Introduction

Acinetobacter spp. are Gram-negative, aerobic, opportunistic bacteria which are widely distributed in hospital environments or hospitalized patients, and also in soil and water (Cisneros and Rodríguez-Baño, 2002). Acinetobacter spp. can survive on either dry or moist surfaces for long periods and grow at a range of different temperatures and pH values. Acinetobacter spp. are also known to form biofilms, known as the most effective virulence factor, which further compromises the use of antibiotics in treating infections. Acinetobacter spp., especially A. baumannii, have been numerously reported for increasing involvement in outbreaks in clinical settings. Furthermore, the emergence of multidrug-resistant (MDR) Acinetobacter has led to a rise in public health concerns (Carvalheira et al., 2021). According to the World Health Organization (WHO), one of the most emphasized antibiotic-resistant “priority pathogens” for which new antibiotics are urgently needed is A. baumannii (Tacconelli et al., 2018). Antibiotic resistance genes are easily transferred in Acinetobacter especially by conjugation, leading to the increasing emergence of MDR Acinetobacter (Leungtongkam et al., 2018).

Recent studies report that Acinetobacter spp. can be introduced into the hospital environment through kitchens or by food (Campos et al., 2019). Several studies have also reported that MDR Acinetobacter spp. is found in agricultural products such as lettuce and fruits (Carvalheira et al., 2017). MDR Acinetobacter spp. poses a major threat to hospitals causing severe nosocomial infections that are related to high mortality rates. However, few studies have reported the prevalence of MDR Acinetobacter spp. in agricultural environments in South Korea (Ababneh et al., 2022; Kim et al., 2016). The purpose of this study was to investigate the prevalence of antimicrobial resistance of Acinetobacter spp. among soil and agricultural products from agricultural fields in South Korea and analyze their virulence-related traits.

Materials and methods

Isolation of Acinetobacter spp. from agricultural environments in South Korea

Soil and crops from agricultural environments were collected randomly from different local fields located in three Korean provinces, Seoul, Jeju, and Chungnam, using standard procedures in September 2022. Collected samples were enriched with Luria–Bertani (LB) broth (Difco, Detroit, MI, USA) at 37°C overnight and plated onto the selective agar medium of Acinetobacter, CHROMagar™ Acinetobacter (CHROMagar, Paris, France). The plates were incubated at 37°C overnight. Colonies on plates were picked and confirmed with PCR using specific primers for Acinetobacter and 16S rRNA sequencing (see supplementary data Table S1). Isolated Acinetobacter spp. were stored in glycerol stock at − 80°C. The Acinetobacter spp. isolates were grown on LB media at 37°C.

Whole genome sequencing and bioinformatics analysis

Genomic DNA (gDNA) was extracted using PureHelix Genomic DNA Prep Kit (Solution Type)-Bacteria (Nanohelix, Daejon, Korea). Then, gDNA was quantified and qualified by gel electrophoresis 260/230 nm and 260/280 nm absorbance ratio and Quant-iT™ PicoGreenR dsDNA Assay Kit (Invitrogen). Following the manufacturer’s guidelines, a Nanopore MinION long-read sequencing library was prepared using a ligation sequencing-native barcoding kit (SQK-NBD114.24; Oxford Nanopore Technologies, UK) and sequenced on a FLO-MIN114 (R10.4.1) flow cell with a MinION Mk1B device and MinKNOW software (22.10.7). De novo assembly were conducted using Flye version 2.9.1 (Kolmogorov et al., 2019). Pangenome analysis was performed using Roary Pangenome Pipeline (Page et al., 2015). Roary was used (with a 95% BLASTp percentage identity cut-off) to cluster the genes encoding complete protein sequences into core (hard core and soft core) and accessory (shell and cloud) genomes.

Growth curve

Overnight cultures were diluted 1:100 in fresh LB broth in a 24-well plate. Growth was monitored every 15 min for 12 h by measuring optical density at 600 nm (OD600) using the SpectraMax i3 Plus Microplate Spectrophotometer (Molecular Devices, USA). Experiments were conducted in triplicates.

Antimicrobial susceptibility testing

Antimicrobial susceptibility was determined using a broth dilution method according to the Clinical and Laboratory Standards Institute (CLSI) guideline (CLSI, 2020). The minimum inhibitory concentrations (MICs) of colistin (Sigma), chloramphenicol (Duchefa), streptomycin (Sigma), gentamycin (Sigma), piperacillin (Duchefa), cefotaxime (Sigma), tetracycline (Sigma), ciprofloxacin (Sigma), doripenem (Sigma), imipenem (Sigma), meropenem (Sigma, Saint Louis, MO, USA) were determined using E. coli ATCC 25922 (American Type Culture Collection; ATCC, Manassas, VA, USA) as a quality control strain (CLSI, 2020). The antibiotic resistance level of chloramphenicol and streptomycin was determined based on previous studies (Wei and Yang, 2017; Yang et al., 2019).

