Biochemical value identification method of staphylococcus strain

Abstract

The invention belongs to the field of microbiological identification, and discloses a biochemical value identification method for strains in staphylococcus. 18 biochemical experiments including L-arabinose, N-acetylglucosamine, mannose and the like are carried out on known staphylococcus and a to-be-identified strain, so that a biochemical reaction positive probability matrix of different known staphylococcus and a reaction positive condition of the to-be-identified strain are obtained; and calculating mode frequencies, total occurrence frequencies, multi-item total occurrence frequencies, identification percentages and mode likelihood ratios T of different known staphylococcus and staphylococcus to be identified on the basis of the probability matrix so as to identify the strains. According to the biochemical value identification method disclosed by the invention, negative or positive identification results presented by the related biochemical reaction are clear in boundary and easy to distinguish, 26 strains of staphylococcus are effectively distinguished, the identification accuracy is as high as 91%, and the method can be comparable with commercial products of the same type at home and abroad.

Description

Technical Field

[0001] The present invention belongs to the field of microbial identification, and particularly relates to a biochemical numerical identification method for species within the genus Staphylococcus. Background Art

[0002] The genus Staphylococcus belongs to Bacillota - Bacilli - Bacillales - Staphylococcaceae, and is a Gram - positive, fermentative, facultative anaerobic coccus. Currently, the genus Staphylococcus includes 72 species and 16 subspecies, which are divided into two categories according to the results of the plasma coagulase test, including coagulase - negative staphylococci (CoNS) and coagulase - positive staphylococci (CoPS). Among them, Staphylococcus aureus, as a typical pathogenic species, causes severe symptoms such as vomiting and diarrhea through direct invasion and systemic dissemination mediated by enterotoxins, resulting in 25% of bacterial food poisoning incidents globally. In contrast, CoNS such as Staphylococcus haemolyticus, Staphylococcus epidermidis, and Staphylococcus hominis present opportunistic pathogenic characteristics, mainly causing urinary tract infections, bacteremia, and endocarditis in immunocompromised populations. It is worth noting that bacteria of this genus account for up to 50% of clinical blood culture isolates, and Staphylococcus aureus and the above three CoNS constitute the main pathogenic spectrum.

[0003] Although MALDI - TOF MS and genotyping techniques are popular, their high cost limits their application. Currently, the detection of Staphylococcus still mainly relies on conventional isolation and identification techniques. The foreign API Staph product is considered a valuable method for rapid detection of Staphylococcus and is the "gold standard" for traditional Staphylococcus detection. So far, there has been no relevant report on a bacterial numerical identification method for differentiating different species within the genus Staphylococcus based on biochemical reactions in China. In view of the defects of the lagging existing systematic classification standard and high price, this study develops an independent - intellectual - property - right Staphylococcus identification system based on the combination of biochemical reactions and numerical theory to provide an efficient and low - cost solution for clinical and food safety. Summary of the Invention

[0004] The purpose of the present invention is to overcome at least one deficiency of the prior art and provide a biochemical numerical identification method for species within the genus Staphylococcus.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A biochemical numerical identification method for species within the genus Staphylococcus, comprising the following steps:

[0007] Carry out biochemical reaction experiments on different known Staphylococcus species. The biochemical reaction experiments include 18 biochemical experiments in total, namely L - arabinose, N - acetylglucosamine, mannose, mannitol, trehalose, maltose, melibiose, sucrose, xylose, ribose, sorbitol, cellobiose, esculin, arginine dihydrolase, urea hydrolysis, p - nitrophenyl phosphate, lactose, and galactose experiments. Obtain the positive rates of biochemical reactions of different Staphylococcus species. Take different known Staphylococcus species as different taxonomic units and determine the probability matrix of each taxonomic unit;

[0008] Calculate the mode frequency of the taxonomic unit Total occurrence frequency P (u / J) , multiple total occurrence frequency S, identification percentage ID, and mode likelihood ratio T, where:

[0009] Mode frequency Is the product of the maximum total occurrence probabilities of the biochemical experiment combinations under this taxonomic unit,

[0010] In the formula: LJ represents the probability of the taxonomic unit J for all biochemical tests, and P(X i / J) represents the probability of a certain biochemical test for the taxonomic unit J, and X i Is the i - th biochemical test;

[0011] Total occurrence frequency P (u / J) Is the product of the actual occurrence probabilities of the biochemical experiment combinations of a certain unknown bacterium to be identified under this taxonomic unit, P (u / J) = LJ = Π I P(X i / J);

