- Email: [email protected]
Development of a rapid identification method for Klebsiella pneumoniae phylogenetic groups and analysis of 420 clinical isolates
942 Clinical Microbiology and Infection, Volume 10 Number 10, October 2004
REFERENCES 1. Kloos WE, Bannerman TL. Update on clinical significance of coagulase-negative staphylococci. Clin Microbiol Rev 1994; 7: 117–140. 2. Couto I, Pereira S, Miragaia M, Sanches IS, de Lencastre H. Identification of clinical staphylococcal isolates from humans by internal transcribed spacer PCR. J Clin Microbiol 2001; 39: 3099–3103. 3. Chesneau O, Morvan A, Aubert S, El Solh N. The value of rRNA gene restriction site polymorphism analysis for delineating taxa in the genus Staphylococcus. Int J Syst Evol Microbiol 2000; 50: 689–697. 4. Edwards KJ, Kaufmann ME, Saunders NA. Rapid and accurate identification of coagulase-negative staphylococci by real-time PCR. J Clin Microbiol 2001; 39: 3047– 3051. 5. Kwok AY, Su SC, Reynolds RP et al. Species identification and phylogenetic relationships based on partial HSP60 gene sequences within the genus Staphylococcus. Int J Syst Bacteriol 1999; 49: 1181–1192. 6. Drancourt M, Raoult D. rpoB gene sequence-based identification of Staphylococcus species. J Clin Microbiol 2002; 40: 1333–1338. 7. Poyart C, Quesne G, Boumaila C, Trieu-Cuot P. Rapid and accurate species-level identification of coagulase-negative staphylococci by using the sodA gene as a target. J Clin Microbiol 2001; 39: 4296–4301. 8. Hall TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95 ⁄ 98 ⁄ NT. Nucleic Acids Symp Ser 1999; 41: 95–98. 9. Altschul SF, Madden TL, Schaffer AA et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997; 25: 3389–3402. 10. Petra´sˇ P. Staphylococcus pulvereri = Staphylococcus vitulus? Int J Syst Bacteriol 1998; 48: 617–618. 11. Chesneau O, Morvan A, Grimont F, Labischinski H, El Solh N. Staphylococcus pasteuri sp. nov., isolated from human, animal, and food specimens. Int J Syst Bacteriol 1993; 43: 237–244. 12. Brun Y, Bes M, Boeufgras JM et al. International collaborative evaluation of the ATB 32 staph gallery for identification of the Staphylococcus species. Zentralbl Bakteriol 1990; 273: 319–326. 13. Chesneau O, Aubert S, Morvan A, Guesdon JL, El Solh N. Usefulness of the ID32 staph system and a method based on rRNA gene restriction site polymorphism analysis for species and subspecies identification of staphylococcal clinical isolates. J Clin Microbiol 1992; 30: 2346–2352. 14. Ieven M, Verhoeven J, Pattyn SR, Goossens H. Rapid and economical method for species identification of clinically significant coagulase-negative staphylococci. J Clin Microbiol 1995; 33: 1060–1063. 15. Renneberg J, Rieneck K, Gutschik E. Evaluation of Staph ID 32 system and Staph-Zym system for identification of coagulase-negative staphylococci. J Clin Microbiol 1995; 33: 1150–1153.
