Label-Free Multiple Reaction Monitoring–Mass\nSpectrometry for Quantifying Phosphopeptides from Extracellular Vesicles

Increasing\nefforts have been made to develop proteins in circulating\nextracellular vesicles (EVs) as potential disease markers. It is in\nparticular intriguing to measure post-translational modifications\n(PTMs) such as phosphorylation, preserved and stable in EVs. To facilitate\nthe quantitative measurement of EV protein phosphorylation for potential\nclinical use, a label-free (LF) multiple reaction monitoring (MRM)\nstrategy is introduced by utilizing a synthetic phosphopeptide set\n(phos-iRT) as the internal standards and a local normalization method.\nThe quantitation method was investigated in terms of its linear dynamic\nrange, sensitivity, accuracy, precision, and matrix effect, with a\ndynamic range spanning from 10 to 1000 ng/mL and an accuracy ranging\nfrom 82.4 to 116.8% for EV samples. Then, the LF-MRM-based local normalization\nmethod was utilized to evaluate and optimize our recently developed\nEVTOP method for the enrichment of phosphopeptides from EVs. Finally,\nwe applied the optimized EV enrichment approach and the LF-MRM-based\nlocal normalization method to quantify phosphopeptides in urine EVs\nfrom patients with prostate cancer (PCa) and healthy individuals,\nshowcasing the strategy’s superiority in quantifying phosphopeptides\nwithout isotopic internal standards and validating that the method\nis generally applicable in MRM-based EV phosphopeptide quantification.

Publication Details

Journal
Figshare
Published
2024-09-12
DOI
https://doi.org/10.1021/acs.analchem.4c03492.s001
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Label-Free Multiple Reaction Monitoring–Mass\nSpectrometry for Quantifying Phosphopeptides from Extracellular Vesicles

Figshare
Extracellular vesicles in disease
article

Label-Free Multiple Reaction Monitoring–Mass\nSpectrometry for Quantifying Phosphopeptides from Extracellular Vesicles

article en

Abstract

Increasing\nefforts have been made to develop proteins in circulating\nextracellular vesicles (EVs) as potential disease markers. It is in\nparticular intriguing to measure post-translational modifications\n(PTMs) such as phosphorylation, preserved and stable in EVs. To facilitate\nthe quantitative measurement of EV protein phosphorylation for potential\nclinical use, a label-free (LF) multiple reaction monitoring (MRM)\nstrategy is introduced by utilizing a synthetic phosphopeptide set\n(phos-iRT) as the internal standards and a local normalization method.\nThe quantitation method was investigated in terms of its linear dynamic\nrange, sensitivity, accuracy, precision, and matrix effect, with a\ndynamic range spanning from 10 to 1000 ng/mL and an accuracy ranging\nfrom 82.4 to 116.8% for EV samples. Then, the LF-MRM-based local normalization\nmethod was utilized to evaluate and optimize our recently developed\nEVTOP method for the enrichment of phosphopeptides from EVs. Finally,\nwe applied the optimized EV enrichment approach and the LF-MRM-based\nlocal normalization method to quantify phosphopeptides in urine EVs\nfrom patients with prostate cancer (PCa) and healthy individuals,\nshowcasing the strategy’s superiority in quantifying phosphopeptides\nwithout isotopic internal standards and validating that the method\nis generally applicable in MRM-based EV phosphopeptide quantification.

Figshare
Openalex Percentile: Top 70%
Extracellular vesicles in disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.