Thermodynamic Modelling of Transcriptional Control: A Sensitivity Analysis
Metadata
Show full item recordEditorial
MDPI
Materia
Gene regulation Transcriptional control Statistical thermodynamic modelling Sensitivity analysis Elasticity function
Date
2022-06-22Referencia bibliográfica
Cambón, M.; Sánchez, Ó. Thermodynamic Modelling of Transcriptional Control: A Sensitivity Analysis. Mathematics 2022, 10, 2169. [https://doi.org/10.3390/math10132169]
Sponsorship
MINECO-Feder (Spanish Government) FPI2015/074837 RTI2018-098850-B-100; Consejeria de Economia, Innovacion, Ciencia y Empleo, Junta de Andalucia (Andalucia Government) PY18-RT-2422; Junta de Andalucia A-FQM-311-UGR18 B-FQM-580-UGR20Abstract
Modelling is a tool used to decipher the biochemical mechanisms involved in transcriptional
control. Experimental evidence in genetics is usually supported by theoretical models in order
to evaluate the effects of all the possible interactions that can occur in these complicated processes.
Models derived from the thermodynamic method are critical in this labour because they are able
to take into account multiple mechanisms operating simultaneously at the molecular micro-scale
and relate them to transcriptional initiation at the tissular macro-scale. This work is devoted to
adapting computational techniques to this context in order to theoretically evaluate the role played
by several biochemical mechanisms. The interest of this theoretical analysis relies on the fact that
it can be contrasted against those biological experiments where the response to perturbations in
the transcriptional machinery environment is evaluated in terms of genetically activated/repressed
regions. The theoretical reproduction of these experiments leads to a sensitivity analysis whose results
are expressed in terms of the elasticity of a threshold function determining those activated/repressed
regions. The study of this elasticity function in thermodynamic models already proposed in the
literature reveals that certain modelling approaches can alter the balance between the biochemical
mechanisms considered, and this can cause false/misleading outcomes. The reevaluation of
classical thermodynamic models gives us a more accurate and complete picture of the interactions
involved in gene regulation and transcriptional control, which enables more specific predictions. This
sensitivity approach provides a definite advantage in the interpretation of a wide range of genetic
experimental results.