Tissue Pixelation for Spatial Gene Mapping
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Solution Overview
Problem
Current methods for spatial gene expression analysis in tissue samples are low throughput, laborious, and decouple analyte isolation and biochemical detection, making them unsuitable for routine research and clinical practice, while direct probe-based techniques face challenges with off-target binding and cellular auto-fluorescence.
Innovation Solution
A platform that pixelates tissue sections into separate islands in microarray wells, allowing for individual analysis using on-chip picoliter real-time reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) reactions without analyte purification, preserving native spatial location and enabling efficient spatial mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If amplification-based spatial gene expression analysis methods are used, then sensitivity and specificity are improved, but throughput decreases and labor requirements increase
Solution Approach 1:
The tissue section is segmented into multiple discrete regions or spots, each containing specific analytes of interest. This segmentation allows parallel processing of multiple samples simultaneously on a single chip, thereby increasing throughput while maintaining the sensitivity and specificity of amplification-based detection for each segmented region.
Solution Approach 2:
Multiple analytical functions (analyte isolation, amplification, and detection) are merged into a single integrated microchip platform. This consolidation enables high-throughput parallel processing of multiple tissue samples while maintaining the sensitivity and specificity of amplification-based methods, resolving the contradiction between precision and productivity.
2Loss of information
If direct probe-based hybridization techniques are used, then spatial visualization is improved, but off-target binding and auto-fluorescence increase
Solution Approach 1:
An intermediary amplification step (such as PCR or isothermal amplification) is introduced between the probe hybridization and detection steps. This intermediary step enriches the target analytes before detection, thereby reducing off-target binding effects and minimizing the impact of auto-fluorescence background, while preserving the spatial information through maintained correspondence between chip positions and tissue locations.
Solution Approach 2:
The direct optical detection method is replaced with an amplification-based detection system that uses biochemical reactions (PCR or isothermal amplification) followed by fluorescent readout. This substitution reduces the impact of auto-fluorescence and off-target binding by providing signal amplification that overcomes background interference, while spatial information is preserved through the positional mapping between chip spots and tissue regions.
3Adaptability or versatility
If methods performing spatially-mapped transcriptome analysis are used, then multiple targets identification is improved, but histologic reference quality decreases
Solution Approach 1:
The tissue section is segmented into multiple discrete regions on the chip, with each region containing specific analytes. This segmentation enables simultaneous analysis of multiple targets across different tissue regions while preserving the spatial context and histologic quality of each segmented region, as the physical separation maintains the integrity of individual tissue areas for subsequent histologic evaluation.
Solution Approach 2:
The microchip platform is designed with universal applicability to analyze multiple different targets (genes, transcripts, or other analytes) across multiple tissue regions simultaneously. This multi-functionality allows comprehensive transcriptome analysis while maintaining histologic reference quality, as the same chip can be used for various analytical targets without compromising the spatial and histologic integrity of the tissue samples.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a highly sensitive, reproducible, and efficient method for spatial gene expression analysis, enabling rapid characterization of molecular variations in tissue samples with minimal sample processing and preserving spatial information, suitable for various applications including pathogen detection and diagnostics.
Implementation Method 1
applying a force to said deformable substrate, thereby forcing underlying tissue sample into the plurality of wells; shearing the tissue sample along the shearing surface into a plurality of tissue sample islands
Data Source
AI summary
Various methods and devices for spatial molecular analysis from tissue is provided. For example, a method of spatially mapping a tissue sample is provided with a microarray having a plurality of wells, wherein adjacent wells are separated by a shearing surface; overlaying said microarray with a tissue sample; applying a deformable substrate to an upper surface of said tissue sample; applying a force to the deformable substrate, thereby forcing underlying tissue sample into the plurality of wells; shearing the tissue sample along the shearing surface into a plurality of tissue sample islands, with each unique tissue sample island positioned in a unique well; and imaging or quantifying said plurality of tissue sample islands, thereby generating a spatial map of said tissue sample. The imaging and/or quantifying may use a nucleic acid amplification technique.