Progress on the development of rapid methods for antimicrobial susceptibility testing

Depósito de investigación de la Universidad de Sevilla https://idus.us.es/ Esta es la versión aceptada del artículo publicado en: This is a accepted manuscript of a paper published in: Journal of Antimicrobial Chemotherapy (2013): December 2013 DOI: https://doi.org/10.1093/jac/dkt253 Copyright: © The Author 2013. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: [email protected] El acceso a la versión publicada del artículo puede requerir la suscripción de la revista. Access to the published version may require subscription. “This is a pre-copyedited, author-produced version of an article accepted for publication in Journal of Antimicrobial Chemotherapy following peer review. The version of record Marina R. Pulido, Meritxell García-Quintanilla, Reyes Martín- Peña, José Miguel Cisneros, Michael J. McConnell, Progress on the development of rapid methods for antimicrobial susceptibility testing, Journal of Antimicrobial Chemotherapy, Volume 68, Issue 12, December 2013, Pages 2710–2717, is available online at: https://academic.oup.com/jac/article/68/12/2710/695468, https://doi.org/10.1093/jac/dkt253”. REVIEW 1 2 Progress on the development of rapid methods for antimicrobial susceptibility 3 testing 4 5 Marina R. PULIDO, Meritxell GARCÍA-QUINTANILLA, Reyes MARTÍN-PEÑA, 6 José Miguel CISNEROS and Michael J. MCCONNELL* 7 8 Unit of Infectious Diseases, Microbiology, and Preventive Medicine and Biomedical 9 Institute of Seville (IBiS), University Hospital Virgen del Rocío/CSIC/University of 10 Sevilla, 41013, Sevilla, Spain. 11 12 13 Author to whom correspondence should be addressed: 14 Michael J. McConnell 15 Unit of Infectious Disease, Microbiology, and Preventive Medicine 16 Hospital Universitario Virgen del Rocío/Instituto de Biomedicina de Sevilla 17 Avenida Manuel Siurot s/n, 41013 Sevilla, Spain 18 e-mail: [email protected] 19 Phone: +34 955923104 20 Fax: +34 955013292 21 22 MRP and MGQ contributed equally to this work 23 Running Title: Rapid susceptibility testing 24 Key Words: susceptibility testing, antibiotic resistance, bacteria 25 26 Synopsis 27 Antimicrobial susceptibility testing is essential for guiding the treatment of 28 many types of bacterial infections, especially in the current context of rising rates of 29 antibiotic resistance. The most commonly employed methods rely on the detection of 30 phenotypic resistance by measuring bacterial growth in the presence of the antibiotic 31 being tested. Although these methods are highly sensitive for the detection of 32 resistance, they require that the bacterial pathogen is isolated from the clinical sample 33 before testing and must employ incubation times that are sufficient for differentiating 34 resistant from susceptible isolates. Knowledge regarding the molecular determinants of 35 antibiotic resistance has facilitated the development of novel approaches with potential 36 for rapidly detecting resistance in bacterial pathogens. PCR-based techniques, mass 37 spectrometry, microarrays, microfluidics, cell lysis-based approaches and whole 38 genome sequencing have all demonstrated the ability to detect resistance in various 39 bacterial species. However, it remains to be determined if these methods can achieve 40 sufficient sensitivity and specificity compared to standard phenotypic resistance testing 41 that would justify their use in routine clinical practice. In the present review, we discuss 42 recent progress in the development of methods for rapid antimicrobial susceptibility 43 testing, and highlight the limitations of each approach that still remain be addressed. 44 45 46 Introduction 47 The administration of appropriate antibiotic therapy for many types of bacterial 48 infections requires that a microbiologic diagnosis, consisting of identification of the 49 causative agent of infection and its resistance profile, is obtained. In routine clinical 50 practice, this process can require between 24 and 72 hours, during which empiric 51 therapy is selected based on the suspected causative organism and local epidemiology. 