ATP yield of fermentation: study to cite?

ATP yield of fermentation: study to cite?

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Everywhere I find the ATP yields of respiratory and fermentative metabolism of glycolysis. While that of oxidative phosphorilation I could find in Stryer to cite one study where this was addressed (Hinkle 1991 observed 30 ATP/glucose) I cannot find a study where the 2 ATP/glucose was observed and the textbooks I've searched do not provide a citation.

Can anyone please provide a link or citation to a paper where the ATP yield of fermentation (regardless of process) was quantified/estimated?


For glycolysis this is really not so much of an issue, because the ATP yield is fixed by stoichiometry. The early biochemistry work by Embden, Meyerhof, Parnas and other that mapped out the reaction mechanisms of the glycolytic pathway shows that you always obtain exactly 2 ATP per glucose; this is simply the stoichiometry of those reactions. There are a number of primary papers documenting these reaction mechanisms, but it's a large undertaking to go through all of it; the glycolysis chapter of Stryer's Biochemistry is a good summary I think. A brief review of the historical development is described in: "A Fresh View of Glycolysis and Glucokinase Regulation: History and Current Status".

For respiration it's very different, since there is no fixed stoichiometry for chemiosmosis --- the ATP yield depends on the proton gradient across the inner mitochondrial membrane, which in turn depends on a number of factors. So in this case ATP yield will differ between cell types and conditions, and must be measured experimentally.

Economics of membrane occupancy and respiro-fermentation

*Corresponding author. Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Rm. 326, Toronto, Ontario, Canada M5S3E5. Tel.: +1 416 946 0996 Fax: +1 416 978 8605 E-mail: [email protected]

The simultaneous utilization of efficient respiration and inefficient fermentation even in the presence of abundant oxygen is a puzzling phenomenon commonly observed in bacteria, yeasts, and cancer cells. Despite extensive research, the biochemical basis for this phenomenon remains obscure. We hypothesize that the outcome of a competition for membrane space between glucose transporters and respiratory chain (which we refer to as economics of membrane occupancy) proteins influences respiration and fermentation. By incorporating a sole constraint based on this concept in the genome-scale metabolic model of Escherichia coli, we were able to simulate respiro-fermentation. Further analysis of the impact of this constraint revealed differential utilization of the cytochromes and faster glucose uptake under anaerobic conditions than under aerobic conditions. Based on these simulations, we propose that bacterial cells manage the composition of their cytoplasmic membrane to maintain optimal ATP production by switching between oxidative and substrate-level phosphorylation. These results suggest that the membrane occupancy constraint may be a fundamental governing constraint of cellular metabolism and physiology, and establishes a direct link between cell morphology and physiology.

Empirical versus theoretical estimates of the ATP cost per cell

There are two complementary methods for answering the question – one experimental, the other theoretical. The amount of ATP used by a population of cells as they grow can be experimentally determined based on the rate of substrate consumption. The average amount of ATP required per cell can then be determined. In the theoretical approach, the amount of ATP necessary for creating all the macromolecules can be calculated from all the known biochemical pathways within a cell. This calculation is based on knowledge of the composition of an E. coli cell, i.e. how much of each amino acid, nucleotide, lipid, etc. exists in a cell or gram of cells. This theoretical computation tests our understanding of the energy-consuming processes of a cell.

To compare experimental and theoretical calculations, the value of YATPmax is commonly used. It is derived from YATP, which is defined as the number of grams of cells (dry weight) that are produced by 1 mole of ATP (Bauchop and Elsden 1960). (see description below on how it is derived). For example, at the slow growth rate of 0.087/hr, and under anaerobic conditions on glucose, an E. coli population produces

3 g cells/mole of ATP (Hempfling and Mainzer 1975). All numbers presented refer to the gram(s) of dry cell weight. 96.1% of the cell’s dry weight is made of macromolecules (Neidhardt et al. 1990)(BNID 101436).

