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Rapid genotyping of Achromobacter xylosoxidans, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and Stenotrophomonas maltophilia isolates using melting curve analysis of RAPD-generated DNA fragments (McRAPD)
Research in Microbiology 162 (2011) 386e392 www.elsevier.com/locate/resmic
Rapid genotyping of Achromobacter xylosoxidans, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and Stenotrophomonas maltophilia isolates using melting curve analysis of RAPD-generated DNA fragments (McRAPD) Pieter Deschaght a,*, Leen Van Simaey a, Ellen Decat b, Els Van Mechelen b, Sylvain Brisse c, Mario Vaneechoutte a a
Laboratory for Bacteriology Research (LBR), Ghent University Hospital, University of Ghent, De Pintelaan 185, 9000 Ghent, Belgium b Faculty of Health Care, University college Ghent, Keramiekstraat 80, 9000 Ghent, Belgium c Institut Pasteur, Genotyping of Pathogens and Public Health, 28 rue du Docteur Roux, 75724 Paris Cedex, France Received 12 October 2010; accepted 19 January 2011 Available online 12 February 2011
Abstract Typing of bacteria is important for monitoring newly emerging pathogens and for examining local outbreaks. We evaluated the randomly amplified polymorphic DNA technique in combination with melting curve analysis (McRAPD) of the amplified DNA fragments to genotype isolates from five Gram-negative species, i.e. Achromobacter xylosoxidans, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and Stenotrophomonas maltophilia. By determining the melting temperature peaks of the amplified DNA fragments, we were able to distinguish the different genotypes of isolates, as they had been assessed by other genotyping techniques, i.e. agarose gel electrophoresis of RAPD fragments, multilocus sequence typing and/or AFLPÔ. According to our results, McRAPD may offer the possibility of genotyping a limited number of bacterial isolates, e.g. in case of suspicion of hospital outbreak, via a less costly, more rapid, less laborious and more user-friendly technique than RAPD followed by electrophoresis. Ó 2011 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved. Keywords: Typing; RAPD; McRAPD; Pseudomonas aeruginosa; Achromobacter xylosoxidans; Acinetobacter baumannii
1. Introduction Typing of bacterial isolates has been used for decades for studying local outbreaks, e.g. nosocomial outbreaks, as well as for national and international surveillance when monitoring newly emerging (resistant) clones, e.g. for pathogens such as Acinetobacter baumannii (Diancourt et al., 2010; Van den Broek et al., 2006), Klebsiella pneumoniae (Brisse et al., * Corresponding author. E-mail addresses: [email protected] (P. Deschaght), Leen. [email protected] (L. Van Simaey), [email protected] (E. Decat), [email protected] (E. Van Mechelen), [email protected] (S. Brisse), [email protected] (M. Vaneechoutte).
2009; Mendonc¸a et al., 2009.), Mycobacterium tuberculosis (Burgos et al., 2004), Neisseria meningitidis (Woods et al., 1996), Pseudomonas aeruginosa (Inglis et al., 2010), and multiresistant Staphylococcus aureus (Makgotlho et al., 2009). During the last decades, genotyping techniques (DNA fingerprinting) have largely replaced phenotypic techniques, such as serotyping, phage susceptibility typing and protein SDS PAGE. Two major DNA fingerprinting approaches can be distinguished, i.e. restriction fragment length polymorphism (RFLP) analysis techniques, such as chromosomal DNA restriction analysis, ribotyping and AFLPÔ, and amplified fragment length polymorphism analysis such as arbitrarily primed-PCR, better known as randomly amplified polymorphic DNA analysis (RAPD), REP-PCR and variable number tandem repeat
0923-2508/$ - see front matter Ó 2011 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved. doi:10.1016/j.resmic.2011.02.002
P. Deschaght et al. / Research in Microbiology 162 (2011) 386e392
(VNTR) amplification (Van Belkum et al., 2007; Vaneechoutte, 1996). With the development of faster, cheaper and more automated sequencing capacity, sequence-based typing, such as multilocus sequence typing (MLST) (Diancourt et al., 2005, 2010; Maiden et al., 1998), is gradually replacing these DNA fingerprinting techniques, basically because sequencing is fully digitizable and less prone to interlaboratory variability. Whereas MLST is a reference approach for large scale surveillance and for population biology studies, there remains a need for rapid, less laborious and cheap approaches, such as RAPD, on a local scale. Although the interrun reproducibility of this approach is known to be limited, it still offers the possibility of studying e within a single run e the genotypic relatedness of a limited number of isolates that might possibly belong to a single outbreak, e.g. in a hospital or hospital ward. Recently, a further improvement has appeared as it became possible to carry out melting curve analysis of amplified DNA fragments. However, thus far, a limited number of publications have described the application of melting curve analysis of the DNA fragments that are generated during RAPD (Plachy´ et al., 2005; Trtkova et al., 2009; Tulsiani et al., 2010), and the designation McRAPD has been proposed (Plachy´ et al., 2005; Trtkova et al., 2009). This approach obviates the need for agarose gel electrophoresis, including the pouring of gels, running the electrophoresis, the usage of ethidium bromide and photography of the stained gels, drastically reducing workload and time-to-results. Here, we compared the discriminatory power of McRAPD for genotyping isolates of several collections of five different Gram-negative species with that of established DNA fingerprinting techniques and/or MLST. 2. Materials and methods 2.1. Bacterial isolates For this study, several Gram-negative bacterial species of nosocomial importance were studied, including Achromobacter xylosoxidans, A. baumannii, K. pneumoniae, P. aeruginosa and Stenotrophomonas maltophilia. The A. xylosoxidans collection consisted of 9 isolates cultured from 3 P. aeruginosa colonized cystic fibrosis (CF) patients, as described previously (Van daele et al., 2005a,b). These isolates had been shown, by RAPD with agarose gel electrophoresis (RAPD-AGE) and with AFLPÔ, to belong to 3 different genotypes. The 10 A. baumannii isolates and the 10 K. pneumoniae isolates originated from different sources and had been typed by MLST (Diancourt et al., 2010; Brisse et al., 2009). Within each of the two species, the 10 isolates could be clustered into 3 clonal complexes and into 5 and 7 MLST genotypes, respectively (Diancourt et al., 2010; Brisse et al., 2009) (Supplementary Table 1). Two collections of P. aeruginosa isolates were tested. The first collection consisted of 12 isolates isolated by means of RAPD-AGE from the burn wound center at the Ghent University Hospital (BWC) and previously shown to belong to 4 different genotypes (unpublished data). The second P. aeruginosa collection consisted of 21 isolates from 20 patients, originating from the same CF population as the A. xylosoxidans isolates, as described previously
