A rapid detection method for total amount of microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence

Abstract

The application provides a rapid detection method for total amount of microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence, wherein the calibration set samples of the traditional Chinese medicinal materials to be detected are added into a buffer, pre-inoculation treatment is performed, the bacterial liquid, an additive and luciferase preparation are uniformly mixed, and then the relative light intensity is detected; the average relative light intensity value or the logarithmic value of the average relative light intensity value is used as the ordinate, the logarithmic value of the total amount of microorganisms is used as the abscissa, and a microorganism content distribution graph is drawn; the longitudinal qualified limit is delimited according to the microbial limit, the early warning limit is delimited according to the misjudgment rate, and partition is performed; whether the detection result is qualified is judged by the position of the average relative light intensity in the microorganism content distribution graph. The rapid detection method for total amount of microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence has the advantages of fast testing speed, low detection cost, high sensitivity and the like, and is suitable for on-site detection of total amount of microorganisms of various traditional Chinese medicinal material varieties.

Description

Technical Field

[0001] This invention belongs to the field of microbial detection, and in particular relates to a rapid method for detecting the total amount of microorganisms in traditional Chinese medicine based on ATP bioluminescence. Background Technology

[0002] Prepared medicinal herbs (TCM) are a class of TCM products that have undergone processing and are used for dispensing, preparation, and clinical applications. TCM prepared medicinal herbs are one of the three pillars of the TCM industry, and their quality directly affects the industry's stable development. Due to factors such as the unstable source of raw materials, diverse processing techniques, and the storage and transportation of prepared medicinal herbs, the risk of microbial contamination is exacerbated. Overall, microbial contamination of TCM prepared medicinal herbs is a serious problem, posing a high risk to microbial safety. Among these, the total number of aerobic bacteria, molds, and yeasts, as well as contamination by Escherichia coli and Salmonella, are among the main challenges facing the microbial safety and quality control of TCM prepared medicinal herbs.

[0003] Currently, culture counting is the gold standard for microbial detection and is adopted by pharmacopoeias of various countries as a routine method for microbial examination. However, given the cyclical nature of microbial growth and the existence of unculturable microorganisms, culture methods have drawbacks such as slow detection speed and inability to detect unculturable microorganisms. The 2020 edition of the Chinese Pharmacopoeia added the "1021 Bacterial DNA Characteristic Sequence Identification Method" for the identification and classification of microorganisms in drug quality control. However, this method has shortcomings such as high detection cost and poor quantitative accuracy, making it unsuitable for the detection of total aerobic bacteria count.

[0004] Adenosine triphosphate (ATP) bioluminescence is a method for rapid detection of microorganisms based on the fluorescence signal generated by the luciferase reaction triggered by ATP within the microorganism. ATP is present in all living cells, and the ATP content of a single living bacterium is generally stable at 10⁻⁶ ppm. -18 In a luciferase reaction system, which includes luciferase, magnesium ions, luciferin, and oxygen, the release of ATP within microbial cells triggers an enzymatic reaction and releases fluorescence. ATP bioluminescence technology is based on the principle of the luciferase-catalyzed reaction, converting ATP within microorganisms into photons. The photon signal is then collected by a photometer and converted into relative light units (RLUs) as the basis for quantitative detection of microorganisms. This method requires aerobic conditions, can detect almost all live aerobic bacteria, and takes less than ten minutes from sample pretreatment to obtaining results, making it suitable for rapid detection of the total microbial population in samples.

[0005] Currently, the ATP bioluminescence method has been included in my country's national standards for evaluating the disinfection effect of food contact surfaces, such as "GB / T 36004-2018 Test Method for Cleaning and Disinfection Effect of Food Contact Surfaces: Adenosine Triphosphate Bioluminescence Method". However, this method has not yet been applied to the rapid detection of microorganisms in traditional Chinese medicine decoction pieces and intermediate products. Summary of the Invention

[0006] In view of this, the present invention aims to overcome the defects in the prior art and proposes a rapid detection method for total microorganisms in Chinese medicinal materials based on ATP bioluminescence.

