Antibiotic resistance genes and screening methods for priority monitoring in mariculture environments
By establishing an ARGs pollution assessment index system and using the analytic hierarchy process to screen key antibiotic resistance genes, the gap in ARGs monitoring in marine aquaculture environments was filled, enabling effective screening and monitoring of ARGs and providing a scientific basis.
Patent Information
- Application Number
- CN202510405025.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-02
- Publication Date
- 2025-11-07
- Estimated Expiration
- 2045-04-02
AI Technical Summary
The lack of effective methods in the current technology for prioritizing the monitoring and control of antibiotic resistance genes (ARGs) in marine aquaculture environments has resulted in the ineffective assessment and control of ARG pollution and human health risks in marine aquaculture environments.
An ARGs pollution assessment index system was established, and the weights of the indexes were determined by the analytic hierarchy process. Ten key antibiotic resistance genes were screened by combining the comprehensive scoring method. The ARGs that need to be focused on were then detected and monitored by ultra-high throughput PCR technology.
It provides a scientific and reasonable method that can effectively screen out ARGs that require key attention, providing a basis for the daily monitoring and control of ARGs in marine aquaculture environments, and has versatility and scalability.
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Figure CN119920324B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of environmental monitoring, in particular to antibiotic resistance genes for priority monitoring in mariculture environment. BACKGROUND
[0002] Currently, the control of antibiotic resistance is mainly based on the monitoring of antibiotics and resistant pathogens. The monitoring of ARGs is still in the exploratory stage. This is mainly because 1) there are many types of ARGs, and there are many subtypes under different types. Based on ultra-high throughput PCR technology, 296 types are mainly concerned, while more can be identified based on metagenomic technology. Not every ARG needs to be concerned; 2) the human health risk assessment system for ARGs in the environment is not perfect. Some studies have proposed an evaluation model for the human health risk of ARGs based on metagenomic technology combined with pathogen databases, which can provide potential health risk data for ARGs, but it requires a large number of existing databases to support and the data processing is complex, and it cannot be maturely applied. Ecological risk assessment is almost non-existent. It is impossible to monitor, control and develop standards for every ARG. Only some ARGs that pose a greater potential threat to human health and ecological balance in special environments can be prioritized. At the same time, ARGs in the environment are considered to have co-occurrence. Monitoring these major ARGs may be equivalent to understanding the overall ARG pollution situation.
[0003] Mariculture is one of the environments closely related to human health. Due to the misuse and abuse of antibiotics, the spread and transmission of aquatic product disease infection, and environmental pollution, the phenomenon of antibiotic resistance has risen sharply. The mariculture area in China is about 2.07 million hectares. ARGs in the mariculture environment can proliferate and spread with the bacterial population, directly entering the body of aquatic products, and posing a threat to human health. They can also spread or be exchanged regularly into natural water bodies from mariculture water bodies, seriously affecting ecological health. Aquaculture tail water is even considered to be an important source of ARGs in coastal waters. Therefore, it is urgent to prioritize the monitoring of ARGs in mariculture environments.
[0004] Unfortunately, the screening of priority monitoring ARGs is still a blank. Traditional screening methods for priority monitoring and control are mainly based on potential hazard index method, comprehensive scoring method, weighted scoring method, and analytic hierarchy process, each of which has its own advantages and disadvantages, and the required data sets are different. SUMMARY
[0005] In view of the above prior art, the present application provides a screening method for antibiotic resistance genes for priority monitoring in mariculture environment and ten antibiotic resistance genes that can be used for daily monitoring, mainly solving the technical problems existing in the background art.
[0006] To achieve the above objectives, the technical solution of this invention is implemented as follows:
[0007] The first aspect of this invention provides a screening method for preferentially monitoring antibiotic resistance genes in a marine aquaculture environment, the screening method comprising:
[0008] An ARGs pollution assessment index system is established, wherein the ARGs indicators in the ARGs pollution assessment index system include environmental occurrence frequency, environmental pollution degree, environmental mobility, co-occurrence indicative, biological occurrence frequency, and biological mobility;
[0009] Determine the weights of the ARGs indicators;
[0010] The target genes to be evaluated were identified through preliminary screening. The ARGs index value of each target gene was calculated, and the ARGs index score was applied to each target gene. ,in This represents the overall score of the target gene. Indicators The weight value, Indicators The individual indicator scores are calculated, where n is a constant. The comprehensive score for each target gene is obtained based on the scoring results and the weights of the ARGs indicators.
