Biomedical Research

The Effect of Ascorbic Acid on Glucose Respiration of Saccharomyces Cerevisiae

By Nicholas JM Wong

Published 10:00 EST, Sat October 16th, 2021


Saccharomyces cerevisiae (commonly known as baker’s yeast) is an opportunistic fungus widely used to ferment human edibles, such as bread and beer (Maicas et al., 2020). As an opportunistic pathogen, S. cerevisiae exhibits the potential to cause illness in immunocompromised individuals. However, the nature of virulent S. cerevisiae strains remains less known because the fungi are unlikely to cause infection. 

Since the 1990s, the number of fungal infections caused by S.cerevisiae has increased while exhibiting risk factors akin to fungi responsible for candidemia (Enache-Angoulvant et al., 2005). Severe cases of S.cerevisiae infections have been primarily found in critically ill patients suffering from immunocompromising underlying conditions such as cancer, HIV infections, and neutropenia (Muñoz et al., 2005). With the emergence of COVID-19 in 2020, S.cerevisiae has also been reported as a co-infectious pathogen in intensive care units of SARS-2 infected patients’ bloodstream (Ventoulis et al., 2020).

Biofilm, an organic substance created by cells, plays a vital role in the virulent spread of S.cerevisiae infections. While there has been limited research done focusing on the significance of biofilms in eukaryotes in contrast to prokaryotes, confocal laser scanning microscopy shows that the biofilm structure of S.cerevisiae is homologous to other infectious yeasts such as Candida albicans and Candida glabrata (Bojsen et al., 2014). C.albicans and S.cerevisiae are also known to be phylogenetically close to each other (Pérez-Torrado et al., 2016). This finding means much of the information surrounding C. albicans, a fungus that is more prevalent and studied, applies to this study. It has been reported that biofilm promotes resistance to antimicrobials by 10-1000 times in C. albicans (Douglas, 2003). Biofilm has also been suggested to be relevant in preventing an immune response in a host’s body. As opposed to planktonic C.albicans cells, leukocytes fail to phagocytose biofilm dispersed cells (Chandra et al., 2007). 

While these examples demonstrate the substances’ significance in defense of the cell, biofilms are also part of the arsenal the fungus uses to cause infections. In contrast to planktonic variants of C.albicans, biofilm dispersed yeast cells exhibit a greater tendency to adhere to surfaces and are more virulent by having direct access to the bloodstream (Uppuluri et al., 2018). The bloodstream’s availability to the fungus unleashes the potential of metastatic infections within the organs of the host (Uppuluri et al., 2010). Most notably, biofilm production allows C.albicans to take residence within the mucosal tissue of the host’s oral cavities, leading to oral infections (Tsui et al., 2016). C.albicans has also been reported to reside within the vagina, causing vaginitis-related infections (Sobel et al., 1984). 

Within S.cerevisiae, the efflux pump also serves as a crucial biological apparatus to cause infections. This pump is a protein located within the cell membrane and is responsible for regulating homeostasis within the cell by diffusing excess substances towards the environment (Pearson et al., 1999). The overexpression of genes encoding for this protein is becoming a prevalent concern across the medical community, as it contributes to growing antimicrobial resistance in microorganisms (Willers et al., 2017). This concern applies towards S.cerevisiae because the gene encoding for the multidrug-efflux pump known as PDR5 is a homologue to the CDR1 gene found within C.albicans (Nakamura et al., 2001). The CDR1 gene is notorious for encoding an energy-dependent multidrug efflux pump responsible for the decrease in susceptibility to azole drug derivatives (Sanglard et al., 1999). In another study, continuous upregulation of the efflux pump has been sufficient to induce an overall resistance towards all azole derivatives (Pfaller, 2012). 

While antifungal medications have been deployed against the fungus, the tolerance of S.cerevisiae to numerous antifungals are poorly understood (Zerva et al, 1996). Despite S.cerevisiae’s known resistance to every azole derivative, it has shown consistent susceptibility to the common drug therapy of amphotericin B and flucytosine (Muñoz et al., 2005). Yet there is a risk to use these two drug therapies frequently due to concerns involving the toxic reactions it may have on patients (Stamm et al., 1987). As of 2017, new antifungals were produced to add to the variety of treatments available, though many possessed chronic or acute negative side effects when administered into patients (Campoy & Adrio, 2017). Furthermore, with the similarity between C.albicans and S.cerevisiae, it is likely that it shares an identical issue in the redundant use of molecular targets in which the former has begun to grow resistance to. Both of these variables limit the deployment and effectiveness of new treatments and calls for new approaches to combat S. cerevisiae. (Sangamwar et al., 2008). 

