Nucleomodulin Detection via Sequence Homology for Altered Gene Expression
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Solution Overview
Problem
Current methods for identifying microbial effector proteins (Nucleomodulins, NMs) that alter host gene expression are cumbersome and require specialized skills, and do not effectively utilize sequence homology for efficient identification.
Innovation Solution
A method and system for identifying NMs by obtaining biological samples, isolating cellular fractions, extracting microbial proteins, scanning against a NMs knowledgebase (NMKB) for sequence similarity, and detecting nuclear localization signals (NLS) using proprietary tools, followed by targeting identified NMs with therapeutic compounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high resolution liquid chromatography coupled to MS or peptide mass mapping using MALDI-TOF/TOF, ELISA, microarray method are used for identification of NMs, then measurement precision is improved, but device complexity and ease of operation deteriorate due to cumbersome procedures and specialized skills required
Solution Approach 1:
The patent uses sequence homology information from known NMs stored in a knowledgebase to identify new NMs through similarity matching. Instead of directly analyzing complex protein samples with sophisticated instruments, the method creates a simplified identification pathway by comparing sequences against reference data, thereby reducing operational complexity while maintaining identification accuracy
Solution Approach 2:
The patent pre-processes and stores NM sequence information in a knowledgebase before actual identification is needed. By preparing reference sequences and homology information in advance, the method eliminates the need for complex real-time analysis procedures during sample identification, simplifying the operational process while preserving measurement precision
2Measurement precision
If high resolution liquid chromatography coupled to MS or peptide mass mapping using MALDI-TOF/TOF, ELISA, microarray method are used for identification of NMs, then measurement precision is improved, but loss of time increases due to cumbersome procedures
Solution Approach 1:
By using sequence homology matching against a pre-built knowledgebase, the patent replaces time-consuming experimental procedures with rapid computational comparisons. This copying approach allows quick identification of NMs based on sequence similarity without requiring lengthy chromatography or mass spectrometry runs, thus reducing time loss while maintaining identification accuracy
Solution Approach 2:
The patent replaces mechanical and chemical analysis systems (liquid chromatography, mass spectrometry, ELISA) with an information-based system using sequence homology matching. This substitution eliminates the need for complex physical procedures and specialized equipment operations, dramatically reducing the time required for NM identification while preserving measurement precision through computational analysis
3Reliability
If sequence homology is not utilized in identification methods, then reliability of identification is improved through direct detection, but productivity deteriorates due to inability to leverage existing knowledgebase data
Solution Approach 1:
The patent copies proven identification criteria from known NMs and applies them to new sequences through homology matching. This approach maintains reliability by using established sequence characteristics as reference standards while dramatically improving productivity by leveraging existing knowledgebase data rather than performing de novo analysis for each identification
Solution Approach 2:
The patent implements a feedback mechanism where identified NMs and their sequence characteristics are added to the knowledgebase, which then serves as a reference for future identifications. This creates a self-improving system where each identification enhances the reliability and productivity of subsequent identifications by expanding the reference database with validated sequence information
Data Source
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AI summary
This disclosure relates generally to a method and system for indicating gene expression changes in the host through identification of a category of microbial effector proteins called 'Nucleomodulins' (NMs). State-of-the-art methods target to fix the impaired cellular functions due to altered gene expression or altered protein expression. However, targeting NMs which are bacterial effector proteins is not yet achieved. The disclosed method provides identification of NMs in the biological sample of the host. Further, the biological sample is analyzed to identify pre-defined set of NMs or an unknown NMs through a plurality of ways. On of the way include constructing and utilizing a knowledgebase comprising NMs identified through curated literature search engines known to cause altered gene expression. Further, functional annotation of the NMs is performed by computationally analysing the corresponding protein sequences. Finally, the NMs are targeted using a nuclear constructs for controlling altered gene expression.