CN113981042B - High-throughput detection method for strain and risk genes in microbial feed product - Google Patents
High-throughput detection method for strain and risk genes in microbial feed product Download PDFInfo
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- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
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- C12Q1/6806—Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay
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- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6869—Methods for sequencing
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Abstract
The invention belongs to the technical field of agriculture, and particularly relates to a high-throughput detection method for strain and risk genes in a microbial product for feeding. The high-throughput detection method of strains in the microbial product for feeding comprises the following steps: extracting genome DNA of microorganisms in a sample to be detected; performing high throughput sequencing; carrying out data analysis on the high-throughput sequencing result to obtain abundance of each microorganism; and displaying the result of the abundance of the microorganisms, wherein the displayed result is displayed as Chinese. The method can effectively extract the total DNA in the microbial feed product, accurately screen non-targeted pathogenic bacteria, quantitatively analyze the content of strains allowed to be used in the feed additive variety catalogue, analyze drug-resistant genes, mobilizable drug-resistant genes and virulence genes in the microbial feed product, analyze the risks of target genes and trace the strains in Chinese description, and effectively solve the problems of the microbial feed product.
Description
Technical Field
The invention belongs to the technical field of agriculture, and particularly relates to a high-throughput detection method for strain and risk gene analysis and strain tracing in a microbial product for feeding.
Background
China is the largest breeding country in the world, and the degree of standardization is in a continuous trend. With the stable development of livestock breeding and the acceleration of the progress of non-resistance breeding, the microbial product for feeding is one of important substitute products of antibiotics, and has good market prospect. However, the rapid development of the market also brings new problems, and the production level of some enterprises is low, so that the products contain pathogenic microorganisms, and some enterprises lack professional background and even use the mixed bacteria except 36 allowed used bacteria in the feed additive variety catalogue (2013) as fermentation strains for mass production, so that huge losses of the breeding industry can be caused due to animal diseases, and meanwhile, human diseases can be caused due to part of pathogenic bacteria, so that serious threat is caused to the life safety of people.
On the other hand, due to the lack of effective detection means, some production strains used by enterprises belong to strains allowed to be used in the feed additive variety catalogue (2013), but contain a large number of risk genes, such as virulence genes, drug resistance genes and mobilizable drug resistance genes, so that the production strains not only cause environmental pollution, but also threaten human and livestock, even can generate super drug resistance bacteria through gene transfer, accelerate the failure of the existing antibiotics, and lead the human to be eventually non-drug and medical. The pollution bacteria in the product also contain the risk genes, so that a method for detecting the risk genes in the product and the production strain and analyzing the strain tracing is required to be established, so that the risk points of the microbial product for feeding can be quickly and effectively searched, the quality control level is improved for enterprises.
The following problems exist in the current microbial products for feeding: (1) a portion of the product contains pathogenic bacteria, creating a use risk; (2) partial product purity is insufficient, and the content of target bacteria is low; (3) Part of products have different using strains and identifiers, and have potential safety hazards; (4) The strain and the product contain virulence genes, drug-resistant genes, mobilizable drug-resistant genes and other risk genes.
The existing detection means and corresponding standards cannot effectively analyze unknown pathogenic bacteria, and do not have a non-targeting detection function. The traditional method has larger limitation: the purity of the detection degree is detected through plate counting, the workload is large, and the accuracy is poor. Most of plate counting belongs to targeted detection, and only one type of plate counting can be detected at a time. The broad-spectrum culture medium using nutrient agar can not reflect the comprehensive condition of the product, and the workload of separation and identification is huge and the time consumption is long; the bacteria with low bacterial load can not be detected. The resolution of the 16s rRNA sequencing to identify the species was insufficient. 16s rRNA sequencing was once considered the gold standard for molecular identification of bacterial species. However, since a large number of new strains are found and the total length of the 16s rRNA gene is only about 1500bp, identification of more and more strains, particularly lactic acid bacteria, is difficult to distinguish by only 16s rRNA sequencing. The PCR technology identifies virulence genes and drug-resistant genes in the strain, the cost is high, and false positives exist. Aiming at the microbial products for feeding and production strains, no mature technology is currently available for analyzing strain tracing of risk genes, especially tracing of migratable drug resistance. Although the Hi-C sequencing technology can trace strains of virulence genes and drug-resistant genes, the cost is high, and the technology is still immature.
In summary, in the prior art, there are no non-targeted detection method for mixed bacteria or pathogenic bacteria in a microbial product for feeding and no quantitative method for 36 strains in the category of feed additives (2013), and no methods for analyzing drug resistance genes, mobilizable drug resistance genes and virulence genes in microbial products for feeding, explaining target gene risks in Chinese and tracing low-cost strains.
Disclosure of Invention
The invention aims to provide a high-throughput detection method of strains suitable for microbial products for feeding.
The invention also aims to provide a high-throughput detection and strain tracing method suitable for the risk genes in the forage microbial products.
A method for high throughput detection of bacterial species in a feed microbial product according to an embodiment of the invention, the method comprising the steps of:
(1) Extracting genome DNA of microorganisms in a sample to be detected;
(2) Carrying out high-throughput sequencing on the genome DNA extracted in the step (1);
(3) Carrying out data analysis on the high-throughput sequencing result in the step (2) to obtain abundance of each microorganism;
(4) And (3) carrying out result display on the abundance of the microorganism obtained in the step (3):
S1, outputting the names and the abundance of the strains if the strains belong to the strains in the permission list;
S2, judging the abundance of the strain if the strain does not belong to the strain in the permission list,
Outputting the names and the abundance of the strains if the abundance of the strains is greater than or equal to 1.5%;
outputting the sum of the abundances of all the strains with the abundance less than 1.5% if the abundance of the strains is less than 1.5%.
The sample to be tested in the invention relates to the aspect of microbial feed products, and specifically comprises microbial feed additives, and other samples added with microbial strains for feed, such as commercial solid, liquid and semisolid (pasty) microbial feed additives and intermediate products in the production process of products, such as production strains, fermented products, products before packaging and the like.
When the abundance of a species in a sample is greater than the detection limit (1.5%) and is not in the allowed list, the sample is judged to be at risk.
It should be noted that, in the result display process, the names of the strains may be displayed as latin names, chinese names or both latin names and chinese names.
According to the high-throughput detection method of the strain in the feeding microbial product, in the step S2, if the abundance of the strain is more than or equal to 1.5% and less than 10%, a first marker of the strain is distributed; and if the abundance of the strain is greater than or equal to 10%, distributing a second marker of the strain.
In the present invention, the first and second markers refer to computer-recognizable and general symbols, for example, "" normal "" "" "" "," excellent "" "" "" "," ", and the like, which are used to indicate a risk sample and draw attention of related people.
And (3) when the result is displayed in the step (4), displaying the obtained strain abundance data by using a Python language or displaying by using other machine languages.
According to the high throughput detection method of strains in a feed microorganism product of an embodiment of the present invention, the data analysis of step (3) includes the steps of:
(3-1) data conversion: converting the high throughput sequencing result of step (2) into FASTQ format;
(3-2) data quality control: deleting the invalid sequence;
(3-3) species annotation: comparing the data processed in the step (3-2) with the sequence, and classifying the species;
(3-4) statistical analysis: and (3) counting the results of the sequence comparison in the step (3-3), and calculating to obtain the abundance of each microorganism.
In step (3-3), the optional species databases include Kraken databases or other databases such as the nt database of NCBI, env_nt, silva, etc.
In the step (3-4), the program for calculating the abundance of the microorganism includes Bracken programs and the like.
