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<p>Mass spectrometry imaging (MSI) is a powerful analytical technique suited for simultaneously measuring and assigning functional roles of multiple analytes directly from intact tissue sections. MSI acquisitions often lead to highly complex datasets with numerous isobaric species. Ion mobility (IM) spectrometry crucially helps to unravel these datasets by providing an orthogonal separation thus supplementing the lack of chromatographic separation in MSI. However, the rich, multidimensional data produced by IM-MSI investigations, combined with the lack of comprehensive software solutions that support the entire data analysis workflow, poses a major challenge preventing IM-MSI full exploitation. Here, we discuss the benefits and challenges of IM-MSI data analysis in metabolomic applications. Finally, Pyxis, a novel, vendor-neutral IT solution for IM-MSI data analysis, is introduced and its capabilities demonstrated on mouse kidney tissue and THP-1 monocytes data.</p> Graphical Abstract <p></p>

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Advancing spatial-omics through Pyxis, vendor-neutral software for ion mobility mass spectrometry imaging data analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月20日

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  • Sara Tortorella,
  • Sebastian Bessler,
  • Giuseppe Arturi,
  • Giulia Sorbi,
  • Jens Soltwisch,
  • Gabriele Cruciani

摘要

Mass spectrometry imaging (MSI) is a powerful analytical technique suited for simultaneously measuring and assigning functional roles of multiple analytes directly from intact tissue sections. MSI acquisitions often lead to highly complex datasets with numerous isobaric species. Ion mobility (IM) spectrometry crucially helps to unravel these datasets by providing an orthogonal separation thus supplementing the lack of chromatographic separation in MSI. However, the rich, multidimensional data produced by IM-MSI investigations, combined with the lack of comprehensive software solutions that support the entire data analysis workflow, poses a major challenge preventing IM-MSI full exploitation. Here, we discuss the benefits and challenges of IM-MSI data analysis in metabolomic applications. Finally, Pyxis, a novel, vendor-neutral IT solution for IM-MSI data analysis, is introduced and its capabilities demonstrated on mouse kidney tissue and THP-1 monocytes data.

Graphical Abstract