[0007] To achieve the above objectives, the technical solution of the present invention is implemented as follows:

[0008] A rapid method for detecting total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence includes the following steps:

[0009] (1) Add the calibration set sample of the Chinese medicinal material to be tested to the buffer solution, shake and dilute to obtain the test solution, add the test solution to the culture medium for culture, and then calculate the total microbial count of the test solution;

[0010] (2) After pre-enriching the test solution in step (1), mix the bacterial solution, adjuvant and luciferase preparation evenly and then detect the relative luminescence intensity.

[0011] (3) Using the average relative luminescence intensity value or the logarithm of the average relative luminescence intensity value (the average value is calculated after at least three parallel measurements) as the vertical axis and the logarithm of the total microbial count obtained in step (1) as the horizontal axis, draw a microbial content distribution map.

[0012] (4) The microbial limit specified in the 2020 edition of the Chinese Pharmacopoeia, "1107 Microbial Limit Standard for Non-sterile Drugs", is 10⁻¹⁰. 6 The longitudinal compliance limit is determined by CFU / g (or CFU / mL), and the warning limit is determined by the false judgment rate.

[0013] (5) Add the test sample of the Chinese medicinal material to be tested to the buffer solution, shake and dilute to obtain the test solution. Perform pre-enrichment and detect the relative luminescence intensity of the test solution according to the method described in step (2). Determine whether the test result is qualified by comparing the average relative luminescence intensity value with the warning limit. If the average relative luminescence intensity value is higher than the warning limit, the test sample is deemed unqualified; if the average relative luminescence intensity value is lower than the warning limit, the test sample is deemed qualified. The total microbial count refers to the total colony count.

[0014] Furthermore, the warning limit in step (4) is the upper warning limit and / or the lower warning limit; the false alarm rate of the upper warning limit is 5-10%; and the false alarm rate of the lower warning limit is 20-30%.

[0015] Furthermore, the microbial content distribution map is divided into zones based on the aforementioned vertical acceptable limits, upper warning limits, and lower warning limits; the area between the upper and lower warning limits is the warning zone; the area enclosed by the vertical acceptable limits, lower warning limits, and the horizontal and vertical axes is the acceptable zone; the area between the vertical acceptable limits and upper warning limits that is far from the origin of the coordinate axis is the unacceptable zone; and the areas between the vertical acceptable limits, lower warning limits, and the portion of the horizontal axis that is greater than the vertical acceptable limits, as well as the areas between the vertical acceptable limits, upper warning limits, and the portion of the vertical axis that is greater than the upper warning limits, are all misjudged zones.

[0016] Furthermore, the detection method further includes the following steps: using the logarithm of the total microbial count of the calibration set samples obtained in step (1) as the ordinate and the total microbial count corresponding to the average relative luminescence intensity value of the calibration set samples obtained in step (3) as the abscissa, a univariate partial least squares regression model of the samples is constructed. The evaluation index of the model includes the coefficient of determination R. 2 The root mean square error (RMSEE) of the correction set and the root mean square error (RMSECV) of the cross-test set are used to predict the total microbial content of the Chinese medicinal material sample by substituting the average relative luminescence intensity value of the test set sample obtained in step (5) into the model. The total microbial content of the sample is then compared with the qualification limit. If the value is lower than the qualification limit, the sample is deemed qualified; if it is higher than the qualification limit, the sample is deemed unqualified. 2 The higher the values ​​and the lower the values ​​of RMSEE and RMSECV, the better the predictive performance of the partial least squares regression model.

[0017] Furthermore, the microorganisms mentioned are at least one of the following: aerobic bacteria, molds and yeasts, Escherichia coli, Salmonella, Staphylococcus aureus, Pseudomonas aeruginosa, bile salt-tolerant Gram-negative bacteria, Candida albicans, and Clostridium.

[0018] Furthermore, the calibration set samples in step (1) and the test set samples in step (5) are Chinese medicinal material samples from the same place of origin, the same year, the same batch, the same source, or the same harvesting part; the calibration set samples are 40-95% of the randomly selected Chinese medicinal material samples, and the test set samples are the remaining Chinese medicinal material samples.

[0019] Furthermore, the Chinese medicinal materials mentioned are at least one of the following: Chinese medicinal extracts, oral Chinese medicinal decoction pieces, Chinese medicinal decoction pieces for infusion, Chinese medicinal decoction pieces for decocting, or Chinese medicinal extracts.