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(Van daele et al., 2005a,b; Van daele et al., 2006). These isolates had been shown by RAPD-AGE and AFLPÔ to belong to 5 different genotypes. The 11 S. maltophilia isolates belonged to 4 RAPD-AGE genotypes (unpublished data) and were isolates from 4 CF patients. For each patient, the different isolates were isolated with a median time interval of 3 months. 2.2. DNA extraction For all species, DNA was extracted from cultured bacteria by simple alkaline lysis. One colony, obtained after 18 h of culture on a 5% (v/v) sheep blood agar plate (Becton Dickinson, Erembodegem, Belgium), was suspended in 20 ml of lysis buffer (0.25% (w/v) SDS, 0.05 N NaCl and 95 ml sterile distilled water) and heated for 15 min at 95 C. After brief centrifugation, 180 ml of HPLC-water was added and this mixture was centrifuged for 5 min at 16,300 g. The crude supernatant was used as DNA extract. For the 12 P. aeruginosa isolates of the BWC collection, DNA extraction was also carried out with the manual High Pure PCR Template Preparation kit (Roche Applied Science, Basel, Switzerland), according to the manufacturer’s recommendations. 2.3. RAPD-AGE All isolates, including those that had already been previously genotyped by RAPD, were genotyped during this study by RAPD, followed by agarose gel electrophoresis (RAPDAGE). RAPD-AGE was performed with Ready-to-Go beads (Amersham Biosciences AB, Uppsala, Sweden) and 2 mM of primer RAPD4 (AAGACGCCGT) or 1 mM of primer ERIC2 (AAGTAAGTGACTGGGGTGAGCG) in total volumes of 12 ml, including 1.2 ml of DNA extract at an annealing temperature of 37 C, as previously described (Van daele et al., 2005a). Agarose gel electrophoresis was carried out at 100 V on an agarose gel of 2.5% (w/v), containing 1 mg/ml ethidium bromide and visualized and photographed on a UV transilluminator at 540 nm. 2.4. McRAPD RAPD in combination with melting curve analysis of amplified DNA fragments (McRAPD (Plachy´ et al., 2005; Trtkova et al., 2009)) was performed on a Lightcycler 1.2 (Roche Applied Science). The total reaction mix per sample was 20 ml and consisted of 2 ml LightcyclerÒ FastStart DNA Master SYBR Green I (Roche Applied Science), 0.5 mM of primer RAPD4 or of primer ERIC2, 2 mM MgCl2, and 2 ml of DNA extract. The PCR protocol started with an activation step of 10 min at 95 C, followed by 40 cycles of denaturation at 95 C for 10 s, annealing at 37 C for 10 s and elongation at 72 C for 30 s. Melting down of the amplification product started with 1 min at 72 C followed by increasing the temperature to 95 C with a ramp rate of 0.1 C/s and a continuous measurement of fluorescence at 530 nm.
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2.5. Analysis of the melting curve data The melting curves were normalized using the ‘Tm calling melting curve analysis’ option, proGram med in Lightcycler Software 4.1.1.21 (Roche Applied Science). Using the normalized melting curve, 3e4 melting peaks with the highest melting temperature were manually selected and 3e4 melting temperatures were used to construct a digital fingerprint consisting of 3e4 values. Comparison of digitized McRAPD fingerprints was done using the differential basepair method (dbp: nAB/aB), as calculated by BaseHopper inhouse software (http://www. basehopper.be).
3. Results 3.1. Grouping of the different genotypes Using McRAPD data, the diverse sets of isolates of 5 different Gram-negative species could all be classified into
almost complete concordance with groups derived from previous genotyping results (Supplementary Table 1). For P. aeruginosa, a total of 33 isolates derived from two collections (BWC and CF) were tested with two primers, RAPD4 and ERIC2. Using primer RAPD4, all genotypes in both collections could be assigned to the same genotypes as established on the basis of RAPD-AGE and/or AFLPÔ (Table 1), except for genotypes C and D in the P. aeruginosa CF-collection, for which the difference was at the limit. Both collections were also tested with primer ERIC2 and a better spread of the melting temperatures could be established (Table 2) (Fig. 1). It should be noted that, with primer ERIC2, differentiation between genotypes C and D was possible, although based on only one different melting temperature (Table 2, TM4). The difference in primer and temperature differentiation corresponded to agarose gel electrophoresis patterns in which, for some of the genotypes, ERIC2-based RAPD patterns (Fig. 2, panel F) differed more between genotypes than RAPD4-based RAPD patterns (Fig. 2, panel E). For A. xylosoxidans, the McRAPD approach was able to group the nine isolates into three genotype clusters (Table 1),
Table 1 Mean melting temperatures of the different species genotypes using the RAPD4 primer. Species
Genotype (n)a
TM1b
TM2
TM3
TM4
A. xylosoxidans
A (4) B (1) C (4)
73.98 (0.42) 73.12 74.14 (0.28)
78.42 (0.08) 78.63 78.49 (0.28)
86.39 (0.08) 82.59 85.74 (0.21)
93.65 (0.08) 89.24 92.08 (0.17)
A. baumannii
A (3) B1 (3) B2 (1) C1 (2) C2 (1)
74.71 (0.16) 73.91 (0.16) 74.09 74.16 (0.13) 74.71
77.95 (0.04) 77.74 (0.36) 77.65 76.88 (0.30) 77.49
85.05 (0.04) 85.13 (0.16) 84.94 84.08 (0.10) 84.47
91.92 (0.21) / / 90.32 (0.28) 90.55
K. pneumoniaec
A1 (16A151) A1 (12A041) A2 (08A418) A3 (Zaire1) B1 (779) B1 (cur15505) B2 (04A025) B2 (01A018) C1 (440) C2 (926)
81.9 81.92 79.27 80.46 80.19 81.11 81.04 80.9 75.39 74.91
85.18 85.55 84.79 85.56 / / / / 80.52 81.76
88.67 88.15 88.31 88.82 88.05 88.08 88.16 88.72 85.93 85.96
91.37 91.08 93.83 91.82 91.84 91.24 91.36 91.42 89.63 88.47
P. aeruginosa BWC
A (3) B (2) C (5) D (2)
73.83 73.75 78.62 79.86
(0.12) (0.10) (0.23) (0.20)
79.62 79.51 82.42 82.58
(0.22) (0.30) (0.15) (0.17)
82.72 82.67 88.79 88.69
(0.21) (0.00) (0.16) (0.15)
88.57 (0.14) 89.9 (0.10) 91.87 (0.19) 92.41 (0.30)
P. aeruginosa CF
A (5) B (2) C (3) D (4) E (7)
75.91 78.66 75.59 75.54 /
(0.72) (0.30) (0.21) (0.29)
81.45 80.84 78.87 77.92 75.12
(0.33) (0.00) (0.61) (1.06) (0.14)
86.51 87.83 80.98 80.63 81.27
(0.12) (0.08) (0.24) (0.18) (0.14)
91.48 92.56 87.84 87.50 88.28
S. maltophilia
A (3) B (2) C (4) D (2)
75.00 75.22 75.25 73.22
(0.18) (0.38) (0.36) (0.00)
