Concentration Of Honey Against Wound Infecting Bacteria Biology Essay

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The purpose of this experiment was to determine the correlation between the concentration of manuka honey against the growth of Staphylococcus aureus and at the same time determining the minimum inhibitory concentration of manuka honey against S.aureus. The manuka honey was mixed with the broth solution along with the bacteria to be cultured in specimen tubes. These tubes were incubated for 24 hours and the turbidity of the solutions which represents the growth of bacteria was determined by using a spectrophotometer. The minimum inhibitory concentration was determined by the lowest concentration of manuka honey that prevented bacterial growth completely, that is, a clear broth solution (low turbidity).A statistical test using the Pearson product-moment coefficient which was carried out at 5 % significance level showed that there was a significant negative correlation between concentration of honey and absorbance which indicates growth of bacteria. The calculated r value (0.7706) was larger than the critical value (0.3172) and this showed a significant negative correlation, hence, the null hypothesis was rejected. The minimum inhibitory concentration of honey to inhibit bacterial growth is about 50% according to the data obtained.

Honey was once used as an antibacterial agent a long time ago but was phased out after the discovery of antibiotics. Recently, due to the prevalence of various antibiotic resistant bacteria there has been a revival of the use of honey, especially for surface infections such as wounds. Honey contains antibacterial activities because of its high sugar content, acidity and presence of hydrogen peroxide.[1][2]

â-²Figure 1: Manuka honey

http://www.amazon.com/Manuka-Spirits-Bay-Active-Standard/dp/B002JEAAHI

(243 words)

Manuka honey is more potent than other types of honey and is particularly effective in destroying bacteria like E.coli and S.aureus (wound infecting bacteria). Manuka honey also contains phytochemical components which are non peroxide antibacterial factors present in the honey. When catalase is used to treat these honeys to remove the hydrogen peroxide, these honeys with the presence of phytochemical components still showed significant antibacterial activity. The honey used in this experiment, manuka honey has been found to have exceptional levels of non peroxide activity.[1][2] The additional phytochemical component of honey has been known as the Unique Manuka Factor (UMF) or more specifically methylglyoxal[7] and due to this property, this honey can be used to kill many bacteria.[1][2][11]

â-²Figure 2: Structure of methylglyoxal

http://en.wikipedia.org/wiki/Methylglyoxal

Wounds in laboratory have been found to heal more rapidly when treated with manuka honey compared to other types of honey.[1] Many bacteria even resistant bacteria which have become resistant to antibiotics are susceptible to the antibacterial activity of manuka honey. Manuka honey has become the only solution to kill bacteria when antibiotics can no longer be used in certain cases. Manuka honey is also stable to heat, light and aging unlike other honey.[1][2]Recent studies also have shown that Manuka honey is able to inhibit enzymes called cysteine proteases which is responsible for muscular dystrophy , viral replication and others.[1][2]

Staphylococcus aureus is a very common wound infecting bacteria found in many types of wounds. Staphylococcus aureus can cause serious infections when they get in through the wound, these include infections in the lungs, bones, joints and many others, but skin infections are most common if they don't get into the body.[3] Staphylococcus is a Gram positive bacterium and are observed either in clusters, individually or in pairs. The cell wall of these bacteria contain peptidoglycan and teichoic acid. Furthermore, these bacteria can survive at temperatures up to 50°C, high salt concentrations and even drying. The ability of this bacteria to clot plasma has served as a common criteria for the identification of these bacteria.[4]

â-²Figure 3: Staphylococcus aureus

http://202.114.65.51/fzjx/wsw/newindex/tuku/MYPER/zxj/92589a.htm

(467 words)

The aim of this experiment was to find out the relationship between the concentration of honey and the growth of bacteria and hence determine the minimum inhibitory concentration of honey to be used on wounds infected with bacteria instead of conventional antibacterial creams or antibiotics. The dependence on antibacterial creams and antibiotics like this will only increase the selection pressure on bacteria and encourage the production of more resistant strains which are more difficult to destroy.

