Proteomics

Dataset Information

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A simple method to quantify protein abundances from one thousand cells


ABSTRACT: The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1,000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2,500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold-changes, and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compare well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as FACS-purified cells from the tunicate Ciona. Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Ciona Robusta Mus Musculus (mouse)

TISSUE(S): Heart, Embryo, Embryonic Stem Cell

SUBMITTER: Shuvadeep Maity  

LAB HEAD: Christine Vogel

PROVIDER: PXD019363 | Pride | 2020-07-16

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
180621_Ciona_proteinGroups.txt Txt
180622_burcu_ciona15_TMT10.raw Raw
180817_20k_proteinGroups.txt Txt
180817_60k_proteinGroups.txt Txt
180817_TMT_20k.raw Raw
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Publications

Simple Method to Quantify Protein Abundances from 1000 Cells.

Vitrinel Burcu B   Iannitelli Dylan E DE   Mazzoni Esteban O EO   Christiaen Lionel L   Vogel Christine C  

ACS omega 20200619 25


The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated  ...[more]

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