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Article

Profiling Antibiotic Resistance in Acinetobacter calcoaceticus

by
Janiece S. Glover
1,
Taylor D. Ticer
2 and
Melinda A. Engevik
1,2,*
1
Department of Regenerative Medicine and Cell Biology, Medical University of South Carolina, Charleston, SC 29425, USA
2
Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA
*
Author to whom correspondence should be addressed.
Antibiotics 2022, 11(7), 978; https://doi.org/10.3390/antibiotics11070978
Submission received: 21 April 2022 / Revised: 14 July 2022 / Accepted: 15 July 2022 / Published: 20 July 2022
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Abstract

:
Background: Acinetobacter spp. have emerged as troublesome pathogens due to their multi-drug resistance. The majority of the work to date has focused on the antibiotic resistance profile of Acinetobacter baumannii. Although A. calcoaceticus strains are isolated in the hospital setting, limited information is available on these closely related species. Methods & Results: The computational analysis of antibiotic resistance genes in 1441 Acinetobacter genomes revealed that A. calcoaceticus harbored a similar repertoire of multi-drug efflux pump and beta-lactam resistance genes as A. baumannii, leading us to speculate that A. calcoaceticus would have a similar antibiotic resistance profile to A. baumannii. To profile the resistance patterns of A. calcoaceticus, strains were examined by Kirby–Bauer disk diffusion and phenotypic microarrays. We found that Acinetobacter strains were moderately to highly resistant to certain antibiotics within fluoroquinolones, aminoglycosides, tetracyclines, and other antibiotic classes. These data indicate that A. calcoaceticus has a similar antibiotic resistance profile as A. baumannii ATCC 19606. We also identified that all Acinetobacter species were sensitive to 5-fluoroorotic acid, novobiocin, and benzethonium chloride. Conclusion: Collectively, these data provide new insights into the antibiotic resistance in A. calcoaceticus and identify several antibiotics that could be beneficial in treating Acinetobacter infections.

Graphical Abstract

1. Introduction

Acinetobacter spp. are Gram-negative bacteria that have become a pressing health concern over the past few decades. Worldwide, Acinetobacter spp. make up 20% of the infections seen in the hospital setting and are considered the main cause of hospital-acquired bacteremia and pneumonia [1]. Once infection occurs, professionals are challenged with formulating strategic treatment plans for patients. This is because Acinetobacter spp. are characterized by their intrinsic antimicrobial resistance [2]. Acinetobacter strains are increasingly resistant to the major classes of antimicrobials, including beta-lactams, aminoglycosides, and fluoroquinolones [3]. Due to the high degree of resistance to multiple classes of antimicrobials, these microbes are classified as “multi-drug resistant” or “MDR” [2,4]. Unfortunately, the prevalence of MDR Acinetobacter isolates has increased in recent years [3], and, according to the World Health Organization (WHO), Acinetobacter are among the most serious MDR organisms [5].
The Acinetobacter baumannii-calcoaceticus (ABC) complex is a group of phenotypically indistinguishable opportunistic pathogens that cause hospital-acquired bacteremia and pneumonia. Among the ABC complex members, A. baumannii, A. pittii, and A. nosocomialis are the most commonly isolated strains [6,7]. A. calcoaceticus strains are also isolated, but less frequently [8]. Based on the frequency of isolation in infections, the majority of studies examining the antimicrobial resistance in Acinetobacter have focused on A. baumannii [2]. These studies have found that A. baumannii strains are resistant to most first-line antibiotics. Several studies have examined the antibiotic resistance in ABC complex isolates but have not distinguished between species [9,10]. Determining the antibiotic profile of strains within ABC complexes is important because some organisms may be more resistant than others. By characterizing the antibiotic profiles of other strains, such as A. calcoaceticus, we may be able to identify antibiotics to which multiple species are sensitive. Currently, few studies have specifically examined the resistance profile of A. calcoaceticus strains. Herein, we sought to address this gap in knowledge by examining the antibiotic sensitivity profile of commercially available A. calcoaceticus and clinical isolates of A. calcoaceticus.

