Abstract
The rising prevalence of multidrug-resistant (MDR) bacteria in poultry, particularly in chickens, poses a serious public health risk, as these pathogens can be transmitted to humans, causing difficult-to-treat gastroenteritis. Therefore, this study was designed to isolate and characterize multidrug-resistant bacteria in poultry chickens, as well as to determine the antibiotic susceptibility and plasmid profiles of resistant bacterial isolates. A total of 360 samples were collected from the cloacae, mouth, and nares of poultry-chickens and analyzed bacteriologically, with antibiotic susceptibility testing conducted following standard microbiological procedures. Plasmid analysis and curing were performed to assess molecular weight and identify resistance mechanisms, whether plasmid-mediated or not. The MDR bacteria isolated from poultry-chickens included Proteus mirabilis (65, 43.6%), Escherichia coli (50, 33.6%), Pseudomonas aeruginosa (7, 4.7%), Serratia marcescens (6, 4.0%), Serratia fonticola (5, 3.4%), Klebsiella oxytoca (3, 2.0%), Klebsiella pneumoniae (2, 1.3%), Salmonella enterica subsp. diarizonae (1, 0.7%), Shigella sonnei (1, 0.7%), Shigella flexneri (1, 0.7%), Escherichia vulneris (1, 0.7%), Enterobacter aerogenes (1, 0.7%), and Morganella morganii (1, 0.7%). Out of the 360 poultry samples analyzed, 137 (38.1%) bacterial isolates were resistant to at least three classes of antibiotics, indicating a high level of multidrug resistance among the isolates. All gastroenteric bacterial isolates (n = 137) showed 100% resistant to both meropenem and cephalosporin, but showed minimal resistance to amikacin (2.9%), making it the most effective antibiotic against these bacteria. Plasmid profiling on ten MDR isolates revealed the presence of at least one plasmid band ranging from 500 bp to 10 kbp, suggesting a possible role of plasmids in mediating antibiotic resistance. These findings underscore the serious implications of antibiotic resistance in poultry and highlights the link between plasmids and resistance, emphasizing the importance of carefully monitoring antibiotic use in developing countries, particularly in poultry farms.
Keywords: Food-borne pathogens, Microbial ecology, Animal husbandry, Plasmid-mediated antimicrobial resistance
Introduction
Chicken meat ranks as a major protein source globally due to its high digestibility, formidable amino acid profile, low fat content, health-promoting micronutrients, safety, affordability, and relatively low environmental impact compared to other meat types. It also plays a vital role in sustainable food production strategies [11, 27, 54]. Although chicken meat is generally regarded as a dependable and safe source of protein, it can, oftentimes, be contaminated with heavy metals and pathogenic microorganisms [14].
Poultry meat quality is influenced by several factors such as breeding practices, genetic traits of the birds, and handling methods during processing [5]. Poor farming practices, including the indiscriminate use or overuse of antibiotics, poor sanitation, overstocking densities, and suboptimal nutrition, can degrade meat quality and increase the risk of pathogen contamination in poultry [28].
Antibiotics are frequently used in poultry farming to prevent and control diseases and promote growth [38]. However, with the increasing demand for poultry products, the indiscriminate use and overuse of antibiotics in chicken production have become serious public health and industry challenges [29]. This challenge is particularly observed in regions where regulatory oversight and awareness are limited [30]. The indiscriminate use and abuse of antimicrobials has accelerated antimicrobial resistance (AMR), leading to difficult-to-treat infections, increased healthcare costs, higher mortality rates, and wider spread of resistant microbial strains- posing serious health and economic challenges globally [32, 34].
An additional concern with the overuse of antibiotics in poultry production is the ‘one health’ framework, which discusses the interconnectivity of disease incidence from one host, reservoir, or environment to a healthy host [13, 43]. The spread of antimicrobial resistance genes (AMGs) poses food safety risks and zoonotic threats—via farm worker exposure, environmental contamination, and consumption of undercooked or contaminated poultry parts- highlighting the interconnectedness of animal, human, and environmental health. Growing global awareness over the adverse effects of antimicrobial resistance (AMR) has prompted increased research into sustainable alternatives to synthetic antibiotics and effective strategies to curb resistance development [2]. Given the importance of chicken products in the human food chain, it is imperative to understand the extent of AMR amongst selected poultry farms in Ikot Ekpene, Nigeria, as part of efforts in addressing this global and imminent public health issue.
Sampling of the cloaca, mouth, and nasal passages of poultry offers valuable insight into the antibiotic-resistant bacteria and resistance genes reservoirs [20, 34]. These poultry parts are thought to be the best places to detect AMR microorganisms, thereby enabling effective identification and monitoring of emerging resistance strains.
This study aimed to isolate and characterize multidrug-resistant bacteria from poultry, assess antibiotic resistance patterns, and analyze plasmids in resistant isolates. These findings offer critical insights for designing evidence-based interventions and policies to combat antimicrobial resistance and spread in poultry farming.
