The effect of antibiotic concentration on bacterial growthIntroductionNull Hypothesis- Increasing the antibiotic concentration has no effect on bacterial growth.
Experimental Hypothesis- Increasing the antibiotic concentration decreases bacterial growth.Scientific TheoryBacteria are prokaryotes and can be identified by their shape. Spherical bacteria are called cocci, rod shaped bacteria are called bacilli, spiral shaped bacteria are called spirilla and curved shape bacteria are called vibrio. All bacteria possess a cell wall, cell membrane and cytoplasm, but no defined nucleus and no nuclear membrane.
Some bacteria may contain other structures such as mesosomes, pili, photosynthetic membranes, 70S ribosomes, flagellum and slime capsules. These can all benefit a bacterium, for example flagellum enables a bacterium to become mobile so that can move to more favorable conditions, and a slime capsule which can prevent cell dehydration and protect against antibiotics. Bacteria mainly function asexually by a process called binary fission, where one cell divides into two daughter cells. Bacteria require nutrients to provide energy and raw materials for biosynthesis.
Energy is needed for the synthesis of new cell materials and for the cell motility. Energy is either obtained from sunlight or from the oxidation of chemical compounds depending on whether the bacteria are phototrophic or chemotrophic.An antibiotic is a compound usually produced by microorganisms, which inhibit or kills bacteria. They generally work in one or two ways; bacteriostatic- inhibits or prevents bacterial growth or bactericidal- actually kill bacteria.
An antibiotic can act on bacteria in one of four ways: Cell membrane disruption- antibiotics alter the cell membrane structure making it more permeable and leading to cell death. Inhibiting cell wall synthesis- antibiotics can inhibit the enzymes involved in the synthesis of peptide cross-links in the cell wall causing the cell wall to weaken. Water constantly enters the cell and the cell bursts due to increase in pressure. This is known as osmotic lysis.
Inhibiting mRNA translation- antibiotics can inhibit protein synthesis by binding across bacterial ribosomes but do not affect eukaryotic cells. Inhibiting nucleic acid synthesis- antibiotics which can inhibit DNA replication.Antibiotics also exist on a spectrum to show how and when they can be used. Some are known as broad spectrum antibiotics and so are effective against a wide range of bacteria and may be initially used in the treatment of undetermined bacterial infections.
Whereas other antibiotics are called narrow spectrum antibiotics, these are effective against a small specific group of bacteria.However antibiotics may not be effective to some bacteria now due to an increasing number of bacterial species becoming resistant to antibiotics. An antibiotic resistant organism develops and is able to grow and reproduce successfully despite the presence of the antibiotic. Bacteria become resistant to antibiotics when they obtain the genes for drug resistance by either spontaneous mutation or the transfer of genes for resistance from other bacteria.
The transmission of antibiotic resistance can occur in two ways. Vertical gene transmission is where resistance to antibiotics arises due to mutation and bacteria containing resistance gene survives when exposed to antibiotic. These bacteria then reproduce and pass the resistance gene onto future generations. Horizontal gene transmission occurs by a process known as conjugation.
The donor cell produces a conjugation tube, which connects two bacterial cells. The donor cells replicates its plasmid which contains a resistance gene and passes the copy of the plasmid to the other bacterium. The recipient cell receives the plasmid and now has the gene for antibiotic resistance.ImplementationApparatus9 sterile test tubes which cotton wool stoppersSterile syringes (10ml)Bunsen burnerIncubator (25oC)Colorimeter10 cuvettesLab coatGogglesNutrient mediaAntibiotic (25ml)Sterile water (25ml)Method1) The workbench was mopped using disinfectant to remove any live microorganisms.
2) A sample of 5ml of bacteria culture was measured out using a sterile syringe and mixed into a small beaker with 45ml of media culture. 3) 9 sterile test tubes with cotton wool bungs were labeled with known concentrations of the antibiotic from the table shown below.Antibiotic concentration (%)Antibiotic volume (ml)Sterile water volume (ml)0 (control)05.0100.
50.51005.004) The concentrations of antibiotics were then made up and then placed in the test tubes and using sterile syringes and placing test tubes through a blue flame on the Bunsen burner to maintain aseptic technique. 5) 5ml of bacteria with nutrient media was then added to each test tube using a sterile syringe.
6) Test tubes were then placed into the incubator at 25oC for 48 hours. 7) Once incubation had taken place the light absorbency of the bacterial cultures were measured using a colorimeter. This was after zeroing the colorimeter using the nutrient media and ensuring that the test tubes were shaken before the samples were placed in the cuvettes.ResultsAntibiotic (%)Volume of antibiotic (cm3)Volume of water (cm3)Light absorbancy (abs)1Light absorbancy (abs)2Light absorbancy (abs)3mean00.
0990.028AnalysisI have produced a graph from my mean results; the graph shows that there is an overall negative correlation and that as you increase the concentration of antibiotic the mean absorbtion of light intensity within the cuvette containing the bacterial culture decreases. This is shown as for my control, which contained no antibiotics the absorbtion levels were as high as 0.192 arbitrary units and had a mean value of 0.
167. When you began to increase the amount of antibiotic in the mixture the mean value decreased down to 0.028 arbitrary units. However there are a few values that I have left out as they are anomalies, as they don’t match the trend being shown on my graph.
