Detection of mutations in Salmonella enterica gyrA, gyrB, parC and parE genes by denaturing high performance liquid chromatography (DHPLC) using standard HPLC instrumentation

L. P. Randall*, N. G. Coldham and M. J. Woodward

Veterinary Laboratories Agency (Weybridge), New Haw, Addlestone, Surrey KT15 3NB, UK


* Corresponding author. Tel: +44-1932-357906; Fax: +44-1932-347046; E-mail: l.randall{at}vla.defra.gsi.gov.uk

Received 2 June 2005; returned 25 July 2005; revised 26 July 2005; accepted 27 July 2005


    Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Aims: Quinolone antibiotics are the agents of choice for treating systemic Salmonella infections. Resistance to quinolones is usually mediated by mutations in the DNA gyrase gene gyrA. Here we report the evaluation of standard HPLC equipment for the detection of mutations (single nucleotide polymorphisms; SNPs) in gyrA, gyrB, parC and parE by denaturing high performance liquid chromatography (DHPLC).

Methods: A panel of Salmonella strains was assembled which comprised those with known different mutations in gyrA (n = 8) and fluoroquinolone-susceptible and -resistant strains (n = 50) that had not been tested for mutations in gyrA. Additionally, antibiotic-susceptible strains of serotypes other than Salmonella enterica serovar Typhimurium strains were examined for serotype-specific mutations in gyrB (n = 4), parC (n = 6) and parE (n = 1). Wild-type (WT) control DNA was prepared from Salmonella Typhimurium NCTC 74. The DNA of respective strains was amplified by PCR using Optimase® proofreading DNA polymerase. Duplex DNA samples were analysed using an Agilent A1100 HPLC system with a Varian HelixTM DNA column. Sequencing was used to validate mutations detected by DHPLC in the strains with unknown mutations.

Results: Using this HPLC system, mutations in gyrA, gyrB, parC and parE were readily detected by comparison with control chromatograms. Sequencing confirmed the gyrA predicted mutations as detected by DHPLC in the unknown strains and also confirmed serotype-associated sequence changes in non-Typhimurium serotypes.

Conclusions: The results demonstrated that a non-specialist standard HPLC machine fitted with a generally available column can be used to detect SNPs in gyrA, gyrB, parC and parE genes by DHPLC. Wider applications should be possible.

Keywords: ciprofloxacin , S. enterica , fluoroquinolones , resistance


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
(Fluoro)quinolone resistance in Salmonella enterica is of clinical importance because ciprofloxacin is the drug of choice for treating invasive human salmonellosis.13 (Fluoro)quinolone resistance in S. enterica is usually mediated by at least one mutation in a DNA topoisomerase gene.4 However, in clinical human and veterinary isolates of Salmonella spp., mutations are usually confined to gyrA.57 Whilst a single mutation in gyrA on its own is not sufficient for clinical resistance to fluoroquinolones, a gyrA mutation is a good marker indicating that fluoroquinolones should not be chosen for treating the respective infection.

In recent years, denaturing high performance liquid chromatography (DHPLC) using specialist equipment has become widely used for detection of single nucleotide polymorphisms (SNPs) including those within the quinolone resistance-determining regions (QRDR) of gyrA, gyrB, parC and parE in Salmonella.6,7 Eaves et al.6 demonstrated that DHPLC showed improved detection of mutations in gyrA of Salmonella compared with LightCycler-based PCR-gyrA hybridization mutation assay (GAMA) or single-strand conformational polymorphism (SSCP).

In addition to target gene mutations, active efflux is also a primary mechanism of resistance to ciprofloxacin in S. enterica8 and selection of multiple (e.g. efflux type) resistance in S. enterica serovar Enteritidis and Typhimurium during treatment with ciprofloxacin and enrofloxacin has been reported.9,10 Clinical laboratories may therefore be interested in evaluating the mechanism of fluoroquinolone resistance in bacteria such as Salmonella to determine whether resistance is associated with mutation within the QRDRs of gyrA, gyrB, parC and parE or with genes associated with efflux such as acrAB.11,12 Many laboratories are equipped with standard HPLC equipment for both quantitative and qualitative chemical analyses. In this study, we evaluated a non-specialist industry standard HPLC (Agilent A1100) system and a readily available Varian HelixTM DNA column for mutation detection by DHPLC. In this study, we focused on mutations in the gyrA, gyrB, parC and parE genes of Salmonella.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Bacterial strains and growth conditions

