JP2010207195A - Primer for measuring microorganism and method for measuring microorganism - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a primer for measuring microorganisms, and to provide a method for measuring the microorganisms using the primer. <P>SOLUTION: The primer set for amplifying nucleic acids originated from the microorganism comprises a forward primer and a reverse primer. The forward primer is a polynucleotide of at least one selected from the group consisting of polynucleotides comprising a first series of sequences, and complementary strands thereof, and composed of continuous 15 to 24 bases of the sequence. The reverse primer is a polynucleotide of at least one selected from the group consisting of polynucleotides comprising a second series of sequences, and complementary strands thereof, and composed of continuous 15 to 24 bases of the sequence. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a bacterial measurement primer and a bacterial measurement method.

  As a microbiological contamination index of food, the number of bacteria, particularly the number of general bacteria (aerobic plate count) is important (Non-patent Document 1). In general, food manufacturers calculate the number of general bacteria by culturing at 35 ° C. for 48 hours on a standard agar plate medium.

  When measuring the number of bacteria, plate culture methods with various changes (addition of sodium chloride, change of culture temperature, extension of culture time, etc.) are considered suitable for including more bacterial groups in the count. (Non-patent document 2, Non-patent document 3, Non-patent document 4). Such a modified method is particularly important for manufacturers producing foods made from seafood and seafood. That is, in fish and shellfish, low-temperature bacteria (low growth temperature zone, sometimes requires a long time for culture) and halophilic bacteria (requires sodium chloride for growth, so growth on standard agar medium is poor) This is because there are cases in which there are many underestimations and the standard method for measuring the number of general bacteria may be underestimated (Non-Patent Document 2, Non-Patent Document 3, Non-Patent Document 4).

  The method for measuring the number of bacteria as described above requires culturing for 2 to 5 days in any case, so there are cases where the product expiration date is not met. For this reason, although the conventional method for measuring the number of bacteria does not change the importance as a standard measuring method, a rapid measuring method that can obtain the results first is required for self-sanitation management.

  Accordingly, various rapid methods have been developed. A film-like dry medium method (Non-Patent Document 5) and a spiral plate method (Non-Patent Document 7), which have the same principle as the culture method, are often used because they have the same accuracy as the conventional method. However, since these require culture, the effect of shortening the time is limited. On the other hand, rapid methods that do not require or shorten culture have been published (ATP measurement method (Non-patent document 8), dissolved oxygen measurement method (Non-patent document 9), luminol chemiluminescence method (Non-patent document 10). Such). Although these methods are fully validated and rapid (within 30 minutes to 6 hours), the physical quantities that are different from colony counts by culture are used as measurement indices, so depending on the sample, the results when compared with the agar plate method Differences are likely to occur. That is, there is a trade-off relationship between accuracy and rapidity in the current bacterial count measurement method, and it can be said that there are very few methods that achieve both in a balanced manner.

  On the other hand, molecular biological techniques have recently been used in the field of food microorganisms. Many of them apply PCR methods such as detection and quantification of various pathogenic microorganisms, phylogenetic analysis between bacteria using 16S rDNA, and flora analysis. The greatest advantage of using PCR is its specificity and rapidity. Therefore, the application method as described above has been used in the field of food microorganisms. However, there are almost no reports of measuring the number of bacteria in food using the PCR method. One reason for this is that it is necessary to count a wide range of bacteria to measure the number of bacteria, but it is very difficult to design universal primers and construct reaction conditions. Accordingly, Lee et al. Use a universal primer for 16S rDNA and use it for bacterial count measurement (Non-patent Document 11). However, 16S rDNA differs in the number of copies per cell among bacterial species (Non-patent Document 12), and the PCR results are not necessarily uniform (Non-patent Document 13). In addition, since multiple types of bacteria are attached to the measurement sample, and their appearance is usually very different, it is important to compare the measurement results between different samples using the 16S rDNA method. It is necessary to think carefully. On the other hand, Takahashi et al. Reported the measurement of the number of fresh vegetables and fruits using a universal primer targeting the rpoB gene (Non-patent Document 14). Since the rpoB gene is considered to be one copy per cell, the quantitative results are clear and comparable between samples. However, although it was practical for fresh vegetables and fruits, it is not completely usable when fresh fish is used as a sample.

Tortorello, M.L., 2003. Indicator organisms for safety and quality-uses and methods for detection: minireview. J AOAC Int 86, 1208-1217. Jay, J.M., 2002. A review of aerobic and psychrotrophic plate count procedures for fresh meat and poultry products.J Food Prot 65, 1200-1206. Reasoner, D.J., 2004. Heterotrophic plate count methodology in the United States. Int J Food Microbiol 92, 307-315. Fujii, T., 1985. Comparative studies on methods for determination of bacterial counts in seafoods-I, comparisons of media, incubation temperatures and plating methods.Bull Tokai Reg Fish Res Lab 118,71-79. Blackburn, C.W., Baylis, C.L., Petitt, S.B., 1996.Evaluation of Petrifilm methods for enumeration of aerobic flora and coliforms in a wide range of foods.Lett Appl Microbiol 22, 137-140. Hovda, MB, Lunestad, BT, Sivertsvik, M., Rosnes, JT, 2007. Characterisation of the bacterial flora of modified atmosphere packaged farmed Atlantic cod (Gadus morhua) by PCR-DGGE of conserved 16S rRNA gene regions.Int J Food Microbiol 117, 68-75. Gilchrist J.E., Donnelly, C.B., Peeler, J.T., Campbell, J.E., 1977. Collaborative study comparing the spiral plate and aerobic plate count methods.J Assoc Off Anal Chem 60, 807-812. Hattori, N., Sakakibara, T., Kajiyama, N., Igarashi, T., Maeda, M., Murakami, S., 2003. Enhanced microbial biomass assay using mutant luciferase resistant to benzalkonium chloride. Anal Biochem 2003, 287- 295. Amano, Y., Arai, J., Yamanaka, S., Isshiki, K., 2001.Rapid and convenient estimation of bacterial cell count in food using oxygen electrode sensor.J Jpn Soc Food Sci Technol 48, 94-98. Kawasaki, S., Yamashoji, S., Asakawa, A., Isshiki, K., Kawamoto, S., 2004. Menadione-catalyzed luminal chemiluminescence assay for the rapid detection of viable bacteria in foods under aerobic conditions.J Food Prot 67 , 2767-2771. Lee, J.L., Levin, R.E., 2006.Use of ethidium bromide monoazide for quantification of viable and dead mixed bacterial flora from fish fillets by polymerase chain reaction.J Microbiol Meth 67, 456-462. Fogel, G.B., Collins, C.R., Li, J., and Brunk, C.F., 1999.Prokaryotic genome size and SSU rDNA copy number: estimation of microbial relative abundance from a mixed population.Microb Ecol 38, 93-113. Farrelly, V., Rainey, F.A., Stackebrandt, E., 1995. Effect of genome size and rrn gene copy number on PCR amplification of 16S rRNA genes from a mixture of bacterial species.Appl Environ Microbiol 61, 2798-2801. Takahashi, H., Konuma, H., Hara-Kudo, Y., 2007. Development of a quantitative real-time PCR method to enumerate total bacterial counts in ready-to-eat fruits and vegetables.J Food Prot 69, 2504- 2508.

