The Antibiotic-Resistance Arrow of Time: Efflux Pump Induction is a General First Step in the ...

39 Pages·2012·5.19 MB·English

AAC Accepts, published online ahead of print on 2 July 2012
Antimicrob. Agents Chemother. doi:10.1128/AAC.05546-11
Copyright © 2012, American Society for Microbiology. All Rights Reserved.
1 The Antibiotic-Resistance Arrow of Time: Efflux Pump Induction is a General First Step
2 in the Evolution of Mycobacterial Drug-Resistance
3 Aurelia M. Schmalstieg1¥, Shashikant Srivastava1¥, Serkan Belkaya2, Devyani Deshpande1,
4 Claudia Meek3, Richard Leff3, Nicolai S.C. van Oers2,4, Tawanda Gumbo1,5*
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5 1Department of Medicine and 2Department of Immunology, UT Southwestern Medical Center, o
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6 3School of Pharmacy, Texas Tech University Health Sciences Center, and Department of lo
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7 Microbiology and 5Office of Global Health, UT Southwestern Medical Center, Dallas, Texas e
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8 ¥Contributed equally. o
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9 Corresponding Author: Tawanda Gumbo, MD tp
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10 Office of Global Health a
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11 UT Southwestern Medical Center s
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12 5323 Harry Hines Blvd r
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13 Dallas, Texas 75390-8507 o
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14 E-mail: [email protected] p
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15 Phone: [phone]
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18 Running title: Efflux pumps as a first step to high-level resistance u
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20 Word count: Abstract-231; Text-4,144
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24 ABSTRACT.
25 We hypothesize that low-level efflux pump expression is a first step in the development of high
26 level drug-resistance in mycobacteria. We performed a 28 day azithromycin dose-effect and
27 dose-scheduling studies in our hollow fiber model of disseminated Mycobacterium avium-
28 intracellulare complex. Both microbial kill and resistance emergence were most closely linked
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29 to the within-macrophage area under the concentration-time curve to MIC (AUC/MIC) ratio. w
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30 Quantitative PCR revealed that sub-therapeutic azithromycin exposures over 3 days led to a 56- a
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31 fold increase in expression of MAV_3306, which encodes a putative ABC transporter, and d

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32 MAV_1406, which encodes a putative major facilitator superfamily pump, in M. avium. By day m

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33 7, a sub-population of M. avium with low-level resistance was encountered and exhibited the tt
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34 classic inverted “U’ curve versus AUC/MIC ratios. The resistance was abolished by an efflux a
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35 pump inhibitor. While maximal microbial kill started to decrease after day 7, a population with a
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36 high-level azithromycin resistance appeared at day 28. This resistance could not be reversed by .o
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37 efflux pump inhibitors. Orthologs of pumps encoded by MAV_3306 and MAV_1406 were o
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38 identified in Mycobacterium tuberculosis, Mycobacterium leprae, Mycobacterium marinum, p
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39 Mycobacterium abscessus, and Mycobacterium ulcerans. All had highly conserved protein 1
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40 secondary structures. We propose that induction of several efflux pumps is the first step in a 0
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41 general pathway to drug resistance that eventually leads to high-level chromosomal mutation b
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42 related resistance in mycobacteria as ordered events in an “antibiotic resistance arrow of time.” u
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46 While many mycobacteria cause human disease, Mycobacterium tuberculosis complex
47 (Mtb), Mycobacterium avium-intracellulare complex (MAC), Mycobacterium ulcerans, and
48 Mycobacterium leprae are by far the most important pathogens in global health. Mycobacterial
49 diseases are difficult to treat, and resistance emergence is a major challenge. The standard belief
50 has been that drug resistance arises sequentially based on stepwise development of chromosomal
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51 mutations (19). In addition, resistance is often said to have “emerged” in mycobacteria at some w
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52 arbitrary time point, usually synonymous with development of chromosomal mutations a
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53 associated with drug resistance or achievement of the 1% threshold of the total population d

