Anaerobic Metabolism in Yeast Cellular Respiration: Freeing Stored ...

LABORATORY EXPLORATIONAnaerobic Metabolism in YeastYou have now been introduced to both statistical methods (null and alternativehypotheses) and the strong inference method. Each of these must be appliedappropriately when an investigator is answering questions about a biological system.In general, the strong inference method is best applied only when the investigatorhas a good understanding of the biological system under investigation, and cangenerate meaningful, educated hypotheses. It is commonly used to solve problems andanswer questions at the molecular and cellular level, as such systems tend to behave ina more predictable fashion than do larger, more inclusive systems in ecology orevolutionary biology. But even when this method is used in molecular and cellularbiology, the researcher must have a very strong understanding of the system in order topose viable, meaningful hypotheses.Statistical methods allow the investigator to make broader statements about asystem that is not well known, or is complex, with many potential confounding factors.These also can be used at the outset of a study, to establish general trends that canthen be used as a foundation for examination via strong inference.In today’s lab, you will investigate aspects of anaerobic respiration in a living modelorganism, Baker’s yeast (Saccharomyces cereviseae). If you feel you have thebackground and equipment available to use the strong inference method to posehypotheses, then this is what you should do. Alternatively, if you wish to run a pilotstudy to determine how a system works, then you should do that. In your presentation,you will then offer potential ways that what you have learned can be expanded, andmore in-depth hypotheses posed using strong inference.Cellular Respiration: Freeing Stored EnergyCells can obtain the energy stored in sugars by breaking the sugar molecules apartin a series of enzyme-mediated reactions. Energy is extracted most efficiently in thepresence of oxygen via the process known as aerobic respiration. Under conditionswhere oxygen is scarce or absent, some cells are still able to split glucose to obtainenergy via the process of anaerobic respiration, also known as fermentation--but farless energy per glucose is extracted, since glucose cannot be fully broken down withoutoxygen.In today’s lab, you will work in teams of four and design an experiment in which youmanipulate some factor affecting the rate of anaerobic metabolism in live yeast.ObjectivesAfter doing this lab, you should be able to:• Design and perform an experiment to test the relative ability of yeast to fermentvarious potential nutrients.• Graph and analyze rate curves on software such as Excel, and then graph andcompare the resulting fermentation rates.• Calculate mean fermentation rates for analysis via statistical tests.• Devise further experiments designed to distinguish between two competinghypotheses regarding yeast’s ability (or inability) to ferment given sugars.Cellular respiration-1

• Synthesize and explain your results on both the proximate (molecular) and ultimate(evolutionary) levels in your presentation, to be given in the next lab session.I. Experimental Inquiry: FermentationCertain organisms can produce ATP by utilizing metabolic pathways that do notrequire the participation of molecular oxygen. Usually, these are referred to aspathways of fermentation or anaerobic glycolysis. These pathways involve thesequential conversion of a carbohydrate into partially oxidized end product(s). Theenergy released during these reactions, and stored in the phosphate bonds of ATP.One species of free-living (i.e., non-parasitic) unicellular fungus, commonly knownas Brewer’s yeast (Saccharomyces cereviseae), can "ferment" various disaccharidesand monosaccharides. For example, it can break down glucose:about 11 enzymatic reactionsC 6 H 12 O 6 -----------------------------------> 2CH 3 CH 2 OH + 2CO 2 + energyUsing appropriate equipment, we can estimate the rate of this pathway for any givensugar by determining the yield of CO 2 over time. This opens a pathway to askingquestions about the fermentation pathway (using yeast as a model organism) andsolving the problems that arise from those questions. One might ask if yeast canferment all sugars equally well. This is a question one can answer with a statisticalhypothesis. But the next question is not so simple. If there is a significant difference inyeast’s ability to ferment different sugars, then why is there that difference? The secondbranch of the “hypothesis tree” brings us to the cellular and molecular level of thisproblem, and it is this level that can be best addressed via strong inference.If you know something about yeast and its enzymes and enzymatic pathways, youcan hypothesize about why yeast might not be able to ferment a particular sugar. Thiscan lead you to target specific aspects of these enzymes and pathways, devisingexperiments that will allow you to determine whether a hypothesis you have formulatedabout this process is correct or not.Similarly, if you know something about the sugars themselves (e.g., whether theyare mono- or disaccharides, what type of bonds hold them together, what is theirspecific molecular structure), you might ask what, specifically, it is about a particularsugar that make it more or less suitable as an energy source for yeast. At this point,you are not searching for ultimate explanations with evolutionary significance (e.g.,yeast can’t ferment sugar X because it is not present in yeast’s natural environment).Instead, you are searching for the proximate causes of yeast’s enzymatic “behavior”with respect to different sugars. Once you have established the reality, you canhypothesize about the origin and significance of that reality.A. Experimental procedureThe materials available to your team include:• 0.5M solutions of different types of sugars• aqueous suspension of live yeast• Four fermentation tubes and holding rack• Syringes and other measuring equipment• Thermometers (to record standard conditions of your reactions)Cellular respiration-2

