Method for detecting caenorhabditis elegans closed-loop adaptive neural function based on specific neural circuit probe

Abstract

The invention relates to the technical field of biomedical detection and environmental toxicology evaluation, and discloses a method for detecting caenorhabditis elegans closed-loop self-adaptive neurological function based on a specific neural circuit probe, which comprises the following steps: S1, preparing a specific neural circuit probe caenorhabditis elegans strain, S2, exposing the caenorhabditis elegans strain to a pollutant to be detected, and S3, detecting the caenorhabditis elegans closed-loop self-adaptive neurological function. The method comprises the steps of S1, carrying out closed-loop adaptive neural function detection on a nematode strain, S4, generating a control input signal based on errors through a digital controller, S5, synchronously collecting time sequence data of actual behavior output and the control input signal, S6, quantifying a neural adaptive damage characteristic spectrum index, and S7, completing neurotoxicity evaluation based on the index. According to the method, high-sensitivity detection on neurotoxicity is realized, a nervous system executes a continuous tracking task, when the function of a neural circuit is only slightly reduced, the control effort paid by the system for maintaining the task is remarkably increased, and sub-lethal nerve injury which is difficult to find by a traditional method can be quantified.

Description

Technical Field

[0001] This invention relates to the field of biomedical detection and environmental toxicology evaluation technology, specifically a method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe. Background Technology

[0002] The neurotoxic threats posed by environmental pollutants, such as pesticides, heavy metals, and novel organic compounds, to ecosystems and human health are receiving increasing attention. Accurate, rapid, and high-throughput screening and evaluation of the neurotoxicity of these chemicals are crucial for environmental safety assessments and disease prevention.

[0003] Caenorhabditis elegans has become a widely used model organism in neurobiology and toxicology research due to its well-defined nervous system structure, clear genetic background, short life cycle, and ease of culture.

[0004] Currently, the standard methods for evaluating neurotoxicity using *C. elegans* mainly rely on passive observation or simple open-loop stimulation. These methods typically involve exposing the nematodes to the test contaminant and measuring their crawling speed on an agar plate, their oscillation frequency in a liquid, their head oscillation amplitude, or their response to a fixed stimulus.

[0005] However, these traditional, passive observation-based phenotypic analysis methods have significant limitations. These methods are often insufficiently sensitive, making it difficult to detect early, mild neurological damage caused by sublethal concentrations of pollutants. A neural circuit may be functionally impaired, but in simple passive tests, its behavioral output may still be within the "normal" range, leading to an underestimation of toxicity. Furthermore, these measurement methods obtain data with a single dimension, typically reflecting only an overall, static behavioral outcome, and cannot delve into which part of the neural circuit the damage occurs, nor can they quantitatively characterize the degree of neurological function deterioration from a dynamic performance perspective. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a method for detecting closed-loop adaptive neural function in *C. elegans* based on specific neural circuit probes. This method solves the problems of insufficient sensitivity, difficulty in detecting early minor damage caused by sublethal exposure, reliance on static behavioral phenotypes for data dimensions, and insufficient evaluation depth when evaluating the neurotoxicity of pollutants.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe, comprising the following steps: S1. Prepare a specific neural circuit probe, a *C. elegans* strain, wherein the *C. elegans* strain specifically expresses a light-sensitive channel protein in a selected upstream neuron and specifically expresses a calcium ion indicator in a downstream effector; S2. Expose the nematode strain prepared in step S1 to a solution containing a pollutant to be tested to complete the exposure treatment; S3. Perform closed-loop adaptive neural function detection. Place the nematode strain exposed in step S2 on a closed-loop adaptive optogenetic microfluidic platform, set a preset target behavior state, collect the actual behavior output of the nematode strain in real time, and calculate the behavior error between the preset target behavior state and the actual behavior output. S4. Generate a control input signal, input the behavior error calculated in step S3 into a preset digital controller algorithm, calculate and output the control input signal, and the control input signal modulates the intensity of light stimulation applied to the upstream neuron in real time. S5. Synchronously acquire and record the time series data of the actual behavior output acquired in step S3 and the control input signal generated in step S4; S6. Quantify the neural adaptive injury characteristic spectrum index, based on the time series data described in step S5, and calculate at least the following two parameters: S6.1 A steady-state error characterizes the average residual error between the actual behavior output and the preset target behavior state after the system enters a steady state; S6.2 A control effort, representing the cost incurred by the system in maintaining the preset target behavior state, is calculated by the integral square value of the control input signal; S7: Based on the steady-state error and control effort calculated in step S6, complete the evaluation of the neurotoxicity of the pollutant to be tested.

