Spatial Transcriptomics Substrate Sandwiching to Reduce Analyte Diffusion
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Solution Overview
Problem
Current spatial transcriptomics methods face challenges in maintaining high spatial resolution due to random diffusion of analytes across multiple substrates, leading to loss of spatial information and reduced accuracy in detecting analyte locations within biological samples.
Innovation Solution
The method involves using two substrates with capture probes, where one substrate has a poly-thymine sequence and the other has spatial barcodes, allowing analytes to passively diffuse and be captured on both, thereby reducing diffusion and enhancing spatial resolution by sandwiching the biological sample between them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple substrates are used to capture analytes, then analyte capture capacity increases, but spatial resolution decreases due to random diffusion
Solution Approach 1:
A gel matrix is introduced as an intermediary medium between the biological sample and the barcoded substrate. This gel matrix restricts the random diffusion of analytes while still allowing them to reach capture probes, thereby maintaining spatial resolution during the capture process on multiple substrates
Solution Approach 2:
The system divides the capture function across multiple substrates (first substrate with capture probes and second substrate with barcoded array), allowing analytes to be captured at their release site while maintaining spatial information through the gel matrix constraint
2Productivity
If analytes are allowed to diffuse freely to reach capture probes, then capture efficiency increases, but spatial information is lost
Solution Approach 1:
The gel matrix creates locally constrained diffusion zones around each biological sample, allowing analytes to diffuse efficiently within restricted regions while preserving the spatial origin information. Each local region maintains its spatial characteristics despite the diffusion process
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 significantly increases the spatial resolution of analyte detection, allowing for more accurate determination of analyte abundance and location within biological samples by minimizing lateral diffusion and preserving native spatial context.
Implementation Method 1
analytes are free to disperse from the biological sample. Because the analytes passively diffuse, they will be captured by the probes on both the first and second slides
Implementation Method 2
The probes on the first slide are arranged on a lawn across the slide and include a capture domain sequence such as a poly d(T) (e.g., an oligo d(T)) sequence
Data Source
AI summary
Provided herein are methods of enhancing spatial resolution of an analyte using sandwich maker system. The methods and systems used herein include a first substrate that includes a plurality of probes that include poly-thymine sequence and a second substrate that includes a plurality of probes comprising a capture domain and a spatial domain.