To arrive at the number of ATP molecules per cell, one needs to know the dry weight of an average E. coli, which is taken to be 0.28 pg (Neidhardt et al. 1990)(BNID 100008) or 3.6 trillion cells/g. Cell size is dependent on growth rate and the value of 0.28 pg is for a growth rate of 0.66, (doubling time 40 minutes).


Many heterotrophs can produce ATP through both respiratory and fermentative pathways, allowing them to survive with or without oxygen. Since the molar ATP yield (molar ATP yield: mole of ATP produced/mole of substrate consumed) from respiration is about 15-fold higher than that from fermentation, ATP production via respiration is more efficient. Surprisingly, at high catabolic rate, many facultative aerobic organisms employ fermentative pathways simultaneously with respiration, even in the presence of abundant oxygen to produce ATP ( Pfeiffer et al, 2001 Vemuri et al, 2006 , 2007 Veit et al, 2007 MacLean, 2008 Molenaar et al, 2009 ). This leads to an observable tradeoff between the ATP yield and the catabolic rate ( Pfeiffer et al, 2001 Vemuri et al, 2006 ). This respiro-fermentation physiology is commonly observed in microorganisms, including Escherichia coli, Bacillus subtilis, Saccharomyces cerevisiae ( Molenaar et al, 2009 ), as well as cancer cells ( Vander Heiden et al, 2009 ). Despite extensive research, the biochemical basis for this phenomenon remains obscure.

One influential theory attributed the utilization of the fermentative pathways to a hypothetical limitation on the respiratory capacity ( Sonnleitner and Kappeli, 1986 Majewski and Domach, 1990 ). This theory suggests that as the respiratory pathway becomes saturated at high substrate influx, the organism may choose to satisfy its ATP demand by fermenting additional substrates, a strategy that offers a fitness advantage at the cost of lowering the ATP yield ( Majewski and Domach, 1990 Varma and Palsson, 1994 Pfeiffer et al, 2001 ). However, overexpressing the genes encoding for the rate-limiting enzymes did not increase the respiratory capacity ( Cupp and McAlister-Henn, 1991 Repetto and Tzagoloff, 1991 ). Furthermore, it is puzzling why the respiratory capacity varies with different substrates. Despite this caveat, metabolic models ( Palsson, 2000 ) such as the flux balance analysis (FBA) ( Varma and Palsson, 1994 Edwards et al, 2001 Feist et al, 2007 ) commonly adopt the ‘respiratory capacity limitation’ theory through the introduction of an empirically measured cap on maximal oxygen uptake rate (OUR) (Figure 1A and B). In addition to respiration, the tricarboxylic acid (TCA) cycle is actively downregulated in E. coli, B. subtilis, and S. cerevisiae during respiro-fermentation ( Vemuri et al, 2006 , 2007 Sonenshein, 2007 ) this implies that the OURs of these organisms at higher catabolic rates are perhaps regulated to be lower than their respective maximal OURs, possibly reflecting an unexplained evolutionary advantage for lowered respiration ( Molenaar et al, 2009 ).

Challenging the conventional assumption that aerobic respiration is always preferred over fermentation ( Majewski and Domach, 1990 Varma and Palsson, 1994 ), a recent theory ( Schuster et al, 2008 ) proposed that while the cellular metabolism maximizes the ATP yield in nutrient-poor environments, it maximizes the catabolic rate and the rate of energy dissipation in nutrient-rich environments. The biochemical basis for this switch in metabolic objective is the prohibitively expensive synthesis costs of respiratory enzymes, particularly during high catabolic rate ( Pfeiffer and Bonhoeffer, 2004 Molenaar et al, 2009 ). This line of reasoning leads to the conclusion that pure fermentation be accompanied with high growth rate. Yet, rapidly growing facultative aerobes also respire. Furthermore, if the catabolic rate is indeed maximized during unlimited growth, it is unclear why the maximum substrate uptake is slower under aerobic condition than anaerobic conditions ( Portnoy et al, 2008 ). Another theory proposed that the tradeoff between ATP yield and catabolic rate is dependent on the fraction of intracellular volume occupied by respiratory enzymes and glycolytic enzymes, respectively ( Vazquez et al, 2008 ). While the FBA with ‘molecular crowding constraint’ (FBAwMC) ( Beg et al, 2007 Vazquez et al, 2008 ) can predict acetate production to a certain extent, it could not predict the experimentally observed changes in growth rate and yield (Supplementary information). Furthermore, FBAwMC cannot predict the production of acetate if the electron transport chain enzymes—membrane-bound enzymes that consumes little intracellular volume—are removed from its formulation (Supplementary information). Despite these shortcomings, these theories highlight that the rate of metabolic processes must be accounted for in addition to the metabolic stoichiometry in understanding respiro-fermentative metabolism.

