Literature DB >> 34905163

Proteomic Profiling of Cerebrospinal Fluid by 16-Plex TMT-Based Mass Spectrometry.

Kaushik Kumar Dey1, Huan Sun1, Zhen Wang1, Mingming Niu1, Hong Wang2, Yun Jiao1, Xiaojun Sun1, Yuxin Li2, Junmin Peng3,4.   

Abstract

Mass spectrometry (MS) has become a mainstream platform for comprehensive profiling of proteome, especially with the improvement of multiplexed tandem mass tag labeling coupled with two-dimensional liquid chromatography and tandem mass spectrometry (TMT-LC/LC-MS/MS). Recently, we have established a robust method for direct profiling of undepleted cerebrospinal fluid (CSF) proteome with the 16-plex TMTpro method, in which we optimized parameters in experimental steps of sample preparation, TMT labeling, LC/LC fractionation, tandem mass spectrometry, and computational data processing. The extensive LC fractionation not only enhances proteome coverage of the CSF but also alleviates ratio distortion of TMT quantification. The crucial quality control steps and improvements specific for the TMT16 analysis are highlighted. More than 3000 proteins can be quantified in a single experiment from 16 different CSF samples. This multiplexed method offers a powerful tool for profiling a variety of complex biofluids samples such as CSF, serum/plasma, and other clinical specimens.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Cerebrospinal fluid; Clinical proteomics; Isobaric labeling; Liquid chromatography; Mass spectrometry; Plasma; Proteome; Proteomics; Serum; Tandem mass tag

Mesh:

Substances:

Year:  2022        PMID: 34905163      PMCID: PMC8890903          DOI: 10.1007/978-1-0716-1936-0_3

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  48 in total

1.  Quantitative protein analysis by mass spectrometry.

Authors:  Vishwajeeth R Pagala; Anthony A High; Xusheng Wang; Haiyan Tan; Kiran Kodali; Ashutosh Mishra; Kanisha Kavdia; Yanji Xu; Zhiping Wu; Junmin Peng
Journal:  Methods Mol Biol       Date:  2015

2.  Depletion of abundant plasma proteins and limitations of plasma proteomics.

Authors:  Chengjian Tu; Paul A Rudnick; Misti Y Martinez; Kristin L Cheek; Stephen E Stein; Robbert J C Slebos; Daniel C Liebler
Journal:  J Proteome Res       Date:  2010-10-01       Impact factor: 4.466

Review 3.  Applying fluid biomarkers to Alzheimer's disease.

Authors:  Henrik Zetterberg
Journal:  Am J Physiol Cell Physiol       Date:  2017-04-19       Impact factor: 4.249

4.  A Strategy to Combine Sample Multiplexing with Targeted Proteomics Assays for High-Throughput Protein Signature Characterization.

Authors:  Brian K Erickson; Christopher M Rose; Craig R Braun; Alison R Erickson; Jeffrey Knott; Graeme C McAlister; Martin Wühr; Joao A Paulo; Robert A Everley; Steven P Gygi
Journal:  Mol Cell       Date:  2017-01-05       Impact factor: 17.970

5.  JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy.

Authors:  Xusheng Wang; Yuxin Li; Zhiping Wu; Hong Wang; Haiyan Tan; Junmin Peng
Journal:  Mol Cell Proteomics       Date:  2014-09-08       Impact factor: 5.911

Review 6.  Mass-spectrometric exploration of proteome structure and function.

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

Review 7.  CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis.

Authors:  Bob Olsson; Ronald Lautner; Ulf Andreasson; Annika Öhrfelt; Erik Portelius; Maria Bjerke; Mikko Hölttä; Christoffer Rosén; Caroline Olsson; Gabrielle Strobel; Elizabeth Wu; Kelly Dakin; Max Petzold; Kaj Blennow; Henrik Zetterberg
Journal:  Lancet Neurol       Date:  2016-04-08       Impact factor: 44.182

8.  MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes.

Authors:  Graeme C McAlister; David P Nusinow; Mark P Jedrychowski; Martin Wühr; Edward L Huttlin; Brian K Erickson; Ramin Rad; Wilhelm Haas; Steven P Gygi
Journal:  Anal Chem       Date:  2014-07-03       Impact factor: 8.008

9.  Integrated analysis of ultra-deep proteomes in cortex, cerebrospinal fluid and serum reveals a mitochondrial signature in Alzheimer's disease.

Authors:  Hong Wang; Kaushik Kumar Dey; Ping-Chung Chen; Yuxin Li; Mingming Niu; Ji-Hoon Cho; Xusheng Wang; Bing Bai; Yun Jiao; Surendhar Reddy Chepyala; Vahram Haroutunian; Bin Zhang; Thomas G Beach; Junmin Peng
Journal:  Mol Neurodegener       Date:  2020-07-25       Impact factor: 14.195

10.  The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease.

Authors:  Minghui Wang; Noam D Beckmann; Panos Roussos; Erming Wang; Xianxiao Zhou; Qian Wang; Chen Ming; Ryan Neff; Weiping Ma; John F Fullard; Mads E Hauberg; Jaroslav Bendl; Mette A Peters; Ben Logsdon; Pei Wang; Milind Mahajan; Lara M Mangravite; Eric B Dammer; Duc M Duong; James J Lah; Nicholas T Seyfried; Allan I Levey; Joseph D Buxbaum; Michelle Ehrlich; Sam Gandy; Pavel Katsel; Vahram Haroutunian; Eric Schadt; Bin Zhang
Journal:  Sci Data       Date:  2018-09-11       Impact factor: 6.444

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