[0012] The multiple total occurrence frequency S is the sum of the total occurrence frequencies of each taxonomic unit, S = ∑P (u / J) = ∑(Π I P(X i / J));

[0013] The identification percentage ID is the total occurrence frequency of each taxonomic unit divided by the multiple total occurrence frequency and then multiplied by 100%. The sum of all identification percentages should be equal to 100%,

[0014] The mode likelihood ratio T is the total occurrence frequency of each taxonomic unit divided by the mode frequency of this taxonomic unit and then multiplied by 100%,

[0015] After the strain to be identified is pure cultured on a selective medium for Staphylococcus, the 18 biochemical reaction experiments are carried out. According to the positive probability data of the biochemical reactions of Staphylococcus, the negative / positive experimental results are converted into probability values, and the pattern frequency of the strain to be identified is calculated. Total occurrence frequency P (u / J) , multiple total occurrence frequency S, identification percentage ID, and pattern likelihood ratio T;

[0016] According to the identification percentage ID and pattern likelihood ratio T of the strain to be identified, the reliability of the identification result of the strain to be tested is evaluated, and the taxonomic unit with the highest score is the identification result of the strain to be tested.

[0017] In some examples, the positive probability data of the biochemical reactions of Staphylococcus are obtained by statistically analyzing the standard strains and isolated strains of Staphylococcus with known positive probability data of the biochemical reactions, or are determined by further combining public data.

[0018] In some examples, when converting the negative / positive experimental results into probability values, the probability value of the positive experimental result is the known positive probability value, and the probability value of the negative experimental result is 100% - the known positive probability value.

[0019] In some examples, to avoid extreme values, if the probability value is 0% or 100%, a close value greater than 0 or a close value less than 100% is used to replace it respectively.

[0020] In some examples, the close value greater than 0% is 1%, and the close value less than 100% is 99%.

[0021] In some instances, the Staphylococcus genus includes: Staphylococcus arlettae, Staphylococcus aureus, Staphylococcus capitis, Staphylococcus caprae, Staphylococcus chromogenes, Staphylococcus cohnii, Staphylococcus ureilyticus, Staphylococcus delphini, Staphylococcus epidermidis, Staphylococcus equorum, Staphylococcus fleurettii, Staphylococcus gallinarum, Staphylococcus haemolyticus, Staphylococcus hominis, Staphylococcus hyicus, Staphylococcus lentus, Staphylococcus microti, Staphylococcus nepalensis, Staphylococcus saprophyticus, Staphylococcus schleiferi, Staphylococcus sciuri, Staphylococcus simiae, Staphylococcus simulans, Staphylococcus vitulinus, Staphylococcus warneri, Staphylococcus xylosus.

[0022] In some instances, the positive probabilities of different biochemical reaction experiments of the Staphylococcus genus are shown in the following table:

[0023]

[0024]

[0025]

[0026] The data in the table are the percentage positive rates of various biochemical reactions. Ara refers to the L - arabinose reaction, Nag refers to the N - acetyl - glucosamine reaction, Mne refers to the mannose reaction, Man refers to the mannitol reaction, Tre refers to the trehalose reaction, Mal refers to the maltose reaction, Raf refers to the raffinose reaction, Suc refers to the sucrose reaction, Xyl refers to the xylose reaction, Rib refers to the ribose reaction, Sor refers to the sorbitol reaction, Cel refers to the cellobiose reaction, Esc refers to the esculin reaction, Adh refers to the arginine dihydrolase reaction, Ure refers to the urea hydrolysis reaction, PNPP refers to the p - nitrophenyl phosphate reaction, Lac refers to the lactose reaction, and Gal refers to the galactose reaction.

[0027] In some examples, the criteria for judging the credibility of the identification results are as follows:

[0028]

[0029] In some examples, the strains to be tested are from food samples, environmental samples, and biological samples.

[0030] In some examples, the inconsistent biochemical experiments of the strains to be tested with each taxonomic unit are listed separately, and other known methods are used for identification to determine the strains to be tested.

[0031] The beneficial effects of the present invention are:

[0032] In the biochemical numerical identification method of some examples of the present invention, the negative or positive identification results presented by the biochemical reactions are clearly demarcated and easy to distinguish, effectively distinguishing 26 species of Staphylococcus, with an identification accuracy rate as high as 91%, comparable to domestic and foreign commercial products of the same type.

