Microbiological detection guided water sample contamination test method

Abstract

The present application relates to the technical field of water quality monitoring, and discloses a water sample pollution inspection method guided by microorganism detection, comprising: applying a pulsed electric field to a biochemical response system to reduce the mass transfer resistance of the cell membrane of an indicator microorganism by using a physical pore-forming effect; injecting a fluorescent substrate and synchronously collecting fluorescence emission intensity and backscattering light intensity; correcting the amplitude of the fluorescence emission intensity by using the backscattering light intensity to eliminate physical shielding interference and obtain a pre-steady-state fluorescence emission sequence; intercepting a characteristic value of the change rate of the pre-steady-state fluorescence emission sequence to calculate an intrinsic catalytic turnover index representing the specific catalytic activity of intracellular enzymes, and determining the pollution degree of the water sample to be tested according to the offset of the index relative to a preset reference value; and the present application can quickly identify pollutants with transmembrane mass transfer disorders and eliminate the influence of endogenous activity fluctuations of microorganisms on the detection result by means of the cooperation of electric pore-forming intervention and calculation logic.

Description

Technical Field

[0001] This invention belongs to the field of water quality monitoring technology, and in particular relates to a method for testing water sample contamination guided by microbial detection. Background Technology

[0002] Currently, in water resource protection and early warning systems, using the biochemical responses of indicator microorganisms to determine the acute toxicity of water bodies is a recognized technical approach. This method uses living microorganisms as sensing nodes, monitoring changes in their metabolic activity to characterize the comprehensive toxic effects of multiple pollutants on biological systems. When specific functional enzymes within microorganisms are subjected to substrate or inducer shocks, their biochemical reactions exhibit distinct kinetic segments, specifically including a short-term pre-steady-state surge phase and a steady-state catalytic phase where the slope tends to be constant. This physical evolution from the instantaneous release of products to reaching saturation equilibrium constitutes the underlying mechanism of water quality biochemical testing. However, deploying such biosensors... When dealing with industrial drainage outlets or water supply points in highly dynamic and complex background environments, there is an inherent conflict between detection timeliness and accuracy. Existing technologies generally observe the macroscopic proliferation or steady-state metabolic levels of microorganisms. Due to the complex protein synthesis and transcription processes involved, the response cycle is relatively long. If the observation time is compressed, it will induce signal logic aliasing between fluctuations in endogenous activity of microorganisms and inhibition by exogenous toxicity. Since the abundance of effective enzyme library of indicator strains drifts randomly with batch, dormancy state and matrix environment, the judgment mechanism based on absolute reaction rate and comparison with historical benchmarks cannot distinguish from the physical level whether the decrease in output value is due to pollutant interference or the activity decay of the biological sensing node itself.

[0003] At the hardware level, existing detection optical paths often struggle to maintain signal stability under strong background noise. At the software level, such as the interpretation logic, existing dynamic monitoring methods have fundamental limitations. For example, Chinese invention patent CN109554437B discloses a dual-wavelength dynamic interpretation and detection method for microbial biochemical reactions, which predicts reaction results by the rate of change of the absorbance ratio of the two wavelengths to address interference from color and turbidity. However, its technical logic remains deeply anchored in the natural metabolic evolution of microorganisms. In actual complex working conditions, due to biochemical inhibition induced by pollutants… The signal and the decline in endogenous activity of microorganisms due to batch differences, aging, or environmental fluctuations have a very high similarity in macroscopic kinetic curves, which makes it impossible for the existing technology to separate background noise and toxicity characteristics from the physical mechanism level. To address the above challenges, linear improvement methods such as simply increasing the inoculation concentration or improving hardware sensitivity only achieve proportional amplification of signal and noise, without addressing the core bottleneck of biological background signal coupling. If the intrinsic parameters that normalize the current enzyme library abundance cannot be extracted in a single measurement stream, it is impossible to establish an anti-interference mechanism against the endogenous fluctuations of biological nodes.

