Journal of Microbiological Methods 106 (2014) 129–134

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Journal of Microbiological Methods

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A novel high-resolution melting analysis-based method for Yersiniaenterocolitica genotyping

Roberto A. Souza, Juliana P. Falcão ⁎Brazilian Reference Center on Yersinia spp. other than Y. pestis, Departamento de Análises Clínicas, Toxicológicas e Bromatológicas, Faculdade de Ciências Farmacêuticas de Ribeirão Preto—USP, Brazil

⁎ Corresponding author at: Departamento de AnáBromatológicas, Faculdade de Ciências Farmacêuticas dCafé, s/no, Campus Universitário USP, Ribeirão Preto, SP 13602 4896; fax: +55 16 3602 4725.

E-mail address: jufalcao@fcfrp.usp.br (J.P. Falcão).

http://dx.doi.org/10.1016/j.mimet.2014.08.0110167-7012/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 15 July 2014Received in revised form 20 August 2014Accepted 21 August 2014Available online 30 August 2014

Keywords:Yersinia enterocoliticaSingle-nucleotide polymorphisms (SNPs)High resolution melting analysis (HRMA)Molecular epidemiologyGenetic variability

Pathogenic Yersinia enterocolitica strains are associated with biotypes 1B, 2-5, while environmental strainswith biotype 1A. In this work a method for Y. enterocolitica genotyping based on HRMA to determine SNPswas developed and the genetic diversity of 50 strains was determined. The strains were clustered into threegroups consistent with the pathogenic profile of each biotype. The results provided a better understandingof the Y. enterocolitica genetic variability.

© 2014 Elsevier B.V. All rights reserved.

Yersinia enterocolitica is a common enteric pathogen that can causedisease in humans and animals with the possibility of extraintestinalcomplications. The disease can range from a self-limiting gastroenteritisto a potentially fatal septicaemia (Drummond et al., 2012). Not all ofthe Y. enterocolitica strains have the same pathogenicity. Strains of 1Abiotype are considered to be mainly non-pathogenic, while of biotypes2, 3, 4, and 5 have low to moderate pathogenicity, and of biotype 1Bare highly pathogenic (Fredriksson-Ahomaa, 2007).

Many of the currently available molecular techniques may becomelaborious, costly and time-consuming when they are applied to large-scale studies for epidemiological purposes (Foxman et al., 2005).The need for molecular assays that circumvent these limitations hastherefore led to the development of the high-resolution meltinganalysis (HRMA) technology (Wittwer et al., 2003).

HRMA is considered to be a fast, cost-effective, sensitive, specific andhigh-throughput method for the interrogation of single-nucleotidepolymorphisms (SNPs), hypervariable repeat regions in PCR products,and also for the discovery of new SNPs (Smith et al., 2010). It consistsof a one-step, closed-tube post-PCR assay that detects sequence varia-tions within specific loci via accurate monitoring of the reduction inthe fluorescence of a PCR product stained with a double-stranded-specific fluorescent dye to monitor the transition from unmelted to

lises Clínicas, Toxicológicas ee Ribeirão Preto—USP, Av. do4040-903, Brazil. Tel.: +55 16

melted DNA. In contrast to traditional melting analysis, the informationof the HRMA method is contained in the shape of the melting curve,rather than just in the calculated melting temperature (TM) (Lévesqueet al., 2011).

In the recent past, SNPs were proposed to be among the mostpromising genetic markers for population genetic studies of microor-ganisms (Brumfield et al., 2003). The high-throughput, low-cost andhigh-resolution characteristics of the HRMA for mutation detectionmake it a desirable genotyping tool for the detection and genotypingof the SNPs of several microorganisms, simultaneously (Smith et al.,2010).

The aims of this work were to develop a method for Y. enterocoliticagenotyping based on determining differences in SNPs by HRMA and totype 50 Y. enterocolitica strains.

A total of 50 Y. enterocolitica strains of biotypes 1A, 1B, 2, 3, 4, and 5were used in this study. The genomic DNA of each strain was extractedas described by Campioni and Falcão (2014). The quantity of DNA wasdetermined using a NanoDrop 1000 (Thermo Scientific), and its puritywas estimated as described by Sambrook and Russel (2001). It isimportant to emphasise that the strains were isolated independentlyfrom different samples.

