A system and method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin

Abstract

The present invention, "A system and method for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin", belongs to the field of bioinformatics technology. The system includes: a calculation unit; the calculation unit includes: a computer-readable storage medium, on which a computer program is stored; when the computer program is executed by a processor, it implements an Exp(-k) power value calculation method; the Exp(-k) power value calculation method is calculated according to the following calculation steps: S1: Calculate the k value according to the following formula I: Formula I: S2: Obtain the Exp(-k) power value with the natural constant e as the base and -k as the exponent; wherein, C1-C6 are the copy numbers of the rmtB, AAC(6')-Ib-cr6, KPC-1, APH(3")-Ib, FosA5, and SHV-25 genes in the Klebsiella pneumoniae strain to be predicted respectively. The accuracy rate of predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin using the prediction method and prediction system of the present invention is about 92.5%.

Description

Technical Field

[0001] The present invention belongs to the field of bioinformatics technology, and particularly relates to a system and method for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin. Background Art

[0002] Antibiotic drugs used to be a "secret weapon" for humans to combat many diseases. In the late 19th and early 20th centuries, due to the discovery of a series of antibiotics, the human lifespan was greatly increased. In recent years, with the continuous application of antibiotics, the situation of drug abuse has gradually emerged, leading to an increasing number of clinical antibiotic resistances and adverse reactions, imposing a heavy burden on the global economy. Effectively controlling the abuse of antibiotics in medical treatment is an important link in addressing the global antibiotic resistance problem.

[0003] Pathogenic microorganisms refer to microorganisms that can invade the human body, cause infections and even infectious diseases, or are called pathogens. They mainly include bacteria, viruses, fungi, parasites, mycoplasmas, chlamydias, rickettsias, spirochetes, etc. There is a wide variety of microbial species. Intestinal samples include feces, mucosa, etc., liquid samples include urine, blood, cerebrospinal fluid, saliva, sputum, bronchoalveolar lavage fluid, amniotic fluid, etc., swab samples include the oral cavity, reproductive tract, skin, etc., and others include tissues, liver, eyes, placenta, etc.

[0004] The Latin name of the genus Klebsiella is Klebsiella Trevisan, and its systematic classification level is genus. It is a straight bacillus with a diameter of 0.3 - 1.0 μm and a length of 0.6 - 6.0 μm. It is arranged singly, in pairs or in short chains. The species (strains) of this genus that have been reported so far include: Klebsiella pneumoniae, Klebsiella aerogenes, Klebsiella oxytoca, Klebsiella quasipneumoniae, Klebsiella variicola, Klebsiella michiganensis, etc.

[0005] Among them, Klebsiella pneumoniae, as the type strain of the genus Klebsiella, is widely present in the environment and is likely to colonize the respiratory tract and intestines of patients, causing common opportunistic pathogens for multi-site infections such as the digestive tract, respiratory tract, and blood. It is one of the pathogenic bacteria causing human pneumonia and one of the common drug-resistant bacteria in hospitals. According to the research of the Second Military Medical University, the drug resistance rate of carbapenem-resistant Klebsiella pneumoniae isolated from 2014 to 2017 to ciprofloxacin was 62.5% (252 / 403).

[0006] Ciprofloxacin is a second-generation broad-spectrum fluoroquinolone antibiotic that can fight against a variety of pathogenic bacteria. The treatment scope includes bone infections, joint infections, abdominal infections, as well as specific types of infectious gastroenteritis, respiratory tract infections, skin infections, typhoid fever, and urinary tract infections, etc.

[0007] Bacterial drug susceptibility testing is the most commonly used method for detecting bacterial drug resistance in domestic and foreign clinics and laboratories at present. There are methods such as the disk diffusion method, agar dilution method, broth dilution method, and gradient method. Among them, except for the disk diffusion method, the other methods can obtain relatively accurate minimum inhibitory concentration (MIC) of drugs. Bacterial drug susceptibility testing first requires obtaining pure cultures, which is not applicable to difficult-to-culture and non-culturable bacteria, and it takes a long time. Sometimes it is difficult to meet the needs of rapid diagnosis and symptomatic treatment of current clinical severe and acute infections. The traditional detection and identification methods of pathogenic microorganisms fail to meet the comprehensive requirements of wide coverage, rapidity, and accuracy. The diagnosis and treatment of infectious diseases mainly rely on empirical and directional methods. Clinicians and patients urgently need innovative detection methods to more comprehensively, accurately, and rapidly identify infectious pathogens, assist in diagnosis and rational and standardized drug treatment, shorten the course of treatment, reduce the mortality rate, and reduce medical costs.