[0020] Furthermore, the Chinese medicinal materials mentioned are at least one of Bupleurum chinense, Dioscorea opposita, Angelica sinensis, Nelumbo nucifera, Crataegus pinnatifida, Zingiber officinale, Salvia miltiorrhiza, Codonopsis pilosula, Glycyrrhiza uralensis, or Lonicera japonica.

[0021] Furthermore, the pre-enrichment step in step (2) takes 0.1-8 hours and is performed at a temperature of 37°C.

[0022] Furthermore, the adjuvants in step (2) are hexadecyltrimethylammonium bromide and β-cyclodextrin; the concentration of hexadecyltrimethylammonium bromide is 2.5 mmol / mL; the concentration of β-cyclodextrin is 3 mg / mL; the concentration of luciferase preparation is 3 mg / mL; and the volume ratio of bacterial culture, hexadecyltrimethylammonium bromide, β-cyclodextrin and luciferase preparation in step (2) is 1:0.1-2:0.2-0.8:0.3-1.6.

[0023] Compared with the prior art, the present invention has the following advantages:

[0024] The rapid detection method for total microbial count in Chinese medicinal materials based on ATP bioluminescence described in this invention has advantages such as fast testing speed, low detection cost, and high sensitivity, and is suitable for on-site detection of total microbial count in various Chinese medicinal materials. Attached Figure Description

[0025] Figure 1 This is a distribution diagram of the total aerobic bacteria in the Bupleurum slices described in Example 1 of the present invention;

[0026] Figure 2 This is a partial least squares regression model diagram of the total aerobic bacteria content in Bupleurum slices as described in Embodiment 3 of the present invention;

[0027] Figure 3 This is a distribution diagram of the total aerobic bacteria in the Bupleurum slices described in Example 5 of the present invention;

[0028] Figure 4 This is a distribution diagram of the total amount of mold and yeast in the Bupleurum slices described in Example 6 of the present invention;

[0029] Figure 5 This is a partial least squares regression model diagram of the total amount of mold and yeast in Bupleurum slices as described in Example 8 of the present invention;

[0030] Figure 6 This is a correlation distribution diagram of the concentration of Escherichia coli and the intensity of ATP bioluminescence assay in the licorice extract sample described in Example 10 of the present invention.

[0031] Figure 7 This is a correlation distribution diagram of the concentration of Staphylococcus aureus and the intensity of ATP bioluminescence assay in the yam extract sample described in Example 11 of the present invention. Detailed Implementation

[0032] Unless otherwise defined, the technical terms used in the following embodiments have the same meanings as commonly understood by those skilled in the art. Unless otherwise specified, the experimental reagents used in the following embodiments are conventional biochemical reagents; and the experimental methods described are conventional methods.

[0033] The present invention will be described in detail below with reference to embodiments.

[0034] Example 1

[0035] A rapid detection method for total aerobic bacteria in Bupleurum chinense slices based on ATP bioluminescence assay includes the following steps:

[0036] (1) 150 Bupleurum chinense slices samples from Gansu production area in 2022 were selected in parallel. 118 samples were randomly selected as the calibration set samples, and the rest were used as the test set samples. 25g of each sample was placed in three conical flasks, and 225mL of sterilized pH=7.0 sodium chloride peptone buffer was added to each flask. The flasks were shaken at 300rpm and 35℃ for 30min. The supernatant of each of the three shaken flasks was used as the test solution and serially diluted. 100μL of the test solution of the appropriate dilution was spread on tryptic soybean agar medium. Three plates were prepared in parallel for each dilution and incubated at 30-35℃ for 5 days. The colonies were counted on the 1st, 3rd and 5th days of incubation. The total number of aerobic bacterial colonies in the test solution was calculated according to this method.

[0037] (2) After pre-enriching the above test solution at 37℃ for 4 hours, take 100 μL of bacterial solution and add it to the luminescent detection tube, then add 50 μL of cetyltrimethylammonium bromide, let it stand for 2 min, then add 50 μL of cyclodextrin, then add 100 μL of luciferase reagent, shake for about 10 s, insert it into the ATP fluorescence meter to detect the cumulative fluorescence signal for 15 s, and record the relative luminescence intensity after 5 minutes;

