Prevalence and Differential Plasmid Versus Chromosomal Distribution of Ribosome-Targeting Antibiotic Resistance Genes in Escherichia coli Isolates from River and Untreated Wastewater Environments

TL;DR

This study examines how ribosome-targeting antibiotic resistance genes spread in E. coli from river and wastewater environments in Panama.

Contribution

It reveals distinct plasmid versus chromosomal distribution patterns of these resistance genes in different aquatic environments.

Findings

Plasmid-associated resistance genes were more common in river isolates.

Chromosomal integration was more frequent in wastewater isolates.

Ribosome-targeting resistance genes were more prevalent than other resistance types combined.

Abstract

Background/Objetives: The bacterial ribosome is a key target for several classes of antibiotics, including aminoglycosides, macrolides, tetracyclines, and amphenicols. Although resistance to these antibiotics is well documented in clinical settings, ribosome-targeting antibiotic resistance genes have received comparatively little attention in studies comprising aquatic environments, where research has primarily focused on β-lactams and fluoroquinolones. Moreover, while plasmid-mediated dissemination of resistance is well recognized, the chromosomal integration of resistance genes in Escherichia coli remains underexplored. Methods: In this study, E. coli isolates were recovered from two contaminated aquatic environments in Panama: surface water from the Juan Díaz River and influent wastewater from the Panama City wastewater treatment plant. Results: Overall, 80.8% of the isolates exhibited resistance to aminoglycosides, 37.4% to tetracycline, and 18.2% to chloramphenicol. Resistance genes against these antibiotics were identified via PCR, and their genomic location (plasmid or chromosome) was determined by whole-genome sequencing. Our results revealed a higher prevalence of plasmid-associated resistance genes in river isolates, while chromosomal integration was more frequent among wastewater isolates. Notably, ribosome-targeting antibiotic resistance genes were more frequently detected than those conferring resistance to β-lactams, quinolones, and sulfonamides together. Conclusions: These findings highlight distinct mechanisms underlying the dissemination of ribosome-targeting antibiotic resistance genes in aquatic environments, where pollutant pressure in surface waters may favor plasmid maintenance, while chromosomal integration may represent a strategy to reduce the fitness cost associated with plasmid carriage and ensure stable resistance persistence.

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1. Introduction

Antibiotics are natural or chemical compounds used to treat infections by inhibiting specific bacterial processes, such as cell wall synthesis, cell membrane biogenesis, membrane matrix formation, nucleic acid synthesis, metabolic pathways, and protein synthesis, ultimately leading to bacterial death [1,2]. Ribosome-targeting antibiotics, such as aminoglycosides, tetracyclines, macrolides, lincosamides, amphenicols, oxazolidinones, and streptogramins, interfere with protein synthesis by binding to distinct sites on bacterial ribosome subunits, causing mistranslation or blocking peptide elongation [3,4]. These antibiotics represent over 60% of the approved antibacterial agents, yet their clinical use has been restricted due to toxicity and the rapid emergence of resistance [5]. While some compounds, like the macrolide azithromycin and the aminoglycosides amikacin and tobramycin, are still used in medicine to treat atypical and life-threatening illnesses, ribosome-targeting antibiotics remain widely used in veterinary medicine and animal husbandry due to their broad-spectrum activity and low cost [6,7,8,9]. However, since most of them cannot be effectively degraded naturally, ribosome-targeting antibiotics are considered persistent pollutants in aquatic environments [10,11,12].

Bacteria have evolved multiple resistance mechanisms to evade ribosome-targeting antibiotics, including enzymatic inactivation, efflux pumps, ribosome protection, rRNA methylation, rRNA and ribosomal protein mutations, as well as overproduction of ribosomes. Among these, enzymatic inactivation is one of the most frequently observed, while rRNA methylation represents a highly effective resistance mechanism [13]. Mechanisms vary notably among antibiotic classes. For example, tetracycline resistance is mediated by over 40 acquired genes encoding efflux pumps, tetracycline-modifying enzymes, and ribosomal protection determinants [14], while resistance to amphenicols is conferred by at least 22 groups of acetyltransferases, 11 membrane transporters, and 1 rRNA methyltransferase [15,16,17]. Macrolide–lincosamide–streptogramin B (MLS) resistance arises through either mutations, ribosome methylation, or efflux pumps [18]. Regarding aminoglycosides, resistance involves a large set of antibiotic-modifying enzymes and rRNA methyltransferases [19,20,21].

