Microarray integrated spatial transcriptomics (MIST) for affordable and robust digital pathology

Juwayria; Priyansh Shrivastava; Kaustar Yadav; Sourabh Das; Shubham Mittal; Sunil Kumar; Deepali Jain; Prabhat Singh Malik; Ishaan Gupta

doi:10.1038/s41540-024-00462-1

Microarray integrated spatial transcriptomics (MIST) for affordable and robust digital pathology

NPJ Syst Biol Appl. 2024 Nov 30;10(1):142. doi: 10.1038/s41540-024-00462-1.

Authors

Juwayria¹, Priyansh Shrivastava¹, Kaustar Yadav², Sourabh Das³, Shubham Mittal¹, Sunil Kumar⁴, Deepali Jain², Prabhat Singh Malik⁵, Ishaan Gupta⁶

Affiliations

¹ Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, New Delhi, India.
² Department of Pathology, All India Institute of Medical Sciences, New Delhi, India.
³ Department of Mechanical Engineering, Indian Institute of Technology, New Delhi, India.
⁴ Department of Surgical Oncology, All India Institute of Medical Sciences, New Delhi, India.
⁵ Department of Medical Oncology, All India Institute of Medical Sciences, New Delhi, India.
⁶ Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, New Delhi, India. ishaan@dbeb.iitd.ac.in.

Abstract

10X Visium, a popular Spatial transcriptomics (ST) method, faces limited adoption due to its high cost and restricted sample usage per slide. To address these issues, we propose Microarray Integrated Spatial Transcriptomics (MIST), combining conventional tissue microarray (TMA) with Visium, using laser-cutting and 3D printing to enhance slide throughput. Our design facilitates independent replication and customization in individual labs to suit specific experimental needs. We provide a step-by-step guide from designing TMAs to the library preparation step. We demonstrate MIST's cost-effectiveness and technical benefits over Visium and GeoMx Nanostring. We also introduce 'AnnotateMap', a novel computational tool for efficient analysis of multiple ROIs processed through MIST.

MeSH terms

Computational Biology / methods
Gene Expression Profiling* / methods
Humans
Oligonucleotide Array Sequence Analysis / methods
Tissue Array Analysis / methods
Transcriptome / genetics