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Ribozyme-based insulator parts buffer synthetic circuits from genetic context.

ABSTRACT: Synthetic genetic programs are built from circuits that integrate sensors and implement temporal control of gene expression. Transcriptional circuits are layered by using promoters to carry the signal between circuits. In other words, the output promoter of one circuit serves as the input promoter to the next. Thus, connecting circuits requires physically connecting a promoter to the next circuit. We show that the sequence at the junction between the input promoter and circuit can affect the input-output response (transfer function) of the circuit. A library of putative sequences that might reduce (or buffer) such context effects, which we refer to as 'insulator parts', is screened in Escherichia coli. We find that ribozymes that cleave the 5' untranslated region (5'-UTR) of the mRNA are effective insulators. They generate quantitatively identical transfer functions, irrespective of the identity of the input promoter. When these insulators are used to join synthetic gene circuits, the behavior of layered circuits can be predicted using a mathematical model. The inclusion of insulators will be critical in reliably permuting circuits to build different programs.

SUBMITTER: Lou C

PROVIDER: S-EPMC3914141 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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Ribozyme-based insulator parts buffer synthetic circuits from genetic context.

Lou Chunbo C Stanton Brynne B Chen Ying-Ja YJ Munsky Brian B Voigt Christopher A CA

Nature biotechnology 20121003 11

Synthetic genetic programs are built from circuits that integrate sensors and implement temporal control of gene expression. Transcriptional circuits are layered by using promoters to carry the signal between circuits. In other words, the output promoter of one circuit serves as the input promoter to the next. Thus, connecting circuits requires physically connecting a promoter to the next circuit. We show that the sequence at the junction between the input promoter and circuit can affect the inp ...[more]

PMID: 23034349

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Project description:For practical construction of complex synthetic genetic networks able to perform elaborate functions it is important to have a pool of relatively simple modules with different functionality which can be compounded together. To complement engineering of very different existing synthetic genetic devices such as switches, oscillators or logical gates, we propose and develop here a design of synthetic multi-input classifier based on a recently introduced distributed classifier concept. A heterogeneous population of cells acts as a single classifier, whose output is obtained by summarizing the outputs of individual cells. The learning ability is achieved by pruning the population, instead of tuning parameters of an individual cell. The present paper is focused on evaluating two possible schemes of multi-input gene classifier circuits. We demonstrate their suitability for implementing a multi-input distributed classifier capable of separating data which are inseparable for single-input classifiers, and characterize performance of the classifiers by analytical and numerical results. The simpler scheme implements a linear classifier in a single cell and is targeted at separable classification problems with simple class borders. A hard learning strategy is used to train a distributed classifier by removing from the population any cell answering incorrectly to at least one training example. The other scheme implements a circuit with a bell-shaped response in a single cell to allow potentially arbitrary shape of the classification border in the input space of a distributed classifier. Inseparable classification problems are addressed using soft learning strategy, characterized by probabilistic decision to keep or discard a cell at each training iteration. We expect that our classifier design contributes to the development of robust and predictable synthetic biosensors, which have the potential to affect applications in a lot of fields, including that of medicine and industry.

Dataset Information

Ribozyme-based insulator parts buffer synthetic circuits from genetic context.

Publications

Ribozyme-based insulator parts buffer synthetic circuits from genetic context.

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