阅读说明：本技术 一种识别特异性标记物地区适用性的评价方法 (Evaluation method for identifying applicability of specific marker in area ) 是由 吴仁人 张杨 陈中颖 李文静 于 2020-04-01 设计创作，主要内容包括：本发明公开了一种识别特异性标记物地区适用性的评价方法,包括步骤：S1：采集样品,并提取DNA；S2：选取特异性引物；S3：制作qPCR反应和标准曲线；S4：选择灵敏度、特异性、源强特征、25th/75th阈值、目标源25th/75th作为评价引物适用性的指标,并计算各个指标的值；S5：利用层次分析法对引物灵敏度、特异性、源强特征、25th/75th阈值、目标源25th/75th五类参数指标进行定权,以得到各引物的综合适应性评价。本发明方法可有效筛选出既具有特异性优势,且兼顾检出水平较高、检出浓度较为稳定的宿主特异性标记物用于后续的水体微生物污染定量源解析工作。(The invention discloses an evaluation method for identifying the applicability of a specific marker area, which comprises the following steps: s1: collecting a sample and extracting DNA; s2: selecting a specific primer; s3: making qPCR reaction and standard curve; s4: selecting sensitivity, specificity, source intensity characteristics, 25th/75th threshold value and target source 25th/75th as indexes for evaluating the applicability of the primers, and calculating the value of each index; s5: and (3) weighting five parameter indexes including sensitivity, specificity, source intensity characteristics, 25th/75th threshold value and target source 25th/75th by using an analytic hierarchy process to obtain comprehensive adaptability evaluation of each primer. The method can effectively screen the host specific marker which has the advantages of specificity, higher detection level and more stable detection concentration for subsequent analysis of the water body microbial pollution quantitative source.)

1. An evaluation method for the regional applicability of a recognition specific marker, comprising the steps of:

s1: collecting a sample and extracting DNA;

s2: selecting a specific primer;

s3: making qPCR reaction and standard curve;

s4: selecting sensitivity, specificity, source intensity characteristics, 25th/75th threshold value and target source 25th/75th as indexes for evaluating the applicability of the primers, and calculating the value of each index;

s5: and (3) weighting five parameter indexes including sensitivity, specificity, source intensity characteristics, 25th/75th threshold value and target source 25th/75th by using an analytic hierarchy process to obtain comprehensive adaptability evaluation of each primer.

2. The method for evaluating the regional suitability of a specific marker for recognition according to claim 1, wherein in step S1, the DNA is extracted by: and (3) adopting a fecal genome extraction kit, uniformly mixing each part of feces, weighing a certain amount of feces, putting the feces into a sterilized centrifuge tube, and further extracting DNA according to the kit specification.

3. The method for evaluating the regional suitability of a specific marker for identification according to claim 1, wherein in step S3, after the specific primers are selected, the selected host-specific primers are amplified using fecal sample DNAs of different human and animals as templates; in order to construct a standard product, PCR amplification is carried out on each specific primer by adopting corresponding sample DNA, and the amplified target product is purified and recovered by a DNA purification kit;

ligation of the recovered phage primer amplification product to the targetConnecting other recovered products to pMD 19-TVector vector on-T vector, transforming to DH5 α competent cell, screening positive clone with plate culture medium containing 1:1000 ampicillin, extracting plasmid DNA, determining corresponding DNA concentration, calculating copy number of target segment, diluting the prepared plasmids 10 times in gradient to 10 times^-0,10^-1，10^-2，10^-3，10^-4，10^-5，10^-67 gradients; using each gradient plasmid as template, setting 3 repeats for each gradient, andand (3) performing qPCR amplification, constructing corresponding standard curves through Cq values obtained by reaction, wherein the correlation coefficient of each standard curve is larger than 0.97, and the amplification efficiency is between 90 and 110 percent, which indicates that each standard curve is qualified.

4. The method for assessing regional suitability for identification of specific markers of claim 3 wherein qPCR amplification comprises both fluorescent dye and fluorescent probe methods.

5. The method for assessing the regional suitability of a specific marker for identification according to claim 1, wherein the sensitivity and specificity are calculated in step S4 by counting the positive and negative reactions in the amplification result using the lowest limit of quantitation of each primer as a threshold.

6. The method for evaluating the suitability of a region for identifying a specific marker according to claim 1, wherein the source intensity characteristic, the 25th/75th threshold value, and the target source 25th/75th belong to quantitative analysis indexes calculated based on the detection concentrations of the primers for the target source and the non-target source in step S4.

