Phenotypic and Genotypic Characterization of Acinetobacter spp. Panel Strains: A Cornerstone to Facilitate Antimicrobial Development

Acinetobacter spp. have emerged as significant pathogens causing nosocomial infections. Treatment of these pathogens has become a major challenge to clinicians worldwide, due to their increasing tendency to antibiotic resistance. To address this, much revenue and technology are currently being dedicated toward developing novel drugs and antibiotic combinations to combat antimicrobial resistance. To address this issue, we have constructed a panel of Acinetobacter spp. strains expressing different antimicrobial resistance determinants such as narrow spectrum β-lactamases, extended-spectrum β-lactamases, OXA-type-carbapenemase, metallo-beta-lactamase, and over-expressed AmpC β-lactamase. Bacterial strains exhibiting different resistance phenotypes were collected between 2008 and 2013 from Severance Hospital, Seoul. Antimicrobial susceptibility was determined according to the CLSI guidelines using agar dilution method. Selected strains were sequenced using Ion Torrent PGM system, annotated using RAST server and analyzed using Geneious pro 8.0. Genotypic determinants, such as acquired resistance genes, changes in the expression of efflux pumps, mutations, and porin alternations, contributing to the relevant expressed phenotype were characterized. Isolates expressing ESBL phenotype consisted of blaPER−1 gene, the overproduction of intrinsic AmpC beta-lactamase associated with ISAba1 insertion, and carbapenem resistance associated with production of carbapenem-hydrolyzing Ambler class D β-lactamases, such as OXA-23, OXA-66, OXA-120, OXA-500, and metallo-β-lactamase, SIM-1. We have analyzed the relative expression of Ade efflux systems, and determined the sequences of their regulators to correlate with phenotypic resistance. Quinolone resistance-determining regions were analyzed to understand fluoroquinolone-resistance. Virulence factors responsible for pathogenesis were also identified. Due to several mutations, acquisition of multiple resistance genes and transposon insertion, phenotypic resistance decision scheme for for evaluating the resistance proved inaccurate, which highlights the urgent need for modification to this scheme. This complete illustration of mechanism contributing to specific resistance phenotypes can be used as a target for novel drug development. It can also be used as a reference strain in the clinical laboratory and for the evaluation of antibiotic efficacy for specific resistance mechanisms.


INTRODUCTION
Acinetobacter spp. are non-motile, non-fermenting Gramnegative bacteria. Over the years, several species have been identified, and the most common and clinically significant are Acinetobacter baumannii, Acinetobacter pittii, and Acinetobacter nosocomialis (Chen et al., 2014). These bacteria have emerged as the most troublesome pathogens in hospital settings, due to their rapid colonization and infection. Incidence and mortality due to A. nosocomialis and A. pittii are lower than those due to A. baumannii; however, these are frequently isolated from nosocomial infections (Wisplinghoff et al., 2012). Acinetobacter spp. have been implicated in many pathological conditions such as ventilator-associated pneumonia, urinary tract infections, skin and wound infections, infective endocarditis, bacteremia, and secondary meningitis (Fishbain and Peleg, 2010;Garnacho-Montero and Amaya-Villar, 2010;Visca et al., 2011;Chusri et al., 2014). These infections have become challenging to treat due to their widespread multidrug resistance owing to mechanisms such as horizontal gene transfer, increased expression of β-lactamases, alterations of membrane permeability, and increased expression of efflux pumps (Singh et al., 2013); (Blair et al., 2015).
For several decades, numerous research have been conducted to understand the mechanisms of resistance and to control its dissemination in clinical settings. Considering the severity of infections, we have constructed a series of panel strains of Acinetobacter spp. expressing different resistance phenotypes such as narrow spectrum β-lactamase and oxacillinase, extended spectrum β-lactamase (ESBL), OXA-type carbapenemase, metallo-β-lactamase (MBL), and over-expressing AmpC β-lactamase. These strains were characterized genotypically using massive parallel sequencing (MPS) technology to understand the observed phenotypes. In this study, we have performed detailed analysis of the whole genome sequence (WGS) related to multidrug-resistance mechanisms, such as acquisition of β-lactamases, transposon insertions, mutations in porins, and changes in efflux pumps, and interpreted the discrepancy observed in phenotypic changes to relevant antibiotics. These panel strains can be used in hospital settings as reference strains, and also in the pharmaceutical industry to check the efficacy of new antibiotic drugs on pathogens expressing different resistance determinants. These strains can be distributed world-wide to institutions working on discovery of novel antibiotics, aiding in their characterization.

