Literature DB >> 23669031

A fast workflow for identification and quantification of proteomes.

Chen Ding1, Jing Jiang, Junying Wei, Wanlin Liu, Wei Zhang, Mingwei Liu, Tianyi Fu, Tianyuan Lu, Lei Song, Wantao Ying, Cheng Chang, Yangjun Zhang, Jie Ma, Lai Wei, Anna Malovannaya, Lijun Jia, Bei Zhen, Yi Wang, Fuchu He, Xiaohong Qian, Jun Qin.   

Abstract

The current in-depth proteomics makes use of long chromatography gradient to get access to more peptides for protein identification, resulting in covering of as many as 8000 mammalian gene products in 3 days of mass spectrometer running time. Here we report a fast sequencing (Fast-seq) workflow of the use of dual reverse phase high performance liquid chromatography - mass spectrometry (HPLC-MS) with a short gradient to achieve the same proteome coverage in 0.5 day. We adapted this workflow to a quantitative version (Fast quantification, Fast-quan) that was compatible to large-scale protein quantification. We subjected two identical samples to the Fast-quan workflow, which allowed us to systematically evaluate different parameters that impact the sensitivity and accuracy of the workflow. Using the statistics of significant test, we unraveled the existence of substantial falsely quantified differential proteins and estimated correlation of false quantification rate and parameters that are applied in label-free quantification. We optimized the setting of parameters that may substantially minimize the rate of falsely quantified differential proteins, and further applied them on a real biological process. With improved efficiency and throughput, we expect that the Fast-seq/Fast-quan workflow, allowing pair wise comparison of two proteomes in 1 day may make MS available to the masses and impact biomedical research in a positive way.

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Year:  2013        PMID: 23669031      PMCID: PMC3734592          DOI: 10.1074/mcp.O112.025023

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  44 in total

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Authors:  M Kanehisa; S Goto
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Review 2.  The application of mass spectrometry to membrane proteomics.

Authors:  Christine C Wu; John R Yates
Journal:  Nat Biotechnol       Date:  2003-03       Impact factor: 54.908

3.  pH gradient reversed-phase HPLC.

Authors:  Roman Kaliszan; Paweł Wiczling; Michał J Markuszewski
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Authors:  Tatsuji Nakamura; Junro Kuromitsu; Yoshiya Oda
Journal:  J Proteome Res       Date:  2008-02-02       Impact factor: 4.466

5.  Quantitative proteomic analysis of cellular protein modulation upon inhibition of the NEDD8-activating enzyme by MLN4924.

Authors:  Hua Liao; Xiaozhen J Liu; Jonathan L Blank; David C Bouck; Hugues Bernard; Khristofer Garcia; Eric S Lightcap
Journal:  Mol Cell Proteomics       Date:  2011-08-26       Impact factor: 5.911

6.  xCT deficiency accelerates chemically induced tumorigenesis.

Authors:  Ami Nabeyama; Ai Kurita; Kenichi Asano; Yasunobu Miyake; Takuwa Yasuda; Ikuo Miura; Gen Nishitai; Satoko Arakawa; Shigeomi Shimizu; Shigeharu Wakana; Hisahiro Yoshida; Masato Tanaka
Journal:  Proc Natl Acad Sci U S A       Date:  2010-03-22       Impact factor: 11.205

7.  An inhibitor of NEDD8-activating enzyme as a new approach to treat cancer.

Authors:  Teresa A Soucy; Peter G Smith; Michael A Milhollen; Allison J Berger; James M Gavin; Sharmila Adhikari; James E Brownell; Kristine E Burke; David P Cardin; Stephen Critchley; Courtney A Cullis; Amanda Doucette; James J Garnsey; Jeffrey L Gaulin; Rachel E Gershman; Anna R Lublinsky; Alice McDonald; Hirotake Mizutani; Usha Narayanan; Edward J Olhava; Stephane Peluso; Mansoureh Rezaei; Michael D Sintchak; Tina Talreja; Michael P Thomas; Tary Traore; Stepan Vyskocil; Gabriel S Weatherhead; Jie Yu; Julie Zhang; Lawrence R Dick; Christopher F Claiborne; Mark Rolfe; Joseph B Bolen; Steven P Langston
Journal:  Nature       Date:  2009-04-09       Impact factor: 49.962

8.  The quantitative proteome of a human cell line.

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Journal:  Mol Syst Biol       Date:  2011-11-08       Impact factor: 11.429

9.  Microarray-assisted pathway analysis identifies MT1X & NFκB as mediators of TCRP1-associated resistance to cisplatin in oral squamous cell carcinoma.

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10.  Interaction with Suv39H1 is critical for Snail-mediated E-cadherin repression in breast cancer.