Methodology
Study design
A cross-sectional study was conducted in six commercial poultry farms in Ikot Ekpene local government area of Akwa Ibom State, Nigeria. Sampling was carried out with the consent and voluntary participation of the farmers.
Sample size
The sample size was determined using Cochran’s formula (Eq. 1) based on previously reported prevalence of 42.5% multidrug-resistant bacterial pathogens from poultry [41].
 |
1 |
where N = sample size
Z = score for a given confidence interval, usually set at 1.96 for 95%
P = prevalence value of 42.5% (0.425).
e = permissible error of estimation, which is taken as 0.05 (5%)
 |
For this research, 120 samples were obtained from layers, broilers, and two-week-old chicks, making a total of 360 samples.
Sample collection
The cloacal, mouth, and nasal swab samples were aseptically collected from each chicken group using sterile cotton swabs. These sampling sites were selected because they harbor bacteria of the Enterobacteriaceae family [36]. The swab samples were immediately placed in an ice pack and transported to the laboratory for bacteriological analysis.
Isolation and identification
Samples were inoculated into 5.0 mL buffered peptone water for pre-enrichment and incubated at 37 °C for 24 h. Subsequently, a loopful of the enriched samples in broth was cultured on distinct selective media such as Eosin methylene blue agar (EMB) for E. coli, Salmonella-Shigella agar (SSA) for Salmonella and Shigella species, MacConkey agar (MCA) for other lactose fermenters, and incubated at 37 °C for 18–24 h.
The cultural characteristics of the resulting colonies were observed. Colonies that appeared bluish black with a green metallic sheen on EMB were indicative of E. coli. Colourless colonies with a dark center on SSA were suggestive of Salmonella species. On MCA, both lactose-fermenting (pink or red) and non-lactose-fermenting colonies were selected for further biochemical testing. Large pink mucoid colonies on MCA were indicative of Klebsiella species, while slightly mucoid, light pink colonies were suggestive of Enterobacter species.
Representative colonies were sub-cultured onto nutrient agar plates and incubated at 37 °C for 24 h to obtain pure cultures. Biochemical identification of the isolates was performed using standard tests, including Methyl Red–Voges Proskauer (MR-VP), citrate utilization, triple sugar iron (TSI), oxidase, urease, and motility tests, as well as examination of colony morphology, microscopy, and Gram staining, following the described standard procedures [7].
Identification of the isolates using VITEK 2 compact
Further identification of the isolates was performed using the VITEK 2 Compact system (bioMérieux, Craponne, France). The VITEK 2 compact system is an automated microbiology system utilizing growth-based technology with a Gram-negative (GN) identification card.
Fresh pure cultures of the isolates were first prepared on NA plates. After overnight incubation, a sterile swab was used to transfer morphologically similar colonies into a test tube containing 3.0 mL of sterile 0.45% saline. The turbidity of the suspension was adjusted to 0.50–0.63 McFarland standard using the VITEK 2 DensiCHECK device.
The tube with the prepared cultural suspension was then placed into the GN cassette, and the corresponding identification card was inserted into the adjacent slot. The transfer tube was fitted into the suspension tube, and the loaded cassette was placed manually into the vacuum chamber station. The card was then sealed and automatically incubated at 35.5 ± 1.0 °C.
The GN card utilizes 47 established biochemical tests and newly developed substrates to identify bacterial species. Final identification results were automatically generated within approximately 10 h or less [40].
Standardization of test bacteria
All test bacterial isolates were standardized before use for antibiotic susceptibility testing by inoculating 5 mL of sterile normal saline into test tubes with a loopful of 18-h plate culture. The bacterial suspension was then diluted with sterile water to achieve a final microbial concentration of 105 colony-forming units per milliliter (cfu/ml). The turbidity of each suspension was adjusted and confirmed by comparing it with the 0.5 McFarland turbidity standard [12, 16].
Antibiotics susceptibility testing
The antibiotic susceptibility profile of the isolates was determined using the Kirby-Bauer disc diffusion method in accordance with the Clinical and Laboratory Standards Institute [10] guidelines. An overnight culture of each test bacterium grown in nutrient broth was adjusted to the 0.5 McFarland turbidity standards. Using sterile cotton swabs, the surface of Mueller–Hinton Agar (MHA) plates was inoculated by swabbing the bacterial suspension evenly in three directions, rotating the plate each time to ensure even distribution.
The inoculated plates were allowed to dry for approximately 10 min at room temperature before antibiotic discs were aseptically placed on the surface of the agar using sterile forceps. The plates were left at room temperature for the pre-diffusion, then inverted and incubated aerobically at 37 °C for 16–18 h.