With the current growing antimicrobial resistance to yeast infections and the limitations in current treatment, identifying a new molecular target is as prevalent as ever. Cellular respiration is a process that cells undergo to metabolize organic molecules to an energy molecule known as adenosine triphosphate (ATP). Although lipids and proteins can be used in respiration, glucose is the organic molecule mainly used in the process. In glucose respiration, glucose molecules are converted into pyruvate through a process known as glycolysis (Caballero et al., 2016). S.cerevisiae is a facultative anaerobe meaning that it has the option to respirate in the absence or presence of oxygen (Krantz et al., 2004). Under the presence of oxygen, pyruvate is converted into several organic intermediate molecules— eventually producing 30-32 ATP (Berg et al., 2002). One byproduct of this process is the release of carbon dioxide (CO2) into the atmosphere. Alternatively, in the absence of oxygen, pyruvate is converted into biofuel, with 2 ATPs and CO2 being produced as a result of anaerobic respiration (Kelly et al., 2001). 

The mitochondria’s significance as a potential target for new drugs stems from the aforementioned virulent factors’ (biofilm and efflux pump) dependency on the organelle and its function. As the efflux pump protein encoded by PDR5 depends on ATP to function, disrupting the production of the energy molecule may inhibit the protein’s effectiveness (Decottignies, 1994). A study explored this concept by applying cyanide to the mitochondria of C. albicans. Affected fungal cells exhibited increased susceptibility to fluconazole, an azole derivative normally ejected by the efflux pump (Yan et al., 2009). However, due to cyanide’s toxicity towards humans, its practical application as a remedy remains limited (Holland, 1986). Mitochondrial respiration also plays a significant role in biofilm formation with specific proteins found within the mitochondria being responsible for biofilm maturation (Calderone et al., 2015). Anaerobic respiration has also even been shown to increase the sturdiness of biofilms, indicating its importance in infections (Yoon et al., 2011). This relationship between biofilm production and mitochondria has been proposed as a possible target for future antifungals in recent studies (Xue et al., 2019). However, exploration of this implication remains limited in scope.

Ascorbic acid is a cofactor responsible for glucose respiration and resistance against infectious diseases in humans (National Center for Biotechnology Information, 2021). Previous literature of its effects on S.cerevisiae indicates that DNA cloned recombinant fungus with the ability to biosynthesize ascorbic acid demonstrated increased anaerobic respiration performance (Branduardi et al., 2007). However, these findings were done through intracellular modification of the cell, thus harmful doses of ascorbic acid could be obstructed through gene regulation— and is a variable the research failed to address (Hahn & Young, 2011). Extracellular insertion of ascorbic acid into S.cerevisiae has not been researched, but, in other eukaryotes it has been correlated with mitochondrial impairment (Bakalova et al., 2020). In 2010, one study published in the National Library of Medicine discussed ascorbic acid’s potential to inhibit glucose respiration in rat adipocytes. Throughout the experiment, adipocytes were incubated in a culture medium containing a presence or absence of 1.6 nM of insulin, and ascorbic acid from a factor of 5-1000 µM. The results concluded that ascorbic acid affected the respiration of insulin-depleted culture medium (Garcia-Diaz et al., 2010). While this study suggests a relationship between respiration and ascorbic acid exists, it does not provide much insight on the performance of S.cerevisiae due to the major differences in respiration pathways as a result of divergent evolution that spans more than 1600 million years (Wang et al., 1999). Furthermore, the study also included insulin as an additional independent variable, which is irrelevant to the present study. 

