WO2023231289A1

WO2023231289A1 - Method for rapidly detecting drug sensitivity

Info

Publication number: WO2023231289A1
Application number: PCT/CN2022/128484
Authority: WO
Inventors: 林恺铖; 蒙思宇; 宋一之; 胡慧杰; 王敬开; 郄兴旺; 何娜; 葛明锋; 李力
Original assignee: 苏州国科医工科技发展(集团)有限公司; 中国科学院苏州生物医学工程技术研究所
Priority date: 2022-05-26
Filing date: 2022-10-31
Publication date: 2023-12-07
Also published as: CN117169207A

Abstract

A method for rapidly detecting drug sensitivity, which method comprises the following steps: 1) providing a gel substrate, which provides a culture environment for in-situ growth of bacteria; 2) spotting bacteria and a test drug on the gel substrate, and performing culturing; 3) imaging the culture under a microscope; and 4) by means of using an image processing method, analyzing and calculating the variation of the bacterial imaging areas in the bacterial images obtained in step 3) so as to determine the drug resistance of the bacteria to the test drug. The method for rapidly detecting drug sensitivity analyzes a change in bacterial growth by means of imaging bacteria which divide and undergo quantity changes under the action of antibiotics, by using the gel substrate as a carrier, and in combination with an image processing method, such that rapid and accurate drug sensitivity detection can be achieved.

Description

Rapid drug susceptibility testing method

Technical field

The invention relates to the field of detection and diagnosis of pathogenic microorganisms, and in particular to a rapid drug sensitivity detection method.

Background technique

Infectious diseases caused by bacterial pathogens are one of the most common causes of death. Antimicrobial susceptibility testing of microorganisms is extremely important for treating bacterial infections and promoting antibiotic stewardship.

Common drug susceptibility testing methods include disk diffusion method, dilution method (including agar and broth dilution method), antibiotic concentration gradient method (E-test method), and automated instruments.

Broth microdilution method is one of the gold standards for drug susceptibility testing. The test principle is that the reagent contains diluted antibacterial drugs, the test bacteria are inhibited by a quantitative amount of antibacterial drugs, and the minimum inhibitory concentration (MIC) of the test bacteria is determined based on the growth inhibition. The drug sensitivity plate needs to be incubated at 35°C ± 2°C for 16 to 20 hours. The experiment takes a long time and seriously affects the diagnostic efficiency, thus delaying the treatment opportunity.

Except for the further highly automated means of existing common methods, most breakthroughs in drug susceptibility testing technology reflect two major trends, namely non-culture technology and single-cell technology. The currently developed non-culture technology is mainly based on molecular diagnosis and is currently the main means of developing rapid pathogen diagnosis. Products such as GeneXpert and Filmarray have been recognized in domestic and foreign markets. However, the target microbial species applicable to molecular diagnostic methods are limited by the number and types of probes and primers, and the detection content of drug resistance genes is relatively simple. More importantly, the existence of drug-resistant genes does not mean that microorganisms have drug-resistant phenotypes, and new drug-resistant phenotypes are often manifested through brand-new drug-resistant genes. Therefore, the development of genetic diagnosis will fundamentally depend on the discovery of new resistance genes, and guidance on the rational application of antibacterial drugs and precise anti-infection is limited. Therefore, phenotype-based drug susceptibility analysis has greater clinical significance. In addition, the high price of molecular diagnostic methods also hinders their clinical popularization.

The use of single cells for drug susceptibility analysis is another development trend. Analysis based on the single-cell level can not only accurately reflect the characteristics of bacteria at a more basic level, but also because single-cell technology does not require traditional microbial culture and does not require long waits for microbial value-added processes, it is currently a promising new method for rapid pathogenic bacteria diagnosis. Methods have also become an international research hotspot, and a series of innovative technical methods based on single-cell imaging have emerged. For example, observing the division process of single cells of bacteria fixed on a matrix under the action of antibiotics under a microscope, and drug resistance evaluation methods based on observation of bacterial division on microfluidic chip channels. However, although the above-mentioned bacterial single-cell division drug resistance evaluation method is relatively sophisticated in microfluidic chip design and has high imaging resolution, it is too complex and difficult to meet the real clinical scenario of testing more than 20 kinds of antibiotics on one sample. Optimize the design of its key technical details and core components. Due to the complexity of the overall design, it is still limited to the laboratory stage, and there is no sufficient data to support its effectiveness.