After incubation, the diameter of the zones of growth inhibition was measured to the nearest millimeter, and results were interpreted as susceptible, intermediate, or resistant according to the CLSI interpretative chart zone size [10, 12]. Isolates exhibiting resistance to three or more classes of antibiotics were classified as multidrug-resistant (MDR) bacteria. The tested antibiotic discs were of different classes commonly used in both humans and veterinary medicine and included tetracycline (10 μg), cotrimoxazole (25 μg), gentamicin (10 μg), cefuroxime (30 μg), ceftriaxone (30 μg), cefotaxime (30 μg), ceftazidime (30 μg), ciprofloxacin (5 μg), chloramphenicol (10 μg), amikacin (30 μg), vancomycin (30 μg) and meropenem (10 μg) (Biomark, India).
Determination of multiple antibiotic resistance index (MARI)
The multiple antibiotic resistance index (MARI) was used to investigate the exposure of the isolates to antibiotics. To determine the resistant profile of the isolates, MARI was evaluated using the Eq. (2) below:
 |
2 |
Where a is the number of antibiotics to which the isolates are resistant, while b is the total number of antibiotics to which the isolates were tested [46].
Plasmid analysis of resistant isolates
Plasmid analysis was performed using the Zyppy™ Miniprep Kit (Catalog No. D4036) (https://www.zymoresearch.com) to determine whether antibiotic resistance was plasmid or chromosomally mediated. Luria–Bertani (LB) broth media were prepared according to the manufacturer’s instructions and sterilized at 121 °C for 15 min.
Exactly 600 μL of bacterial culture grown in LB medium was transferred to a 1.5 mL microcentrifuge tube and centrifuged for 30 s at 14,000 rpm. The supernatant was discarded, and 100 μL of 7X Blue Lysis Buffer 1 was added. The tube was gently inverted 4–6 times to ensure thorough mixing. The solution changed from opaque to clear blue, indicating complete lysis.
Subsequently, 350 μL of cold Yellow Neutralization Buffer was added and mixed thoroughly by inverting the tube. The solution turned yellow, with the formation of a yellowish precipitate, indicating successful neutralization. To ensure complete neutralization, the sample was inverted for an additional 2–3 times and then centrifuged at 11,000–16,000 × g for 2–4 min.
Approximately 900 μL of the resulting supernatant was transferred to the Zymo-Spin™ IIN column placed in a collection tube and centrifuged for 15 s. The flow-through was discarded, and the column was returned to the same collection tube. Next, 200 μL of Endo-Wash Buffer was added and centrifuged for 30 s, followed by 400 μL of Zyppy™ Wash Buffer and centrifugation for 1 min.
The column was then transferred to a clean 1.5 mL microcentrifuge tube, and 30 μL of Zyppy™ Elution Buffer was added directly to the column matrix. After standing for 1 min at room temperature, the column was centrifuged for 30 s to elute the plasmid DNA [9].
Agarose gel electrophoresis for plasmid profiling
Two grams of agarose were weighed and mixed with 100 mL 1xTAE in a microwavable flask. This was microwaved for 3 min until the agarose completely dissolved. The agarose solution was allowed to cool down to about 50 °C for 5 min. Next, 10 μL EZ Vision™ DNA stain was added to the molten agarose to enable visualization of the DNA under ultraviolet (UV) light.
The agarose solution was poured into a gel tray with the comb in place and left to stand at room temperature for 2—30 min until completely solidified. After solidification, the comb was carefully removed, and the gel was placed in the electrophoresis tank. The gel box was filled with 1 × TAE buffer until the gel was fully submerged.
A molecular weight DNA ladder was introduced into the first well, and loading buffer was added to each of the purified plasmid DNA samples before carefully loading them into the remaining wells. Electrophoresis was carried out at 100 V for about 1 h. The power supply was turned off after the run, followed by disconnecting the electrodes. The gel was then carefully removed from the gel box and visualized under UV light to observe the purified DNA fragments [45].
Plasmid curing
Plasmid curing was performed using acridine orange dye. Each bacterial isolate was grown overnight in Luria–Bertani (LB) broth containing 10% sodium dodecyl sulfate (SDS). A stock solution of acridine orange (10,000 µg/mL) was prepared in sterile distilled water, and 1 mL of the stock solution was dispensed into test tubes containing 2 mL of the broth. The content of the tubes was vortexed thoroughly to ensure proper mixing and then allowed to settle. Subsequently, 20 µL of standardized bacterial culture was inoculated into each tube containing the acridine orange- LB broth mixture and incubated overnight at 37 °C.
Following incubation, cultures were sub-cultured to obtain pure colonies. Antibiotic susceptibility testing was then performed to determine any change in the resistant pattern, indicating plasmid loss [37].
Statistical analysis
All variables in this study were compared and analyzed using the Statistical Package for Social Sciences (SPSS version 24.0). P-value < 0.05 was considered statistically significant, and > 0.05 was insignificant.
