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1.  DEAD-Box Helicase Proteins Disrupt RNA Tertiary Structure Through Helix Capture 
PLoS Biology  2014;12(10):e1001981.
Single-molecule fluorescence experiments reveal how DEAD-box proteins unfold structured RNAs to promote conformational transitions and refolding to the native functional state.
DEAD-box helicase proteins accelerate folding and rearrangements of highly structured RNAs and RNA–protein complexes (RNPs) in many essential cellular processes. Although DEAD-box proteins have been shown to use ATP to unwind short RNA helices, it is not known how they disrupt RNA tertiary structure. Here, we use single molecule fluorescence to show that the DEAD-box protein CYT-19 disrupts tertiary structure in a group I intron using a helix capture mechanism. CYT-19 binds to a helix within the structured RNA only after the helix spontaneously loses its tertiary contacts, and then CYT-19 uses ATP to unwind the helix, liberating the product strands. Ded1, a multifunctional yeast DEAD-box protein, gives analogous results with small but reproducible differences that may reflect its in vivo roles. The requirement for spontaneous dynamics likely targets DEAD-box proteins toward less stable RNA structures, which are likely to experience greater dynamic fluctuations, and provides a satisfying explanation for previous correlations between RNA stability and CYT-19 unfolding efficiency. Biologically, the ability to sense RNA stability probably biases DEAD-box proteins to act preferentially on less stable misfolded structures and thereby to promote native folding while minimizing spurious interactions with stable, natively folded RNAs. In addition, this straightforward mechanism for RNA remodeling does not require any specific structural environment of the helicase core and is likely to be relevant for DEAD-box proteins that promote RNA rearrangements of RNP complexes including the spliceosome and ribosome.
Author Summary
In addition to carrying genetic information from DNA to protein, RNAs function in many essential cellular processes. This often requires the RNA to form a specific three-dimensional structure, and some functions require cycling between multiple structures. However, RNAs have a strong propensity to become trapped in nonfunctional, misfolded structures. Due to the intrinsic stability of local structure for RNA, these misfolded species can be long-lived and therefore accumulate. ATP-dependent RNA chaperone proteins called DEAD-box proteins are known to promote native RNA folding by disrupting misfolded structures. Although these proteins can unwind short RNA helices, the mechanism by which they act upon higher order tertiary contacts is unknown. Our current work shows that DEAD-box proteins capture transiently exposed RNA helices, preventing any tertiary contacts from reforming and potentially destabilizing the global RNA architecture. Helix unwinding by the DEAD-box protein then allows the product RNA strands to form new contacts. This helix capture mechanism for manipulation of RNA tertiary structure does not require a specific binding motif or structural environment and may be general for DEAD-box helicase proteins that act on structured RNAs.
PMCID: PMC4211656  PMID: 25350280
2.  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
3.  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

Results 1-3 (3)