Significant difference in drug susceptibility distribution between Mycobacterium avium

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JCM Accepts, published online ahead of print on 1 October 2014 J. Clin. Microbiol. doi:10.1128/jcm.02127-14 Copyright 2014, American Society for Microbiology. All Rights Reserved. 1 2 Significant difference in drug susceptibility distribution between Mycobacterium avium and Mycobacterium intracellulare. 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Aurélie Renvoisé 1,2,3, Christine Bernard 1,2,3, Nicolas Veziris 1,2,3, Eve Galati 1*, Vincent Jarlier 1,2,3, Jérôme Robert 1,2,3#. 1 AP-HP, Hôpital Pitié-Salpêtrière, Centre National de Référence des Mycobactéries et de la Résistance des Mycobactéries aux Antituberculeux, Bactériologie-Hygiène, Paris, France; 2 Sorbonne Universités, UPMC Univ Paris 06, U1135, Centre for Immunology and Microbial Infections, team 13, Paris, France; 3 INSERM, U1135, Centre for Immunology and Microbial Infections, team 13, Paris, France Running title: Differences in drug susceptibility distribution in MAC #Address correspondence to: jerome.robert0@upmc.fr *Present adress: laboratoire AMP, centre hospitalier de Dreux, Dreux, France Key words: M. avium, M. intracellulare, drug susceptibility distribution, clarithromycin, amikacin, susceptible. Abstract: Not applicable. 1

23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 Letter to the editor type new data Mycobacterium avium and Mycobacterium intracellulare are referred as the M. avium complex (MAC) (1) and are known as causative agents of opportunistic infections in humans (1-3). The first-line recommended treatment consists of a combination of either clarithromycin or azithromycin, rifampin, and ethambutol, the two latter drugs being considered as companion drugs to prevent the emergence of macrolide resistance (4);(5). Amikacin is an alternative to macrolides for the treatment of MAC lung cavitary disease or in case of macrolide resistance (6). To date, the treatment guidelines refer to MAC as a complex (4), but there is no clear data regarding the antibiotic susceptibility of each species separately. Therefore, we sought to delineate the susceptibility profiles of both species toward clarithromycin and amikacin (4;5). All clinically relevant MAC isolates sent to the French National Reference Centre for Mycobacteria between 2009 and 2011 were routinely identified by using line probe assays GenoType Mycobacterium CM/AS (Hain, Lifescience), as recommended by the manufacturer, leading to the identification of M. avium ssp. or M. intracellulare (7). After exclusion of duplicates, only isolates from patients with no history of previous antibiotic treatment were selected to be representative of a wild population. Minimal inhibitory concentrations (MICs) were determined by broth-microdilution method using Sensititre SLOMYCO (Biocentric) (8). The Kruskall-Wallis test was used for statistical comparisons. Epidemiological cut-off (ECOFF) values were determined as values larger than the modal MIC + 1 twofold-dilution (variability of the test) and including at least 95% of isolates. A total of 186 M. avium and 154 M. intracellulare were studied. The distributions of clarithromycin and amikacin MICs were unimodal for both species (Figure1). Clarithromycin MICs were lower for M. intracellulare than for M. avium isolates (MIC50: 2 mg/l versus 8 mg/l, respectively; p < 0.001) (Table1). The same observation can be made for amikacin 2

48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 MICs, although the difference was not as drastic (MIC50: 8 mg/l versus 16 mg/l, respectively; p < 0.001). Consequently, the tentative ECOFFs were slightly lower for M. intracellulare than for M. avium (Table1). Many studies report MAC as a single entity. Our results demonstrate that M. avium and M. intracellulare have different patterns of clarithromycin and amikacin susceptibility. Such a difference has been previously reported (9;10), but recent data considering both clarithromycin and standardized methods (recommended by CLSI (8)) were lacking at the time of these publications. Considering (i) that clarithromycin and amikacin MICs have been linked to treatment outcome (6;11), and (ii) higher MICs against M. avium, one could expect more therapeutic failures and a higher rate of selection of resistant mutants for this species if associated to a large mutant selection window (which remains to be determined). A limitation of the present study is, however, the use the line probe assays GenoType Mycobacterium CM/AS to identify M. avium and M. intracellulare. Other MAC species, such as M. chimaera, may have been misidentified as one of the two main species with this assay, although the impact on the results is likely to be limited because the other species are less frequently encountered (7;12). In fine, our results need to be further confirmed by definitive species identification method, such as sequencing. In conclusion, there are differences in antibiotic susceptibility among MAC species in terms of MIC50 and ECOFFs. Whether differences are clinically sound remains to be determined; indeed, there are not a wide variety of drugs and dosage options for the treatment of MAC infections, and the choice of the antibiotic regimen could be based on MICs determination despite definite species identification. On the opposite, these differences will be of interest in determining the correlation between in vitro results and clinical and bacteriological outcomes. 3

