CN-121999880-A - Automatic control method and system for escherichia coli culture

CN121999880ACN 121999880 ACN121999880 ACN 121999880ACN-121999880-A

Abstract

The embodiment of the invention provides an automatic control method and system for escherichia coli culture, and belongs to the technical field of escherichia coli culture. The automatic control method comprises the steps of constructing an ANN model for identifying a DO baseline, constructing a data generation algorithm based on a numerical variation rule of the DO baseline in the DO-stat strategy operation process, sending the training sample into the ANN model to train the ANN model, collecting DO_realtem values (real-time dissolved oxygen values) at equal intervals, sending the DO_realtem values into the trained ANN model to obtain an original baseline value, conducting filtering processing based on the obtained original baseline value to obtain a baseline_smooth (smooth baseline value), and automatically conducting oxygen supply condition control and carbon source and nitrogen source condition control according to the obtained baseline_smooth. The automatic control method can realize the full-process unattended operation of the fermentation production of the escherichia coli and the high-density fermentation of the escherichia coli and the high-efficiency expression of products.

Inventors

XU ZHIGUO
ZHOU MENGXUAN
Gan Zhiren
JIANG JINGYAN
DING JIAN
XIE ZHENGGANG
LI XUELIANG

Assignees

迪必尔生物工程(上海)有限公司

Dates

Publication Date: 20260508
Application Date: 20260115

Claims (10)

1. An automatic control method for culturing escherichia coli, which is characterized by comprising the following steps: Constructing an ANN model for identifying DO baselines; based on the numerical variation rule of the DO baseline in the DO-stat strategy operation process, constructing a data generation algorithm for generating training samples; The training sample is sent into the ANN model to train the ANN model; Collecting DO_realtem values (real-time dissolved oxygen values) at equal intervals, and sending the DO_realtem values into the trained ANN model to obtain an original baseline value; Filtering processing is carried out based on the obtained original baseline value to obtain a baseline_smooth (smooth baseline value); Automatically controlling oxygen supply conditions according to the acquired baseline_smooth, and controlling carbon source and nitrogen source conditions; In the control process, when the actual fermentation time exceeds the set induction time, a peristaltic pump is automatically started to finish the addition of the inducer IPTG, and the culture temperature is adjusted to the set temperature.
2. The automatic control method according to claim 1, wherein constructing an ANN model for identifying DO baseline includes employing a feed-forward multi-layer perceptron structure, including 60 neurons in an input layer, 4 fully connected layers in a hidden layer, 1024, 512, 256, and 128 neurons in number, respectively, and one neuron in an output layer to represent a baseline value of DO baseline at a current time point.
3. The automatic control method according to claim 1, wherein the step of collecting DO_realtem values (real-time dissolved oxygen values) at equal intervals and feeding them into the trained ANN model to obtain the original baseline values includes collecting DO_realtem values once per second and storing the DO_realtem values into a sliding time window at intervals of 1min, and setting the time window length of the sliding time window to 60 so that the sliding time window always stores DO_realtem values within the latest 1h and updates them once per minute, and after updating is completed, inputting the current sliding time window into the trained ANN model.
4. The automatic control method according to claim 1, wherein performing a filter process based on the acquired original baseline value to obtain baseline_smooth (baseline value) includes: Acquiring the current moment and the previous preset number of original baseline values as a data window; bringing the data window into equation (1) and fitting the baseline values in the data window by least squares to determine the parameters in equation (1): Formula (1), Wherein, the Representing a fit function that satisfies all baseline values in the baseline window at the current time, 、、 Representing constant term, first term coefficient and second term coefficient, Indicating the relative time corresponding to the baseline value; Reconstructing the formula (1) according to the acquired parameters, and bringing t corresponding to the current moment into the formula (1) to obtain the filtered baselloth.
5. The automatic control method according to claim 1, wherein the automatic oxygen supply condition control and the carbon source and nitrogen source condition control are performed based on the acquired baseline_smooth, comprising: agitate _rate (initial agitation rate) and air_flow (aeration rate) are set, inoculation is completed, and updated baseline_smooth is obtained; judging whether the baseline_smooth is lower than baseline_lb or not according to the acquired baseline_smooth; When the baseline_smooth is lower than baseline_lb, the agitate _rate is increased by 20r/min, and the air_flow is increased by 0.05L/min; After the fermentation lasts for a set time, judging whether the baseline_smooth is higher than baseline_ub (upper limit value) according to the acquired baseline_smooth; When the basejsmooth is higher than basejub, agitate _rate is reduced by 20 r/min, while air_flow is reduced by 0.05L/min.
6. The automatic control method according to claim 1, wherein the automatic oxygen supply condition control and the carbon source and nitrogen source condition control are performed based on the acquired baseline_smooth, comprising: Acquiring a DO_readalime value and a basesize; Judging whether the DO_dealtime value is greater than the sum of the base_smooth and threshold_ increase (increase threshold); Under the condition that the DO_readalime value is larger than the sum of the baseline_smooth and the threshold_ increase, triggering glucose feeding operation, and continuously feeding glucose according to a preset rate; judging whether the DO_readiness value is smaller than the sum of baseline_smooth and baseline_ increase (increase baseline) in the case of glucose supplementation for a set time; In the case where the DO_dealtime value is smaller than the sum of basesize and basesize increase, glucose feeding is stopped.
7. The automatic control method according to claim 6, wherein the oxygen supply condition control and the carbon source and nitrogen source condition control are automatically performed based on the acquired baseline_smooth, comprising acquiring a duration of glucose feeding and stopping the operation of glucose feeding if the duration of glucose feeding exceeds a preset time.
8. The automatic control method according to claim 6, wherein the automatic oxygen supply condition control and the carbon source and nitrogen source condition control are performed based on the acquired baseline_smooth, comprising the steps of acquiring an operation of triggering glucose feeding for the first time, starting constant-speed feeding of the nitrogen source while the glucose feeding is performed for the first time, and fixing a feeding rate (V_ns) to be 1.0 g/L/h.
9. The automatic control method according to claim 1, wherein the set temperature is 28 ℃.
10. An automatic control system for culturing escherichia coli, comprising: the data acquisition module is used for acquiring various data in the escherichia coli culture process; An execution module for executing an automatic control method for E.coli culture according to any one of claims 1 to 9 based on the acquired data.