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54 (6,7,37). Efflux pump induction is increasingly being considered as an important mechanism of m

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55 resistance in many bacteria, including in Mtb (9,26,31,32,34). We recently demonstrated for Mtb tp
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56 that efflux pumps were a first step that allowed for the development of high-level ethambutol a
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57 resistance (41,45). We hypothesized that this could be a general pathway in the development of s
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58 drug-resistance in other pathogenic mycobacteria. Here, we investigated if this were true using o
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59 azithromycin treatment in a model of disseminated MAC (12, 13). o
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60 MAC infection often presents as either pulmonary disease or disseminated disease. p
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61 Disseminated MAC is an important AIDS defining illness (27). While interest in this disease has 1
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62 waned in the era of anti-retroviral therapy, many of our own patients still present with this 0
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63 potentially fatal disease when AIDS is first diagnosed (11). Therapy consists of at least two b
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64 drugs, a macrolide such as azithromycin or clarithromycin in combination with ethambutol, for a u
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65 duration of at least a year (21,27). Immune reconstitution due to anti-retroviral therapy is the t
66 essential therapeutic event that leads to stopping therapy. On the other hand, disseminated MAC
67 continues to be a problem in non-AIDS patients with more intractable immunodeficiency such as
68 post-transplant patients and those on chronic immunosuppressive therapy (24,25). In these
69 patients, there is no obvious end point for when therapy should be stopped. Efficacy in these
70 patients could be improved by pharmacokinetic-pharmacodynamic (PK/PD) based dosing.
71 Therapy outcomes for disseminated MAC depend on macrolide susceptibility at the start
72 of therapy, while patients also fail therapy if resistance to macrolides develops during the therapy
73 (4,20). Resistance is due to mutations in the peptidyltransferase region of the 23S ribosomal
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74 RNA gene (35,36,40). We were interested in examining the role of efflux pumps in MAC’s w
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75 resistance to azithromycin for several reasons. First, our studies with Mtb from which we a
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76 identified the role of low-level resistance efflux pumps were based on standard anti-TB agents d

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77 such as ethambutol and isoniazid. Second, in disseminated MAC the bacteria reside inside cells m

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78 of the reticuloendothelial system (47,48), as opposed to Mtb in active pulmonary TB is tp
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79 predominantly extracellular (16). We wanted to determine if efflux pumps would play the same a
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80 role in the intracellular milieu. Third, macrolide-resistance is a crucial determinant of therapy s
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81 failure in disseminated MAC. Strategies to suppress macrolide resistance emergence could lead o
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82 to more effective treatments. Fourth, due to ease of cultivation compared to other mycobacteria o
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83 such as M. ulcerans and M. leprae, and the lack of requirement of a BSL-3 laboratory, MAC is p
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84 an attractive model to study the molecular events associated with emergence of drug resistance in 1
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85 mycobacterial response to different PK/PD exposures. 0
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86 b
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87 METHODS. u
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88 Bacterial isolate. We utilized M. avium subspecies hominissuis (ATCC # 700898) for all
89 our studies. Stock cultures were stored in Middlebrook 7H9 broth and 10% glycerol at -80°C.
90 Prior to each experiment we thawed the bacterial stock and incubated it in a water bath under
91 shaking conditions at 37°C in Middlebrook 7H9 broth with 10% oleic acid-albumin-dextrose-
92 catalase for 4 days. Azithromycin MIC was performed based on two methods, each performed
93 twice: E-test (AB Biodisk) and an agar dilution test (7).
94 Materials. Azithromycin was purchased from UT Southwestern Medical Center
95 Pharmacy. Thioridazine was purchased from SIGMA. Azithromycin and thioridazine were
96 dissolved in water, sterile filtered, and then diluted to the desired concentration in sterile water.
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97 Thioridazine was shielded from direct light in all experiments. Hollow fiber cartridges were w
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98 purchased from FiberCell (Frederick, MD). a
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99 Hollow fiber system (HFS) studies of disseminated MAC. The hollow fiber has been fr
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100 used as a model study bacteria-antibiotic interaction since around 1985; we adapted it for use in
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101 Mtb and intracellular MAC (5,12,13,22,23). The hollow fiber model of disseminated MAC has :
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102 been described in detail in the past (12,13). THP-1 macrophages (ATCC# TIB-202) were c
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103 cultured in RPMI 1640 containing 10% FBS. The cells were infected overnight with MAC at a m
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104 bacteria-to-macrophage ratio of 10:1. The macrophages were then centrifuged, extracellular rg
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105 bacteria washed away and the cells inoculated into the peripheral compartments of HFS. This n

