A2 Biology Coursework

A1- Develop a hypothesis
Outline your biological knowledge or research related to the problem under investigation
Yeast are eukaryotic species and make up approximately one percent of species in the kingdom Fungi. One of the most well studied yeast species, Saccharomyces cerevisiae, commonly known as bakers yeast, and also used in the fermentation of alcohols, is a model species for the study of eukaryotic cells. They are known to reproduce either sexually, by mitosis, or asexually, by budding, depending on environmental conditions. Yeast grow and reproduce by producing enzymes to catabolise polysaccharides. Upon maturation the parent cell passes its genetic information to the bud which then becomes a genetic copy of the original cell and adds to the population. A growth curve demonstrates the four stages of population growth for a yeast cell as follows:
Diagram 1.

Reference: http://classconnection.s3.amazonaws.com/33/flashcards/602033/jpg/bacterial_growth_curve1320203184633.jpg
Lag phase: Indicates the process of assimilation of nutrients by the initial population. Growth is restricted as the yeast are adjusting to their environment and synthesising cellular macromolecules.
Exponential phase: Growth is increasing rapidly at this stage and competition for resources is minimal allowing for the yeast to bud at maximum capacity.
Stationary phase: The population is now stabilising as resources become depleted and competition increases; yeast cells are dying at a similar rate of budding due to the accumulation of cytotoxic wastes and metabolic byproducts, such as ethanol, are produced.
Death phase: Due to the exhaustion of resources and increasing levels of toxic waste the population of yeast starts to decrease. Budding cannot occur at this point as there is limited space for growth reducing the population over time.

Use appropriate biological knowledge and understanding
When considering the growth of yeast cells it is important to understand other factors involved in enzyme activity when metabolising sugars that can directly affect the ability if yeast to reproduce via budding . An enzyme substrate process within the cells affects the metabolism of yeast by which enzymes and substrates move freely about in the cell and in doing so collide with each other. The concentration of both enzymes and substrates will affect the rate in which reactions take place within a yeast cell. The collision theory indicates they have specific binding sites for substrates during collision and in doing so substrate material is taken in by the cell. It is then released by the active site after this transfer of material. Kinetic theory is also influential in yeast growth as more energy causes an increase in enzyme movement within the cell and will affect the rate of collision with substrates and therefore increase yeast growth and reproductive activity.
Enzymes are proteins with a tertiary structure of globular shapes of a folded polypeptide chain held together by hydrogen bonds, ionic bonds and sulphuric bonds. Enzymes have an optimal temperature for activity and when this is surpassed denaturisation of that enzyme can occur causing the active site to be destroyed and the enzyme to become inactive. Acidity and alkalinity can also a factor in the population growth of yeast as there is an optimum pH for enzyme activity. A concentration of hydrogen ions significantly above or below the optimum will lead to a complete loss in enzyme activity and denaturisation.

Select ideas from the information relevant to the investigation
All organisms have optimum temperatures for growth as defined by their specific physiology. Some grow optimally at low temperatures (psychrophiles) and some at high temperatures (thermophiles). Baker’s yeast is a mesophilic microorganism and grows optimally at 40°C because the majority of its metabolic processes have evolved to function at these temperatures. The same can be said for Baker’s yeast in relation to the optimum pH on its metabolic processes. As discussed a pH level that is significantly higher or lower will also affect the strength of non-covalent bonds which are required for tertiary and quaternary structure of proteins.

Link your ideas together to suggest an explanation
At sub-optimal temperatures, the slower movement of molecules in the culture medium and cytosol leads to a slower metabolic rate and therefore growth of the yeast population. At supra-optimal temperatures, the increased kinetic energy is detrimental as the cellular macromolecules begin to become denatured and bonds between the active site of enzymes and their substrates are coincidentally weakened. To counteract the denaturing effects of supra-optimal temperatures, many yeast species synthesise heat-shock proteins. This takes away from resources for growth, also causing a reduction in growth rate.

State precisely in a hypothesis the most appropriate explanation
As stated previously, any supra-optimal temperature will be detrimental to metabolic processes and therefore cell growth and division. The hypothesis is that at temperatures within the optimal growth range of Baker’s yeast, 30 to 40 oC, and population growth will be at a maximum; whereas any temperature exceeding this will result in a decreased growth rate.

A2- Plan a procedure

Using suitable equipment and materials Haemocytometer Cover slip Microscope Pipettes Solution of 1% glucose and 1% yeast solution Water baths (30 and 60 oC) Test tubes
Select a suitable range for the independent variable or suggest conditions for the experimental treatment
For this experiment I will be using a range of 30 0C to 60 oC at 10 degree intervals to provide 5 temperatures to sample from

