Cellular computation and communications using engineered genetic regulatory networks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 130-138).In this thesis, I present an engineering discipline for obtaining complex, predictable, and reliable cell behaviors by embedding biochemical logic circuits and programmed intercellular communications into cells. To accomplish this goal, I provide a well-characterized component library, a biocircuit design methodology, and software design tools. I have built and characterized an initial cellular gate library with biochemical gates that implement the NOT, IMPLIES, and AND logic functions in E. coli cells. The logic gates perform computation using DNA-binding proteins, small molecules that interact with these proteins, and segments of DNA that regulate the expression of the proteins. I introduce genetic process engineering, a methodology for modifying the DNA encoding of existing genetic elements to achieve the desired input/output behavior for constructing reliable circuits of significant complexity. I demonstrate the feasibility of digital computation in cells by building several operational in-vivo digital logic circuits, each composed of three gates that have been optimized by genetic process engineering.(cont.) I also demonstrate engineered intercellular communications with programmed enzymatic activity and chemical diffusions to carry messages, using DNA from the Vibrio fischeri lux operon. The programmed communications is essential for obtaining coordinated behavior from cell aggregates. In addition to the above experimental contributions, I have developed BioSPICE, a prototype software tool for biocircuit design. It supports both static and dynamic simulations and analysis of single cell environments and small cell aggregates. Finally, I present the Microbial Colony Language (MCL), a model for programming cell aggregates. The language is expressive enough for interesting applications, yet relies on simple primitives that can be mapped to the engineered biological processes described above.by Ron Weiss.Ph.D

Biological Peer-to-Peer Networks: From Bacterial Communication to the Development of Synthetic Distributed Systems

Poster presented at the ESC-EBSCO Conference: Biology of plastids: Towards a blueprint for synthetic organelles which took place in 2014 June 21-23, in Pultusk (POLAND). The Web Site of the event: http://bioplastids.esf.org/This communication was supported by a European Science Foundation gran

Modelización de Sistemas de Computación Distribuida con Bacterias Sintéticas mediante Autómatas Celulares

La conjugación es un sistema de comunicación distribuido que permite los intercambios de información genética entre bacterias. Este mecanismo peer-to-peer permite a las bacterias compartir estrategias de supervivencia implementadas en plásmidos de ADN. El presente trabajo se centra en la modelización de las dinámicas de conjugación mediante el uso de un autómata celular asíncrono y pretende servir como una aproximación formal y una herramienta de validación conceptual dentro del ámbito de la biología sintética. Este modelo se ha centrado en un caso de uso específico, una colonia heterogénea de bacterias modificadas genéticamente para discriminar plásmidos en base a la afinidad de los promotores y factores de transcripción de dos conjuntos de partida.Conjugation is a distributed communication system which allows exchanges of genetic information among bacteria. This peer-to-peer mechanism allows bacteria to share survival strategies implemented in DNA plasmids. This paper focuses on the modeling of conjugation dynamics by using asynchronous cellular automata. It intends to serve in the field of synthetic biology as a formal approach and a conceptual validation tool. This model has been focused on a specific use case, a heterogeneous colony of engineered bacteria that discriminate plasmids by evaluating affinity among pairs of promoters and transcription factors