The Synergistic Effect of Three Essential Oils against Bacteria Responsible for the Development of Lithiasis Infection: An Optimization by the Mixture Design

The present study aimed to determine the chemical composition and the synergistic effect of three plants' essential oils (EOs), Eucalyptus camaldulensis (ECEO), Mentha pulegium (MPEO), and Rosmarinus officinalis (ROEO), against three bacterial strains, Proteus mirabilis, Klebsiella pneumoniae, and Staphylococcus aureus, in order to increase the antimicrobial effectiveness by the use of a low dose of essential oils, consequently decreasing the toxicity and negative impact. For this reason, an augmented simplex-centroid mixture design was used to build polynomial models in order to highlight the synergy between the essential oils against bacterial strains. Antimicrobial effect screening was performed by the disc diffusion method and the minimal inhibitory concentrations (MIC) were also studied. The gas chromatography/mass spectrometry (GC-MS) results show the richness of these essential oils by terpenic compounds, especially 1,8-Cineole and P-Cymene for ECEO, Pulegone for MPEO, and α-Pinene and Camphene for ROEO. Moreover, a significant antibacterial effect has been demonstrated and the best values were revealed by MPEO and ECEO against P. mirabilis and K. pneumoniae, with inhibition zones (IZ) of 25 and 20 mm, respectively, and an MIC of 0.0391% (v:v) against K. pneumoniae. The optimal mixtures showed a synergistic effect of essential oils, and the lowest minimal inhibitory concentrations of the mixtures (MICm) were in the order of 29.38% of MPEO, 45.37% of ECEO, and 25.25% of ROEO against P. mirabilis and in the order of 60.61% of MPEO and 39.39% of ROEO against K. pneumoniae. These results indicate the antibacterial efficacy of the three essential oils combined and suggest their importance in the treatment of urinary tract infections caused by resistant bacterial strains.


Introduction
Urinary tract infection is one of the most common bacterial infections in women and men, affecting more than 150 million people around the world every year [1][2][3]. It can cause life-threatening septicemia, but most infections are less severe [4]. However, this infection is a risk factor for lithogenesis, which can be the cause of infectious stones, especially carbapatite and struvite. ese stones may also be secondary to a nonurinary infectious agent, Oxalobacter formigenes, as well as nanobacteria [5].
Infection stones are formed as part of an infection of the upper urinary tract by urease-producing bacteria (Proteus, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, Aspergillus fumigatus, and Enterobacter) [6,7]. ese microorganisms hydrolyze urea to produce ammonia and hydroxide, increasing the urine pH and therefore increasing the dissociation of phosphate to form trivalent phosphate. e latter bind with magnesium to form a "triple crystal" of struvite (magnesium ammonium phosphate) and/or calcium carbonate apatite stones. ose stones generally develop in branched form (staghorn), which occupies a large part of the collector system [8,9].
In revanche, essential oils have gained increased interest and are considered as an alternative for the fight against bacterial infections, especially drug resistance [10][11][12][13]. Furthermore, the individual compounds of the plants often act in synergy so as to potentiate the activity of the combination significantly compared to that of the individual components [14].
In this regard, this study was focused on determining the antibacterial effects of the combined essential oils of three plants, Eucalyptus camaldulensis, Mentha pulegium, and Rosmarinus Officinalis, against three bacterial strains: P. mirabilis, K. pneumoniae, and S. aureus. is combination was chosen in order to increase the efficiency and minimize the dose of essential oils, thus decreasing their toxicity and negative impact. For this, a simplex-centroid augmented mixture design was used to build polynomial models in order to highlight the synergy between the essential oils against bacterial strains. In addition, the chemical composition of EOs has been identified and the correlation between these compounds and the antibacterial activity has also been determined. Essential oils from the Eucalyptus camaldulensis leaves and the aerial parts of Mentha pulegium and Rosmarinus Officinalis were extracted by the hydrodistillation method using the Clevenger-type equipment. 100 g of each sample was subjected to hydrodistillation for 4 hours at the water boiling temperature (100°C). Once extracted, the essential oils obtained were dried on anhydrous sodium sulfate, stored at a temperature of 4°C in dark glass flacons until use [49].

