WO2022126698A1

WO2022126698A1 - Synthetic gene circuit model and construction method

Info

Publication number: WO2022126698A1
Application number: PCT/CN2020/138716
Authority: WO
Inventors: 傅雄飞; 袁慧丽; 白阳
Original assignee: 中国科学院深圳先进技术研究院
Priority date: 2020-12-16
Filing date: 2020-12-23
Publication date: 2022-06-23
Also published as: CN112562782B; CN112562782A

Abstract

A method for constructing a synthetic gene circuit model. The method comprises: establishing a gene circuit constrained resource allocation flux balance analysis method, and simulating a cell growth rate; constructing a growth rate regulated gene circuit model by combining the cell growth rate with a gene circuit dynamic model, and obtaining a dynamic behavior result of a gene circuit; and performing a quantitative experiment on the dynamic behavior of the gene circuit to obtain an experiment result, and correcting the model by means of a comparison result. According to the method, Escherichia coli is taken as a research object, the physiological state of cells is fully characterized using the method of combining flux balance analysis and a bacterial growth law on the basis of an Escherichia coli genome metabolic network model, the growth rate of the cells is simulated, and in conjunction with quantitative experiment data for standardizing a typical gene circuit, a gene circuit dynamic model depending on the cell growth rate is constructed, thereby accurately predicting the influence of the cell growth rate on the function of the synthetic gene circuit.

Description

A synthetic gene circuit model and construction method

technical field

The invention relates to the field of synthetic gene circuit model construction, in particular to a synthetic gene circuit model and a construction method.

Background technique

Traditional gene circuit design is a custom, manual, and error-prone process, which usually suffers from long experimental cycles, high trial-and-error costs, and difficulty in scaling up. Designing and simulating circuits with computer-aided tools is changing that. Among them, the most representative one is Cello, a tool developed in 2016 for automatically designing complex gene circuits. Although this method can greatly improve the design efficiency of artificial gene circuits, it does not consider the influence of the interaction between gene circuits and the physiological state of cells.

Studies have shown that the metabolic properties, intracellular resource allocation and gene circuits of chassis cells are interconnected and interfere with each other. On the one hand, the resources (ribosomes, amino acids, energy, etc.) in cells for life activities are limited. In order to optimize their own growth, cells need to balance these resources according to the growth environment. The introduction of synthetic gene circuits would disrupt this balance, placing an additional burden on the chassis cells and slowing down cell growth. The resource redistribution of cellular proteins not only affects the distribution of cellular metabolic fluxes, but also regulates the preset functions of gene circuits. On the other hand, the expression of synthetic gene circuits will also change the distribution of metabolic flux in the metabolic pathway, which will eventually lead to the rearrangement of the distribution of metabolic flux in the entire network. In short, the interference effect between the gene circuit and the physiological state of the chassis cells affects the global state including the gene circuit and the accuracy of the prediction of the performance of the gene circuit. Therefore, the design and simulation of synthetic gene circuits requires precise consideration of the physiological state of the chassis cells.

Based on the fact that cells must balance limited protein, ribosome and energy pools to achieve different tasks, some studies have combined gene expression with cell growth rate by constructing mathematical models to accurately predict the impact of different synthetic elements on host behavior. A team has developed an integrated model framework that combines the biochemical dynamics of synthetic gene circuits with a model of the physiological state of the chassis cells to accurately predict the behavior of gene circuits and improve the effectiveness of synthetic circuit design. These models can comprehensively capture the overall physiological changes and parameters as well as the effects of exogenous gene circuits on gene expression mechanisms, providing a theoretical reference for understanding how gene circuits are linked to chassis cell resource allocation and growth. However, these models are established by simply analyzing the experimental data from different systems and different conditions, so there are generally problems of insufficient reliability and difficult to popularize and apply. In addition, these works remain at the level of theoretical research, lacking direct and systematic quantitative experimental verification.

SUMMARY OF THE INVENTION

Therefore, the purpose of the present invention is to address the above problems, and provide a synthetic gene circuit model and construction method, electronic device and storage medium combined with the physiological state of bacteria.