You will use Durham fermentation tubes (Figure 6-1) to measure the rate of CO 2generation by yeast. Because our tubes are hand-blown and unmarked, you mustcalibrate them before you begin your experiment. With a syringe, introduce water intothe tube, 0.5 cc at a time, and tip the tube so that the water enters the sealed end of thetube. Each time you add water, mark the meniscus with a wax pencil. Make marks asfar up the neck of the tube as possible, as shown in Figure 6-1. Your TA willdemonstrate how this is done. Alternatively, you can add exactly 10ml of water to thetube, measure how many centimeters that occupies. You can then calculate theml/distance (either in centimeters or millimeters, depending on how accurately you thinkyou can measure your column). At the end of your experimental run, measure thelength of the gas column, and convert it into the volume inside the tube.Available at the back table are 0.5M solutions of several different sugars (see Figure6-2) and an aqueous suspension of live yeast. (HINT: For this size of tube, 2.0 ml ofyeast suspension mixed with 10 ml of sugar suspension provides a fine yeast feast thatwill last for about two hours. You might not need to use the entire two hours if yourteam chooses to replicate the experiments, sequentially.)Figure 6-1. A Durham fermentation tube. To calibrate the tube,introduce 0.5 cc (= ml) of water into the bowl and tilt so that the liquid flowsinto the closed neck. Mark the bottom of the meniscus with a wax pencil.Repeat this procedure until the entire neck is calibrated with 0.5 cc marks,as shown in the illustration.The water-suspended yeast have been incubated aerobically so that they will use upall their carbohydrate reserves. Why do you suppose this was necessary?Now that we mention it, what is the difference between a solution and a suspension?Write it here:Solution:Suspension:Cellular respiration-3

α-D-Fructosesucrose = glucose–α(1→2)–fructosemaltose = glucose–α(1→4)–glucosecellobiose = glucose–β(1→4)–glucoselactose = galactose–β(1→4)–glucoseMolecular structures modified from:Timson and Reese 2003 (glucose and galactose)Diwan 2008 (fructose)Dew 2007 (disaccharides)Figure 6-2. Molecular structures of selected monosaccharides and disaccharidesthat may be nutrients for yeast.Cellular respiration-4

Now the creative process begins. Begin with proximate questions. You might wishto consider the molecular structures and bonds of the sugars themselves and formulatea hypothesis about this. Or perhaps the channels in the plasma membrane of the yeastare the limiting factors. Do as much background discussion as possible to come up witha reasonable hypothesis.In terms of the bigger, evolutionary picture (which you should consider once youhave a proximate answer to your question), consider where yeast are found in nature.HINT: what’s that “bloom” on the grape (Figure 6-3, and see Rossini et al. 1982)? Howdo you suppose prehistoric people discovered fermented fruit (a.k.a. wine) andfermented grain porridge (a.k.a. beer)? See Legras et al. (2007) for more about thehistory of symbiosis between yeast and humans.Figure 6-3. Ripening Syrah grapes showing the characteristic powdery whitecoating, or ‘bloom’, on their surface that is composed of yeast (Hass 2008).Now consider whether the various organic compounds available in the lab(monosaccharides and disaccharides) could be found in the microhabitat of yeast.Even if a potential nutrient molecule could be utilized, consider whether it is able enterthe cell, or if it would need to be modified to enter the glycolysis pathway.Compare the molecular structures of the compounds—size, shape, bonding, etc.Ask questions, share ideas, and incorporate these larger ideas into the introduction ofyour presentation to help you explain why these questions are interesting and relevant.As before, have your TA check your design and give helpful suggestions. Your TAmay allow the various teams to discuss their experiments, and then give a briefexplanation to the entire class in order to generate feedback from your colleagues.Many brains are often better than a few, once a framework has been established.What is your question/problem?What is your prediction?Cellular respiration-5

If you plan to use statistical methods (e.g., comparing rates of fermentation of twodifferent sugars), then what are your null and alternative hypotheses for the particularexperimental protocol you will be using?H o : _______________________________________________________________________________________________________________________________________H a : ________________________________________________________________________________________________________________________________________rationale for H a : _______________________________________________________________________________________________________________________________Remember that to compare mean rates, you must run more than one experiment withthe same variable. You may do this by running four tubes, each with a different sugar,or by running the same experiment twice or more, and measuring gas generation for ashorter time in each experiments. We will leave it to individual teams to decide which isthe more logical method.1. List the materials your group will use2. Briefly describe your experimental set-up and procedure. (Remember: you need notgive a detailed explanation of equipment here, unless it is unique to your experimentand really requires an explanation for the educated reader to understand what you willbe doing. Simply refer to the lab manual as a literature cited for equipment specifics.)3. Do you think it is sufficient to run only one experimental run with each variable? Orshould you run multiple trials? Explain your answer:4. How many times will you replicate your experiment for each variable?Cellular respiration-6