2. Results

Despite the diverse targets of antibiotic classes (Figure 1A), Acinetobacter species are well documented for their ability to counteract the effects of antibiotics through multidrug efflux pumps and targeted mechanisms. Since antibiotic resistance mechanisms are commonly studied in A. baumannii species, we sought to compare the genomic capacity of A. calcoaceticus strains to resist antibiotics to that of A. baumannii and unclassified Acinetobacter strains. We identified 1290 genomes of A. baumannii, 23 genomes of A. calcoaceticus, and 128 genomes of unclassified Acinetobacter spp. in the Integrated Microbial Genomes (IMG) database (img.jgi.doe.gov; accessed on 9 October 2021) and examined key genes in the antibiotic resistance pathways, as identified in the KEGG database (KEGG: Kyoto Encyclopedia of Genes and Genomes, https://www.genome.jp; accessed on 9 October 2021) (Figure 1B). We found several multidrug efflux pump genes, including TolC/AcrA/AcrB, MexA/MexB/OprM, OMP/RND/MFP, and AdeA/AdeB/AdeC, in the majority of examined Acinetobacter genomes. These efflux proteins are known to secrete various antibiotics out of the outer cell wall, thereby limiting the effectiveness of these antimicrobial compounds. A. baumannii is well characterized for its resistance to beta-lactams via alterations in outer membrane proteins (OMPs) production, beta-lactamases, penicillin-binding proteins (PBPs), and the increased activity of efflux pumps [11]. In our genome analysis, we found that A. baumannii, A. calcoaceticus, and Acinetobacter spp. genomes did not have genes encoding the beta-lactam transporters OprD, OmpF, OmpC, OmpU, or PorB, indicating that these bacteria can limit the uptake of beta-lactams into the outer membrane. We also found that >95% of the A. baumannii and A. calcoaceticus genomes harbored Class C (AmpC) beta-lactamases. Some A. baumannii genomes contained the genes for Class A (blaTEM; 20.5%), Class D (pxa23; 22.9%), and Class B (bla2; 3.4%) beta-lactamases. Only a few A. calcoaceticus genomes had Class A (4.3%) beta-lactamases, and no genomes had Class B or D beta-lactamases. Interestingly, only 21% of unclassified Acinetobacter species harbored Class C beta-lactamases, and 8.6% had Class C beta-lactamases. These findings suggest that A. calcoaceticus is similar to A. baumannii in terms of its genomic capacity to resist antibiotics.
To examine the antibiotic resistance profile of A. calcoaceticus, we examined commercially available A. calcoaceticus ATCC 23055 and A. calcoaceticus CB1 and A. calcoaceticus clinical isolates (M31602, T82482, X75393, and M53152) using the Kirby Bauer Disc Diffusion Assay (Table 1). For comparison, we also examined Acinetobacter spp. ATCC 27244 and A. baumannii ATCC 19606. We observed that all Acinetobacter strains were resistant to erythromycin (macrolide) and colistin (miscellaneous antibiotic). All strains had an intermediate resistance to ceftazidime (cephalosporin), meropenem (carbapenem), and tetracycline (tetracycline) and were sensitive to imipenem (carbapenem), amikacin (aminoglycoside), gentamicin (aminoglycoside), tobramycin (aminoglycoside), and tigecycline (tetracycline) (Table 1).
To expand our antibiotic profile, we also employed Biolog phenotypic microarrays, which contain a variety of antibiotics. The growth with antibiotics was contrasted to the growth without antibiotics. We considered bacteria to be resistant if >75% growth was observed in the presence of antibiotics, moderately resistant if the growth was between 25% and 75% with antibiotics, and sensitive if the bacteria grew <25% with antibiotics. We first examined the cephalosporins cefazolin, ceftriaxone, and cephalothin as well as the carbapenem imipenem (Figure 2A). All Acinetobacter strains were moderately resistant to the cephalosporins and sensitive to the carbapenem imipenem. We also examined fluoroquinolones and found that all the strains were moderately resistant to the antibiotics lomefloxacin, enoxacin, and ofloxacin (Figure 2B). We then examined aminoglycosides (Figure 2C). All strains were moderately resistant or resistant to kanamycin, neomycin, capreomycin, gentamicin, colistin, and amikacin (Figure 2C). Notably, A. baumannii ATCC 19606 was more resistant than the A. calcoaceticus strains to paromomycin, sisomicin, tobramycin, and spectinomycin.
A. calcoaceticus strains, unclassified Acinetobacter, and A. baumannii were moderately resistant to chlortetracycline and demeclocycline (Figure 3A). All Acinetobacter strains were sensitive to tetracycline, minocycline, and penimepicycline (Figure 3A). These data indicate that A. calcoaceticus has a similar resistance profile to tetracyclines as A. baumannii. We also examined beta-lactam antibiotics and observed a strain-dependent and antibiotic-specific resistance (Figure 3B). We found that all Acinetobacter strains were moderately resistant to penicillin G, carbenicillin, cloxacillin, nafcillin, and amoxicillin. Oxacillin was more effective in limiting the growth of the Acinetobacter strains compared to the other beta-lactams tested (Figure 3B). These data emphasize that, even within classes such as beta-lactams, resistance is specific to the individual antibiotic.
Finally, we examined antibiotics that fall into the miscellaneous category. Significant differences in antibiotic resistance between A. calcoaceticus and A. baumannii were observed in response to sulfonamides: sulfadiazine sulfathiazole and sulfa-methoxazole (Figure 3C). We found that all A. calcoaceticus strains were sensitive to these antibiotics, while A. baumannii was more resistant. In response to acids, A. baumannii had a higher degree of resistance to D,L-serine hydroxamate than the A. calcoaceticus and unclassified Acinetobacter strains (Figure 3C). Surprisingly, all the Acinetobacter strains were sensitive to the acid-derived antibiotic 5-fluoroorotic acid, rifampicin, dodecyltrimethyl ammonium bromide, and novobiocin (Figure 3C), suggesting that these antibiotics may be useful in treating Acinetobacter species infections.