Antibiotic resistance genes (ARGs) are emerging contaminants, mainly occurring in environments impacted by human activity [22]. The mobilization of these genes, particularly on plasmids, has increased significantly over the years, markedly so in low- and middle-income countries, posing a potential human and ecological risk [23]. Furthermore, plasmids are strongly associated with the spread of multidrug-resistant (MDR) bacteria, as they can transfer resistance genes both vertically (via cell division) and horizontally (to other bacteria) [24]. Moreover, ARGs can integrate into bacterial chromosomes as an adaptive strategy to reduce fitness costs [25], which can also increase the transmission of resistance through the spread of resistant clones.

Aquatic ecosystems act as key reservoirs and transmission routes for ARGs, thus representing a major concern given the possibility of the emergence of antibiotic-resistant pathogens [26]. To date, nearly all clinically relevant resistance mechanisms have been detected in rivers, lakes, oceans, and even groundwater across the world. However, environmental studies have disproportionately focused on β-lactam resistance genes, especially those encoding extended-spectrum β-lactamases (ESBLs), while overlooking resistance to ribosome-targeting antibiotics [27,28]. This underrepresentation limits our understanding of the environmental reservoirs of such ARGs and their potential contribution to future clinical resistance [29].

Considering the central role of the ribosome in bacterial viability and the increasing use of ribosome-targeting antibiotics in veterinary and agricultural settings, this study investigates the prevalence and the genomic localization (plasmid vs. chromosomal) of ribosome-targeting ARGs in E. coli isolates from two distinct contaminated water sources in Panama City. These sites represent human-derived and mixed anthropogenic pollution sources, respectively. The findings aim to shed light on the environmental dissemination of ribosomal resistance determinants and their potential mobility across bacterial populations.

2. Results

2.1. Antibiotic Susceptibility of E. coli Isolates

A total of 100 E. coli strains were isolated (50 isolates from each water sample) using the fermentation and β-D-glucuronidase (GUR) activity method [23]. The uidA gene of one strain from the Wastewater Treatment Plant (WWTP) was not detected by multiplex PCR, and therefore, this isolate was excluded from this study.

E. coli isolates resistant to aminoglycosides, tetracycline, and chloramphenicol were found in both river and wastewater samples. A total of 83 out of 99 isolates were resistant to at least one antibiotic. A similar number of resistant E. coli were isolated from the Juan Diaz River sample (42/50 isolates) and the WWTP sample (41/49 isolates). Overall, 80.8% of the isolates exhibited resistance to aminoglycosides, followed by tetracycline (37.4%) and chloramphenicol (18.2%) (Figure 1A). The proportion of resistant strains for each antibiotic class was similar in both river (Figure 1B) and WWTP samples (Figure 1C).

All 18 chloramphenicol-resistant isolates exhibited co-resistance to aminoglycosides, tetracycline, or both antibiotic classes, with most of them (15/18) exhibiting multidrug resistance (Figure 1D). Furthermore, all the isolates resistant to chloramphenicol from the river (7/7) were MDR, and 60% (12/20) of tetracycline-resistant isolates presented co-resistance to aminoglycosides (Figure 1E). In contrast, 73% (8/11) of chloramphenicol-resistant isolates from the WWTP sample were MDR, and 35% (7/17) of the tetracycline-resistant isolates presented co-resistance to aminoglycosides (Figure 1F).

Aminoglycoside-resistant isolates were found in both water samples, and such resistance extended to amikacin, gentamicin, kanamycin, neomycin, streptomycin, and tobramycin (Figure 2A). Gentamicin showed the highest proportion of resistant isolates (59/99), followed by neomycin (40/99), streptomycin (26/99), amikacin (25/99), kanamycin (13/99), and tobramycin (9/99). Resistance to gentamicin alone was the most prevalent among all the aminoglycoside-resistant isolates (Figure 2B), and other phenotypes, including multiple cases of resistance to aminoglycosides, were also identified. Among the MDR isolates from both wastewater and river samples, the most common resistance phenotype included streptomycin, tetracycline, and chloramphenicol (Figure 1D–F).