[0033] In the biochemical numerical identification method of some examples of the present invention, the reaction positive rate data of different species of Staphylococcus are obtained by statistical analysis after biochemical experiments on a large number of isolates, ensuring the accuracy and timeliness of the basic data. Detailed implementation manners

[0034] A biochemical numerical identification method for species within Staphylococcus includes the following steps:

[0035] Perform biochemical reaction experiments on different known Staphylococcus species. The biochemical reaction experiments include 18 biochemical experiments in total, namely L - arabinose, N - acetylglucosamine, mannose, mannitol, trehalose, maltose, melezitose, sucrose, xylose, ribose, sorbitol, cellobiose, esculin, arginine dihydrolase, urea hydrolysis, p - nitrophenyl phosphate, lactose, and galactose experiments. Obtain the positive rates of biochemical reactions of different Staphylococcus species. Use different known Staphylococcus species as different taxonomic units and determine the probability matrix for each taxonomic unit;

[0036] Calculate the modal frequency of the taxonomic unit Total occurrence frequency P (u / J) , multiple total occurrence frequency S, identification percentage ID, and modal likelihood ratio T, where:

[0037] Modal frequency Is the product of the maximum total occurrence probabilities of the biochemical experiment combinations under this taxonomic unit,

[0038] In the formula: LJ represents the probability of the taxonomic unit J for all biochemical tests, and P(X i / J) represents the probability of a certain biochemical test for the taxonomic unit J, and X i Is the i - th biochemical test;

[0039] Total occurrence frequency P (u / J) Is the product of the actual occurrence probabilities of the biochemical experiment combinations of a certain unknown bacterium to be identified under this taxonomic unit, P (u / J) = LJ = Π I P(X i / J);

[0040] The multiple total occurrence frequency S is the sum of the total occurrence frequencies of each taxonomic unit, S = ∑P (u / J) = ∑(Π I P(X i / J));

[0041] The identification percentage ID is the total occurrence frequency of each taxonomic unit divided by the multiple total occurrence frequency and then multiplied by 100%. The sum of all identification percentages should be equal to 100%,

[0042] The modal likelihood ratio T is the total occurrence frequency of each taxonomic unit divided by the modal frequency of this taxonomic unit and then multiplied by 100%,

[0043] After pure - culturing the strain to be identified on a Staphylococcus - selective medium, perform the above - mentioned 18 biochemical reaction experiments. According to the positive probability data of Staphylococcus biochemical reactions, convert the negative / positive experimental results into probability values and calculate the modal frequency of the strain to be identified Total occurrence frequency P (u / J) , multiple total occurrence frequencies S, identification percentage ID, and pattern likelihood ratio T;

[0044] Based on the identification percentage ID and pattern likelihood ratio T of the strain to be identified, the reliability of the identification result of the strain to be tested is evaluated, and the taxonomic unit with the highest score is the identification result of the strain to be tested.

[0045] In some examples, the standard strains and isolated strains of Staphylococcus with known positive probability data of biochemical reactions are obtained by statistical analysis of the biochemical reaction experiments, or further determined by combining public data.

[0046] In some examples, when converting the negative / positive experimental results into probability values, the probability value of the positive experimental result is the known positive probability value, and the probability value of the negative experimental result is 100% - the known positive probability value.

[0047] In some examples, to avoid extreme values, if the probability value is 0% or 100%, a close value greater than 0 or less than 100% is used for substitution respectively.

[0048] In some examples, the close value greater than 0% is 1%, and the close value less than 100% is 99%. Using such close values can obtain better discrimination values.

[0049] In some examples, the Staphylococcus genus includes: Staphylococcus arlettae, Staphylococcus aureus, Staphylococcus capitis, Staphylococcus caprae, Staphylococcus chromogenes, Staphylococcus cohnii, Staphylococcus ureilyticus, Staphylococcus delphini, Staphylococcus epidermidis, Staphylococcus equorum, Staphylococcus fleurettii, Staphylococcus gallinarum, Staphylococcus haemolyticus, Staphylococcus hominis, Staphylococcus hyicus, Staphylococcus lentus, Staphylococcus microti, Staphylococcus nepalensis, Staphylococcus saprophyticus, Staphylococcus schleiferi, Staphylococcus sciuri, Staphylococcus simiae, Staphylococcus simulans, Staphylococcus vitulinus, Staphylococcus warneri, Staphylococcus xylosus. These Staphylococcus genera already include common Staphylococcus genera and can meet the needs of daily identification.

