Correlative Microscopy Visualization for Protein Localization
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Solution Overview
Problem
Current microscopy techniques fail to visualize proteins and cell structures simultaneously, limiting the understanding of cellular biology due to limitations in correlating fluorescence light microscopy and electron microscopy images, particularly in precise protein localization within subcellular contexts.
Innovation Solution
A method for correlating sub-diffraction resolution microscopy images with electron microscopy images using feature markers, such as natural cell structures or introduced fiducial markers, to register and combine datasets from different modalities, enabling the production of a single image that displays both cellular structures and protein localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fluorescence light microscopy is used for protein localization, then protein distribution can be visualized, but subcellular context and organelles are absent
Solution Approach 1:
The patent combines fluorescence light microscopy images (showing protein localization) with electron microscopy images (showing subcellular structures and organelles) into a single correlated image. This merging allows simultaneous visualization of both protein distribution and subcellular context, resolving the contradiction between protein localization precision and preservation of subcellular information.
2Loss of information
If electron microscopy is used to map cell membranes and organelles, then subcellular context is visible, but the ability to specifically localize proteins is limited
Solution Approach 1:
The patent merges electron microscopy data (providing subcellular context) with fluorescence microscopy data (providing protein localization precision) through image correlation. This combination allows the final image to simultaneously display organelles and membranes with high structural detail while precisely locating proteins within that context.
Solution Approach 2:
The patent uses fiducial markers as intermediary objects that are visible in both fluorescence and electron microscopy modalities. These markers serve as reference points to align and correlate the two different image types, enabling accurate overlay of protein localization data onto subcellular structures.
3Loss of information
If correlative approaches are used to image specimens with both fluorescence light microscopy and electron microscopy, then both protein localization and subcellular context can be captured, but effective correlation process is lacking
Solution Approach 1:
The patent introduces fiducial markers as intermediary reference objects that simplify the correlation process. These markers are incorporated into the sample and visible in both microscopy modalities, providing automatic reference points for image alignment and reducing the complexity of manual correlation procedures.
Solution Approach 2:
The patent creates a digital copy or representation of the spatial relationships between fiducial markers and cellular features from one modality to register images from another modality. This computational approach to correlation reduces manual intervention and simplifies the integration process.
4Measurement precision
If conventional fluorescence microscopy is used, then protein localization is achieved, but resolution is limited and precise localization in relation to specific organelles is precluded
Solution Approach 1:
The patent combines conventional fluorescence microscopy (providing protein localization) with electron microscopy (providing high-resolution subcellular structures). The correlation of these two modalities allows protein positions to be precisely related to organelle structures, overcoming the resolution limits of conventional light microscopy.
Data Source
AI summary
A method is described for correlating microscopy images from a number of modalities in a sub diffraction resolution environment. The method may include receiving a number of datasets that may represent microscopy captures from a number of different modalities. The microscopy captures may contain feature markers that may be used to register a number of data points contained in a dataset with data points from another dataset. Upon registering the data points of the datasets, a combined dataset may be produced and a visual image of the combined dataset may be provided.