80.55 80.15 78.96 78.18
(0.50) (0.53) (0.25) (0.20)
88.03 83.40 88.27 85.33
(1.63) (0.38) (0.07) (0.30)
/ 89.76 (0.16) / 90.85 (0.10)
a
(0.15) (0.10) (0.17) (0.11) (0.28)
Number in brackets indicates number of isolates belonging to each genotype, except for K. pneumoniae, for which the isolate name is shown. Mean melting temperatures (in C) of amplified DNA fragments with the highest melting temperatures, with standard deviation (calculated on the basis of the different melting temperatures of the isolates with the same genotype) in brackets. c For K. pneumoniae, melting temperatures of all isolates are shown. b
P. Deschaght et al. / Research in Microbiology 162 (2011) 386e392 Table 2 Comparison of digitized McRAPD patterns of burn wound center (BWC) P. aeruginosa isolates using ERIC2 primer. Collection Genotypea TM1b
TM2
TM3
TM4
BWC
A (3) B (2) C (5) D (2)
77.95 76.73 77.21 78.07
(0.13) (0.00) (0.49) (0.10)
83.26 85.26 79.38 82.58
(0.17) (0.10) (0.43) (0.49)
87.67 87.72 83.04 89.20
(0.29) (0.40) (0.40) (0.10)
92.05 91.18 89.44 92.73
(0.54) (0.50) (0.12) (0.10)
CF
A (5) B (2) C (3) D (4) E (7)
76.35 79.76 79.28 79.56 76.46
(0.056) (0.15) (0.22) (0.24) (0.16)
79.32 87.07 81.33 81.35 80.03
(0.32) (0.071) (0.29) (0.14) (0.20)
87.31 89.86 86.79 86.44 86.67
(035) (0.049) (0.080) (0.056) (0.21)
92.34 92.36 93.15 91.62 92.25
(0.17) (0.21) (0.21) (0.14) (0.44)
a
Number of strains included tested for each genotype. Mean melting temperatures (in C) of RAPD-amplified DNA fragments with the highest melting temperatures, with standard deviation (calculated on the basis of the different melting temperatures of the isolates with the same genotype) in brackets. b
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corresponding to clusters obtained with RAPD-AGE and AFLPÔ clustering (Supplementary Table 1). All three genotypes had a common peak at around 78.5 C, but the melting temperature values of the three other fragments clearly enabled distinction between the three genotypes. For A. baumannii, isolates had been previously classified into three clonal complexes by means of MLST (Diancourt et al., 2010). Using McRAPD, the isolates could also be grouped into three genotypes (Table 1), corresponding to previously published MLST data and the RAPD-AGE data obtained during this study (Supplementary Table 1). Based on TM1 and TM2, there was not a great difference between the different genotypes, while based on TM3 and TM4 the three genotypes could be distinguished. However, with both RAPD methods, there were no clear differences between the various sequence types (STs) within the different clonal complexes. For K. pneumoniae, MLST had shown that the 10 isolates belonged to 7 different STs (A1, A2, A3, B1, B2, C1 and C2), which could be clustered into three clonal complexes (A, B, C)
Fig. 1. McRAPD patterns of P. aeruginosa CF isolates with primer ERIC2. Legend Panel A: Genotype A, Panel B: Genotype B, Panel C: Genotype C, Panel D: Genotype D, Panel E: Genotype E.
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(Brisse et al., 2009). For K. pneumoniae, isolates were differentially clustered on the basis of RAPD-AGE and McRAPD rather than on the basis of MLST. With RAPD-AGE and McRAPD, sequence type A2 could be distinguished from sequence types A1 and A3; moreover, sequence types C1 and C2 could be distinguished from each other (Table 1) (Fig. 3), in agreement with MLST results. However, for genotype B, three RAPD genotypes, not corresponding to MLST results, could be differentiated. On the basis of McRAPD and RAPDAGE, isolate 779 (MLST genotype B1) was separate, isolates cur15505 (MLST genotype B1) and 04A025 (MLST genotype B2) clustered together and isolate 01A018 (MLST genotype B2) was again separate (Table 1) (Fig. 3). It should be noticed that McRAPD showed better correspondence with MLST than RAPD-AGE since, with McRAPD it was possible to distinguish between sequence types A1 and A3 on the basis of a melting temperature difference of 1.5 C for peak 1, whereas A1 and A3 RAPD-AGE profiles could not be differentiated from each other upon visual inspection of the agarose gel. The 11 S. maltophilia isolates, grouped into four genotypes according to RAPD-AGE patterns, could also be grouped into the same genotypes according to McRAPD data (Supplementary Table 1). For genotypes A and C, only three melting temperature peaks could be selected. These melting profiles of these genotypes had two melting temperatures in common (TM1 and TM3), but the third peak (TM2) enabled
clear differentiation between the two genotypes due to a ΔTM of 1.5 C. One isolate of RAPD-AGE genotype A had a completely different McRAPD pattern in comparison with the McRAPD pattern of the other two genotype A RAPD isolates, which explains the high standard deviation values for this genotype. 4. Discussion In this study, we used RAPD followed by melting curve analysis of some of the amplified DNA fragments (McRAPD) for genotyping collections of isolates of five Gram-negative species, and we compared this approach with genotyping results obtained previously by means of MLST (for A. baumannii and K. pneumoniae), AFLPÔ (for the CF A. xylosoxidans and P. aeruginosa isolates) and RAPD followed by agarose gel electrophoresis (RAPD-AGE) (for all isolates). Our results show that McRAPD is a valid alternative to RAPD-AGE and yields a discriminatory power comparable to RAPD-AGE. By indicating the melting point peaks, clear differentiation is possible between the various genotypes. Previously, the McRAPD technique had been used to identify pathogenic yeast species (Plachy´ et al., 2005; Trtkova et al., 2009). For bacteria, melting curve analysis to distinguish different genotypes has already been based on the melting profile of amplified clustered, regularly interspaced short palindromic repeats (CRISPRs) (Price et al., 2007; Bratcikov
Fig. 2. McRAPD patterns (primer RAPD4, panels AeD) and RAPD-AGE patterns (primer RAPD4, panel E and primer ERIC2, panel F) of P. aeruginosa genotypes, derived from the Ghent University Hospital Burn Wound Center (BWC). Panels AeD: McRAPD genotypes for the 12 P. aeruginosa BWC isolates are shown in the different panels (A, B, C, D); each panel contains patterns of a single cluster. The different curves in each panel represent the individual McRAPD genotype for each isolate. Vertical solid black lines indicate selected melting temperature peaks, used to construct digitized McRAPD patterns (Table 1). Panels E and F: M: 100 bp molecular weight marker (Fermentas, Burlington, Canada), lanes 1e3: genotype A, lanes 4e5: genotype B, lanes 6e10: genotype C, lanes 11e12: genotype D.
