Biology subjects

Soltwisch, J.

Publications and source records attributed to Soltwisch, J..

9 recordsLinked to original sources

bioRxiv2026

Tensile Expansion Mass Spectrometry for single cell metabolomics imaging

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) enables the spatial mapping of endogenous biomolecules within native biological specimens; however, it remains limited in achieving single-cell resolution. While advances in instrument modifications, computational processing methods, and tissue-based sample preparation have facilitated high lateral resolutions and cellular level imaging, resolving metabolic heterogeneity at the single-cell level remains challenging for users without specific expertise or custom instrumentation. Here, we present tensile expansion mass spectrometry (TExMS), a cost-effective approach for single-cell MALDI-MSI that is compatible with commercial MSI instrumentation. TExMS utilizes highly stretchable hydrogels as a substrate for live-cell seeding, attachment, and desiccation, avoiding the need for chemical fixation and enabling the retention of both intracellular and extracellular metabolites, including media-derived components that are lost during fixation and washing. We used TExMS to expand individual cells of a human high-grade serous ovarian cancer (HGSOC) cell line and spatially map their small molecule (<800 Da) production. TExMS enabled [~]4-fold linear expansion of the hydrogel, translating to a [~]1.7-fold increase in average cell area and [~]1.3-fold increase in nuclear area and resulting in improved lateral resolution of metabolite distributions. Benchmarking against other platforms for high resolution MALDI-MSI, TExMS offered comparable spatial resolution to microgrid-enabled MALDI-MSI with 15 to 20-fold shorter acquisition times. We then used TExMS to map numerous intermediates from glycolysis, the tricarboxylic acid (TCA) cycle, and amino acid biosynthesis and probe the effects of serum starvation conditions on metabolic flux through these pathways, demonstrating a powerful use case for single-cell MALDI-MSI through TExMS. Table of Contents (TOC) O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/745024v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@18f8c09org.highwire.dtl.DTLVardef@132bc4aorg.highwire.dtl.DTLVardef@1e7c2caorg.highwire.dtl.DTLVardef@a586cf_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

TSP1/TGF-β1 drives arachidonic acid metabolism to orchestrate neutrophil swarming

Neutrophil swarming has emerged as a conserved multicellular behaviour observed across tissues and pathological contexts. Yet, the molecular cues and the spatially coordinated cellular circuits that drive the process of neutrophil swarming leading to cluster formation remain poorly understood. Here, we combine spatial proteomics and lipid profiling in a model of urinary tract infection to define the epithelial-immune circuits driving neutrophil cluster formation. We identify thrombospondin-1 (TSP1)-mediated activation of transforming growth factor beta 1 (TGF-{beta}1) as key epithelial signal licensing neutrophil clustering and enhancing bacterial control. Spatial lipid analysis further reveals that TSP1/TGF-{beta}1 signalling locally activates arachidonic acid metabolism in epithelial neutrophils, with 5-lipoxygenase dependent leukotriene synthesis required for swarm formation and infection clearance. These findings uncover a spatially coordinated defence mechanism in which epithelial-derived TSP1/TGF-{beta}1 engages neutrophil lipid metabolism to orchestrate neutrophil swarming behaviour and reinforce antibacterial immunity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/688397v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@114ea92org.highwire.dtl.DTLVardef@345244org.highwire.dtl.DTLVardef@10520baorg.highwire.dtl.DTLVardef@1a7c0fe_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

immunology↗

bioRxiv2025

Vascular Basement Membrane Laminins Modulate Functional Zonation of Cerebral Microvessels

We investigated whether vascular basement membrane (BM) laminins influence vascular zonation by performing single-cell RNA sequencing on cerebral blood vessels from mice lacking the major vascular laminins in endothelial and smooth muscle BMs, laminin 4 (Lama4-/-) and laminin 5 (Tek-cre:Lama5-/-), and wild-type littermates. Our dataset expands existing cerebral vascular transcriptomic profiles and reveals that Lama4-/- endothelial cells exhibit increased arterial marker expression and reduced postcapillary venule identity. In vitro and in vivo studies indicate that compensatory upregulation of laminin 5 in Lama4-/-vessels enhances expression of junctional proteins (Ocln, Cldn5) and promotes vessel contractility via increased expression of contractile molecules in mural cells. Additionally, loss of Lama4 upregulates expression of large artery markers (Gja4, Dll4, Tgfb2) and results in elevated autotaxin (Enpp2) levels, a key enzyme in lysophosphatidic acid production implicated in stroke. Accordingly, Lama4-/- mice exhibit worsened stroke outcomes, driven not by immune infiltration or junctional defects, but by increased vascular permeability likely mediated by autotaxin and/or activation of resident myeloid cells. Our data suggest that laminin 4/5 ratios in vascular BMs regulate functional zonation between arterioles, capillaries and postcapillary venules by modulating metabolic pathways in endothelial and mural cells, and indirectly influencing resident myeloid cells.

cell biology↗

bioRxiv2025

LipidQMap - An Open-Source Tool for Quantitative Mass Spectrometry Imaging of Lipids

