CN115678958A - Method for rapidly identifying carbapenem-resistant Klebsiella pneumoniae - Google Patents
Method for rapidly identifying carbapenem-resistant Klebsiella pneumoniae Download PDFInfo
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Abstract
The invention belongs to the technical field of drug-resistant bacteria identification, and particularly relates to a method for rapidly identifying carbapenem-resistant klebsiella pneumoniae, which comprises screening carbapenem-resistant and sensitive carbapenem-resistant klebsiella pneumoniae for library construction, detecting drug-resistant genes of the carbapenem-resistant klebsiella pneumoniae, preparing mass spectrum samples, differentiating protein mass spectrum bands, establishing a protein mass spectrum band differential database of different klebsiella pneumoniae strains, and performing clinical identification by using the established mass spectrum database. The accuracy of identifying the carbapenem-resistant Klebsiella pneumoniae by the mass spectrum is 81.5 percent, the average time for identifying one strain of bacteria is 0.5 minute, and the average identification time for identifying 20 strains of bacteria is 10 minutes.
Description
Technical Field
The invention belongs to the technical field of drug-resistant bacteria identification, and particularly relates to a method for rapidly identifying carbapenem-resistant Klebsiella pneumoniae.
Background
Currently, the emergence of drug-resistant bacteria due to antibiotic abuse is becoming a global and common crisis. The world health organization's data shows that about 70 million people die worldwide each year from antibiotic resistance. It is also estimated by the british committee on the evaluation of antibacterial drugs that by 2050, 1000 million people worldwide will experience antibiotic resistance problems. Aiming at the problem of drug-resistant bacteria, the main problem of world health day in 2017 is to control bacterial drug resistance, no action is taken today, and no drug is available in the next day. Among the 12 major drug-resistant bacteria considered by the world health organization to be urgently needed to develop new antibiotics, the enterobacteriaceae resistant to carbapenem antibiotics including klebsiella pneumoniae, pseudomonas aeruginosa and acinetobacter baumannii are the first group, and the highest degree of urgency for the new antibiotics is required.
Klebsiella pneumoniae (K.pneumoniae: (B))Klebsiella pneumoniae，KPn) is a fermentative gram-negative bacillus, one of the major opportunistic pathogens of hospital acquired infections. Organ transplantation, burns, immune system suppression and patients in intensive care units are all very susceptible to klebsiella pneumoniae, increasing morbidity and mortality. Carbapenem drugs are atypical beta-lactam antibacterial drugs, have strong antibacterial action, are stable to a plurality of beta-lactamases such as Extended Spectrum Beta Lactamase (ESBLs) and continuous high-yield C-type cephalosporinase (AmpC), are one of empirical treatment drugs for serious infection in hospitals, and are gradually increased in clinical application. However, in recent years, the drug resistance of bacteria to the drugs is increased, especially to klebsiella pneumoniae, and carbapenem-resistant klebsiella pneumoniae is popular in many countries. In 2003 to 2017, the drug resistance monitoring result of 13 national education colleges shows that the drug resistance rate of meropenem is increased from 13% to 25%; the drug resistance rate of imipenem is slightly increased and is maintained at 25-30%; there is also a proportion of multidrug resistant klebsiella pneumoniae. According to the Chinese largest drug resistance monitoring network CHINET data, the national carbapenem-resistant Klebsiella pneumoniae (Carbapenem resistant)Klebsiella pneumoniaeCRKP) ratio increased from 0.9% in 2000 to 20168.7 percent. In Henan province, the proportion of carbapenem drug-resistant Klebsiella pneumoniae is 23.2% in 2016 years, and occupies the second province in China. Among the bacteria detected in 2016 year blood culture by the present applicant, klebsiella pneumoniae accounted for position 1.