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106 system comprises a circulating system containing RPMI 1640 supplemental with 2% FBS. ril
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107 Dose ranging studies were performed to achieve concentration-time profiles similar to 2
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108 those achieved in patients treated with azithromycin doses between 250 mg and 16,000 mg a day 9

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109 (every 24hrs) for 28 days (29,33). The peripheral compartment of each system was sampled on g
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110 days 4, 7, 10, 14, 21, and 28 for macrophage count and for culture. Macrophages were separated st
111 from media by centrifugation, and then ruptured to release MAC for culture on Middlebrook
112 7H10 agar, as described before (12,13). MAC cultures on Middlebrook agar were used to
113 calculate the total bacillary population, as described before (12,13). To enumerate the low-level
114 azithromycin resistant sub-population the agar was supplemented with 3 times the MIC of
115 azithromycin. For high-level resistance the agar was supplemented with 256 mg/L azithromycin,
116 which is the standard critical concentration on Middlebrook 7H10 agar (7). In order to
117 demonstrate the effect of efflux pumps, the same samples were cultured on agar that had been
118 further supplemented with efflux pump inhibitor, thioridazine at a concentration of 1 mg/L. This
119 concentration of thioridazine does not kill MAC and does not change azithromycin MIC, based
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120 on preliminary studies. For pharmacokinetic studies, samples were drawn from both the central w
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121 and peripheral compartments of each HFS after day 28 at 0, 0.5, 1.5, 2, 4, 8, 12, and 24hrs post a
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122 dose. Macrophage counts and volumes were determined as described below. Media and d

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123 macrophages were separated using methods described before (12,13). The relationship between m

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124 bacterial burden and drug concentration was examined using the inhibitory sigmoid Emax model tp
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125 in GraphPad Prism 5 software. a
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126 Dose-scheduling studies were performed with HFS treated with azithromycin for a total s
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127 of 28 days. Azithromycin exposures such as the concentration associated with 20% of maximal o
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128 kill (EC20), 50% of maximal kill (EC50), and 80% of maximal kill (EC80), based on the inhibitory on

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129 sigmoid Emax model for dose-effect studies were administered to HFSs. Each of these exposures p
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130 was administered as one of three dosing schedules: the entire cumulative 1 week exposure once a 1
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131 week, or split into two and administered every 3.5 days, or split into 7 and administered daily. 0
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132 Macrophage counts and MAC cultures were examined on days 3, 7, 14, 21, and 28 for total b
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133 bacterial burden as well as azithromycin-resistant subpopulations. u
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134 Measurement of azithromycin concentrations and pharmacokinetic analysis. t
135 Azithromycin concentration was measured using a Shimadzu HPLC system interfaced with a
136 tandem, triple-quadrupole mass spectrometer (AB Sciex, API 3000). Samples (100 µL),
137 carbonate buffer pH=9.5 (300µL) and internal standard (roxithromycin, 30 µL) were extracted
138 using 3.5 mL hexane:ethyl acetate (50:50). The organic phase was separated, evaporated, and
139 reconstituted with 100 µL of mobile phase for injection. Following injection (10 µL),
140 chromatographic separation was performed using a Sunrise C18 3.5 µ (5 cm x 2.1 mm) column,
141 isocratic elution using a mixture of 0.6 mL of glacial acetic acid, 1.54 gm of ammonium acetate,
142 250 mL of water, 570 mL of acetonitrile, and 180 mL of methanol at 0.2 mL/min, at room
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143 temperature. Azithromycin and internal standard were analyzed using positive electrospray w
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144 ionization combined with multiple reaction monitoring. Quantitation using the a
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145 precursor→product ion combinations of 749.50→591.4 and 838.50→680.50 m/z resulted with 5 d