The results from this experiment clearly portray that even though honey was diluted to a certain extent still had significant antibacterial activity. The minimum inhibitory concentration was also found so that it would save cost for hospitals if they were to use honey to treat wounds. Manuka honey costs a lot, so if hospitals were to dilute the honey and at the same time achieve bacterial inhibition or significant bacterial inhibition, this would save a lot of money and at the same time reduce the probability of superbugs developing. Therefore, there is a very high possibility of increasing the usage of honey for treatment of wounds instead of using conventional antibiotics and the effect on bacterial inhibition is comparable to that of antibiotics but with a very great advantage of not producing more superbugs.

â-²Results showing how bacterial inhibition changes with concentration of manuka honey[12]

(819 words)

Null hypothesis

There is no correlation between the concentration of manuka honey and the growth of bacteria.

Experimental hypothesis

The higher the concentration of manuka honey used, the lower the turbidity (indication of bacterial growth).

Variables

Manipulated variable: Concentrations of honey used

Responding variable: Turbidity (indicates growth of bacteria)

Fixed variable: Temperature of the solutions, temperature of incubation, volume of broth solution used, type and amount of bacteria used, type and volume of honey used.

Apparatus

Specimen tubes, label stickers, 1000µl micropipette, electronic balance, Bunsen burner, sterile swabs, spectrophotometer, sterile beakers.

Materials

Sterile nutrient broth, Staphylococcus aureus suspension, sterilized distilled water, manuka honey, antiseptic solution, cuvettes and sterile cotton wool.

(929 words)

Planning

Trials

A trial experiment was conducted to determine which method and also which materials were most suitable to be used in this experiment. All these experiments were carried out using Staphylococcus aureus as it is a common bacterium present on skin and when there is a wound, it is almost always present.[3] This species of bacteria is also used in research using manuka honey.[4][9]

Trial 1: Type of honey

This trial was done using two types of manuka honey which were obtained from a hypermarket and a pharmacy respectively. The manuka honey obtained from the market was intended for daily consumption so it was obtained at a relatively cheaper price. The manuka honey obtained at the pharmacy was lab tested for its antibacterial properties and it was referred to as medical grade manuka honey. The antibacterial properties of these 2 honeys were tested by mixing the honey with broth so that the antibacterial properties of these 2 honeys will be more prominent as it is in direct contact with bacteria.

Broth mixed with manuka honey from hypermarket and bacteria

The broth solution was not clear

Broth mixed with medical grade manuka honey and bacteria

The broth solution was clear

â-²Table 1: The results obtained with respect to the different types of honey used

According to the results above, medical grade manuka honey showed visible antibacterial activity. The medical grade manuka honey was chosen.

(1165 words)

Trial 2: Methods of testing the antibacterial activity

This trial was carried out using a variety of methods to test for the antibacterial properties of the manuka honey. These methods included the disc diffusion method, the well diffusion method, mixing the honey solution directly with the broth and incubating the agar seeded with bacteria prior to adding the honey. Disc diffusion method involves using a sterile paper disc soaked in the honey and then placed on solidified nutrient agar seeded with bacteria. Well diffusion also involves using nutrient agar, but instead of using a paper disc to introduce the honey onto the medium, a well is made using a sterile cork borer and the honey is placed in the well. A control using sterilized distilled water was used as comparison in this trial.

Disc diffusion method

No significant difference from control

Well diffusion method

No significant difference from control

Mixing honey directly with bacteria and broth

The broth mixed with honey showed a clear solution whereas the broth mixed with sterilized distilled water showed a solution that was not clear

Introducing the honey onto the nutrient agar seeded with bacteria

No significant difference from control

â-²Table 2: The results obtained with respect to the different methods used

Mixing honey directly with the broth solution showed results that were most significant. This method was chosen to test for the antibacterial activity of manuka honey against wound infecting bacteria.