MIC analysis revealed that gentamicin-resistant isolates exhibited MIC values ≤ 8 mg/L, and despite the high number of resistant strains to this aminoglycoside, no isolate was resistant to high concentrations of gentamicin. In contrast, some isolates resistant to neomycin, kanamycin, and especially streptomycin showed MICs exceeding 128 mg/L (Figure S1). On the other hand, for tetracycline, the highest MIC observed was >128 mg/L, while sensitive isolates displayed MICs of 1 mg/L—the lowest tested value—except for one isolated with an MIC of 8 mg/L, thus earning resistant classification. Regarding chloramphenicol, the maximum MIC recorded was 256 mg/L. No significant differences were found (p > 0.05) in the MIC distributions for any of the ribosome-targeting antibiotics tested when comparing river and wastewater isolates.

E. coli isolates exhibiting high MICs for erythromycin (up to 1024 mg/L) were also found in both samples. The lowest MIC observed was 32 mg/L, and 94% of the isolates presented MICs ≥ 64 mg/L (Figure S2). Since erythromycin ECOFF is not reported for E. coli due to its intrinsic resistance, no isolate was categorized as resistant. However, macrolide resistance genes were detected in the nine isolates showing an MIC > 128 mg/L.

2.2. Ribosome-Targeting Antibiotic Resistance Genes

Molecular detection of ribosome-targeting ARGs revealed the presence of 14 distinct genes among all 83 resistant isolates from both water samples, including 6 associated with aminoglycoside resistance, 3 for tetracyclines, 3 for amphenicols, and 2 for macrolides. Moreover, 10 genes were shared between both samples; however, tet(B), catA1, and aac(3)-IId were exclusively detected in wastewater isolates, while aac(3)-IIa was detected in a single isolate from river water. The most prevalent genes in both samples, according to the antibiotic classes, were tet(A) (86.5% of tetracycline-resistant isolates), floR (83.3% of amphenicol-resistant isolates), and mphA (78% of macrolide-resistant isolates). The prevalence of aminoglycoside resistance genes was higher in the WWTP sample than in the one from the Juan Díaz River, and no 16S rRNA methyltransferases were detected. The distribution of ribosome-targeting ARGs by resistance phenotype and sample site is detailed in Table 1, with a cumulative detection of 143 genes among all resistant isolates.

PCR detection analysis revealed the presence of multiple genes conferring resistance to the same antibiotic class in most cases, except for macrolide resistance genes mph(A) and mef(B), which were not co-detected. Among the 32 isolates harboring tet(A), 6 also harbored tet(B) and/or tet(M). In fact, all four isolates harboring tet(M) also carried tet(A), and one of them additionally harbored tet(B); however, MIC difference was not observed in these isolates compared to those carrying one single tet gene. Regarding amphenicol resistance, the co-occurrence of floR and cmlA was more frequent than the presence of either gene alone, being detected in 8 out of 18 chloramphenicol-resistant strains. One of them also carried the catA1 gene. In the case of aminoglycoside resistance, gene combinations were diverse; however, ant(3″)-Ia, aph(3″)-Ib, aph(6)-Id, aph(3′)-Ia, and their combinations accounted for eight of the nine distinct aminoglycoside resistance genotypes observed.

Altogether, the combination of the ARGs detected by PCR was found to contribute to a total of 30 resistance genotype patterns among the 83 resistant isolates, where up to 11 ribosome-targeting ARGs were detected within the same host. A total of 14 and 12 unique genotype patterns were found in the WWTP and river isolates, respectively. Only four identical patterns were found in isolates from both samples (Table S2).

2.3. Whole-Genome Analysis

WGS was performed for 22 E. coli isolates obtained from untreated influent wastewater at the WWTP (n = 12) and the river water sample (n = 10). These included all MDR isolates, a subset of co-resistant isolates, and one gentamicin-resistant isolate for which PCR failed to detect resistance genes that could explain the observed phenotype. De novo assembly of WGS data revealed that 20 isolates harbored between one and four suspected plasmids, while 2 isolates had no detectable plasmids (Table S3). These plasmids ranged in size from 24 to 187 kb and were distinct within each individual isolate. Assessment of genome completeness using BUSCO identified 99–100% of the genes from the reference ‘enterobacterales_odb10’ lineage in all assemblies.