7. The method for evaluating the regional applicability of the recognition specific marker according to claim 1, wherein in step S5, five types of parameter indexes are weighted by an analytic hierarchy process to obtain a comprehensive applicability evaluation of each primer, and the method comprises:

s5.1: establishing a hierarchical structure, namely sequentially arranging a target layer A, a criterion layer B and a variable layer C from the highest layer to the lowest layer, wherein the target layer A is used for evaluating the adaptability of the primers; the criterion layer B refers to five types of parameter indexes for representing adaptability, and the variable layer C refers to candidate primers, namely primers to be evaluated;

s5.2: constructing a judgment matrix for the criterion layer B: establishing a judgment matrix according to the comparison of importance degrees of five parameter indexes, namely sensitivity, specificity, source intensity characteristics, a 25th/75th threshold value and a target source 25th/75 th;

s5.3: calculating the maximum characteristic value and the corresponding characteristic root of the judgment matrix constructed by the criterion layer B;

s5.4: carrying out consistency check on the judgment matrix;

s5.5: if the calculation result of the step S5.3 passes the consistency check, taking the calculation result as the determined maximum characteristic value and the corresponding characteristic root, wherein the characteristic root corresponding to the maximum characteristic value is the relative weight of the five types of parameter indexes of the layer B when the target layer A is aligned;

s5.6: calculating the scores of the primers of the variable layer C under each index of the criterion layer B, namely standardizing the primer characteristic representation values of the primers of the variable layer C under each parameter index of the criterion layer B, which are obtained by experiments;

s5.7: and weighting the scoring condition of each primer of the variable layer C under each parameter evaluation index of the criterion layer B, wherein the weight is the weight from the target layer A to the criterion layer B, and obtaining the adaptive comprehensive score of each primer.

8. The method for evaluating the regional applicability of the identification specific marker as claimed in claim 7, wherein in step S5.3, the maximum eigenvalue of the judgment matrix and the corresponding characteristic root are calculated by a square root method, and the steps are as follows:

s5.3.1, calculating the geometric mean value of all elements in each row of the judgment matrix:

to obtain A vector representing the average composition of the rows; j denotes the j-th column of the decision matrix, a_ijAn element representing the ith row and the jth column of the judgment matrix, wherein i represents the ith row of the judgment matrix;

s5.3.2, willNormalization, i.e. calculating:

to obtainThe feature root corresponding to the maximum feature value is the relative weight omega of the five parameter indexes of the layer B when the target layer A is aligned;

s5.3.3, calculating the maximum characteristic value of the judgment matrix:

whereinThe i-th element of the vector a ω, a represents the decision matrix.

9. The method according to claim 7, wherein in step S5.4, the consistency of the judgment matrix is tested by introducing a random consistency ratio CR, and the calculation formula is as follows:

in the formula: p is the order of the judgment matrix, CI is a consistency index, CR is a random consistency ratio, RI is a random consistency index, if CR <0.1, the judgment matrix has good consistency and is reasonable in judgment; if CR is equal to 0.1, judging that the matrix has better consistency and more reasonable judgment; if CR is greater than 0.1, the matrix is judged not to be in accordance with the consistency principle and needs to be readjusted.

10. The method for evaluating the regional applicability of the identification specific marker according to claim 7, wherein in step S5.6, for the parameter index of which the higher the characterization value of the experimental primer characteristic is, the better the primer adaptability is, the standardized formula is as follows:

for the parameter index of which the characteristic value of the experimental primer is larger, the adaptability of the primer is poorer, the standardized formula is as follows:

wherein x is_ijRefers to the non-standardized experimental score of the ith primer under the jth parameter index, y_ijRefers to the normalized experimental score of the ith primer under the jth parameter index.

Technical Field

The invention relates to the field of microbial pollution prevention and treatment research, in particular to an evaluation method for identifying the applicability of a specific marker in a region.

Background

Human and animal feces contain various pathogenic microorganisms and enteroviruses, and the untreated (or incompletely treated) feces are discharged into natural water bodies, so that serious water body microbial pollution is caused, and great risks are brought to human health. For example, many areas of china have reported cases of norovirus gastroenteritis each year, with the primary route of transmission being "fecal-oral". And the new coronavirus (2019-nCoV) outbreak at the end of 2019 also has the possibility of spreading through feces-mouth. Therefore, how to quickly and accurately identify the microbial pollution sources and evaluate the contribution rates of the respective pollution sources becomes a key link for effectively carrying out targeted source control and reducing the risk of microbial pollution.

