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Article

Relationships among Hydrogen Peroxide Concentration, Catalase, Glucose Oxidase, and Antimicrobial Activities of Honeys

by
Sandra M. Osés
1,*,
Carlos Rodríguez
1,
Olga Valencia
2,
Miguel A. Fernández-Muiño
1 and
M. Teresa Sancho
1
1
Department of Biotechnology and Food Science, Universidad de Burgos (University of Burgos), Pza. Misael Bañuelos s/n, 09001 Burgos, Spain
2
Department of Mathematics and Computation, Universidad de Burgos (University of Burgos), Pza. Misael Bañuelos s/n, 09001 Burgos, Spain
*
Author to whom correspondence should be addressed.
Foods 2024, 13(9), 1344; https://doi.org/10.3390/foods13091344
Submission received: 22 March 2024 / Revised: 19 April 2024 / Accepted: 25 April 2024 / Published: 26 April 2024
(This article belongs to the Special Issue Honey and Bee Products: Characterization, Bioactivities and Authenticity)
Browse Figures
Versions Notes

Abstract

:
Honey is a natural sweetener made by bees that exhibits antimicrobial activity, mainly related to its H2O2 content. The aim of this work was to research the H2O2 concentration of 24 Spanish honeys from different botanical origins, studying their possible correlation with glucose oxidase (GOx), catalase (CAT), and anti-Staphylococcus aureus activities (minimal inhibition concentration (MIC), minimal bactericidal concentration (MBC), and percentage of inhibition at 5% (w/v) honey against Staphylococcus aureus), as well as possible correlations among all the analyzed parameters. The results showed that the H2O2 concentration did not depend on the botanical origin of the honeys. There were neither correlations between the H2O2 concentration and the activities of GOx and CAT, nor between GOx and antimicrobial activity. However, CAT and antimicrobial activities were positively correlated. Therefore, CAT could be successfully used as a possible marker of the antimicrobial activity of honeys against Staphylococcus aureus. Furthermore, a linear regression model has been fitted to explain the antimicrobial activity from CAT and GOx activity and H2O2 concentration. Although H2O2 is one of the compounds involved in honey’s antibacterial activity, this capacity also strongly depends on other honey components (such as low water activity, acidity, osmolarity, and phenolic compounds). The very high anti-Staphylococcus aureus activity exhibited by all samples could be interesting for commercial honey-based formulations also helping to promote local beekeeping.

1. Introduction

Staphylococcus aureus is one of the bacteria often associated with wound and burn infections [1], being on the World Health Organization’s list of priority pathogens for which antibiotics are highly needed [2]. Nowadays, due to the increase in multi-drug resistance organisms, researchers are looking for several alternatives.
Honey is a natural and traditional food made by bees from flowers’ nectar or honeydew, which is collected, processed, and stored in hives. This product has been used since ancient times (6000 BC) as sweetener for humans [3], exhibiting antioxidant, antibacterial, and anti-inflammatory properties. Therefore, honey has been used for medical purposes [4], such as the treatment of surface wounds, burns, and inflammation in natural medicine [5,6,7]. Commercial honey-based formulations (gels, dressing, ointment, cream, paste, syrup, and pastilles, among many others) are nowadays widely available on the market [8]. Most of these products contain Manuka honey or buckwheat honey, with sage and honeydew honeys also being used as ingredients. Research on the antibacterial activities and antibacterial-related parameters of other honeys from different botanical origins could open different commercialization possibilities, helping boost local beekeeping practices.
Honey exhibits antimicrobial activity against different bacteria, fungi, viruses, and parasites [9]. The antimicrobial activity of honey has been commonly divided into peroxide (hydrogen peroxide) and non-peroxide factors. Non-peroxide factors include low water activity, acidity, osmolarity, phenolic compounds, methylglyoxal (Manuka honey), defensin-1, lysozyme, volatile compounds, and lactic bacteria [9,10,11]. H2O2 is a honey compound responsible for most honey bacteriostatic and bactericidal activity [12,13,14,15]. The hydrogen peroxide concentration in a given honey depends on its glucose oxidase and catalase activities [14]. Hydrogen peroxide is produced from glucose (glucose + water + oxygen → gluconic acid + H2O2) by the enzyme glucose oxidase (GOx) that is synthesized in the hypopharyngeal glands of honeybees [16]. Catalase (CAT) originates from pollen, being mainly responsible for hydrolyzing H2O2 to water and oxygen. GOx and CAT are of utmost importance for honey quality control, being positively or negatively related to antioxidant and antimicrobial activities. However, the analysis of both enzymes is complex, taking a considerably longer time than the analysis of other honey enzymes, such as diastase or invertase. GOx has been analyzed in several studies. In contrast, CAT has not been so extensively researched, although Weston [14] described the important role that this enzyme has in the antimicrobial activity of honeys.
Different studies have concluded that despite there being a correlation between the antimicrobial activity of honey and its H2O2 concentration, there is no relation between H2O2 and GOx due to the complex pathways of H2O2 production and destruction. Brudzynski [17] reviewed the relation of the H2O2 variation with different factors, such as the different GOx bee production (related to age and cast of the bee and pollen nutrition), glucose concentration, water activity, and osmolarity (high glucose concentration and osmolarity and low water activity reduced the mobility of molecules, inhibiting the GOx reaction), H2O2 accumulation, sensitivity of H2O2 to light and heat, catalase activity, decomposition by metal-containing enzymes and ascorbic acid, products from polyphenols autoxidation, presence of GOx in some flowers, or/and H2O2 production by microorganisms present in honey [18,19,20]. Godocikova [13] highlighted the importance of studying the relation between GOx and CAT activities, because these two enzymes had not been broadly analyzed in different commercial honeys at the same time yet. Sagona [21] verified that both enzymes together with other factors such as gluconic acid and phenolic acid seemed to play a role in the microbial inhibitory activity of honeys.
After China, the European Union (EU) is the world’s second-largest honey producer. Although the total number of beehives is increasing, the EU is only 60% self-sufficient with regard to honey, so imports are needed to cover the EU’s domestic consumption [22]. The quality and properties of honeys are key purchasing factors for consumers and users. Therefore, simplifying the analytical procedures related to beneficial properties that would be written on the honey label is of paramount importance nowadays.
Possible relationships between the antimicrobial activity of honeys, concentration of H2O2, as well as GOx and CAT activities have hardly been researched. GOx is naturally present in an inactive state in honey due to the low pH conditions. When honey is diluted, GOx is activated [11]. Thus, we consider that it is of utmost importance to determine the real activity of GOx instead of the GOx content that was already measured by other researchers [13,15,23]. Therefore, the purpose of this research was to determine the possible relationships among CAT and GOx activities, the concentration of H2O2, and the antimicrobial activity of honeys against Staphylococcus aureus.

