Figure 37.9 describes experiments that were conducted to determine how changes in the overlap of actin and myosin filaments within the sarcomeres of a muscle fiber affect muscle force. Answer the questions after the figure to practice interpreting data and understanding experimental design. These questions refer to concepts that are explained in the following three brief data analysis primers from a set of four available on LaunchPad.
You can find these primers by clicking on the button labeled “Resources” in the menu at the upper right on your main LaunchPad page, then click on “Content by type.” Within the following questions, click on “Primer Section” to read the relevant section from these primers. Click on the button labeled “Key Terms” to see pop-up definitions of boldfaced terms.
HOW DO WE KNOW?
BACKGROUND From the 1930s through the 1960s, British muscle physiologists studied the properties of striated frog muscle fibers. In the first set of experiments, A. V. Hill examined how a muscle’s shortening velocity affects its force production. In the second set of studies, British physiologists Andrew Gordon and Andrew Huxley, together with American physiologist Fred Julian, studied how a muscle’s contractile length affects its force-generating ability.
HYPOTHESIS They hypothesized that changes in overlap between myosin and actin affect the number of cross-bridges and thus the force the muscle can produce.
EXPERIMENT Gordon, Huxley, and Julian isolated a single muscle fiber and used optical microscopy to measure sarcomere length. They kept this length constant while the fiber was stimulated to produce force. Measurements of force were obtained at different sarcomere lengths.
RESULTS The top graph shows the data charted by Gordon, Huxley, and Julian, and the bottom graph reinterprets their data in terms of force and percent of muscle length. Their experiments showed that the muscle fiber produced maximal force at an intermediate sarcomere length (approximately 2.3 µm). At this length, the greatest number of cross-bridges were hypothesized to form, generating maximal force. As the sarcomere length was decreased or stretched, and then stimulated to contract, force declined. These results were consistent with a decrease in the number of cross-bridges that could form as a result of decreased actin–myosin overlap.
FOLLOW-UP WORK Other studies confirmed that changes in myosin cross-bridge formation are linked to changes in actin and myosin filament overlap at different sarcomere lengths, supporting the sliding filament model of muscle contraction.
SOURCE Gordon, A. M., A. F. Huxley, and F. J. Julian. 1966. “The Variation in Isometric Tension with Sarcomere Length in Vertebrate Muscle Fibres.” Journal of Physiology 184 :170–192.
The researchers’ experimental hypothesis was that changes in actin and myosin overlap would alter the number of myosin cross-bridges that could form within a sarcomere, and specifically that:
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hypothesis | A tentative explanation for one or more observations that makes predictions that can be tested by experiments or additional observations. |
Experimental Design
Experiments provide one way to make sense of the world. There are many different kinds of experiments, some of which begin with observations. Charles Darwin began with all kinds of observations—the relationship between living organisms and fossils, the distribution of organisms on the Earth, species found on islands and nowhere else—and inferred an evolutionary process to explain what he saw. Other experiments begin with data collection. For example, genome studies begin by collecting vast amounts of data—the sequence of nucleotides in all of the DNA of an organism—and then ask questions about the patterns that are found.
Such observations can lead to questions – Why are organisms adapted to their environment? Why are there so many endemic species (organisms found in one place and nowhere else) on islands? Why does the human genome contain vast stretches of DNA that do not code for protein?
Types of Hypotheses
A hypothesis, as we saw in Chapter 1, is a tentative answer to the question, an expectation of what the results might be. This might at first seem counterintuitive. Science, after all, is supposed to be unbiased, so why should you expect any particular result at all? The answer is that it helps to organize the experimental setup and interpretation of the data.
Let’s consider a simple example. We design a new medicine and hypothesize that it can be used to treat headaches. This hypothesis is not just a hunch—it is based on previous observations or experiments. For example, we might observe that the chemical structure of the medicine is similar to other drugs that we already know are used to treat headaches. If we went into the experiment with no expectation at all, it would be unclear what to measure.
A hypothesis is considered tentative because we don’t know what the answer is. The answer has to wait until we conduct the experiment and look at the data. When an experiment predicts a specific effect, as in the case of the new medicine, it is typical to also state a null hypothesis, which predicts no effect. Hypotheses are never proven, but it is possible based on statistical analysis to reject a hypothesis. When a null hypothesis is rejected, the hypothesis gains support.
Sometimes, we formulate several alternative hypotheses to answer a single question. This may be the case when researchers consider different explanations of their data. Let’s say for example that we discover a protein that represses the expression of a gene. Our question might be: How does the protein repress the expression of the gene? In this case, we might come up with several models—the protein might block transcription, it might block translation, or it might interfere with the function of the protein product of the gene. Each of these models is an alternative hypothesis, one or more of which might be correct.