These are the mean results at 10%, 40% and 70% of antibiotic concentration.Spearmans rankAntibiotic concentrationRankingMean absorbancyRankingDD2010.1678-7491020.1709-7492030.
06034169080.048263610090.0281864?D2=238rs= 1- 6?D2 = 1- 6×238 = -0.98n(n2-1) 9(92-1)Critical value at 5% level of significance for 9 pairs of values = (-)0.
60Therefore from the results of my spearmans rank, I can reject my null hypothesis and say that there is a 95% chance that my results are not due to chance because I have a value above the critical value of (-)0.60.As my results show that increasing the concentration of antibiotics reduces the amount of bacteria, this supports my scientific theory. Therefore proving that antibiotics do kill bacteria and reduce bacterial growth.
The antibiotic could be doing this by altering the cell membrane of the bacterial cells and making it more permeable therefore leading to cell death, inhibiting the enzymes involved in the synthesis of peptide cross-links in the cell wall causing the cell wall to weaken so that water constantly enters the cell and the cell bursts due to increase in pressure. They could be inhibiting protein synthesis by binding across bacterial ribosome or they could be inhibiting the DNA replication of the bacterial cells. You cannot tell from this investigation how the antibiotic is working but only that it is. As the experiment was started with a 0% concentration of antibiotics this is the control of my experiment and I got a mean result of 0.
167 arbitrary units, this should be the highest value of all my results if it is true that increasing the concentration of antibiotics reduces the bacterial growth. However, this is not the case as for my mean value at 10% concentration of antibiotics in the media, I got a result of 0.170 arbitrary units. On my graph I treated this as an anomaly though as it does not match the trend on the rest of my results and is probably caused by a number of things.
For example there could have been a contamination of bacteria duringthe experiment which led to an increase growth of bacteria in that test tube, the cotton wool bung may have become looser or been smaller on that test tube aswell which meant more O2 could enter the test tube which would increase the amount of respiration and therefore the increase the bacterial growth in the test tube. The cuvette, which I used to measure the light absorbency of this sample, may have been scratched or dirty, which would have then increased the amount of light being absorbed and caused a higher value than usual. The syringe may have also caused this anomaly, as even though they were used to maintain aseptic technique they may have contained bubbles so less antibiotic could have been measured than what was needed, or more growth media could have been added than in the other tubes, which would both benefit the growth of bacteria. These reasons for anomalies may also be the cause for the anomalies at 40% and 50% concentrations where I feel that they are also higher than they should have been and do not fit the rest of the trend, and also the odd values within my 3 repeats which have been highlighted on my table.
Whereas within my results at the 70% concentration of antibiotics I got a really low result in my first out of three repeats. This lower anomaly may have resulted because of a number of things, for example the tube may not have been shaken properly before a sample was put into the cuvette, this means that any bacteria present may have been stuck to the bottom of the test tube. The cotton wool was not controlled and the same for each test tube so there may have been less O2 entering the tube, so less respiration and less bacterial growth. Also as stated before the syringe is not very accurate due to bubbles and it being harder to read, so there might have been a higher volume of antibiotic in this test tube then there should have been, or a lower volume of nutrient media, which is required for bacterial growth.
EvaluationThere were a lot of limitations to this experiment, which could of affected the results and their reliability. These include things like the cotton wool bungs, as they were not controlled as I have previously mentioned, this means they are all different sizes and so will let different amounts of oxygen into each test tube. This could have affected my results by meaningthere was more or less bacterial growth depending on whether more or less oxygen was entering the test tube compared to the other test tubes. The sterile syringes that were used were also a limitation; this is because there are not precise enough and usually got air bubbles in.
This meant that you could not guarantee that the correct volume was being measured for each solution, an alternative to the syringes could have been pipettes as they are more precise and easier to use and read. When using the colorimeter to measure the light absorbancy of each bacterial solution, the same cuvette was not used each time, therefore the results may not have been accurate as one cuvette may have been brand new whereas others could have been older and dirty or scratched which would have affected the reading on the colorimeter. Also using the colorimeter to measure the light absorbancy of these test tubes to give a measurement of the bacteria is a limitation in itself. This is because colorimetry can only be used for a total cell count and not a viable cell count.
This means that any dead bacterial cells will still be counted along with the live bacterial cells. This would affect the results of the investigation as the antibiotics may have killed the bacteria in the test tube but the colorimeter will still identify them because they are dead cells, this could also be why there are higher anomalies at 10% 40% and 70%. Lastly this investigation was only tested on one antibiotic and one bacteria, this is a limitation because you can make a conclusion about these bacteria and antibiotic, but you cannot apply the results to every other bacteria and antibiotic, the test would have to be carried out on more samples of different bacteria and antibiotic first to make the results more reliable.Overall these limitations could affect the graph being produced for this investigation.
If a limitation has caused a shift of a point on the graph, maybe at 20% making it higher than it should be, if this value was accurate it may be lower, and therefore these limitations can change the point at which the majority of bacteria is killed off. However the limitations will not affect the overall conclusion for the investigation, because there is still an overall trend that as the antibiotic concentration increased the number of bacteria decreases.
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