Dataset Information

GwAAP: A Genome-wide Amino Acid coding-decoding quantitative Proteomic system

ABSTRACT: GwAAP: A Genome-wide Amino Acid coding-decoding quantitative Proteomic system was designed in which each protein could be assigned with a distinct code. Using synthetic biology technology, the amino acids codes were coded in N terminal of the corresponding proteins in the genome of yeast (Saccharomyces cerevisiae), so that the copy number of the code sequences were identical with the targeted proteins in yeast. The code sequences were enriched by HA antibody and decoded and quantified by mass spectrometry strategy. In general, this method increased the detection sensitivity by peptide enrichment, which reduced the dynamic range and the complexity of proteomics. In addition, coding sequence with similar physical and chemical properties resulted in the comparable linear signal response of the mass spectrum, which significantly improve the accuracy of proteomic quantification.

ORGANISM(S): Saccharomyces Cerevisiae

SUBMITTER: Fuchu He

PROVIDER: PXD023100 | iProX | Wed Dec 22 00:00:00 GMT 2021

REPOSITORIES: iProX

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Publications

GwAAP: A genome-wide amino acid coding-decoding quantitative proteomics system.

Cheng Li L Yue Xuetong X Qin Zhaoyu Z Sun Xiaogang X He Fuchu F Dai Junbiao J Ding Chen C

iScience 20221102 12

Mass spectrometry-based proteomic technology has greatly improved and has been widely applied in various biological science fields. However, proteome-wide accurate quantification of proteins in signaling pathways remains challenging. Here, we report a genome-wide amino acid coding-decoding quantitative proteomic (GwAAP) system to facilitate precise proteome quantification. For each protein, a unique code peptide was assigned and incorporated into the N-terminus of the targeted protein and used f ...[more]

PMID: 36465122

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Project description:Saccharomyces cerevisiae is unique among yeasts for its ability to grow rapidly in the complete absence of oxygen. S. cerevisiae is therefore an ideal eukaryotic model to study physiological adaptation to anaerobiosis. Recent transcriptome analyses have identified hundreds of genes that are transcriptionally regulated by oxygen availability but the relevance of this cellular response has not been systematically investigated at the key control level of the proteome. Therefore, the proteomic response of the S. cerevisiae to anaerobiosis was investigated using metabolic stable isotope labeling in aerobic and anaerobic glucose-limited chemostat cultures, followed by proteome analysis to relatively quantify protein expression. Using independent replicate cultures and stringent statistical filtering, a robust dataset of 474 quantified proteins was generated, of which 249 showed differential expression levels. While some of these changes were consistent with previous transcriptome studies, many responses of S. cerevisiae to oxygen availability were hitherto unreported. Comparison of transcriptome and proteome from identical cultivations yielded strong evidence for post-transcriptional regulation of key cellular processes, including glycolysis, amino-acyl tRNA synthesis, purine-nucleotide synthesis and amino-acid biosynthesis. The use of chemostat cultures provided well-controlled and reproducible culture conditions, which are essential for generating robust datasets at different cellular information levels. Integration of transcriptome and proteome data led to new insights in the physiology of anaerobically growing yeast that would not have been apparent from differential analyses at either the messenger RNA or protein level alone, thus illustrating the power of multi-level studies in yeast systems biology. Protein levels versus transcript level: Systematic analysis of the control levels at which the yeast response to anaerobiosis takes place was performed using previously published transcript data obtained from yeast cultures grown under strictly identical conditions as described for the current proteome analysis. Affymetrix microarrays from five aerobic and four anaerobic independent culture replicates were used for this analysis. These comparison data are summarized in the table below. These array data are publicly available at the gene expression repository Gene Expression Omnibus under accession number GSE4804. Keywords: proteomic, nanoflow-LC-MS/MS

Dataset Information

GwAAP: A Genome-wide Amino Acid coding-decoding quantitative Proteomic system

Publications

GwAAP: A genome-wide amino acid coding-decoding quantitative proteomics system.

Similar Datasets

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