Prof. Keita Kamino
Institute of Molecular Biology, Academia Sinica

Title:Efficient information usage by cells – and cell biologists

Abstract: Organisms acquire and use sensory information to guide their behaviors. Likewise, scientists acquire and use the information contained in experimental data to better understand systems of interest. In both cases, the amounts of information available are usually limited, so using it efficiently is critical. In this seminar, I will discuss two aspects of efficient information usage. First, I explore information usage by cells, describing how we have discovered that motile Escherichia coli cells (arguably the simplest model of biological behavior) acquire very little information but use it highly efficiently. Second, I examine information usage by scientists, elaborating on how faced with noisy fluorescence data from single E. coli cells, we developed a method to extract relevant signals from raw data with theoretically maximal efficiency. Finally, I examine the similarities between these two processes.

References: 
Kamino, K., Keegstra, J. M., Long, J., Emonet, T., & Shimizu, T. S. (2020). Adaptive tuning of cell sensory diversity without changes in gene expression. Science Advances, 6(46), eabc1087.
Mattingly*, H. H., Kamino*, K., Machta, B. B., & Emonet, T. (2021). Escherichia coli chemotaxis is information limited. Nature Physics, 17(12), 1426-1431. (*Equal contribution)
Kamino*, K., Kadakia, N., Avgidis, F., Liu, Z. X., Aoki, K., Shimizu, T. S., & Emonet*, T. (2023). Optimal inference of molecular interaction dynamics in FRET microscopy. Proceedings of the National Academy of Sciences, 120(15), e2211807120. (*Correspondence)

Mini-bio: Keita Kamino is an Assistant Research Fellow at the Institute of Molecular Biology (IMB) in Academia Sinica in Taipei, Taiwan. Before joining IMB in 2022, he studied physics at the University of Tokyo. In 2013, he earned his PhD in biophysics from the same institution, where he discovered a scale-invariant property in cell-to-cell signaling of the social amoeba, Dictyostelium. During his postdoctoral appointment at AMOLF in Amsterdam, the Netherlands, and Yale in the USA, he combined fluorescence microscopy, microfluidics, Bayesian inference, and information theory to explore information processing in bacterial chemotaxis.