52 The use of methods that are able to rapidly detect antibiotic resistance in bacterial 53 isolates therefore has the potential to reduce the duration of empiric therapy and 54 facilitate early initiation of targeted treatment with proven antibiotic activity against the 55 causative agent of infection. This is of importance in light of studies that have 56 demonstrated that the rapid availability of antimicrobial susceptibility testing results can 57 improve patient outcomes,1-3 and that a delay in the initiation of appropriate antibiotic 58 therapy is associated with higher patient mortality in certain bacterial infections.4, 5 In 59 addition, rapid antimicrobial resistance testing may contribute to reducing healthcare 60 costs given studies showing that the early availability of antibiotic susceptibility 61 information can result in the ordering of fewer laboratory tests, a decrease in the number 62 of invasive procedures performed, and reduced hospital stay.1, 2 An additional 63 foreseeable benefit of the rapid availability of antibiotic susceptibility testing results is 64 its potential to contribute to antimicrobial stewardship efforts, which include the 65 administration of appropriate antibiotic therapy once susceptibility testing results are 66 available.6 In this context, the early initiation of adequate therapy with the narrowest 67 spectrum needed for appropriate treatment of the infecting bacteria could play a role in 68 reducing the emergence and transmission of resistant strains. In the present review, we 69 give an overview of the techniques that have been developed for rapidly detecting 70 antibiotic resistance in bacterial pathogens (excluding Mycobacteria, a topic which has 71 recently been reviewed7, 8) and provide examples of how these techniques have been 72 employed for detecting resistance in a variety of bacterial pathogens. In addition, we 73 discuss the questions that still remain to be addressed regarding these approaches. 74 75 Currently-used methods 76 The most widely used methods for characterizing antibiotic resistance in clinical 77 isolates detect phenotypic resistance by measuring bacterial growth in the presence of 78 the antibiotic being tested. These techniques include broth microdilution, antimicrobial 79 gradient methods (e.g. Etest strips), disk diffusion, and various commercially available 80 automated systems (e.g. the MicroScan WalkAway system from Siemens, the Phoenix 81 Automated Microbiology System from BD Diagnostics and the Vitek systems from 82 bioMerieux). In addition to their high sensitivity for detecting antibiotic resistance, a 83 major advantage of these techniques is that they have been highly standardized, a 84 process that has been facilitated by the elaboration of international guidelines for 85 antimicrobial susceptibility testing such as those published by the CLSI and the 86 EUCAST.9, 10 For each of these methods, a variety of commercial suppliers provides 87 reagents in ready-to-use formats that facilitate their use in clinical microbiology 88 laboratories with high work loads. In the cases of broth microdilution and antimicrobial 89 gradient methods, an MIC value is obtained, which provides information on the 90 concentration of antibiotic necessary for inhibiting bacterial growth. However, despite 91 their broad use and high sensitivity, there are some limitations associated with these 92 approaches. These methods generally require purity culture before susceptibility testing 93 can be performed, although some protocols may allow for testing directly with clinical 94 samples. In addition, because these techniques measure bacterial growth in order to 95 detect resistance, incubation times that are sufficient for differentiating susceptible from 96 resistant strains must be employed. In the following sections, we comment on the 97 advantages and disadvantages of techniques and protocols that are being developed for 98 rapidly identifying antibiotic resistance with respect to these commonly-used methods. 