A rapid drug sensitivity detection method

Abstract

The invention discloses a rapid drug sensitivity detection method, comprising the following steps: S1, mixing a bacterial liquid of a strain to be detected, an antibiotic solution and a suitable culture medium, and incubating the mixture at a suitable temperature to allow the bacteria to react with the antibiotic; S2, using an electrochemical sensor to monitor the mixed solution after incubation in real time, and reflecting the growth state of the bacteria and the inhibitory effect of the antibiotic by measuring the change of a specific electrochemical signal; S3, judging the antibiotic sensitivity of the bacteria according to the degree of change of the electrochemical signal and a preset threshold value. The invention can monitor the growth state of the bacteria and the inhibitory effect of the antibiotic in real time through electrochemical monitoring, especially using a microbial fuel cell (MFC) sensor, greatly shortening the time of drug sensitivity detection. Compared with the traditional culture method, the method does not need to wait for the formation of bacterial colonies, thereby significantly improving the detection efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of drug sensitivity detection, and in particular to a rapid drug sensitivity detection method. Background Art

[0002] The problem of bacterial resistance is a global problem. The abuse of antibiotics has led to an increasing number of drug-resistant bacteria, and even the emergence of super bacteria resistant to multiple antibiotics. Clinically, it is necessary to conduct drug sensitivity testing on drug-resistant bacteria. The drug sensitivity testing method, that is, the drug sensitivity test, is mainly to determine whether antimicrobial drugs have inhibitory or bactericidal effects on pathogenic microorganisms in vitro, which is of great significance for guiding clinical selection of medication and timely control of infection.

[0003] Timely detection of bacterial resistance or sensitivity to antibiotics in clinical practice is crucial for effective treatment of patients, especially critically ill patients (such as sepsis and pneumonia). At present, mainstream hospitals and institutions all use traditional phenotypic drug sensitivity tests, namely the disc diffusion method (KB value) or the microbroth dilution method (MIC value). This traditional clinical drug sensitivity test relies on bacterial growth. It takes 1 day for the drug sensitivity results of common fast-growing bacteria, while it takes several weeks for slow-growing bacteria, which makes it impossible for patients to receive accurate and effective treatment, resulting in drug resistance and increased mortality. However, molecular drug sensitivity detection technology (mass spectrometry, NGS) has great limitations and cannot be applied on a large scale in clinical practice. In addition, although the automatic drug sensitivity testers used in clinical laboratories, such as the BioMérieux VITEK-2 and BD Phoenix M50 drug sensitivity instruments, are simple, they require more than ten hours of overnight culture to obtain drug sensitivity results. The detection time of slow-growing bacteria such as Mycobacterium tuberculosis is as long as 2-4 weeks, which is time-consuming and easily affected by the operator.

[0004] In view of this, in recent years, many research institutions and enterprises want to make breakthroughs and seek innovations at the technical level. Nowadays, most of the automated drug sensitivity testers on the market use photoelectric colorimetry and fluorescence methods. The former measures the bacterial viability by measuring the changes in pH and transmittance caused by the growth of bacteria using substrates, while the latter adds enzyme substrates to the small holes of the test card to combine with the enzymes produced by bacteria to generate fluorescent substances. However, both methods cannot avoid the occurrence of false negatives; BGI uses molecular biological methods to develop detection kits to identify drug-resistant bacteria by detecting bacterial resistance gene mutations. The accuracy is high, but this method has low universality and cannot cover all phenotypic resistance (gold standard); in addition, there are kits that use biochemical methods to detect drug-resistant bacteria, such as the Antu Biological Mycoplasma Drug Sensitivity Kit and the Merieux Pneumococcal Drug Sensitivity Kit. These kits are generally small in scope and can only detect one or several common drug-resistant bacteria. In addition, although methods for detecting bacterial metabolic states (such as Raman spectroscopy) and detecting morphological changes of single bacteria under the action of antibiotics can shorten the drug sensitivity time to 2-3 hours, these technologies have low throughput and their accuracy needs to be improved or verified.

