Literature DB >> 29988108

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry.

Philipp Mertins1,2,3, Lauren C Tang1, Karsten Krug1, David J Clark4, Marina A Gritsenko5, Lijun Chen4, Karl R Clauser1, Therese R Clauss5, Punit Shah4, Michael A Gillette1, Vladislav A Petyuk5, Stefani N Thomas4, D R Mani1, Filip Mundt1, Ronald J Moore5, Yingwei Hu4, Rui Zhao5, Michael Schnaubelt4, Hasmik Keshishian1, Matthew E Monroe5, Zhen Zhang4, Namrata D Udeshi1, Deepak Mani1, Sherri R Davies6, R Reid Townsend6, Daniel W Chan4, Richard D Smith5, Hui Zhang4, Tao Liu5, Steven A Carr7.   

Abstract

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

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Year:  2018        PMID: 29988108      PMCID: PMC6211289          DOI: 10.1038/s41596-018-0006-9

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  43 in total

1.  Addressing accuracy and precision issues in iTRAQ quantitation.

Authors:  Natasha A Karp; Wolfgang Huber; Pawel G Sadowski; Philip D Charles; Svenja V Hester; Kathryn S Lilley
Journal:  Mol Cell Proteomics       Date:  2010-04-10       Impact factor: 5.911

2.  Does trypsin cut before proline?

Authors:  Jesse Rodriguez; Nitin Gupta; Richard D Smith; Pavel A Pevzner
Journal:  J Proteome Res       Date:  2007-12-08       Impact factor: 4.466

3.  Practical implementation of 2D HPLC scheme with accurate peptide retention prediction in both dimensions for high-throughput bottom-up proteomics.

Authors:  Ravi C Dwivedi; Vic Spicer; Michael Harder; Mihaela Antonovici; Werner Ens; Kenneth G Standing; John A Wilkins; Oleg V Krokhin
Journal:  Anal Chem       Date:  2008-08-08       Impact factor: 6.986

4.  Low-pH Solid-Phase Amino Labeling of Complex Peptide Digests with TMTs Improves Peptide Identification Rates for Multiplexed Global Phosphopeptide Analysis.

Authors:  Gitte Böhm; Petra Prefot; Stephan Jung; Stefan Selzer; Vikram Mitra; David Britton; Karsten Kuhn; Ian Pike; Andrew H Thompson
Journal:  J Proteome Res       Date:  2015-05-13       Impact factor: 4.466

5.  Ion coalescence of neutron encoded TMT 10-plex reporter ions.

Authors:  Thilo Werner; Gavain Sweetman; Maria Fälth Savitski; Toby Mathieson; Marcus Bantscheff; Mikhail M Savitski
Journal:  Anal Chem       Date:  2014-03-11       Impact factor: 6.986

6.  Integrated proteomic analysis of post-translational modifications by serial enrichment.

Authors:  Philipp Mertins; Jana W Qiao; Jinal Patel; Namrata D Udeshi; Karl R Clauser; D R Mani; Michael W Burgess; Michael A Gillette; Jacob D Jaffe; Steven A Carr
Journal:  Nat Methods       Date:  2013-06-09       Impact factor: 28.547

7.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

8.  Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.

Authors:  Juri Rappsilber; Matthias Mann; Yasushi Ishihama
Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

9.  Gas-phase purification enables accurate, multiplexed proteome quantification with isobaric tagging.

Authors:  Craig D Wenger; M Violet Lee; Alexander S Hebert; Graeme C McAlister; Douglas H Phanstiel; Michael S Westphall; Joshua J Coon
Journal:  Nat Methods       Date:  2011-10-02       Impact factor: 28.547

10.  i-Tracker: for quantitative proteomics using iTRAQ.

Authors:  Ian P Shadforth; Tom P J Dunkley; Kathryn S Lilley; Conrad Bessant
Journal:  BMC Genomics       Date:  2005-10-20       Impact factor: 3.969

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  118 in total

1.  The conserved translation factor LepA is required for optimal synthesis of a porin family in Mycobacterium smegmatis.

Authors:  Skye R S Fishbein; Francesca G Tomasi; Ian D Wolf; Charles L Dulberger; Albert Wang; Hasmik Keshishian; Luke Wallace; Steven A Carr; Thomas R Ioerger; E Hesper Rego; Eric J Rubin
Journal:  J Bacteriol       Date:  2020-12-23       Impact factor: 3.490

2.  Proteomic Interrogation in Cancer Biomarker.

Authors:  Un-Beom Kang
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

3.  A Curated Resource for Phosphosite-specific Signature Analysis.

Authors:  Karsten Krug; Philipp Mertins; Bin Zhang; Peter Hornbeck; Rajesh Raju; Rushdy Ahmad; Matthew Szucs; Filip Mundt; Dominique Forestier; Judit Jane-Valbuena; Hasmik Keshishian; Michael A Gillette; Pablo Tamayo; Jill P Mesirov; Jacob D Jaffe; Steven A Carr; D R Mani
Journal:  Mol Cell Proteomics       Date:  2018-12-18       Impact factor: 5.911

4.  TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach.

Authors:  Jana Zecha; Shankha Satpathy; Tamara Kanashova; Shayan C Avanessian; M Harry Kane; Karl R Clauser; Philipp Mertins; Steven A Carr; Bernhard Kuster
Journal:  Mol Cell Proteomics       Date:  2019-04-09       Impact factor: 5.911

5.  Boosting to Amplify Signal with Isobaric Labeling (BASIL) Strategy for Comprehensive Quantitative Phosphoproteomic Characterization of Small Populations of Cells.