According to the high throughput detection method of strains in the feeding microbial product of the specific embodiment of the invention, in the step (3-2), the invalid sequence refers to a low quality sequence, a pollution sequence, a joint sequence and the like, and specifically can be set to comprise a sequence with the N base content of more than 10% in a single sequence or with the number of bases with the Q value of less than 5 of more than 50%; for example, a sequence contains 150 bases, the sequencing quality of each base is represented by a Q value, and when the number of bases with a Q value less than 5 exceeds 75, the sequence is discarded.
The permission list in the invention comprises a feed additive variety list.
The nutrient feed additives and general feed additives issued by the Ministry of agriculture in the catalogue of feed additives are in accordance with the varieties specified in the catalogue of feed additives, and any other additive except the catalogue of feed additives is not approved by the Ministry of agriculture and cannot be used as feed additives in feed production. The feed additive variety catalogue has been updated from 2006, 2008 version to 2013 version.
The method of the invention can be applied to strains disclosed in 2006 version, 2008 version and 2013 version of feed additive variety catalogue and other versions updated later.
According to the method for high throughput detection of bacterial species in a feed microorganism product of an embodiment of the present invention, the strains in the permission list include Bacillus licheniformis, bacillus subtilis, bifidobacterium bifidum, enterococcus faecium, lactobacillus lactis, lactobacillus acidophilus, lactobacillus casei, lactobacillus delbrueckii subspecies lactis, lactobacillus plantarum, pediococcus acidilactici, pediococcus pentosaceus, candida utilis, saccharomyces cerevisiae, rhodopseudomonas palustris, bifidobacterium infantis, bifidobacterium longum, bifidobacterium breve, bifidobacterium adolescentis, streptococcus thermophilus, lactobacillus reuteri, bifidobacterium animalis, aspergillus niger, aspergillus oryzae, bacillus lentus, bacillus pumilus, lactobacillus bifidus, lactobacillus fermentum, lactobacillus delbrueckii, propionibacterium, lactobacillus buchneri, lactobacillus paracasei, bacillus coagulans, clostridium sporogenes, and Lactobacillus johnsonii.
According to the high throughput detection method of strains in a feed microorganism product according to an embodiment of the present invention, extracting genomic DNA of microorganisms in the feed microorganism product comprises the steps of:
(1-1) taking a sample, washing the sample with TE buffer;
(1-2) lysing microorganisms in the sample;
(1-3) adding ribonuclease to the sample obtained in the step (1-2) to remove RNA in the sample;
(1-4) adding protease to the sample obtained in the step (1-3) to remove protein in the sample;
(1-5) adding a magnetic bead mixed solution into the sample obtained in the step (1-4) to adsorb bacterial DNA, wherein the magnetic bead mixed solution comprises magnetic beads and PEG, and the volume ratio of the magnetic beads to the PEG is 1: 1-4, and the final concentration of the magnetic beads is 0.5-5 mg/mL.
(1-6) Washing the DNA obtained in step (1-5).
According to the high throughput detection method of bacterial species in a feed microorganism product of an embodiment of the present invention, in step (1-1), the sample is washed with 10×TE buffer.
Wherein, the TE buffer is Tris-EDTA buffer, the 10 XTE buffer is 10 times concentration of TE buffer, the reagent composition is Tris-HCl (100 mM), EDTA (10 mM), and the pH is 8.0.
In the step (1-2), normal saline is added into the sample obtained in the step (1), vibration suspension is carried out to precipitate, 40-60 mg/mL lysozyme is added and uniformly mixed, after reaction is carried out for 0.5-4.5 h at 37 ℃, centrifugation is carried out, and supernatant fluid is taken.
Lysozyme (lysozyme), also known as muramidase (muramidase) or N-acetylmuramidase hydrolase (N-acetylmuramide glycanohydrlase), is an alkaline enzyme capable of hydrolyzing mucopolysaccharides in bacteria.
In the step (1-2), zirconium beads and a lysate are added into the collected thalli to lyse microorganisms in a sample, wherein the volume ratio of the sample to the lysate is 1: 3-7, wherein the composition of the lysate comprises 1-5% SDS, 0.5-10 xTE buffer solution and 0.3-3M NaCl, and the pH of the lysate is 7.0-9.0.
The volume of the zirconium beads is measured to be equal to that of the sample, and the final concentration of the zirconium beads is 0.1g/mL-0.85g/mL.
Adding the lysate in the step (1-2), grinding and vibrating, cracking for 5-200 min at 65-75 ℃, centrifuging, and taking the supernatant.
In the step (1-3), 1-5 mg/mL ribonuclease is added to the sample obtained in the step (1-2), and the mixture is incubated at 36.5-37.5 ℃ for 5 minutes-12 hours.
In the step (1-4), 1-5 mg/mL proteinase K is added into the sample obtained in the step (1-3), and the mixture is incubated for 5 minutes to 2 hours at the temperature of 65-75 ℃.
In the step (1-5), the final concentration of the magnetic beads is 0.5-5 mg/mL.
In the step (1-6), 70% ethanol and water are sequentially used for washing and eluting.
In the step (1-6), 70% ethanol is added into DNA obtained by adsorption, pure water is used after cleaning, suspended magnetic beads are oscillated, and after incubation at 70 ℃, centrifugation and magnetic adsorption are carried out, thus obtaining the DNA.
In the step (1-1), a sample is measured using a PCR tube.
According to the method for extracting the nucleic acid in the feed microorganism product, the TE buffer is used for cleaning free DNA and impurities in a sample of the feed microorganism product, so that the yield of the final product is increased, and the pollution of host DNA is reduced; the extraction method has the advantages that the consumption of ribonuclease and protease is large, the traditional steps of nucleic acid precipitation, nucleic acid washing and the like can be omitted, the operation time is saved, and purer total DNA can be obtained; the extraction method of the invention uses the PCR tube to measure the sample and the magnetic beads respectively, thus not only having simple operation, but also having fixed measuring amount.
The nucleic acid extracted by the method has high purity and high integrity; can be used for subsequent high-throughput sequencing analysis.
A method for high throughput detection of risk genes in a feed microorganism product according to an embodiment of the present invention, the detection method comprising the steps of:
(1) Extracting genome DNA of microorganisms in a sample to be detected;
(2) Carrying out high-throughput sequencing on the genome DNA extracted in the step (1);
(3) Comparing the data obtained by the high-throughput sequencing in the step (2) with sequences stored in a target gene database to determine a risk gene;
(4) Comparing the risk genes determined in the step (3) with sequences stored in a species database, and performing strain tracing on the risk genes;
(5) Comparing the strains determined by tracing in the step (4) with the permission list to determine whether microorganisms in the permission list contained in the sample to be detected contain risk genes.
The high-throughput detection method of the risk genes in the microbial feed product according to the specific embodiment of the invention further comprises the following steps before the step (3):
(3-1) converting the high throughput sequencing result of step (2) into FASTQ format;
(3-2) data quality control: deleting the invalid sequence;
(3-3) performing sequence splicing on the sequence processed in the step (2) to obtain the contig nucleic acid fragment of the microorganism in the sample.
Wherein, the invalid sequence refers to a low quality sequence, a contaminating sequence, a linker sequence, etc., and specifically may be set to include a sequence in which the N base content in a single sequence exceeds 10%, or the number of bases with Q value less than 5 exceeds 50%. And after deleting the invalid sequence, obtaining high-quality data, and performing sequence splicing on the filtered high-quality data by utilizing megahit or spades software.