RESEARCH NOTE Development of a rapid identification method for Klebsiella pneumoniae phylogenetic groups and analysis of 420 clinical isolates S. Brisse1,2, T. van Himbergen2, K. Kusters2 and J. Verhoef2 1
Unite´ Biodiversite´ des Bacte´ries Pathoge`nes Emergentes (U389 INSERM), Institut Pasteur, Paris, France and 2Eijkman-Winkler Centre, University Medical Centre Utrecht, Utrecht, The Netherlands
ABSTRACT A rapid method combining gyrA PCR–restriction fragment length polymorphism analysis, parC PCR and adonitol fermentation was developed to identify Klebsiella pneumoniae phylogenetic groups KpI, KpII and KpIII. Analysis of 420 clinical isolates from 26 hospitals showed that the three groups were widespread geographically. KpI comprised 80.3% of 305 isolates from blood and 82.2–97.2% of isolates from other clinical sources. KpIII was never found among isolates from urinary tract infections. KpI isolates from blood were generally less susceptible than KpIII isolates to the ten antimicrobial agents tested, with KpII being intermediate. The frequencies of ceftazidime resistance were 21.6% and 8.6% in KpI and KpIII isolates, respectively (p 0.01). Keywords Epidemiology, identification, pneumoniae, Klebsiella variicola, resistance
Klebsiella
Original Submission: 4 February 2004; Revised Submission: 10 March 2004; Accepted: 12 April 2004
Clin Microbiol Infect 2004; 10: 942–945 10.1111/j.1469-0691.2004.00973.x Klebsiellae are opportunistic pathogens that cause septicaemia, pneumonia, urinary tract infections
Corresponding author and reprint requests: S. Brisse, Unite´ Biodiversite´ des Bacte´ries Pathoge`nes Emergentes (U389 INSERM), Institut Pasteur, 28 rue du Docteur Roux, 75724 Paris Cedex 15, France E-mail: [email protected]
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950
Research Note 943
and soft tissue infections [1,2]. Klebsiella pneumoniae is responsible for 75–80% of Klebsiella infections, with antimicrobial resistance, particularly that associated with extended-spectrum b-lactamases, posing an increasingly serious problem [3–6]. Based on nucleotide variation of the gyrA and parC genes, clinical isolates of K. pneumoniae fall into three phylogenetic groups named KpI, KpII and KpIII [7], with the newly described species Klebsiella variicola [8] appearing to correspond to KpIII [8] (S. Brisse, unpublished results). The present study aimed to develop a rapid method for the identification of these phylogenetic groups, to determine their relative prevalence in nosocomial infections, and to compare their levels of antimicrobial susceptibility. In total, 420 clinical isolates (including 120 isolates investigated previously [7]) and eight reference strains were studied. The 420 clinical isolates were collected from 23 hospitals located in 13 European countries and three hospitals in South Africa [4,9], and were derived from blood (n = 305), nosocomial respiratory tract infections (n = 56), urinary tract infections (UTIs; n = 35), and wound infections (n = 24). Only one isolate ⁄ patient was included. In-silico restriction analysis of a 441-bp PCR fragment of the gyrA gene (gyrA PCR–restriction fragment length polymorphism (PCR-RFLP)) [7] revealed that use of TaqI and HaeIII separately would distinguish between KpI (profiles TaqI-B, HaeIII-C), KpII (TaqI-E, HaeIII-C or HaeIII-D) and KpIII (TaqI-B and HaeIII-B). PCR-RFLP patterns were obtained by digestion of the amplified PCR fragment [7] and electrophoresis on a NuSieve GTG agarose 3% w ⁄ v gel. Identification of Klebsiella spp. remains difficult [10], and profile HaeIII-B was also obtained for all control strains of Klebsiella oxytoca (n = 29), Klebsiella planticola (n = 15) and Klebsiella terrigena (n = 5) tested. However, enzyme HincII did not cut the gyrA PCR products from K. planticola and K. terrigena, whereas it generated profile HincII-B (298 bp and 143 bp) for all K. pneumoniae isolates and profile C (196 bp, 168 bp and 77 bp) for all isolates of K. oxytoca. Use of the above technique confirmed that all 420 clinical isolates were K. pneumoniae. TaqI and HaeIII restriction profiles were as expected for isolates for which the gyrA gene had been sequenced previously [7] (Fig. 1). In total, 345 (82.1%) clinical isolates were identified as KpI, 29
HaeIII
TaqI B B
E
M
C B B B C C M
bp 300 200
100
Fig. 1. Examples of restriction profiles obtained after cutting the 441-bp gyrA PCR product with enzymes TaqI and HaeIII. The profile codes are indicated by a letter above each lane. M: molecular size marker (300-bp, 200-bp and 100-bp fragments). Profile TaqI-B consists of the expected 197-bp, 142-bp, 93-bp and 9-bp fragments, and profile TaqIE of the expected 197-bp, 151-bp and 93-bp fragments. Profile HaeIII-B consists of the expected 175-bp, 174-bp and 92-bp fragments, profile HaeIII-C of the expected 175-bp, 129-bp, 92-bp and 45-bp fragments, and profile D (not shown) of the expected 267-bp, 129-bp and 45-bp fragments.
