Academic literature on the topic 'Vibrio. luxR'

Information exchange between cellular compartments allows us to engineer systems based around cooperative principles. In this chapter we consider a unique bacterial communication system, the conjugative plasmid transfer of Enterococcus faecalis. Using these bacteria, we describe how to engineer a logically controlled information gate and build a logical inverter based upon it. Cellular computing is an alternative computing paradigm based on living cells. Microscale organisms, especially bacteria, are well suited for computing for several reasons. A small culture provides an almost limitless supply of bacterial “hardware.” Bacteria can be stored and easily modified by gene recombination. In addition, and important for our purposes, bacteria can produce various signal molecules that are useful for computation. DNA-binding proteins recognize specific regulatory regions of DNA, bind them, and regulate their genetic expression. These proteins are available for use as computing signals inside the cell. Weiss et al. have shown, for example, how to construct logic circuits based on gene expression regulated by DNA-binding proteins. Some signal molecules are associated with intercellular communications between individuals. Intercellular communication is one of the fundamental characteristics of multicellular organisms, but it is also found in single-celled microorganisms, including bacteria. Communication mediated by homoserine lactones can widely be seen in various Gram-negative bacteria. The mechanism of this behavior was well characterized in Vibrio fischeri, due to their bioluminescent activity mediated by homoserine lactones. It has been shown that bacterial information transfer can be engineered as an extension of Escherichia coli into which the lux genes of Vibrio fischeri are transformed. The communication abilities of bacteria therefore allow us to build microbial information processors for cellular computing. Communication mechanisms in Gram-positive bacteria are not yet well understood. One of the exceptions to this is the conjugative plasmid transfer system in Enterococcus faecalis. E. faecalis conjugate in response to a pheromone is released by other cells. Pheromones are seven- or eight-residue amino peptides produced in E. faecalis. In the case of cPD1, the pheromone is produced by truncation of a 22-residue precursor that is the signal peptide of a lipoprotein.

In this chapter we 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. We have built and characterized an initial cellular gate library with biochemical gates that implement the NOT, IMPLIES, andANDlogic 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. We 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. This chapter is structured as follows: the first section describes experimental measurements of the device physics of in vivo logic gates, as well as genetic process engineering to modify gates until they have the desired behavior. The second section presents experimental results of programmed intercellular communications, including time–response measurements and sensitivity to variations in message concentrations. Potentially the most important element of biocircuit design is matching gate characteristics. Experimental results in this section demonstrate that circuits with mismatched gates are likely to malfunction. In generating biology’s complex genetic regulatory networks, natural forces of selection have resulted in finely tuned interconnections between the different regulatory components. Nature has optimized and matched the kinetic characteristics of these elements so that they cooperatively achieve the desired regulatory behavior. In building de novo biocircuits, we frequently combine regulatory elements that do not interact in their wild-type settings. Therefore, naive coupling of these elements will likely produce systems that do not have the desired behavior. In genetic process engineering, the biocircuit designer first determines the behavioral characteristics of the regulatory components and then modifies the elements until the desired behavior is attained. Below, we show experimental results of using this process to convert a nonfunctional circuit with mismatched gates into a circuit that achieves the correct response.