Biofilm formation assay

The biofilm formation capacity of each strain was estimated using the crystal violet staining method described previously (Cha et al., 2019). Briefly, strains were cultured in LB broth overnight and was diluted to reach OD600 = 0.1 with fresh LB broth in 96-well plates. After incubation at 37°C for 24 h in static conditions, the plates were washed three times with PBS (Dulbecco’s Phosphate-Buffered Saline, GenDEPOT), and each well was stained with 200 μl of 0.1% crystal violet (CV) for 20 min. The plates were again washed three times to remove excess stain, and solubilized with 200 μl of 33% acetic acid for 20 min. The OD570 was then measured using the microplate spectrophotometer, to calculate the biofilm formation capacity of the isolates. The extent of biofilm formation of each isolate was compared to the reference strain, A. baumannii CCARM 12001, which is known as a multidrug-resistant strain. A. baumannii CCARM 12001 was obtained from the Culture Collection of Antimicrobial Resistant Microbes, Korea. Un-inoculated LB broth was used as a negative control. All experiments were carried out in triplicates.

Swarming motility assay

Freshly grown cultures were stabbed to enable spread of bacteria on the surface of the medium (0.4% semisolid) as described previously (Choi et al., 2013). Modified LB broth (tryptone—10 g/l; NaCl—5 g/l; yeast extract—5 g/l; micro-agar—4 g/l) was used for the motility assay (Vijayakumar et al., 2016). Plates were prepared on the same day as the inoculation. A 2 μl aliquot of an overnight culture diluted to an OD600 of 1 was spotted in the middle of the plate and allowed to dry at room temperature. Then, plates were incubated at 37°C for 24 h. Experiments were performed at least three times.

Results and discussion

Isolation and identification of Acinetobacter isolates

Eight strains of Acinetobacter spp. were isolated from soil and crops from agricultural fields in South Korea. Various Acinetobacter spp. was identified including A. seifertii, A. vivianii, A. pittii, and A. baumannii isolates (Table 1). A. seifertii and A. pittii are close relatives of A. baumannii isolates, the control of which is critical in clinical settings (Towner, 2009). The phylogenetic tree of the 8 isolated strains was constructed, showing that the isolates could be divided into 2 big clades, where RAES06 is distinctly separated from the rest of the 7 isolates (Fig. 1).

Table 1 Isolates of Acinetobacter in this study
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Fig. 1
figure 1

Phylogenetic tree and pangenome analysis of Acinetobacter isolates. Each row corresponds to a branch on the tree. Blue indicates gene presence and white indicates gene absence. The phylogeny reflects the clustering of complete protein sequence encoding genes into core and accessory genomes

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Antimicrobial resistance profiles and pangenome analysis of Acinetobacter isolates

Antibiotic susceptibility results showed that Acinetobacter isolates were highly resistant to colistin (8/8, 100%), chloramphenicol (7/8, 87.5%), and streptomycin (4/8, 50%), whereas all isolates were susceptible to gentamycin, piperacillin, cefotaxime, tetracycline, ciprofloxacin, and carbapenems (Table 2). Since previous studies have reported that mcr-1 gene was detected in colistin-resistant Acinetobacter, we tested the presence of mcr-1 gene in the isolates (Hameed et al., 2019; Kalová et al., 2021). The mcr-1 gene was not detected in all isolates based on PCR results (data not shown). However, the emrA or emrB gene, which encodes efflux pumps associated with colistin resistance in Acinetobacter, was present in all isolates (see supplementary data Table S2) (Boinett et al., 2019; Lin et al., 2017). Based on the pangenome analysis, we discovered poor correlation between the aadA gene and streptomycin resistance in isolates (Fig. 1 and Table S2). The aadA gene, which encodes 3′′-adenylyltransferase, causes resistance to streptomycin and spectinomycin (Svab et al., 1990). All isolates, except RAES03, encoded the aadA gene, but only 50% of the isolates showed high resistance to streptomycin (see supplementary data Table S2). This result may be explained by poor expression or silencing of the aadA gene (Schmidt et al., 2018). All isolates also encoded the cat and the craA gene, which are both related to chloramphenicol resistance, and all isolates except RAES06 showed high resistance to chloramphenicol (see supplementary data Table S2) (Devaud et al., 1982; Roca et al., 2009). It is notable that Acinetobacter isolates from agricultural fields are mostly resistant to colistin, chloramphenicol, and especially to streptomycin, given the prevalent and abundant use of antibiotics as pesticides in South Korea (Lee et al., 2021; Sundin and Wang, 2018).