(6.9%) as KpII and 46 (11%) as KpIII. The gyrA and parC genes of a further 60 randomly selected clinical isolates (45 KpI, eight KpII and seven KpIII) were sequenced, and gyrA PCR-RFLP group identification was confirmed in all cases. The property of adonitol fermentation was shown previously to be distributed unequally among the phylogenetic groups [7]. In the present study, 336 (97.4%) of 345 KpI isolates were adonitol-positive, with the nine adonitol-negative isolates confirmed as KpI by parC sequencing. For KpII, 19 (65.5%) of 29 isolates were adonitolpositive, whereas only two (4.3%) of 46 KpIII isolates were positive, with these two isolates confirmed as KpIII by parC sequencing. In order to confirm group identification, a KpIIspecific PCR assay targeting the parC gene was tested on 220 of the 420 isolates identified previously by gyrA PCR-RFLP. Primers parC21 (GGCGCAACCCTTCTCCTAT) and parC2-3 (GAGCAGGATGTTTGGCAGG) were designed to match KpII sequences, but to have mismatches compared to KpI and KpIII sequences [7]. The positions of the primers did not include sites
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950
944 Clinical Microbiology and Infection, Volume 10 Number 10, October 2004
Table 1. Proportions of susceptible, intermediate and resistant blood isolates of the three K. pneumoniae phylogenetic groups Susceptible (%) KpI
Intermediate (%)
Resistant (%)
KpII KpIII KpI KpII KpIII KpI KpII KpIII
Ampicillin 0 4 0 Piperacillin 35.5 28.0 80.0 Piperacillin– 80.4 88.0 94.3 tazobactam Ceftazidime 88.4 84.0 91.4 Ceftriaxone 88.0 84.0 91.4 Imipenem 100 100 100 Gentamicin 82.6 93.6 94.3 Amikacin 93.1 93.6 94.3 Trimethoprim– 77.2 92.0 88.6 sulphamethoxazole Ciprofloxacin 92.6 88.0 97.1
1.2 4.0 21.6 36.0 4.1 0 0 5.3 0 2.8 6.9 –
0 0 0 3.2 3.2 –
3.7
0
22.8 8.6 0
98.8 92.0 42.9 36.0 15.5 12.0
87.2 11.4 5.7
0 0 0 0 5.7 22.8
21.6 16.0 16.7 16.0 0 0 14.6 3.2 0 3.2 8.0 11.4
8.6 8.6 0 5.7 0
0
3.7 12.0
2.9
involved in quinolone resistance. PCR amplification with a 50C annealing temperature yielded the expected 232-bp product with none of 146 KpI and 45 KpIII isolates tested, whereas 28 of 29 KpII isolates were positive. The discrepant KpII isolate was confirmed to be KpII by parC sequencing. Thus, the KpII-specific parC PCR showed excellent specificity (100%) and sensitivity (97%) for detection of KpII strains. Overall, the results indicated that gyrA PCRRFLP assigns isolates reliably to one of the three K. pneumoniae groups. Although less informative than gene sequencing, gyrA PCR-RFLP provides information faster and at a lower cost than gyrA sequencing, but identification should ideally be confirmed with independent markers. KpI was found in all 26 hospitals, KpII in 16 hospitals, and KpIII in 17 hospitals. KpI was the most common group in clinical specimens from most hospitals (80.3–83.3% from blood, respiratory tract infections and wounds, and 97.2% from UTIs); KpIII was never found in UTIs. The MICs of ten antimicrobial agents were determined for the 420 clinical isolates by National Committee for Clinical Laboratory Standards broth microdilution methods [11]. Resistance rates in UTI, blood and respiratory tract infection isolates, respectively, were 42%, 22% and 14% for ceftazidime, 61%, 44% and 28% for piperacillin, 42%, 24% and 14% for co-trimoxazole, 21%, 13% and 19% for gentamicin, and 9%, 4% and 6% for ciprofloxacin. Similar trends were observed for most other antimicrobial agents. Table 1 compares the results for blood
isolates of the three K. pneumoniae groups. For most agents, the level of resistance was highest in KpI, intermediate in KpII, and lowest in KpIII. The difference between KpI and KpIII resistance levels was statistically significant (p £ 0.01) for ceftazidime (indicating extended-spectrum b-lactamase production) and piperacillin. Piperacillin resistance levels were statistically different between KpII and KpIII (p 0.0005). Resistance to ampicillin was significantly different between KpI and KpII (p 0.001) and between KpI and KpIII (p < 0.0001), mostly because of KpII and KpIII isolates with intermediate resistance (MIC 16 mg ⁄ L). The differences for ampicillin and piperacillin resistance remained statistically significant even if only the 216 KpI, 21 KpII and 32 KpIII ceftazidime-susceptible blood isolates (MIC £ 16 mg ⁄ L) were considered. For many antimicrobial agents, the