Antibiotic resistance gene preferentially monitored in mariculture environment and screening method

Abstract

The invention discloses a screening method for preferentially monitoring antibiotic resistance genes in a mariculture environment and ten antibiotic resistance genes needing to be preferentially monitored. The screening method comprises the following steps: establishing an ARGs pollution evaluation index system, aRGs indexes in the ARGs pollution evaluation index system comprise environment occurrence frequency, environment pollution degree, environment mobility, co-occurrence indication, biological occurrence frequency and biological mobility; determining the weight of the ARGs index; performing coarse screening to determine to-be-evaluated target genes, performing ARGs index scoring on each target gene, and obtaining a comprehensive score of each target gene based on a scoring result and the weight of the ARGs index; and screening the first ten target genes with the highest comprehensive score as antibiotic resistance genes for preferential monitoring in the aquaculture environment.

Description

Technical Field

[0001] The invention relates to the technical field of environmental monitoring, in particular to antibiotic resistance genes that are preferentially monitored in a marine aquaculture environment. Background Art

[0002] At present, the control of antibiotic resistance is mainly based on the monitoring of antibiotics and resistant pathogens, and 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, there are mainly 296 types of concern, while more can be identified based on metagenomic technology. Not every ARG needs attention; 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 pathogenic bacteria databases, which can provide potential health risk data for ARGs, but it requires a large number of existing databases to support it, and the data processing is complex and cannot be maturely applied; and there is almost no ecological risk assessment. It is impossible to monitor, control and formulate standards for each ARG. We can only give priority to controlling some ARGs in special environments that pose a greater potential threat to human health and ecological balance. 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 pollution of ARGs.

[0003] Marine aquaculture is one of the environments closely related to human health. Due to the abuse and misuse of antibiotics, the spread and transmission of aquatic disease infections, and environmental pollution, the phenomenon of antibiotic resistance has risen sharply. The marine aquaculture area in my country is about 2.07 million hectares. ARGs in the aquaculture environment can directly enter the aquatic products as the bacteria proliferate and spread, posing a threat to human health; they can also spread with the aquaculture water or be regularly exchanged to natural water bodies, seriously affecting ecological health. Aquaculture tail water has even been considered by research to be an important source of ARGs in coastal waters. Therefore, it is urgent to prioritize the monitoring of ARGs in the marine aquaculture environment.

[0004] Unfortunately, the screening of priority monitoring ARGs is still blank. Traditional screening methods for priority monitoring and control are mainly based on potential hazard index method, comprehensive scoring method, weighted scoring method, hierarchical analysis method, etc. Each method has its own advantages and disadvantages, and the required data sets are also different. Summary of the invention

[0005] In view of the above-mentioned prior art, the present invention provides a method for screening antibiotic resistance genes for priority monitoring in marine aquaculture environments and ten antibiotic resistance genes that can be used for daily monitoring, mainly to solve the technical problems existing in the above-mentioned background technology.

[0006] To achieve the above object, the technical solution of the embodiment of the present invention is implemented as follows: The first aspect of the present invention provides a screening method for preferentially monitoring antibiotic resistance genes in a marine aquaculture environment, the screening method comprising: Establishing an ARGs pollution evaluation index system, wherein the ARGs indicators in the ARGs pollution evaluation index system include environmental occurrence frequency, environmental pollution degree, environmental mobility, co-occurrence indicator, biological occurrence frequency, and biological mobility; Determining the weight of the ARGs indicator; Roughly screen and determine the target gene to be evaluated, calculate the ARGs index value of each target gene, and perform ARGs index scoring on each target gene ,in Represents the comprehensive score of the target gene, Indicators The weight value of Indicators The single indicator score of n is a constant, and the comprehensive score of each target gene is obtained based on the scoring result and the weight of the ARGs indicator; Target genes with higher comprehensive scores were screened as antibiotic resistance genes for priority monitoring in seawater environments.

[0007] Optionally, an ARGs index score is performed for each of the target genes, specifically including: dividing each ARGs index into 4 levels, assigning values ​​of 20 points, 40 points, 60 points and 80 points respectively, and assigning corresponding score values ​​according to the ARGs index evaluation results of each target gene.

[0008] Optionally, the weight of each of the ARGs indicators is determined based on the hierarchical analysis method.

