Open
Abstract
De novo peptide sequencing for large-scale proteomics remains challenging because of the lack of full coverage of ion series in tandem mass spectra. We developed a mirror protease of trypsin, acetylated LysargiNase (Ac-LysargiNase), with superior activity and stability. The mirror spectrum pairs derived from the Ac-LysargiNase and trypsin treated samples can generate full b and y ion series, which provide mutual complementarity of each other, and allow us to develop a novel algorithm, pNovoM, for de novo sequencing. Using pNovoM to sequence peptides of purified proteins, the accuracy of the sequence was close to 100%. More importantly, from a large-scale yeast proteome sample digested with trypsin and Ac-LysargiNase individually, 48% of all tandem mass spectra formed mirror spectrum pairs, 97% of which contained full coverage of ion series, resulting in precision de novo sequencing of full-length peptides by pNovoM. This enabled pNovoM to successfully sequence 21,249 peptides from 3,753 proteins and interpreted 44-152% more spectra than pNovo+ and PEAKS at a 5% FDR at the spectrum level. Moreover, the mirror protease strategy had an obvious advantage in sequencing long peptides. We believe that the combination of mirror protease strategy and pNovoM will be an effective approach for precision de novo sequencing on both single proteins and proteome samples.
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Affiliation(s)
- Hao Yang
- From the ‡Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS; University of Chinese Academy of Sciences; Institute of Computing Technology, CAS, Beijing 100190, China
| | - Yan-Chang Li
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Ming-Zhi Zhao
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Fei-Lin Wu
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Xi Wang
- From the ‡Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS; University of Chinese Academy of Sciences; Institute of Computing Technology, CAS, Beijing 100190, China
| | - Wei-Di Xiao
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Yi-Hao Wang
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Jun-Ling Zhang
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Fu-Qiang Wang
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Feng Xu
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China
| | - Wen-Feng Zeng
- From the ‡Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS; University of Chinese Academy of Sciences; Institute of Computing Technology, CAS, Beijing 100190, China
| | - Christopher M Overall
- ‖Centre for Blood Research, University of British Columbia, Vancouver, British Columbia, Canada
| | - Si-Min He
- From the ‡Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS; University of Chinese Academy of Sciences; Institute of Computing Technology, CAS, Beijing 100190, China;.
| | - Hao Chi
- From the ‡Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS; University of Chinese Academy of Sciences; Institute of Computing Technology, CAS, Beijing 100190, China;.
| | - Ping Xu
- §State Key Laboratory of Proteomics; Beijing Proteome Research Center; National Center for Protein Sciences Beijing; Beijing Institute of Lifeomics, Beijing 102206, China;; ¶Key Laboratory of Combinatorial Biosynthesis and Drug Discovery of Ministry of Education Wuhan University, Wuhan University School of Pharmaceutical Sciences, Wuhan 430071, China;; College of Life Sciences, Hebei University, Baoding 071002, China.
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16
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Schräder CU, Moore S, Goodarzi AA, Schriemer DC. Lysine Propionylation To Boost Sequence Coverage and Enable a “Silent SILAC” Strategy for Relative Protein Quantification. Anal Chem 2018; 90:9077-9084. [DOI: 10.1021/acs.analchem.8b01403] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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17
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Andjelković U, Josić D. Mass spectrometry based proteomics as foodomics tool in research and assurance of food quality and safety. Trends Food Sci Technol 2018. [DOI: 10.1016/j.tifs.2018.04.008] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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18
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Affiliation(s)
- Nicholas
M. Riley
- Department
of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Genome
Center of Wisconsin, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Joshua J. Coon
- Department
of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Genome
Center of Wisconsin, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department
of Biomolecular Chemistry, University of
Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Morgridge
Institute for Research, Madison, Wisconsin 53715, United States
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19
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Vlastaridis P, Kyriakidou P, Chaliotis A, Van de Peer Y, Oliver SG, Amoutzias GD. Estimating the total number of phosphoproteins and phosphorylation sites in eukaryotic proteomes. Gigascience 2017; 6:1-11. [PMID: 28327990 PMCID: PMC5466708 DOI: 10.1093/gigascience/giw015] [Citation(s) in RCA: 116] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Accepted: 12/20/2016] [Indexed: 12/03/2022] Open
Abstract
Background Phosphorylation is the most frequent post-translational modification made to proteins and may regulate protein activity as either a molecular digital switch or a rheostat. Despite the cornucopia of high-throughput (HTP) phosphoproteomic data in the last decade, it remains unclear how many proteins are phosphorylated and how many phosphorylation sites (p-sites) can exist in total within a eukaryotic proteome. We present the first reliable estimates of the total number of phosphoproteins and p-sites for four eukaryotes (human, mouse, Arabidopsis, and yeast). Results In all, 187 HTP phosphoproteomic datasets were filtered, compiled, and studied along with two low-throughput (LTP) compendia. Estimates of the number of phosphoproteins and p-sites were inferred by two methods: Capture-Recapture, and fitting the saturation curve of cumulative redundant vs. cumulative non-redundant phosphoproteins/p-sites. Estimates were also adjusted for different levels of noise within the individual datasets and other confounding factors. We estimate that in total, 13 000, 11 000, and 3000 phosphoproteins and 230 000, 156 000, and 40 000 p-sites exist in human, mouse, and yeast, respectively, whereas estimates for Arabidopsis were not as reliable. Conclusions Most of the phosphoproteins have been discovered for human, mouse, and yeast, while the dataset for Arabidopsis is still far from complete. The datasets for p-sites are not as close to saturation as those for phosphoproteins. Integration of the LTP data suggests that current HTP phosphoproteomics appears to be capable of capturing 70 % to 95 % of total phosphoproteins, but only 40 % to 60 % of total p-sites.
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Affiliation(s)
- Panayotis Vlastaridis
- Bioinformatics Laboratory, Department of Biochemistry and Biotechnology, University of Thessaly, Larisa, 41500, Greece
| | - Pelagia Kyriakidou
- Bioinformatics Laboratory, Department of Biochemistry and Biotechnology, University of Thessaly, Larisa, 41500, Greece
| | - Anargyros Chaliotis
- Bioinformatics Laboratory, Department of Biochemistry and Biotechnology, University of Thessaly, Larisa, 41500, Greece
| | - Yves Van de Peer
- Department of Plant Systems Biology, VIB and Department of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Ghent, Belgium.,Bioinformatics Institute Ghent, Technologiepark 927, B-9052 Ghent, Belgium.,Department of Genetics, Genomics Research Institute, University of Pretoria, Pretoria 0028, South Africa
| | - Stephen G Oliver
- Cambridge Systems Biology Centre & Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
| | - Grigoris D Amoutzias
- Bioinformatics Laboratory, Department of Biochemistry and Biotechnology, University of Thessaly, Larisa, 41500, Greece
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