resistance rate in KpI isolates was two- or three-fold higher than that in KpIII isolates. Resistance levels are higher in K. pneumoniae than in K. oxytoca isolates [4], but resistance rates in KpIII isolates appear similar or lower to those observed in K. oxytoca. Resistance was not clustered in particular hospitals, so the differences in antimicrobial susceptibility among K. pneumoniae groups cannot be attributed to over-representation of a few resistant strains following clonal spread. The higher prevalence of KpI isolates could be a consequence of higher resistance rates, since resistance is a critical parameter for the transmission of this mainly nosocomial and opportunistic pathogen [12,13]. In summary, reliable identification of the three K. pneumoniae phylogenetic groups can be obtained by combining gyrA PCR-RFLP, parC PCR and adonitol fermentation. For isolates with discrepant results, parC gene sequencing can be used for confirmation. The different distribution and frequencies of antimicrobial resistance observed in this study suggest distinctive pathogenic and epidemiological characteristics among the three groups, which may be relevant for the control of K. pneumoniae infections. ACKNOWLEDGEMENTS Most strains analysed in this study were collected in the framework of the European SENTRY Antimicrobial Surveillance Program. Part of this work was supported by the GENE project (contract QLK2-2000-01404) of the European Union
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950
Research Note 945
Fifth Framework Programme. We thank A. C. Fluit, D. Milatovic and F.-J. Schmitz for kindly contributing the major part of the antimicrobial susceptibility data.
RESEARCH NOTE
REFERENCES
Sequence and structure relatedness of matrix protein of human respiratory syncytial virus with matrix proteins of other negative-sense RNA viruses
1. Podschun R, Ullmann U. Klebsiella spp. as nosocomial pathogens: epidemiology, taxonomy, typing methods, and pathogenicity factors. Clin Microbiol Rev 1998; 11: 589–603. 2. Grimont F, Grimont PAD, Richard C. The genus Klebsiella. In: Balows A, Tru¨per HG, Dworkin M, Harder W, Schleifer K-H, eds. The prokaryotes. New York: Springer-Verlag, 1992; 2775–2796. 3. Babini GS, Livermore DM. Antimicrobial resistance amongst Klebsiella spp. collected from intensive care units in Southern and Western Europe in 1997–1998. J Antimicrob Chemother 2000; 45: 183–189. 4. Brisse S, Milatovic D, Fluit AC, Verhoef J, Schmitz FJ. Epidemiology of quinolone resistance of Klebsiella pneumoniae and Klebsiella oxytoca in Europe. Eur J Clin Microbiol Infect Dis 2000; 19: 64–68. 5. Livermore DM, Yuan M. Antibiotic resistance and production of extended-spectrum beta-lactamases amongst Klebsiella spp. from intensive care units in Europe. J Antimicrob Chemother 1996; 38: 409–424. 6. Sirot J, Nicolas-Chanoine MH, Chardon H et al. Susceptibility of Enterobacteriaceae to beta-lactam agents and fluoroquinolones: a 3-year survey in France. Clin Microbiol Infect 2002; 8: 207–213. 7. Brisse S, Verhoef J. Phylogenetic diversity of Klebsiella pneumoniae and Klebsiella oxytoca clinical isolates revealed by randomly amplified polymorphic DNA, gyrA and parC genes sequencing and automated ribotyping. Int J Syst Evol Microbiol 2001; 51: 915–924. 8. Rosenblueth M, Martı´nez L, Silva J, Martı´nez-Romero E. Klebsiella variicola, a novel species with clinical and plantassociated isolates. Syst Appl Microbiol 2004; 27: 27–35. 9. Jones ME, Jones RN, Sader H, Verhoef J, Acar J. Current susceptibilities of staphylococci to glycopeptides determined as part of an international resistance surveillance programme. Sentry Antimicrobial Surveillance Program. J Antimicrob Chemother 1998; 42: 119–121. 10. Monnet D, Freney J, Brun Y, Boeufgras JM, Fleurette J. Difficulties in identifying Klebsiella strains of clinical origin. Zentralbl Bakteriol 1991; 274: 456–464. 11. National Committee for Clinical Laboratory Standards. Methods for dilution antimicrobial tests for bacteria that grow aerobically. Approved standard M7-A4. Wayne, PA: NCCLS, 1997. 12. Montgomerie JZ. Epidemiology of Klebsiella pneumoniae and hospital-associated infections. Rev Infect Dis 1979; 1: 736–753. 13. Selden R, Lee S, Wang WL, Bennett JV, Eickhoff TC. Nosocomial Klebsiella infections: intestinal colonization as a reservoir. Ann Intern Med 1971; 74: 657–664.
