Method and device for quantitatively detecting active microorganisms in solid / semi-solid sample

Abstract

The invention discloses a method and a device for quantitatively detecting active microorganisms in a solid / semi-solid sample, and belongs to the field of microorganism detection. According to the method, detection is carried out based on a PMA-qPCR method, influence factors of the stability of an experimental result are analyzed, and a stability analysis model is constructed; the stability analysis model is shown in the specification; wherein S is a comprehensive stability score, and the higher the S value is, the better the stability of the experiment result is; the weight coefficient is the weight coefficient of the ith influence factor; the performance function is the performance function of the ith influence factor; the influence factors comprise sample suspension dilution ratio, PMA dye concentration, dye incubation time, blue light irradiation time, blue light irradiation area and impurity particle size. The method can be used for simultaneously detecting the activity of various microorganisms in a solid / semi-solid sample, the accuracy is high, the experimental period is short, and the quantitative result has important guiding significance.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of microorganism detection, and particularly relates to a method and device for quantitatively detecting active microorganisms in solid / semi-solid samples. BACKGROUND

[0002] Existing methods for detecting live bacteria include microscopic detection, methylene blue staining, plate colony counting, PMA-qPCR, etc. Microscopic detection is used to observe the number and activity of microorganisms under a microscope. This method is suitable for quickly estimating the number of microorganisms, but cannot distinguish between dead and live bacteria. Methylene blue staining uses methylene blue staining solution to stain microorganisms. Live bacteria can reduce methylene blue due to cell metabolism, while dead bacteria cannot reduce methylene blue and appear blue. After staining, the proportion of live and dead bacteria is observed under a microscope to calculate the survival rate. However, methylene blue staining can only distinguish between live and dead bacteria, and cannot identify the types of live bacteria. Plate colony counting involves diluting a microorganism suspension and inoculating it onto solid culture medium. After incubation, the number of colonies is counted. This method is suitable for detecting the total number of live bacteria, but the incubation time is relatively long.

[0003] PMA-qPCR removes dead bacterial DNA by PMA (propidium monoazide bromide) treatment and quantitatively detects the number of live bacteria using qPCR technology. However, solid / semi-solid samples are a complex sample system containing a large amount of organic matter, sugars, alcohol, and other microorganisms. These components can interfere with the PMA treatment process and subsequent qPCR detection, resulting in large detection errors. High concentrations of alcohol can affect the permeability of PMA; other microorganisms or metabolites in solid / semi-solid samples can non-specifically bind to PMA, interfering with the detection results; in addition, large particles and some dark matter in the solid / semi-solid sample suspension can greatly reduce the efficiency of PMA blue light irradiation treatment. SUMMARY

[0004] To address the deficiencies in the prior art, the present application solves the technical problem of large experimental result errors and long incubation periods in existing methods for detecting active microorganisms in solid / semi-solid samples. A method and device for quantitatively detecting active microorganisms in solid / semi-solid samples are provided, which can simultaneously quantitatively detect multiple active microorganisms in solid / semi-solid samples, with high accuracy and short experimental periods.

[0005] To solve the technical problem, the technical solution adopted by the present application is as follows: In one aspect, the present application provides a method for quantitatively detecting active microorganisms in solid / semi-solid samples. The method is based on PMA-qPCR detection, analyzes the factors affecting the stability of the experimental results, and constructs a stability analysis model. The stability analysis model is as follows: ; wherein S is a comprehensive stability score, the higher the S value, the better the stability of the experimental results; wi is the weight coefficient of the ith influencing factor, indicating the relative importance of the influencing factor in the stability of the experimental results; fi is the performance function of the ith influencing factor, which maps the actual measured value of the influencing factor to a standardized score between 0 and 1, reflecting the contribution of the influencing factor to stability; The influencing factors include sample suspension dilution, PMA dye concentration, dye incubation time, blue light irradiation time, blue light irradiation area, and impurity particle size.

[0006] It should be noted that the initial average weight is set through experimental data and experience =0.167. In the experiment, the non-strict linear change of each influencing factor will have disturbances, but the overall trend is linear change.