Finally, these aforementioned theories assume that the observed tradeoff between the ATP yield and the catabolic rate is solely caused by the utilization of fermentative pathways. However, experimental evidence (Supplementary information) suggests that the efficiency of the respiratory pathway itself may be compromised due to the utilization of less-efficient dehydrogenases and cytochromes. Given that there exists a thermodynamic tradeoff between the turnover rate and the energetic efficiency of an enzyme ( Meyer and Jones, 1973 Waddell et al, 1997 Pfeiffer and Bonhoeffer, 2002 ), less-efficient enzymes may be preferred for their increased turnover rate. Based on these observations, we propose a simple, alternative explanation of the respiro-fermentation phenomenon by considering membrane occupancy, which provides a mechanistic explanation to all the observed physiological changes during the transition from respiratory to respiro-fermentative metabolism.


Slop food waste is a substantial portion of total waste from civilian and military culinary operations [1,2]. The high water content of slop food waste makes it a poor substrate for combustion based waste to energy conversions. Therefore, to achieve maximal energy efficiency and on-site waste mitigation, alternate technologies need to be explored. One promising possibility is fermentation of slop food waste, which is rich in carbohydrates and other nutrients, to fuels such as butanol or ethanol. The anaerobic bacterium Clostridium acetobutylicum is an excellent candidate to perform this task due to its abilities to use a wide variety of carbohydrates and to produce fuels in the form of hydrogen gas, ethanol, and butanol [3-5]. C. acetobutylicum has been used at the industrial scale for production of the solvents acetone, butanol, and ethanol from plant based starches [4,6,7]. To optimize fermentation of slop food wastes, which are heterogeneous, it is necessary to establish a thorough understanding of how carbohydrates found in food are metabolized, and their contribution to metabolic output.

Two major factors controlling metabolic output of fermentations are the redox state of the feedstock and the pathway used for metabolism [8-10]. Slop food waste contains a vast array of carbohydrates and their derivatives, some of which are more oxidized than the hexoses commonly used in the study of C. acetobutylicum’s metabolism [11-13]. Two such carbohydrate derivatives are gluconate and galacturonate [11,12]. Gluconate is more oxidized than glucose by 2 electrons, and is found in fruit, honey, rice, meat, and other foods [11]. Galacturonate is more oxidized than glucose by 4 electrons, and is the primary constituent of pectin [12]. While all plant cell walls contain pectin, many foods such as fruit are enriched for this complex carbohydrate [12]. Since both of these carbohydrate derivatives are enriched in food, their contribution to metabolic output is especially important for food waste fermentation.

Numerous clostridial species are capable of fermenting galacturonate and gluconate, but little is known about the pathways and the associated genes contributing to this process in solventogenic clostridia [14-18]. An early study comparing C. acetobutylicum fermentations on substrates with varying degrees of oxidation showed fermentation of gluconate resulted in higher acetate:butyrate ratios when compared to glucose fermentations [10]. Additionally, acetone was the predominant solvent produced during solventogenesis for gluconate fermentations, while butanol was the main solvent produced in glucose fermentations [10]. Other studies showed C. aceticum, C. formicoaceticum, C. butyricum, C. pasteurianum, C. roseum, and C. butylicum fermented gluconate via the Entner-Doudoroff (ED) pathway, but no evidence has verified that C. acetobutylicum uses the ED for gluconate metabolism [14,18]. To the best of our knowledge the only Clostridium species where a complete pathway for galacturonate utilization has been experimentally confirmed is C. thermosaccharolyticum, which uses the Ashwell pathway (also called the Modified Entner-Doudoroff pathway, 2-keto-3-deoxy-6-phospho-D-gluconate (KDPG) pathway, or isomerase pathway) to metabolize galacturonate in a similar manner to Escherichia coli and Erwinia chrysanthemi [19-22]. While it is common knowledge that fermentation of increasingly oxidized substrates results in increasingly oxidized products, to our knowledge there is only one report describing the metabolic output of a solventogenic bacterium during growth on galacturonate, and it revealed C. butryricum produced predominately acetate from polygalacturonate [23].