To identify the presence of SNPs in the 16S rRNA, glnA, gyrB,hsp60 and recA genes, the sequences of 15 Y. enterocolitica strainspreviously deposited in the GenBank/EMBL/DDBJ databases wereused. The GenBank/EMBL/DDBJ accession numbers of gene sequencesof each strain used for the SNP identifications are presented inTable S1.

The presence of SNPs was assessed by visually inspecting contigscomposed of sequences from the same loci of the aforementioned

Table 1Primer sequences and conditions used in the HRMA assay.

Primer designation a Primers sequence (5′ → 3′) SNPs Amplicon size (bp) Annealing temperature (°C) HRMA region (°C)

16S rRNA-SNP1.F16S rRNA-SNP1.R

GAGCGGCAGCGGGAAGTAGTTTATCCATCAGGCAGTTTCCCAGACAT

T/C 80 55 79.00–86.00

glnA-SNP1.FglnA-SNP1.R

AGGCATTAACGAATCCGACATGGTTGGCTCAAGGATGTCACAACGGAT

T/C 109 55 77.00–83.50

glnA-SNP2-3.Fb

glnA-SNP2-3.RbTATCCGTTGTGACATCCTTGAGCCCGAACGTCGTCGAACAGGAAGAA

T/C and T/C 159 55 78.00–85.00

glnA-SNP4.FglnA-SNP4.R

TTGTTTGGGCCAGAGCCAGAATTTGTTGCCGCCTTCGTATTTGGTG

T/C 134 55 79.50–85.50

hsp60-SNP1.Fhsp60-SNP1.R

ATCTCTAACATCCGCGAAATGCTGCCTAACCACCAGAGTTGCCAGAGCTT

T/C/G 115 55 78.00–85.00

hsp60-SNP2-3.Fb

hsp60-SNP2-3.RbGAAGATGTTGAAGGCGAAGCTCTGTCTTGCAGCATGGCTTTACGAC

T/A and T/C 119 55 78.50–85.50

hsp60-SNP4-5.Fb

hsp60-SNP4-5.RbATATCGCTACCCTGACTGCGGATAACAACACGTTTCGCCTGACCC

T/C and T/C 103 55 75.50–83.50

a F, forward; R, reverse.b The primer pair was designed in order to flank two SNPs.

130 R.A. Souza, J.P. Falcão / Journal of Microbiological Methods 106 (2014) 129–134

strains. The comparison was performed with the aid of the ChromasPro1.5 software package (Technelysium Pty Ltd). One, four, and five SNPswere identified in the 16S rRNA, glnA, and hsp60 genes, respectively,

T

T

Fig. 1. High-resolution melting curves of the 16S rRNA-SNP1 (a), glnA-SNP1 (b), glnA-SNP2-3 ((adenine), C (cytosine), G (guanine), and T (thymine).

in the 15 Y. enterocolitica strains assessed. Notably, the diversities ofthe gyrB and recA sequences of the strains used did not allow the designof primers that could be used for SNP differentiation.

(a)

(b)

C

C

c), glnA-SNP4 (d), hsp60-SNP1 (e), hsp60-SNP2-3 (f), and hsp60-SNP4-5 (g) fragments. A

(c)

C-CC-T

T-T

(d)

(e)

C

T

C

T G

Fig. 1 (continued).

131R.A. Souza, J.P. Falcão / Journal of Microbiological Methods 106 (2014) 129–134

(f)

T-C

A-T

(g)

T-C

C-C

Fig. 1 (continued).

132 R.A. Souza, J.P. Falcão / Journal of Microbiological Methods 106 (2014) 129–134

To identify each SNP detected, primer pairs were designed to flankthe regions that contained the SNPs in the Y. enterocolitica 16S rRNA,glnA and hsp60 genes, according to Souza and Falcão (2012). One,three and three primer pairs were designed, respectively, for the 16SrRNA, glnA and hsp60 sequences. The primer sequences and theircharacteristics are presented in Table 1.

All oligonucleotides were synthesised using standard, desaltedprimers by Integrated DNA Technologies, Inc. (Coralville), and wereemployed without further purification. The primer pair specificitieswere confirmed using agarose gel electrophoresis andmelting analyses.

Real-time PCR and theHRMAwere performed as described by Souzaand Falcão (2012), using 1 ng/μL of DNA. Heteroduplex formation wasachieved by mixing 10 ng of the DNA of the tested strain with 10 ngof the DNA of the Y. enterocolitica ATCC 9610T strain before the real-time PCR and HRMA steps. Reaction mixtures without a DNA templatewere used as negative controls.

