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1.  Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’ 
Nature  2010;469(7329):212-215.
Computation underlies the organization of cells into higher-order structures, for example during development or the spatial association of bacteria in a biofilm1–3. Each cell performs a simple computational operation, but when combined with cell–cell communication, intricate patterns emerge. Here we study this process by combining a simple genetic circuit with quorum sensing to produce more complex computations in space. We construct a simple NOR logic gate in Escherichia coli by arranging two tandem promoters that function as inputs to drive the transcription of a repressor. The repressor inactivates a promoter that serves as the output. Individual colonies of E. coli carry the same NOR gate, but the inputs and outputs are wired to different orthogonal quorum-sensing ‘sender’ and ‘receiver’ devices4,5. The quorum molecules form the wires between gates. By arranging the colonies in different spatial configurations, all possible two-input gates are produced, including the difficult XOR and EQUALS functions. The response is strong and robust, with 5- to >300-fold changes between the ‘on’ and ‘off’ states. This work helps elucidate the design rules by which simple logic can be harnessed to produce diverse and complex calculations by rewiring communication between cells.
PMCID: PMC3904220  PMID: 21150903
2.  Non-transcriptional regulatory processes shape transcriptional network dynamics 
Nature reviews. Microbiology  2011;9(11):817-828.
Information about the extra- or intracellular environment is often captured as biochemical signals propagating through regulatory networks. These signals eventually drive phenotypic changes, typically by altering gene expression programs in the cell. Reconstruction of transcriptional regulatory networks has given a compelling picture of bacterial physiology, but transcriptional network maps alone often fail to describe phenotypes. In many cases, the dynamical performance of transcriptional regulatory networks depends on post-transcriptional or post-translational regulation and pleiotropic effects. Cellular response dynamics are ultimately determined by interactions between transcriptional and non-transcriptional networks with dramatic implications for physiology and evolution. Here, we provide an overview of non-transcriptional interactions that can affect the performance of natural and synthetic bacterial regulatory networks.
PMCID: PMC3755963  PMID: 21986901
3.  Multichromatic control of gene expression in Escherichia coli 
Journal of molecular biology  2010;405(2):315-324.
Light is a powerful tool for manipulating living cells because it can be applied with high resolution across space and over time. We previously constructed a red-light sensitive E. coli transcription system based on a chimera between the red/far red switchable cyanobacterial phytochrome Cph1 and the E. coli EnvZ/OmpR two-component signaling pathways. Here we report the development of a green light inducible transcription system in E. coli based on a recently discovered green/red photoswitchable two-component system from cyanobacteria. We demonstrate that transcriptional output is proportional to the intensity of green light applied and that the green sensor is orthogonal to the red sensor at intensities of 532nm light less than 0.01W/m2. Expression of both sensors in a single cell allows two-color optical control of transcription in both batch culture and in patterns across a lawn of engineered cells. Because each sensor functions as a photoreversible switch, this system should allow the spatial and temporal control of the expression of multiple genes though different combinations of light wavelengths. This feature should aid precision single cell and population-level studies in systems and synthetic biology.
PMCID: PMC3053042  PMID: 21035461
Light-regulated promoter; synthetic biology; two-component system; phytochrome; cyanobacteriochrome
4.  A Synthetic Genetic Edge Detection Program 
Cell  2009;137(7):1272-1281.
Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E.coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.
PMCID: PMC2775486  PMID: 19563759
5.  Engineering Stochasticity in Gene Expression 
Molecular bioSystems  2008;4(7):754-761.
Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that engineering exogenous genetic elements can significantly affect the natural noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise.
PMCID: PMC2630191  PMID: 18563250
stochasticity; mRNA; ribosome; ribosome binding site; operon
6.  Deoxyribozymes that recode sequence information 
Nucleic Acids Research  2006;34(8):2166-2172.
Allosteric nucleic acid ligases have been used previously to transform analyte-binding into the formation of oligonucleotide templates that can be amplified and detected. We have engineered binary deoxyribozyme ligases whose two components are brought together by bridging oligonucleotide effectors. The engineered ligases can ‘read’ one sequence and then ‘write’ (by ligation) a separate, distinct sequence, which can in turn be uniquely amplified. The binary deoxyribozymes show great specificity, can discriminate against a small number of mutations in the effector, and can read and recode DNA information with high fidelity even in the presence of excess obscuring genomic DNA. In addition, the binary deoxyribozymes can read non-natural nucleotides and write natural sequence information. The binary deoxyribozyme ligases could potentially be used in a variety of applications, including the detection of single nucleotide polymorphisms in genomic DNA or the identification of short nucleic acids such as microRNAs.
PMCID: PMC1450334  PMID: 16648360

Results 1-6 (6)