The number of ribosome-targeting ARGs per isolate ranged from 1 to 13, with no statistically significant difference in the median number of genes between river and wastewater isolates (Figure 3A). In total, 21 plasmids harboring ARGs were identified: 12 from river isolates and 9 from WWTP isolates. Plasmids from river isolates carried a higher number of ribosome-targeting ARGs compared to those from wastewater isolates. Notably, 6 out of 10 river isolates and 3 out of 12 wastewater isolates carried ribosome-targeting ARGs exclusively on plasmids. Conversely, chromosomal DNA from WWTP isolates contained more resistance genes (a median of three resistance genes) than river isolates (with a median of zero resistance genes) and, at the same time, WWTP isolates harbored more resistance genes in chromosomes than in plasmids (Figure 3B). Additionally, 9 of 12 E. coli isolated from WWTP harbored ribosome-targeting ARGs within the chromosome, compared to only 4 of 10 river isolates.

Resistance genes detected by PCR were confirmed via WGS, which also revealed additional aminoglycoside resistance genes—aadA2, aadA5, aadA17, aadA8b—and the lincosamide resistance gene lnu(F). Genes were mapped to plasmids or chromosomal locations based on their genomic coordinates, and clear associations between specific resistance genes and their genetic context were observed (Figure 3C).

Tetracycline resistance genes tet(A) and tet(M) were predominantly associated with plasmids, whereas tet(B) was exclusively chromosomal. Similarly, the amphenicol resistance genes floR and cmlA1 were mainly plasmid-borne, while catA1 was restricted to chromosomes. Among aminoglycoside resistance genes, aadA1 (also known as ant(3″)-Ia) and aadA2 were primarily plasmid-associated, whereas aph(3″)-Ib and aph(6)-Id were found on both plasmids and chromosomes. Due to low detection frequency, no clear genetic association could be established for macrolide–lincosamide–streptogramin (MLS) resistance genes (Figure 3D).

Overall, 63% (111/177) of the ARGs identified in the sequenced genomes were classified as ribosome-targeting ARGs. The number of ribosome-targeting ARGs per isolate was significantly higher than the combined total of other resistance genes, including those against β-lactams, sulfonamides, and quinolones (t-test, p < 0.05; Figure 4A). Both chromosomal and plasmid-borne resistance genes were proportionally enriched for ribosome-targeting mechanisms, with more than 50% of resistance genes in each element belonging to this category (Figure 4B). No significant difference in the proportion of ribosome-targeting ARGs was observed between isolates from the two sampling sites (p = 0.857; Figure 4C).

Although the MDR phenotype was primarily associated with the presence of a single MDR plasmid (observed in 9 out of 13 MDR isolates), chromosomal insertions containing up to seven ribosome-targeting ARGs were also identified in 4 out of 13 MDR isolates. Generally, chromosomally inserted ribosome-targeting ARGs were clustered with ARGs of other families within one or two mobile genetic elements, such as genomic resistance islands and transposons (e.g., ~35 kb resistant island from the genome of A3 isolate in Figure 5A). Similarly, MDR plasmids harbored multiple ribosome-targeting ARGs and other ARGs conferring resistance to β-lactams, quinolones, sulfonamides, trimethoprim, and even disinfectants (e.g., ~45 kb plasmid fragment from D7 isolate in Figure 5B). In addition, IS6 family transposases were frequently detected in both plasmids and chromosomal resistance islands carrying ribosome-targeting ARGs.

3. Discussion

This work analyzed the resistance profile against antibiotics targeting the bacterial ribosome of E. coli isolates from running waters in Panama City. These antibiotic classes, including aminoglycosides, tetracycline, amphenicols, and macrolides, represent the largest proportion of antimicrobial agents approved to treat infections in medicinal, veterinary, and agricultural settings. Resistance to aminoglycosides, tetracycline, and chloramphenicol was detected in both the Juan Diaz River and the WWTP of Panama City. Previous reports from two provinces in Panama identified E. coli resistant to tetracycline and chloramphenicol isolated from surface waters and fecal samples from livestock and humans [30]. Similarly, E. coli strains resistant to aminoglycosides and tetracycline have been isolated from the feces of domestic cats in Panama City [31]. Prevalence of resistance to these antibiotics is consistent with findings from broader Latin American surveillance studies [32].

Tetracycline-resistant E. coli was found in both water samples, often linked with co-resistance to chloramphenicol. In line with our findings, the presence of tetracycline-resistant E. coli in surface waters is strongly associated with sewage contamination [33]. In previous studies, co-resistance to tetracycline and ampicillin has been observed in all chloramphenicol-resistant strains isolated from wastewater effluents in Korea [34], and over 90% of chloramphenicol-resistant E. coli from humans and food animals in the United States were also resistant to tetracycline [35].