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Fig. 3. McRAPD (panels AeC) and RAPD-AGE (panel D) patterns of K. pneumoniae isolates obtained with primer RAPD4. Panel A: Melting curves of isolates classified by MLST in clonal complex A. Sequence type (ST) 1: solid line (A1 in panel D), ST 2: green dotted line (A2 in panel D), ST 3: red dashed line (A3 in panel D). Panel B: Melting curve of isolates classified in clonal complex B. ST 1: solid line (B1 in panel D), ST 2: dotted line (B2 in panel D). Panel C: Melting curve of isolates classified in clonal complex C. ST 1: solid line (C1 in panel D), ST 2: dotted line (C2 in panel D). Panel D: M: 100 bp molecular weight marker (Fermentas), A, B, C: clonal complex, 1, 2, 3: STs within each clonal complex.
and Mauricas, 2009) which, at present, have been found in about 40% of all bacterial species (Horvath and Barrangou, 2010) and therefore may be limited to those species. Also, genotyping based on the melting profile of amplified variable numbers of tandem repeats (VNTRs) has been carried out (Naze et al., 2010). To our knowledge, until now, only Tulsiani et al. (2010) used McRAPD to genotype bacteria and, more specifically, to differentiate between serovars of Leptospira species (Tulsiani et al., 2010). In our opinion, McRAPD has the potential for being easily implemented in routine genotyping because it has several advantages over RAPD-AGE while achieving the same discriminatory power, at least for the Gram-negative species tested here. Comparison of McRAPD with MLST data show that McRAPD could be used to rapidly identify major clones of these species, including multidrug-resistant and particularly virulent clones. McRAPD is faster, less costly, more environmentally and userfriendly (no ethidium bromide), less labor-intensive and technically less demanding than RAPD-AGE because there is no need to pour gels, run gel electrophoresis, stain with ethidium bromide or
photograph the gels. McRAPD is also a non-destructive method, i.e. the McRAPD product can still be analyzed on gel in case of a doubtful result. McRAPD has some of the same advantages and limitations as RAPD-AGE. Because it is an amplification based protocol, the DNA extracts may be crude lysates, whereas restriction-based protocols such as AFLPÔ and macrorestriction analysis (PFGE) require pure, i.e. more laborious and more expensive, DNA extracts in order to produce interpretable fingerprints. In this study, we also studied the influence of the DNA extraction method on McRAPD fingerprints, for a collection of P. aeruginosa isolates (data not presented). Crude alkaline lysates yielded the same genotype assignations as more purified DNA extracts, as obtained after commercial Roche-kit-based DNA extraction, although McRAPD and RAPD-AGE fingerprints obtained with the two DNA extraction methods applied to the same isolate sometimes differed. However, as is the case with RAPD-AGE, for which different gel patterns are obtained for different PCR runs of the same isolate, different melting profiles with McRAPD were also obtained for the same isolate in different PCRs (data not presented). Nevertheless, the resulting genotype assignment
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was comparable between runs. Although fingerprints may look different between runs, epidemiological information, i.e. assignment of isolates to different genotypes, will be the same, as was the case when different DNA extracts were used. This means that fingerprints of different thermal cycling runs cannot be compared and thus no large series can be studied. Therefore, this approach remains limited to the study of local outbreaks with a limited number of isolates, e.g. a maximum of 32 when using LightCycler 1.2. Although we provided evidence for the discriminatory power of this technique, further optimization is possible. Use of more advanced melting analysis hardware and software, more discriminatory high-resolution melting dyes such as ResoLight (Roche Applied Science) instead of Sybr Green I, and more optimized primers may continue to increase the discriminatory power and reproducibility of this technique. Acknowledgment None of the authors has a conflict of interest to declare. Pieter Deschaght is indebted to the IWT for PhD research grant IWT-SB/71184. Appendix. Supplementary material Supplementary material related to this article can be found online at doi:10.1016/j.resmic.2011.02.002. References Bratcikov, M., Mauricas, M., 2009. The use of high-resolution melting analysis for Salmonella spp. CRISPR sequence genotyping. Acta Med. Lituanica. 16, 98e102. Brisse, S., Fevre, C., Passet, V., Issenhuth-Jeanjean, S., Tournebize, R., Diancourt, L., Grimont, P., 2009. Virulent clones of Klebsiella pneumoniae: identification and evolutionary scenario based on genomic and phenotypic characterization. Plos One 4, e4982. Burgos, M.V., Me´ndez, J.C., Ribon, W., 2004. Molecular epidemiology of tuberculosis: methodology and applications. Biomedica 24 (Suppl.), 188e201. Diancourt, L., Passet, V., Verhoef, J., Grimont, P.A., Brisse, S., 2005. Multilocus sequence typing of Klebsiella pneumoniae nosocomial isolates. J. Clin. Microbiol. 43, 4178e4182. Diancourt, L., Passet, V., Nemec, A., Dijkshoorn, L., Brisse, S., 2010. The population structure of Acinetobacter baumannii: expanding multiresistant clones from an ancestral susceptible genetic pool. Plos One 5, e10034. Horvath, P., Barrangou, R., 2010. CRISPR/Cas, the immune system of bacteria and archaea. Science 327, 167e170. Inglis, T.J., Benson, K.A., O’Reilly, L., Bradbury, R., Hodge, M., Speers, D., Heath, C.H., 2010. Emergence of multi-resistant Pseudomonas aeruginosa in a Western Australian hospital. J. Hosp. Infect. 76, 60e65. Maiden, M.C., Bygraves, J.A., Feil, E., Morelli, G., Russell, J.E., Urwin, R., Zhang, Q., Zhou, J., Zurth, K., Caugant, D.A., Feavers, I.M., Achtman, M.,