Table 2 Minimum inhibitory concentrations (MICs) of different antibiotics against Acinetobacter isolates
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Growth rates of Acinetobacter isolates

The acquisition of antibiotic resistance is known to impair bacterial fitness resulting in a growth defect (Andersson and Hughes, 2010; Song et al., 2014). To estimate the growth rates of Acinetobacter spp. isolates, we measured bacterial growth with the MDR A. baumannii CCARM 12001 as a control strain. Most isolates exhibited significantly higher growth rates compared to the control strain (Fig. 2). Notably, RAES13, RAES19 and RAES20 showed a more rapid exponential growth phase compared to the other strains, with RAES06 exhibiting the slowest growth (Fig. 2). Interestingly, the fast-growing isolates showed the highest antibiotic resistance (27.3%) among the eight isolates, whereas RAES06 was the most susceptible (9.0%) to antibiotics (Table 2).

Fig. 2
figure 2

Growth curve of Acinetobacter isolates. Growth was monitored every 30 min for 12 h. The inset shows a magnified view at the end of the growth curve. Experiments were repeated three times and the data represent mean ± standard deviation. Results were analyzed based on CCARM 12001 results by the Student’s t-test. *P < 0.05; **P < 0.01; ns, not significant

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Biofilm formation of Acinetobacter isolates

Previous study states that biofilm formation is one of the major virulence factors of Acinetobacter. (Dehbanipour and Ghalavand, 2022). To determine the extent of biofilm formation of each isolate, the biofilm formation assay was conducted and the biofilm formation ability of each isolate was compared to the MDR A. baumannii CCARM 12001 strain. RAES01, RAES06, RAES13, and RAES20 showed similar values with the control strain, exhibiting strong biofilm formation capability (Fig. 3). On the other hand, RAES03, RAES10, RAES11, and RAES19 showed low biofilm formation compared to the control strain (Fig. 3). Some reports claim the correlation between antibiotic resistance and biofilm formation in Acinetobacter (Babapour et al., 2016; Bardbari et al., 2017). However, our results do not show any correlation between antibiotic resistance and biofilm formation (Table 2 and Fig. 3). Considering that growth and motility affect biofilm formation of bacteria, further study is required for deeper analysis (Goller and Romeo, 2008). Our results support the idea that biofilm formation does not necessarily associate with antibiotic resistance in Acinetobacter.

Fig. 3
figure 3

Biofilm formation of Acinetobacter isolates. Biofilm was quantified utilizing the crystal violet staining assay and measuring optical density at 570 (OD570). Isolates were incubated at 37°C for 24 h in static conditions. Experiments were repeated three times and the data represent mean ± standard deviation. Results were analyzed based on CCARM 12001 results by the Student’s t-test. *P < 0.05; **P < 0.01; ns, not significant

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Motility assay of Acinetobacter isolates

Motility is one of the important virulence factors of Acinetobacter (Dehbanipour and Ghalavand, 2022). To compare the motility of the Acinetobacter isolates, we investigated the swarming motility with comparison to A. baumannii CCARM 12001. All isolates were highly motile compared to the control strain (Fig. 4). RAES06 showed the lowest motility among the isolates, which may be associated with its slow growth rate (Fig. 2). Interestingly, isolates with high biofilm-producing ability were revealed to have relatively low motility than low biofilm-forming isolates in our study (Figs. 3 and 4). Low motility is suggested to be coupled with higher adherence to surfaces, enhancing the efficiency of biofilm formation. Our results demonstrated the strong correlation between low motility and high biofilm formation in Acinetobacter spp. isolated from agricultural environments.

Fig. 4
figure 4

Swarming motility of Acinetobacter isolates. (A) Bar diagram of bacterial motility. The diameter of bacterial cells present on the plate was each measured for quantitative analysis. (B) Motility agar plates 24 h post-inoculation of Acinetobacter isolates. Experiments were repeated in triplicates and the data represent mean ± standard deviation. Results were analyzed based on CCARM 12001 results by the Student’s t-test. *P < 0.05; **P < 0.01; ***P < 0.001

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In conclusion, the findings in this study demonstrated that Acinetobacter isolates from agricultural fields in South Korea were resistant to many antibiotics and showed a high biofilm formation and motility capability. Since contaminated agricultural products can be a possible transmission route of MDR Acinetobacter spp., further investigation is needed to control and reduce MDR Acinetobacter spp. in agricultural environments.