|
|
|
Lab 1- Science and Model Organisms Part 1: The Scientific Method There are many different variations on the scientific method, yet all share similarities. Below is one version of this method (website 1). 1.1: What is the "scientific method"? The scientific method is the best way yet discovered for winnowing the truth from lies and delusion. The simple version looks something like this:
This leaves out the co-operation between scientists in building theories, and the fact that it is impossible for every scientist to independently do every experiment to confirm every theory. Because life is short, scientists have to trust other scientists. So a scientist who claims to have done an experiment and obtained certain results will usually be believed, and most people will not bother to repeat the experiment. Experiments do get repeated as part of other experiments. Most scientific papers contain suggestions for other scientists to follow up. Usually the first step in doing this is to repeat the earlier work. So if a theory is the starting point for a significant amount of work then the initial experiments will get replicated a number of times. Many philosophers of science would argue that there is no such thing as the scientific method. 1.2: What is the difference between a fact, a theory and a hypothesis? In popular usage, a theory is just a vague and fuzzy sort of fact. But to a scientist a theory is a conceptual framework that explains existing facts and predicts new ones. For instance, today I saw the Sun rise. This is a fact. This fact is explained by the theory that the Earth is round and spins on its axis while orbiting the sun. This theory also explains other facts, such as the seasons and the phases of the moon, and allows me to make predictions about what will happen tomorrow. This means that in some ways the words fact and theory are interchangeable. The organization of the solar system, which I used as a simple example of a theory, is normally considered to be a fact that is explained by Newton's theory of gravity. And so on. A hypothesis is a tentative theory that has not yet been tested. Typically, a scientist devises a hypothesis and then sees if it "holds water" by testing it against available data. If the hypothesis does hold water, the scientist declares it to be a theory. An important characteristic of a scientific theory or hypothesis is that it be "falsifiable". This means that there must be some experiment or possible discovery that could prove the theory untrue. For example, Einstein's theory of Relativity made predictions about the results of experiments. These experiments could have produced results that contradicted Einstein, so the theory was (and still is) falsifiable. On the other hand the theory that "there is an invisible snorg reading this over your shoulder" is not falsifiable. There is no experiment or possible evidence that could prove that invisible snorgs do not exist. So the Snorg Hypothesis is not scientific. On the other hand, the "Negative Snorg Hypothesis" (that they do not exist) is scientific. You can disprove it by catching one. Similar arguments apply to yetis, UFOs and the Loch Ness Monster. See also question 5.2 on the age of the Universe. 1.3: Can science ever really prove anything? Yes and no. It depends on what you mean by "prove". For instance, there is little doubt that an object thrown into the air will come back down (ignoring spacecraft for the moment). One could make a scientific observation that "Things fall down". I am about to throw a stone into the air. I use my observation of past events to predict that the stone will come back down. Wow - it did! But next time I throw a stone, it might not come down. It might hover, or go shooting off upwards. So not even this simple fact has been really proved. But you would have to be very perverse to claim that the next thrown stone will not come back down. So for ordinary everyday use, we can say that the theory is true. You can think of facts and theories (not just scientific ones, but ordinary everyday ones) as being on a scale of certainty. Up at the top end we have facts like "things fall down". Down at the bottom we have "the Earth is flat". In the middle we have "I will die of heart disease". Some scientific theories are nearer the top than others, but none of them ever actually reach it. Skepticism is usually directed at claims that contradict facts and theories that are very near the top of the scale. If you want to discuss ideas nearer the middle of the scale (that is, things about which there is real debate in the scientific community) then you would be better off asking on the appropriate specialist group. 1.4: If scientific theories keep changing, where is the Truth? In 1666 Isaac Newton proposed his theory of gravitation. This was one of the greatest intellectual feats of all time. The theory explained all the observed facts, and made predictions that were later tested and found to be correct within the accuracy of the instruments being used. As far as anyone could see, Newton's theory was the Truth. During the nineteenth century, more accurate instruments were used to test Newton's theory, and found some slight discrepancies (for instance, the orbit of Mercury wasn't quite right). Albert Einstein proposed his theories of Relativity, which explained the newly observed facts and made more predictions. Those predictions have now been tested and found to be correct within the accuracy of the instruments being used. As far as anyone can see, Einstein's theory is the Truth. So how can the Truth change? Well the answer is that it hasn't. The Universe is still the same as it ever was, and Newton's theory is as true as it ever was. If you take a course in physics today, you will be taught Newton's Laws. They can be used to make predictions, and those predictions are still correct. Only if you are dealing with things that move close to the speed of light do you need to use Einstein's theories. If you are working at ordinary speeds outside of very strong gravitational fields and use Einstein, you will get (almost) exactly the same answer as you would with Newton. It just takes longer because using Einstein involves rather more math. One other note about truth: science does not make moral judgments. Anyone who tries to draw moral lessons from the laws of nature is on very dangerous ground. Evolution in particular seems to suffer from this. At one time or another it seems to have been used to justify Nazism, Communism, and every other -ism in between. These justifications are all completely bogus. Similarly, anyone who says "evolution theory is evil because it is used to support Communism" (or any other -ism) has also strayed from the path of Logic.