[0008] With the popularization of emerging technologies such as PCR technology, whole-genome sequencing technology, microfluidic technology, and VITEK-2compact fully automatic bacterial identification / susceptibility system, the exploration of new technologies for detecting bacterial drug resistance has gradually deepened, and various new methods for detecting bacterial drug resistance have become increasingly mature. Although the VITEK-2compact fully automatic bacterial identification / susceptibility system is simple and rapid, its accuracy of identifying / susceptibility evaluation of strains is affected by the sample status and the culture conditions of the strains, and its use cost is relatively high.

[0009] Therefore, there is an urgent need in this field to develop a method and system that can quickly and accurately predict the sensitivity of Klebsiella pneumoniae strains to ciprofloxacin at a relatively low cost. Summary of the Invention

[0010] In view of the above deficiencies and requirements in the existing technologies in this field, the present invention aims to provide a system and method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin.

[0011] The technical solution of the present invention is as follows:

[0012] A system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin is provided with: a calculation unit; the calculation unit includes: a computer-readable storage medium on which a computer program is stored; when the computer program is executed by a processor, it implements a method for calculating the Exp(-k) power value; the method for calculating the Exp(-k) power value includes the following calculation steps:

[0013] S1: Calculate the k value according to the following formula I:

[0014] Formula I:

[0015] S2: Obtain the Exp(-k) power value with the natural constant e as the base and -k as the exponent;

[0016] In Formula I:

[0017] C1 is the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted,

[0018] C2 is the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted,

[0019] C3 is the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted,

[0020] C4 is the copy number of the APH(3”)-Ib gene in the Klebsiella pneumoniae strain to be predicted,

[0021] C5 is the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted,

[0022] C6 is the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted.

[0023] The system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin is further provided with: a result output unit; the calculation unit transmits the calculated Exp(-k) power value to the result output unit, and the result output unit identifies the Exp(-k) power value and outputs the result;

[0024] Preferably, the natural constant e = 2.718281828459045.

[0025] When the result output unit identifies that the Exp(-k) power value < 1, it outputs the drug resistance result R;

[0026] The result output unit identifies and outputs the sensitive result S when the Exp(-k) power value ≥ 1;

[0027] The result output unit and the calculation unit are connected by a data path, and the Exp(-k) power value calculated by the calculation unit is transported to the result output unit through the data path;

[0028] Preferably, the sensitive result S refers to the susceptibility of Klebsiella pneumoniae to ciprofloxacin to be predicted; the drug resistance result R refers to the resistance of Klebsiella pneumoniae to ciprofloxacin to be predicted.

[0029] The described system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin is further provided with: an experimental unit and a data input unit;

[0030] The experimental unit and the data input unit are connected by a data path; the experimental unit outputs the experimental results, transports them to the data input unit through the data path and converts them into independent variable data;

[0031] The data input unit and the calculation unit are connected by a data path; the independent variable data is transported to the calculation unit through the data path.

[0032] The independent variable data includes: the numerical values of C1, C2, C3, C4, C5, and C6;

[0033] Preferably, the experimental results include: the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the APH(3”)-Ib gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted, and the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted.

[0034] A method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin, characterized by including:

[0035] S1: Calculate the k value according to the following formula I:

[0036] Formula I:

[0037] S2: Obtain the Exp(-k) power value with the natural constant e as the base and -k as the exponent;

[0038] In formula I:

[0039] C1 is the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted,

[0040] C2 is the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted,

[0041] C3 is the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted,

[0042] C4 is the copy number of the APH(3”)-Ib gene in the Klebsiella pneumoniae strain to be predicted,

[0043] C5 is the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted,

[0044] C6 is the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted;

[0045] The predicted result corresponding to the Exp(-k) power value < 1 is that Klebsiella pneumoniae is resistant to ciprofloxacin, and the predicted result corresponding to the Exp(-k) power value ≥ 1 is that Klebsiella pneumoniae is sensitive to ciprofloxacin.

