Open AccessMulti‐bit Boolean model for chemotactic drift of Escherichia coli
Author(s) -
Deshpande Anuj,
Samanta Sibendu,
Govindarajan Sutharsan,
Layek Ritwik Kumar
Publication year - 2020
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.2020.0060
Subject(s) - chemotaxis , biological system , modular design , escherichia coli , computer science , steady state (chemistry) , exponential function , algorithm , mathematics , biology , chemistry , mathematical analysis , biochemistry , receptor , gene , operating system
Dynamic biological systems can be modelled to an equivalent modular structure using Boolean networks (BNs) due to their simple construction and relative ease of integration. The chemotaxis network of the bacterium Escherichia coli ( E. coli ) is one of the most investigated biological systems. In this study, the authors developed a multi‐bit Boolean approach to model the drifting behaviour of the E. coli chemotaxis system. Their approach, which is slightly different than the conventional BNs, is designed to provide finer resolution to mimic high‐level functional behaviour. Using this approach, they simulated the transient and steady‐state responses of the chemoreceptor sensory module. Furthermore, they estimated the drift velocity under conditions of the exponential nutrient gradient. Their predictions on chemotactic drifting are in good agreement with the experimental measurements under similar input conditions. Taken together, by simulating chemotactic drifting, they propose that multi‐bit Boolean methodology can be used for modelling complex biological networks. Application of the method towards designing bio‐inspired systems such as nano‐bots is discussed.