Therefore, a more reliable solution is now needed.

Contents of the invention

The technical problem to be solved by the present invention is to provide a rapid drug sensitivity detection method in view of the above-mentioned deficiencies in the prior art.

In order to solve the above technical problems, the technical solution adopted by the present invention is: a rapid drug sensitivity detection method, which includes the following steps:

1) Provide a gel base that provides a culture environment for bacterial in-situ growth;

2) Spot bacteria and test drugs on the gel base and culture;

3) Imaging under a microscope;

4) Use image processing methods to analyze and calculate the change in the bacterial imaging area in the bacterial image obtained in step 3) to determine the bacterial resistance to the test drug.

Preferably, step 4) specifically includes:

4-1) Extract the area containing noise in the bacterial image as an ROI image;

4-2) For a certain noise point p in the ROI image, obtain the coordinates (x, y) of the noise point p in the image from the ROI image obtained at each moment, and calculate the coordinates of the noise point p at each moment i and the The difference between the horizontal and vertical coordinates of the coordinates of the noise point p at the initial moment is used to obtain the displacement amounts Δx _i and Δy _i of the noise point i at each moment; among the displacement amounts Δx and Δy at all times, the maximum values of Δx and Δy are taken and recorded respectively. are maxΔx and maxΔy; take the minimum value of -Δx and -Δy, and record them as minΔx and minΔy respectively; use maxΔx, maxΔy, minΔx and minΔy as the maximum deviation to draw the image, put the ROI images at all times in the same coordinate system, and extract The area included in all ROI images is used as the final image set Z used for calculation;

4-3) In the image set Z, perform negative phase operations on the images and background at different times, and then subtract the background from the image at each time to obtain the feature area; then use perimeter, area, shape, and grayscale as feature pairs Screen the characteristic areas, outline the bacteria in the image, and record the bacterial parameters: number, total area, average perimeter and average area. By calculating the change rate of at least one of the four bacterial parameters at different times, determine whether the bacteria are growing. To determine the bacterial resistance to the test drug;

Among them, for different types of bacteria, the characteristic areas are screened with different ranges of perimeter, area, shape, and grayscale.

Preferably, the step 4-1) is specifically: extract a block area from the bacterial image, perform negative phase processing on it, and then convert it into a grayscale image, and then use the Otsu threshold method to convert the image into a binary image; Value filtering is used to smooth the binary image, and finally the canny operator is used to extract the contour of the area and finally find the location of the noise in the background, thereby obtaining all areas containing noise in the bacterial image and serving them as ROI images.

Preferably, the gel base includes a culture medium and a gel material, and the culture medium is an MH culture medium.

Preferably, the components of the MH culture medium include: beef extract powder, soluble starch, acid hydrolyzed casein and ultrapure water.

Preferably, the preparation method of the MH culture medium is as follows: adding beef extract powder, soluble starch, and acid-hydrolyzed casein into ultrapure water, and heating in a sterilizing pot to completely dissolve the mixture into a clear solution to obtain liquid MH. culture medium.

Preferably, the preparation method of the gel base is: adding the gel material to the liquid MH medium, heating it in a sterilizing pot, and after the gel material is completely dissolved, take the mixture out of the sterilizing pot, Transfer to a microplate and allow to cool naturally to form a gel base.

Preferably, the gel material is any one or more of agarose, gelatin, carrageenan, xanthan gum and agar.

Preferably, the preparation method of the MH culture medium is: add 0.4g beef dipping powder, 0.3g soluble starch, and 3.5g acid hydrolyzed casein into 200 ml ultrapure water, and use a sterilizing pot to heat to 121 at 0.1 MPa. ℃, the mixture is completely dissolved into a clear solution, and a liquid MH medium is obtained.

