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Determining the MIC and Comparative Efficacy of Gentamicin and Kanamycin Against E. coliNardos Gebresenebt
Abstract
Antibiotic resistance poses a significant threat to global public health, with Escherichia coli (E. coli) being one of the most prevalent antibiotic-resistant bacteria. The aim of this study was to determine the minimum inhibitory concentrations (MICs) of kanamycin and gentamicin on E. coli, and to compare their effectiveness at different concentrations. A disc diffusion method was employed under standardized laboratory conditions using four increasing concentrations of each antibiotic, and then areas of inhibition zones were measured. The results showed that both antibiotics exhibited MICs between 6–30 µg/mL, with no statistically significant difference in their inhibitory effectiveness (p > 0.05). These findings indicate that both antibiotics are comparably effective against the E. coli strain tested within this concentration range. This suggests potential interchangeability depending on clinical and situational needs. Determining accurate MIC values is essential for selecting appropriate dosages that minimize the risk of resistance development. Ultimately, this contributes to more effective treatment strategies and helps mitigate the broader impact of antimicrobial resistance in pathogenic bacteria like E. coli.
Key words:
Aminoglycosides
Antibiotic resistance
Zone of inhibition
Gram-negative bacteria
and Bactericidal activity
Contents
Introduction 3
Methods 3
Results 4
Discussion 6
References 8
Appendices 11
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IntroductionE. coli is clinically significant because of its pathogenic mechanisms and the development of antibiotic resistance in various strains (Hassan, Ojo & Abdulrahman, 2021). As a gram-negative bacterium, E. coli possesses an outer membrane rich in lipopolysaccharides that limits antibiotic penetration, while efflux pumps and enzymes like beta-lactamases expel or degrade antibiotics before they can reach their targets (Alves et al., 2017; Kakoullis et al., 2021; Nasrollahian, Graham & Halaji, 2024). As a result, E. coli is one of the most prevalent antibiotic-resistant bacteria in humans (Alves et al., 2017; Pormohammad, Nasiri & Azimi, 2019). Hence, studying its antibiotic response is essential, as it has significant implications for morbidity and mortality (Bezabih et al., 2021).
Aminoglycoside antibiotics, such as kanamycin and gentamicin, block bacterial protein production by binding to the 30S ribosomal subunit, thereby inhibiting translation and causing bacterial cell death (Grayson et al., 2017). This mode of action, combined with their ability to penetrate the outer membrane via porin channels, makes them particularly effective against gram-negative bacteria such as E. coli (Gauba and Rahman, 2023). Among aminoglycosides, kanamycin and gentamicin were selected due to their clinical relevance and proven effectiveness against E. coli (Grayson et al., 2017). Despite their widespread use, direct comparative data on their effective MICs against E. coli remains limited. MIC values are essential for guiding clinical decisions and optimizing dosing strategies to prevent under-dosing of antibiotics, which contributes to the rise of resistant strains (Kowalska-Krochmal & Dudek-Wicher, 2021). This experiment aimed to determine the MICs of kanamycin and gentamicin on E. coli by analysing the area of inhibition zones at different concentrations, hypothesizing that gentamicin, with its broader spectrum of activity, may show greater inhibitory effect at lower concentrations (Grayson et al., 2017). Identifying MICs for specific antibiotics helps ensure more targeted and effective treatment methods while also addressing the growing global health threat posed by antibiotic-resistant E. coli (Bezabih et al., 2021).
Methods
This experiment aimed to determine the MIC of the aminoglycoside antibiotics kanamycin and gentamicin on E. coli by assessing the area of inhibition zones at four different concentrations using the disc diffusion method. A quantitative design was used under standardised conditions, and the area of the inhibition zones served as a measurable indicator of the antibiotics' bactericidal effects.