In a similar vein to the above findings, Avci et al. (2016) investigated respiration changes in C. albicans when administering 90 mM of ascorbic acid. The investigators grew C. albicans in either dextrose or phosphate-buffered saline growth mediums and monitored their growth by measuring the concentration of mitochondrial NADH produced. The authors concluded that ascorbic acid in this concentration was sufficient to inhibit mitochondrial respiration and induce cell death. This finding applies better to S.cerevisiae than those published by Garcia-Diaz et al. because the two fungi share closer evolutionary history and genetics. Despite their similarities, S.cerevisiae lacks NADH complex I proteins found in C.albican’s mitochondria. (Sun et al., 2019). As complex I is vital in the production of NADH, the absence of complex I in S.cerevisiae means the physiological effects that ascorbic may have on baker yeast’s respiration remains unknown (Sharma et al., 2009). Thus, this experiment aimed to determine the effects of varying ascorbic acid concentrations towards the cellular respiration of S. cerevisiae. The results collected from this experiment will yield insight in generating new implications and directions for antifungal medication towards virulent strains of S. cerevisiae


As this study imposed a possible treatment towards an experimental unit, and documented empirical evidence, the methodology followed a scientific experimental design with the objective of discovering the effects of varying ascorbic acid concentrations towards the respiration of S.cerevisiae. S.cerevisiae cultures were groomed in petri dishes and separated into three groups of two depending on whether they were the experimental or positive or negative control group. One out of the two yeast cultures for each group represented the operation under aerobic respiration, whereas the other half performed anaerobic respiration. Both types of respiration were evaluated in this experiment to specifically analyze how these two types of respiration fare with the addition of ascorbic acid from a factor of 0.5 to 1.5 mL. Quantitative data from the concentration of carbon dioxide present, and images at a microscopic level assists in creating novel conclusions for the experiment’s purpose.

Rationale and Hypotheses

It was hypothesized the following effects would occur in this experiment: (1) If ascorbic acid is inserted into a culture of S.cerevisiae then the respiration rate will decrease; (2) If cellular respiration rate continues to decrease then the cell will lyse. Based on Avci et al.’s findings on C.albicans’ exposure to ascorbic acid, the former predicts ascorbic acid is the underlying mechanism for a decrease in respiration, whereas the latter predicts that the lack of ATP being produced from decreased respiration rate will prevent upregulation of intracellular functions. S.cerevisiae strains purchased commercially for this experiment were rationalised as an approximate estimate for the variants responsible for clinical infections. The reason behind this was not only due to the infeasibility of obtaining infectious variations of the fungus, but also because they are in the same species and still contain near-identical genes. 

Biosafety Regulations 

Due to the experiment involving the incubation of microorganisms in a house setting, biosafety must be considered for the safety of the residents. According to the Laboratory Biosafety Manual published by the World Health Organisation, biosafety regulation is determined by the likeliness for the organism in question to be a pathogen. The Hong Kong University Biological Safety Policy and Guidance Policy deems S.cerevisiae to be a part of risk group 1 (no or low individual community risk), therefore with its unlikeliness to be a pathogen, biosafety level 1 protocols was deemed to be the most appropriate for this experiment (Hong Kong University Safety Office, 2019).

Table 1. Relation of risk groups to biosafety levels, practices, and equipment. BSC, biological safety cabinet; GMT, good microbiological techniques. Adapted from World Health Organisation (2004, pp. 2)

Biosafety Level 1 was strictly practiced by having the experiment be performed on a spare flat table. A hand sanitizer spray was used once upon entering the workbench and exiting it, and gloves were worn on site to demote direct skin contact with the fungal culture cells. The surrounding area was sprayed with the sanitiser after completion of each trial in prevention of eliminating spores that escaped through the air due to the opening of the agar plate’s lid to measure respiration. Upon finishing the experiment, used agar plates were immediately washed-out with sodium hypochlorite (bleach) and were immediately disposed of in a plastic bag alongside other materials used throughout the experiment. The exception to this was the CO2 detector which underwent exposure to not only hand sanitizer sprays but with wet tissue. After the final trial, the detector underwent the previous procedures mentioned before being placed in a plastic bag and was exposed to constant UV rays through the sun for 24 hours. Only afterwards was it considered decontaminated. 

Harvesting the Fungus

The experiment extracted from a sample pool of  9 baker’s yeast bags (one for each trial). For a single trial, a bag of yeast was poured into a collection tube, and exposed to 2.5 mL of warm water. The tube was then shaken by hand for approximately 5 seconds. Yeast samples were then extracted through sterilised Q-tips and swabbed onto 6 different petri dishes, containing either sabouraud dextrose agar (SDA) or no media. SDA was used as the growth medium for both the positive control and experimental group culture, while no media was used to facilitate the growth of the negative control group in the petri dish. SDA was the most appropriate growth medium for this experiment, because it is composed of dextrose, a monohydrate variant of glucose; which was the input of respiration this experiment was measuring (National Center for Biotechnology Information, 2021). The stroking pattern followed a “zig-zag” pattern horizontally across the petri-dish before the dish was rotated approximately 120 degrees and the same pattern occurred two more times. Incubation time lasted for approximately 24 hours and under a temperature of 20.0-22.2℃. 