Spratt, B.G., 1998. Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc. Natl. Acad. Sci. U S A 95, 3140e3145. Makgotlho, P.E., Kock, M.M., Hoosen, A., Lekalakala, R., Omar, S., Dove, M., Ehlers, M.M., 2009. Molecular identification and genotyping of MRSA isolates. FEMS Immunol. Med. Microbiol. 57, 104e115. Mendonc¸a, N., Ferreira, E., Louro, D., Participants, A.R.S.I.P., Canic¸a, M., 2009. Molecular epidemiology and antimicrobial susceptibility of extended- and broad-spectrum beta-lactamase-producing Klebsiella pneumoniae isolated in Portugal. Int. J. Antimicrob. Agents 34, 29e37. Naze, F., Jouen, E., Randriamahazo, R.T., Simac, C., Laurent, P., Ble´riot, A., Chiroleu, F., Gagnevin, L., Pruvost, O., Michault, A., 2010. A Pseudomonas aeruginosa outbreak in a neonatal intensive care unit linked to mineral water bottles: fast typing using high resolution melting analysis of variable number of tandem repeats locus. J. Clin. Microbiol. 48, 3146e3152. Plachy´, R., Hamal, P., Raclavsky´, V., 2005. McRAPD as a new approach to rapid and accurate identification of pathogenic yeasts. J. Microbiol. Meth. 60, 107e113. Price, E.P., Smith, H., Huygens, F., Giffard, P.M., 2007. High-resolution DNA melt curve analysis of the clustered, regularly interspaced short-palindromic-repeat locus of Campylobacter jejuni. Appl. Env. Microbiol. 73, 3431e3436. Trtkova, J., Pavlicak, P., Ruskova, L., Hamal, P., Koukalova, D., Raclavsky, V., 2009. Performance of optimized McRAPD in identification of 9 yeast species frequently isolated from patient samples: potential for automation. BMC Microbiol. 9, 234. Tulsiani, S.M., Craig, S.B., Graham, G.C., Cobbold, R.C., Dohnt, M.F., Burns, M.A., Leung, K.P., Field, H.E., Smythe, L.D., 2010. High-resolution melt-curve analysis of random-amplified-polymorphic-DNA markers, for the characterisation of pathogenic Leptospira. Ann. Trop. Med. Parasitol. 104, 151e161. Van Belkum, A., Tassios, P.T., Dijkshoorn, L., Haeggman, S., Cookson, B., Fry, N.K., Fussing, V., Green, J., Feil, E., Gerner-Smidt, P., Brisse, S., Struelens, M.European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group on Epidemiological Markers (ESGEM), 2007. Guidelines for the validation and application of typing methods for use in bacterial epidemiology. Clin. Microbiol. Infect. 13 (Suppl.), 1e46. Van daele, S., Verhelst, R., Claeys, G., Verschraegen, G., Franckx, H., Van Simaey, L., De Ganck, C., De Baets, F., Vaneechoutte, M., 2005a. Shared genotypes of Achromobacter xylosoxidans strains isolated from patients at a cystic fibrosis rehabilitation center. J. Clin. Microbiol. 43, 2998e3002. Van daele, S., Franckx, H., Verhelst, R., Schelstraete, P., Haerynck, F., Van Simaey, L., Claeys, G., Vaneechoutte, M., De Baets, F., 2005b. Epidemiology of Pseudomonas aeruginosa in a cystic fibrosis rehabilitation centre. Eur. Respir. J. 25, 474e481. Van daele, S., Vaneechoutte, M., De Boeck, K., Knoop, C., Malfroot, A., Lebecque, P., Leclercq-Foucart, J., Van Schil, L., Desager, K., De Baets, F., 2006. Survey of Pseudomonas aeruginosa genotypes in colonised cystic fibrosis patients. Eur. Respir. J. 28, 740e747. Van den Broek, P.J., Arends, J., Bernards, A.T., De Brauwer, E., Mascini, E.M., van der Reijden, T.J., Spanjaard, L., Thewessen, E.A., van der Zee, A., van Zeijl, J.H., Dijkshoorn, L., 2006. Epidemiology of multiple Acinetobacter outbreaks in The Netherlands during the period 1999e2001. Clin. Microbiol. Infect. 12, 837e843. Vaneechoutte, M., 1996. DNA fingerprinting techniques for microorganisms. a proposal for classification and nomenclature. Mol. Biotech. 6, 115e142. Woods, C.R., Koeuth, T., Estabrook, M.M., Lupski, J.R., 1996. Rapid determination of outbreak-related strains of Neisseria meningitidis by repetitive elementbased polymerase chain reaction genotyping. J. Infect. Dis. 174, 760e767.
Rapid genotyping of Achromobacter xylosoxidans, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and Stenotrophomonas maltophilia isolates using melting curve analysis of RAPD-generated DNA fragments (McRAPD) Pieter Deschaght a,*, Leen Van Simaey a, Ellen Decat b, Els Van Mechelen b, Sylvain Brisse c, Mario Vaneechoutte a a
Laboratory for Bacteriology Research (LBR), Ghent University Hospital, University of Ghent, De Pintelaan 185, 9000 Ghent, Belgium b Faculty of Health Care, University college Ghent, Keramiekstraat 80, 9000 Ghent, Belgium c Institut Pasteur, Genotyping of Pathogens and Public Health, 28 rue du Docteur Roux, 75724 Paris Cedex, France Received 12 October 2010; accepted 19 January 2011 Available online 12 February 2011
Abstract Typing of bacteria is important for monitoring newly emerging pathogens and for examining local outbreaks. We evaluated the randomly amplified polymorphic DNA technique in combination with melting curve analysis (McRAPD) of the amplified DNA fragments to genotype isolates from five Gram-negative species, i.e. Achromobacter xylosoxidans, Acinetobacter baumannii, Klebsiella pneumoniae, Pseudomonas aeruginosa and Stenotrophomonas maltophilia. By determining the melting temperature peaks of the amplified DNA fragments, we were able to distinguish the different genotypes of isolates, as they had been assessed by other genotyping techniques, i.e. agarose gel electrophoresis of RAPD fragments, multilocus sequence typing and/or AFLPÔ. According to our results, McRAPD may offer the possibility of genotyping a limited number of bacterial isolates, e.g. in case of suspicion of hospital outbreak, via a less costly, more rapid, less laborious and more user-friendly technique than RAPD followed by electrophoresis. Ó 2011 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved. Keywords: Typing; RAPD; McRAPD; Pseudomonas aeruginosa; Achromobacter xylosoxidans; Acinetobacter baumannii
1. Introduction Typing of bacterial isolates has been used for decades for studying local outbreaks, e.g. nosocomial outbreaks, as well as for national and international surveillance when monitoring newly emerging (resistant) clones, e.g. for pathogens such as Acinetobacter baumannii (Diancourt et al., 2010; Van den Broek et al., 2006), Klebsiella pneumoniae (Brisse et al., * Corresponding author. E-mail addresses: [email protected] (P. Deschaght), Leen. [email protected] (L. Van Simaey), [email protected] (E. Decat), [email protected] (E. Van Mechelen), [email protected] (S. Brisse), [email protected] (M. Vaneechoutte).