[0007] As a preferred embodiment, the method comprises the following steps: 1) dissolving the solid / semi-solid sample with water to obtain a sample suspension, and centrifuging to obtain the upper suspension; 2) adding PMA dye to the upper suspension for incubation, then transferring to a glass container for blue light irradiation, and then centrifuging to collect the precipitate; 3) extracting genomic DNA from the collected precipitate; 4) using the extracted total nucleic acid sample as a template, performing PCR amplification using primers, and determining the viable cell count of the target active microorganism by real-time fluorescent quantitative PCR technology; The method further comprises a dilution step, which is performed before the sample suspension is subjected to blue light irradiation.

[0008] As a preferred embodiment, in step 1), the centrifugation speed is 400-600 rpm; In step 2), the centrifugation speed is 10000-13000 rpm.

[0009] The above technical solution limits the centrifugation speed of steps 1) and 2). Step 1 uses low speed to make larger particle impurities sink to the bottom. Step 2 uses high speed centrifugation to ensure that cells pass through the centrifugation and sink to the bottom as much as possible, so as to collect as much cell precipitate as possible and avoid large errors in experimental results. Without complex steps such as gradient medium, simple operation can achieve the purpose of preliminary separation of impurities.

[0010] As a preferred embodiment, the solid / semi-solid sample is fermented grains, and the target active microorganism includes yeast cells; ​The yeast cells include Saccharomyces cerevisiae, Schizosaccharomyces pombe and Pichia pastoris. The primer of the Saccharomyces cerevisiae includes: N-F: 5'-TGTCGTCCTGGTTGGTATGC-3'; N-R: 5'-GCCAGCTAAGTGGATCGGAG-3'; The primer of the Schizosaccharomyces pombe includes: S-F: 5'-GCTGATGGCAGCAAAATCCC-3'; S-R: 5'-TTGCGAGGAACACCACTCTC-3'; The primer of the Pichia pastoris includes: B-F: 5'-GTTTGAGCGTCGTTTCCATC-3'; B-R: 5'-AGCTCCGACGCTCTTTACAC-3'.

[0011] It is to be noted that at present, the active yeast in the fermented grains in the brewing industry is mainly detected by the method of plate coating, although the PMA-qPCR method has been reported for detecting the active bacteria, but the method has not been applied to the detection of the fermented grains sample. The biggest difficulty in detecting the fermented grains sample by the PMA-qPCR method is the interference of the complex system in the fermented grains on the detection result. The present application mainly solves the interference of the impurities on the PMA treatment process and improves the PMA treatment efficiency.

[0012] The conventional method generally adopts the separation method for the impurity treatment, but most of the impurities in the fermented grains sample are fine particles, and the physical separation is easy to cause the cell loss and large detection error. The dilution treatment before the blue light and the exploration of the blue light irradiation area mainly solve the situation that the impurities and the cells coexist, the dispersion degree of the impurities is enlarged, the combination efficiency of the dye and the dead cells is improved, so that the interference of the impurities is reduced. The dye concentration, dye incubation time and other factors mainly aim to improve the treatment efficiency of the PMA dye.

[0013] The above technical solution limits the primers of the Saccharomyces cerevisiae, the Schizosaccharomyces pombe and the Pichia pastoris, because the three kinds of yeast can be detected at the same PCR program condition.

[0014] As preferred, when the influencing factor is the dilution multiple of the sample suspension, The calculation method is as follows: ; Wherein, is the dilution multiple of the sample suspension; = 10 fold (lower limit of dilution range); = 1000 fold (threshold of optimal stable dilution).

[0015] As a preference, when the influencing factor is PMA dye concentration, The calculation method is as follows: ; Wherein, PMA dye concentration; = 20 uM (optimal PMA dye concentration); = 5 uM (lower limit of PMA dye); = 40 uM (upper limit of PMA dye).

[0016] As a preference, when the influencing factor is incubation time, The calculation method is as follows: ; Wherein, Incubation time; = 5 min (lower limit of incubation time); = 15 min (threshold of incubation time for optimal effect).

[0017] As a preference, when the influencing factor is blue light irradiation time, The calculation method is as follows: ; Wherein, Blue light irradiation time; = 15 min (lower limit of blue light irradiation time); = 30 min (threshold of blue light irradiation time for optimal effect).

[0018] As a preference, when the influencing factor is blue light irradiation area, The calculation method is as follows: ; Wherein, Blue light irradiation area; = 0 ; = 34 .

[0019] As preferred, when the influencing factor is the impurity particle size, The calculation method is as follows: ; Wherein, The impurity particle size is; =1000um; =10um.

[0020] It should be noted that for cell detection in an aqueous solution, the existing PMA-qPCR method is already mature, but the system in the fermented grains is complex, there are many types of cells, and there are many impurities. The impurities in the fermented grains are complex, and cannot be controlled during the experiment. After preliminary separation, a large amount of small particles and cells still exist in the system, causing interference.

[0021] The experimental process of the present application is improved, which is essentially to reduce the interference of impurities, so the impurity particle size is considered as a necessary factor. Larger impurity particles can be removed by low-speed centrifugation, while small particles similar in size to yeast cells are difficult to remove by physical separation and will accompany each step of cell processing, so they will seriously interfere with the accuracy of detection. For impurities below 10 μm, which are closest in size to cells, the interference with experimental results is the greatest. Greater than 1000 μm, can be removed by the first step of low-speed centrifugation.

[0022] In the second aspect of the present application, a blue light treatment device for the method for quantitatively detecting active microorganisms in a solid / semi-solid sample is provided, and the blue light treatment device comprises: A box body is provided with a cavity inside; A sample holder is arranged in the cavity and used for placing a container for storing a fermented grains suspension; A blue LED lamp panel is arranged in the cavity and used for irradiating the container for storing the fermented grains suspension with blue light; A fan is arranged on the side wall of the box body and communicates the cavity with the outside, and is used for cooling the container for storing the fermented grains suspension and the blue LED lamp panel.

[0023] Compared with the prior art, the present application has the following beneficial effects: The present application provides a method for quantitatively detecting active microorganisms in a solid / semi-solid sample, which can improve the accuracy of microorganism quantification in a solid / semi-solid sample, has a short experimental period, and the quantitative results have important guiding significance for the wine-making industry; The present application relies on PMA-qPCR technology, reduces the interference of impurities on the detection results by changing the sample processing conditions, and achieves the quantification of the viable cell numbers of Saccharomyces cerevisiae, Schizosaccharomyces pombe and Pichia in fermented grains, which is qualitative and quantitative and has high specificity. The application provides a blue light treatment device, which is simple and practical, low in cost, uses a fan to replace ice compress cooling, achieves blue light treatment while cooling the sample, prevents overheating of the sample, avoids damage of the cell membrane in the treatment process, thereby reduces the occurrence of false negative results, and saves time cost. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 Quantitative results of different container bottom surface areas provided by the embodiments of the present application; Figure 2 Quantitative results of different dye incubation times provided by the embodiments of the present application; Figure 3 Quantitative results of different blue light irradiation times provided by the embodiments of the present application; Figure 4 Saccharomyces cerevisiae standard curve provided by the embodiments of the present application; Figure 5 Schizosaccharomyces pombe standard curve provided by the embodiments of the present application; Figure 6 Pichia standard curve provided by the embodiments of the present application; Figure 7 qPCR amplification curve provided by the embodiments of the present application; Figure 8 qPCR dissolution curve provided by the embodiments of the present application; Figure 9 Quantitative detection results of target active yeast cells in four different sites of a fermentation pile by using a conventional qPCR method and the PMA-qPCR method of the present application; Figure 10 Quantitative results comparison of the plate coating method and the PMA-qPCR method of the present application; Figure 11 Structure schematic view of the blue light treatment device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0025] The technical solutions in the specific embodiments of the present application will be described in detail and completely below with reference to the drawings. Obviously, the described embodiments are only part of the specific embodiments of the general technical solution of the present application, rather than all the embodiments. Based on the general concept of the present application, all other embodiments obtained by those skilled in the art fall within the scope of protection of the present application.

[0026] In order to more clearly and specifically introduce the method and device for quantitatively detecting active microorganisms in a solid / semi-solid sample provided by the embodiments of the present application, the following will be described in combination with specific embodiments.