[0046] The natural constant e = 2.718281828459045;

[0047] The copy numbers of the rmtB, AAC(6')-Ib-cr6, KPC-1, APH(3”)-Ib, FosA5, and SHV-25 genes in the Klebsiella pneumoniae strain to be predicted are obtained by the second-generation high-throughput sequencing method.

[0048]

[0049] Preferably, the genomic contigs are the longest contigs fragments obtained by assembling the sequencing results using the SPAdes v3.13.0 assembly software;

[0050] The depth of the genomic contigs is the depth of the genomic contigs calculated by the SPAdes v3.13.0 assembly software;

[0051] The depth of the contigs where the gene is located refers to the sum of the depths of the gene on each contig with a copy of the gene;

[0052] Preferably, each contig with a copy of the gene is annotated by aligning the cds and protein sequences of the gene to the CARD database using the blat (v.36) software and the diamond (v2.0.4.142) software;

[0053] Preferably, the depth of the gene on each contig with a copy of the gene is calculated by the SPAdes v3.13.0 assembly software.

[0054] The beneficial effects of the present invention are as follows:

[0055] Based on the prediction system and prediction method of the present invention, the obtained microbial samples can be subjected to conventional processing, and then necessary steps of sequencing such as DNA extraction can be performed. After bioinformatics process analysis, the state of the relevant features of the Klebsiella pneumoniae prediction system in the sample can be obtained, and the drug sensitivity of the sample can be predicted by importing the feature state information into the system. Compared with traditional methods, it has the advantages of simple operation, short detection time, and accurate species identification.

[0056] In order to effectively judge the performance of a prediction system, a set of data that is not involved in the establishment of the prediction system is required, and the accuracy of the prediction system is evaluated on this data set. This set of independent data sets is called a test set. The system prediction effect evaluation methods include F1-score, precision, recall and confusion matrix.

[0057] The method of the present invention also has the following advantages:

[0058] The present invention uses a test set to evaluate the accuracy of the system. The average accuracy of the method is 0.925, the F1-score is 0.925, and the recall score is 0.956. On the one hand, the present invention is less affected by subjective factors such as operators and has good detection stability; on the other hand, it can achieve rapid and accurate identification of infectious pathogens and predict the drug sensitivity of the sample to be tested, assist in diagnosis and reasonable and standardized drug treatment, and has high throughput, reducing medical costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A schematic diagram of the structure of a drug resistance prediction system provided for some embodiments of the present invention (within the dotted box) and its workflow diagram.

[0060] Figure 2 A schematic structural diagram (within the dotted box) and a workflow diagram of a drug resistance prediction system provided for other embodiments of the present invention. DETAILED DESCRIPTION

[0061] In order to facilitate the understanding of the present invention, the present invention will be described more comprehensively in the following examples.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0063] Unless otherwise specified, the reagents used in the following examples are commercially available.

[0064] Source of biomaterials

[0065] The 93 samples used in the experimental examples of the present invention are pure cultures of Klebsiella pneumoniae isolated from clinical blood cultures and are from Peking Union Medical College Hospital, Chinese Academy of Medical Sciences.

[0066] All the tested bacterial strains were identified as Klebsiella by MALDI-TOF MS (scientific name: Genus Klebsiella, Latin name: Klebsiella Trevisan, systematic classification level: Genus).

[0067] On the Illumina Novaseq NGS sequencing platform, these strains include 69 cases of Klebsiella pneumoniae, 11 cases of Klebsiella aerogenes, 4 cases of Klebsiella oxytoca, 4 cases of Klebsiella quasipneumoniae, 3 cases of Klebsiella variicola, and 2 cases of Klebsiella michiganensis, all of which are reported species or strains of the genus Klebsiella.