2009; Mendonc¸a et al., 2009.), Mycobacterium tuberculosis (Burgos et al., 2004), Neisseria meningitidis (Woods et al., 1996), Pseudomonas aeruginosa (Inglis et al., 2010), and multiresistant Staphylococcus aureus (Makgotlho et al., 2009). During the last decades, genotyping techniques (DNA fingerprinting) have largely replaced phenotypic techniques, such as serotyping, phage susceptibility typing and protein SDS PAGE. Two major DNA fingerprinting approaches can be distinguished, i.e. restriction fragment length polymorphism (RFLP) analysis techniques, such as chromosomal DNA restriction analysis, ribotyping and AFLPÔ, and amplified fragment length polymorphism analysis such as arbitrarily primed-PCR, better known as randomly amplified polymorphic DNA analysis (RAPD), REP-PCR and variable number tandem repeat
0923-2508/$ - see front matter Ó 2011 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved. doi:10.1016/j.resmic.2011.02.002
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(VNTR) amplification (Van Belkum et al., 2007; Vaneechoutte, 1996). With the development of faster, cheaper and more automated sequencing capacity, sequence-based typing, such as multilocus sequence typing (MLST) (Diancourt et al., 2005, 2010; Maiden et al., 1998), is gradually replacing these DNA fingerprinting techniques, basically because sequencing is fully digitizable and less prone to interlaboratory variability. Whereas MLST is a reference approach for large scale surveillance and for population biology studies, there remains a need for rapid, less laborious and cheap approaches, such as RAPD, on a local scale. Although the interrun reproducibility of this approach is known to be limited, it still offers the possibility of studying e within a single run e the genotypic relatedness of a limited number of isolates that might possibly belong to a single outbreak, e.g. in a hospital or hospital ward. Recently, a further improvement has appeared as it became possible to carry out melting curve analysis of amplified DNA fragments. However, thus far, a limited number of publications have described the application of melting curve analysis of the DNA fragments that are generated during RAPD (Plachy´ et al., 2005; Trtkova et al., 2009; Tulsiani et al., 2010), and the designation McRAPD has been proposed (Plachy´ et al., 2005; Trtkova et al., 2009). This approach obviates the need for agarose gel electrophoresis, including the pouring of gels, running the electrophoresis, the usage of ethidium bromide and photography of the stained gels, drastically reducing workload and time-to-results. Here, we compared the discriminatory power of McRAPD for genotyping isolates of several collections of five different Gram-negative species with that of established DNA fingerprinting techniques and/or MLST. 2. Materials and methods 2.1. Bacterial isolates For this study, several Gram-negative bacterial species of nosocomial importance were studied, including Achromobacter xylosoxidans, A. baumannii, K. pneumoniae, P. aeruginosa and Stenotrophomonas maltophilia. The A. xylosoxidans collection consisted of 9 isolates cultured from 3 P. aeruginosa colonized cystic fibrosis (CF) patients, as described previously (Van daele et al., 2005a,b). These isolates had been shown, by RAPD with agarose gel electrophoresis (RAPD-AGE) and with AFLPÔ, to belong to 3 different genotypes. The 10 A. baumannii isolates and the 10 K. pneumoniae isolates originated from different sources and had been typed by MLST (Diancourt et al., 2010; Brisse et al., 2009). Within each of the two species, the 10 isolates could be clustered into 3 clonal complexes and into 5 and 7 MLST genotypes, respectively (Diancourt et al., 2010; Brisse et al., 2009) (Supplementary Table 1). Two collections of P. aeruginosa isolates were tested. The first collection consisted of 12 isolates isolated by means of RAPD-AGE from the burn wound center at the Ghent University Hospital (BWC) and previously shown to belong to 4 different genotypes (unpublished data). The second P. aeruginosa collection consisted of 21 isolates from 20 patients, originating from the same CF population as the A. xylosoxidans isolates, as described previously
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(Van daele et al., 2005a,b; Van daele et al., 2006). These isolates had been shown by RAPD-AGE and AFLPÔ to belong to 5 different genotypes. The 11 S. maltophilia isolates belonged to 4 RAPD-AGE genotypes (unpublished data) and were isolates from 4 CF patients. For each patient, the different isolates were isolated with a median time interval of 3 months. 2.2. DNA extraction For all species, DNA was extracted from cultured bacteria by simple alkaline lysis. One colony, obtained after 18 h of culture on a 5% (v/v) sheep blood agar plate (Becton Dickinson, Erembodegem, Belgium), was suspended in 20 ml of lysis buffer (0.25% (w/v) SDS, 0.05 N NaCl and 95 ml sterile distilled water) and heated for 15 min at 95 C. After brief centrifugation, 180 ml of HPLC-water was added and this mixture was centrifuged for 5 min at 16,300 g. The crude supernatant was used as DNA extract. For the 12 P. aeruginosa isolates of the BWC collection, DNA extraction was also carried out with the manual High Pure PCR Template Preparation kit (Roche Applied Science, Basel, Switzerland), according to the manufacturer’s recommendations. 2.3. RAPD-AGE All isolates, including those that had already been previously genotyped by RAPD, were genotyped during this study by RAPD, followed by agarose gel electrophoresis (RAPDAGE). RAPD-AGE was performed with Ready-to-Go beads (Amersham Biosciences AB, Uppsala, Sweden) and 2 mM of primer RAPD4 (AAGACGCCGT) or 1 mM of primer ERIC2 (AAGTAAGTGACTGGGGTGAGCG) in total volumes of 12 ml, including 1.2 ml of DNA extract at an annealing temperature of 37 C, as previously described (Van daele et al., 2005a). Agarose gel electrophoresis was carried out at 100 V on an agarose gel of 2.5% (w/v), containing 1 mg/ml ethidium bromide and visualized and photographed on a UV transilluminator at 540 nm. 2.4. McRAPD RAPD in combination with melting curve analysis of amplified DNA fragments (McRAPD (Plachy´ et al., 2005; Trtkova et al., 2009)) was performed on a Lightcycler 1.2 (Roche Applied Science). The total reaction mix per sample was 20 ml and consisted of 2 ml LightcyclerÒ FastStart DNA Master SYBR Green I (Roche Applied Science), 0.5 mM of primer RAPD4 or of primer ERIC2, 2 mM MgCl2, and 2 ml of DNA extract. The PCR protocol started with an activation step of 10 min at 95 C, followed by 40 cycles of denaturation at 95 C for 10 s, annealing at 37 C for 10 s and elongation at 72 C for 30 s. Melting down of the amplification product started with 1 min at 72 C followed by increasing the temperature to 95 C with a ramp rate of 0.1 C/s and a continuous measurement of fluorescence at 530 nm.
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2.5. Analysis of the melting curve data The melting curves were normalized using the ‘Tm calling melting curve analysis’ option, proGram med in Lightcycler Software 4.1.1.21 (Roche Applied Science). Using the normalized melting curve, 3e4 melting peaks with the highest melting temperature were manually selected and 3e4 melting temperatures were used to construct a digital fingerprint consisting of 3e4 values. Comparison of digitized McRAPD fingerprints was done using the differential basepair method (dbp: nAB/aB), as calculated by BaseHopper inhouse software (http://www. basehopper.be).
