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US 2026/0308700 A1Published application
Systems and Methods For The Identification And Characterization Of Pathogens In Urine Samples To Inform Patient Treatment
AssigneeBiotia, Inc.
InventorsNiamh B. O'Hara, Mara Couto-Rodriguez, Dorottya Nagy-Szakal, David C. Danko
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Abstract
The disclosure describes a system combining a clinical-grade next-generation sequencing (NGS)-based diagnostic assay and software systems for the detection, identification, and characterization of pathogens in urine specimens to inform treatment of urogenital infections. The system is trained and incorporates a bioinformatic pipeline that uses machine learning (ML) to identify pathogens based on the NGS output from the urine sample.
Claims23
A urine assay, comprising the steps of:
- extracting a set of genomic nucleic acids from a urine sample of a subject, whereby the extracting comprises the steps of:
- removing one or more inhibitors from the urine sample;
- submitting one or more microorganisms in the urine sample to one or more cycles of heating and cooling thus releasing a subset of genomic nucleic acids from the urine sample;
- converting the subset of genomic nucleic acids into a library of fragments that can be sequenced on a next-generation sequencing instrument;
- sequencing the extracted genomic DNA in the next-generation metagenomics sequencing instrument thereby generating a plurality of sequencing reads;
- uploading the plurality of sequencing reads into a system comprising:
- a memory comprising computer readable instructions stored thereon;
- and
- a processor configured to execute the computer readable instructions to:
- receive the plurality of sequencing reads;
- determine whether the plurality of sequencing reads meet one or more thresholds in a pangenome index or a duplication index;
- and
- outputting a result of the assay.
10 more elements
A system for organizing and representing genetic diversity, comprising:
- a memory comprising computer readable instructions stored thereon;
- and
- a processor configured to execute the computer readable instructions to:
- receive a genome sequence from a reference database;
- determine whether the genome sequence meets a threshold;
- if the genome sequence does not meet the threshold, select another genome sequence from the reference database;
- if the genome sequence meets the threshold, process the genome sequence according to a pangenome index and a duplication index,
- wherein the pangenome index integrates sequences from diverse individuals into a unified structure, facilitating rapid searches and analysis of genetic variations, and the duplication index quantifies gene duplications, offering insights into evolutionary and functional consequences;
- generate a score for the processed genome sequence based on input from a human expert, wherein the score comprises metrics, percentages, thresholds, or ranges;
- transmit the score to the reference database for storage, contributing to the refinement of the database;
- and
- continuously update and refine the threshold based on classifications generated in the reference database, wherein the continuous updating is provided by the human expert via a device such that the threshold is updated in real-time.
9 more elements
A computer-implemented method for organizing and representing genetic diversity, comprising:
- receiving a genome sequence from a reference database;
- determining whether the genome sequence meets a threshold;
- if the genome sequence does not meet the threshold, selecting another genome sequence from the reference database;
- if the genome sequence meets the threshold, processing the genome sequence with novel metrics, including a pangenome index and a duplication index, wherein the pangenome index integrates sequences from diverse individuals into a unified structure, facilitating rapid searches and analysis of genetic variations, and the duplication index quantifies gene duplications, offering insights into evolutionary and functional consequences;
- generating a score for the processed genome sequence based on input from a human expert, wherein the score comprises metrics, percentages, thresholds, or ranges;
- transmitting the score to the reference database for storage, contributing to the refinement of the database;
- and
- continuously updating and refining the threshold based on classifications generated in the reference database, wherein the continuous updating is provided by the human expert via a device such that the threshold is updated in real-time.
5 more elements
Dependencies are inferred from the claim text.