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146 minute run time. A liquid-liquid extraction technique was adopted for sample preparation; the m

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147 observed recovery of azithromycin was 98%. The standard curve was linear (r=0.9987) and tp
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148 ranged from 1 ng/mL to 1,000 ng/mL. The limits of quantitation were 1 ng/mL. Intra-day and a
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149 inter-day precision were equivalent and was less than 5% RSD throughout the validated range of s
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150 concentrations. o
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151 In order to calculate the azithromycin concentration per macrophage, the concentration of o
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152 azithromycin per mL was divided by the number of macrophages in each mL in each HFS. p
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153 Macrophage volumes were determined using a Coulter counter. The azithromycin concentration 1
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154 in macrophages was then calculated as the concentration per macrophage divided by the average 0
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155 volume of each infected macrophage. This calculation does not account for possible leakage of b
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156 azithromycin out of the macrophages and may thus underestimate the intracellular concentration. u
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157 Pharmacokinetic modeling was performed using ADAPT 5 software (8). Azithromycin t
158 concentrations from central compartment were modeled as a one compartment model with first-
159 order input and elimination. Intra-macrophage pharmacokinetics were modeled as a one
160 compartment model and as a two compartment model with the best model chosen using Akaike’s
161 information criteria (2).
162 Induction of efflux pump encoding genes early during therapy.
163 Macrolide efflux as a resistance mechanism has been well described in such gram
164 positive pathogens as Staphylococcus aureus and Streptococcus pneumoniae. These include D
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165 msrA in S. aureus encoded by SAV1361, the S. pneumoniae mel protein encoded by SPR1021, n
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166 and the S. pneumoniae mefE encoded by SPR0971; as well as several genes in antibiotic d
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167 producing Streptomyces species which encode for efflux pumps against the antibiotics they fr
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168 secrete (9,10,17,18,28,44,49). We hypothesized that orthologs of these genes to known
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169 macrolide efflux pumps in MAC would also be induced by macrolides. Candidate orthologs were :
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170 chosen by use of Kyoto Encyclopedia of Genes and Genomes (KEGG) bioinformatics resource c
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171 at www.genome.jp/kegg. Three MAC macrolide efflux pump candidate genes were chosen and m
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172 were MAV_1406, MAV_3306, and MAV_1695. We were interested in performing quantitative rg
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173 real time polymerase chain reactions to demonstrate that at least one of these genes was n

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174 upregulated early in response to azithromycin, prior to the first time point when phenotypic ril
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175 resistance was demonstrated via reversal of low-level resistance by efflux pump inhibitors. ,

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176 MAC cultures on day 4 of log-phase growth were adjusted to a bacterial density of 8.7 1
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177 log10 CFU/mL suspension in Middlebrook 7H9 broth with 10% OADC and were treated with 16 y
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178 mg/L azithromycin (i.e., ½ MIC) or saline (sham) in triplicate, and incubated at 37°C under 5% e
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179 CO2. We chose this approach instead of intracellular MAC in the HFS to demonstrate that the
180 efflux pump induction is independent of the role of macrophages and the immune system. At 0,
181 1, 24, 48, and 72hrs, the cultures were divided into two portions for either determination of
182 CFU/mL or for RNA extraction. In order to enumerate the bacillary burden at each time point,
183 cultures were washed, serially diluted, and then cultured on Middlebrook agar at 37°C under 5%
184 CO2. RNA extraction was performed using the RNeasy Mini kit (Qiagen), per the manufacturer’s
185 protocol. Column purified RNA was treated with Turbo DNase (Ambion) for 30 minutes at 37°C
186 according to the manufacturers’ recommendations. Quality and quantity of the RNA was
187 measured using NanoDrop. One hundred nanograms of RNA was reverse transcribed into cDNA
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188 with the BluePrint Reverse Transcription Kit (Takara Bio Inc., Japan) by incubating the reaction w
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189 mixture at 30°C for 10 min followed by incubation at 42°C for 15 min and 70°C for 5 min. a
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190 Custom primers and TaqMan probes (5’-6-FAM reporter and 3’-TAMRA quencher) for putative d

