Literature DB >> 35385261

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform.

Kei G I Webber1, Thy Truong1, S Madisyn Johnston1, Sebastian E Zapata1, Yiran Liang1, Jacob M Davis1, Alexander D Buttars1, Fletcher B Smith1, Hailey E Jones1, Arianna C Mahoney1, Richard H Carson1, Andikan J Nwosu1, Jacob L Heninger1, Andrey V Liyu2, Gregory P Nordin3, Ying Zhu2, Ryan T Kelly1,2.   

Abstract

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. We explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

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Year:  2022        PMID: 35385261      PMCID: PMC9356711          DOI: 10.1021/acs.analchem.2c00646

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   8.008


  44 in total

1.  Making broad proteome protein measurements in 1-5 min using high-speed RPLC separations and high-accuracy mass measurements.

Authors:  Yufeng Shen; Eric F Strittmatter; Rui Zhang; Thomas O Metz; Ronald J Moore; Fumin Li; Harold R Udseth; Richard D Smith; Klaus K Unger; Dipika Kumar; Dieter Lubda
Journal:  Anal Chem       Date:  2005-12-01       Impact factor: 6.986

Review 2.  Advances in proteomics data analysis and display using an accurate mass and time tag approach.

Authors:  Jennifer S D Zimmer; Matthew E Monroe; Wei-Jun Qian; Richard D Smith
Journal:  Mass Spectrom Rev       Date:  2006 May-Jun       Impact factor: 10.946

3.  Proteomic Analysis of Single Mammalian Cells Enabled by Microfluidic Nanodroplet Sample Preparation and Ultrasensitive NanoLC-MS.

Authors:  Ying Zhu; Geremy Clair; William B Chrisler; Yufeng Shen; Rui Zhao; Anil K Shukla; Ronald J Moore; Ravi S Misra; Gloria S Pryhuber; Richard D Smith; Charles Ansong; Ryan T Kelly
Journal:  Angew Chem Int Ed Engl       Date:  2018-06-14       Impact factor: 15.336

4.  Increased throughput and reduced carryover of mass spectrometry-based proteomics using a high-efficiency nonsplit nanoflow parallel dual-column capillary HPLC system.

Authors:  Hong Wang; Samir M Hanash
Journal:  J Proteome Res       Date:  2008-05-31       Impact factor: 4.466

5.  Combined tissue and fluid proteomics with Tandem Mass Tags to identify low-abundance protein biomarkers of disease in peripheral body fluid: An Alzheimer's Disease case study.

Authors:  Claire L Russell; Amanda Heslegrave; Vikram Mitra; Henrik Zetterberg; Jennifer M Pocock; Malcolm A Ward; Ian Pike
Journal:  Rapid Commun Mass Spectrom       Date:  2017-01-30       Impact factor: 2.419

6.  apQuant: Accurate Label-Free Quantification by Quality Filtering.

Authors:  Johannes Doblmann; Frederico Dusberger; Richard Imre; Otto Hudecz; Florian Stanek; Karl Mechtler; Gerhard Dürnberger
Journal:  J Proteome Res       Date:  2018-11-02       Impact factor: 4.466

7.  Improved Single-Cell Proteome Coverage Using Narrow-Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry.

Authors:  Yongzheng Cong; Yiran Liang; Khatereh Motamedchaboki; Romain Huguet; Thy Truong; Rui Zhao; Yufeng Shen; Daniel Lopez-Ferrer; Ying Zhu; Ryan T Kelly
Journal:  Anal Chem       Date:  2020-01-21       Impact factor: 6.986

8.  Reversal of inflammation-associated dihydrodiol dehydrogenases (AKR1C1 and AKR1C2) overexpression and drug resistance in nonsmall cell lung cancer cells by wogonin and chrysin.

Authors:  Hao-Wei Wang; Chin-Ping Lin; Jen-Hwey Chiu; Kuan-Chih Chow; Kuang-Tai Kuo; Chen-Sung Lin; Liang-Shun Wang
Journal:  Int J Cancer       Date:  2007-05-01       Impact factor: 7.396

9.  A Double-Barrel Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) System to Quantify 96 Interactomes per Day.

Authors:  Fabian Hosp; Richard A Scheltema; H Christian Eberl; Nils A Kulak; Eva C Keilhauer; Korbinian Mayr; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2015-04-17       Impact factor: 5.911

10.  TCRD and Pharos 2021: mining the human proteome for disease biology.

Authors:  Timothy K Sheils; Stephen L Mathias; Keith J Kelleher; Vishal B Siramshetty; Dac-Trung Nguyen; Cristian G Bologa; Lars Juhl Jensen; Dušica Vidović; Amar Koleti; Stephan C Schürer; Anna Waller; Jeremy J Yang; Jayme Holmes; Giovanni Bocci; Noel Southall; Poorva Dharkar; Ewy Mathé; Anton Simeonov; Tudor I Oprea
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

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  1 in total

1.  Separation methods in single-cell proteomics: RPLC or CE?

Authors:  Kellye A Cupp-Sutton; Mulin Fang; Si Wu
Journal:  Int J Mass Spectrom       Date:  2022-08-17       Impact factor: 1.934

  1 in total

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