Description

Automatic control method and system for escherichia coli culture Technical Field The invention relates to the technical field of escherichia coli culture, in particular to an automatic control method and system for escherichia coli culture. Background DO-stat is a common feed strategy to control substrate concentration at a critical value and is widely used due to its ease of operation and sensitivity of response. However, in actual operation, the DO baseline in the substrate sufficient state is dynamically changed due to the influence of various factors such as the rheological property of the fermentation liquid, the oxygen transfer efficiency and the response property of the O2 sensor, and an operator is required to adjust the DO threshold for starting the fed-batch in real time according to the change of the DO baseline. Thus, stable operation of the DO-stat strategy requires a high level of experience and knowledge from the operator. If the control parameters are improperly set, excessive or insufficient addition of the bottom stream is easily caused, so that the stability of the process is affected. Therefore, development of a fully automatic control method and system capable of adaptively adjusting DO-stat strategy control parameters according to the metabolic characteristics of cells and real-time changes of the reactor DO is important for ensuring the stability of the E.coli recombinant protein expression process. Disclosure of Invention The embodiment of the invention aims to provide an automatic control method and system for escherichia coli culture, and the automatic control method can realize the full-process unattended operation of escherichia coli fermentation production and high-density fermentation of escherichia coli and high-efficiency expression of products. In order to achieve the above object, an embodiment of the present invention provides an automatic control method for culturing escherichia coli, the automatic control method comprising: Constructing an ANN model for identifying DO baselines; based on the numerical variation rule of the DO baseline in the DO-stat strategy operation process, constructing a data generation algorithm for generating training samples; The training sample is sent into the ANN model to train the ANN model; Collecting DO_realtem values (real-time dissolved oxygen values) at equal intervals, and sending the DO_realtem values into the trained ANN model to obtain an original baseline value; Filtering processing is carried out based on the obtained original baseline value to obtain a baseline_smooth (smooth baseline value); Automatically controlling oxygen supply conditions according to the acquired baseline_smooth, and controlling carbon source and nitrogen source conditions; In the control process, when the actual fermentation time exceeds the set induction time, a peristaltic pump is automatically started to finish the addition of the inducer IPTG, and the culture temperature is adjusted to the set temperature. Optionally, constructing the ANN model for identifying the DO baseline includes adopting a feed-forward multi-layer perceptron structure, wherein the input layer comprises 60 neurons, the hidden layer comprises 4 fully-connected layers, the number of the neurons is 1024, 512, 256 and 128 respectively, and the output layer comprises one neuron to represent the baseline value of the DO baseline at the current time point. Optionally, collecting DO_real time values (real-time dissolved oxygen values) at equal intervals, and sending the DO_real time values into the trained ANN model to obtain an original baseline value, wherein the DO_real time values are collected once per second, the DO_real time values are stored in a sliding time window at intervals of 1min, the time window length of the sliding time window is set to be 60, so that the DO_real time values in the latest 1h are always stored in the sliding time window, the DO_real time values are updated once per minute, and after the updating is completed, the current sliding time window is input into the trained ANN model. Optionally, filtering processing is performed based on the obtained original baseline value to obtain a baseline_smooth (baseline value), including: Acquiring the current moment and the previous preset number of original baseline values as a data window; bringing the data window into equation (1) and fitting the baseline values in the data window by least squares to determine the parameters in equation (1): Formula (1), Wherein, the Representing a fit function that satisfies all baseline values in the baseline window at the current time,、、Representing constant term, first term coefficient and second term coefficient,Indicating the relative time corresponding to the baseline value; Reconstructing the formula (1) according to the acquired parameters, and bringing t corresponding to the current moment into the formula (1) to obtain the filtered baselloth. Optionally, the oxygen supply con