1. Introduction
Acetic acid bacteria (AAB) are primarily Gram-negative bacteria that prevalent in the atmosphere, playing a crucial role in vinegar production [
1]. These bacteria contribute to the characteristic tangy taste and acidity of vinegar by oxidizing ethanol into acetic acid during the alcohol fermentation process [
2]. This process is essential for maintaining the stability and quality of vinegar. Without the activity of AAB, vinegar production would be significantly impeded [
3,
4]. AAB are utilized in the production of various fermented foods and beverages, such as kefir, certain types of beer, nanocellulose, kombucha tea, and nata de coco. They are also found in diverse environments of warm and humid regions and are commonly present in natural settings such as fruits, flowers, fruit fly guts, and plants [
5,
6,
7]. Their adaptation in diverse environments indicates significant genetic diversity and physiological characteristics. Their adaptation to diverse environments indicates substantial genetic diversity and physiological characteristics, prompting ongoing research into their efficient industrial and food processing applications, including acetic acid production rates, tolerance to acetic acid and ethanol, and high-temperature resistance [
8,
9,
10,
11].
Concurrently, the antibiotic susceptibility of AAB, which have promising applications, has raised significant concerns regarding food safety and fermentation processes. Accordingly, unpasteurized and uncooked fermented foods may present unique antibiotic resistance risks compared to other commonly consumed foods. Most food-fermenting lactic acid bacteria, yeasts and filamentous fungi are non-pathogenic, posing limited direct threats to human health. However, the presence of antibiotic resistance genes in these beneficial fermentation microbes could still be problematic. Metagenomic studies on various fermented products have identified resistance genes in several kombucha samples, suggesting a restricted potential for AAB to harbor antibiotic resistance. Additionally, antibiotic resistance in
Acetobacter was demonstrated in a specific strain of
Acetobacter indonesiensis isolated from patient samples, which exhibited multi-drug resistance [
12]. Recently, a metagenomic analysis of human fecal samples identified the genus
Acetobacter as one of the carriers of antibiotic resistance genes [
13]. Furthermore, it has been suggested that the genetic determinants potentially involved in antibiotic resistance in
Acetobacter and
Komagataeibacter species from vinegar samples encode efflux pumps [
14].
Bacteria that survive in diverse environments may possess inherent resistance to specific classes of antibiotics, facilitated by various adaptive mechanisms. Specifically, AAB feature a unique bilayer membrane structure with an effective intracellular equilibrium mechanism, allowing them to maintain a balance between environmental and cytoplasmic pH levels. These bacteria can withstand various pH levels, contributing to their acid resistance. Factors contributing to the acid resistance of AAB include pyrroloquinoline quinone-dependent alcohol dehydrogenase (PQQADH), the lipid composition of the cell membrane, proton motive force-dependent efflux pumps, ABC transporters, and enzymes and stress proteins associated with the TCA cycle [
15,
16]. These factors may prevent the selective entry of antibiotic drugs [17‒19].
Since 2018, we have been isolating AAB from vinegar samples collected from various local regions in South Korea and the United States. To enhance the safe utility of these wild isolates, we analyzed their antibiotic susceptibility. We conducted Minimum Inhibitory Concentration (MIC) tests on 26 AAB strains using 10 different antibiotics representing various structural groups and modes of action. Currently, the primary strains used in the industrial production of acetic acid in Northeast Asia and Europe are
A. pasteurianus, isolated from traditional vinegars [11,20‒22]. Additionally, we aimed to enhance the industrial applicability of the high-acidity-producing acetic acid bacteria
K. saccharivorans CV1, which we isolated [
23]. Following the work of Wu et al. [
13], who identified
Acetobacter as one of the genera carrying top 20 antibiotic resistance gene types, Cepec and Trček [
14] selected model groups of
Acetobacter and
Komagataeibacter species to analyze antibiotic resistance through genome sequences to gather more information about antibiotic resistance in AAB. We explored potential genetic information for antibiotic resistance in the genome sequence of CV1 from the
Komagataeibacter species. This background information is crucial for advancing research and understanding of antibiotic resistance, particularly in studies involving acetic acid bacteria.
3. Discussion
Acetic acid bacteria (AAB) are widely distributed microorganisms in the natural environment. They have been utilized for the production of various fermented foods and beverages [
2] and have also been employed in the production of pharmaceuticals and medical products [
8]. While generally considered safe, antibiotic resistance in AAB has not been systematically investigated. Our research aims to contribute to the understanding of antibiotic resistance in AAB.