Preferably, the preparation method of the gel base is: weigh 4g of agarose powder, add it to 200ml of MH culture medium, use a sterilizing pot to heat to 121°C at 0.1mpa, and wait until the gel is completely dissolved. Remove the mixture from the sterilization pot, transfer it to a microplate with a pipette, and allow to cool naturally to form a gel base.

The beneficial effects of the present invention are: the rapid drug susceptibility detection method provided by the present invention uses a gel base as a carrier to image the division and quantitative changes of bacteria under the action of antibiotics, and combines image processing methods to analyze bacterial growth changes. This can determine the bacterial resistance to the test drug and enable rapid and accurate drug susceptibility testing.

Description of the drawings

Figure 1 is a comparison of the effects of MH culture medium and LB and TB culture media in the embodiment of the present invention;

Figure 2 is a microscopic image of ATCC29213 growing freely on a drug-sensitive plate with a gel base for 3 hours without adding antibacterial drugs;

Figure 3 is a microscopic image of ATCC29213 inhibiting growth for 3 hours on a drug-sensitive plate with a gel base when vancomycin is added;

Figure 4 shows the growth curve of ATCC29213 within 3 hours under the action of vancomycin at different concentrations;

Figure 5 shows the average area of ATCC29213 measured at different times under the action of vancomycin at different concentrations.

Detailed ways

The present invention will be further described in detail below with reference to the examples, so that those skilled in the art can implement it according to the text of the description.

It should be understood that terms such as "having," "comprising," and "including" as used herein do not exclude the presence or addition of one or more other elements or combinations thereof.

Example 1

A rapid drug sensitivity detection method in this embodiment includes the following steps:

1) Provide a gel base, which provides a culture environment for bacterial in-situ growth;

2) Spot bacteria and test drugs on the gel base and place them in a 37°C incubator for culture;

3) Imaging under a microscope;

In this embodiment, the gel base includes culture medium and gel material. The gel base has a low moisture content and does not support the free movement of bacteria. It is used to provide a culture surface for bacterial in-situ growth and can also facilitate imaging observation. Among them, the culture medium is used to provide nutrients required for bacterial growth, and the gel material is used to form a gel-like base to provide a bacterial entrapment carrier.

In a preferred embodiment, the medium is an MH medium. Further, the components of the MH medium include: beef extract powder, soluble starch, acid hydrolyzed casein and ultrapure water. The gel material is any one or more of agarose, gelatin, carrageenan, xanthan gum and agar. However, it should be understood that nutrients with similar functions to MH culture medium, such as LB and TB culture media, as well as substances with similar functions to the above-mentioned gel materials, should be regarded as within the scope of protection of this patent.

It can be seen from the physical structure of agarose that agarose is a linear polymer whose chemical structure consists of alternating 1,3-linked β-D-galactose and 1,4-linked 3,6-endether-L-galactose. Made up of long connected chains. Agarose is dissolved in water when heated to 80°C. A good semi-solid gel will be formed at 35-40°C. The gel has a high water content and has a strong ability to absorb water. Therefore, when we drop the culture liquid on the agarose gel, the water, inorganic salts and organic small molecules in the culture medium enter the network structure of the agarose gel, leaving only bacteria on the surface of the gel, so that it can be easily It is easy to observe changes in the number of different types of bacteria at the same location under a microscope, so that the growth of bacteria can be judged.

Therefore, in this example, MH medium was selected, and agarose was used as the gel material. Furthermore, in this example, the ingredients of the gel base were optimized, specifically: 0.4g beef extract powder, 0.3g soluble starch, 3.5g acid-hydrolyzed casein, 200ml ultrapure water, and 4g agarose powder.

The preparation method of the gel base is:

1. Prepare MH culture medium: Add 0.4g beef dipping powder, 0.3g soluble starch, and 3.5g acid-hydrolyzed casein into 200ml ultrapure water, use a sterilizing pot to heat to 121°C at 0.1mpa, and completely dissolve the mixture into Clarify the solution to obtain liquid MH medium;

2. Prepare the gel base: weigh 4g of agarose powder, add it to 200ml of MH culture medium, use a sterilizing pot to heat it to 121°C at 0.1mpa, and after the gel is completely dissolved, remove the mixture from the sterilizing pot. Take it out, transfer it to a microwell plate with a pipette, and let it cool naturally to form a gel base.