[0050] In some examples, the positive probabilities of different biochemical reaction experiments of the Staphylococcus genus are shown in the following table:

[0051]

[0052]

[0053] The data in the table are the percentage positive rates of various biochemical reactions. Ara refers to the L - arabinose reaction, Nag refers to the N - acetylglucosamine reaction, Mne refers to the mannose reaction, Man refers to the mannitol reaction, Tre refers to the trehalose reaction, Mal refers to the maltose reaction, Raf refers to the raffinose reaction, Suc refers to the sucrose reaction, Xyl refers to the xylose reaction, Rib refers to the ribose reaction, Sor refers to the sorbitol reaction, Cel refers to the cellobiose reaction, Esc refers to the esculin reaction, Adh refers to the arginine dihydrolase reaction, Ure refers to the urea hydrolysis reaction, PNPP refers to the p - nitrophenyl phosphate reaction, Lac refers to the lactose reaction, and Gal refers to the galactose reaction.

[0054] In some examples, the criteria for determining the credibility of the identification results are as follows:

[0055]

[0056]

[0057] In some examples, for unacceptable identification results of suspicious identification results, other methods are further used for identification to obtain more accurate identification results.

[0058] In some examples, the test strains are from food samples, environmental samples, and biological samples.

[0059] In some examples, the inconsistent biochemical experiments of the test strain with each taxonomic unit are listed separately, and other known methods are used for identification to determine the test strain.

[0060] The present invention will be further described below in conjunction with the embodiments, but it is not a limitation of the present invention. Unless otherwise defined, the technical and scientific terms used in the following embodiments have the same meanings as commonly understood by those skilled in the art to which the present invention belongs.

[0061] Example 1: Determining the species of Staphylococcus

[0062] The species of Staphylococcus determined in this example include: Staphylococcus arlettae (S. arlettae), Staphylococcus aureus (S. aureus), Staphylococcus capitis (S. capitis), Staphylococcus caprae (S. caprae), Staphylococcus chromogenes (S. chromogenes), Staphylococcus cohnii (S. cohnii), Staphylococcus ureilyticus (S. ureilyticus), Staphylococcus delphini (S. delphini), Staphylococcus epidermidis (S. epidermidis), Staphylococcus equorum (S. equorum), Staphylococcus fleurettii (S. fleurettii), Staphylococcus gallinarum (S. gallinarum), Staphylococcus haemolyticus (S. haemolyticus), Staphylococcus hominis (S. hominis), Staphylococcus hyicus (S. hyicus), Staphylococcus lentus (S. lentus), Staphylococcus microti (S. microti), Staphylococcus nepalensis (S. nepalensis), Staphylococcus saprophyticus (S. saprophyticus), Staphylococcus schleiferi (S. schleiferi), Staphylococcus sciuri (S. sciuri), Staphylococcus simiae (S. simiae), Staphylococcus simulans (S. simulans), Staphylococcus vitulinus (S. vitulinus), Staphylococcus warneri (S. warneri), Staphylococcus xylosus (S. xylosus).

[0063] Example 2: Select the biochemical experiments required in the numerical method

[0064] Through a non-probabilistic data matrix cladogram, 18 biochemical tests were selected: L-arabinose (Ara), N-acetyl-glucosamine (Nag), Mannose (Mne), Mannitol (Man), Trehalose (Tre), Maltose (Mal), Raffinose (Raf), Sucrose (Suc), Xylose (Xyl), Ribose (Rib), Sorbitol (Sor), Cellobiose (Cel), Esculin hydrolysis (Esc), Arginine dihydrolase (Adh), Urease (Ure), p-Nitrophenyl phosphate (PNPP), Lactose (Lac), Galactose (Gal).

[0065] Example 3: Establish a mathematical model in the numerical method

[0066] (1) Establish a positive probability database

[0067] Based on a total of 370 standard strains and isolated strains of Staphylococcus in our laboratory, the above 18 biochemical experiments were carried out. According to the results, the positive rates of various biochemical reactions of different bacteria were statistically analyzed, and combined with data such as Bergey's Manual of Determinative Bacteriology, a positive probability database of Staphylococcus was established. The specific is shown in Table 1 below.