Bacterial Strains
All bacterial strains were collected from Severance Hospital, Seoul from 2008 to 2013. Almost 4,000 strains were shortlisted depending on their in-silico resistance prediction from the hospital patient database, according to the resistance determination decision tree to interpret the type of resistance based on phenotypic observation by François et al. (2004) and Richard Bonnet (2010). Strains were categorized according to their resistance phenotype such as narrow spectrum β-lactamase and oxacillinase, ESBL, OXA-type-carbapenemase, MBL and over-expressed AmpC β-lactamase. Bacteria were identified using the direct colony method with MALDI-TOF MS (Bruker Daltonics, Bremen, Germany). In addition, RNA polymerase β-subunit gene (rpoB)-based identification was used to delineate species within the Acinetobacter genus (La Scola et al., 2006).
In addition, the minimum-inhibitory concentrations (MIC) for bacterial strains were determined using agar dilution technique. E-test was used to measure the MIC of levofloxacin, trimethoprim/sulfamethoxazole, tigecycline, tetracycline, gentamicin, rifampicin, clindamycin, erythromycin and chloramphenicol. All of the procedures and results interpretation followed the Clinical and Laboratory Standards Institute (CLSI) guidelines. AmpC β-lactamase-, MBL, and ESBL-producing strains were selected using ertapenemamino phenylboronic acid (APBA), imipenem-EDTA, and cefepime-clavulanate double disk synergy tests, respectively (Lee et al., 2001). Modified Hodge tests were also performed with cefoxitin disk for AmpC beta-lactamase detection, and imipenem disk for carbapenemase detection (Lee et al., 2010).

Whole Genome Sequencing and Bioinformatics Analysis
A few strains from each phenotypic resistance class were randomly selected and cultured overnight. Genomic DNA extractions were performed using Wizard genomic DNA purification kit (Promega, WI, USA) with a few modifications to the manufacturer's protocol, such as adding 5 µl of RNase solution during cell lysis as well as incubating the supernatant carrying the DNA at −20 • C for 1 h after addition of isopropanol. DNA concentration was measured using Qubit dsDNA BR assay kit (Molecular Probes, OR, USA) before sequencing.
Whole genome libraries were prepared using Ion plus fragment library kit, and Emulsion PCR was carried out using Ion one touch 200 Template kit v2 DL (Life technologies, CA, USA). Sequencing of the amplicon libraries was carried out on a 318 chip, using Ion Personal Genome Machine Ion Torrent sequencer through Ion Sequencing 200 kit (Life technologies, CA, USA). The resultant reads were assembled using MIRA plugin (version 4.0) of Torrent suite software. Genome assemblies were annotated using RAST annotation pipeline, and further validated with Geneious pro 8.0 (Aziz et al., 2008;Kearse et al., 2012). Genes encoding the efflux systems, porins, and virulence factors of the panel strains were aligned using Clustal Omega, and verified for the polymorphisms (Sievers et al., 2011). Resistance genes were identified using Resfinder (Zankari et al., 2012), and manually curated using NCBI BLAST. Multi-locus sequence typing was performed using MLST 1.8 (Zankari et al., 2013) and Acinetobacter baumannii MLST website (Jolley and Maiden, 2010).