[0068] The above-mentioned species or strains can be obtained from common cases of Klebsiella pneumoniae pneumonia or from the applicant's laboratory. The applicant undertakes to distribute the strains to the public within 20 years from the filing date of the present invention for verifying the technical effects of the present invention.

[0069] Group 1 Examples, the drug resistance prediction system of the present invention

[0070] This group of examples provides a system for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin. All examples in this group have the following common features: As Figure 1 and Figure 2 shown, the system for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin is provided with: a calculation unit; the calculation unit includes: a computer-readable storage medium on which a computer program is stored; characterized in that when the computer program is executed by a processor, it implements an Exp(-k) power value calculation method; the Exp(-k) power value calculation method is calculated according to the following calculation steps:

[0071] S1: Calculate the k value according to the following formula I:

[0072] Formula I:

[0073] S2: Obtain the value of Exp(-k) with the base of the natural constant e and the exponent of -k;

[0074] In Formula I:

[0075] C1 is the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted;

[0076] C2 is the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted;

[0077] C3 is the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted;

[0078] C4 is the copy number of the APH(3”)-Ib gene in the Klebsiella pneumoniae strain to be predicted;

[0079] C5 is the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted;

[0080] C6 is the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted.

[0081] In some embodiments of the present invention, the value of the natural constant e is 2.718281828459045.

[0082] In more specific embodiments, the above genes are all genes reported in the art, specifically as follows:

[0083] The rmtB gene is the rmtB gene described in the article "Evolution and Comparative Genomics of F33:A-:B-Plasmids Carrying blaCTX-M-55 or blaCTX-M-65 in Escherichia coli and Klebsiella pneumoniae Isolated from Animals, Food Products, and Humans in China".

[0084] The AAC(6')-Ib-cr6 gene is the AAC(6')-Ib-cr6 gene described in the article "Genomic Analysis of Multidrug-Resistant Hypervirulent (Hypermucoviscous) Klebsiella pneumoniae Strain Lacking the Hypermucoviscous Regulators (rmpA / rmpA2)".

[0085] The KPC-1 gene is the KPC-1 gene described in the article "Novel Carbapenem-Hydrolyzing b-Lactamase, KPC-1, from a Carbapenem-Resistant Strain of Klebsiella pneumoniae".

[0086] The APH(3”)-Ib gene is the APH(3”)-Ib gene described in the article "Whole genome sequencing of Klebsiella pneumoniae clinical isolates sequence type 627 isolated from Egyptian patients".

[0087] The FosA5 gene is the FosA5 gene described in the article "Prevalence of fosfomycin resistance and plasmid-mediated fosfomycin-modifying enzymes among carbapenem-resistant Enterobacteriaceae in Zhejiang, China".

[0088] The SHV-25 gene is the SHV-25 gene described in the article "Diversity of SHV and TEMβ-Lactamases in Klebsiella pneumoniae: Gene Evolution in Northern Taiwan and Two Novel β-Lactamases, SHV-25 and SHV-26".

[0089] In a further embodiment, as Figure 1 and Figure 2 shown, the system for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin is further provided with: a result output unit; the result output unit outputs a sensitive result or a drug-resistant result; the sensitive result means that the Klebsiella pneumoniae to be predicted is sensitive to ciprofloxacin; the drug-resistant result means that the Klebsiella pneumoniae to be predicted is resistant to ciprofloxacin;

[0090] When the Exp(-k) power value < 1, the result output unit outputs a drug-resistant result R;

[0091] When the Exp(-k) power value ≥ 1, the result output unit outputs a sensitive result S;

[0092] Preferably, the result output unit and the calculation unit are connected by a data path;

[0093] Preferably, the Exp(-k) power value calculated by the calculation unit is transmitted to the result output unit through the data path.

[0094] In a further embodiment, as Figure 1 shown, the system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin further includes: an experimental unit and a data input unit;

[0095] The experimental unit and the data input unit are connected by a data path; the experimental results output by the experimental unit are transmitted to the data input unit through the data path and converted into independent variable data;

[0096] The data input unit and the calculation unit are connected by a data path; the independent variable data is transmitted to the calculation unit through the data path;

[0097] In a more specific embodiment, the data path is a data transmission carrier well-known to those skilled in the computer field and the electronic field. The data path is selected from a wired form or a wireless form. For example, it can be a wired path, a line, or a wireless path, a wifi connection, a wireless channel, etc.

