title: Comparison of adaptation motifs: temporal, stochastic and spatial responses.
abstract: The cells' ability to adapt to changes in the external environment is crucial for the survival of many organisms. There are two broad classes of signalling networks that achieve perfect adaptation. Both rely on complementary regulation of the response by an external signal and an inhibitory process. In one class of systems, inhibition comes about from the response itself, closing a negative feedback (NFB) loop. In the other, the inhibition comes directly from the external signal in what is referred to as an incoherent feedforward (IFF) loop. Although both systems show adaptive behaviour to constant changes in the level of the stimulus, their response to other forms of stimuli can differ. Here the authors consider the respective response to various such disturbances, including ramp increases, removal of the stimulus and pulses. The authors also consider the effect of stochastic fluctuations in signalling that come about from the interaction of the signalling elements. Finally, the authors consider the possible effect of spatially varying signals. The authors show that both the NFB and the IFF motifs can be used to sense static spatial gradients, under a local excitation, global inhibition assumption. The results may help experimentalists develop protocols that can discriminate between the two adaptation motifs.
authors.affiliation: Departments of Cell Biology, Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA. pi@jhu.edu.
authors.forename: Pablo A
authors.initials: PA
authors.lastname: Iglesias
authors.affiliation: Department of Electrical and Computer Engineering, The Johns Hopkins University, 3400 N. Charles St., Baltimore, MD 21218, USA.
authors.forename: Changji
authors.initials: C
authors.lastname: Shi
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology*; D006706:Homeostasis; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*; D013269:Stochastic Processes; D049490:Systems Biology / Q000379:methods*