System and method for determining a personalized probiotic therapeutic regimen

A system comprising:

• a memory storing instructions;
• and
• one or more hardware processors, wherein the one or more hardware processors are configured by the instructions to:
• receive an information specific to one or more dietary preferences of a subject requiring personalization from one or more communication media;
• define a set of metabolic constraints for the one or more dietary preferences of the subject requiring personalization, wherein the set of metabolic constraints are used for one or more metabolic simulations;
• receive a test biological sample of the subject requiring personalization from the one or more communication media;
• extract DNA (Deoxyribonucleic Acid) from the test biological sample, using a DNA extraction technique;
• determine a microbial abundance of each microbe present in the test biological sample, from the microbial DNA which comprises the gut microbiota, using a set of probes specific to each of the microbes from stretches of DNA sequences sequenced from the microbial DNA extracted from the test biological sample, to obtain a microbial taxonomic profile associated with the test biological sample, wherein the microbial taxonomic profile associated with the test biological sample comprises microbial abundance of each of the microbes corresponding to a set of microbial DNA sequences present in the test biological sample;
• obtain an information specific to a plurality of probiotic organisms from at least one probiotic organisms dataset to evaluate the efficacy of the plurality of probiotic organisms;
• create a plurality of genome scale metabolic models of each of a plurality of microbes comprised in the gut microbiota of the subject and each of the plurality of probiotic organisms whose efficacy are be evaluated;
• assign M-type to the plurality of microbes comprised in the gut microbiota as T=+1 for at least one of beneficial microbes and commensal microbes and T=−1 for at least one of pathogenic microbes and opportunistic microbes;
• perform the one or more metabolic simulations to ascertain a mono-culture growth of each of the plurality of microbes comprising the gut microbiota and each of the organism comprised in the plurality of probiotic organisms by using the defined set of metabolic constraints for simulating the one or more dietary preferences of the subject;
• perform the one or more metabolic simulations to ascertain a co-culture growth of every pair of the microbes comprised in the gut microbiota and each of the organism comprised in the plurality of probiotic organisms by using the defined set of metabolic constraints for simulating the one or more dietary preferences of the subject, wherein the one or more metabolic simulations include in-silico metabolic simulations including a flux balance simulation for simulating metabolic behaviour of an organism under the set of metabolic constraints and simulating an effect of probiotic interventions on a plurality of gut microbiota compositions and the one or more dietary preferences of the subject;
• compute sustainability of each of the organism comprised in the plurality of probiotic organisms for evaluating the capability of each of the organism comprised in the plurality of probiotic organisms to proliferate within the gut, wherein the sustainability is defined as:
• D
• [
• Sustainability
• ]
• a
• =
• ∑
• (
• G
• a
• p
• G
• a
• s
• )
• *
• A
• b
• ;
• where ‘D’ is the set of metabolic constraints defining the one or more dietary preferences of the subject requiring personalization, ‘a’ is the probiotic organism, ‘b’ represents each of the microbes constituting the gut microbiota of the subject requiring personalization, Ab is the abundance of organism ‘b’ the gut microbiota of the subject requiring personalization,
• G
• a
• p
• is the growth rate of organism ‘a’ in co-growth condition with each of the microbes constituting the gut microbiota of the subject requiring personalization ‘b’ in ‘D’,
• G
• a
• s
• is the growth rate of organism ‘a’ in mono-culture condition in ‘D’;
• compute net-effect of each of the organism comprised in the plurality of probiotic organisms for quantifying an overall influence of the plurality of probiotic organisms as a score by summating a plurality of positive influences and a plurality of negative influences on each of the microbes comprised in the gut microbiota, wherein the plurality of positive influences comprise the growth and proliferation of at least one of the beneficial microbes and at least one of the commensal microbes and the plurality of negative influences comprise the growth and proliferation of at least one of the pathogenic microbes and at least one of the opportunistic microbes, wherein the net-effect reflects a net change in growth rates of the plurality of microbes in the gut microbiota as a consequence of administering a probiotic, and wherein the net-effect is defined as:
• D
• [
• Net
• -
• effect
• ]
• a
• =
• ∑
• (
• G
• b
• p
• G
• b
• s
• )
• *
• A
• b
• *
• T
• b
• ;
• where ‘D’ is the set of metabolic constraints defining the one or more dietary preference of the subject requiring personalization, ‘b’ represents each of the microbes constituting the gut microbiota of the subject requiring personalization,
• G
• b
• p
• is the growth rate of organism ‘b’ in co-cultured condition with the probiotic organism ‘a’ in ‘D’,
• G
• b
• s
• is the growth rate of organism ‘b’ in mono-culture condition in ‘D’, Ab is the abundance of organism ‘b’ in the gut microbiota of the subject requiring personalization, Tb is the M-types of organism ‘b’, wherein the abundance of the organism ‘b’ in the gut microbiota of the subject requiring personalization is capped by an abundance factor to avoid over-estimating an influence including the sustainability or the net-effect due to large variation in the abundance of the microbe comprising the gut microbiota of the subject requiring personalization;
• select an efficacious probiotic organism based on at least one of the net-effect and the sustainability;
• design a personalized probiotic intervention regimen in the form of a probiotics treatment to the subject based on the selected efficacious probiotic organism;
• and
• administer the efficacious probiotic organism to the subject to improve the gut microbiota, wherein a dosage requirement for the efficacious probiotic organism is least when the efficacious probiotic organism is selected with a highest sustainability and the net-effect to deliver optimal therapeutic outcome,
• wherein when a probiotic organism with both the highest sustainability and the net-effect is not identified, then a probiotic organism with the highest sustainability and moderately high net-effect is selected and administration or the dosage requirement of the probiotic organism is the least of all available probiotic therapy options,
• wherein when the probiotic organism with a highest net-effect and a moderately high sustainability is selected, then the effect of the probiotic intervention is optimal of all the available probiotic therapy options, and the dosage requirement of the probiotic organism is more frequent or higher dosage, and
• wherein the system is implemented for the probiotics treatment to the subject requiring personalization based on the efficacious probiotic organism to improve the gut microbiota.

One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:

• receiving an information specific to one or more dietary preferences of a subject requiring personalization from one or more communication media;
• defining a set of metabolic constraints for the one or more dietary preferences of the subject requiring personalization, wherein the set of metabolic constraints are used for one or more metabolic simulations;
• receiving a test biological sample of the subject requiring personalization from the one or more communication media;
• extracting DNA (Deoxyribonucleic Acid) from the test biological sample, using a DNA extraction technique;
• determining a microbial abundance of each microbe present in the test biological sample, from the microbial DNA which comprises a gut microbiota, using a set of probes specific to each of the microbes from stretches of DNA sequences sequenced from the microbial DNA extracted from the test biological sample, to obtain a microbial taxonomic profile associated with the test biological sample, wherein the microbial taxonomic profile associated with the test biological sample comprises microbial abundance of each of the microbes corresponding to a set of microbial DNA sequences present in the test biological sample;
• obtaining an information specific to a plurality of probiotic organisms from at least one probiotic organisms dataset to evaluate the efficacy of the plurality of probiotic organisms;
• creating a plurality of genome scale metabolic models of each of a plurality of microbes comprised in the gut microbiota of the subject and each of the plurality of probiotic organisms whose efficacy are be evaluated;
• assigning M-type to the plurality of microbes comprised in the gut microbiota as T=+1 for at least one of beneficial microbes and commensal microbes and T=−1 for at least one of pathogenic microbes and opportunistic microbes;
• performing the one or more metabolic simulations to ascertain a mono-culture growth of each of the plurality of microbes comprising the gut microbiota and each of the organism comprised in the plurality of probiotic organisms by using the defined set of metabolic constraints for simulating the one or more dietary preferences of the subject;