[0009] Optionally, a rough screening is performed to determine the target genes to be evaluated, specifically including obtaining target ARGs and MGEs as target genes from target environmental samples and biological samples, or, based on the current status of target environmental research, selecting a plurality of target ARGs and MGEs that need attention and detecting them as target genes.

[0010] An application for monitoring antibiotic resistance pollution in a marine aquaculture environment, using the screening method as described in any of the above items, to screen out ten subtypes of antibiotic resistance genes from common antibiotic resistance gene pollution 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 above genes are used for daily monitoring of marine aquaculture environments; The aadA-01 gene is amplified by the primer sequences described in SEQ ID NO.49 and SEQ ID NO.50; The aadA2 gene is amplified by the primer sequences described in SEQ ID NO.47 and SEQ ID NO.48; The cmlA gene is amplified by the primer sequences described in SEQ ID NO.27 and SEQ ID NO.28; The floR gene is amplified by the primer sequences described in SEQ ID NO.25 and SEQ ID NO.26; The mphA-01 gene is amplified by the primer sequences described in SEQ ID NO.51 and SEQ ID NO.52; The ereA gene is amplified by the primer sequences described in SEQ ID NO.53 and SEQ ID NO.54; The ermF gene is amplified by the primer sequences described in SEQ ID NO.57 and SEQ ID NO.58; The aac(6')-Ib-cr gene is amplified by the primer sequences described in SEQ ID NO.67 and SEQ ID NO.68; The sul1 gene is amplified by the primer sequences described in SEQ ID NO.29 and SEQ ID NO.30; The sul2 gene is amplified by the primer sequences described in SEQ ID NO.31 and SEQ ID NO.32.

[0011] The beneficial effects of the present invention are as follows: the method of the present invention effectively fills the gap in the current priority monitoring and screening of antibiotic resistance genes. The overall method is reasonably designed and conforms to the principles of scientificity and rationality. ARGs that need to be focused on are screened out based on the hierarchical analysis method and the comprehensive scoring method, which can provide a strong basis for the daily monitoring and control of ARGs pollution. The model of the calculation method of the present invention is universal and extensible. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 This is a schematic diagram of a screening method for preferentially monitoring antibiotic resistance genes in a marine aquaculture environment in an embodiment of the present application; Figure 2 This is a schematic diagram of the composition of the ARGs pollution evaluation index system in the embodiment of the present application; Figure 3 These are the single evaluation index results for the 33 ARGs in the examples of this application. DETAILED DESCRIPTION

[0013] The technical solution of the present invention is further elaborated in detail below in conjunction with the drawings and specific embodiments of the specification. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field 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. In the following description, the expression "some embodiments" is related to 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.

[0014] In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is apparent to those skilled in the art that the present invention can be implemented without one or more of these details. In other examples, in order to avoid confusion with the present invention, some technical features well known in the art are not described.

[0015] It should be understood that the present invention can be implemented in different forms and should not be interpreted as being limited to the embodiments proposed herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and the scope of the present invention will be fully conveyed to those skilled in the art. And the purpose of the terms used herein is only to describe specific embodiments and is not intended to be a limitation of the present invention. When used herein, the singular forms of "one", "one" and "said / the" are also intended to include plural forms, unless the context clearly indicates another way. It should also be understood that the terms "compose" and / or "include" when used in this specification determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0016] It should also be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "inside", "outside", "left", "right" and similar expressions used herein are for illustrative purposes only and are not intended to be the only implementation method.

[0017] In order to fully understand the present invention, a detailed structure will be proposed in the following description to illustrate the technical solution proposed by the present invention. The optional embodiments of the present invention are described in detail as follows, but in addition to these detailed descriptions, the present invention may also have other implementations.

[0018] Please refer to the attached Figure 1 The first aspect of the present invention provides a screening method for preferentially monitoring antibiotic resistance genes in a marine aquaculture environment, the screening method comprising: S1. Establishing an ARGs pollution evaluation index system, wherein the ARGs indicators in the ARGs pollution evaluation index system include environmental occurrence frequency, environmental pollution degree, environmental mobility, co-occurrence indicator, biological occurrence frequency, and biological mobility; Specifically, ARGs in the marine aquaculture environment can directly cause risks to the environment, so the present invention selects the environmental effect of ARGs as the primary indicator. At the same time, compared with traditional environmental areas, marine aquaculture has high-density and high-intensity characteristics, and ARGs will threaten the health of aquatic products. The typical or concerning organisms in the aquaculture environment are more clear, so the biological effect of aquatic products is selected as another primary indicator.