A laboratory strain of E. coli grown in liquid culture was used as the test bacterium. An inoculum was prepared by diluting the culture using sterile nutrient broth based on OD600 measurements. Kanamycin and gentamicin sulfate, both at an initial stock concentration of 1 mg/mL, were serially diluted fivefold with sterile deionised water to yield four working concentrations: 750 µg/mL, 150 µg/mL, 30 µg/mL, and 6 µg/mL. The positive control was 1 mg/mL of gentamicin, selected due to its proven effectiveness against E. coli (Grayson et al., 2017), and the negative control was sterile deionised water. Nutrient agar (pH ~ 7.0) was used as the growth medium. The experiment was conducted using 12 agar plates, with three replicate plates for each of the 4 antibiotic concentrations (kanamycin and gentamicin) and controls. Antibiotic assay discs were placed on each plate to accommodate the different antibiotic concentrations and controls. Standard aseptic techniques were followed throughout the procedure using a Bunsen burner to create a sterile field, and ethanol was used to sterilise the forceps, and glass spreaders. A Gilson pipette with sterile tips was used for the accurate transfer of liquids.
100 µL of diluted E. coli culture was pipetted onto each agar plate and evenly spread using a sterilised glass spreader. After the plates had dried for approximately ten minutes, the underside of each agar plate was divided into four sections to indicate the positions of kanamycin, gentamicin, positive and negative controls. Antibiotic assay discs were aseptically placed in each section using sterilised forceps. Then, 10 µL of the corresponding antibiotic concentration and control solution were added to each disc. The same procedure was followed for each concentration and replicated three times (see Appendix A for an image of the plate showing this setup). The plates were incubated overnight at 37°C.
On the following day, the diameter of each zone of inhibition was measured in millimetres using a ruler. The area of inhibition zones was calculated using the formula A = πr², and the results were then analysed with a two-way ANOVA to assess the effects of antibiotic type and concentration. Microsoft Excel was used for initial data recording and calculations, while R programming software was used to perform the statistical calculations and visualise the results.
Results
Figure 1. Mean area of zone of inhibition (mm²) of E. coli exposed to four concentrations (6, 30, 150, and 750 µg/mL) of kanamycin and gentamicin, along with a positive control (1 mg/mL gentamicin) and a negative control (sterile deionised water). Data points represent the mean of three replicates (n = 3), with error bars indicating standard deviation. A two-way ANOVA revealed no statistically significant difference between kanamycin and gentamycin (p > 0.05). Key: Each line/colour represents a different antibiotic or control: kanamycin (green), gentamicin (red), positive control (purple), and negative control (blue).
The graph demonstrates a clear trend: as the concentration of both antibiotics increased, so did the mean area of the zone of inhibition. At 6 µg/mL, no inhibition was observed, but as concentrations increased, antibacterial activity for both antibiotics rose. Gentamicin initially showed slightly greater effectiveness, producing larger inhibition zones at 30 and 150 µg/mL. However, this difference diminished at higher concentrations, and by 750 µg/mL, kanamycin slightly exceeded gentamicin, with mean inhibition areas converging around 220–250 mm².
The positive control consistently produced the largest inhibition zones, reaching approximately 530 mm². In contrast, the negative control exhibited no inhibition in all plates. Although both controls were applied at a constant concentration across all plates, slight variations were observed in the inhibition zones across some plates in the positive control. These controls were included in the graph as references to compare the inhibition zones observed with varying antibiotic concentrations.
Statistical analysis using a two-way ANOVA revealed no significant difference between kanamycin and gentamicin across the tested concentrations (p > 0.05), as supported by the overlapping standard deviation error bars. On the other hand, both antibiotics differed significantly from the controls (p < 0.05), as indicated by distinct, non-overlapping error bars.
Discussion
The experiment demonstrated that increasing concentrations of both gentamicin and kanamycin led to a corresponding increase in the mean area of inhibition against E. coli, reflecting a concentration-dependent antibacterial response. Notably, neither antibiotic produced inhibition at 6 µg/mL, while both showed activity at 30 µg/mL and higher concentrations. Gentamicin appeared to perform slightly better at lower concentrations, whereas kanamycin showed a marginally larger inhibition zone at the highest concentration tested (750 µg/mL). However, statistical analysis revealed no significant difference between the two antibiotics (p > 0.05), and the overlapping error bars further support the observed variations likely reflect random biological variability rather than true differences in antimicrobial potency. These results indicate broadly similar antibacterial activity between the two antimicrobials against the tested E. coli strain.
