Size matters: the impact of nucleus size on results from spatial transcriptomics

Journal of Translational Medicine

Research

Marcin Jąkalski¹  Katarzyna Chojnowska¹  Anna Kostecka¹  Natalia Filipowicz¹  Magdalena Koczkowska¹  Paweł Olszewski¹  Arkadiusz Piotrowski¹  Jakub Mieczkowski¹  Elyas Mohammadi¹  Jan P. Dumanski²  Michał A. Żmijewski³  Justyna M. Wierzbicka³  Hanna Davies⁴  Bradley T. Hyman⁵  Michał Bieńkowski⁶  Martin Ingelsson⁷ 

[1]3P-Medicine Laboratory, Medical University of Gdańsk, 80 210, Gdańsk, Poland

[2]3P-Medicine Laboratory, Medical University of Gdańsk, 80 210, Gdańsk, Poland

[3]Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden

[4]Department of Histology, Medical University of Gdańsk, 80 210, Gdańsk, Poland

[5]Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, 751 85, Uppsala, Sweden

[6]Department of Neurology, Massachusetts General Hospital, 02114, Boston, MA, USA

[7]Massachusetts Alzheimer’s Disease Research Center, 02129, Charlestown, MA, USA

[8]Harvard Medical School, 02115, Boston, MA, USA

[9]Department of Pathomorphology, Medical University of Gdańsk, 80 210, Gdańsk, Poland

[10]Department of Public Health and Caring Sciences, Geriatrics, Rudbeck Laboratory, Uppsala University, 751 85, Uppsala, Sweden

[11]Krembil Brain Institute, University Health Network, M5G 2C4, Toronto, ON, Canada

[12]Department of Medicine and Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, M5S 1A8, Toronto, ON, Canada

关键词: Spatial transcriptomics;    Cerebral cortex;    Neuronal nuclei;    Consecutive tissue sections;    Data integration;   

DOI  :  10.1186/s12967-023-04129-z

 received in 2023-01-04, accepted in 2023-04-12,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundVisium Spatial Gene Expression (ST) is a method combining histological spatial information with transcriptomics profiles directly from tissue sections. The use of spatial information has made it possible to discover new modes of gene expression regulations. However, in the ST experiment, the nucleus size of cells may exceed the thickness of a tissue slice. This may, in turn, negatively affect comprehensive capturing the transcriptomics profile in a single slice, especially for tissues having large differences in the size of nuclei.MethodsHere, we defined the effect of Consecutive Slices Data Integration (CSDI) on unveiling accurate spot clustering and deconvolution of spatial transcriptomic spots in human postmortem brains. By considering the histological information as reference, we assessed the improvement of unsupervised clustering and single nuclei RNA-seq and ST data integration before and after CSDI.ResultsApart from the escalated number of defined clusters representing neuronal layers, the pattern of clusters in consecutive sections was concordant only after CSDI. Besides, the assigned cell labels to spots matches the histological pattern of tissue sections after CSDI.ConclusionCSDI can be applied to investigate consecutive sections studied with ST in the human cerebral cortex, avoiding misinterpretation of spot clustering and annotation, increasing accuracy of cell recognition as well as improvement in uncovering the layers of grey matter in the human brain.

【 授权许可】

CC BY   
© The Author(s) 2023

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