METHODS, APPARATUSES, AND SYSTEMS FOR ANALYZING MICROORGANISM STRAINS FROM COMPLEX HETEROGENEOUS COMMUNITIES, PREDICTING AND IDENTIFYING FUNCTIONAL RELATIONSHIPS AND INTERACTIONS THEREOF, AND SELECTING AND SYNTHESIZING MICROBIAL ENSEMBLES BASED THEREON
First Claim
1. A method for forming a synthetic ensemble of active microorganism strains configured to alter a property in a biological environment, based on two or more sample sets each having a plurality of environmental parameters, at least one parameter of the plurality of environmental parameters being a common environmental parameter that is similar between the two or more sample sets and at least one environmental parameter being a different environmental parameter that is different between each of the two or more sample sets, each sample set including at least one sample comprising a heterogeneous microbial community obtained from a biological sample source, at least one of the active microorganism strains being a subtaxon of one or more organism types, the method comprising:
- detecting the presence of a plurality of microorganism types in each sample;
determining the absolute number of cells of each of the detected microorganism types in each sample;
measuring the number of unique first markers in each sample, and quantity thereof, a unique first marker being a marker of a microorganism strain;
measuring the level of expression of one or more unique RNA markers, wherein a unique RNA marker is a marker of activity of a microorganism strain;
determining activity of each of the detected microorganism strains for each sample based on the level of expression of the one or more unique RNA markers exceeding a specified threshold;
calculating the absolute cell count of each detected active microorganism strain in each sample based upon the quantity of the one or more first markers and the absolute number of cells of the microorganism types from which the one or more microorganism strains is a subtaxon, the one or more active microorganism strains expressing one or more unique RNA markers above the specified threshold;
analyzing the active microorganism strains of the two or more sample sets, the analyzing including conducting nonparametric network analysis of each of the active microorganism strains for each of the two or more sample sets, the at least one common environmental parameter, and the at least one different environmental parameter, the nonparametric network analysis including (1) determining the maximal information coefficient score between each active microorganism strain and every other active microorganism strain and (2) determining the maximal information coefficient score between each active microorganism strain and the at least one different environmental parameter;
selecting a plurality of active microorganism strains from the one or more active microorganism strains based on the nonparametric network analysis; and
forming a synthetic ensemble of active microorganism strains comprising the selected plurality of active microorganism strains and a microbial carrier medium, the ensemble of active microorganism strains configured to selectively alter a property of a biological environment when the synthetic ensemble of active microorganism strains is introduced into that biological environment.
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Abstract
Methods, apparatuses, and systems for screening, analyzing and selecting microorganisms from complex heterogeneous communities, predicting and identifying functional relationships and interactions thereof, and synthesizing microbial ensembles based thereon are disclosed. Methods for identifying and determining the absolute cell count of microorganism types and strains, along with identifying the network relationships between active microorganisms and environmental parameters, are also disclosed.
22 Citations
30 Claims
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1. A method for forming a synthetic ensemble of active microorganism strains configured to alter a property in a biological environment, based on two or more sample sets each having a plurality of environmental parameters, at least one parameter of the plurality of environmental parameters being a common environmental parameter that is similar between the two or more sample sets and at least one environmental parameter being a different environmental parameter that is different between each of the two or more sample sets, each sample set including at least one sample comprising a heterogeneous microbial community obtained from a biological sample source, at least one of the active microorganism strains being a subtaxon of one or more organism types, the method comprising:
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detecting the presence of a plurality of microorganism types in each sample; determining the absolute number of cells of each of the detected microorganism types in each sample; measuring the number of unique first markers in each sample, and quantity thereof, a unique first marker being a marker of a microorganism strain; measuring the level of expression of one or more unique RNA markers, wherein a unique RNA marker is a marker of activity of a microorganism strain; determining activity of each of the detected microorganism strains for each sample based on the level of expression of the one or more unique RNA markers exceeding a specified threshold; calculating the absolute cell count of each detected active microorganism strain in each sample based upon the quantity of the one or more first markers and the absolute number of cells of the microorganism types from which the one or more microorganism strains is a subtaxon, the one or more active microorganism strains expressing one or more unique RNA markers above the specified threshold; analyzing the active microorganism strains of the two or more sample sets, the analyzing including conducting nonparametric network analysis of each of the active microorganism strains for each of the two or more sample sets, the at least one common environmental parameter, and the at least one different environmental parameter, the nonparametric network analysis including (1) determining the maximal information coefficient score between each active microorganism strain and every other active microorganism strain and (2) determining the maximal information coefficient score between each active microorganism strain and the at least one different environmental parameter; selecting a plurality of active microorganism strains from the one or more active microorganism strains based on the nonparametric network analysis; and forming a synthetic ensemble of active microorganism strains comprising the selected plurality of active microorganism strains and a microbial carrier medium, the ensemble of active microorganism strains configured to selectively alter a property of a biological environment when the synthetic ensemble of active microorganism strains is introduced into that biological environment. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method of forming an active microorganism bioensemble of active microorganism strains configured to alter a property in a target biological environment, comprising:
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obtaining at least two samples sharing at least one common characteristic and having at least one different characteristic; for each sample, detecting the presence of one or more microorganism types in each sample; determining a number of each detected microorganism type of the one or more microorganism types in each sample; measuring a number of unique first markers in each sample, and quantity thereof, each unique first marker being a marker of a microorganism strain; integrating the number of each microorganism type and the number of the first markers to yield the absolute cell count of each microorganism strain present in each sample; measuring at least one unique second marker for each microorganism strain based on a specified threshold to determine an activity level for that microorganism strain in each sample; filtering the absolute cell count by the determined activity to provide a list of active microorganisms strains and their respective absolute cell counts for each of the at least two samples; comparing the filtered absolute cell counts of active microorganisms strains for each of the at least two samples with at least one measured metadata for each of the at least two samples, the comparison including determining the co-occurrence of the active microorganism strains in each sample with the at least one measured metadata, determining the co-occurrence of the active microorganism strains and the at least one measured metadata in each sample including creating matrices populated with linkages denoting metadata and microorganism strain relationships, the absolute cell count of the active microorganism strains, and the measure of the unique second markers, to represent one or more heterogeneous microbial community networks; grouping the active microorganism strains into at least two groups according to predicted function and/or chemistry based on at least one of nonparametric network analysis and cluster analysis identifying connectivity of each active microorganism strain and measured metadata within an active heterogeneous microbial community network; selecting at least one microorganism strain from each of the at least two groups; and combining the selected microorganism strains and with a carrier medium to form a bioensemble of active microorganisms configured to alter a property corresponding to the at least one metadata of target biological environment when the bioensemble is introduced into that target biological environment. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification