Electroactive microbial detection method and kit

Abstract

The application discloses a kind of electroactive microorganism detection method and kit.The application utilizes the catalytic action of electroactive microorganism extracellular electron transfer key protein (outer membrane cytochrome c) and chemiluminescence technology, combined with the photographing function of smart phone, picture information processing technology, provide a kind of electroactive microorganism detection method and detection kit.No need to use any nanomaterial or special equipment, by commonly used smart phone and computer application program can realize signal acquisition, processing, calculation and result output;Convenient and fast, good stability, low cost, simple operation, the whole detection process can be completed without professional training;And response speed is fast, the whole detection process can be completed in 2min;It can be widely used in field detection.

Description

Technical Field

[0001] This invention belongs to the field of biological detection and relates to a method and reagent kit for detecting electroactive microorganisms. Background Technology

[0002] Electroactive microorganisms are a class of microorganisms capable of exchanging electrons with the environmental medium. They have broad application prospects in fields such as organic pollutant degradation, heavy metal reduction and transformation, bioenergy, biosynthesis, and biosensing. Isolating and identifying novel electroactive strains and enriching strain libraries are crucial prerequisites for in-depth research into the mechanisms of electroactive bacteria and their widespread application. Establishing rapid, sensitive, and high-throughput screening or detection methods is essential for discovering new electroactive microbial strains. Currently, various screening / detection methods for electroactive microorganisms have been developed. Traditional screening methods mainly involve multiple steps, including enrichment, purification, physiological and biochemical identification, molecular biological identification, and activity determination, making the process complex, time-consuming, and labor-intensive. Electrochemical identification methods developed in recent years typically require customized electrodes and electrolytic cells, making it impossible to simultaneously detect multiple samples and hindering widespread application. While using nanomaterials such as tungsten oxide as indicators for electroactive microorganism screening allows for the simultaneous detection of multiple samples, the synthesis of these nanomaterials is complex, and the detection stability is poor. Summary of the Invention

[0003] The first objective of this invention is to provide a detection product for electroactive microorganisms.

[0004] A second aspect of the present invention is to provide a device for detecting electroactive microorganisms.

[0005] The third objective of this invention is to provide a method for detecting electroactive microorganisms.

[0006] The fourth aspect of this invention aims to provide applications of the aforementioned testing products or testing devices.

[0007] The technical solution adopted in this invention is:

[0008] In a first aspect, the present invention provides a detection product for electroactive microorganisms, comprising: 0.4-0.8 mM luminol or luminol derivatives, and 0.5-4 mM hydrogen peroxide.

[0009] In some embodiments of the present invention, the hydrogen peroxide concentration is 0.6 to 2 mM.

[0010] In some embodiments of the present invention, the hydrogen peroxide concentration is 0.8 to 1 mM.

[0011] In some embodiments of the present invention, the luminol derivatives include sodium luminol, isoluminol, or N-(4-aminobutyl)-N-ethylisoluminol.

[0012] In some embodiments of the present invention, the volume ratio of luminol or luminol derivative to peroxide is (1-3):(1-5).

[0013] A second aspect of the present invention provides a detection device for electroactive microorganisms, comprising the detection product described in the first aspect of the present invention.

[0014] In some embodiments of the present invention, the detection device further includes a color data extraction device.

[0015] In some embodiments of the present invention, the extraction device includes: a carrier and a color digitization processing program recorded on the carrier.

[0016] In some embodiments of the present invention, the carrier is a smartphone, a camera, or a computer.

[0017] A third aspect of the present invention provides a method for detecting electroactive microorganisms, using the kit described in the first aspect of the present invention or the detection device described in the second aspect of the present invention to detect electroactive microorganisms.

[0018] In some embodiments of the present invention, the detection method includes the following steps:

[0019] S1: The sample to be tested is mixed with luminol and hydrogen peroxide and then reacted to obtain a reaction mixture;

[0020] S2: Extract the color data of the reaction mixture obtained in step S1, obtain the B value in the RGB color values ​​of the color data, and thus determine the presence and / or content of electroactive microorganisms in the sample to be tested.

[0021] In some embodiments of the present invention, the reaction conditions are: a reaction in the dark for 5 to 15 seconds.

[0022] In some embodiments of the present invention, the pH of the mixture is 9 to 12.

[0023] In some embodiments of the present invention, the pH of the mixture is adjusted by a pH adjuster.

[0024] In some embodiments of the present invention, the pH adjuster includes a hydroxide base, which includes sodium hydroxide, potassium hydroxide, etc.

[0025] In some embodiments of the present invention, the concentration of the hydroxide base is 0.005 to 0.05 mol / L.

[0026] In some embodiments of the present invention, the volume ratio of the sample, luminol, and hydrogen peroxide is 1:(1-3):(1-5).

[0027] In some embodiments of the present invention, the image is captured under the condition of taking pictures in the dark.

[0028] In some embodiments of the present invention, the extraction includes obtaining the color data using a color digitization processing procedure.

[0029] In some embodiments of the present invention, the color digitization processing program is a program that can convert the color information of the object to be extracted into numerical information.

[0030] In some embodiments of the present invention, the color digitization processing program is a program that can convert the color information of the object to be extracted into numerical information.

[0031] In some embodiments of the present invention, the color digitization processing program is loaded onto a device selected from the group consisting of: mobile phones, cameras, and computers.

[0032] In some embodiments of the present invention, the color digitization processing program includes Photoshop.

[0033] In some embodiments of the present invention, the specific way of using Photoshop is as follows: select the eyedropper tool, set the sampling range to 11×11, and read the B value in the RGB value.

[0034] In some embodiments of the present invention, the extraction further includes taking a picture of the object to be extracted and obtaining the color data of the resulting picture.

[0035] A fourth aspect of the present invention provides the application of the detection product of the first aspect of the present invention or the detection device of the second aspect of the present invention in the rapid detection of the presence and / or content of electroactive microorganisms.

[0036] The beneficial effects of this invention are:

[0037] This invention utilizes the catalytic activity of a key extracellular electron transport protein (outer membrane cytochrome c) in electroactive microorganisms and chemiluminescence technology, combined with smartphone camera functionality and image processing technology, to provide a method and kit for detecting electroactive microorganisms. It eliminates the need for any nanomaterials or specialized equipment; signal acquisition, processing, calculation, and result output can be achieved through common smartphones and computer applications. It is convenient, fast, stable, low-cost, and simple to operate, requiring no professional training to complete the entire detection process. Furthermore, it boasts a rapid response time, with the entire detection process completed within 2 minutes; it can be widely used for on-site testing. Attached Figure Description

[0038] Figure 1 This is a schematic diagram illustrating the principle of chemiluminescence immunoassay for detecting electroactive microorganisms.

[0039] Figure 2 Feasibility analysis results of chemiluminescence immunoassay for detecting electroactive microorganisms;

[0040] Figure 3 Optimization of chemiluminescence reaction time;

[0041] Figure 4 To optimize luminol concentration;

[0042] Figure 5 To optimize the hydrogen peroxide concentration;

[0043] Figure 6 Optimized for pH value;

[0044] Figure 7 The regression curve shows the relationship between the chemiluminescence image signal value and the concentration of electroactive microorganisms.

[0045] Figure 8 Graphs showing the chemiluminescence reaction results of different microorganisms. Detailed Implementation

[0046] The following will describe the concept and technical effects of the present invention clearly and completely with reference to embodiments, so as to fully understand the purpose, features and effects of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are all within the scope of protection of the present invention.

[0047] Example 1: Feasibility Assessment of Chemiluminescence for the Detection of Electroactive Microorganisms

[0048] To demonstrate the feasibility of using chemiluminescence for the detection of electroactive microorganisms, 100 μL of 0.01 mol / L cytochrome c and 100 μL of 3.125 × 10⁻⁶ mol / L cytochrome c were mixed. 7 CFU / mL: Shewanella oneidensis MR-1 or Escherichiacoli K12 were mixed with a chemiluminescence reagent kit (100 μL 0.5 mM luminol, 100 μL 0.8 mM hydrogen peroxide, 20 μL 0.01 mol / L NaOH) and placed in a dark chamber for reaction. The luminescent reaction product was photographed using a smartphone in the dark chamber. The photos were opened in Photoshop, and the sampling range was set to 11 × 11 using the pipette tool. The B value in the RGB values ​​was read. See [link to detailed procedure] for more information. Figure 1 The test results are as follows: Figure 2 As shown, cytochrome c and the model electroactive microorganism *S. oneidensis* MR-1 exhibited high blue light intensity values, while the non-electroactive microorganism *Escherichia coli* K12 and the blank control showed only very weak intensity values. Differential analysis of the four experimental groups revealed that cytochrome c and the model electroactive microorganism *S. oneidensis* MR-1 were significantly different not only from the blank control but also from the non-electroactive bacterium *Escherichia coli* K12, indicating that this method can distinguish between electroactive and non-electroactive bacteria. This demonstrates that this method is feasible for detecting electroactive microorganisms.

[0049] Example 2: Chemiluminescence for the detection of electroactive microorganisms.

