On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging

Steffen Heuckeroth, Arne Behrens, Carina Wolf, Arne Fütterer, Ilona D. Nordhorn, Katharina Kronenberg, Corinna Brungs, Ansgar Korf, Henning Richter, Astrid Jeibmann, Uwe Karst and Robin Schmid ()
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Steffen Heuckeroth: University of Münster
Arne Behrens: Bruker Daltonics GmbH & Co. KG
Carina Wolf: University of Münster
Arne Fütterer: Bruker Daltonics GmbH & Co. KG
Ilona D. Nordhorn: University of Münster
Katharina Kronenberg: University of Münster
Corinna Brungs: Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences
Ansgar Korf: Bruker Daltonics GmbH & Co. KG
Henning Richter: University of Zurich
Astrid Jeibmann: University Hospital Münster
Uwe Karst: University of Münster
Robin Schmid: Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

Date: 2023
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DOI: 10.1038/s41467-023-43298-9

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