[0011] The target genes with higher comprehensive scores were selected as priority antibiotic resistance genes for monitoring in marine environments.
[0012] Optionally, each target gene is scored using ARGs indicators, specifically including: dividing each ARGs indicator into 4 levels, assigning values of 20, 40, 60 and 80 respectively, and assigning corresponding scores based on the ARGs indicator evaluation results of each target gene.
[0013] Optionally, the weight of each of the ARGs indicators can be determined based on the analytic hierarchy process (AHP).
[0014] Optionally, a preliminary screening can be conducted to identify the target genes to be evaluated. Specifically, this includes obtaining target ARGs and MGEs as target genes from target environmental samples and biological samples, or selecting multiple target ARGs and MGEs of interest based on the current status of target environmental research and detecting them as target genes.
[0015] The application is a marine aquaculture environment antibiotic resistance pollution monitoring application, which applies the screening method of any one of the preceding to screen ten subtypes of antibiotic resistance genes from the antibiotic resistance gene pollution commonly found in aquaculture environments, including aadA-01 gene, aadA2 gene, cmlA gene, floR gene, mphA-01 gene, ereA gene, ermF gene, aac(6')-Ib-cr gene, sul1 gene, and sul2 gene, and the foregoing genes are applied to daily condition monitoring of the marine aquaculture environment.
[0016] The aadA-01 gene is amplified by the primer sequences described in SEQ ID NO. 49 and SEQ ID NO. 50;
[0017] The aadA2 gene is amplified by the primer sequences described in SEQ ID NO. 47 and SEQ ID NO. 48;
[0018] The cmlA gene is amplified by the primer sequences described in SEQ ID NO. 27 and SEQ ID NO. 28;
[0019] The floR gene is amplified by the primer sequences described in SEQ ID NO. 25 and SEQ ID NO. 26;
[0020] The mphA-01 gene is amplified by the primer sequences described in SEQ ID NO. 51 and SEQ ID NO. 52;
[0021] The ereA gene is amplified by the primer sequences described in SEQ ID NO. 53 and SEQ ID NO. 54;
[0022] The ermF gene is amplified by the primer sequences described in SEQ ID NO. 57 and SEQ ID NO. 58;
[0023] The aac(6')-Ib-cr gene is amplified by the primer sequences described in SEQ ID NO. 67 and SEQ ID NO. 68;
[0024] The sul1 gene is amplified by the primer sequences described in SEQ ID NO. 29 and SEQ ID NO. 30;
[0025] The sul2 gene is amplified by the primer sequences described in SEQ ID NO. 31 and SEQ ID NO. 32.
[0026] The application has the beneficial effects that the method of the application effectively makes up the blank of the current antibiotic resistance gene priority monitoring screening. The overall method design is reasonable, conforms to the principles of scientificity and rationality, selects the ARGs that need to be focused on based on the analytic hierarchy process and comprehensive scoring method, and can provide a strong basis for the daily monitoring and control of ARGs pollution. The model of the calculation method has universality and scalability. BRIEF DESCRIPTION OF DRAWINGS
[0027] Figure 1 A flowchart of the screening method for priority monitoring of antibiotic resistance genes in the seawater culture environment in the embodiments of the application is shown.
[0028] Figure 2 A schematic diagram of the composition of the ARGs pollution evaluation index system in the embodiments of the application is shown.
[0029] Figure 3 The single evaluation index results of 33 ARGs in the embodiments of the application are shown. DETAILED DESCRIPTION
[0030] The technical solutions of the application are further described in detail below in combination with the drawings and specific embodiments. Unless otherwise defined, all the technical and scientific terms used herein have the same meanings as those commonly understood by the person skilled in the art to which the application belongs. The terms used in the specification of the application herein are only for the purpose of describing the specific embodiments and are not intended to limit the application. In the following description, the expression "some embodiments" describes a subset of all possible embodiments, but it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with each other without conflict.
[0031] In the following description, a large number of specific details are given in order to provide a more thorough understanding of the application. However, it is obvious to the person skilled in the art that the application can be implemented without one or more of these details. In other examples, some technical features known in the art are not described in order to avoid obscuring the application.