[0027] Example 1: Influence of dilution fold on PMA treatment 1. Test method: S1: Obtain simulated stacked fermentation grains: count the concentration of Saccharomyces cerevisiae bacterial solution, dilute the concentration to (1.4 x 10 6 cell / mL); parallelly dispense multiple 1 mL to EP tubes, 95℃ heat treatment for 5 minutes, 12000 rpm, centrifugation for 5 min, discard the supernatant, and obtain inactivated yeast cell precipitate as simulated stacked fermentation grains; S2: Take 1g of simulated stacked fermentation grains, perform ultraviolet sterilization treatment, then dissolve with 10 mL of sterile water and vortex oscillation; S3: Gradient dilute the sterile water to obtain 50x, 100x and 1000x suspensions, each in parallel two copies to EP tubes, one for PMA treatment and the other for omission of PMA treatment; take 1 mL of corresponding dilution suspension to resuspend the inactivated yeast cell precipitate, and obtain simulated grain suspension; Resuspend the inactivated yeast cell precipitate with 1 mL of undiluted suspension as a control sample; S4: PMA treatment, add PMA dye with a final concentration of 20μM to the grain suspension, wrap with tin foil paper, and place in a 30℃ shaking bed for dark incubation for 15 min; S5: Blue light treatment, place the EP tube into a blue light treatment device, and take it out after 30 min; S6: High-speed centrifugation of the suspension after blue light treatment at 13000 rpm for 10 min, discard the supernatant, and keep the precipitate; S7: Extract genomic DNA according to the instructions of the yeast DNA extraction kit; S8: Use the extracted total nucleic acid sample as a template, perform PCR amplification with primers, and determine the viable cell count of target active yeast through real-time fluorescent quantitative PCR technology; The target active yeast cells include Saccharomyces cerevisiae, Schizosaccharomyces pombe and Pichia pastoris; The primers for Saccharomyces cerevisiae are shown in Table 1; The qPCR reaction system is shown in Table 2; The qPCR reaction conditions are: first react at 95℃ for 30 s, then react at 95℃ for 5 s, and finally react at 60 for 30 s; cycle 40 times.

[0028] Table 1 primer sequence

[0029] Table 2 qPCR reaction system

[0030] 2. Test results Table 3 Test results at different dilution multiples

[0031] As can be seen from Table 3, the quantitative results of the control group prove that the impurities in the fermented grains can reduce the accuracy of the quantification of living cells by PMA-qPCR and severely reduce the treatment efficiency of PMA. The dCT difference between before and after PMA treatment of the fermented grain suspension increased by dilution treatment is ≥8, proving that the treatment efficiency for dead cells is 99%, indicating that the dilution method is effective. It is recommended that the dilution range of the fermented grains be 1000 times or more.

[0032] Example 2: Effect of centrifugal treatment on PMA treatment As can be seen from Example 1, the higher the dilution multiple of the fermented grain suspension, the smaller the interference of the impurities in the fermented grains on the accuracy of the entire experimental results. However, a higher dilution multiple means an increase in the complexity of the downstream treatment steps. Therefore, differential centrifugation is added on the basis of Case 1, low-speed centrifugation is first performed to remove insoluble impurities and at the same time to ensure that the yeast cells are not lost, and then high-speed centrifugation is performed to collect the precipitate after PMA treatment before DNA extraction. After differential centrifugation treatment, the dilution multiple of the experimental operation is reduced on the basis of Case 1, and the experimental operation is simplified.

[0033] 1. Test steps: S1: Obtain a simulated fermented grain suspension: count the concentration of the brewer's yeast liquid, dilute the concentration to (1.4 x 10 6 cell / mL); parallelly dispense multiple 1 mL into EP tubes, heat treat at 95°C for 5 minutes, centrifuge at 12000 rpm for 5 min, discard the supernatant, and obtain the inactivated yeast cell precipitate as a simulated heap fermentation fermented grain; S2: Take 1 g of the simulated heap fermentation fermented grain, perform ultraviolet sterilization treatment, then dissolve with 10 mL of sterile water and vortex oscillate; S3: Parallelly take 3 portions of 1 mL of the suspension, resuspend the inactivated yeast cell precipitate with the corresponding suspension to obtain a simulated fermented grain suspension; No. 1 sample is not treated, and No. 2 and No. 3 samples are centrifuged at 500 rpm for 2 min, and the supernatant is taken into a new EP tube; S4: No. 3 is treated with PMA, 20 μM of PMA dye is added to the fermented grain suspension, wrapped with tin foil paper, and placed in a 30°C shaking incubator for dark incubation for 15 min; S5: The No. 3 treated sample is diluted 10 times with sterile water, transferred into a 100 mL glass flask, and placed in a blue light device, and taken out after 30 min; S6: The suspensions of No. 1-3 are high-speed centrifuged at 13000 rpm for 10 min, the supernatant is discarded, and the precipitate is retained. S7: Extract the genomic DNA according to the instructions of the yeast DNA extraction kit; S8: Use the extracted total nucleic acid sample as a template, perform PCR amplification with primers, and determine the viable cell count of the target active yeast by real-time fluorescent quantitative PCR technology; The primers, qPCR reaction system and qPCR reaction conditions of S. cerevisiae are consistent with those of Example 1.