3. Discussion

The limitations surrounding the treatment for Acinetobacter infections continue to be a healthcare concern, and while multiple studies have identified antibiotic resistance in A. baumannii strains, there is only a partial characterization of the antibiotic-resistance in A. calcoaceticus infections. Based on our computation analysis, the genome of A. calcoaceticus resembles that of A. baumannii in terms of several antibiotic resistance genes. Consistent with this notion, we found that A. baumannii had a similar sensitivity profile to A. calcoaceticus for most antibiotics. For example, A. calcoaceticus and A. baumannii were both resistant to carbenicillin, cefazolin, ceftriaxone, and cephalothin and sensitive to 5-fluoroorotic acid, benzethonium chloride, and novobiocin. However, we did note some differences. These data suggest that although A. calcoaceticus is antibiotic-resistant, A. baumannii likely has a larger antibiotic resistant repertoire. Together, these data provide insight into the antibiotic sensitivity of A. calcoaceticus strains and highlight that antibiotic resistance is strain-dependent and antibiotic-specific.
To date, there have only been a few studies that directly focus on A. calcoaceticus. One study found that one strain of A. calcoaceticus was resistant to ampicillin, clindamycin, chloramphenicol, and cefazolin [12]. To the best of our knowledge, this is the only study to specifically examine antibiotic resistance in A. calcoaceticus, although many studies have examined A. baumannii-calcoaceticus (ABC) complexes where the specific species cannot be distinguished. In our study, we found several antibiotics that significantly reduced the growth of Acinetobacter spp. in drug classifications that are not normally used to treat these organisms. For example, we found that Acinetobacter spp. are sensitive to novobiocin. Novobiocin interferes with the ATPase activity of DNA gyrase and inhibits the DNA repair/replication processes initiated by double-strand breaks [13]. Importantly, novobiocin has been shown to inhibit the acquisition of antimicrobial resistance through DNA damage-induced mutagenesis in the A. baumannii strain ATCC 17978 [13] and be effective against A. baumannii AB5075 [14]. Our study demonstrates that novobiocin is also effective against A. calcoaceticus strains and an unclassified Acinetobacter species. These data suggest that novobiocin could serve as a potential therapy for patients with Acinetobacter infections. Additionally, combination drugs can be explored, such as novobiocin and rifampicin. Recently, nine dilipid ultrashort tetrabasic peptidomimetics (dUSTBPs) were found to potentiate novobiocin and rifampicin activity against multidrug-resistant (MDR) clinical isolates of A. baumannii [15].
We also found that all Acinetobacter strains were highly sensitive to 5-fluoroorotic acid. 5-fluoroorotic acid has been used experimentally for many years in yeasts and archaea studies [16]. Non-toxic 5-fluoroorotic acid is converted to the toxic 5-fluoro-UMP by the two genes encoding orotate phosphoribosyltransferase (pyrE) and orotidine 5-phosphate decarboxylase (pyrF) in micro-organisms. Our data indicate that A. calcoaceticus, unclassified Acinetobacter spp. ATCC 27244, and A. baumannii ATCC 19606 are highly sensitive to 5-fluoroorotic acid. This finding is consistent with a previous study that found that the A. baumannii strains DR2 and AB067 were also sensitive to 5-fluoroorotic acid [17]. Importantly, human cell lines (HT-1080, IMR-90, HeLa S3, and HL-60) and a mouse cell line (L-1210) have been shown to be relatively tolerant of 5-fluoroorotic acid [18], indicating that 5-fluoroorotic acid could be used to treat infections in patients.
A major limitation of our study is that we did not identify minimum inhibitor concentrations (MICs) for the strains. Additionally, our Biolog Phenotypic Microarrays were performed in a chemically defined medium. The advantage of using a chemically defined medium is that the supernatant is amenable to downstream LC-MS/MS analysis since it does not contain components such as peptone and yeast extract. We have used this defined medium to examine the growth of diverse microbes and measure bacterial metabolites and proteins by LC-MS/MS [19,20,21,22,23]. However, this medium has not been validated for antibiotic studies, and the current gold standard medium is Mueller Hinton broth. In the future, it will be important to obtain standard MICs with the A. calcoaceticus strains.