[0008] Preferably, when the upstream neuron in step S1 is an excitatory neuron, the light-sensitive channel protein is Channelrhodopsin-2; and the downstream effector is a VB / DB type motor neuron or the body wall muscle innervated by it, the calcium ion indicator is GCaMP6s; when the upstream neuron in step S1 is an inhibitory neuron, the light-sensitive channel protein is an inhibitory optogenetic tool; and the downstream effector is a VB / DB type motor neuron inhibited by it or the body wall muscle innervated by it, the calcium ion indicator is GCaMP6s.

[0009] Preferably, the closed-loop adaptive optogenetic microfluidic platform in step S3 includes a microfluidic chip with a physical capture structure for partially fixing the body of the nematode strain and allowing its head region to swing freely.

[0010] Preferably, the preset target behavior state set in step S3 is a constant target value of the nematode head swaying frequency, and the actual behavior output is the instantaneous swaying frequency of the nematode head.

[0011] Preferably, the step of real-time acquisition of the instantaneous swaying frequency of the nematode's head in step S3 is to acquire bright-field images using a high frame rate camera and extract the data by real-time analysis of the bright-field images using a machine vision algorithm.

[0012] Preferably, the digital controller algorithm in step S4 is a PID controller, and the generation of the control input signal is calculated based on a proportional term, an integral term, and a derivative term of the behavior error; The proportional gain, integral gain, and derivative gain remain constant in the pollutant exposure group and the control group.

[0013] Preferably, in step S4, the control input signal modulates the light stimulation intensity by driving a digital micromirror device or a scanning galvanometer.

[0014] Preferably, the neural adaptive injury feature spectrum index calculated in step S6 further includes at least one of the following parameters: A rise time characterizes the system's response speed to a step change in the target's behavioral state; A peak overshoot represents the maximum oscillation amplitude of the system's response to a step change in the target behavior state.

[0015] Preferably, the exposure treatment in step S2 is to subject the nematode strain to static liquid exposure.

[0016] Preferably, the pollutant to be tested is a PPD quinone derivative, including one or more of IPPD-Q, DPPD-Q, or DTPD-Q.

[0017] This invention provides a method for detecting closed-loop adaptive neural function in *C. elegans* based on specific neural circuit probes. It has the following beneficial effects: 1. This invention achieves highly sensitive detection of neurotoxicity. Unlike traditional passive observation methods, this method forces the nervous system to perform a continuous tracking task. This significantly increases the control effort the system puts into maintaining the task, even when the function of the neural circuits has only slightly declined and has not yet led to behavioral paralysis. This allows for the quantification of sub-lethal neurological damage that is difficult to detect using traditional methods.

[0018] 2. This invention innovatively applies performance standards derived from control engineering to toxicological evaluation. This method no longer relies on a single, passive behavioral phenotype, but provides multi-dimensional, quantifiable data from the perspective of dynamic control performance (such as system accuracy and response cost), transforming the vague concept of "neural function impairment" into precise engineering parameters, greatly improving the objectivity and depth of the evaluation.

[0019] 3. This invention constructs an automated closed-loop detection platform. This platform can achieve precise fixation, targeted stimulation, and real-time behavioral quantification of individual nematodes, overcoming the interference of individual differences in traditional group testing, and has the potential for high-throughput screening. It provides an efficient and reliable tool for rapidly evaluating the effects of different pollutants or drugs on specific neural circuits. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method of the present invention; Figure 2 The flowcharts for the two neural circuit probes of the present invention are shown below; Figure 3 This is a flowchart of the neural adaptive injury feature spectrum index of the present invention. Detailed Implementation

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see the appendix Figure 1 - Appendix Figure 3 This invention provides a method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe, comprising the following steps: S1: Prepare a specific neural circuit probe, the nematode strain of *C. elegans*, which specifically expresses a light-sensitive channel protein in a selected upstream neuron and a calcium ion indicator in a downstream effector. S2. Expose the nematode strain prepared in step S1 to a solution containing a pollutant to be tested to complete the exposure treatment; S3. Perform closed-loop adaptive neural function detection. Place the nematode strain exposed in step S2 on a closed-loop adaptive optogenetic microfluidic platform, set a preset target behavior state, collect the actual behavior output of the nematode strain in real time, and calculate the behavior error between the preset target behavior state and the actual behavior output. S4. Generate a control input signal, input the behavior error calculated in step S3 into a preset digital controller algorithm, calculate and output the control input signal, and the control input signal modulates the intensity of light stimulation applied to the upstream neuron in real time. S5. Synchronously acquire and record the time series data of the actual behavior output acquired in step S3 and the control input signal generated in step S4; S6: Quantify the neural adaptive injury feature spectrum index. Based on the time series data in step S5, calculate at least two parameters, including steady-state error and control effort. The steady-state error represents the average residual error between the actual behavior output of the system after entering steady state and the preset target behavior state. The control effort represents the cost paid by the system to maintain the preset target behavior state. It is calculated by the integral square value of the control input signal. S7: Based on the steady-state error and control effort calculated in step S6, complete the evaluation of the neurotoxicity of the pollutant to be tested.