Outer Membrane Protein Detection
Bacterial cells were grown in Muller-Hinton broth until logarithmic phase, and centrifuged at 5,000 g for 15 min, washed twice in 10-mM phosphate buffer, and lysed by sonication at 18-20% amplitude for 2 × 30 s cycles, each comprised 6 × 5 s sonication steps separated by 1 s of no sonication, and 30 s of no sonication between the two cycles. Unbroken cells were eliminated using centrifugation at 3,000 g for 5 min, and outer membrane was solubilized with 2% sodium lauroyl sarcosinate. Insoluble outer membrane fraction was recovered by ultracentrifugation at 25,000 g for 1 h, as described previously (Hernandez-Alles et al., 1999). OMP profiles were determined using SDS-PAGE using Mini-Protean TGX gels (12%), followed by Coomassie blue staining (Bio-Rad, CA, USA). Additionally, OMPs were identified using Matrix-Assisted Laser Desorption-Time of Flight Mass Spectrometry on Tinkerbell LT (ASTA, Suwon, Korea), as described . All experiments were repeated three times independently to check for reproducibility of the results.

Quantitative Real-Time RT-qPCR
Total RNA of the 12 Acinetobacter spp. isolates were extracted from exponentially grown bacterial cells with optical density at 600 nm of 0.7-0.8, using RNeasy Mini Kit (Qiagen, Hilden, Germany). Quantity and quality of RNA samples were checked using NanoDrop spectrophotometer (ND-2000 Thermo scientific, USA). RNA samples with 260/280 ratio from 1.9 to 2.1, 260/230 ratio from 2.0 to 2.5 were used for further analysis. All of the RNA samples were adjusted to the same concentration. Then, 1 µg of total RNA was used to synthesize cDNA by reverse transcription using M-MLV cDNA Synthesis Kit (Enzynomics, Korea) in a 20 µl reaction using 50 µM random hexamers. cDNA was further diluted and stored at −20 • C until PCR. Real-time PCR was performed with a 20-µl reaction volume containing 2 µl (100ng) of cDNA, 1X iQ SYBR Green Supermix (Bio-Rad, CA, USA), and gene-specific primers, 300 nM each (for adeB, adeG, adeJ, baeSR, carO, 33-36kDa omp, and oprD genes), on StepOne Real-Time PCR System (Life technologies, CA, USA) with the following cycle: 1 cycle at 95 • C for 3 min followed by 40 cycles of 95 • C for 10 s and 56 • C for 1 min. Dissociation curve was generated to check PCR amplification specificity. In each run, 2 µl RNase-free water was used as a no template control (NTC) for each gene. The primers used for RT-qPCR were designed using Primer3web (version 4.1.0) (Untergasser et al., 2012), validated using Geneious pro 8.0. (Kearse et al., 2012), synthesized commercially by Macrogen, Inc., Korea, and are shown in Table S9. Different primers were used for different species due to the polymorphism identified in efflux pumps. Each experiment was performed in triplicates at least twice independently. The changes in expression level for each gene was calculated according to a previous study (Livak and Schmittgen, 2001). In brief, for each sample, the threshold cycle (Ct) of target gene was determined and normalized to Ct value of rpoB gene, and then calculated relatively to the calibrator (strain YMC/2009/2/B2968) using formula 2 − Ct (data is represented as mean ± standard error). Detailed experimental conditions used in RT-qPCR based on MIQE requirements are described in Table S10.