A panel of Salmonella strains (n = 69) was assembled from a collection held at the Veterinary Laboratories Agency (VLA), UK. These comprised strains that had mutations in gyrA and had been characterized previously (n = 8, Table 1).7 The panel also comprised strains that were only partially characterized. This included a panel of fluoroquinolone-susceptible isolates (ciprofloxacin MIC < 0.125 mg/L, n = 22) and isolates with reduced susceptibility (ciprofloxacin MIC > 0.125 mg/L, n = 28) which were tested for mutations in gyrA by DHPLC. Additionally, antibiotic-susceptible non-Typhimurium strains were tested for serotype-specific mutations in gyrB (n = 4), parC (n = 6) and parE (n = 1). Wild-type (WT) Salmonella Typhimurium NCTC 74 was used as control strain. Strains were grown in Luria-Bertani broth at 37°C for 16 to 24 h to produce DNA template for PCR.


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Table 1. Salmonella control strains with known mutations gyrA and susceptibility to quinolone antibiotics

 


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Figure 2. DHPLC analyses of S. enterica strains at 61°C with mutations in the following regions of gyrA: Ser-83->Phe + Asp-144->Asp (A), Asp-114->Asp (B), Asp-87->Asn (C), Ser-83->Phe (D), Ser-83->Tyr (E), Asp-87->Gly (F), Asp-87->Tyr (G), Asp-82->Asn (H) and wild-type (WT).

 
PCR

To prepare the template for PCR, 1 mL of an overnight bacterial culture was placed in an Eppendorf tube and centrifuged. The bacterial pellet, after washing, was suspended in HPLC water and then placed in a boiling water bath for 5 min, centrifuged again and the supernatant was stored at –20°C and used as the DNA template.

PCR primers to amplify the QRDR from gyrA, gyrB, parC and parE were: gyrA-F (5'CGTTGGTGACGTAATCGG3'), gyrA-R (5'CCGTACCGTCATAGTTAT 3'), gyrB-F (5' GCGCTGTCCGAACTGTACCT 3'), gyrB-R (5' CGGTGATCAGCGTCGCCACTTCC 3'), parC-F (5' CTATGCGATGTCAGAGCTGG 3'), parC-R (5' TAACAGCAGCTCGGCGTATT 3'), parE-F (5' TCTCTTCCGATGAAGTGCTG 3') and parE-R (5' ATACGGTATAGCGGCGGTAG 3'). Primers were designed from accession number sequences X78977, Z68167, M68936 and L05544 and resulting amplicon sizes were 251, 246, 260 and 237 base pairs for gyrA, gyrB, parC and parE, respectively. Other PCR conditions were as previously described6 with the exception that Optimase® proofreading DNA polymerase (Transgenomic®, catalogue no. 703045) was used.13

DHPLC analysis

DHPLC analysis was performed using an Agilent series 1100 HPLC system comprising a solvent degasser unit, binary pump, autosampler with cooling module (set to 4°C during analysis), column thermostat and variable wavelength detector. PCR products were chromatographed on a Varian HelixTM DNA column (3 x 50 mm; catalogue no. CP28353, Varian, Inc.) installed in the column thermostat and plumbed with distal connection to the 3 and 6 µL reservoirs for thermal equilibration of the mobile phase. Chromatography was achieved at a flow rate of 0.45 mL/min with a linear binary gradient of Varian Helix BufferPaks A and B (Varian Inc., Catalogue nos. 0393558101 and 0393558102, respectively) (t = 0 min, 55% A; t = 0.5 min, 50% A; t = 6 min, 32% A; t = 7.0 min 32% A; t = 7.1 min, 55% A; t = 8.5 min, 55% A; t = 15 min, 55% A and next injection) and an injection volume of 5 µL.14 Duplexes were detected at a wavelength of 260 nm. General procedures for performing DHPLC were as described previously6 with the following exceptions. Correct partial denaturing temperatures for mutation scanning based on the sequence of wild-type DNA from Salmonella Typhimurium NCTC 74 were determined using the DHPLC Melt Program available at the Stanford University web site.15 The optimal temperature to detect mutations for each gene was then confirmed empirically by comparing chromatograms obtained for PCR products from wild-type and known mutants at the melt programme temperature ± up to 5°C. Each DHPLC batch of samples included the puC18 HaeIII digest (Varian Inc., catalogue no. CP 28353) and DYS271 SNP standards (Varian Inc., catalogue no. 393566301) which were analysed at 50°C and 56°C, respectively using Varian published methods Univ50 and Univ56,14 to monitor and ensure effective and reproducible chromatography. Peaks were detected using the following integration parameters: Slope sensitivity 1; Peak width 0.04; Area reject 1; Height reject 0.7; Shoulders off.

