Literature DB >> 35931778

High-throughput proteomic sample preparation using pressure cycling technology.

Xue Cai1,2, Zhangzhi Xue1,2, Chunlong Wu3, Rui Sun1,2, Liujia Qian1,2, Liang Yue1,2, Weigang Ge3, Xiao Yi3, Wei Liu3, Chen Chen3, Huanhuan Gao3, Jing Yu3, Luang Xu3, Yi Zhu4,5, Tiannan Guo6,7.   

Abstract

High-throughput lysis and proteolytic digestion of biopsy-level tissue specimens is a major bottleneck for clinical proteomics. Here we describe a detailed protocol of pressure cycling technology (PCT)-assisted sample preparation for proteomic analysis of biopsy tissues. A piece of fresh frozen or formalin-fixed paraffin-embedded tissue weighing ~0.1-2 mg is placed in a 150 μL pressure-resistant tube called a PCT-MicroTube with proper lysis buffer. After closing with a PCT-MicroPestle, a batch of 16 PCT-MicroTubes are placed in a Barocycler, which imposes oscillating pressure to the samples from one atmosphere to up to ~3,000 times atmospheric pressure. The pressure cycling schemes are optimized for tissue lysis and protein digestion, and can be programmed in the Barocycler to allow reproducible, robust and efficient protein extraction and proteolysis digestion for mass spectrometry-based proteomics. This method allows effective preparation of not only fresh frozen and formalin-fixed paraffin-embedded tissue, but also cells, feces and tear strips. It takes ~3 h to process 16 samples in one batch. The resulting peptides can be analyzed by various mass spectrometry-based proteomics methods. We demonstrate the applications of this protocol with mouse kidney tissue and eight types of human tumors.
© 2022. Springer Nature Limited.

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Year:  2022        PMID: 35931778      PMCID: PMC9362583          DOI: 10.1038/s41596-022-00727-1

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   17.021


  38 in total

1.  Proteomic analysis of formalin-fixed prostate cancer tissue.

Authors:  Brian L Hood; Marlene M Darfler; Thomas G Guiel; Bungo Furusato; David A Lucas; Bradley R Ringeisen; Isabell A Sesterhenn; Thomas P Conrads; Timothy D Veenstra; David B Krizman
Journal:  Mol Cell Proteomics       Date:  2005-08-09       Impact factor: 5.911

2.  Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues.

Authors:  S-I Hwang; J Thumar; D H Lundgren; K Rezaul; V Mayya; L Wu; J Eng; M E Wright; D K Han
Journal:  Oncogene       Date:  2006-06-26       Impact factor: 9.867

3.  Universal sample preparation method for proteome analysis.

Authors:  Jacek R Wiśniewski; Alexandre Zougman; Nagarjuna Nagaraj; Matthias Mann
Journal:  Nat Methods       Date:  2009-04-19       Impact factor: 28.547

Review 4.  Mass-spectrometric exploration of proteome structure and function.

Authors:  Ruedi Aebersold; Matthias Mann
Journal:  Nature       Date:  2016-09-15       Impact factor: 49.962

5.  SnapShot: Clinical proteomics.

Authors:  Yi Zhu; Ruedi Aebersold; Matthias Mann; Tiannan Guo
Journal:  Cell       Date:  2021-09-02       Impact factor: 41.582

6.  Ultrasensitive proteome analysis using paramagnetic bead technology.

Authors:  Christopher S Hughes; Sophia Foehr; David A Garfield; Eileen E Furlong; Lars M Steinmetz; Jeroen Krijgsveld
Journal:  Mol Syst Biol       Date:  2014-10-30       Impact factor: 11.429

7.  Rapid mass spectrometric conversion of tissue biopsy samples into permanent quantitative digital proteome maps.

Authors:  Tiannan Guo; Petri Kouvonen; Ching Chiek Koh; Ludovic C Gillet; Witold E Wolski; Hannes L Röst; George Rosenberger; Ben C Collins; Lorenz C Blum; Silke Gillessen; Markus Joerger; Wolfram Jochum; Ruedi Aebersold
Journal:  Nat Med       Date:  2015-03-02       Impact factor: 53.440

8.  Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts.

Authors:  Mark A Eckert; Fabian Coscia; Agnieszka Chryplewicz; Jae Won Chang; Kyle M Hernandez; Shawn Pan; Samantha M Tienda; Dominik A Nahotko; Gang Li; Ivana Blaženović; Ricardo R Lastra; Marion Curtis; S Diane Yamada; Ruth Perets; Stephanie M McGregor; Jorge Andrade; Oliver Fiehn; Raymond E Moellering; Matthias Mann; Ernst Lengyel
Journal:  Nature       Date:  2019-05-01       Impact factor: 49.962

9.  Multi-organ proteomic landscape of COVID-19 autopsies.

Authors:  Xiu Nie; Liujia Qian; Rui Sun; Bo Huang; Xiaochuan Dong; Qi Xiao; Qiushi Zhang; Tian Lu; Liang Yue; Shuo Chen; Xiang Li; Yaoting Sun; Lu Li; Luang Xu; Yan Li; Ming Yang; Zhangzhi Xue; Shuang Liang; Xuan Ding; Chunhui Yuan; Li Peng; Wei Liu; Xiao Yi; Mengge Lyu; Guixiang Xiao; Xia Xu; Weigang Ge; Jiale He; Jun Fan; Junhua Wu; Meng Luo; Xiaona Chang; Huaxiong Pan; Xue Cai; Junjie Zhou; Jing Yu; Huanhuan Gao; Mingxing Xie; Sihua Wang; Guan Ruan; Hao Chen; Hua Su; Heng Mei; Danju Luo; Dashi Zhao; Fei Xu; Yan Li; Yi Zhu; Jiahong Xia; Yu Hu; Tiannan Guo
Journal:  Cell       Date:  2021-01-09       Impact factor: 41.582

Review 10.  High-throughput proteomics and AI for cancer biomarker discovery.

Authors:  Qi Xiao; Fangfei Zhang; Luang Xu; Liang Yue; Oi Lian Kon; Yi Zhu; Tiannan Guo
Journal:  Adv Drug Deliv Rev       Date:  2021-06-26       Impact factor: 15.470

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