Ockham's Razor ("Occam" is a Latinized variant) is the principle proposed by William of Ockham in the fifteenth century that "Pluralitas non est ponenda sine neccesitate", which translates as "entities should not be multiplied unnecessarily". Various other rephrasings have been incorrectly attributed to him. In more modern terms, if you have two theories which both explain the observed facts then you should use the simplest until more evidence comes along. See W.M. Thorburn, "The Myth of Occam's Razor," Mind 27:345-353 (1918) for a detailed study of what Ockham actually wrote and what others wrote after him. The reason behind the razor is that for any given set of facts there are an infinite number of theories that could explain them. For instance, if you have a graph with four points in a line then the simplest theory that explains them is a linear relationship, but you can draw an infinite number of different curves that all pass through the four points. There is no evidence that the straight line is the right one, but it is the simplest possible solution. So you might as well use it until someone comes along with a point off the straight line. 1.7: Galileo was persecuted, just like researchers today. People putting forward extraordinary claims often refer to Galileo as an example of a great genius being persecuted by the establishment for heretical theories. They claim that the scientific establishment is afraid of being proved wrong, and hence is trying to suppress the truth. This is a classic conspiracy theory. The Conspirators are all those scientists who have bothered to point out flaws in the claims put forward by the researchers. The usual rejoinder to someone who says "They laughed at Columbus, they laughed at Galileo" is to say "But they also laughed at Bozo the Clown". (From Carl Sagan, Broca's Brain, Coronet 1980, p79). Incidentally, stories about the persecution of Galileo Galilei and the ridicule Christopher Columbus had to endure should be taken with a grain of salt. During the early days of Galileo's theory church officials were interested and sometimes supportive, even though they had yet to find a way to incorporate it into theology. His main adversaries were established scientists - since he was unable to provide HARD proofs they didn't accept his model. Galileo became more agitated, declared them ignorant fools and publicly stated that his model was the correct one, thus coming in conflict with the church. 1.8: What is the "Experimenter effect"? It is unconscious bias introduced into an experiment by the experimenter. It can occur in one of two ways:
A classic example of the first kind of bias was the "N-ray", discovered early this century. Detecting them required the investigator to look for very faint flashes of light on a scintillator. Many scientists reported detecting these rays. They were fooling themselves. For more details, see "The Mutations of Science" in Science Since Babylon by Derek Price (Yale Univ. Press). A classic example of the second kind of bias was the detailed investigations into the relationship between race and brain capacity in the last century. Skull capacity was measured by filling the empty skull with lead shot or mustard seed, and then measuring the volume of beans. A significant difference in the results could be obtained by ensuring that the filling in some skulls was better settled than others. For more details on this story, read Stephen Jay Gould's The 1.9.1: Did Mendel fudge his results? Gregor Mendel was a 19th Century monk who discovered the laws of inheritance (dominant and recessive genes etc.). More recent analysis of his results suggests that they are "too good to be true". Mendelian inheritance involves the random selection of possible traits from parents, with particular probabilities of particular traits. It seems from Mendel's raw data that chance played a smaller part in his experiments than it should. This does not imply fraud on the part of Mendel. First, the experiments were not "blind" (see the questions about double blind experiments and the experimenter effect). Deciding whether a particular pea is wrinkled or not needs judgment, and this could bias Mendel's results towards the expected. This is an example of the "experimenter effect". Second, Mendel's Laws are only approximations. In fact it does turn out that in some cases inheritance is less random than his Laws state. Third, Mendel might have neglected to publish the results of `failed' experiments. It is interesting to note that all 7 of the characteristics measured in his published work are controlled by single genes. He did not report any experiments with more complicated characteristics. Mendel later started experiments with a more complex plant, hawkweed, could not interpret the results, got discouraged and abandoned plant science. 