Skin Microbiome Signatures Using DNA Sequencing for Trait Prediction
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Solution Overview
Problem
There is a need to better characterize different skin types to provide appropriate cosmetic treatments, as existing methods do not adequately account for the unique microbial profiles of sensitive and other skin types.
Innovation Solution
A method is developed to generate a skin microbial signature by identifying the presence or abundance of specific microbial species or genera, using nucleic acid extraction and sequencing, to predict skin characteristics such as hydration, sebum levels, age, sensitivity, and skin barrier function, utilizing techniques like swabbing, nucleic acid amplification, and sequencing to create predictive thresholds for high, low, or intermediate levels of these characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional skin characterization methods are used, then general skin assessment is possible, but accurate prediction of specific skin characteristics and microbial profiles cannot be achieved
Solution Approach 1:
The invention segments the skin microbiome analysis into distinct operational stages: sample collection, DNA extraction, 16S rRNA gene amplification, sequencing, and bioinformatic analysis. Each stage is optimized independently to achieve high prediction accuracy for specific skin characteristics while managing overall complexity through systematic breakdown of the analytical process
Solution Approach 2:
The invention changes the analytical parameter from general skin assessment to specific microbial taxonomic composition (genera and species-level identification). By focusing on specific microbial parameters and their relative abundances, the method achieves precise prediction of skin characteristics through defined thresholds and signature profiles
2Loss of information
If comprehensive microbial profiling is performed, then detailed skin type characterization is achieved, but analysis time and resource requirements increase
Solution Approach 1:
The invention extracts only the essential microbial information needed for skin characterization by focusing on specific taxa (genera and species) and their relative abundances. The bioinformatic analysis extracts key signature profiles from comprehensive sequencing data, identifying discriminant taxa that predict skin characteristics without requiring analysis of all microbial parameters
Solution Approach 2:
The invention performs preliminary bioinformatic processing and quality control on sequencing data before full analysis. Pre-defined thresholds and signature profiles are established in advance, allowing rapid classification of skin types once the microbial data is obtained, reducing the time required for interpretation
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
The method allows for accurate prediction of skin characteristics by generating microbial signatures that can reliably determine high, low, or intermediate levels of traits like sebum, hydration, and sensitivity, enabling personalized cosmetic treatments.
Implementation Method 1
using nucleic acid extraction and sequencing
Implementation Method 2
utilizing techniques like swabbing, nucleic acid amplification, and sequencing
Data Source
AI summary
The present invention relates to methods of identifying microbial signatures that are predictive of particular skin characteristics, and methods of using the signatures to predict skin characteristics.