Carl’s interest in modeling evolution extends beyond antibiotic resistance. He also models how new human pathogens, such as SARS and HIV, evolve to infect humans and how the human immune system affects the evolution of such pathogens. In all of these areas, modeling is a useful tool because it allows one to make testable predictions about evolution.
Increasingly, we are realizing that many of the biological problems we face, from controlling an HIV infection to preventing the destruction of a crop by pests to maintaining effective antibiotics, are fundamentally problems of managing evolution. And scientists, as well as funding agencies, are waking up to that reality. As Carl puts it, “There is a tremendous focus in evolutionary biology on understanding how evolutionary processes operate in systems that we care about for commercial or public health reasons, like hospitals and farms. This brings with it a new focus. We rarely thought about how we control evolution…Now we are asking a different kind of question — an engineers’ kind of question: what parameters or what environmental conditions would make evolution do this.”
This shift in focus, from reconstructing past evolution to managing current evolution, is an important one. It has the potential to both increase our understanding of evolutionary processes and to improve the quality of human lives, through medicine, agriculture, environmental health, and, in fact, any area in which humans depend upon living (and hence, potentially evolving!) systems.
Discussion and extension questions:
- What are the four basic characteristics that result in natural selection? Explain how bacteria encountering an antibiotic exhibit each of these characteristics.
- How was “cycling” supposed to slow the evolution of antibiotic resistant bacteria?
- What situation did Carl build a model of? What did that model predict? How did he test his model?
- Describe one situation in which you could use an experiment to test a hypothesis about evolution.
- What are some of the benefits of using a computer model to test an idea instead of an experiment?