2. Materials and Methods

2.1. Materials

Reagents: Sodium dihydrogen phosphate (99.99%) and di-sodium hydrogen phosphate anhydrous (99.99%) were acquired from Merck (Steinheim, Germany). o-dianisidine dihydrochloride (D9154), horseradish peroxidase (P8375-5KU), hydrogen peroxide (>30%), and dialysis membrane (D6191) were acquired from Sigma-Aldrich (St. Louis, MO, USA), which is a part of Merck. Potassium permanganate, sodium oxalate, hydrochloric acid, Baird Parker agar base (BP), and egg yolk emulsion with potassium tellurite were acquired from VWR International Eurolab, which is part of Avantor (Llinars del Vallés, Cataluña, Spain). D-(+)-Glucose (99.99%) was acquired from Panreac (Barcelona, Spain). Nutrient broth no. 2 (NB) and Ringer’s solution were acquired from Oxoid, which is part of Thermo Fisher (Basingstoke, Hampshire, UK). Water was deionized using a Milli-Q water purification system (Wasserlab, Navarra, Spain).
Apparatus: We used the Varian Cary Bio 400 spectrophotometer (Varian, part of Agilent Technologies, Santa Clara, CA, USA) and fluorometer Varioskan LUX microplate reader (Thermo Fisher, Kanderl, Germany). We also used sterile 96-well round-bottomed polystyrene microtiter plates (Brand, Wertheim, Germany).

2.2. Honey Samples

This study was carried out with twenty-four honeys from different botanical origins harvested in 2020 by beekeepers from Castilla y León (Spain). Botanical origins (Table 1) were determined using melissopalynology and sensory analyses [24,25,26,27,28,29]. The samples were stored in the dark at room temperature (20 °C ± 2 °C) until the analyses (for 5 months).

2.3. Catalase and Glucose Oxidase Activity

Sample dialysis: Honey (7.5 g) was dissolved in 4 mL of 0.015 M phosphate buffer (pH 7.0) and quantitatively transferred to the previously activated dialysis membrane. The membrane was closed with tubing clasps and placed into a beaker containing 3 L of phosphate buffer 0.015 M and stored at 4 °C for 11 h. Then, the membrane was placed into another 3 L beaker containing fresh 0.015 M phosphate buffer and stored for another 11 h. Finally, the honey was transferred to a 50 mL volumetric flask at room temperature, and we rinsed the membrane with buffer and used rinsing to dilute the dialyzed honey to the volume [30]. This sample was used for the analysis of GOx and CAT activities.
Catalase activity was performed by the procedure described by Huidobro et al. [30]. The procedure was based on the reaction between the remaining H2O2, after honey’s catalase, and o-dianisidine and peroxidase, measuring the absorbance of the colored product at 400 nm during 30 min at 5, 10, 20, and 30 min each. The result was expressed as the catalase activity (Kf: min−1 g−1) per gram of honey. The standard curve was prepared from 0.00 to 22.48 µg H2O2.
Glucose oxidase activity was performed by the procedure described by Sánchez-Castro [31]. The procedure was based on the reaction between the H2O2 formed in the GOx reaction with o-dianisidine and peroxidase, measuring the colored product spectrophotometrically at 400 nm. The glucose oxidase activity was calculated as the amount of H2O2 (µg) that is obtained in 1 h through the effect of the glucose oxidase contained in 1 g of honey (µg H2O2 h−1 g−1) [18]. The standard curve was prepared from 0.00 to 10.11 µg H2O2.

2.4. Hydrogen Peroxide Concentration

The hydrogen peroxide concentration was performed according to the manufacturer’s instruction of the Flourimetric Hydrogen Peroxide Assay Kit (MAK 165, Sigma-Aldrich). The fluorescence formed was measured at 540 nm excitation and at 590 nm emission after 15 min of incubation at room temperature. The standard curve was generated using dilutions of a fresh 20 mM H2O2 stock solution.