Addition of Ascorbic Acid

A tablet containing 25 g of ascorbic acid (s) purchased from a pharmacy was first stirred and diluted in 300 mL of distilled water under a temperature of 16℃. The surrounding solution was bright orange in color. Then, 0.5 (± 0.25) mL of diluted ascorbic acid (aq) was later extracted through a pipette and inserted into the yeast cultures. The surrounding areas turned opaque and grey in color after the insertion of the acid. This procedure repeated three times for each dosage factor, as subsequent variations of this experiment increased ascorbic acid concentration by 0.5 mL. For example, yeast cultures stemming from the 3rd experiment would have been exposed to 1.5 mL. Throughout the trial runs, randomly selected colonies for dosage were done by another individual to minimise unconscious biased results. Only after the collection of the respiration rate data from each of the 6 yeast cultures was it revealed which data corresponds to which yeast culture. 

Calculating Respiration

To quantify the rate of respiration in the yeast samples, carbon dioxide concentration was chosen as an ideal form of cellular respiration. This method was chosen, because changes in CO2 atmospheric concentration could be noticed and quantitatively measured with ease using a CO2 detector (Massaroni et al., 2019). Furthermore, as this experiment was performed at home, it lacked the resources to analyze the effects of respiration under a molecular level (e.g., concentration of respiration coenzymes). CO2 detectors were vastly more commercially and financially available in contrast to the briefly discussed alternative. 

The CO2 detector model used in this experiment was the WP6003 Bluetooth APP Air Quality Detector and the detector’s data was displayed on the XiaoMei Smart app through bluetooth. Respiration rate in this experiment was measured in the concentration of carbon dioxide for every 5 minutes, and for each yeast culture, the detector was first calibrated to measure the initial concentration of CO2 (ppm) present throughout the household. Therefore, changes in the initial CO2 concentration when measuring each petri dish is a result of the addition of CO2 from respiration output.

Picture 1. Sample screenshot of CO2 detector and XiaoMei Smart app used to record data. TVOC, total volatile organic compounds; HCHO, formaldehyde; ppm, parts per million.

Measuring Anaerobic Respiration

Anaerobic respiration yeast cultures had the petri dish’s lid be kept on top. This served to stimulate an environment in which oxygen count is negligible or nonexistent in order for the cell to start utilising anaerobic respiration. Once every 5 minutes, the lid was removed momentarily and CO2 concentration was measured before the lid was placed back on top. This process repeated 5 times for each individual trial. 

Measuring Aerobic Respiration

Aerobic respiration required the presence of oxygen for the process to begin. Therefore, groomed yeast cultures that represented this type of respiration throughout the experiment had its lid removed once ascorbic acid was inserted into the experimental group. Once each trial was over, the cover was immediately placed back on top of the petri dish, and the surrounding area was sprayed with hand sanitizer spray as mentioned above.

Observation of Yeast Under Light Microscope

Unfortunately, the light microscope used during the experiment was damaged – therefore, this experiment was only able to salvage qualitative data from the third trial of each dosage factor. Yeasts after the 5th recording of respiration data followed a wet mounting procedure. S. cerevisiae from each group with the exception of the negative control groups were swabbed with a sterilised q-tip onto a microscope slide that contained a 0.5 mL drop of distilled water. In the experimental groups, the sterilised q-tips specifically targeted the opaque regions of the culture medium. Each slide was stained with iodine, and observed under a magnification power of 1200X. The aforementioned staining procedure was replicated for each subsequent trial, and pictures were taken through an iPhone XS Max’s camera lens. The pictures taken serves as qualitative data to gather more insight of how ascorbic acid affected the fungus’ respiration rate on a microscopic scale and to test whether it induced cell death. 