Gas Chromatography/Mass Spectrometry (GC-MS)
Analysis of Essential Oils. e essential oils have been analyzed on a ermo Fischer Trace GC ULTRA gas chromatograph coupled to a mass spectrometer (Polaris Q MS with ion trap). e gas chromatography device is equipped with a VB-5 (Methylpolysiloxane 5% phenyl) column (30 m * 0.25 mm * 0.25 µm). e gas used is Helium with a flow rate of 1.4 mL/min and samples are injected in split mode. e injection temperature and injected volume are 220°C and 1 µL, respectively. e column initial temperature is 40°C for 2 min and it increases from 40°C to 180°C at a rate of 4°C·min − 1 and from 180°C to 300°C at a rate of 2

Inoculum Preparation.
From a bacterial culture (24 hours), identical colonies were scraped off using a sealed Pasteur pipette. A volume of 10 mL was discharged into a sterile saline solution (0.9%), the bacterial suspension was homogenized, and its opacity was reduced to 0.5 McFarland corresponding to 10 7 CFU·mL − 1 . After that, the suspension was diluted to give an inoculum of 10 6 CFU·mL − 1 [51].

Disc Diffusion Method.
e Agar diffusion method allows predicting with certainty the in vitro efficacy of the essential oils and the antibiotics; it is in fact a qualitative assessment of the activity. It was carried out by the protocol described by Abdelli et al. [51] with some modifications.
Each strain is subcultured into 2 ml of Mueller-Hinton broth solution (BMH) and incubated at 37°C for 2.5 to 3 hours. Subsequently, 20 ml of Mueller-Hinton agar medium is poured into a Petri dish, and once the agar has cooled, the bacterial inoculum is inoculated by the swabbing technique. After 5 min, a sterile filter paper disc with a diameter of 6 mm is aseptically deposited on the surface of each plate and 10 μl essential oil is added. In parallel, a virgin witness in essential oil is prepared. e Petri dishes are left for 1 hour at 4°C and then inverted and incubated at 37°C for 18 to 24 hours. After incubation, the inhibition diameter is measured in mm, including the disc [51].
e broth microdilution method was used to evaluate the MIC, using the dimethyl sulfoxide (DMSO) as an emulsifier and triphenyl tetrazolium chloride (TTC) as an indicator of bacterial growth. 20 µl of DMSO was distributed from the second to the twelfth well of the 96-well microplate (Greiner, VWR). Later, 40 µl of the essential oil was added to the first test well of each line in the microplate, from which 20 µL geometric base 2 dilution was made from the second to the eleventh well. e twelfth well was considered a growth control. en, 160 μL of Mueller-Hinton Broth (BMH) and 20 μL of a 10 6 CFU·ml − 1 bacterial suspension are added to all wells. After 18 hours of incubation at 37°C, the reading was taken by adding 10 µL of color indicator (TTC) diluted in sterile distilled water in the order of 0.2 g·ml − 1 , followed by incubation for 10 min at 37°C. e TTC reveals the presence of live bacteria by the appearance of red coloration [13,52].

Antibacterial Effect of a ree-Essential-Oils Mixture by Mixture Design.
e mixture designs are a specific branch of the experimental designs. e response in this plan depends only on the relative proportions of the factors and not on the quantities of mixture used, which must be between zero and one and their sum equal to one (or 100%). Lower and upper limits may be imposed (for one or more factors) for security reasons or due to economic constraints [53][54][55].
is experimental design methodology was used to find the optimal formulation while minimizing the experiments number.
us, it allows determining the relationship between the variables and the experimental responses measured. In our study, the optimization aimed at finding the constituents of the formulation giving the best essential oils combination allowing the highest antibacterial activity, which is illustrated by minimum inhibitory concentration of the mixtures MIC m .

Experimental Matrix and Mathematical Model.
e simplex-centroid augmented design was chosen to optimize and determine the synergistic antibacterial effect of the three essential oils: ECEO, MPEO, and ROEO. is design includes ten experiments distributed as follows: the three EOs in the triangle's vertices (experiments 1, 2, and 3), the binary mixtures 0.5/0.5 (experiments 4, 5, and 6), the mixture in equal proportions of the three constituents (experiments 7), and control points (experiments 8, 9, and 10) (Figure 1). Experiment 7 was replicated three times to determine the pure error and compare it with the lack of fit. Consequently, the number of experiments for this design was equal to 12 (Table 1) [12,13]. e responses were the antibacterial effects of EOs quantified as minimum inhibitory concentration of the mixtures MIC m and were evaluated by the microdilution method.
en, the data were fitted to a special cubic polynomial model using least-squares regression to estimate the unknown coefficients in the following equation: Evidence-Based Complementary and Alternative Medicine where Y is the overall response of the mixture. X1, X2, and X3 are the proportions of the components in the mixture. b1, b2, and b3 are the magnitudes of the effect from each component. b12, b13, and b23 are the magnitudes of the interaction effect of two components. b123 is the magnitude of the interaction effect of the three components.

