Multiplex Analyte Detection via Sample Segmentation
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Solution Overview
Problem
Current multiplex detection methods, such as proximity extension assays (PEA) and proximity ligation assays (PLA), face challenges in accurately detecting proteins with varying concentrations, as high-concentration proteins can overwhelm signals from low-concentration proteins, leading to failure in detecting the latter.
Innovation Solution
The method involves dividing a sample into multiple aliquots, each containing a subset of analytes selected based on predicted abundance, and performing separate multiplex assays for each aliquot, with the use of PCR reactions and internal controls to amplify and detect reporter nucleic acid molecules, ensuring accurate detection across a wide range of concentrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiplex detection is performed to detect multiple proteins in a single sample, then the ability to detect multiple analytes is improved, but the signal from high-concentration proteins overwhelms the signal from low-concentration proteins, resulting in failure to detect low-abundance analytes
Solution Approach 1:
The sample is divided into multiple aliquots, and the analytes are segmented into different subsets based on their predicted abundance. Each aliquot is then processed separately to detect a specific subset of analytes, preventing signal overlap between high-abundance and low-abundance analytes while maintaining comprehensive multiplex detection capability
Solution Approach 2:
Different aliquots are assigned different detection sensitivities and analyte subsets tailored to their specific purposes. Aliquots detecting low-abundance analytes use optimized conditions for high sensitivity, while aliquots detecting high-abundance analytes use conditions optimized for their concentration range, allowing each local detection process to operate at optimal quality
2Device complexity
If a single multiplex assay is used to detect all analytes, then the assay complexity is reduced, but the dynamic range of detection is limited due to signal saturation from high-concentration proteins
Solution Approach 1:
The detection system is segmented into multiple parallel assays, each optimized for specific concentration ranges. This segmentation extends the overall dynamic range by ensuring that analytes across different concentration levels are detected in appropriate assays, while maintaining protocol simplicity through standardized processing steps
Solution Approach 2:
The assay parameters such as probe concentrations, detection sensitivities, and signal thresholds are changed and optimized for different aliquots based on the predicted abundance of analytes in each aliquot, enabling detection across a wider dynamic range while maintaining manageable protocol complexity
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 reliable detection of multiple analytes with varying concentrations, improving the accuracy of multiplex detection and allowing for precise quantification of biomarkers, particularly in the context of personalized medicine.
Implementation Method 1
nucleic acid moieties linked to the analyte-binding domains of a probe pair hybridise to one another when the probes are in close proximity
Implementation Method 2
extended using a nucleic acid polymerase. The extension product forms a reporter nucleic acid
Implementation Method 3
a PCR reaction is performed to amplify the reporter nucleic acid molecule
Implementation Method 4
a separate component which is present in a pre-determined amount, and which is, or comprises, or leads to the generation of, a control nucleic acid molecule which is amplified by the same primers as the reporter nucleic acid molecules
Data Source
AI summary
The present invention provides a method of detecting multiple analytes in a sample, wherein said analytes have varying levels of abundance in the sample, said method comprising: (i) providing multiple aliquots from the sample; and (ii) in each aliquot, detecting a different subset of the analytes by performing a separate multiplex assay for each aliquot, wherein the analytes in each subset are selected based on their predicted abundance in the sample.