4. Conclusions

This work sheds light onto how A. calcoaceticus strains respond to antibiotics and demonstrates that A. calcoaceticus behaves in a similar manner as A. baumannii in terms of antibiotic resistance. We believe this work can provide new insights into Acinetobacter resistance and new targets for antibiotic therapy.

5. Materials and Methods

5.1. Bacterial Culture Conditions

A.calcoaceticus ATCC 23055 and A. calcoaceticus Carolina Biological (CB1) strains were purchased for use in this study. Four clinical isolates of A. calcoaceticus (M31602, T82482, X75393, and M53152) were obtained [24]. For comparison, Acinetobacter baumannii ATCC 19606 and Acinetobacter spp. ATCC 27244 were used. All strains were cultured on Leeds Acinetobacter agar, a selective and differential medium for Acinetobacter spp. [25] Single colonies were used to inoculate liquid cultures of brain–heart infusion (BHI). All bacteria were grown at 37 °C aerobically in 10 mL conical tubes and shaken overnight at 150 rpm. The bacterial growth of liquid cultures was assessed by optical density (OD600nm) on a Spectronic 200 spectrophotometer (ThermoFisher, Waltham MA, USA).

5.2. Antibiotic Treatment

The antibiotic sensitivity of Acinetobacter strains was determined using the Kirby–Bauer method. Antibiotic disks were purchased from FisherScientific (Waltham MA, USA) and include: 30 µg Amikacin (cat# CT0107B); 30 µg Ceftazidime (cat# CT0412B); 10 µg Gentamicin (cat# CT0024B); 10 µg Colistin (cat# CT0017B); 15 µg Erythocycline (cat# 237093); 10 µg Imipenem (cat# CT0455B); 10 µg Meropenem (cat# CT0774B); 30 µg Tetracycline (cat# 230998); 15 µg Tigecycline (cat# CT1841B); and 10 µg Tobramycin (cat# CT0056B). Bacteria were diluted at a McFarland of 0.5 and incubated on Mueller Hinton Agar plates overnight (20 h) at 37 °C with the antibiotic disks. Zone diameters were recorded, and the susceptibility results were categorized as sensitive, moderately resistant, or resistant based on the CLSI breakpoint criteria [26].
To measure the growth of Acinetobacter in the presence of antibiotics, overnight BHI cultures were adjusted to an OD600nm = 0.1 in chemically defined media termed ZMB1 [27]. A total of 100 μL of this OD600nm adjusted ZMB1 was placed into each 96 well of the PM11 and PM12B Phenotype Microarray Biolog plate (n = 4 per antibiotic; repeated two independent times). Growth was monitored after 16 h of incubation at 37 °C on a Synergy HT BioTek plate reader. Antibiotic-treated microbes were compared to untreated microbes in ZMB1, and strains were considered to be sensitive to an antibiotic when there was <50% growth with an applied antibiotic compared to untreated microbes. Strains were considered moderately resistant to an antibiotic when there was 25–50% growth and highly resistant to an antibiotic when there was >75% growth in antibiotics compared to growth without antibiotics.