In this example, the effects of MH medium, LB and TB medium were compared. Refer to Figure 1, which shows the natural growth curve of ATCC29213 under different concentrations and types of medium. It can be seen that MH medium has more Conducive to the growth of bacteria, the growth rate is obviously ahead. Doubling the concentration of MH was not used because doubling the concentration did not significantly change the growth rate.

In the present invention, an automated image processing method is used to process the image obtained by the microscope. By analyzing parameters such as the number, total area, and average area of bacteria in the image, the growth status of the bacteria is determined, thereby determining the effect of the bacteria on the test drug. Drug resistance, the specific steps of image processing are as follows:

4-1) Extract the area containing noise in the bacterial image as an ROI image:

The image easily contains background impurities that are difficult to distinguish from bacteria, so the image needs to be background removed; and some displacement deviations caused by minor manual operations will be introduced during the actual shooting process, so the displacement deviation needs to be eliminated to accurately image the images. Subsequent bacterial images at different times are processed for background removal. The method used in this embodiment is as follows: extract block areas from the bacterial image, perform negative phase processing on it, and then convert it into a grayscale image. Then use the Otsu threshold method to convert the image into a binary image; use median filtering to convert the binary image into a binary image. The image is smoothed, and finally the canny operator is used to extract the contour of the area and finally find the location of the noise in the background, thereby obtaining all areas containing noise in the bacterial image and serving them as ROI images.

4-3) In the image set Z, perform negative phase operations on the images and background at different times, and then subtract the background from the image at each time to obtain the feature area; then use perimeter, area, shape, and grayscale as feature pairs Screen the characteristic areas, outline the bacteria in the image, and record the bacterial parameters: number, total area, average perimeter and average area. By calculating the change rate of at least one of the four bacterial parameters at different times, determine whether the bacteria are growing. This determines the bacterial resistance to the test drug.

Among them, for different types of bacteria, the characteristic areas are screened with different ranges of perimeter, area, shape, and grayscale. For example, for Staphylococcus aureus, step 3) is specifically:

Based on the adaptive threshold obtained by the histogram threshold method, the image is converted into a binary image, and all feature areas are found. The following judgments are made on all extracted feature areas: the perimeter is greater than 50 and less than 180 pixels; the roundness is less than 2; the area is greater than 250 and less than 1200 pixels, if these conditions are met, it is determined to be bacteria; finally, the growth rate of the average area of bacteria is used to determine whether the bacteria are growing, thereby determining the resistance of the bacteria to the test drug.

Refer to Figure 2, which is a microscopic image of ATCC29213 growing freely on a drug-sensitive plate with a gel base for 3 hours without adding antibacterial drugs; Figure 3 is a photo of ATCC29213 growing freely on a drug-sensitive plate with a gel base when vancomycin is added. The microscopic imaging photo of the plate inhibiting growth for 3 hours clearly shows that bacterial growth is inhibited by vancomycin. Among them, gel imaging uses white light and transmission mode, which can be an inverted objective lens or an upright objective lens. In this embodiment, an inverted microscope is used.

Refer to Figure 4, which shows the growth curve of ATCC29213 within 3 hours under the action of vancomycin at different concentrations in this example. It can be seen that the antibiotic has no obvious inhibitory effect at the beginning, but as the concentration increases, the inhibitory effect decreases. It's starting to become obvious. The MIC of ATCC29213 was measured at 2ug/ml using the broth dilution method. Using this method, the MIC can be obtained within 3 hours. Through this imaging drug susceptibility method, the original 16-24 hour drug susceptibility test can be shortened to a same-day report.

Referring to Figure 5, in this example, the average area of ATCC29213 measured at different times under the action of vancomycin at different concentrations is shown.

Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and embodiments. They can be applied to various fields suitable for the present invention. For those familiar with the art, they can easily Additional modifications may be made, and therefore the invention is not limited to the specific details without departing from the general concept defined by the claims and equivalent scope.