Indicator microorganisms such as faecal coliform and escherichia coli have been used by countries in the world for many years as traditional indicators for reflecting the microbial pollution condition of water bodies, and the surface water environmental quality standard (GB3838-2002) of China also adopts faecal coliform to establish corresponding water quality evaluation standards. However, the conventional indicator microorganisms widely exist in intestinal tracts of various animals, only reflect the fecal pollution level of natural water, cannot identify the fecal pollution source, and cannot analyze the contribution rate of each pollution source. Because of lack of accurate information of a microorganism pollution source, the prevention and treatment of the microorganism pollution of the water body still stays in a passive mode of 'pollution treatment by pollution', not only the cost of pollution treatment is increased, but also the difficulty in preventing the transmission of water-mediated diseases is serious. In order to solve the problems, developed countries in Europe, America and the like have developed microbial pollution source analysis technology based on host specific biological markers in recent years, and specific primers of various animals such as human, pig, ruminant, poultry and the like are designed by taking specific fragments of microbial sequences such as bacteroides, bacteriophage and the like in different hosts as target sequences, so that effective information is provided for targeted treatment of water body microbial pollution.

However, due to differences in dietary habits, climate, lifestyle, etc. in different regions, the composition and structure of intestinal microorganisms in various hosts generally exhibit regional variability. Therefore, the performance of the same primer may vary greatly in different regions. The method is an important link for analyzing the water body microbial pollution source by verifying the applicability and the effectiveness of each primer in a target research area in advance. In the past, two indexes of sensitivity and specificity are generally adopted for primer applicability evaluation, but the two evaluation factors can only carry out qualitative analysis on primer characteristics and are difficult to reflect the expression levels of primers in different regions, so that microbial contamination from different host sources can not be quantified due to the difference of the detection concentration of each primer in the practical application process.

Disclosure of Invention

The invention mainly aims to overcome the defects and shortcomings of the prior art and provide an evaluation method for identifying the regional applicability of a specific marker.

The purpose of the invention is realized by the following technical scheme: an evaluation method for identifying the applicability of a specific marker in a region comprises the following steps:

s1: collecting a sample and extracting DNA;

s2: selecting a specific primer;

s3: making qPCR reaction and standard curve;

s4: selecting sensitivity, specificity, source intensity characteristics, 25th/75th threshold value and target source 25th/75th as indexes for evaluating the applicability of the primers, and calculating the value of each index;

s5: and (3) weighting five parameter indexes including sensitivity, specificity, source intensity characteristics, 25th/75th threshold value and target source 25th/75th by using an analytic hierarchy process to obtain comprehensive adaptability evaluation of each primer.

Preferably, in step S1, the DNA extraction method is: and (3) adopting a fecal genome extraction kit, uniformly mixing each part of feces, weighing a certain amount of feces, putting the feces into a sterilized centrifuge tube, and further extracting DNA according to the kit specification. The extracted DNA was measured for mass by an ultramicro spectrophotometer and stored in a refrigerator at-20 ℃.

Preferably, in step S3, after selecting specific primers, amplifying the selected host specific primers by using DNA of stool samples of different humans and animals as templates; in order to construct a standard product, PCR amplification is carried out on each specific primer by adopting corresponding sample DNA, and the amplified target product is purified and recovered by a DNA purification kit;

ligation of the recovered phage primer amplification product to the targetConnecting other recovered products to pMD19-T Vector, transforming to DH5 α competent cells, screening positive clone with plate culture medium containing 1:1000 ampicillin, extracting plasmid DNA, determining corresponding DNA concentration, calculating copy number of target fragment, diluting the prepared plasmids 10 times in gradient to 10^-0,10^-1，10^-2，10^-3，10^-4，10^-5，10^-67 gradients; using each gradient plasmid as template, setting 3 repeats for each gradient, carrying out qPCR amplification, constructing corresponding standard curve by Cq value obtained by reaction, and correlation coefficient (R) of each standard curve²) All are larger than 0.97, and the amplification efficiency is between 90 and 110 percent, which indicates that each standard curve is qualified.

Further, qPCR amplification includes both fluorescent dye and fluorescent probe methods.

Preferably, in step S4, the sensitivity and specificity are calculated by counting the positive and negative reactions in the amplification result using the lowest limit of quantitation of each primer as a threshold.