[0098] Preferably, the independent variable data includes: the values of C1, C2, C3, C4, C5, and C6;

[0099] Preferably, the experimental results include: the copy numbers of the rmtB, AAC(6')-Ib-cr6, KPC-1, APH(3”)-Ib, FosA5, and SHV-25 genes in the Klebsiella pneumoniae strain to be predicted, respectively.

[0100] The copy numbers of known genes in known strains can be routinely obtained by those skilled in the fields of molecular biology and bioinformatics through conventional technical means (such as sequencing and bioinformatics analysis). The rmtB, AAC(6')-Ib-cr6, KPC-1, APH(3”)-Ib, FosA5, and SHV-25 genes involved in the experimental results output by the prediction system of the present invention are all genes reported in the art, and their gene information and primary structure sequences can be queried through the NCBI website or other known bioinformatics databases. The copy numbers of each of the above genes in the Klebsiella pneumoniae strain to be predicted can be obtained by performing whole-genome sequencing on the strain.

[0101] In some other specific embodiments, the copy numbers of the rmtB, AAC(6')-Ib-cr6, KPC-1, APH(3”)-Ib, FosA5, and SHV-25 genes in the Klebsiella pneumoniae strain to be predicted are obtained by the second-generation high-throughput sequencing method.

[0102] In more specific embodiments,

[0103]

[0104] Preferably, the genomic contigs are the longest contig fragments obtained by assembling the sequencing results using the SPAdes v3.13.0 assembly software;

[0105] The depth of the genomic contigs is the depth of the genomic contigs calculated by the SPAdes v3.13.0 assembly software;

[0106] The depth of the contigs where the gene is located refers to the sum of the depths of the gene on each contig having a copy of the gene;

[0107] Preferably, each contig having a copy of the gene is annotated by aligning the cds and protein sequences of the gene against the CARD database using the blat (v.36) software and the diamond (v2.0.4.142) software;

[0108] Preferably, the depth of the gene on each contig having a copy of the gene is obtained by calculating using the SPAdes v3.13.0 assembly software.

[0109] The second-generation high-throughput sequencing method has the conventional technical meaning well-known to those skilled in the art, and obtaining the gene copy number by using the second-generation high-throughput sequencing method is a conventional technical means well-known to those skilled in the art.

[0110] In some specific embodiments, the specific method for calculating the gene copy number is as follows:

[0111] The strain is sequenced using the second-generation high-throughput sequencing method. The average sequencing depth is about 150x, and the approximate sequencing amount for Klebsiella pneumoniae is about 1G. Using the depth of the contigs calculated during the assembly process by the SPAdes (v3.13.0) assembly software as the standard, the longest contig fragment is defined as the genomic fragment, and the prokka software (1.14.6) is used to predict genes on the contigs to obtain all gene cds and protein sequences on the contigs. The blat (v.36) software and the diamond (v2.0.4.142) software are respectively used to align the cds and protein sequences against the CARD database, and the sequences with a similarity greater than 90% are positive sequences to obtain the annotation results of all drug-resistant genes. The copy number of all genes on the contigs is calculated according to formula II as follows:

[0112] Formula II:

[0113] If a gene has two or more genomic copies on different contigs or on the same contig, the final gene copy number is equal to the sum of all calculated copy numbers of the gene. An example of the calculation method is as follows:

[0114] Assume that the KPC-1 gene has only one copy on all contigs, then the copy number of the KPC-1 gene is:

[0115]

[0116] Assume that the KPC-1 gene has 2 copies on one contig and no copies on other contigs, then the copy number of the KPC-1 gene is:

[0117]

[0118] Assume that the KPC-1 gene has 1 copy on one contig1 and contig2 and no copies on other contigs, then the copy number of the KPC-1 gene is:

[0119]

[0120] In a more specific embodiment, the result output unit, the experimental unit, and the data input unit are all provided with computer-readable storage media, on which computer programs are stored.