Reproducibility

The reproducibility [between sample batches (runs)] was determined under non-denaturing and denaturing conditions using standard preparations; within a batch but between different PCRs of the same strain; and within a batch but between repeat injections of the same PCR product. To determine reproducibility between batches (n = 10), the mean ± 1 SD retention times for the first and last peaks of the HaeIII (non-denaturing) and DYS271 (denaturing) standards was assessed. To determine reproducibility between different PCRs (n = 10) of the same strain, the mean ± 1 SD retention times for the first peak for a Salmonella Typhimurium gyrA Ser-83->Phe mutation were assessed at 61°C and 63°C. To determine reproducibility between repeat injections, the mean ± 1 SD retention for consecutive injections (n = 10) of the WT were assessed at 61°C and 63°C.

Analysis of results

Chromatograms for control and unknown PCR products were compared against each other and to the WT profile using the ChemStation software (Agilent) overlay utility. Different peak profiles to the WT or same peak profiles but with a shift in retention time at a specific temperature were considered to indicate the presence of a mutation. For testing the 50 strains with unknown mutations (tested for mutations in gyrA only), strains with known mutations were included in the batch as controls. Match of a peak profile for a strain with an unknown mutation and a strain with a known mutation was taken as evidence that the unknown strain had that mutation. This was further confirmed by DNA sequencing of a limited number of strains.

Sequencing

All strains shown in Table 1 had been previously sequenced.6,7 Sequencing was also performed to confirm the DHPLC predicted mutations in the gyrA regions of the unknown strains (n = 50) and for mutations in the gyrB, parC and parE sequences. Sequencing was performed by Lark TechnologiesTM (Saffron Walden, UK) using PCR products as DNA templates; the primers used for sequencing were the same as those used to generate these PCR products. Sequences were compared with the Salmonella Typhimurium sequences for gyrA, gyrB, parC and parE (accession nos. AE008801, AE008878, AE008846 and AE008846, respectively). Alignment of DNA with the known sequence for Salmonella Typhimurium was performed using SeqMan (Lasergene, DNAStar Inc., USA).


    Results
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Temperatures used for mutant detection

The effect of increasing temperature on the peaks observed for an Asp-87->Asn mutation in gyrA is shown in Figure 1. These DHPLC profiles show single peaks at 59°C and 60°C and double peaks at all other temperatures. The predicted melt temperature of the entire strand of the Salmonella gyrA PCR product was 61.5°C and the recommended melt temperature was 62°C.15



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Figure 1. DHPLC analyses of an S. enterica strain with an Asp-87->Asn mutation at 59°C (right-hand side) to 65°C (left-hand side).

 
Based on predicted melt temperature and test DHPLC profiles, DHPLC analysis was performed at temperatures of both 61°C and 63°C to detect mutations in gyrA and gyrB and at both 62°C and 64°C to detect mutations in parC and parE using the Varian published methods Univ61, Univ62, Univ63 and Univ64.14 Batches were set up in such a way that the temperature was progressively increased during the batch and a blank sample was included after each temperature increase to ensure thermal equilibration was reached before analysing further samples. The WT gave rise to a single peak over the temperature range of 59°C to 65°C (results not shown).

Repeatability between and within batches

Results for reproducibility between batches (or runs), and within a batch but between PCRs and between repeat injections are shown in Table 2. As a result of the relatively large variations in retention times between batches, comparisons between unknowns and control strains for mutation detection were made within the same batch. On the basis of these results, a shift in retention time of ≥7 s was taken to be indicative of a mutation and this was based on 2x the largest SD of the batch results obtained for repeat injections of WT at 61°C (Table 2).


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Table 2. Reproducibility between batches (runs) and within a batch (repeat PCRs and repeat injections)

 
gyrA mutation detection

Results for DHPLC analysis of eight different gyrA mutations (Table 1) at 61°C are shown in Figure 2. All mutants other than Asp-87->Gly (peak F) gave rise to two peaks at 61°C and 63°C and could be distinguished from each other on the basis of peak profile and/or retention time. Asp-87->Gly (peak F, Figure 2) could be distinguished from the WT at 61°C on the basis of shift in retention and at 63°C, two peaks were observed (results not shown).

