Literature DB >> 30792265

Streamlined Protocol for Deep Proteomic Profiling of FAC-sorted Cells and Its Application to Freshly Isolated Murine Immune Cells.

Samuel A Myers1, Andrew Rhoads2, Alexandra R Cocco3, Ryan Peckner3, Adam L Haber4, Lawrence D Schweitzer3, Karsten Krug3, D R Mani3, Karl R Clauser3, Orit Rozenblatt-Rosen4, Nir Hacohen5, Aviv Regev6, Steven A Carr7.   

Abstract

Proteomic profiling describes the molecular landscape of proteins in cells immediately available to sense, transduce, and enact the appropriate responses to extracellular queues. Transcriptional profiling has proven invaluable to our understanding of cellular responses; however, insights may be lost as mounting evidence suggests transcript levels only moderately correlate with protein levels in steady state cells. Mass spectrometry-based quantitative proteomics is a well-suited and widely used analytical tool for studying global protein abundances. Typical proteomic workflows are often limited by the amount of sample input that is required for deep and quantitative proteome profiling. This is especially true if the cells of interest need to be purified by fluorescence-activated cell sorting (FACS) and one wants to avoid ex vivo culturing. To address this need, we developed an easy to implement, streamlined workflow that enables quantitative proteome profiling from roughly 2 μg of protein input per experimental condition. Utilizing a combination of facile cell collection from cell sorting, solid-state isobaric labeling and multiplexing of peptides, and small-scale fractionation, we profiled the proteomes of 12 freshly isolated, primary murine immune cell types. Analyzing half of the 3e5 cells collected per cell type, we quantified over 7000 proteins across 12 key immune cell populations directly from their resident tissues. We show that low input proteomics is precise, and the data generated accurately reflects many aspects of known immunology, while expanding the list of cell-type specific proteins across the cell types profiled. The low input proteomics methods we developed are readily adaptable and broadly applicable to any cell or sample types and should enable proteome profiling in systems previously unattainable.
© 2019 Myers et al.

Entities:  

Keywords:  Animal models*; Cell sorting; FACS; Gene Expression*; Immunology*; Low Input; Post-transcriptional regulation; Systems biology*; TMT

Mesh:

Substances:

Year:  2019        PMID: 30792265      PMCID: PMC6495249          DOI: 10.1074/mcp.RA118.001259

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  51 in total

1.  Missing value estimation methods for DNA microarrays.

Authors:  O Troyanskaya; M Cantor; G Sherlock; P Brown; T Hastie; R Tibshirani; D Botstein; R B Altman
Journal:  Bioinformatics       Date:  2001-06       Impact factor: 6.937

2.  Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS.

Authors:  Andrew Thompson; Jürgen Schäfer; Karsten Kuhn; Stefan Kienle; Josef Schwarz; Günter Schmidt; Thomas Neumann; R Johnstone; A Karim A Mohammed; Christian Hamon
Journal:  Anal Chem       Date:  2003-04-15       Impact factor: 6.986

3.  Comparative gene marker selection suite.

Authors:  Joshua Gould; Gad Getz; Stefano Monti; Michael Reich; Jill P Mesirov
Journal:  Bioinformatics       Date:  2006-05-18       Impact factor: 6.937

4.  The Immunological Genome Project: networks of gene expression in immune cells.

Authors:  Tracy S P Heng; Michio W Painter
Journal:  Nat Immunol       Date:  2008-10       Impact factor: 25.606

5.  Global quantification of mammalian gene expression control.

Authors:  Björn Schwanhäusser; Dorothea Busse; Na Li; Gunnar Dittmar; Johannes Schuchhardt; Jana Wolf; Wei Chen; Matthias Selbach
Journal:  Nature       Date:  2011-05-19       Impact factor: 49.962

6.  Transcriptomes of the B and T lineages compared by multiplatform microarray profiling.

Authors:  Michio W Painter; Scott Davis; Richard R Hardy; Diane Mathis; Christophe Benoist
Journal:  J Immunol       Date:  2011-02-09       Impact factor: 5.422

7.  Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells.