(1402 words)

Trial 3: Using different concentrations of honey

The concentrations used were set in a wide range so that patterns or trends could be identified. The concentrations used were 100%, 50%, 25%, 12.5% and 6.25%. The honey solutions were prepared as follows.

Mass of honey (g)

Volume of distilled water (cm3)

Concentration of solution (%)

2

0

100.00

2

2

50.00

2

6

25.00

2

14

12.50

2

30

6.25

â-²Table 3: The different concentrations of honey solutions used and how they were prepared

The following solutions of honey were mixed with nutrient broth solution and a fixed volume of bacteria. The clearness of the solution was determined using a spectrophotometer. The 100% honey solution was not used in obtaining the results as the honey itself contained colour and would affect the reading. The other more dilute solutions would not affect the readings so much as it has a light colour. The spectrophotometer was calibrated using the nutrient broth. The following results were obtained.

Concentration of honey solution (%)

Reading of spectrophotometer

50.00

0.096

25.00

0.225

12.50

0.162

6.25

0.221

â-²Table 4: The results obtained with respect to the different concentrations of honey used

The higher readings indicate a solution that is less clear. The 25 % solution is an anomaly, but the other readings show a visible trend.

From this trial, I learnt that more concentrations need to be used to obtain a more accurate picture of trends shown. Instead of only 5 concentrations, I increased the number of concentrations in the main experiment so that the huge gaps in concentrations could be filled and clearer trends could be seen. I also learnt from this trial that repeats need to be done to obtain an average and also to increase the amount of data available to perform a significant statistical analysis. Repeats carried out can also increase the accuracy of the results obtained. I also learnt that calibrating the spectrophotometer with the nutrient broth together with the different concentrations of honey would produce a more accurate reading of absorbance.

(1715 words)

Real experimental procedure

Preparation of honey solutions

1. A mass of 2 g of honey was weighed using an electronic balance in a sterile beaker.

2. Different volumes of water was added as shown in table to prepare the different concentrations of honey required in the experiment. The concentration of honey was calculated using the following equation:

*1 ml of water was assumed to be 1 g

Concentration of honey/ %

Mass of honey/ g

Volume of water/ ml

50.000

2

2

25.000

2

6

12.500

2

14

6.250

2

30

3.125

2

62

2.000

2

98

â-²Table 5: Mass of honey and volume of water needed to prepare the different concentrations of honey

Experimental procedure

1. 35 sterile specimen tubes were prepared.

2. Each of these tubes was labeled by stating the concentrations of honey solutions that would be put into each specimen tube. The tubes were divided into 6 sets, so that 5 repeats could be performed for each concentration of honey. The remaining 5 tubes were used as controls.

3. Each tube was filled with 4ml of sterile nutrient broth.

4. 400 µl of bacteria was pipetted into the tube followed by 600 µl of honey solution.

5. Each of the specimen tubes were vortexed slightly to mix the contents of the tube.

6. The tubes were placed in a rack and placed in the incubator at a temperature of 37°C for 24 hours.

7. At the end of the incubation period, the tubes were removed from the incubator.

8. The tubes were vortexed again so that all the contents were mixed evenly.

9. A spectrophotometer was calibrated using nutrient broth together with each concentration of honey which was already prepared earlier.

10. The solution in the tube was removed and inserted into a cuvette and placed in the spectrophotometer after ensuring that the cuvette is clean.

11. The reading was recorded.

12. This was repeated for all the other solutions in the other specimen tubes.

13. All the results were recorded in a table.

14. A graph of absorbance was plotted against concentration of honey.

15. A Pearson product-moment correlation coefficient statistical test was carried out to analyse the data.

(2035 words)

Risk assessment

Throughout the whole experiment, aseptic technique was used and given the highest priority to ensure accurate results and to prevent contamination. The table or bench used was cleaned with 70% ethanol solution to kill all bacteria present on the surface.

Hands were washed using antibacterial handwash to remove the risk of bacteria from hands contaminating the experiment.