[0038] (3) Using the average relative luminescence intensity of the 118 samples as the ordinate and the logarithm of the total aerobic bacteria count obtained in the above steps as the abscissa, a microbial content distribution map was plotted. The 2020 edition of the Chinese Pharmacopoeia sets the limit standard for the total aerobic bacteria count of orally administered and infused traditional Chinese medicine decoction pieces at 10. 5 The CFU / g value is used to determine the acceptable limit. When the false positive rate is 10%, the integer number of false positive samples is 12, and the upper warning limit (average relative luminescence intensity value of 3800) is determined accordingly. When the false positive rate is 20%, the integer number of false positive samples is 24, and the lower warning limit (average relative luminescence intensity value of 2200) is determined accordingly. Determining the warning limit is crucial for quickly assessing the microbial contamination risk level of the tested medicinal herb sample. Once the false positive rate is selected, the warning limit can be determined. For the sample to be tested, only the average relative luminescence intensity value of the sample needs to be tested. Based on the comparison with the warning limit, the aerobic microbial contamination risk category of the sample can be determined. Figure 1 As shown;

[0039] (4) This method can be used to quickly determine the total number of aerobic bacteria in 32 test samples of Bupleurum chinense slices from Gansu production area in 2022. After the test sample is tested in parallel for 3 times according to this method, the corresponding average relative luminescence intensity value can be calculated. If the average relative luminescence intensity is higher than the upper limit of the warning, the total number of aerobic bacteria in the test sample is deemed unqualified. If the average relative luminescence intensity is lower than the lower limit of the warning, the total number of aerobic bacteria in the test sample is deemed qualified. If the average relative luminescence intensity falls within the warning zone, it indicates that the total number of aerobic bacteria in this test sample has a high risk factor for contamination and needs attention. If necessary, the traditional culture counting method should be used for retesting.

[0040] Example 2: Traditional Culture Counting Method

[0041] A method for detecting total aerobic bacteria in Bupleurum chinense slices was developed. Thirty-two test samples of Bupleurum chinense slices from Gansu province in 2022 were selected. 25g of each sample was placed in three conical flasks, and 225mL of sterilized pH 7.0 sodium chloride peptone buffer was added to each flask. The flasks were shaken at 300rpm and 35℃ for 30min. The supernatant from each of the three shaken flasks was used as the test solution and serially diluted. 100μL of the appropriately diluted test solution was spread onto tryptic soy peptone agar. Three plates were prepared for each dilution and incubated at 30–35℃ for 5 days. Counts were made on days 1, 3, and 5, and the total aerobic bacterial count was calculated based on this method.

[0042] Example 3: Partial Least Squares Regression Model Method

[0043] Using cross-validation, a univariate partial least squares regression model was constructed with the logarithm of the total aerobic bacteria count in the Bupleurum chinense slices test set obtained in Example 1 as the x-axis and the logarithm of the culture counting method as the y-axis. Figure 2 As shown. Coefficient of determination R 2 The mean square error (RMSEE) of the calibration set was 0.826, the mean square error of the cross-test set (RMSECV) was 0.468, and the mean square error of the cross-test set (RMSECV) was 0.465. To quickly predict the total aerobic bacteria content of a sample in a test set, the average relative luminescence intensity of the sample is first obtained using the method described in Example 1. Then, this value is substituted into the partial least squares regression model to determine the aerobic bacteria content. This method is convenient and accurate, eliminating the need to record the culture counts on days 1, 3, and 5 as described in Example 2. Furthermore, compared to Example 1, it accurately provides the aerobic bacteria content information of the sample, not just the regional range. In summary, this partial least squares regression model can relatively accurately and quickly predict the aerobic bacteria content information of unknown samples. Specific comparisons are shown in Table 1.

[0044] Table 1 Comparison of detection results of the three methods

[0045]

[0046] Example 4

[0047] Using cross-validation, a univariate partial least squares regression model was constructed with the total aerobic bacteria count predicted by the ATP rapid detection method in Example 1 as the x-axis and the logarithm of the total aerobic bacteria count measured by the culture counting method as the y-axis. The coefficient of determination R of the model was... 2 The root mean square error of the corrected set and the root mean square error of the cross-test set are shown in Table 2. It can be seen that the partial least squares regression model performs better after logarithmic processing.

[0048] Table 2. Comparison of partial least squares regression models for total aerobic bacteria count in Bupleurum slices.