[0034] 2. Test results Table 4 Test results under different treatments

[0035] As shown in Table 4, after increasing the differential centrifugation to remove impurities, the dCT difference before and after PMA treatment = 4, indicating that the method of removing impurities is effective. The PMA efficiency is 94%, which meets the technical requirements. The dilution factor is reduced, simplifying the cumbersome operation.

[0036] Example 3: Effect of container bottom surface area on PMA treatment This example verifies the effect of the selected container size on blue light irradiation based on Case 2.

[0037] The treatment of the fermented grains is the same as that of Sample No. 3 in Case 2.

[0038] Because the impurities in the fermented grains cannot be completely removed, the differential centrifugation plus dilution treatment still has a small amount of fine impurities and dark matter that can interfere with the PMA efficiency. Therefore, when the suspension is treated with blue light, the light transmittance and light receiving surface area of the selected container are also key factors in improving the accuracy of quantification. Therefore, the quantitative results of different container bottom surface areas are compared, as shown in Table 5. Figure 1 The bottom light irradiation surface area of the glass container selected to contain the fermented grain suspension is 34 cm 2 with a more transparent material as the final sample container for blue light irradiation.

[0039] From the comparison of the experimental results, the dCT difference of the experimental group is ≥4, and the PMA efficiency is ≥94% (dCt = 4 indicates a reduction of about 16 times, i.e., 94% of dead bacterial DNA is removed). Selecting a container with a more transparent material, better light transmittance, lower light loss rate, and higher blue light utilization efficiency; secondly, a larger surface area means a larger light receiving area at the bottom and sides of the container, and the impurities are more dispersed, which is more conducive to reducing the interference of impurities on PMA.

[0040] Example 4: Effect of different dye incubation times on PMA treatment This example verifies the effect of different dye incubation times based on Case 2.

[0041] To verify the effect of different dye incubation time on PMA treatment, in addition to the dye incubation time (0 min, 5 min, 10 min, 15 min, 20 min, 30 min), the other steps of the fermented grains treatment are the same as the steps of sample No. 3 in Case 2.

[0042] As shown in Figure 2 , the dye incubation time threshold for optimal effect is 15 min.

[0043] Example 5: Effect of blue light irradiation time on PMA treatment This example is based on Case 2 to verify the effect of blue light irradiation time.

[0044] To verify the effect of different blue light irradiation time on PMA treatment, in addition to the blue light irradiation time (0 min, 15 min, 20 min, 30 min, 40 min, 50 min), the other steps of the fermented grains treatment are the same as the steps of sample No. 3 in Case 2.

[0045] As shown in Figure 3 , the blue light irradiation time threshold for optimal effect is 30 min.

[0046] Example 6 Based on the above examples, the factors affecting the stability of the experimental results are summarized: the dilution factor of the fermented grains sample, the PMA dye concentration, the dye incubation time, the blue light irradiation time, the blue light irradiation area, and the size of the impurity particles. Based on the optimized data of each influencing factor, a stability analysis model is constructed.

[0047] Factor one, sample dilution factor, ranges from 10 to 1000 times, and the effect on stability becomes smaller and smaller. Factor two, dye concentration, ranges from 5 to 40 micromoles, and 20 micromoles is optimal. Factor three, dye incubation time, 5-30 min, and the effect on stability is basically unchanged after 15 min. Factor four, blue light irradiation time, 15-50 min, and the effect on stability is basically unchanged after 30 min. Factor five, blue light irradiation area, 0-80 cm 2 , 34 cm 2 , and the effect on stability is basically unchanged with increasing area. Factor six, impurity particle size, 10 um-1000 um, and the smaller the particle size, the greater the effect on stability. Less than 10 um has the greatest impact, and greater than 1000 um has basically no effect on stability. Using the above information, a comprehensive stability analysis formula is established.

[0048] ; Wherein, S is the comprehensive stability score, the higher the S value, the better the stability of the experimental results; Wi is the weight coefficient of the ith influencing factor, indicating the relative importance of the influencing factor in the stability of the experimental results; Fi is the performance function of the ith influencing factor, which maps the actual measurement value of the influencing factor to a standardized score between 0 and 1, reflecting the contribution of the influencing factor to stability.