[0050] The testing steps are as follows:

[0051] 1) Add 100 μL of the microbial suspension to be tested, 100 μL of 0.5 mM luminol, 100 μL of 0.8 mM hydrogen peroxide and 20 μL of 0.01 mol / L NaOH to a white 96-well plate, mix quickly, and place in a light-proof box for reaction;

[0052] 2) Set the smartphone's exposure time to 5 seconds, place it on top of a light-shielding box, and take a picture to obtain a photo of the chemiluminescence reaction.

[0053] 3) Open the photo obtained in step 2) with Photoshop, select the eyedropper tool, set the sampling range to 11×11, and read the B value in the RGB values.

[0054] Example 3: Kinetic Analysis of Chemiluminescence Reactions in Electroactive Microorganisms

[0055] To determine the time required for the chemiluminescence intensity to reach its maximum, 100 μL of 0.01 mol / L luminol stock solution and 100 μL of 1000 μg / mL hydrogen peroxide standard solution were added to white microplates. Finally, 100 μL of *S. oneidensis* MR-1 bacterial culture with an OD600 of 1 was added, and the plates were immediately placed in a light box for photography, with images taken every 5 seconds. For the control group, 100 μL of 0.01 mol / L luminol stock solution and 100 μL of 1000 μg / mL hydrogen peroxide standard solution were added to white microplates, and finally, 100 μL of purified water was added. The plates were immediately placed in a light box for photography, with images taken every 5 seconds. The results are as follows: Figure 3 As shown, the luminescence reaction is very rapid, starting to increase 5 seconds after the addition of the luminescent reagent, reaching its maximum value after about 10 seconds, and then gradually decreasing in brightness. Therefore, 10 seconds is taken as the time for subsequent chemiluminescence reactions.

[0056] Example 4: Optimization of working conditions for chemiluminescence detection of electroactive microorganisms

[0057] To achieve the best detection results, this embodiment further optimizes the concentrations of luminol, hydrogen peroxide, and pH value, which affect the detection performance.

[0058] (1) Optimization of luminol concentration

[0059] Take 100 μL of S. oneidensis MR-1 with OD600 = 1, add 100 μL of 0.8 mM hydrogen peroxide, and then add 100 μL of luminol. Set the luminol concentrations to 0.8 mM, 0.5 mM, 0.4 mM, 0.2 mM, and 0.1 mM to investigate the effect of luminol concentration on detection. The results are shown in […]. Figure 4 The results showed that the relative intensity value ΔB of the luminescence reaction was the largest when the luminol concentration was 0.5 mM. The ΔB values ​​of 0.8 mM and 0.5 mM luminol solutions were not significantly different. Therefore, the optimal luminol concentration in this experiment was 0.5 mM.

[0060] (2) Hydrogen peroxide concentration optimization

[0061] Take 100 μL of S. oneidensis MR-1 with OD600 = 1, add 100 μL of 0.5 mM luminol, and add 100 μL of hydrogen peroxide. The hydrogen peroxide concentrations were set to 0.5 mM, 0.8 mM, 1 mM, 2 mM, 3 mM, 4 mM, and 5 mM to investigate the effect of hydrogen peroxide concentration on detection. The results are shown in […]. Figure 5 The results showed that the relative intensity value ΔB of chemiluminescence was the largest when the hydrogen peroxide concentration was 0.8 mM. Therefore, the optimal hydrogen peroxide concentration is 0.8 mM.

[0062] (3) pH optimization

[0063] Take 100 μL of S. oneidensis MR-1 with OD600 = 1, add 100 μL of 0.5 mM luminol and 100 μL of 0.8 mM hydrogen peroxide. Adjust the pH of the mixed reaction system to 8, 9, 10, 11, and 12 by adding different volumes of 0.01 mol / L NaOH. Investigate the effect of pH on detection. The results are shown in [Figure number missing]. Figure 6 The results showed that the relative chemiluminescence intensity ΔB reached its maximum value at pH 11, i.e., when 20 μL of 0.01 mol / L NaOH was added. Therefore, the optimal pH value is 11.

[0064] Example 5: Optimal Scheme for Microbial Detection

[0065] Based on the parameter optimization results of Example 4, the optimal method for detecting electroactive microorganisms was obtained, which specifically includes the following steps:

[0066] 1) Add 100 μL of the microbial suspension to be tested (OD600=1) to a white 96-well plate along with 100 μL of 0.5 mM luminol, 100 μL of 0.8 mM hydrogen peroxide and 20 μL of 0.01 mol / L NaOH, mix quickly, and place in a dark-proof lamp box to react for 10 s;

[0067] 2) Set the smartphone's exposure time to 5 seconds, place it on top of a light-shielding box, and take a picture to obtain a photo of the chemiluminescence reaction.