Extended-Spectrum Beta-Lactamases
In Korea a high prevalence of bla PER−1 ESBL-producing Acinetobacter spp. was reported between 2001 and 2005 (Yong et al., 2003), and the level has been reducing over the years. The bla PER−1 belongs to class A extended-spectrum beta-lactamase, which has been detected in P. aeruginosa (Ranellou et al., 2012), P. mirabilis (Pagani et al., 2004), S. enterica (Poirel et al., 2005), and Acinetobacter spp. (Naas et al., 2006), and disseminated worldwide since its first detection in France on 1993 (Nordmann et al., 1993). ESBLs are a class of group A β-lactamases, which hydrolyze third generation cephalosporin's but are inhibited by beta-lactamase inhibitors like clavulanic acid (Bradford, 2001;Jacoby and Munoz-Price, 2005). Antimicrobial susceptibility for beta-lactams is similar in ESBLs and highlevel AmpC β-lactamase-producing Acinetobacter spp. We have categorized the strains depending according to the presence of ESBL or AmpC-producing genes, along with IS elements. a) Acinetobacter baumannii YMC2003/5/C86: This strain was resistant to all antibiotics tested in this study, except ceftazidime-clavulanate. WGS analysis indicated the presence of bla PER−1 , bla TEM−1D , bla ADC−31, and bla OXA−82 . The bla PER−1 gene was flanked by the putative transposase gene tpnA1 and tpnA2 in upstream and downstream region. Insertion sequence ISAba1 was located immediate upstream region of AmpC beta-lactamase gene, bla ADC−31 and carbapenemase gene, bla OXA−82 (Zander et al., 2013) ( Figure S1). Beta-lactam and cephalosporin resistance of this isolate can be clearly argued by the presence of these encoded β-lactamase genes along with the insertion elements, providing the additional promoters for their increased expression (Lin et al., 2010). Resistance to aminoglycosides and gentamicin are contributed by aac(3 ′ )-Ia, aac(6 ′ )-Il, aph(3 ′ )-Ic, and strAB genes (Tables 1, 2). Levofloxacin resistance was conferred due to the mutations observed in gyrA and parC genes ( Table 3). Twenty to seventyfold up-regulation of adeB and adeJ efflux pumps genes were confirmed, which are assumed to contribute to the resistance of levofloxacin, trimethoprim/sulfamethoxazole, tigecycline, clindamycin, chloramphenicol, and tetracyclines (Table 1, Figure 1). b) Acinetobacter nosocomialis YMC2003/1/R306 was susceptible to imipenem, meropenem, and ciprofloxacin, intermediate to piperacillin-tazobactam, but resistant to piperacillin, ceftazidime, cefepime, and ampicillin-sulbactam. This isolate is an ideal candidate for ESBL strain, as it carries bla PER−1 ,which is identified as a part of composite transposon bracketed by two insertion elements ISPa12 and ISPa13, belonging to IS4 family ( Figure S2). Expression of this gene was driven by ISPa12 promoter, and its genetic environment is similar to the bla PER−1 found in Providencia stuartii and Pseudomonas aeruginosa isolates, as reported previously (Yong et al., 2003;Poirel et al., 2005). Efflux pumps showed lower expression, which correlated to its increased susceptibility toward fluoroquinolones and tetracyclines (Tables 1, 3, Figure 1).

OXA-Type-Carbapenemases
Carbapenem resistance in Acinetobacter spp. is mediated by various mechanisms such as membrane impermeability due to loss of porins, but it is mostly mediated by enzymatic hydrolysis of antibiotics (Bou et al., 2000;Quale et al., 2003;Bonomo and Szabo, 2006;Poirel and Nordmann, 2006;. Carbapenem-hydrolyzing class D beta-lactamases (CHDLs) or OXA-type-carbapenemases (OXA-51-like, 23-like, -58-like, -143-like, -40-like, and 235-like), often associated with upstream  insertion elements, lead to their over-expression resulting in carbapenem resistance (Poirel et al., 2010). Studies have indicated that OXA-40-and OXA-143-type carbapenemases were not associated with insertion sequences nor integrons (Higgins et al., 2009;Evans and Amyes, 2014). Below we have illustrated the mechanism of few strains expressing OXA-type carbapenemases. According to the resistance determination decision tree, these strains were similar to the phenotype observed in metallobeta lactamase producers, except its susceptibility toward ceftazidime and cefepime. However, due to the complex resistance mechanism involving multiple beta-lactamases and efflux pumps, most of the strains in this class were resistant to these two antibiotics.
In addition, there was insertion of ISAba1 upstream of bla ADC−30 and bla OXA−23 , providing additional promoter leading to increased resistance due to overexpressions of AmpC beta-lactamase and carbapenemase, respectively. Increased expression of adeb, adeG, and adeJ, along with aminoglycoside and fluoroquinolones resistance genes such as armA, aph(3 ′ )-Ic, strAB, aph(3 ′ )-VIb, aadA1, and aac(6 ′ )Ib-cr decreased the susceptibility toward gentamicin, tetracycline, trimethoprim/sulfamethoxazole, rifampicin, and chloramphenicol (Table 1, Figure 1). In addition, mutations were observed in gyrA and parC genes, which caused levofloxacin resistance (Table 3). d) Acinetobacter baumannii YMC2012/9/R2209 was intermediate to imipenem but resistant to all other cephalosporin and carbapenems used in our study ( Table 1). This isolate was AmpC beta-lactamase hyper-producer along with CHDL, which was revealed by the presence of ISAba1bla OXA−82 and ISAba1-bla ADC−30 (Figure S8). Increased carbapenem resistance was caused by ISAba1-bla OXA−82 (Zander et al., 2013). Susceptibility toward tigecycline, gentamicin and tetracycline were due to the absence of aminoglycoside resistance genes and lower expressions of adeB and adeG efflux pumps (Table 1, Figure 1). In contrast, increased relative expression of adeJ gene might have increased resistance to fluoroquinolones, such as ciprofloxacin and levofloxacin, along with gyrA and parC genes mutations.

