Dataset Information

¹⁵N Metabolic Labeling Quantification Workflow in Arabidopsis Using Protein Prospector.

ABSTRACT: Metabolic labeling using stable isotopes is widely used for the relative quantification of proteins in proteomic studies. In plants, metabolic labeling using ¹⁵N has great potential, but the associated complexity of data analysis has limited its usage. Here, we present the ¹⁵N stable-isotope labeled protein quantification workflow utilizing open-access web-based software Protein Prospector. Further, we discuss several important features of ¹⁵N labeling required to make reliable and precise protein quantification. These features include ratio adjustment based on labeling efficiency, median and interquartile range for protein ratios, isotope cluster pattern matching to flag incorrect monoisotopic peak assignment, and caching of quantification results for fast retrieval.

SUBMITTER: Shrestha R

PROVIDER: S-EPMC8885517 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

15N Metabolic Labeling Quantification Workflow in Arabidopsis Using Protein Prospector.

Shrestha Ruben R Reyes Andres V AV Baker Peter R PR Wang Zhi-Yong ZY Chalkley Robert J RJ Xu Shou-Ling SL

Frontiers in plant science 20220215

Metabolic labeling using stable isotopes is widely used for the relative quantification of proteins in proteomic studies. In plants, metabolic labeling using 15N has great potential, but the associated complexity of data analysis has limited its usage. Here, we present the 15N stable-isotope labeled protein quantification workflow utilizing open-access web-based software Protein Prospector. Further, we discuss several important features of 15N labeling required t ...[more]

PMID: 35242158

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Project description:Clostridioides difficile (formerly Clostridium difficile) is a Gram-positive, anaerobe, spore-forming pathogen, which causes drug-induced diseases in hospitals worldwide. A detailed analysis of the proteome may provide new targets for drug development or therapeutic strategies to combat this pathogen. The application of metabolic labeling (ML) would allow for accurate quantification of significant differences in protein abundance, even in the case of very small changes. Additionally, it would be possible to perform more accurate studies of the membrane or surface proteomes, which usually require elaborated sample preparation. Such studies are therefore prone to higher standard deviations during the quantification. The implementation of ML strategies for C. difficile is complicated due to the lack in arginine and lysine auxotrophy as well as the Stickland dominated metabolism of this anaerobic pathogen. Hence, quantitative proteome analyses could only be carried out by label free or chemical labeling methods so far. In this paper, a ML approach for C. difficile is described. A cultivation procedure with 15N-labeled media for strain 630Δerm was established achieving an incorporation rate higher than 97%. In a proof-of-principle experiment, the performance of the ML approach in C. difficile was tested. The proteome data of the cytosolic subproteome of C. difficile cells grown in complex medium as well as two minimal media in the late exponential and early stationary growth phase obtained via ML were compared with two label free relative quantification approaches (NSAF and LFQ). The numbers of identified proteins were comparable within the three approaches, whereas the number of quantified proteins were between 1,110 (ML) and 1,861 (LFQ) proteins. A hierarchical clustering showed clearly separated clusters for the different conditions and a small tree height with ML approach. Furthermore, it was shown that the quantification based on ML revealed significant altered proteins with small fold changes compared to the label free approaches. The quantification based on ML was accurate, reproducible, and even more sensitive compared to label free quantification strategies.

Dataset Information

¹⁵N Metabolic Labeling Quantification Workflow in Arabidopsis Using Protein Prospector.

Publications

<sup>15</sup>N Metabolic Labeling Quantification Workflow in Arabidopsis Using Protein Prospector.

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