K. Latiff1,2,3, J. Meanger1,2, J. Mills1 and R. Ghildyal1,2,3 1
Children’s Virology Research Unit, Macfarlane Burnet Institute of Medical Research and Public Health, 2Department of Microbiology, Monash University and 3Monash University Department of Medicine, Department of Respiratory and Sleep Medicine, Monash Medical Centre, Melbourne, Australia
ABSTRACT Matrix proteins of viruses within the order Mononegavirales have similar functions and play important roles in virus assembly. Protein sequence alignment, phylogenetic tree derivation, hydropathy profiles and secondary structure prediction were performed on selected matrix protein sequences, using human respiratory syncytial virus matrix protein as the reference. No general conservation of primary, secondary or tertiary structure was found, except for a broad similarity in the hydropathy pattern correlating with the fact that all the proteins studied are membraneassociated. Interestingly, the matrix proteins of Ebola virus and human respiratory syncytial virus shared secondary structure homology. Keywords Ebola virus, matrix protein, Mononegavirales, respiratory syncytial virus, RNA viruses Original Submission: 29 October 2003; Revised Submission: 9 February 2004; Accepted: 29 March 2004
Clin Microbiol Infect 2004; 10: 945–948 10.1111/j.1469-0691.2004.00980.x Matrix proteins of negative-sense single-strand RNA viruses play an important role in virus
Corresponding author and reprint requests: R. Ghildyal, Monash University Department of Medicine, Monash Medical Centre, Melbourne, Australia E-mail: [email protected]
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950
REFERENCES 1. Kloos WE, Bannerman TL. Update on clinical significance of coagulase-negative staphylococci. Clin Microbiol Rev 1994; 7: 117–140. 2. Couto I, Pereira S, Miragaia M, Sanches IS, de Lencastre H. Identification of clinical staphylococcal isolates from humans by internal transcribed spacer PCR. J Clin Microbiol 2001; 39: 3099–3103. 3. Chesneau O, Morvan A, Aubert S, El Solh N. The value of rRNA gene restriction site polymorphism analysis for delineating taxa in the genus Staphylococcus. Int J Syst Evol Microbiol 2000; 50: 689–697. 4. Edwards KJ, Kaufmann ME, Saunders NA. Rapid and accurate identification of coagulase-negative staphylococci by real-time PCR. J Clin Microbiol 2001; 39: 3047– 3051. 5. Kwok AY, Su SC, Reynolds RP et al. Species identification and phylogenetic relationships based on partial HSP60 gene sequences within the genus Staphylococcus. Int J Syst Bacteriol 1999; 49: 1181–1192. 6. Drancourt M, Raoult D. rpoB gene sequence-based identification of Staphylococcus species. J Clin Microbiol 2002; 40: 1333–1338. 7. Poyart C, Quesne G, Boumaila C, Trieu-Cuot P. Rapid and accurate species-level identification of coagulase-negative staphylococci by using the sodA gene as a target. J Clin Microbiol 2001; 39: 4296–4301. 8. Hall TA. BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95 ⁄ 98 ⁄ NT. Nucleic Acids Symp Ser 1999; 41: 95–98. 9. Altschul SF, Madden TL, Schaffer AA et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997; 25: 3389–3402. 10. Petra´sˇ P. Staphylococcus pulvereri = Staphylococcus vitulus? Int J Syst Bacteriol 1998; 48: 617–618. 11. Chesneau O, Morvan A, Grimont F, Labischinski H, El Solh N. Staphylococcus pasteuri sp. nov., isolated from human, animal, and food specimens. Int J Syst Bacteriol 1993; 43: 237–244. 12. Brun Y, Bes M, Boeufgras JM et al. International collaborative evaluation of the ATB 32 staph gallery for identification of the Staphylococcus species. Zentralbl Bakteriol 1990; 273: 319–326. 13. Chesneau O, Aubert S, Morvan A, Guesdon JL, El Solh N. Usefulness of the ID32 staph system and a method based on rRNA gene restriction site polymorphism analysis for species and subspecies identification of staphylococcal clinical isolates. J Clin Microbiol 1992; 30: 2346–2352. 14. Ieven M, Verhoeven J, Pattyn SR, Goossens H. Rapid and economical method for species identification of clinically significant coagulase-negative staphylococci. J Clin Microbiol 1995; 33: 1060–1063. 15. Renneberg J, Rieneck K, Gutschik E. Evaluation of Staph ID 32 system and Staph-Zym system for identification of coagulase-negative staphylococci. J Clin Microbiol 1995; 33: 1150–1153.