According to the high-throughput detection method for risk genes in the feeding microbial product, in the step (3), when data obtained by high-throughput sequencing are compared with sequences stored in a target gene database, the risk genes are screened by taking the similarity percentage of more than or equal to 75% and the similarity percentage of more than or equal to 85% and the e value of less than 10 -10 as judgment standards.
The above-mentioned judging standard can find the risk gene to the maximum on the basis of guaranteeing the identification accuracy, make the security of the sample get the full assessment, prevent to miss.
A method for high throughput detection of risk genes including virulence genes and/or drug resistance genes in a feeding microbial product according to an embodiment of the invention.
According to the high throughput detection method of risk genes in the feed microorganism product of the specific embodiment of the invention, the target gene database used in the step (3) comprises a drug resistance gene database, a virulence gene database and/or a plasmid database.
When the risk genes to be screened are drug-resistant genes, the target database correspondingly used in the step (3) is a drug-resistant gene database, wherein the drug-resistant gene database comprises CARD, resFinder and the like;
When the risk genes to be screened are virulence genes, the target database correspondingly used in the step (3) is a virulence gene database; the virulence gene database comprises VFDB, PAI DB, CGE and the like;
When the risk genes to be screened are drug resistance genes derived from plasmids, in step (3), drug resistance genes are screened using a drug resistance gene database, and at the same time, plasmid genes are screened using a plasmid gene library to determine mobilizable drug resistance genes from plasmids, the plasmid database including PLSDB, plasmidfinder and the like.
According to the high-throughput detection method of risk genes in the feeding microbial product, which is provided by the embodiment of the invention, after tracing the source strain, the English description of the risk genes is translated in Chinese, and a dictionary is established. The Chinese risk description corresponding to the risk gene can be added to the rear of the English description by using a Python program.
According to the high-throughput detection method of risk genes in the feeding microbial product, which is provided by the embodiment of the invention, after tracing the source strain, the Latin name of the annotated strain is translated in Chinese, and a dictionary is established. The Chinese name of the traceable strain is added behind the Latin of the strain by using a Python program.
The invention has the beneficial effects that:
The invention can accurately screen non-targeted pathogenic bacteria which are not recorded in the permission list, and quantitatively analyze the strain content in the permission list, thereby effectively solving the problems of the microbial product for feeding.
The invention verifies the detection method, and has good detection noise, detection limit, quantitative range, repeatability, reproducibility and the like.
The drug resistance gene and virulence gene detection method can locate the risk genes to corresponding species, trace the species, make the risk sources of the products clearer, facilitate the production enterprises to have clear knowledge of the risk points of the products, and further adjust the production process in time. The method used by the invention has lower cost which is about 50 times of the current Hi-C sequencing technology, and has good application prospect. The migration resistant gene established by the invention ensures that the risk of the resistant gene is more targeted, and solves the defect that the inherent resistant gene and the migration resistant gene cannot be distinguished in the existing method, thereby effectively judging whether the microorganisms in the permission list contained in the sample to be detected contain the risk genes.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a graph showing the comparison of the DNA extraction effect of the method of the present invention with that of a commercially available kit;
FIG. 2 shows the results of a test of a microbial feed product, (1) a test of a purer sample; (2) Displaying the condition for the detection result of the sample containing the non-targeted risk microorganisms;
FIG. 3 is a graph of abundance of microbial feed additive samples containing different biomass enterococcus faecium (CFU) versus corresponding biomass measured using the method of the invention;
FIG. 4 is a graph of abundance of microbial feed additive samples containing different biomass bacillus subtilis (CFU) versus corresponding biomass measured using the method of the invention;
FIG. 5 is a graph showing the reproducibility of the detection of a microbial feed additive product of Bacillus subtilis by the method of the present invention;
FIG. 6 is a graph showing the reproducibility of the method of the present invention for detecting Lactobacillus plantarum microbial feed additive products.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, based on the examples herein, which are within the scope of the invention as defined by the claims, will be within the scope of the invention as defined by the claims.
FASTQ format: the text format encoded in ASCII, storing the nucleic acid sequence and corresponding quality assessment is a standard format for high throughput sequencing.
Python language: an object-oriented programming, dynamic, interpreted computer programming language.
Bracken procedure: a highly accurate statistical method that can calculate the abundance of species in DNA sequences from metagenomic samples. Braken uses the class label specified in Kraken to estimate the number of reads per species in the sample.
Kraken procedure: a very fast system for classifying short or long DNA sequences from microbiome or metagenomic samples.
Kraken2 procedure: the latest version of Kraken program uses the same classification algorithm, but is improved in terms of speed and memory, with faster database construction time, smaller database size, and faster classification speed.
Fastp procedure: tools are designed to provide fast integrated preprocessing for FastQ files.
Drug resistance gene: a nucleotide sequence encoding a resistance trait.
Virulence genes: a nucleotide sequence encoding a virulence factor.
Plasmid gene: a nucleotide sequence for plasmid typing.
Migratable drug resistance genes: the drug-resistant genes carried by the plasmids can be transmitted among strains of the same bacteria or even different bacteria by means of conjugation, transformation, transduction and the like.
Drug resistance gene database: a stored collection of nucleic acid sequences and/or amino acid sequences of drug-resistant genes in various microorganisms is recorded, possibly with an instruction for each gene.
Risk gene database: a stored collection of nucleic acid sequences and/or amino acid sequences of virulence genes of various microorganisms are recorded, possibly with instructions for each gene.
Plasmid gene database: a stored collection of nucleic acid sequences and/or amino acid sequences, possibly together with a description of each gene, of distinguishable plasmid types in various microorganisms are recorded.
A contig nucleic acid fragment: the sequencing data are spliced to form larger nucleic acid fragments.
Example 1 extraction of microbial nucleic acids from feed additives
1. 200 Mu L of a sample is taken from a PCR tube and added into a 2mL tube;
2. adding 1mL 10xTE into the sample obtained in the step (1), oscillating for 1min by a grinder, and cleaning thalli for 2 times; adding physiological saline into thalli, oscillating to suspend sediment, adding 50mg/mL lysozyme mother solution, uniformly mixing, reacting for 1h at 37 ℃, centrifuging, discarding clear liquid, and collecting thalli;
3. The PCR tube takes 200 mu L of zirconium beads, adds the zirconium beads into a sample, adds 1mL of lysate, and shakes for 3min by a grinder;
4. Cracking at 70deg.C for 15min, and reversing for 6 times every 5min;
5. 13000g are centrifuged at 4 ℃ for 15min;
6. Taking the supernatant into a new 1.5mL tube, adding 40 mu L of RNase A and incubating at 37 ℃ for 15min;
7. adding 40 mu L of proteinase K, incubating for 10min at 70 ℃ and incubating for 10min at 70 ℃;
8. adding 300 mu L of magnetic bead mixed solution (mixing magnetic beads and 40% PEG according to the volume ratio of 1:2), reversing and uniformly mixing, and standing for 3-5min;
9. Magnetically adsorbing with a magnetic rack for 2-5min, and pouring out the liquid;
10. Adding 70% ethanol 700 microliter of 1mL, reversing for cleaning for several times, magnetically adsorbing for 1min, pouring out the liquid, and cleaning twice;
11. drying in a fume hood for 4min;
12. Adding 100 mu L of pure water, vibrating the suspension magnetic beads, and incubating for 5min at 70 ℃;
13. After microcentrifugation, the liquid was transferred to a new 1.5mL tube by magnetic adsorption for 1-3 min.
In the above-mentioned method, the method comprises,
Preparation method of 10 xTE (pH 8.0): 200ml 500mM Tris-HCl (pH 8.0), 100ml0.1M EDTA (pH 8.0) to a volume of 1L.