[0023] The following content will provide a detailed, non-restrictive disclosure of the technical features in the above steps.

[0024] This method utilizes a specific neural circuit probe, the *C. elegans* strain. The nematode strain was constructed to form an "input-output" neural system that can be precisely controlled and measured externally. Upstream neurons, acting as the system's input, receive optogenetic stimulation; downstream effectors, acting as the system's output, have their activity levels measured indirectly or directly using calcium ion indicators.

[0025] In one specific embodiment, the nematode strain in step S1 is defined as follows: when the upstream neuron in step S1 is an excitatory neuron, the light-sensitive channel protein is Channelrhodopsin-2; and the downstream effector is a VB / DB type motor neuron or the body wall muscle it innervates, with GCaMP6s as the calcium ion indicator; when the upstream neuron in step S1 is an inhibitory neuron, the light-sensitive channel protein is an inhibitory optogenetic tool; and the downstream effector is a VB / DB type motor neuron inhibited by it or the body wall muscle it innervates, with GCaMP6s as the calcium ion indicator. Excitatory and inhibitory neurons are chosen because they play important roles in chemosensing, and their functional state is directly related to exposure to environmental pollutants. VB / DB type motor neurons and the muscles they innervate are chosen as downstream because they directly regulate the head swaying and forward / backward behavior of the nematode, forming a complete functional loop from environmental sensing to motor output.

[0026] This method is executed on a closed-loop adaptive optogenetic microfluidic platform. In one embodiment, the closed-loop adaptive optogenetic microfluidic platform in step S3 includes a microfluidic chip with a physical trapping structure. This physical trapping structure, for example, a gradually narrowing microchannel fabricated from PDMS (polydimethylsiloxane) material using soft lithography, functions to partially immobilize the nematode strain's body while allowing free movement of its head region. This design restricts the macroscopic movement of the nematode's body, thereby eliminating displacement interference with measurements while not affecting the free expression of the core behavioral indicator of head movement.

[0027] The platform also integrates a photostimulation module, a behavior acquisition module, and a central control unit (e.g., a computer). The photostimulation module applies light stimulation and may include a 470 nm wavelength LED light source or laser. The light path is spatially modulated via a digital micromirror device (DMD) or scanning galvanometer, and then focused onto excitatory or inhibitory neurons in the nematode's head through a microscope objective. The behavior acquisition module is typically a high-frame-rate CMOS or CCD camera that captures bright-field images of the nematode's head through a microscope. The central control unit runs specific control software (e.g., programs written in LabVIEW or Python) to perform image processing, controller algorithm calculations, and photostimulation signal generation, forming a complete closed-loop system.

[0028] The specific implementation steps of the method may include: Step S1: Prepare the above-mentioned specific neural circuit probe, the *C. elegans* strain.

[0029] Step S2: Expose the nematode strain to a solution containing the test contaminant to complete the exposure treatment. In one specific embodiment, the exposure treatment in step S2 involves static liquid exposure of the nematode strain, for example, placing a synchronized L4 stage nematode population in an M9 buffer solution containing the test contaminant and incubating it at 20 degrees Celsius for 4 hours. A control group containing only the corresponding concentration of solvent (e.g., DMSO) is also established.

[0030] Step S3: Perform closed-loop adaptive neural function detection. Load the exposed nematode strain into the microfluidic chip using a pipette and place it into the physical capture structure.

[0031] In a preferred embodiment, the behavioral parameters in step S3 are defined, with the preset target behavioral state being a constant target value for the nematode's head swaying frequency, for example, set to 1 Hz. Setting a constant target value is to provide the nervous system with a continuous and stable task load, thereby enabling more sensitive detection of its dynamic performance decline. Correspondingly, the actual behavioral output is the instantaneous swaying frequency of the nematode's head.