2.5. Antimicrobial Activity

The antimicrobial activity of honeys was assayed against Staphylococcus aureus CECT 435. Bacterium was grown in BP with egg yolk with potassium tellurite for 24 h at 37 °C. Then, one colony was grown in NB 18 h at 37 °C. Cell suspensions were diluted in sterile Ringer’s solution to obtain initial cell counts of 6 log cfu/mL (determined using plate counts).
The antimicrobial activity was evaluated by a broth microdilution assay. For each sample, 9 different honey concentrations (60%, 40%, 30%, 20%, 15%, 10%, 5%, 1%, and 0.5%) dissolved in NB were studied. A total of 80 µL of 6 log CFU/mL of S. aureus was mixed with 720 µL of each sample dilution in sterile Eppendorf tubes. Finally, 200 µL of each tube was pipetted by triplicate into the wells, incubating the plate for 24 h at 37 °C. The contamination control (180 µL honey dilution + 20 µL Ringer), positive control (180 µL NB + 20 µL S. aureus), and negative control (170 µL NB + 20 µL S. aureus + 10 µL bleach) were also established. The minimum inhibitory concentration was defined as the minimum honey concentration where no turbidity was observed after incubation for 24 h at 37 °C. Then, 10 µL of each well, in which no turbidity was observed, was plated on BP and incubated for 24 h at 37 °C. The minimum bactericidal concentration was defined as the minimum concentration of honey at which bacterium did not grow on the agar plates.
Furthermore, the optical density of each well was measured at 600 nm before and after incubation to determine S. aureus growth and the honeys’ inhibition percentage. The inhibition percentage at a 5% honey concentration was calculated considering 100% of growth of the subtraction of the optical density of the wells containing 200 µL of sterile NB from the optical density of the positive control.

2.6. Statistical Analysis

All the analyses were performed in triplicate, expressing the results as mean values and standard deviations. A one-way analysis of variance (ANOVA) followed by the LSD honestly significant difference test (p < 0.05) were performed. Pearson correlations were applied to the results. A multiple regression model was fitted to explain the inhibition percentage at a 5% honey concentration, from CAT and GOx activity, and the H2O2 concentration. The statistical software Statgraphics Centurion XIX was used (Statgraphics Technologies, Inc., The Plains, VA, USA).

3. Results and Discussion

3.1. Catalase and Glucose Oxidase Activity

The honeys showed mean values of catalase activity ranging between non-detected and 88.54 × 10−3 min−1 g−1 (Figure 1A). These values were similar to the results obtained by other authors [21,30,32]. In the honeys in which catalase was not detected, diastase and hydroxymethylfurfural (HMF) were determined. Assays of diastase and HMF were performed according to the harmonized methods of the International Honey Commission [33]. The results of both parameters were in accordance with the standards [34,35], discarding the idea that long storage could be the cause of the non-detection of catalase activity. The CAT activity was very variable. In general, honeydew honeys exhibited the highest activities, while lavender honeys showed the lowest ones. Catalase is the main factor responsible for H2O2 degradation, and its origin is vegetal. Therefore, the catalase activity varied depending on the botanical origin of the samples. Other researchers showed that heather (Erica spp.) and honeydew honeys had higher catalase activity than other honeys [30].
The mean GOx activity for each honey ranged between 130 and 1089 µg H2O2 g−1 h−1 (Figure 1B). The GOx activities in our Spanish honeys were higher that the activities described by other authors in Croatian (25–400 µg H2O2 g−1 h−1) and Turkish honeys (0 and 11.2 µg H2O2 g−1 h−1) [36,37,38], but similar to those obtained by Sánchez [31] in other Spanish honeys (169–858 µg H2O2 g−1 h−1). These discrepancies can be explained considering that the GOx activity significantly varies in different honeys due to various factors, such as pollen in the apiary, bee’s age, bee’s tasks, and the genetic diversity of honeybees [20]. Although the botanical origin could have little to do with the GOx activity [20], our results showed that heather honeys in general had higher activity and lavender honeys had lower activity than others. Strelec et al. [36] and Flanjak et al. [37] described significant differences according to botanical origin, exhibiting that black locust honeys had a considerably lower GOx activity than sage, chestnut, lime, mint, and honeydew honeys.

3.2. Hydrogen Peroxide Concentration

The H2O2 concentration in honeys ranged from 7.26 to 47.56 µg H2O2 g−1 (Figure 1C). These data agree with the values obtained by other authors, ranging from 1 to 47.2 µg g−1 [15,39,40,41]. We did not find any relationship between the amount of H2O2 and the botanical origin of honeys, unlike other researchers [42] who described that honeydew and chestnut honey contained large amounts of H2O2, while acacia, heather, and rape honeys had a lower capacity to produce hydrogen peroxide. On the other hand, Strelec et al. [36] found that lime and chestnut honeys exhibited the highest H2O2 content compared to honeydew, mint, and black locust honeys.
The quantity of H2O2 mainly depends on the CAT and GOx activities. Therefore, it is expected that the H2O2 concentration increases when the CAT activity decreases and GOx activity increases. However, this is not always the case [14,43]. In this work, no correlation was found between H2O2 and GOx and between H2O2 and CAT (p > 0.05) (Table 2). A lack of correlation between GOx and H2O2 was already reported, concluding that GOX activity is not a reliable parameter for the prediction of H2O2 and the antimicrobial activity of honey [13,15,23,36].
In our study, there were four behavioral tendencies of the analyzed honeys regarding the CAT and GOx activities and H2O2 concentration, which can be divided into four different cases:
(1)
Samples exhibiting the expected behavior, with H2O2 mainly being produced by the enzymatic pathway: (a) samples with high GOx activity and non-detected or low CAT activity with a medium-to-high H2O2 concentration (i.e., H1, H4, H6, H7, C); (b) samples with low GOx activity, showing low H2O2, regardless of the CAT activity (i.e., HD1, HD3, M1, M2, LV2), and (c) samples with high GOx activity and medium CAT activity with a medium-to-high H2O2 concentration (H2, H5, HD2, HD5).
(2)
Samples showing a lack of statistical correlation between GOx and H2O2 [23]: samples with high GOx and high CAT with medium-to-low H2O2 concentration (i.e., H8, HD4, M3). In these samples, although GOx would be able to produce H2O2, there is high CAT activity that breaks down H2O2, and therefore the catalase activity neutralizes H2O2.
(3)
Samples in which other factors could be responsible for H2O2 decomposition, such as metal-containing enzymes (i.e., superoxide dismutase), Fenton reaction in the presence of transition metals, ascorbic acid (can be oxidized by H2O2 to dehydroascorbic acid), light, and heat [17,42]: samples with medium-to-high GOx activity and non-detected or low CAT with a low H2O2 concentration (i.e., H3, H10, HB).
(4)
Samples showing medium-to-low GOx activity and high H2O2 concentration (H9, M4, LV1, and HH). In these samples, despite GOx being low, the GOX activity was enough to produce H2O2, there being a lack of or low CAT activity, as well as other pathways responsible for H2O2 decomposition, so that it is likely that H2O2 was kept for longer. Likewise, H2O2 could also be generated by other pathways, such as polyphenols, that in the presence of transition metals are involved in the generation of H2O2, through REDOX processes experienced by nectar, as well as by various fungi and yeasts such as Aspergillus sp. and Penicillum sp., Saccharomyces sp. [15,17,20,44].
Therefore, with regard to the H2O2 contents, significant differences were found among honeys of the same botanical origin, and no differences were found among honeys of different origin. Our results underline the fact that honeys’ H2O2 concentration does not depend on the botanical origin, being instead affected by the previously described factors.