[0005] Based on the above content, the inventors found that there is a lack of methods on the market that can perform drug sensitivity testing in a short time and ensure the accuracy and applicability of the test results. To this end, we proposed a rapid drug sensitivity testing method. Summary of the invention

[0006] The main purpose of the present invention is to provide a rapid drug sensitivity detection method. The present invention can monitor the growth state of bacteria and the inhibitory effect of antibiotics in real time through electrochemical monitoring, especially by using a microbial fuel cell (MFC) sensor, thereby greatly shortening the time of drug sensitivity detection. Compared with the traditional culture method, the method does not need to wait for the formation of bacterial colonies, thereby significantly improving the detection efficiency. The composition and proportion of the culture medium of the present invention can be adjusted as needed according to the specific needs of the strain to be tested, so that the method can be applied to different types of bacteria, enhancing the practicality and scope of application of the method. The concentration of the antibiotic solution is also adjustable within the commonly used clinical concentration range, providing experimenters with greater flexibility and operating space, and can effectively solve the problems in the background technology.

[0007] To achieve the above object, the technical solution adopted by the present invention is:

[0008] A rapid drug sensitivity detection method comprises the following steps:

[0009] S1. Mix the bacterial solution of the strain to be tested, the antibiotic solution and a suitable culture medium, and incubate them at a suitable temperature to allow the bacteria to react with the antibiotics;

[0010] S2. Using an electrochemical sensor to monitor the mixed solution after incubation in real time, and to reflect the growth status of bacteria and the inhibitory effect of antibiotics by measuring the changes in specific electrochemical signals;

[0011] S3. Determine the antibiotic sensitivity of bacteria based on the degree of change of the electrochemical signal and the preset threshold.

[0012] In the present invention, a comprehensive and systematic rapid drug sensitivity detection method is provided. The method uses electrochemical monitoring to monitor bacterial growth and metabolic activity by measuring current or voltage changes, which can directly reflect the inhibitory effect of antibiotics on bacteria. From mixed incubation to electrochemical monitoring to result judgment, the steps are clear and easy to operate. The method covers the interaction between bacteria and antibiotics, can truly reflect the growth state of bacteria under the action of antibiotics, and provide a reliable basis for drug sensitivity detection.

[0013] Further, in step S2, the electrochemical sensor is a microbial fuel cell (MFC) sensor, and the growth and metabolic activity of bacteria are monitored by measuring the current or voltage changes generated by the MFC.

[0014] In the present invention, a microbial fuel cell (MFC) sensor is used as an electrochemical sensor, which has the characteristics of high sensitivity and strong real-time monitoring capability. The MFC sensor monitors bacterial growth and metabolic activity by measuring current or voltage changes, which can directly reflect the inhibitory effect of antibiotics on bacteria and improve the accuracy of drug sensitivity detection.

[0015] Furthermore, the specific steps of step S2 are as follows:

[0016] (1) constructing an MFC sensor, including an anode chamber, a cathode chamber and a separator, wherein the anode chamber is inoculated with a bacterial solution of the strain to be tested, and an electrolyte solution is added to the cathode chamber;

[0017] (2) adding the antibiotic solution into the anode chamber, mixing it with the bacterial solution of the strain to be tested, and starting incubation;

[0018] (3) During the incubation process, monitor the current or voltage changes generated by the MFC in real time and record the data;

[0019] (4) Evaluate the inhibitory effect of antibiotics on bacterial growth based on the changing trend and amplitude of current or voltage.

[0020] In the present invention, the construction and use steps of the MFC sensor are described in detail to ensure the repeatability and accuracy of the experiment, and by real-time monitoring of the current or voltage changes generated by the MFC and recording the data, rich experimental data are provided for subsequent drug sensitivity judgment.

[0021] Furthermore, in step S3, the preset threshold is derived based on a large amount of experimental data and is used to distinguish the sensitive, intermediate and resistant states of bacteria to antibiotics.

[0022] In the present invention, the preset threshold is derived based on a large amount of experimental data, which ensures the objectivity and accuracy of drug sensitivity judgment, and provides strong support for clinical drug use by distinguishing the sensitive, intermediate and resistant states of bacteria to antibiotics.

[0023] Furthermore, in step S1, the composition and proportion of the culture medium can be adjusted as needed according to the specific requirements of the strain to be tested to ensure normal growth and reproduction of the bacteria.

