The user can customize the colors displayed for different types of signals: match (shifted or non-shifted), mismatch, metabolite match, or unassigned m/z. The colors assigned to each signal type are also kept in the report analysis.
The user can draw new metabolites or product chemical structures and validate them by comparing the virtual fragmentation of the compounds with the spectral information extracted from the peak. This functionality can also be applied to manually generated compounds during the new peak generation workflow in the Chromatogram Browser.
An automatic compound set is defined during the SDF file import process. When chemical structures are imported into the Compound Library, the compound set is established, enabling users to perform various predictions—such as MetaSite fragmentation, and model predictions—directly on the generated compound set. This minimizes the time required to obtain results.
August 13, 2024
Jayden C. McKinnon, Rachelle Balez, Reuben S.E. Young, Mikayla L. Brown, Jeremy S. Lum, Liam Robinson, Mikhail E. Belov, Lezanne Ooi, Sara Tortorella, Todd W. Mitchell, Shane R. Ellis*
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) can provide valuable insights into the metabolome of complex biological systems such as organ tissues and cells. However, obtaining metabolite data at single-cell spatial resolutions presents a few technological challenges. Generally, spatial resolution is defined by the increment the sample stage moves between laser ablation spots. Stage movements less than the diameter of the focused laser beam (i.e., oversampling) can improve spatial resolution; however, such oversampling conditions result in a reduction in sensitivity. To overcome this, we combine an oversampling approach with laser postionization (MALDI-2), which allows for both higher spatial resolution and improved analyte ionization efficiencies. This approach provides significant enhancements to sensitivity for various metabolite classes (e.g., amino acids, purines, carbohydrates etc.), with mass spectral intensities from 6 to 8 μm pixel sizes (from a laser spot size of ∼13 μm) being commensurate with or higher than those obtained by conventional MALDI at 20 μm pixel sizes for many different metabolites. This technique has been used to map the distribution of metabolites throughout mouse spinal cord tissue to observe how metabolite localizations change throughout specific anatomical regions, such as those distributed to the somatosensory area of the dorsal horn, white matter, gray matter, and ventral horn. Furthermore, this method is utilized for single-cell metabolomics of human iPSC-derived astrocytes at 10 μm pixel sizes whereby many different metabolites, including nucleotides, were detected from individual cells while providing insight into cellular localizations.
© 2024 American Society for Mass Spectrometry. Published by American Chemical Society. All rights reserved.
72nd ASMS Conference on Mass Spectrometry. June 2024
Introduction
Single-cell metabolomics and lipidomics using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI MSI) is emerging as an exciting tool to study metabolic alterations across heterogeneous cell populations. Single-cell analysis using MALDI MSI does however come with technical challenges, including sample preparation workflows compatible with fluorescent microscopy and downstream MS analysis, as well as dedicated data processing workflow to coregister microscopy with MSI and extract profiles from defined cells for later analysis. Here, we introduce an efficient single-cell MSI data analysis pipeline utilising the cutting-edge Pyxis software platform. The performance and versatility of the pipeline are demonstrated by single-cell lipidomics and metabolomics analysis of human-derived astrocytes, unravelling intricate molecular insights at the single-cell level.
Methods
Human astrocytes were generated using induced pluripotent stem cell-derived neurons. Live astrocyte cultures were stained with CellBrite Green and Hoechst, fixed with PFA and washed with cold ammonium acetate prior to microscopy. Following microscopy cells were coated in 2,5-DHA matrix via sublimation for lipid imaging or NEDC matrix using a HTC TM-Sprayer for metabolite imaging for MALDI and MALDI-2 analysis, respectively, using an Orbitrap Elite coupled to a Spectroglyph MALDI/ESI ion source (Spectroglyph LLC, Kennewick, WA, USA). Coregistration with microscopy, segmentation at single-cell level, extraction of spectra generated from single cells, and dedicated statistics to process single-cell spectra were performed using Pyxis (Mass Analytica, Spain). Features of interest were annotated using HMDB and LIPID MAPS databases integrated in Pyxis.
Preliminary data
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