RESEARCH NOTE Development of a rapid identification method for Klebsiella pneumoniae phylogenetic groups and analysis of 420 clinical isolates S. Brisse1,2, T. van Himbergen2, K. Kusters2 and J. Verhoef2 1
Unite´ Biodiversite´ des Bacte´ries Pathoge`nes Emergentes (U389 INSERM), Institut Pasteur, Paris, France and 2Eijkman-Winkler Centre, University Medical Centre Utrecht, Utrecht, The Netherlands
ABSTRACT A rapid method combining gyrA PCR–restriction fragment length polymorphism analysis, parC PCR and adonitol fermentation was developed to identify Klebsiella pneumoniae phylogenetic groups KpI, KpII and KpIII. Analysis of 420 clinical isolates from 26 hospitals showed that the three groups were widespread geographically. KpI comprised 80.3% of 305 isolates from blood and 82.2–97.2% of isolates from other clinical sources. KpIII was never found among isolates from urinary tract infections. KpI isolates from blood were generally less susceptible than KpIII isolates to the ten antimicrobial agents tested, with KpII being intermediate. The frequencies of ceftazidime resistance were 21.6% and 8.6% in KpI and KpIII isolates, respectively (p 0.01). Keywords Epidemiology, identification, pneumoniae, Klebsiella variicola, resistance
Klebsiella
Original Submission: 4 February 2004; Revised Submission: 10 March 2004; Accepted: 12 April 2004
Clin Microbiol Infect 2004; 10: 942–945 10.1111/j.1469-0691.2004.00973.x Klebsiellae are opportunistic pathogens that cause septicaemia, pneumonia, urinary tract infections
Corresponding author and reprint requests: S. Brisse, Unite´ Biodiversite´ des Bacte´ries Pathoge`nes Emergentes (U389 INSERM), Institut Pasteur, 28 rue du Docteur Roux, 75724 Paris Cedex 15, France E-mail: [email protected]
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950
Research Note 943
and soft tissue infections [1,2]. Klebsiella pneumoniae is responsible for 75–80% of Klebsiella infections, with antimicrobial resistance, particularly that associated with extended-spectrum b-lactamases, posing an increasingly serious problem [3–6]. Based on nucleotide variation of the gyrA and parC genes, clinical isolates of K. pneumoniae fall into three phylogenetic groups named KpI, KpII and KpIII [7], with the newly described species Klebsiella variicola [8] appearing to correspond to KpIII [8] (S. Brisse, unpublished results). The present study aimed to develop a rapid method for the identification of these phylogenetic groups, to determine their relative prevalence in nosocomial infections, and to compare their levels of antimicrobial susceptibility. In total, 420 clinical isolates (including 120 isolates investigated previously [7]) and eight reference strains were studied. The 420 clinical isolates were collected from 23 hospitals located in 13 European countries and three hospitals in South Africa [4,9], and were derived from blood (n = 305), nosocomial respiratory tract infections (n = 56), urinary tract infections (UTIs; n = 35), and wound infections (n = 24). Only one isolate ⁄ patient was included. In-silico restriction analysis of a 441-bp PCR fragment of the gyrA gene (gyrA PCR–restriction fragment length polymorphism (PCR-RFLP)) [7] revealed that use of TaqI and HaeIII separately would distinguish between KpI (profiles TaqI-B, HaeIII-C), KpII (TaqI-E, HaeIII-C or HaeIII-D) and KpIII (TaqI-B and HaeIII-B). PCR-RFLP patterns were obtained by digestion of the amplified PCR fragment [7] and electrophoresis on a NuSieve GTG agarose 3% w ⁄ v gel. Identification of Klebsiella spp. remains difficult [10], and profile HaeIII-B was also obtained for all control strains of Klebsiella oxytoca (n = 29), Klebsiella planticola (n = 15) and Klebsiella terrigena (n = 5) tested. However, enzyme HincII did not cut the gyrA PCR products from K. planticola and K. terrigena, whereas it generated profile HincII-B (298 bp and 143 bp) for all K. pneumoniae isolates and profile C (196 bp, 168 bp and 77 bp) for all isolates of K. oxytoca. Use of the above technique confirmed that all 420 clinical isolates were K. pneumoniae. TaqI and HaeIII restriction profiles were as expected for isolates for which the gyrA gene had been sequenced previously [7] (Fig. 1). In total, 345 (82.1%) clinical isolates were identified as KpI, 29
HaeIII
TaqI B B
E
M
C B B B C C M
bp 300 200
100
Fig. 1. Examples of restriction profiles obtained after cutting the 441-bp gyrA PCR product with enzymes TaqI and HaeIII. The profile codes are indicated by a letter above each lane. M: molecular size marker (300-bp, 200-bp and 100-bp fragments). Profile TaqI-B consists of the expected 197-bp, 142-bp, 93-bp and 9-bp fragments, and profile TaqIE of the expected 197-bp, 151-bp and 93-bp fragments. Profile HaeIII-B consists of the expected 175-bp, 174-bp and 92-bp fragments, profile HaeIII-C of the expected 175-bp, 129-bp, 92-bp and 45-bp fragments, and profile D (not shown) of the expected 267-bp, 129-bp and 45-bp fragments.