According to a first aspect of the present disclosure, there is provided a method for constructing a synthetic gene circuit model, the method comprising: establishing a flow balance analysis method for gene circuit intervention resource allocation, and simulating cells according to the flow balance analysis method for gene circuit intervention resource allocation Growth rate; Substitute the cell growth rate into the gene circuit dynamics model to construct a growth rate-regulated gene circuit model, simulate the dynamic behavior of the gene circuit according to the growth rate-regulated gene circuit model, and obtain the simulation results; Quantitative experiments are performed on behaviors, experimental results are obtained, and the gene circuit coupling model is revised by comparing the simulation results with the experimental results.

In some possible embodiments, the flow balance analysis method of gene circuit intervention resource allocation is configured to construct a bacterial genome metabolic network model with the cellular proteome data related to the synthetic gene circuit as an additional constraint.

In some possible embodiments, the gene circuit coupling model takes Escherichia coli as the research object, and is constructed based on the genome metabolic network model of Escherichia coli cells.

In some possible embodiments, types of synthetic gene circuits include oscillatory circuits, toggle switch circuits, and logic gate circuits.

According to a second aspect of the present disclosure, a synthetic gene circuit model is provided, which is constructed by the aforementioned method for constructing a synthetic gene circuit model.

According to a third aspect of the present disclosure, a synthetic gene circuit model is provided, which includes the metabolic properties of chassis cells and the physiological state of proteomic resource allocation and the dynamic behavior of exogenous gene circuits.

According to a fourth aspect of the present disclosure, there is provided an electronic device including a processor, a memory, and a program or instruction stored in the memory and executable on the processor, the program or instruction being executed by the processor to achieve the aforementioned synthesis Steps of a method for constructing a gene circuit model.

According to a fifth aspect of the present disclosure, a readable storage medium is provided, and a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the steps of the aforementioned method for constructing a synthetic gene circuit model are implemented.

Based on the Escherichia coli genome metabolic network model, the invention fully characterizes the physiological state of cells by combining flow balance analysis and bacterial growth laws, simulates the growth rate of cells, and combines quantitative experimental data for standardizing typical gene circuits to construct dependent Gene circuit dynamics model based on cell growth rate to accurately predict the effect of cell growth rate on the function of synthetic gene circuits.

Description of drawings

In order to explain the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore do not It should be regarded as a limitation of the scope, and for those of ordinary skill in the art, other related drawings can also be obtained according to these drawings without any creative effort.

Fig. 1 shows the construction flow of a synthetic gene circuit according to an embodiment of the present disclosure;

FIG. 2 shows the accuracy comparison results of simulation results of an embodiment of the present disclosure with prior art and experimental results.

Detailed ways

In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all of them. Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

As shown in FIG. 1 , the present disclosure provides a method for constructing a synthetic gene circuit model, the method comprising: building a gene circuit based on the cellular proteome data related to the synthetic gene circuit, combined with a bacterial genome metabolic network model Flow balance analysis method of intervention resource allocation (SC-CAFBA), and simulate cell growth rate according to the flow balance analysis method of gene circuit intervention resource allocation; Substitute the cell growth rate into the gene circuit dynamics model to construct a growth rate regulation gene circuit Model, simulate the dynamic behavior of the gene circuit according to the gene circuit model regulated by the growth rate, and obtain the simulation results; conduct quantitative experiments on the dynamic behavior of the gene circuit to obtain the experimental results, and correct the gene circuit by comparing the simulation results and the experimental results. coupled model.

The expression of exogenous synthetic gene circuits, due to the occupation of intracellular amino acids, will change the protein allocation of chassis cells, and will also rearrange the metabolic flux distribution of the entire metabolic network. With the help of the response associations between genes and proteins in the metabolic network model, we mapped the cellular proteome data involving gene circuits for protein response mapping and partitioned proteins according to the bacterial growth law as a constraint on the flow balance analysis method that restricts protein allocation. , to establish a resource allocation flow balance analysis method for gene circuit interference. Combining the aforementioned analytical methods with a metabolic network model simulates and predicts the optimal growth state (ie, growth rate) of cells.