Globally, aminoglycoside resistance genes are a major component of the E. coli resistome in wastewater [36]. These antibiotics are frequently used to treat intestinal infections in livestock, and such usage contributes to the development and spread of resistance. In this study, a high proportion of isolates were resistant to the aminoglycosides gentamicin, neomycin, and streptomycin. Comparable findings have been reported in E. coli from poultry, cattle, and pigs in countries such as Bangladesh, Korea, and Spain, with up to 100% of strains being resistant to these antibiotics [37,38,39].

The most frequently detected resistance genes in both river and wastewater isolates were aph(3″)-Ib, aph(6)-Id (aminoglycosides), tet(A) (tetracyclines), mph(A) (macrolides), and floR (amphenicols). Similar patterns have been reported globally, with these genes being prevalent in environmental and human sources across more than 50 countries [40]. In addition, studies from Colombia also reported the abundance of aminoglycoside and macrolide–lincosamide–streptogramin (MLS) resistance genes in WWTP samples [41]. Genes aph(3″)-Ib and aph(6)-Id were detected in streptomycin-resistant isolates, while aph(3′)-Ia was associated with kanamycin and neomycin resistance. These findings are in line with previously described resistance patterns [42,43], and both aph(3″)-Ib and aph(6)-Id are commonly found in pathogenic E. coli strains from wastewater [34].

Resistance to aminoglycosides such as streptomycin and kanamycin was mostly explained by the presence of genes encoding aminoglycoside-modifying enzymes. However, despite the high prevalence of gentamicin-resistant isolates, no acquired resistance genes were detected for this antibiotic. Resistance to aminoglycosides like gentamicin and amikacin may result from mutations in ribosomal components, translation machinery, energy metabolism genes, or biofilm formation pathways [44,45]. Up to 106 conditionally essential genes (i.e., those critical for bacterial survival under aminoglycoside pressure) have been associated with resistance to streptomycin, gentamicin, and neomycin, including genes involved in membrane structure, stress response, cell division, ATP metabolism, and enterobacterial common antigen biosynthesis [46]. Reduced susceptibility may also be due to decreased membrane permeability [43]. Further genomic and transcriptomic studies (e.g., SNP analysis and qRT-PCR) are required to identify mutations contributing to this resistance.

Tet(B) was the second most common tetracycline resistance gene after tet(A). This is consistent with the distribution of tetracycline resistance determinants reported in Panama and across Latin America [30,47]. Notably, this is the first report of the tet(M) gene in Panama, found in isolates also carrying tet(A). In agreement with our findings, the presence of multiple tetracycline resistance genes per isolate, including tet(A), tet(B), and tet(M), has been previously documented in human and environmental isolates [33]. The co-occurrence of tet(A) and tet(M) may suggest horizontal gene transfer, possibly from enterococci to E. coli via plasmids [48,49]. Consistent with previous reports of a negative association between tet(A) and tet(B), likely due to plasmid incompatibility [49], we found that the tet(B) gene was chromosomally integrated in isolates with plasmid-borne tet(A), and no isolate harbored both genes within plasmids. This coexistence may reflect selective pressure and gene exchange driven by environmental tetracycline levels [50].

The cmlA gene was also detected in chloramphenicol-resistant isolates, though less frequently than floR. The prevalence of these genes varies geographically. For instance, predominance of floR has been reported in isolates from pig feces and water samples in Peru and China [51,52], while cmlA seems to be more common in Pakistan and Nigeria [53,54]. Chloramphenicol and tetracycline resistance are often positively correlated, possibly due to co-localization in plasmids or transposons [55]. In our findings, floR and tet(A) were frequently located on the same plasmid.

Although E. coli is considered intrinsically resistant to macrolides like erythromycin due to low outer membrane permeability, it can still act as a reservoir for macrolide resistance genes [56]. In our study, the mph(A) gene was found in isolates from both river and wastewater samples. This gene has been identified as the most prevalent macrolide resistance gene in other reports [57]. The mef(B) gene was also detected in two isolates, one from each water source, consistent with previous detections in E. coli and Salmonella from food-producing animals [58,59,60,61].