Recently, many cases of nosocomial infection of Klebsiella pneumoniae with drug resistance and high toxicity have been reported, diffused nosocomial infection of Klebsiella pneumoniae with drug resistance and high toxicity easily occurs in wards with serious patients such as burn wards, ICU and neurosurgery, and high death rate of the serious patients is easily caused if the nosocomial infection is not found and treated in time. Therefore, the method can be used for identifying and diagnosing the pan-drug resistant high-toxicity Klebsiella pneumoniae in time, and has important significance for the clinical reasonable application of antibacterial drugs and the prevention of nosocomial infection outbreak. The traditional microorganism identification method is mainly based on phenotype detection, including gram staining, microorganism culture and biochemical tests, drug sensitivity tests and the like, and usually takes a long time, and at least 72 hours are needed for feeding the results back to clinic.
Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a novel bacteria identification technology developed in recent years, can quickly and accurately identify bacteria within 10 minutes, can also be used for directly identifying some sterile samples such as blood and urine, and greatly shortens the detection time to one hour. The principle is that a detection sample and a matrix solution are mixed or respectively added on a sample target in a point mode, and a cocrystallization of the sample and the matrix is formed after a solvent is volatilized; using laser as an energy source to radiate crystals, enabling a matrix to absorb energy from the laser to desorb a sample, enabling sample molecules to be ionized by charge transfer between the matrix and the sample, and forming a mass spectrum by taking a mass spectrum peak as a vertical coordinate and a mass-to-charge ratio (m/z) as a horizontal coordinate through a flight time detector; and analyzing and comparing by software, screening and determining a specific map, thereby realizing the distinguishing and identification of the target microorganisms. The specific fingerprint spectrum can be formed by MALDI-TOF-MS detection of various bacteria, and the species of the bacteria can be determined by establishing a spectrum library of the bacteria and comparing the mass spectrum of the bacteria to be detected with the spectrum library.
Although mass spectrometry technology and real-time fluorescent quantitative PCR technology are reported at present, carbapenem-resistant Klebsiella pneumoniae of blood culture positive specimens can be rapidly identified within two hours, but the method has the defects of complicated operation steps, high cost and the like, and is not suitable for wide clinical application.
Disclosure of Invention
Aiming at the problems, the invention provides a method for rapidly identifying the carbapenem-resistant Klebsiella pneumoniae, the average time for identifying a strain of bacteria is about 0.5 minute, and the method has better accuracy and more perfect species identification.
In order to solve the problems, the invention is realized by the following technical scheme:
a method for rapidly identifying carbapenem-resistant Klebsiella pneumoniae is designed, and comprises the following steps:
(1) Screening of carbapenem-resistant and sensitive carbapenem Klebsiella pneumoniae for building storehouse
Phenotypic drug resistant or sensitive Klebsiella pneumoniae were identified and screened by conventional drug susceptibility testing (vitek 2 or BD Phonix100 drug sensitive panels), and the screened carbapenem resistant or sensitive Klebsiella pneumoniae (carbapenem resistant and sensitive Klebsiella pneumoniae, CRKP and CSKP) were rechecked using KB (drug sensitive paper) method or E-test method. The Clinical and Laboratory Standards Institute (CLSI) drug susceptibility standard (CLSI-2021-M45) was used to determine whether Klebsiella pneumoniae is resistant to carbapenem drugs such as imipenem and meropenem.
(2) Drug-resistant gene detection of screened carbapenem-resistant Klebsiella pneumoniae
And (3) detecting KPC, IPM, NDM, VIM and OXA carbapenemase resistant genes of the screened CRKP strain by utilizing a PCR technology, and screening the carbapenem-resistant Klebsiella pneumoniae strain with the above drug resistant genes.
(3) Sample preparation
Selecting screened strains (2-3 clone colonies), placing the strains in 300 mu L of sterile water, adding 900 mu L of absolute ethyl alcohol, centrifuging 12000g for 3 minutes, then discarding the supernatant, adding 20 mu L of formic acid, vortexing and shaking for 3 minutes, then adding 20 mu L of acetonitrile, placing for 3 minutes, centrifuging 12000g for 3 minutes, then taking 1 mu L of the supernatant to evenly spot the target, drying at room temperature, then covering with 1 mu L of matrix (HCCA), naturally drying at room temperature, and then using for mass spectrometry detection. 3 target sites were prepared per sample.