Once the system was validated for detection of mutation in gyrA, the panel of fluoroquinolone-susceptible (ciprofloxacin MIC < 0.125 mg/L, n = 22) and reduced susceptibility (ciprofloxacin MIC > 0.125 mg/L, n = 28) strains with unknown mutations were all tested for mutations in gyrA by DHPLC, using known strains as controls. There were four DHPLC profiles seen which corresponded to DHPLC control strains with WT, Ser-83->Phe, Asp-87->Tyr and Asp-87->Asn genotypes. Resistance phenotype correlated with the DHPLC predicted genotype. Sequencing was performed for these unknown strains with WT profile (n = 2), Ser-83->Phe profile (n = 5), Asp-87->Tyr profile (n = 4) and Asp-87->Asn (n = 4) and all confirmed the DHPLC predicted genotype.

gyrB, parC and parE mutation detection

Most of the antibiotic-susceptible non-Typhimurium sequences tested had serotype-associated sequence changes compared with the Typhimurium sequence and relevant sequences have been deposited with EMBL (Table 3). When DHPLC was then performed using an appropriate serotype for comparison, single peaks were seen unless non-serotype-associated sequence changes were also observed (e.g. as for mutation in gyrA in Salmonella Senftenberg in strain VLA 153, Table 1 and Figure 2, peak A). DHPLC gave differing peak profiles when there were multiple (maximum of six seen) mutations, however, in some instances, the additional peaks were small (Figure 3).


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Table 3. Serotype-associated mutations compared with Typhimurium sequence

 


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Figure 3. DHPLC analyses of S. enterica strains at 61°C with mutations in parC—comparisons with Typhimurium WT strain. (A) Salmonella Fischerkietz: three silent mutations (accession number AJ969935) compared with WT Salmonella Typhimurium. (B) Salmonella Senftenberg: six silent mutations (accession number AJ969936) compared with WT Salmonella Typhimurium. (C) WT Salmonella Typhimurium NCTC 74.

 

    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
In recent years, DHPLC has become widely used to detect SNPs in both eukaryotic and prokaryotic organisms.13 However, for some laboratories, the cost of purchasing specialist DHPLC equipment may be a factor preventing the wide application of this technique despite the presence of standard equipment. As such, we evaluated an industry standard HPLC machine and a readily available DHPLC column for detection of mutations in the QRDR of gyrA, gyrB, parC and parE of S. enterica.

It was interesting to note that, for fully susceptible strains, the Salmonella Senftenberg gyrA, the Salmonella Enteritidis gyrB, the Salmonella Fischerkietz and Senftenberg parC and the Salmonella Fischerkietz parE sequences all differed from the published Typhimurium sequence. As such, care must be taken when performing DHPLC with different serotypes of Salmonella to use a fully susceptible control strain of corresponding serotype as WT, unless sequencing has shown that there are no serotype-associated sequence changes. These serotype-associated differences demonstrate the fact that DHPLC can potentially be used to identify bacteria and previous workers have used DHPLC as a method for identifying Bacillus anthracis by analysing two chromosomal targets, the 16S–23S intergenic spacer region (ISR) and the gyrA gene.16

In all instances, DHPLC performed in this study was able to resolve the test mutants from the WT. DHPLC was also able to distinguish all mutants from each other on the basis of peak profile and or shift in retention time.

The peak shapes in our study did not correspond to the peak shapes of a previous study that used the same strains but alternative specialist DHPLC equipment6 and this may reflect the use of a different column and analysis parameters. This would suggest that each user must define their own peak profiles in relation to specific mutations and then use DNA with known mutations as controls in batched test runs.

Variation in retention time between different batches for the same samples was such that it was necessary to make comparisons with specific control strains within a batch. However, as each batch can comprise 100 samples, this was not considered an issue. The retention time for repeats within a batch (both repeat PCRs and repeat injections of WT) was highly stable with a maximum coefficient of variation of 1.095% when the temperature was constant. However, if the temperature of the analysis was increased and later in the batch decreased, the retention time for a repeat at the original temperature was shifted. This would suggest that within a batch, the samples should be arranged in such a way that they are tested in temperature order, e.g. starting with samples at the lowest temperature and moving to samples to be tested at higher temperatures.