Claims

A rapid drug susceptibility testing method, characterized by comprising the following steps:

1) Provide a gel base that provides a culture environment for bacterial in-situ growth;

2) Spot bacteria and test drugs on the gel base and culture;

3) Imaging under a microscope;

4) Use image processing methods to analyze and calculate the change in the bacterial imaging area in the bacterial image obtained in step 3) to determine the bacterial resistance to the test drug.
The rapid drug susceptibility testing method according to claim 1, wherein step 4) specifically includes:

4-1) Extract the area containing noise in the bacterial image as an ROI image;

4-2) For a certain noise point p in the ROI image, obtain the coordinates (x, y) of the noise point p in the image from the ROI image obtained at each moment, and calculate the coordinates of the noise point p at each moment i and the The difference between the horizontal and vertical coordinates of the coordinates of the noise point p at the initial moment is used to obtain the displacement amounts Δx i and Δy i of the noise point i at each moment; among the displacement amounts Δx and Δy at all times, the maximum values of Δx and Δy are taken and recorded respectively. are maxΔx and maxΔy; take the minimum value of -Δx and -Δy, and record them as minΔx and minΔy respectively; use maxΔx, maxΔy, minΔx and minΔy as the maximum deviation to draw the image, put the ROI images at all times in the same coordinate system, and extract The area included in all ROI images is used as the final image set Z used for calculation;

4-3) In the image set Z, perform negative phase operations on the images and background at different times, and then subtract the background from the image at each time to obtain the feature area; then use perimeter, area, shape, and grayscale as feature pairs Screen the characteristic areas, outline the bacteria in the image, and record the bacterial parameters: number, total area, average perimeter and average area. By calculating the change rate of at least one of the four bacterial parameters at different times, determine whether the bacteria are growing. To determine the bacterial resistance to the test drug;

Among them, for different types of bacteria, the characteristic areas are screened with different ranges of perimeter, area, shape, and grayscale.
The rapid drug susceptibility detection method according to claim 2, characterized in that the step 4-1) specifically includes: extracting a block area from the bacterial image, performing negative phase processing on it, and then converting it into a grayscale image, and then using The Otsu threshold method converts the image into a binary image; the binary image is smoothed through median filtering, and finally the canny operator is used to extract the contour of the area and finally find the location of the noise in the background, thereby obtaining all noise-containing features in the bacterial image. area and serve as ROI image.
The rapid drug sensitivity detection method according to claim 1, characterized in that the gel base includes a culture medium and a gel material, and the culture medium is an MH culture medium.
The rapid drug susceptibility testing method according to claim 4, wherein the components of the MH culture medium include: beef extract powder, soluble starch, acid hydrolyzed casein and ultrapure water.
The rapid drug susceptibility detection method according to claim 5, characterized in that the preparation method of the MH culture medium is: adding beef dipping powder, soluble starch and acid hydrolyzed casein into ultrapure water, and heating it using a sterilizing pot , completely dissolve the mixture into a clear solution, and obtain a liquid MH medium.
The rapid drug susceptibility detection method according to claim 6, characterized in that the preparation method of the gel base is: adding the gel material to the liquid MH culture medium, using a sterilizing pot to heat it, and until the gel material After complete dissolution, the mixture is removed from the sterilization pot, transferred to a microplate, and allowed to cool naturally to form a gel base.
The rapid drug susceptibility testing method according to claim 7, wherein the gel material is any one or more of agarose, gelatin, carrageenan, xanthan gum and agar.
The rapid drug susceptibility detection method according to claim 8, characterized in that the preparation method of the MH culture medium is: adding 0.4g beef dipping powder, 0.3g soluble starch, 3.5g acid hydrolyzed casein into 200ml ultrapure water , use a sterilizing pot to heat to 121°C at 0.1 MPa, so that the mixture is completely dissolved into a clear solution, and a liquid MH medium is obtained.
The rapid drug susceptibility detection method according to claim 9, characterized in that the preparation method of the gel base is: weigh 4g agarose powder, add it to 200ml of MH culture medium, use a sterilizing pot at 0.1mpa Heat to 121°C. After the gel is completely dissolved, take the mixture out of the sterilization pot, transfer it to a microwell plate with a pipette, and let it cool naturally to form a gel base.