Communicate an ordered sequence to follow procedure 1% glucose and 1% yeast solutions placed in separate test tubes and incubated in 30 oC and 60 oC water baths for 24 hours Grid cells will be located on a haemocytometer using a microscope A dropper will be used to agitate the solutions before taking a sample from the centre of the solution I will use the pipettes with solution to place a drop on the cell grid of the haemocytometer to allow the cover slip to draw the solution in via capillary action. Using the top left rule of counting I will select 25C squares at random to count the number of yeast cells in each The haemocytometer will then be cleaned and the method repeated for the alternative temperature
Which provides a fair test?
The only varied factors in this experiment are the temperature of the water baths for the investigation. The controlled variables are as follows: Concentration of glucose (1%) Population incubated for 24 hours The pH remains the same by using a buffer The same species of yeast (bakers yeast) is used Top left rule of C cell counting

Predict a result of the test of the hypothesis
It is my hypothesis that the yeast population will be greater at 30 oC and lesser 60 oC and null hypothesis that there is no significant difference in the yeast population at 30oC and 60 oC

A3- Planning for analysis
Clearly state what must be recorded
The number of yeast cells counted in 5 randomly selected B squares each containing 5 randomly selected C squares at 30 oC and 60 oC per 0.00025mm3 and an average taken for both that will be multiplied by 4000 to give the number of yeast cells per mm3
What format will be used to present the results?
A table of personal results will be drawn with the mean number of yeast cells per mm3 worked out.
Table 1.
Table of personal results showing the number of yeast cells per B and C square after being incubated for 24 hours at temperatures of 30 and 60 degrees
B squares C squares No. of yeast cells per 0.00025mm3 at 30 degrees No. of yeast cells per 0.00025mm3 at 60 degrees
1 1 2 3 4 5
2 6 7 8 9 10
3 11 12 13 14 15
4 16 17 18 19 20
5 21 22 23 24 25 Average No. of yeast cells per C square Average No. of yeast cells per mm3

Decide which method of analysis is most appropriate and justify your selection
Class results will be collated by retrieving 13 sets of results from the average number of yeast cells per mm3. This will allow the standard deviation of results to work out the confidence limits and determine if there is a significant difference between the two temperatures being used and give a statistical analysis of our results.
Table 2.
Class table showing results for the average number of yeast cells per mm3 in 1% yeast and 1% glucose solution, after being incubated for 24 hours in water baths of 30oC and 60oC
Name Average number of yeast cells present at 30oC Average number of yeast cells present at 60oC

Mean number of yeast cells per mm3

Decide how much replication is required for successful analysis
I have determined that the optimal amount of replication of the results to prove or disprove the null hypothesis is 30 times for successful analysis.

Consider the feasibility of replication given the time and materials available
Unfortunately due to time and equipment limitations in conducting the experiment only temperatures of 30 oC and 60 oC were used to derive results

B2- Recording and communicating

Organisation of the raw data with the dependant variable in the body of the table and treatments or range of the independent variable as columns or rows
Table 3.
Table of personal results showing the number of yeast cells in 1% yeast and 1% glucose solution; per B and C square after being incubated for 24 hours at temperatures of 30 and 60 degrees
B squares C squares No. of yeast cells per 0.00025mm3 at 30 degrees No. of yeast cells per 0.00025mm3 at 60 degrees
1 1 17 6 2 21 5 3 25 4 4 22 5 5 15 7
2 6 19 4 7 28 6 8 14 6 9 20 3 10 21 3
3 11 18 3 12 23 3 13 24 4 14 27 8 15 25 1
4 16 15 3 17 16 2 18 18 8 19 15 3 20 24 2
5 21 23 3 22 20 4 23 22 2 24 22 1 25 16 2 Average No. of yeast cells per C square 20.4 3.92 Average No. of yeast cells per mm3 8.16 x 104 1.57 x 104

Table 4.
Class table showing results for the average number of yeast cells per mm3 in 1% yeast and 1% glucose solution, after being incubated for 24 hours in water baths of 30oC and 60oC
Name Average number of yeast cells present at 30oC Average number of yeast cells present at 60oC
Adam 8.99 x 104 2.54 x 104
Paul 8.62 x 104 1.87 x 104
Katie 8.17 x 104 2.37 x 104
Catherine 8.91 x 104 2.13 x 104
Lisa 8.98 x 104 2.08 x 104
George 7.33 x 104 2.00 x 104
Lucy 8.83 x 104 1.38 x 104
Kezia 9.27 x 104 1.31 x 104
Andrew 8.16 x 104 1.57 x 104
Ali 7.90 x 104 1.65 x 104
Ryan 7.22 x 104 1.90 x 104
Lucy 8.01 x 104 1.76 x 104
Danielle 7.71 x 104 1.01 x 104
Mean number of yeast cells per mm3 8.32 x 104 1.81 x 104

C1- Analysis graphical analysis

A table of statistical parameters Yeast population at 30oC Yeast population at 60oC
Mean (x) 8.31 x 104 1.81 x 104
Standard Deviation (sd) 0.67 x 104 0.43 x 104
Standard Error (se) 0.19 x 104 0.12 x 104
Upper Confident Limit 8.72 x 104 2.07 x 104
Lower Confident Limit 7.89 x 104 1.55 x 104

Standard deviation at 30oC
SD=√((Sum of squared deviations from mean)/(sample size))=√((5.8357x〖10〗^8 )^ /13)
Standard deviation at 60 oC.
SD=√((Sum of squared deviations from mean)/(sample size))=√((2.4037x〖10〗^8 )^ /13)