(4) Comparing the difference of the bands of the protein mass spectrum of the carbapenem-resistant Klebsiella pneumoniae and the sensitive carbapenem-resistant Klebsiella pneumoniae
The mass spectrum data of the sample is collected by using an ampere chart automs1000 mass spectrometer and Flex Control software. Selecting a positive ion linear operation mode, wherein the mass range is 2000-20000, adopting 3 images for each target position, and bombarding the laser for 100 times. The 9 maps obtained for each sample were opened in a flex analysis, the low quality maps were removed, and at least 6 valid maps were retained.
Before data acquisition each time, a calibrator is used for mass correction, mass spectrometry of protein bands is carried out on carbapenem-resistant and sensitive carbapenem Klebsiella pneumoniae strains and various genotypes, and a differential protein mass spectrometry band with obvious specificity is searched.
(5) Establishing a protein mass spectrum band difference database of different Klebsiella pneumoniae strains
The effective spectrum of the same strain is created as the predicted spectrum (MSP) of the strain by using a conventional self-database building method, and the database is built by using the collected predicted spectrum of 916 strains.
(6) Clinical identification with established mass spectral database
Firstly, acquiring mass spectrum data of a strain to be detected (by using Flex Control software); and then selecting a built standard database by a Biotyper MSP Identification standard method in MALDI Biotyper 3 software, and calling mass spectrum data of the strain to be detected for matching Identification.
The identification result takes the logarithmic value from 0 to 10 as a judgment score, the score is less than or equal to 2.999, the color is red, and the identification is not identified; the score is 3.000-4.999, is yellow and represents possible identification of the genus name; the score is 5.000-7.000, is green and represents the reliable generic name and possible species name; the scores ranged from 7.001 to 10.000, and were green, indicating highly reliable seed names. Taking the highest score as the identification result of the 3-time repetition values of each strain to be detected.
The invention has the following positive and beneficial effects:
the invention takes phenotype screening as a gold standard, screens carbapenem-resistant and sensitive carbapenem Klebsiella pneumoniae and various genotypes, and constructs a database through specific differential protein mass spectrum bands. The accuracy of identifying the carbapenem-resistant Klebsiella pneumoniae by mass spectrometry is 81.5%, the average time for identifying one strain of bacteria is 0.5 min, and the average identification time for identifying 20 strains of bacteria is 10 min.
Drawings
FIG. 1 shows PCR electrophoretogram of carbapenem-resistant drug gene screening of Klebsiella pneumoniae;
FIG. 2 is a graph of the difference peaks of the mass spectra of carbapenem-resistant Klebsiella pneumoniae and sensitive Klebsiella pneumoniae.
Detailed Description
The present invention will be described in further detail with reference to specific examples, but the embodiments of the present invention are not limited thereto. The reagents used in the examples are, unless otherwise specified, commercially available reagents or starting materials, and the test methods used are, unless otherwise specified, conventional in the art.
Example 1
A method for rapidly identifying carbapenem-resistant Klebsiella pneumoniae comprises the following steps:
(1) Screening of carbapenem-resistant and sensitive carbapenem Klebsiella pneumoniae
The applicant hospital establishes a microorganism alliance which is participated in 150 hospitals in cities in regions and places in Henan province, has sufficient Klebsiella pneumoniae strains, and screens 916 Klebsiella pneumoniae strains which are separated from drug-resistant candidate research strains. 313 CRKP and 603 CSKP were obtained by screening using a conventional drug susceptibility test.
Screening a drug susceptibility phenotype test of klebsiella pneumoniae, which judges the sensitivity or drug resistance of bacteria according to the minimum inhibitory concentration of bacteria to imipenem or meropenem according to a break point established by the drug susceptibility judgment standard (CLSI-2021-M45) of the american Clinical and Laboratory Standards Institute (CLSI), and commercially available automatic laths and automatic instruments manufactured by the american BD company or the french merley company are currently available;
(2) Carbapenem drug-resistant gene detection
The 313 CRKP is subjected to the detection of all drug-resistant genes KPC, IPM, NDM, VIM and OXA of Klebsiella pneumoniae by using a PCR technology (see figure 1), and Klebsiella pneumoniae strains with various drug-resistant genes are screened.
