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DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Jun 6, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

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

Juwayria¹, Priyansh Shrivastava¹, Kaustar Yadav²

¹Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology, New Delhi, India.

NPJ Systems Biology and Applications

|November 30, 2024

Summary

This summary is machine-generated.

Microarray Integrated Spatial Transcriptomics (MIST) enhances spatial transcriptomics (ST) by combining tissue microarrays with 10X Visium. This cost-effective method increases throughput and allows for customized, independent lab replication.

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Area of Science:

Molecular Biology
Genomics
Biotechnology

Background:

10X Visium spatial transcriptomics (ST) is a powerful tool but faces adoption barriers due to high costs and limited sample capacity per slide.
Existing ST methods may not be cost-effective or flexible enough for widespread laboratory use.
There is a need for scalable and affordable spatial transcriptomics solutions.

Purpose of the Study:

To develop a cost-effective and high-throughput spatial transcriptomics method.
To enable independent replication and customization of spatial transcriptomics experiments in individual laboratories.
To introduce a novel computational tool for analyzing spatial transcriptomics data from multiple regions of interest.

Main Methods:

Developed Microarray Integrated Spatial Transcriptomics (MIST) by combining tissue microarray (TMA) techniques with 10X Visium.
Utilized laser-cutting and 3D printing technologies to enhance slide throughput and sample integration.
Provided a comprehensive guide for TMA design and library preparation compatible with MIST.
Introduced 'AnnotateMap', a new computational tool for analyzing multiple regions of interest (ROIs) from MIST experiments.

Main Results:

Demonstrated MIST's cost-effectiveness compared to standard 10X Visium and GeoMx Nanostring.
Highlighted the technical advantages and increased throughput offered by the MIST approach.
Validated the feasibility of independent replication and customization of MIST in laboratory settings.
Showcased the utility of 'AnnotateMap' for efficient analysis of MIST-generated data.

Conclusions:

MIST offers a scalable, cost-effective, and customizable alternative for spatial transcriptomics.
The developed method overcomes key limitations of existing ST technologies, promoting broader adoption.
MIST, coupled with 'AnnotateMap', provides a powerful platform for spatial gene expression analysis.