Dataset Information

Quantitative Measurement of Transthyretin Mistargeting by Proximity Labeling and Parallel Reaction Monitoring.

ABSTRACT: Proximity labeling is a powerful approach for characterizing subcellular proteomes. We recently demonstrated that proximity labeling can be used to identify mistrafficking of secretory proteins, such as occurs during pre-emptive quality control (pre-QC) following endoplasmic reticulum (ER) stress. This assay depends on protein quantification by immunoblotting and densitometry, which sometimes suffers from poor sensitivity. Here, we integrate parallel reaction monitoring (PRM) mass spectrometry to enable a more quantitative platform, and assess how chemical ER stressors impact pre-QC of the model secretory protein transthyretin in HEK293T cells. We find that some drug treatments affect labeling efficiency, which can be controlled for by normalizing to APEX2 auto-labeling. While some chemical ER stress inducers including Brefeldin A and thapsigargin induce pre-QC, tunicamycin and dithiothreitol do not, indicating ER stress alone is not sufficient. This finding contrasts with the canonical model of pre-QC induction, and establishes the utility of our platform.

SUBMITTER: Lyu Z

PROVIDER: S-EPMC10764115 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Quantitative Measurement of Transthyretin Mistargeting by Proximity Labeling and Parallel Reaction Monitoring.

Lyu Ziqi Z Genereux Joseph C JC

Frontiers in chemical biology 20231109

Proximity labeling is a powerful approach for characterizing subcellular proteomes. We recently demonstrated that proximity labeling can be used to identify mistrafficking of secretory proteins, such as occurs during pre-emptive quality control (pre-QC) following endoplasmic reticulum (ER) stress. This assay depends on protein quantification by immunoblotting and densitometry, which sometimes suffers from poor sensitivity. Here, we integrate parallel reaction monitoring (PRM) mass spectrometry t ...[more]

PMID: 38173467

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Project description:High-density lipoprotein (HDL), a lipid nanoparticle containing many different low abundance proteins, is an attractive target for clinical proteomics because its compositional heterogeneity is linked to its cardioprotective effects. Selected reaction monitoring (SRM) is currently the method of choice for targeted quantification of proteins in such a complex biological matrix. However, model system studies suggest that parallel reaction monitoring (PRM) is more specific than SRM because many product ions can be used to confirm the identity of a peptide. We therefore compared PRM and SRM for their abilities to quantify proteins in HDL, using (15)N-labeled apolipoprotein A-I (HDL's most abundant protein) as the internal standard. PRM and SRM exhibited comparable linearity, dynamic range, precision, and repeatability for protein quantification of HDL. Moreover, the single internal standard protein performed as well as protein-specific peptide internal standards when quantifying 3 different proteins. Importantly, PRM and SRM yielded virtually identical quantitative results for 26 proteins in HDL isolated from 44 subjects. Because PRM requires less method development than SRM and is potentially more specific, our observations indicate that PRM in concert with a single isotope-labeled protein is a promising new strategy for quantifying HDL proteins in translational studies.Biological significanceHDL, a complex matrix composed of lipids and proteins, is implicated in cardioprotection. Its cholesterol content correlates inversely with cardiovascular disease and it is the current metric to assess cardiovascular risk. However, the cholesterol content does not capture HDL's complexity and heterogeneity. Devising metrics that better capture HDL's cardioprotective effects, we developed an optimized method for quantification of HDL proteome, using PRM in concert with a single labeled protein as internal standard. The availability of a method that increases sample throughput without compromising the reproducibility, sensitivity, and accuracy could therefore point to better risk assessment for CVD or other diseases.

Dataset Information

Quantitative Measurement of Transthyretin Mistargeting by Proximity Labeling and Parallel Reaction Monitoring.

Publications

Quantitative Measurement of Transthyretin Mistargeting by Proximity Labeling and Parallel Reaction Monitoring.

Similar Datasets

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