[0004] Therefore, how to construct a testing method that can in situ remove the interference of endogenous microbial activity and decouple the pollution characteristic signal from the biological background noise has become the technical problem to be solved by this invention. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: A method for testing water sample contamination guided by microbial detection, comprising the following steps: Step S101: Introduce the water sample to be tested and indicator microorganisms with preset initial activity into the reactor to construct a biochemical response system; Step S102: A pulsed electric field is applied to the biochemical response system to generate a physical pore-forming effect and reduce the mass transfer resistance of the indicator microorganism's cell membrane, allowing organic pollutants in the water sample to enter the indicator microorganism's cell and come into contact with intracellular enzymes; wherein, the field strength of the pulsed electric field is 150V / cm to 450V / cm, the pulse width is 10μs to 50μs, the frequency of the pulsed electric field is 5Hz, the duration of a single pulse is 20s, and the inoculum concentration of the indicator microorganism in the biochemical response system is 1×10⁻⁶. 7 CFU / mL; In step S103, a fluorescent substrate and carbonyl cyano-m-chlorophenylhydrazone as a metabolic uncoupling agent are injected into the biochemical response system. The final concentration of the fluorescent substrate in the biochemical response system is set to 0.5 mmol / L, and the concentration of the metabolic uncoupling agent is set to 20 μmol / L. The fluorescence emission intensity produced by the indicator microorganism under the action of intracellular enzymes is collected in real time, the backscatter light intensity of the biochemical response system is collected simultaneously, and the initial absorbance value used to characterize the effective biomass concentration of the indicator microorganism is collected. Step S104: Perform physical shielding effect subtraction calculation on fluorescence emission intensity based on backscattered light intensity to obtain the pre-steady-state fluorescence emission intensity time sequence; Step S105: Extract the rate of change characteristic value of the reaction initiation stage from the time sequence of pre-steady-state fluorescence emission intensity. Calculate the intrinsic catalytic turnover index using the rate of change characteristic value and the initial absorbance value. Determine the pollution level of the water sample to be tested based on the normalized offset of the intrinsic catalytic turnover index relative to a preset benchmark value. The preset benchmark value is the intrinsic catalytic turnover index obtained by detecting the same batch of indicator microorganisms using uncontaminated standard water samples.

[0006] Preferably, the pulsed electric field in step S102 is used to shorten the transmembrane response delay of organic pollutants to the range of 1 to 5 minutes through the physical pore-forming effect while maintaining the integrity of the indicated microbial cells.

[0007] Preferably, the fluorescent substrate in step S103 is fluorescein diphosphate, 4-methylumbelliferone phosphate, or fluorescein digalactoside; the indicator microorganism is Escherichia coli with inhibited dehydrogenase activity, luminescent bacteria, or activated sludge complex microorganisms.

[0008] Preferably, the rule for calculating the intrinsic catalytic turnover index K in step S105 follows the formula below: Where F(t) is the pre-steady-state fluorescence emission intensity time series at the acquisition time. to The fluorescence emission intensity function within, where B is the initial absorbance value collected in step S103.

[0009] Preferably, the physical shielding effect subtraction calculation in step S104 includes: using the backscattered light intensity as a turbidity compensation factor to perform algebraic compensation on the amplitude of the fluorescence emission intensity, so as to eliminate the interference of suspended particulate matter in the water sample to be tested on the optical path.

[0010] Preferably, the reaction initiation phase in step S105 is 10s to 300s after the fluorescent substrate is injected; the rate of change characteristic value is the maximum value of the first derivative of the pre-steady-state fluorescence emission intensity time sequence.

[0011] Preferably, before introducing the indicator microorganism in step S101, the indicator microorganism is placed in a preset nutrient substrate and activated and revived at 20°C to 37°C for 30 min to 120 min, so that the initial metabolic load of the biochemical response system is within a preset fluctuation range.

[0012] Preferably, the intrinsic catalytic turnover index fluctuates within a range of less than 5% when the initial activity changes or the water sample is diluted; when the absolute value of the normalized offset exceeds 20%, it is determined that the water sample contains exogenous inhibitory substances.

[0013] Preferably, the physical pore-forming effect generated by the pulsed electric field in step S102 and the intrinsic catalytic turnover index calculation logic in step S105 work together to offset the detection error caused by fluctuations in the activity of the indicator microorganisms themselves when detecting organic pollutants with transmembrane resistance.

[0014] Preferably, after determining the pollution level of the water sample to be tested, the following steps are also included: monitoring the rate of change of the intrinsic catalytic turnover index over time, and outputting a water quality abnormality warning command when the rate of change exceeds the preset alarm threshold for three consecutive detection cycles.