The growth rate obtained by combining the cellular genome metabolic network model and the SC-CAFBA algorithm was substituted into the gene circuit dynamics model to construct a gene circuit coupling model for growth rate regulation (

), and used the model to predict the performance of gene circuits under different cell growth rates to obtain simulation results. Then, with the help of a high-throughput biological platform to regulate parameters such as bacterial growth rate, fluorescent gene expression and other parameters for standardized quantitative measurement, quantitatively characterize the dynamic behavior of gene circuits to obtain experimental results. Then compare the simulation results with the experimental results to correct the model.

In some embodiments, the genomic metabolic network model is configured as an E. coli-based genomic metabolic network model.

In some embodiments, representative synthetic gene circuit types of oscillatory circuits, toggle switch circuits and logic gate circuits are selected as research objects, and corresponding gene circuit dynamics models are built.

In some embodiments, a synthetic gene circuit model is used, which is constructed by the aforementioned construction method of the synthetic gene circuit model.

In some embodiments, an electronic device is used that includes a processor, a memory, and programs or instructions stored on the memory and executable on the processor, which program or instructions, when executed by the processor, implement a synthetic gene circuit as described above The steps of the model's construction method.

In some embodiments, a readable storage medium is used, and the readable storage medium stores programs or instructions that, when executed by a processor, implement the steps of the aforementioned method for constructing a synthetic gene circuit model.

Example 1: SC-CAFBA mimics the effect of overexpression of exogenous non-essential proteins on cell growth.

The experimental results are shown in Figure 2, wherein M1, M2, and M3 represent three different culture media, respectively. E. coli grown on these three media exhibited three different growth rates. The solid line represents the simulation results using the invention, the dashed line represents the published simulation results in the prior art, and the circles represent the published experimental data results.

This example proves by comparing with the published simulation results and published experimental data: the SC-CAFBA method of the present invention has been used to simulate and predict the overexpression of non-essential proteins in three different culture media.

effect on cell growth rate. The simulation results (solid line) of this example show that with

The growth rate of the cells gradually decreased with increasing. This is consistent with the experimental data (circles) reported by the predecessors, and it is also improved compared with the models published by the previous people, which proves that this example has a good predictive ability and can be used for the analysis of the performance of synthetic gene circuits under different growth rates.

While the present invention has been illustrated and described in further detail by preferred embodiments, the present invention is not limited to the disclosed examples and other modifications may be derived therefrom by those skilled in the art without departing from the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

A method for constructing a synthetic gene circuit model, characterized in that the method comprises:

Establish a flow balance analysis method of gene circuit intervention resource allocation, and simulate cell growth rate according to the flow balance analysis method of gene circuit intervention resource allocation;

Substitute the cell growth rate into the gene circuit dynamics model, construct a growth rate-regulated gene circuit model, simulate the dynamic behavior of the gene circuit according to the growth rate-regulated gene circuit model, and obtain a simulation result;

Quantitative experiments are performed on the dynamic behavior of the gene circuit, experimental results are obtained, and the gene circuit coupling model is corrected by comparing the simulation results with the experimental results.
The method for constructing a synthetic gene circuit model according to claim 1, wherein the flow balance analysis method of gene circuit intervention resource allocation takes proteome distribution containing exogenous gene circuit as an additional restriction condition of the flow balance analysis method, Combined with bacterial genome metabolic network model construction.
The method for constructing a synthetic gene circuit model according to claim 1, wherein the gene circuit model is based on the genome metabolic network model of Escherichia coli cells.
The method for constructing a synthetic gene circuit model according to claim 1, wherein the types of the synthetic gene circuit include an oscillatory circuit, a toggle switch circuit and a logic gate circuit.
A synthetic gene circuit model, characterized in that it is constructed by the method for constructing a synthetic gene circuit model according to any one of claims 1 to 4.
A synthetic gene circuit model is characterized in that it includes the metabolic characteristics of chassis cells, the physiological state of proteome resource allocation, and the dynamic behavior of exogenous gene circuits.
An electronic device, characterized in that it includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor, the program or instruction being executed by the processor to achieve the right The steps of the method for constructing a synthetic gene circuit model according to any one of claims 1 to 4.
A readable storage medium, characterized in that a program or an instruction is stored on the readable storage medium, and when the program or instruction is executed by a processor, the execution of the synthetic gene circuit model according to any one of claims 1 to 4 is realized. Steps to build a method.