If you plan to run multiple trials at each value of your variable—a wise choice—thenyou will need to calculate the mean rate of reaction of the runs. (For example, if youran your experiment three times with a particular sugar, then you must calculate themean reaction rate for each sugar from your three runs with that sugar. If you did threeruns with glucose, then average the rate of those three runs and report that mean asyour rate of reaction of glucose). You should already know how to do this, but if youneed a refresher, refer to the lab on enzyme reaction rate you did earlier in thesemester.If you wish, you may the table below to record your experimental set up quantities,or create your own, if the one below is not appropriate for your team’s needs.Tabletestingtube#. Quantities of yeast suspension and 0.5 M sugar solutions used inml (cc)yeast suspensionml (cc)sugar solutiontype of sugarvariable(if applicable)B. Parameters and Data AnalysisWhat type of data are you collecting? Is it attribute, discrete numerical, or continuousnumerical data, as described in Appendix 2.1. What parameter will you measure?2. How will you analyze your data?C. Predictions and InterpretationsIn the spaces below, list all possible outcomes of your experimental trials. (Asbefore, we have given you more spaces than you might need for this.)Each outcome should be accompanied by an explanation of how it supports or refuteseach hypothesis and its companion predictions.Remember that the result is not the same as the interpretation. The outcome is thesummary of the results themselves, whereas the interpretation is the logical, reasonedexplanation for the observed results. The explanation of your outcome can serve as thebasis for the next level of posing hypotheses, so be prepared to go to that next level.Cellular respiration-7

Outcome 1:Explanation:Outcome 2:Explanation:Outcome 3:Explanation:Outcome 4:Explanation:D. Data CollectionYou may use the table provided below to record your experimental results, or createyour own. Provide an appropriate legend.Once you have set up your experimental vessels, it may take about 30 minutesbefore you observe any generation of CO 2 . Take this time to open your laptop (or takeadvantage of the computer lab next door) and do some research on yeast, the sugarsyou have chosen, etc. on a deeper level: cellular and molecular. This will help youinterpret your results, and to generate the next level of hypotheses that will help youexplain your results with further experiments. The online resources available from theRichter Library and Google Scholar (www.googlescholar.com) are both good sources ofscholarly, peer-reviewed articles that will give you enough background to further exploreyour fermentation system via strong inference.Keep an eye on your fermentation vessels, however. Once the process begins, itcan proceed quite rapidly.Cellular respiration-8

Table .time(minutes)zero102030405060708090100110120tube 1(cc CO2)tube 2(cc CO2)tube 3(cc CO2)tube 4(cc CO2)E. Data analysis1. When you have completed the experiment, plot the raw data for each experimentalrun, and calculate reaction rate.2. Calculate the mean reaction rate for each variable.3. Create an appropriate figure, comparing the reaction rates at each of your variables.Be sure to label your axes correctly, and provide an appropriate legend. If you arenot sure how to do so, review Appendix 2.)When discussing your results, consider the following and integrate them into yourpresentation in a logical fashion. You may wish to use some of these ideas as aspringboard to inspire the next level of investigation. (For example, if there was asignificant difference in the rate of fermentation of two different sugars, what might besome possible reasons for this difference? How would you test each of thesehypotheses?)1. To what degree might the the yeast cell membrane permeable to each of thesesugars?2. Even if a sugar passes through the cell membrane, it may not be fermented. Whymight this be? HINT: Consider that glycolysis is mediated by many enzymes. Alsoconsider the evolutionary history of Saccharomyces cereviseae, a fungus which hasevolved to obtain its nutrients from plant sugars. Where is each of the sugars youused found in nature?3. Was CO 2 the only component of the gas produced in your experiment? Whatelse might be there? How might this affect your analysis?4. In using the fermentation tube, did you quantify all the CO 2 being generated?Does this affect your data analysis? Why or why not?Cellular respiration-9