[0015] Compared with existing technologies, the microbial detection-guided water sample contamination testing method of the present invention has the following advantages: 1. In water sample pollution testing, the target enzyme inside the microorganism is triggered to enter the extreme catalytic state by metabolic uncoupling agents. This changes the detection process from observing the macroscopic growth cycle of the microorganism to monitoring the transient catalytic kinetic response of the intracellular characteristic enzyme. This avoids the long steady-state establishment time required for gene transcription and protein synthesis in organisms, compressing the biochemical response window, which was originally on the order of hours, to the order of minutes, thereby improving the early warning timeliness of sudden water pollution events.

[0016] 2. Employing a homologous coupling mechanism between the pre-steady-state surge integral value and the steady-state enzymatic reaction rate, the pre-steady-state fluorescence signal generated instantaneously by the uncoupling agent shock characterizes the true effective enzyme library abundance within the system. This signal is then used as an endogenous reference standard to normalize subsequent steady-state reaction rates, generating an evaluation index that reflects only the intrinsic catalytic turnover capacity of enzyme molecules. This endogenous self-calibration method eliminates parasitic interferences from indicator strain inoculation errors, strain aging, and physical dilution of water samples on the detection output. This elevates the pollution analysis index from the absolute reaction rate, which is susceptible to environmental fluctuations, to an intrinsic constant characterizing the microscopic conformational integrity of enzyme molecules. It resolves the signal logic aliasing problem between endogenous activity fluctuations and exogenous toxicity inhibition in biological systems, enhancing the system's operational stability under complex industrial conditions.

[0017] 3. By utilizing the synergistic effect of sublethal electroporation pulse treatment and biochemical reaction system, the pore size of microbial cell membranes is reversibly expanded through a transient electric field, eliminating the mass transfer resistance of macromolecular pollutants entering the cell across the membrane, and forcing toxins to make instantaneous contact with intracellular target enzymes. This combination of physical pulse and biochemical triggering ensures that the detection system can capture organic pollution signals with slow permeation rates, expands the response spectrum of indicator microorganisms to pollutants of different molecular weights, and enhances the ability to identify potential pollution risks. Attached Figure Description

[0018] Figure 1 This is a flowchart of the water pollution testing process based on electroporation and fluorescence response of the present invention. Figure 2 This is a logic diagram for pollution assessment and early warning of the intrinsic catalytic turnover index of this invention. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0020] A microbial detection-guided method for testing water sample contamination includes the following steps: Step S101: Introduce the water sample to be tested and indicator microorganisms with preset initial activity into the reactor to construct a biochemical response system; Step S102: A pulsed electric field is applied to the biochemical response system to generate a physical pore-forming effect and reduce the mass transfer resistance of the indicator microorganism's cell membrane, allowing organic pollutants in the water sample to enter the indicator microorganism's cell and come into contact with intracellular enzymes; wherein, the field strength of the pulsed electric field is 150V / cm to 450V / cm, the pulse width is 10μs to 50μs, the frequency of the pulsed electric field is 5Hz, the duration of a single pulse is 20s, and the inoculum concentration of the indicator microorganism in the biochemical response system is 1×10⁻⁶. 7 CFU / mL; In step S103, a fluorescent substrate and carbonyl cyano-m-chlorophenylhydrazone as a metabolic uncoupling agent are injected into the biochemical response system. The final concentration of the fluorescent substrate in the biochemical response system is set to 0.5 mmol / L, and the concentration of the metabolic uncoupling agent is set to 20 μmol / L. The fluorescence emission intensity produced by the indicator microorganism under the action of intracellular enzymes is collected in real time, the backscatter light intensity of the biochemical response system is collected simultaneously, and the initial absorbance value used to characterize the effective biomass concentration of the indicator microorganism is collected. Step S104: Perform physical shielding effect subtraction calculation on fluorescence emission intensity based on backscattered light intensity to obtain the pre-steady-state fluorescence emission intensity time sequence; Step S105: Extract the rate of change characteristic value of the reaction initiation stage from the time sequence of pre-steady-state fluorescence emission intensity. Calculate the intrinsic catalytic turnover index using the rate of change characteristic value and the initial absorbance value. Determine the pollution level of the water sample to be tested based on the normalized offset of the intrinsic catalytic turnover index relative to a preset benchmark value. The preset benchmark value is the intrinsic catalytic turnover index obtained by detecting the same batch of indicator microorganisms using uncontaminated standard water samples.

[0021] Preferably, the pulsed electric field in step S102 is used to shorten the transmembrane response delay of organic pollutants to the range of 1 to 5 minutes through the physical pore-forming effect while maintaining the integrity of the indicated microbial cells.

