MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments

Author:

Morosi Lavinia1,Miotto Matteo1,Timo Sara1,Carloni Sara12,Bruno Eleonora3,Meroni Marina4,Menna Elisabetta15,Lodato Simona12,Rescigno Maria12,Martano Giuseppe15ORCID

Affiliation:

1. IRCCS Humanitas Research Hospital , Via Manzoni 56, Rozzano (MI) , Italy

2. Department of Biomedical Sciences, Humanitas University , Via R. Levi Montalcini 4, Pieve Emanuele (MI) , Italy

3. Department of Experimental Oncology, Fondazione IRCCS Istituto Nazionale dei tumori di Milano . Via Venezian 1, Milan, Italy

4. Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Oncology , via Mario Negri 2, Milan , Italy

5. Institute of Neuroscience, National Research Council of Italy (CNR) c/o Humanitas Mirasole S.p.A , Via Manzoni 56, Rozzano (MI) , Italy

Abstract

Abstract Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.

Funder

IRCCS Humanitas Research Hospital Metabolomics

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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