[0068] (2) Construct a numerical identification system for Staphylococcus bacteria

[0069] According to the positive probability results of Staphylococcus biochemical reactions in Table 1, a database for the numerical identification system of Staphylococcus bacteria was constructed (the probability value of 100% was replaced by 99%, and the probability value of 0% was replaced by 1%).

[0070] (3) Determine the calculation method in the numerical method

[0071] According to the bacterial probability identification theory, determine the mode frequency of each taxonomic unit Total occurrence frequency P (u / J) , multiple total occurrence frequency S, identification percentage (ID, Identification Scores), and mode likelihood ratio (T, Tindex). The specific calculation functions include:

[0072] Mode frequency is the product of the maximum total occurrence probability of the biochemical experiment combination under this taxonomic unit,

[0073] In the formula: LJ represents the probability of taxonomic unit J for all biochemical tests, P(X i / J) represents the probability of a certain biochemical test for taxonomic unit J, and X i is the i-th biochemical test;

[0074] Total occurrence frequency P (u / J) is the product of the actual occurrence probability of the biochemical experiment combination of a certain unknown bacterium to be identified under this taxonomic unit, P (u / J) = LJ = Π I P(X i / j);

[0075] Multiple total occurrence frequency S is the sum of the total occurrence frequencies of each taxonomic unit, S = ∑P (u / J) = ∑(∏ I P(X i / J));

[0076] The identification percentage ID value is the total occurrence frequency of each taxon divided by the total occurrence frequency of multiple items and then multiplied by 100%. The sum of all identification percentages should be equal to 100%.

[0077] The pattern likelihood ratio T is the total occurrence frequency of each taxon divided by the pattern frequency of that taxon and then multiplied by 100%.

[0078] (4) Determine the result evaluation criteria

[0079] According to the magnitude of the identification percentage and the T value, judge the credibility of the identification result according to the evaluation criteria in Table 2. In the result display, give the Chinese and Latin names in contrast for the taxon.

[0080] Table 2. Evaluation of identification results

[0081]

[0082] Example 4: Establish the identification process of the strain to be tested

[0083] After the strain to be tested is purified and cultured on mannitol sodium chloride agar medium, perform the 18 biochemical experiments described in Example 2. Commercial identification strips can be used, or biochemical tubes can be purchased or the culture medium can be prepared by oneself for biochemical experiments, and record the experimental results.

[0084] After obtaining the biochemical experimental results of the strain to be tested, first convert the biochemical experimental results into probability values according to the recorded negative or positive results of the biochemical reactions: that is, if the experimental result is positive, it is the positive probability value of the corresponding biochemical experiment, and if it is negative, 100% minus the positive probability value of the biochemical experiment. If the above positive probability value is 0 or 100%, it is replaced by the approximate values of 1% or 99%. Then calculate the pattern frequency, total occurrence frequency, total occurrence frequency of multiple items, identification percentage, and pattern likelihood ratio T value of each taxon of the strain to be tested according to the calculation method in Example 3. Due to limited space, it is impossible to list all the 18 reaction positive rates of each taxon, so examples are given using taxon A, taxon B, taxon C and their biochemical experiments 1, 2, 3, 4, 5.

[0085] The biochemical experimental results of the strain to be tested and the reaction positive rates of taxon A, taxon B, and taxon C are shown in Table 3.

[0086] Table 3. Biochemical experimental results of the strain to be tested and reaction positive rates of known bacteria

[0087]

[0088] Pattern frequencies of known typical bacteria:

[0089] (A) = 0.99 × 0.99 × 0.99 × 0.99 × 0.99 = 0.951;

[0090] (B) = 0.99 × 0.99 × 0.99 × 0.99 × 0.99 = 0.951;

[0091] (C) = 0.99 × 0.99 × 0.99 × 0.99 × 0.99 = 0.951.

[0092] Total occurrence frequency of the bacteria to be tested:

[0093] (A) = 0.01 × 0.99 × 0.99 × 0.99 × 0.99 = 0.0096;

[0094] (B) = 0.99 × 0.99 × 0.99 × 0.99 × 0.99 = 0.951;

[0095] (C) = 0.99 × 0.01 × 0.99 × 0.99 × 0.01 = 0.0096.

[0096] Total occurrence frequency of multiple taxonomic units = 0.0096 + 0.951 + 0.0096 = 0.9702

[0097] Identification percentage ID value:

[0098] (A): ID = 0.0096 / 0.9702 × 100% = 0.9901%;

[0099] (B) = 0.951 / 0.9702 × 100% = 98.02%;

[0100] (C) = 0.0096 / 0.9702 × 100% = 0.9901%.

