Model‐guided design of ligand‐regulated RNAi for programmable control of gene expression

Progress in constructing biological networks will rely on the development of more advanced components that can be predictably modified to yield optimal system performance. We have engineered an RNA‐based platform, which we call an shRNA switch, that provides for integrated ligand control of RNA interference (RNAi) by modular coupling of an aptamer, competing strand, and small hairpin (sh)RNA stem into a single component that links ligand concentration and target gene expression levels. A combined experimental and mathematical modelling approach identified multiple tuning strategies and moves towards a predictable framework for the forward design of shRNA switches. The utility of our platform is highlighted by the demonstration of fine‐tuning, multi‐input control, and model‐guided design of shRNA switches with an optimized dynamic range. Thus, shRNA switches can serve as an advanced component for the construction of complex biological systems and offer a controlled means of activating RNAi in disease therapeutics.     

Design of simple synthetic RNA thermometers for temperature-controlled gene expression in Escherichia coli

RNA thermometers are thermosensors that regulate gene expression by temperature-induced changes in RNA conformation. Naturally occurring RNA thermometers exhibit complex secondary structures which are believed to undergo a series of gradual structural changes in response to temperature shifts. Here, we report the de novo design of considerably simpler RNA thermometers that provide useful RNA-only tools to regulate bacterial gene expression by a shift in the growth temperature. We show that a single small stem-loop structure containing the ribosome binding site is sufficient to construct synthetic RNA thermometers that work efficiently at physiological temperatures. Our data suggest that the thermometers function by a simple melting mechanism and thus provide minimum size on/off switches to experimentally induce or repress gene expression by temperature.     

Inducible Gene Targeting in Mice Using the Cre/loxSystem

Molecular techniques now allow the design of precise genetic modifications in the mouse. Not only can defined nucleotide changes be engineered into the genome of the mouse, but genetic switches can be designed to target expression or ablation of any gene (for which basic molecular information is available) to any tissue at any defined time. These strategies promise to contribute substantially to an increased understanding of individual gene function in development and pathogenesis. A powerful tool, both for the design of such genetic switches and for speeding the creation of gene-modified animals, is the Cre site-specific DNA recombinase of bacteriophage P1. Precise DNA rearrangements and genetic switches can be efficiently generated in a straightforward manner using Cre recombinase. In conjunction with inducible systems for controlling Cre expression and function, these recombination-based strategies are likely to have a profound impact on developmental biology and the generation of useful animal models of human disease.     

“Toehold Switches; a foothold for Synthetic Biology”

Toehold switches are de novo designed riboregulators that contain two RNA components interacting through linear-linear RNA interactions, regulating the gene expression. These are highly versatile, exhibit excellent orthogonality, wide dynamic range, and are highly programmable, so can be used for various applications in synthetic biology. In this review, we summarized and discussed the design characteristics and benefits of toehold switch riboregulators over conventional riboregulators. We also discussed applications and recent advancements of toehold switch riboregulators in various fields like gene editing, DNA nanotechnology, translational repression, and diagnostics (detection of microRNAs and some pathogens). Toehold switches, therefore, furnished advancement in synthetic biology applications in various fields with their prominent features.     

Single nucleotide RNA choreography

New structural analysis methods, and a tree formalism re-define and expand the RNA motif concept, unifying what previously appeared to be disparate groups of structures. We find RNA tetraloops at high frequencies, in new contexts, with unexpected lengths, and in novel topologies. The results, with broad implications for RNA structure in general, show that even at this most elementary level of organization, RNA tolerates astounding variation in conformation, length, sequence and context. However the variation is not random; it is well-described by four distinct modes, which are 3-2 switches (backbone topology variations), insertions, deletions and strand clips.     

A computational method for the investigation of multistable systems and its application to genetic switches

Background

Genetic switches exhibit multistability, form the basis of epigenetic memory, and are found in natural decision making systems, such as cell fate determination in developmental pathways. Synthetic genetic switches can be used for recording the presence of different environmental signals, for changing phenotype using synthetic inputs and as building blocks for higher-level sequential logic circuits. Understanding how multistable switches can be constructed and how they function within larger biological systems is therefore key to synthetic biology.

Results

Here we present a new computational tool, called StabilityFinder, that takes advantage of sequential Monte Carlo methods to identify regions of parameter space capable of producing multistable behaviour, while handling uncertainty in biochemical rate constants and initial conditions. The algorithm works by clustering trajectories in phase space, and iteratively minimizing a distance metric. Here we examine a collection of models of genetic switches, ranging from the deterministic Gardner toggle switch to stochastic models containing different positive feedback connections. We uncover the design principles behind making bistable, tristable and quadristable switches, and find that rate of gene expression is a key parameter. We demonstrate the ability of the framework to examine more complex systems and examine the design principles of a three gene switch. Our framework allows us to relax the assumptions that are often used in genetic switch models and we show that more complex abstractions are still capable of multistable behaviour.