Authors:  Lian Yi; Chia-Feng Tsai; Ercument Dirice; Adam C Swensen; Jing Chen; Tujin Shi; Marina A Gritsenko; Rosalie K Chu; Paul D Piehowski; Richard D Smith; Karin D Rodland; Mark A Atkinson; Clayton E Mathews; Rohit N Kulkarni; Tao Liu; Wei-Jun Qian
Journal:  Anal Chem       Date:  2019-03-15       Impact factor: 6.986

6.  An Integrated Workflow for Global, Glyco-, and Phospho-proteomic Analysis of Tumor Tissues.

Authors:  Yangying Zhou; Tung-Shing Mamie Lih; Ganglong Yang; Shao-Yung Chen; Lijun Chen; Daniel W Chan; Hui Zhang; Qing Kay Li
Journal:  Anal Chem       Date:  2020-01-03       Impact factor: 6.986

7.  Large-scale proteomic analysis of Alzheimer's disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation.

Authors:  Erik C B Johnson; Eric B Dammer; Duc M Duong; Lingyan Ping; Maotian Zhou; Luming Yin; Lenora A Higginbotham; Andrew Guajardo; Bartholomew White; Juan C Troncoso; Madhav Thambisetty; Thomas J Montine; Edward B Lee; John Q Trojanowski; Thomas G Beach; Eric M Reiman; Vahram Haroutunian; Minghui Wang; Eric Schadt; Bin Zhang; Dennis W Dickson; Nilüfer Ertekin-Taner; Todd E Golde; Vladislav A Petyuk; Philip L De Jager; David A Bennett; Thomas S Wingo; Srikant Rangaraju; Ihab Hajjar; Joshua M Shulman; James J Lah; Allan I Levey; Nicholas T Seyfried
Journal:  Nat Med       Date:  2020-04-13       Impact factor: 53.440

8.  Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy.

Authors:  Karsten Krug; Eric J Jaehnig; Shankha Satpathy; Lili Blumenberg; Alla Karpova; Meenakshi Anurag; George Miles; Philipp Mertins; Yifat Geffen; Lauren C Tang; David I Heiman; Song Cao; Yosef E Maruvka; Jonathan T Lei; Chen Huang; Ramani B Kothadia; Antonio Colaprico; Chet Birger; Jarey Wang; Yongchao Dou; Bo Wen; Zhiao Shi; Yuxing Liao; Maciej Wiznerowicz; Matthew A Wyczalkowski; Xi Steven Chen; Jacob J Kennedy; Amanda G Paulovich; Mathangi Thiagarajan; Christopher R Kinsinger; Tara Hiltke; Emily S Boja; Mehdi Mesri; Ana I Robles; Henry Rodriguez; Thomas F Westbrook; Li Ding; Gad Getz; Karl R Clauser; David Fenyö; Kelly V Ruggles; Bing Zhang; D R Mani; Steven A Carr; Matthew J Ellis; Michael A Gillette
Journal:  Cell       Date:  2020-11-18       Impact factor: 41.582

9.  Mitochondrial Reprogramming Underlies Resistance to BCL-2 Inhibition in Lymphoid Malignancies.

Authors:  Romain Guièze; Vivian M Liu; Daniel Rosebrock; Alexis A Jourdain; María Hernández-Sánchez; Aina Martinez Zurita; Jing Sun; Elisa Ten Hacken; Kaitlyn Baranowski; Philip A Thompson; Jin-Mi Heo; Zachary Cartun; Ozan Aygün; J Bryan Iorgulescu; Wandi Zhang; Giulia Notarangelo; Dimitri Livitz; Shuqiang Li; Matthew S Davids; Anat Biran; Stacey M Fernandes; Jennifer R Brown; Ana Lako; Zoe B Ciantra; Matthew A Lawlor; Derin B Keskin; Namrata D Udeshi; William G Wierda; Kenneth J Livak; Anthony G Letai; Donna Neuberg; J Wade Harper; Steven A Carr; Federica Piccioni; Christopher J Ott; Ignaty Leshchiner; Cory M Johannessen; John Doench; Vamsi K Mootha; Gad Getz; Catherine J Wu
Journal:  Cancer Cell       Date:  2019-09-19       Impact factor: 31.743

10.  Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma.

Authors:  Yingwei Hu; Jianbo Pan; Punit Shah; Minghui Ao; Stefani N Thomas; Yang Liu; Lijun Chen; Michael Schnaubelt; David J Clark; Henry Rodriguez; Emily S Boja; Tara Hiltke; Christopher R Kinsinger; Karin D Rodland; Qing Kay Li; Jiang Qian; Zhen Zhang; Daniel W Chan; Hui Zhang
Journal:  Cell Rep       Date:  2020-10-20       Impact factor: 9.423

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