Dissemination of Aminoglycoside-Modifying Enzymes and 16S rRNA Methylases Among Acinetobacter baumannii and Pseudomonas aeruginosa Isolates

Abstract

Aims: The purpose of the present study was to investigate the diversity of the genes encoding aminoglycoside-modifying enzymes (AMEs) and their associations with resistance phenotypes and clonality in Acinetobacter baumannii and Pseudomonas aeruginosa isolates. Methods: Seventy six P. aeruginosa and 75 A. baumannii isolates were collected from three University affiliated hospitals in Tehran. MIC determination of amikacin and gentamicin as well as the disk diffusion method for tobramycin, netilmicin, and kanamycin were carried out. Nine AMEs genes and three RNA methylases were investigated in all isolates using the PCR method. Clonality for A. baumannii and P. aeruginosa was investigated using repetitive extragenic palindromic and enterobacterial repetitive intergenic consensus PCR, respectively. Results: aph(3′)-VIa (90.6%) and aph(3′)-IIb (61.8%) were the most prevalent AME genes in A. baumannii and P. aeruginosa, respectively. Eight (26%) amikacin highly resistant A. baumannii isolates were positive for armA methylase. Phenotypes and clonality did not link to the genetic determinants of resistance to aminoglycosides in our isolates. Conclusions: AMEs genes are disseminated in different clones of A. baumannii and P. aeruginosa isolates in Iran. Other than AMEs, there are more complex and multifactorial mechanisms that result in aminoglycoside-resistant phenotypes.

Introduction

Aminoglycoside antibiotics are widely used in clinical settings, especially for the treatment of life-threatening infections caused by nonfermenter bacteria such as Pseudomonas aeruginosa and Acinetobacter baumannii.²³ Unfortunately, their efficacy has been reduced by the surge and dissemination of resistance.¹⁶ Resistance to aminoglycosides has been attributed mainly to enzymatic inactivation by aminoglycoside-modifying enzymes (AMEs) classified into acetyltransferases (AACs), nucleotidyltranferases, and phosphotransferases (APHs). A. baumannii and P. aeruginosa strains often contain multiple enzymes of these classes.¹⁵ More recently, 16S rRNA methylase genes have been reported among these species.^4,10 AMEs differ in aminoglycosides modified, whereas 16s rRNA methylases confer a high level of resistance to all formulated aminoglycosides. The distribution of AME genes is largely dependent on bacterial species, but the combination of AMEs is correlated with the use of aminoglycosides in specific geographic regions.⁴ So far, there are just some limited reports about the distribution of AME genes in A. baumannii and P. aeruginosa isolates from Iran.^20,2 To the best of our knowledge, our study is the first report of armA methylase from our country.

In this study, we aimed to first determine antimicrobial susceptibility patterns of A. baumannii and P. aeruginosa against aminoglycosides, second, to characterize the genetic determinants involved in enzymatic inactivation of this class of antibiotics, and third, to analyze the homology of the isolates by repetitive extragenic palindromic (REP) and enterobacterial repetitive intergenic consensus (ERIC)-PCR for typing of A. baumannii and P. aeruginosa isolates, respectively.

Materials and Methods

Bacterial isolates

A total of 250 nonfermenter bacterial isolates were collected during November 2010 through June 2011 from three University affiliated hospitals. Based on conventional biochemical tests, 151 nonrepetitive isolates were identified as 76 P. aeruginosa and 75 Acinetobacter spp. Twenty nine isolates of P. aeruginosa recovered from the sputum of the cystic fibrosis patients admitted to the Children Medical Center and the other 47 isolates were collected from hospitalized patients in the Level I burn care center at the same time. All burn isolates were recovered from burn wound infections. Forty three Acinetobacter spp. isolates were collected from burn patients and the other 32 obtained from different patients hospitalized in various wards, including ICU, medicine, surgery, neurology, and a pediatric unit. These isolates were cultured from tracheal aspirates (n=17), urine (n=7), wound (n=1), ENT (n=1), blood (n=1), and sputum (n=5). Genomic species of Acinetobacter spp. were confirmed by Amplified Ribosomal DNA Restriction Analysis (ARDRA).¹⁹ ARDRA profiles were interpreted according to the previously published scheme.⁸ A. baumannii ATCC 19606 was used as a reference strain in the ARDRA method. Isolates were then identified by species-specific PCR for the bla _OXA-51-like gene, which is an intrinsic β-lactamase in A. baumannii.¹⁸

Ethics standards

Ethics approval to perform the study was obtained from the institutional review board of Tabriz University of Medical Sciences. Written informed consent was obtained from all patients included in the study.