3. Results 3.1. Grouping of the different genotypes Using McRAPD data, the diverse sets of isolates of 5 different Gram-negative species could all be classified into
almost complete concordance with groups derived from previous genotyping results (Supplementary Table 1). For P. aeruginosa, a total of 33 isolates derived from two collections (BWC and CF) were tested with two primers, RAPD4 and ERIC2. Using primer RAPD4, all genotypes in both collections could be assigned to the same genotypes as established on the basis of RAPD-AGE and/or AFLPÔ (Table 1), except for genotypes C and D in the P. aeruginosa CF-collection, for which the difference was at the limit. Both collections were also tested with primer ERIC2 and a better spread of the melting temperatures could be established (Table 2) (Fig. 1). It should be noted that, with primer ERIC2, differentiation between genotypes C and D was possible, although based on only one different melting temperature (Table 2, TM4). The difference in primer and temperature differentiation corresponded to agarose gel electrophoresis patterns in which, for some of the genotypes, ERIC2-based RAPD patterns (Fig. 2, panel F) differed more between genotypes than RAPD4-based RAPD patterns (Fig. 2, panel E). For A. xylosoxidans, the McRAPD approach was able to group the nine isolates into three genotype clusters (Table 1),
Table 1 Mean melting temperatures of the different species genotypes using the RAPD4 primer. Species
Genotype (n)a
TM1b
TM2
TM3
TM4
A. xylosoxidans
A (4) B (1) C (4)
73.98 (0.42) 73.12 74.14 (0.28)
78.42 (0.08) 78.63 78.49 (0.28)
86.39 (0.08) 82.59 85.74 (0.21)
93.65 (0.08) 89.24 92.08 (0.17)
A. baumannii
A (3) B1 (3) B2 (1) C1 (2) C2 (1)
74.71 (0.16) 73.91 (0.16) 74.09 74.16 (0.13) 74.71
77.95 (0.04) 77.74 (0.36) 77.65 76.88 (0.30) 77.49
85.05 (0.04) 85.13 (0.16) 84.94 84.08 (0.10) 84.47
91.92 (0.21) / / 90.32 (0.28) 90.55
K. pneumoniaec
A1 (16A151) A1 (12A041) A2 (08A418) A3 (Zaire1) B1 (779) B1 (cur15505) B2 (04A025) B2 (01A018) C1 (440) C2 (926)
81.9 81.92 79.27 80.46 80.19 81.11 81.04 80.9 75.39 74.91
85.18 85.55 84.79 85.56 / / / / 80.52 81.76
88.67 88.15 88.31 88.82 88.05 88.08 88.16 88.72 85.93 85.96
91.37 91.08 93.83 91.82 91.84 91.24 91.36 91.42 89.63 88.47
P. aeruginosa BWC
A (3) B (2) C (5) D (2)
73.83 73.75 78.62 79.86
(0.12) (0.10) (0.23) (0.20)
79.62 79.51 82.42 82.58
(0.22) (0.30) (0.15) (0.17)
82.72 82.67 88.79 88.69
(0.21) (0.00) (0.16) (0.15)
88.57 (0.14) 89.9 (0.10) 91.87 (0.19) 92.41 (0.30)
P. aeruginosa CF
A (5) B (2) C (3) D (4) E (7)
75.91 78.66 75.59 75.54 /
(0.72) (0.30) (0.21) (0.29)
81.45 80.84 78.87 77.92 75.12
(0.33) (0.00) (0.61) (1.06) (0.14)
86.51 87.83 80.98 80.63 81.27
(0.12) (0.08) (0.24) (0.18) (0.14)
91.48 92.56 87.84 87.50 88.28
S. maltophilia
A (3) B (2) C (4) D (2)
75.00 75.22 75.25 73.22
(0.18) (0.38) (0.36) (0.00)
80.55 80.15 78.96 78.18
(0.50) (0.53) (0.25) (0.20)
88.03 83.40 88.27 85.33
(1.63) (0.38) (0.07) (0.30)
/ 89.76 (0.16) / 90.85 (0.10)
a
(0.15) (0.10) (0.17) (0.11) (0.28)
Number in brackets indicates number of isolates belonging to each genotype, except for K. pneumoniae, for which the isolate name is shown. Mean melting temperatures (in C) of amplified DNA fragments with the highest melting temperatures, with standard deviation (calculated on the basis of the different melting temperatures of the isolates with the same genotype) in brackets. c For K. pneumoniae, melting temperatures of all isolates are shown. b
P. Deschaght et al. / Research in Microbiology 162 (2011) 386e392 Table 2 Comparison of digitized McRAPD patterns of burn wound center (BWC) P. aeruginosa isolates using ERIC2 primer. Collection Genotypea TM1b
TM2
TM3
TM4
BWC
A (3) B (2) C (5) D (2)
77.95 76.73 77.21 78.07
(0.13) (0.00) (0.49) (0.10)
83.26 85.26 79.38 82.58
(0.17) (0.10) (0.43) (0.49)
87.67 87.72 83.04 89.20
(0.29) (0.40) (0.40) (0.10)
92.05 91.18 89.44 92.73
(0.54) (0.50) (0.12) (0.10)
CF
A (5) B (2) C (3) D (4) E (7)
76.35 79.76 79.28 79.56 76.46
(0.056) (0.15) (0.22) (0.24) (0.16)
79.32 87.07 81.33 81.35 80.03
(0.32) (0.071) (0.29) (0.14) (0.20)
87.31 89.86 86.79 86.44 86.67
(035) (0.049) (0.080) (0.056) (0.21)
92.34 92.36 93.15 91.62 92.25
(0.17) (0.21) (0.21) (0.14) (0.44)
a
Number of strains included tested for each genotype. Mean melting temperatures (in C) of RAPD-amplified DNA fragments with the highest melting temperatures, with standard deviation (calculated on the basis of the different melting temperatures of the isolates with the same genotype) in brackets. b
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corresponding to clusters obtained with RAPD-AGE and AFLPÔ clustering (Supplementary Table 1). All three genotypes had a common peak at around 78.5 C, but the melting temperature values of the three other fragments clearly enabled distinction between the three genotypes. For A. baumannii, isolates had been previously classified into three clonal complexes by means of MLST (Diancourt et al., 2010). Using McRAPD, the isolates could also be grouped into three genotypes (Table 1), corresponding to previously published MLST data and the RAPD-AGE data obtained during this study (Supplementary Table 1). Based on TM1 and TM2, there was not a great difference between the different genotypes, while based on TM3 and TM4 the three genotypes could be distinguished. However, with both RAPD methods, there were no clear differences between the various sequence types (STs) within the different clonal complexes. For K. pneumoniae, MLST had shown that the 10 isolates belonged to 7 different STs (A1, A2, A3, B1, B2, C1 and C2), which could be clustered into three clonal complexes (A, B, C)
Fig. 1. McRAPD patterns of P. aeruginosa CF isolates with primer ERIC2. Legend Panel A: Genotype A, Panel B: Genotype B, Panel C: Genotype C, Panel D: Genotype D, Panel E: Genotype E.
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(Brisse et al., 2009). For K. pneumoniae, isolates were differentially clustered on the basis of RAPD-AGE and McRAPD rather than on the basis of MLST. With RAPD-AGE and McRAPD, sequence type A2 could be distinguished from sequence types A1 and A3; moreover, sequence types C1 and C2 could be distinguished from each other (Table 1) (Fig. 3), in agreement with MLST results. However, for genotype B, three RAPD genotypes, not corresponding to MLST results, could be differentiated. On the basis of McRAPD and RAPDAGE, isolate 779 (MLST genotype B1) was separate, isolates cur15505 (MLST genotype B1) and 04A025 (MLST genotype B2) clustered together and isolate 01A018 (MLST genotype B2) was again separate (Table 1) (Fig. 3). It should be noticed that McRAPD showed better correspondence with MLST than RAPD-AGE since, with McRAPD it was possible to distinguish between sequence types A1 and A3 on the basis of a melting temperature difference of 1.5 C for peak 1, whereas A1 and A3 RAPD-AGE profiles could not be differentiated from each other upon visual inspection of the agarose gel. The 11 S. maltophilia isolates, grouped into four genotypes according to RAPD-AGE patterns, could also be grouped into the same genotypes according to McRAPD data (Supplementary Table 1). For genotypes A and C, only three melting temperature peaks could be selected. These melting profiles of these genotypes had two melting temperatures in common (TM1 and TM3), but the third peak (TM2) enabled
clear differentiation between the two genotypes due to a ΔTM of 1.5 C. One isolate of RAPD-AGE genotype A had a completely different McRAPD pattern in comparison with the McRAPD pattern of the other two genotype A RAPD isolates, which explains the high standard deviation values for this genotype. 4. Discussion In this study, we used RAPD followed by melting curve analysis of some of the amplified DNA fragments (McRAPD) for genotyping collections of isolates of five Gram-negative species, and we compared this approach with genotyping results obtained previously by means of MLST (for A. baumannii and K. pneumoniae), AFLPÔ (for the CF A. xylosoxidans and P. aeruginosa isolates) and RAPD followed by agarose gel electrophoresis (RAPD-AGE) (for all isolates). Our results show that McRAPD is a valid alternative to RAPD-AGE and yields a discriminatory power comparable to RAPD-AGE. By indicating the melting point peaks, clear differentiation is possible between the various genotypes. Previously, the McRAPD technique had been used to identify pathogenic yeast species (Plachy´ et al., 2005; Trtkova et al., 2009). For bacteria, melting curve analysis to distinguish different genotypes has already been based on the melting profile of amplified clustered, regularly interspaced short palindromic repeats (CRISPRs) (Price et al., 2007; Bratcikov
Fig. 2. McRAPD patterns (primer RAPD4, panels AeD) and RAPD-AGE patterns (primer RAPD4, panel E and primer ERIC2, panel F) of P. aeruginosa genotypes, derived from the Ghent University Hospital Burn Wound Center (BWC). Panels AeD: McRAPD genotypes for the 12 P. aeruginosa BWC isolates are shown in the different panels (A, B, C, D); each panel contains patterns of a single cluster. The different curves in each panel represent the individual McRAPD genotype for each isolate. Vertical solid black lines indicate selected melting temperature peaks, used to construct digitized McRAPD patterns (Table 1). Panels E and F: M: 100 bp molecular weight marker (Fermentas, Burlington, Canada), lanes 1e3: genotype A, lanes 4e5: genotype B, lanes 6e10: genotype C, lanes 11e12: genotype D.