  An object of the present invention is to provide a primer for measuring bacteria and a method for measuring bacteria using the same.

To achieve the above object, the present invention provides:
A primer set for amplifying bacterial nucleic acid, the primer set comprising a forward primer and a reverse primer,
The forward primer is at least one selected from the group consisting of the sequence shown in SEQ ID NO: 41, the polynucleotide shown in SEQ ID NO: 42, the polynucleotide consisting of the sequence shown in SEQ ID NO: 43, and the complementary strand thereof, and the sequence continuation A polynucleotide consisting of 15 to 24 bases,
The reverse primer is at least one selected from the group consisting of the sequence shown in SEQ ID NO: 46 and the sequence shown in SEQ ID NO: 47 and its complementary strand, and consists of 15 to 24 bases in the sequence. It is a primer set which is a polynucleotide.

  According to the present invention, a primer for measuring bacteria and a method for measuring bacteria using the same are provided.

The graph which shows the Ct value of the tuf real-time PCR method in a pure culture cell. The graph which compares the number of bacteria by TSA-ASW agar medium, and Ct value by real-time PCR method (correlation coefficient 0.935). The figure which shows the correlation between the number of bacteria by TSA-ASW agar medium and the estimated number of bacteria by real-time PCR method in fish and shellfish (correlation coefficient 0.94). The figure which shows the amplification result of various bacteria by real-time PCR. The figure which shows the correlation of the number of bacteria by a trypticase soy agar medium and the estimated number of bacteria by real-time PCR method in livestock meat (correlation coefficient 0.80). The figure which shows the correlation between the number of bacteria by trypticase soy agar medium and the estimated number of bacteria by real-time PCR method in fresh vegetables (correlation coefficient 0.85).

  As a result of the present inventors' extensive research, the present invention can comprehensively and uniformly detect various microorganisms frequently detected in foods by targeting the protein elongation factor Tu (tuf) gene. This was achieved by clarifying that it was possible.

  The present invention provides a primer for measuring the number of bacteria of fungi widely detected in foods and a method for measuring the number of bacteria in foods using the same.

The primer of the present invention was designed from the base sequence information of the tuf gene of microorganisms frequently found in foods. The primer is a primer set composed of a forward primer and a reverse primer. The forward primer was designed from information on the base sequence around position 769, with the translation start site of the gene product of the tuf gene as position 1. The reverse primer was designed from information on the base sequence around position 1068, with the translation start site of the gene product of the tuf gene as position 1.

  By using the primer set as a universal primer and amplifying bacterial genes, tuf genes of a wide range of bacterial species can be amplified with equal and good efficiency.

  The result of performing the amplification by real-time PCR and the result of counting the number of bacteria by the conventional plate method have a very good correlation (y = -2.753x + 37.599, correlation coefficient 0.94 y, PCR result; x, common logarithm of the number of bacteria by the plate method).

  The primer consists of a forward primer and a reverse primer. The forward primer includes a sequence represented by SEQ ID NO: 1, a sequence represented by SEQ ID NO: 2, a sequence represented by SEQ ID NO: 3, a sequence represented by SEQ ID NO: 4, a sequence represented by SEQ ID NO: 5, and a sequence SEQ ID NO: 6 The sequence shown by SEQ ID NO: 7, the sequence shown by SEQ ID NO: 8, the sequence shown by SEQ ID NO: 9, the sequence shown by SEQ ID NO: 10, the sequence shown by SEQ ID NO: 11, the sequence shown by SEQ ID NO: 12 The sequence shown in SEQ ID NO: 13, the sequence shown in SEQ ID NO: 14, the sequence shown in SEQ ID NO: 15, the sequence shown in SEQ ID NO: 16, the sequence shown in SEQ ID NO: 17, the sequence shown in SEQ ID NO: 18, the sequence The sequence shown by No. 19, the sequence shown by SEQ ID No. 20, the sequence shown by SEQ ID No. 21, the sequence shown by SEQ ID No. 22 and its complementary sequence, and several bases are substituted Deletions may be at least selected from a polynucleotide including additional sequences.

  The reverse primer is represented by SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28. Sequence, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34 , At least one selected from the group consisting of the sequence represented by SEQ ID NO: 35 and the sequence represented by SEQ ID NO: 36, and its complementary sequence, and a polynucleotide comprising a sequence in which several bases are substituted, deleted, or added. Good.