Antimicrobial susceptibility testing

The disk diffusion method was employed to determine the susceptibility of isolates to tobramycin, kanamycin, and netilmicin (MAST). MICs for gentamicin and amikacin were determined using the E-test method (AB Biodisk). Susceptibility breakpoints were defined according to Clinical and Laboratory Standards Institute guidelines.⁵

Isolates showing intermediate levels of susceptibility were classified as nonsusceptible. P. aeruginosa ATCC 27853 and Escherichia coli ATCC 25922 were used as control strains for susceptibility testing.

REP-PCR analysis for A. baumannii isolates

The primer pair REP1 (5′-IIIGCGCCGICATCAGGC-3′) and REP2 (5′-ACGTCTTATCAGGCCTAC-3′) was used to amplify putative REP-like elements in the genomic bacterial chromosomes according to the previous reports.³ Amplification reactions were carried out in a Master gradient thermal cycler (Eppendorf), with an initial denaturation (10 min at 94°C), followed by 30 cycles of denaturation (1 min at 94°C), annealing (1 min at 45°C), and extension (2 min at 72°C), with a single final extension of 16 min at 72°C. Amplified products were subjected to electrophoresis. Strains belonging to the same type showed identical profiles or highly similar profiles (up to two bands difference).

ERIC-PCR analysis for P. aeruginosa isolates

ERIC-PCR was carried out using the primer sequence ERIC-2 (5′-AAGTAAGTGACTGGGGTGAGCG-3′) as described previously.²¹ The following cycling conditions were used: 5 min at 94°C for initial denaturation; 4 cycles of 1 min at 94°C, 2 min at 26°C, and 1 min at 72°C; and then a final extension for 10 min at 72°C.

Screening of AME genes

Chromosomal DNA suitable for PCR amplification was extracted by the Cetyl Trimethyl Ammonium Bromide method as described previously.⁷ PCR experiments were carried out using primers specific for the armA, rmtA, rmtB, aph(3′)-IIb, aph(3′)-VIa, aph(3′)-Ia, aac(6′)-Ib, aac(3′)-Ia, aac(3′)-IIa, ant(4′)-IIb, ant(3′′)-Ia, and ant(2′′)-Ia genes as described previously (Table 1). Among these, rmtA, aph(3′′)-IIb, and ant(4′)-IIb primers were used only for P. aeruginosa isolates. Some of the PCR products obtained from AME-producing isolates were randomly selected, purified, and then sequenced to confirm the presence of genes.

Table 1.

Primers for Amplification of Genes

Gene	Forward sequence (5′-3′)	Reverse sequence (5′-3′)	Amplicon size (bp)	Reference
armA	TGCATCAAATATGGGGGTCT	GGATTGAAGCCACAACCAAA	214	1
rmtA	CTAGCGTCCATCCTTTCCTC	TTTGCTTCCATCCCCTTGCC	635	9
rmtB	CCCAAACAGACCGTAGAGGC	CTCAAACTCGGCGGGCAAGC	585	9
aph(3′)-Ia	CGAGCATCAAATGAAACTGC	GCGTTGCCAATGATGTTACAG	624	9
aph(3′)-IIb	ATGCATGATGCAGCCACCTCCAT	CCTACTCTAGAAGAACTCGTCCA	813	13
aph(3′)-Via	ATGGAATTGCCCAATATTATTC	TCAATTCAATTCATCAAGTTTTA	736	11
aac(3′)-Ia	ATGGGCATCATTCGCACATGTAGG	TTAGGTGGCGGTACTTGGGTC	421	11
aac(3′)-IIa	ATGCATACGCGGAAGGCAATAAC	CTAACCGGAAGGCTCGCAAG	719	11
aac(6′)-Ib	GAGTGGGGCGGAGAAGA	CCCAAGCCTTTGCCCAGTTG	245	13
ant(2′′)-Ia	ATGGACACAACGCAGGTCGC	TTAGGCCGCATATCGCGACC	495	11
ant(3′′)-Ia	ATGAGGGAAGCGGTGATCG	TTATTTGCCGACTACCTTGGT	624	11
ant(4′)-IIb	TTACCGCACCTGGATAGAGC	GATGGGGATCAACAATGTCG	340	13

Statistical methods

The χ² test was used to examine the association of aminoglycoside resistance with genes encoding AMEs. The statistical test was performed with the SPSS program (version 16.0; SPSS, Inc.). A p value of<0.05 was considered statistically significant.