[0022] Preferably, the fluorescent substrate in step S103 is fluorescein diphosphate, 4-methylumbelliferone phosphate, or fluorescein digalactoside; the indicator microorganism is Escherichia coli with inhibited dehydrogenase activity, luminescent bacteria, or activated sludge complex microorganisms.

[0023] Preferably, the rule for calculating the intrinsic catalytic turnover index K in step S105 follows the formula below: Where F(t) is the pre-steady-state fluorescence emission intensity time series at the acquisition time. to The fluorescence emission intensity function within, where B is the initial absorbance value collected in step S103.

[0024] Preferably, the physical shielding effect subtraction calculation in step S104 includes: using the backscattered light intensity as a turbidity compensation factor to perform algebraic compensation on the amplitude of the fluorescence emission intensity, so as to eliminate the interference of suspended particulate matter in the water sample to be tested on the optical path.

[0025] Preferably, the reaction initiation phase in step S105 is 10s to 300s after the fluorescent substrate is injected; the rate of change characteristic value is the maximum value of the first derivative of the pre-steady-state fluorescence emission intensity time sequence.

[0026] Preferably, before introducing the indicator microorganism in step S101, the indicator microorganism is placed in a preset nutrient substrate and activated and revived at 20°C to 37°C for 30 min to 120 min, so that the initial metabolic load of the biochemical response system is within a preset fluctuation range.

[0027] Preferably, the intrinsic catalytic turnover index fluctuates within a range of less than 5% when the initial activity changes or the water sample is diluted; when the absolute value of the normalized offset exceeds 20%, it is determined that the water sample contains exogenous inhibitory substances.

[0028] Preferably, the physical pore-forming effect generated by the pulsed electric field in step S102 and the intrinsic catalytic turnover index calculation logic in step S105 work together to offset the detection error caused by fluctuations in the activity of the indicator microorganisms themselves when detecting organic pollutants with transmembrane resistance.

[0029] Preferably, after determining the pollution level of the water sample to be tested, the following steps are also included: monitoring the rate of change of the intrinsic catalytic turnover index over time, and outputting a water quality abnormality warning command when the rate of change exceeds the preset alarm threshold for three consecutive detection cycles.

[0030] Example 1: When the system faces continuous water quality monitoring of high-turbidity chemical wastewater discharge outlets containing organic matter, biochemical testing methods based on indicators of microbial proliferation or metabolism require gene transcription and protein synthesis cycles, resulting in a response time delay. Furthermore, the physical quenching effect of suspended particles in the water and the inhibition by exogenous toxicity cause signal aliasing. Introducing the water sample to be tested into the reactor and placing it in a pre-set nutrient substrate at 35°C... Escherichia coli, activated and revived for 60 min under certain conditions to ensure the initial metabolic load of the biochemical response system is within a preset fluctuation range, was used as the preset indicator microorganism for initial activity. The inoculum concentration of the indicator microorganism in the biochemical response system was controlled at [specific value]. A biochemical response system was constructed using CFU / mL. A pulsed electric field with a strength of 250V / cm and a pulse width of 30μs was applied to the biochemical response system. The pulse frequency was set to 5Hz and the duration of a single pulse was 20s. Under the condition of maintaining the integrity of the indicator microbial cells, a physical pore-forming effect was generated, which reduced the mass transfer resistance of the indicator microbial cell membrane. This allowed organic pollutants in the water sample to enter the indicator microbial cell and come into contact with the intracellular enzymes, thus shortening the transmembrane response delay of organic pollutants to 2min.