We analyzed the susceptibility of
Komagataeibacter and
Acetobacter species that we isolated from fruit and grain vinegars in various geographical regions. Pearson correlation coefficients were calculated to evaluate the relationship among the 26 test bacterial strains for each antibiotic (
Figure 3). The heatmap displayed relative values for the maximum MIC (µg/mL) of each antibiotic, showing the relationship between susceptibility and resistance of AAB to antibiotics with different chemical structures and mechanisms of action.
The AAB, especially
Acetobacter and
Komagataeibacter strains, possess outstanding abilities to tolerate and produce acetic acid [
46,
47,
48]. Several mechanisms enhance the survival of AAB in acidic environments. The proton motive force-dependent efflux pump can expel intracellular acetic acid out of the cell, preventing the accumulation of acetate from adversely affecting the growth and metabolism of the bacteria. This acetate efflux pump, functioning as an H
+ antiporter, differs from ABC transporters. ABC transporters, which are expected to affect the acid resistance of
E. coli, are membrane proteins named AatA. Comparing the macrolide transporter used as an antibiotic efflux pump with AatA, it is shown that they share a common structure, suggesting that the ABC transporter in
E. coli may have similar functions to antibiotic efflux pumps. Based on the findings described above, the activity of multidrug pumps could lead to resistance against various toxic compounds while also potentially increasing sensitivity to certain others.
Komagataeibacter exhibited higher resistance rates to chloramphenicol, erythromycin, and ciprofloxacin compared to
Acetobacter. Additionally, the resistance rates of AAB from fruit-based vinegar (
Figure 3B) to these antibiotics were higher than those from grains-based vinegar (
Figure 3C). This suggests that the resistance to acid is stronger in
Komagataeibater and could be attributed to the higher acidity of fruits compared to grains [
49].
One important characteristic of Gram-negative bacteria is the presence of an outer membrane that acts as a barrier against harsh external conditions such as heat or acids, protecting the cell. Additionally, the outer membrane contains beta-barrels that help maintain the internal stability of the cell and selectively allow molecules to enter. This feature is crucial as it increases the barrier against penetration by large molecules like many antibiotics, enhancing bacterial resistance [
26,
50]. However, transport across the outer membrane is mediated by porin proteins forming water-filled channels [
25,
26]. Tetracycline, which showed sensitivity to strain 26, is considered an intermediate lipophilic molecule. Porin channels, namely OmpF and OmpC, allow the entry of cation-tetracycline complexes. These cation-metal ion-antibiotic complexes are attracted through the membrane by the transmembrane potential, accumulating in the periplasm. Here, the metal ion-tetracycline complex is likely released, generating tetracycline, a weakly lipophilic substance, which can diffuse through the inner (cytoplasmic) membrane region of the cell membrane [
51]. This combination of properties is crucial for tetracycline to function as an antibiotic because it can traverse both the aqueous and lipid barriers to reach its target site within bacterial cells. Additionally, hydrophilic compounds of the aminoglycoside antibiotic family (GM, SM, KM) enter the periplasm through porins via self-promoted uptake [
44]. Thus, the reason for sensitivity to strain 26 could be understood. The sensitivity of aminoglycoside antibiotics, GM, SM, and KM, as well as tetracycline antibiotics, was greater for AAB originating from cereal vinegar (
Figure 3B,C).
Penicillin-like antibiotics also enter bacteria through porins, and the rate of diffusion through these porins depends on the size of the drug molecule. Aztreonam, which is similar in size to penicillin, is expected to enter slowly through porins. This was indicated by its high resistance (>256 µg/mL) observed in tested 26 AAB strains. In contrast, smaller antibiotics like ampicillin diffuse much faster, demonstrating sensitivity in the tested 26 AAB strains. This suggested that the size of antibiotics and the characteristics of porins play a crucial role in determining susceptibility or resistance to specific penicillins. The sensitivity of penicillin antibiotics, particularly ampicilline, was greater for AAB originating from cereal vinegar (
Figure 3B,C).
To gain a comprehensive understanding of antibiotic resistance mechanisms in AAB, genome-wide studies have been conducted to explore integrated antibiotic resistance systems. These studies, previously reviewed [
13,
14], play a crucial role in understanding the mechanisms of antibiotic resistance. Through genomic analysis of
K. saccharivorans CV1, we identified intrinsic genetic information related to multidrug resistance efflux pump transporters. Understanding the resistance mechanisms of
Komagataeibacter species and
Acetobacter species was facilitated through comparative literature analysis, as depicted in
Table 3. Genetic homologs associated with chloramphenicol resistance, such as the multidrug efflux pump AcrAB [
52] and the Bcr/CflA subfamily [
36,
37], as well as NorM involved in ciprofloxacin resistance [
39], and MFS family (EmrA) or ATP-transporters related to macrolides-lincosamides resistance [
44], have been detected. This helped understand the resistance observed to clindamycin antibiotics in all 26 strains of AAB.