5. Can you state with confidence that the fermentation rates are significantly different?Why or why not? How could you determine whether the rates are significantlydifferent? How might you repeat these experiments so that the results could bemore easily analyzed with a statistical test?II. Your Team PresentationBefore you leave lab today, make sure every team member has a copy of the rawdata and any analysis your team has done together, either on a laptop or flash drive.You should also arrange times and places to meet together during the next week so thatyou can finish analyzing your data and put together a PowerPoint presentation on yourexperiment. DO THIS BEFORE YOU LEAVE LAB so there will be no confusion and nolost souls unable to contact the other team members.Instructions for creating an effective presentation can be found under Lab #4, whichyou have already read. Be sure to follow those instructions carefully, because—asalways--you and your team will be graded not only on your results and interpretation,but also on the effectiveness with which you present your findings to your colleagues.Rendering your data into clear, analyzable form is only the beginning of a scientificpresentation or report. As before, remember that as long as you have performed yourexperiment with care and rigor, there are no "right" or "wrong" results—only valid andinvalid explanations for the observations. The most important part of this lab is toexplain your results logically, even if they are not what you expected. Think about yourresults and discuss them intelligently.This time, you are required to go further than simply explaining the results of today’sexperiments. Perhaps the most important part of a pilot study like the one you did todayis to determine the next step in elucidating how this sytem works, and why.Use the resources available in the library and online to learn more about this speciesof yeast, where it is found, why it might “behave” the way it does on both a cellular andmolecular level. Once you understand this, you will not only be better equipped to posethe next meaningful hypotheses, but also should be able to propose experiments toallow you to choose which of your competing hypotheses is correct. This is how stronginference works: From a position of knowledge, you will know how recognizemeaningful biological problems, how to formulate competing hypotheses to address thisproblem, and how to devise rigorous experiments that will allow you to precisely choosewhich of your competing hypotheses is correct.A Sample Analysis: Going the Next Step via Strong InferenceLet’s say that your results have shown that yeast can ferment Sugar X (amonosaccharide) at a significantly greater rate than Sugar Y (a disaccharide).The next step is to hypothesize why, on a proximal, cellular/molecular level, this mightbe the case. One possible reason might be:“There is a difference in the rate of fermentation between Sugar X and Sugar Y becauseyeast cannot break the glycosidic bond between Sugar Y’s two monomer components.”(Note: You should not stop at just one possible reason/hypothesis for your results. Listall the possible reasons/hypotheses that there might be a difference in fermentation ratebetween these two sugars (or, if you didn’t test the difference between sugars, then theCellular respiration-10

eason for whatever results you obtained). You will probably be able to test only onehypothesis at a time, but creating multiple hypotheses will not only reduce bias in yourexperiments, but also prepare you for the next step, should your first hypothesis beincorrect.)Next, re-state the reason in the form of competing hypotheses. For example:If it is the glycosidic bond alone that prevents yeast from fermenting SugarY as efficiently as it ferments Sugar X, then yeast will ferment Sugar W—adifferent disaccharide has the same type of glycosidic bonds as Sugar Y—at the same rate as Sugar Y.If it is NOT the glycosidic bond alone that prevents yeast from fermentingSugar Y as efficiently as it ferments Sugar X, then yeast will fermentSugar W—a different disaccharide has the same type of glycosidic bondsas Sugar Y—at a different rate than Sugar Y.Notice that with this careful wording, you cannot fail to be able to choose betweenthese competing hypotheses once you have experimental results. Since your predictionis that the glycosidic bond is the limiting factor, you should predict that if you allow yeastto ferment Sugar W, it will be as ineffective at doing so as it is at fermenting Sugar Y.Note that even here you must be cautious. Be sure to account for any otherpossible differences between Sugar Y and Sugar W that could confound your results.In your presentation, you should present as many possible explanations for yourresults as possible, and set up competing hypotheses for each one. Proposepossible experiments you could use to test these hypotheses, even if it is only tosay, “Subjecting the yeast to a reagent that does XXX (e.g., opens a particularmembrane channel) should allow us to determine whether this feature (themembrane channel’s permeability) is part of this complex system.”Proceed with care, rigorous thinking, lots of background learning about your system,and you will succeed.ReferencesDew, S. 2007? Disaccharides. Chemistry Explained. http://www.chemistryexplained.com/Co-Di/Disaccharides.html. Accessed 6/3/2010.Diwan, J. 2008. Carbohydrates - Sugars and Polysaccharides. Biochemistry of Metabolism.http://www.rpi.edu/dept/bcbp/molbiochem/MBWeb/mb1/part2/sugar.htmHaas, J. 2008. Harvest, week of September 15th: Watching and waiting. Blog Tablas Creek,Tablas Creek Vineyard, http://tablascreek.typepad.com/tablas/2008/09/harvest-week--1.htmlLegras, J-L, D. Merdinoglu, J-M. Cornuet, and F. Karst 2007. Bread, beer and wine:Saccharomyces cerevisiae diversity reflects human history. Molecular Ecology 16: 2091-2102.Rossini, G., F. Federici, and A. Martini 1982. Yeast flora of grape berries during ripening. MicrobialEcology 8(1): 83-89.Timson, D. and R. Reese 2003. Sugar recognition by human galactokinase. BMC Biochemistry4:16, http://www.biology-online.org/articles/sugar_recognition_human_galactokinase/figures.htmlCellular respiration-11