The preparation method of the lysate comprises the following steps: 1.2g of SDS, 4mL of 10xTE and 4mL of 5M NaCl are added to 32mL of pure water, thus obtaining the product.
The final concentration of RNase added is 1-5 mg/mL, and optional concentrations include 1mg/mL, 2mg/mL, 3mg/mL, 4mg/mL and 5mg/mL, and after RNase is added to the sample, the sample can be incubated for 5, 10 or 15min at 36.5, 37 or 37.5 ℃ for 12 hours at most.
The final concentration of the added proteinase K is 1-5 mg/mL, and the optional concentration comprises 1mg/mL, 2mg/mL, 3mg/mL, 4mg/mL or 5mg/mL, and after the proteinase K is added into the sample, the sample can be incubated for 5, 10 or 15min at 65, 70 or 75 ℃ for 2 hours at most.
The volume ratio of the magnetic beads to the PEG is 1:1-4, the volume ratio of the magnetic beads to the PEG can be selected from 1:1, 1:2, 1:3 or 1:4, and the concentration of the PEG can be selected from 30%, 35%, 40%, 45% or 50%.
The final concentration of the magnetic beads is 0.5-5 mg/mL, preferably 0.5mg/mL, 1mg/mL or 1.5mg/mL, and at most 5mg/mL.
The concentration of lysozyme is 40-60 mg/mL, and the final concentration of lysozyme is preferably 40mg/mL, 40.5mg/mL, 41mg/mL, 41.5mg/mL, 42mg/mL, 45mg/mL, 50mg/mL, 55mg/mL or 60mg/mL.
DNA from a commercial lactobacillus microbial feed additive sample was extracted by the method of example 1 of the present invention, and the extraction results were compared with two foreign nucleic acid extraction kits, DNeasy PowerLyzer PowerSoil Kit (QIAGEN) and FASTDNA TM SPIN KIT for soil (MPbio).
As shown in FIG. 1, compared with Qiagen and MP nucleic acid extraction kits, the DNA extracted by the method has obvious bands in the region larger than 2000bp, which indicates that the nucleic acid extracted by the method is complete and pure, and is suitable for constructing DNA library in high-throughput detection.
Example 2 high throughput detection
2.1 Construction of metagenomic libraries
(1) Fragmentation of DNA
Ultrasonic method: pure water was added to the genomic DNA extracted in example 1 in a total volume of about 400. Mu.L, and the nucleic acid concentration was more than 10 ng/. Mu.L. Place 1.5mL centrifuge tube on ice bin, use ultrasonicator for DNA fragmentation, ultrasonic parameters set as: ultrasound for 4s, interval 6s, power 25% and time 5min. 10 mu L of ultrasonic genome DNA is taken for 1.5% TAE agarose gel electrophoresis detection, and the fragment position is 100-1000 bp. 1. Mu.L of the genomic DNA after the ultrasound was used for quantitative Qubit analysis.
The method comprises the steps of carrying out an ultrasonic genome DNA enzymatic method, carrying out a reaction of DNA end repair and A addition, carrying out a joint connection of DNA fragments, purifying DNA fragment connection products, carrying out library amplification, purifying library amplification products and carrying out fragment separation, wherein the above processes are all operated according to instructions in a commercial kit.
For example, using a kitDNA Library Prep Kit V2The total DNA extracted is subjected to library building, and the general process is as follows:
1. thawing at room temperature for 5 xTTBL, and mixing upside down for use. Confirm whether 5×ts is at room temperature or not and whether there is a precipitate on the wall of the flick tube. If precipitate exists, heating at 37 ℃ and mixing uniformly by vortex oscillation, and dissolving the precipitate.
2. The following reaction system was formulated in a sterilized PCR tube:
3. The mixture was gently applied with a pipette for 20 times and thoroughly mixed.
4. The reaction tube was placed in a PCR instrument and the following reaction procedure was run:
5. the fragmented products were purified using VAHTS DNA CLEAN heads
① Vortex shaking to mix VAHTS DNA CLEAN beams and aspirate 50 μl to 50 μl of fragmented product, vortex shaking or pipetting 10 times to mix thoroughly, incubate for 5min at room temperature.
② The reaction tube was briefly centrifuged and placed on a magnetic rack to separate the beads from the liquid, and the supernatant was carefully removed after the solution was clear (about 5 min).
③ The reaction tube was kept on a magnetic rack all the time, the beads were rinsed with 200 μl of freshly prepared 80% ethanol, incubated for 30sec at room temperature, and the supernatant carefully removed.
④ Step ③ is repeated for a total of two rinses.
⑤ The reaction tube is kept on the magnetic frame all the time, and the cover is opened for air drying for about 5min.
⑥ The reaction tube was removed from the magnet holder and eluted by the addition of 26. Mu.L of sterilized ultrapure water. Vortex shaking or beating 10 times by using a pipettor, fully mixing, and incubating for 5min at room temperature.
⑦ The reaction tube was briefly centrifuged and placed on a magnetic rack to separate the beads from the liquid, and 24 μl of supernatant was carefully aspirated into a new sterilized PCR tube after the solution was clarified (about 5 min).
6. The PCR tube was placed on ice to prepare the following reaction system:
| Kit goods number | TD501 | TD502/TD503 |
| ddH2O | ------ | 4μL |
| Step 09-1 product | 24μL | 25μL |
| 5×TAB | 10μL | 10μL |
| PPM | 5μL | ------ |
| N5XX* | 5μL | 5μL |
| N7XX* | 5μL | 5μL |
| TAE | 1μL | 1μL |
7. The reaction tube was placed in a PCR instrument with gentle pipetting with thorough mixing, and the following reaction procedure was run:
8. Vortex shaking to mix VAHTS DNA CLEAN beams and aspirate 30.0 μl volume into 50 μl of the product, vortex shaking or pipetting 10 times to mix thoroughly, incubate for 5min at room temperature.
9. The reaction tube was briefly centrifuged and placed on a magnetic rack to separate the beads from the liquid, and after the solution was clarified (about 5 min) the supernatant was carefully transferred to a new sterile PCR tube and the beads discarded.
10. Vortex shaking to mix VAHTS DNA CLEAN beams and aspirate 7.5 μl volume into the supernatant, vortex shaking or pipetting 10 times to mix thoroughly, incubating for 5min at room temperature.
11. The reaction tube was briefly centrifuged and placed on a magnetic rack to separate the beads from the liquid, and the supernatant was carefully removed after the solution was clear (about 5 min).
12. The reaction tube was kept on a magnetic rack all the time, and 200. Mu.L of freshly prepared 80% ethanol was added to rinse the beads. Incubate for 30sec at room temperature, carefully remove the supernatant.
13. Step 5 was repeated for a total of two rinses.
14. The reaction tube is kept on the magnetic frame all the time, and the magnetic beads are dried by uncovering the air for about 5min.
15. The reaction tube was removed from the magnet holder and eluted by adding 22. Mu.L of sterilized ultrapure water. Vortex shaking or beating 10 times by using a pipettor, fully mixing, and incubating for 5min at room temperature.
16. The reaction tube was briefly centrifuged and placed on a magnetic rack to separate the beads from the liquid, and after the solution was clarified (about 5 min) 20 μl of supernatant was carefully aspirated into a fresh sterilized PCR tube and stored at-20 ℃.
For the library constructed, a determination of concentration and distribution range of DNA fragment sizes was made.