  The forward primer includes an amino acid sequence represented by SEQ ID NO: 37, an amino acid sequence represented by SEQ ID NO: 38, an amino acid sequence represented by SEQ ID NO: 39, a base sequence encoding the amino acid sequence represented by SEQ ID NO: 40, and a complement thereof. The polynucleotide may be at least one selected from the group consisting of the polynucleotides represented by the sequences, and may be, for example, SEQ ID NO: 41, SEQ ID NO: 42, SEQ ID NO: 43, or a complementary sequence thereof. A partial fragment that has a length sufficient to function as a primer may be used as a primer. Such length is, for example, about 10 bases to about 24 bases, preferably about 15 bases to about 24 bases, preferably about 19 bases, about 20 bases, about 21 bases or about 22 bases.

  The reverse primer is at least one selected from the group consisting of a polynucleotide encoding the amino acid sequence represented by the amino acid sequence represented by SEQ ID NO: 44, a polynucleotide encoding the amino acid sequence represented by SEQ ID NO: 45, and a complementary sequence thereof. It may be a polynucleotide. Such a polynucleotide may be, for example, a nucleotide sequence encoding the amino acid sequence represented by SEQ ID NO: 46, a nucleotide sequence encoding the amino acid sequence represented by SEQ ID NO: 47, or a polynucleotide represented by a complementary sequence thereof. Further, a fragment of a part of these sequences and having a length sufficient to function as a primer may be used as a primer. Such length is, for example, about 10 bases to about 24 bases, preferably about 15 bases to about 24 bases, preferably about 19 bases, about 20 bases, about 21 bases or about 22 bases.

  When the polynucleotides represented by SEQ ID NO: 41, SEQ ID NO: 42, SEQ ID NO: 43, SEQ ID NO: 46, and SEQ ID NO: 47 are used as primers, “n”, “k”, “h”, About "y" and "r", it is preferable to use all corresponding base sequences as mixed primers. Here, the one-letter code of each base is as well known to those skilled in the art. “N” refers to all bases, ie, adenine, guanine, cytosine and thymine. “K” indicates guanine and thymine. “H” represents adenine, cytosine or thymine. “Y” represents thymine or cytosine. “R” represents guanine and cytosine.

  Most preferably, in order to perform a more comprehensive measurement, the forward primer is a sequence represented by SEQ ID NO: 1, a sequence represented by SEQ ID NO: 2, a sequence represented by SEQ ID NO: 3, a sequence represented by SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: SEQ ID NO: 11 sequence, SEQ ID NO: 12 sequence, SEQ ID NO: 13 sequence, SEQ ID NO: 14 sequence, SEQ ID NO: 15 sequence, SEQ ID NO: 16 sequence, SEQ ID NO: 17 The sequence shown, the sequence shown in SEQ ID NO: 18, the sequence shown in SEQ ID NO: 19, the sequence shown in SEQ ID NO: 20, the sequence shown in SEQ ID NO: 21 and the sequence shown in SEQ ID NO: 22 A forward primer set consisting of a sequence or a complementary sequence thereof, wherein the reverse primer is a sequence represented by SEQ ID NO: 23, a sequence represented by SEQ ID NO: 24, a sequence represented by SEQ ID NO: 25, a sequence represented by SEQ ID NO: 26 , A sequence represented by SEQ ID NO: 27, a sequence represented by SEQ ID NO: 28, a sequence represented by SEQ ID NO: 29, a sequence represented by SEQ ID NO: 30, a sequence represented by SEQ ID NO: 31, a sequence represented by SEQ ID NO: 32, a sequence A reverse primer set comprising the sequence shown by No. 33, the sequence shown by SEQ ID No. 34, the sequence shown by SEQ ID No. 35 and the sequence shown by SEQ ID No. 36, or their complementary sequences, and these forward primer sets and It is preferred to use a reverse primer set together. These forward primers are also referred to as “769f primers”. These forward primers are polynucleotides comprising a base sequence of 20 bases from positions 769 to 788, with the translation start site of the gene product of the tuf gene as position 1. These reverse primers are also referred to as “1068r primers”. These reverse primers are polynucleotides composed of a base sequence of 21 bases from position 1068 to position 1048, with the translation initiation site of the tuf gene as position 1.

These sequences are shown in Tables 2 and 3. Table 2 shows the genera that are preferably detected.

  The primer can be produced by a chemical synthesis method and a biological synthesis method known per se.

  The primer can detect fungi that serve as a microbiological contamination index. Fungi detected with the primer are bacteria that are widely detected in food.

  Such bacteria may be bacteria that are detected in, for example, fresh food such as livestock meat, vegetables, fruits and fresh fish.

  For example, Firmicutes, such as Bacillus, Actinobacteria, such as Cochlear and Micrococcus, Bacteroidetes, such as Chrysobacterium and Flavobacterium, Proteobacteria, such as Proteobacteria Proteobacteria α, such as Sphingomonas, proteobacteria β, such as Alkalinegenes, proteobacteria γ, such as E. coli, and the like.

  In addition, for example, it may be a bacterium classified into the following genus: Acinetobacter, Aeromonas, Alteromonas, Bacillus, Brachybacterium, Brocotrix, Barkholderia, Criseobacterium, Cytobacter, Colweria, Enterobacter, Erwinia, Flavobacterium, Janibacter, Klebsiella, Cochlear, Lactobacillus, Lactococcus, Listeria, Microbacterium, Micrococcus, Morganella, Paracoccus, Photobacterium, Planomicrobium, Pseudoarteromonas, Pseudomonas , Cyclobacter, Cyclomonas, Rahanella, Rhodia, Salinibacterium, Salmonella, Cineraria, Sejondia, Serratia, Shuwanella, Sphingobacteria, Sphin Gomonasu, Staphylococcus, Vibrio, Xanthomonas, Yersinia.

  The bacterial measurement method according to the present invention comprises amplifying a sample nucleic acid to be measured using the primer set. Further, the method may comprise detecting the bacterium based on the amplification product obtained by the amplification and / or calculating the number of the bacterium based on the amplification product obtained by the amplification. You may comprise.