Gloves were worn at all times to prevent bacteria from hands contaminating equipment and the experiment and also to prevent bacteria from the experiment getting on hands as Staphylococcus aureus can cause serious infections if it gets into the body.

The specimen tubes were also kept close at all times and opened very slightly when solutions were to be inserted into them to prevent contamination from surroundings.

Great care was taken so that none of the contents of the specimen tubes were spilled. Care was also taken that none of the solution was spilled on the spectrophotometer when results were obtained.

The flasks containing nutrient broth and the bottles containing bacteria culture were flamed before and after use.

All the solutions and specimen tubes from the experiment were disposed of in a biohazard waste bag so that it can be autoclaved before disposal.

Results

Concentration of honey

Absorbance

1

2

3

4

5

Mean

Control

0.396

0.390

0.423

0.514

0.503

0.445

50%

0.040

0.043

0.048

0.021

0.037

0.038

25%

0.497

0.464

0.477

0.514

0.474

0.485

12.5%

0.570

1.074

0.729

0.605

0.753

0.746

6.25%

0.363

0.929

0.326

0.179

0.986

0.557

3.125%

0.783

0.693

0.656

0.856

0.626

0.723

2%

0.630

0.649

0.690

0.682

0.622

0.655

â-²Table 6: The absorbance by solution when different concentrations of honey was used

â-²Graph 1: Graph of absorbance against concentration

(2317 words)

Statistical analysis

I chose Pearson product-moment correlation coefficient (PMCC) to measure the strength of the correlation between the 2 variables tested in this experiment which is the absorbance which indicates bacterial growth and concentration of honey. The correlation coefficient, r has a range between -1 and 1. 1 indicates a perfectly positive correlation where an increase of one variable is accompanied by an increase in another variable. A value of -1 indicates a perfectly negative correlation where an increase in a variable is accompanied by a decrease in the other. A value of 0 indicates that there is no correlation between the 2 variables.[6]

x

y

x2

y2

xy

50

0.04

2500

0.0016

2

50

0.043

2500

0.001849

2.15

50

0.048

2500

0.002304

2.4

50

0.021

2500

0.000441

1.05

50

0.037

2500

0.001369

1.85

25

0.497

625

0.247009

12.425

25

0.464

625

0.215296

11.6

25

0.477

625

0.227529

11.925

25

0.514

625

0.264196

12.85

25

0.474

625

0.224676

11.85

12.5

0.57

156.25

0.3249

7.125

12.5

1.074

156.25

1.153476

13.425

12.5

0.729

156.25

0.531441

9.1125

12.5

0.605

156.25

0.366025

7.5625

12.5

0.753

156.25

0.567009

9.4125

6.25

0.363

39.0625

0.131769

2.26875

6.25

0.929

39.0625

0.863041

5.80625

6.25

0.326

39.0625

0.106276

2.0375

6.25

0.179

39.0625

0.032041

1.11875

6.25

0.986

39.0625

0.972196

6.1625

3.125

0.783

9.765625

0.613089

2.446875

3.125

0.693

9.765625

0.480249

2.165625

3.125

0.656

9.765625

0.430336

2.05

3.125

0.856

9.765625

0.732736

2.675

3.125

0.626

9.765625

0.391876

1.95625

2

0.63

4

0.3969

1.26

2

0.649

4

0.421201

1.298

2

0.69

4

0.4761

1.38

2

0.682

4

0.465124

1.364

2

0.622

4

0.386884

1.244

Æ©x= 494.38

Æ©y= 16.02

Æ©x2=16670.39

Æ©y2= 11.03

Æ©xy= 151.97

â-²Table 7: Calculations required for Pearson product-moment correlation analysis

(2594 words)

Using formula to find the correlation coefficient, r

(2614 words)

Degree of freedom= N-2

N equals number of data observed which in this case is 30. Degree of freedom is 28.