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Fig. 3. McRAPD (panels AeC) and RAPD-AGE (panel D) patterns of K. pneumoniae isolates obtained with primer RAPD4. Panel A: Melting curves of isolates classified by MLST in clonal complex A. Sequence type (ST) 1: solid line (A1 in panel D), ST 2: green dotted line (A2 in panel D), ST 3: red dashed line (A3 in panel D). Panel B: Melting curve of isolates classified in clonal complex B. ST 1: solid line (B1 in panel D), ST 2: dotted line (B2 in panel D). Panel C: Melting curve of isolates classified in clonal complex C. ST 1: solid line (C1 in panel D), ST 2: dotted line (C2 in panel D). Panel D: M: 100 bp molecular weight marker (Fermentas), A, B, C: clonal complex, 1, 2, 3: STs within each clonal complex.
and Mauricas, 2009) which, at present, have been found in about 40% of all bacterial species (Horvath and Barrangou, 2010) and therefore may be limited to those species. Also, genotyping based on the melting profile of amplified variable numbers of tandem repeats (VNTRs) has been carried out (Naze et al., 2010). To our knowledge, until now, only Tulsiani et al. (2010) used McRAPD to genotype bacteria and, more specifically, to differentiate between serovars of Leptospira species (Tulsiani et al., 2010). In our opinion, McRAPD has the potential for being easily implemented in routine genotyping because it has several advantages over RAPD-AGE while achieving the same discriminatory power, at least for the Gram-negative species tested here. Comparison of McRAPD with MLST data show that McRAPD could be used to rapidly identify major clones of these species, including multidrug-resistant and particularly virulent clones. McRAPD is faster, less costly, more environmentally and userfriendly (no ethidium bromide), less labor-intensive and technically less demanding than RAPD-AGE because there is no need to pour gels, run gel electrophoresis, stain with ethidium bromide or
photograph the gels. McRAPD is also a non-destructive method, i.e. the McRAPD product can still be analyzed on gel in case of a doubtful result. McRAPD has some of the same advantages and limitations as RAPD-AGE. Because it is an amplification based protocol, the DNA extracts may be crude lysates, whereas restriction-based protocols such as AFLPÔ and macrorestriction analysis (PFGE) require pure, i.e. more laborious and more expensive, DNA extracts in order to produce interpretable fingerprints. In this study, we also studied the influence of the DNA extraction method on McRAPD fingerprints, for a collection of P. aeruginosa isolates (data not presented). Crude alkaline lysates yielded the same genotype assignations as more purified DNA extracts, as obtained after commercial Roche-kit-based DNA extraction, although McRAPD and RAPD-AGE fingerprints obtained with the two DNA extraction methods applied to the same isolate sometimes differed. However, as is the case with RAPD-AGE, for which different gel patterns are obtained for different PCR runs of the same isolate, different melting profiles with McRAPD were also obtained for the same isolate in different PCRs (data not presented). Nevertheless, the resulting genotype assignment
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was comparable between runs. Although fingerprints may look different between runs, epidemiological information, i.e. assignment of isolates to different genotypes, will be the same, as was the case when different DNA extracts were used. This means that fingerprints of different thermal cycling runs cannot be compared and thus no large series can be studied. Therefore, this approach remains limited to the study of local outbreaks with a limited number of isolates, e.g. a maximum of 32 when using LightCycler 1.2. Although we provided evidence for the discriminatory power of this technique, further optimization is possible. Use of more advanced melting analysis hardware and software, more discriminatory high-resolution melting dyes such as ResoLight (Roche Applied Science) instead of Sybr Green I, and more optimized primers may continue to increase the discriminatory power and reproducibility of this technique. Acknowledgment None of the authors has a conflict of interest to declare. Pieter Deschaght is indebted to the IWT for PhD research grant IWT-SB/71184. Appendix. Supplementary material Supplementary material related to this article can be found online at doi:10.1016/j.resmic.2011.02.002. References Bratcikov, M., Mauricas, M., 2009. The use of high-resolution melting analysis for Salmonella spp. CRISPR sequence genotyping. Acta Med. Lituanica. 16, 98e102. Brisse, S., Fevre, C., Passet, V., Issenhuth-Jeanjean, S., Tournebize, R., Diancourt, L., Grimont, P., 2009. Virulent clones of Klebsiella pneumoniae: identification and evolutionary scenario based on genomic and phenotypic characterization. Plos One 4, e4982. Burgos, M.V., Me´ndez, J.C., Ribon, W., 2004. Molecular epidemiology of tuberculosis: methodology and applications. Biomedica 24 (Suppl.), 188e201. Diancourt, L., Passet, V., Verhoef, J., Grimont, P.A., Brisse, S., 2005. Multilocus sequence typing of Klebsiella pneumoniae nosocomial isolates. J. Clin. Microbiol. 43, 4178e4182. Diancourt, L., Passet, V., Nemec, A., Dijkshoorn, L., Brisse, S., 2010. The population structure of Acinetobacter baumannii: expanding multiresistant clones from an ancestral susceptible genetic pool. Plos One 5, e10034. Horvath, P., Barrangou, R., 2010. CRISPR/Cas, the immune system of bacteria and archaea. Science 327, 167e170. Inglis, T.J., Benson, K.A., O’Reilly, L., Bradbury, R., Hodge, M., Speers, D., Heath, C.H., 2010. Emergence of multi-resistant Pseudomonas aeruginosa in a Western Australian hospital. J. Hosp. Infect. 76, 60e65. Maiden, M.C., Bygraves, J.A., Feil, E., Morelli, G., Russell, J.E., Urwin, R., Zhang, Q., Zhou, J., Zurth, K., Caugant, D.A., Feavers, I.M., Achtman, M.,
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