Synthetic riboswitches for the analysis of tRNA processing by eukaryotic RNase P enzymes.

Removal of the 5'-leader region is an essential step in the maturation of tRNA molecules in all domains of life. This reaction is catalyzed by various RNase P activities, ranging from ribonucleoproteins with ribozyme activity to protein-only forms. In Escherichia coli, the efficiency of RNase P-mediated cleavage can be controlled by computationally designed riboswitch elements in a ligand-dependent way, where the 5'-leader sequence of a tRNA precursor is either sequestered in a hairpin structure or presented as a single-stranded region accessible for maturation. In the presented work, the regulatory potential of such artificial constructs is tested on different forms of eukaryotic RNase P enzymes-two protein-only RNase P enzymes (PRORP1 and PRORP2) from Arabidopsis thaliana and the ribonucleoprotein of Homo sapiens The PRORP enzymes were analyzed in vitro as well as in vivo in a bacterial RNase P complementation system. We also tested in HEK293T cells whether the riboswitches remain functional with human nuclear RNase P. While the regulatory principle of the synthetic riboswitches applies for all tested RNase P enzymes, the results also show differences in the substrate requirements of the individual enzyme versions. Hence, such designed RNase P riboswitches represent a novel tool to investigate the impact of the structural composition of the 5'-leader on substrate recognition by different types of RNase P enzymes.

Ligand-dependent tRNA processing by a rationally designed RNase P riboswitch.

We describe a synthetic riboswitch element that implements a regulatory principle which directly addresses an essential tRNA maturation step. Constructed using a rational in silico design approach, this riboswitch regulates RNase P-catalyzed tRNA 5'-processing by either sequestering or exposing the single-stranded 5'-leader region of the tRNA precursor in response to a ligand. A single base pair in the 5'-leader defines the regulatory potential of the riboswitch both in vitro and in vivo. Our data provide proof for prior postulates on the importance of the structure of the leader region for tRNA maturation. We demonstrate that computational predictions of ligand-dependent structural rearrangements can address individual maturation steps of stable non-coding RNAs, thus making them amenable as promising target for regulatory devices that can be used as functional building blocks in synthetic biology.

Beyond Plug and Pray: Context Sensitivity and in silico Design of Artificial Neomycin Riboswitches.

Gene regulation in prokaryotes often depends on RNA elements such as riboswitches or RNA thermometers located in the 5' untranslated region of mRNA. Rearrangements of the RNA structure in response, e.g., to the binding of small molecules or ions control translational initiation or premature termination of transcription and thus mRNA expression. Such structural responses are amenable to computational modelling, making it possible to rationally design synthetic riboswitches for a given aptamer. Starting from an artificial aptamer, we construct the first synthetic transcriptional riboswitches that respond to the antibiotic neomycin. We show that the switching behaviour in vivo critically depends not only on the sequence of the riboswitch itself, but also on its sequence context. We therefore developed in silico methods to predict the impact of the context, making it possible to adapt the design and to rescue non-functional riboswitches. We furthermore analyse the influence of 5' hairpins with varying stability on neomycin riboswitch activity. Our data highlight the limitations of a simple plug-and-play approach in the design of complex genetic circuits and demonstrate that detailed computational models significantly simplify, improve, and automate the design of transcriptional circuits. Our design software is available under a free licence on GitHub (https://github.com/xileF1337/riboswitch_design).

Evolving methods for rational de novo design of functional RNA molecules.

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.

In silico design of ligand triggered RNA switches.

This contribution sketches a work flow to design an RNA switch that is able to adapt two structural conformations in a ligand-dependent way. A well characterized RNA aptamer, i.e., knowing its Kd and adaptive structural features, is an essential ingredient of the described design process. We exemplify the principles using the well-known theophylline aptamer throughout this work. The aptamer in its ligand-binding competent structure represents one structural conformation of the switch while an alternative fold that disrupts the binding-competent structure forms the other conformation. To keep it simple we do not incorporate any regulatory mechanism to control transcription or translation. We elucidate a commonly used design process by explicitly dissecting and explaining the necessary steps in detail. We developed a novel objective function which specifies the mechanistics of this simple, ligand-triggered riboswitch and describe an extensive in silico analysis pipeline to evaluate important kinetic properties of the designed sequences. This protocol and the developed software can be easily extended or adapted to fit novel design scenarios and thus can serve as a template for future needs.