Bioinformatically driven metabolic network reconstructions for C. acetobutylicum by the genome annotation, BioCyc, and KEGG identified complete pathways for galacturonate metabolism via the Ashwell pathway [19,21]. However, these reconstructions either misidentified or did not identify genes responsible for gluconate metabolism [24-26]. This study provides insight into gluconate and galacturonate metabolism by using manual curation to reconstruct C. acetobutylicum’s gluconate utilization pathway, yields the first experimental evidence for gluconate utilization via the ED pathway, and examines metabolic output of fermentations of oxidized carbohydrate derivatives. The information provided by this study is useful for designing strategies to increase production of desired products from heterogeneous feedstocks such as food waste.

Four-stage dissolved oxygen strategy based on multi-scale analysis for improving spinosad yield by Saccharopolyspora spinosa ATCC49460

Dissolved oxygen (DO) is an important influencing factor in the process of aerobic microbial fermentation. Spinosad is an aerobic microbial-derived secondary metabolite. In our study, spinosad was used as an example to establish a DO strategy by multi-scale analysis, which included a reactor, cell and gene scales. We changed DO conditions that are related to the characteristics of cell metabolism (glucose consumption rate, biomass accumulation and spinosad production). Consequently, cell growth was promoted by maintaining DO at 40% in the first 24 h and subsequently increasing DO to 50% in 24 h to 96 h. In an in-depth analysis of the key enzyme genes (gtt, spn A, spn K and spn O), expression of spinosad and specific Adenosine Triphosphate (ATP), the spinosad yield was increased by regulating DO to 30% within 96 h to 192 h and then changing it to 25% in 192 h to 240 h. Under the four-phase DO strategy, spinosad yield increased by 652.1%, 326.1%, 546.8%, and 781.4% compared with the yield obtained under constant DO control at 50%, 40%, 30%, and 20% respectively. The proposed method provides a novel way to develop a precise DO strategy for fermentation.

© 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.


Spinosad production at different DO…

Spinosad production at different DO level of (■) 20%, (○) 30%, (△) 40%…

Relative expression ratios (experimental group…

Relative expression ratios (experimental group (40%–50%–25% DO ) /control group (40%–50%–30% DO )…

The comparison of SATP among…

The comparison of SATP among 20%, 25%, 30% and 35% DO strategy after…

Changes over time in spinosad…

Changes over time in spinosad fermentation with four-stage DO strategy in a 10-l…

In tube 1, CO2 will not evolve because yeast is not present in the solution.

In tube 2, CO2 will not evolve because glucose is not present in the solution.

In tube 3, small amount of CO2 will evolve because of the quantity (little) of yeast present in the solution.

In tube 4, CO2 will evolve because yeast is present in the solution.

In tube 5, CO2 will evolve because yeast is present in the solution containing sucrose.

In tube 6, CO2 will evolve because yeast is present in the solution containing lactose.

Beneficial Mutations from Evolution Experiments Increase Rates of Growth and Fermentation

A major goal of evolutionary biology is to understand how beneficial mutations translate into increased fitness. Here, we study beneficial mutations that arise in experimental populations of yeast evolved in glucose-rich media. We find that fitness increases are caused by enhanced maximum growth rate (R) that come at the cost of reduced yield (K). We show that for some of these mutants, high R coincides with higher rates of ethanol secretion, suggesting that higher growth rates are due to an increased preference to utilize glucose through the fermentation pathway, instead of respiration. We examine the performance of mutants across gradients of glucose and nitrogen concentrations and show that the preference for fermentation over respiration is influenced by the availability of glucose and nitrogen. Overall, our data show that selection for high growth rates can lead to an enhanced Crabtree phenotype by the way of beneficial mutations that permit aerobic fermentation at a greater range of glucose concentrations.