3.3. Antimicrobial Activity

The MIC and MBC of honey against S. aureus ranged from 5% to 20% (Figure 2), highlighting the sample H4 for its higher antimicrobial activity. These values are in accordance with the results obtained by other authors [23,40,44,45] who found MIC values ranging from 2 to 25%, while other researchers found higher MIC values (between 3 and 50%) [15,39]. Manuka honey assayed by Bucekova [44] showed a 5% MIC value and 10% MBC, similar to MIC for H4 and several MBCs of our honeys. The profile of the MBC values was similar or slightly higher than the MIC values, presenting a correlation value of r = 0.7193 (p < 0.001) between the MIC and the MBC.
The botanical origins seemed not to be relevant, and no significant correlation was found between the MIC or MBC and H2O2 or GOx activity. However, heather honeys showed higher GOx and antimicrobial activities, whereas honeydew, multifloral, and lavender honeys showed lower antimicrobial activity than the others, exhibiting lavender honeys with low GOx activities. Therefore, a weak relationship (not statistically significant) was observed between the antimicrobial activity of honey and GOx activity. Other authors found no correlation between antimicrobial activity and H2O2 nor GOx in honeydew honeys, which they related with the presence of catalase, polyphenols, or natural inhibitors of GOx [15,44,46]. Most researchers found correlations between MIC and H2O2 concentrations [13,39,40] and between MIC and GOx activities [45], concluding that the antimicrobial properties of honey depend on the accumulation of H2O2.
Other researchers described higher antimicrobial activity in honeydew honeys than in blossom honeys [13,44], relating dark honeys with higher polyphenol compounds and higher biological activities [47]. Heather honeys are dark honeys, and in previous research, they showed higher phenolics contents than honeydew honeys [48], so it is likely that those compounds contribute to antimicrobial activity.
The sample with the highest antimicrobial activity was H4, which also exhibited a high GOx activity and non-detected CAT, while the six samples that showed MIC values higher than 10% (H8, HD3, HD4, M2, M3, and LV1) and therefore lower antimicrobial activity could have enhanced CAT activity (H8, HD3, HD4, and M3). This fact was confirmed after observing the strong and medium correlations between MIC and MBC and CAT activity (r = 0.6411 and r = 0.4368, respectively) (Table 2). This indicates that the greater the activity of CAT, the greater the MIC and MBC, demonstrating that there is a relationship between antimicrobial activity and the amount of H2O2 that this enzyme can decompose. A previous correlation was shown by Huidobro et al. [30], who described the activity of this enzyme as the main responsible factor for H2O2 decomposition and a possible marker of antimicrobial activity of honeys.
Despite showing all the honeys with medium-to-high antimicrobial activity, with MBC being lower than or equal to 20% (w/v), the inhibition percentages obtained for each honey at a concentration of 5% covered a range from 9.43 (HD5) to 98.58% (H4) (Figure 3). Large variations were observed between honeys of the same botanical origin. Other studies [49] presented inhibition percentages against S. aureus between 66 and 95% for a 10% honey concentration, so that all the honeys analyzed in this study had greater antimicrobial capacity. In the study by Mirzaei et al. [50], lower inhibition percentages were also obtained at higher concentrations of honey (18–40% at a concentration of 25% honey), which corroborates this fact.

3.4. Modeling the Antimicrobial Activity by Means Multiple Regression Models

Linear regression models, using ordinary least squares, have been fitted to explain the antimicrobial activity from CAT and GOx activities and the H2O2 concentration.
As the MIC and MBC response variables take a small number of different values and, in addition, are observational measures, the percentage of inhibition, %Inh. (5%), has been considered to be more suitable to be modeled.
The model for % Inh. (5%) (Equation (1)) accounts for 75.45% of the variability in the percentage of inhibition. The remaining 24.55% is attributable to deviations from the model, which might be partially due to other factors not included in the study, such as acidity, phenolic compounds, or volatile compounds, among others.
%Inh. (5%) = −0.261892 × AT + 0.0416462 × GOx + 0.420271 × H2O2
To illustrate the effect of each predictor, Figure 4 shows the component effects plot, that is, the portion of the fitted regression model corresponding to each variable. The line on the plot is defined by β ^ j x j − x ¯ j , where β ^ j is the estimated regression coefficient for variable j, x j represents the value of variable j as plotted on the horizontal axis, and x ¯ j is its average value. The vertical positions of the points are equal to the component effect plus the residual from the fitted model, which allows us to see the relative importance of a factor compared to the residuals.
In Figure 4A, CAT changes from 0 to 95, while the component effect changes from about 5 to −20, although some residuals are larger than the effect of CAT. Anyway, the first coefficient is negative, meaning that higher levels of CAT lead to lower percentages of inhibitions. Regarding the concentration of GOx, Figure 4B shows that this factor has a positive effect on the percentage of inhibition, given that it changes from about 100 to 1200, whereas the component effect changes from about −26 to 24. Some residuals are also in this case larger than the effect of GOx. Similarly, for a concentration of H2O2 ranging from about 5 to 55, the component effect changes from −9 to 16 (Figure 4C), although some residuals are larger than the effect of H2O2, indicating that other important regressors may be missing from the model.

