16S rRNA Hypervariable Region Sequencing for Microbial Species Identification
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Solution Overview
Problem
Current methods for studying the human microbiome, such as 16S amplicon sequencing, are limited in their ability to discriminate microbes at a finer species level, leading to inconsistencies in species assignment across different databases.
Innovation Solution
A method involving the sequencing of hypervariable regions of 16S rRNA genes in bacterial genomes, followed by comparison to a database containing hypervariable region sequences and copy numbers of different bacterial species, to identify and qualify microbial species in a human subject.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 16S amplicon sequencing is used to study the human microbiome, then overall microbial diversity can be evaluated at the family or genus level, but the ability to discriminate microbes at the species level is limited
Solution Approach 1:
The patent extracts and analyzes multiple specific hypervariable regions (V1-V9) from the 16S rRNA gene separately, rather than treating the entire gene as a single unit. This extraction of specific regions enables species-level discrimination while maintaining the simplicity of amplicon sequencing approaches.
Solution Approach 2:
The patent changes the analytical parameters by considering multiple hypervariable regions with different lengths and characteristics simultaneously. By adjusting which regions are analyzed and how they are combined, the method achieves higher resolution species identification without requiring full-length sequencing.
2Reliability
If different databases (Greengenes and SILVA) are used for taxonomic assignment, then comprehensive microbial coverage is achieved, but disagreement in species assignment occurs for more than half of identical sequences
Solution Approach 1:
The patent merges information from multiple hypervariable regions and integrates results from different databases (Greengenes and SILVA) through a unified analysis framework. By combining the strengths of multiple databases and regions, the method achieves consistent species assignment while maintaining comprehensive microbial coverage.
Solution Approach 2:
The patent implements a feedback mechanism where discordant assignments between databases are identified and resolved through additional analysis of multiple hypervariable regions. The system uses the disagreements as feedback to refine species assignment rather than simply accepting the first result.
3Measurement precision
If whole-genome shotgun sequencing is used to map microbial sequences to the species level, then fine mapping of microbial species is enabled, but deep sequencing coverage and extensive computational effort are required, precluding routine application on a population scale
Solution Approach 1:
The patent applies partial action by sequencing only the hypervariable regions of the 16S rRNA gene rather than performing complete whole-genome shotgun sequencing. This partial approach achieves sufficient species-level resolution for population-scale studies while dramatically reducing sequencing depth requirements and computational burden.
Solution Approach 2:
The patent uses a simplified, cost-effective amplicon sequencing approach that can be routinely applied to large numbers of samples. By replacing expensive, computationally intensive WGS with targeted hypervariable region sequencing, the method enables population-scale microbiome studies with routine laboratory equipment and analysis pipelines.
Data Source
AI summary
The present disclosure relates generally to systems and methods for identifying and qualifying microbial species, such as those isolated from a human individual. Once the individual is identified as be deficient in certain microbial species, care can be given accordingly to increase the microbial species and thus improve health of the individual.