Wherein 1. Mu.L of the library was added with a fluorescent dye, and the concentration of the library was analyzed by a fluorescence photometer, resulting in more than 20 ng/. Mu.L.
The distribution range of the library DNA fragment size was analyzed by agarose gel electrophoresis at 1.5%, and as a result, it was about 470 bp.
2.2 High throughput sequencing
(1) After the library is built, sequencing by using a high-throughput sequencer;
the selectable sequencing platform in the invention is mainly a Hiseq series system, novaseq system and the like, the selectable sequencing mode is PE150, the obtained data size is more than 6Gb, and the Q30 is not less than 80%;
(2) Data analysis
(2-1) Data conversion:
raw data from high throughput sequencing is converted to FASTQ format,
All parameters may be used to select default parameters for the software using the bcl2fastq program;
(2-2) data quality control:
deletion of unwanted sequences of low quality, contamination or adaptors etc.,
Deleting a sequence with more than 10% of N bases or more than 50% of bases with Q value less than 5 by fastp;
(2-3) species annotation:
performing sequence comparison on the filtered data in the step (2-2) and a Kraken database by utilizing a Kraken program to finish species classification;
(2-4) statistical analysis:
Counting the comparison results in the step (2-3) by utilizing Bracken program, and calculating the nucleic acid proportion of each microorganism;
(2-5) result judgment:
Judging according to the nucleic acid proportion of the microorganism obtained in the step (2-4),
S1, outputting the names and abundance of strains if the strains belong to the strains in the feed additive variety catalogue;
s2, judging the abundance of the strain if the strain does not belong to the strain in the feed additive variety catalogue
Outputting the names of the strains and the abundance thereof if the abundance of the strains is more than or equal to 10%, and assigning a second marker;
outputting the names and the abundance of the strains if the abundance of the strains is between 1.5 and 10 percent, and distributing a first marker;
if the abundance of the strain is less than 1.5%, the name of the strain is not displayed, and the sum of the abundance of the strain and other strains with abundance of less than 1.5% is output.
As shown in fig. 2, this example demonstrates the detection of purer samples and samples containing non-targeted risk microorganisms.
Example 3 determination of the detection Limit of the method of the invention
In order to determine noise of a risk microorganism detection method, the invention selects standard strains of microorganism feed additive products which are most common in the current market for pure culture so as to determine the misjudgment rate of species annotation in the method.
Test strain: standard strains of ATCC 23857 (bacillus subtilis), ATCC 14580 (bacillus licheniformis), ATCC 31284 (bacillus coagulans), ATCC 53671 (lactobacillus acidophilus), ATCC 19398 (clostridium butyricum), ATCC 19434 (enterococcus faecium), ATCC 10241 (lactobacillus plantarum) and ATCC 39392 (lactobacillus casei) were used.
Test medium: the ATCC Medium 415 is used for culturing bacillus subtilis; the ATCC Medium 3 is used for culturing bacillus licheniformis; the ATCC Medium 18 is used for culturing bacillus coagulans; ATCC Medium 416 used for culturing Lactobacillus acidophilus, lactobacillus plantarum and Lactobacillus casei; ATCC Medium 2107 Medium was used for the cultivation of Clostridium butyricum; ATCC Medium 44 is used for the cultivation of enterococcus faecium.
The results are shown in tables 1 to 8.
TABLE 1 partial detection results of pure cultures of Bacillus subtilis
TABLE 2 partial detection results of pure cultures of Lactobacillus casei
TABLE 3 partial detection results of pure cultures of Bacillus licheniformis
TABLE 4 partial detection results of pure cultures of Bacillus coagulans
TABLE 5 results of partial detection of pure cultures of Lactobacillus acidophilus
TABLE 6 results of partial detection of pure cultures of Clostridium butyricum
TABLE 7 results of partial detection of pure cultures of enterococcus faecium
TABLE 8 results of partial detection of pure cultures of Lactobacillus plantarum
As can be seen from tables 1-8, the maximum misjudgment rates of pure cultures of different species were 0.00213, 0.0029, 0.00398, 0.00077, 0.00123, 0.00225, 0.00122 and 0.00201, respectively, and were less than 0.004, using Kraken software for species annotation.
The detection limit of the method is 0.012, based on the principle that the detection limit is 3 times the noise. To further reduce the chance of the method, the detection of the method according to the invention is finally limited to 0.015, i.e. when the microbial feed additive has a microbial content of more than 0.015 and the microorganism is not in the feed additive inventory, the sample will be judged to be at risk.
Example 4 determination of quantitative Limit and Linear Range for Strain content detection methods
4.1. Experiment of adding enterococcus faecium into Bacillus licheniformis sample
To determine the quantitative limit and linear range of the strain content detected by the method of the invention, enterococcus faecium (CFU) with different biomass is added to a bacillus licheniformis sample without enterococcus faecium.
Preparation of enterococcus faecium suspension:
The enterococcus faecium single colony on the flat plate is picked up by a sterile toothpick to be placed in ATCC Medium 44 liquid culture Medium, and the temperature is 37 ℃ and the mixture is uniformly mixed by shaking before use.
Preparation and counting of samples with different bacterial contents:
1g of bacillus licheniformis sample is weighed, 100 mu L of enterococcus faecium suspension and enterococcus faecium suspension gradient diluent are respectively added into the sample (the dilution factors are 10、102、103、104、105、106、107、108、109、1010、1011、1012、1013、1014). respectively, and simultaneously 100 mu L of enterococcus faecium suspension gradient diluent are respectively taken for plate counting so as to determine the content (unit is cfu/g) of enterococcus faecium in each sample.
Pretreatment of the sample:
To each sample, 10mL of sterile physiological saline was added, and the mixture was vortexed for 3 minutes to mix thoroughly. 1mL was pipetted into a new sterile centrifuge tube (1.5 mL format). And then carrying out subsequent operation by using the operation steps of the mass label, and determining the quantitative limit and the linear range of the method.
As shown in FIG. 3, when the content of enterococcus faecium in the sample is 10 4-107 CFU/g, the percentage of enterococcus faecium in the sample and the bacterial content show good linear relation, and R 2 is 0.9949.
4.2. Experiment of adding Bacillus subtilis to Lactobacillus plantarum sample
Preparation of bacillus subtilis suspension:
The bacillus subtilis single colony on the flat plate is picked up by a sterile toothpick and put into ATCC Medium 415 culture Medium, and is cultured for 12 hours by shaking at 220rpm, the temperature is 37 ℃, and the bacillus subtilis single colony is mixed evenly by shaking before use.
Preparation and counting of samples with different bacterial contents:
1g of lactobacillus plantarum sample is weighed, 100 mu L of bacillus subtilis suspension and bacillus subtilis suspension gradient diluent are respectively added into the sample (the dilution factors are 10、102、103、104、105、106、107、108、109、1010、1011、1012、1013、1014). respectively, and simultaneously 100 mu L of bacillus subtilis suspension gradient diluent are respectively taken for plate counting so as to determine the content (unit is cfu/g) of enterococcus faecium in each sample.
Pretreatment of the sample:
To each sample, 10mL of sterile physiological saline was added, and the mixture was vortexed for 3 minutes to mix thoroughly. 1mL was pipetted into a new sterile centrifuge tube (1.5 mL format). And then carrying out subsequent operation by using the operation steps of the mass label, and determining the quantitative limit and the linear range of the method.
As shown in FIG. 4, when the content of Bacillus subtilis in the sample was 10 4-107 CFU/g, the percentage of Bacillus subtilis in the sample exhibited a good linear relationship with the bacterial content, and R 2 was 0.9997.
