| CPC G16B 5/20 (2019.02) [G16B 5/00 (2019.02)] | 8 Claims |
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1. A method for analyzing metabolic state of a cell at a genome scale by measuring concentrations of a one or more metabolites, the method comprising:
measuring a concentration of the one or more metabolites present in the cell and the cell culture by Quadrupole time-of-flight mass spectrometry (Q-Tof), liquid chromatography-mass spectrometric multiple reaction monitoring (LC-MRM/MS), nuclear magnetic resonance (NMR), ultra-performance liquid chromatography (UPLC), spectrophotometry, or circular dichroism;
measuring a growth rate of the cell in the cell culture, wherein the growth rate of the cell is measured from one of an optical density (OD) of the cell culture or cell doubling rate obtained from one of a cell counter instrument, a microscopic or cytometric method;
creating, via one or more processors, a genome scale metabolic model (GEM) for the cell based on transcriptomic data, metabolomic data or thermodynamic constraints of a cellular organism, wherein the GEM model comprises a biomass function as an objective function, and wherein the measured concentration of the one or more metabolites is incorporated into a combinatorial sink reaction of the GEM, the GEM comprising a combinatorial sink function:
 wherein m is a number of metabolite concentrations measured, m⊆M where M is all the produced metabolites present in the network, ci is the concentration of the metabolite measured (in mM units) and vaccum is a sink function;
calculating, via the one or more hardware processors, a predetermined first percentage value and a predetermined second percentage value of a flux based on the measured growth rate of the cell;
performing, via the one or more hardware processors, a first steady state simulation of the GEM to obtain the flux through a biomass function wherein the biomass function is optimized by applying minimal constraints on reaction fluxes, wherein the minimal constraints are based on predefined input parameters comprising at least one of type and concentration of nutrients, pH, oxygen availability, and antimicrobial treatment, and wherein the obtained flux through biomass function pertains to steady state flux values through all reactions in the GEM;
constraining, via the one or more hardware processors, a lower bound of the biomass function by one of restricting a reaction flux to a predetermined first percentage value of the obtained flux through the biomass function using the first steady state simulation or to the predetermined first percentage value of the flux calculated based on the measured growth rate of the cell;
constraining, via the one or more hardware processors, an upper bound of the biomass function by one of restricting the reaction flux to a predetermined second percentage value of the obtained flux through the biomass function using the first steady state simulation or to the predetermined second percentage value of the flux calculated based on the measured growth rate of the cell;
performing, via the one or more hardware processors, a second steady state simulation to optimize reaction flux through the combinatorial sink reaction;
calculating, via the one or more hardware processors, reaction fluxes through all reactions in the GEM from the second steady state simulation;
determining the metabolic state of the cell based on the calculated fluxes from the second steady state simulation;
determining an effect of uptake of nutrients by the cell in the cell culture on biomass production or production of a biotechnological or a pharmaceutical compound in the cell culture based on the determined metabolic state of the cell; and
optimizing one or more reactions in the GEM based on the determined effect of the nutrients' uptake for increasing yield of a biomass, the biotechnological compound or the pharmaceutical compound in the cell culture.
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