Conclusions

Our results suggest many ways in which genetic switches can be enhanced and offer designs for the construction of novel switches. Our analysis also highlights subtle changes in correlation of experimentally tunable parameters that can lead to bifurcations in deterministic and stochastic systems. Overall we demonstrate that StabilityFinder will be a valuable tool in the future design and construction of novel gene networks.

     

Structural features in TAR RNA of human and simian immunodeficiency viruses: a phylogenetic analysis.

A comparative analysis of TAR RNA structures in human and simian immunodeficiency viruses reveals the conservation of certain structural features despite the divergence in sequence. Both the TAR elements of HIV-1 and SIV-chimpanzee can be folded into relatively simple one-stem hairpin structures. Chemical and RNAase probes were used to analyze the more complex structure of HIV-2 TAR RNA, which folds into a branched hairpin structure. A surprisingly similar RNA conformation can be proposed for SIV-mandrill, despite considerable divergence in nucleotide sequence. A third structural presentation of TAR sequences is seen for SIV-african green monkey. These results are generally consistent with the classification of HIV-SIV viruses in four subgroups based on sequence analyses (both nucleotide- and amino acid-sequences). However, some conserved TAR structures were detected for members of different virus subgroups. It is therefore proposed that RNA structure analysis might provide an additional tool for determining phylogenetic relationships among the HIV-SIV viruses.     

Inducible suppression of Fgfr2 and Survivin in ES cells using a combination of the RNA interference (RNAi) and the Cre-LoxP system

RNA interference (RNAi) is a simple and powerful tool widely used for studying gene function in a number of species. Recently, inducible regulation of RNAi in mammalian cells using either tetracycline- or ecdysone-responsive systems has been developed to prevent potential lethality or non-physiological responses associated with persistent suppression of genes that are essential for cell survival or cell cycle progression. Here we show that the inducible regulation of RNAi also can be achieved by using a Cre-LoxP approach. We demonstrate that the insertion of a loxP-flanked neomycin cassette into RNA polymerase III promoter, which controls a vector-based RNAi unit, impairs the promoter activity. However, the expression of RNAi construct can be completely restored upon the removal of the neo cassette using a tamoxifen inducible Cre construct. We show that this system works with high efficiency in suppression of two endogenous genes, Fgfr2 and Survivin, in mouse embryonic stem (ES) cells, as evidenced by the decrease of levels of gene expression, reduced cell proliferation and colony formation. This system provides a potentially important yet simple approach to establish mutant mouse strains for functional study at defined stages upon turning on the inducible switches controlled by the Cre-LoxP system.     

Inducible suppression of Fgfr2 and Survivin in ES cells using a combination of the RNA interference (RNAi) and the Cre–LoxP system

RNA interference (RNAi) is a simple and powerful tool widely used for studying gene function in a number of species. Recently, inducible regulation of RNAi in mammalian cells using either tetracycline- or ecdysone-responsive systems has been developed to prevent potential lethality or non-physiological responses associated with persistent suppression of genes that are essential for cell survival or cell cycle progression. Here we show that the inducible regulation of RNAi also can be achieved by using a Cre–LoxP approach. We demonstrate that the insertion of a loxP-flanked neomycin cassette into RNA polymerase III promoter, which controls a vector-based RNAi unit, impairs the promoter activity. However, the expression of RNAi construct can be completely restored upon the removal of the neo cassette using a tamoxifen inducible Cre construct. We show that this system works with high efficiency in suppression of two endogenous genes, Fgfr2 and Survivin, in mouse embryonic stem (ES) cells, as evidenced by the decrease of levels of gene expression, reduced cell proliferation and colony formation. This system provides a potentially important yet simple approach to establish mutant mouse strains for functional study at defined stages upon turning on the inducible switches controlled by the Cre–LoxP system.     

RNA pseudoknot prediction in energy-based models.

RNA molecules are sequences of nucleotides that serve as more than mere intermediaries between DNA and proteins, e.g., as catalytic molecules. Computational prediction of RNA secondary structure is among the few structure prediction problems that can be solved satisfactorily in polynomial time. Most work has been done to predict structures that do not contain pseudoknots. Allowing pseudoknots introduces modeling and computational problems. In this paper we consider the problem of predicting RNA secondary structures with pseudoknots based on free energy minimization. We first give a brief comparison of energy-based methods for predicting RNA secondary structures with pseudoknots. We then prove that the general problem of predicting RNA secondary structures containing pseudoknots is NP complete for a large class of reasonable models of pseudoknots.     

