Gut Microbiota Maturity Prediction via Age-Discriminatory Taxa
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Solution Overview
Problem
There is a need for methods to define microbiota maturity using bacterial taxonomic biomarkers that are highly discriminatory for age to characterize the health status of the gut microbiota, as existing approaches lack effectiveness in diagnosing and treating gastrointestinal health issues.
Innovation Solution
A method involving the calculation of relative abundance of specific bacterial taxa from fecal samples, applied to regression models to determine microbiota age, allowing for the characterization of gut maturity and classification of normal maturation, and the use of these biomarkers for preventing and treating diseases such as acute malnutrition and diarrhea.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a limited number of bacterial taxa are used to define microbiota maturity, then the method complexity is reduced and diagnostic efficiency is improved, but the measurement precision may be compromised
Solution Approach 1:
The patent extracts and focuses on a limited set of age-discriminatory bacterial taxa from the complex gut microbiota community. By identifying and isolating specific taxa that show significant changes in relative abundance with age (such as Bifidobacterium, Lactobacillus, and other specific species), the method captures the essential maturation signal without requiring analysis of the entire microbiota, thus improving diagnostic efficiency while maintaining measurement precision through targeted biomarker selection
Solution Approach 2:
The patent transforms the complex microbiota composition data into a simplified maturity metric by tracking changes in relative abundance of specific bacterial taxa. The regression model converts multiple bacterial abundance parameters into a single microbiota age estimate, changing the parameter space from high-dimensional composition data to a one-dimensional maturity score that is easier to interpret and diagnose
2Measurement precision
If regression models are used to predict microbiota age from bacterial taxa abundance, then the characterization of gut maturity is improved, but the device complexity increases
Solution Approach 1:
The patent segments the complex microbiota community into distinct functional groups based on their maturation patterns. By dividing the microbiota into age-discriminatory taxa (those that change with age) and non-discriminatory taxa, the regression model only needs to process the relevant segment, reducing computational complexity while maintaining prediction accuracy. The model focuses on specific bacterial groups rather than attempting to model the entire microbiota simultaneously
3Measurement precision
If age-discriminatory bacterial taxa are identified and used as biomarkers, then the ability to characterize gastrointestinal health is improved, but the difficulty of detecting and measuring these taxa increases
Solution Approach 1:
The patent uses 16S rRNA gene sequencing to detect and quantify bacterial taxa, where each taxon can be thought of as having a distinct 'color' or signature in the sequence data. By targeting specific age-discriminatory taxa with known 16S sequences, the method can detect these biomarkers through sequence matching, transforming the complex task of microbiota analysis into a targeted detection problem similar to identifying specific colored components in a mixture
Solution Approach 2:
The patent uses 16S rRNA gene sequencing as an intermediary method to detect bacterial taxa without requiring direct observation or culture of the bacteria. This molecular intermediary approach allows for indirect but accurate measurement of bacterial abundance by detecting conserved genomic regions, simplifying the detection process while maintaining measurement precision for the age-discriminatory taxa
Data Source
AI summary
The present invention provides a method to define normal maturation of the gut microbiota using a limited number of bacterial taxa found in the gut microbiota. Regressing the relative abundance of age-discriminatory taxa in their gut microbiota against the chronological age of each healthy subject at the time a sample of the gut microbiota was collected produces a regression model that may be used to characterize the maturity of another subject's gut microbiota to provide a measure of gastrointestinal health without having to query the whole microbiota. The present invention also provides composition and methods for preventing and/or treating a disease in a subject in need thereof.