Team:csu_china

CA(Cellular automata) Based Gene Circuit Visualization Model

Overview

Sweet guard aims to help as many diabetic patients as possible to get rid of the pain in the future. Due to the cutting-edge nature of genetic engineering, it will be quite meaningful for every user and the people around them to understand the basic principles of our products. Although Sweet Guard is well-designed and has been initially verified in the wet laboratory, helping users understand the basic principles of Sweet Guard is a non-trivial problem for complicated gene circuits and experiments. Besides, genetic engineering, as an emerging technology, are facing many ethical controversies, which may lead to unnecessary misunderstandings of Sweet Guard among certain populations, while it is necessary to eliminate this non-objective understanding. Hence, building a model to describe Sweet Guard in a friendly and intuitive way will be a great help for our whole program.

The theory of cellular automata is immensely rich, with simple rules and structures being capable of producing a great variety of unexpected behaviors, which is widely implemented in the fields of transportation, infectious diseases, etc., and inspired we creatively developed an interactive animation simulation model based on it. Instead of traditional animation model, our model uses p5.js(oriented from processing) to draw and precisely control every graphical element based on quantity logic and synthetic biology. Users can simulate several physiological processes related to glucose metabolism through interaction with our model, and then the model will respond as the gene circuit and present the workflow of Sweet Guard.

Assumptions

In order to make the model easy to understand and design, we make the following assumptions:

The model was simplified into three compartments: internal environment, engineering cells, and tissue cells (only in output module).
In the internal environment, blood glucose at a certain concentration is spreading under physiological or pathological conditions; insulin secreted by engineered cells will also be released into the internal environment.
The process of glucose regulating the transcription of Gal4 gene is simplified as the transcription of GIP promoter to generate Gal4 mRNA, and the transcription rate is dependent only on intracellular glucose concentration.
Ignore the organelles and molecules that are not directly related to the gene circuit in the cell, and only retain the ribosome, the GIP of the nucleus, VP16, the gene transcription region of miRNA, the vesicles that secrete insulin, the cell membrane, the glucose transporter GLUT, insulin receptors on the membrane and downstream signaling molecules produced because of their activation.
The motion rules of microscopic substances are changed. For example, in the real world, GLUT transports glucose follows the rule of chemical process in the enzymatic reaction. Glucose and GLUT may need to be combined and separated many times so that glucose can be transported to the other side. At the same time, GLUT itself will also undergo structural change, and in this model, we simplified GLUT into a channel through which glucose can pass directly.

Some more changes and assumptions are different from the real physiological structure that are not explained here. In principle, this model is developed for the convenience of users for understanding and visualization. Emphasis should be placed on the aspects of the model illustrating the working principle of the product during interpretation.

Introduction

This is our model introduction video, through which you can get a preliminary understanding of our model and its functions. It’s worth mentioning that we deployed the model to the team’s web page. Everyone can directly experience and read our model by clicking on the link attached to its corresponding model description.

Click for CA model interface showed in the video

Model Description

In this part of the animation, we simulate the process of the entire gene circuit.

The existing models are mostly based on compliance with experimental data or the perspective of common sense, or just presented itself in a too simple and easy-to-understand animation form. These ways may make the model too obscure or unable to transmit enough information to concretize readers' cognition.In contrast, the CABGCV developed by us has been improved on the basis of general forms of animation, avoiding the shortcomings of most existing models:

Our model constructed an interactive animation， which means that users can manipulate different buttons to propel the animation process. It helps inspire users' interest in the design and inner thought of Sweet Guard，and reduces the barriers to understand our model.
Our model can relatively quantify and visualize the main parameters. Although the model starts from the form of animation, we set up a dashboard interface (which will be introduced below) to present the relatively quantitative results of the main parameters in the form of charts. To a certain extent, we respect the experimental data and ensure the scientificity of the model.
The dashboard can visually display the approximate experimental data, which can further help users understand the content and significance of the experimental work.
The user can add blood sugar particles to the internal environment by clicking the mouse to simulate the blood sugar's rise after eating. The cell then feels the increase in blood glucose concentration. After that, if the user operates to irradiate the blue light, the insulin transcription factor is produced, which secretes insulin to the extracellular environment and lowers blood sugar. When the extracellular concentration of insulin is too high and it binds to the insulin receptor on the cell membrane, it will inhibit the production of insulin transcription factors.