[0032] In step S3, the actual behavioral output of the nematode strain is acquired in real time through the behavior acquisition module. In a specific embodiment, the step of acquiring the instantaneous swaying frequency of the nematode's head in real time is achieved by acquiring bright-field images of the nematode's head using a high frame rate camera and then using a machine vision algorithm to analyze the bright-field images in real time for extraction. The machine vision algorithm completes the following calculations within one control cycle (e.g., 20 milliseconds): first, it locks the nematode's head region through background subtraction and threshold segmentation; then, it calculates the horizontal displacement time series of the centroid of the head region; finally, it calculates the instantaneous frequency of the time series using Fast Fourier Transform (FFT) or zero-crossing detection.

[0033] The system calculates the behavior error (e(t)) between the preset target behavior state (r(t)) and the actual behavior output (y(t)) in real time. The calculation formula is as follows:

[0034] Where r(t) is the time series of the target behavior state, and y(t) is the time series of the actual behavior output. Step S4: Generate a control input signal. Input the behavior error e(t) into a preset digital controller algorithm to calculate and output a control input signal u(t). In a preferred embodiment, the digital controller algorithm in step S4 is a PID controller. The generation of the control input signal u(t) is based on a proportional term, an integral term, and a derivative term of the behavior error e(t). In this biological control application, the proportional term is used to respond to the current frequency deviation, the integral term is used to correct long-term, continuous performance degradation of the system (e.g., decreased sensitivity of neurons to light stimulation), and the derivative term is used to predict the deviation trend to suppress behavioral oscillations. Its discrete calculation formula in the digital system can be:

[0035] Where u(k) is the control input signal at the current moment; e(k) is the behavior error at the current moment; e(k - 1) is the behavior error at the previous moment; Δt is the control cycle time; K_p is the proportional gain; K_i is the integral gain; and K_d is the differential gain.

[0036] To ensure the fairness of the evaluation, the proportional gain, integral gain, and derivative gain were kept constant in both the pollutant exposure group and the control group.

[0037] In a specific embodiment based on a PID controller, the control input signal in step S4 The intensity of light stimulation applied to upstream neurons is modulated in real time by driving the light stimulation module (i.e., the digital micromirror device or scanning galvanometer mentioned above).

[0038] Step S5: Throughout the entire closed-loop detection process, synchronously acquire and record the actual behavior output. and control input signals Time series data.

[0039] Step S6: Quantify a set of neural adaptive injury characteristic spectrum indicators. The indicators are calculated based on the time series data recorded in step S5 and are used to characterize the dynamic control performance of neural circuits.

[0040] As defined in step S6 of claim 1, the index includes at least one steady-state error ( ) and a control effort ( ).

[0041] steady-state error After the system reaches steady state (e.g., the latter half of closed-loop operation), the actual behavior output... With respect to the preset target behavior state The average residual error between [the two systems]. In biology, a significantly increased steady-state error indicates severe damage to the neural circuit, rendering it unable to complete its intended task even under sustained maximum external drive. It is calculated as follows:

[0042] in, and The steady-state time interval of the system is defined.

[0043] Control effort The cost incurred by the representation system in maintaining a preset target behavioral state is determined by controlling the input signals. The integral squared value is used for calculation. This value reflects how much energy the controller needs to output to compensate for the functional deficits of the nervous system. Biologically, a significantly increased control effort value is a direct quantification of the compensatory function of the nervous system, indicating that although the neural circuit can still complete the task, its intrinsic driving force has decreased, requiring stronger external stimulation to maintain normal function. This is a highly sensitive indicator for measuring sublethal neurotoxicity. Its calculation method is as follows:

[0044] in, This represents the total detection time.

[0045] In an optional embodiment, the neural adaptive injury feature spectrum index calculated in step S6 may further include at least one of the following parameters: An upward time When characterizing the target behavior state of a system in response to a step change, the time required for the system to rise from 10% to 90% reflects the system's response speed. A peak overshoot When characterizing the target behavior state of a system in response to a step change, the actual output exceeds the target value by the maximum percentage, reflecting the oscillation amplitude of the system.

[0046] Step S7: Based on steady-state error and control efforts The numerical value is used to evaluate the neurotoxicity of the pollutant being tested. For example, compared to the unexposed control group, if the steady-state error of the exposed group is... Significantly increased, and / or controlled effort A significant increase indicates that the pollutant being tested has damaged the dynamic control performance of this neural circuit, and therefore exhibits neurotoxicity.

[0047] In one specific application embodiment, the method of the present invention is used to evaluate the neurotoxicity of PPD quinone derivatives. That is, the analyte is a PPD quinone derivative, including one or more of IPPD-Q, DPPD-Q, or DTPD-Q.

[0048] The AWC-VB / DB loop probe nematodes, as in step S1, were exposed to gradient concentrations (e.g., 1, 10, 50 μmol / L) of PPD quinone derivative solutions and to a control solution containing only the solvent.