Narrow Spectrum β-Lactamase
Acinetobacter pittii YMC2010/8/T346 belongs to a novel sequence type 1385 (ST 1385), and is susceptible to ampicillinsulbactam, piperacillin-tazobactam, ceftazidime, cefepime, imipenem, ceftazidime-clavulanate, and ciprofloxacin but resistant to meropenem (Tables 1, 3). Sequence analysis indicated the presence of bla OXA−506, variant of A. pittii intrinsic bla OXA−213−like , bla ADC−41 , and bla OXA−499, which were not associated with insertion elements (Table 2, Figure S10). The bla OXA−499 is a novel variant of carbapenem hydrolyzing oxacillinase, bla OXA−143 . This gene was first found in South Korea, and is the carbapenem hydrolyzing gene which explains its resistance to the meropenem, as reported previously . Wide susceptibility toward aminoglycosides, tetracyclines, and fluoroquinolones was observed due to the lower expression of efflux pumps and absence of any corresponding resistance genes (Tables 1, 3, Figure 1).

Narrow Spectrum Oxacillinase
Acinetobacter pittii YMC2009/2/B2968 belonging to novel ST1638, was not resistant to the antibiotics tested in this study ( Table 1). Whole genome analysis revealed bla OXA−421 , a CHDL belonging to A. pittii intrinsic bla OXA−213 family and bla ADC−22 (Table 2, Figure S11). However, no existing study has yet demonstrated that the carbapenemase activity of bla OXA421. bla ADC−22 is a naturally occurring cephalosporinase gene in A. baumannii, which is repressed under normal conditions (Beceiro et al., 2009;Li et al., 2015). This strain exhibited the highest susceptibility toward aminoglycosides, tetracyclines, and fluoroquinolones among all other panel strains, due to the absence of corresponding resistance genes and lowest expression of efflux pumps. Therefore, this was selected as the reference strain to calculate the relative expression of efflux pumps for other strains.

Analysis of QRDRs for gyrA and parC Genes and Fluoroquinolone Resistance
The MICs of ciprofloxacin and levofloxacin were determined ( Table 3). Both antibiotics functioned by inhibiting DNA gyrase subunit A (GyrA), DNA gyrase subunit B (GyrB), and toposiomerase IV subunit C (ParC) (Drlica and Zhao, 1997), and hence exhibited similar resistance phenotypes for the panel strains. Resistance to fluoroquinolone in bacteria was mediated by spontaneous mutations in gyrA, gyrB, and parC genes (Park et al., 2011;Ardebili et al., 2015). We identified the substitutions in GyrA (Ser81Leu) and ParC (Ser84Leu) in all fluoroquinolone resistant strains ( Table 3). Ser467Gly and Glu88Lys mutation in ParC did not correlate with the resistance phenotypes. As opposed to the previous studies, we found GyrA (Ser81Leu) and ParC (Ser467Gly) mutations in A. nosocomialis YMC2003/1/R306, which were susceptible to fluoroquinolone (Vila et al., 1995). We could not find Glu479Asp, Cys423Ser, Glu479Asp, Leu420Gln, Cys423Ser, Leu433His, Glu479Asp, and D644Y mutations in GyrB which were previously described as novel substitutions (Park et al., 2011), except A677V in A. baumannii YMC2003/5/C86.