(6.9%) as KpII and 46 (11%) as KpIII. The gyrA and parC genes of a further 60 randomly selected clinical isolates (45 KpI, eight KpII and seven KpIII) were sequenced, and gyrA PCR-RFLP group identification was confirmed in all cases. The property of adonitol fermentation was shown previously to be distributed unequally among the phylogenetic groups [7]. In the present study, 336 (97.4%) of 345 KpI isolates were adonitol-positive, with the nine adonitol-negative isolates confirmed as KpI by parC sequencing. For KpII, 19 (65.5%) of 29 isolates were adonitolpositive, whereas only two (4.3%) of 46 KpIII isolates were positive, with these two isolates confirmed as KpIII by parC sequencing. In order to confirm group identification, a KpIIspecific PCR assay targeting the parC gene was tested on 220 of the 420 isolates identified previously by gyrA PCR-RFLP. Primers parC21 (GGCGCAACCCTTCTCCTAT) and parC2-3 (GAGCAGGATGTTTGGCAGG) were designed to match KpII sequences, but to have mismatches compared to KpI and KpIII sequences [7]. The positions of the primers did not include sites
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950
944 Clinical Microbiology and Infection, Volume 10 Number 10, October 2004
Table 1. Proportions of susceptible, intermediate and resistant blood isolates of the three K. pneumoniae phylogenetic groups Susceptible (%) KpI
Intermediate (%)
Resistant (%)
KpII KpIII KpI KpII KpIII KpI KpII KpIII
Ampicillin 0 4 0 Piperacillin 35.5 28.0 80.0 Piperacillin– 80.4 88.0 94.3 tazobactam Ceftazidime 88.4 84.0 91.4 Ceftriaxone 88.0 84.0 91.4 Imipenem 100 100 100 Gentamicin 82.6 93.6 94.3 Amikacin 93.1 93.6 94.3 Trimethoprim– 77.2 92.0 88.6 sulphamethoxazole Ciprofloxacin 92.6 88.0 97.1
1.2 4.0 21.6 36.0 4.1 0 0 5.3 0 2.8 6.9 –
0 0 0 3.2 3.2 –
3.7
0
22.8 8.6 0
98.8 92.0 42.9 36.0 15.5 12.0
87.2 11.4 5.7
0 0 0 0 5.7 22.8
21.6 16.0 16.7 16.0 0 0 14.6 3.2 0 3.2 8.0 11.4
8.6 8.6 0 5.7 0
0
3.7 12.0
2.9
involved in quinolone resistance. PCR amplification with a 50C annealing temperature yielded the expected 232-bp product with none of 146 KpI and 45 KpIII isolates tested, whereas 28 of 29 KpII isolates were positive. The discrepant KpII isolate was confirmed to be KpII by parC sequencing. Thus, the KpII-specific parC PCR showed excellent specificity (100%) and sensitivity (97%) for detection of KpII strains. Overall, the results indicated that gyrA PCRRFLP assigns isolates reliably to one of the three K. pneumoniae groups. Although less informative than gene sequencing, gyrA PCR-RFLP provides information faster and at a lower cost than gyrA sequencing, but identification should ideally be confirmed with independent markers. KpI was found in all 26 hospitals, KpII in 16 hospitals, and KpIII in 17 hospitals. KpI was the most common group in clinical specimens from most hospitals (80.3–83.3% from blood, respiratory tract infections and wounds, and 97.2% from UTIs); KpIII was never found in UTIs. The MICs of ten antimicrobial agents were determined for the 420 clinical isolates by National Committee for Clinical Laboratory Standards broth microdilution methods [11]. Resistance rates in UTI, blood and respiratory tract infection isolates, respectively, were 42%, 22% and 14% for ceftazidime, 61%, 44% and 28% for piperacillin, 42%, 24% and 14% for co-trimoxazole, 21%, 13% and 19% for gentamicin, and 9%, 4% and 6% for ciprofloxacin. Similar trends were observed for most other antimicrobial agents. Table 1 compares the results for blood