All of the runs included four Y. enterocolitica strains (ATCC 9610T,8081, FCF 352, and FCF 505), for which the sequences of the genesstudied were known, which allowed them to be used as referencestrains. The SNPs of the 50 tested strainswere determined by comparing

their melting profiles with those of the reference strains. All of thesamples were tested in duplicate to ensure assay reproducibility.

Differentmeltingprofileswere revealed for all seven fragments fromthe 50 Y. enterocolitica strains genotyped. The discrimination among theSNPs identified in the hsp60-SNP1 fragment was only possible afterheteroduplex formation. The normalised melting curves are presentedin Fig. 1.

The phylogenetic analysis was based on sequences composed of thenucleotides identified in each fragment for each Y. enterocolitica straingenotyped. Clustering was performed with the software packageBioNumerics 7.0 (Applied Maths NV) and using the unweighted pairgroup method with arithmetic mean (UPGMA) with Dice similaritycoefficient and Jukes–Cantor distance correction model. Bootstrapvalues (1000 replicates) were used to estimate the robustness of thephylogenetic analysis.

The phylogenetic tree clustered the 50 Y. enterocolitica strains intothree groups. The first group (A) was composed of all Y. enterocoliticastrains of the biotype 1B and one of the biotype 1A (ATCC 9610T). Thesecond group (B) consisted of Y. enterocolitica strains of the biotypes 2,3, 4, and 5, and the third (C) was composed exclusively of strains of

133R.A. Souza, J.P. Falcão / Journal of Microbiological Methods 106 (2014) 129–134

the biotype 1A. High bootstrap values were obtained for the threegroups (Fig. 2).

The phylogenetic analysis using HRMA developed here furtherconfirmed the grouping of the Y. enterocolitica biotypes into threeclusters in correlation with their pathogenic potential and biotypes. In

Fig. 2. Genetic relatedness among Y. enterocolitica strains based on the concatenated sequenceglnA-SNP4, hsp60-SNP1, hsp60-SNP2-3, and hsp60-SNP4-5 fragments. Clusters were determincorrection model. Bootstrap values are presented in front of the nodes.

agreement, distinct pathogenic potentials were well characterisedand associated with different Y. enterocolitica biotypes (Fredriksson-Ahomaa, 2007). Also, the HRMA-based method developed revealedthat strains with different serotypes produced identical HRMA profiles.This suggests that although the strains demonstrate a large amount

s composed by the identified nucleotides in the 16S rRNA-SNP1, glnA-SNP1, glnA-SNP2-3,ed using the UPGMA tree with the Dice similarity coefficient and Jukes–Cantor distance

134 R.A. Souza, J.P. Falcão / Journal of Microbiological Methods 106 (2014) 129–134

of heterogeneity in their O antigens, they are related genetically, as sug-gested by studies usingmultilocus sequence typing (MLST) (Kotetishviliet al., 2005).

Similar to Sihvonen et al. (2012), our results showed that the patho-genic biotypes of Y. enterocolitica (1B, 2, 3, 4 and 5) are more similar toeach other than to the biotype 1A, which is considered to be mainlynon-pathogenic. Additionally, our study also confirmed that biotype1A is genetically more diverse in its genetic composition than theother biotypes.

The present study was able to provide a better understanding of theY. enterocolitica genetic variability once differences were observedbetween environmental isolates (1Abiotype) and putatively pathogenicisolates (1B, 2, 3, 4, and 5 biotypes) and corroborated a previous studysuggesting that biotype 1A should be designated as a third subspeciesof Y. enterocolitica (Howard et al., 2006). However, it failed to subtypestrains of the same biotype or to reveal unequivocal relationshipsbetween the HRMA types and the epidemiological links of thestrains. Therefore, deeper understanding of the genetic variability ofY. enterocolitica species based on the HRMA data presented here maybe further obtained by increasing the discriminatory power of thismethod through resolving SNPs in other housekeeping genes. More-over, further analysis of a larger number of isolates from various geo-graphic areas is required to reveal the potential of our HRMA-basedmethod to be used unequivocally for epidemiological investigations ofall biotypes of Y. enterocolitica.

This study was supported by the São Paulo Research Foundation(FAPESP) (Proc. 2010/19830-5). During the course of this work, R. A.Souza was supported by a scholarship from FAPESP (Proc. 2009/08455-1).

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.mimet.2014.08.011.

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