Dual-Mode Wheat Germ Agglutinin Labeling – A Versatile Cell Segmentation Strategy for High-Resolution LA-ICP-TOFMS Bioimaging

Single-cell analysis by laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOFMS) enables high-resolution mapping of elemental distributions and cellular phenotypes. Segmentation of individual cells necessitates labeling of both nuclei and membranes, the latter often requiring extensive tissue-specific optimization. In this study, we present a broadly applicable segmentation protocol based on wheat germ agglutinin (WGA), a lectin that binds to <i>N</i>-acetylglucosamine and sialic acid residues ubiquitously expressed on the cell membrane. By combining fluorescently labeled WGA with a metal-tagged anti-WGA antibody, we introduce a dual-labeling strategy compatible with both fluorescence microscopy and LA-ICP-TOFMS, enabling cross-validation of membrane labeling and enhancing segmentation accuracy. With recent advancements in laser ablation technology, such as higher repetition rates and submicrometer spot sizes, high-resolution imaging across large sample areas has become increasingly feasible. The robust, high-contrast membrane labeling achieved with our method facilitates precise cell segmentation at these resolutions and enhances the quality of the downstream single-cell data analysis. Beyond that, our approach reduces staining costs, streamlines workflows, and provides a scalable alternative to existing membrane-labeling strategies.

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Publication Details

Journal
Analytical Chemistry
Published
2025-09-18
DOI
https://doi.org/10.1021/acs.analchem.5c04060
Citations
1
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
1.63
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article

Dual-Mode Wheat Germ Agglutinin Labeling – A Versatile Cell Segmentation Strategy for High-Resolution LA-ICP-TOFMS Bioimaging

Martin Schaier, Michael Gutmann, Gunda Koellensperger, Walter Berger et al.
1 citations
Analytical Chemistry
Cell Image Analysis Techniques
1.63
article

Dual-Mode Wheat Germ Agglutinin Labeling – A Versatile Cell Segmentation Strategy for High-Resolution LA-ICP-TOFMS Bioimaging

Martin Schaier, Michael Gutmann, Gunda Koellensperger, Walter Berger, Gabriel Braun, Claude Molitor, David Loibnegger
article en
1 citations

Abstract

Single-cell analysis by laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOFMS) enables high-resolution mapping of elemental distributions and cellular phenotypes. Segmentation of individual cells necessitates labeling of both nuclei and membranes, the latter often requiring extensive tissue-specific optimization. In this study, we present a broadly applicable segmentation protocol based on wheat germ agglutinin (WGA), a lectin that binds to <i>N</i>-acetylglucosamine and sialic acid residues ubiquitously expressed on the cell membrane. By combining fluorescently labeled WGA with a metal-tagged anti-WGA antibody, we introduce a dual-labeling strategy compatible with both fluorescence microscopy and LA-ICP-TOFMS, enabling cross-validation of membrane labeling and enhancing segmentation accuracy. With recent advancements in laser ablation technology, such as higher repetition rates and submicrometer spot sizes, high-resolution imaging across large sample areas has become increasingly feasible. The robust, high-contrast membrane labeling achieved with our method facilitates precise cell segmentation at these resolutions and enhances the quality of the downstream single-cell data analysis. Beyond that, our approach reduces staining costs, streamlines workflows, and provides a scalable alternative to existing membrane-labeling strategies.

Analytical ChemistryVol. 97(38)
University of Vienna (AT), Comprehensive Cancer Center Vienna (AT), Diplomatic Academy of Vienna (AT), Institute of Inorganic Chemistry of the Slovak Academy of Sciences (SK), Center for Cancer Research (US), Czech Academy of Sciences, Institute of Analytical Chemistry (CZ), UC Davis Comprehensive Cancer Center, Medical University of Vienna (AT)
Openalex Percentile: Top 12%
Cell Image Analysis Techniques
1.63
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