[0031] Luciferin diphosphate was injected into the biochemical response system as a fluorescent substrate, with a final concentration of 0.5 mmol / L. Simultaneously, carbonyl cyano-m-chlorophenylhydrazone (CCCP) at a concentration of 20 μmol / L was added as an uncoupling agent. This uncoupling agent forced the intracellular target enzyme into its ultimate catalytic state by eliminating the proton gradient across the cell membrane. The fluorescence emission intensity produced by the indicator microorganism under the action of the intracellular enzyme was collected in real time, and the backscattered light intensity of the biochemical response system was simultaneously collected. Data were also collected for characterizing the indicator microorganism. The initial absorbance value of the effective biomass concentration of microorganisms was determined. Backscattered light intensity was used as a turbidity compensation factor to algebraically compensate for the amplitude of fluorescence emission intensity, eliminating the interference of suspended particulate matter in the water sample on the optical path, thus obtaining the pre-steady-state fluorescence emission intensity time series. The period from 15 s to 180 s after substrate injection in the pre-steady-state fluorescence emission intensity time series was taken as the reaction initiation stage. The maximum value of the first derivative was extracted from this sequence as the rate of change characteristic value. The intrinsic catalytic turnover index K was calculated using the rate of change characteristic value and the initial absorbance value, following the formula... Where F(t) is the pre-steady-state fluorescence emission intensity time series at the acquisition time. to The fluorescence emission intensity function within the system, where B is the initial absorbance value collected, is used in this calculation step. This step performs a normalized division process on the pre-steady-state surge integral area reflecting the abundance of the total effective target enzyme library within the system and the overall biomass scalar. The output is an in-situ quantitative parameter reflecting the biochemical evolution state within a single measurement stream. The transient catalytic area (integral term) of the intracellular enzyme library, which is forcibly activated by a pulsed electric field, and the static total biomass (B value) constitute a dynamic comparison feature. Since the B value of aged strains remains unchanged but the transient catalytic area will decrease proportionally, the ratio generated by dividing the two represents the intrinsic turnover rate of a single enzyme molecule. Experimental calibration shows that when the initial enzyme activity of the indicator microorganism fluctuates within the range of 50% to 120% due to batch differences, the absolute value of the normalized offset of this ratio parameter always remains below 3%.

[0032] The physical pore-forming effect generated by the pulsed electric field works in synergy with the intrinsic catalytic turnover index calculation logic to offset the detection error caused by fluctuations in the activity of the indicator microorganisms themselves. When the initial activity changes or the water sample is diluted, the integral area and absorbance scalar are scaled proportionally, and the fluctuation range of the intrinsic catalytic turnover index is less than 4.5%. Exogenous toxic substances in the water cause the index to decrease. The normalized offset of the intrinsic catalytic turnover index relative to the preset benchmark value is monitored. The preset benchmark value is the intrinsic catalytic turnover index obtained by detecting the same batch of indicator microorganisms using uncontaminated standard water samples. When the absolute value of the normalized offset exceeds 20%, it is determined that there are exogenous inhibitory substances in the water sample. After determining the degree of pollution of the water sample, the rate of change of the intrinsic catalytic turnover index over time is monitored. When the rate of change exceeds the preset alarm threshold for three consecutive detection cycles, a water quality abnormality warning command is output. The pollution analysis basis is reconstructed using the internal reference mechanism of single measurement data.

[0033] Example 2: This example uses a continuous flow bioreactor testing platform equipped with a high-voltage pulse generator with a voltage output range of 0V to 1000V and a pulse width resolution of 1μs, and a dual-channel optical detector composed of a photomultiplier tube and a photodiode. A synthetic test water sample containing 50mg / L humic acid and 200NTU of kaolin suspension is injected into the platform as a background noise source. The pulse electric field strength parameter is set to balance the transmembrane mass transfer rate of organic pollutants with the integrity of the microbial cell membrane. Increasing the electric field strength... The cell membrane induces an increase in transmembrane potential, and the expansion of membrane pore size reduces the mass transfer resistance of macromolecular pollutants. When the electric field strength exceeds the dielectric breakdown threshold of the cell membrane, irreversible cell rupture and death are triggered. Preliminary cell viability fluorescence staining data showed that reversible electroporation of the cell membrane occurred when the pulsed electric field strength was in the range of 150V / cm to 450V / cm and the pulse width was in the range of 10μs to 50μs. A field strength of 250V / cm and a pulse width of 30μs were selected as the baseline parameters, and a boundary control group was set to extract performance inflection point data.

