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MALDI-TOF Mass Spectrometry

MALDI-TOF Mass Spectrometry

Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...

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Updated: Mar 1, 2026

Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models

Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models

Published on: December 5, 2014

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling.

Troy J Comi¹, Elizabeth K Neumann¹, Thanh D Do¹

¹Department of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA.

Journal of the American Society for Mass Spectrometry

|June 9, 2017

Summary

This summary is machine-generated.

A new software, microMS, simplifies image-guided mass spectrometry (MS) for analyzing diverse samples like single cells and tissue sections. This tool enhances spatial targeting and profiling across multiple mass spectrometers.

Keywords:

Image-guided mass spectrometry MALDI SIMS Single cell analysis Software

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Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization IR-MALDESI

Whole-body Mass Spectrometry Imaging by Infrared Matrix-assisted Laser Desorption Electrospray Ionization IR-MALDESI

Published on: March 24, 2016

Area of Science:

Analytical Chemistry
Biotechnology
Microscopy

Background:

Image-guided mass spectrometry (MS) enables spatial analysis of biological samples.
Existing methods require complex workflows for target selection and MS analysis.
There is a need for user-friendly software to streamline this process.

Purpose of the Study:

To develop and present microMS, a software package for microscopy-guided mass spectrometry.
To simplify the selection and spatial targeting of samples for MS analysis.
To demonstrate the versatility of microMS across different mass spectrometry instruments.

Main Methods:

Development of a Python-based software package, microMS, with a graphical user interface.
Integration of microscopy image analysis for target selection and spatial localization.
Implementation of a flexible class hierarchy for compatibility with various MS systems.

Main Results:

microMS facilitates targeted profiling of diverse samples, including single cells and tissue sections.
The software simplifies the selection of analysis regions using various target patterns.
Demonstrated successful off-line analysis of single cells on three distinct mass spectrometers.

Conclusions:

microMS offers an intuitive and versatile platform for image-guided MS profiling.
The software enhances accessibility for novice users and integrates diverse MS systems.
microMS is freely available, supporting broader research in spatial omics.