Characterizing multistationarity regimes in biochemical reaction networks

Abstract

12 páginas, 5 figuras, 3 tablas ; Switch like responses appear as common strategies in the regulation of cellular systems. Here we present a method to characterize bistable regimes in biochemical reaction networks that can be of use to both direct and reverse engineering of biological switches. In the design of a synthetic biological switch, it is important to study the capability for bistability of the underlying biochemical network structure. Chemical Reaction Network Theory (CRNT) may help at this level to decide whether a given network has the capacity for multiple positive equilibria, based on their structural properties. However, in order to build a working switch, we also need to ensure that the bistability property is robust, by studying the conditions leading to the existence of two different steady states. In the reverse engineering of biological switches, knowledge collected about the bistable regimes of the underlying potential model structures can contribute at the model identification stage to a drastic reduction of the feasible region in the parameter space of search. In this work, we make use and extend previous results of the CRNT, aiming not only to discriminate whether a biochemical reaction network can exhibit multiple steady states, but also to determine the regions within the whole space of parameters capable of producing multistationarity. To that purpose we present and justify a condition on the parameters of biochemical networks for the appearance of multistationarity, and propose an efficient and reliable computational method to check its satisfaction through the parameter space. ; Funding provided by Spanish government, Ministry of Science and Innovation project MultiSysBio (ref. DPI2008-06880-C03-02) and DPI2004-07444-C04-03, Xunta de Galicia (PGIDIT02-PXIC40209PN). Consejo Superior de Investigaciones Científicas intramural project BioREDES (ref. PIE-201170E018). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ; Peer reviewed