Applicability of a computational design approach for synthetic riboswitches.

Riboswitches have gained attention as tools for synthetic biology, since they enable researchers to reprogram cells to sense and respond to exogenous molecules. In vitro evolutionary approaches produced numerous RNA aptamers that bind such small ligands, but their conversion into functional riboswitches remains difficult. We previously developed a computational approach for the design of synthetic theophylline riboswitches based on secondary structure prediction. These riboswitches have been constructed to regulate ligand-dependent transcription termination in Escherichia coli. Here, we test the usability of this design strategy by applying the approach to tetracycline and streptomycin aptamers. The resulting tetracycline riboswitches exhibit robust regulatory properties in vivo. Tandem fusions of these riboswitches with theophylline riboswitches represent logic gates responding to two different input signals. In contrast, the conversion of the streptomycin aptamer into functional riboswitches appears to be difficult. Investigations of the underlying aptamer secondary structure revealed differences between in silico prediction and structure probing. We conclude that only aptamers adopting the minimal free energy (MFE) structure are suitable targets for construction of synthetic riboswitches with design approaches based on equilibrium thermodynamics of RNA structures. Further improvements in the design strategy are required to implement aptamer structures not corresponding to the calculated MFE state.

RNAblueprint: flexible multiple target nucleic acid sequence design.

MOTIVATION: Realizing the value of synthetic biology in biotechnology and medicine requires the design of molecules with specialized functions. Due to its close structure to function relationship, and the availability of good structure prediction methods and energy models, RNA is perfectly suited to be synthetically engineered with predefined properties. However, currently available RNA design tools cannot be easily adapted to accommodate new design specifications. Furthermore, complicated sampling and optimization methods are often developed to suit a specific RNA design goal, adding to their inflexibility. RESULTS: We developed a C ++ library implementing a graph coloring approach to stochastically sample sequences compatible with structural and sequence constraints from the typically very large solution space. The approach allows to specify and explore the solution space in a well defined way. Our library also guarantees uniform sampling, which makes optimization runs performant by not only avoiding re-evaluation of already found solutions, but also by raising the probability of finding better solutions for long optimization runs. We show that our software can be combined with any other software package to allow diverse RNA design applications. Scripting interfaces allow the easy adaption of existing code to accommodate new scenarios, making the whole design process very flexible. We implemented example design approaches written in Python to demonstrate these advantages. AVAILABILITY AND IMPLEMENTATION: RNAblueprint , Python implementations and benchmark datasets are available at github: https://github.com/ViennaRNA . CONTACT: s.hammer@univie.ac.at, ivo@tbi.univie.ac.at or sven@tbi.univie.ac.at. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Design of Artificial Riboswitches as Biosensors.

RNA aptamers readily recognize small organic molecules, polypeptides, as well as other nucleic acids in a highly specific manner. Many such aptamers have evolved as parts of regulatory systems in nature. Experimental selection techniques such as SELEX have been very successful in finding artificial aptamers for a wide variety of natural and synthetic ligands. Changes in structure and/or stability of aptamers upon ligand binding can propagate through larger RNA constructs and cause specific structural changes at distal positions. In turn, these may affect transcription, translation, splicing, or binding events. The RNA secondary structure model realistically describes both thermodynamic and kinetic aspects of RNA structure formation and refolding at a single, consistent level of modelling. Thus, this framework allows studying the function of natural riboswitches in silico. Moreover, it enables rationally designing artificial switches, combining essentially arbitrary sensors with a broad choice of read-out systems. Eventually, this approach sets the stage for constructing versatile biosensors.

The primary transcriptome of the major human pathogen Helicobacter pylori.