Minimum Inhibitory Concentration of the Mixtures (MIC m ).
e MIC m of the three EOs mixtures were carried out in the same way as in Section 2.3.5 with the change in concentration of the stock solution. In this work, we used the concentrations that gave the MIC of each EO against each bacterial strain as the stock solution in order to see if there are any agonist or antagonist interactions between its EOs and to avoid the over-effect of one EO on the other EOs.

Statistical Analysis.
Test design and statistical analysis for model validation were performed using Minitab 18 software. e ratio between the mean square due to regression (CMR) and the residual mean square (CMr), F ratio (R/r), was used at a significance level of 95% to check the statistical significance of the model. e variability of the data around its mean is explained adequately by the higher F value. e quality of the first-order polynomial fit was also expressed by the coefficient of determination R 2 . is coefficient measures the adequacy of the regression equation (model) with the experimental data. In fact, it measures the correlation between observed and predicted responses and is often expressed as a percentage. Student's t-test was used at a significance level of 95% to confirm or reject the significance of the factors. In the table of coefficients, each factor is associated with the values of Student's t-test and p value. Student's t-test values are used to determine the significance of the regression coefficients for each parameter and the p values are defined as the lowest level of importance leading to the rejection of the null hypothesis [13]. e principal component analysis (PCA) was carried out using IBM SPSS Statistics 20 software.

Essential Oils' Chemical Composition.
e identification of the chemical compounds in each EO was based on the comparison of their mass spectra with those of the NIST database. Indeed, the results of the ECEO, MPEO, and ROEO chemical compounds identification are represented in Tables 2-4 . e chemical composition analysis of Eucalyptus camaldulensis leaves' essential oil revealed 67 compounds representing 96.48% of the total oil (Table 2). In fact, the terpene composition consists mainly of monoterpenes, with 45.92% oxygenated monoterpenes and 25.08% hydrocarbon monoterpenes. Meanwhile, sesquiterpenes represent only 12.3% of those oxygenated and 8.07% of the hydrocarbons. e main compounds of this oil are 1,8-Cineole (19.05%), P-Cymene (17.06%), (− )-Spathulenol (9.42%), Cryptone (5.99%), Phellandral (5.34%), and Cuminaldehyde (4.56%). Our chromatographic profile is almost in concordance with another study by Elgat et al. [56]. However, Medhi et al. [18] found a higher proportion of 1,8-Cineole (69.46%) followed by c-Terpinene (15.10%). Meanwhile, Knezevic et al. [57] reported a variation in the chemical compound proportion of this EO between samples collected from two different geographical areas. e proportion of P-Cymene found in this work is greater than that of Farah et al. [58] which are worked on the samples harvested from the experimental plot EU. PL25 (Sidi Yahia du Gharb, Northwest of Morocco) and its natural hybrid are collected from the experimental plot Ell. II (forest zone of Sidi Slimane du Gharb, Northwest of Morocco). Nevertheless, other compounds such as 1,8-Cineole and α-Pinene are presented with significant proportion, especially in hybrid samples [58,59].        Table 3 displays the presence of 45 compounds, regrouping a cumulative area corresponding to 95.77% of the total constituents. Oxygenated monoterpenes represent the majority of terpene with a percentage of 77.09% against 5.27 and 3.69% for hydrocarbon monoterpenes and oxygenated sesquiterpenes, respectively. In addition, Pulegone is the predominant compound with a rate of 51.02%, followed by Isopulegone (6.69%), Piperitenone (5.90%), and (− )-1R-8-Hydroxy-p-menth-4-en-3-one (4.08%). e same majority compound was found in the works of Brahmi et al. [60], Abdelli et al. [51], Bouyahya et al. [61], and Chraibi et al. [62]. e two latter works have been accomplished by the Moroccan samples. 50 chemical compounds that represent 97.78% of the total accumulated air were identified in Rosmarinus officinalis EO (Table 4). is latter is marked by the abundance of hydrocarbon monoterpenes (60.96%), followed by oxygenated monoterpenes (28.16%) and hydrocarbon sesquiterpenes (5.58%). In addition, α-Pinene (24.90%), Camphene (9.32%), D-Limonene (7.15%), (+)-Camphor (6.11%), and α-Fenchene (4.24%) are the majority compounds. However, the results obtained for this oil are close to those of Liu et al. [63] who reported α-Pinene as the majority compound. e study conducted by Ainane et al. [64]