99 100 PCR-based techniques 101 PCR-based techniques (both conventional and real-time) rely on the sequence 102 specific amplification of nucleic acids. For this reason, PCR was initially used in 103 microbiologic testing for the rapid identification and quantification of causative agents 104 of infections through the amplification of sequences specific to a particular pathogen.11 105 With increased knowledge of the genetic bases of antibiotic resistance that has been 106 acquired in recent years, PCR-based approaches have been developed for detecting the 107 presence of genetic determinants of resistance to a variety of antibiotics for a number of 108 different bacterial species. One salient example has been the use of PCR to identify 109 methicillin resistant Staphylococcus aureus (MRSA) through the detection of the mecA 110 gene, which encodes a modified penicillin-binding protein with reduced affinity for β-111 lactam antibiotics. Many PCR assays (both conventional and real-time) have been 112 described for detecting mecA and/or associated sequences,12-16 including commercial 113 systems that in some cases have the ability to detect MRSA directly from clinical 114 samples in less than two hours.17-19 Examples of commercialized systems that employ 115 real-time PCR for detection are the BD GeneOhm MRSA assay from Becton-Dickinson 116 and the GeneXpert system from Cepheid, the latter of which showed high sensitivity 117 (>93%) compared to routine methods for detecting MRSA in a multicenter study.20 A 118 recent study demonstrating that the clinical implementation of a test for detection of the 119 mecA gene reduced the time to receiving optimal antibiotic therapy by an average of 120 25.4 hours in patients with S. aureus bacteremia illustrates the potential utility of this 121 method.21 PCR-based approaches have also been developed for detecting vancomycin 122 resistance associated with the vanA and vanB genes, and have primarily been used for 123 detecting resistance in Enterococcus species. The sensitivity and specificity of these 124 assays varies depending on the study, however a number of these studies have reported 125 high false positive rates for the detection of the vanB gene, resulting in reduced 126 specificity.22-25 Assays for detecting the presence of resistance genes in Gram negative 127 bacteria have also been developed. Most notably, this has included assays for 128 identifying numerous carbapenemase-encoding genes including, but not limited to, 129 KPC, NDM, IMP, VIM, AmpC, TEM, SHV, and the OXA carbapenemases in 130 Acinetobacter baumannii, Pseudomonas aeruginosa, Klebsiella pneumoniae and 131 Escherichia coli.26-32 132 The major advantage of these PCR-based approaches is that they can be carried 133 out in a relatively short period of time, in some cases using clinical samples without the 134 need for purity culture. PCR thus clearly has the potential to significantly reduce turn-135 around times and rapidly provide information on antibiotic resistance. The major 136 limitation of this approach however, is that the presence of resistance genes may not 137 always correlate with phenotypic resistance. This is less worrisome in cases were the 138 presence of a genotype is highly associated with phenotypic resistance, such as the 139 presence of the mecA, vanA and vanB genes. However, other cases are not so clear cut, 140 such as the presence of carbapenemases in Gram negative bacteria. There are dozens of 141 distinct carbapenemases for which phenotypic resistance may depend not only on the 142 presence of the gene, but on its level of expression. One example is the OXA-51 gene 143 of A. baumannii which only produces phenotypic resistance if it is highly expressed, for 144 example due to the integration of mobile insertion sequences in the gene’s promoter 145 region that increase expression.33, 34 The development of techniques that rely on the 146 measurement of