Example 3 the noise of the method of the invention was determined to be 0.004, and the quantitative limit of the detection method was 0.04 according to the principle that the quantitative limit is 10 times of the noise, i.e. the strains with the ratio lower than 0.04 and greater than 0.015 were detected, but could not be accurately quantified; the quantitative range of the detection method is finally determined to be 0.04-1, namely 4% -100%.
Example 5 determination of stability of method for detecting seed content
The sample (dilution factor 10 9、1010、1011、1012、1013、1014) detected without the addition of bacteria in example 3 was used as a parallel, and the relative standard deviation was calculated.
As a result, as shown in FIG. 5, the Bacillus licheniformis content of the Bacillus licheniformis sample was 97.39%, 97.87%, 97.62%, 97.73%, 97.93% and 97.95%, respectively, and the relative standard deviation was 0.22%; the bacillus subtilis contents were 1.06%, 0.86%, 0.89%, 0.97%, 0.84% and 0.89%, respectively, with a relative standard deviation of 8.96%. It follows that the relative standard deviation of the present method is less than 15%.
As can be seen from FIG. 6, the Lactobacillus plantarum samples contained 98.99%, 99.32%, 99.16%, 99.1%, 99.14% and 99.02% Lactobacillus plantarum, respectively, with a relative standard deviation of 0.12%. It follows that the relative standard deviation of the present method is less than 15%.
Example 6 determination of reproducibility of the method for detecting seed content
Samples of 13 microbial feed additives were randomly selected for comparison with a third party institution, with the following specific results:
Table 9 results of three-way comparison of randomly selected 13 microbial feed additive samples
As can be seen from Table 9, the strain content in 13 samples was mostly reproducible, the relative standard deviation was 10% or less, and the relative standard deviation was more than 10% for Other strain content in samples B10, B52, B64, 14.84%, 14.48% and 20.49%, respectively, but since this strain was the sum of the low-content strains, the strain content was lower than the quantitative limit, and was not statistically significant, and therefore, it was negligible.
Example 7 search of drug resistance Gene and Strain tracing
The method for detecting the drug resistance gene in the microbial product for feeding comprises the following steps:
(1) After the library is built, sequencing by using a high-throughput sequencer;
the selectable sequencing platform in the invention is mainly a Hiseq series system, novaseq system and the like, the selectable sequencing mode is PE150, the obtained data size is more than 6Gb, and the Q30 is not less than 80%;
(2) Data analysis
(2-1) Data conversion:
raw data from high throughput sequencing is converted to FASTQ format,
All parameters may be used to select default parameters for the software using the bcl2fastq program;
(2-2) data quality control:
deletion of unwanted sequences of low quality, contamination or adaptors etc.,
Deleting a sequence with more than 10% of N bases or more than 50% of bases with Q value less than 5 by fastp;
(2-3) obtaining the contig nucleic acid fragments of all microorganisms
The filtered high quality data was sequence spliced using megahit or spades software to obtain contig nucleic acid fragments for all microorganisms in each microbial feed additive.
(2-4) Screening for drug resistance genes
Comparing the assembled contig with sequences stored in a latest drug-resistant gene database by using a blastn and blastx program, analyzing whether known drug-resistant genes exist in all genetic materials of a sample, and judging the sample to be the drug-resistant genes if the coverage is more than or equal to 75%, the similarity percentage is more than or equal to 85% and the e value is less than 10 -10;
recording the contig number containing the drug resistance gene by using pyhton script;
(2-5) traceable drug resistance Gene
Extracting nucleic acid sequence corresponding to contig containing target gene, comparing sequence with nt database in NCBI database,
In the comparison result, the species number taxid of the highest-scoring highest-ranking matching nucleic acid sequence is selected, a taxonomy species identification database in NCBI is searched, species annotation is carried out on contig containing a target gene, and the annotated strain is the traceable strain of the drug-resistant gene.
(2-6) Performing Chinese translation on the English descriptions of all the found drug resistance genes, and establishing a dictionary. Then adding Chinese drug resistance genes corresponding to the drug resistance genes into the rear of English description by using a Python program;
(2-7) performing Chinese translation on Latin of all strains, and establishing a dictionary.
The Chinese name of the traceable strain is added behind the Latin of the strain by using a Python program.
So far, the names of all drug-resistant genes, corresponding contig numbers, chinese descriptions corresponding to the drug-resistant genes, latin names of traceable strains and Chinese names for strain pairs in the microbial feed additive sample are obtained. The generated table can be used for evaluating the safety of the microbial feed additive drug resistance genes.
(2-8) Matching all the species obtained by the annotation with 36 strains allowed to be used in the feed additive variety catalogue, wherein the matched contig is the genome of the allowed strains.
The target gene contained in the contig is the drug-resistant gene contained in the allowed strain.
The generated table can be used to assess the safety of drug-resistant genes of the production strains allowed to be used in the catalogue.
By using the screening method of the drug-resistant gene, the sample is detected, and the result is as follows:
TABLE 10 drug resistance genes and traceable Strain results
As can be seen from Table 10, sample D15 contains drug resistance genes tet (L) and rphB, lmrB, mphK, tmrB, ermD, respectively, wherein rphB and ErmD are derived from Bacillus licheniformis and are classified into rifampicin, lincolamine, macrolide and streptomycin types. Other genes are from bacillus subtilis, and the corresponding drug resistant types are tetracyclines, lincolamines, macrolides and nucleic acids. Sample D16 contains drug-resistant genes AAC (6') -Ii and rphB from enterococcus faecium and Bacillus licheniformis respectively, and the corresponding drug-resistant types are aminoglycosides and rifampicin.
Example 8 search for migratable drug resistance genes and Strain tracing
The detection method of the mobilizable drug resistance genes in the microbial feed product comprises the following steps:
(1) After the library is built, sequencing by using a high-throughput sequencer;
the selectable sequencing platform in the invention is mainly a Hiseq series system, novaseq system and the like, the selectable sequencing mode is PE150, the obtained data size is more than 6Gb, and the Q30 is not less than 80%;
(2) Data analysis
(2-1) Data conversion:
raw data from high throughput sequencing is converted to FASTQ format,
All parameters may be used to select default parameters for the software using the bcl2fastq program;
(2-2) data quality control:
deletion of unwanted sequences of low quality, contamination or adaptors etc.,
Deleting a sequence with more than 10% of N bases or more than 50% of bases with Q value less than 5 by fastp;
(2-3) obtaining the contig nucleic acid fragments of all microorganisms
The filtered high quality data was sequence spliced using megahit or spades software to obtain contig nucleic acid fragments for all microorganisms in each microbial feed additive.
(2-4) Screening of plasmid Gene
Comparing the assembled contigs with sequences stored in a latest plasmid database by using a blastn and blastx program, and analyzing whether known plasmid replicons or promoters and other elements exist in all genetic materials of the sample so as to judge whether the corresponding contigs are plasmids or part of plasmids;
Screening the contig corresponding to the plasmid by taking the coverage of more than or equal to 75%, the similarity percentage of more than or equal to 85% and the e value of less than 10 -10 as a judgment standard;
The contig numbers were recorded using pyhton scripts.
(2-5) Screening for drug resistance Gene
The blastn and blastx programs compare the contig obtained in the step (2) with sequences stored in the latest drug resistance gene database, and analyze whether known drug resistance genes exist in all genetic materials of the sample;
Screening drug-resistant genes by taking the coverage of more than or equal to 75%, the similarity percentage of more than or equal to 85% and the e value of less than 10 -10 as a judgment standard;
recording the contig number containing the target gene by utilizing pyhton script;
The obtained contig is a plasmid fragment containing the drug resistance gene, and the drug resistance gene contained in the plasmid fragment can migrate the drug resistance gene.