Agar Disc Diffusion-Screening of the Antibacterial Effect of the Essential Oils and Resistance to Antibiotics.
e qualitative demonstration of the antibacterial effect of essential oils (ECEO, MPEO, and ROEO) and antibiotics on three bacterial strains, P. mirabilis, K. pneumoniae, and S. aureus, was evaluated by the disk diffusion method; the results of the inhibition zones are shown in Table 5.
e antibiotic effects screening indicates that the strains studied in this work have a very high resistance profile against antibiotics, hence its importance to find alternatives to these agents. However, according to Table 5, K. pneumoniae is sensitive to three antibiotics (OFX, NOR, and CTX) among the seven evaluated. S. aureus is sensitive to OFX and NOR, while P. mirabilis is resistant to all antibiotics. Moreover, the inhibition zones for pure essential oils (Table 5) show that the MPEO revealed a very important antimicrobial effect against the three strains, with values of 20, 20, and 10 mm, while the ECEO values are 25, 12, and 10 mm for P. mirabilis, K. pneumoniae, and S. aureus, respectively. Meanwhile, the ROEO profile marks no effect on the S. aureus strain.

Minimum Inhibitory Concentration (MIC).
e results of the minimum inhibitory concentration (MIC) of the three plant essential oils are shown in Table 6.
According to Table 6, all the essential oils studied display a significant MIC, except for ROEO which shows no reaction against S. aureus (Gram-positive). e recorded concentrations are with respect to 0.3125, 0.0391, and 0.0781% (v:v)

Principal Component Analysis (PCA).
e principal component analysis was applied to highlight the relationship between the EOs chemical composition of three plants studied and their antibacterial activities. In fact, the results are shown in Figures 2 and 3 .
According to Figure 2(a), the first component (PC1) represents 57.64% of the total variation and is dominated mainly by hydrocarbon monoterpenes (α-ujene, β-Myrcene, uja-2, 4(10)-diene, and (− )-β-Pinene) and MIC against S. aureus (group a). Meanwhile, the second component (PC2) represents 42.36% of the variability and is linked principally to hydrocarbon sesquiterpenes (β-Cadinene, c-Muurolene, and α-Copaene) (group b). e loading plot shows also three other groups; group c includes hydrocarbon and oxygenated monoterpenes (β-Pinene, α-Fenchene, D-Limonene, α-Pinene, c-Terpinene, Linalool, α-Terpineol, Verbenone, 3-Carene, and Cyclofenchene) and a hydrocarbon sesquiterpene (β-Caryophyllene); these variables are correlated with each other and have a weak positive correlation with PC2 and a negative one with PC1. e variables gathered in group d are also the hydrocarbon and oxygenated monoterpenes principally (O-Cymene, p-Mentha-3, 8-diene, Pulegone, and Piperitenone), the oxygenated sesquiterpenes (Caryophyllene oxide and Humulene epoxide II), the compound 3-Octanol, and the growth inhibition zone of K. pneumoniae variable, but this group is anticorrelated with the two PCs. Group e regrouped the variables that are related to the antimicrobial activity against the three bacterial strains studied. e score plot (Figure 2(b)) explores the correlations between the PCs and the studied essential oils, making it possible to determine which variables discriminate these three EOs. Indeed, ECEO has a strong score for PC1 which is linked to group a variables, and groups c and d discriminate ROEO and MPEO, respectively. e PCA which compares the chemical class proportion and the antibacterial activity of the three studied EOs plants ( Figure 3) reveals a correlation between the P. mirabilis inhibition zone, MIC against S. aureus, and the oxygenated sesquiterpene; these variables characterize the ECEO. Meanwhile MPEC is characterized by a high proportion of oxygenated monoterpene and an inhibitory effect against the K. pneumoniae bacterial strain growth.
is result may explain the important effect of oxygenated terpene compounds in inhibiting bacterial growth.

Optimization of the Antibacterial Effect of a ree-Essential-Oils Mixture by the Mixture Design.
e optimization of the essential oils mixture's antibacterial effect against three bacterial strains, P. mirabilis, K. pneumoniae, and S. aureus, has been determined by MIC m . Recalling that, in this section, the concentrations of the stock solutions were selected from the MICs found in Section 3.3 for each bacterial strain, indeed, the observed responses for each experiment are displayed in Table 7.