Preferably, in step S4, the source intensity characteristic, the 25th/75th threshold, and the target source 25th/75th belong to quantitative analysis indexes, and are calculated based on the detection concentrations of the primers with respect to the target source and the non-target source.

Preferably, in step S5, five types of parameter indexes are weighted by an analytic hierarchy process to obtain a comprehensive suitability evaluation of each primer, which includes:

s5.1: establishing a hierarchical structure, namely sequentially arranging a target layer A, a criterion layer B and a variable layer C from the highest layer to the lowest layer, wherein the target layer A is used for evaluating the adaptability of the primers; the criterion layer B refers to five types of parameter indexes for representing adaptability, and the variable layer C refers to candidate primers, namely primers to be evaluated;

s5.2: constructing a judgment matrix for the criterion layer B: establishing a judgment matrix according to the comparison of importance degrees of five parameter indexes, namely sensitivity, specificity, source intensity characteristics, a 25th/75th threshold value and a target source 25th/75 th;

s5.3: calculating the maximum characteristic value and the corresponding characteristic root of the judgment matrix constructed by the criterion layer B;

s5.4: carrying out consistency check on the judgment matrix;

s5.5: if the calculation result of the step S5.3 passes the consistency check, taking the calculation result as the determined maximum characteristic value and the corresponding characteristic root, wherein the characteristic root corresponding to the maximum characteristic value is the relative weight of the five types of parameter indexes of the layer B when the target layer A is aligned;

s5.6: calculating the scores of the primers of the variable layer C under each index of the criterion layer B, namely standardizing the primer characteristic representation values of the primers of the variable layer C under each parameter index of the criterion layer B, which are obtained by experiments;

s5.7: and weighting the scoring condition of each primer of the variable layer C under each parameter evaluation index of the criterion layer B, wherein the weight is the weight from the target layer A to the criterion layer B, and obtaining the adaptive comprehensive score of each primer.

Further, in step S5.3, the maximum eigenvalue of the judgment matrix and the corresponding characteristic root are calculated by using a square root method, which includes the following steps:

s5.3.1, calculating the geometric mean value of all elements in each row of the judgment matrix:

to obtainA vector composed of the average values of the rows, j represents the j-th column of the judgment matrix, a_ijAn element representing the ith row and the jth column of the judgment matrix, wherein i represents the ith row of the judgment matrix;

s5.3.2, willNormalization, i.e. calculating:

to obtainThe feature root corresponding to the maximum feature value is the relative weight omega of the five parameter indexes of the layer B when the target layer A is aligned;

s5.3.3, calculating the maximum characteristic value of the judgment matrix:

whereinThe i-th element of the vector a ω, a represents the decision matrix.

Furthermore, in step S5.4, the consistency check is performed on the judgment matrix by introducing a random consistency ratio CR, and the calculation formula is as follows:

in the formula: p is the order of the judgment matrix, CI is a consistency index, CR is a random consistency ratio, RI is a random consistency index, if CR <0.1, the judgment matrix has good consistency and is reasonable in judgment; if CR is equal to 0.1, judging that the matrix has better consistency and more reasonable judgment; if CR is greater than 0.1, the matrix is judged not to be in accordance with the consistency principle and needs to be readjusted.

Furthermore, in step S5.6, for the parameter index with better primer adaptability as the characteristic value of the experimental primer is larger, the standardized formula is as follows:

for the parameter index of which the characteristic value of the experimental primer is larger, the adaptability of the primer is poorer, the standardized formula is as follows:

wherein x is_ijRefers to the non-standardized experimental score of the ith primer under the jth parameter index, y_ijRefers to the normalized experimental score of the ith primer under the jth parameter index.

Compared with the prior art, the invention has the following advantages and beneficial effects:

in the invention, the conventional primer applicability evaluation index is improved, and a new evaluation method is established. The improved evaluation method increases quantitative analysis indexes, so that the evaluation indexes are improved. Meanwhile, the regional applicability of the primers can be more accurately and comprehensively evaluated by determining the weight of each index in an evaluation system, and the performance of the primers in different regions can be more intuitively understood. The primer screened by the invention can accurately identify the source and contribution rate of microbial pollution in the environmental water body.

Drawings

FIG. 1 is a schematic diagram of a sample collection city in this example.

FIG. 2(a) is a graph showing the detected concentration distribution of human-derived specific primers.

FIG. 2(b) is a graph showing the detected concentration distribution of the non-human specific primers.

Fig. 3 is a flowchart of the method of the present embodiment.

Detailed Description

The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.