Chen, Beini

English

University of Tennessee, Knoxville: Trace

Cells have the ability to detect and respond to diverse environmental stimuli by means of biochemical signaling pathways that propagate information from the cell membrane into the cell. In this work, we use computational	  methods	  to	  study	  a	  common	  signaling	  pathway	  that	  exhibits	  bistability	  and	  observe	  how	  its	  dynamical	  and	  steady	  state	  behavior	  is	  affected	  by	  various	  cellularly	  relevant	  factors.	  Bistable	  networks	  have	  two	  distinct	  stable	  steady	  states	  and	  are	  commonly	  used	  in	  cellular	  decision-­‐making.	  In	  the	  network	  studied,	  a	  substrate	  protein	  can	  be	  phosphorylated	  and	  dephosphorylated	  at	  two	  residues	  by	  kinase	  and	  phosphatase	  proteins.	  The	  reaction	  network	  is	  simulated	  using	  computational	  methods	  based	  on	  ordinary	  differential	  equations,	  and	  the	  transition	  from	  bistable	  to	  monostable	  behavior	  is	  characterized	  by	  observing	  the	  time	  dependence	  of	  the	  system	  starting	  from	  different	  initial	  conditions.	  We	  find	  that	  confining	  the	  system,	  which	  leads	  to	  increased	  concentration,	  promotes	  bistability	  while	  decreasing	  the	  rate	  at	  which	  enzymes	  become	  activated	  suppresses	  bistability.	  In	  addition,	  we	  consider	  effects	  of	  network	  topology	  by	  including	  additional	  reactions	  with	  reaction	  rates	  proportional	  to	  an	  independent	  control	  parameter.	  The	  reactions,	  which	  mimic	  the	  ability	  of	  proteins	  to	  rapidly	  rebind	  when	  in	  close	  spatial	  proximity,	  are	  found	  to	  greatly	  influence	  the	  signaling	  dynamics.	  

Effects of system size and network topology on the bistability of cell signaling networks

https://trace.tennessee.edu/cgi/viewcontent.cgi?article=1037&amp;context=utk_eureca

Effects of system size and network topology on the bistability of cell signaling networks

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University of Tennessee, Knoxville: Trace