(2-6) Extracting a nucleic acid sequence corresponding to the contig containing the target gene, and performing sequence alignment by using blastn and an nt database in the NCBI database;
And in the comparison result, selecting the species number taxid of the highest-scoring highest-ranking matched nucleic acid sequence, searching a taxonomy species identification database in NCBI, and carrying out species annotation on the contig containing the target gene, wherein the annotated species is the traceable strain of the drug-resistant gene.
(2-7) Performing Chinese translation on Latin of all strains, and establishing a dictionary.
The Chinese name of the traceable strain is added behind the Latin of the strain by using a Python program.
So far, the names of all the mobilizable drug-resistant genes, corresponding contig numbers, chinese descriptions corresponding to the drug-resistant genes, latin names of traceable strains and Chinese names for strain pairs in the microbial feed additive sample are obtained. The generated table can be used for evaluating the safety of the microbial feed additive drug resistance genes.
(2-8) Matching all the species obtained by the annotation with 36 strains allowed to be used in the feed additive variety catalogue, wherein the matched contig is the genome of the allowed strains.
The target gene contained in the contig is the drug-resistant gene contained in the allowed strain.
The generated table can be used to assess the safety of drug-resistant genes of the production strains allowed to be used in the catalogue.
By using the screening method of the mobilizable drug resistance gene, a sample is detected, and the result is as follows:
table 11 results of detection of migratable drug-resistant genes and traceable strains
As shown in Table 11, the mobilizable drug resistance genes contained in sample B18 were cat, and were carried on pCW7 plasmid, and the drug resistance type was chloramphenicol from enterococcus faecium. The migratory drug resistance genes contained in sample B23 are tet (L), tetM, ANT (6) -Ia, ANT (9) -Ia, lsaE, lnuB and ErmB, all carried by pARO1.1 plasmid, from enterococcus faecium, and the corresponding drug resistance types are chloramphenicol, tetracyclines, aminoglycosides, lincomamide, streptomycin A, clindamycin and erythromycin.
Example 9 searching for virulence Gene and Strain tracing
The method for detecting virulence genes in the microbial feed product comprises the following steps:
(1) After the library is built, sequencing by using a high-throughput sequencer;
the selectable sequencing platform in the invention is mainly a Hiseq series system, novaseq system and the like, the selectable sequencing mode is PE150, the obtained data size is more than 6Gb, and the Q30 is not less than 80%;
(2) Data analysis
(2-1) Data conversion:
raw data from high throughput sequencing is converted to FASTQ format,
All parameters may be used to select default parameters for the software using the bcl2fastq program;
(2-2) data quality control:
deletion of unwanted sequences of low quality, contamination or adaptors etc.,
Deleting a sequence with more than 10% of N bases or more than 50% of bases with Q value less than 5 by fastp;
(2-3) obtaining the contig nucleic acid fragments of all microorganisms
The filtered high quality data was sequence spliced using megahit or spades software to obtain contig nucleic acid fragments for all microorganisms in each microbial feed additive.
(2-4) Screening for virulence genes
The blastn and blastx programs compare the assembled contigs with sequences stored in the latest virulence gene database (including but not limited to VFDB, PAI DB, CGE, etc.), analyze whether known virulence genes are present in all genetic material of the sample, and if the coverage is greater than or equal to 75%, the percent similarity is greater than or equal to 85% and the e value is less than 10 -10, determine the virulence genes;
recording the contig number containing virulence genes by using pyhton script;
(2-5) traceable virulence Gene
Extracting nucleic acid sequence corresponding to contig containing target gene, comparing sequence with nt database in NCBI database,
In the comparison result, the species number taxid of the highest-scoring highest-ranking matching nucleic acid sequence is selected, a taxonomy species identification database in NCBI is searched, species annotation is carried out on the contig containing the target gene, and the annotated strain is the traceable strain of the virulence gene.
(2-6) Performing Chinese translation on the English descriptions of all the found virulence genes, and establishing a dictionary. Then adding Chinese virulence genes corresponding to the virulence genes into the rear of English description by using a Python program;
(2-7) performing Chinese translation on Latin of all strains, and establishing a dictionary.
The Chinese name of the traceable strain is added behind the Latin of the strain by using a Python program.
So far, the names of all virulence genes, corresponding contig numbers, chinese descriptions corresponding to virulence genes, latin names of traceable strains and Chinese names for strain pairs in the microbial feed additive sample are obtained. The generated table can be used to evaluate the safety of virulence genes of microbial feed additives.
(2-8) Matching all the species obtained by the annotation with 36 strains allowed to be used in the feed additive variety catalogue, wherein the matched contig is the genome of the allowed strains.
The target gene contained in the contig is the drug-resistant gene contained in the allowed strain.
The generated table can be used to assess the safety of drug-resistant genes of the production strains allowed to be used in the catalogue.
The sample is detected by the screening method of virulence genes, and the result is as follows:
TABLE 12 virulence Gene and traceable Strain detection results
As can be seen from Table 12, sample D9 contains virulence genes acm and sgrA, respectively, which are enterococcus faecium, and which are classified into the corresponding virulence factor types as collagen adhesin precursors and cell wall anchored proteins. Sample D12 contains virulence genes EF3023 and gelE, both from enterococcus faecalis, and the corresponding virulence factors are polysaccharide lyase and lysin.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (12)
1. A method for high throughput detection of bacterial species in a feed microbial product, the method comprising the steps of:
(1) Extracting genome DNA of microorganisms in a sample to be detected;
Extracting genomic DNA of a microorganism in a feed microorganism product comprises the steps of:
(1-1) washing the sample with 10 XTE buffer composed of Tris-HCl, EDTA;
(1-2) lysing microorganisms in a sample:
adding normal saline into the sample obtained in the step (1-1), vibrating and suspending the precipitate, adding 40-60 mg/mL lysozyme, uniformly mixing, reacting at 37 ℃ for 0.5-4.5 h, centrifuging, discarding the clear liquid, and collecting thalli;
adding zirconium beads and lysate into the collected thalli, and lysing microorganisms in a sample, wherein the volume ratio of the sample to the lysate is 1:3 to 7, wherein the lysate comprises 1 to 5 percent of SDS, 0.5 to 10 xTE buffer solution and 0.3 to 3MNaCl, and the pH value of the lysate is 7.0 to 9.0;
Adding the cracking liquid, grinding and vibrating, cracking for 5-200 min at 65-75 ℃, centrifuging, and taking supernatant;
(1-3) adding ribonuclease to the sample obtained in the step (1-2) to remove RNA in the sample;
Adding 1-5 mg/mL ribonuclease, and incubating at 36.5-37.5 ℃ for 5 min-12 h;
(1-4) adding protease to the sample obtained in the step (1-3) to remove protein in the sample;
Adding 1-5 mg/mL proteinase K, and incubating at 65-75 ℃ for 5 min-2 h;
(1-5) adding a magnetic bead mixed solution into the sample obtained in the step (1-4) to adsorb bacterial DNA, wherein the magnetic bead mixed solution comprises magnetic beads and PEG, and the volume ratio of the magnetic beads to the PEG is 1: 1-4, wherein the final concentration of the magnetic beads is 0.5-5 mg/mL;
(1-6) washing the DNA obtained in the step (1-5);
(2) Carrying out high-throughput sequencing on the genome DNA extracted in the step (1);
If the abundance of the strain is greater than or equal to 1.5% and less than 10%, distributing a first marker of the strain; if the abundance of the strain is greater than or equal to 10%, distributing a second marker of the strain;
(3) Carrying out data analysis on the high-throughput sequencing result in the step (2) to obtain abundance of each microorganism,
(4) And (3) carrying out result display on the abundance of the microorganism obtained in the step (3):
S1, outputting the names and the abundance of the strains if the strains belong to the strains in the permission list;
S2, judging the abundance of the strain if the strain does not belong to the strain in the permission list,
Outputting the names and the abundance of the strains if the abundance of the strains is greater than or equal to 1.5%;
outputting the sum of the abundances of all the strains with the abundance less than 1.5% if the abundance of the strains is less than 1.5%.