1.10: Are scientists wearing blinkers? One of the commonest allegations against mainstream science is that its practitioners only see what they expect to see. Scientists often refuse to test fringe ideas because "science" tells them that this will be a waste of time and effort. Hence they miss ideas which could be very valuable. This is the "blinkers" argument, by analogy with the leather shields placed over horses eyes so that they only see the road ahead. It is often put forward by proponents of new-age beliefs and alternative health. It is certainly true that ideas from outside the mainstream of science can have a hard time getting established. But on the other hand the opportunity to create a scientific revolution is a very tempting one: wealth, fame and Nobel prizes tend to follow from such work. So there will always be one or two scientists who are willing to look at anything new. Part 2: Model Organisms This portion of the lab is adapted from the W.O.R.M Initiative (See References) we will examine some of the common model organisms used in biology. Certain organisms have been used in research laboratories and in classrooms to advance our understanding of life and human diseases. These organisms become "model organisms" because of advantages in studying them. Model organisms are less costly, fewer ethical constraints are encountered using them, and, historically, more research data have been generated in the past. Model organisms are those that useful data sets have been already gathered to describe basic biological processes. And they are more amenable to asking certain questions due to their simplicity of structure and features (Bolker, 1995). A model system is a simpler, idealized system that can be accessible and easily manipulated (Rosenblueth & Wiener, 1945). Therefore, when selecting living organisms as models to work with, certain criteria are used depending upon the experimental purposes. As a result, there is a wide range of characteristics common to model organisms, including: 1) rapid development with short life cycles 2) small adult size 3) ready availability 4) tractability Being small, growing rapidly and being readily available are crucial in terms of housing them, given the budget and space limitations of research and teaching laboratories. Tractability relates to the ease with which they can be manipulated. For example, C. elegans is a popular research organism as it possesses all the characteristics mentioned, yet shares many essential biological properties with humans. For instance, researchers who study apoptosis (programmed cell death) use C. elegans as an experimental organism in the hope of finding treatments for certain types of human cancers, such as leukemia. By studying apoptosis in C. elegans, researchers hope to identify genes that switch-on cell death in cancer cells, thus, using the cell's own genetic machinery to rid the body of malignant cells. Because leukemia is the unregulated growth of white blood cells, identifying genes involved in apoptosis may provide researchers with a tool for treating the rapid proliferation of cancer cells. In general, scientists have to work with organisms different from the ones they wish to apply their findings to for several reasons (Flannery, 1997). Krogh (1929) wrote " … for a large number of problems there will be some animal of choice or a few such animals on which it can be most conveniently studied." Model organisms act as surrogates that enable experiments to be carried out under a more favorable environment than would be available in the original system (Rosenblueth & Wiener, 1945).The biological insights gained from using model organisms have helped to cure human diseases and improve people's understanding of life. Moreover, by studying organisms unrelated to humans, insight into scientific concepts can sometimes be more easily achieved.