[0034] Synthetic test water samples and Escherichia coli activated and revived at 35°C for 60 min in a pre-set nutrient substrate were introduced into the reactor to construct a biochemical response system. The inoculum concentration was set at [value missing]. CFU / mL; The experimental group using baseline parameters was set up, namely, pulse field strength 250 V / cm, pulse width 30 μs, frequency 5 Hz, duration 20 s, and 20 μmol / L CCCP decoupling agent; Control group 1 was set up with the pulse electric field application step removed and the field strength 0 V / cm; Control group 2 was set up with the pulse electric field strength 100 V / cm as the out-of-range group below the lower limit; Control group 3 was set up with the pulse electric field strength 600 V / cm as the out-of-range group above the upper limit; Control group 4 was set up with the backscattered light intensity calculated by physical shielding. Each group was injected with 0.5 mmol / L fluorescein II. Phosphate was used to collect fluorescence emission intensity, backscattered light intensity, and initial absorbance values ​​in real time. The raw data showed that the initial fluorescence signal of each group exhibited baseline drift due to the optical shielding effect of kaolin and humic acid. After applying algebraic compensation to the fluorescence emission intensity amplitude based on the backscattered light intensity, the baseline of the pre-steady-state fluorescence emission intensity time series of the experimental group and control groups 1 to 3 tended to be stable. The reaction initiation stage was taken from 15s to 180s after substrate injection for each group, and the change rate characteristic value was extracted. Combined with the initial absorbance value, the intrinsic catalytic turnover index was calculated. The extracted measured data showed gradient changes and nonlinear inflection points. The lack of physical pore formation effect in control group 1 led to organic pollution. Transmembrane mass transfer was hindered, resulting in an intrinsic catalytic turnover index of 0.12 and a response delay of 45.5 min. In control group 2, the electric field strength did not reach the membrane pore size expansion threshold, with an intrinsic catalytic turnover index of 0.28 and a response delay of 18.2 min. In the experimental group, at an electric field strength of 250 V / cm, transmembrane mass transfer resistance decreased, the intrinsic catalytic turnover index increased to 1.45, and the response delay shortened to 1.8 min. When the electric field strength was increased to 600 V / cm (control group 3), a deterioration inflection point appeared; the initial absorbance value decreased by 41.5% after pulse application. The superdielectric limiting electric field caused cell rupture in the indicator microorganisms, leading to a loss of effective biomass in the system. Unable to extract the maximum effective first derivative, the characteristic value of the rate of change extracted from control group 4 was interfered with by the scattering of suspended particles, and the false value of the intrinsic catalytic turnover index was 0.85, which was 41.3% different from the experimental group. The continuously extracted intrinsic catalytic turnover index and response delay parameters showed that there was a definite correlation between the set pulse electric field input range and the characteristic value of the pre-steady-state fluorescence rate of change. The physical porosimetry effect excited by the specific field strength and pulse width, combined with the algebraic compensation operation of the dual-channel optical signal, eliminated the interference of high turbidity background and shortened the pollutant permeation time. The output intrinsic catalytic turnover index constituted a quantitative parameter for the determination of external inhibitory substances in water.

[0035] Example 3: When the system operates under continuous water quality monitoring conditions with high-frequency electromagnetic interference and optical sensor aging, the derivative of the pre-steady-state fluorescence emission intensity time series with background noise produces false change rate peaks, and the static setting of the preset benchmark value cannot adapt to the activity drift between batches of indicating microorganisms. The controller inputs the original pre-steady-state fluorescence emission intensity time series intercepted from 15s to 180s after substrate injection. The controller inputs the original pre-steady-state fluorescence emission intensity time series into the moving average filter module, sets the sliding window length to 5 sampling periods, and outputs a smoothed fluorescence intensity sequence by calculating the arithmetic mean of the fluorescence emission intensity of continuous sampling points within the window. For adjacent data points in the smoothed fluorescence intensity sequence, the discrete first derivative sequence is extracted by calculating the difference between the value of the next sampling point and the value of the previous sampling point and dividing it by the sampling time interval. The point with the largest value in the discrete first derivative sequence is retrieved as the change rate feature value.

[0036] To determine the preset benchmark value used to judge the normalization offset, the controller outputs a valve switching signal to cut off the water sample to be tested and inject uncontaminated standard water sample into the reactor. According to the set pulse electric field strength, pulse width, and fluorescent substrate injection conditions, the biochemical response system performs detection steps. The intrinsic catalytic turnover index of the standard water sample under the current sensor transmittance state and the current batch of indicator microorganisms is collected and calculated. The calculated value is written to the memory register address to overwrite the old benchmark value of the previous period, generating an updated preset benchmark value. The calculation logic of the intrinsic catalytic turnover index K works in conjunction with the moving average filter module and the benchmark reconstruction procedure to perform normalization calculation by combining the characteristic value of filtering high-frequency disturbances and the real-time biomass scalar, and outputs quantitative parameters that eliminate short-term random electromagnetic noise and long-term hardware baseline drift interference.