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191 MAC efflux pump genes were designed using the real-time primer designing tool available m

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192 online from GeneScript and Integrated DNA Technologies; the list of probes and primers we tp
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193 designed and used are shown in Table 1. Real-time PCR was performed using 5 ng cDNA and a
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194 2X TaqMan Universal Master Mix II (no UNG) on an ABI 7300 series PCR machine (Applied s
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195 Biosystems, Carlsbad, CA), following the manufacturers’ instructions. The final concentration of o
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196 primers and probes in the reaction mixture was 900 nM and 250 nM, respectively. The real-time o
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197 cycling parameters were: 1 cycle at 95°C for 10 min followed by 40 cycles of 95°C for 15 sec p
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198 and 60°C for 1 min. All reactions were performed in triplicate, and repeated at least three times. 1
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199 Relative expression of the each gene in each replicate at each time point was calculated the by 0
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200 the comparative threshold method (∆∆CT) with the GroEL gene as the endogenous control. b
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201 We were also interested in demonstrating that other important pathogenic mycobacteria e
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202 contained similar systems to MAC, making it likely that our findings would apply to other
203 mycobacteria. Genes for putative MAC efflux pumps that demonstrated at least two fold
204 induction were then chosen. We searched for orthologs in Mtb H37Rv, M. bovis, M. leprae, M.
205 marinum. M. ulcerans, and M. abscessus, important global health pathogens. Mycobacterium
206 avium subspecies paratuberculosis (M. paratuberculosis), which causes Johnne’s disease in
207 animals, and has been implicated as playing a role in Crohn’s disease (38), was also examined.
208 Ortholgs were chosen by use of the KEGG bioinformatics resource. The predicted secondary
209 protein structures of the orthologs were then compared to those of the MAC proteins by use of
210 the CLC Protein workbench version 5.8.1 (CLC bio, Cambridge, MA).
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211 n
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212 RESULTS. e
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213 Azithromycin MIC was 32 mg/L, similar to the MIC90 of clinical isolates from patients om

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214 with disseminated MAC (15). Azithromycin mean pharmacokinetic parameter estimates (±SD) t
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215 for the central compartment were a total clearance of 24.1±2.41 L/h and a volume of 290±41.7L. /a
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216 However, when the concentrations of azithromycin achieved in the central compartment were .a
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217 related to the MIC, as shown in table 2, the exposures achieved with each dose rarely exceeded .
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218 the MIC except at very high doses such as those equivalent to16,000 mg a day in patients. /
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219 However, the concentrations of azithromycin achieved within macrophages were several A
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220 thousand-fold higher than in the central or peripheral compartment (figure 1). Figure 1 il
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221 demonstrates that the ratio of the intracellular to extracellular concentrations varied with time, 2
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222 and drifted down 3.9 fold from the start of the dosing interval until the 4hr time point, after 9

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223 which the ratios remained stable. Thus the relationship between intracellular and extracellular g
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224 azithromycin concentration was non-linear. The azithromycin pharmacokinetics within the st
225 macrophages were best described by a two compartment model with an absorption rate constant
226 of 3.18±3.83/hr, a mean total clearance of 0.0012±0.0007 L/hr, volume of central compartment
227 of 0.00004+0.00007 L, an inter-compartmental clearance of 18.53±23.62 L/h, and a relatively
228 larger volume of peripheral compartment of 0.02±0.01 L. Thus the azithromycin clearance from