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The hypothesis which states that the simpler the nature of substrate, the faster the rate of cellular respiration of yeast was tested using the smith fermentation tube method. The experiment used six smith fermentation tubes, distilled water and sugar substrates. It composed of six set-ups which used 15ml of 10% yeast suspension, 15 ml distilled water and 15 ml of their assigned sugar substrate namely: starch, lactose, sucrose glucose and fructose respectively. Set-up six was the controlled set-up and did not contain any sugar substrate. The opening of the tube was covered with a cotton ball to prevent oxygen from entering. The set-ups were then observed every five minutes for thirty minutes. The volume and rate of carbon dioxide (CO2) evolved was calculated and recorded. Results showed that set-up 2 which contained the sucrose substrate yielded the highest rate of cellular respiration in yeast (0.46 ml/min.) followed by glucose (0.34 ml/min.), fructose (0.17 ml/min.) and starch (0 ml/min), lactose (0 ml/min.) and distilled water (0 ml/min.) respectively. The hypothesis was rejected but due to the sources of errors conducted by the researchers and the facts presented by the anaerobic respiration equation and other sources, it was accepted and concluded that the simpler the nature of substrate, the faster the rate of cellular respiration of yeast.

Living cells need transfusion of energy from outside sources to perform many tasks. A process called cellular respiration is done by living organisms to acquire this energy in the form of adenosine triphosphate or ATP. It is the process of breaking down nutrient molecules to from energy produced by photo synthesizers (Mader, 2010). It can also be defines as the transfer of energy from organic molecules into food and then converted to ATP (

Cellular respiration can be classified as aerobic respiration in which oxygen is required as a reactant along with the organic fuel to produce energy and anaerobic respiration in which oxygen is not required to form ATP. Reece (2011) stated that aerobic respiration is similar to the principle of combustion of gasoline in an automobile engine in where oxygen is mixed with fuel. In this process, food serves as fuel for respiration and releases carbon dioxide (CO2)and water (H2O). This process can be summarized as :

Organic Compounds + Oxygen ---------> carbon dioxide + water + energy
The input-output equation for each reaction utilizing the use of glucose as a substrate may be written as:
C6H12O6 + 6H20 + 6O2 ------------> 6CO2 + 12H2O + energy (456,000 cal/mol) enzymes

C6H12O6 ----------------------> 2CO2 + 2C2H5OH + energy ( 24, 000 cal/mol) enzymes

C6H12O6 ----------------------> 2C3H6O3 + energy ( 36, 000 cal/mol) enzymes

The breakdown of glucose in aerobic respiration is complete and the energy released is greater than that of anaerobic respiration as seen in the equations above (Duka et al., 2009).
Anaerobic respiration can further be broken down into two types namely facultative and obligate anaerobes. Another term that is closely related to anaerobic respiration is fermentation, a process that produces small amounts of ATP molecules in the absence of oxygen (Mader, 2010). Fermentation is much the same like anaerobic respiration but without the net removal of electrons. In fermentation, the most common agent is yeast. Yeast uses substrates such as glucose to facilitate anaerobic respiration as seen from the equation above.

These glucose substrates vary in their complex structures. Sugars also called saccharides come in three forms: monosaccharides, disaccharides and polysaccharides. Monosaccharides have the chemical formula C6H12O6 and are known to be the most simple sugars while disaccharides have the chemical formula of C12H22O12 and are composed of two monosaccharides joined together by glycocydic bonds (Reece,2011). However, many different configurations exist for each of the two kinds. These different configuration of atoms are called isomers. Isomers of sugars are important to life since organisms have evolved various enzymes to access the energy in each form. Some organisms are therefore better at getting at some forms of sugar than other forms because of the enzymes that they can use.