Most resistance genes were detected by PCR in isolates from both the Juan Diaz River and the WWTP, while WGS revealed differences in gene location and distribution. Resistance determinants for all antibiotic classes studied were found on both chromosomes and plasmids. In the Juan Diaz River, resistance appeared to be primarily plasmid-driven, whereas in WWTP isolates, resistance genes were found on both plasmids and chromosomal regions. This may reflect different selective pressures in each environment. The energetic cost of plasmid maintenance can be offset in contaminated environments where antibiotics or their residues are present [62]. Thus, surface waters like those of the Juan Diaz River may favor plasmid maintenance. Conversely, the chromosomal integration of resistance genes observed in WWTP isolates could represent an adaptive strategy that reduces plasmid-related fitness costs while preserving resistance [25]. However, to date, antibiotic concentrations in these environments have not been quantified and should be assessed in future studies. Further experiments should also be conducted to confirm the plasmid localization of previously described ARGs, as the plasmids in this study were identified solely based on de novo assembly, specifically as molecules flagged as circular by the Canu assembler and distinct from the much larger E. coli chromosome.

The potential advantages of chromosomal insertion of resistance genes over plasmids were not evaluated in this study. However, previous research suggests that chromosomal insertions often affect essential or conserved genes, whereas plasmids encoding multiple resistance traits can distribute fitness cost more efficiently [63]. Chromosomal resistance loci in our study frequently included two or more aminoglycoside resistance genes and one tetracycline or chloramphenicol resistance gene; for example, aph(3″)-Ib, aph(6)-Id, tet(A), and catA1 were often together and flanked by insertion sequences such as IS26 and transposons like Tn2. Meanwhile, plasmid-borne genes included aph(3″)-Ib, aph(6)-Id, mph(A), tet(A), and class I integrons. The same genes and mobile genetic elements were previously found in plasmids and E. coli chromosomes [62].

Although we did not directly assess the possible linkage between the WWTP and the Juan Diaz River, it is important to note that the WWTP discharges treated effluent into the river near its mouth. WWTPs are known hotspots for the dissemination of antimicrobial resistance (AMR) and ARGs [64]. Furthermore, WWTPs regularly use chlorine disinfection to kill contaminant bacteria, a treatment that may paradoxically promote AMR in receiving waters. In this scenario, other environmental bacteria may develop AMR by acquisition of ARGs through horizontal gene transfer or natural transformation involving DNA uptake from the lysed cells [65]. Additionally, treated effluents may also supply nutrients that facilitate E. coli proliferation [66].

4. Materials and Methods

4.1. Water Sources

A raw wastewater sample was collected in the influent at the WWTP of Panama City (9°0′59.69″ N, 79°26′47.86″ W). Wastewater at this plant is treated using aerobic treatment, nutrient removal, sludge treatment, and biogas production systems, and the effluent is discharged into the mouth of the Juan Diaz River, a 28 km long river considered one of the most contaminated rivers in Panama City, which receives raw sewage, chemical residues, and solid waste as a result of uncontrolled urbanization. Accordingly, another water sample was collected from the Juan Díaz River (9°1′7.17″ N, 79°26′13.05″ W) upstream of the treated water discharge, approximately 1 km away from the WWTP.

The samples of each site were mixed to obtain a composite water sample. Both samples were collected on the same day (less than 1 h apart), kept at 4 °C during storage and shipment, and then processed within 6 h. Samples were collected in January 2023 during the dry season.

4.2. E. coli Detection and Isolation

Detection was performed according to the Microbiological Examination of Water and Wastewater method for the determination of E. coli [67]. Briefly, detection of E. coli was based on lactose fermentation in Lauryl Tryptose broth at 37 °C, followed by incubation in Brilliant Green Bile broth at 44.5 °C. Cultivation on Eosin Methylene Blue agar at 37 °C was conducted for the isolation of presumptive E. coli. A final confirmation step was performed in EC broth supplemented with 4-methylumbelliferyl-β-D-glucuronide (EC-MUG) at 37 °C to test both lactose fermentation and β-D-glucuronidase (GUR) activity.

4.3. Molecular Confirmation of E. coli Isolates

A multiplex PCR targeting lacZ, uidA, cyd, and lacY genes was performed to confirm the identity of the EC-MUG isolates, as previously described [68], with minor modifications. The reaction mixture consisted of 1X GoTaq (Promega, Madison, WI, USA), 0.2 µM of each primer (except for lacY, which was used at 0.5 µM) (IDT), and a small portion of a bacterial colony. PCR amplification was carried out under the following conditions: initial denaturation at 94 °C for 2 min, followed by 30 cycles of denaturation at 94 °C for 30 s, annealing at 58 °C for 30 s, and extension at 72 °C for 30 s, before a final extension step at 72 °C for 5 min. Amplification products were separated by electrophoresis in 1× TBE buffer on a 1.8% agarose gel containing GelRed^®^ (Hayward, CA, USA) and visualized under UV light.

