Dataset Information

Maximally-multiplexed proteome quantification platform for isotopic metabolic and chemical labeling

ABSTRACT: Quantitative proteomic platforms based on precursor intensity in mass spectrometry (MS1-level) uniquely support in vivo metabolic labeling with superior quantification accuracy but suffers from limited multiplexity (≤3-plex) and frequent missing quantities. Herein, we present a maximally-multiplexed MS1-level quantification platform that comprises new six-plex in vivo SILAC or in vitro di-ethylation with a dedicated algorithm. We demonstrate accurate and missing quantity-free quantification of highly complex samples with broad dynamic ranges. With our platform, we globally profile the proteome dynamics under the heat shock response of HeLa cells.

INSTRUMENT(S): Orbitrap Fusion Lumos, Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Epithelial Cell, Cell Culture

DISEASE(S): Cervix Carcinoma

SUBMITTER: Yeon Choi

LAB HEAD: Jong-Seo Kim

PROVIDER: PXD009952 | Pride | 2020-03-19

REPOSITORIES: Pride

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Publications

MS1-Level Proteome Quantification Platform Allowing Maximally Increased Multiplexity for SILAC and In Vitro Chemical Labeling.

Choi Yeon Y Jeong Kyowon K Shin Sanghee S Lee Joon Won JW Lee Young-Suk YS Kim Sangtae S Kim Sun Ah SA Jung Jaehun J Kim Kwang Pyo KP Kim V Narry VN Kim Jong-Seo JS

Analytical chemistry 20200324 7

Quantitative proteomic platforms based on precursor intensity in mass spectrometry (MS1-level) uniquely support in vivo metabolic labeling with superior quantification accuracy but suffer from limited multiplexity (≤3-plex) and frequent missing quantities. Here we present a new MS1-level quantification platform that allows maximal multiplexing with high quantification accuracy and precision for the given labeling scheme. The platform currently comprises 6-plex in vivo SILAC or i ...[more]

PMID: 32167278

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Project description:The therapeutic benefits of L–3,4–dihydroxyphenylalanine (L-DOPA) in Parkinson’s disease (PD) patients severely diminishes with the onset of L-DOPA-induced dyskinesia (LID), a debilitating motor side effect. LID is mainly due to altered dopaminergic signaling in the striatum, a brain region that controls motor and cognitive functions. However, the molecular mechanisms that promote LID remain unclear. Here, we have reported that increased striatal RasGRP1 (also known as CalDAG-GEF-II) is instrumentally linked to the development of LID in a 6-hydroxydopamine (6-OHDA) lesioned mouse model of PD. L-DOPA treatment rapidly upregulated RasGRP1 in the dopamine-1 receptor positive neurons in the dorsal striatum. RasGRP1 deleted mice (RasGRP1–/–) had drastically diminished LID, and RasGRP1–/– mice did not interfere with the therapeutic benefits of L-DOPA. In terms of its mechanism, RasGRP1 mediated L-DOPA-induced extracellular regulated kinase (ERK), the mammalian target of rapamycin kinase (mTOR) and the cAMP/PKA pathway. RasGRP1 bind directly with and acts 2 as a guanine nucleotide exchange (GEF) for Ras-homolog-enriched in the brain (Rheb), a potent activator of mTOR, both in vitro and in the intact striatum. High-resolution tandem mass tag mass spectrometry analysis of striatal tissue revealed significant targets, such as phosphodiesterase 10a (Pde10a), Pde2a, catechol-o-methyltransferase (Comt), and glutamate decarboxylase 1 and 2 (Gad1 and Gad2), as downstream regulators of RasGRP1 that are linked to LID vulnerability. Moreover, we found that RASGRP1 protein is also upregulated predominantly in the striatum of MPTP-lesioned macaque treated with L-DOPA, emphasizing the translational potential of this protein. Collectively, the findings of this study demonstrated that RasGRP1 is a major regulator of LID in the dorsal striatum. Pharmacological or gene-depletion strategies targeting RasGRP1 may offer novel therapeutic opportunities for preventing LID in PD patients.

Project description:Measuring the properties of endogenous cell proteins, such as expression level, subcellular localization and turnover rates, on a whole proteome level remains a major challenge in the post-genome era. Quantitative methods for measuring mRNA expression do not reliably predict corresponding protein levels and provide little or no information on other protein properties. Here we describe a combined pulse-labelling, spatial proteomics and data analysis strategy to characterize the expression, localization, synthesis, degradation and turnover rates of endogenously expressed, untagged human proteins in different subcellular compartments. Using quantitative mass spectrometry and SILAC, a total of 80,098 peptides from 8,041 HeLa proteins were quantified, and their spatial distribution between the cytoplasm, nucleus and nucleolus determined and visualised using specialised software tools developed in PepTracker. Using information from ion intensities and rates of change in isotope ratios, protein abundance levels and protein synthesis, degradation and turnover rates were calculated for the whole cell and for the respective cytoplasmic, nuclear and nucleolar compartments. Expression levels of endogenous HeLa proteins varied by up to seven orders of magnitude. The average turnover rate for HeLa proteins was approximately 20 hours. Turnover rate did not correlate with either molecular weight or net charge, but did correlate with abundance, with highly abundant proteins showing longer than average half-lives. Fast turnover proteins had overall a higher frequency of PEST motifs than slow turnover proteins but no general correlation was observed between amino or carboxy terminal amino acid identities and turnover rates. A subset of proteins was identified that exist in pools with different turnover rates depending on their subcellular localization. This strongly correlated with subunits of large, multi-protein complexes, suggesting a general mechanism whereby their assembly is controlled in a different subcellular location to their main site of function.

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Dataset Information

Maximally-multiplexed proteome quantification platform for isotopic metabolic and chemical labeling

Publications

MS1-Level Proteome Quantification Platform Allowing Maximally Increased Multiplexity for SILAC and <i>In Vitro</i> Chemical Labeling.

Similar Datasets

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