[0024] In the present invention, the composition and proportion of the culture medium can be adjusted as needed according to the specific needs of the strain to be tested, thereby improving the scope of application and accuracy of drug sensitivity testing. This flexibility enables the method to be applicable to different types of bacteria, thereby enhancing the practicality and applicability of the method.

[0025] Furthermore, in step S1, the concentration of the antibiotic solution is within the commonly used clinical concentration range, such as 60 to 256 μg / mL, and the specific concentration can be adjusted according to experimental needs.

[0026] In the present invention, the concentration of the antibiotic solution of the present invention is within the commonly used clinical concentration range, ensuring the practicality and reference value of the drug sensitivity test results. The specific concentration can be adjusted as needed according to experimental needs, providing experimenters with greater flexibility and good operating space.

[0027] Furthermore, in step S1, the incubation temperature is 34-37°C and the incubation time is 10 min-3 h, and the specific time is determined according to the growth rate of the bacteria and the action time of the antibiotics.

[0028] In the present invention, the incubation temperature and time range are reasonable, ensuring that the bacteria grow and reproduce under suitable conditions, and the incubation time is determined according to the growth rate of the bacteria and the action time of the antibiotics, thereby improving the accuracy and reliability of drug sensitivity detection.

[0029] Furthermore, in step S2, the electrochemical sensor needs to undergo professional technical calibration and cleaning pretreatment before use to ensure the accuracy and stability of the measurement results.

[0030] In the present invention, the electrochemical sensor undergoes professional technical calibration and cleaning pretreatment before use, which ensures the accuracy and stability of the measurement results. This pretreatment step is crucial to improving the accuracy and reliability of drug sensitivity detection data.

[0031] Furthermore, in step S3, the existing machine learning algorithm can be combined with a large amount of existing drug sensitivity detection data to perform intelligent analysis and prediction of electrochemical signals to improve the accuracy and efficiency of drug sensitivity detection.

[0032] In the present invention, the existing machine learning algorithm is used to perform intelligent analysis and prediction of electrochemical signals, which can improve the accuracy and efficiency of drug sensitivity detection. By combining a large amount of existing drug sensitivity detection data, the machine learning algorithm can more accurately determine the antibiotic sensitivity of bacteria and provide a more scientific basis for clinical drug use.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention can monitor the growth status of bacteria and the inhibitory effect of antibiotics in real time through electrochemical monitoring, especially by using a microbial fuel cell (MFC) sensor, greatly shortening the time of drug sensitivity detection. Compared with the traditional culture method, this method does not need to wait for the formation of bacterial colonies, thereby significantly improving the detection efficiency.

[0035] The MFC sensor used in the present invention has high sensitivity and can capture tiny changes in electrochemical signals. These changes directly reflect the growth status of bacteria and the inhibitory effect of antibiotics. By setting a preset threshold, the method can accurately distinguish the sensitive, intermediate and resistant states of bacteria to antibiotics, providing a reliable basis for clinical medication.

[0036] The composition and proportion of the culture medium of the present invention can be adjusted as needed according to the specific needs of the strain to be tested, so that the method can be applied to different types of bacteria, enhancing the practicality and applicability of the method. The concentration of the antibiotic solution is also adjustable within the commonly used clinical concentration range, providing experimenters with greater flexibility and operating space.

[0037] The present invention cooperates with the existing machine learning algorithm, and the method can perform intelligent analysis and prediction of electrochemical signals, further improving the accuracy and efficiency of drug sensitivity detection. The application of intelligent technology makes the method more efficient and accurate in data processing and result judgment, providing a more scientific basis for clinical drug use. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The present invention is a detailed operation flow chart of a rapid drug sensitivity detection method. DETAILED DESCRIPTION

[0039] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0040] Embodiment 1

[0041] A rapid drug sensitivity detection method comprises the following steps:

[0042] S1. Mix the bacterial solution of the strain to be tested, the antibiotic solution and a suitable culture medium, and incubate them at a suitable temperature to allow the bacteria to react with the antibiotics;

[0043] S2. Using an electrochemical sensor to monitor the mixed solution after incubation in real time, and to reflect the growth status of bacteria and the inhibitory effect of antibiotics by measuring the changes in specific electrochemical signals;

[0044] S3. Determine the antibiotic sensitivity of bacteria based on the degree of change of the electrochemical signal and the preset threshold.

