2018.03.27 Sensory Adaptation by Stochastic Adaptive Sampling in Receptor Neurons ---- A Multi-scale Modelling
题 目：Sensory Adaptation by Stochastic Adaptive Sampling in Receptor Neurons ---- A Multi-scale Modelling Approach
报告人：Dr. Zhuoyi Song (宋卓异)
Department of Biomedical Science at the University of Sheffield, UK
Receptor neurons supersede manmade sensors in their ability to adapt according to environmental changes (adaptation). The underlying mechanisms still remain traditional challenges in sensory neuroscience. To study this adaptation process, I construct multi-scale computational models for sensory receptors, which aim to link signal transduction dynamics from the molecular to the systems level.
I will talk about the modeling approach and how it helped to uncover several 100-year scientific puzzles in sensory adaptation. For example, how the models revealed a stochastic adaptive sampling mechanism, by which a fly photoreceptor can encode logarithmic light intensity changes. I will show how we think that the mechanism is general in information encoding, and I want to discuss why and how these rules may work with other sensory modalities.
I will also briefly talk about how the models are scalable by adding new modules. A new version of the model helped to predict how the fly eyes achieve hyper-acuity by moving the photoreceptors to light signals. This result has been published in a 149-page Elife paper and has been reported by over 100 international media.
Description of allostery is fundamental to understanding most processes involving biological macromolecules. Site-specific incorporation of photo-responsive unnatural amino acids (Uaas) into proteins by the genetic code expansion technology adds unprecedented photochemical properties to varieties of proteins. Although there is a long history to engineer light-activatable proteins, for example ion channels and kinases, the development of light-induced allosteric modulations of pharmacological importance – is a more recent phenomenon. In this talk, I will summarize our findings of light-sensitive GPCRs and neuronal NMDA receptors (NMDARs). Light-sensitive Uaas have been incorporated at specific sites of the receptors. In the case of NMDARs, targeting sites within heterodimer interfaces led us to identify a series of robust light-sensitive receptors of GluN2A and GluN2B subtypes. Characterizations of light-induced allosteric modulations in the presence of inhibitors (Zn2+ and ifenprodil) and potentiators (spermine) have provided a unified view of how the same N-terminal domains of both subtypes, distant to the agonists binding domains, bidirectionally modulate receptors functions. Our works are important for neuropharmacology because the NMDARs are promising drug targets for the development of therapeutic compounds to treat neuronal diseases including depression and the Alzheimer’s.
Dr. Zhuoyi Song is a research associate in BMS, UoS, UK. She received her B.S. in Electrical Engineering and Automation at Hebei University of Technology in 2003, her M.E. in Control Science and Engineering at the Harbin Institute of Technology in 2005 and her Ph.D. in the Department of Automatic Control and System Engineering & the Department of Biomedical Science at University of Sheffield in 2011.
She worked on computational modeling at the Okinawa Institute of Science and Technology (OIST), University of Sheffield and the UCL Centre for Computation, Mathematics and Physics in the Life Sciences and Experimental Biology. Now she is focused on developing multi-scale modeling and inference computational framework for sensory systems in the Department of Biomedical Science at the University of Sheffield.