2013.8.29 From molecules to development: revealing simple rules of biological clocks

2019-07-11 12:20:25

2013.8.29 From molecules to development: revealing simple rules of biological clocks

 

 

 

Qiong Yang, Ph.D.

 

 

Postdoctoral Fellow, Stanford University, Stanford, CA

Department of Chemical & Systems Biology

 

 

  

Time:14:00pm, Aug. 29, 2013

 

 

Address:Rm. 102, Old Chemistry Building, east Wing, 1rd floor, CQB

 

Abstract:

 

 

 

Organisms from cyanobacteria through vertebrates make use of biochemical and genetic oscillators to drive repetitive processes like cell cycle progression and vertebrate somitogenesis. Oscillators also allow organisms to anticipate natural environmental rhythms, as exemplified by the circadian clock. Despite the complexity and variety of biological oscillators, their core design is thought to be shared. Notably, most of them contain a core positive-plus-negative feedback architecture. In this talk, I will use two dynamic systems as motivating examples, and discuss first how several modifications of a basic activator/repressor circuit can promote oscillation within individual biological clocks, and second, how multiple clocks coordinate their oscillations within single cells. In one system, we have dissected a mitotic oscillator in the Xenopus laevis early embryos, and found that the positive feedback functions as a bistable switch and the negative feedback as a time-delayed, digital switch (Yang and Ferrell, Nat Cell Biol,  2013;  Ferrell,  Tsai,  and  Yang,  Cell,  2011). Mathematical  modeling  indicates  that this  time  delay  must  be coupled  to the  ultrasensitivity  to  ensure  robust  oscillations  and segregation  of  cell-cycle  phases.  Principles  uncovered  here  may  also  apply  to  other activator-repressor  oscillators  and  help  in  designing  robust  synthetic  clocks. In  another system, we revealed the coupling between two cell-autonomous oscillators, the circadian clock  and  the  cell  division  cycle,  within  individual  cells  (Yang,  Pando,  et  al.  Science, 2010).  A  simple  model  can  fit  our  data  well  and  helps  us  to  identify  the  molecular machinery underlying the coupling (Dong, Yang, et al. Cell, 2010).

 

 

 

Host:Professor Chao TANG