msiFlow: automated workflows for reproducible and scalable multimodal mass spectrometry imaging and microscopy data analysis.

Spangenberg P; Bessler S; Widera L; Bottek J; Richter M; Thiebes S; Siemes D; Krauß SD; Migas LG; Kasarla SS; Phapale P; Kleesiek J; Führer D; Moeller LC; Heuer H; Van de Plas R; Gunzer M; Soehnlein O; Soltwisch J; Shevchuk O; Dreisewerd K; Engel DR

Abstract

Multimodal imaging by matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI MSI) and microscopy holds potential for understanding pathological mechanisms by mapping molecular signatures from the tissue microenvironment to specific cell populations. However, existing software solutions for MALDI MSI data analysis are incomplete, require programming skills and contain laborious manual steps, hindering broadly applicable, reproducible, and high-throughput analysis to generate impactful biological discoveries. Here, we present msiFlow, an accessible open-source, platform-independent and vendor-neutral software for end-to-end, high-throughput, transparent and reproducible analysis of multimodal imaging data. msiFlow integrates all necessary steps from raw data import to analytical visualisation along with state-of-the-art and self-developed algorithms into automated workflows. Using msiFlow, we unravel the molecular heterogeneity of leukocytes in infected tissues by spatial regulation of ether-linked phospholipids containing arachidonic acid. We anticipate that msiFlow will facilitate the broad applicability of MSI in multimodal imaging to uncover context-dependent cellular regulations in disease states.