Single-Molecule Label Quantification Using Signal Subtraction
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Solution Overview
Problem
Existing methods struggle to accurately quantify large numbers of single molecules due to challenges in discerning and counting individual labels, especially when they are adjacent to each other, leading to difficulties in resolving rare events, heterogeneous events, and transient processes, and requiring costly and inefficient processes like PCR for genetic analysis.
Innovation Solution
A method using electronic devices with processors and memory to analyze multi-dimensional digital data, segment and subtract reference signals, and quantify labels based on intensity values over time, facilitating accurate quantification of labels on substrates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional detection methods are used to detect single molecules, then detection capability is achieved, but quantification accuracy deteriorates when multiple labels are adjacent to one another
Solution Approach 1:
The patent segments the detection process into multiple sequential imaging rounds, where each round detects a subset of labels. By temporally separating the detection of adjacent labels through stochastic activation and sequential imaging, the system resolves labels that would otherwise be indistinguishable in a single simultaneous detection event.
Solution Approach 2:
The system employs periodic imaging cycles with stochastic activation of labels between cycles. Labels are activated and deactivated in a periodic fashion, allowing the detection system to capture individual label signals at different time points. This periodic action transforms the continuous overlap problem into discrete, separable detection events.
2Productivity
If conventional methods are used for genetic analysis, then analysis can be performed, but cost and efficiency deteriorate due to requirement of PCR processes
Solution Approach 1:
The patent replaces the mechanical amplification process of PCR with a direct single-molecule detection approach. By detecting individual molecules without amplification and using computational methods to quantify results, the system eliminates the need for costly reagents and time-consuming thermal cycling processes while maintaining analytical capability.
Solution Approach 2:
The system creates multiple digital copies of the detection data through sequential imaging rounds. Each imaging round generates a digital record of detected labels, and these digital copies are computationally integrated to achieve accurate quantification, replacing the need for physical amplification of biological material.
3Loss of information
If single-molecule detection is used to understand properties of individual molecules, then molecular property understanding is improved, but quantification of large numbers of molecules deteriorates
Solution Approach 1:
The patent merges information from multiple single-molecule detection events by combining data from numerous sequential imaging rounds. By statistically integrating signals from many individual molecule detections, the system achieves both detailed molecular property information and accurate bulk quantification, resolving the contradiction between single-molecule insight and population-level measurement.
Data Source
AI summary
A method for quantifying labels on a substrate is performed by an electronic device with one or more processors and memory. The method includes obtaining digital data corresponding to a multi-dimensional measurement over the substrate; identifying a first set of sub-portions of the digital data; and, for a respective sub-portion of the first set of sub-portions of the digital data: increasing a quantity of labels, and subtracting a reference signal distribution from the respective sub-portion to obtain subtracted sub-portion data. The method also includes obtaining subtracted digital data. The subtracted digital data includes the subtracted sub-portion data for the respective sub-portion. The method further includes identifying a second set of one or more sub-portions of the subtracted digital data; and, for a respective sub-portion of the second set of one or more sub-portions of the subtracted digital data, increasing a quantity of labels.


