Title :
Tuning receiver characteristics in bacterial quorum communication: An evolutionary approach using standard virtual biological parts
Author :
Hallinan, J.S. ; Gilfellon, O. ; Misirli, G. ; Wipat, A.
Author_Institution :
Sch. of Comput. Sci., Newcastle Univ., Newcastle upon Tyne, UK
Abstract :
Populations of bacteria acting in collaboration can produce complex behaviors which are not achievable by individual cells. There has, consequently, been considerable interest in the engineering of bacterial populations. Here we describe an approach for the engineering of aspects of bacterial quorum communication, using Standard Virtual Parts, a synthetic biology programming language, dubbed SVPWrite, and an evolutionary algorithm. We apply this system to engineering the output characteristics of the subtilin receiver system of Bacillus subtilis. Simple modifications, such as altering the strength of the output response to a subtilin input, are easily achieved. More complex adaptations, such as modifying the shape of the receiver response curve, necessitate alterations to the topology of the regulatory network. More generally, the use of Standard Virtual Parts and a programming language allow circuit design, simulation and evaluation to easily be automated, permitting exploration of a far larger proportion of design space than would be possible using standard manual design approaches.
Keywords :
biology computing; cellular biophysics; evolutionary computation; learning (artificial intelligence); microorganisms; programming languages; Bacillus subtilis; bacterial populations; bacterial quorum communication; circuit design; complex adaptations; complex behaviors; design space proportion; dubbed SVPWrite; evolutionary algorithm; individual cells; receiver response curve; regulatory network; standard manual design approaches; standard virtual parts; subtilin input; subtilin receiver system; synthetic biology programming language; tuning receiver characteristics; Biological system modeling; Computational modeling; Genetics; Integrated circuit modeling; Microorganisms; Receivers; Standards; Design automation; Evolutionary computation; Machine learning; Synthetic biology;
Conference_Titel :
Computational Intelligence in Bioinformatics and Computational Biology, 2014 IEEE Conference on
Conference_Location :
Honolulu, HI
DOI :
10.1109/CIBCB.2014.6845520