The primary aim was to determine the minimum inhibitory concentration (MIC) of gentamicin and kanamycin, alongside a comparison of their relative effectiveness against E. coli. Based on the observation that no inhibition occurred at 6 µg/mL, but measurable inhibition was present at 30 µg/mL, the MIC for both antibiotics appears to lie within this range (6–30 µg/mL) under the given experimental conditions. In comparing gentamicin and kanamycin, although gentamicin produced slightly larger inhibition zones at lower concentrations, statistical analysis revealed no significant difference between the two. This indicates that neither antibiotic demonstrated clear superiority. Thus, while gentamicin may have a marginal potency advantage, this was not strong enough to draw definitive conclusions within the scope of this study.
The findings from this study align with previously reported MIC ranges for gentamicin (1–64 µg/mL) and kanamycin (2–64 µg/mL) across various E. coli strains (Jakobsen et al., 2007; Mogre et al., 2014; Rezapour et al., 2024; Fneish, Abd El Galil and Domiati, 2025). The narrower MIC range observed in this study (6–30 µg/mL) may reflect the use of a laboratory E. coli strain with reduced resistance variability (Salmon and Watts, 2000). In terms of comparative effectiveness, some studies suggest that gentamicin has greater potency due to its higher affinity for the 30S ribosomal subunit and more efficient cellular uptake (Kim, 1985; Grayson et al., 2017). However, other research, such as Bodendoerfer et al. (2020) and Paul et al. (2022), shows that gentamicin and kanamycin share similar uptake mechanisms and resistance profiles. This is consistent with the findings of this study, where no significant difference was observed between the two antibiotics. Furthermore, the concentration-dependent activity seen in this study is consistent with the general pharmacodynamic behaviour of aminoglycosides (Sime and Roberts, 2017).
On a broader scale, the results of the study align with the understanding of aminoglycoside efficacy and suggest that kanamycin and gentamicin can be considered similarly effective against E. coli in controlled laboratory conditions. Given this similarity, factors such as cost, availability, or patient-specific responses might guide antibiotic selection in clinical contexts (Sime and Roberts, 2017). Additionally, the concentration-dependent effect reinforces the importance of correct antibiotic dosing, as suboptimal dosing has been linked to the survival of resistant bacteria (Ali et al., 2022). This experiment supports the need for establishing reliable MIC values to prevent subtherapeutic exposure. Knowing the MIC also helps identify effective bactericidal concentrations for combating resistant E. coli strains, contributing to efforts in addressing the growing problem of antimicrobial resistance (Kowalska-Krochmal & Dudek-Wicher, 2021).
The study's limitations include antibiotic discs shifting from their original positions, which complicated the accurate measurement of inhibition zones. Additionally, uneven bacterial spreading on the agar plates may have affected the consistency of bacterial exposure to the antibiotics (see Appendix B for an image of a plate illustrating this). In some plates, the antibiotic discs may not have been fully soaked, potentially limiting diffusion, and leading to underestimated inhibition zones. A notable example of this issue was observed with the positive control (gentamicin,1 mg/mL), where despite maintaining the same concentration across all plates, slight variations in inhibition zones were observed. These procedural inconsistencies could have introduced minor variability and reduced precision in the results.
Further research can build on the estimated MIC range (6–30 µg/mL) established in this study for both gentamicin and kanamycin against E. coli. This benchmark may help guide future studies in avoiding subtherapeutic dosing, a key factor in the emergence of antibiotic resistance. Nevertheless, methodological inconsistencies may have introduced variability in inhibition zone measurements, underscoring the importance of refining experimental techniques. Apart from this, since MIC values can differ across strains, additional studies involving diverse clinical or environmental E. coli isolates are essential to validate these findings. In addition, the comparable antibacterial efficacy observed between gentamicin and kanamycin in this study suggests that combining or rotating these antibiotics in therapeutic settings could enhance treatment efficacy and limit the development of resistance (Beardmore et al., 2017). Furthermore, comparative studies involving other aminoglycosides or different antibiotic classes may offer deeper insight into optimal strategies for managing microbial resistance. Ultimately, identifying the MIC is crucial for selecting the most effective antibiotic concentration to combat resistance in E. coli and reduce its broader impact on global health.