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Ion Mobility-Mass Spectrometry Imaging Workflow.

Daniela Mesa Sanchez1, Steve Creger1, Veerupaksh Singla2

  • 1Department of Chemistry, Purdue University, West Lafayette, Indiana 47906, United States.

Journal of the American Society for Mass Spectrometry
|August 26, 2020
PubMed
Summary
This summary is machine-generated.

We developed a new workflow and Python script (IM-MSIC) to visualize ion mobility-mass spectrometry imaging (IM-MSI) data. This open-access tool addresses a key bottleneck in analyzing complex biological tissue samples.

Keywords:
IM-QTOFimage processingion mobilitymass spectrometry imaging

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Area of Science:

  • Analytical Chemistry
  • Biotechnology
  • Computational Biology

Background:

  • Mass spectrometry imaging (MSI) provides label-free, spatially resolved analysis of biological tissues.
  • Coupling ion mobility (IM) separation with MSI enhances isobar separation and peak assignment confidence.
  • Increased accessibility of ion mobility-mass spectrometry imaging (IM-MSI) instruments highlights the need for robust data analysis software.

Purpose of the Study:

  • To present an open-access imaging workflow for visualizing IM-MSI data.
  • To develop a Python script (IM-MSIC) for data processing on the Agilent 6560 IM-MSI system.
  • To bridge the gap between untargeted feature detection and ion image generation for IM-MSI data.

Main Methods:

  • Development of the ion mobility-mass spectrometry image creation script (IM-MSIC) using Python.
  • Integration of Agilent Mass Hunter Mass Profiler for untargeted feature detection.
  • Utilization of MacCoss lab's Skyline software command-line interface for ion chronogram extraction and image generation.

Main Results:

  • Successful generation of drift time and mass-to-charge-selected ion images from IM-MSI data.
  • A streamlined workflow enabling visualization of IM-MSI data within a single user interface.
  • Demonstration of postprocessing capabilities using accompanying scripts.

Conclusions:

  • The presented workflow and IM-MSIC script effectively visualize IM-MSI data, addressing a critical bottleneck in the field.
  • The workflow is adaptable for data from various major instrument vendors, promoting broader adoption.
  • This open-access solution facilitates more confident peak assignments and analysis in IM-MSI experiments.