  Here, the “sample nucleic acid” may be any nucleic acid derived from a sample food, such as vegetables, fruits and fresh fish, and attached microorganisms. The sample nucleic acid is prepared by any means known per se, and such means may comprise steps such as mince, homogenate, filtration operation, centrifugation operation, heat treatment, extraction and purification.

  Amplification of the sample nucleic acid may be performed by a known amplification reaction per se, for example, PCR, real-time PCR and the like. Further, the practitioner can arbitrarily select the amplification conditions from known amplification conditions.

  Further, when the real-time PCR method is used as the amplification reaction, the number of bacteria can be measured rapidly, that is, in about 2 hours.

  In the method for measuring bacteria, the presence or absence of bacteria can be detected. In such a method, a sample nucleic acid is amplified by using the primer set, and the presence of the bacterium can be confirmed based on information obtained by analyzing the obtained amplification product. The amplification product may be analyzed by any means known per se that can confirm the presence of bacteria. For example, it may be performed by electrophoresis and / or detection of the presence or absence of hybridization between the amplification product and the probe. Similarly, information regarding the type of bacteria present in the test system may be obtained by analyzing the amplification products.

  In addition, in the method for measuring bacteria, the number of bacteria can be calculated. The number of bacteria can be calculated by performing regression analysis after amplification using the primer set. For example, it may be converted from the correlation between the number of detection cycles and the number of plate bacteria for the amplified product. The conversion may be performed every time the measurement method is performed, or a correlation function may be obtained in advance from the number of plate bacteria and the standard amplification reaction result, and the correlation function may be used for the subsequent measurement. It is advantageous to obtain the correlation function in advance because it is not necessary to obtain the correlation function every time the measurement method is performed.

  Here, the “number of detection cycles” refers to the number of amplification cycles performed until the amplification product amount reaches a predetermined threshold, and is also referred to as “Ct” here.

  In particular, the primers included in the primer set according to the present invention are advantageous for use as universal primers. That is, the primer set can uniformly amplify a plurality of types of bacteria included in the test system in one amplification reaction without bias. This makes it possible to uniformly amplify and detect a wide variety of bacteria adhering to food by a single amplification reaction, and to determine the number of these bacteria.

  In the conventional method, it is difficult to count various bacterial groups adhering to the food at the same time with a speed of about 2 hours, comprehensively, and at the same time. However, according to the present invention, it is possible to count the number of bacteria quickly, exhaustively and simultaneously without bias.

2． Example 1
2.1. Microbial strains used and culture conditions Table 4 shows a total of 63 strains (26 fresh fish isolates and 37 standard strains) used in the experiment.

All standard strains were cultured as instructed by the distribution agencies, and fresh fish isolates were agar medium (TSA-ASW) prepared with tripticase soy agar (Becton Dickinson, Sparks, MD, USA) in 50% artificial sea water and The cells were cultured in marine broth 2216 (Becton Dickinson) or tripticase soy broth (Becton Dickinson). The composition of 100% artificial sea water is as follows; 23.5 g of NaCl, 0.66 g of KCl, 3.9 g of Na ₂ SO ₄ , 10.6 g of MgCl ₂ -6H ₂ O, and 1.5 g of CaCl ₂ -2H ₂ O per 1 liter of distilled water (Okuzumi et al., 1981).

2.2. Bacterial count and bacterial flora analysis Fresh fish samples of 6 mackerel samples, 3 flounder samples, and 3 horse mackerel samples were purchased from the market in Tokyo and transported to the laboratory on ice. 10 g containing 10 cm ² of the epidermis was aseptically collected, homogenized in 90 mL of physiological saline, an appropriate dilution was prepared, and 100 μl thereof was smeared on a TSA-ASW plate. After culturing at 20 ° C. for 5 days, the number of colonies was counted, and 20 randomly selected colonies were purely separated and subjected to a flora analysis. The strain was identified by base sequence analysis of 16S rDNA (50-500 bp or 50-1400 bp).

2.3. Tuf gene sequence analysis and primer design
DNA of each strain prepared according to the method of Murray and Thompson (1980) was used as a sample, and an approximately 880 bp partial fragment of the tuf gene was amplified with the primers of Paradis et al. (2005). Amplified products were cloned into pT7 blue T-vector (Novagen, Madison, Wis.), And multiple clones were sequenced (primers; T7 and M13-M4, Takara). The nucleotide sequence analysis was performed using BigDye terminator ready reaction kit V3.1 (Applied Biosystems, Foster city, CA, USA) and ABI3130 genetic analyzer (Applied Biosystems). The obtained sequence was analyzed using GENETYX 7.0 software (Software development Co., Ltd, Tokyo, Japan). The resulting sequences were aligned (prime alignment), and primers tuf-769f and tuf-1068r were designed at sites that appeared to be good.

2.4. Real-time PCR
PCR reaction was performed under the following conditions: 12.5 μl SYBR Premix Ex Taq II (Takara Bio, Shiga, Japan), 0.5 μl 6-carboxy-X-rhodamine (ROX) reference dye (Takara Bio), 720 nmol / l 769f primer, 560 nmol / l 1068r primer, 2 μl solution to be measured. Temperature conditions are 95 ° C for 15 seconds → (95 ° C for 10 seconds to 60 ° C for 1 minute) × 35 times → 72 ° C for 5 minutes. The instrument used was ABI 7900HT sequence detector (Applied Biosystems). The measured fluorescence value (Rn) was corrected with the fluorescence intensity of the ROX reference (Rn ⁺ ), and ΔRn (Rn ⁺ -Rn ⁻ , Rn ⁻ = average fluorescence value of cycles 3 to 15) was calculated. Detection cycle number (Ct) is ΔRn threshold ^- and the number of cycles has been reached (Rn base standard deviation × 10 times the fluorescence value of the line in the 3 to 15 cycles used in the calculation).

