Spatially Barcoded Substrate for Tissue Transcriptome Mapping
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Solution Overview
Problem
Current methods for spatially resolved tissue sample analysis are limited by the number of distinct molecules that can be assayed, spatial resolution, and throughput, making it challenging to effectively link tissue, cellular, and molecular processes in biology, development, disease, and homeostasis.
Innovation Solution
A substrate with discrete labeling regions and reference regions, comprising barcode labels that can be transferred into tissue samples, allowing for spatially resolved analysis and gene expression profiling by encoding spatial coordinates, enabling the mapping of cellular components back to their original positions within the tissue.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If spatially resolved tissue analysis methods are used to preserve spatial context, then spatial information is maintained, but the number of distinct molecules that can be assayed is limited
Solution Approach 1:
The substrate is divided into multiple discrete labeling regions arranged in a spatial pattern, with each region containing unique barcode labels. This segmentation allows simultaneous assay of multiple molecules across different spatial locations while preserving the spatial context of the tissue sample.
Solution Approach 2:
The invention adds a spatial dimension to molecular analysis by arranging barcode labels in a two-dimensional grid pattern on the substrate. This allows the system to multiplex beyond the limitation of fluorescence channels by utilizing spatial position as an additional dimension for distinguishing different molecular assays.
2Productivity
If bulk analysis methods are used to analyze large areas, then throughput is improved, but spatial resolution is reduced
Solution Approach 1:
The substrate divides the analysis area into multiple discrete labeling regions that can be analyzed in parallel. Each region maintains its spatial coordinates, allowing bulk processing of large tissue areas while preserving single-cell spatial resolution through the unique barcode labels in each region.
Solution Approach 2:
The invention combines bulk analysis capabilities with spatial resolution by integrating multiple labeling regions on a single substrate. This allows simultaneous analysis of large tissue areas (bulk) while maintaining the ability to resolve individual cell positions through the spatially encoded barcode labels.
3Loss of information
If in situ assays are conducted on tissue samples, then spatial context is preserved, but the procedure becomes time consuming
Solution Approach 1:
The substrate is pre-loaded with multiple unique barcode labels in spatially organized regions before contact with the tissue sample. This preliminary preparation allows the assay to proceed rapidly upon contact, as the barcode labels are already positioned and ready for transfer, reducing the overall procedure time while maintaining spatial context.
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 enables single-cell transcriptome recovery while capturing spatial patterns of gene expression across larger scales, providing detailed insights into cell-type-specific gene expression and spatial heterogeneity, enhancing the understanding of tissue homeostasis and disease diagnostics.
Implementation Method 1
each labeling region comprises one or more barcode labels, wherein the one or more barcode labels can be transferred from the matrix into a tissue sample upon contacting the substrate with the tissue sample
Data Source
AI summary
Substrates and methods for spatially resolved analyses of tissue samples are provided, allowing the data from such analyses to be mapped back to the tissue's initial architecture. For analyses that have previously been conducted on bulk, homogenized samples or on dissociated cell components not directly traceable to their prior positions in the tissue sample, spatial resolution of this data can allow better characterization of cell-cell and cell-microenvironment relationships and interactions. This spatial context can aid in determining structure-function relationships in healthy and diseased tissues may thereby enhance the scientific understanding of tissue homeostasis, development, disease, and repair. The information determined using the methods of the disclosure can also be applied to enhancing diagnostics evaluation of diseased tissues.