Table 2. Raw data of CO2 concentration throughout the 25 minutes observation

CulturesInitial CO2 Concentration (ppm)5 minutes CO2 Concentration (ppm)10 minutes CO2 Concentration (ppm)15 minutes CO2 Concentration (ppm) 20 minutes CO2 Concentration (ppm)25 minutes CO2 Concentration (ppm)
0.5 mL (Trial 1) 
Aerobic Experimental Group  103 126 483 497 199 212 
Anaerobic Experimental Group 211 21880114231398
Aerobic Positive Control 5420313811416475
Anaerobic Positive Control 611558392265120
Aerobic Negative Control 
Anaerobic Negative Control 2
0.5 mL (Trial 2)
Aerobic Experimental Group172548414117611226
Anaerobic Experimental Group65021170397338 
Aerobic Positive Control 124330239 157127158 
Anaerobic Positive Control 8350 62 12127 
Aerobic Negative Control 32000
Anaerobic Negative Control 013040
0.5 mL (Trial 3) 
Aerobic Experimental Group  54728331311
Anaerobic Experimental Group 1200116
Aerobic Positive Control 664947313260
Anaerobic Positive Control 6682977
Aerobic Negative Control 100000
Anaerobic Negative Control 006006
1 mL (Trial 1) 
Aerobic Experiment 167222186131180
Anaerobic Experiment 1662518614711469
Aerobic Positive Control 103300267249188117
Anaerobic Positive Control751311115597
Aerobic Negative Control000000
Anaerobic Negative Control 000200
1 mL (Trial 2)
Aerobic Experiment 95471629170316
Anaerobic Experiment 3746018214094891 
Aerobic Positive Control 81440230148466191 
Anaerobic Positive Control976011255146170
Aerobic Negative Control2142602
Anaerobic Negative Control 700259
1  mL (Trial 3)
Aerobic Experiment 46141937328
Anaerobic Experiment 1627762
Aerobic Positive Control 501441517663
Anaerobic Positive Control9234915
Aerobic Negative Control000300
Anaerobic Negative Control 0490000
1.5 mL (Trial 1) 
Aerobic Experimental Group  423359162130131
Anaerobic Experimental Group 6217388100120
Aerobic Positive Control 186152165213158347
Anaerobic Positive Control 2011051958363202
Aerobic Negative Control 000000
Anaerobic Negative Control 000000
1.5  mL (Trial 2)
Aerobic Experimental Group  15736801172979
Anaerobic Experimental Group 535721410740  29
Aerobic Positive Control 3112141717153118
Anaerobic Positive Control 60346162555486
Aerobic Negative Control 000000
Anaerobic Negative Control 000000
1.5 mL (Trial 3)
Aerobic Experimental Group  21292247
Anaerobic Experimental Group 550718106
Aerobic Positive Control 203021662971
Anaerobic Positive Control 53022201117
Aerobic Negative Control 000060
Anaerobic Negative Control 000000
Table 2. This table shows the change in CO2 concentration within each yeast culture using the unit measurement of ppm over the 25 minute observations between the control yeast cultures and yeasts exposed to 25g of ascorbic acid ranging from 0.5 mL to 1.5 mL.


To test the statistical significance of the collected data, an initial assumption was made that the data followed a normal distribution—as the sample size failed to follow the central limit theorem (number of trials>30). This assumption allowed the data to be put through hypothesis testing and analyzed of its variances (ANOVA). A factorial ANOVA was deemed the most fit for this type of data analysis, because there are two independent variables (6 different of S. cerevisiae culture and 4 dosage factors) and one dependent variable (CO2 concentration). Then the test groups were put under a Tukey’s honestly significance test under a 95% family-wise confidence level. The margin of error (MOE) for each point estimate sample mean was calculated under a 95% confidence level using the equation: Margin of Error =  Critical Value  Standard Error— in which the chosen critical value was a t-score. Unfortunately, as each experimental factor was only tested three times respectively, the range from the data collected was not sufficient enough to determine outliers. Negative control groups were also excluded from this calculation, because mathematically, negative results (getting a 0) would be deemed an outlier using the following equation when it is in fact the purpose of a negative control. The equation to determine outliers was done only towards the positive control groups through the computation of the interquartile range and the numerical threshold using the equation: Lower Outlier Q1-1.5(Q3-Q1)and Higher Outlier Q3+1.5(Q3-Q1). 