Figure1.Overview of gene circuit visualization

The visual model is divided into three interfaces: view(left upper)、control center (left bottom) and Panel(right). In the view interface, you can see the initialized engineered cells (whose color is orange), the blood sugar pool (the left side), and the legend of the main structures and substances on the right. There is GLUT, through which glucose particles can enter the cells, and insulin receptors on the membrane of the initialized engineered cells. There is nuclei, which can respond to various signals to express corresponding genes, and several ribosomes involved in gene expression in the cell.

At the beginning of the control center interface, there were six buttons and two sliders.

By clicking on the Reset button, you will initialize the state of the view and the dashboard.

By clicking on the Run button, you will start the operation of the model.

By clicking on the Light button, you will exert blue light on the cells (cell's background will blue).

By clicking on the Eat button, you will add the number of blood glucose particles in the blood glucose pool to simulate the process of blood glucose increase in the internal environment after eating.

By clicking on the Track glucose button, you will focus on the behavior of a single glucose particle.

By clicking on the Track miRNA button, you will focus on the behavior of a single miRNA particle.

By draging the Speed slider, you will adjust the rate of model evolution.

By draging the Metabolic rate slider, you will regulate the degradation rate of glucose in cells.

In the dashboard interface, three dynamic dashboards (each index is 0 at the initial state, so there is no content) can be seen. These three dashboards display the dynamic quantitative indexes of the corresponding particles in the view interface in real time with the help of the ThemeRiver map and the line graph.

In the initial state, users can click on the Run to start our model animation. There is some initial blood glucose of certain concentration in the blood glucose pool. Clicking the Eat button represents eating, with the blood glucose increasing immediately. The glucose level can be seen on the Glucose and Insulin dashboard. Metabolic rate can be dragged to the left to simulate the defected glucose metabolism ability of diabetic patients. The goal of Sweet Guard is to regulate uncontrolled and elevated blood glucose to a relatively stable and normal level. Click Light to activate VP16, which will further trigger the regulation of Sweet Guard. The number of molecules involved in this process is visible on "Gal4 and Complex" and "VP16 and VP16*" dashboards.

When we press the light button, under the condition of blue light, the protein VP16 in cell will be activated. From the red box in the lower right corner of the above figure, it can be seen that the number of activated VP16 protein increased after blue light radiation.

Fig.2 Press the light button

When we press the eat button, we are simulating the eating behavior of patients using sweet guard. It can be observed that the number of glucose displayed in the upper right dial is slowly rising as the process of blood glucose rising.

Fig.3 Press the eat button

After a period of observation, we can find that our gene circuit design is feasible. From the frame in the upper right corner of the graph, we can conclude that the glucose concentration and insulin concentration tend to a stable value, which verifies the feasibility and stability of our model.

Fig.4 The glucose concentration and insulin concentration tend to a stable value

Click for CA model interface

Algorithm FLow

Based on quantity logic and synthetic biology, we designed the algorithm for our cellular autumota. Here is our algorithm flow.

Fig.5 Algorithm Flow

Model Disassembly

For the purpose of more intuitive observation of the key points of each process in the circuit, the convenience of modularization and fine adjustment of the model, we decompose the complete gene circuit into three modules and present them separately according to the independence and expansion of each module's function：

Input module，the part of the process from rises of the number of blood sugar to TF generation;
Output module，the part of the process from insulin gene's expression to blood sugar reduction;
Adjustment module，the part of the process from insulin receptor's singnal transduction to inhibition for insulin secretion.

The three modules can perform their functions independently, and are closely related in the aspect of space-time relationship and structural function. The output of Input module can be used as the input of Output module; output module output can also be used as input to Adjustment module; for another, the results of Output module and Adjust module will regulate the input of Input module. We finally organize these three modules to the complete genetic circuits.