[0049] The formula is explained, and the initial average weight is set through experimental data and experience =0.167, the stability score is normalized to 0 to 1, which is convenient for users to understand, and the non-linear change of each factor in the experiment will have disturbance, but the overall is the linear change trend.

[0050] Formula details: 1. Factor one: sample dilution ratio ( ), when the dilution ratio is less than 10 times, the stability score is the lowest (0), between 10 and 1000 times, the score increases gradually, and when it reaches or exceeds 1000 times, the stability score reaches the highest (1); ; Wherein, is the dilution ratio of the wine lees suspension; =10 times (lower limit of dilution ratio range); =1000 times (threshold value of optimal stable dilution ratio).

[0051] 2. Factor two: PMA dye concentration ( ), when the optimal concentration is 20 micromoles, the score is the highest (1), when the concentration deviates to both sides, the score decreases in a parabolic manner, and when the concentration is 5 micromoles and 40 micromoles, the score decreases to 0; ; Wherein, is the PMA dye concentration; =20uM (optimal PMA dye concentration); =5uM (lower limit of PMA dye); =40uM (upper limit of PMA dye).

[0052] 3. Factor three: dye incubation time ( ​), the score is lowest (0) when the incubation time is less than 5 minutes, the score gradually increases between 5 to 15 minutes, and reaches the highest (1) when it is equal to or more than 15 minutes;

[0053] wherein, is the incubation time; = 5 min (lower limit of incubation time); = 15 min (threshold value of incubation time to reach the optimal effect).

[0054] 4. Factor 4: Blue light irradiation time (Tblue) ), the score is lowest (0) when the irradiation time is less than 15 minutes, the score gradually increases between 15 to 30 minutes, and reaches the highest (1) when it is equal to or more than 30 minutes;

[0055] wherein, is the blue light irradiation time; = 15 min (lower limit of blue light irradiation time); = 30 min (threshold value of blue light irradiation time to reach the optimal effect).

[0056] 5. Factor 5: Blue light irradiation area (Ablue) ), the score is lowest (0) when the irradiation area is less than 0 cm 2 , the score gradually increases between 0 to 34 cm 2 , and reaches the highest (1) when it is equal to or more than 34 cm 2 .

[0057]

[0058] wherein, is the blue light irradiation area; = 0 ; = 34 .

[0059] 6. Factor 6: Impurity particle size (Dp) ), the score is lowest (0) when the particle size is less than 10 um, the score gradually increases between 10 to 1000 um, and reaches the highest (1) when it is equal to or more than 1000 um.

[0060]

[0061] wherein, is the size of the impurity particles; = 1000 um; = 10 um.

[0062] It can be understood that the optimal value is the optimized parameter of the experimental system used in the research process of the present application, and for the detection of fermented grains samples, the establishment of the stability model can more widely promote the application of the technology. The repeated exploration experiment becomes more systematic. For similar detection applications, such as the dairy industry, the brewing industry and other applications involving complex sample components, the model can be used as a template, combined with the characteristics of the actual application samples, and targeted control can be carried out. The establishment of the stability model has more practical reference significance than simply giving the optimal value of the experiment.

[0063] Application example 1. Test steps: S1: Take 1 g of fermented grains from different sites of a certain white wine, respectively dissolve with 10 mL of sterile water according to the ratio of 1:10, and vortex to obtain a fermented grains suspension; S2: Take 1 mL of the suspension, centrifuge at low speed, and centrifuge the fermented grains suspension at 500 rpm for 2 min, and take the upper suspension to a new centrifuge tube; S3: PMA treatment, add PMA dye with a final concentration of 20 μM to the upper fermented grains suspension, wrap with tin foil paper, and incubate at 30°C in a shaking incubator for 15 min in the dark; S4: Dilute the PMA-treated suspension 10 times with sterile water, and transfer to glass containers with a bottom surface area of 34 cm 2 ; S5: Blue light treatment, place the glass containers in the blue light treatment equipment, and take them out after 30 min; S6: Collect the suspension after blue light treatment in the glass containers, centrifuge at high speed at 13000 rpm for 10 min, discard the supernatant, and leave the precipitate; S7: Extract genomic DNA according to the instructions of the yeast DNA extraction kit; S8: Use the extracted total nucleic acid sample as a template, use primers for PCR amplification, and use real-time fluorescent quantitative PCR technology to determine the viable cell count of the target active yeast; The primers, qPCR reaction system and qPCR reaction conditions of Saccharomyces cerevisiae, Schizosaccharomyces pombe and Pichia pastoris are consistent with Example 1.