4. Conclusions

A relationship was found between catalase activity and antimicrobial activity, so that this enzyme could be successfully used as marker for the antimicrobial activity of honey. Moreover, a linear regression model explained the antimicrobial activity (%Inh. (5%)) from CAT and GOx activities and the H2O2 concentration.
Spanish honeys showed good antimicrobial activity against S. aureus, regardless of their botanical origins. Various factors contributed to this activity, with the generation of H2O2 being the primary factor. Additionally, several components, such as flavonoids and other polyphenols, likely act synergistically alongside catalase activity. Spanish honeys showed MIC values comparable to those of other medical grade honeys. Therefore, Spanish honeys could be successfully employed for other uses apart from food, improving the potential biological activities of honey-based formulations (i.e., gels, dressing, ointment, cream, paste, syrup, and pastilles), which can help boost local beekeeping. Further research is needed to verify the activity of all peroxide-related parameters during storage, as well as to identify the honey constituents responsible for the strong non-peroxide antibacterial activity of Spanish honeys.

Author Contributions

Conceptualization, S.M.O. and M.T.S.; methodology, S.M.O., O.V., M.A.F.-M. and M.T.S.; software, C.R., O.V. and S.M.O.; validation, C.R. and S.M.O.; formal analysis, C.R.; investigation, C.R., S.M.O., M.T.S. and M.A.F.-M.; resources, M.T.S. and M.A.F.-M.; data curation, C.R., O.V., S.M.O. and M.T.S.; writing—original draft preparation, S.M.O. and M.T.S.; writing—review and editing, S.M.O., M.T.S. and M.A.F.-M.; visualization, S.M.O.; supervision, S.M.O. and M.T.S.; project administration, S.M.O. and M.T.S.; funding acquisition, M.T.S. and M.A.F.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding authors. The data are not publicly available due to privacy restrictions.