Simultaneous characterization of cellular RNA structure and function with in-cell SHAPE-Seq

Many non-coding RNAs form structures that interact with cellular machinery to control gene expression. A central goal of molecular and synthetic biology is to uncover design principles linking RNA structure to function to understand and engineer this relationship. Here we report a simple, high-throughput method called in-cell SHAPE-Seq that combines in-cell probing of RNA structure with a measurement of gene expression to simultaneously characterize RNA structure and function in bacterial cells. We use in-cell SHAPE-Seq to study the structure–function relationship of two RNA mechanisms that regulate translation in Escherichia coli. We find that nucleotides that participate in RNA–RNA interactions are highly accessible when their binding partner is absent and that changes in RNA structure due to RNA–RNA interactions can be quantitatively correlated to changes in gene expression. We also characterize the cellular structures of three endogenously expressed non-coding RNAs: 5S rRNA, RNase P and the btuB riboswitch. Finally, a comparison between in-cell and in vitro folded RNA structures revealed remarkable similarities for synthetic RNAs, but significant differences for RNAs that participate in complex cellular interactions. Thus, in-cell SHAPE-Seq represents an easily approachable tool for biologists and engineers to uncover relationships between sequence, structure and function of RNAs in the cell.     

In vitro selections with RNAs of variable length converge on a robust catalytic core

In vitro selection is a powerful tool that can be used to understand basic principles of molecular evolution. We used in vitro selection to understand how changes in length and the accumulation of point mutations enable the evolution of functional RNAs. Using RNA populations of various lengths, we performed a series of in vitro experiments to select for ribozymes with RNA ligase activity. We identified a core ribozyme structure that was robust to changes in RNA length, high levels of mutagenesis, and increased selection pressure. Elaboration on this core structure resulted in improved activity which we show is consistent with a larger trend among functional RNAs in which increasing motif size can lead to an exponential improvement in fitness. We conclude that elaboration on conserved core structures is a preferred mechanism in RNA evolution. This conclusion, drawn from selections of RNAs from random sequences, is consistent with proposed evolutionary histories of specific biological RNAs. More generally, our results indicate that modern RNA structures can be used to infer ancestral structures. Our observations also suggest a mechanism by which structural outcomes of early RNA evolution would be largely reproducible even though RNA fitness landscapes consist of disconnected clusters of functional sequences.     

Generating new ligand-binding RNAs by affinity maturation and disintegration of allosteric ribozymes

Allosteric ribozymes are engineered RNAs that operate as molecular switches whose rates of catalytic activity are modulated by the binding of specific effector molecules. New RNA molecular switches can be created by using "allosteric selection," a molecular engineering process that combines modular rational design and in vitro evolution strategies. In this report, we describe the characterization of 3',5'-cyclic nucleotide monophosphate (cNMP)-dependent hammerhead ribozymes that were created using allosteric selection (Koizumi et al., Nat Struct Biol, 1999, 6:1062-1071). Artificial phylogeny data generated by random mutagenesis and reselection of existing cGMP-, cCMP-, and cAMP-dependent ribozymes indicate that each is comprised of distinct effector-binding and catalytic domains. In addition, patterns of nucleotide covariation and direct mutational analysis both support distinct secondary-structure organizations for the effector-binding domains. Guided by these structural models, we were able to disintegrate each allosteric ribozyme into separate ligand-binding and catalytic modules. Examinations of the independent effector-binding domains reveal that each retains its corresponding cNMP-binding function. These results validate the use of allosteric selection and modular engineering as a means of simultaneously generating new nucleic acid structures that selectively bind ligands. Furthermore, we demonstrate that the binding affinity of an allosteric ribozyme can be improved through random mutagenesis and allosteric selection under conditions that favor tighter binding. This "affinity maturation" effect is expected to be a valuable attribute of allosteric selection as future endeavors seek to apply engineered allosteric ribozymes as biosensor components and as controllable genetic switches.     

RNAapt3D: RNA aptamer 3D-structural modeling database

RNA aptamers are oligonucleotides with high binding affinity and specificity for target molecules and are expected to be a new generation of therapeutic molecules and targeted delivery materials. The tertiary structure of RNA molecules and RNA-protein interaction sites are increasingly important as potential targets for new drugs. The pathological mechanisms of diseases must be understood in detail to guide drug design. In developing RNA aptamers as drugs, information about the interaction mechanisms and structures of RNA aptamer-target protein complexes are useful. We constructed a database, RNA aptamer 3D-structural modeling (RNAapt3D), consisting of RNA aptamer data that are potential drug candidates. The database includes RNA sequences and computationally predicted RNA tertiary structures based on secondary structures and implements methods that can be used to predict unknown structures of RNA aptamer-target molecule complexes. RNAapt3D should enable the design of RNA aptamers for target molecules and improve the efficiency and productivity of candidate drug selection. RNAapt3D can be accessed at https://rnaapt3d.medals.jp.     

3dRNAscore: a distance and torsion angle dependent evaluation function of 3D RNA structures

Model evaluation is a necessary step for better prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statistical potentials have also been proposed to evaluate predicted models of RNA tertiary structures. The benchmark tests showed that they can identify the native structures effectively but further improvements are needed to identify near-native structures and those with non-canonical base pairs. Here, we present a novel knowledge-based potential, 3dRNAscore, which combines distance-dependent and dihedral-dependent energies. The benchmarks on different testing datasets all show that 3dRNAscore are more efficient than existing evaluation methods in recognizing native state from a pool of near-native states of RNAs as well as in ranking near-native states of RNA models.