[0064] 2. Test results: A linear standard curve was constructed with the logarithm of the total bacterial count (base 10) as the x-axis and the CQ value as the x-axis. The following are examples of *Saccharomyces cerevisiae*, *Schizosaccharomyces simulans*, and *Pichia pastoris*. Figures 4-6 As shown.

[0065] Figure 7 This is a qPCR amplification curve, primarily used to evaluate amplification efficiency, template amount, and reaction specificity. Analyzing the curve shape can determine whether the reaction was successful and whether contamination or non-specific amplification occurred.

[0066] Figure 8 These are qPCR melting curves. From left to right, the melting curves are for: *Saccharomyces cerevisiae*, *Schizosaccharomyces cerevisiae*, and *Pichia pastoris*. Melting curves are primarily used to verify the specificity of the amplified products. By analyzing the DNA double-strand melting temperature (Tm value), the presence of non-specific amplification or primer dimers can be determined. In this experiment, the Tm was between 75 and 90℃, indicating good specificity.

[0067] like Figure 9 As shown, the cell concentration obtained by conventional qPCR is higher than that obtained by PMA-qPCR. This is because conventional qPCR detects all cells containing the target nucleic acid in the sample, regardless of whether these cells are alive, dead, partially degraded, or even free DNA fragments. PMA-qPCR inhibits DNA amplification in dead cells and also has a certain inhibitory effect on free DNA, thus providing a more accurate quantitative result for the concentration of live cells in the sample.

[0068] Figure 10 To compare the quantitative results of the plate plating method with those of the PMA-qPCR method used in this patent, as shown in the figure, N1-N4 represent the quantitative results of yeast cells at four sites in *Saccharomyces cerevisiae*, S represents *Schizosaccharomyces cerevisiae*, and B represents *Pichia pastoris*. The correlation coefficient r between the two sets of data was calculated to be 0.9570, which also demonstrates the practicality of the PMA-qPCR method of this invention.

[0069] Example 7: This invention provides a blue light processing device for the method of quantitative detection of active yeast in fermented mash, such as... Figure 11 As shown, the blue light processing device includes: a housing with an internal cavity for accommodating other components; and a blue LED light panel 1, disposed within the cavity, for irradiating the container storing the fermented mash suspension with blue light. The blue LED light panel 1 can be flexibly installed on the side or top of the device's internal cavity to accommodate the structural and material characteristics of different sample containers, maximizing illumination efficiency.

[0070] Sample holder 2, arranged in the cavity, for placing the container storing the fermented grains suspension. The sample holder 2 can be rotated and vibrated by using the common driving assembly (such as motor) in the prior art, so that each sample can be uniformly irradiated by the light generated by the blue LED lamp panel 1 below. In order to make full use of space and improve the efficiency of the device, the sample holder 2 can be one or more layers to place more samples as needed.

[0071] Fan 3, arranged on the side wall of the box and connected with the cavity and the outside, for cooling the container storing the fermented grains suspension and the blue LED lamp panel. The fan 3 can be installed at the top, bottom or other positions in the inner cavity of the device according to the specific structure and layout of the light source and sample holder, and air is introduced into the inner cavity of the device by using the air duct to achieve the optimal efficiency, space utilization and noise control.

[0072] Function control area 4, arranged on the box, for controlling the blue light illumination intensity, the rotation speed and vibration intensity of the sample holder 2, the automatic starting condition, rotation speed and working time setting of the fan 3, etc., so that the device is more convenient and adaptable to use.

[0073] The difference between the present blue light processing device and the prior art is that a fan is arranged, and the rest is the same as the prior art, as long as the corresponding functions can be realized. Since the light source generates heat when it works, in order to control the temperature rise of the lamp beads and reduce the light decay, and at the same time to avoid the influence of heat radiation and heat convection of the light source on the sample, a fan 3 is installed in the inner cavity of the device, which starts to work according to the device program setting when the blue light source is turned on, so that the fan 3 can draw the air outside the device into the cavity and blow the sample and LED lamp beads to take away the heat.

