Microbial Identification via Probabilistic DNA Sequencing
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Solution Overview
Problem
Current methods for identifying microbial populations in samples are limited to the genus level and cannot accurately determine species, sub-species, and strain levels, leading to false negatives due to genetic mutations and horizontal gene transfer, and require time-consuming and labor-intensive culturing methods.
Innovation Solution
A system and method using probabilistic matching to identify microbial genomes by comparing metagenomic fragments to reference genomic databases, enabling identification of species, sub-species, and strain levels with relative concentrations, and accounting for biodiversity and machine errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static methods such as PCR and microchip arrays are used to detect pre-specified organisms, then detection of known organisms can be achieved, but false negative results occur when mutations or horizontal gene transfer have altered the nucleic acid sequence
Solution Approach 1:
The patent transitions from static detection methods (PCR, microchip arrays) that rely on predetermined signatures to dynamic direct DNA sequencing that adapts to detect any organism regardless of prior knowledge. The sequencing approach continuously generates new data without relying on fixed probes or primers, enabling detection of mutated and novel organisms while maintaining reliability through comprehensive sequence analysis
Solution Approach 2:
The invention changes the fundamental parameter of detection from targeted signature matching to comprehensive sequence reading. By sequencing entire genomes or metagenomic samples rather than targeting specific regions, the system captures all genetic variations including mutations and horizontally transferred genes, thereby resolving the contradiction between reliability for known organisms and adaptability for novel variants
2Measurement precision
If conventional culturing methods are used for bacterial identification, then organisms can be identified to species level, but the process is time consuming and expensive
Solution Approach 1:
The patent replaces the mechanical culturing process with direct DNA sequencing technology. Instead of relying on biological growth processes that require days or weeks, the system directly sequences genetic material from samples, achieving species and strain-level identification in hours or less. This substitution of mechanical/biological methods with molecular sequencing resolves the time-consuming nature of conventional culturing while maintaining high identification precision
Solution Approach 2:
The invention performs preliminary DNA extraction and sequencing before final analysis, preparing the genetic material in advance for rapid identification. By having the sequencing data ready and using computational methods to quickly analyze the sequences, the system achieves fast identification without the time-consuming culturing steps, thereby reducing loss of time while preserving measurement precision
3Measurement precision
If direct DNA sequencing is used for metagenomic samples, then comprehensive genomic identification at species and strain level can be achieved, but complex data analysis and computational resources are required
Solution Approach 1:
The patent segments the complex metagenomic sequencing data into manageable units for analysis. By dividing the comprehensive sequence data into individual reads or contigs and analyzing them separately through systematic computational pipelines, the system achieves accurate species and strain identification while reducing the apparent complexity of the overall analysis process
Solution Approach 2:
The invention introduces computational algorithms and bioinformatics tools as intermediaries between the raw sequencing data and the final identification results. These intermediary computational methods systematically process the complex metagenomic data, transforming it into meaningful biological insights without requiring direct complex manual analysis, thereby achieving high measurement precision while managing device complexity through automated computational pipelines
Data Source
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AI summary
The present invention relates to systems and methods capable of characterizing populations of organisms within a sample. The characterization may utilize probabilistic matching of short strings of sequencing information to identify genomes from a reference genomic database to which the short strings belong. The characterization may include identification of the microbial community of the sample to the species and/or sub-species and/or strain level with their relative concentrations or abundance. In addition, the system and methods may enable rapid identification of organisms including both pathogens and commensals in clinical samples, and the identification may be achieved by a comparison of many (e.g., hundreds to millions) metagenomic fragments, which have been captured from a sample and sequenced, to many (e.g., millions or billions) of archived sequence information of genomes (i.e., reference genomic databases).