Acknowledgments

The authors would like to thank A. Colina (Saluberia S.L., Spain) for kindly collecting the samples for this study and the Food Technology and Microbiology divisions of the Universidad de Burgos (Spain) for providing their premises and facilities.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Hazrati, M.; Mehrabani, D.; Japoni, A.; Montasery, H.; Azarpira, N.; Hamidian-shirazi, A.R.; Tanideh, N. Effect of honey on healing of Pseudomonas aeruginosa infected burn wounds in rat. J. Appl. Anim. Res. 2010, 37, 161–165. [Google Scholar] [CrossRef]
  2. World Health Organization. WHO Publishes List of Bacteria for Which New Antibiotics Are Urgently Needed. Available online: https://www.who.int/news/item/27-02-2017-who-publishes-list-of-bacteria-for-which-new-antibiotics-are-urgently-needed (accessed on 19 March 2024).
  3. Bogdanov, S. A Short History of Honey. The Book of Honey, Chapter 1. 2011. Available online: https://www.bee-hexagon.net/english/bee-products/downloads-honey-book/ (accessed on 19 March 2024).
  4. Wang, H.; Li, L.; Lin, X.; Bai, W.; Xiao, G.; Liu, G. Composition, functional properties and safety of honey: A review. J. Sci. Food Agric. 2023, 103, 6767–6779. [Google Scholar] [CrossRef] [PubMed]
  5. Dunford, C.R.; Cooper, P.; Molan, P.; White, R. The use of honey in wound treatment. Nurs. Stand. 2000, 15, 63. [Google Scholar] [CrossRef] [PubMed]
  6. Subrahmanyam, M. Topical application of honey for burn wound treatment-an overview. Ann. Burn. Fire Disasters 2007, 20, 137. Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3188068/ (accessed on 8 April 2024).
  7. Majtan, J. Honey: An inmunomodulator in wound healing. Wound Repair Regen. 2014, 22, 187–192. [Google Scholar] [CrossRef]
  8. Hossain, M.L.; Lim, L.Y.; Hammer, K.; Hettiarachchi, D.; Locher, C. Honey-based medicinal formulations: A critical review. Appl. Sci. 2021, 11, 5159. [Google Scholar] [CrossRef]
  9. Feknous, N.; Boumendjel, M. Natural bioactive compounds of honey and their antimicrobial activity. Czech J. Food Sci. 2022, 40, 163–178. [Google Scholar] [CrossRef]
  10. Molan, P.C. The antibacterial activity of honey. Bee World 1992, 73, 59–76. [Google Scholar] [CrossRef]
  11. Almasaudi, S. The antibacterial activities of honey. Saudi J. Biol. Sci. 2021, 28, 2188–2196. [Google Scholar] [CrossRef]
  12. Nolan, V.C.; Harrison, J.; Cox, J.A.G. Dissecting the antimicrobial composition of honey. Antibiotics 2019, 8, 251. [Google Scholar] [CrossRef]
  13. Godocikova, J.; Bugarova, V.; Kast, C.; Majtan, V.; Majtan, J. Antibacterial potential of Swiss honeys and characterization of their bee-derived bioactive compounds. J. Sci. Food Agric. 2020, 100, 335–342. [Google Scholar] [CrossRef] [PubMed]
  14. Weston, R.J. The contribution of catalase and other natural products to the antibacterial activity of honey: A review. Food Chem. 2000, 71, 235–239. [Google Scholar] [CrossRef]
  15. Bucekova, M.; Jardekova, L.; Jurivoca, V.; Bugarova, V.; Di Marco, G.; Gismondi, A.; Leonardi, D.; Farkasovska, J.; Godocikova, J.; Laho, M.; et al. Antibacterial activity of different blossom honeys: New findings. Molecules 2019, 24, 1573. [Google Scholar] [CrossRef] [PubMed]
  16. Khataybeh, B.; Jaradat, Z.; Ababneh, Q. Anti-bacterial, anti-biofilm and anti-quorum sensing activities of honey: A review. J. Ethnopharmacol. 2023, 317, 116830. [Google Scholar] [CrossRef] [PubMed]
  17. Brudzynski, K. A current perspective on hydrogen peroxide production in honey. A review. Food Chem. 2020, 332, 127229. [Google Scholar] [CrossRef] [PubMed]
  18. White, J.W.; Subers, M.H.; Schepartz, A.I. The identification of inhibine, the antibacterial factor in honey, as hydrogen peroxide and its origin in a honey glucose-oxidase system. Biochim. Biophys. Acta 1963, 73, 57–70. [Google Scholar] [CrossRef]
  19. Brudzynski, K. Effect of hydrogen peroxide on antibacterial activities of Canadian honeys. Can J. Microbiol. 2006, 52, 1228–1237. [Google Scholar] [CrossRef] [PubMed]
  20. Bucekova, M.; Valachova, I.; Kohutova, L.; Prochazka, E.; Klaudiny, J.; Majtan, J. Honeybee glucose oxidase-its expression in honeybee workers and comparative analyses of its content and H2O2-mediated antibacterial activity in natural honeys. Naturwissenschaften 2014, 101, 661–670. [Google Scholar] [CrossRef] [PubMed]
  21. Sagona, S.; Turchi, B.; Fratini, F.; Giusti, M.; Torracca, B.; Biondi, C.; Nuvoloni, R.; Cerri, D.; Felicioli, A. Antimicrobial activity of fifteen Italian honeys against Paenibacillus larvae ATCC 9545. J. Hellenic Vet. Med. Soc. 2017, 68, 547–556. [Google Scholar] [CrossRef]
  22. European Commission. Honey Market Presentation. Expert Group for Agricultural Markets. 2023. Available online: https://ec.europa.eu/info/food-farming-fisheries/animals-and-animal-products/animal-products/honey_en. (accessed on 19 March 2024).
  23. Bugarova, V.; Godocikova, J.; Bucekova, M.; Brodschneider, R.; Majtan, J. Effects of the carbohydrate sources nectar, sucrose and invert sugar on antibacterial activity of honey and bee-processed syrups. Antibiotics 2021, 10, 985. [Google Scholar] [CrossRef]
  24. Louveaux, J.; Maurizio, A.; Vorwohl, G. International Commission for Bee Botany of IUBS. In Methods of Melissopalynology. Bee World 1978, 59, 139–157. [Google Scholar] [CrossRef]
  25. Marcazzan, G.L.; Mucignat-Caretta, C.; Marchese, C.M.; Piana, M.L. A review of methods for honey sensory analysis. J. Apic. Res. 2018, 57, 75–87. [Google Scholar] [CrossRef]
  26. Persano Oddo, L.; Piro, R. Main European unifloral honeys: Descriptive sheets. Apidologie 2004, 35, 38–81. [Google Scholar] [CrossRef]
