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Related Experiment Video

Updated: May 13, 2026

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Published on: March 14, 2013

Library dependent LC-MS/MS acquisition via mzAPI/Live.

James T Webber¹, Manor Askenazi, Scott B Ficarro

¹Department of Cancer Biology and Blais Proteomics Center, Dana-Farber Cancer Institute, Boston, MA 02215-5450, USA.

|March 5, 2013

Summary

This study introduces mzAPI/Live, an open-source Python framework for creating complex liquid chromatography-mass spectrometry (LC-MSn) acquisition methods. It enables real-time data analysis for biology-driven mass spectrometry.

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Published on: December 8, 2023

Area of Science:

Analytical Chemistry
Biochemistry
Computational Biology

Background:

Mass spectrometry (MS) is crucial for analyzing biological samples, but complex matrices and analyte ranges challenge comprehensive analysis.
Commercial mass spectrometers offer advanced control systems, yet their acquisition methods lack end-user customization beyond basic parameters.

Purpose of the Study:

To present mzAPI/Live, an open-source framework enabling custom LC-MS(n) acquisition method generation.
To demonstrate real-time tandem mass spectra assignment for adaptive data acquisition.

Main Methods:

Development of an open-source Python framework (mzAPI/Live) for creating complex LC-MS(n) methods.
Implementation of real-time tandem mass spectra assignment by querying NIST peptide libraries.

Main Results:

Users can generate arbitrarily complex LC-MS(n) acquisition methods using Python scripting.
Demonstrated real-time analyte structure determination and adaptive acquisition decisions during runs.

Conclusions:

mzAPI/Live offers unprecedented control for biology-driven MS data acquisition.
This framework empowers researchers with customizable and adaptive mass spectrometry workflows.