Genome scale metabolic network model-based metabolic engineering design prediction method

Abstract

The invention discloses a genome scale metabolic network model-based metabolic engineering design prediction method, which comprises the following steps of: acquiring target bacteria wet experimental data and a high-quality genome scale metabolic network model respectively; setting simulation conditions according to the wet experimental data; simulating the growth state of experimental bacteria to obtain metabolic flux distribution and simulating the growth state of optimized engineering bacteria to obtain metabolic flux distribution; comparing the two metabolic flux distributions to determine difference of reaction flux distribution between the two metabolic flux distributions; obtaining a corresponding gene prediction result according to the comparison result and gene-reaction correspondence of the genome scale metabolic network model, thereby determining metabolic engineering modification required for modifying the experimental bacteria into the optimized engineering bacteria to make a corresponding wet experimental strategy. The genome scale metabolic network model-based metabolic engineering design prediction method can be applied to any species with a genome scale metabolic network and simulating and predicting any product in a network model computing capacity range, and particularly has great guiding significance to metabolic engineering bacteria with unclear gene sequences.

Description

technical field [0001] The invention relates to computer prediction of metabolic engineering design. In particular, it relates to a metabolic engineering design prediction method based on a genome-scale metabolic network model that can be applied to any species with a genome-scale metabolic network. Background technique [0002] At present, the computer prediction using the genome-scale metabolic network model is mostly the prediction of essential genes or the prediction of the utilization of different substrates. The method used is flux balance analysis. The optimal synthesis pathway of the target product can be obtained through computer prediction, but it cannot be determined How wild bacteria or engineered bacteria used in the laboratory can be modified to achieve the optimal synthesis pathway. At the same time, the metabolic network model established based on the genome of wild bacteria cannot simulate the metabolic status of engineered bacteria whose gene sequence is n...

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Problems solved by technology

[0002] At present, the computer prediction using the genome-scale metabolic network model is mostly the prediction of essential genes or the prediction of the utilization of different substrates. The method used is flux balance analysis. The optimal synthesis pathway of the target product can be obtained through computer prediction, but it cannot be determined How can wild bacteria or engineered bacteria used in the laboratory be modified to achieve the optimal synthesis route?

At the same time, the metabolic network model established based on the genome of wild bacteria cannot simulate the metabolic status of engineered bacteria whose gene sequence is not yet known

In addition, for Saccharomyces cerevisiae, there has been a method to predict the increase in the yield of the target product by adding exogenous genes, but there is no computer prediction method for metabolic engineering of existing genes in the bacteria

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