Genome sequencing of Helicobacter pylori has revealed the potential proteins and genetic diversity of this prevalent human pathogen, yet little is known about its transcriptional organization and noncoding RNA output. Massively parallel cDNA sequencing (RNA-seq) has been revolutionizing global transcriptomic analysis. Here, using a novel differential approach (dRNA-seq) selective for the 5' end of primary transcripts, we present a genome-wide map of H. pylori transcriptional start sites and operons. We discovered hundreds of transcriptional start sites within operons, and opposite to annotated genes, indicating that complexity of gene expression from the small H. pylori genome is increased by uncoupling of polycistrons and by genome-wide antisense transcription. We also discovered an unexpected number of approximately 60 small RNAs including the epsilon-subdivision counterpart of the regulatory 6S RNA and associated RNA products, and potential regulators of cis- and trans-encoded target messenger RNAs. Our approach establishes a paradigm for mapping and annotating the primary transcriptomes of many living species.

Design criteria for synthetic riboswitches acting on transcription.

Riboswitches are RNA-based regulators of gene expression composed of a ligand-sensing aptamer domain followed by an overlapping expression platform. The regulation occurs at either the level of transcription (by formation of terminator or antiterminator structures) or translation (by presentation or sequestering of the ribosomal binding site). Due to a modular composition, these elements can be manipulated by combining different aptamers and expression platforms and therefore represent useful tools to regulate gene expression in synthetic biology. Using computationally designed theophylline-dependent riboswitches we show that 2 parameters, terminator hairpin stability and folding traps, have a major impact on the functionality of the designed constructs. These have to be considered very carefully during design phase. Furthermore, a combination of several copies of individual riboswitches leads to a much improved activation ratio between induced and uninduced gene activity and to a linear dose-dependent increase in reporter gene expression. Such serial arrangements of synthetic riboswitches closely resemble their natural counterparts and may form the basis for simple quantitative read out systems for the detection of specific target molecules in the cell.

De novo design of a synthetic riboswitch that regulates transcription termination.

Riboswitches are regulatory RNA elements typically located in the 5'-untranslated region of certain mRNAs and control gene expression at the level of transcription or translation. These elements consist of a sensor and an adjacent actuator domain. The sensor usually is an aptamer that specifically interacts with a ligand. The actuator contains an intrinsic terminator or a ribosomal binding site for transcriptional or translational regulation, respectively. Ligand binding leads to structural rearrangements of the riboswitch and to presentation or masking of these regulatory elements. Based on this modular organization, riboswitches are an ideal target for constructing synthetic regulatory systems for gene expression. Although riboswitches for translational control have been designed successfully, attempts to construct synthetic elements regulating transcription have failed so far. Here, we present an in silico pipeline for the rational design of synthetic riboswitches that regulate gene expression at the transcriptional level. Using the well-characterized theophylline aptamer as sensor, we designed the actuator part as RNA sequences that can fold into functional intrinsic terminator structures. In the biochemical characterization, several of the designed constructs show ligand-dependent control of gene expression in Escherichia coli, demonstrating that it is possible to engineer riboswitches not only for translational but also for transcriptional regulation.

TSSAR: TSS annotation regime for dRNA-seq data.

BACKGROUND: Differential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular. Hitherto, dRNA-seq data were analyzed by visualizing the sequencing reads mapped to the reference genome and manually annotating reliable positions. This is very labor intensive and, due to the subjectivity, biased. RESULTS: Here, we present TSSAR, a tool for automated de novo TSS annotation from dRNA-seq data that respects the statistics of dRNA-seq libraries. TSSAR uses the premise that the number of sequencing reads starting at a certain genomic position within a transcriptional active region follows a Poisson distribution with a parameter that depends on the local strength of expression. The differences of two dRNA-seq library counts thus follow a Skellam distribution. This provides a statistical basis to identify significantly enriched primary transcripts.We assessed the performance by analyzing a publicly available dRNA-seq data set using TSSAR and two simple approaches that utilize user-defined score cutoffs. We evaluated the power of reproducing the manual TSS annotation. Furthermore, the same data set was used to reproduce 74 experimentally validated TSS in H. pylori from reliable techniques such as RACE or primer extension. Both analyses showed that TSSAR outperforms the static cutoff-dependent approaches. CONCLUSIONS: Having an automated and efficient tool for analyzing dRNA-seq data facilitates the use of the dRNA-seq technique and promotes its application to more sophisticated analysis. For instance, monitoring the plasticity and dynamics of the transcriptomal architecture triggered by different stimuli and growth conditions becomes possible.The main asset of a novel tool for dRNA-seq analysis that reaches out to a broad user community is usability. As such, we provide TSSAR both as intuitive RESTful Web service ( http://rna.tbi.univie.ac.at/TSSAR) together with a set of post-processing and analysis tools, as well as a stand-alone version for use in high-throughput dRNA-seq data analysis pipelines.