Table 3. Factorial ANOVA Test 

Yeast Culture1040955520819118.1025.48e-15
Ascorbic Acid Concentration19484817114620.9970.463
Yeast and ascorbic acid interaction87511485109250.8950.719
Table 3. This table represents the two-level ANOVA test when the calculated threshold is the following for 3 null hypotheses for the experiment’s data to be statistically significant; (1) Yeasts average CO2 concentration are the same when p>0.001; (2) Average ascorbic acid concentrations are all equal when p>1; (3) There is no interaction between ascorbic acid and yeasts when p>0.1. SS, sum of squares; df, degrees of freedom; MSQ, mean square.

Table 4. 95% Family-Wise Confidence Level Tukey’s HSD Test

 DifferenceP. (Adj)
Exp-aer & exp-anae -14.8890.979
Exp-aer & neg-aer -124.685P<0.01
Exp-aer & Neg-ana -123.796P<0.01
Exp-aer & pos-aer 16.8890.964
Exp-aer & pos-ana-41.6480.336
Exp-ana & neg-aer-109.796P<0.01
Exp-ana & neg-ana-108.907P<0.01
Exp-ana & pos-aer31.7780.639
Exp-ana & pos-aer-26.7590.787
Neg-aer & neg-ana0.8891.000
Neg-aer & pos-aer141.574P<0.01
Neg-aer & pos-ana83.0370.001
Neg-ana & pos-aer140.685P<0.001
Neg-ana & pos-ana82.148P<0.001
Pos-ana & pos-aer-58.5370.056 
Table 4. This table represents Tukey’s honestly significant difference test done following the factorial ANOVA test. Exp-aer, experimental aerobic culture; exp-ana, experimental anaerobic culture; neg-aer, negative control aerobic culture; neg-ana, negative control anaerobic culture; pos-aer, positive control aerobic culture; pos-ana, positive control anaerobic culture.

Graph 1. Average change in CO2 concentration based on time and dosage factors

Graph 1. This graph represents the average CO2 concentration calculated and is separated based on time of measurement and dosage factors. E represents the dosage factors (E1 = 0.5 mL, E3 = 1.5 mL) and the two digits following the dash, demonstrates time (e.g -00 = 0 minutes, -20 = 20 minutes).

Table 5. Summary table of CO2 mean respiration rate in varying cultures

InitialMOE5 minutes MOE10 minutesMOE15 minutesMOE20 minutesMOE25 minutesMOE
Average Experimental Aerobic 0.5 mL93.3208.48240.3669.18 308.3609.18215.7614.21313.7645.28146.3313.17
Average Experimental Anaerobic 0.5 mL113.7255.6090.0281.7633.7103.0694.7215.22209.7494.03250.7510.34 
Average Experimental Aerobic 1 mL33.3132.7038.369.58141.7229.05123.3134.8158.058.18174.7357.92 
Average Experimental Anaerobic 1 mL73.0201.77162.3641.06 125.0253.9298.0195.9671.3142.73320.71229.88
Average Experimental Aerobic 1.5 mL73.3181.8923.746.7349.390.62100.3177.54 54.3165.7572.3154.69 
Average Experimental Anaerobic 1.5 mL40.076.1293.3171.60103.0259.1345.0133.7616.751.71 51.7149.79 
Average Positive Aerobic 110.5368.76192.43112.94 146.5370.79 117.1363.07154.80101.88133.3770.70 
Average Positive Anaerobic 64.351.35 93.63390.14 116.77 128.54 
Average Negative Aerobic1.11.50 1.83.570.440.6711.64 0.661.55 0.2220.51 
Average Negative Anaerobic 1.1251.80 0.12512.521.1251.640.50.51 1.1251.55 1.882.61 
Table 5. This table represents the average respiration rate throughout the 25 minutes of observations based on the different types of yeast cultures. MOE, Margin of Error. 

Graph 2. Positive controls CO2 concentration boxplot and outliers 

Graph 2. The multi-group boxplot represents the CO2 concentration collected throughout the experiment in the different intervals. It is separated into groups representing the type of respiration and time they were collected in. Outliers are represented using blue dots.

Figure 1. Trial 3 yeast cultures in 0.5 mL experiment 

Figure 1. The darkish brown “dots” on the imaging are yeast cells.

Figure 2. Trial 3 yeast cultures in 1 mL experiment 

Figure 2. Water bubbles and foreign debris are found on the top left and right as well as the center bottom of the experimental group measuring aerobic respiration. The positive controls’ debris are found in the center of each imageand are circlish black in color.