[0121] In some embodiments, when the computer program on the computer-readable storage medium of the result output unit is executed by a processor, it implements a method for comparing the magnitude of the Exp(-k) power value with 1 and outputs the result;

[0122] The method for comparing the magnitude of the Exp(-k) power value with 1 and outputting the result means:

[0123] When the Exp(-k) power value < 1, the result output unit outputs the drug resistance result R;

[0124] When the Exp(-k) power value ≥ 1, the result output unit outputs the sensitive result S.

[0125] In some other embodiments, when the computer program on the computer-readable storage medium of the experimental unit is executed by a processor, it implements a method for calculating gene copy number;

[0126] The method for calculating a gene copy number is a conventional technical means well-known to those skilled in the art, and is specifically calculated according to the following steps:

[0127] S1: Obtain the genomic contigs by taking the maximum value of the depths of the genomic contigs calculated by the SPAdes v3.13.0 assembly software.

[0128] S2: Use the blat (v.36) software and the diamond (v2.0.4.142) software to align the cds and protein sequences of a certain gene with the CARD database and annotate to obtain each contig with a copy of this gene.

[0129] S3: The SPAdes v3.13.0 assembly software calculates the depth of this gene on each contig with a copy of this gene.

[0130] S4: Obtain the sum of the depths of this gene on each contig with a copy of this gene to get the depth of the contig where the gene is located.

[0131] S5: Calculate the copy number of this gene according to the following formula:

[0132]

[0133] In some embodiments, when the computer program on the computer-readable storage medium of the data input unit is executed by the processor, it realizes the dimensionless processing of the copy number of the gene.

[0134] The dimensionless processing means: removing the data dimension or data unit of the copy number of the gene to obtain a dimensionless value, that is, the independent variable data. Generally, the data dimension or data unit of the copy number of the gene is: copy, piece or copies.

[0135] In some other embodiments, as Figure 2 shown, the system for predicting the sensitivity of Klebsiella to ciprofloxacin may not be provided with a data input unit. The experimental unit is directly connected to the calculation unit through the data path, so that the copy number of the gene or the independent variable data calculated by the experimental unit can be directly input into the calculation unit for the calculation of the Exp(-k) power value.

[0136] Group 2 embodiments, the method for predicting the ciprofloxacin resistance of Klebsiella pneumoniae of the present invention

[0137] This group of embodiments provides a method for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin. This group of embodiments has the following common features: The method includes the following steps:

[0138] S1: Calculate the k value according to the following formula I:

[0139] Formula I:

[0140] S2: Obtain the power value of Exp(-k) with the natural constant e as the base and -k as the exponent;

[0141] In Formula I:

[0142] C1 is the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted;

[0143] C2 is the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted;

[0144] C3 is the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted;

[0145] C4 is the copy number of the APH(3”)-Ib gene in the Klebsiella pneumoniae strain to be predicted;

[0146] C5 is the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted;

[0147] C6 is the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted.

[0148] The predicted result corresponding to the Exp(-k) power value < 1 is that Klebsiella pneumoniae is resistant to ciprofloxacin, and the predicted result corresponding to the Exp(-k) power value ≥ 1 is that Klebsiella pneumoniae is sensitive to ciprofloxacin.

[0149] In the above Formula I, e, as a mathematical constant, is the base of the natural logarithm function, also known as the natural constant, natural base, or Euler's number. It is an infinite non-repeating decimal with the conventional technical meaning commonly understood by those of ordinary skill in the mathematical field, and its value is approximately: e = 2.71828182845904523536...

[0150] In some embodiments of the present invention, the value of the natural constant e is 2.718281828459045.

[0151] In some specific embodiments, the copy numbers of the rmtB, AAC(6')-Ib-cr6, KPC-1, APH(3”)-Ib, FosA5, and SHV-25 genes in the Klebsiella pneumoniae strain to be predicted are obtained by the next-generation high-throughput sequencing method.

