Image Signal Separation for Autofluorescence and Cross-Reactivity
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Solution Overview
Problem
Current multiplexed imaging techniques face challenges in using primary antibodies from the same host species due to antibody cross-reactivity and high autofluorescence, particularly in formalin-fixed paraffin-embedded specimens, leading to signal bleed-through and misinterpretations in spatial proteomics analysis.
Innovation Solution
The ERASURE algorithm employs Gram-Schmidt orthogonalization to iteratively separate autofluorescence and antibody cross-reactivity signals in a single imaging round, using a signal separation algorithm to distinguish between different fluorophore signals and autofluorescence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If primary antibodies from the same host species are used in indirect immunostaining, then signal intensity is improved, but antibody cross-reactivity causes signal bleed-through between proteins
Solution Approach 1:
The patent segments the mixed fluorescence signals into individual protein signals through computational unmixing algorithms. By acquiring spectral information across multiple wavelengths and mathematically decomposing the overlapping signals, the system separates contributions from different fluorophores conjugated to primary antibodies from the same host species, enabling simultaneous detection of multiple proteins without cross-reactivity interference
Solution Approach 2:
The patent changes the detection parameter from single-wavelength fluorescence to multi-wavelength spectral detection. By measuring fluorescence intensity across a spectrum of wavelengths rather than at a single peak wavelength, the system captures unique spectral fingerprints of each fluorophore, allowing computational separation of signals even when fluorophores have overlapping emission spectra
2Object-generated harmful factors
If chemical quenching agents are used to eliminate autofluorescence, then autofluorescence signals are reduced, but fluorophore signals are also reduced and background signals are introduced
Solution Approach 1:
The patent extracts autofluorescence signals from the total fluorescence signal through spectral unmixing. By acquiring autofluorescence reference spectra from regions without specific staining and subtracting these from the total signal, the system removes autofluorescence contributions while preserving the integrity of fluorophore signals without requiring chemical quenching agents
Solution Approach 2:
The patent introduces computational algorithms as an intermediary between signal acquisition and analysis. Rather than using chemical agents to modify the biological sample, the system uses mathematical models to separate and remove autofluorescence signals from the acquired spectral data, preserving the original sample state and avoiding introduction of background signals
3Object-generated harmful factors
If photobleaching is used to eliminate autofluorescence, then autofluorescence signals are permanently removed, but fluorescent protein signals are also bleached and excessive time is required
Solution Approach 1:
The patent converts the harmful effect of autofluorescence into a separable spectral component. Rather than attempting to physically remove or quench autofluorescence, the system acquires its spectral signature and uses computational methods to subtract it from the total signal, effectively eliminating autofluorescence interference while preserving all fluorophore signals without photobleaching
4Measurement precision
If spectral unmixing techniques are used to address fluorophore overlap, then signal separation is improved, but the limited availability of validated antibodies from diverse host species remains a constraint
Solution Approach 1:
The patent makes the detection system universal by enabling the use of primary antibodies from any host species through computational unmixing. By removing the constraint that requires antibodies from different host species, the system allows researchers to use commercially available validated antibodies from the same host species for multiple targets, significantly expanding the versatility of multiplexed imaging experiments
Data Source
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AI summary
Disclosed are an image processing method and system for removing autofluorescence and cross-reactivity of antibodies using a signal separation algorithm. An image processing method according to one embodiment may comprise the steps of: obtaining, from a biological tissue, a first unseparated image in which a first molecule is displayed and a second unseparated image in which the first molecule and a second molecule are simultaneously displayed; and generating a first separated image for the first molecule on the basis of the first unseparated image, and a second separated image for the second molecule on the basis of the first unseparated image and the second unseparated image.