Granted Patent B2

US 10,360,348 · App. 15/621,445 · Granted Jul 23, 2019

Inventors: Zachary Apte (San Francisco, CA); Daniel Almonacid (San Francisco, CA); Jessica Richman (San Francisco, CA)

Assignee: uBiome, Inc.

G06F19/3418G16B35/00G16B40/00G16B50/00G16C20/60G16H50/20Y02A90/26

Abstract

Claims (30)

1. A method for characterizing a stroke condition for a subject, the method comprising:

for each sample of an aggregate set of samples comprising at least one sample comprising microorganisms associated with the stroke condition:

determining nucleic acid sequences of a microorganism component of the sample upon fragmenting nucleic acid material from the sample and amplifying the fragmented nucleic acid material using a primer; and

determining alignments of the nucleic acid sequences to reference nucleic acid sequences set;

generating a microbiome feature dataset based on the alignments;

generating a characterization model of the stroke condition based on the microbiome feature dataset;

characterizing the subject with the stroke condition based upon processing a subject sample of the subject with the characterization model;

determining a therapy for the subject with the stroke condition upon processing the sample subject with a therapy model; and

providing the therapy to the subject, wherein the therapy is operable to adjust microbiome function in the subject.

2. The method of claim 1 , further comprising: determining, with a primer design model, the primer for the nucleic acid sequences associated with the stroke condition.

3. The method of claim 2 , wherein determining the primer comprises identifying at least one primer corresponding to a 16S RNA sequence associated with a set of taxa.

4. The method of claim 1 , wherein the microbiome feature dataset comprises at least one of: microbiome composition features associated with a set of taxa, microbiome composition diversity features and microbiome functional diversity features.

5. The method of claim 4 , wherein generating the characterization model of the stroke condition comprises evaluating features of the microbiome feature dataset associated with a set of taxonomic features associated with Cronobacter (genus).

6. The method of claim 5 , wherein generating the characterization model of the stroke condition comprises evaluating features of the microbiome feature dataset further associated with Cronobacter sakazakii (species).

7. The method of claim 4 , wherein generating the characterization model of the stroke condition comprises evaluating features of the microbiome feature dataset associated with a set of taxonomic features associated with Gammaproteobacteria (class).

8. The method of claim 7 , wherein generating the characterization model of the stroke condition comprises evaluating features of the microbiome feature dataset further associated with at least one of: Clostridiales bacterium A2-162 (species), Barnesiella (genus), Erysipelotrichaceae (family), and Pseudomonadales (order).

9. The method of claim 4 , wherein generating the characterization model comprises evaluating features of the microbiome feature dataset associated with at least one of: clusters of orthologous groups of proteins features, genomic functional features from the Kyoto Encyclopedia of Genes and Genomes (KEGG), chemical functional features, and systemic functional features.

10. The method of claim 1 , wherein generating the characterization model further comprises extracting a supplementary dataset from a population of subjects, the supplementary dataset comprising data from at least one of: a neurological examination, computed tomography imaging, magnetic resonance imaging, Doppler ultrasound, and arteriography.

11. A method for characterizing and treating a stroke condition in a subject, the method comprising:

receiving a sample from the subject;

determining a microorganism sequence for content of the sample upon amplifying nucleic acid material of the sample using a primer;

generating a microbiome feature dataset from the microorganism sequence;

generating a characterization of the stroke condition in the subject upon processing the microbiome feature dataset with a characterization model generated from a set of subjects; and

providing a therapy to the subject based on the characterization, wherein the therapy comprises a consumable operable to modulate microbiome function in the subject with the stroke condition.

12. The method of claim 11 , wherein generating the characterization comprises evaluating features of the microbiome feature dataset associated with Cronobacter (genus).

13. The method of claim 12 , wherein generating the characterization comprises evaluating features of the microbiome feature dataset further associated with Cronobacter sakazakii (species).

14. The method of claim 12 , wherein generating the characterization comprises evaluating features of the microbiome feature dataset further associated with Gammaproteobacteria (class).

15. The method of claim 13 , wherein generating the characterization comprises evaluating features of the microbiome feature dataset further associated with at least one of: Clostridiales bacterium A2-162 (species), Barnesiella (genus), Erysipelotrichaceae (family), and Pseudomonadales (order).

16. The method of claim 11 , wherein providing the therapy comprises providing physical rehabilitation therapy to the subject with the stroke condition.

17. The method of claim 16 , wherein providing the consumable comprises providing a medication to the subject with the stroke condition.

Assignments (2)

Continuity (19)