Authors:  C Dong; Y Wu; Y Wang; C Wang; T Kang; P G Rychahou; Y-I Chi; B M Evers; B P Zhou
Journal:  Oncogene       Date:  2012-05-07       Impact factor: 9.867

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  38 in total

1.  An Anatomically Resolved Mouse Brain Proteome Reveals Parkinson Disease-relevant Pathways.

Authors:  Sung Yun Jung; Jong Min Choi; Maxime W C Rousseaux; Anna Malovannaya; Jean J Kim; Joachim Kutzera; Yi Wang; Yin Huang; Weimin Zhu; Suman Maity; Huda Yahya Zoghbi; Jun Qin
Journal:  Mol Cell Proteomics       Date:  2017-02-02       Impact factor: 5.911

2.  The neddylation-cullin 2-RBX1 E3 ligase axis targets tumor suppressor RhoB for degradation in liver cancer.

Authors:  Junfeng Xu; Lihui Li; Guangyang Yu; Wantao Ying; Qiang Gao; Wenjuan Zhang; Xianyu Li; Chen Ding; Yanan Jiang; Dongping Wei; Shengzhong Duan; Qunying Lei; Peng Li; Tieliu Shi; Xiaohong Qian; Jun Qin; Lijun Jia
Journal:  Mol Cell Proteomics       Date:  2014-12-24       Impact factor: 5.911

3.  Firmiana: towards a one-stop proteomic cloud platform for data processing and analysis.

Authors:  Jinwen Feng; Chen Ding; Naiqi Qiu; Xiaotian Ni; Dongdong Zhan; Wanlin Liu; Xia Xia; Peng Li; Bingxin Lu; Qi Zhao; Peng Nie; Lei Song; Quan Zhou; Mi Lai; Gaigai Guo; Weimin Zhu; Jian Ren; Tieliu Shi; Jun Qin
Journal:  Nat Biotechnol       Date:  2017-05-09       Impact factor: 54.908

4.  Precision De Novo Peptide Sequencing Using Mirror Proteases of Ac-LysargiNase and Trypsin for Large-scale Proteomics.

Authors:  Hao Yang; Yan-Chang Li; Ming-Zhi Zhao; Fei-Lin Wu; Xi Wang; Wei-Di Xiao; Yi-Hao Wang; Jun-Ling Zhang; Fu-Qiang Wang; Feng Xu; Wen-Feng Zeng; Christopher M Overall; Si-Min He; Hao Chi; Ping Xu
Journal:  Mol Cell Proteomics       Date:  2019-01-08       Impact factor: 5.911

5.  Multidimensional Proteomics Reveals a Role of UHRF2 in the Regulation of Epithelial-Mesenchymal Transition (EMT).

Authors:  Mi Lai; Lizhu Liang; Jiwei Chen; Naiqi Qiu; Sai Ge; Shuhui Ji; Tieliu Shi; Bei Zhen; Mingwei Liu; Chen Ding; Yi Wang; Jun Qin
Journal:  Mol Cell Proteomics       Date:  2016-04-25       Impact factor: 5.911

6.  Systematic Evaluation of Immobilized Trypsin-Based Fast Protein Digestion for Deep and High-Throughput Bottom-Up Proteomics.

Authors:  Xiaojing Shen; Liangliang Sun
Journal:  Proteomics       Date:  2018-04-15       Impact factor: 3.984

7.  Ion mobility-enhanced MS(E)-based label-free analysis reveals effects of low-dose radiation post contextual fear conditioning training on the mouse hippocampal proteome.

Authors:  Lin Huang; Samanthi I Wickramasekara; Tunde Akinyeke; Blair S Stewart; Yuan Jiang; Jacob Raber; Claudia S Maier
Journal:  J Proteomics       Date:  2016-03-26       Impact factor: 4.044

8.  Enhanced Purification of Ubiquitinated Proteins by Engineered Tandem Hybrid Ubiquitin-binding Domains (ThUBDs).

Authors:  Yuan Gao; Yanchang Li; Chengpu Zhang; Mingzhi Zhao; Chen Deng; Qiuyan Lan; Zexian Liu; Na Su; Jingwei Wang; Feng Xu; Yongru Xu; Lingyan Ping; Lei Chang; Huiying Gao; Junzhu Wu; Yu Xue; Zixin Deng; Junmin Peng; Ping Xu
Journal:  Mol Cell Proteomics       Date:  2016-04       Impact factor: 5.911

9.  Strong cation exchange-reversed phase liquid chromatography-capillary zone electrophoresis-tandem mass spectrometry platform with high peak capacity for deep bottom-up proteomics.

Authors:  Daoyang Chen; Xiaojing Shen; Liangliang Sun
Journal:  Anal Chim Acta       Date:  2018-02-05       Impact factor: 6.558

10.  Proteomics provides individualized options of precision medicine for patients with gastric cancer.

Authors:  Wenwen Huang; Dongdong Zhan; Yazhuo Li; Nairen Zheng; Xin Wei; Bin Bai; Kecheng Zhang; Mingwei Liu; Xuefei Zhao; Xiaotian Ni; Xia Xia; Jinwen Shi; Cheng Zhang; Zhihao Lu; Jiafu Ji; Juan Wang; Shiqi Wang; Gang Ji; Jipeng Li; Yongzhan Nie; Wenquan Liang; Xiaosong Wu; Jianxin Cui; Yongsheng Meng; Feilin Cao; Tieliu Shi; Weimin Zhu; Yi Wang; Lin Chen; Qingchuan Zhao; Hongwei Wang; Lin Shen; Jun Qin
Journal:  Sci China Life Sci       Date:  2021-07-09       Impact factor: 6.038

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