Efflux-Mediated Antimicrobial Resistance
Overexpression of efflux pumps are one of the major mechanisms that contribute to the multidrug resistance in Acinetobacter species. Genes encoding these systems are carried by mobile genetic elements or chromosomes, and thus be responsible for acquired or intrinsic resistance (Coyne et al., 2011). Five categories of efflux pump systems have been described, which are responsible for pumping out diverse classes of antibiotics: resistance-nodulation-cell division (RND) family, ATP-binding cassette (ABC) transporters, major facilitator superfamily (MFS), small multidrug resistance (SMR) family, and the recently identified multidrug and toxic compound extrusion (MATE) family (Piddock, 2006;Vila et al., 2007). Considering the broadrange substrate specificity of the three RND-type efflux pump systems, AdeABC, AdeFGH, and AdeIJK, we investigated the expressions of adeB, adeG, and adeJ genes (Figures 1A-C).
Reference gene rpoB was used as a control, and susceptible strain A. pittii YMC2009/2/B2968 was used as a reference. Tigecycline appeared to be the best substrate for adeB pump, which correlated with their increased resistance and seven to 50-fold increase in its expression. This was consistent with previous findings (Perez et al., 2007;Ruzin et al., 2007;Hornsey et al., 2010) (Table 1, Figure 1). In addition, decreased susceptibility toward tetracycline, trimethoprim/sulfamethoxazole, and gentamicin also correlated with the increased expression with few exceptions. We screened for mutations in AdeRS, a two-component regulator system that controls the expression of AdeRS. G186V substitution in AdeS and A136V in AdeR was detected in all of the isolates overexpressing adeB gene, which was previously linked to increased tigecycline resistance (Hornsey et al., 2010;Rumbo et al., 2013) (Tables S3, S4). The isolate A. baumannii YMC2011/7/R812 did not contain adeRS, adeA, and adeC genes ( Table S2). The adeC gene was also absent from A. baumannii YMC2012/9/R2209 and all A. pittii strains ( Table S2). The expressions of adeG and adeJ were variable and strain-specific. Therefore, we could not find the suitable phenotypic marker regulating the pump. Overall, A. baumannii isolates showed increased expression of three RND efflux systems compared to A. pittii and A. nosocomialis. AdeFGH and its LysR-type transcriptional regulator AdeL were present in all strains (Table S5). TetR transcriptional repressor AdeN, controlling AdeIJK were interrupted by ISAba1 insertion sequence in A. baumannii YMC2012/9/R2209, YMC2012/7/R3167, and YMC2011/2/C582, which increased AdeIJK expression (Rosenfeld et al., 2012) (Table S5). In addition, we were unable to correlate the expression of BaeSR two-component system, which was previously known to influence tigecycline susceptibility by regulating adeABC genes (Lin et al., 2014) (Figure 1D). The limitation of our qRT-PCR was using different primers for different species due to the polymorphism identified in efflux pumps. This might have led to different amplicon kinetics resulting in errors in differential expressions. Finally, we could also detect the genes related to non-RND efflux pumps such as cra, amvA, abeM, abeS, and adeXYZ in all of the Acinetobacter strains. The adeDE gene was identified in YMC2003/1/R306 and YMC2013/3/R2081, and cmlA was present only in isolate YMC2013/3/R2081 ( Table S6).

