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Introducing FISCAS, a Tool for the Effective Generation of Single Cell MALDI-MSI Data. | LitMetric

AI Article Synopsis

  • The Fluorescence Integrated Single-Cell Analysis Script (FISCAS) merges fluorescence microscopy with MALDI mass spectrometry imaging (MALDI-MSI) to enhance single-cell analysis by auto-selecting measurement regions and minimizing off-target data.
  • FISCAS applies MALDI-compatible staining to identify membranes, nuclei, and lipid droplets, which allows for the quick collection of fluorescence data before mass spectrometry measurements on stimulated THP-1 cells at various time points.
  • The results reveal significant molecular diversity among individual cells during differentiation into macrophages, highlighting a more detailed analysis of the differentiation phases and potential lipid markers, which showcases the benefits of combining mass spectrometry with fluorescence data.

Article Abstract

We introduce Fluorescence Integrated Single-Cell Analysis Script (FISCAS), which combines fluorescence microscopy with MALDI-MSI to streamline single-cell analysis. FISCAS enables automated selection of tight measurement regions, thereby reducing the acquisition of off-target pixels, and makes use of established algorithms for cell segmentation and coregistration to rapidly compile single-cell spectra. MALDI-compatible staining of membranes, nuclei, and lipid droplets allows the collection of fluorescence data prior to the MALDI-MSI measurement on a timsTOF fleX MALDI-2. Usefulness of the software is demonstrated by the example of THP-1 cells during stimulated differentiation into macrophages at different time points. In this proof-of-principle study, FISCAS was used to automatically generate single-cell mass spectra along with a wide range of morphometric parameters for a total number of roughly 1300 cells collected at 24, 48, and 72 h after the onset of stimulation. Data analysis of the combined morphometric and single-cell mass spectrometry data shows significant molecular heterogeneity within the cell population at each time point, indicating an independent differentiation of each individual cell rather than a synchronized mechanism. Here, the grouping of cells based on their molecular phenotype revealed an overall clearer distinction of the different phases of differentiation into macrophages and delivered an increased number of lipid signals as possible markers compared with traditional bulk analysis. Utilizing the linkage between mass spectrometric data and fluorescence microscopy confirmed the expected positive correlation between lipid droplet staining and the overall signal for triacylglyceride (TG), demonstrating the usefulness of this multimodal approach.

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Source
http://dx.doi.org/10.1021/jasms.4c00279DOI Listing

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