[0032] It is to be understood that the application can assume various alternative embodiments, and should not be limited to the examples described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art. Also, the terminology used here is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising", when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein the term "and / or" includes any and all combinations of associated items.
[0033] It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising", when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein the term "and / or" includes any and all combinations of associated items.
[0034] For a thorough understanding of the application, reference will be made to the following detailed description, in conjunction with the accompanying drawings, in which:
[0035] The application will be described in greater detail with reference to the following drawings, in which: Figure 1 The first aspect of the present application provides a screening method for preferentially monitoring antibiotic resistance genes in a mariculture environment, the screening method comprising:
[0036] S1, establishing an ARGs pollution evaluation index system, the ARGs index in the ARGs pollution evaluation index system comprising environmental occurrence frequency, environmental pollution degree, environmental migration, co-occurrence indication, biological occurrence frequency, and biological migration;
[0037] Specifically, ARGs in a mariculture environment can directly cause risks to the environment, so the environmental effects of ARGs are selected as the first-level index in the present application. Meanwhile, compared with traditional environmental areas, aquatic products in mariculture show high density and high intensification characteristics, and ARGs can pose a threat to the health of aquatic products, and the typical or concerned organisms in the mariculture environment are more definite, so the biological effects of aquatic products are selected as another first-level index.
[0038] The environmental effect index can represent the environmental occurrence frequency and the environmental pollution degree, and is used for reflecting the pollution degree of the ARGs in the target mariculture environment, and includes the following two indexes: 1. The environmental occurrence frequency refers to the detection rate of the ARGs in the seawater environment medium; 2. The environmental pollution degree refers to the proportion X of the total relative abundance of the ARGs in the total relative abundance of ARGs; 3. The environmental migration refers to the significance of the positive correlation between the ARGs and the mobile genetic elements (MGEs); 4. The co-occurrence indication refers to the proportion Y of the connection degree of the ARGs in the total connection degree in the co-occurrence network analysis.
[0039] The biological effect index includes the following two indexes: 1. The biological occurrence frequency refers to the detection rate of the ARGs in aquatic products, and reflects the pollution of the ARGs in the aquatic products; 2. The biological migration refers to the significance of the positive correlation between the ARGs and the MGEs in the aquatic products, and reflects the migration and transmission ability of the ARGs in the aquatic products.
[0040] S2, determining the weight of the ARGs index;
[0041] The weight of the evaluation index of the priority monitoring ARGs is calculated based on the analytic hierarchy process, which includes the following four steps: establishing a hierarchical structure model of the system, constructing a single-target judgment matrix, hierarchical single sorting and consistency checking, and hierarchical total sorting and consistency checking.
[0042] S21, establishing a hierarchical structure model of the system, establishing a systematic hierarchical structure according to the determined screening evaluation index, and dividing the index into three layers according to the meaning, which is specifically shown in Figure 2 .
[0043] S21, constructing a single-target judgment matrix, the present application uses the 1-9 scale method to compare the indexes between each other, wherein the meaning of the scale between the indexes is shown in Table 1:
[0044] Table 1 Definition of important scale between indexes
[0045]
[0046] Constructing a judgment matrix of each level , determining the relative importance between each evaluation index, and using the geometric mean method (formula 1) to calculate the weight vector of each index .
[0047] i = 1, 2, 3...n (1)
[0048] The judgment matrix composed of the level A and the level B is F 1, specifically as shown in Table 2, the judgment matrix composed of the level B1 and the level C F2, as shown in Table 3; the judgment matrix composed of hierarchy B2 and hierarchy C F 3, as shown in Table 4.
[0049] Table 2
[0050]
[0051] Table 3
[0052]
[0053] Table 4
[0054]
[0055] S23, hierarchy single ordering and consistency check. According to formula (2) and Table 5, the calculation and search are performed F 1, F 2, F 3 the consistency index of matrix CI and the average random consistency index RI , and the consistency ratio is calculated according to formula (3) CR, When CR <0.10, the matrix consistency can be accepted.
[0056] (2)
[0057] (3)
[0058] wherein, is the maximum eigenvalue of the matrix.