73 74 75 76 77 Acknowledgements. We are grateful to Stanley Pang for editing the manuscript and to Anton Granzhan for his help in preparing the manuscript. We have no conflict of interest to declare. This work was supported by annual grant of the Institut National de Veille Sanitaire to the French National Reference Center for Mycobacteria and antimycobacterial resistance. 78 Downloaded from http://jcm.asm.org/ on October 4, 2018 by guest 4

79 References 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 1. Esteban J, Garcia-Pedrazuela M, Munoz-Egea MC, Alcaide F. 2012 Current treatment of nontuberculous mycobacteriosis: an update. Expert Opin Pharmacother 13:967-986. 2. van Ingen J. 2013 Diagnosis of nontuberculous mycobacterial infections. Semin Respir Crit Care Med 34:103-109. 3. Dailloux M, Abalain ML, Laurain C, Lebrun L, Loos-Ayav C, Lozniewski A, Maugein J. 2006 Respiratory infections associated with nontuberculous mycobacteria in non-hiv patients. Eur Respir J 28:1211-1215. 4. Griffith DE, Aksamit T, Brown-Elliott BA, Catanzaro A, Daley C, Gordin F, Holland SM, Horsburgh R, Huitt G, Iademarco MF, Iseman M, Olivier K, Ruoss S, von Reyn CF, Wallace RJ, Jr., Winthrop K. 2007 An official ATS/IDSA statement: diagnosis, treatment, and prevention of nontuberculous mycobacterial diseases. Am J Respir Crit Care Med 175:367-416. 5. Brown-Elliott BA, Nash KA, Wallace RJ, Jr. 2012 Antimicrobial susceptibility testing, drug resistance mechanisms, and therapy of infections with nontuberculous mycobacteria. Clin Microbiol Rev 25:545-582. 97 98 6. Brown-Elliott BA, Iakhiaeva E, Griffith DE, Woods GL, Stout JE, Wolfe CR, Turenne CY, Wallace RJ, Jr. 2013 In vitro activity of amikacin against isolates 5

99 100 of Mycobacterium avium complex with proposed MIC breakpoints and finding of a 16S rrna gene mutation in treated isolates. J Clin Microbiol 51:3389-3394. 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 7. Russo C, Tortoli E, Menichella D. 2006 Evaluation of the new GenoType Mycobacterium assay for identification of mycobacterial species. J Clin Microbiol 44:334-339. 8. Woods GL, Brown-Elliott BA, Conville PS, Desmond EP, Hall GS, Lin G, Pfyffer GE, Ridderhof JC, Siddiqi SH, Wallace RJJ, Warren N, Witebsky F. 2011 Susceptibility Testing of Mycobacteria, Nocardiae, and Other Aerobic Actinomycetes; Approved Standard Second Edition. 9. Saito H, Tomioka H, Sato K, Tasaka H, Tsukamura M, Kuze F, Asano K. 1989 Identification and partial characterization of Mycobacterium avium and Mycobacterium intracellulare by using DNA probes. J Clin Microbiol 27:994-997. 10. Hombach M, Somoskovi A, Homke R, Ritter C, Bottger EC. 2013 Drug susceptibility distributions in slowly growing non-tuberculous mycobacteria using MGIT 960 TB exist. Int J Med Microbiol 303:270-276. 11. Kobashi Y, Abe M, Mouri K, Obase Y, Kato S, Oka M. 2012 Relationship between clinical efficacy for pulmonary MAC and drug-sensitivity test for isolated MAC in a recent 6-year period. J Infect Chemother 18:436-443. 6

118 119 120 12. Tortoli E, Pecorari M, Fabio G, Messino M, Fabio A. 2010 Commercial DNA probes for mycobacteria incorrectly identify a number of less frequently encountered species. J Clin Microbiol 48:307-310. 121 122 123 Downloaded from http://jcm.asm.org/ on October 4, 2018 by guest 7

124 125 126 Figure legend. Figure 1. MIC distribution for clarithromycin (a) and amikacin (b) in M. avium and M. intracellulare, and box plots of MIC distribution (c). 127 8

128 Table 1. Statistical analysis of MIC values for clarithromycin and amikacin in MAC. Clarithromycin Amikacin MIC value (mg/l) M. avium M. intracellulare M. avium M. intracellulare (n = 186) (n = 154) (n = 186) (n = 154) 129 Modal 8 2 16 8 MIC50 8 2 16 8 MIC90 16 4 16 16 Geometric mean 6.7 1.7 10.7 7.4 Range 1-16 0.25-16 2-32 2-32 ECOFF 16 8 32 16 Downloaded from http://jcm.asm.org/ on October 4, 2018 by guest 9

Figure 1. MIC distribution for clarithromycin (a) and amikacin (b) in M. avium and M. intracellulare, and box plots of MIC distribution (c).