Thermodynamic analysis of 5' and 3' single- and 3' double-nucleotide overhangs neighboring wobble terminal base pairs

microRNAs Biogenesis, Functions and Role in Tumor Angiogenesis

microRNAs (miRNAs) are small non-coding RNA molecules, evolutionary conserved. They target more than one mRNAs, thus influencing multiple molecular pathways, but also mRNAs may bind to a variety of miRNAs, either simultaneously or in a context-dependent manner. miRNAs biogenesis, including miRNA transcription, processing by Drosha and Dicer, transportation, RISC biding, and miRNA decay, are finely controlled in space and time. miRNAs are critical regulators in various biological processes, such as differentiation, proliferation, apoptosis, and development in both health and disease. Their dysregulation is involved in tumor initiation and progression. In tumors, they can act as onco-miRNAs or oncosuppressor-miRNA participating in distinct cellular pathways, and the same miRNA can perform both activities depending on the context. In tumor progression, the angiogenic switch is fundamental. miRNAs derived from tumor cells, endothelial cells, and cells of the surrounding microenvironment regulate tumor angiogenesis, acting as pro-angiomiR or anti-angiomiR. In this review, we described miRNA biogenesis and function, and we update the non-classical aspects of them. The most recent role in the nucleus, as transcriptional gene regulators and the different mechanisms by which they could be dysregulated, in tumor initiation and progression, are treated. In particular, we describe the role of miRNAs in sprouting angiogenesis, vessel co-option, and vasculogenic mimicry. The role of miRNAs in lymphoma angiogenesis is also discussed despite the scarcity of data. The information presented in this review reveals the need to do much more to discover the complete miRNA network regulating angiogenesis, not only using high-throughput computational analysis approaches but also morphological ones.

microRNA strand selection: Unwinding the rules

microRNAs (miRNAs) play a central role in the regulation of gene expression by targeting specific mRNAs for degradation or translational repression. Each miRNA is post‐transcriptionally processed into a duplex comprising two strands. One of the two miRNA strands is selectively loaded into an Argonaute protein to form the miRNA‐Induced Silencing Complex (miRISC) in a process referred to as miRNA strand selection. The other strand is ejected from the complex and is subject to degradation. The target gene specificity of miRISC is determined by sequence complementarity between the Argonaute‐loaded miRNA strand and target mRNA. Each strand of the miRNA duplex has the capacity to be loaded into miRISC and possesses a unique seed sequence. Therefore, miRNA strand selection plays a defining role in dictating the specificity of miRISC toward its targets and provides a mechanism to alter gene expression in a switch‐like fashion. Aberrant strand selection can lead to altered gene regulation by miRISC and is observed in several human diseases including cancer. Previous and emerging data shape the rules governing miRNA strand selection and shed light on how these rules can be circumvented in various physiological and pathological contexts.

This article is categorized under:

RNA Processing > Processing of Small RNAs

Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs

Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs

Analysis of RNA nearest neighbor parameters reveals interdependencies and quantifies the uncertainty in RNA secondary structure prediction

RNA secondary structure prediction is often used to develop hypotheses about structure-function relationships for newly discovered RNA sequences, to identify unknown functional RNAs, and to design sequences. Secondary structure prediction methods typically use a thermodynamic model that estimates the free energy change of possible structures based on a set of nearest neighbor parameters. These parameters were derived from optical melting experiments of small model oligonucleotides. This work aims to better understand the precision of structure prediction. Here, the experimental errors in optical melting experiments were propagated to errors in the derived nearest neighbor parameter values and then to errors in RNA secondary structure prediction. To perform this analysis, the optical melting experimental values were systematically perturbed within the estimates of experimental error and alternative sets of nearest neighbor parameters were then derived from these error-bounded values. Secondary structure predictions using either the perturbed or reference parameter sets were then compared. This work demonstrated that the precision of RNA secondary structure prediction is more robust than suggested by previous work based on perturbation of the nearest neighbor parameters. This robustness is due to correlations between parameters. Additionally, this work identified weaknesses in the parameter derivation that makes accurate assessment of parameter uncertainty difficult. Considerations for experimental design are provided to mitigate these weaknesses are provided.

Native characterization of nucleic acid motif thermodynamics via non-covalent catalysis

DNA hybridization thermodynamics is critical for accurate design of oligonucleotides for biotechnology and nanotechnology applications, but parameters currently in use are inaccurately extrapolated based on limited quantitative understanding of thermal behaviours. Here, we present a method to measure the ΔG° of DNA motifs at temperatures and buffer conditions of interest, with significantly better accuracy (6- to 14-fold lower s.e.) than prior methods. The equilibrium constant of a reaction with thermodynamics closely approximating that of a desired motif is numerically calculated from directly observed reactant and product equilibrium concentrations; a DNA catalyst is designed to accelerate equilibration. We measured the ΔG° of terminal fluorophores, single-nucleotide dangles and multinucleotide dangles, in temperatures ranging from 10 to 45 °C.

