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A "Quenchergenic" Chemoselective Protein Labeling Strategy.

ABSTRACT: Dynamic changes in protein structure can be monitored by using a fluorescent probe and a dark quencher. This approach is contingent upon the ability to precisely introduce a fluorophore/quencher pair into two specific sites of a protein of interest. Despite recent advances, there is continued demand for new and convenient approaches to site-selectively label proteins with such optical probes. We have recently developed a chemoselectively rapid azo-coupling reaction (CRACR) for site-specific protein labeling; it relies on rapid coupling between a genetically encoded 5-hydroxytryptophan residue and various aromatic diazonium ions. Herein, it is reported that the product of this conjugation reaction, a highly chromophoric biarylazo group, is a potent fluorescence quencher. The absorption properties of this azo product can be tuned by systematically altering the structure of the aryldiazonium species. A particular "quenchergenic" aryldiazonium has been identified that, upon conjugation, efficiently quenches the fluorescence of green fluorescent protein, which is a widely used genetically encoded fluorescent probe that can be terminally attached to target proteins. This fluorophore/quencher pair was used to evaluate the protein-labeling kinetics of CRACR, as well as to monitor the proteolysis of a fusion protein.

SUBMITTER: Addy PS

PROVIDER: S-EPMC6663590 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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A "Quenchergenic" Chemoselective Protein Labeling Strategy.

Addy Partha Sarathi PS Zheng Yunan Y Italia James S JS Chatterjee Abhishek A

Chembiochem : a European journal of chemical biology 20190503 13

Dynamic changes in protein structure can be monitored by using a fluorescent probe and a dark quencher. This approach is contingent upon the ability to precisely introduce a fluorophore/quencher pair into two specific sites of a protein of interest. Despite recent advances, there is continued demand for new and convenient approaches to site-selectively label proteins with such optical probes. We have recently developed a chemoselectively rapid azo-coupling reaction (CRACR) for site-specific prot ...[more]

PMID: 30740850

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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 630?erm 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

A "Quenchergenic" Chemoselective Protein Labeling Strategy.

Publications

A "Quenchergenic" Chemoselective Protein Labeling Strategy.

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