30 research outputs found
A Characterization of Scale Invariant Responses in Enzymatic Networks
An ubiquitous property of biological sensory systems is adaptation: a step
increase in stimulus triggers an initial change in a biochemical or
physiological response, followed by a more gradual relaxation toward a basal,
pre-stimulus level. Adaptation helps maintain essential variables within
acceptable bounds and allows organisms to readjust themselves to an optimum and
non-saturating sensitivity range when faced with a prolonged change in their
environment. Recently, it was shown theoretically and experimentally that many
adapting systems, both at the organism and single-cell level, enjoy a
remarkable additional feature: scale invariance, meaning that the initial,
transient behavior remains (approximately) the same even when the background
signal level is scaled. In this work, we set out to investigate under what
conditions a broadly used model of biochemical enzymatic networks will exhibit
scale-invariant behavior. An exhaustive computational study led us to discover
a new property of surprising simplicity and generality, uniform linearizations
with fast output (ULFO), whose validity we show is both necessary and
sufficient for scale invariance of enzymatic networks. Based on this study, we
go on to develop a mathematical explanation of how ULFO results in scale
invariance. Our work provides a surprisingly consistent, simple, and general
framework for understanding this phenomenon, and results in concrete
experimental predictions
An observability result related to active sensing
For a general class of translationally invariant systems with a specific
category of nonlinearity in the output, this paper presents necessary and
sufficient conditions for global observability. Critically, this class of
systems cannot be stabilized to an isolated equilibrium point by dynamic output
feedback. These analyses may help explain the active sensing movements made by
animals when they perform certain motor behaviors, despite the fact that these
active sensing movements appear to run counter to the primary motor goals. The
findings presented here establish that active sensing underlies the maintenance
of observability for such biological systems, which are inherently nonlinear
due to the presence of the high-pass sensor dynamics
Scale-invariant systems realize nonlinear differential operators
In recent years, several biomolecular systems have been shown to be scale-invariant (SI), i.e. to show the same output dynamics when exposed to geometrically scaled input signals (u β pu, p > 0) after pre-adaptation to accordingly scaled constant inputs. In this article, we show that SI systems-as well as systems invariant with respect to other input transformations-can realize nonlinear differential operators: when excited by inputs obeying functional forms characteristic for a given class of invariant systems, the systems' outputs converge to constant values directly quantifying the speed of the input
Fold-change detection and scalar symmetry of sensory input fields
Recent studies suggest that certain cellular sensory systems display fold-change detection (FCD): a response whose entire shape, including amplitude and duration, depends only on fold changes in input and not on absolute levels. Thus, a step change in input from, for example, level 1 to 2 gives precisely the same dynamical output as a step from level 2 to 4, because the steps have the same fold change. We ask what the benefit of FCD is and show that FCD is necessary and sufficient for sensory search to be independent of multiplying the input field by a scalar. Thus, the FCD search pattern depends only on the spatial profile of the input and not on its amplitude. Such scalar symmetry occurs in a wide range of sensory inputs, such as source strength multiplying diffusing/convecting chemical fields sensed in chemotaxis, ambient light multiplying the contrast field in vision, and protein concentrations multiplying the output in cellular signaling systems. Furthermore, we show that FCD entails two features found across sensory systems, exact adaptation and Weber's law, but that these two features are not sufficient for FCD. Finally, we present a wide class of mechanisms that have FCD, including certain nonlinear feedback and feed-forward loops. We find that bacterial chemotaxis displays feedback within the present class and hence, is expected to show FCD. This can explain experiments in which chemotaxis searches are insensitive to attractant source levels. This study, thus, suggests a connection between properties of biological sensory systems and scalar symmetry stemming from physical properties of their input fields