gene transcripts (RNA levels) instead of the presence of a gene may 147 provide a potential solution to this problem. PCR-based techniques that detect the 148 presence of resistance genes are also unable to detect novel or uncharacterized 149 mechanisms of resistance for which the genetic determinant is unknown. This may be 150 especially important in the case of carbapenemases in Gram negative bacteria given the 151 continuous emergence of new variants. This is a critical point given that the inability of 152 a technique to detect resistance would lead to the inappropriate classification of a 153 resistant isolate as susceptible, an error that could lead to the administration of 154 ineffective therapy. A final consideration is that these methods do not provide MIC 155 values, which can be useful for guiding clinical decisions regarding therapy. 156 In addition to using PCR for detecting the presence of genetic determinants of 157 resistance, the ability of real-time PCR to accurately quantify the number of copies of a 158 specific nucleic acid in a sample has led to the development of approaches that employ 159 this method for measuring bacterial growth. This approach monitors the number of 160 bacterial genome copies present during growth of the isolated bacteria in the presence of 161 the antibiotic being tested. Since quantitative real-time PCR can provide precise 162 information regarding genome copy numbers, very short incubation times can be used 163 for differentiating susceptible from resistant strains. One recent example is the detection 164 of resistance to imipenem, ciprofloxacin and colistin in clinical isolates of A. baumannii 165 using a real-time PCR assay targeting highly conserved sequences of the ompA gene.35 166 As shown in Figure 1, growth of a resistant strain in the presence of antibiotics could be 167 detected with relatively short incubation times. This approach has been applied to a 168 number of bacterial species with various antibiotics.36, 37 One advantage of this 169 approach with respect to the PCR-based approaches described above is that it does not 170 depend on the mechanism of resistance and that the assay is indirectly measuring 171 phenotypic resistance by detecting growth in the presence of antibiotic. The major 172 disadvantage is that, unlike PCR-based approaches that detect the presence of resistance 173 determinants, this approach requires previous culture and cannot be used directly with 174 clinical samples. 175 176 Matrix-assisted laser desorption/ionization time of flight mass spectrometry 177 (MALDI-TOF MS) 178 MALDI-TOF MS identifies molecules based on their time of flight through a 179 vacuum tube after laser irradiation of a matrix which is co-crystallized with the sample. 180 The time of flight allows for determination of the mass/charge ratio (m/z) of the ions 181 present, and a spectrum of the sample is generated. The spectrum is then compared with 182 a reference database in order to identify the analyte. Similar to PCR, MALDI-TOF was 183 originally introduced into clinical microbiology laboratories for the identification of 184 pathogens, and has only recently been applied to the detection of resistance. The use of 185 MALDI-TOF to detect resistance most commonly aims to differentiate spectra from 186 resistant and susceptible isolates using whole cells or crude extracts. Comparison of 187 fingerprints from E. coli ATCC 700926 and the same strain carrying the β-lactamase-188 producing plasmid pUC19 determined just one discriminatory peak corresponding to a 189 β-lactamase.38 However, no pattern was found that could reliably identify β-lactamase 190 resistance in clinical isolates of E. coli, K. pneumoniae and P. aeruginosa.39 The 191 detection of vancomycin-resistant enterococci has been recently demonstrated by 192 identifying discriminatory peaks between vanB-positive Enterococcus faecium isolates 193 from those lacking vanB.40 In the case of MRSA, different results have been obtained 194 in individual studies. Some