DNA hybridisation thermodynamics parameters underlie rational design of oligonucleotides for diagnostics and nanotechnology. Here, the authors present an accurate method to measure the free energy of a given DNA structure at specific temperature and buffer conditions.

Regulation of miRNA strand selection: follow the leader?

miRNA strand selection is the process that determines which of the two strands in a miRNA duplex becomes the active strand that is incorporated into the RISC (RNA-induced silencing complex) (named the guide strand, leading strand or miR) and which one gets degraded (the passenger strand or miR*). Thermodynamic features of the duplex appear to play an important role in this decision; the strand with the weakest binding at its 5′-end is more likely to become the guide strand. Other key characteristics of human miRNA guide strands are a U-bias at the 5′-end and an excess of purines, whereas the passenger strands have a C-bias at the 5′-end and an excess of pyrimidines. Several proteins are known to play a role in strand selection [Ago (Argonaute), DICER, TRBP (trans-activation response RNA-binding protein), PACT (protein activator of dsRNA-dependent protein kinase) and Xrn-1/2]; however, the mechanisms by which these proteins act are largely unknown. For several miRNAs the miR/miR* ratio varies dependent on cell type, developmental stage and in different disease states, suggesting that strand selection is a tightly controlled process. The present review discusses our current knowledge regarding the factors and processes involved in strand selection and the many questions that still remain.

The determination of RNA folding nearest neighbor parameters

The stability of RNA secondary structure can be predicted using a set of nearest neighbor parameters. These parameters are widely used by algorithms that predict secondary structure. This contribution introduces the UV optical melting experiments that are used to determine the folding stability of short RNA strands. It explains how the nearest neighbor parameters are chosen and how the values are fit to the data. A sample nearest neighbor calculation is provided. The contribution concludes with new methods that use the database of sequences with known structures to determine parameter values.

Influence of 8-oxoguanosine on the fine structure of DNA studied with biasing-potential replica exchange simulations

Chemical modification or radiation can cause DNA damage, which plays a crucial role for mutagenesis of DNA, carcinogenesis, and aging. DNA damage can also alter the fine structure of DNA that may serve as a recognition signal for DNA repair enzymes. A new, advanced sampling replica-exchange method has been developed to specifically enhance the sampling of conformational substates in duplex DNA during molecular dynamics (MD) simulations. The approach employs specific biasing potentials acting on pairs of pseudodihedral angles of the nucleic acid backbone that are added in the replica simulations to promote transitions of the most common substates of the DNA backbone. The sampled states can exchange with a reference simulation under the control of the original force field. The application to 7,8-dihydro-8oxo-guanosine, one of the most common oxidative damage in DNA indicated better convergence of sampled states during 10 ns simulations compared to 20 times longer standard MD simulations. It is well suited to study systematically the fine structure and dynamics of large nucleic acids under realistic conditions, including explicit solvent and ions. The biasing potential-replica exchange MD simulations indicated significant differences in the population of nucleic acid backbone substates in the case of 7,8-dihydro-8oxo-guanosine compared to a regular guanosine in the same sequence context. This concerns both the ratio of the B-DNA substates B(I) and B(II) associated with the backbone dihedral angles ε and ζ but also coupled changes in the backbone dihedral angles α and γ. Such differences may play a crucial role in the initial recognition of damaged DNA by repair enzymes.

MicroRNA biogenesis and variability

MicroRNAs (miRNAs) are cell-endogenous small noncoding RNAs that, through RNA interference, are involved in the posttranscriptional regulation of mRNAs. The biogenesis and function of miRNAs entail multiple elements with different alternative pathways. These confer a high versatility of regulation and a high variability to generate different miRNAs and hence possess a broad potential to regulate gene expression. Here we review the different mechanisms, both canonical and noncanonical, that generate miRNAs in animals. The ‘miRNome’ panorama enhances our knowledge regarding the fine regulation of gene expression and provides new insights concerning normal, as opposed to pathological, cell differentiation and development.

A 5'-cap for DNA probes binding RNA target strands

Detecting short RNA strands with high fidelity at any of the bases of their sequence, including the termini, can be challenging, since fraying, wobbling, and refolding all compete with canonical base pairing. We performed a search for 5'-substituents of oligodeoxynucleotides that increase base pairing fidelity at the terminus of duplexes with RNA target strands. From a total of over 70 caps, differing in stacking moiety and linker, a phosphodiester-linked sequence of the residues of L-prolinol, glycine, and oxolinic acid, dubbed ogOA, was identified as a 5'-cap that stabilizes any of the four canonical base pairs, with ΔT(m) values of up to +13.1 °C for an octamer. At the same time, the cap increases discrimination against any of the 12 possible terminal mismatches, including mismatches that are more stable than their perfectly matched counterparts in the control duplex, such as A:A. A probe with the cap also showed increased selectivity in the detection of two closely related microRNAs, let7c and let7a, with a ΔT(m) value of 9.2 °C. Melting curves also yielded thermodynamic data that shed light on the uniformity of molecular recognition in the sequence space of DNA:DNA and DNA:RNA duplexes. Hybridization probes with fidelity-enhancing caps should find applications in the individual and parallel detection of biologically active RNA species.