[0037] Example 4: When the system is in operation of changing different batches of indicator microorganisms, a preset nutrient substrate and microbial dry powder are injected into a separately set bypass container and revived at 35°C for 60 minutes. The activated bacterial solution is extracted from the bypass container and injected into a calibration cell pre-filled with a 1 mg / L potassium dichromate standard solution. A pulsed electric field with a field strength of 250 V / cm and a pulse width of 30 μs is applied to the calibration cell and fluorescein diphosphate is injected. The intrinsic catalytic turnover index of the activated bacterial solution is calculated, and the decay rate of this value relative to the non-toxic control cell is extracted and it is determined whether it falls within the range of 45% to 55%. If the decay rate falls within the range, the injection valve is triggered to introduce the activated bacterial solution in the bypass container into the reactor to construct a biochemical response system. If the decay rate does not fall within the range, the activated bacterial solution in the bypass container is emptied and an abnormal status electrical signal is output to block the abnormal activity microbial community from entering the detection water path.

[0038] During the on-site deployment and commissioning phase for high-turbidity water discharge outlets, the controller drives the inlet pump to continuously extract on-site raw water that has been confirmed to be free of exogenous toxicity within 72 hours. The system sequentially applies pulsed electric fields to the on-site raw water in each sampling period and extracts the time series of pre-steady-state fluorescence emission intensity calculated after backscattering light intensity compensation. It then calculates and outputs the historical sequence of intrinsic catalytic turnover index under the background conditions of the on-site raw water. The processor extracts the arithmetic mean and standard deviation of each value in the historical sequence, multiplies them by a constant of 3, and sets the resulting value as the preset alarm threshold. The above steps establish a numerical mapping between the threshold parameter and the fluid optical and physical background of the deployment environment, and output the discrimination boundary parameter that matches the background fluctuation of the on-site water body.

[0039] Example 5: When the system operates in environments where the particle size distribution and refractive index of suspended particulate matter vary across different industrial sites, static constant compensation will cause baseline shift in fluorescence emission intensity calibration. To eliminate this interference, the system initiates a pre-deployment optical reference calibration procedure. The controller activates the infusion pump to draw raw water from the discharge port, guiding it through a 0.22 μm pore size filter membrane assembly and into a calibration container as an optical blank matrix. A 100 μg / L concentration of free sodium fluorescein is injected into the calibration container, and the stirrer is activated. The infusion pump then injects kaolin standard turbidity solution into the calibration container in increments of 10 NTU to 200 NTU, establishing a dynamic water sample sequence containing multiple scattering intensities. After each turbidity gradient stabilizes, a photomultiplier tube and a photodiode... The tube synchronously collects the original fluorescence emission intensity and backscatter light intensity of the current water sample, constructing a discrete data array composed of multiple sets of synchronous data points. Since the concentration of free sodium fluorescein is fixed, the theoretical fluorescence emission intensity remains constant. The processor determines the optical compensation coefficient by executing a calibration subroutine: the inlet pump is turned on with a step gradient of 10 NTU, so that the turbidity in the calibration container increases linearly from 0 NTU to 200 NTU. After stabilizing for 5 seconds at each step point, 20 sets of discrete data pairs of backscatter light and fluorescence are collected. The fitting algorithm sets the initial search value of the compensation coefficient to 0.010, and performs least squares iteration in a step of 0.001 within a preset physical threshold range of 0.005 to 0.015 until the sum of squared residuals is less than 0.001, at which point the final coefficient is locked.

[0040] The processor receives a discrete data array, uses the least squares method to fit the data points in the array, and calculates the coefficients of the algebraic compensation model. The algebraic compensation model follows the relational expression... ,in, The pre-steady-state fluorescence emission intensity, The original fluorescence emission intensity, To determine the backscattered light intensity, the theoretical constant and the intensity under each gradient are minimized. The residual sum of squares is used to calculate the specific value of the optical compensation coefficient γ specific to the current water body; the processor writes this specific value into non-volatile memory to replace the default parameter, and calls this exclusive value in subsequent detection steps to perform real-time correction of the fluorescence signal, establishes the mathematical conversion relationship between backscattered light intensity and fluorescence physical shielding effect, eliminates measurement distortion caused by differences in the physical properties of suspended matter in specific water bodies, and outputs signal compensation rules that fit the optical background of the fluid on site.

[0041] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.