Extracting the genome DNA of the CRKP strain by using a bacterial genome extraction kit, and amplifying various drug-resistant genes KPC, IPM, NDM, VIM and OXA of the CRKP by using the genome DNA as a template to obtain various drug-resistant genotypes of the CRKP. Reference is made to Ellington MJ, findlay J, hopkins KL, meuner D, alvarez-Buyla A, horner C, et al, M μ Ltic evaluation of a real-time PCR assay to detect genes encoding clinical reagents in C μ Ldetailed bacteria.Int J Antimicrob Agents 2016; 47(2): 151-4。
Primer sequence and annealing temperature
(3) Sample preparation
Selecting screened strains (2-3 clone colonies), placing in 300 mu L of sterile water, adding 900 mu L of absolute ethyl alcohol, centrifuging at 12000g for 3 minutes, then discarding the supernatant, adding 20 mu L of formic acid, vortex, shaking for 3 minutes, then adding 20 mu L of acetonitrile, placing for 3 minutes, centrifuging at 12000g for 3 minutes, then taking 1 mu L of supernatant to evenly spot the target, drying at room temperature, then covering with 1 mu L of matrix (HCCA), naturally drying at room temperature, and then using for mass spectrum detection. 3 target sites were prepared per sample.
(4) Comparing the difference of the bands of the protein mass spectrum of the carbapenem-resistant Klebsiella pneumoniae and the sensitive carbapenem-resistant Klebsiella pneumoniae
The mass spectrum data of the sample is collected by using an ampere chart automs1000 mass spectrometer and Flex Control software. Selecting a positive ion linear operation mode, wherein the mass range is 2000-20000, adopting 3 images for each target position, and bombarding the laser for 100 times. The 9 maps obtained for each sample were opened in a flex analysis, the low quality maps were removed, and the 6 valid maps were retained.
Before data acquisition each time, a calibrator is used for mass correction, mass spectrometry of protein bands is carried out on carbapenem-resistant and sensitive carbapenem Klebsiella pneumoniae strains and various genotypes, and a differential protein mass spectrometry band with obvious specificity is searched.
(5) Mass spectrum self-building database
Since the original german brueck mass spectrometer does not have a database of CRKP and CSKP, CRKP and CSKP cannot be identified. The applicant constructed a database using the self-library construction method of an Ancharian instrument, in which 6 effective spectra of the same strain were created as a Main Spectral Projection (MSP) of the strain, and the collected predicted spectra of 313 drug-resistant strains and 603 sensitive strains were used.
(6) Clinical identification with established mass spectral database
Firstly, acquiring mass spectrum data of a strain to be detected (by using Flex Control software); and then selecting a built standard database by a Biotyper MSP Identification standard method in MALDI Biotyper 3 software, and calling mass spectrum data of the strain to be detected for matching Identification.
The identification result takes the logarithmic value of 0 to 10 as a judgment score, the score is less than or equal to 2.999, the color is red, and the identification is not identified; the score is 3.000-4.999, is yellow and represents possible genus name identification; the score is 5.000-7.000, is green, and represents the reliable generic name and possible species name; the score was 7.001-10.000, green, indicating a highly reliable seed name. Taking the highest score as the identification result of the 3-time repetition value of each strain to be detected.
The mass spectrum peak graphs of 110 CRKP strains and 106 CSKP strains screened by the prior phenotype and genotype are analyzed by utilizing an extraction method and a mass spectrum technology, a differential peak graph library of the CRKP and the CSKP is established, the differential peak graphs of the two Klebsiella pneumoniae strains are concentrated at 4179, 4519, 4734 and 5141 m/z, as shown in figure 2, the accuracy after the identification by the invention is 81.5 percent, the average time for identifying one strain of bacteria is 0.5 minute, and the average identification time for identifying 20 strains of bacteria is 10 minutes.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof.