[0045] In the present invention, a comprehensive and systematic rapid drug sensitivity detection method is provided. The method uses electrochemical monitoring to monitor bacterial growth and metabolic activity by measuring current or voltage changes, which can directly reflect the inhibitory effect of antibiotics on bacteria. From mixed incubation to electrochemical monitoring to result judgment, the steps are clear and easy to operate. The method covers the interaction between bacteria and antibiotics, can truly reflect the growth state of bacteria under the action of antibiotics, and provide a reliable basis for drug sensitivity detection.

[0046] Wherein, in step S2, the electrochemical sensor is a microbial fuel cell (MFC) sensor, and the growth and metabolic activity of bacteria are monitored by measuring the current or voltage changes generated by the MFC.

[0047] In the present invention, a microbial fuel cell (MFC) sensor is used as an electrochemical sensor, which has the characteristics of high sensitivity and strong real-time monitoring capability. The MFC sensor monitors bacterial growth and metabolic activity by measuring current or voltage changes, which can directly reflect the inhibitory effect of antibiotics on bacteria and improve the accuracy of drug sensitivity detection.

[0048] The specific steps of step S2 are as follows:

[0049] (1) constructing an MFC sensor, including an anode chamber, a cathode chamber and a separator, wherein the anode chamber is inoculated with a bacterial solution of the strain to be tested, and an electrolyte solution is added to the cathode chamber;

[0050] (2) adding the antibiotic solution into the anode chamber, mixing it with the bacterial solution of the strain to be tested, and starting incubation;

[0051] (3) During the incubation process, monitor the current or voltage changes generated by the MFC in real time and record the data;

[0052] (4) Evaluate the inhibitory effect of antibiotics on bacterial growth based on the changing trend and amplitude of current or voltage.

[0053] In the present invention, the construction and use steps of the MFC sensor are described in detail to ensure the repeatability and accuracy of the experiment, and by real-time monitoring of the current or voltage changes generated by the MFC and recording the data, rich experimental data are provided for subsequent drug sensitivity judgment.

[0054] Wherein, in step S3, the preset threshold is obtained based on a large amount of experimental data and is used to distinguish the sensitive, intermediate and resistant states of bacteria to antibiotics.

[0055] In the present invention, the preset threshold is derived based on a large amount of experimental data, which ensures the objectivity and accuracy of drug sensitivity judgment, and provides strong support for clinical drug use by distinguishing the sensitive, intermediate and resistant states of bacteria to antibiotics.

[0056] Wherein, in step S1, the composition and proportion of the culture medium can be adjusted as needed according to the specific requirements of the strain to be tested to ensure the normal growth and reproduction of bacteria.

[0057] In the present invention, the composition and proportion of the culture medium can be adjusted as needed according to the specific needs of the strain to be tested, thereby improving the scope of application and accuracy of drug sensitivity testing. This flexibility enables the method to be applicable to different types of bacteria, thereby enhancing the practicality and applicability of the method.

[0058] Wherein, in step S1, the concentration of the antibiotic solution is within the commonly used clinical concentration range, such as 256 μg / mL, and the specific concentration can be adjusted according to experimental needs.

[0059] In the present invention, the concentration of the antibiotic solution of the present invention is within the commonly used clinical concentration range, ensuring the practicality and reference value of the drug sensitivity test results. The specific concentration can be adjusted as needed according to experimental needs, providing experimenters with greater flexibility and good operating space.

[0060] Wherein, in step S1, the incubation temperature is 37°C and the time is 0.5 hour, and the specific time is determined according to the growth rate of bacteria and the action time of antibiotics.

[0061] In the present invention, the incubation temperature and time range are reasonable, ensuring that the bacteria grow and reproduce under suitable conditions, and the incubation time is determined according to the growth rate of the bacteria and the action time of the antibiotics, thereby improving the accuracy and reliability of drug sensitivity detection.

[0062] Wherein, in step S2, the electrochemical sensor needs to undergo professional technical calibration and cleaning pretreatment before use to ensure the accuracy and stability of the measurement results.

[0063] In the present invention, the electrochemical sensor undergoes professional technical calibration and cleaning pretreatment before use, which ensures the accuracy and stability of the measurement results. This pretreatment step is crucial to improving the accuracy and reliability of drug sensitivity detection data.