[0049]

[0050] Example 5

[0051] A rapid detection method for total aerobic bacteria in Bupleurum chinense slices based on ATP bioluminescence assay is proposed. Steps (1) and (2) are the same as in Example 1. The only difference between step (3) and step (3) in Example 1 is that the vertical axis is the logarithm of the average relative luminescence intensity value. A microbial content distribution map is plotted, with the limit standard of 10 for the total aerobic bacteria in the traditional Chinese medicine slices. 5 The acceptable limit is set at CFU / g, with an upper warning limit set at a false positive rate of 10% (logarithm of average relative luminescence intensity value of 3.6), and a lower warning limit set at a false positive rate of 20% (logarithm of average relative luminescence intensity value of 3.3). Figure 3 As shown, this method is used for the rapid determination of the total aerobic bacteria count in the 2022 Gansu Province Bupleurum chinense slices test set. If the logarithm of the average relative luminescence intensity value is higher than the upper warning limit, the total aerobic bacteria count of the test sample is deemed unqualified. If the logarithm of the average relative luminescence intensity value is lower than the lower warning limit, the total aerobic bacteria count of the test sample is deemed qualified. If the logarithm of the average relative luminescence intensity value falls within the warning zone, it indicates that the total aerobic bacteria contamination risk coefficient of this test sample is high and requires attention. If necessary, the traditional culture counting method should be used for retesting.

[0052] Example 6

[0053] A rapid detection method for total mold and yeast content in Bupleurum chinense slices based on ATP bioluminescence assay includes the following steps:

[0054] (1) One hundred samples of Bupleurum chinense slices from Gansu Province in 2022 were selected in parallel. Seventy samples were randomly selected as the calibration set and the remaining 30 samples were selected as the test set. 25g of each sample was placed in three conical flasks, and 225mL of sterilized pH 7.0 sodium chloride peptone buffer was added to each flask. The flasks were shaken at 300rpm and 35℃ for 30min. The supernatant of each of the three shaken flasks was used as the test solution and serially diluted. 100μL of the test solution of the appropriate dilution was spread on Sabouraud dextrose agar medium. Three plates of each dilution were prepared in parallel and incubated at 20-25℃ for 7 days. The colonies were counted on the 4th and 7th days. The total number of mold and yeast colonies in the test solution was calculated according to this method.

[0055] (2) Perform a relative luminescence intensity test according to the method in step (2) of Example 1, and adjust the enrichment time to 2h;

[0056] (3) Using the average relative luminescence intensity of the 70 samples as the ordinate and the logarithm of the total number of molds and yeasts obtained in the above steps as the abscissa, plot the distribution of the total number of molds and yeasts. According to the standard for the limit of total number of molds and yeasts in traditional Chinese medicine decoction pieces, 10... 3 Determine the acceptable limit. Since the actual testing conditions of the samples made it impossible to obtain a 10% false positive rate, a warning limit was set based on a 20% false positive rate (average relative luminous intensity value of 370). Figure 4 As shown. This method can be used for the rapid determination of the total number of molds and yeasts in the 2022 Gansu Province Bupleurum chinense slices test set. If the average relative luminescence intensity is higher than the warning limit, the total number of molds and yeasts in the test sample is deemed unqualified; if the average relative luminescence intensity is lower than the warning limit, the total number of molds and yeasts in the test sample is deemed qualified, and the sample does not have a warning zone.

[0057] Example 7

[0058] A rapid method for detecting total mold and yeast counts in Bupleurum chinense slices was developed. Samples from a 2022 Gansu production area were collected. 25g of each sample was placed in three conical flasks, and 225mL of sterilized pH 7.0 sodium chloride peptone buffer was added to each flask. The flasks were shaken at 300rpm and 35℃ for 30min. The supernatant from each of the three shaken flasks was used as the test solution and serially diluted. 100μL of the appropriately diluted test solution was plated on Sabouraud dextrose agar. Three plates were prepared for each dilution and incubated at 20–25℃ for 7 days. Counts were performed on day 4 and day 7, and the total number of mold and yeast colonies in the test solution was calculated using this method.