[0152] In more specific embodiments,

[0153]

[0154] Preferably, the genomic contigs are the longest contigs fragments obtained by assembling the sequencing results with the SPAdes v3.13.0 assembly software;

[0155] The depth of the genomic contigs is the depth of the genomic contigs calculated by the SPAdes v3.13.0 assembly software;

[0156] The depth of the contigs where the gene is located refers to the sum of the depths of the gene on each contig having a copy of the gene;

[0157] Preferably, each contig having a copy of the gene is obtained by annotating the cds and protein sequences of the gene against the CARD database using the blat (v.36) software and the diamond (v2.0.4.142) software;

[0158] Preferably, the depth of the gene on each contig having a copy of the gene is obtained by calculation using the SPAdes v3.13.0 assembly software.

[0159] The second-generation high-throughput sequencing method has the conventional technical meaning well-known to those skilled in the art, and obtaining the gene copy number by using the second-generation high-throughput sequencing method is a conventional technical means well-known to those skilled in the art.

[0160] In some specific embodiments, the specific method for calculating the gene copy number is as follows:

[0161] Use the second-generation high-throughput sequencing method to sequence the strain. The average sequencing depth is about 150x, and the approximate sequencing volume for Klebsiella pneumoniae is about 1G. Using the depth of the contigs obtained by calculation during the assembly process by the SPAdes (v3.13.0) assembly software as the standard, define the longest contig fragment as the genomic fragment, use the prokka software (1.14.6) to predict genes on the contigs, obtain all gene cds and protein sequences on the contigs, and use the blat (v.36) software and the diamond (v2.0.4.142) software to align the cds and protein sequences against the CARD database respectively. Sequences with a similarity greater than 90% are positive sequences, and obtain the annotation results of all drug-resistant genes. The copy number of all genes on the contigs is calculated according to formula II as follows:

[0162] Formula II:

[0163] If a gene has two or more genomic copies on different contigs or the same contig, the final gene copy number is equal to the sum of all calculated copy numbers of the gene. The calculation method example is as follows:

[0164] Assume that the KPC-1 gene has only one copy on all contigs, then the copy number of the KPC-1 gene is:

[0165]

[0166] Assume that the KPC-1 gene has 2 copies on one contig and no copies on other contigs. Then the copy number of the KPC-1 gene is:

[0167]

[0168] Assume that the KPC-1 gene has 1 copy on contig1 and contig2 and no copies on other contigs. Then the copy number of the KPC-1 gene is:

[0169]

[0170] Experimental Example, Performance Evaluation of the Prediction System and Prediction Method of the Present Invention

[0171] Ninety-three clinical samples were used to evaluate the prediction system of the present invention. The classification results of the broth microdilution method and the system prediction results of the 93 clinical samples are shown in Table 1 below. In the following table, S represents sensitive and R represents resistant.

[0172] Table 1

[0173]

[0174]

[0175]

[0176] The test result data generated the confusion matrix as shown in Table 2 below:

[0177] Table 2

[0178]

[0179] Assume that TP (True Positive) represents the number of true positive cases, FP (False Positive) represents the number of false positive cases, FN (False Negative) represents the number of false negative cases, and TN (True Negative) represents the number of true negative cases. Precision refers to the proportion of positive samples among the positive cases determined by the classifier. Recall rate refers to the proportion of the cases predicted as positive among the total positive cases. Accuracy refers to the proportion of the entire sample correctly judged by the classifier. F1-score is the harmonic mean of precision and recall rate, with a maximum of 1 and a minimum of 0. The calculation results of each index are as follows:

[0180]

[0181]

[0182]

[0183]

[0184] The embodiments described above only represent the implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the appended claims.

Claims

1. A system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin, provided with: a calculation unit and a result output unit; the calculation unit includes: A computer-readable storage medium having a computer program stored thereon; characterized in that when the computer program is executed by a processor, it implements a method for calculating the Exp(-k) power value; the Exp(-k) power value calculation method includes the following calculation steps: S1: Calculate the k value according to the following formula I: Formula I: ; S2: Obtain the Exp(-k) power value with the natural constant e as the base and -k as the exponent; In formula I: C1 is the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted, C2 is the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted, C3 is the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted, C4 is the copy number of the APH(3'')-Ib gene in the Klebsiella pneumoniae strain to be predicted, C5 is the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted, C6 is the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted; The result output unit outputs the drug resistance result R when it recognizes that the Exp(-k) power value < 1; The result output unit outputs the sensitive result S when it recognizes that the Exp(-k) power value ≥ 1.