Standard error at 30oC
SE=√((Standard deviation squared)/(sample size))=√((0.67x〖10〗^4 )^2/13)
Standard error at 60 oC
SE=√((Standard deviation squared)/(sample size))=√((0.43x〖10〗^4 )^2/13)

Upper confidence limits at 30 oC
CL=Mean+T x SE=8.31 x 〖10〗^4+ (2.179 x 0.19 x 〖10〗^4)
Lower confidence limits at 30 oC
CL=Mean+T x SE=8.31 x 〖10〗^4- (2.179 x 0.19 x 〖10〗^4)

Upper confidence limits at 60 oC
CL=Mean+T x SE=1.81 x 〖10〗^4+ (2.179 x 0.12 x 〖10〗^4)
Lower confidence limits at 60 oC
CL=Mean+T x SE=1.81 x 〖10〗^4- (2.179 x 0.12 x 〖10〗^4)

T value taken from students t values at 95% confidence limits where P=0.05 and the D.F worked out as follows:
D.F= n-1=13-1=12 n= sample size=13

C2- Interpretation

Assessment of the reliability of the data using statistical evidence
The confidence limits calculated and plotted on a graph show the reliability of the results taken from the class. As the confidence limits do not overlap for both temperatures on the graph plotted this suggests a significant difference between the two samples and thus proves the hypothesis stated.

Comments about the reliability of the data
The results for 60 oC are more reliable as there is a narrower bar on the graph plotted between the upper and lower confidence limits and mean than the results for 30 oC. This is because at 60 oC the standard error and confidence limits are smaller than the results derived from the 30 oC samples.

Trends clearly identified using statistical evidence
I can conclude that from the results and statistical evidence there is a significant difference between the mean numbers of yeast cells per mm3 at 30 oC and 60 oC as there is no overlapping in confidence limits proving my hypothesis correct.

Explanation of trends
This is due to the supra-optimal temperature of 60 oC causing a denaturing effect on the yeast enzymes and a detrimental effect on the growth of the yeast population at the death phase (diagram 1). Whereas at 30 oC enzyme activity will not have changed as the optimal temperature for the yeast cells metabolic rate is approximately 40oC causing the yeast population to grow into the exponential phase (diagram 1).

Use of appropriate biological knowledge and understanding
Yeast growth is directly proportional to enzyme activity within a yeast cells affecting its ability to metabolize sugars that provide the energy needed for reproduction via budding. Temperature is an important factor in yeast growth and the experiment conducted proves this as the mean growth rate of yeast per mm3 at 30oC is greater than that at 60 oC.
The tertiary structure of the enzyme becomes denatured when the optimal temperature of 40 oC is surpassed destroying the enzyme substrate process within the yeast cell and effecting population growth as the substrates will not fit to their specific binding sites any more. However this process works at temperatures below 40 oC and enzymes with more kinetic energy close to the optimal temperature can synthesise energy at the maximum growth rate as the enzyme substrate process works more efficiently with increased kinetic energy enabling more collisions to occur.

C3- Evaluation of the practical procedures

Comment on the appropriateness of the range of the independent variable or the conditions for the experimental treatment
The initial range of temperatures I had planned to use were 30-60 oC at 10 degree intervals enabling me to gain 5 sets of results for each temperature. However due to time and equipment constraints I was only able to conduct the experiment at 30 oC and 60 oC. I was still able to carry out a statistical analysis of the results to allow me to prove the hypothesis and get a significant difference between both sets of results with the range chosen.

The procedures used to prevent variation of factors not under investigation
The following procedures were carried out to prevent any variation and ensure a fair test: Concentration of yeast (1%) and glucose (1%) Length of time incubated (24 hours) The same species of yeast was used Top left method of C square counting The same haemocytometer was used and cleaned between counts pH was kept the same using a buffer Amount of yeast and glucose used was the same Same length of time in water baths

Comment on the appropriateness of the observations/ measurement
Although there were only 13 sets of class results for statistical analysis there was still sufficient evidence to prove the hypothesis correct. If more class results were collated perhaps a more reliable set of results could be obtained. The yeast cells were counted using a haemocytometer which is a very accurate piece of equipment that enable counts to be taken to 0.00025mm3 with appropriate concentrations of solution used for the experiment.

Assessment of the validity of the implementation of the procedure
Human error may have caused variation in the results as yeast cells may have been double counted when recording results and place solutions on the haemocytometer correctly, as well as replicating the method for the next temperature. Using a computer to count yeast cells would help remove human error and increase the validity of the results. The temperature within the water baths fluctuate therefore this can also affect the validity of the results. Using a machine to agitate the solution before counting may also reduce the variation in results and make the results more valid.

An outline of how another independent variable could be investigated
Another method of investigation into yeast population growth would be to study the effect of pH on yeast growth. Temperature could be used as a controlled variable along with concentration in this experiment and the pH range that I would use for the study would be pH 3-11. However for a more valid and reliable set of results using a pH range of 1-14 would provide this.