Results

A. baumannii isolates

All 75 Acinetobacter spp. were positive for the bla _OXA-51-like gene and also showed the same restriction patterns of A. baumannii ATCC 19606. Among all aminoglycosides tested, netilmicin showed the highest susceptibility rate (38.7%) followed by tobramycin (30.7%), amikacin (18.6%), gentamicin (8.0%), and kanamycin (6.7%).

Among A. baumannii isolates which were resistant to at least one of the studied aminoglycosides, one or more AME genes were detected. As shown in Table 2, the most common AME gene was aph(3′)-VIa (68 strains) followed by ant(2′′)-Ia (40 strains), aac(3′)-Ia (24 strains), ant(3′′)-Ia (13 isolates), aph(3′)-Ia (13 isolates), and aac(6′)-Ib (6 isolates). Isolates were negative for aac(3′)-IIa and rmtB genes in our isolates. We found the armA gene in only eight isolates, which all had amikacin MIC of ≥256 μg/ml. Among isolates which were resistant to at least one of the studied aminoglycosides, 13 (17.3%) isolates had one AME gene, 34 (45.3%) isolates had two AME genes, 17 (22.6%) isolates had three AME genes, 4 (5.3%) isolates had four genes, and 3 (4.0%) isolates had five genes. Four (5.3%) susceptible isolates were negative for any type of the studied AME genes. The aph(3′)-VIa gene had statistically significant association with amikacin, gentamicin, and kanamycin resistance individually (χ² test, p≤0.02). The association between ant(2′′)-Ia and gentamicin or tobramycin was also significant (p≤0.01). Aminoglycoside-resistant genotypes matched their phenotypes in 55 of 55 isolates (100%) for gentamicin, 58 of 68 isolates (85.2%) for amikacin, 35 of 41 isolates (85.3%) for tobramycin, 47 of 47 isolates (100%) for kanamycin, and 1 of 6 isolates (16.6%) for netilmicin. Susceptibility was retained in the presence of at least one AME gene in 0 isolates for gentamicin, 10 (14.9%) isolates for amikacin, 6 (14.6%) isolates for tobramycin, 0 isolates for kanamycin, and 5 (83.3%) isolates for netilmicin. However, the AME genotypes to all five aminoglycosides matched the predicted phenotype in only 8 (10.6%) isolates.

Table 2.

Frequency of AME Genotypes According to Their Predicted Substrates Specificity and the Results of Susceptibility Testing in 75 Acinetobacter baumannii Isolates