Procedures Escherichia coli - Make Wet Mount and Sketch Escherichia coli, a prokaryotic organism without a nuclear membrane, is a representative living material often used in laboratories and classrooms (Flannery, 1997). E. coli reproduces rapidly (under optimal situation 0.5 hr/generation) such that results for a number of experiments can be quickly obtained. Saccharomyces cerevisiae - Make Wet Mount and Sketch Yeast are unicellular fungi that are characterized by a wide dispersion of natural habitats. Common on plant leaves and flowers, soil and salt water. Yeasts are also found on the skin surfaces and in the intestinal tracts of warm-blooded animals, where they may live symbiotically or as parasites. Yeasts multiply as single cells that divide by budding (eg Saccharomyces) or direct division (fission), or they may grow as simple irregular filaments (mycelium). The power of yeast as models in genetic studies is partially due to the ability to quickly map a phenotype producing gene to a region of the S. cerevisiae genome (Botstein and Fink , 1988). The basic cellular mechanics of replication, recombination, cell division and metabolism are generally conserved between yeast and larger eukaryotes, including mammals (http://genome-www.stanford.edu/Saccharomyces/VL-what_are_yeast.html). Drosophila - Observe Under Dissection Microscope Drosophila is very popular and successful as a model organism because it has short life cycle of two weeks, making it possible to study numerous generations over the course of the semester (Kramer, 1986). It is easy to culture and inexpensive to house large numbers (Jeszenszky, 1997). Also, it is large enough that many attributes can be seen with the naked eye or under low-power magnification (Sofer & Tompkins, 1994). Moreover, it has a very long history in biological research (since the early 1900s) and there are many useful tools to facilitate genetic study. Caenorhabditis elegans - Observe Under Dissection Microscope In the last two decades, a nematode, Caenorhabditis elegans, has captured the hearts of developmental biologists and geneticists hoping to solve the enigma of cell development and related biological problems, such as aging. Its popularity as a model organism is because it is transparent, thus cells of interest can be observed using a dissecting microscope. It is small (about 1- 1.5 mm) and easy to cultivate, which makes it possible to house large numbers of C. elegans. It has a short life cycle (3 days), which makes the production of numerous generations possible. It can be crossed at will. Male and hermaphrodites are the two sexes. Hermaphrodites can self fertilize or mate with males to produce offspring. Thus, cross or self-fertilization can be manipulated as desired. Arabidopsis thaliana (mustard plant) - Observe Arabidopsis thaliana is a small flowering plant that is widely used as a model organism in plant biology. Its complete genome has recently been sequenced. Arabidopsis is a member of the mustard (Brassicaceae) family, which includes cultivated species such as cabbage and radish. It has a small genome (114.5 Mb/125 Mb total) that has been sequenced. It has a rapid life cycle (about 6 weeks from germination to mature seed) and provides prolific seed production and easy cultivation in restricted space. Zebrafish (Danio rerio) - Observe This small fish is a relatively new model. As a vertebrate, it is a good model for aspects of human biology, but is cheaper and easier to handle than mice, as well as having a transparent and readily accessible embryo for developmental biology work. Its genome is in the process of being sequenced. African Clawed Frog (Xenopus laevis) - Observe Amphibian embryos remained the embryos of choice for experimental embryologists for many decades. Amphibian embryos are large, can be obtained in large numbers and can be maintained easily and inexpensively in the laboratory. One disadvantage of traditional amphibian species is that they are seasonal breeders. This meant that investigators could not do their experiments throughout the year. Xenopus laevis, the South African Clawed Frog, is a notable exception. In fact, it was its ability to spawn when induced with an injection of gonadotropic hormone that led to its common usage for human pregnancy tests in the 1950s: An injection of pregnancy urine (which contains chorionic gonadotropin) would induce spawning (http://www.ucalgary.ca/UofC/eduweb/virtualembryo/frogsrus.html). Mice (Mus musculus) - Observe The closest model organism to humans is especially used in development, genetic and immunology studies Questions: For each of the model organisms list their advantages and disadvantages for the study of inheritance.
Materials: Dissecting Microscopes Slides and cover slips for wet mounts depression slides Live cultures of E. coli. Live cultures of S. cerevisiae Live cultures of Caenorhabditis elegans, Vials of Drosophlia Arabidopsis thaliana Zebrafish (Carolina stock) - embryos if available from our stock cultures Xenopus Mice
References: Bolker, J. A. (1995). Model systems in developmental biology. BioEssays, 17(5), 451-455. Botstein, D., & Fink, R. G. (1988). Yeast: an experimental organism for modern biology. Science, 240, 1439-1443. Flannery, C. M. (1997). Models in biology. American Biology Teacher, 59(Apr), 244-248. Jeszenszky, W. A. (1997). Managing the fruit fly experiment. American Biology Teacher, 59(5), 292-294. Kramer, C. D. (1986). The classroom animal - fruit flies. Science and Children, Apr, 30-33. Krogh, A. (1929). Progress in physiology. American Journal of Physiology, 90, 243-251. W.O.R.M Initiative www.loci.wisc.edu/outreach/index.html Rosenblueth, A., & Wiener, N. (1945). The role of models in science. Philosophy of Science, 12, 316-321. Sofer, W., & Tompkins, L. (1994). Genetics in the classroom - drosophila genetics in the classroom. Genetics, 136, 417-422. |