  27. Piana, M.L.; Persano Oddo, L.; Bentabol, A.; Bruneau, E.; Bogdanov, S.; Guyot Declerck, C. Sensory analysis applied to honey: State of the art. Apidologie 2004, 35, 26–37. [Google Scholar] [CrossRef]
  28. Terradillos, L.A.; Muniategui, S.; Sancho, M.T.; Huidobro, J.F.; Simal-Lozano, J. An alternative method for analysis of honey sediment. Bee Sci. 1994, 3, 86–93. Available online: https://www.researchgate.net/publication/235423715_An_Alternative_Method_For_Analysis_Of_Honey_Sediment (accessed on 8 April 2024).
  29. Von der Ohe, W.; Persano Oddo, L.; Piana, M.L.; Morlot, M.; Martin, P. Harmonized methods of melissopalynology. Apidologie 2004, 35, 18–25. [Google Scholar] [CrossRef]
  30. Huidobro, J.F.; Sánchez, M.P.; Muniategui, S.; Sancho, M.T. Precise method for the measurement of catalase activity in honey. J. AOAC Int. 2005, 88, 800–804. [Google Scholar] [CrossRef] [PubMed]
  31. Sánchez-Castro, M. Evolución de la Actividad de las Principales Enzimas de la miel “Producto Galego de Calidade-Mel de Galicia”. Ph.D. Thesis, Santiago de Compostela University, Santiago de Compostela, Spain, 1999. Available online: https://dialnet.unirioja.es/servlet/tesis?codigo=71751 (accessed on 19 March 2024).
  32. Schepartz, A.; Subers, M. Catalase in honey. J. Apic. Res. 1966, 5, 37–43. [Google Scholar] [CrossRef]
  33. International Honey Commission. Harmonised Methods of the International Honey Commission. 2009. World Network of Honey Science. Available online: https://www.ihc-platform.net/ihcmethods2009.pdf (accessed on 24 April 2024).
  34. Codex Alimentarius. Standard for Honey. 2001. FAO, World Health Organization. CXS, 12-1981. Available online: http://www.fao.org/fao-who-codexalimentarius/sh-proxy/en/?lnk=1&url=https%253A%252F%252Fworkspace.fao.org%252Fsites%252Fcodex%252FStandards%252FCXS%2B12-1981%252FCXS_012e.pdf (accessed on 24 April 2024).
  35. EU Monitor. Council Directive 2001/110/EC of 20 December 2001 Relating to Honey. Off. J. Eur. Communities 2002, L10, 47–52. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32001L0110&from=EN (accessed on 10 April 2024).
  36. Strelec, I.; Crevar, B.; Kovaç, T.; Rajs, B.B.; Primorac, L.; Flanjak, I. Glucose oxidase activity and hydrogen peroxide accumulation in Croatian honeys. Croat. J. Food Sci. Technol. 2018, 10, 33–41. [Google Scholar] [CrossRef]
  37. Flanjak, I.; Strelec, I.; Kenjerić, D.; Primorac, L. Croatian produced unifloral honeys characterized according to the protein and proline content and enzyme activities. J. Apic. Sci. 2016, 60, 39–48. [Google Scholar] [CrossRef]
  38. Şahin, H.; Kolayli, S.; Beykaya, M. Comparison of the activity of invertase and glucose-oxidase of raw and commercial honey as a distinguishing parameter. Uludag Bee J. 2020, 20, 13–23. [Google Scholar] [CrossRef]
  39. Faúndez, X.; Báez, M.E.; Martínez, M.; Zúñiga-López, M.C.; Espinoza, J.; Fuentes, E. Evaluation of the generation of reactive oxygen species and antibacterial activity of honey as a function of its phenolic and mineral composition. Food Chem. 2023, 426, 136561. [Google Scholar] [CrossRef]
  40. Farkasovska, J.; Bugarova, V.; Godocikova, J.; Majtan, V.; Majtan, J. The role of hydrogen peroxide in the antibacterial activity of different floral honeys. Eur. Food Res. Technol. 2019, 245, 2739–2744. [Google Scholar] [CrossRef]
  41. Lin, T.; Huang, L.; Cheng, N.; Wang, Y.; Ning, Z.; Huang, S.; Wu, Y.; Chen, T.; Su, S.; Lin, Y. The in vitro and in vivo antibacterial activities of uniflorous honey from a medicinal plant, Scrophularia ningpoensis Hemsl., and characterization of its chemical profile with UPLC-MS/MS. J. Ethnopharmacol. 2022, 296, 115499. [Google Scholar] [CrossRef] [PubMed]
  42. Dustman, J.H. Messung von Wasserstoffperoxid und enzymaktivität in mitteleneuropäischen honigen. Z. Bienenforsch. 1967, 9, 66–73. [Google Scholar]
  43. Madras-Majewska, B. Selected mechanisms of the antimicrobial effect of honey in the aspect of drug resistance of bacteria. Med. Weter 2022, 78, 597–605. [Google Scholar] [CrossRef]
  44. Bucekova, M.; Buriova, M.; Pekarik, L.; Majtan, V.; Majtan, J. Phytochemicals-mediated production of hydrogen peroxide is crucial for high antibacterial activity of honeydew honey. Sci. Rep. 2018, 8, 9061. [Google Scholar] [CrossRef]
  45. Bucekova, M.; Godocikova, J.; Gueyte, R.; Chambrey, C.; Majtan, J. Characterisation of physicochemical parameters and antibacterial properties of New Caledonian honeys. PLoS ONE 2023, 18, e0293730. [Google Scholar] [CrossRef]
  46. Tsavea, E.; Vardaka, F.P.; Savvidaki, E.; Kellil, A.; Kanelis, D.; Bucekova, M.; Grigorakis, S.; Godocikova, J.; Gotsiou, P.; Dimou, M.; et al. Physicochemical characterization and biological properties of pne honey produced across Greece. Foods 2022, 11, 943. [Google Scholar] [CrossRef]
  47. Di Marco, G.; Gismondi, A.; Panzanella, L.; Canuti, L.; Impei, S.; Leonardi, D.; Canini, A. Botanical influence on phenolic profile and antioxidant level of Italian honeys. J. Food Sci. Technol. 2018, 55, 4042–4050. [Google Scholar] [CrossRef] [PubMed]
  48. Alevia, M.; Rasines, S.; Cantero, L.; Sancho, M.T.; Fernández-Muiño, M.A.; Osés, S.M. Chemical extraction and gastrointestinal digestion of honey: Influence on its antioxidant, antimicrobial and anti-inflammatory activities. Foods 2021, 10, 1412. [Google Scholar] [CrossRef] [PubMed]
  49. Moussa, A.; Noureddine, D.; Mohamed, H.S.; Abdelmelek, M.; Saad, A. Antibacterial activity of various honey types of Algeria Against Staphylococcus aureus and Streptococcus pyogenes. Asian Pac. J. Trop. Med. 2012, 5, 773–776. [Google Scholar] [CrossRef] [PubMed]