Examples of monosaccharides are glucose, galactose and fructose while sucrose, lactose and maltose are examples of disaccharides. Polysaccharides such as starch and glycogen serves as storage form of energy in plants and animals respectively.

If so, a hypothesis was derived which states that "the simpler the nature of substrate, the faster the rate of cellular respiration of yeast." This is due to the reason that monosaccharides are easily taken up during fermentation rather than disaccharides and polysaccharides.

This study aimed to determine if the nature of substrates will have an effect on the rate of cellular respiration of yeast by anaerobic respiration under fermentation. Specifically it aimed to:
1 To explain the effect of different nature of substrates on the rate of cellular respiration of yeast 2 To determine the substrate that would yield the highest rate of cellular respiration.
This study was conducted at the Institute of Biology and Sciences (IBS), University of the Philippines Los Baños Campus, Laguna last September 16, 2013.

To measure the rate of fermentation of yeast with different substrates, the smith fermentation tube method was used. This method involved the construction of six set-ups utilizing smith fermentation tubes, cotton plugs, 10 % yeast suspension, distilled water and five different sugars that differ in complexity, namely : starch, lactose, glucose, sucrose and fructose.

In each set-up, 15 ml of their assigned sugar was poured inside the smith fermentation tube, all with a concentration of 10% to be use as substrates for the experiment. 15 ml of distilled water followed and lastly 15 ml of 10% yeast suspension. In Set-up 1, a polysaccharide with a chemical formula of (C6H10O5)n was used. This complex sugar is generally known as starch. In set-up 2, lactose (C12H22O11), a disaccharide made from glucose and galactose was used. Set-up 3 utilized another disaccharide in the presence of sucrose (C12H22O11). This sugar is made from the combination of glucose and fructose. The sugar used in set-up 4 is glucose, a monosaccharide with a chemical formula of C6H12O6. Fructose (C6H12O6), another common monosaccharide was used in set-up 5. Lastly, as the controlled set-up, set-up 6 did not contain any sugar substrate and used distilled water instead.

The set-ups were then shaken to blend the mixture together. The opening of the tube was covered with the palm of one hand and was tilted horizontally so that no bubbles were trapped at the closed end of the tube. After it was ensured that no bubbles were formed, a cotton plug was placed at the opening of the tube to prevent oxygen from entering. The set-ups were then set-aside, secured with rubber bands in a upright position. This was done as to avoid having contact with the tube as the body emits energy in the form of heat that may also be a factor in the rate of fermentation. For an interval of five minutes for thirty minutes, the evolution of carbon dioxide (CO2), the height the gas occupied was measured, recorded and tabulated in Table 1. A graph showing the results in Table 1 was made as Figure 1.1 After collecting the data, the final height of the bubbles of each set-up after thirty minutes was used to compute for the volume of carbon dioxide (CO2) using the following equation:

Volume of carbon dioxide (CO2) = V= pi r^2h
r = 4.5mm
h = height of bubbles after thirty minutes.

To calculate for the rate CO2 evolution in each set-up, the following formula was derived:
Rate of carbon dioxide (CO2) production = Volume of CO2
The calculated results on both computations can be seen in Table 2 and plotted in Figure 2.1 and 2.2 respectively.

Table 1 shows the volume occupied by CO2 evolved every five minutes for a duration of thirty minutes. In set-up 1, the mixture containing starch, no evolution of gas was seen since the final height of CO2 gas evolved after thirty minutes was zero. This was also true for set-up 2 containing the mixture with lactose sugar. Set-ups 3 , 4 and 5, containing sugars of sucrose, glucose and galactose respectively showed an increase in the volume of CO2 gas evolved every 5 minutes for thirty minutes. In set-up 6, no evolution of CO2 gas was present during the span of time allotted for the experiment since no breakdown of glucose molecules occurred due to the absence of a substrate.

