Data Access and Scientific Societies
Author(s): Meagher, TR
As part of the changing landscape of science, data archiving is becoming a widespread practice. This has in turn created an opportunity to more directly integrate archived data resources into teaching at all levels. For example, it is possible to develop student exercises that reconstruct the underlying analysis presented in published work, and perhaps to explore other dimensions of such work in creative ways. In order to facilitate such exploration-based learning, there is a need for developing scientific data as a teaching tool. An approach to doing so being led by the Ecological Society of America, in collaboration with the Society for the Study of Evolution and other scientific societies, has been to establish an online resource library of peer-reviewed data-based educational modules, EcoED (http://ecoed.esa.org/). In the very near future, this online resource is planned to grow to include various modules, including one geared to the evolution community, EvoED (http://evoed.evolutionsociety.org/). Integration of the vast online resource into educational modules that encourage exploration and analytical approaches to science is an important step change in science teaching that will promote better understanding among students of science as a process as well as a product.
The Jackprot Simulation: slot-machine model to teach the non-random nature of protein evolution
Author(s): Paz-y-Mino-C, G, Espinosa, A
Protein evolution is not a random process. We use slot-machine probabilities and ion channels, in an inquiry-based learning scenario, to show biological directionality on molecular change. The slot-machine represents the cellular chemical apparatus, product itself of Darwinian evolution, required to generate, step by step, each of the nucleotides coding for an amino acid of a model protein. Teachers and students can access the Jackprot Simulation and run statistical analysis of protein evolution by cutting and pasting nucleotide sequences obtained from the WWW. The Jackprot generates statistics on nucleotide evolution under selection (observed vs. expected values) and at random (without selection). We will use the following example when explaining hands-on how to use the Jackprot: Because ion channels reside in the lipid bilayer of cell membranes, their residue location must be in balance with the membrane’s hydrophobic/philic nature; a selective ‘pore’ for ion passage is located within the hydrophobic region. We will contrast the random generation of DNA sequence for KcsA, a bacterial two-transmembrane-domain (2TM) potassium channel, from Streptomyces lividans, with an under-selection scenario, the ‘Jackprot,’ which predicts much faster evolution than chance. We will distribute guidelines on how to use the online interface The Jackprot Simulation (JAVA APPLET Version 1.0) to model a numerical interaction between mutation rate and natural selection during the scenario of polypeptide evolution. Winning the ‘Jackprot,’ or highest-fitness complete-peptide sequence, requires cumulative smaller ‘wins’ (rewarded by selection) at the first, second and third positions in each of the 161 KcsA codons (‘jackdons’ that led to ‘jackacids’ that led to the ‘Jackprot’). The ‘Jackprot,’ as didactic tool, helps students understand how mutation rate coupled with natural selection suffice to explain the evolution of specialized, complex proteins. Student learning data will be shared.