Results
Out of the 360 poultry samples (cloaca, mouth, and nasal swabs) examined, 137 were culture-positive, presenting a 38.06% prevalence of gastroenteric bacteria. Salmonella enterica subsp. diarizonae, Shigella sonnei, Shigella flexneri, Escherichia vulneris, Enterobacter aerogenes, and Morganella morganii subsp. Sibonii were the least common bacteria, while Proteus mirabilis (65; 47.45%) and Escherichia coli (50; 36.50%) were the most prevalent, respectively. Table 1 shows the prevalence of intestinal bacteria isolated from chicken parts in Ikot Ekpene. The P-value of 1.0 indicates that there was no statistically significant difference in the distribution of bacterial isolates.
Table 1.
Distribution of Gastroenteric Bacteria Isolated from Poultry (n = 360)
| Bacteria | Number of Bacteria (%) | P-value |
|---|---|---|
| Salmonella enterica | 1 (0.73) | 1.0 |
| Shigella sonnei | 1 (0.73) | |
| Shigella flexneri | 1 (0.73) | |
| Escherichia vulneris | 1 (0.73) | |
| Enterobacter aerogenes | 1 (0.73) | |
| Morganella morganii | 1 (0.73) | |
| Klebsiella pneumoniae | 2 (1.46) | |
| Klebsiella oxytoca | 3 (2.19) | |
| Serratia fonticola | 5 (3.65) | |
| Serratia marcescens | 6 (4.38) | |
| Escherichia coli | 50 (36.50) | |
| Proteus mirabilis | 65 (47.45) | |
| Total | 137 (38.06) |
The distribution of gastroenteric bacterial isolates among different poultry types is presented in Table 2. Two-week-old chicks showed the lowest bacterial prevalence (26.28%), whereas the layers recorded the highest prevalence (39.42%), followed by broilers (34.31%). However, since the P-value was greater than 0.05, the differences observed amongst the three poultry types were not statistically significant.
Table 2.
Distribution of Gastroenteric Bacteria by Poultry Breeds
| Bacteria species | Layers (n = 120) (%) | Chicks (n = 120) (%) | Broilers (n = 120)(%) | Total Frequency (n = 360) (%) |
|---|---|---|---|---|
| Salmonella enterica | 1 (1.85) | 0 (0.00) | 0 (0.00) | 1 (0.73) |
| Shigella sonnei | 0 (0.00) | 1 (2.78) | 0 (0.00) | 1 (0.73) |
| Shigella flexneri | 1 (1.85) | 0 (0.00) | 0 (0.00) | 1 (0.73) |
| Klebsiella pneumoniae | 0 (0.00) | 2 (5.56) | 0 (0.00) | 2 (1.46) |
| Klebsiella oxytoca | 1 (1.85) | 1 (2.78) | 1 (2.13) | 3 (2.19) |
| Escherichia coli | 20 (37.04) | 18 (50.0) | 12 (25.53) | 50 (36.5) |
| Escherichia vulneris | 0 (0.00) | 0 (0.00) | 1 (2.13) | 1 (0.73) |
| Enterobacter aerogenes | 0 (0.00) | 1 (2.78) | 0 (0.00) | 1 (0.73) |
| Morganella morganii | 0 (0.00) | 0 (0.00) | 1 (2.13) | 1 (0.73) |
| Serratia marcescens | 0 (0.00) | 3 (8.33) | 3 (6.38) | 6 (4.38) |
| Serratia fonticola | 1 (1.85) | 2 (5.56) | 2 (4.26) | 5 (3.65) |
| Proteus mirabilis | 30 (55.56) | 8 (22.22) | 27 (57.45) | 65 (47.45) |
| Total | 54 (39.42) | 36 (26.28) | 47 (34.31) | 137 (38.06) |
The antibiotic susceptibility pattern of gastrointestinal bacteria isolates is shown in Fig. 1. Overall, there was variable levels of resistance were observed among bacterial isolates against tested antibiotics, with most showing resistance to at least two antibiotic agents. All isolates (n = 137) were resistant to meropenem (100%), followed by cefotaxime and ceftazidime (98.54%). High resistance to cefuroxime (83.21%) and ceftriaxone (70.07%) was also observed, while amikacin (2.92%) recorded the least resistance.
Fig. 1.
Antibiotic Resistance of Gastroenteric Bacteria to the Tested Antibiotics. KEY: TET = Tetracycline, COT = Cotrimoxazole, GEN = Gentamicin, AMK = Amikacin,CRX = Cefuroxime, CTR = Ceftriaxone, CTX = Cefotaxime, CPZ = Ceftazidime, CHL = Chloramphenicol, CIP = Ciprofloxacin, VAN = Vancomycin, MEM = Meropenem
Figures 2 and 3 illustrate the resistance profiles of individual bacterial species, revealing that all gastroenteric bacteria were highly resistant to meropenem and all the tested cephalosporins.
Fig. 2.