studies have reported measureable differences in spectra 195 when comparing to methicillin-susceptible S. aureus isolates,41-44 whereas other authors 196 below 1.5% and the major error rate (the classification of a susceptible isolate as 347 resistant) must be below 3.0%.77 One of the key limitations that must be addressed 348 regarding many of these methods in order to ensure that they meet these criteria is how 349 often there is discordance between the presence of a resistant determinant and 350 phenotypic resistance. This is of particular importance with the use of techniques that 351 rely solely on the detection of resistance determinants, such as PCR for gene detection 352 or MALDI-TOF. How these tests will deal with novel or uncharacterized resistance 353 mechanisms must also be considered, since the inability of a test to identify resistance 354 will lead to very major errors. Additional aspects that will need to be addressed on a 355 case-by-case basis are whether or not the tests being developed require highly-qualified 356 personal, the added expense associated with the test, and the acceptance of test results 357 by clinicians. However, given the potential benefits in terms of improving patient 358 outcomes by reducing the period of time during which empiric therapy is administered 359 and in terms of reducing healthcare costs, the continued development of these 360 approaches is warranted. 361 362 363 Acknowledgements 364 The authors thank Pilar Pérez-Romero for critical reading of the manuscript and José 365 Luis Fernández for providing the images used in Figure 2. 366 367 Funding 368 This work was funded by a grant from the European Community’s 7th Programme 369 Framework (MagicBullet; Grant Agreement Number: 278232) and the Ministerio de 370 Economía y Competitividad, Instituto de Salud Carlos III - co-financed by European’s 371 Development Regional Fund "A way to achieve Europe" ERDF, Spanish Network for 372 the Research in Infectious Diseases (REIPI RD06/0008/0000). MJM is supported by 373 the Subprograma Miguel Servet from the Ministerio de Economía y Competitividad of 374 Spain (CP11/00314). 375 376 Transparency Declaration 377 All authors declare no potential conflicts of interest. 378 379 References 380 1. Barenfanger J, Drake C, Kacich G. Clinical and financial benefits of rapid 381 bacterial identification and antimicrobial susceptibility testing. J Clin Microbiol 1999; 382 37: 1415-8. 383 2. Doern GV, Vautour R, Gaudet M et al. Clinical impact of rapid in vitro 384 susceptibility testing and bacterial identification. J Clin Microbiol 1994; 32: 1757-62. 385 3. Trenholme GM, Kaplan RL, Karakusis PH et al. Clinical impact of rapid 386 identification and susceptibility testing of bacterial blood culture isolates. J Clin 387 Microbiol 1989; 27: 1342-5. 388 4. Iregui M, Ward S, Sherman G et al. Clinical importance of delays in the 389 initiation of appropriate antibiotic treatment for ventilator-associated pneumonia. Chest 390 2002; 122: 262-8. 391 5. Luna CM, Aruj P, Niederman MS et al. Appropriateness and delay to initiate 392 therapy in ventilator-associated pneumonia. Eur Respir J 2006; 27: 158-64. 393 6. Dryden M, Johnson AP, Ashiru-Oredope D et al. Using antibiotics responsibly: 394 right drug, right time, right dose, right duration. J Antimicrob Chemother; 2011; 66: 395 2441-3. 396 7. Moore DA, Shah NS. Alternative methods of diagnosing drug resistance--what 397 can they do for me? J Infect Dis; 2011; 204 Suppl 4: S1110-9. 398 8. Wilson ML. Recent advances in the laboratory detection of Mycobacterium 399 tuberculosis complex and drug resistance. Clin Infect Dis; 2011; 52: 1350-5. 400 9. Clinical Laboratory Standards Institute. Performance Standards for 401 Antimicrobial Susceptibility Testing: Twenty-third Informational Supplement M100-402 S15. CLSI, Wayne, PA, USA, 2013. 403 10. Leclercq R, Canton R, Brown DF et al. EUCAST expert rules in antimicrobial 404 susceptibility testing. Clin Microbiol Infect; 2013; 19: 141-60. 