4.4. MIC Testing/Susceptibility Testing

The MIC of ribosome-targeting antibiotics against E. coli isolates was determined by the broth microdilution plate method [69]. Aminoglycosides (amikacin, tobramycin, kanamycin, gentamicin, neomycin, and streptomycin), amphenicol (chloramphenicol), tetracycline, and macrolide (erythromycin) antibiotic classes were used. Resistance was determined according to the Epidemiological cut-off value (ECOFF) established by the European Committee on Antimicrobial Susceptibility Testing (EUCAST; see Table 2). E. coli strain ATCC 25922 was used as a control.

4.5. Antibiotic Resistance Gene Detection

DNA was extracted via boiling and quantified using Nanodrop (Thermo Fisher Scientific, Waltham, MA, USA). Antibiotic resistance genes were detected by PCR. Specific primers were used to detect aminoglycoside, tetracycline, chloramphenicol, and erythromycin resistance genes. Reactions were carried out using 1× GoTaq MasterMix (Promega, USA), 0.5 µM each primer, and 1 µL of template DNA. Synthetic fragments (TwistBioscience, San Francisco, CA, USA) were used as PCR-positive controls, and random positive samples were verified by Sanger sequencing. Primer sequences and expected product sizes for each gene are detailed in Supplementary Data (Table S1).

4.6. Whole-Genome Sequencing (WGS)

DNA extraction for WGS was performed using NucleoSpin^®^ Microbial DNA kit (Macherey-Nagel, Dueren, Germany). The WGS library was prepared with a V14 Chemistry Ligation Sequencing kit (Psomagen Inc., Rockville, MD, USA) and sequenced in a PromethION instrument (Oxford Nanopore Technologies, Oxford, UK) with a R10.4.1 flow cell. Dorado v.1.0.2 (https://github.com/nanoporetech/dorado, accessed on 14 July 2025) was used for basecalling of raw sequencing data with model ‘dna_r10.4.1_e8.2_400bps_sup@v4.2.0’. De novo assembly was performed with Canu v.2.2 [70] with built-in error correction and the ‘genomeSize = 4.6 m’ option. Medaka v.2.0.0 (https://github.com/nanoporetech/medaka, accessed on 14 July 2025) was used for consensus polishing of de novo assemblies with model ‘1041_e82_400bps_bacterial_methylation’. Genome annotation was performed with the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) v.6.8 [71]. Genome completeness was assessed with BUSCO v.5.4.4 [72]. All molecules assembled de novo and flagged as circular by the Canu assembler, excluding the expected E. coli chromosome, were considered to be plasmids.

ARGs were identified using ResFinder v.4.6.0 [73] with a 90% identity threshold and the CARD database (RGI v.6.0.5 with CARD v.4.0.1) [74] with perfect and strict hit criteria. Overlapping hits between datasets were curated to avoid redundancy. Ribosome-targeting resistance mechanisms were listed and classified as plasmid-related or chromosomal-related genes according to their location within the genome. Identification of mobile genetic elements and insertion sequences was carried out using ISfinder BLAST v.2.2.31+ [75] and manually curated to include overlapping and truncated genetic elements with ≥90% identity.

4.7. Statistical Analysis

Differences between the MIC distribution of antibiotics between river and wastewater isolates were compared by using the Wilcoxon signed-rank test, performed using the ‘coin’ package. One-way ANOVA was performed to compare the number of ribosome-targeting and total antibiotic resistance genes associated with plasmid and chromosome insertions. Analyses were performed using R v.4.2.2 [76] at a significance level of 0.05.

5. Conclusions

This study highlights the widespread presence of antibiotic-resistant E. coli in both river and wastewater environments in Panama City, with high levels of resistance to aminoglycosides, tetracycline, and chloramphenicol. Ribosome-targeting ARGs were frequently detected, with distinct patterns of gene localization depending on the sample source. While plasmid-borne resistance predominated in river isolates, chromosomal integration was more common in wastewater isolates, suggesting different selective pressures or ecological dynamics. The detection of multidrug-resistant strains and mobile genetic elements carrying multiple ARGs underscores the potential for environmental dissemination of antimicrobial resistance. These findings emphasize the need for continued monitoring of urban water systems and assessment of antibiotic residues in the environment.