Genotype	Substrate	MIC (μg/ml)							T^c(n)		N^d(n)		K^e(n)^f
			4	16	32	64	128	256	S^g	NS^h	S	NS	S	NS
aph(3′)-VIa+aac(3)-Ia	A, G	A^a	1	3	3	−	1	4	7	5	4	8	0	12
		G^b	−	6	3	−	−	3
aph(3′)-VIa+aac(3)-Ia+ant(3′′)-Ia+ant(2′′)-Ia	A, G, T, K	A	−	1	1	−	−	1	1	2	0	3	0	3
		G	−	−	−	−	1	2
ph(3′)-VIa+ant(2′′)-Ia	A, G, T, K	A	−	2	1	3	6	7	1	18	6	13	0	19
		G	−	−	1	−	−	18
aph(3′)-VIa+ant(2′′)-Ia+aac(3)-Ia	A, G, T, K	A	−	−	2	−	−	1	1	2	2	1	0	3
		G	−	−	1	−	2	−
aph(3′)-VIa+ant(3′′)-Ia+ant(2′′)-Ia	A, G, T, K	A	−	1	2	−	1	−	0	4	1	3	0	4
		G	−	−	−	−	1	3
aac(6′)-Ib+aph(3′)-VIa+aac(3)-Ia	A, G, T, N	A	−	−	1	−	−	−	0	1	0	1	0	1
		G	−	−	1	−	−	−
aph(3′)-Ia+aph(3′)-VIa+ant(3′′)-Ia+ant(2′′)-Ia+aac(3′)-Ia	A, G, T, K	A	−	−	−	1	1	−	1	1	0	2	0	2
		G	−	−	−	1	−	1
aph(3′)-Via	A	A	1	−	−	−	3	6	4	6	2	8	1	9
		G	2	1	1	1	1	4
aph(3′)-Ia+aph(3′)-VIa+ant(3′′)-Ia+ant(2′′)-Ia	A, G, T, K	A	−	−	−	−	−	1	1	0	0	1	0	1
	G	−	1	−	−	−	−
ant(2′′)-Ia	G, T, K	A	−	−	−	−	1	−	0	1	1	0	0	1
		G	−	−	−	−	−	1
aph(3′)-Ia+aph(3′)-VIa	A, K	A	−	−	−	−	1	1	0	2	0	2	0	2
		G	−	−	−	−	1	1
aph(3′)-VIa+ant(3′′)-Ia+aac(3′)-Ia	A, G	A	−	−	1	−	−	−	1	0	1	0	0	1
		G	−	−	1	−	−	−
aph(3′)-Ia+aph(3′)-VIa+aac(3′)-Ia	A, G, K	A	−	1	1	−	−	−	1	1	0	2	0	2
		G	−	1	1	−	−	−
aac(6′)-Ib+aph(3′)-VIa+ant(2′′)-Ia	A, G, T, K, N	A	−	−	−	1	−	2	0	3	3	0	0	3
		G	−	−	−	−	−	3
aph(3′)-Ia+aph(3′)-VIa+aac(6′)-Ib+ant(3′′)-Ia+ant(2′′)-Ia	A, G, T, K, N	A	−	−	1	−	−	−	0	1	1	0	0	1
		G	−	−	−	−	−	1
aph(3′′)-VIa+ant(3′′)-Ia	A	A	−	−	−	−	1	−	0	1	1	0	0	1
		G	−	−	−	−	1	−
aph(3′)-Ia+aph(3′)-VIa+ant(2′′)-Ia	A, G, T, K	A	−	−	−	−	2	−	1	1	2	0	0	2
		G	−	−	1	−	−	1
aph(3′)-Ia	K	A	−	−	−	−	−	2	0	2	0	2	0	2
		G	−	−	−	−	−	2
aph(3′)-Ia+aac(6′)-Ib+aph(3′)-Via	A, T, K, N	A	−	−	−	−	−	1	0	1	1	0	0	1
		G	−	−	−	−	−	1
None present	−	A	4						4	0	4	0	4	0
		G	4

A, amikacin; ^bG, gentamicin; ^cT, tobramycin; ^dN, netilmicin; ^eK, kanamycin; ^fn, number of isolate; ^gS, susceptible; ^hNS, nonsusceptible.

AME, aminoglycoside-modifying enzymes.

The distribution of some AMEs between burn and nonburn isolates were different that we found significant differences in aac(3′)-Ia, ant(2′′)-Ia, ant(3′′)-Ia, and armA (p≤0.05) (see Table 3).

Table 3.

Frequency of AMEs According to Their Source of Infections Among A. baumannii Isolates

A. Baumannii
Sample (n)	armA	aph(3′)-Ia	aph(3′)-VIa	ant(3′′)-Ia	ant(2′′)-Ia	aac(3′)-Ia	aac(6′)-Ib
Burn (43)	7	9	41	4	27	5	5
Non burn (32)	1	4	27	9	13	19	1

For REP analysis, 6 distinct patterns (A to F) were recognized among the 75 isolates. Five multidrug susceptible isolates did not show similar patterns with types A–F. Most of the nonburn isolates clustered in pattern A and isolates with pattern B were mainly recovered from burn patients, but there were no correlations between AME gene types and the REP-PCR patterns or between aminoglycoside-resistant phenotypes and REP-PCR types.