405 11. Espy MJ, Uhl JR, Sloan LM et al. Real-time PCR in clinical microbiology: 406 applications for routine laboratory testing. Clin Microbiol Rev 2006; 19: 165-256. 407 12. Cuny C, Witte W. PCR for the identification of methicillin-resistant 408 Staphylococcus aureus (MRSA) strains using a single primer pair specific for SCCmec 409 elements and the neighbouring chromosome-borne orfX. Clin Microbiol Infect 2005; 410 11: 834-7. 411 13. Huletsky A, Giroux R, Rossbach V et al. New real-time PCR assay for rapid 412 detection of methicillin-resistant Staphylococcus aureus directly from specimens 413 containing a mixture of staphylococci. J Clin Microbiol 2004; 42: 1875-84. 414 14. Jones CH, Tuckman M, Howe AY et al. Diagnostic PCR analysis of the 415 occurrence of methicillin and tetracycline resistance genes among Staphylococcus 416 aureus isolates from phase 3 clinical trials of tigecycline for complicated skin and skin 417 structure infections. Antimicrob Agents Chemother 2006; 50: 505-10. 418 15. Sinsimer D, Leekha S, Park S et al. Use of a multiplex molecular beacon 419 platform for rapid detection of methicillin and vancomycin resistance in Staphylococcus 420 aureus. J Clin Microbiol 2005; 43: 4585-91. 421 16. Zhang K, McClure JA, Elsayed S et al. Novel multiplex PCR assay for 422 characterization and concomitant subtyping of staphylococcal cassette chromosome mec 423 types I to V in methicillin-resistant Staphylococcus aureus. J Clin Microbiol 2005; 43: 424 5026-33. 425 17. Grobner S, Dion M, Plante M et al. Evaluation of the BD GeneOhm StaphSR 426 assay for detection of methicillin-resistant and methicillin-susceptible Staphylococcus 427 aureus isolates from spiked positive blood culture bottles. J Clin Microbiol 2009; 47: 428 1689-94. 429 18. Paule SM, Hacek DM, Kufner B et al. Performance of the BD GeneOhm 430 methicillin-resistant Staphylococcus aureus test before and during high-volume clinical 431 use. J Clin Microbiol 2007; 45: 2993-8. 432 19. Wang XP, Ginocchio CC. Automation of the BD GeneOhm methicillin-resistant 433 Staphylococcus aureus assay for high-throughput screening of nasal swab specimens. J 434 Clin Microbiol 2009; 47: 1546-8. 435 20. Wolk DM, Picton E, Johnson D et al. Multicenter evaluation of the Cepheid 436 Xpert methicillin-resistant Staphylococcus aureus (MRSA) test as a rapid screening 437 method for detection of MRSA in nares. J Clin Microbiol 2009; 47: 758-64. 438 21. Carver PL, Lin SW, DePestel DD et al. Impact of mecA gene testing and 439 intervention by infectious disease clinical pharmacists on time to optimal antimicrobial 440 therapy for Staphylococcus aureus bacteremia at a University Hospital. J Clin 441 Microbiol 2008; 46: 2381-3. 442 22. Gazin M, Lammens C, Goossens H et al. Evaluation of GeneOhm VanR and 443 Xpert vanA/vanB molecular assays for the rapid detection of vancomycin-resistant 444 enterococci. Eur J Clin Microbiol Infect Dis; 2012; 31: 273-6. 445 23. Mak A, Miller MA, Chong G et al. Comparison of PCR and culture for 446 screening of vancomycin-resistant Enterococci: highly disparate results for vanA and 447 vanB. J Clin Microbiol 2009; 47: 4136-7. 448 24. Stamper PD, Cai M, Lema C et al. Comparison of the BD GeneOhm VanR assay 449 to culture for identification of vancomycin-resistant enterococci in rectal and stool 450 specimens. J Clin Microbiol 2007; 45: 3360-5. 451 25. Usacheva EA, Ginocchio CC, Morgan M et al. Prospective, multicenter 452 evaluation of the BD GeneOhm VanR assay for direct, rapid detection of vancomycin-453 resistant Enterococcus species in perianal and rectal specimens. Am J Clin Pathol; 454 2010; 134: 219-26. 455 26. Monteiro J, Widen RH, Pignatari AC et al. Rapid detection of carbapenemase 456 genes by multiplex real-time PCR. J Antimicrob Chemother 2012; 67: 906-9. 457 27. Chroma M, Hricova K, Kolar M et al. Using newly developed multiplex 458 polymerase chain reaction and melting curve analysis for detection and discrimination 459 of beta-lactamases in Escherichia coli isolates from intensive care patients. Diagn 460 Microbiol Infect Dis 2011; 71: 181-91. 