5.3. Computational Analysis

Acinetobacter genomes were identified in the Integrated Microbial Genomes (IMG) database (img.jgi.doe.gov) available through the Joint Genomes Institute (JGI) (Version 6.0; Berkeley, CA, USA) [28]. We identified 1290 genomes of A. baumannii, 23 genomes of A. calcoaceticus, and 128 genomes of unclassified Acinetobacter spp. The genes involved in beta-lactam resistance were identified in the KEGG database (KEGG: Kyoto Encyclopedia of Genes and Genomes, https://www.genome.jp; accessed on 9 October 2021). Based on a KEGG pathway analysis, we queried the Acinetobacter genomes for the following antibiotic-resistant genes: TolC (K12340), AcrA (K03585), AcrB (K18138), MexA (K03585), MexB (K18138), OrpM (K18139), RND (K18146), MFP (K18145), OMP (K12340), AdeA (K18145), AdeB (K18146), AdeC (K18147), blaTEM (Class A; K18698), Bla2 (Class B; K17837), AmpC (Class C; K20319), Pxa23 (Class D; K18793), OprD (K18093), OmpF (K09476), OmpC (K09475), OmpU (K08720), PorB (K18133), PBP1a/2 (K05366), PBP2 (K05515), and Fts1 (K03587).

5.4. Statistics

The data are presented as the mean ± standard deviation. Comparisons between the groups were made with One-way Analysis of Variance (ANOVA). GraphPad was used to generate the graphs and statistics (GraphPad Software v9.3, Inc. La Jolla, CA, USA). A * p < 0.05 value was considered significant.

Author Contributions

Conceptualization: J.S.G., T.D.T. and M.A.E.; methodology, J.S.G.; formal analysis, J.S.G. and M.A.E., writing—original draft preparation, J.S.G.; writing—review and editing, J.S.G., T.D.T. and M.A.E.; funding acquisition, M.A.E. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Institute of General Medical Sciences (NIGMS): T32GM132055-01 (J.S.G.); and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): T32DK124191-01A1 (T.D.T.) and K01K12319501 (M.A.E.).

Data Availability Statement

All data are available upon request.

Conflicts of Interest

The authors declare no conflict of interest.