  50. Mirzaei, A.; Karanmolah, K.S.; Mahnaie, M.P.; Mousavi, F.; Moghadam, P.M.; Mahmoudi, H. Antibacterial activity of honey against methicillin-resistant and sensitive Staphylococcus aureus isolated from patients with diabetic foot ulcer. Open Microbiol. J. 2020, 14, 260–265. [Google Scholar] [CrossRef]
Foods 13 01344 g001
Figure 1. Catalase activity (A), glucose oxidase activity (B), and H2O2 concentration (C) in Spanish honeys from different botanical origins. H: ling heather; HB: ling heather and broom; HD: honeydew; M: multifloral; LV: lavender; HH: holly; C: cornflower. a–j: different letters indicate significant differences (p < 0.05) between honey samples. (n = 3).
Figure 1. Catalase activity (A), glucose oxidase activity (B), and H2O2 concentration (C) in Spanish honeys from different botanical origins. H: ling heather; HB: ling heather and broom; HD: honeydew; M: multifloral; LV: lavender; HH: holly; C: cornflower. a–j: different letters indicate significant differences (p < 0.05) between honey samples. (n = 3).
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Figure 2. Minimal inhibition concentration (MIC, %, w/v) and minimal bactericidal concentration (MBC, %, w/v) of Spanish honeys from different botanical origins against S. aureus. H: heather; HB: heather and broom; HD: honeydew; M: multifloral; LV: lavender; HH: holly; C: cornflower. (n = 3). Triplicates show identical MBC for each sample. Different MBC values indicate significant differences (p < 0.05) among samples.
Figure 2. Minimal inhibition concentration (MIC, %, w/v) and minimal bactericidal concentration (MBC, %, w/v) of Spanish honeys from different botanical origins against S. aureus. H: heather; HB: heather and broom; HD: honeydew; M: multifloral; LV: lavender; HH: holly; C: cornflower. (n = 3). Triplicates show identical MBC for each sample. Different MBC values indicate significant differences (p < 0.05) among samples.
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Figure 3. Inhibition percentage (%) of S. aureus growth of 5% (w/v) Spanish honeys from different botanical origin. H: heather; HB: heather and broom; HD: honeydew; M: multifloral; LV: lavender; HH: holly; C: cornflower. a–l: different letters indicate significant differences (p < 0.05) between honey samples (n = 3).
Figure 3. Inhibition percentage (%) of S. aureus growth of 5% (w/v) Spanish honeys from different botanical origin. H: heather; HB: heather and broom; HD: honeydew; M: multifloral; LV: lavender; HH: holly; C: cornflower. a–l: different letters indicate significant differences (p < 0.05) between honey samples (n = 3).
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Figure 4. Component effect plots in the %Inh. (5%) model. %Inh. (5%) = −0.261892 × CAT + 0.0416462 × GOx + 0.420271 × H2O2. (A): Component effects plot corresponding to CAT; (B): Component effects plot corresponding to GOx; (C): Component effects plot corresponding to H2O2).
Figure 4. Component effect plots in the %Inh. (5%) model. %Inh. (5%) = −0.261892 × CAT + 0.0416462 × GOx + 0.420271 × H2O2. (A): Component effects plot corresponding to CAT; (B): Component effects plot corresponding to GOx; (C): Component effects plot corresponding to H2O2).
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Table 1. Botanical origins of honey samples.
Table 1. Botanical origins of honey samples.
HoneyBotanical OriginScientific Name
H1Ling heatherCalluna vulgaris
H2Ling heatherCalluna vulgaris
H3Ling heatherCalluna vulgaris
H4Ling heatherCalluna vulgaris
H5Ling heatherCalluna vulgaris
H6Ling heatherCalluna vulgaris
H7Ling heatherCalluna vulgaris
H8Ling heatherCalluna vulgaris
H9Ling heatherCalluna vulgaris
H10Ling heatherCalluna vulgaris
HBLing heather and Broom Calluna vulgaris, Retama sp.
HD1Honeydew
HD2Honeydew
HD3Honeydew
HD4Honeydew
HD5Honeydew
M1Multifloral
M2Multifloral
M3Multifloral
M4Multifloral
LV1LavenderLavandula sp.
LV2LavenderLavandula sp.
HHHollyIlex aquifolium
CCornflowerCentaurea cyanus
Table 2. Pearson rank correlation coefficients between catalase, glucose oxidase, H2O2 concentration, MIC, MBC, and % of S. aureus inhibition at 5% of Spanish honeys from different botanical origin.
Table 2. Pearson rank correlation coefficients between catalase, glucose oxidase, H2O2 concentration, MIC, MBC, and % of S. aureus inhibition at 5% of Spanish honeys from different botanical origin.
CATGOxH2O2MICMBC% Inh. (5%)
CAT
GOx0.2894 *
H2O2−0.2175−0.1157
MIC0.6411 ***−0.0086−0.0919
MBC0.4368 **−0.1252−0.14800.7193 ***
% Inh. (5%)−0.3784 **0.1733−0.0298−0.4841 ***−0.5125 ***
* p-value < 0.05; ** p-value < 0.01; *** p-value < 0.001.
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Osés, S.M.; Rodríguez, C.; Valencia, O.; Fernández-Muiño, M.A.; Sancho, M.T. Relationships among Hydrogen Peroxide Concentration, Catalase, Glucose Oxidase, and Antimicrobial Activities of Honeys. Foods 2024, 13, 1344. https://doi.org/10.3390/foods13091344

AMA Style

Osés SM, Rodríguez C, Valencia O, Fernández-Muiño MA, Sancho MT. Relationships among Hydrogen Peroxide Concentration, Catalase, Glucose Oxidase, and Antimicrobial Activities of Honeys. Foods. 2024; 13(9):1344. https://doi.org/10.3390/foods13091344

Chicago/Turabian Style

Osés, Sandra M., Carlos Rodríguez, Olga Valencia, Miguel A. Fernández-Muiño, and M. Teresa Sancho. 2024. "Relationships among Hydrogen Peroxide Concentration, Catalase, Glucose Oxidase, and Antimicrobial Activities of Honeys" Foods 13, no. 9: 1344. https://doi.org/10.3390/foods13091344

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