2. The system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 1, wherein The calculation unit transports the calculated Exp(-k) power value to the result output unit, and the result output unit recognizes the Exp(-k) power value and outputs the result.

3. A system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 1, wherein, The natural constant e = 2.718281828459045.

4. A system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 1, characterized in that, The result output unit and the calculation unit are connected by a data path, and the Exp(-k) power value calculated by the calculation unit is transported to the result output unit via the data path.

5. A system for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin according to claim 1, characterized in that, The sensitive result S means that the Klebsiella pneumoniae to be predicted is sensitive to ciprofloxacin; the drug resistance result R means that the Klebsiella pneumoniae to be predicted is resistant to ciprofloxacin.

6. A system for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin according to any one of claims 1-4, characterized in that, There is also provided: an experimental unit and a data input unit; The experimental unit and the data input unit are connected by a data path; the experimental unit outputs the experimental result, transports it to the data input unit via the data path and converts it into independent variable data; The data input unit and the calculation unit are connected by a data path; the independent variable data is transported to the calculation unit via the data path.

7. A system for predicting the sensitivity of Klebsiella pneumoniae to ciprofloxacin according to claim 6, characterized in that, The independent variable data includes: the values of C1, C2, C3, C4, C5, C6.

8. A system for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 6, characterized in that, The experimental result includes: the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the APH(3'')-Ib gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted, the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted.

9. A method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin, characterized in that, Including: S1: Calculate the k value according to the following formula I: Formula I: ; S2: Obtain the Exp(-k) power value with the natural constant e as the base and -k as the exponent; In formula I: C1 is the copy number of the rmtB gene in the Klebsiella pneumoniae strain to be predicted, C2 is the copy number of the AAC(6')-Ib-cr6 gene in the Klebsiella pneumoniae strain to be predicted. C3 is the copy number of the KPC-1 gene in the Klebsiella pneumoniae strain to be predicted. C4 is the copy number of the APH(3'')-Ib gene in the Klebsiella pneumoniae strain to be predicted. C5 is the copy number of the FosA5 gene in the Klebsiella pneumoniae strain to be predicted. C6 is the copy number of the SHV-25 gene in the Klebsiella pneumoniae strain to be predicted. The predicted result corresponding to the Exp(-k) power value < 1 is that Klebsiella pneumoniae is resistant to ciprofloxacin, and the predicted result corresponding to the Exp(-k) power value ≥ 1 is that Klebsiella pneumoniae is sensitive to ciprofloxacin.

10. The method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 9, characterized in that, The natural constant e = 2.718281828459045.

11. A method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 9, characterized in that, The copy numbers of the rmtB, AAC(6')-Ib-cr6, KPC-1, APH(3'')-Ib, FosA5, and SHV-25 genes in the Klebsiella pneumoniae strain to be predicted are obtained by the next-generation high-throughput sequencing method.

12. A method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 11, characterized in that, Copy number of the gene in the Klebsiella pneumoniae strain to be predicted = .

13. A method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 12, characterized in that, The genomic contigs are the longest contigs fragments obtained by assembling the sequencing results using the SPAdes v3.13.0 assembly software. The depth of the genomic contigs is the depth of the genomic contigs calculated by the SPAdes v3.13.0 assembly software. The depth of the contigs where the gene is located refers to the sum of the depths of the gene on each contig with a copy of the gene.

14. A method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 13, characterized in that, Each contig with a copy of the gene is annotated after aligning the cds and protein sequences of the gene to the CARD database using the blat version number v.36 software and the diamond version number v2.0.4.142 software.

15. A method for predicting the susceptibility of Klebsiella pneumoniae to ciprofloxacin according to claim 13, wherein The depth of the gene on each contig with a copy of the gene is calculated by the SPAdes v3.13.0 assembly software.

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