[0019] Environmental effect indicators can represent the frequency of environmental occurrence and the degree of environmental pollution, and are used to reflect the degree of pollution of ARGs in the target marine aquaculture environment. They include the following secondary indicators: 1. Environmental occurrence frequency, which refers to the detection rate of ARGs in the marine environmental medium; 2. Environmental pollution degree, which refers to the proportion of the total relative abundance of ARGs in the total relative abundance of ΣARGs, X; 3. Environmental mobility, which refers to the significance of the positive correlation between ARGs and mobile genetic elements (MGEs); 4. Co-occurrence indicator, which refers to the proportion of the connectivity of ARGs in the co-occurrence network analysis to the total connectivity, Y; The biological effect indicators include the following secondary indicators: 1. Biological occurrence frequency; it indicates the detection rate of ARGs in aquatic products, reflecting the contamination of ARGs in aquatic products; 2. Biological mobility, that is, the significance of the positive correlation between ARGs and MGEs in aquatic products, reflecting the ability of ARGs to migrate and spread in aquatic products.

[0020] S2. Determine the weight of the ARGs indicator; The weights of the evaluation indicators for priority monitoring of ARGs are calculated based on the analytic hierarchy process, which is divided into four steps: establishing a systematic hierarchical model, constructing a single-objective judgment matrix, hierarchical single sorting and consistency test, and hierarchical total sorting and consistency test.

[0021] S21. Establish a systematic hierarchical model. According to the determined screening and evaluation indicators, establish a systematic hierarchical structure. According to the significance of the indicators, it is divided into three levels. See Figure 2 .

[0022] S21. Construct a single-target judgment matrix. The present invention uses the 1-9 scaling method to compare and judge between two indicators at each level. The meaning of the scale between indicators is shown in Table 1: Table 1 Definition of important scales between indicators

[0023] Construct judgment matrices at each level , determine the relative importance of each evaluation index, and use the geometric mean method (Formula 1) to calculate the weight vector of each index .

[0024] ,i=1,2,3...n (1) The judgment matrix composed of level A and level B is F 1. As shown in Table 2, the judgment matrix composed of level B1 and level C F 2, as shown in Table 3; Judgment matrix composed of level B2 and level C F 3, as detailed in Table 4.

[0025] Table 2

[0026] Table 3

[0027] Table 4

[0028] S23, hierarchical single sorting and consistency test. Calculate and find according to formula (2) and Table 5 F 1. F 2. F 3 Matrix consistency index CI and the average random consistency index RI , and calculate the consistency ratio according to formula (3) CR, when CR When <0.10, the matrix consistency is acceptable.

[0029] (2) (3) in, is the largest eigenvalue of the matrix.

[0030] Table 5 Average random consistency index of 1~15 dimensional matrices repeated 1000 times

[0031] Judgment Matrix F 1. F 2. F 3The consistency test results are as follows: CR All are less than 0.10, and the consistency test passed: F 1 ： ; ; ; ; F 2 ： ; ; ; ; F 3 ： ; ; ; ; S25, total ranking and consistency test of levels. B i The consistency index of a single sort is CI j , the corresponding average random consistency index is RI j , then the total ranking consistency ratio of level C is calculated according to formula 4.

[0032]

[0033] CR =0.0116<0.10, the consistency of the total ranking results of level C is acceptable.

[0034] After testing, the priority monitoring ARGs screening evaluation indicators and the established hierarchical structure model were reliable. The ranking weights of each screening evaluation indicator at level C were calculated according to formula (5). The results are shown in Table 6.

[0035]

[0036] Table 6 Weights of evaluation indicators

[0037] Finally, the ARGs and MGEs pollution data were substituted into the screening framework. The comprehensive scoring method was used to calculate the comprehensive score of ARGs based on the product of the single score of each evaluation indicator and the corresponding weight: ,in Represents the comprehensive score of the target gene, Indicator The weight value of Indicator The score of a single indicator, n is a constant.