461 28. Mendes RE, Kiyota KA, Monteiro J et al. Rapid detection and identification of 462 metallo-beta-lactamase-encoding genes by multiplex real-time PCR assay and melt 463 curve analysis. J Clin Microbiol 2007; 45: 544-7. 464 29. Brolund A, Wisell KT, Edquist PJ et al. Development of a real-time SYBRGreen 465 PCR assay for rapid detection of acquired AmpC in Enterobacteriaceae. J Microbiol 466 Methods 2010; 82: 229-33. 467 30. Geyer CN, Reisbig MD, Hanson ND. Development of a TaqMan multiplex PCR 468 assay for detection of plasmid-mediated ampC beta-lactamase genes. J Clin Microbiol 469 2012; 50: 3722-5. 470 31. Pérez-Pérez FJ, Hanson ND. Detection of plasmid-mediated AmpC beta-471 lactamase genes in clinical isolates by using multiplex PCR. J Clin Microbiol 2002; 40: 472 2153-62. 473 32. Bogaerts P, Hamels S, de Mendonca R et al. Analytical validation of a novel 474 high multiplexing real-time PCR array for the identification of key pathogens causative 475 of bacterial ventilator-associated pneumonia and their associated resistance genes. J 476 Antimicrob Chemother 2012; 68: 340-7. 477 33. Figueiredo S, Bonnin RA, Poirel L et al. Identification of the naturally occurring 478 genes encoding carbapenem-hydrolysing oxacillinases from Acinetobacter 479 haemolyticus, Acinetobacter johnsonii, and Acinetobacter calcoaceticus. Clin Microbiol 480 Infect 2011; 18: 907-13. 481 34. Turton JF, Ward ME, Woodford N et al. The role of ISAba1 in expression of 482 OXA carbapenemase genes in Acinetobacter baumannii. FEMS Microbiol Lett 2006; 483 258: 72-7. 484 35. Martín-Peña R, Domínguez-Herrera J, Pachón J et al. Rapid detection of 485 antibiotic resistance in Acinetobacter baumannii using quantitative real-time PCR. J 486 Antimicrob Chemother 2013; doi:10.1093/jac/dkt057 487 36. Beuving J, Verbon A, Gronthoud FA et al. Antibiotic susceptibility testing of 488 grown blood cultures by combining culture and real-time polymerase chain reaction is 489 rapid and effective. PLoS One 2011; 6: e27689. 490 37. Rolain JM, Mallet MN, Fournier PE et al. Real-time PCR for universal antibiotic 491 susceptibility testing. J Antimicrob Chemother 2004; 54: 538-41. 492 38. Camara JE, Hays FA. Discrimination between wild-type and ampicillin-resistant 493 Escherichia coli by matrix-assisted laser desorption/ionization time-of-flight mass 494 spectrometry. Anal Bioanal Chem 2007; 389: 1633-8. 495 39. Schaumann R, Knoop N, Genzel GH et al. A step towards the discrimination of 496 beta-lactamase-producing clinical isolates of Enterobacteriaceae and Pseudomonas 497 aeruginosa by MALDI-TOF mass spectrometry. Med Sci Monit 2012; 18: MT71-7. 498 40. Griffin PM, Price GR, Schooneveldt JM et al. Use of matrix-assisted laser 499 desorption ionization-time of flight mass spectrometry to identify vancomycin-resistant 500 enterococci and investigate the epidemiology of an outbreak. J Clin Microbiol 2012; 50: 501 2918-31. 502 41. Du Z, Yang R, Guo Z et al. Identification of Staphylococcus aureus and 503 determination of its methicillin resistance by matrix-assisted laser desorption/ionization 504 time-of-flight mass spectrometry. Anal Chem 2002; 74: 5487-91. 505 42. Edwards-Jones V, Claydon MA, Evason DJ et al. Rapid discrimination between 506 methicillin-sensitive and methicillin-resistant Staphylococcus aureus by intact cell mass 507 spectrometry. J Med Microbiol 2000; 49: 295-300. 508 43. Jackson KA, Edwards-Jones V, Sutton CW et al. Optimisation of intact cell 509 MALDI method for fingerprinting of methicillin-resistant Staphylococcus aureus. J 510 Microbiol Methods 2005; 62: 273-84. 511 44. Majcherczyk PA, McKenna T, Moreillon P et al. The discriminatory power of 512 MALDI-TOF mass spectrometry to differentiate between isogenic teicoplanin-513 susceptible and teicoplanin-resistant strains of methicillin-resistant Staphylococcus 514 aureus. FEMS Microbiol Lett 2006; 255: 233-9. 