Authors:  Michal Rabani; Joshua Z Levin; Lin Fan; Xian Adiconis; Raktima Raychowdhury; Manuel Garber; Andreas Gnirke; Chad Nusbaum; Nir Hacohen; Nir Friedman; Ido Amit; Aviv Regev
Journal:  Nat Biotechnol       Date:  2011-04-24       Impact factor: 54.908

8.  Molecular definition of the identity and activation of natural killer cells.

Authors:  Natalie A Bezman; Charles C Kim; Joseph C Sun; Gundula Min-Oo; Deborah W Hendricks; Yosuke Kamimura; J Adam Best; Ananda W Goldrath; Lewis L Lanier
Journal:  Nat Immunol       Date:  2012-08-19       Impact factor: 25.606

9.  The cytotoxic T cell proteome and its shaping by the kinase mTOR.

Authors:  Jens L Hukelmann; Karen E Anderson; Linda V Sinclair; Katarzyna M Grzes; Alejandro Brenes Murillo; Phillip T Hawkins; Len R Stephens; Angus I Lamond; Doreen A Cantrell
Journal:  Nat Immunol       Date:  2015-11-09       Impact factor: 25.606

10.  Expression profiling of constitutive mast cells reveals a unique identity within the immune system.

Authors:  Daniel F Dwyer; Nora A Barrett; K Frank Austen
Journal:  Nat Immunol       Date:  2016-05-02       Impact factor: 25.606

View more
  20 in total

1.  Virtual Issue: Technological Innovations.

Authors:  Anne-Claude Gingras; Steven A Carr; Alma L Burlingame
Journal:  Mol Cell Proteomics       Date:  2020-03-17       Impact factor: 5.911

2.  High-speed Analysis of Large Sample Sets - How Can This Key Aspect of the Omics Be Achieved?

Authors:  Rainer Cramer
Journal:  Mol Cell Proteomics       Date:  2020-08-12       Impact factor: 5.911

3.  Identification of RIOK2 as a master regulator of human blood cell development.

Authors:  Shrestha Ghosh; Mahesh Raundhal; Samuel A Myers; Steven A Carr; Xi Chen; Gregory A Petsko; Laurie H Glimcher
Journal:  Nat Immunol       Date:  2021-12-22       Impact factor: 25.606

4.  Proteomic Profiling of the ECM of Xenograft Breast Cancer Metastases in Different Organs Reveals Distinct Metastatic Niches.

Authors:  Jess D Hebert; Samuel A Myers; Alexandra Naba; Genevieve Abbruzzese; John M Lamar; Steven A Carr; Richard O Hynes
Journal:  Cancer Res       Date:  2020-02-04       Impact factor: 12.701

5.  Simple and Efficient Microsolid-Phase Extraction Tip-Based Sample Preparation Workflow to Enable Sensitive Proteomic Profiling of Limited Samples (200 to 10,000 Cells).

Authors:  James C Kostas; Michal Greguš; Jan Schejbal; Somak Ray; Alexander R Ivanov
Journal:  J Proteome Res       Date:  2021-02-24       Impact factor: 4.466

6.  An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics.

Authors:  Chia-Feng Tsai; Rui Zhao; Sarah M Williams; Ronald J Moore; Kendall Schultz; William B Chrisler; Ljiljana Pasa-Tolic; Karin D Rodland; Richard D Smith; Tujin Shi; Ying Zhu; Tao Liu
Journal:  Mol Cell Proteomics       Date:  2020-03-03       Impact factor: 5.911

7.  Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications.

Authors:  Lindsay K Pino; Jacob Rose; Amy O'Broin; Samah Shah; Birgit Schilling
Journal:  Biochem Soc Trans       Date:  2020-10-30       Impact factor: 5.407

8.  Deep Profiling of Microgram-Scale Proteome by Tandem Mass Tag Mass Spectrometry.

Authors:  Danting Liu; Shu Yang; Kanisha Kavdia; Jeffrey M Sifford; Zhiping Wu; Boer Xie; Zhen Wang; Vishwajeeth R Pagala; Hong Wang; Kaiwen Yu; Kaushik Kumar Dey; Anthony A High; Geidy E Serrano; Thomas G Beach; Junmin Peng
Journal:  J Proteome Res       Date:  2020-11-11       Impact factor: 4.466

9.  Mast cell surfaceome characterization reveals CD98 heavy chain is critical for optimal cell function.

Authors:  Siddhartha S Saha; Nyssa B Samanas; Irina Miralda; Nicholas J Shubin; Kerri Niino; Gauri Bhise; Manasa Acharya; Albert J Seo; Nathan Camp; Gail H Deutsch; Richard G James; Adrian M Piliponsky
Journal:  J Allergy Clin Immunol       Date:  2021-07-27       Impact factor: 10.793

Review 10.  Plasma cell biology: Foundations for targeted therapeutic development in transplantation.

Authors:  Amy P Rossi; Rita R Alloway; David Hildeman; E Steve Woodle
Journal:  Immunol Rev       Date:  2021-07-12       Impact factor: 10.983

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.