Methods for identifying interactions amongst microorganisms
AssigneeThe Regents of the University of California
InventorsNicholas B. Justice, Adam P. Arkin
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Abstract
Disclosed herein are methods, compositions, and systems for determining specific microbial taxa, within a complex consortia of mixed taxa, which are interacting with each other in an environment of interest. In some embodiments, after diluting a sample comprising multiple different taxa of microorganisms, dilutions of the sample are cultivated for determining taxonomic information and interactions of multiple taxa of microorganisms in the sample.
Claims23
-46. (canceled)
A method for conducting a multi-variate assay of a plurality of taxa of microorganisms in a sample to generate an output indicative of the fitness of one or more taxa in the sample, the method comprising:
- obtaining the sample comprising a plurality of taxa of microorganisms;
- generating a plurality of subcultures from the sample;
- adjusting variables for one or more subcultures in the plurality of subcultures, the variables comprising:
- one or more biotic conditions, and
- one or more abiotic conditions,
- assaying the plurality of taxa in the plurality of subcultures;
- and
- generating an output indicative of the fitness of the one or more taxa in the microbial population with respect to at least one of the one or more variables.
A computer system for identifying a plurality of co-occurring outputs in a plurality of strings, comprising:
- a computer-readable memory storing executable instructions;
- and
- a computer processor programmed by the executable instructions to:
- receive a file comprising a plurality of strings, each string (1) indexed by a first parameter and a second parameter and (2) corresponding to an output wherein the plurality of strings comprises sequence information, and wherein the sequence information corresponds to a plurality of taxa of microorganisms in a sample;
- quantify an abundance of each of the plurality of strings indexed by the first parameter and the second parameter to generate a plurality of string counts, each string count of the plurality corresponding to the output to generate a plurality of string counts;
- and
- process the plurality of string counts to generate the plurality of co-occurring outputs in the plurality of strings, wherein the plurality of co-occurring outputs is significantly non-random when processed with respect to the first parameter and the second parameter;
- save the plurality of co-occurring outputs to the memory.
(canceled)
(canceled)
A computer system for determining a microbial interaction, comprising:
- a computer-readable memory storing executable instructions;
- and
- a computer processor programmed by the executable instructions to:
- receive taxonomic information of taxa in a plurality of cultivated dilutions, wherein the taxonomic information comprises abundances of the taxa in the plurality of cultivated dilutions, wherein the plurality of cultivated dilutions is cultivated from a subset of a plurality of dilutions of a sample in a first cultivation condition, wherein the sample comprises a plurality of taxa of microorganisms, wherein the subset of the plurality of dilutions comprises a first dilution and a second dilution with an identical inoculum density, wherein the first dilution comprises a first taxon and a second taxon, wherein the second dilution comprises the first taxon and not the second taxon, and wherein an abundance of the first taxon in a first cultivated dilution of the plurality of cultivated dilutions cultivated from the first dilution is different from an abundance of the first taxon in a second cultivated dilution of the plurality of cultivated dilutions cultivated from the second dilution;
- and
- process the taxonomic information of the taxa in the plurality of cultivated dilutions to identify a non-random occurrence of the first taxon in the presence or absence of the second taxon to determine an interaction within the plurality of taxa of microorganisms in the sample in the first cultivation condition.
Dependencies are inferred from the claim text.