SM3DD with segmented PCA: a comprehensive method for interpreting 3D spatial transcriptomics

Blick, T; Kilgallon, A; Monkman, J; Cooper, C; Tan, CW; Killingbeck, EE; Pan, L; Kim, Y; Liang, Y; Nam, A; Leon, M; Guimaraes, PSF; Nagashima, S; Martins, APC; Machado-Souza, C; de Noronha, L; Fraser, JF; Belz, GT; Souza-Fonseca-Guimaraes, F; Kulasinghe, A

Author(s): Blick, T; Kilgallon, A; Monkman, J; Cooper, C; Tan, CW; Killingbeck, EE; Pan, L; Kim, Y; Liang, Y; Nam, A; Leon, M; Guimaraes, PSF; Nagashima, S; Martins, APC; Machado-Souza, C; de Noronha, L; Fraser, JF; Belz, GT; Souza-Fonseca-Guimaraes, F; Kulasinghe, A;
Details: Publication Year 2026-03,Volume 8,Issue #1,Page lqag007
Journal Title: NAR Genomics & Bioinformatics
Abstract: We developed Standardised Minimum 3D Distance (SM3DD), an entirely cell segmentation/annotation-free approach to the analysis of spatial RNA datasets, using it to compare lung tissue from 16 clinically normal individuals to that of 18 SARS-CoV-2 patients who died from acute respiratory distress syndrome. RNA spatial coordinates were determined using the CosMx™ Spatial Molecular Imager (Bruker Spatial Biology, US). For each individual transcript location, we calculated the three-dimensional distances to the nearest transcript of each transcript type, standardising the distances to each transcript type. Mean SM3DDs were compared between normal and SARS-CoV-2 patients. Notably, hierarchical clustering of the directional log10(P) values organized genes by functionality, making it easier to interpret biological contexts, and for FKBP11, where a decrease in distance to MZT2A was the most significant difference, suggesting a role in interferon signalling. Using a segmented principal components analysis of the entire SM3DD dataset, we identified multiple pathways, including 'SARS-CoV-2 infection', even though the assay did not include any SARS-CoV-2 transcripts.
Publisher: Oxford Academic
Keywords: Humans; *COVID-19/genetics/virology/pathology; *SARS-CoV-2/genetics; *Transcriptome; Principal Component Analysis; *Gene Expression Profiling/methods; Lung/metabolism/pathology/virology; Imaging, Three-Dimensional/methods; Male
Research Division(s): Bioinformatics and Computational Biology
PubMed ID: 41608733
Publisher's Version: https://doi.org/10.1093/nargab/lqag007
Open Access at Publisher's Site: https://doi.org/10.1093/nargab/lqag007
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2026-02-09 09:18:21

Last Modified: 2026-02-09 09:23:24