[0059] Table 5 the average random consistency index of 10,000 times of repeated calculation of a 15-dimensional matrix
[0060]
[0061] judgment matrix F 1, F 2, F 3 the consistency check results are as follows, CR all less than 0.10, the consistency check is passed:
[0062] F 1 ： ; ; ; ;
[0063] F 2 ： ; ; ; ;
[0064] F 3 ： ; ; ; ;
[0065] S25, Hierarchical Overall Ranking and Consistency Test. The C-factor at level [level]... B i The consistency metric for a single sort is CI j The corresponding average random consistency index is RI j Then the overall sorting consistency ratio of level C is calculated according to formula 4.
[0066]
[0067] CR =0.0116 < 0.10, the consistency of the overall sorting result in level C is acceptable.
[0068] After verification, the priority monitoring ARGs screening evaluation indicators and the established hierarchical structure model are reliable. The ranking weights of each screening evaluation indicator in level C are calculated according to formula (5), and the results are shown in Table 6.
[0069]
[0070] Table 6. Weights of Evaluation Indicators
[0071]
[0072] Finally, the obtained ARGs and MGEs pollution data were substituted into the screening framework. A comprehensive scoring method was used to calculate the comprehensive score of the ARGs based on the sum of the products of the individual scores of each evaluation indicator and their corresponding weights. ,in This represents the overall score of the target gene. Indicators The weight value, Indicators The score for each individual indicator, where n is a constant.
[0073] S3. The target genes to be evaluated are determined by preliminary screening, the ARGs index value of each target gene is calculated, the ARGs index score of each target gene is performed, and the comprehensive score of each target gene is obtained based on the score results and the weight of the ARGs index.
[0074] Specifically, target environmental samples (water, sediment) and biological samples are taken, where the biological samples mainly refer to the intestinal contents of typical or dominant aquatic products in mariculture environments. Based on ultra-high-throughput PCR and metagenomic technology, the presence of ARGs and MGEs is comprehensively obtained; or according to the current research status of the target environment, target ARGs and MGEs that need to be concerned are screened out and detected.
[0075] In scoring, each ARGs indicator is divided into 4 grades, respectively assigned as 20 points, 40 points, 60 points and 80 points, and the grading standards of each indicator are shown in Table 7.
[0076] Table 7 Evaluation index grading and score
[0077]
[0078] Exemplarily, due to the large number of ARGs subtypes, in order to narrow down the screening range, the embodiment screens out 33 common ARGs, 2 integrase genes and internal reference genes in the aquaculture environment according to the related research reports of ARGs in the aquaculture environment. 16S rRNA As target genes, see Table 8 for details.
[0079] Table 8 36 common genes in the aquaculture environment
[0080]
[0081] Subsequently, water samples and biological intestinal samples (a total of 53 water samples and 7 biological samples of Trachurus japonicus, Seriola quinqueradiata, Pseudosciaena crocea, Epinephelus akaara, Lates calcarifer, Sparus aurata and Nematistius pectoralis) from four aquaculture environments are collected, the sample genes are extracted using a kit, and the target 36 genes are detected based on ultra-high-throughput qPCR technology, to obtain the basic pollution situation of 33 ARGs in the four regions.
[0082] The results of 6 screening indicators of each ARG (environmental frequency of occurrence, i.e. the detection frequency of each ARGs in 53 water samples. Environmental pollution degree, refers to the proportion of the total relative abundance of each ARGs in the total relative abundance of all ARGs. Environmental mobility, refers to the significance of the positive correlation between each ARGs and mobile genetic elements (MGEs). Co-occurrence indicative, refers to the proportion of the connectivity of each ARG in the co-occurrence network analysis in the total connectivity. In the present embodiment, the relative abundance data is used, based on the pairwise Spearman rank correlation, and the relationships with significance (p<0.05) are retained for network visualization. Biological frequency of occurrence, refers to the detection frequency of each ARGs in biological samples. Biological mobility, refers to the significance of the positive correlation between each ARGs in the biological sample and mobile genetic elements (MGEs). intl1 / intl2 intl1 / intl2 Figure 3 Figure 3 The single evaluation index results of 33 ARGs.
[0083] The single evaluation index results of ARGs were scored according to the grading and scoring criteria of each index (Table 7), and further combined with the corresponding weight of the index (Table 8). Figure 3 The scores and comprehensive scores of the single evaluation index of 33 ARGs were calculated using the comprehensive score calculation formula. The specific results are shown in Table 9.