[0101] Pattern likelihood ratio T value:

[0102] (A) T = 0.0096 / 0.951 × 100% = 1.01%;

[0103] (B) T = 0.951 / 0.951 × 100% = 100%;

[0104] (C) T = 0.0096 / 0.951 × 100% = 1.01%.

[0105] According to the size of the identification percentage, the identification results are sorted in descending order, and the evaluation criteria for the identification results described in Example 3 are used for judgment. For example, in this embodiment, the classification unit B with the maximum value of 98.02% is taken. The final identification result of the tested bacteria is: the tested bacteria is the known species corresponding to the classification unit B, the identification percentage is 98.02%, and the model likelihood ratio T value is 100.00%, which is an excellent identification result. The inconsistent biochemical experiments between the tested strains and each classification unit in the identification results are listed separately and displayed in the results, and the Chinese and Latin comparisons are given for the classification units.

[0106] Example 5: Evaluation of the effect of the numerical rapid identification method of Staphylococcus

[0107] In order to verify the feasibility of the numerical rapid identification method for Staphylococcus, 422 strains of Staphylococcus isolates were selected as test objects, and the strains to be tested were identified according to the process described in Example 4. After obtaining the biochemical experimental results (see Table 4 for details), the identification percentage and pattern likelihood ratio T value of each classification unit were calculated according to the numerical identification method for Staphylococcus established in Example 3. The identification percentages are arranged in descending order, and the strain corresponding to the highest identification percentage is the classification unit to which the standard strain to be tested belongs, and the credibility of the identification results is determined according to the evaluation criteria in Table 2. The results of the numerical identification method are shown in Table 5.

[0108] Table 5. Evaluation of the results of the numerical identification system for Staphylococcus aureus

[0109]

[0110]

[0111]

[0112]

[0113]

[0114] 111 biochemical spectrum types were finally obtained for 422 Staphylococcus isolates. The reliability of the identification results was evaluated and it was found that the identification effect was acceptable for most of the tested Staphylococcus isolates.

[0115] The identification results of MALDI-TOF MS were used as reference standards and compared with the detection results of the numerical identification method of the present invention for the Staphylococcus species. The results showed that the overall identification accuracy of the biochemical numerical identification method of this study for 422 Staphylococcus isolates reached 91% (Table 6). In general, the numerical identification method of the Staphylococcus species established by the present invention has a high identification level.

[0116] Table 6. Accuracy rate of the biochemical numerical identification method for Staphylococcus species in the present invention

[0117]

[0118] Note: The accuracy rate is the accuracy rate of the biochemical numerical identification method for Staphylococcus species in the present invention. The calculation formula is: Accuracy rate (%) = Number of strains with consistent results between the numerical identification method and MALDI-TOF MS / Number of strains identified by MALDI-TOF MS × 100%.

[0119] The above is a further detailed description of the present invention, which should not be regarded as a limitation to the specific implementation of the present invention. For those of ordinary skill in the technical field to which the present invention pertains, any simple deduction or substitution without departing from the concept of the present invention falls within the protection scope of the present invention.

[0120]

[0121]

[0122]

[0123]

[0124]

