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Genome-scale proteome quantification by DEEP SEQ mass spectrometry.


ABSTRACT: Advances in chemistry and massively parallel detection underlie DNA-sequencing platforms that are poised for application in personalized medicine. In stark contrast, systematic generation of protein-level data lags well behind genomics in virtually every aspect: depth of coverage, throughput, ease of sample preparation and experimental time. Here, to bridge this gap, we develop an approach based on simple detergent lysis and single-enzyme digest, extreme, orthogonal separation of peptides and true nanoflow liquid chromatography-tandem mass spectrometry that provides high peak capacity and ionization efficiency. This automated, deep efficient peptide sequencing and quantification mass spectrometry platform provides genome-scale proteome coverage equivalent to RNA-seq ribosomal profiling and accurate quantification for multiplexed isotope labels. In a model of the embryonic to epiblast transition in murine stem cells, we unambiguously quantify 11,352 gene products that span 70% of Swiss-Prot and capture protein regulation across the full detectable range of high-throughput gene expression and protein translation.

SUBMITTER: Zhou F 

PROVIDER: S-EPMC3770533 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Genome-scale proteome quantification by DEEP SEQ mass spectrometry.

Zhou Feng F   Lu Yu Y   Ficarro Scott B SB   Adelmant Guillaume G   Jiang Wenyu W   Luckey C John CJ   Marto Jarrod A JA  

Nature communications 20130101


Advances in chemistry and massively parallel detection underlie DNA-sequencing platforms that are poised for application in personalized medicine. In stark contrast, systematic generation of protein-level data lags well behind genomics in virtually every aspect: depth of coverage, throughput, ease of sample preparation and experimental time. Here, to bridge this gap, we develop an approach based on simple detergent lysis and single-enzyme digest, extreme, orthogonal separation of peptides and tr  ...[more]

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