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Antibiotics 11 00978 g001 550
Figure 1. Genomic analysis of Acinetobacter resistance genes. (A) Diagram highlighting the mechanism of action of the antibiotics used in this study. The inset shows the specific mechanisms of antibiotic resistance previously identified in Acinetobacter species. (B) Heat map of the percentage of A. baumannii, A. calcoaceticus, or unclassified Acinetobacter spp. genomes that have at least one gene copy of antibiotic resistance genes.
Figure 1. Genomic analysis of Acinetobacter resistance genes. (A) Diagram highlighting the mechanism of action of the antibiotics used in this study. The inset shows the specific mechanisms of antibiotic resistance previously identified in Acinetobacter species. (B) Heat map of the percentage of A. baumannii, A. calcoaceticus, or unclassified Acinetobacter spp. genomes that have at least one gene copy of antibiotic resistance genes.
Antibiotics 11 00978 g001
Antibiotics 11 00978 g002 550
Figure 2. A. calcoaceticus resistance to cephalosporins, carbapenems, fluoroquinolones, and aminoglycosides. Antibiotic resistance was measured by the percentage (%) of growth at a 16 h time point with antibiotics compared to that without antibiotics. A. calcoaceticus ATCC 23055, A. calcoaceticus CB1; A. calcoaceticus M31602, A. calcoaceticus T82482, A. calcoaceticus X75393, A. calcoaceticus M53152, unclassified Acinetobacter ATCC 27244, and A. baumannii ATCC 19606 were grown with (A) cephalosporins, carbapenems, (B) fluoroquinolones, and (C) aminoglycosides.
Figure 2. A. calcoaceticus resistance to cephalosporins, carbapenems, fluoroquinolones, and aminoglycosides. Antibiotic resistance was measured by the percentage (%) of growth at a 16 h time point with antibiotics compared to that without antibiotics. A. calcoaceticus ATCC 23055, A. calcoaceticus CB1; A. calcoaceticus M31602, A. calcoaceticus T82482, A. calcoaceticus X75393, A. calcoaceticus M53152, unclassified Acinetobacter ATCC 27244, and A. baumannii ATCC 19606 were grown with (A) cephalosporins, carbapenems, (B) fluoroquinolones, and (C) aminoglycosides.
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Figure 3. A. calcoaceticus resistance to tetracyclines, penicillin, and miscellaneous antibiotics. Antibiotic resistance was measured by the percentage (%) of growth at a 16 h time point with antibiotics compared to that without antibiotics. A. calcoaceticus ATCC 23055, A. calcoaceticus CB1, A. calcoaceticus M31602, A. calcoaceticus T82482, A. calcoaceticus X75393, A. calcoaceticus M53152, unclassified Acinetobacter ATCC 27244, and A. baumannii ATCC 19606 were grown with (A) tetracyclines, (B) penicillin, and (C) miscellaneous antibiotics.
Figure 3. A. calcoaceticus resistance to tetracyclines, penicillin, and miscellaneous antibiotics. Antibiotic resistance was measured by the percentage (%) of growth at a 16 h time point with antibiotics compared to that without antibiotics. A. calcoaceticus ATCC 23055, A. calcoaceticus CB1, A. calcoaceticus M31602, A. calcoaceticus T82482, A. calcoaceticus X75393, A. calcoaceticus M53152, unclassified Acinetobacter ATCC 27244, and A. baumannii ATCC 19606 were grown with (A) tetracyclines, (B) penicillin, and (C) miscellaneous antibiotics.
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Table
Table 1. Measurements of the zones of inhibition of Acinetobacter strains (mm). R, resistant; I, intermediate resistant; S, sensitive.
Table 1. Measurements of the zones of inhibition of Acinetobacter strains (mm). R, resistant; I, intermediate resistant; S, sensitive.
A. calcoaceticus A. baumannii Acinetobacter spp.
ClassAntibioticsConcentration23055CB1M31602M53152T82482X75393Category19606Category27244Category
CephalosporinsCeftazidime30 µg192019191919I19I19I
CarbapenemImipenem10 µg283029292929S29S29S
CarbapenemMeropenem10 µg252424242424I24I24I
AminoglycosideAmikacin30 µg202120202020S20S20S
AminoglycosideGentamicin10 µg242223222322S23S22S
AminoglycosideTobramycin10 µg212121212121S21S21S
TetracyclinesTetracycline30 µg151615151515I15I15I
TetracyclinesTigecycline15 µg232423232323S23S23S
MacrolidesErythromycin15 µg151113121312R12R12R
MiscellaneousColistin Sulphate10 µg151414141414R14R14R
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Glover, J.S.; Ticer, T.D.; Engevik, M.A. Profiling Antibiotic Resistance in Acinetobacter calcoaceticus. Antibiotics 2022, 11, 978. https://doi.org/10.3390/antibiotics11070978

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Glover JS, Ticer TD, Engevik MA. Profiling Antibiotic Resistance in Acinetobacter calcoaceticus. Antibiotics. 2022; 11(7):978. https://doi.org/10.3390/antibiotics11070978

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Glover, Janiece S., Taylor D. Ticer, and Melinda A. Engevik. 2022. "Profiling Antibiotic Resistance in Acinetobacter calcoaceticus" Antibiotics 11, no. 7: 978. https://doi.org/10.3390/antibiotics11070978

APA Style

Glover, J. S., Ticer, T. D., & Engevik, M. A. (2022). Profiling Antibiotic Resistance in Acinetobacter calcoaceticus. Antibiotics, 11(7), 978. https://doi.org/10.3390/antibiotics11070978

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