Claims

1. A biochemical numerical identification method for Staphylococcus species, comprising the following steps: Performing biochemical reaction experiments on known Staphylococcus species of different types. The biochemical reaction experiments include 18 biochemical experiments in total, namely L - arabinose, N - acetylglucosamine, mannose, mannitol, trehalose, maltose, melibiose, sucrose, xylose, ribose, sorbitol, cellobiose, esculin, arginine dihydrolase, urea hydrolysis, p - nitrophenyl phosphate, lactose, and galactose experiments. Obtaining the positive rates of biochemical reactions of different Staphylococcus species, taking different known Staphylococcus species as different taxonomic units, and determining the probability matrix of each taxonomic unit; Calculating the modal frequency of taxonomic units Total occurrence frequency P (u / J) , the multiple total occurrence frequency S, the identification percentage ID, and the modal likelihood ratio T, where: Mode frequency which is the product of the maximum total occurrence probabilities of the biochemical experiment combinations under this taxon, where: LJ represents the probability of occurrence of all biochemical tests for taxon J, P(X i / J) represents the probability of occurrence of a certain biochemical test for taxon J, where X i is the i-th biochemical test; Total occurrence frequency P (u / J) is the product of the actual occurrence probabilities of a biochemical experiment combination for a to-be-identified unknown bacterium under this taxonomic unit, P (u / J) = LJ = Π I P(X i / J); The total frequency of multiple occurrences S is the sum of the total occurrence frequencies of each taxonomic unit, S = ∑P (u / J) = ∑(Π I P(X i / J)); The identification percentage ID is the total occurrence frequency of each taxonomic unit divided by the total occurrence frequency of the multiple items and then multiplied by 100%. The sum of all identification percentages should be equal to 100%. The pattern likelihood ratio T is the total occurrence frequency of each taxonomic unit divided by the pattern frequency of that taxonomic unit and then multiplied by 100%, After the strain to be identified is pure cultured on a selective medium for Staphylococcus, the 18 biochemical reaction experiments are carried out. According to the positive probability data of the biochemical reactions of Staphylococcus, the negative / positive experimental results are converted into probability values, and the pattern frequency of the strain to be identified is calculated. Total occurrence frequency P (u / J) , the multiple total occurrence frequency S, the identification percentage ID, and the pattern likelihood ratio T; According to the identification percentage ID of the strain to be identified and the pattern likelihood ratio T, evaluating the credibility of the identification result of the strain to be tested. The taxonomic unit with the highest score is the identification result of the strain to be tested.

2. The biochemical value identification method according to claim 1, characterized in that, The positive probability data of the biochemical reactions of the Staphylococcus standard strains and isolates with known data are obtained by performing the above - mentioned biochemical reaction experiments, or further determined by combining public data.

3. The biochemical value identification method according to claim 1, wherein When converting the negative / positive experimental results into probability values, the probability value of a positive experimental result is the known positive probability value, and the probability value of a negative experimental result is 100% - the known positive probability value.

4. The biochemical value identification method according to claim 2, characterized in that, To avoid extreme values, if the probability value is 0% or 100%, a value close to >0 or <100% is used for substitution respectively.

5. The biochemical value identification method according to claim 4, characterized in that The value close to >0% is 1%, and the value close to <100% is 99%.

6. The biochemical value identification method according to any one of claims 1 to 5, characterized in that, The Staphylococcus genus includes: Staphylococcus arlettae, Staphylococcus aureus, Staphylococcus capitis, Staphylococcus caprae, Staphylococcus chromogenes, Staphylococcus cohnii, Staphylococcus ureilyticus, Staphylococcus delphini, Staphylococcus epidermidis, Staphylococcus equorum, Staphylococcus fleurettii, Staphylococcus gallinarum, Staphylococcus haemolyticus, Staphylococcus hominis, Staphylococcus hyicus, Staphylococcus lentus, Staphylococcus microti, Staphylococcus nepalensis, Staphylococcus saprophyticus, Staphylococcus schleiferi, Staphylococcus sciuri, Staphylococcus simiae, Staphylococcus simulans, Staphylococcus vitulinus, Staphylococcus warneri, Staphylococcus xylosus.

7. The biochemical value identification method according to claim 6, wherein The positive probabilities of different biochemical reaction experiments of the Staphylococcus genus are shown in the following table: The data in the table are the percentage positive rates of various biochemical reactions. Ara refers to the L-arabinose reaction, Nag refers to the N-acetylglucosamine reaction, Mne refers to the mannose reaction, Man refers to the mannitol reaction, Tre refers to the trehalose reaction, Mal refers to the maltose reaction, Raf refers to the raffinose reaction, Suc refers to the sucrose reaction, Xyl refers to the xylose reaction, Rib refers to the ribose reaction, Sor refers to the sorbitol reaction, Cel refers to the cellobiose reaction, Esc refers to the esculin reaction, Adh refers to the arginine dihydrolase reaction, Ure refers to the urea hydrolysis reaction, PNPP refers to the p-nitrophenyl phosphate reaction, Lac refers to the lactose reaction, and Gal refers to the galactose reaction.

8. The biochemical value identification method according to any one of claims 1 to 5, characterized in that, The criteria for judging the credibility of the identification results are as follows:

9. The biochemical value identification method according to any one of claims 1 to 5, characterized in that The test strains are from food samples, environmental samples, and biological samples.

10. The biochemical value identification method according to any one of claims 1 to 5, characterized in that List the inconsistent biochemical experiments of the test strains with each taxonomic unit separately, and use other known methods to identify and determine the test strains.

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