The values in Table 1 was plotted using a line graph as seen in figure 1.1. The graph shows that sucrose had the highest rate for yeast metabolism (13.67 ml/min) for a span of thirty minutes. After sucrose is glucose (10.05 ml) and coming third is fructose (5.04 ml). Starch and lactose did not show any sign of having an effect on yeast metabolism within thirty minutes.

The values of Table 2 was derived using the formula in V=pir^2h. Table 2 shows the volume and rate of CO2 produced after 30 minutes. In Figure 2.1 and 2.2, it can be observed that set-up 3 containing sucrose had the highest volume and rate of CO2 evolved with the value of 13.67 ml and 0.46 ml/min respectively. This was followed by set-up 4 containing glucose with values of 10.05 ml and 0.34 ml/min respectively. Set-up 5 containing fructose came in third with values of 5.04 ml and 0.17 ml/min respectively. Set-ups 1,2 and 6 containing starch, lactose an distilled water did not show any signs of CO2 evolution thus with values of zero.

In Table 1.1, lactose and starch did not release any carbon dioxide (CO2) within thirty minutes because they are complex sugars. Yeast lacks enzymes to accesses these sugars and break their bonds. In set-up 6, yeast cannot produce CO2 since no substrate is present in the mixture which is needed for fermentation.

The problem with the results in Table 1 and Figure 1.1 is that, glucose or fructose, a monosaccharide should perform the highest rate of yeast metabolism compared to sucrose, a disaccharide. This is due to the fact that they are simple sugar that are easily available in nature and can be broken down effortlessly rather than disaccharides and polysaccharides.

Based on the results of the experiment, the hypothesis, which states that the simpler the nature of substrate , the higher the rate of cellular respiration in yeast, should be rejected but, based on the anaerobic respiration equation and from, simple sugars are used in the fermentation of yeast or it is used as starting compound for breakdown to produce CO2 and energy. Disaccharides are also great sources of food for yeast but before they are utilized, they are first transformed into simple sugars and thus begins fermentation.

The only possible explanation for the outcome of the experiment is due to the errors conducted by the researchers . Some sources of errors may be the inaccurate amount of yeast suspension or substrates used, the exact time of intervals for recording measurements was not observed, negligence of the researcher while conducting the experiment, occurrence of spills, cotton balls not properly placed and oxygen entered the tube, not all bubbles were removed prior to observation, and constant touching of the set-up that may have resulted to contact with heat that may serve as a variable for the rate of respiration in yeast.

To prove the hypothesis that the simpler the nature of substrate, the higher the rate of cellular respiration of yeast, an experiment using the Smith Fermentation Tube Method was performed. This involved the use of six smith fermentation tubes, 10% yeast solution, distilled water (H2O) and five different sugar substrates of 10% concentration namely: starch, lactose, sucrose, glucose and fructose. Each set-up comprised of 15ml distilled H2O, 15 ml of 10% yeast solution and 15 ml of 10% glucose solution that is assigned to each set-up except in set-up 6, the controlled set-up, where the substrate used is distilled water. A cotton plug was placed at the opening of the tube after ensuring that no bubbles were formed after mixing the substances together. The set-ups were then set-aside for observation. The level of carbon dioxide gas evolved was recorded every five minutes for a duration of thirty minutes. The values were recorded in Table 1 and plotted in Figure 1.1. After recording all the values, the volume and rate of carbon dioxide (CO2) after thirty minutes was computed and recorded in Table 2, and was graphed in Figure 2.1 and 2.2.

Results showed that set-up 2 which contained the sucrose substrate yielded the highest rate of cellular respiration in yeast (0.46 ml/min.) This was followed by glucose (0.34 ml/min.) , fructose (0.17 ml/min.) and starch (0 ml/min), lactose (0 ml/min.) and distilled water (0 ml/min.) respectively.


Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, 61801, Illinois, USA

Na Wei, Josh Quarterman, Soo Rin Kim & Yong-Su Jin

Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, 61801, Illinois, USA

Na Wei, Josh Quarterman, Soo Rin Kim & Yong-Su Jin

Department of Molecular and Cell Biology, University of California at Berkeley, Berkeley, 94720, California, USA

Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, 94720, California, USA