Phenotypic antibiotic resistance (%) of Proteus, E. coli, Salmonella, and Morganella species. KEY: TET = Tetracycline, COT = Cotrimoxazole, GEN = Gentamicin,AMK = Amikacin,CRX = Cefuroxime, CTR = Ceftriaxone, CTX = Cefotaxime, CPZ = Ceftazidime, CHL = Chloramphenicol, CIP = Ciprofloxacin, VAN = Vancomycin, MEM = Meropenem
Fig. 3.
Phenotypic antibiotic resistance (%) of Shigella, E. aerogenes, Klebsiella, and Serratia species. KEY: TET = Tetracycline, COT = Cotrimoxazole, GEN = Gentamicin,AMK = Amikacin,CRX = Cefuroxime, CTR = Ceftriaxone, CTX = Cefotaxime, CPZ = Ceftazidime, CHL = Chloramphenicol, CIP = Ciprofloxacin, VAN = Vancomycin, MEM = Meropenem
The MDR profile of bacterial isolates is summarized in Table 3. All 137 gastroenteric bacterial isolates were resistant to at least three different classes of antibiotics, indicating a high level of multidrug resistance. The proportion of isolates (25.5%) were resistant to five antibiotics classes, followed by 19.7% resistant to six antibiotics classes.
Table 3.
Multidrug Resistance Pattern of Bacterial Isolates from Poultry
| Number of classes of antibiotics resisted | Number of Isolates | Percentage of Isolates |
|---|---|---|
| Three | 19 | 13.9 |
| Four | 16 | 11.7 |
| Five | 35 | 25.5 |
| Six | 27 | 19.7 |
| Seven | 22 | 16.1 |
| Eight | 18 | 13.1 |
Table 4 presents the distribution of MDR profiles among the bacterial species, showing that each bacterial species exhibited resistance to at least one agent in three or more antimicrobial classes. The distribution of antibiotic resistance among the bacterial isolates was highly variable.
Table 4.
Multidrug Resistance Profile among Bacterial Species from Poultry
| Bacterial species | No. of Isolate | Resistant Classes |
|---|---|---|
| Salmonella enterica | 1 | TET, SUL, AMG, CEPH, FQ, GLY, CAR |
| Shigella flexneri | 1 | TET, SUL, CEPH, FQ |
| Escherichia coli | 1 | TET, SUL, AMG, CEPH, PHN, FQ, GLY, CAR |
| Enterobacter aerogenes | 1 | TET, SUL, CEPH, GLY, CAR |
| Morganella morganii | 1 | TET, CEPH, FQ, GLY, CAR |
| Klebsiella pneumoniae | 1 | TET, SUL, AMG, CEPH, FQ, GLY, CAR |
| Serratia marcescens | 1 | TET, SUL, AMG, CEPH, PHN, FQ, GLY, CAR |
| Proteus mirabilis | 1 | TET, SUL, AMG, CEPH, PHN, FQ, GLY, CAR |
| Pseudomonas aeruginosa | 1 | TET, SUL, AMG, CEPH, PHN, FQ, GLY, CAR |
| Paracoccus yeei | 1 | TET, SUL, AMG, CEPH, FQ, GLY, CAR |
| Rhizobium radiobacter | 1 | SUL, CEPH, FQ, CAR |
TET Tetracycline, SUL Sulfonamides, AMG Aminoglycosides, FQ Fluroquinolones, GLY Glycopeptides, CAR Carbapenems, CEPH Cephalosporins, PHN Phenicols
As shown in Table 5, three isolates exhibited resistance to eleven antibiotics, including TET, COT, GEN, CRX, CTR, CTX, CPZ, CHL, CIP, VAN, and MEM. Additionally, ten isolates were resistant to ten antibiotics —TET, COT, GEN, CRX, CTR, CTX, CPZ, CHL, CIP, and MEM.
Table 5.