isolates of the three K. pneumoniae groups. For most agents, the level of resistance was highest in KpI, intermediate in KpII, and lowest in KpIII. The difference between KpI and KpIII resistance levels was statistically significant (p £ 0.01) for ceftazidime (indicating extended-spectrum b-lactamase production) and piperacillin. Piperacillin resistance levels were statistically different between KpII and KpIII (p 0.0005). Resistance to ampicillin was significantly different between KpI and KpII (p 0.001) and between KpI and KpIII (p < 0.0001), mostly because of KpII and KpIII isolates with intermediate resistance (MIC 16 mg ⁄ L). The differences for ampicillin and piperacillin resistance remained statistically significant even if only the 216 KpI, 21 KpII and 32 KpIII ceftazidime-susceptible blood isolates (MIC £ 16 mg ⁄ L) were considered. For many antimicrobial agents, the resistance rate in KpI isolates was two- or three-fold higher than that in KpIII isolates. Resistance levels are higher in K. pneumoniae than in K. oxytoca isolates [4], but resistance rates in KpIII isolates appear similar or lower to those observed in K. oxytoca. Resistance was not clustered in particular hospitals, so the differences in antimicrobial susceptibility among K. pneumoniae groups cannot be attributed to over-representation of a few resistant strains following clonal spread. The higher prevalence of KpI isolates could be a consequence of higher resistance rates, since resistance is a critical parameter for the transmission of this mainly nosocomial and opportunistic pathogen [12,13]. In summary, reliable identification of the three K. pneumoniae phylogenetic groups can be obtained by combining gyrA PCR-RFLP, parC PCR and adonitol fermentation. For isolates with discrepant results, parC gene sequencing can be used for confirmation. The different distribution and frequencies of antimicrobial resistance observed in this study suggest distinctive pathogenic and epidemiological characteristics among the three groups, which may be relevant for the control of K. pneumoniae infections. ACKNOWLEDGEMENTS Most strains analysed in this study were collected in the framework of the European SENTRY Antimicrobial Surveillance Program. Part of this work was supported by the GENE project (contract QLK2-2000-01404) of the European Union
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950
Research Note 945
Fifth Framework Programme. We thank A. C. Fluit, D. Milatovic and F.-J. Schmitz for kindly contributing the major part of the antimicrobial susceptibility data.
RESEARCH NOTE
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K. Latiff1,2,3, J. Meanger1,2, J. Mills1 and R. Ghildyal1,2,3 1
Children’s Virology Research Unit, Macfarlane Burnet Institute of Medical Research and Public Health, 2Department of Microbiology, Monash University and 3Monash University Department of Medicine, Department of Respiratory and Sleep Medicine, Monash Medical Centre, Melbourne, Australia
ABSTRACT Matrix proteins of viruses within the order Mononegavirales have similar functions and play important roles in virus assembly. Protein sequence alignment, phylogenetic tree derivation, hydropathy profiles and secondary structure prediction were performed on selected matrix protein sequences, using human respiratory syncytial virus matrix protein as the reference. No general conservation of primary, secondary or tertiary structure was found, except for a broad similarity in the hydropathy pattern correlating with the fact that all the proteins studied are membraneassociated. Interestingly, the matrix proteins of Ebola virus and human respiratory syncytial virus shared secondary structure homology. Keywords Ebola virus, matrix protein, Mononegavirales, respiratory syncytial virus, RNA viruses Original Submission: 29 October 2003; Revised Submission: 9 February 2004; Accepted: 29 March 2004
Clin Microbiol Infect 2004; 10: 945–948 10.1111/j.1469-0691.2004.00980.x Matrix proteins of negative-sense single-strand RNA viruses play an important role in virus
Corresponding author and reprint requests: R. Ghildyal, Monash University Department of Medicine, Monash Medical Centre, Melbourne, Australia E-mail: [email protected]
2004 Copyright by the European Society of Clinical Microbiology and Infectious Diseases, CMI, 10, 922–950