[0064] Among them, in step S3, the existing machine learning algorithm can be combined with a large amount of existing drug sensitivity detection data to perform intelligent analysis and prediction of electrochemical signals to improve the accuracy and efficiency of drug sensitivity detection.

[0065] In the present invention, the existing machine learning algorithm is used to perform intelligent analysis and prediction of electrochemical signals, which can improve the accuracy and efficiency of drug sensitivity detection. By combining a large amount of existing drug sensitivity detection data, the machine learning algorithm can more accurately determine the antibiotic sensitivity of bacteria and provide a more scientific basis for clinical drug use.

[0066] Embodiment 2

[0067] A rapid drug sensitivity detection method comprises the following steps:

[0068] S1. Mix the bacterial solution of the strain to be tested, the antibiotic solution and a suitable culture medium, and incubate them at a suitable temperature to allow the bacteria to react with the antibiotics;

[0069] S2. Using an electrochemical sensor to monitor the mixed solution after incubation in real time, and to reflect the growth status of bacteria and the inhibitory effect of antibiotics by measuring the changes in specific electrochemical signals;

[0070] S3. Determine the antibiotic sensitivity of bacteria based on the degree of change of the electrochemical signal and the preset threshold.

[0071] Wherein, in step S2, the electrochemical sensor is a microbial fuel cell (MFC) sensor, and the growth and metabolic activity of bacteria are monitored by measuring the current or voltage changes generated by the MFC.

[0072] The specific steps of step S2 are as follows:

[0073] (1) constructing an MFC sensor, including an anode chamber, a cathode chamber and a separator, wherein the anode chamber is inoculated with a bacterial solution of the strain to be tested, and an electrolyte solution is added to the cathode chamber;

[0074] (2) adding the antibiotic solution into the anode chamber, mixing it with the bacterial solution of the strain to be tested, and starting incubation;

[0075] (3) During the incubation process, monitor the current or voltage changes generated by the MFC in real time and record the data;

[0076] (4) Evaluate the inhibitory effect of antibiotics on bacterial growth based on the changing trend and amplitude of current or voltage.

[0077] Wherein, in step S3, the preset threshold is obtained based on a large amount of experimental data and is used to distinguish the sensitive, intermediate and resistant states of bacteria to antibiotics.

[0078] Wherein, in step S1, the composition and proportion of the culture medium can be adjusted as needed according to the specific requirements of the strain to be tested to ensure the normal growth and reproduction of bacteria.

[0079] Wherein, in step S1, the concentration of the antibiotic solution is within the commonly used clinical concentration range, such as 60 μg / mL, and the specific concentration can be adjusted according to experimental needs.

[0080] Wherein, in step S1, the incubation temperature is 34°C and the time is 35 minutes. The specific time is determined according to the growth rate of bacteria and the action time of antibiotics.

[0081] Wherein, in step S2, the electrochemical sensor needs to undergo professional technical calibration and cleaning pretreatment before use to ensure the accuracy and stability of the measurement results.

[0082] Among them, in step S3, the existing machine learning algorithm can be combined with a large amount of existing drug sensitivity detection data to perform intelligent analysis and prediction of electrochemical signals to improve the accuracy and efficiency of drug sensitivity detection.

[0083] Embodiment 3

[0084] A rapid drug sensitivity detection method comprises the following steps:

[0085] S1. Mix the bacterial solution of the strain to be tested, the antibiotic solution and a suitable culture medium, and incubate them at a suitable temperature to allow the bacteria to react with the antibiotics;

[0086] S2. Using an electrochemical sensor to monitor the mixed solution after incubation in real time, and to reflect the growth status of bacteria and the inhibitory effect of antibiotics by measuring the changes in specific electrochemical signals;

[0087] S3. Determine the antibiotic sensitivity of bacteria based on the degree of change of the electrochemical signal and the preset threshold.

[0088] Wherein, in step S2, the electrochemical sensor is a microbial fuel cell (MFC) sensor, and the growth and metabolic activity of bacteria are monitored by measuring the current or voltage changes generated by the MFC.