515 45. Bernardo K, Pakulat N, Macht M et al. Identification and discrimination of 516 Staphylococcus aureus strains using matrix-assisted laser desorption/ionization-time of 517 flight mass spectrometry. Proteomics 2002; 2: 747-53. 518 46. Wolters M, Rohde H, Maier T et al. MALDI-TOF MS fingerprinting allows for 519 discrimination of major methicillin-resistant Staphylococcus aureus lineages. Int J Med 520 Microbiol 2011; 301: 64-8. 521 47. Burckhardt I, Zimmermann S. Using matrix-assisted laser desorption ionization-522 time of flight mass spectrometry to detect carbapenem resistance within 1 to 2.5 hours. 523 J Clin Microbiol 2011; 49: 3321-4. 524 48. Hrabak J, Walkova R, Studentova V et al. Carbapenemase activity detection by 525 matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin 526 Microbiol 2011; 49: 3222-7. 527 49. Hrabak J, Studentova V, Walkova R et al. Detection of NDM-1, VIM-1, KPC, 528 OXA-48, and OXA-162 carbapenemases by matrix-assisted laser desorption ionization-529 time of flight mass spectrometry. J Clin Microbiol 2012; 50: 2441-3. 530 50. Hooff GP, van Kampen JJ, Meesters RJ et al. Characterization of beta-lactamase 531 enzyme activity in bacterial lysates using MALDI-mass spectrometry. J Proteome Res 532 2012; 11: 79-84. 533 51. Sparbier K, Schubert S, Weller U et al. Matrix-assisted laser desorption 534 ionization-time of flight mass spectrometry-based functional assay for rapid detection of 535 resistance against beta-lactam antibiotics. J Clin Microbiol 2012; 50: 927-37. 536 52. Carvalhaes CG, Cayo R, Assis DM et al. Detection of SPM-1-producing 537 Pseudomonas aeruginosa and class D beta-lactamase-producing Acinetobacter 538 baumannii isolates by use of liquid chromatography-mass spectrometry and matrix-539 assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 540 2013; 51: 287-90. 541 53. Kempf M, Bakour S, Flaudrops C et al. Rapid detection of carbapenem 542 resistance in Acinetobacter baumannii using matrix-assisted laser desorption ionization-543 time of flight mass spectrometry. PLoS One 2012; 7: e31676. 544 54. Cohen Stuart J, Dierikx C, Al Naiemi N et al. Rapid detection of TEM, SHV and 545 CTX-M extended-spectrum beta-lactamases in Enterobacteriaceae using ligation-546 mediated amplification with microarray analysis. J Antimicrob Chemother 2010; 65: 547 1377-81. 548 55. Grimm V, Ezaki S, Susa M et al. Use of DNA microarrays for rapid genotyping 549 of TEM beta-lactamases that confer resistance. J Clin Microbiol 2004; 42: 3766-74. 550 56. Lee Y, Lee CS, Kim YJ et al. Development of DNA chip for the simultaneous 551 detection of various beta-lactam antibiotic-resistant genes. Mol Cells 2002; 14: 192-7. 552 57. Leinberger DM, Grimm V, Rubtsova M et al. Integrated detection of extended-553 spectrum-beta-lactam resistance by DNA microarray-based genotyping of TEM, SHV, 554 and CTX-M genes. J Clin Microbiol 2010; 48: 460-71. 555 58. Naas T, Cuzon G, Bogaerts P et al. Evaluation of a DNA microarray (Check-556 MDR CT102) for rapid detection of TEM, SHV, and CTX-M extended-spectrum beta-557 lactamases and of KPC, OXA-48, VIM, IMP, and NDM-1 carbapenemases. J Clin 558 Microbiol 2011; 49: 1608-13. 559 59. Naas T, Cuzon G, Truong H et al. Evaluation of a DNA microarray, the check-560 points ESBL/KPC array, for rapid detection of TEM, SHV, and CTX-M extended-561 spectrum beta-lactamases and KPC carbapenemases. Antimicrob Agents Chemother 562 2010; 54: 3086-92. 563 60. Peter H, Berggrav K, Thomas P et al. Direct detection and genotyping of 564 Klebsiella pneumoniae carbapenemases from urine by use of a new DNA microarray 565 test. J Clin Microbiol 2012; 50: 3990-8. 566 61. Choi J, Jung YG, Kim J et al. Rapid antibiotic susceptibility testing by tracking 567 single cell growth in a microfluidic agarose channel system. Lab Chip; 2013; 13: 280-7. 568 62. Mach KE, Mohan R, Baron EJ et al. A biosensor platform for rapid 569 antimicrobial susceptibility testing directly from clinical samples. J Urol; 185: 148-53. 570 63. Tang Y, Zhen L, Liu J et al. Rapid antibiotic susceptibility testing in a 571 microfluidic pH sensor. Anal Chem; 2013; 85: 2787-94. 572