Claims

1. A method for testing water sample contamination guided by microbial detection, characterized in that, Includes the following steps: Step S101: Introduce the water sample to be tested and indicator microorganisms with preset initial activity into the reactor to construct a biochemical response system; Step S102: A pulsed electric field is applied to the biochemical response system to generate a physical pore-forming effect and reduce the mass transfer resistance of the indicator microorganism's cell membrane, allowing organic pollutants in the water sample to enter the indicator microorganism's cell and come into contact with intracellular enzymes; wherein, the field strength of the pulsed electric field is 150V / cm to 450V / cm, the pulse width is 10μs to 50μs, the frequency of the pulsed electric field is 5Hz, the duration of a single pulse is 20s, and the inoculum concentration of the indicator microorganism in the biochemical response system is 1×10⁻⁶. 7 CFU / mL; In step S103, a fluorescent substrate and carbonyl cyano-m-chlorophenylhydrazone as a metabolic uncoupling agent are injected into the biochemical response system. The final concentration of the fluorescent substrate in the biochemical response system is set to 0.5 mmol / L, and the concentration of the metabolic uncoupling agent is set to 20 μmol / L. The fluorescence emission intensity produced by the indicator microorganism under the action of intracellular enzymes is collected in real time, the backscatter light intensity of the biochemical response system is collected simultaneously, and the initial absorbance value used to characterize the effective biomass concentration of the indicator microorganism is collected. Step S104: Perform physical shielding effect subtraction calculation on fluorescence emission intensity based on backscattered light intensity to obtain the pre-steady-state fluorescence emission intensity time sequence; Step S105: Extract the rate of change characteristic value of the reaction initiation stage from the time sequence of pre-steady-state fluorescence emission intensity. Calculate the intrinsic catalytic turnover index using the rate of change characteristic value and the initial absorbance value. Determine the pollution level of the water sample to be tested based on the normalized offset of the intrinsic catalytic turnover index relative to a preset benchmark value. The preset benchmark value is the intrinsic catalytic turnover index obtained by detecting the same batch of indicator microorganisms using uncontaminated standard water samples.

2. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, The pulsed electric field in step S102 is used to shorten the transmembrane response delay of organic pollutants to the range of 1 to 5 minutes through the physical pore-forming effect while maintaining the integrity of the indicated microbial cells.

3. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, The fluorescent substrate in step S103 is fluorescein diphosphate, 4-methylumbelliferone phosphate, or fluorescein digalactoside; the indicator microorganism is Escherichia coli with inhibited dehydrogenase activity, luminescent bacteria, or activated sludge complex microorganisms.

4. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, The rule for calculating the intrinsic catalytic turnover index K in step S105 follows the formula below: Where F(t) is the pre-steady-state fluorescence emission intensity time series at the acquisition time. to The fluorescence emission intensity function within, where B is the initial absorbance value collected in step S103.

5. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, The physical shielding effect subtraction calculation in step S104 includes: using the backscattered light intensity as a turbidity compensation factor to perform algebraic compensation on the amplitude of fluorescence emission intensity in order to eliminate the interference of suspended particulate matter in the water sample to be tested on the optical path.

6. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, The reaction initiation phase in step S105 is from 10 s to 300 s after fluorescent substrate injection; the rate of change characteristic value is the maximum value of the first derivative of the pre-steady-state fluorescence emission intensity time sequence.

7. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, Before introducing the indicator microorganism in step S101, the indicator microorganism is placed in a preset nutrient substrate and activated and revived at 20°C to 37°C for 30 min to 120 min, so that the initial metabolic load of the biochemical response system is within the preset fluctuation range.

8. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, The intrinsic catalytic turnover index fluctuates within a range of less than 5% when the initial activity changes or the water sample is diluted; when the absolute value of the normalized offset exceeds 20%, it is determined that there are exogenous inhibitory substances in the water sample.

9. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, The physical pore-forming effect generated by the pulsed electric field in step S102 works in conjunction with the intrinsic catalytic turnover index calculation logic in step S105 to offset the detection error caused by fluctuations in the activity of the indicator microorganisms themselves when detecting organic pollutants with transmembrane resistance.

10. The method for testing water sample contamination guided by microbial detection according to claim 1, characterized in that, After determining the pollution level of the water sample to be tested, the following steps are also included: monitoring the rate of change of the intrinsic catalytic turnover index over time, and outputting a water quality abnormality warning command when the rate of change exceeds the preset alarm threshold for three consecutive detection cycles.

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