P. aeruginosa isolates

Compared with four other aminoglycosides, amikacin demonstrated an excellent activity against P. aeruginosa isolates (46.1%), whereas tobramycin, gentamicin, netilmicin, and kanamycin were less effective with 38.2%, 28.9%, 26.3%, and 0% susceptibility rates, respectively.

Among 9 AME genes in order of prevalence, aph(3′)-IIb, aac(6′)-Ib, aph(3′)-Ia, ant(2′′)-Ia, ant(3′′)-Ia, aph(3′)-Via, and aac(3′)-Ia detected in 47 (61.8%) isolates, 46 (60.5%) isolates, 35 (46.1%) isolates, 11 (14.5%) isolates, 8 (10.5%) isolates, 7 (9.2%) isolates, and 4 (5.3%) isolates, respectively (Table 4). None of the isolates were positive for ant(4′)-IIb, aac(3′)-IIa, rmtA, rmtB, and armA genes. Among isolates which were resistant to at least one of the studied aminoglycosides, 16 (21.0%) isolates had one AME gene, 24 (31.5%) isolates had 2 AME genes, 20 (26.3%) isolates had 3 AME genes, 7 (9.2%) isolates had 4 AME genes, and 3 (3.9%) isolates had 5 AME genes. The aac(6′)-Ib gene had a significant association with resistance to amikacin, gentamicin, tobramycin, and netilmicin (p=0.0). The ant(2′′)-Ia was significantly associated with gentamicin and tobramycin resistance (p≤0.01). Aminoglycosides resistance matched the predicted phenotype in 12 of 13 isolates (92.3%) for gentamicin, 38 of 50 isolates (76.0%) for amikacin, 42 of 47 isolates (89.3%) for tobramycin, 37 of 45 isolates (82.2%) for kanamycin, and 41 of 44 isolates (93.1%) for netilmicin. Susceptibility was retained in the presence of gene/genes in one isolate (7.6%) for gentamicin, 12 isolates (24.0%) for amikacin, 5 isolates (10.6%) for tobramycin, 8 isolates (17.7%) for kanamycin, and 3 isolates (6.8%) for netilmicin. However, susceptibility to all five aminoglycosides matched the predicted phenotype in only 15 isolates (19.7%). Six isolates did not yield positive PCR results for any of the AME genes investigated, but unexpected resistance to at least one aminoglycoside was observed.

Table 4.

Frequency of AME Genotypes According to Their Predicted Substrates Specificity and the Results of Susceptibility Testing in 76 Pseudomonas aeruginosa Isolates