2.5. Real-time PCR reactivity test
DNA of each strain prepared according to the method of Murray and Thompson (1980) was used as a sample to obtain a DNA solution having a constant concentration (5 ng / μl) (concentration was calculated from absorbance, Sambrook et al., 1989). 2 μl of each concentration of DNA solution obtained by 10-fold serial dilution was subjected to PCR. PCR amplification was confirmed by 3.0% agarose gel electrophoresis (NuSieve 3: 1 agarose gel, FMC Bioproducts, Rockland, ME, USA). Comparison of PCR amplification efficiency between different strains was performed by comparing the regression line formulas of scatter plots plotting DNA amount and Ct value. Specifically, the amplification efficiency was determined by using the slope (s) of the regression line and amplification efficiency (e) = 10 ^{1 / s-1} . Amplification efficiency e is _Xn = _Xo * (1 + e) ⁿ ( _Xn : concentration of target DNA in cycle n = copy number, _Xo : initial amount of target DNA, n: number of cycles). That is, the value of e is 0 to 1.0, and if the amplification efficiency is 100%, the value of e takes 1.0.

2.6. Application of real-time PCR to pure strains Overnight cultures of Eromonas Moras column FI56, Shuwanella Frigidimarina FI20, and Staphylococcus pastori FI64 were added to trypticase soy medium (TSB,
Becton Dickinson) 10-fold serially diluted, DNA was extracted from each 1 ml, and subjected to real-time PCR. For the DNA extraction, Mag extractor DNA isolation kit (Toyobo, Co., Ltd, Tokyo, Japan) was used. This method is based on the Boom method (Boom et al., 1990). In summary, 850 μl of lysis solution (containing guanidine hydrochloride) was used to lyse bacterial cells, 40 μl of silica-coated magnetic particles were added, and the mixture was stirred for 10 min. During this time, DNA is adsorbed to silica. Thereafter, the magnetic particles were collected by centrifugation at 3000 g, and washed twice with a washing solution and twice with 70% ethanol. DNA was eluted from the air-dried magnetic particles by stirring with 50 μl of sterile distilled water for 10 min, and the centrifuged supernatant was used as a DNA sample. All eluates were stored at -20 ° C.

  In parallel, the number of viable cells in the overnight culture was counted using a TSA-ASW plate.

2.7. Correlation between bacterial counts in fish samples and real-time PCR results 30 mackerel samples, 11 horse mackerel samples and 12 sardine samples were purchased at different dates. To obtain samples with varying numbers of bacteria, some samples were stored at 5 ° C, 10 ° C, or 20 ° C for 18 hours immediately after purchase. 10 g of each sample was homogenized with 90 ml of physiological saline, smeared on a TSA-ASW agar medium to determine the number of bacteria, and DNA was extracted from 1 ml of the homogenized solution using the above-described Mag-extractor DNA extraction kit. 2 μl of the extract was subjected to the above-mentioned real-time PCR, and the obtained Ct value and the number of bacteria (converted to logarithm) by the TSA-ASW agar medium were plotted in a scatter diagram. Regression analysis was performed with Microsoft Excel 2003 (Microsoft Corp., Co., Ltd., Redmond, WA, USA).

2.8. Comparison of Estimated Number of Cells by Real-Time PCR and Number of Platelets by Plate Medium Method Total 47 samples of fresh fish (23 samples of horse mackerel, 8 samples of mackerel, 9 samples of sardine, 3 samples of saury, 2 samples of flounder and Two samples of bonito) were newly purchased from the market. Some samples were stored at 5 ° C, 10 ° C, or 20 ° C for 18 h to obtain samples with various numbers of bacteria. Bacterial count and real-time PCR were performed as described above. When the number of bacteria was estimated from the Ct value of real-time PCR, the following formula was used; the estimated number of bacteria by the PCR method (logarithmic value) = (37.599-Ct) × 2.75 ⁻¹ . The obtained number of plate bacteria and the estimated number of bacteria by PCR were converted into common logarithm values and plotted in a scatter diagram. For some samples, colonies were isolated from TSA-ASW agar for understanding the flora and used for the flora analysis.

2.9. Nucleotide Sequence Information The nucleotide sequence information of the tuf gene determined and / or used here is registered in an international database, and the numbers are shown in Table 4.

3.Result
3.1. Fresh fish flora The composition of the fungal group forming the number counted as the number of bacteria, that is, the colonies appearing on the plate, was analyzed. Table 5 shows the results of analysis from a total of 12 fresh fish samples.

  From this sample, Cyclobacter was most frequently isolated (10 out of 12 samples; isolated from all 6 mackerels, 2 sample horse mackerel, all 3 samples). Three of them were dominant species (April 2007, Mackerel in January 2008, Horse mackerel in February 2007). Shwanella and Pseudoalteromonas were also well isolated (from 8 and 5 specimens, respectively). Gram-negative bacteria belonging to the Bacteroides group, Chryseobacterium genus and Flavobacterium genus were isolated from 3 and 6 samples, respectively (26% of 260 total isolates from 10%, 12 specimens were Bacteroides group isolates) ). From the group of actinomycetes, which are Gram-positive bacteria with a high G + C content, Kokria, Micrococcus and Rhodia were isolated (4.2%, 11/260).

3.2. Design of primers for real-time PCR The partial sequences of the determined tuf gene were aligned (Table 6). A closer look at the 300 bp region that was considered to be highly conserved revealed that 58.6% (Chrysobacterium formsense FI55 vs. Brachybacterium tyrofermentans FI38) to 99.3% (staphylococcus) at the DNA level. Aureus vs. Listeria monocytogenes). Therefore, universal primers were designed at 769 to 788 bp and 1048 to 1068 bp as base positions at both ends of this region (base position notation follows the sequence of Escherichia coli K-12 MG1655 strain: registration number AE000410) (Table 7). In designing the primer, the degeneracy was taken into consideration so that no mismatch was included within 10 bases from the 3 ′ end (Table 8).

  Amplification with the designed primers was tested for all strains, confirming good amplification and specific amplification (FIG. 4).

3.3. Real-time PCR primer reactivity test Table 9 shows the results (Ct value) of real-time PCR targeting the tuf gene using 10 ng of chromosomal DNA extracted and purified from each strain as a template.