[0059] Example 8

[0060] Using cross-validation, a univariate partial least squares regression model was constructed by plotting the logarithmic values ​​of the total mold and yeast counts in the Bupleurum chinense slices test set obtained in Example 6 on the x-axis and the logarithmic values ​​measured by the culture counting method on the y-axis. Figure 5 As shown. Coefficient of determination R 2 The mean square error of the calibration set (RMSEE) was 0.778, the mean square error of the cross-test set (RMSECV) was 0.543, and the mean square error of the cross-test set (RMSECV) was 0.541. To quickly predict the total amount of mold and yeast in a test set sample, the average relative luminescence intensity of the sample is first obtained using the method described in Example 6. Then, this value is substituted into the partial least squares regression model to determine the total amount of mold and yeast in the sample. This method is convenient and accurate, eliminating the need to record the culture counts on days 4 and 7 as described in Example 7. Furthermore, compared to Example 6, it accurately provides the total amount of mold and yeast in the sample, rather than simply dividing the content range. In summary, this partial least squares regression model can relatively accurately and quickly predict the total amount of mold and yeast in unknown samples. See Table 3 for specific comparisons.

[0061] Table 3 Comparison of detection results of the three methods

[0062]

[0063] Example 9

[0064] Using cross-validation, a univariate partial least squares regression model was constructed with the total amount of mold and yeast in the Bupleurum chinense slices test set samples predicted by the ATP rapid detection method in Example 6 as the x-axis and the logarithm of the total amount of mold and yeast measured by the culture counting method as the y-axis. The coefficient of determination R of the model was... 2 The root mean square error of the corrected set and the root mean square error of the cross-test set are shown in Table 4. It can be seen that the partial least squares regression model performs better after logarithmic processing.

[0065] Table 4. Comparison of partial least squares regression models for total mold and yeast counts in Bupleurum chinense slices.

[0066]

[0067] Example 10

[0068] A rapid detection method for total Escherichia coli in licorice extract based on ATP bioluminescence assay was developed. Licorice slices from Hebei province, 2018, were decocted and concentrated according to national standard methods to obtain licorice extract. Single colonies of Escherichia coli were picked from slant culture and placed in 10 mL of broth culture medium, incubated at 35℃ and 150 rpm for 16 h. 1 mL of the culture supernatant was transferred to a sterile centrifuge tube and centrifuged at 4000 rpm for 18 min at 4℃. The supernatant was discarded, and 1 mL of PBS buffer was added. The centrifugation process was repeated three times to obtain a pure Escherichia coli culture. The pure culture was then serially diluted with PBS buffer to 10⁻¹⁰. 9 CFU / mL, 50 μL of bacterial suspension at each concentration gradient was mixed with licorice extract solution to obtain licorice extract samples containing different concentrations of Escherichia coli, each with a volume of 100 μL. 10 μL of cetyltrimethylammonium bromide was added to each sample, and the mixture was allowed to stand for 2 min. Then, 30 μL of cyclodextrin was added, followed by 120 μL of luciferase reagent. After shaking for approximately 10 s, the sample was inserted into an ATP fluorescence analyzer to detect the cumulative fluorescence signal for 15 s. The relative luminescence intensity was recorded after 5 minutes. A correlation distribution diagram was obtained between the concentration of Escherichia coli in the licorice extract samples and the intensity measured by the ATP bioluminescence method, with the average relative luminescence intensity as the ordinate and the logarithm of the total Escherichia coli count obtained in the above steps as the abscissa. Figure 6 As shown.

[0069] Example 11

[0070] A rapid detection method for total Staphylococcus aureus in yam extract based on ATP bioluminescence assay is proposed. Yam slices from Henan province, harvested in 2022, were decocted and concentrated according to national standard methods to obtain yam extract. Yam extract samples containing different concentrations of Staphylococcus aureus were obtained using the method described in Example 10, with each sample having a volume of 100 μL. ATP bioluminescence assay was performed according to the method described in Example 10. The average relative luminescence intensity was plotted on the ordinate, and the logarithm of the total Staphylococcus aureus count obtained in the above steps was plotted on the abscissa to obtain a correlation distribution diagram between the Staphylococcus aureus concentration in the yam extract sample and the ATP bioluminescence assay test intensity. Figure 7 As shown.