Some more changes and assumptions are different from the real physiological structure that are not explained here. In principle, this model is developed for the convenience of users for understanding and visualization. Emphasis should be placed on the aspects of the model illustrating the working principle of the product during interpretation.

The user can add blood sugar particles to the internal environment by clicking the mouse to simulate the blood sugar's rise after eating. The cell then feels the increase in blood glucose concentration. After that, if the user operates to irradiate the blue light, the insulin transcription factor is produced, which secretes insulin to the extracellular environment and lowers blood sugar. When the extracellular concentration of insulin is too high and it binds to the insulin receptor on the cell membrane, it will inhibit the production of insulin transcription factors.

Input module

In this part, the biological process includes the input of increased blood sugar, the cell’s response to glucose input, the input of blue light on, and TF output finally. This part of the model, which exerts in gene circuit as major input compartment, possesses two interactive modules. Furthermore, TF output can activate the downstream process, i.e. insulin generation.

TF generated from binding of Gal4 and VP16 is triggered by two steps: click to add glucose produces Gal4 and switch the blue light on to activate VP16 (background in cell turns blue). Gal4 mRNA is transcribed in GIP, and the rate depends on the concentration of intracellular glucose (GIP's color changes with the intracellular glucose concentration).

In the Input module model, you can simulate the eating behavior by clicking on the outside of the cell with the mouse, and you can simulate the blue light environment by pressing Bor b on the keyboard

Click for input module interface

Output module

The hypoglycemic process of insulin is activated by TF produced in part1, composed of insulin secretion, insulin targeting, and hypoglycemic effect.

So far, our whole loop has been tested and every part can function well to complete the insulin secretion under the condition of hyperglycemia and blue light exposure, suppress the insulin secretion under the condition of high insulin concentration and hypoglycemia to form a close loop.

The increased rate of tissue cells’ glucose uptake and degradation is triggered by insulin targeting.

Click for output module interface

Adjustment module

Even if two parts above could implement hypoglycemic function independently, we set this part in order to achieved fine negative feedback and make model a closed loop. One can change parameters in this module to improve performance. Biological process in the module includes binding of extracellular insulin to its receptor, miRNA production by receptor downstream signaling and degradation of Gal4 mRNA

Gal4 mRNA that regulates production of insulin is degraded by miRNA generated from insulin receptor downstream signaling.

Click for adjustment module interface

Data Analysis

There are a few insulin molecules and glucose molecules at the beginning. Glucose began to increase after 'Eat'.

Figure6. Glucose began to increase after 'Eat'.

After turning on the blue light, the current VP16 almost completely transforms to VP16* and binds with Gal4 to generate Complex in a short time.

Figure7. Turning on the blue light

However, insulin doesn’t rise simultaneously.

Figure8,9. Time lag effect

After a considerable period, insulin began to increase, to shorten the number of uncontrolled blood glucose; at this time, although miRNA began to play a continuous role in reducing the new birth of Gal4, the existing Gal4 and Transcription Factors were still playing a role, making insulin produces continuously before being inhibited by negative feedback.

Figure10. Switch off the blue light.

After turning off the blue light, insulin began to fall, and because of no uptake, the index of different molecules can eventually return to the initial state, maintaining a stable level.

Figure11. The num of particles are maintaining a stable level

Conclusion

In the process of testing the animated model, we discovered a feature of the gene circuits when it works: there is a time lag longer than expected between the insulin's secretion and the blood sugar's reduction. In a considerable period of time, blood sugar has always been maintained at a high level. This observation is consistent with the corresponding experimental data, that is, after the light turns on, the reporter gene doesn't increase sharply in a short time, which indicates our visualization model is highly consistent with the real world, and during the running process, we found that there was also a delay in the process of miRNA lowering the uncontrolled secretion of insulin, and blood glucose had undergone a significant decrease before insulin returned to a relatively stable level, which suggests the animated model also can predict the behavior of the product and extract the information we are interested in, providing guidance for the optimization and improvement of the product.

Figure12. Time lag

This allows our dry experiment part to test a variety of programs more quickly and provides a preliminary basis for the exploration of specific parameters such as the relationship between blue light working hours and eating, and specific blue light working hours.

Team:CSU CHINA/Visualization Model