From life cell imaging to single cell metabolomics – Multimodal imaging bridging fluorescence microscopy and mass spectrometry imaging

Session

Session 1 - Multimodal Imaging including Correlative

Authors

Maria Sievers (1), Mohanad Ridha (1), Jens Wittner (1), Judith Neumann (1), Hanna Bednarz (1), Karsten Niehaus (1)

Affiliations

1. Bielefeld University

Keywords

life cell imaging, mass spectrometry imaging, single cell metabolomics, multimodal imaging, multi channel images 

Abstract text

Life cell imaging is a well-established field to characterize biological functions of target cells and tissues on the single cell level and beyond using fluorescence microscopy. Beside fluorescent dyes that stain compartments of living cells (e.g. nucleus, mitochondria, membranes, ER, Golgi, Lysosomes, etc.), fluorescent molecular probes allow to visualize and quantify biological activities (e.g. mitochondrial activity, ion-concentrations, dynamics of the cytoskeleton). Recent approaches use multiple dyes to stain cells and use artificial intelligence (AI) to characterize cellular responses. Additionally, Mass spectrometry imaging (MSI), established about 20 years ago, opened the possibility to localize small molecules in thin sections of tissues. The widely used MALDI-based MSI reaches spatial resolutions below 5 µm, allowing to analyze single cells out of cell cultures. 

Here we present a multimodal approach that combines life cell imaging and MSI. Cell cultures (melanoma cells, macrophages) are monitored over time by fluorescence microscopy. As an endpoint determination the identical cells were analyzed by MSI resulting in the identification of up to 100 metabolites per single cell. We established a pipeline to analyze the multimodal datasets using common software tools (FiJi, CellProfiler, QuPath, SCILS). Beside melanoma cell cultures an infection assay using the bacterial intracellular pathogen Listeria monocytogenes and RAW-macrophages will be presented.  Functional fluorescence imaging of living cells and single cell metabolomics can be combined to better understand biological processes of individual cells.

Single-cell analysis of the metabolite taurine for Ma-Mel-86c. (A) Brightfield image. (B) The Bisbenzimide channel was declared as cell seed (green) for a region-growing algorithm (watershed) to detect cell boundaries (magenta). (C) Upon cellular segmentation, an individual number is assigned to each cell. (D) Ion distribution image of taurine (m/z 124.0066) exported from SCiLS. (E) Overlay of ion image with segmentation mask in CellProfiler and display of color-coded cellular mean intensity of taurine. (F) Single-cell data: mean intensity of taurine for selected cells. Scale bar: 200 μm (100 μm for zoomed-in area). 

References

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