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The team observed viruses as they evolved over hundreds of generations to infect bacteria. They found that when the bacteria could evolve defences, the viruses evolved at a quicker rate and generated greater diversity, compared to situations where the bacteria were unable to adapt to the viral infection. The study shows, for the first time, that the American evolutionary biologist Leigh Van Valen was correct in his 'Red Queen Hypothesis'. The theory, first put forward in the 1970s, was named after a passage in Lewis Carroll's Through the Looking Glass in which the Red Queen tells Alice, 'It takes all the running you can do to keep in the same place'. This suggested that species were in a constant race for survival and have to continue to evolve new ways of defending themselves throughout time. Dr Steve Paterson, from the University's School of Biosciences, explains: "Historically, it was assumed that most evolution was driven by a need to adapt to the environment or habitat. The Red Queen Hypothesis challenged this by pointing out that actually most natural selection will arise from co-evolutionary interactions with other species, not from interactions with the environment. "This suggested that evolutionary change was created by 'tit-for-tat' adaptations by species in constant combat. This theory is widely accepted in the science community, but this is the first time we have been able to show evidence of it in an experiment with living things." Dr Michael Brockhurst said: "We used fast-evolving viruses so that we could observe hundreds of generations of evolution. We found that for every viral strategy of attack, the bacteria would adapt to defend itself, which triggered an endless cycle of co-evolutionary change. We compared this with evolution against a fixed target, by disabling the bacteria's ability to adapt to the virus. "These experiments showed us that co-evolutionary interactions between species result in more genetically diverse populations, compared to instances where the host was not able to adapt to the parasite. The virus was also able to evolve twice as quickly when the bacteria were allowed to evolve alongside it."

By reworking a theory first proposed by physicists in the 1920s, the researchers discovered a new way to predict important characteristics of a new material before it's been created. The new formula allows computers to model the properties of a material up to 100,000 times faster than previously possible and vastly expands the range of properties scientists can study. "The equation scientists were using before was inefficient and consumed huge amounts of computing power, so we were limited to modeling only a few hundred atoms of a perfect material," said Emily Carter, the engineering professor who led the project. "But most materials aren't perfect," said Carter, the Arthur W. Marks '19 Professor of Mechanical and Aerospace Engineering and Applied and Computational Mathematics. "Important properties are actually determined by the flaws, but to understand those you need to look at thousands or tens of thousands of atoms so the defects are included. Using this new equation, we've been able to model up to a million atoms, so we get closer to the real properties of a substance." By offering a panoramic view of how substances behave in the real world, the theory gives scientists a tool for developing materials that can be used for designing new technologies. Car frames made from lighter, strong metal alloys, for instance, might make vehicles more energy efficient, and smaller, faster electronic devices might be produced using nanowires with diameters tens of thousands of times smaller than that of a human hair.