Synthesis of orthogonal transcription-translation networks

An, Wenlin; Chin, Jason W.

doi:10.1073/pnas.0900267106

Cited by 119 publications

(100 citation statements)

References 33 publications

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“…Using our techniques for quantifying sources of variation to analyze models whose parameters have been fitted to experimental data, for example, provides such an alternative approach. More generally, advances in synthetic biology that aim to create biochemistry "orthogonal" to the endogenous biochemistry may make suitably conjugate reporters commonplace (38).…”

Section: Discussionmentioning

confidence: 99%

Identifying sources of variation and the flow of information in biochemical networks

Bowsher

Swain

2012

Proc. Natl. Acad. Sci. U.S.A.

136

170

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To understand how cells control and exploit biochemical fluctuations, we must identify the sources of stochasticity, quantify their effects, and distinguish informative variation from confounding "noise." We present an analysis that allows fluctuations of biochemical networks to be decomposed into multiple components, gives conditions for the design of experimental reporters to measure all components, and provides a technique to predict the magnitude of these components from models. Further, we identify a particular component of variation that can be used to quantify the efficacy of information flow through a biochemical network. By applying our approach to osmosensing in yeast, we can predict the probability of the different osmotic conditions experienced by wildtype yeast and show that the majority of variation can be informational if we include variation generated in response to the cellular environment. Our results are fundamental to quantifying sources of variation and thus are a means to understand biological "design."analysis of variance | internal history | gene expression | signal transduction | intrinsic and extrinsic noise C ells must make decisions in fluctuating environments using stochastic biochemistry. Such effects create variation between isogenic cells, which despite sometimes being disadvantageous for individuals may be advantageous for populations (1). Although the random occurrence and timing of chemical reactions are the primary intracellular source, we do not know how much different biochemical processes contribute to the observed heterogeneity (2). It is neither clear how fluctuations in one cellular process will affect variation in another nor how an experimental assay could be designed to quantify this effect. Further, we cannot distinguish variation that is extraneous "noise" from that generated by the flow of information within and between biochemical networks. We will show that a general technique to decompose fluctuations into their constituent parts provides a solution to these problems.Previous work divided variation in gene expression in isogenic populations into two components (3, 4): intrinsic and extrinsic variation. Both components necessarily include a variety of biochemical processes yet dissecting the effects of these processes has previously not been possible. Intrinsic variation should be understood as the average "variability" in gene expression between two copies of the same gene under identical intracellular conditions (4); extrinsic variation is the additional variation generated by interaction with other stochastic systems in the cell and the cell's environment. Single-cell experiments established that stochasticity generated during gene expression can be substantial in both bacteria (3, 5) and eukaryotes (6, 7), but did not identify the biochemical processes that generate this variation, regardless of whether the variation is intrinsic or extrinsic. Decomposing Variation in Biochemical SystemsConsider a fluctuating molecular species in a biochemical system and let ...

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Section: Discussionmentioning

confidence: 99%

Identifying sources of variation and the flow of information in biochemical networks

Bowsher

Swain

2012

Proc. Natl. Acad. Sci. U.S.A.

136

170

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“…As far as translational resources are concerned, orthogonal ribosomes (O-ribosomes) have been proposed as a mechanism to decouple translation of endogenous mRNA from translation of the mRNA of synthetic circuits [64,65]. O-ribosomes specifically translate their cognate O-mRNA, which is not recognized by endogenous ribosomes.…”

Section: Modularity Of Functional Modules: the E↵ects Of Resource Shamentioning

confidence: 99%

Modularity, context-dependence, and insulation in engineered biological circuits

Vecchio¹

2015

Trends in Biotechnology

121

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Abstract. The ability of linking systems together such that they behave as predicted once interacting with each other is an essential requirement for the forward engineering of robust synthetic biological circuits. Unfortunately, because of context dependencies, parts and functional modules often behave unpredictably once interacting in the cellular environment. In this paper, we review some recent advances toward establishing a rigorous engineering framework for insulating parts and modules from their context to improve modularity. Overall, a synergy between engineering better parts and higher-level circuit design that overcome the physical limitations of available parts will be important to resolve the problem of context dependence. Modularity and context-dependence in engineered biological systemsSynthetic biology, that is, the use of molecular biology techniques to forward engineer cellular behavior, is a rising branch of biological research [1]. One aim of the field is to gather a better understanding of natural systems by re-wiring their subsystems and exporting them to new settings. The ability of re-designing living systems has especially potential in the biotechnology industry, promising a number of breakthroughs in human health and the environment. Designing living systems does not simply relay on the engineering of parts, such as proteins or genetic sequences. In contrast, it essentially requires the ability of linking parts together to create sophisticated functionalities. Linking parts together to achieve a predictable behavior is 1

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“…THE HYPE Cells can simply be rewired system in E. coli that is separate from the cell's built-in system 7 . To transcribe DNA into RNA, the team uses a polymerase enzyme that recognizes genes only if they have a specific promoter sequence that is not present in the cell's natural genes.…”

Section: Slim Films H Campbellmentioning

confidence: 99%