Role of Porins in Resistance
Porins play a vital role in the mechanism of carbapenem resistance in Enterobacteriaceae. However, in Acinetobacter spp., their contributions toward resistance are debated, and their functions remain ambiguous (Marti et al., 2006). Previous studies indicated that loss of porins such as CarO, OprD, and 33-36Kda Omp conferred carbapenem resistance (Bou et al., 2000;Fernandez-Cuenca et al., 2003;Mussi et al., 2005;Siroy et al., 2005;Peleg et al., 2008). To determine the potential role of these porins in resistance, we performed SDS-PAGE (data not shown) and MALDI-TOF ( Figure S12). All of the panel strains showed identical OMP profiles, which were also confirmed by WGS analysis (Table S7). These results suggested that the porins did not have any role in carbapenem resistance among the panel strains. In addition, qRT-PCR for CarO, oprD, and 33-36Kda Omp did not show any significant correlation to antimicrobial resistance ( Figure S13).
In summary, all of the panel strains in our study were shortlisted depending on the resistance scheme given by François et al. (2004) and Naas and Nordmann in Antibiogram . Similar to our previous study in Klebsiella pneumoniae (Dsouza et al., 2017), we found several discrepancies in the detection scheme. The ESBL strain YMC2003/5/C86 isolated in our study was resistant to carbapenems due to presence of OXA-82, albeit the scheme indicates that ESBL strains should be susceptible to carbapenems. Similarly, it also indicates that OXA-type carbapenemases are susceptible to ceftazidime and cefepime. However, the isolated strains in FIGURE 1 | Expression of (A) AdeB, (B) AdeG, (C) AdeJ, and (D) BaeS relative to rpoB. Susceptible strain A. pittii YMC2009/2/B2968 was used as a reference and each isolate was tested in triplicate in two independent experiments. The data represent the mean ± standard error for three independent replicates. The significant difference of expression levels between samples were indicated by bars and asterisks as follows: *p < 0.05, **p < 0.01, and ***p < 0.001 using the Student's t-test. this study were resistant to both antibiotics. Therefore, we suggest the scheme to be updated and modified considering the novel mutations, acquisition of multiple resistance genes, and transposon insertion, for better detection. The main drawback of this study was characterizing unequal number of strains in each resistance classes. Strains were obtained retrospectively and therefore, limiting the number of strains.
The basic rule in the pharmaceutical industry for developing new antibiotics, or for clinicians prescribing antibacterial therapy, depends on comprehensive understanding of the mechanism(s) of resistance. For some time now, Acinetobacter spp. have been implicated in several pathological conditions, and constant efforts are being undertaken to control the spread of these organisms in hospital and community settings (Maragakis and Perl, 2008;Vila and Pachon, 2008;Metan et al., 2009;Garnacho-Montero and Amaya-Villar, 2010;Evans et al., 2013;Wisplinghoff and Seifert, 2014;Dramowski et al., 2015). There are several mechanisms suggested for Acinetobacter spp. resistance for β-lactams and other antibiotics that we have outlined in this study. In hospital settings and research laboratories, it is quite common to encounter these pathogens with various resistance phenotypes. The genotypic and phenotypic correlations in our study would definitely help clinicians and researchers to better understand the mechanism associated, along with utilizing these pathogens as reference strains. In addition, these panel strains would be highly beneficial for evaluating the efficacy of novel antibiotics or antibiotic kit on Acinetobacter spp. displaying different resistance phenotypes. An in-depth study involving the genetic mechanism conferring resistance can open many opportunities for novel drug target study and ways to control the antimicrobial resistance. We have studied the role of various resistance genes attributing to the specific resistance in detail, by referring to previous publications. Therefore, we believe that we have constructed a single platform consisting of various resistance genes illustrating its role, which can help antimicrobial researchers to understand the basics of antimicrobial resistance. Further, studies could be warranted to determine the lineage analysis on this strain and also understand the expression of virulence factors contributing toward the bacterial pathogenesis.

AUTHOR CONTRIBUTIONS
DY, JC, and YC designed the study and secured the funding. RD, NP, NLP, and TV performed the experiments. RD, PH, J-HB, and DY analyzed and interpreted the data and wrote the manuscript.