The critical value for degree of freedom 4 and a one tailed test at 0.05 significance has a value of 0.3172.[6]

r = 0.7706> 0.3172

An analysis using PMCC showed a statistically significant negative linear relationship between concentration of honey and growth of bacteria since the calculated r value was greater than the critical value at 0.05 significance. The calculated r value was very much larger than the critical value and this signifies that there is only a 5% chance that the negative correlation obtained is by coincidence.

The null hypothesis is rejected.

(2728 words)

Data analysis

Table 5 shows the absorbance obtained using a spectrophotometer from the solutions which contained a fixed volume of nutrient broth, fixed volume of bacteria and a fixed volume of the 6 concentrations of honey. The absorbance obtained from the 5 repeats carried out indicates the extent of growth of bacteria in these solutions. The higher the reading of absorbance obtained, the more extensive the growth of bacteria. The statistical analysis using PMCC verified the negative correlation between the 2 variables. The table showed a general trend of the values indicating that the lower the concentration of honey the lower the inhibition towards bacterial growth.

Graph 1 shows clearly the trend of a negative correlation between these two variables, further illustrating what is shown by the data in the table. A trend line of the data was plotted to show the general trend and relationship between the variables. The least growth of bacteria was observed when 50% of honey solution was used, it gave the lowest reading on the spectrophotometer.

Unfortunately, there were a few anomalies in the data obtained as they did not show a linear negative correlation. There were fluctuations especially with the lower concentrations. At 3.125% and 12.5% concentration of honey solution, the growth of bacteria increased when it was supposed to decrease according to the expected trend.

A control experiment was carried out for each set of concentrations so that a valid comparison can be made between the tubes with honey and those tubes without. The absence of honey in the control experiments allowed bacteria to grow freely as they would in a normal environment which contained no antibacterial agents. This clearly demonstrates the effectiveness of the different concentrations of honey against the growth of bacteria.

The data indicates that only the 50% honey solution shows inhibition of growth compared to the control. The concentrations of honey below 50% all showed a growth of bacteria higher than the control experiments without the honey. This indicates that honey at high concentrations can inhibit or restrict the growth of bacteria but at lower concentrations this does not happen.

(3079 words)

From the data, it is safe to say that the minimum inhibitory concentration of manuka honey is about 50%. This is because as stated above, the concentrations of honey solution lower that 50% did not inhibit bacterial growth as they showed more growth compared to the control experiments. The minimum inhibitory concentration obtained here was compared with an investigation carried out by the Honey Research Unit at University of Waikato in New Zealand. There is a significant difference between the results obtained by them and my results. The reasons for this difference will be further discussed in the evaluation.

â-²Results obtained by the Honey Research Unit at University of Waikato, New Zealand[8]

(3244 words)

Evaluation

Broth was used is this experiment to enable the honey to be mixed directly with the bacteria. This direct contact of the honey with the bacteria gives significantly more visible results. The trend of growth of bacteria can be seen clearly as the concentration changes. The broth was allowed to cool down before being poured into the tubes so that the high temperature of the broth does not kill the bacteria and hence affecting the results. The volumes of the broth, bacteria, honey and also incubation temperature was kept constant so that the only factor affecting the growth of bacteria would be the concentration of honey solution.

There is some variation in the results obtained in this experiment. First of all, for one particular concentration of honey, the readings from the spectrophotometer show quite a wide range. For example, the readings obtained for 12.5% of honey. The maximum reading obtained was 1.074 and the minimum was 0.570. One reason that might have caused this was that the contents of the tube which was the broth, bacteria and honey were not mixed evenly, in this case; vortexing the mixture. Problems may also arise when the bacteria sinks to the bottom and forms sediments which stick to the bottom of the tube and don't mix with the solution. This could give an inaccurate reading. The highest reading on the spectrophotometer of 1.074 was mainly caused by the foam present in the solution due to vigorous mixing of the solution. The same could be said for the concentration of 6.25%. The inconsistent data was mainly caused by the same reasons as mentioned above.

