Method and system for microbiome-derived diagnostics and therapeutics for conditions associated with microbiome taxonomic features

Abstract

A method for at least one of characterizing, diagnosing, and treating a condition associated with microbiome taxonomic features in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

We claim: 
     
         1 . A method for characterizing a gastrointestinal or gastroesophageal reflux condition, the method comprising:
 at a sample handling network, receiving an aggregate set of samples from a population of subjects;   at a computing system in communication with the sample handling network, generating a microbiome composition dataset and a microbiome functional feature dataset for the population of subjects upon processing content of each of the aggregate set of samples, wherein processing content of each of the aggregate set of samples comprises processing nucleic content with a fragmentation operation, a multiplexed amplification operation using a set of primers, and a sequencing analysis operation;   at the computing system, receiving a supplementary dataset that is informative of gastrointestinal reflux condition presence within the population of subjects;   at the computing system, transforming the supplementary dataset and features extracted from at least one of the microbiome composition and the microbiome functional feature datasets into a characterization model of the gastrointestinal reflux condition; and   based upon the characterization model, generating a therapy model configured to improve a health state of an individual diagnosed with the gastrointestinal reflux condition by the characterization model.   
     
     
         2 . The method of  claim 1 , further comprising: diagnosing the individual with the gastrointestinal reflux condition, upon generating an association between a sample processed from the individual and a set of taxonomic features and a set of functional features according to the characterization model. 
     
     
         3 . The method of  claim 2 , wherein the set of taxonomic features includes at least one of: a first taxonomic feature related to Clostridiaceae (family), a second taxonomic feature related to Lactobacillaceae (family), a third taxonomic feature related to  Sarcina  (genus), a fourth taxonomic feature related to  Blautia  (genus), a fifth taxonomic feature related to Ruminococcaceae (family), a sixth taxonomic feature related to  Proteobacteria  (phylum), and a seventh taxonomic feature related to  Terrisporobacter  (genus). 
     
     
         4 . The method of  claim 2 , wherein the set of taxonomic features includes at least three of: a first taxonomic feature related to Clostridiaceae (family), a second taxonomic feature related to Lactobacillaceae (family), a third taxonomic feature related to  Sarcina  (genus), a fourth taxonomic feature related to  Blautia  (genus), a fifth taxonomic feature related to Ruminococcaceae (family), a sixth taxonomic feature related to  Proteobacteria  (phylum), and a seventh taxonomic feature related to  Terrisporobacter  (genus). 
     
     
         5 . The method of  claim 2 , wherein the set of taxonomic features includes at least five of: a first taxonomic feature related to Clostridiaceae (family), a second taxonomic feature related to Lactobacillaceae (family), a third taxonomic feature related to  Sarcina  (genus), a fourth taxonomic feature related to  Blautia  (genus), a fifth taxonomic feature related to Ruminococcaceae (family), a sixth taxonomic feature related to  Proteobacteria  (phylum), and a seventh taxonomic feature related to  Terrisporobacter  (genus). 
     
     
         6 . The method of  claim 2 , wherein the set of taxonomic features includes at least six of: a first taxonomic feature related to Clostridiaceae (family), a second taxonomic feature related to Lactobacillaceae (family), a third taxonomic feature related to  Sarcina  (genus), a fourth taxonomic feature related to  Blautia  (genus), a fifth taxonomic feature related to Ruminococcaceae (family), a sixth taxonomic feature related to  Proteobacteria  (phylum), a seventh taxonomic feature related to  Terrisporobacter  (genus), and an eighth taxonomic feature related to  Faecalibacterium  (genus). 
     
     
         7 . The method of  claim 2 , wherein the set of taxonomic features includes at least one of: a ninth taxonomic feature related to  Clostridium  (genus), a tenth taxonomic feature related to  Odoribacter  (genus), a eleventh taxonomic feature related to  Thalassospira  (genus) and a twelfth taxonomic feature related to  Barnesiella  (genus). 
     
     
         8 . The method of  claim 2 , wherein the set of taxonomic features includes at least one of: a thirteenth taxonomic feature related to Rhodospirillaceae (family), a fourteenth taxonomic feature related to Lachnospiraceae (family), a fifteenth taxonomic feature related to Bifidobacteriaceae (family) and a sixteenth taxonomic feature related to Flavobacteriaceae (family). 
     
     
         9 . The method of  claim 2 , wherein the set of taxonomic features includes at least one of: a seventeenth taxonomic feature related to  Alphaproteobacteria  (class) and an eighteenth taxonomic feature related to  Flavobacteriia  (class). 
     
     
         10 . The method of  claim 2 , wherein the set of functional features includes at least one of: a first functional feature related to cell motility, a second functional feature related to secretion system function, a third functional feature related to selenocompound metabolism, a fourth functional feature related to fructose and mannose metabolism, a fifth functional feature related to carbohydrate metabolism, and a sixth functional feature related to bacterial chemotaxis. 
     
     
         11 . The method of  claim 2 , wherein the set of functional features includes at least three of: a first functional feature related to cell motility, a second functional feature related to secretion system function, a third functional feature related to selenocompound metabolism, a fourth functional feature related to fructose and mannose metabolism, a fifth functional feature related to carbohydrate metabolism, and a sixth functional feature related to bacterial chemotaxis. 
     