Phenotypic Resistance Profile of Bacterial Isolates from Poultry in Ikot Ekpene Town
| Resistance Phenotypes | Number of Isolates |
|---|---|
| TET, COT, GEN, AMK, CRX, CTR, CTX, CPZ, CHL, CIP, VAN, MEM | 3 |
| COT, GEN, AMK, CRX, CTR, CTX, CPZ, CHL, CIP, VAN, MEM | 1 |
| TET, COT, GEN, CRX, CTR, CTX, CPZ, CHL, CIP, VAN, MEM | 10 |
| TET, COT, GEN, AMK, CRX, CTR, CTX, CPZ, CHL, CIP, MEM | 1 |
| TET, COT, AMK, CRX,CTX, CPZ, CHL, CIP, VAN, MEM | 1 |
| TET, COT, GEN, AMK, CRX, CTR, CPZ, CHL, CIP, MEM | 1 |
| TET, COT, GEN, CTR, CTX, CPZ, CHL, CIP, VAN, MEM | 2 |
| TET, COT, GEN, CRX, CTR, CTX, CPZ, CHL, CIP, MEM | 1 |
| TET, COT, CRX, CTR, CTX, CPZ, CHL, CIP, VAN, MEM | 2 |
| TET, GEN, CRX, CTR, CTX, CPZ, CHL, CIP, VAN, MEM | 2 |
| TET, COT, GEN, CRX, CTR, CTX, CPZ, CIP, VAN, MEM | 5 |
| TET, COT, GEN, CRX, CTX, CPZ, CHL, CIP, VAN, MEM | 2 |
| COT, GEN, CRX, CTR, CTX, CPZ, CHL, CIP, VAN, MEM | 1 |
| TET, COT, GEN, CRX, CTX, CPZ, CIP, VAN, MEM | 5 |
| TET, COT, GEN, AMK, CTR, CTX, CPZ, VAN, MEM | 1 |
| TET, COT, CRX, CTX, CPZ, CHL, CIP, VAN, MEM | 2 |
| TET, GEN, CRX, CTR, CTX, CPZ, CHL, CIP, MEM | 1 |
| TET, COT, GEN, CTX, CPZ, CHL, CIP, VAN, MEM | 1 |
| TET, COT, GEN, CRX,CTR,CTX, CPZ, CIP, MEM | 1 |
| TET, COT, CRX, CTR, CTX, CPZ, CHL, CIP, MEM | 2 |
| TET, COT, CRX, CTR, CTX, CPZ, CHL, VAN, MEM | 1 |
| TET, COT, GEN, CRX, CTR,CTX, CPZ, CIP, MEM | 1 |
| TET, COT, CRX, CTR, CTX, CPZ, CIP, VAN, MEM | 3 |
| TET, COT, CRX, CTR, CTX, CPZ, CHL, MEM | 1 |
| COT, GEN, CRX, CTR, CTX, CPZ, CIP, MEM | 3 |
| TET, COT, CRX, CTR, CTX, CPZ, VAN, MEM | 5 |
| COT, CRX, CTR, CTX, CPZ, CIP, VAN, MEM | 1 |
| TET, CRX, CTR, CTX, CPZ, CIP, VAN, MEM | 3 |
| TET, COT, CRX, CTR, CTX, CPZ, CIP, MEM | 7 |
| TET, GEN, CRX, CTR, CTX, CPZ, VAN, MEM | 2 |
| TET, CRX, CTR, CTX, CPZ, CHL, CIP, MEM | 2 |
| COT, GEN, CRX, CTX, CPZ, CHL, CIP, MEM | 1 |
| COT, CTR,CTX, CPZ, CHL, CIP, VAN, MEM | 1 |
| TET, COT, CRX, CTX, CPZ, CHL,VAN, MEM | 2 |
| TET, GEN, CTR,CTX, CPZ, CHL, VAN, MEM | 1 |
| TET, COT, GEN, CRX, CTX, CPZ, CHL, MEM | 1 |
| TET, GEN, CRX,CTR,CTX, CPZ, CIP, MEM | 1 |
| TET, COT, CRX, CTX, CPZ, CHL, CIP, MEM | 2 |
| TET, COT, GEN, CRX, CTX, CPZ, CIP, MEM | 2 |
| TET, COT, CRX, CTX, CPZ, CIP, VAN, MEM | 1 |
| TET, CRX, CTX, CPZ, CIP, VAN, MEM | 2 |
These findings highlight a concerning frequency of antibiotics resistance among the sampled poultry population and suggest a high level of multidrug resistance, likely associated with the indiscriminate or excessive use of antibiotics in poultry production.
The MARI values of the isolates, shown in Fig. 4, ranged from 0.3 to 0.9. The largest proportion of isolates (24.16%) had a MARI value of 0.7, followed by 23.49% with a MARI of 0.8 and 18.80% with a MARI of 0.6. The lowest frequency (4.70%) corresponded to a MARI of 0.3. These results indicate that a substantial proportion of bacterial isolates exhibited resistance to multiple antibiotics, with MARI values ≥ 0.7 (Fig. 5).
Fig. 4.
Multiple Antibiotic Resistance Indices of Bacteria Isolated from Poultry
Fig. 5.
Multiple Antibiotic Resistance Indices based on Bacterial Species
Plasmid analysis revealed detectable plasmid bands ranging from 500 bp to 10 Kbp, as shown in Fig. 6. Of the ten MDR bacterial isolates selected for plasmid analysis, only one isolate—Enterobacter aerogenes (lane 6)—showed no detectable plasmid band. Table 6 presents the molecular weight of plasmid DNA isolated from MDR bacteria, while Fig. 7 shows agarose gel electrophoresis results of cured plasmid DNA.
Fig. 6.