[0084] Table 9 Single evaluation index scores of 33 ARGs
[0085]
[0086] In order to illustrate the uniqueness of the names of the aforementioned genes, the primer sequences of the target genes are listed in Table 10.
[0087] Table 10
[0088]
[0089] S4, the top ten target genes with the highest comprehensive scores are selected as the antibiotic resistance genes for priority monitoring in seawater environment.
[0090] For example, considering the diversity of ARGs, the top 10 ARGs in the total score results obtained above are determined as the ARGs for priority monitoring in the water environment of aquaculture. The 10 ARGs subtypes in the water body include two aminoglycosides ( aadA-01 , aadA2 ), two chloramphenicols ( cmlA , floR ), three macrolides ( mphA-01 , ereA , ermF ), one quinolone ( aac(6’)-Ib-cr ), and two sulfonamides ( sul1 , sul2 ). These selected ARGs subtypes comprehensively reflect the six selected indicators of C1-C6, and are representative for the preliminary reflection of the daily status of ARGs in the aquaculture environment.
[0091] The second aspect of the present application provides a seawater culture environment antibiotic resistance pollution monitoring application, which screens ten subtypes of antibiotic resistance genes from the antibiotic resistance gene pollution commonly found in aquaculture environments, including aadA-01 gene, aadA2 gene, cmlA gene, floR gene, mphA-01 gene, ereA gene, ermF gene, aac(6')-Ib-cr gene, sul1 gene, and sul2 gene, and the foregoing genes are applied to daily condition monitoring of seawater culture environments.
[0092] The aadA-01 gene is amplified by the primer sequences described in SEQ ID NO. 49 and SEQ ID NO. 50;
[0093] The aadA2 gene is amplified by the primer sequences described in SEQ ID NO. 47 and SEQ ID NO. 48;
[0094] The cmlA gene is amplified by the primer sequences described in SEQ ID NO. 27 and SEQ ID NO. 28;
[0095] The floR gene is amplified by the primer sequences described in SEQ ID NO. 25 and SEQ ID NO. 26;
[0096] The mphA-01 gene is amplified by the primer sequences described in SEQ ID NO. 51 and SEQ ID NO. 52;
[0097] The ereA gene is amplified by the primer sequences described in SEQ ID NO. 53 and SEQ ID NO. 54;
[0098] The ermF gene is amplified by the primer sequences described in SEQ ID NO. 57 and SEQ ID NO. 58;
[0099] The aac(6')-Ib-cr gene is amplified by the primer sequences described in SEQ ID NO. 67 and SEQ ID NO. 68;
[0100] The sul1 gene is amplified by the primer sequences described in SEQ ID NO. 29 and SEQ ID NO. 30;
[0101] The sul2 gene is amplified by the primer sequences described in SEQ ID NO. 31 and SEQ ID NO. 32.
[0102] Exemplarily, the aforementioned ten genes are applied in a baseline survey, i.e., in a breeding cycle, the concentration of the ten priority monitoring resistance genes in the target breeding and the surrounding environment is detected by using technologies such as quantitative PCR or high-throughput quantitative PCR, background data is obtained, and the use of antibiotics, feed additives and the like are recorded, and the potential pollution sources and the gene concentration data are correlated.
[0103] Further, in some optional embodiments, a warning threshold is set with reference to the background data and the real-time data of the breeding cycle, and the pollution of the ten resistance genes is continuously and regularly monitored.
[0104] To sum up, the ARGs pollution evaluation index system disclosed in the present application covers six indexes of environmental occurrence frequency, environmental pollution degree, environmental migration, co-occurrence indication, biological occurrence frequency and biological migration, covering the core dimensions of the distribution abundance, transmission potential, biological pollution level and health risk of ARGs in the environment. The environmental occurrence frequency and the pollution degree reflect the ecological load of ARGs; the environmental / biological migration is evaluated through the co-occurrence of MGEs, which is consistent with the mechanism of ARGs transmission through horizontal gene transfer; the co-occurrence indication is based on network analysis, which reveals the relevance of ARGs and other microbial functions; the weight determination is the analytic hierarchy process (AHP), which is an internationally recognized multi-criteria decision-making method. The judgment matrix is constructed by expert scoring and the weight is calculated. The 1-9 scale method is used to quantify the importance difference of the indexes, reducing the subjective randomness, and the consistency test (CR<0.1) is strictly ensured to ensure the logical self-consistency.