Figure 3. Trial 3 yeast cultures in 1.5 mL experiment 

Figure 3. The bottom right image’s change in background color to complete yellow is due to excess iodine staining. Foreign molecules are detected in the center of that image in the form of a blackish yellow circle. Water molecules are also detected in the image of experimental anaerobic respiring yeast culture on the center left and right side of the picture.

Data Analysis

Throughout the experiment, carbon dioxide concentration was the dependent variable used to determine ascorbic acid’s effects on S.cerevisae’s respiration. Preliminary ANOVA hypothesis testing suggests that there is no interaction between the yeast’s respiration and the different dosage factors of ascorbic acid. Table 3 supports this claim, as shown in the third column, as the p-value (0.719) is not within the area of the significance level (0.1). Graph 1 alongside the summary table, further supports the non-significance of the data—as for example, the point estimate mean for the aerobic respiring culture exposed to 0.5 mL of ascorbic acid in trial 1 can still deviate by 208.48—which falls within the interval of the positive aerobic control. Tukey’s HSD also demonstrates that the adjusted p-value remains statistically insignificant at an alpha as high as 0.1 when comparing the respective experimental cultures to its positive control counterparts. 

Experimental precision is left a bit to be desired, table 2 shows that the negative controls in each dosage factor may not always produce 0 ppm—despite the purpose of the negative control being to produce no data. Graph 2 also indicates that the individual CO2 concentration for the positive respiring yeast cultures contained outliers. Nevertheless, table 4 indicates that each of the negative respiring cultures were statistically different to their positive and experimental counterparts. 


The results yielded results that failed to reject the null hypothesis—which asserts that the difference in numerical values in the respiration data has no relationship with ascorbic acid. One possible explanation for the failure to reject the null was the poor sample size this experiment used for the treatment groups. The lack of sampling variability, means that the results were dependent on factors found within the yeast cultures being measured. Alternatively and more likely to be the case, this null hypothesis truly reflected the effect of ascorbic acid when inserted into the yeast. The microscopic images reinforce this claim, as it provides little to no convincing evidence that cell lysis occurred in the experimental group despite hypothesizing earlier such an event might be plausible if respiration was inhibited. In figure 3, the distribution of S.cerevisae’s presence is approximately identical to each other, figure 2 displays this phoenomanum too. Although the aerobic respiring experimental culture seems to have less yeast cells in its surroundings, the excess water bubbles found throughout the image and it being more prevalent compared to any of the other pictures suggests that the yeast cultures could have been swept away by the water bubbles to other parts of the microscope slides. Figure 1’s yeast follows approximately the same cell count as the previous 2 figures would show. Furthermore, in some of the figures (e.g Figure 2 positive anaerobic and experimental anaerobic and Figure 1 experimental aerobic and positive aerobic), the clustered cells suggests that the yeasts under observation were specifically biofilm dispersed cells—given that both experimental and positive cultures are producing biofilms, this reinforces the connotation that cellular respiration and the mitochondria were not affected. However without an electron microscope, there is no visual evidence to prove whether these cells were truly intact as a result of the organic compound. The difference between S.cerevisae’s cellular respiration and the C.albicans’ respiration is the latter’s use of NADH complex I throughout the process. The change in outcome from this study’s finding suggests that ascorbic acid actively denatures complex I—the effectiveness of ascorbic acid as a treatment is dependent on whether the organism in question is reliant on complex I for mitochondrial respiration.    


The purpose of this experiment was to provide empirical evidence on the effectiveness of ascorbic acid as a possible treatment that targeted the cellular respiration of S.cerevisiae. It has been rationalized and predicted that based on the effectiveness of ascorbic acid treatment towards C.albicans, that the end result would have been homogenous, however this was proven false by the ANOVA testing, as the probability of obtaining such a sample under the pretense the null hypothesis was true is 71%—a value significantly higher than the alpha threshold. In addition, there has been not only a lack of evidence that yeast cellular necrosis in any way has occurred, but also, conversely, the suspected presence of biofilm across the experimental groups further suggests that the mitochondria has not been impaired by the insertion of ascorbic acid into the culture medium. 