[0089] The specific steps of step S2 are as follows:

[0090] (1) constructing an MFC sensor, including an anode chamber, a cathode chamber and a separator, wherein the anode chamber is inoculated with a bacterial solution of the strain to be tested, and an electrolyte solution is added to the cathode chamber;

[0091] (2) adding the antibiotic solution into the anode chamber, mixing it with the bacterial solution of the strain to be tested, and starting incubation;

[0092] (3) During the incubation process, monitor the current or voltage changes generated by the MFC in real time and record the data;

[0093] (4) Evaluate the inhibitory effect of antibiotics on bacterial growth based on the changing trend and amplitude of current or voltage.

[0094] Wherein, in step S3, the preset threshold is obtained based on a large amount of experimental data and is used to distinguish the sensitive, intermediate and resistant states of bacteria to antibiotics.

[0095] Wherein, in step S1, the composition and proportion of the culture medium can be adjusted as needed according to the specific requirements of the strain to be tested to ensure the normal growth and reproduction of bacteria.

[0096] Wherein, in step S1, the concentration of the antibiotic solution is within the commonly used clinical concentration range, such as 160 μg / mL, and the specific concentration can be adjusted according to experimental needs.

[0097] Wherein, in step S1, the incubation temperature is 36°C and the time is 40 minutes, and the specific time is determined according to the growth rate of bacteria and the action time of antibiotics.

[0098] Wherein, in step S2, the electrochemical sensor needs to undergo professional technical calibration and cleaning pretreatment before use to ensure the accuracy and stability of the measurement results.

[0099] Among them, in step S3, the existing machine learning algorithm can be combined with a large amount of existing drug sensitivity detection data to perform intelligent analysis and prediction of electrochemical signals to improve the accuracy and efficiency of drug sensitivity detection.

[0100] It should be noted that the present invention is a rapid drug sensitivity detection method, and the specific and detailed operation process is as follows:

[0101] 1. Preparation stage:

[0102] ① Strain preparation: Obtain the bacterial strain to be tested and prepare a bacterial solution of appropriate concentration.

[0103] ② Culture medium preparation: Prepare and adjust the composition and proportion of the culture medium according to the specific needs of the strain to be tested to ensure the normal growth and reproduction of bacteria.

[0104] ③ Preparation of antibiotic solution: Prepare antibiotic solution in the commonly used clinical concentration range (such as 60-256 μg / mL). The specific concentration can be adjusted according to experimental needs.

[0105] ④Electrochemical sensor preparation: Use microbial fuel cell (MFC) sensors and perform professional technical calibration and cleaning pretreatment to ensure the accuracy and stability of the measurement results.

[0106] 2. Mixed incubation stage:

[0107] ① Mixing: Mix the bacterial solution of the strain to be tested, the antibiotic solution and the appropriate culture medium together.

[0108] ② Incubation: Incubate at an appropriate temperature (34-37°C) for 10 minutes to 3 hours. The specific time depends on the growth rate of the bacteria and the action time of the antibiotic. During this stage, the bacteria and antibiotics react.

[0109] 3. Electrochemical monitoring stage:

[0110] ① Construct an MFC sensor: including an anode chamber, a cathode chamber and a separator. The bacterial solution of the strain to be tested is inoculated in the anode chamber, and an electrolyte solution is added to the cathode chamber.

[0111] ② Real-time monitoring: During the incubation process, the MFC sensor is used to monitor the current or voltage changes in real time and record the data. These data reflect the growth status of bacteria and the inhibitory effect of antibiotics.

[0112] 4. Result judgment stage:

[0113] ① Data analysis: According to the degree of change of the electrochemical signal, combined with the preset threshold (derived from a large amount of experimental data, used to distinguish the sensitive, intermediate and resistant states of bacteria to antibiotics), the antibiotic sensitivity of bacteria is judged.

[0114] ② Intelligent analysis: In conjunction with existing machine learning algorithms and a large amount of existing drug sensitivity testing data, intelligent analysis and prediction of electrochemical signals are performed to improve the accuracy and efficiency of drug sensitivity testing.

[0115] The operating principle of the present invention is as follows: the present invention utilizes electrochemical monitoring to monitor the growth and metabolic activity of bacteria through a microbial fuel cell (MFC) sensor. The MFC sensor reflects the growth state of bacteria by measuring changes in current or voltage. When bacteria grow and metabolize in the anode chamber, they generate electrons, which are transferred to the cathode chamber through an external circuit to form an electric current. The addition of antibiotics inhibits the growth and metabolic activity of bacteria, thereby reducing the number of electrons generated, resulting in changes in current or voltage.

