Proteomics

Dataset Information

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The subcellular proteome of mouse pluripotent embryonic stem cells


ABSTRACT: Our understanding of the biology of embryonic stem (ES) cells is deeply rooted in characterization of their transcriptomes, epigenetics and underlying gene regulatory networks. There is evidence that post-transcriptional processes such as signaling, adhesion, protein turnover and post translational modifications make a significant contribution to regulating the balance between self-renewal and differentiation, and it is therefore necessary to also characterize ES cells at the protein level. In this experiment, we used a workflow termed hyperLOPIT (hyperplexed localization of organelle proteins by isotope tagging) to characterize the subcellular distribution of proteins in a population of self-renewing E14TG2a mouse ES cells. Over 5,000 protein groups were quantified in both of the two replicates, enabling characterization of protein localization to organelles (including sub-nuclear resolution), cell surface, cytoskeleton and cytosol. The steady-state localization of transitory proteins, protein complex constituents, and signaling cascades could also be mapped.

INSTRUMENT(S): Orbitrap Fusion

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Stem Cell, Cell Culture

SUBMITTER: Andy Christoforou  

LAB HEAD: Kathryn S. Lilley

PROVIDER: PXD001279 | Pride | 2016-01-14

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
Replicate1.pep.xml Pepxml
Replicate1_fraction1.msf Msf
Replicate1_fraction1.raw Raw
Replicate1_fraction10.msf Msf
Replicate1_fraction10.raw Raw
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Publications


Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to  ...[more]

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