Evaluation and Future Directions

As the experiment failed to reject the null hypothesis, exploration of ascorbic acid as a potential treatment for S.cerevisiae infections has no future direction, however there are nevertheless improvements that can be made to this experiment. The most serious error committed throughout the course of the entire experiment was the lack of subsequent trials done towards the experimental group and the consequence of this failure reverberates across the results and statistical calculations. This is best demonstrated by the margin of error calculated in the summary table, as a large deviation from the point estimate is present in almost every trial. This huge range deters the reliability of the experiment’s results of S.cerevisae’s susceptibility to ascorbic acid. Furthermore, although there were enough trials to detect outliers in the positive control groups, for other cultures, the limitations of being bound to three trials prevented the computation of an interquartile range. This limited precision and skewed the final mean—as data inconsistencies could not be thrown away and justified as an anomaly. To circumvent this issue, the increase in the number of trials for future iterations of this experiment is highly recommended, which will not only lower the variability in the margin of error—providing more clarity on the statistical significance of the data, but also lower the probability that the failure to reject the null hypothesis is a case of type II error.

Despite the best efforts to prevent any extraneous variables from influencing the data through practicing biosafety regulations, there are still confounding variables that when accounted for—damages the reliability of the data. Glucose respiration was not the only dependent variable being measured in this experiment, which is best observed in some of the negative controls having an increase in CO2 concentration despite being grown in no culture medium. On the day of equipment disposal, the formation of molds on the petri dish is testimony that the petri dishes were contaminated with other microorganisms, and thus, the data gathered is possibly an overestimate of the CO2 concentration produced if the medium only grew baker’s yeast. This is a confounding variable brought forth by budgeting constraints—if this experiment was performed in a laminar chamber, the contamination of the petri dish by other microbes would be severely limited. Mold spores present may also be further circumvented by having this experiment be performed in a positive pressure chamber. 

Although there is no future directions of using ascorbic acid as a possible treatment for S.cerevisiae, the data obtained from this experiment in relation to previous studies with yeast cells containing complex I suggests that there could be a correlation between ascorbic acid’s ability to inhibit this coenzyme. Future research may confirm this prediction by conducting an experiment which measures complex I’s function in the presence of ascorbic acid in varying microorganisms. 


The making of this paper would not be possible without the collaboration and assistance of many. I would first like to thank my AP Research teacher: Ms. Laura Brown and Dr. Jennifer Gresham for all their hard work in guiding me through my journey as a research student. Although they had no background in the scientific field, the lessons and knowledge I’ve obtained from them will no doubt help me in my future endeavors in academia—and their persistence throughout the school year to try and understand my paper should be acknowledged.

Although I had many expert advisors, I would like to specifically thank my main advisor: Ms. Sabrina Hoong, for taking the time to further develop my research question even under unexpected and immediate circumstances during the late month of October to November. I would also like to thank her for facilitating my learning in her AP Biology class, while also pushing through the hardships of the school year during the pandemic. In the making of the inquiry proposal form, I would like to acknowledge Ms. Erin Baugher for her second and expert opinion at the expense of time from her IB biology class to help a person that she only came to know from Ms. Brown. In addition, I would like to thank Mr. Micheal Benestante for his third opinion on the inquiry proposal form. 

Most of the equipment used in this research project would not have been possible without the gracious help of Dr. Sophie St-Hilaire and her daughter—one of my best friends, Nicola Chalmers—who allowed me to use the City University of Hong Kong’s laboratory equipment without the need to reimburse them. Dr. St-Hilaire’s contributions to previous science projects in the past have yet to be acknowledged till now, and I am grateful for her continued support and sponsorship. 

In polishing the finishing touches to my paper, I would like to thank Dr. Lloyd Mirto and Ms. Kathleen Abel for their invaluable feedback. Although the following that will be listed did not directly contribute to the making of the paper, I would like to thank Mr. Eunsup Kang for being my AP Statistics teacher this year and his contributions to my current understanding of statistical analysis.

To Dr. Steven Paul Rines and Ms. Christina Sheng-Wei Lin, the latter who was a significant figure in building up my passion and pre-existing knowledge for biology prior to even stepping foot into this class, while the former was crucial in honing my skill in writing academic papers in the form of lab reports. Such a skill was vital in the creation of this paper, which in many ways was structured like a lab report.

Last but not least, I would like to thank my two families for their constant support. The first is my biological family, who allowed me to use the house as a temporary laboratory throughout the course of my experiment, whereas my second family was the 4 classmates present in my small AP Research class. I’ve enjoyed working with every single one of them throughout the school year, and the constant support and fun we had as a class is something I will cherish. I wish them all the best moving forwards outside of this course.  

Nicholas JM Wong, Youth Medical Journal 2021


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