[0071] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A rapid method for detecting total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence, characterized in that: Includes the following steps: (1) Add the calibration set sample of the Chinese medicinal material to be tested to the buffer solution, shake and dilute to obtain the test solution, add the test solution to the culture medium for culture, and then calculate the total microbial count of the test solution; (2) After pre-enriching the test solution in step (1), mix the bacterial solution, adjuvant and luciferase preparation evenly and then detect the relative luminescence intensity. (3) Using the average relative luminescence intensity value or the logarithm of the average relative luminescence intensity value as the vertical axis and the logarithm of the total amount of microorganisms obtained in step (1) as the horizontal axis, draw a microbial content distribution map. (4) The microbial limit is 10⁻¹⁰. 6 The longitudinal compliance limit is determined by CFU / g, and the warning limit is determined by the false judgment rate; (5) Add the test set sample of the Chinese medicinal material to be tested to the buffer solution, shake and dilute to obtain the test solution, and pre-enrich the test solution according to the method described in step (2) and detect the relative luminescence intensity. By comparing the average relative luminescence intensity value with the warning limit, it is determined whether the test result is qualified. If the average relative luminescence intensity value is higher than the warning limit, the test sample is deemed unqualified. If the average relative luminescence intensity value is lower than the warning limit, the test sample is deemed qualified. The warning limit in step (4) is the upper warning limit and / or the lower warning limit; the false alarm rate of the upper warning limit is 5-10%; the false alarm rate of the lower warning limit is 20-30%. Microorganisms are partitioned in the microbial content distribution map based on the aforementioned vertical acceptable limit, upper warning limit, and lower warning limit; the area between the upper and lower warning limits is the warning zone; the area enclosed by the vertical acceptable limit, lower warning limit, and the horizontal and vertical axes is the acceptable zone; the area between the vertical acceptable limit and the upper warning limit that is far from the origin of the coordinate axis is the unacceptable zone; the areas between the vertical acceptable limit, lower warning limit, and the portion of the horizontal axis that is greater than the vertical acceptable limit, and the areas between the vertical acceptable limit, upper warning limit, and the portion of the vertical axis that is greater than the upper warning limit are all misjudged zones; The microbial detection method further includes the following steps: using the logarithm of the total microbial count of the calibration set samples obtained in step (1) as the ordinate and the total microbial count corresponding to the average relative luminescence intensity value of the calibration set samples obtained in step (3) as the abscissa, a univariate partial least squares regression model of the samples is constructed. The evaluation index of the model includes the coefficient of determination R. 2 The root mean square error of the correction set (RMSEE) and the root mean square error of the cross-test set (RMSECV) are used to predict the total microbial content of the Chinese medicinal materials by substituting the average relative luminescence intensity value of the test set samples obtained in step (5) into the model. The total microbial content of the samples is then compared with the qualification limit. If the sample is lower than the qualification limit, it is considered qualified; if it is higher than the qualification limit, it is considered unqualified. The microorganisms mentioned are aerobic bacteria.

2. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The microorganisms mentioned are molds or yeasts.

3. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The microorganisms mentioned are bile salt-resistant Gram-negative bacteria.

4. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The microorganisms mentioned are at least one of Escherichia coli, Salmonella, Staphylococcus aureus, Pseudomonas aeruginosa, or Candida albicans.

5. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The calibration set samples in step (1) and the test set samples in step (5) are Chinese medicinal materials samples from the same place of origin, year, batch, source or harvesting part; the calibration set samples are 40-95% of the randomly selected Chinese medicinal materials samples, and the test set samples are the remaining Chinese medicinal materials samples.

6. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The Chinese medicinal materials mentioned are at least one of the following: Chinese medicinal extracts, Chinese medicinal herbs for soaking or decocting, or Chinese medicinal extracts.

7. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The Chinese medicinal materials mentioned are at least one of the following: Bupleurum chinense, Dioscorea opposita, Angelica sinensis, Nelumbo nucifera, Crataegus pinnatifida, Zingiber officinale, Salvia miltiorrhiza, Codonopsis pilosula, Glycyrrhiza uralensis, or Lonicera japonica.

8. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The time for the pre-enrichment step in step (2) is 0.1-8 h.

9. The rapid detection method for total microorganisms in traditional Chinese medicinal materials based on ATP bioluminescence according to claim 1, characterized in that: The adjuvants in step (2) are hexadecyltrimethylammonium bromide and β-cyclodextrin; the concentration of hexadecyltrimethylammonium bromide is 2.5 mmol / mL; the concentration of β-cyclodextrin is 3 mg / mL; the concentration of luciferase preparation is 3 mg / mL; the volume ratio of bacterial culture, hexadecyltrimethylammonium bromide, β-cyclodextrin and luciferase preparation in step (2) is 1:0.1-2:0.2-0.8:0.3-1.6.

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