Agarose Gel Electrophoresis of Plasmid DNA from MDR Bacteria. KEY: Lanes 1 kbp and 50 bp are a DNA ladder from NEB, respectively. Lane 1 = Salmonella enterica; Lane 2 = E. coli; Lane 3 = Shigella flexneri; Lane 4 = Morganella morganii; Lane 5 = Klebsiella pneumonia; Lane 6 = Enterobacter aerogenes; Lane 7 = Proteus mirabilis; Lane 8 = Proteus mirabilis; Lane 9 = Serratia marcescens; Lane 10 = Pseudomonas aeruginosa
Table 6.
Plasmid Profile of Selected MDR bacterial Isolates Harboring Plasmids
| Bacteria Isolate | Number of Plasmids | Molecular Sizes (bp) |
|---|---|---|
| Salmonella enterica | 3 | 10,000, 1500, 550 |
| Escherichia coli | 2 | 10,000, 1500 |
| Shigella flexneri | 4 | 10,000, 2000, 1500, 950 |
| Morganella morganii | 4 | 10,000, 2000, 1500, 916 |
| Klebsiella pneumoniae | 2 | 10,000, 1500 |
| Enterobacter aerogenes | 0 | 0 |
| Proteus mirabilis | 2 | 10,000, 1500 |
| Proteus mirabilis | 3 | 10,000, 1500, 500 |
| Serratia marcescens | 2 | 10,000, 1500 |
| Pseudomonas aeruginosa | 2 | 10,000, 1500 |
Fig. 7.
Agarose Gel Electrophoresis of Cured Plasmid DNA
All isolates harboring plasmids were successfully cured of the lower molecular weight plasmids, retaining only the 10 Kbp plasmids. Table 7 summarizes the antibiotic resistance profiles of bacterial species before and after plasmid curing. Enterobacter aerogenes maintained its resistance pattern after curing, indicating resistance was chromosomally mediated.
Table 7.
Antibiotic Resistance Patterns of Bacterial Species pre- and post-Plasmid Curing
| Bacteria species | Pre-curing Resistant Profile | Post-curing Resistant Profile |
|---|---|---|
| Salmonella enterica | TET-COT-GEN-CPZ-MEM | COT-CPZ-MEM |
| Escherichia coli | TET-COT-GEN-CRX-CTR-CTX-CPZ-CIP-VAN-MEM | CRX-CTR-CTX |
| Shigella flexneri | TET-COT-CTX-CPZ-CIP-MEM | CTX-CPZ-MEM |
| Morganella morganii | TET-CRX-CTX-CPZ-CIP-VAN-MEM | CPZ-VAN |
| Klebsiella pneumoniae | TET-COT-CRX-CTR-CTX-CPZ-CIP-VAN-MEM | CTR-CPZ-MEM |
| Enterobacter aerogenes | TET-COT-CRX-CTR-CTX-CPZ-VAN-MEM | TET-COT-CRX-CTR-CTX-CPZ-VAN-MEM |
| Proteus mirabilis | TET-COT-GEN-CRX-CTR-CTX-CPZ-CHL-CIP-VAN-MEM | MEM |
| Proteus mirabilis | TET-COT-GEN-CRX-CTR-CTX-CPZ-CIP-VAN-MEM | VAN-MEM |
| Serratia marcescens | TET-CRX-CTX-CPZ-CIP-MEM | MEM |
| Pseudomonas aeruginosa | TET-COT-GEN-AMK-CRX-CTR-CTX-CPZ-CHL-CIP-VAN-MEM | VAN-MEM |
Discussions
Numerous previous studies have identified and characterized various pathogenic and commensal microbial isolates associated with poultry samples, including Escherichia coli, Salmonella sp., Campylobacter sp., and Enterococcus sp. [26, 34]. These diverse bacterial populations can contribute to foodborne illnesses in humans, making their presence and antibiotic resistance patterns of critical importance in poultry systems. A related study examining caecal bacterial populations from broilers, layers, and their F1 cross [53] revealed differences among the groups, demonstrating a strong correlation between genetic factors and bacterial population composition within poultry strains. The bacterial types isolated also align with other findings that recovered E. coli, Salmonella sp., Shigella sp., and P. mirabilis from poultry farms in Kano [52]. Retrospective research [18, 22] reported the presence of common bacteria like E. coli, P. mirabilis, and Pseudomonas sp. Interestingly, P. mirabilis was more prevalent in our study, unlike other findings where E. coli usually dominates. E. coli rates varied globally, with reports of 60.7% in South Africa [44], 58.0% in Kenya [33], 86.3% in Ecuador [3], and others. Our E. coli prevalence consistent with Nigerian studies, though slightly lower than some regional findings [15, 18, 36]. These variations highlight regional differences in poultry bacterial communities.
