Literature DB >> 29278786

High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.

Lin Lin1, Jiaxin Zheng2, Quan Yu3, Wendong Chen4, Jinchun Xing2, Chenxi Chen2, Ruijun Tian5.   

Abstract

Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery. BIOLOGICAL SIGNIFICANCE: Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application, because the usage of small sample amounts makes blood testing much less invasive, the fully integrated sample preparation by the SISPROT technology greatly improve sample preparation throughput and reproducibility, and the scan feature of DIA method provides a way to convert nonrenewable clinical specimens into permanent digital proteome maps which could be easily reanalyzed.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biomarker; Data independent acquisition; Proteomic profiling; Serum

Mesh:

Substances:

Year:  2017        PMID: 29278786     DOI: 10.1016/j.jprot.2017.12.014

Source DB:  PubMed          Journal:  J Proteomics        ISSN: 1874-3919            Impact factor:   4.044


  17 in total

1.  SWATH-MS Protocols in Human Diseases.

Authors:  Maria Del Pilar Chantada-Vázquez; María García Vence; Antonio Serna; Cristina Núñez; Susana B Bravo
Journal:  Methods Mol Biol       Date:  2021

2.  HBFP: a new repository for human body fluid proteome.

Authors:  Dan Shao; Lan Huang; Yan Wang; Xueteng Cui; Yufei Li; Yao Wang; Qin Ma; Wei Du; Juan Cui
Journal:  Database (Oxford)       Date:  2021-10-13       Impact factor: 3.451

3.  Serum Proteomic Analysis Identifies SAA1, FGA, SAP, and CETP as New Biomarkers for Eosinophilic Granulomatosis With Polyangiitis.

Authors:  Jing Xiao; Shaohua Lu; Xufei Wang; Mengdi Liang; Cong Dong; Xiaoxian Zhang; Minzhi Qiu; Changxing Ou; Xiaoyin Zeng; Yanting Lan; Longbo Hu; Long Tan; Tao Peng; Qingling Zhang; Fei Long
Journal:  Front Immunol       Date:  2022-06-10       Impact factor: 8.786

Review 4.  The Peripheral and Intratumoral Immune Cell Landscape in Cancer Patients: A Proxy for Tumor Biology and a Tool for Outcome Prediction.

Authors:  Annette Schnell; Christian Schmidl; Wolfgang Herr; Peter J Siska
Journal:  Biomedicines       Date:  2018-02-24

5.  In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine.

Authors:  Meng Xu; Jingwen Deng; Kaikun Xu; Tiansheng Zhu; Ling Han; Yuhong Yan; Danni Yao; Hao Deng; Dan Wang; Yaoting Sun; Cheng Chang; Xiaomei Zhang; Jiayu Dai; Liang Yue; Qiushi Zhang; Xue Cai; Yi Zhu; Hu Duan; Yuan Liu; Dong Li; Yunping Zhu; Timothy R D J Radstake; Deepak M W Balak; Danke Xu; Tiannan Guo; Chuanjian Lu; Xiaobo Yu
Journal:  Theranostics       Date:  2019-04-13       Impact factor: 11.556

6.  Dissecting the multi-omics atlas of the exosomes released by human lung adenocarcinoma stem-like cells.

Authors:  Hai-Tao Luo; Yuan-Yuan Zheng; Jun Tang; Li-Juan Shao; Yi-Heng Mao; Wei Yang; Xiao-Fei Yang; Yang Li; Rui-Jun Tian; Fu-Rong Li
Journal:  NPJ Genom Med       Date:  2021-06-14       Impact factor: 8.617

Review 7.  Proteomic approaches for characterizing renal cell carcinoma.

Authors:  David J Clark; Hui Zhang
Journal:  Clin Proteomics       Date:  2020-07-29       Impact factor: 3.988

8.  Resolution Matters: Correlating Quantitative Proteomics and Nanoscale-Precision Microscopy for Reconstructing Synapse Identity.

Authors:  Andras Gabor Miklosi; Giorgia Del Favero; Doris Marko; Tibor Harkany; Gert Lubec
Journal:  Proteomics       Date:  2018-07       Impact factor: 3.984

9.  Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer.

Authors:  Lin Lin; Quan Yu; Jiaxin Zheng; Zonglong Cai; Ruijun Tian
Journal:  Clin Proteomics       Date:  2018-12-22       Impact factor: 3.988

10.  Data-Independent Acquisition Proteomics Reveals Long-Term Biomarkers in the Serum of C57BL/6J Mice Following Local High-Dose Heart Irradiation.

Authors:  Omid Azimzadeh; Christine von Toerne; Vikram Subramanian; Wolfgang Sievert; Gabriele Multhoff; Michael J Atkinson; Soile Tapio
Journal:  Front Public Health       Date:  2021-07-02
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