     
         12 . The method of  claim 2 , wherein the set of functional features includes at least five of: a first functional feature related to cell motility, a second functional feature related to secretion system function, a third functional feature related to selenocompound metabolism, a fourth functional feature related to fructose and mannose metabolism, a fifth functional feature related to carbohydrate metabolism, and a sixth functional feature related to bacterial chemotaxis. 
     
     
         13 . The method of  claim 2 , wherein generating the characterization model comprises analyzing a set of features from the microbiome composition dataset with a statistical analysis, wherein the set of features includes features associated with: relative abundance of different taxonomic groups represented in the microbiome composition dataset, interactions between different taxonomic groups represented in the microbiome composition dataset, and phylogenetic distance between taxonomic groups represented in the microbiome composition dataset. 
     
     
         14 . The method of  claim 2 , further comprising: at an output device associated with the individual and in communication with the computing system, promoting a therapy to the individual diagnosed with the gastrointestinal reflux condition, in accordance with the therapy model, wherein promoting the therapy comprises promoting a microbiome modifying therapy to the individual, the microbiome modifying therapy comprising a consumable configured to affect a taxonomic group associated with at least one of the set of taxonomic features and the set of functional features, in order to improve the health state the individual with the gastrointestinal reflux condition. 
     
     
         15 . A method for diagnosing and treating a gastrointestinal reflux condition, the method comprising:
 at a sample handling network, processing content of a sample from a subject, thereby generating a microbiome composition dataset and a microbiome functional feature dataset associated with the sample;   at a computing system in communication with the sample handling network, identifying an association between the sample and at least one of a taxonomic feature from the microbiome composition dataset and a functional feature from the microbiome functional feature dataset;   based upon the association, diagnosing the subject with the gastrointestinal reflux condition; and   delivering a therapy to the subject, wherein delivering the therapy comprises delivering a microbiome modifying therapy to the subject in order to improve a health state of the subject with the gastrointestinal reflux condition.   
     
     
         16 . The method of  claim 15 , wherein diagnosing the subject with the gastrointestinal reflux condition comprises diagnosing the subject with at least one of acid reflux and gastroesophageal reflux disease (GERD) based upon at least one of the taxonomic feature from the microbiome composition dataset and a functional feature from the microbiome functional feature dataset. 
     
     
         17 . The method of  claim 16 , wherein diagnosing the subject with the gastrointestinal reflux condition comprises identifying the association between the sample and at least one of: a set of taxonomic features from the microbiome composition dataset and a set of functional features from the microbiome functional feature dataset. 
     
     
         18 . The method of  claim 17 , wherein the set of taxonomic features includes at least one of: a first taxonomic feature related to Clostridiaceae (family), a second taxonomic feature related to Lactobacillaceae (family), a third taxonomic feature related to  Sarcina  (genus), and a fourth taxonomic feature related to  Blautia  (genus); and wherein the set of functional features includes at least one of: a first functional feature related to cell motility, a second functional feature related to secretion system function, and a third functional feature related to selenocompound metabolism. 
     
     
         19 . The method of  claim 17 , wherein the set of taxonomic features includes at least two of: a first taxonomic feature related to Clostridiaceae (family), a second taxonomic feature related to Lactobacillaceae (family), a third taxonomic feature related to  Sarcina  (genus), and a fourth taxonomic feature related to  Blautia  (genus); and wherein the set of functional features includes at least two of: a first functional feature related to cell motility, a second functional feature related to secretion system function, a third functional feature related to selenocompound metabolism, and a fourth functional feature related to fructose and mannose metabolism. 
     
     
         20 . The method of  claim 17 , wherein the set of taxonomic features includes at least one of: a fifth taxonomic feature related to Ruminococcaceae (family), a sixth taxonomic feature related to  Proteobacteria  (phylum), a seventh taxonomic feature related to  Terrisporobacter  (genus), and an eighth taxonomic feature related to  Faecalibacterium  (genus); and wherein the set of functional features includes at least one of: a fourth functional feature related to fructose and mannose metabolism, a fifth functional feature related to carbohydrate metabolism, and a sixth functional feature related to bacterial chemotaxis. 
     
     
         21 . The method of  claim 17 , wherein the set of taxonomic features includes at least two of: a fifth taxonomic feature related to Ruminococcaceae (family), a sixth taxonomic feature related to  Proteobacteria  (phylum), a seventh taxonomic feature related to  Terrisporobacter  (genus), and an eighth taxonomic feature related to  Faecalibacterium  (genus); and wherein the set of functional features includes at least two of: a fourth functional feature related to fructose and mannose metabolism, a fifth functional feature related to carbohydrate metabolism, and a sixth functional feature related to bacterial chemotaxis. 
     
     
         22 . The method of  claim 15 , wherein the functional feature is derived from at least one of:
 clusters of orthologous groups features, features derived from a Kyoto Encyclopedia of Genes and Genomes and gene ontology features.   
     
     
         23 . The method of  claim 15 , wherein delivering the therapy comprises promoting at least one of a probiotic therapy and a prebiotic therapy to the subject, wherein the therapy comprises a consumable that selectively modulates at least one of: a population size of a desired taxon and a population size of a desired microbiome function, associated with improving the health state of the subject with the gastrointestinal reflux condition.