Claims (8)
1. A method for rapidly identifying carbapenem-resistant Klebsiella pneumoniae is characterized by comprising the following steps: the method comprises the following steps:
(1) Screening of carbapenem-resistant and sensitive carbapenem Klebsiella pneumoniae for building storehouse
Identifying and screening phenotype drug-resistant or sensitive Klebsiella pneumoniae through a drug susceptibility test, and rechecking the screened carbapenem-resistant or sensitive carbapenem Klebsiella pneumoniae;
(2) Drug-resistant gene detection of screened carbapenem-resistant Klebsiella pneumoniae
Detecting KPC, IPM, NDM, VIM and OXA carbapenemase resistant genes of the screened carbapenem resistant Klebsiella pneumoniae strain by utilizing a PCR technology, and screening the carbapenem resistant Klebsiella pneumoniae strain with the drug resistant genes;
(3) Mass Spectrometry sample preparation
Selecting the screened strains, preparing mass spectrum samples for mass spectrum detection, and preparing at least 3 target positions for each sample;
(4) Comparing the difference of the bands of the protein mass spectrum of the carbapenem-resistant Klebsiella pneumoniae and the sensitive carbapenem-resistant Klebsiella pneumoniae
Collecting mass spectrum data of a sample by using a mass spectrometer; carrying out mass spectrum analysis of protein bands on carbapenem-resistant and sensitive carbapenem Klebsiella pneumoniae strains and various genotypes, and searching for differential protein mass spectrum bands with obvious specificity;
(5) Establishing a protein mass spectrum band difference database of different Klebsiella pneumoniae strains
Establishing an effective spectrum of the same strain as a predicted spectrum of the strain by adopting a conventional self-library establishment method;
(6) Clinical identification using established mass spectrometry databases
Firstly, acquiring mass spectrum data of a strain to be detected; and then selecting the established standard database, and calling mass spectrum data of the strain to be detected for matching identification.
2. The method of claim 1, wherein: the drug sensitivity test in the step (1) is carried out by adopting a vitek 2 or BD Phonix100 drug sensitivity strip; the rechecking is carried out by adopting a drug sensitive paper sheet method or an E-test method.
3. The method of claim 1, wherein: the mass spectrum sample in the step (3) is prepared by the following method: placing the strain in sterile water, adding a proper amount of absolute ethyl alcohol, centrifuging, removing supernatant, adding a proper amount of formic acid, adding a proper amount of acetonitrile after vortex oscillation, placing, centrifuging, taking a proper amount of supernatant, uniformly spotting a target, drying at room temperature, covering with a proper amount of matrix, and naturally drying at room temperature.
4. The method of claim 1, wherein: selecting a positive ion linear operation mode in the step (4) to acquire mass spectrum data, wherein the mass range is 2000-20000, each target position acquisition image is at least 3, and each image bombards laser for at least 100 times; and removing the low quality from the obtained pattern of each sample, and retaining at least 6 effective patterns.
5. The method of claim 1, wherein: and (5) performing quality correction by using a calibrator before data acquisition in the step (4).
6. The method of claim 1, wherein: in the step (6), the matching Identification is carried out by using a Biotyper MSP Identification standard method in MALDI Biotyper 3 software.
7. The method of claim 1, wherein: in the identification result in the step (6), the logarithmic value from 0 to 10 is used as a judgment score, the score is less than or equal to 2.999, the color is red, and the result shows that the identification is not carried out; the score is 3.000-4.999, is yellow and represents possible genus name identification; the score is 5.000-7.000, is green and represents the reliable generic name and possible species name; the scores ranged from 7.001 to 10.000, and were green, indicating highly reliable seed names.
8. The method of claim 1, wherein: and (6) taking the highest score of the repeated values of each strain to be tested as an identification result.
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| CN117612747A (en) * | 2024-01-24 | 2024-02-27 | 杭州广科安德生物科技有限公司 | Drug sensitivity prediction method and device for klebsiella pneumoniae |
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| CN117612747A (en) * | 2024-01-24 | 2024-02-27 | 杭州广科安德生物科技有限公司 | Drug sensitivity prediction method and device for klebsiella pneumoniae |
| CN117612747B (en) * | 2024-01-24 | 2024-05-03 | 杭州广科安德生物科技有限公司 | Drug sensitivity prediction method and device for klebsiella pneumoniae |
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