[0038] S3. Roughly screen and determine the target gene to be evaluated, calculate the ARGs index value of each target gene, perform ARGs index scoring on each target gene, and obtain a comprehensive score for each target gene based on the scoring result and the weight of the ARGs index; Specifically, target environmental samples (water, sediment) and biological samples are taken, where biological samples mainly refer to the intestinal contents of typical or dominant aquatic products in marine aquaculture environments. Based on ultra-high throughput PCR and metagenomic technology, a comprehensive picture of the presence of ARGs and MGEs is obtained; or based on the current status of target environmental research, target ARGs and MGEs that need attention are roughly screened out and tested.

[0039] When scoring, each ARGs indicator is divided into four levels, with values ​​of 20, 40, 60 and 80 points respectively. The specific grading standards for each indicator are shown in Table 7.

[0040] Table 7 Evaluation index classification and scores

[0041] For example, due to the large number of ARGs subtypes, in order to narrow the screening scope, the embodiment roughly screened out 33 ARGs, 2 integron genes and internal reference genes that are more common in aquaculture environments based on relevant research reports on ARGs in aquaculture environments. 16S rRNA As target genes, see Table 8 for details.

[0042] Table 8 36 genes commonly found in aquaculture environments

[0043] Subsequently, water samples and biological intestinal samples from four aquaculture environments (a total of 53 water bodies and 7 biological samples including hairtail, sweet sea bream, whitefish, turbot, pike, black sea bream, and golden pomfret) were collected, sample genes were extracted using a kit, and 36 target genes were detected based on ultra-high throughput qPCR technology to obtain the basic pollution status of 33 ARGs in the four areas.

[0044] The six screening index results of each ARG were calculated (environmental occurrence frequency, that is, 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 relationship between each ARGs and mobile genetic elements ( intl1 / intl2) significance of positive correlation. Co-occurrence indicator refers to the proportion of connectivity of each ARG in the co-occurrence network analysis to the total connectivity. This example uses relative abundance data, based on pairwise Spearman rank correlation, to retain significant (p < 0.05) relationships for network visualization. Biological occurrence frequency refers to the detection frequency of each ARGs in biological samples. Biological mobility refers to the frequency of each ARGs in biological samples and mobile genetic elements ( intl1 / intl2 ) for the significance of the positive correlation. Figure 3 , Figure 3 Results of single evaluation indicators for 33 ARGs.

[0045] According to the classification and scoring standards of each indicator (Table 7), the single evaluation indicator results of ARGs are scored, and further combined with the corresponding weights of the indicators ( Figure 3 ), the scores of single evaluation indicators and comprehensive scores of 33 ARGs were calculated using the comprehensive score calculation formula. The specific results are shown in Table 9.

[0046] Table 9 Single evaluation index scores of 33 ARGs

[0047] In order to illustrate the uniqueness of the aforementioned gene names, the primer sequences of the target genes are listed in Table 10.

[0048] Table 10

[0049] S4. Screen the top ten target genes with the highest comprehensive scores as antibiotic resistance genes for priority monitoring in seawater environments.

[0050] For example, considering the diversity of ARGs, this example takes the top 10 ARGs in the total score results obtained above and determines them as the ARGs to be monitored in the aquaculture environment water. The 10 ARGs subtypes in the water body include aminoglycosides ( aadA-01 , aadA2 ) two, chloramphenicol ( A , fR ) two, macrolides ( mphA-01 , eA , f ) three, quinolones ( aac(6')-Ib-cr ) a, sulfonamide ( sul1 , sul2 These selected ARGs subtypes comprehensively reflect the six selected indicators C1-C6, and are representative for preliminarily reflecting the daily status of ARGs in the aquaculture environment.

[0051] The second aspect of the present invention provides an application for monitoring antibiotic resistance pollution in aquaculture environments, using the screening method described in any of the above items to screen out ten subtypes of antibiotic resistance genes from common antibiotic resistance gene pollution 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 aforementioned genes are used for daily monitoring of the marine aquaculture environment; The aadA-01 gene is amplified by the primer sequences described in SEQ ID NO.49 and SEQ ID NO.50; The aadA2 gene is amplified by the primer sequences described in SEQ ID NO.47 and SEQ ID NO.48; The cmlA gene is amplified by the primer sequences described in SEQ ID NO.27 and SEQ ID NO.28; The floR gene is amplified by the primer sequences described in SEQ ID NO.25 and SEQ ID NO.26; The mphA-01 gene is amplified by the primer sequences described in SEQ ID NO.51 and SEQ ID NO.52; The ereA gene is amplified by the primer sequences described in SEQ ID NO.53 and SEQ ID NO.54; The ermF gene is amplified by the primer sequences described in SEQ ID NO.57 and SEQ ID NO.58; The aac(6')-Ib-cr gene is amplified by the primer sequences described in SEQ ID NO.67 and SEQ ID NO.68; The sul1 gene is amplified by the primer sequences described in SEQ ID NO.29 and SEQ ID NO.30; The sul2 gene is amplified by the primer sequences described in SEQ ID NO.31 and SEQ ID NO.32.

