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Though the theory of evolution is well established, there are aspects scientists don’t fully understand. Biologists and physicists are trying to fill in some of the gaps in our knowledge, by creating more quantitative models and approaching evolution from new perspectives. In a well-attended session at the APS March Meeting, several scientists discussed various aspects of the foundations of evolution.
Michael Deem of Rice University talked about how “life has evolved to evolve.” That is, evolvability itself is a selectable trait, especially when the environment changes rapidly. The findings have implications for drug resistance, and could be used to help hospitals develop strategies to get the most use out of a collection of antibiotics before bacteria become resistant to all of them.
Daniel Fisher of Harvard discussed what is known and what is not well understood about evolution, and described a quantitative model he has developed to help answer some of the open questions. For instance, it is well known that mutation leads to heritable variation and selection, but we don’t have a good grasp of what can evolve on what time scales, he said. At short time scales, we can watch evolution happen in the lab, such as when bacteria evolve antibiotic resistance. But at longer time scales, we don’t know the details of what can evolve, said Fisher. He described his quantitative model of how fast populations can evolve under various conditions.
We could also benefit from a new view of DNA and genomics, said biologist Jim Shapiro of the University of Chicago. Viewing the cell as a sort of computer provides a useful perspective, said Shapiro, who discussed what he called a “21st century view of genomes and evolution.”
Life has evolved sophisticated information processing tools that we can learn a lot from, he said. Genomes function in complicated ways, and genomics cannot be viewed as a simple one gene-one trait system, he pointed out. DNA acts as a data storage medium, and is always in communication with the rest of the cell. DNA doesn’t do things by itself, he emphasized.
Furthermore, mutations are not always just undirected random changes. Cells are filled with mechanisms for formatting, restructuring and repairing DNA. The immune system is one example. As another example, Shapiro described how the DNA of E. coli is formatted so that it can execute an algorithm to discriminate between lactose and glucose and decide how to process them, depending on whether one or both are present in the cell.
“Cells have powerful information-processing networks,” said Shapiro. Cells control hundreds of millions of biochemical and biomechanical events per cell cycle. When replicating its DNA, E.coli copies 1000 nucleotides per second, with very few mistakes. “Biological systems are unbelievably efficient,” he said. “If we could mimic that, we’d be on to something.”
Juan Keymer of Princeton University described how he has constructed a sort of cellular automaton based on how bacteria adapt to conditions in different tiny microhabitats. He used microfabrication techniques to build a landscape of habitat patches, each about 100 micrometers on a side, linked by microchannels through which the bacteria can move. In each of the tiny square pens, colonies of E. coli grow and reproduce.
Keymer can control the conditions in each microhabitat, for instance by altering the amount of food available to organisms in that pen, or by shining ultraviolet light on it. He then studies how the bacteria move from one microenvironment to the next, and develop mutations to adapt to local conditions. Because the bacteria reproduce and mutate in a predictable manner, they could form a living cellular automaton, with 0s and 1s represented by the presence or absence of bacteria in each cell.
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