• performing the one or more metabolic simulations to ascertain a co-culture growth of every pair of the plurality of microbes comprised in the gut microbiota and each of the organism comprised in the plurality of probiotic organisms by using the defined set of metabolic constraints for simulating the one or more dietary preferences of the subject, wherein the one or more metabolic simulations include in-silico metabolic simulations including a flux balance simulation for simulating metabolic behaviour of an organism under the set of metabolic constraints and simulating an effect of probiotic interventions on a plurality of gut microbiota compositions and the one or more dietary preferences of the subject;
• computing sustainability of each of the organism comprised in the plurality of probiotic organisms for evaluating the capability of each of the organism comprised in the plurality of probiotic organisms to proliferate within the gut, wherein the sustainability is defined as:
• D
• [
• Sustainability
• ]
• a
• =
• ∑
• (
• G
• a
• p
• G
• a
• s
• )
• *
• A
• b
• ;
• where ‘D’ is the set of metabolic constraints defining the one or more dietary preferences of the subject requiring personalization, ‘a’ is the probiotic organism, ‘b’ represents each of the microbes constituting the gut microbiota of the subject requiring personalization, Ab is the abundance of organism ‘b’ the gut microbiota of the subject requiring personalization,
• G
• a
• p
• is the growth rate of organism ‘a’ in co-growth condition with each of the microbes constituting the gut microbiota of the subject requiring personalization ‘b’ in ‘D’,
• G
• a
• s
• is the growth rate of organism ‘a’ in mono-culture condition in ‘D’;
• computing net-effect of each of the organism comprised in the plurality of probiotic organisms for quantifying an overall influence of the plurality of probiotic organisms as a score by summating a plurality of positive influences and a plurality of negative influences on each of the microbes comprised in the gut microbiota, wherein the plurality of positive influences comprise the growth and proliferation of at least one of the beneficial microbes and at least one of the commensal microbes and the plurality of negative influences comprises the growth and proliferation of at least one of the pathogenic microbes and at least one of the opportunistic microbes, wherein the net-effect reflects a net change in growth rates of the plurality of microbes in the gut microbiota as a consequence of administering a probiotic, and wherein the net-effect is defined as:
• D
• [
• Net
• -
• effect
• ]
• a
• =
• ∑
• (
• G
• b
• p
• G
• b
• s
• )
• *
• A
• b
• *
• T
• b
• ;
• where ‘D’ is the set of metabolic constraints defining the one or more dietary preference of the subject requiring personalization, ‘b’ represents each of the microbes constituting the gut microbiota of the subject requiring personalization,
• G
• b
• p
• is the growth rate of organism ‘b’ in co-cultured condition with the probiotic organism ‘a’ in ‘D’,
• G
• b
• s
• is the growth rate of organism ‘b’ in mono-culture condition in ‘D’, Ab is the abundance of organism ‘b’ in the gut microbiota of the subject requiring personalization, Tb is the M-types of organism ‘b’, wherein the abundance of the organism ‘b’ in the gut microbiota of the subject requiring personalization is capped by an abundance factor to avoid over-estimating an influence including the sustainability or the net-effect due to large variation in the abundance of the microbe comprising the gut microbiota of the subject requiring personalization;
• selecting an efficacious probiotic organism based on at least one of the net-effect and the sustainability;
• designing a personalized probiotic intervention regimen in the form of a probiotics treatment to the subject based on the selected efficacious probiotic organism;
• and
• administering the efficacious probiotic organism to the subject to improve the gut microbiota, wherein a dosage requirement for the efficacious probiotic organism is least when the efficacious probiotic organism is selected with a highest sustainability and the net-effect to deliver optimal therapeutic outcome,
• wherein when a probiotic organism with both the highest sustainability and the net-effect is not identified, then a probiotic organism with the highest sustainability and moderately high net-effect is selected and administration or the dosage requirement of the probiotic organism is the least of all available probiotic therapy options,
• wherein when the probiotic organism with a highest net-effect and a moderately high sustainability is selected, then the effect of the probiotic intervention is optimal of all the available probiotic therapy options, and the dosage requirement of the probiotic organism is more frequent or higher dosage, and
• wherein a method is implemented for the probiotics treatment to the subject requiring personalization based on the efficacious probiotic organism to improve the gut microbiota.