Statistical Validation of the Model Postulated.
Statistical analysis of the experimental response data corresponding to each bacterial strain was carried out in order to verify the special cubic model chosen, which describes the relationship between factors and responses. e results of the findings are shown in Table 8.
According to Table 8, the analysis of variance (ANOVA) shows that the F ratio (R/r) calculated for P. mirabilis (9.733) and K. pneumoniae (6.178) is higher than the tabular value (4.95) at the 95% confidence level. In addition, the p value is in order of 0.0123 and 0.0321 (<0.05), respectively. In fact, these results prove that the regression main effect is statistically significant for these two models. Moreover, the coefficients of determination R 2 for P. mirabilis and K. pneumoniae are 0.92 and 0.88, respectively, which is an indicator of the correlation between  Evidence-Based Complementary and Alternative Medicine the experimental and predicted values in the adapted mathematical model. However, the regression main effect is statistically insignificant for the model that examines the responses of S. aureus with an F ratio (R/r) of 2.349 and a p value of 0.183, and the coefficient of determination R 2 � 0.74 displays the insufficiency of the correlation; therefore the model will be excluded.

Effect of the Mixture Components, eir Interactions, and the Models Applied.
e interaction between different essential oil compounds can reduce or increase antimicrobial efficiency. ese interactions can produce four types of results: indifferent, additive, antagonistic, and synergistic results [12]. However, the effects of all factors studied, the statistical values of Student's t-test, and p value are reported in Table 9.  Tables 2-4.    e interpretation of the models data relating the responses to the factors (Table 9) shows that the coefficients of the terms that represent the effects of the pure components (b1, b2, and b3) are significant against the P. mirabilis and K. pneumoniae bacterial strains, with p value values less than 0.05. Binary interactions between MPEO and ECEO (b12) and between ECEO and ROEO (b23) are significant against P. mirabilis (p < 0.05), and interactions between MPEO and ROEO (b13) and between ECEO and ROEO (b23) are significant against K. pneumoniae (p < 0.05). Meanwhile the coefficients of the ternary interaction terms are not significant (p > 0.05) and show no effect on the two bacterial strains. In fact, after eliminating all nonsignificant coefficients from the postulated models, the mathematical models representing the response in terms of the three components are represented by equations (2) and (3) for P. mirabilis and K. pneumoniae, respectively.
In general, coefficients with positive signs for mixtures indicate that the two components act synergistically or are complementary, resulting in an increased response. Meanwhile, negative coefficients suggest an antagonistic effect relative to each other; therefore there is a decrease in response. In fact, this study aims to minimize the response that represents MIC m values; hence the coefficient with a negative sign reflects the ability of its associated factor to increase the antibacterial effect. However, the binary combination of MPEO and ECEO exhibits a significant synergistic effect against P. mirabilis. A significant synergistic effect against K. pneumoniae was revealed by the combination of MPEO and ROEO. Meanwhile the interaction between ECEO and ROEO has a significant synergistic effect against these two bacterial strains. ese results are clearly observed in the 2D contour and 3D surface plots in Figure 4.

Mixture
Optimization. Mixture optimization was evaluated by the desirability function method in order to obtain a formulation of the optimal essential oil proportions resulting in a lowest MIC m . e results obtained are illustrated in Figure 5.
According to the desirability profile of antimicrobial activity against P. mirabilis ( Figure 5(a)), the lowest MIC m value can reach 1.367% with desirability of 100%. is value can be obtained by mixing essential oils with proportions of 29.38% for MPEO, 45.37% for ECEO, and 25.25% for ROEO. Regarding K. pneumoniae ( Figure 5(b)), a mixture of 60.61% MPEO and 39.39% ROEO predicts an MIC m of 2,098%, with 97,55% desirability. is result confirms the hypothesis of synergy in the binary combination between MPEO and ROEO.
Moreover, the optimal essential oils concentrations in the mixture generating a minimal MIC m against bacterial strains were calculated by the following equation: optimal essential oil concentration � MICm * DF of the initial EO concentration * % essential oil found by the mixing design.

(4)
DF is the dilution factor; MIC m is the minimum inhibitory concentration of the mixtures. e minimum concentrations found against P. mirabilis are around 0.0126% (v:v) for MPEO, 0.0194% (v:v) for ECEO, and 0.0863% (v:v) for ROEO. A mixture with a concentration of 0.0050% (v:v) for MPEO and 0.8264% (v:v) for ROEO is able to inhibit K. pneumoniae growth.

