MODELING CELLULAR INFORMATION PROCESSING OF PULSATILE INPUTS AND THE EMERGENCE OF RESONANCES

ALEJANDRA VENTURA; JULIANA REVES SZEMERE

Buenos Aires

Congreso; Reunión Biociencias; 2017

 In many biological contexts it is importantto understand how the cell signaling system responds to time-dependent inputs.For example, gene expression in neuronal cells is affected by thetime-dependent signals that the cells receive from their afferent neurons, andthis is essential for memory formation. Signaling pathways stimulated by inputsthat change rapidly over time need to process a significant amount ofinformation. How much information they are able to process per unit of time isproportional to its bandwidth, which is determined by measuring thesystem?s response to fluctuating signals at differentfrequencies. The larger the bandwidth of a pathway, the shorter itsresponse time and the more accurately its response to a rapidly varyingsignal. It has been shown that certainsmall signaling networks behave as low-pass filters wherethe response is maximized at the zero input frequency. The focus of the workpresented here is to identify conditions for which simple signaling topologiescan optimize a given response at certain intermediate inputfrequencies, where by optimizing we mean, for example, maximizingthe production or the level of activation of a protein at thesefrequencies. We refer to this optimization as resonance. Resonance is typicallymeasured in quasi steady-state (long lasting pulsatile signals). By using a combinedcomputational and theoretical approach, we show that resonance can be obtainedfor pulsatile input signals that are active for a short number of periods as comparedwith the time scale of the signaling component processing that input,. We callthis effect transient resonance since  thesystems we consider do not exhibit resonance when using long lasting pulsatilesignal. Transient resonance also emerges for the same signaling system, withthe long lasting pulsatile signal, provided that the downstream singlingcomponents are fast enough to read pre-steady-state information.