Spatial Mapping via Stochastic Barcode Particles
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Solution Overview
Problem
Current methods for characterizing target analytes in biological samples are limited by resolution, signal-to-noise ratio, ability to characterize locations in multiple dimensions, and handling different types of analytes, particularly in situ and in vitro, with high precision and uniformity requirements for accurate mapping.
Innovation Solution
The development of systems and methods for spatial biology, including spatial transcriptomics and proteomics, that utilize capture probes and functionalized particles to generate high-resolution spatial maps of target analytes, achieving resolutions greater than one target per 500 um2 and signal-to-noise ratios of up to 100,000, with minimal noise and false positives, by close packing functionalized particles to minimize empty space and optimize target capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current mapping methods are used, then mapping can be performed, but resolution is limited and multiple targets cannot be characterized simultaneously at high density
Solution Approach 1:
The system segments the mapping function across multiple functionalized particle types, where each particle type is specialized for detecting a specific target analyte. This segmentation enables simultaneous characterization of multiple targets while maintaining high spatial resolution, as each particle type contributes to a different aspect of the multiplexed detection without interfering with others.
Solution Approach 2:
The system employs universal imaging features that can detect and characterize multiple different target analytes simultaneously. The functionalized particles are designed with universal detection capabilities that work across various target types, enabling the system to perform multiplexed mapping of multiple targets with a single unified approach.
2Ease of operation
If functionalized particles are spaced further apart, then target capture is easier, but empty space increases and resolution decreases
Solution Approach 1:
The system applies local quality by functionalizing specific regions of particles with target-specific moieties while maintaining uniform spatial distribution. This allows particles to be closely spaced for high resolution while the localized functionalization ensures efficient target capture without requiring large spacing between particles.
3Measurement precision
If mapping resolution is increased, then more targets per unit area can be characterized, but signal-to-noise ratio decreases due to background noise
Solution Approach 1:
The system introduces universal imaging features as intermediaries between the functionalized particles and the detection system. These imaging features serve as mediators that enhance the signal from target-analyte interactions while providing a consistent reference framework that reduces background noise, thereby maintaining high signal-to-noise ratio even at high mapping resolutions.
4Measurement precision
If high precision and uniformity are required for accurate mapping, then composition uniformity must be maintained, but manufacturing complexity increases
Solution Approach 1:
The system employs parameter changes by utilizing stochastic barcodes with defined statistical properties rather than requiring precise control of particle composition. By shifting from composition-based identification to statistically-defined barcode sequences, the system achieves high mapping accuracy without the need for complex manufacturing processes to maintain composition uniformity.
Data Source
AI summary
Systems, methods, and compositions for generating a high-resolution spatial map of a distribution of targets of a sample are described. Processes for generating the spatial map can include: receiving the sample at a substrate having a distribution of functionalized particles, each having a stochastic barcode sequence paired with a position on the substrate; promoting interactions between the distribution of targets of the sample and the distribution of functionalized particles upon transmitting heat to a surface of the substrate opposite the distribution of functionalized particles; applying a set of reactions to the sample at the substrate, obtaining a set of sequences of a population of molecules generated from the set of reactions, the set of sequences associated with the distribution of targets labeled using the stochastic barcode sequences of the distribution of functionalized particles, and returning a set of positions of the distribution of targets upon processing the set of sequences.