[0068] 3) Open the photo obtained in step 2) using Photoshop. In the menu, select Image, Adjustments, Threshold. Set the threshold to 100. Select the Eyedropper tool and set the sampling range to 11×11 to read the B value from the RGB values.

[0069] Example 6: Linear Range Analysis of Chemiluminescence Detection of Electroactive Microorganisms

[0070] Using *S. oneidensis* MR-1 as the model electroactive microorganism, chemiluminescence reactions were conducted on *S. oneidensis* MR-1 bacterial suspensions at different concentrations with 0.5 mM luminol, 0.8 mM hydrogen peroxide, pH 11, and a photographing time of 10 s. The chemiluminescence intensity was measured, and the results are shown in [Figure number missing]. Figure 7 The results showed that at 1.95×10 6 -3.125×10 7 CFU / mL and 3.125×10 7 -5.0×10 8 Within the CFU / mL concentration range, the luminescence intensity B value showed a good linear relationship with the bacterial concentration, with linear equations of Y = 128.04X – 779.12 and y = 37.54x – 69.02, respectively, and correlation coefficient R. 2 The values ​​are 0.9959 and 0.9554.

[0071] Example 7 Selective Detection

[0072] For a concentration of 3.125 × 10 7Chemiluminescence reactions and luminescence intensity signals were detected in *S. oneidensis* MR-1, *Shewanella putrefaciens* SP200 (*S. putrefaciens*), *Comamonas guandongensis* CY01 (*C. guandongensis* CY01), *Pseudomonas aeruginosa* PAH-1 (*P. aeruginosa* PAH-1), and *Escherichia coli* (*E. coli*) at CFU / mL. The results are as follows: Figure 8 The results showed that *S. putrefaciens* and the electroactive bacterial model strain *S. oneidensis* both exhibited high chemiluminescence intensities with no significant difference. *C. guandongensis* showed a certain chemiluminescence intensity, significantly different from both the electroactive bacterial model strain *S. oneidensis* (p<=0.001) and the non-electroactive bacterium *E. coli* (p<=0.001). *P. aeruginosa* showed a significant difference from the electroactive bacterial model strain *S. oneidensis* (p<=0.001) but no significant difference from the non-electroactive bacterium *E. coli*. This suggests that this method has a certain selectivity for detecting different electroactive microorganisms.

[0073] The effectiveness of the microbial detection method and detection kit of the present invention will be further evaluated below.

[0074] Example 8: Analysis of spiked samples

[0075] Using the standard curve established in Example 6, the smartphone photography method was applied to determine the concentration of *S. oneidensis* MR-1 in common water bodies. The method was evaluated for practical application by spiked detection of *S. oneidensis* MR-1 in lake water. The results are shown in Table 1. After the experiment, the average recovery rate of *S. oneidensis* MR-1 was between 90.2% and 94.4%, and the relative standard deviation of the three parallel experiments was less than 5%. These results indicate that the method has good accuracy in the detection of actual samples.

[0076] Table 1. Spiked recoveries of S. oneidensis MR-1 concentration in actual water samples (n=3)

[0077]

[0078] The above detailed embodiments have provided a comprehensive description of the present invention. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention. Furthermore, unless otherwise specified, the embodiments of the present invention and the features thereof can be combined with each other.

Claims

1. A method for detecting electroactive microorganisms for non-disease diagnostic purposes, characterized in that, Includes the following steps: S1: The sample to be tested is mixed with 0.4-0.8mM luminol and 0.5-4mM hydrogen peroxide and then reacted to obtain a reaction mixture; S2: Take a picture of the reaction mixture, use a color digitization processing program to convert the color information of the reaction mixture into numerical information, obtain the color data of the reaction mixture, read the B value in the RGB color value in the color data, and thus determine the presence and / or content of electroactive microorganisms in the sample to be tested. The reaction conditions described in S1 are: reaction in the dark for 5 to 15 seconds.

2. The method according to claim 1, characterized in that, The pH of the mixture is 9–12.

3. A detection device for electroactive microorganisms used to implement the method of claim 1, characterized in that, The detection device contains a detection product for electroactive microorganisms; The tested products are 0.4–0.8 mM luminol and 0.5–4 mM hydrogen peroxide; The detection device also includes a color data extraction device; The extraction device includes: a carrier and a color digitization processing program recorded on the carrier; The carrier can be a smartphone, camera, or computer.

4. The application of the detection method according to any one of claims 1 to 2 or the detection device according to claim 3 in the rapid detection of the presence and / or content of electroactive microorganisms for non-disease diagnostic purposes.

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