[0052] Exemplarily, the aforementioned ten genes are applied in a baseline survey, that is, in one breeding cycle, quantitative PCR or high-throughput quantitative PCR and other technologies are used to detect the concentrations of ten priority monitored resistance genes in the target breeding and surrounding environment to obtain background data, while recording the use of antibiotics, feed additives, etc., and correlating potential pollution sources with gene concentration data.

[0053] Furthermore, in some optional implementations, warning thresholds are set with reference to background data and actual conditions of the breeding cycle, and the contamination of the ten resistance genes is continuously and regularly monitored.

[0054] In summary, the ARGs pollution evaluation index system disclosed in this application covers six major indicators: environmental occurrence frequency, environmental pollution degree, environmental mobility, co-occurrence indicator, biological occurrence frequency, and biological mobility, covering the core dimensions of ARGs distribution abundance in the environment, transmission potential, pollution level in organisms, and health risks. Environmental occurrence frequency and pollution degree reflect the ecological load of ARGs; environmental / biological mobility is evaluated by the co-occurrence of MGEs, which is consistent with the mechanism of ARGs transmission through horizontal gene transfer; co-occurrence indicator is based on network analysis, revealing the correlation between ARGs and other microbial functions; weight-determined hierarchical analysis method: AHP is an internationally recognized multi-criteria decision-making method. It constructs a judgment matrix and calculates weights through expert scoring, uses a 1-9 scale method to quantify the importance of indicators, reduces subjective arbitrariness, and ensures self-consistency of judgment logic through strict consistency tests (CR<0.1).

[0055] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A screening method for preferentially monitoring antibiotic resistance genes in a marine aquaculture environment, characterized in that: The screening method comprises: Establishing an ARGs pollution evaluation index system, wherein the ARGs indicators in the ARGs pollution evaluation index system include environmental occurrence frequency, environmental pollution degree, environmental mobility, co-occurrence indicator, biological occurrence frequency, and biological mobility; Determining the weight of the ARGs indicator; The target gene to be evaluated is determined by rough screening, and each target gene is scored by the ARGs index, and the comprehensive score of each target gene is obtained based on the scoring result and the weight of the ARGs index. ,in Represents the comprehensive score of the target gene, Indicator The weight value of Indicator The score of a single indicator, n is a constant; Target genes with higher comprehensive scores were screened as antibiotic resistance genes for priority monitoring in seawater environments.

2. The method for screening antibiotic resistance genes for priority monitoring in a marine aquaculture environment according to claim 1, characterized in that: The ARGs index is scored for each target gene, specifically including: each ARGs index is divided into 4 levels, and the values ​​are assigned to 20 points, 40 points, 60 points and 80 points respectively, and the corresponding score value is assigned according to the ARGs index evaluation result of each target gene.

3. The method for screening antibiotic resistance genes for priority monitoring in a marine aquaculture environment according to claim 2, characterized in that: The weight of each ARGs indicator is determined based on the hierarchical analysis method.

4. The method for screening antibiotic resistance genes for priority monitoring in a marine aquaculture environment according to claim 3, characterized in that: The target genes to be evaluated are determined by rough screening, specifically including obtaining target ARGs and MGEs as target genes from target environmental samples and biological samples, or, based on the current status of target environmental research, selecting multiple target ARGs and MGEs that need attention and detecting them as target genes.

5. Ten antibiotic resistance genes that are prioritized for monitoring in marine aquaculture environments are characterized by: Using the screening method as described in any one of claims 1 to 4, ten subtypes of antibiotic resistance genes are screened out from common antibiotic resistance gene pollution 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 aforementioned genes are used for daily monitoring of marine aquaculture environments; 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 in SEQ ID NO.75; The nucleotide sequence of the sul2 gene is shown in SEQ ID NO.76.

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