[0116] By real-time monitoring of the changes in these electrochemical signals, the inhibitory effect of antibiotics on bacterial growth can be evaluated. Combined with the preset threshold, the sensitivity of bacteria to antibiotics can be determined. The preset threshold is based on a large amount of experimental data and can distinguish between the sensitive, intermediate and resistant states of bacteria to antibiotics.

[0117] In addition, the method also combines machine learning algorithms for intelligent analysis and prediction, further improving the accuracy and efficiency of drug sensitivity testing; machine learning algorithms can use a large amount of existing drug sensitivity testing data to more accurately analyze and predict electrochemical signals, providing a more scientific basis for clinical drug use;

[0118] In summary, the rapid drug sensitivity detection method of the present invention realizes the rapid and accurate judgment of bacterial antibiotic sensitivity through the combination of electrochemical monitoring and machine learning algorithm, providing strong support for clinical drug use.

[0119] It should be noted that the present invention is a rapid drug sensitivity detection method, and the components in the present invention are all components known to those skilled in the art, and their structures and principles are all known to those skilled in the art through technical manuals or through conventional experimental methods.

[0120] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A rapid drug sensitivity detection method, characterized in that: The following steps are involved: S1. Mix the bacterial solution of the strain to be tested, the antibiotic solution and a suitable culture medium, and incubate them at a suitable temperature to allow the bacteria to react with the antibiotics; S2. Using an electrochemical sensor to monitor the mixed solution after incubation in real time, and to reflect the growth status of bacteria and the inhibitory effect of antibiotics by measuring the changes in specific electrochemical signals; S3. Determine the antibiotic sensitivity of bacteria based on the degree of change of the electrochemical signal and the preset threshold.

2. A rapid drug sensitivity detection method according to claim 1, characterized in that: In step S2, the electrochemical sensor is a microbial fuel cell (MFC) sensor, and the growth and metabolic activity of bacteria are monitored by measuring the current or voltage changes generated by the MFC.

3. A rapid drug sensitivity detection method according to claim 2, characterized in that: The specific steps of step S2 are as follows: (1) constructing an MFC sensor, including an anode chamber, a cathode chamber and a separator, wherein the anode chamber is inoculated with a bacterial solution of the strain to be tested, and an electrolyte solution is added to the cathode chamber; (2) adding the antibiotic solution into the anode chamber, mixing it with the bacterial solution of the strain to be tested, and starting incubation; (3) During the incubation process, monitor the current or voltage changes generated by the MFC in real time and record the data; (4) Evaluate the inhibitory effect of antibiotics on bacterial growth based on the changing trend and amplitude of current or voltage.

4. A rapid drug sensitivity detection method according to claim 1, characterized in that: In step S3, the preset threshold is derived based on a large amount of experimental data and is used to distinguish the sensitive, intermediate and resistant states of bacteria to antibiotics.

5. A rapid drug sensitivity detection method according to claim 1, characterized in that: In step S1, the composition and proportion of the culture medium can be adjusted as needed according to the specific requirements of the strain to be tested to ensure the normal growth and reproduction of the bacteria.

6. A rapid drug sensitivity detection method according to claim 5, characterized in that: In step S1, the concentration of the antibiotic solution is within the commonly used clinical concentration range, such as 60 to 256 μg / mL, and the specific concentration can be adjusted according to experimental needs.

7. A rapid drug sensitivity detection method according to claim 6, characterized in that: In step S1, the incubation temperature is 34-37°C and the incubation time is 10 minutes to 3 hours. The specific time depends on the growth rate of the bacteria and the action time of the antibiotics.

8. A rapid drug sensitivity detection method according to claim 1, characterized in that: In step S2, the electrochemical sensor needs to undergo professional technical calibration and cleaning pretreatment before use to ensure the accuracy and stability of the measurement results.

9. A rapid drug sensitivity detection method according to claim 1, characterized in that: In step S3, the existing machine learning algorithm can be combined with a large amount of existing drug sensitivity detection data to perform intelligent analysis and prediction of electrochemical signals to improve the accuracy and efficiency of drug sensitivity detection.

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