The AAB registered as food raw materials by the Ministry of Food and Drug Safety (MFDS) in South Korea for vinegar production include
A. aceti,
A. pasteurianus,
K. europaeus, and
K. hanseni. Among these,
A. pasteurianus is the most commonly used for vinegar production [
16]. However,
Komagataeibacter, which exhibits strong alcohol tolerance and excellent acid production, is also commonly used in vinegar production [
49].
K. saccharivorans CV1, isolated by us, also demonstrated industrial value with acid production of 9.3% and 8.4% at alcohol concentrations of 10% and 9%, respectively [
23]. In the analysis of antibiotic sensitivity for food safety evaluation of CV1, the antibiotic sensitivity of CV1 was found to be similar to that of
A. pasteurianus originating from fruit vinegar rather than
A. pasteurianus originating from grain vinegar, as demonstrated by Pearson correlation (
Figure 4A,B). It appears that the pattern of antibiotic resistance in
K. saccharivorans CV1 corresponded to the acid resistance of
Komagataeibacter species and the acid-adapted AAB originating from fruit vinegar [
49].
4. Materials and Methods
4.1. Preparation of Acetic Acid Bacteria (AAB)
In our study, we used the 26 strains of AAB isolated from traditional vinegars and revived from frozen stocks stored at -80°C using culture medium for AAB named YGC agar medium, which is composed of yeast extract (5 g/L), glucose (30 g/L), CaCO
3 (10 g/L), ethanol (40 g/L), and agar (20 g/L) [
10]. The plates were incubated for two days at 30°C.
4.2. Assesment of Antibiotic Resistance for AAB
The method used to detect resistance in AAB involved applying MIC-gradient strips directly onto agar plates that had been inoculated with AAB. After successful recovery, the strains were pre-cultured on YGC media and incubated at 30°C for two days. Subsequently, the biomass obtained from each plate was harvested into a liquid medium composed of yeast extract (5 g/L), glucose (5 g/L), glycerin (10 g/L), and MgSO4·7H2O (0.2 g/L). The turbidity was then adjusted to an OD660 of 0.5. The prepared bacterial suspension was evenly spread across the entire surface of either Mueller-Hinton (MH; Oxoid Ltd., Basingstoke, Hants, UK) or YGC (without CaCO3 and ethanol) plates using a sterilized swab (BD BBL™ Culture Swab™, Sparks, MD, USA). Then, antibiotic Etests were applied to the plates using the following commercial antibiotic strips from bioMerieux Inc. (Hazelwood, MO, USA): ampicillin (AM, 0.016~256 µg/mL), chloramphenicol (CL, 0.016~256 µg/mL), erythromycin (EM, 0.016~256 µg/mL), gentamicin (GM, 0.016~256 µg/mL), streptomycin (SM, 0.064~1024 µg/mL), kanamycin (KM, 0.016~256 µg/mL), clindamycin (CM, 0.016~256 µg/mL), tetracycline (TC, 0.016~256 µg/mL), aztreonam (AT, 0.016~256 µg/mL), and ciprofloxacin (CI, 0.002~32 µg/mL). Measurements were taken after incubating the inoculated medium at 30°C for two days. The MIC values were recorded as the lowest concentration of antibiotics at which bacterial growth was completely inhibited. The antibiotic resistance of the strains was categorized into three levels such as resistant (R), intermediate (I), and susceptible (S) as recommended by CLSI.
4.3. Bioinformatics
To analyze the presence of homologs related to antibiotic resistance in the genomic sequences of the acetate-producing bacterial CV1 strains listed in
Table 1, we utilized the online tool Clusters of Orthologous Groups of proteins (COGs) analysis using the NCBI database [
53]. In COG analysis, we used BLAST to compare the given sequences with the COG database to identify orthologous groups and gained insights into the potential functions of query sequences based on their similarity to known sequences in the COG database. We primarily evaluated the significance of matches through information such as similarity of matches, E-value, and bit score. Predicted proteins were subjected to psiblast (v. 2.6.0+) against COG database with followed options; -max_target_seqs 1 -evalue 0.1 -comp_based_stats 0. Proteins of defense mechanisms such as multidrug efflux pump within COG categories were shown in Supplementary
Table 2.
4.4. Correlation Heatmap
The acquisition of relevant graphs was achieved by Excel version 2020 (Microsoft Office Professional Plus), while a significant difference analysis was performed by SPSS (SAS Institute Inc., USA) (ANOVA), where P < 0.05 indicated a significant difference between samples. The related value percentage (%) was calculated using the following formula:
Related Value (RV) % = Maximum value/corresponding value × 100.