Speaker
Description
Collectives of microbes exhibit functions that individual species cannot, such as degrading waste, producing vitamins, and creating biofuels, which can benefit humans. To improve these functions, researchers suggest using artificial selection on collectives to choose the best-performing ones for the next generation. However, this method has shown that there is a limitation to improving the function. In our study, we propose an alternative approach where we select collectives with a bias to counteract natural selection during maturation instead of selecting the best-performing collectives. Our results demonstrate that this strategy leads to further enhancements in collective function by exploring pathways to higher-functioning collectives. Our findings suggest that incorporating a bias will be a promising strategy for improving collective function.
