1st International ICST Conference on Bio Inspired Models of Network, Information and Computing Systems

Research Article

Towards in vivo computing: quantitative analysis of an artificial gene regulatory network behaving as a RS flip-flop and simulating the system in silico

  • @INPROCEEDINGS{10.1145/1315843.1315850,
        author={Sikander  Hayat and Kai  Ostermann and Lutz  Brusch and Wolfgang  Pompe and Gerhard R\o{}del},
        title={Towards in vivo computing: quantitative analysis of an artificial gene regulatory network behaving as a RS flip-flop and simulating the system in silico},
        proceedings={1st International ICST Conference on Bio Inspired Models of Network, Information and Computing Systems},
        publisher={ACM},
        proceedings_a={BIONETICS},
        year={2006},
        month={12},
        keywords={in vivo computing toggle switch RS flip-flop quorum sensing artificial gene regulatory networks NP-hard problems flow cytometry},
        doi={10.1145/1315843.1315850}
    }
    
  • Sikander Hayat
    Kai Ostermann
    Lutz Brusch
    Wolfgang Pompe
    Gerhard Rödel
    Year: 2006
    Towards in vivo computing: quantitative analysis of an artificial gene regulatory network behaving as a RS flip-flop and simulating the system in silico
    BIONETICS
    ACM
    DOI: 10.1145/1315843.1315850
Sikander Hayat1, Kai Ostermann1, Lutz Brusch1, Wolfgang Pompe1, Gerhard Rödel1
  • 1: Institut für Genetik, Institut für Werkstoffwissenschaft, Zentrum für Informationsdienste und Hochleistungsrechnen (ZIH), Technische Universität Dresden, 01062 Dresden, Germany

Abstract

Artificial gene regulatory networks (AGRNs) are instrumental in elucidating basic principles that govern the dynamics and consequences of stochasticity in the gene expression of naturally occurring "gene regulatory networks". In contrast to state of the art computer engineering circuits, these AGRNs are evolutionarily highly optimized and fault tolerant. We draw motivation from the fact that Non-deterministic Polynomial-time (NP) and NP-hard computational tasks can not be solved using conventional computing techniques. This study is a stepping stone towards solving problems such as "Traveling salesman problem" (TSP) in a time bound fashion using interconnection-free bio-computing devices. In this in vivo study we quantitatively show that a reporter gene encoding the green fluorescent protein (GFP) can be switched from high to low expression states and vice versa, thus mimicking a "RS flip-flop". This was accomplished by using the bistable, transgenic AGRN incorporating the N-acyl homoserine lactone (AHL) sensing lux operon from Vibrio fischeri along with a toggle switch in Escherichia coli, developed by Collins et al. (2004). The inducers and temperature act as inputs to the AGRN. GFP expression was quantified using flow cytometry. The "plug and play" property was demonstrated by showing that any output gene could be expressed based on a similar logic. The software model, previously proposed by Collins et al. (2004) was extended and analyzed by incorporating the function of the inducer Isopropyl-β-D-thiogalactopyranoside (IPTG) and temperature. We also demonstrate that such a system is robust and fault tolerant.