Integration of cellular signals in chattering environments

Abstract

Cells are constantly exposed to fluctuating environmental conditions. External signals are sensed, processed and integrated by cellular signal transduction networks, which translate input signals into specific cellular responses by means of biochemical reactions. These networks have a complex nature, and we are still far from having a complete characterization of the process through which they integrate information, specially given the noisy environment in which that information is embedded. Guided by the many instances of constructive influences of noise that have been reported in the physical sciences in the last decades, here we explore how multiple signals are integrated in an eukaryotic cell in the presence of background noise, or chatter. To that end, we use a Boolean model of a typical human signal transduction network. Despite its complexity, we find that the network is able to display simple patterns of signal integration. Furthermore, our computational analysis shows that these integration patterns depend on the levels of fluctuating background activity carried by other cell inputs. Taken together, our results indicate that signal integration is sensitive to environmental fluctuations, and that this background noise effectively determines the information integration capabilities of the cell.

Reciprocal Encoding of Signal Intensity and Duration in a Glucose-Sensing Circuit

“…Cells constantly sense and respond to changes in their extracellular environment (Rué et al, 2012; Waltermann and Klipp, 2011). The heterogeneous and fluctuating nature of the micro-environment requires that cells possess complex signaling pathways to interpret and respond to a broad range of environmental conditions.…”

Independent Pathways Can Transduce the Life-Cycle Differentiation Signal in Trypanosoma brucei

“…Commonly, the existence of multiple cues ensures that cells do not embark prematurely on a developmental process that could damage their viability or fitness [1]. Additionally, the presence of multiple cues can lower the threshold at which cells respond to differentiation signals or refine their response, with inputs from distinct signalling pathways co-operating to generate a specific developmental outcome (e.g.…”

Synchronization-based computation through networks of coupled oscillators

“…The network is not a static circuit which computes passively the response to the inputs but a whole collection of circuits (based in the logic gates described here) which reconfigures itself depending of the input received. This type of complex networks of logic gates which reconfigure themselves dynamically to adapt its response to specific inputs has been found in other natural systems such as the signaling networks in eukaryotic cells (Domedel-Puig et al, 2011 ; Rué et al, 2012 ). As said above, we do not claim, however, that the brain is a circuit of boolean gates but a highly complex dynamical system able to process information in a very sophisticated manner at the mesoscale.…”