  Several actinomycetes, Cochlia, Janibacter, Microbacteria, and Micrococcus showed relatively delayed Ct values (25.4 ± 2.5) (11 batiles averaged 17.2 ± 1.8 42) Gram-negative bacteria averaged 16.2 ± 1.6).

The average amplification efficiency for the 11 strains of Bachley was 0.99 ± 0.03 (0.93 to 1.05). In some actinomycetes groups, amplification efficiency could not be calculated due to poor efficiency, but in Rhodia and Salinibacterium amurskiens, 0.91 to 0.98 was sufficiently acceptable. The proteobacterial gram-negative bacteria averaged 1.01 ± 0.07 (0.79, bulk-Holdelia caledonica to 1.09) on average among the 38 strains tested. However, Bacteroidetes (4 strains) showed a slightly low value of 0.93 ± 0.06 (0.85, Sejongdia antaractica to 0.99, Chrysobacterium formenseens).
3.4. Comparison of Ct value and number of bacteria in pure strains Ct values of DNA solutions extracted from the cultures of Staphylococcus aureus FI64, Aeromonas Moras column FI56, and Schwannella frigidimarina FI20, and the number of each bacteria have a good correlation. Shown (FIG. 1). The regression equation was y = −3.29x + 41.2, and the correlation coefficient was 0.98. In the graph, the white triangle is the Schwanella Frigidimarina FI20, the white square is the Staphylococcus pastori FI64, and the black circle is the Aeromonas Moras Column FI56.

3.5. Correlation between real-time PCR Ct value and number of bacteria in fish sample
Real-time PCR Ct values and bacterial counts were plotted on a scatter diagram for 30 samples of mackerel, 11 samples of horse mackerel, and 12 samples of sardine (FIG. 2). The regression lines were y = −2.753x + 37.628 (mackerel) y = −2.8611x + 38.207 (Aji) and y = −2.937x + 37.833 (sardine), with correlation coefficients of 0.936, 0.939, and 0.937, respectively. . When these three types of plots are combined into a single regression line, y = −2.753x + 37.599, which is almost the same as the regression line for each fish type. Therefore, the formula for estimating the number of bacteria from the Ct value of real-time PCR was derived from this formula; the estimated number of bacteria by the PCR method (logarithmic value) / g = (37.599-Ct) /2.753.

3.6. Real-time PCR Estimated Bacterial and Plate Bacterial Counts The number of bacteria and plate counts estimated by real-time PCR were 23 aji, 8 mackerel, 9 sardines, 2 flounder, 3 saury. Two specimens of bonito were compared as samples. The number of bacteria in the sample is in the range of about 2.5 to 9.0 log CFU / g, and FIG. 3 is a plot of the number of bacteria and the number of real-time PCR estimated bacteria, respectively. The regression line of this plot was y = 1.00x + 0.21 (correlation coefficient 0.94), the 95% confidence interval of the slope was 0.92 to 1.08, and the 95% confidence interval of the y-intercept was -0.27 to 0.68. This shows that neither the slope nor the intercept is significantly different from 1 and 0 (when the two methods are equivalent, the slope is 1 and the intercept is 0).

For 6 specimens of the test sample, colonies were isolated from the plate and examined for bacterial flora (Table 10).

  The bacterial flora is not much different from the results in Table 5, and various marine products-related bacteria with the dominant bacteria group such as Vibrio spp., Cyclobacter spp., Shuwanella spp., Acinetobacter spp. .

4. Discussion
The protein elongation factor Tu (Ef-Tu) encoded by the tuf gene plays an important role in binding aminoacyl transfer RNA (tRNA) to the A site of the ribosome during protein synthesis. For this reason, the structure and the sequence are well conserved among organisms. Therefore, in bacteria, the tuf gene has been used for phylogenetic analysis and species identification. The tuf gene has 1 or 2 copies on the chromosome (Warren et al., 2001). From these facts, it is considered that the tuf gene is excellent as a gene used in real-time PCR for quantifying a wide variety of bacterial species by the same reaction. That is, it is expected that the influence on the quantification result due to the copy number variation and the sequence variation is expected to be small. Here, we found a highly conserved region in the region of 769-1069 bp. In this region, six β-sheet structures are involved in the formation of β-barrel structures and are involved in the reaction of aminoacyl tRNA binding to the Ef-Tu / GTP complex (Nissen et al., 1995). In other words, it was considered highly conserved because of its high functional importance, and a primer was designed in this region.

As a result of comparing the estimated number of bacteria by real-time PCR and the number of plate bacteria for 47 samples, a significant correlation was found (FIG. 3). From this, it can be said that the formula shown here, the estimated number of bacteria by the PCR method (logarithmic value) = (37.599−Ct) × 2.75 ⁻¹ (FIG. 1) is sufficiently usable. The slope and intercept of the regression line of 47 samples were 1.00 and 0.21, respectively, and were not significantly different from 1 and 0. From this, it was shown that the estimated value by the real-time PCR method has no bias and can be used without requiring correction between log3 and log9. The influence on the quantitative value due to the difference in the bacterial flora of the samples was not observed here because the results in Table 10 were sufficiently varied (Table 10). The difference in values between the real-time PCR method and TSA-ASW agar culture (20 ° C culture) is 26 samples or less | 0.5 | log or less and 21 samples are between | 0.5 | to | 1.0 | log), no difference exceeding 1.0 log was observed. This also meets the conditions indicated in the Camden Guidelines: “If the ratio of the number of samples with a common logarithmic difference in the number of bacteria exceeding ± 1 is within 5%, it is considered to be equivalent performance” (Campden , 2001). For the 47 samples, the average difference between the bacterial count estimation results by real-time PCR and the TSA-ASW agar plate measurement results was 0.44 ± 0.28 SD, which was comparable in all bacterial count ranges. This spec can be said to be sufficiently usable in practice for microbial testing. However, it is slightly inferior to the rapid method based on other cultures; for example, in the film agar plate method and automatic MPN method, it is <± 0.5 log at 90% or more data points compared to the reference method. Fits in the difference. However, the real-time PCR method can give this result in 2 hours (one hour each for sample preparation and real-time PCR). Therefore, it can be said that the real-time PCR method achieved a good balance between practical accuracy and speed of results.