Discussion
is study demonstrates the potential of Eucalyptus camaldulensis, Mentha pulegium, and Rosmarinus officinalis essential oils and their combination against three bacterial strains, P. mirabilis, K. pneumoniae, and S. aureus, which are marked by antibiotic resistance. e inhibition zones revealed by the disc diffusion method (Table 5) prove the individual efficacy of these EOs, especially by MPEO, while the RMEO shows no reaction against S. aureus. In fact, the inhibition zones for the latter reported by Bozin et al. [47] and Safaei-Ghomi and Ahd [25] with essential oils of Rosmarinus officinalis and eucalyptus, respectively, were superior to ours, but this strain studied in their work does not mark antibiotics-resistance (Penicillin and Gentamicin); similarly, Mattazi et al. [68] have found an antibacterial effect against S. aureus and Klebsiella by Rosmarinus officinalis samples collected from the Biougra region (province of Chtouka Ait Baha, Agadir city. Morocco). Furthermore, our results of the MPEO effect against P. mirabilis are similar to those reported by Abdelhakim et al. who worked on the Mentha pulegium plant from the Ouezzane region (Northwest Morocco) [61]. In addition, the minimum inhibitory concentration (MIC) method, which allows determining the lowest EOs concentration that is able to inhibit the bacteria growth, confirms the screening results found by the disc diffusion method. e data obtained related to the mixture EOs optimization show the importance of binary combinations in increasing the antibacterial effect, as well as the decrease of these essential oils' concentrations and consequently the reduction of toxicity. However, the GC-MS analysis of the EOs studied in this work showed their richness in bioactive chemical compounds, the PCA revealed the correlations between these latter and the antibacterial effect, and consequently these compounds probably act individually or in synergy on bacterial strains. In addition, Ložienė et al. [69] have established a very strong antibacterial effect of the α-Pinene fractions with an enantiomers mixture (1S)-(− ) < (1R)-(+) α-Pinene as well as the (1R)-(+)-α-Pinene standard against S. aureus ATCC, with an MIC of 0.01% (w:v). Similarly, Pulegone [70], 1,8-Cineole, Camphore, Verbenone, and Borneol [71], and Menthol and Menthone [72] have also shown a great capacity to inhibit this last bacterial strain. e study performed by Vuuren and Viljoen [73] reveals a remarkable antimicrobial activity of 1,8-Cineole compound against the K. pneumoniae strain with an MIC of 8 mg/ml. Meanwhile Shahverdi et al. [74] reported that the antimicrobial activity of Furazolidone and Nitrofurantoin (a marketed antibacterial agent) against K. pneumoniae and Proteus spp. increases with the presence of Piperitone.
However, the essential oil mechanisms action remains less clear, and their complexity comes from the diversity of chemical molecules, each of which can act on a different target [75,76]. Several EOs antibacterial mechanisms have been described by Bouyahya et al. [76]; these action mechanisms include cell membrane crossing, potassium leakage and respiratory chain disruption, impairment of cell division, and quorum detection signalling pathways inhibition resulting in decreased bacterial resistance [61,76,77].
In conclusion, this work highlighted the chemical composition and the antimicrobial efficacy of Mentha pulegium, Eucalyptus camaldulensis, and Rosmarinus officinalis plants' essential oils, as well as their combinations against three bacterial strains, P. mirabilis, K. pneumoniae, and S. aureus. e analysis by GC-MS shows the richness of ECEO by 1,8-Cineole and P-Cymene, and MPEO has a very   of the models that examine the responses of MIC m against P. mirabilis and K. pneumoniae. e synergistic effect between essential oils has been demonstrated, and the optimal mixtures that reveal the lowest MIC m values against these last bacterial strains are in order of 29.38% MPEO, 45.37% ECEO, and 25.25% ROEO against P. mirabilis and in order of 60.61% MPEO and 39.39% ROEO against K. pneumoniae. ese results suggest that these essential oils can be used as antimicrobial agents, especially against resistant bacterial strains.
Data Availability e datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest
e authors declare that they have no conflicts of interest.

Authors' Contributions
RK and GBT conceived and designed the experiments, performed the experiments, analyzed and interpreted the data, and wrote the paper. TSH conceived and designed the experiments and analyzed and interpreted the data. REH, MM, MC, AK, and GEM performed the experiments. AL and BB conceived and designed the experiments, analyzed and interpreted the data, contributed reagents, materials, analysis tools, and data, and wrote the paper. All authors read and approved the final manuscript.