To minimize the errors caused by the problems above, repeats were carried out. Even though, there was considerable variation in the repeats carried out, this was overcome by the mean that was calculated. The mean values were the values used in plotting the graph. The mean values are a better representation of the results as they are the averages of the results obtained. The anomalies mentioned above were included in the calculations of the mean for each concentration to show consistency in the data used, in this case, 5 data for each concentration.

(3608 words)

The control experiments carried out above were for comparison with those containing honey. According to the results obtained, the control experiments had a lower bacterial growth compared to the lower concentrations of honey. This indicates that even with the presence of honey, the bacterial growth is more extensive than the bacterial growth in the control experiments. The only concentration that showed bacterial inhibition was 50% concentration of honey. There is more bacterial growth in the lower concentrations of honey because it promotes the growth of bacteria at lower concentrations instead of inhibiting it.[10] At low concentrations of honey, the typical properties of honey has been minimized. The high sugar concentration that is often associated with the osmotic effect is minimized in low concentrations of honey solution. This provides an ideal environment for bacterial growth since both moisture and food is present. Bacteria like to multiply on nutritious food[5], like rice which is a form of carbohydrate. These carbohydrates when broken down are sugars and these sugars are readily present in the diluted solution of honey, this favors bacterial growth, hence the lower concentrations of honey have more bacteria than the control experiments.

The bacteria used have to be from the same bottle. This is due to the fact that different batches of bacteria which have been cultured at different times may contain different concentrations of bacteria. This may cause inconsistencies in results if a different batch of bacteria is used in the same experiment. This can be avoided by using bacteria from the same bottle to ensure that each tube has the same starting concentration of bacteria, and the only factor that will be affecting the bacteria is the concentration of honey.

Another limitation is that during the experiment, the broth used may be sterile, but while carrying out the experiment, it is exposed to air. This gives an opportunity of microbes in the air to contaminate the broth. This can be avoided by covering the broth every time it is not being used. The surfaces of the bench and the equipment are also exposed to the same risk, so gloves are used to minimize the amount of contamination to equipment and hence obtaining more accurate results.

One more limitation is that when the honey solution is mixed with the broth, the honey is further diluted by the broth. This means that the honey concentration in the tubes is not exactly the concentration of honey prepared from the pure honey. This will affect the results obtained and also the minimum inhibitory concentration. This could have been overcome by taking into account this and preparing a honey solution of higher concentration so that when it is diluted by the broth, the wanted concentration of honey is obtained. This was ignored in the experiment because the error is cancelled out when the same error is present in all the solutions, and it still showed the expected negative correlation. The honey solutions used were still in decreasing concentrations, so the bacterial growth increased.

(4108 words)

All these limitations and anomalies mentioned above caused the error in determining the minimum inhibitory concentration but still managed to show a significant negative correlation between concentration of honey and bacterial growth. This indicates that honey has a huge potential to replace conventional antibiotics in wound care and hence reduce the production of "superbugs".

Conclusion

The higher the concentration of manuka honey, the lower the bacterial growth. The minimum inhibitory concentration form the experiment is 50% manuka honey.

(4186 words)

Source evaluation

Source 1 and 2 is about the antibacterial properties of manuka honey and also about how it is effective on wounds. The information from these sources tally and since one of the sources is from the results and research done by the Honey Research Unit at Waikato University and information from here is considered credible. Source 3, 4 and 5 are all about Staphylococcus aureus, how it infects and also the conditions required for its growth. The information obtained are from medical websites and this can serve as reassurance that the source is reliable. Source 6 is a published book about the statistical analysis in research. It was written by a Professor at Jacksonville University and hence it is a very reliable source. Sources 7,8, 9 10 and 11 are online journals about research done on manuka honey, the type of bacteria it can be used against and the active ingredient in manuka honey. These journals were published on websites like Science direct and Springerlink and also some are published by research units of universities. The journals obtained from these sources are all peer reviewed and this means that other scientists agree with the work done in these journals and the information is reliable.

(4344 words)

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