Retroactivity effects dependency on the transcription factors binding mechanisms

• Published in: Journal of theoretical biology 2016-12, Vol.410, p.77-106
• Main Authors: Pantoja-Hernández, Libertad, Álvarez-Buylla, Elena, Aguilar-Ibáñez, Carlos F., Garay-Arroyo, Adriana, Soria-López, Alberto, Martínez-García, Juan Carlos
• Format: Article
• Language: English
• Subjects: Animals; Binding processes; Dimerization; Humans; Models, Biological; ODE simulations; Protein Binding - physiology; Protein Multimerization - physiology; Regulation; Sequential binding; SSA; Stochastic Processes; Transcription Factors - chemistry; Transcription Factors - metabolism; Transcription, Genetic - physiology
• ISSN: 0022-5193; 1095-8541
• DOI: 10.1016/j.jtbi.2016.08.012

Downstream connection effects on transcription are caused by retroactivity. When biomolecular dynamical systems interconnect retroactivity is a property that becomes important. The biological functional meaning of these effects is increasingly becoming an area of interest. Downstream targets, which are operator binding sites in transcriptional networks, may induce behaviors such as ultrasensitive responses or even represent an undesired issue in regulation. To the best of our knowledge, the role of the binding mechanisms of transcription factors in relation to minimizing – or enhancing – retroactivity effects has not been previously addressed. Our aim is to evaluate retroactivity effects considering how the binding mechanism impacts the number of free functional transcription factor (FFTF) molecules using a simple model via deterministic and stochastic simulations. We study four transcription factor binding mechanisms (BM): simple monomer binding (SMB), dimer binding (DB), cooperative sequential binding (CSB) and cooperative sequential binding with dimerization (CSB_D). We consider weak and strong binding regimes for each mechanism, where we contrast the cases when the FFTF is bound or unbound to the downstream loads. Upon interconnection, the number of FFTF molecules changed less for the SMB mechanism while for DB they changed the most. Our results show that for the chosen mechanisms (in terms of the corresponding described dynamics), retroactivity effects depend on transcription binding mechanisms. This contributes to the understanding of how the transcription factor regulatory function—such as decision making—and its dynamic needs for the response, may determine the nature of the selected binding mechanism. •Our aim is to find out how binding mechanisms account for differential retroactivity effects.•We examined changes in the FFTF and its variability in presence of loads.•We modeled the mechanisms assuming all the systems reach the same steady state. Simple monomer binding was the most resistant mechanism to retroactivity.•DB is the mechanism where loads changed the most the SS and FFTF number of molecules.