When a blind test was done, DHPLC was able to ascribe 50 strains with unknown gyrA genotype to WT or three different mutations based on peak shape and/or retention time, although for two of the different mutations, peaks were similar and care was needed to differentiate them. For the four different DHPLC profiles, sequencing of selected strains confirmed the DHPLC predicted genotype and all results corresponded 100% with the known phenotype. Overall, the results demonstrate that standard HPLC equipment and a commercially available column can be used to perform DHPLC to detect mutations in the gyrA, gyrB, parC and parE regions of Salmonella. However, care and some user experience is required to distinguish between similar peak profiles. As the technique requires several internal controls, it is not a ready application to a routine analysis laboratory without acquisition of suitable control strains and some experience in analysing the results obtained with them. However, for laboratories that are prepared to invest some time in assembling suitable control strains and gaining experience in analysing results, it could prove to be a useful technique. The results also suggest that the methodology described could be used to detect SNPs in other genes.


    Acknowledgements
 
We would like to thank Professor Laura Piddock and her group at the University of Birmingham for donation of some of the strains and for advice with DHPLC procedures. This work was funded by the VLA internal investment ‘seedcorn’ programme, project grant SC0137 awarded to L. P. R.


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
1. Dutta P, Rasaily R, Saha MR et al. Ciprofloxacin for treatment of severe typhoid fever in children. Antimicrob Agents Chemother 1993; 37: 1197–9.[Abstract]

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3. Wang F, Gu XJ, Zhang MF et al. Treatment of typhoid fever with ofloxacin. J Antimicrob Chemother 1989; 23: 785–8.[Abstract]

4. Piddock LJV. Fluoroquinolone resistance in Salmonella serovars isolated from humans and food animals. FEMS Microbiol Rev 2002; 26: 3–16.[CrossRef][ISI][Medline]

5. Ling JM, Chan EW, Lam AW et al. Mutations in topoisomerase genes of fluoroquinolone-resistant salmonellae in Hong Kong. Antimicrob Agents Chemother 2003; 47: 3567–73.[Abstract/Free Full Text]

6. Eaves DJ, Liebana E, Woodward MJ et al. Detection of gyrA mutations in quinolone-resistant Salmonella enterica: denaturing HPLC, a rapid method to detect novel and multiple mutations in bacterial genes. J Clin Microbiol 2002; 40: 4121–4.[Abstract/Free Full Text]

7. Eaves DJ, Randall LP, Gray DT et al. (2004). Effect of mutations within the QRDR of gyrA, gyrB, parC or parE in quinolone-resistant S. enterica from humans and animals. Antimicrob Agents Chemother 2004; 48: 4012–5.[Abstract/Free Full Text]

8. Giraud E, Cloeckaert A, Kerboeuf D et al. Evidence for active efflux as the primary mechanism of resistance to ciprofloxacin in Salmonella enterica serovar Typhimurium. Antimicrob Agents Chemother 2000; 44: 1223–8.[Abstract/Free Full Text]

9. Pers C, Sogaard P, Pallesen L. Selection of multiple resistance in Salmonella enteritidis during treatment with ciprofloxacin. Scand J Infect Dis 1996; 28: 529–31.[ISI][Medline]

10. Randall LP, Eaves D, Cooles SW et al. Fluoroquinolone treatment of experimental Salmonella enterica serovar Typhimurium DT104 infections in chickens selects for both gyrA mutations and changes in efflux pump gene expression. J Antimicrob Chemother 2005; 56: 297–306.[Abstract/Free Full Text]

11. Baucheron S, Chaslus-Dancla E, Cloeckaert A. Role of TolC and parC mutation in high-level fluoroquinolone resistance in Salmonella enterica serotype Typhimurium DT204. J Antimicrob Chemother 2004; 53: 657–9.[Abstract/Free Full Text]

12. Baucheron S et al. AcrAB-TolC directs efflux-mediated multidrug resistance in Salmonella enterica serovar Typhimurium DT104. Antimicrob Agents Chemother 2004; 48: 3729–35.[Abstract/Free Full Text]

13. Hecker KH. Genetic Variance Detection, Nuts and Bolts of DHPLC in Genomics. USA: Xela Schenk, DNA Press, 2003.

14. Anonymous (a). Helix Guidelines and Procedures. http://www.varianinc.com/cgi-bin/nav?products/biosolutions/helix/guide_proced&cid= JPIMLNHFP (20 May 2005, date last accessed).

15. Anonymous (b). Run the DHPLC Melt Program. http://insertion.stanford.edu/melt.html (20 May 2005, date last accessed).

16. Hurtle W, Bode E, Kaplan RS et al. Use of denaturing high-performance liquid chromatography to identify Bacillus anthracis by analysis of the 16S–23S rRNA interspacer region and gyrA gene. J Clin Microbiol 2003; 41: 4758–66.[Abstract/Free Full Text]





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