Genotype	Substrate	MIC (μg/ml)							T^c(n)		N^d(n)		K^e(n)^f
			4	16	32	64	128	256	S^g	NS^h	S	NS	S	NS
aph(3′)-IIb+aph(3′)-Ia	K	A^a	16	−	−	−	−	1	16	1	9	8	0	17
		G^b	13	2	−	1	−	1
aac(6′)-Ib	A, T, N	A	2	−	−	2	−	11	2	13	2	13	0	15
		G	1	1	−	5	2	6
aac(6′)-Ib+aph(3′)-IIb+ant(2′′)-Ia+aph(3′)-Ia	A, G, T, K, N	A	−	−	−	−	1	1	0	2	0	2	0	2
	G	−	−	−	−	−	2
aac(6′)-Ib+aph(3′)-IIb+aph(3′)-Ia	A, T, K, N	A	2	1	−	1	2	10	3	13	1	15	0	16
		G	3	−	1	5	5	2
aac(6′)-Ib+aph(3′)-IIb+ant(2′′)-Ia+aph(3′)-VIa+aph(3′)-Ia	A, G, T, K, N	A	−	−	−	−	−	1	0	1	0	1	0	1
		G	−	−	−	−	−	1
ant(2′′)-Ia+aph(3′)-IIb+aph(3′)-VIa+aph(3′)-Ia	A, T, K	A	1	−	−	−	−	−	0	1	1	0	0	1
	G	−	−	−	1	−	−
aac(6′)-Ib+ant(2′′)-Ia	A, G, T, N	A	−	−	−	−	−	4	0	4	0	4	0	4
		G	−	−	−	1	1	2
aph(3′)-IIb+ant(2′′)-Ia+aph(3′)-Ia	G, T, K	A	−	1	−	−	−	−	0	1	1	0	0	1
		G	−	−	−	−	−	1
aph(3′)-Via	A	A	−	1	−	−	−	−	0	1	1	0	0	1
		G	−	−	−	−	−	1
ant(2′′)-Ia+aph(3′)-VIa	A, G, T	A	1	−	−	−	−	−	0	1	1	0	0	1
		G	−	−	−	−	−	1
aph(3′)-IIb+aph(3′)-VIa+aph(3′)-Ia	A, K	A	1	1	−	−	−	−	1	1	1	1	0	2
		G	−	−	−	−	−	2
aac(6′)-Ib+aph(3′)-IIb+ant(3′′)-Ia+aph(3′)-Ia	A, T, K, N	A	−	−	−	−	−	3	0	3	0	3	0	3
	G	−	−	−	2	−	1
aac(3′)-Ia+ant(3′′)-Ia	G	A	−	−	−	−	−	1	1	0	0	1	0	1
		G	−	−	−	−	−	1
aac(3′)-Ia+aph(3′)-IIb+aac(6′)-Ib+ant(3′′)-Ia+aph(3′)-Ia	A, G, T, K, N	A	−	1	−	−	−	1	0	2	0	2	0	2
		G	1	−	−	−	1	−
ant(3′′)-Ia+aph(3′)-VIa	A	A	−	1	−	−	−	−	0	1	1	0	0	1
		G	1	−	−	−	−	−
ant(3′′)-Ia+aph(3′)-IIb+aph(3′)-Ia	K	A	1	−	−	−	−	−	1	0	0	1	0	1
		G	−	1	−	−	−	−
aac(6′)-Ib+aac(3′)-Ia+aph(3′)-IIb+aph(3′)-Ia	A, G, T, K, N	A	−	−	−	−	−	1	0	1	0	1	0	1
	G	−	−	−	−	−	1
None present	−	A	2	2				2	5	1	1	5	0	6
		G	3	1			1	1

A, amikacin; ^bG, gentamicin; ^cT, tobramycin; ^dN, netilmicin; ^eK, kanamycin, ^fn, number of isolate; ^gS, susceptible; ^hNS, nonsusceptible.

There were significant differences between burn and cystic fibrosis (CF) isolates in aac(6′)-Ib, aph(3′)-Ia, and ant(3′′)-Ia (p≤0.02) (see Table 5).

Table 5.

Frequency of AMEs According to the Source of Infection Among P. aeruginosa isolates

P. aeruginosa
Sample (n)	aph(3′)-IIb	aph(3′)-Ia	aph(3′)-VIa	ant(3′′)-Ia	ant(2′′)-Ia	aac(3′)-Ia	aac(6′)-Ib
Burn (47)	21	8	4	0	4	0	38
CF (29)	26	27	3	8	7	4	8

Among 76 P. aeruginosa isolates, 65 were successfully typed by ERIC-PCR, which showed 16 patterns. There was no clonal relatedness between a specific clone and aminoglycoside resistance phenotypes or AME combination phenotypes.

Discussion

In this study, occurrence of different AME genes, 16s rRNA methylases, and their correlation with aminoglycoside resistance in P. aeruginosa and A. baumannii isolates were investigated.

Many of the AME genes are widespread in P. aeruginosa and A. baumannii isolates.^11,12,14 There were notable differences in the distribution patterns of AME genes between these two studied groups of isolates. Frequency of aph(3′)-VIa and ant(2′′)-Ia were significantly higher in A. baumannii. These results are similar to those reported in other studies.^2,11 Regarding to P. aeruginosa isolates, we found aac(6′)-Ib and aph(3′)-IIb as the most prevalent AME genes. This is in contrast to the report from Iran,²⁰ which showed ant(2′′)-Ia as the most common AME gene in P. aeruginosa isolates. A high overall incidence of APH(3′)-class enzyme among both burn and nonburn isolates of A. baumannii was observed similar to that of the CF group of P. aeruginosa isolates, but we found aac(6′)-Ib to be the predominant gene among burn isolates of P. aeruginosa.

