2026-10-14T08:38:59Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33968778 2026-09-22T20:20:30Z category_1 category_4 category_146 category_7 category_12 category_13 category_16 category_21 category_272 category_873 category_734 category_931 category_135 portal_63 item_type_3 month_year_09_2026

Enabling High-Throughput Tissue Sectioning for Robust Lipid Mass Spectrometry Imaging Ruben Jacobs (21176991) Ritesh Chidambaram (18210761) Vincent Steinbacher (25091655) Chenwei Wei (25091658) Tim Ragan (11175963) Michiel Vandenbosch (14425444) Ron M. A. Heeren (7181636) Biophysics Biochemistry Space Science Medicine Cell Biology Genetics Physiology Biotechnology Environmental Sciences not elsewhere classified Chemical Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified Computational Biology spectrometry imaging toward significantly reduces sample improved biological interpretation every single section assisted laser desorption sample preparation remain resolution digital images reliable data acquisition fully automated workflow throughput tissue sectioning robust molecular information spatial resolution preparation variability acquisition time workflow demonstrating structural reference specific comparisons spatial characterization significant source serial two seamlessly integrated recent advances powerful tool pfa fixation multiplexed detection maldi workflow experimental variability enabling high downstream analyses anatomical context agarose embedding acquire high Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has been established as a powerful tool for the spatial characterization of molecules. Recent advances have been driven by improvements in the spatial resolution, acquisition time, and sensitivity. Although MALDI-MSI excels in the label-free, multiplexed detection of biomolecules, variations in sample preparation remain a significant source of experimental variability. Here, we present a workflow demonstrating the integration of a robust, completely automated tissue section processing system into a MALDI workflow. Importantly, PFA fixation and agarose embedding are demonstrated to preserve lipid compositional distributions. Combined, it enables robust and stable lipid imaging across a completely sectioned mouse brain. The integration of the Marinus MP system advances mass-spectrometry imaging toward a fully automated workflow, significantly reduces sample-preparation variability, and enables more consistent, reliable data acquisition and improved biological interpretation. Parallel with sectioning, serial two-photon (STP) tomography is used to acquire high-resolution digital images of every single section, providing a structural reference for downstream analyses. We demonstrate how the Allen Mouse Brain Atlas can be seamlessly integrated with these multimodal imaging data sets. This workflow enables precise region-specific comparisons and enriches the anatomical context with robust molecular information. 2026-09-22T00:00:00Z Dataset Dataset 10.1021/acs.analchem.6c03106.s001 https://figshare.com/articles/dataset/Enabling_High-Throughput_Tissue_Sectioning_for_Robust_Lipid_Mass_Spectrometry_Imaging/33968778 CC BY-NC 4.0