The indiscriminate use of antibiotics in poultry production- both for disease control and growth promotion- is a major driver of MAR in associated microbial populations. This global phenomenon poses a serious threat to the health of animals and humans alike [26, 55]. In this study, the bacterial isolates exhibited varying resistance and susceptibility patterns to the tested antibiotics. All isolates were resistant to MEM, while CTX and CPZ showed 98% resistance. The highest susceptibility was observed with AMK at 83%, followed by CHL at 32%. Antibiotic resistance among poultry gastrointestinal bacteria is primarily driven by genetic mutations, horizontal gene transfer that facilitates the acquisition of resistance genes, and enzymatic modification or degradation of antibiotics, such as the production of β-lactamases that hydrolyze β-lactam antibiotics [8, 21, 24]. A recent report [17], consistent with our findings, also documented complete resistance to meropenem among Enterobacteriaceae isolates.
Concerns with antibiotic resistance are its declining efficacy and rising rates of illness and death of poultry birds. Some supporting reports are the meropenem resistance in E. coli and Proteus mirabilis [1], as well as carbapenem resistance in pathogens [48] isolated from poultry. In this study, Salmonella enterica subsp. diarizonae demonstrated 100% resistance to all tested antibiotics, except amikacin, ceftriaxone, and chloramphenicol. This trend could be due to the limited exposure to these antibiotics or the presence of MDR genes. Similar reports indicating a troubling trend have demonstrated 100% [49], 92.6% [56], and 88.9% [31] vancomycin resistance by certain pathogens. Vancomycin resistance can occur due to the co-use of macrolide antibiotics in poultry. Shared (macrolide and vancomycin) resistance genes on plasmids may lead to simultaneous selection for both resistances, potentially driving vancomycin resistance even without direct vancomycin use [23, 35].
In this study, MARI values for all the bacterial isolates exceeded 0.20. These findings indicate that the bacterial isolates likely originated from environments with high antibiotic selection pressure, such as poultry farms with frequent or excessive antibiotic use [42, 51]. A high MARI values were notably recorded for key pathogens: Escherichia coli (0.92), Proteus mirabilis (0.92), and Serratia species (0.83). These MARI values strongly suggest multidrug resistance (MDR), which presents significant challenges for both veterinary and human medicine. High MAR indices in these bacteria have been widely reported as an indicator of a potential dissemination of AMR genes into the broader environment, especially through contaminated water sources, litter management, and use of untreated wastewater for irrigation [19, 25, 50].
The detection of antimicrobial resistance plasmids in these isolates is concerning, as it suggests the presence of a mobile genetic element that facilitates the horizontal transfer of resistance genes to other bacterial species. This horizontal transfer speeds up the spread of MDR pathogens, posing a significant challenge to antimicrobial therapy and endangering public health [4, 47]. In this study, Shigella flexneri harboured four plasmids, whereas Enterobacter aerogenes had none.
Plasmids may also carry virulence genes, enhancing bacterial pathogenicity. Such virulence plasmids typically exceed 40 kb in size, are maintained at low copy numbers, and often impose a fitness cost on the bacterial host [39]. Interestingly, plasmids replicate independently of the bacterial chromosome through specific replication (rep) genes and are stably inherited by daughter cells during bacterial division [6, 47].
Conclusion
This study has provided critical insights into the escalating threat posed by multidrug-resistant bacteria in poultry-chickens. The widespread and often indiscriminate use of antibiotics in poultry farming has led to the emergence of resistance in both pathogenic and commensal bacteria that can easily affect human health via contact and food chain.
Based on the findings of this study, it can be deduced that poultry chickens serve as an important reservoir of multidrug-resistant (MDR) bacteria with serious public health implications. The high level of resistance to MEM and cephalosporins observed among the isolates presents a significant challenge to effective therapy, whereas the comparatively low resistance to AMK suggests its continued potential as a treatment option. The detection of plasmid bands in resistant isolates further indicates that plasmid-mediated resistance plays a key role in the dissemination of MDR traits among these pathogens. There is a need for continuous surveillance exercises for antibiotic resistance patterns, and the implementation of robust antibiotic stewardship programs to minimize the risk of transmission of resistant pathogens from poultry to humans.
Acknowledgements
The molecular part of this work was carried out at Bioformatics Services Laboratory, Festac Hill, Ibadan. We are very grateful.
Authors’ contributions
IAI: carried out the laboratory investigations and wrote the first draft of the manuscript USE: designed and supervised the work UA: Writing – review & editing, Validation, Data curation. MC: Writing – review & editing, Validation, Investigation, Data curation. ODA: Writing – review & editing, Visualization, Validation, Data curation. All authors read and approved the final manuscript.
Funding
Not applicable.
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
Informed consent was obtained from commercial poultry farm owners before taking samples from the chickens. The care and use of animals were conducted in accordance with the National Institute of Health Guide for the Use of Laboratory Animals. However, ethical approval was obtained from the University of Uyo Health Research Ethics Committee to carry out this research.
Consent for publication
Not Applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Otobong Donald Akan, Email: Otobongakan@aksu.edu.ng.
Uduak Akpabio, Email: udiakpabio@gmail.com.
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Associated Data
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Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.