[0049] After exposure, closed-loop detection and data analysis were performed on at least 20 nematodes in each group according to steps S3 to S7 above. The control efforts of the exposed group and the control group were compared. ) and steady-state error ( The mean and distribution of PPD quinone derivatives can be used to quantitatively evaluate the dose-response relationship of neurotoxicity in AWC-mediated motor control circuits. For example, it can be observed that at low concentrations, only controlled effort... Significantly increased; while under high concentration exposure, control efforts and steady-state error All of them increased significantly, thus achieving precise characterization of different degrees of damage.

[0050] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for detecting closed-loop adaptive neural function in *C. elegans* based on specific neural circuit probes, characterized in that, Includes the following steps: S1. Prepare a specific neural circuit probe, a *C. elegans* strain, wherein the *C. elegans* strain specifically expresses a light-sensitive channel protein in a selected upstream neuron and specifically expresses a calcium ion indicator in a downstream effector; S2. Expose the nematode strain prepared in step S1 to a solution containing a pollutant to be tested to complete the exposure treatment; S3. Perform closed-loop adaptive neural function detection. Place the nematode strain exposed in step S2 on a closed-loop adaptive optogenetic microfluidic platform, set a preset target behavior state, collect the actual behavior output of the nematode strain in real time, and calculate the behavior error between the preset target behavior state and the actual behavior output. S4. Generate a control input signal, input the behavior error calculated in step S3 into a preset digital controller algorithm, calculate and output the control input signal, and the control input signal modulates the intensity of light stimulation applied to the upstream neuron in real time. S5. Synchronously acquire and record the time series data of the actual behavior output acquired in step S3 and the control input signal generated in step S4; S6. Quantify the neural adaptive injury characteristic spectrum index, based on the time series data described in step S5, and calculate at least the following two parameters: S6.1 A steady-state error characterizes the average residual error between the actual behavior output and the preset target behavior state after the system enters a steady state; S6.2 A control effort, representing the cost incurred by the system in maintaining the preset target behavior state, is calculated by the integral square value of the control input signal; S7: Based on the steady-state error and control effort calculated in step S6, complete the evaluation of the effect of the pollutant to be tested on the function of the selected neuron.

2. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 1, characterized in that, In step S1, when the upstream neuron is an excitatory neuron, the light-sensitive channel protein is Channelrhodopsin-2; and the downstream effector is a VB / DB type motor neuron or the body wall muscle innervated by it, the calcium ion indicator is GCaMP6s; when the upstream neuron in step S1 is an inhibitory neuron, the light-sensitive channel protein is an inhibitory optogenetic tool; and the downstream effector is a VB / DB type motor neuron inhibited by it or the body wall muscle innervated by it, the calcium ion indicator is GCaMP6s.

3. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 1, characterized in that... The closed-loop adaptive optogenetic microfluidic platform in step S3 includes a microfluidic chip with a physical capture structure for partially fixing the body of the nematode strain and allowing its head region to swing freely.

4. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 1, characterized in that, The preset target behavior state set in step S3 is a constant target value for the nematode head swaying frequency, and the actual behavior output is the instantaneous swaying frequency of the nematode head.

5. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 4, characterized in that, The step S3, which involves real-time acquisition of the instantaneous swaying frequency of the nematode's head, is achieved by acquiring bright-field images using a high frame rate camera and then using machine vision algorithms to analyze and extract the data in real time.

6. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 1, characterized in that, The digital controller algorithm in step S4 is a PID controller, and the generation of the control input signal is calculated based on a proportional term, an integral term, and a derivative term of the behavior error. The proportional gain, integral gain, and derivative gain remain constant in the pollutant exposure group and the control group.

7. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 6, characterized in that, In step S4, the control input signal modulates the intensity of the light stimulation by driving a digital micromirror device or a scanning galvanometer.

8. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 1, characterized in that, The neural adaptive injury feature spectrum index calculated in step S6 further includes at least one of the following parameters: A rise time characterizes the system's response speed to a step change in the target's behavioral state; A peak overshoot represents the maximum oscillation amplitude of the system's response to a step change in the target behavior state.

9. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 1, characterized in that, The exposure treatment in step S2 involves subjecting the nematode strain to static liquid exposure.

10. The method for detecting closed-loop adaptive neural function in *C. elegans* based on a specific neural circuit probe according to claim 1, characterized in that, The pollutant to be tested is a PPD quinone derivative, including one or more of IPPD-Q, DPPD-Q, or DTPD-Q.

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