Since all our isolates were collected from the same geographic area at the same time with probably the same antibiotic treatment regimen, it was expected that they shared the same distribution patterns of AME genes, but our findings showed that their distributions were completely different among these two organisms. This happened because mechanisms of aminoglycosides resistance for Pseudomonas spp. and Acinetobacter spp. are considered genus specific and do not seem to vary geographically.¹⁷

To our knowledge, this is the first report about the distribution of rmtA, rmtB, and armA from Iran. It is important to note that we found only 30.7% (8 out of 26) of A. baumannii isolates with amikacin MIC ≥256 μg/ml were positive for armA methylase. Conversely, different studies from China²³ and South Korea⁴ reported different prevalences of armA in amikacin highly resistant A. baumannii isolates (85.2% and 98.3%, respectively). It is believed that this enzyme is capable of conferring an extraordinary high level of resistance against most aminoglycosides,²² but we found three armA-positive isolates, which were susceptible to gentamicin or tobramycin. The other 18 isolates with a high level of resistance to amikacin possessed aph(3′)-VIa alone or in combination with other AME genes. In contrast to armA methylase, the role of aph(3′)-VIa or aac(6′)-Ib in the development of resistance to more common aminoglycosides is less clear.¹ However, our findings showed a significant association between the presence of aph(3′)-VIa and resistance to amikacin as expected, also with gentamicin and kanamycin as unexpected substrates.

It seems that ant(2′′)-Ia, is an important determinant for resistance against gentamicin and tobramycin in both A. baumannii and P. aeruginosa isolates. All of the A. baumannii and P. aeruginosa isolates, carrying this determinant were resistant to gentamicin. Interestingly, 31 out of 40 positive ant(2′′)-Ia A. baumannii isolates were highly resistant to gentamicin (MIC level ≥256 μg/ml). Moreover, all P. aeruginosa and 85% of A. baumannii isolates harboring ant(2′′)-Ia were resistant to tobramycin.

Among P. aeruginosa isolates, the prevalence of aac(6′)-Ib was significantly higher (60.5%) compared with the previous report from Iran²⁰ that detected only 7% positive isolates. We found significant correlations between this AME and resistance to each of amikacin, gentamicin, tobramycin and netilmicin, although gentamicin was an unexpected substrate for aac(6′)-Ib. The association between netilmicin and aac(6′)-Ib was very significant, since, we characterized 41 out of 45 positive aac(6′)-Ib isolates, were resistant to netilmicin. Conversely, we could not demonstrate the same association in A. baumannii. Similar finding about the role of this AME has been reported previously in A. baumannii.¹ One possible explanation is that the gene is typically carried on integrons as a gene cassette lacking its own promoters and, thus, its expression may be suboptimal depending on its distance from the common promoter sequences located at the 5′ conserved segment of the integrons.⁶

Some aminoglycoside resistance genes were distributed among several genotypically distinct groups of isolates demonstrated by REP and ERIC-PCR. We found no correlations between the presence of resistance genes and their patterns, which indicate that AME genes have spread by means of horizontal transfer as well as clonal dissemination.

We observed frequent disagreements between the predicted and the actual aminoglycoside phenotypes, with the phenotypes for only 8 (10.6%) in A. baumannii and 15 (19.7%) in P. aeruginosa isolates being in full agreement. This suggests that other resistance mechanisms against aminoglycosides such as impermeability, efflux pumps, or rare types of AMEs and unknown 16S rRNA methylases can play roles in the development of resistance against this class of antibiotics.

In conclusion, it seems that the distribution of AMEs among A. baumannii and P. aeruginosa isolates were unexpectedly different in the same geographic region. For most isolates, the AME genotype was an inadequate predictor of the aminoglycoside phenotype, suggesting the contribution of multiple concurrent resistance mechanisms.

Footnotes

Acknowledgments

This work was supported fully by Tabriz Research Center of Infectious and Tropical Diseases (grant No.89/16), Tabriz University of Medical Sciences, Tabriz, Iran.

This is a report of a database from thesis entitled “Evaluation of MexAB-OprM and MexXY-OprM efflux systems, AmpC cephalosporinase and OprD protein expressions to investigate their association with resistance against carbapenemes in P. aeruginosa isolated from clinical specimens” registered in Tabriz University of Medical Sciences.

Disclosure Statement

No competing financial interests exist.

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