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High-Performance Liquid Chromatography: Instrumentation

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Related Experiment Video

Updated: May 12, 2026

Automated 90Sr Separation and Preconcentration in a Lab-on-Valve System at Ppq Level

Automated ⁹⁰Sr Separation and Preconcentration in a Lab-on-Valve System at Ppq Level

Published on: June 6, 2018

Automated quality control system for LC-SRM setups.

Johan Teleman¹, Sofia Waldemarson, Johan Malmström

¹Department of Immunotechnology, Lund University, BMC D13, 22184 Lund, Sweden.

Journal of Proteomics

|April 16, 2013

Summary

This summary is machine-generated.

A new quality control workflow and software enhance Selected Reaction Monitoring (SRM) protein quantification. This system monitors instrument performance, ensuring reliable and reproducible results for proteomics labs.

Keywords:

Mass spectrometry Quality control Selected reaction monitoring Software Targeted proteomics

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Last Updated: May 12, 2026

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Published on: May 7, 2018

Area of Science:

Proteomics
Analytical Chemistry
Biotechnology

Background:

Selected Reaction Monitoring (SRM) is a key technique for high-throughput protein quantification.
Ensuring stable system performance is critical for reliable SRM results.
Current methods lack automated monitoring for Liquid Chromatography-SRM (LC-SRM) setups.

Purpose of the Study:

To present a quality control workflow for monitoring SRM system performance.
To introduce automated software for assessing system stability.
To improve the reliability and quality of SRM-based protein quantification.

Main Methods:

Developed a quality control workflow using repeated analysis of a standard sample.
Created automated software to monitor signal intensities and retention time stability.
Evaluated the software using 407 repeated injections over six months.

Main Results:

Identified outliers in relative peptide signal intensities and fragment ratios.
Detected deviations indicating a need for instrument maintenance.
Demonstrated the software's ability to provide insight into SRM setup stability.

Conclusions:

The presented workflow and software enable automated monitoring of LC-SRM systems.
This approach enhances the reliability and quality of SRM protein quantification.
The tools are vital for labs performing regular SRM analysis, strengthening SRM's role in proteomics.