Claims

1. A method for quantitative detection of viable microorganisms in a solid / semi-solid sample, characterized in that, The method is based on PMA-qPCR method for detection, analyzes the influencing factors of the stability of experimental results, and constructs a stability analysis model; The stability analysis model is: ； Wherein, S is the comprehensive stability score, the higher the S value, the better the stability of the experimental results; wi is the weight coefficient for the ith influencing factor; performance function for the i-th influencing factor; The influencing factors include sample suspension dilution multiple, PMA dye concentration, dye incubation time, blue light irradiation time, blue light irradiation area and impurity particle size.

2. The method for quantitative detection of active microorganisms in a solid / semi-solid sample according to claim 1, characterized in that, The method comprises the following steps: 1) dissolving the solid / solid sample with water to obtain a sample suspension, and centrifuging to obtain the upper suspension; 2) adding PMA dye to the upper suspension for incubation, then transferring to a glass container for blue light irradiation, and then centrifuging to collect the precipitate; 3) extracting genomic DNA from the collected precipitate; 4) using the extracted total nucleic acid sample as a template, PCR amplification is carried out using primers, and real-time fluorescent quantitative PCR technology is used to determine the viable count of target active microorganisms; The method further comprises a dilution step, which is carried out before the sample suspension is subjected to blue light irradiation.

3. The method for quantitative detection of microorganisms in a solid / semi-solid sample according to claim 1 or 2, characterized in that, The solid / solid sample is fermented grains, and the target active microorganisms include yeast cells; The yeast cells include Saccharomyces cerevisiae, Schizosaccharomyces pombe and Pichia pastoris; The primer of Saccharomyces cerevisiae includes: N-F: 5'-TGTCGTCCTGGTTGGTATGC-3'; N-R: 5'-GCCAGCTAAGTGGATCGGAG-3'; The primer of Schizosaccharomyces pombe includes: S-F: 5'-GCTGATGGCAGCAAAATCCC-3'; S-R: 5'-TTGCGAGGAACACCACTCTC-3'; The primer of Pichia pastoris includes: B-F: 5'-GTTTGAGCGTCGTTTCCATC-3'; B-R: 5'-AGCTCCGACGCTCTTTACAC-3'.

4. The method for quantitative detection of microorganisms in a solid / semi-solid sample according to claim 3, characterized in that, When the influencing factor is the dilution factor of the sample suspension, The calculation method is as follows: ； wherein, Dilution factor for sample suspension; = 10 times; = 1000 fold.

5. The method for quantitative detection of microorganisms in a solid / semi-solid sample according to claim 3, characterized in that, When the influencing factor is the PMA dye concentration, The calculation method is as follows: ； wherein, PMA dye concentration; = 20 uM; = 5 uM; = 40 uM.

6. The method for quantitative detection of microorganisms in a solid / semi-solid sample according to claim 3, characterized in that, When the influencing factor is the dye incubation time, The calculation method is as follows: ； wherein, is the dye incubation time; = 5 min; = 15 min.

7. The method for quantitative detection of microorganisms in a solid / semi-solid sample according to claim 3, characterized in that, When the influencing factor is the blue light exposure time, The calculation method is as follows: ； wherein is the blue light exposure time; = 15 min; = 30 min.

8. The method for quantitative detection of microorganisms in a solid / semi-solid sample according to claim 2, characterized in that, As a preference, when the influencing factor is the blue light irradiation area, The calculation method is as follows: ； wherein is the blue light irradiation area; =0 ； =34 。 9. The method for quantitative detection of microorganisms in a solid / semi-solid sample according to claim 1, characterized in that, When the influencing factor is the size of the impurity particles, The calculation method is as follows: ； wherein, is the size of the impurity particles; = 1000 um; = 10 um.

10. A blue light treatment device for use in the method of quantitatively detecting viable microorganisms in a solid / semi-solid sample according to any one of claims 1 to 9, characterized in that, The blue light treatment device comprises: A box body with a cavity inside; A sample holder arranged in the cavity for placing a container for storing fermented grain suspension; A blue LED lamp panel arranged in the cavity for blue light irradiation of the container for storing fermented grain suspension; A fan arranged on the side wall of the box body and communicating with the cavity and the outside for cooling the container for storing fermented grain suspension and the blue LED lamp panel.

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