[0105] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. The protection scope of the present application should be subject to the protection scope of the claims.
Claims
1. A screening method for prioritizing the monitoring of antibiotic resistance genes in a mariculture environment, characterized by, The screening method comprises: An ARGs pollution evaluation index system is established, and the ARGs index in the ARGs pollution evaluation index system comprises environmental occurrence frequency, environmental pollution degree, environmental migration, co-occurrence indication, biological occurrence frequency, and biological migration; The environmental occurrence frequency indicates the detection rate of ARGs in seawater environmental media; The environmental pollution degree indicates the proportion of the total relative abundance of each ARGs in the total relative abundance of all ARGs; The environmental migration indicates the significance of the positive correlation between ARGs and mobile genetic elements; The co-occurrence indication indicates the proportion of the connectivity of ARGs in the total connectivity in co-occurrence network analysis; The biological occurrence frequency indicates the detection rate of ARGs in aquatic products, reflecting the pollution of ARGs in aquatic products; The biological migration indicates the significance of the positive correlation between ARGs and MGEs in aquatic products, reflecting the migration and transmission ability of ARGs in aquatic products; The weight of the ARGs index is determined. coarse screening determines the target genes to be evaluated, each of the target genes is scored by the ARGs index, and a comprehensive score of each target gene is obtained based on the score and the weight of the ARGs index wherein represents the comprehensive score of the target gene, represents the weight value of the index , n is a constant; represents the single index score of the index , n is a constant; The target gene with a high comprehensive score is screened as an antibiotic resistance gene for priority monitoring in seawater environment.
2. The screening method for preferentially monitoring antibiotic resistance genes in a marine culture environment according to claim 1, characterized by, Each of the target genes is scored according to the ARGs index, specifically comprising: dividing each ARGs index into four levels, and assigning values of 20 points, 40 points, 60 points and 80 points, respectively; and assigning corresponding score values according to the evaluation results of the ARGs index of each target gene.
3. The screening method for preferentially monitoring antibiotic resistance genes in a marine culture environment according to claim 2, characterized by, The weight of each ARGs index is determined based on the analytic hierarchy process.
4. The screening method for preferentially monitoring antibiotic resistance genes in a marine culture environment according to claim 3, characterized by, The target gene to be evaluated is determined by coarse screening, specifically comprising: obtaining target ARGs and MGEs from target environmental samples and biological samples as target genes, or selecting a plurality of target ARGs and MGEs that need to be concerned according to the current situation of target environment and detecting them as target genes.
5. Ten antibiotic resistance genes to be prioritized for monitoring in mariculture environments, characterized in that, The screening method according to any one of claims 1-4 is applied to screen ten subtypes of antibiotic resistance genes from the pollution of antibiotic resistance genes commonly found in aquaculture environment, which are aadA-01 gene, aadA2 gene, cmlA gene, floR gene, mphA-01 gene, ereA gene, ermF gene, aac(6’)-Ib-cr gene, sul1 gene and sul2 gene, and the foregoing genes are applied to daily monitoring of seawater aquaculture environment; The nucleotide sequence of the aadA-01 gene is shown in SEQ ID NO. 78; The nucleotide sequence of the aadA2 gene is shown in SEQ ID NO. 77; The nucleotide sequence of the cmlA gene is shown in SEQ ID NO. 74; The nucleotide sequence of the floR gene is shown in SEQ ID NO. 73; The nucleotide sequence of the mphA-01 gene is shown in SEQ ID NO. 79; The nucleotide sequence of the ereA gene is shown in SEQ ID NO. 80; The nucleotide sequence of the ermF gene is shown in SEQ ID NO. 81; The nucleotide sequence of the aac(6’)-Ib-cr gene is shown in SEQ ID NO. 82; The nucleotide sequence of the sul1 gene is shown as SEQ ID NO. 75; The nucleotide sequence of the sul2 gene is shown as SEQ ID NO. 76.
Citation Information
Patent Citations
Pollution risk assessment method for antibiotic resistance gene
CN117219270A