  The ability to rapidly measure the number of bacteria consisting of various fungal groups by real-time PCR has great advantages in the food production process. The real-time PCR method made it possible to estimate the number of fresh fish in 2 hours in the range of 3-6 log CFU / g for the tuf gene. Conventional rapid measurement methods are also practically useful, but few have achieved both speed and accuracy. This is due in part to the fact that differences in the bacterial flora and cellular state (such as the presence of damaged bacteria) and differences in food-derived components affect each sample. On the other hand, many quantifications of bacterial cells using real-time PCR have been reported for specific (single) bacteria and fungal groups. There are several merits of quantification using real-time PCR: (i) Unlike other biomolecules, the amount of DNA is itself proportional to the number of cells in a unicellular organism. (Ii) From the physical and chemical properties of DNA molecules It is easier to extract and purify than other biomolecules. (Iii) Real-time PCR does not use the biochemical reaction to be measured (eg enzyme reaction) but only measures the amount of DNA using an external reaction system. Insensitive to ingredients. The real-time PCR method is applied to the bacterial count measurement taking advantage of such advantages.

  In this example, it was described that chromosomal DNA derived from a wide range of bacteria can be rapidly and quantitatively amplified by real-time PCR targeting the tuf gene. The tuf gene universal primer was designed by sequencing from a wide variety of strains to enable good amplification.

Example 2
2.2.1 Comparison of live cell counts estimated by real-time PCR and plate culture method counts A total of 12 livestock samples were purchased from retail stores in Tokyo. The number of bacteria was measured on a tripch case soy agar medium (Becton Dickinson), and real-time PCR was performed as described above. When estimating the bacterial count from the Ct value of real-time PCR, the following formula was used; estimated bacterial count (logarithmic value) = (37.599-Ct) × 2.75 ⁻¹ . The obtained number of plate bacteria and the estimated number of bacteria by PCR were converted into logarithmic values and plotted on a scatter diagram.

2.2.2. Comparison of real-time PCR estimated bacteria and plate counts and discussion The number of bacteria in the sample is in the range of about 3.6 to 8.0 log CFU / g, plotting the number of plate bacteria and the number of real-time PCR estimated bacteria, respectively. Is FIG. The regression line of this plot was y = 1.00x + 0.00 (correlation coefficient 0.80), indicating a good correlation. It is expected that better correlation can be secured by improving the protocol according to livestock meat.

  All the differences between the count values of the real-time PCR method and trypticase soy agar were within ± 1 common logarithmic value difference, and no difference exceeding ± 1 common logarithmic value difference was observed. This is a guideline (Campden, 2001) indicated in the Camden guideline, “If the ratio of the number of specimens with a common logarithmic difference in the number of bacteria exceeding ± 1 is within 5%, it is regarded as equivalent performance”. It is compatible and supports the validity of the bacterial count method by the real-time PCR method.

Example 3
2.3.1 Comparison of the estimated number of vegetable bacteria by real-time PCR and the number of bacteria by the plate culture method A total of 25 samples of fresh vegetables and raw vegetables such as fresh vegetable salad were purchased from retail stores in Tokyo. The number of bacteria was measured on a tripch case soy agar medium (Becton Dickinson), and real-time PCR was performed as described above. When estimating the bacterial count from the Ct value of real-time PCR, the following formula was used; estimated bacterial count (logarithmic value) = (37.599-Ct) × 2.75 ⁻¹ . The obtained number of plate bacteria and the estimated number of bacteria by PCR were converted into logarithmic values and plotted on a scatter diagram.

2.3.2. Real-time PCR Estimated Results Comparison and Discussion of Bacterial and Plate Bacterial Counts The number of bacteria and plate counts estimated from real-time PCR were compared using 25 samples of raw vegetables and foods made of raw vegetables as samples. The number of bacteria in the sample is in the range of about 2.6 to 9.1 log CFU / g, and FIG. 6 is a plot of the number of bacteria on the plate and the number of bacteria estimated by real-time PCR. The regression line of this plot was y = 0.98x + 0.13 (correlation coefficient 0.85), confirming a very good correlation.

  The difference between the count values of the real-time PCR method and trypticase soy agar is within ± 1 common logarithmic difference for 23 of 25 samples, and the difference exceeding ± 1 common logarithmic value is observed only in one sample According to the guideline (Campden, 2001) shown in the Camden guideline, “If the ratio of the number of specimens whose common logarithmic difference in the number of bacteria exceeds ± 1 is within 5%, it is regarded as equivalent performance” It is compatible and supports the validity of the bacterial count method by the real-time PCR method.

References
Boom, R., Sol, CJA, Salimans, MMM, Jansen, CL, Dillen, PMEW, Noordaa, J., 1990.Rapid and simple method for purification of nucleic acids.J Clin Microbiol 28, 495-503.
Campden Company. 2001. Guideline 29. Guidelines for establishing the suitability of food microbiological methods. CCFRA, Gloucestershire, UK.
Paradis, S., Boissinot, M., Paquette, N., Belanger, SD, Martel, EA, Boudreau, DK, Picard, FJ, Ouellette, M., Roy, PH, Bergeron, M., 2005. Phylogeny of the Enterobacteriaceae based on genes encoding elongation factor Tu and F-ATPase β-subunit. Int J Syst Evol Microbiol 55, 2013-2025.
Murray, MG, Thompson, WF, 1980.Rapid isolation of high molecular weight plant DNA.Nucl Acids Res 8, 4321-4325
Sambrook, JE, Fritsch, F. and Maniatis, TS (1989) Molecular Cloning: A Laboratory Manual, 2nd Edn. Cold Spring Harbor, New York: Cold Spring Harbor Laboratory.
Nissen, P., Kjeldgaard, M., Thirup, S., Polekhina, G., Reshetnikova, L., Clark, BFC, Nyborg, J., 1995.Crystal structure of the ternary complex of the Phe-tRNA ^Phe , EF -Tu, and a GTP analog.Science 270, 1464-1472.
Warren, C., Lathe, III., And Bork, P., 2001. Evolution of tuf genes: ancient duplication, differential loss and gene conversion.FEBS Lett 502, 113-116.