The ribosome binding site calculator

The Ribosome Binding Site (RBS) Calculator is a design method for predicting and controlling translation initiation and protein expression in bacteria. The method can predict the rate of translation initiation for every start codon in an mRNA transcript. The method may also optimize a synthetic RBS sequence to achieve a targeted translation initiation rate. Using the RBS Calculator, a protein coding sequence's translation rate may be rationally controlled across a 100,000+ fold range. We begin by providing an overview of the potential biotechnology applications of the RBS Calculator, including the optimization of synthetic metabolic pathways and genetic circuits. We then detail the definitions, methodologies, and algorithms behind the RBS Calculator's thermodynamic model and optimization method. Finally, we outline a protocol for precisely measuring steady-state fluorescent protein expression levels. These methods and protocols provide a clear explanation of the RBS Calculator and its uses.

Complexity of the microRNA repertoire revealed by next-generation sequencing

MicroRNAs (miRNAs) have been implicated to play key roles in normal physiological functions, and altered expression of specific miRNAs has been associated with a number of diseases. It is of great interest to understand their roles and a prerequisite for such study is the ability to comprehensively and accurately assess the levels of the entire repertoire of miRNAs in a given sample. It has been shown that some miRNAs frequently have sequence variations termed isomirs. To better understand the extent of miRNA sequence heterogeneity and its potential implications for miRNA function and measurement, we conducted a comprehensive survey of miRNA sequence variations from human and mouse samples using next generation sequencing platforms. Our results suggest that the process of generating this isomir spectrum might not be random and that heterogeneity at the ends of miRNA affects the consistency and accuracy of miRNA level measurement. In addition, we have constructed a database from our sequencing data that catalogs the entire repertoire of miRNA sequences (http://galas.systemsbiology.net/cgi-bin/isomir/find.pl). This enables users to determine the most abundant sequence and the degree of heterogeneity for each individual miRNA species. This information will be useful both to better understand the functions of isomirs and to improve probe or primer design for miRNA detection and measurement.

Binding of short oligonucleotides to RNA: studies of the binding of common RNA structural motifs to isoenergetic microarrays

Binding of short oligonucleotides to RNA is important for many biological processes. On the basis of RNAi phenomena, antisense, and ribozyme approaches, it is useful in the inhibition of biological functions. To be considered as potential therapeutics, oligonucleotides must bind strongly and selectively to a complementary fragment of target RNA. Microarray technologies also involve the binding of oligonucleotide probes to DNA or RNA. Herein, the hybridization of common structural motifs of RNA, i.e., hairpins, internal loops, bulges, 3'- and 5'-dangling ends, and pseudoknots to isoenergetic microarray probes is presented. The analysis demonstrates that microarray probes bind to bulges, internal loops, and dangling ends as expected. Probes may also bind to terminal helixes, however, possibly due to the rearrangement of base pairs. These results suggest that isoenergetic microarray mapping can provide data to facilitate and improve RNA secondary structure prediction. However, optimal results require combination with chemical and/or enzymatic mapping.

Optical melting measurements of nucleic acid thermodynamics

Optical melting experiments provide measurements of thermodynamic parameters for nucleic acids. These thermodynamic parameters are widely used in RNA structure prediction programs and DNA primer design software. This review briefly summarizes the theory and underlying assumptions of the method and provides practical details for instrument calibration, experimental design, and data interpretation.

Automated design of synthetic ribosome binding sites to control protein expression

Microbial engineering often requires fine control over protein expression; for example, to connect genetic circuits 1-7 or control flux through a metabolic pathway 8-13. We have developed a predictive design method for synthetic ribosome binding sites that enables the rational control of a protein's production rate on a proportional scale. Experimental validation of over 100 predictions in Escherichia coli shows that the method is accurate to within a factor of 2.3 over a range of 100,000-fold. The design method also correctly predicts that reusing a ribosome binding site sequence in different genetic contexts can result in different protein expression levels. We demonstrate the method's utility by rationally optimizing a protein's expression level to connect a genetic sensor to a synthetic circuit. The proposed forward engineering approach will accelerate the construction and systematic optimization of large genetic systems.

Automated design of synthetic ribosome binding sites to control protein expression

Microbial engineering often requires fine control over protein expression--for example, to connect genetic circuits or control flux through a metabolic pathway. To circumvent the need for trial and error optimization, we developed a predictive method for designing synthetic ribosome binding sites, enabling a rational control over the protein expression level. Experimental validation of >100 predictions in Escherichia coli showed that the method is accurate to within a factor of 2.3 over a range of 100,000-fold. The design method also correctly predicted that reusing identical ribosome binding site sequences in different genetic contexts can result in different protein expression levels. We demonstrate the method's utility by rationally optimizing protein expression to connect a genetic sensor to a synthetic circuit. The proposed forward engineering approach should accelerate the construction and systematic optimization of large genetic systems.