Bioinformatics of prokaryotic RNAs.

The genome of most prokaryotes gives rise to surprisingly complex transcriptomes, comprising not only protein-coding mRNAs, often organized as operons, but also harbors dozens or even hundreds of highly structured small regulatory RNAs and unexpectedly large levels of anti-sense transcripts. Comprehensive surveys of prokaryotic transcriptomes and the need to characterize also their non-coding components is heavily dependent on computational methods and workflows, many of which have been developed or at least adapted specifically for the use with bacterial and archaeal data. This review provides an overview on the state-of-the-art of RNA bioinformatics focusing on applications to prokaryotes.

Genome-wide transcriptome analysis of the plant pathogen Xanthomonas identifies sRNAs with putative virulence functions.

The Gram-negative plant-pathogenic bacterium Xanthomonas campestris pv. vesicatoria (Xcv) is an important model to elucidate the mechanisms involved in the interaction with the host. To gain insight into the transcriptome of the Xcv strain 85-10, we took a differential RNA sequencing (dRNA-seq) approach. Using a novel method to automatically generate comprehensive transcription start site (TSS) maps we report 1421 putative TSSs in the Xcv genome. Genes in Xcv exhibit a poorly conserved -10 promoter element and no consensus Shine-Dalgarno sequence. Moreover, 14% of all mRNAs are leaderless and 13% of them have unusually long 5'-UTRs. Northern blot analyses confirmed 16 intergenic small RNAs and seven cis-encoded antisense RNAs in Xcv. Expression of eight intergenic transcripts was controlled by HrpG and HrpX, key regulators of the Xcv type III secretion system. More detailed characterization identified sX12 as a small RNA that controls virulence of Xcv by affecting the interaction of the pathogen and its host plants. The transcriptional landscape of Xcv is unexpectedly complex, featuring abundant antisense transcripts, alternative TSSs and clade-specific small RNAs.

Assessing the Quality of Cotranscriptional Folding Simulations.

Structural changes in RNAs are an important contributor to controlling gene expression not only at the posttranscriptional stage but also during transcription. A subclass of riboswitches and RNA thermometers located in the 5' region of the primary transcript regulates the downstream functional unit - usually an ORF - through premature termination of transcription. Not only such elements occur naturally, but they are also attractive devices in synthetic biology. The possibility to design such riboswitches or RNA thermometers is thus of considerable practical interest. Since these functional RNA elements act already during transcription, it is important to model and understand the dynamics of folding and, in particular, the formation of intermediate structures concurrently with transcription. Cotranscriptional folding simulations are therefore an important step to verify the functionality of design constructs before conducting expensive and labor-intensive wet lab experiments. For RNAs, full-fledged molecular dynamics simulations are far beyond practical reach because of both the size of the molecules and the timescales of interest. Even at the simplified level of secondary structures, further approximations are necessary. The BarMap approach is based on representing the secondary structure landscape for each individual transcription step by a coarse-grained representation that only retains a small set of low-energy local minima and the energy barriers between them. The folding dynamics between two transcriptional elongation steps is modeled as a Markov process on this representation. Maps between pairs of consecutive coarse-grained landscapes make it possible to follow the folding process as it changes in response to transcription elongation. In its original implementation, the BarMap software provides a general framework to investigate RNA folding dynamics on temporally changing landscapes. It is, however, difficult to use in particular for specific scenarios such as cotranscriptional folding. To overcome this limitation, we developed the user-friendly BarMap-QA pipeline described in detail in this contribution. It is illustrated here by an elaborate example that emphasizes the careful monitoring of several quality measures. Using an iterative workflow, a reliable and complete kinetics simulation of a synthetic, transcription-regulating riboswitch is obtained using minimal computational resources. All programs and scripts used in this contribution are free software and available for download as a source distribution for Linux® or as a platform-independent Docker® image including support for Apple macOS® and Microsoft Windows®.

RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data.

With the availability of genome-wide transcription data and massive comparative sequencing, the discrimination of coding from noncoding RNAs and the assessment of coding potential in evolutionarily conserved regions arose as a core analysis task. Here we present RNAcode, a program to detect coding regions in multiple sequence alignments that is optimized for emerging applications not covered by current protein gene-finding software. Our algorithm combines information from nucleotide substitution and gap patterns in a unified framework and also deals with real-life issues such as alignment and sequencing errors. It uses an explicit statistical model with no machine learning component and can therefore be applied "out of the box," without any training, to data from all domains of life. We describe the RNAcode method and apply it in combination with mass spectrometry experiments to predict and confirm seven novel short peptides in Escherichia coli and to analyze the coding potential of RNAs previously annotated as "noncoding." RNAcode is open source software and available for all major platforms at http://wash.github.com/rnacode.

Mapping the RNA-Seq trash bin: unusual transcripts in prokaryotic transcriptome sequencing data.

Prokaryotic transcripts constitute almost always uninterrupted intervals when mapped back to the genome. Split reads, i.e., RNA-seq reads consisting of parts that only map to discontiguous loci, are thus disregarded in most analysis pipelines. There are, however, some well-known exceptions, in particular, tRNA splicing and circularized small RNAs in Archaea as well as self-splicing introns. Here, we reanalyze a series of published RNA-seq data sets, screening them specifically for non-contiguously mapping reads. We recover most of the known cases together with several novel archaeal ncRNAs associated with circularized products. In Eubacteria, only a handful of interesting candidates were obtained beyond a few previously described group I and group II introns. Most of the atypically mapping reads do not appear to correspond to well-defined, specifically processed products. Whether this diffuse background is, at least in part, an incidental by-product of prokaryotic RNA processing or whether it consists entirely of technical artifacts of reverse transcription or amplification remains unknown.

Tailored machine learning models for functional RNA detection in genome-wide screens.

The in silico prediction of non-coding and protein-coding genetic loci has received considerable attention in comparative genomics aiming in particular at the identification of properties of nucleotide sequences that are informative of their biological role in the cell. We present here a software framework for the alignment-based training, evaluation and application of machine learning models with user-defined parameters. Instead of focusing on the one-size-fits-all approach of pervasive in silico annotation pipelines, we offer a framework for the structured generation and evaluation of models based on arbitrary features and input data, focusing on stable and explainable results. Furthermore, we showcase the usage of our software package in a full-genome screen of Drosophila melanogaster and evaluate our results against the well-known but much less flexible program RNAz.

RNA Design Principles for Riboswitches that Regulate RNase P-Mediated tRNA Processing.

Riboswitches are an attractive target for the directed design of RNA-based regulators by in silico prediction. These noncoding RNA elements consist of an aptamer platform for the highly selective ligand recognition and an expression platform which controls gene activity typically at the level of transcription or translation. In previous work, we could successfully apply RNA folding prediction to implement a new riboswitch mechanism regulating processing of a tRNA by RNase P. In this contribution, we present detailed information about our pipeline consisting of in silico design combined with the biochemical analysis for the verification of the implemented mechanism. Furthermore, we discuss the applicability of the presented biochemical in vivo and in vitro methods for the characterization of other artificial riboswitches.

Proteinortho: detection of (co-)orthologs in large-scale analysis.

BACKGROUND: Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. RESULTS: The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. CONCLUSIONS: Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.