Claims (12)

A primer set for amplifying bacterial nucleic acid, the primer set comprising a forward primer and a reverse primer,
The forward primer is at least one selected from the group consisting of the sequence shown in SEQ ID NO: 41, the polynucleotide shown in SEQ ID NO: 42, the polynucleotide consisting of the sequence shown in SEQ ID NO: 43, and the complementary strand thereof, and the sequence continuation A polynucleotide consisting of 15 to 24 bases,
The reverse primer is at least one selected from the group consisting of the sequence shown in SEQ ID NO: 46 and the sequence shown in SEQ ID NO: 47 and its complementary strand, and consists of 15 to 24 bases in the sequence. A primer set that is a polynucleotide. The primer set according to claim 1,
The forward primer comprises a polynucleotide consisting of the sequence represented by SEQ ID NO: 41, the sequence represented by SEQ ID NO: 42 or the sequence represented by SEQ ID NO: 43, or a complementary strand,
A primer set comprising a polynucleotide comprising a sequence represented by SEQ ID NO: 46 or a sequence represented by SEQ ID NO: 47 or a complementary strand as the reverse primer. The primer set according to claim 1,
The forward primer is a mixed base, and comprises a polynucleotide or a complementary strand consisting of a sequence represented by SEQ ID NO: 41, a sequence represented by SEQ ID NO: 42, and a sequence represented by SEQ ID NO: 43;
The reverse primer is a mixed base, and a primer set comprising a polynucleotide or a complementary strand consisting of the sequence represented by SEQ ID NO: 46 and the sequence represented by SEQ ID NO: 47. The primer set according to claim 1,
The forward primer is represented by SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 5, SEQ ID NO: 6 The sequence shown by SEQ ID NO: 7, the sequence shown by SEQ ID NO: 8, the sequence shown by SEQ ID NO: 9, the sequence shown by SEQ ID NO: 10, the sequence shown by SEQ ID NO: 11, the sequence shown by SEQ ID NO: 12 The sequence shown in SEQ ID NO: 13, the sequence shown in SEQ ID NO: 14, the sequence shown in SEQ ID NO: 15, the sequence shown in SEQ ID NO: 16, the sequence shown in SEQ ID NO: 17, the sequence shown in SEQ ID NO: 18, the sequence At least from the group consisting of the sequence shown by No. 19, the sequence shown by SEQ ID No. 20, the sequence shown by SEQ ID No. 21, the sequence shown by SEQ ID No. 22 and its complementary sequence It consists of a sequence selected,
The reverse primer is represented by SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28. Sequence, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34 A primer set consisting of at least one sequence selected from the group consisting of the sequence shown in SEQ ID NO: 35 and the sequence shown in SEQ ID NO: 36, and its complementary sequence. The primer set according to claim 1,
The forward primer is represented by SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 5, SEQ ID NO: 6 The sequence shown by SEQ ID NO: 7, the sequence shown by SEQ ID NO: 8, the sequence shown by SEQ ID NO: 9, the sequence shown by SEQ ID NO: 10, the sequence shown by SEQ ID NO: 11, the sequence shown by SEQ ID NO: 12 The sequence shown in SEQ ID NO: 13, the sequence shown in SEQ ID NO: 14, the sequence shown in SEQ ID NO: 15, the sequence shown in SEQ ID NO: 16, the sequence shown in SEQ ID NO: 17, the sequence shown in SEQ ID NO: 18, the sequence A sequence comprising the sequence shown by No. 19, the sequence shown by SEQ ID No. 20, the sequence shown by SEQ ID No. 21 and the sequence shown by SEQ ID No. 22, or a complementary sequence thereof It is a de primer set,
The reverse primer is represented by SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28. Sequence, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34 A primer set which is a reverse primer set consisting of the sequence shown in SEQ ID NO: 35 and the sequence shown in SEQ ID NO: 36, or a complementary sequence thereof.   The primer set according to any one of claims 1 to 5, wherein the amplification of bacteria by the primer set is a comprehensive amplification of nucleic acids derived from a plurality of types of bacteria.   The primer set according to any one of claims 1 to 6, wherein the bacterium is selected from at least one selected from the group consisting of fermicote, actinobacteria, bacteroidetes, and proteobacteria.   The bacteria are Acinetobacter, Aeromonas, Alteromonas, Bacillus, Brachybacterium, Brocotrix, Barkholderia, Chryseobacterium, Cytobacter, Colwellia, Enterobacter, Erwinia, Flavobacterium, Janibacter, Klebsiella, Cochlear, Lact Bacillus, Lactococcus, Listeria, Microbacterium, Micrococcus, Morganella, Paracoccus, Photobacterium, Planomicrobium, Pseudoarteromonas, Pseudomonas, Cyclobacter, Cyclomonas, Rahanella, Rhodia, Salinibacterium, Salmonella , Cineraria, Sejongdia, Serratia, Shuwanella, Sphingobacterium, Sphingomonas, Staphylococcus, Vibrio, Zant Primer set according to any one of claims 1 to 6, at least one selected from eggplant and the group consisting of Yersinia.   A method for measuring bacteria, comprising amplifying a sample nucleic acid with the primer set according to any one of claims 1 to 8, and detecting the bacteria from the amplification product.   The method according to claim 9, further comprising determining the number of bacteria from the detection result of the bacteria.   The method according to claim 10, wherein the sample nucleic acid includes nucleic acids derived from a plurality of types of bacteria.   The method according to claim 10, wherein the nucleic acids derived from the plurality of types of bacteria are comprehensively amplified.

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