Mass spectrometry imaging (MSI) is a powerful tool in both basic and clinical research, enabling spatial visualization of biomolecules and drugs in tissue sections. However, factors influencing mass spectrometric response during imaging are increasingly recognized for their impact on apparent molecular distribution. Quantitative mass spectrometry imaging (qMSI) addresses this variability by incorporating analytical standards that undergo the same processes as analytes. While qMSI sample preparation protocols for omics-scale quantitative lipidomics are actively evolving, software solutions for downstream data processing remain scarce. Here, we introduce LipidQMap, the first open-source platform for processing omics-scale qMSI lipidomics data. LipidQMap applies one-point calibration, normalizing annotated lipid signals against class-specific standards on a pixel-by-pixel basis, and generates concentration heat maps in pmol/mm2. The software supports centroided data import, recalibration, and lipid identification using a built-in, user-modifiable lipid database. LipidQMap resolves Na/H adduct isobaric overlaps by leveraging sodiated-to-protonated adduct ratios of standards, validated across several MSI platforms using mouse brain sections. Type II isobaric overlaps are corrected using predicted isotopic patterns. Extensive validation demonstrates that LipidQMap is robust across MSI platforms and harmonizes qMSI data, enabling more accurate and reproducible spatial lipid quantification.

bioinformatics↗

bioRxiv2025

Single-cell mass spectrometry imaging combined with immunofluorescence reveals neutrophil heterogeneity in inflammation

Multimodal single-cell approaches allow for a holistic analysis of complex biological systems. In this study, we developed a novel single-cell analysis pipeline integrating immunofluorescence-based protein with mass spectrometry imaging-based lipid analysis of circulating human neutrophils. The combination of both modalities identified the emergence of pathogenic neutrophils in liver cirrhosis patients thus epitomizing the potential of this technology to reveal cellular phenotypes in health and disease.

immunology↗

bioRxiv2025

Subcellular mass spectrometry imaging of lipids and nucleotides using transmission geometry ambient laser desorption and plasma ionisation

Demand for mass spectrometry imaging (MSI) technologies offering subcellular resolution for tissues and cell imaging is rapidly increasing. To accomplish this, efficient analyte ionisation is essential, given the small amounts of material sample in each pixel. Herein, we describe an atmospheric pressure transmission-geometry matrix-assisted laser desorption source equipped with plasma ionisation. By utilising a novel pre-staining method for sample preparation lipid signal intensities were enhanced by an order of magnitude compared to conventional matrix-only methods, while serendipitously enabling imaging of numerous nucleotides. The system enables detection of up to 200 lipids and nucleotides in tissues at 1 {micro}m-pixel size while informative MSI data is still obtained down to 250 nm pixel size. The use of sub-micron pixels is shown to discern subcellular features through combinations with fluorescence microscopy. This method provides a powerful tool for cellular and sub-cellular imaging of small molecules from tissues and cells for spatial biology applications.

cell biology↗

bioRxiv2024

Histology-Guided Single-Cell Mass Spectrometry Imaging using Integrated Bright-field and Fluorescence Microscopy

The rapidly evolving field of spatial biology revolves around the analysis of cells in their native microenvironment. This analysis can include morphological features, the presence of specific antigens or gene expression. To add another layer of information, recent methodological advances in matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) now enable the untargeted analysis of lipids and metabolites at subcellular resolution. The integration of MALDI-MSI at the single-cell level with established optical modalities, however, relies on an accurate yet intricate co-registration. Here, we describe the integration of bright-field and fluorescence microscopy into a prototype ion source of a state-of-the art MALDI-MSI instrument to obtain lipid and fluorescence microscopy-derived information from the same specimen, hence with intrinsic spatial correlation. We demonstrate the potential of the combined mass spectrometric and optical single-cell analysis on three examples. This includes the visualization of intracellular lipid distributions in macrophages, the introduction of pre-MALDI immunofluorescence staining on the example of murine cerebellum, and the heterogeneity of lipid profiles of tumor infiltrating neutrophils correlated to their individual microenvironments. Overall, the achieved tight correlation of single-cell lipid profiles with morphologic features and protein expression patterns constitutes a powerful resource for cell biology.

cell biology↗

bioRxiv2024

msiFlow: Automated Workflows for Reproducible and Scalable Multimodal Mass Spectrometry Imaging and Immunofluorescence Microscopy Data Processing and Analysis

Multimodal imaging by matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI MSI) and immunofluorescence microscopy holds great potential for understanding pathological mechanisms by mapping molecular signatures from the tissue microenvironment to specific cell populations. However, existing open-source software solutions for analysis of MALDI MSI data are incomplete, require programming skills and contain laborious manual steps, hindering broadly applicable, reproducible, and high-throughput analysis to generate impactful biological discoveries across interdisciplinary research fields. 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 import and pre-processing of raw MALDI MSI data to visual analysis output, as well as registration, along with state-of-the-art and newly 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 the emerging field of multimodal imaging to uncover context-dependent cellular regulations in disease states.

bioinformatics↗

bioRxiv2024

Large-Scale Evaluation of Spatial Metabolomics Protocols and Technologies

Spatial metabolomics using imaging mass spectrometry (MS) enables untargeted and label-free metabolite mapping in biological samples. Despite the range of available imaging MS protocols and technologies, our understanding of metabolite detection under specific conditions is limited due to sparse empirical data and predictive theories. Consequently, challenges persist in designing new experiments, and accurately annotating and interpreting data. In this study, we systematically measured the detectability of 172 biologically-relevant metabolites across common imaging MS protocols using custom reference samples. We evaluated 24 MALDI-imaging MS protocols for untargeted metabolomics, and demonstrated the applicability of our findings to complex biological samples through comparison with animal tissue data. We showcased the potential for extending our results to further analytes by predicting metabolite detectability based on molecular properties. Additionally, our interlaboratory comparison of 10 imaging MS technologies, including MALDI, DESI, and IR-MALDESI, showed extensive metabolite coverage and comparable results, underscoring the broad applicability of our findings within the imaging MS community. We share our results and data through a new interactive web application integrated with METASPACE. This resource offers an extensive catalogue of detectable metabolite ions, facilitating protocol selection, supporting data annotation, and benefiting future untargeted spatial metabolomics studies.

systems biology↗