Open AccessImpact of negative feedback in metabolic noise propagation
Author(s) -
Borri Alessandro,
Palumbo Pasquale,
Singh Abhyudai
Publication year - 2016
Publication title -
iet systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.367
H-Index - 50
eISSN - 1751-8857
pISSN - 1751-8849
DOI - 10.1049/iet-syb.2016.0003
Subject(s) - feedback control , noise (video) , synthetic biology , negative feedback , sensitivity (control systems) , replicate , computer science , positive feedback , product (mathematics) , computation , control theory (sociology) , parameter space , systems biology , biological system , control (management) , electronic engineering , control engineering , mathematics , engineering , biology , computational biology , artificial intelligence , algorithm , statistics , geometry , electrical engineering , voltage , image (mathematics)
Synthetic biology combines different branches of biology and engineering aimed at designing synthetic biological circuits able to replicate emergent properties useful for the biotechnology industry, human health and environment. The role of negative feedback in noise propagation for a basic enzymatic reaction scheme is investigated. Two feedback control schemes on enzyme expression are considered: one from the final product of the pathway activity, the other from the enzyme accumulation. Both schemes are designed to provide the same steady‐state average values of the involved players, in order to evaluate the feedback performances according to the same working mode. Computations are carried out numerically and analytically, the latter allowing to infer information on which model parameter setting leads to a more efficient noise attenuation, according to the chosen scheme. In addition to highlighting the role of the feedback in providing a substantial noise reduction, our investigation concludes that the effect of feedback is enhanced by increasing the promoter sensitivity for both schemes. A further interesting biological insight is that an increase in the promoter sensitivity provides more benefits to the feedback from the product with respect to the feedback from the enzyme, in terms of enlarging the parameter design space.