title: Stochastic adaptation and fold-change detection: from single-cell to population behavior.
abstract: BACKGROUND
  In cell signaling terminology, adaptation refers to a system's capability of returning to its equilibrium upon a transient response. To achieve this, a network has to be both sensitive and precise. Namely, the system must display a significant output response upon stimulation, and later on return to pre-stimulation levels. If the system settles at the exact same equilibrium, adaptation is said to be 'perfect'. Examples of adaptation mechanisms include temperature regulation, calcium regulation and bacterial chemotaxis.
  
  
  RESULTS
  We present models of the simplest adaptation architecture, a two-state protein system, in a stochastic setting. Furthermore, we consider differences between individual and collective adaptive behavior, and show how our system displays fold-change detection properties. Our analysis and simulations highlight why adaptation needs to be understood in terms of probability, and not in strict numbers of molecules. Most importantly, selection of appropriate parameters in this simple linear setting may yield populations of cells displaying adaptation, while single cells do not.
  
  
  CONCLUSIONS
  Single cell behavior cannot be inferred from population measurements and, sometimes, collective behavior cannot be determined from the individuals. By consequence, adaptation can many times be considered a purely emergent property of the collective system. This is a clear example where biological ergodicity cannot be assumed, just as is also the case when cell replication rates are not homogeneous, or depend on the cell state. Our analysis shows, for the first time, how ergodicity cannot be taken for granted in simple linear examples either. The latter holds even when cells are considered isolated and devoid of replication capabilities (cell-cycle arrested). We also show how a simple linear adaptation scheme displays fold-change detection properties, and how rupture of ergodicity prevails in scenarios where transitions between protein states are mediated by other molecular species in the system, such as phosphatases and kinases.
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich, Universitätsstrasse 6, CH-8092 Zurich, Switzerland. tatiana.marquezlago@gmail.com
authors.forename: Tatiana T
authors.initials: TT
authors.lastname: Marquez-Lago
authors.forename: André
authors.initials: A
authors.lastname: Leier
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology*; D002450:Cell Communication / Q000502:physiology*; D003198:Computer Simulation; D005434:Flow Cytometry; D008954:Models, Biological; D017510:Protein Folding; D011506:Proteins / Q000378:metabolism*; D013269:Stochastic Processes
chemical_list: D011506:Proteins