2. The method for high throughput detection of bacterial species in a fed microbial product of claim 1, wherein the data analysis of step (3) comprises the steps of:
(3-1) data conversion: converting the high throughput sequencing result of step (2) into FASTQ format;
(3-2) data quality control: deleting the invalid sequence;
(3-3) species annotation: performing sequence comparison on the data processed in the step (3-2) and a species database, and performing species classification;
(3-4) statistical analysis: and (3) counting the results of the sequence comparison in the step (3-3), and calculating to obtain the abundance of each microorganism.
3. The method of high throughput detection of bacterial species in a fed microbial product according to claim 2, wherein in step (3-2), the null sequence comprises a sequence having a base content of more than 10% of N bases in a single sequence, or a base content of more than 50% of Q value of less than 5.
4. The method for high throughput detection of bacterial species in a feed microorganism product of claim 1, wherein said permission list comprises "feed additive variety list".
5. The method for high throughput detection of species in a fed microbial product of claim 1 or 4, wherein the species in the permission list comprises bacillus licheniformis, bacillus subtilis, bifidobacterium bifidum, enterococcus faecalis, enterococcus faecium, enterococcus lactis, lactobacillus acidophilus, lactobacillus casei, lactobacillus delbrueckii subsp lactis, lactobacillus plantarum, pediococcus acidilactici, pediococcus pentosaceus, candida utilis, saccharomyces cerevisiae, rhodopseudomonas palustris, bifidobacterium infantis, bifidobacterium longum, bifidobacterium breve, bifidobacterium adolescentis, streptococcus thermophilus, lactobacillus reuteri, bifidobacterium animalis, aspergillus niger, aspergillus oryzae, bacillus lentus, bacillus pumilus, lactobacillus cellobiose, lactobacillus fermentum, lactobacillus delbrueckii subsp bulgaricus, propionibacterium propionicum, lactobacillus buchneri, lactobacillus paracasei, bacillus coagulans, brevis, clostridium butyricum, lactobacillus johnsonii.
6. A high throughput detection method of risk genes in a feed microorganism product, characterized in that the detection method comprises the following steps:
(1) Extracting genome DNA of microorganisms in a sample to be detected;
the method for extracting the genome DNA of the microorganism in the sample to be detected comprises the following steps:
(1-1) PCR tube sample 200. Mu.L, add to 2mL tube;
(1-2) adding 1mL of 10 xTE to the sample obtained in the step (1-1), vibrating for 1min by a grinder, and cleaning the thalli for 2 times; adding physiological saline into thalli, oscillating to suspend sediment, adding 50mg/mL lysozyme mother solution, uniformly mixing, reacting for 1h at 37 ℃, centrifuging, discarding clear liquid, and collecting thalli;
(1-3) taking 200 mu L of zirconium beads from a PCR tube, adding the zirconium beads into a sample, adding 1mL of lysate, and oscillating for 3min by a grinder;
(1-4) cleavage at 70℃for 15min, during which 6 times are reversed every 5 min;
(1-5) 13000g centrifugal 15min at 4 ℃;
(1-6) taking the supernatant into a new 1.5mL tube, adding 40. Mu.L of RNaseA, and incubating at 37℃for 15min;
(1-7) adding 40 mu L of proteinase K and incubating at 70 ℃ for 10min;
(1-8) adding 300 mu L of magnetic bead mixed solution, reversing and uniformly mixing, and standing for 3-5 min; the magnetic bead mixed solution is prepared from magnetic beads and 40% PEG according to the volume ratio of 1:2, mixing;
(1-9) magnetically adsorbing for 2-5 min by a magnetic frame, and pouring out the liquid;
(1-10) adding 70% ethanol 700 microliter 1mL, reversing for several times to clean, magnetically adsorbing for 1min, pouring out the liquid, and cleaning twice;
(1-11) fume hood drying for 4min;
(1-12) adding 100 mu L of pure water, vibrating the suspension magnetic beads, and incubating at 70 ℃ for 5min;
(1-13) carrying out magnetic adsorption for 1-3 min after micro-centrifugation, and transferring the liquid into a new 1.5mL tube;
preparation method of 10×TE with pH 8.0: 200mL 500mM pH 8.0 Tris-HCl, 100mL 0.1M pH 8.0 EDTA, constant volume to 1L;
the preparation method of the lysate comprises the following steps: adding 1.2g SDS, 4mL 10 xTE and 4mL 5MNaCl into 32mL of pure water to obtain the product;
the final concentration of the RNase added is 1-5 mg/mL;
The final concentration of the added proteinase K is 1-5 mg/mL;
The volume ratio of the magnetic beads to the PEG is 1:1 to 4;
the final concentration of the magnetic beads is 0.5-5 mg/mL;
the concentration of the lysozyme is 40-60 mg/mL;
(2) Carrying out high-throughput sequencing on the genome DNA extracted in the step (1);
(3) Comparing the data obtained by the high-throughput sequencing in the step (2) with sequences stored in a target gene database to determine a risk gene;
(4) Comparing the risk genes determined in the step (3) with sequences stored in a species database, and performing strain tracing on the risk genes;
(5) Comparing the strains determined by tracing in the step (4) with the permission list to determine whether microorganisms in the permission list contained in the sample to be detected contain risk genes.
7. The method for high throughput detection of risk genes in a fed microbial product of claim 6, further comprising the steps of, prior to step (3):
(3-1) converting the high throughput sequencing result of step (2) into FASTQ format;
(3-2) data quality control: deleting the invalid sequence;
(3-3) performing sequence splicing on the sequence processed in the step (3-2) to obtain the contig nucleic acid fragment of the microorganism in the sample.
8. The method for high throughput detection of risk genes in a feed microorganism product according to claim 6 or 7, wherein in the step (3), when the data obtained by high throughput sequencing is compared with sequences stored in a target gene database, the risk genes are selected by taking the percentage of similarity of not less than 75% and not less than 85% and the e value of <10 -10 as the judgment standard.
9. The method for high throughput detection of risk genes in a fed microbial product of claim 8, wherein the risk genes comprise virulence genes and/or drug-resistant genes.
10. The method for high throughput detection of drug resistance genes in a feeding microbial product according to claim 6 or 9, wherein the target gene database used in step (3) comprises a drug resistance gene database, a virulence gene database and/or a plasmid database.
11. The method for high throughput detection of risk genes in a feed microorganism product according to claim 6, wherein after the step (4) tracing the strain, chinese translation is performed on the english description of the risk genes.
12. The method for high throughput detection of risk genes in a fed microbial product of claim 6, wherein step (4) is followed by a traceable strain, and chinese translation is performed on the latin name of the annotated strain.
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| CN113981042A (en) | 2022-01-28 |
| CN114214390A (en) | 2022-03-22 |
| CN114214390B (en) | 2024-04-02 |
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