Autism-related deficits via dysregulated eIF4E-dependent translational control.

Hyperconnectivity of neuronal circuits due to increased synaptic protein synthesis is thought to cause autism spectrum disorders (ASDs). The mammalian target of rapamycin (mTOR) is strongly implicated in ASDs by means of upstream signalling; however, downstream regulatory mechanisms are ill-defined. Here we show that knockout of the eukaryotic translation initiation factor 4E-binding protein 2 (4E-BP2)-an eIF4E repressor downstream of mTOR-or eIF4E overexpression leads to increased translation of neuroligins, which are postsynaptic proteins that are causally linked to ASDs. Mice that have the gene encoding 4E-BP2 (Eif4ebp2) knocked out exhibit an increased ratio of excitatory to inhibitory synaptic inputs and autistic-like behaviours (that is, social interaction deficits, altered communication and repetitive/stereotyped behaviours). Pharmacological inhibition of eIF4E activity or normalization of neuroligin 1, but not neuroligin 2, protein levels restores the normal excitation/inhibition ratio and rectifies the social behaviour deficits. Thus, translational control by eIF4E regulates the synthesis of neuroligins, maintaining the excitation-to-inhibition balance, and its dysregulation engenders ASD-like phenotypes.

Structural dynamics control the MicroRNA maturation pathway.

MicroRNAs (miRNAs) are crucial gene expression regulators and first-order suspects in the development and progression of many diseases. Comparative analysis of cancer cell expression data highlights many deregulated miRNAs. Low expression of miR-125a was related to poor breast cancer prognosis. Interestingly, a single nucleotide polymorphism (SNP) in miR-125a was located within a minor allele expressed by breast cancer patients. The SNP is not predicted to affect the ground state structure of the primary transcript or precursor, but neither the precursor nor mature product is detected by RT-qPCR. How this SNP modulates the maturation of miR-125a is poorly understood. Here, building upon a model of RNA dynamics derived from nuclear magnetic resonance studies, we developed a quantitative model enabling the visualization and comparison of networks of transient structures. We observed a high correlation between the distances between networks of variants with that of their respective wild types and their relative degrees of maturation to the latter, suggesting an important role of transient structures in miRNA homeostasis. We classified the human miRNAs according to pairwise distances between their networks of transient structures.

MiRBooking simulates the stoichiometric mode of action of microRNAs.

In eucaryotes, gene expression is regulated by microRNAs (miRNAs) which bind to messenger RNAs (mRNAs) and interfere with their translation into proteins, either by promoting their degradation or inducing their repression. We study the effect of miRNA interference on each gene using experimental methods, such as microarrays and RNA-seq at the mRNA level, or luciferase reporter assays and variations of SILAC at the protein level. Alternatively, computational predictions would provide clear benefits. However, no algorithm toward this task has ever been proposed. Here, we introduce a new algorithm to predict genome-wide expression data from initial transcriptome abundance. The algorithm simulates the miRNA and mRNA hybridization competition that occurs in given cellular conditions, and derives the whole set of miRNA::mRNA interactions at equilibrium (microtargetome). Interestingly, solving the competition improves the accuracy of miRNA target predictions. Furthermore, this model implements a previously reported and fundamental property of the microtargetome: the binding between a miRNA and a mRNA depends on their sequence complementarity, but also on the abundance of all RNAs expressed in the cell, i.e. the stoichiometry of all the miRNA sites and all the miRNAs given their respective abundance. This model generalizes the miRNA-induced synchronistic silencing previously observed, and described as sponges and competitive endogenous RNAs.

RNA G-Quadruplexes in the model plant species Arabidopsis thaliana: prevalence and possible functional roles.

Tandem stretches of guanines can associate in hydrogen-bonded arrays to form G-quadruplexes, which are stabilized by K(+) ions. Using computational methods, we searched for G-Quadruplex Sequence (GQS) patterns in the model plant species Arabidopsis thaliana. We found ∼ 1200 GQS with a G(3) repeat sequence motif, most of which are located in the intergenic region. Using a Markov modeled genome, we determined that GQS are significantly underrepresented in the genome. Additionally, we found ∼ 43,000 GQS with a G(2) repeat sequence motif; notably, 80% of these were located in genic regions, suggesting that these sequences may fold at the RNA level. Gene Ontology functional analysis revealed that GQS are overrepresented in genes encoding proteins of certain functional categories, including enzyme activity. Conversely, GQS are underrepresented in other categories of genes, notably those for non-coding RNAs such as tRNAs and rRNAs. We also find that genes that are differentially regulated by drought are significantly more likely to contain a GQS. CD-detected K(+) titrations performed on representative RNAs verified formation of quadruplexes at physiological K(+) concentrations. Overall, this study indicates that GQS are present at unique locations in Arabidopsis and that folding of RNA GQS may play important roles in regulating gene expression.

Structural messenger RNA contains cytokeratin polymerization and depolymerization signals.

We have previously shown that VegT mRNA plays a structural (translation-independent) role in the organization of the cytokeratin cytoskeleton in Xenopus oocytes. The depletion of VegT mRNA causes the fragmentation of the cytokeratin network in the vegetal cortex of Xenopus oocytes. This effect can be rescued by the injection of synthetic VegT RNA into the oocyte. Here, we show that the structural function of VegT mRNA in Xenopus oocyte depends on its combinatory signals for the induction or facilitation and for the maintenance of the depolymerization vs. polymerization status of cytokeratin filaments and that the 300-nucleotide fragment of VegT RNA isolated from the context of the entire molecule induces and maintains the depolymerization of cytokeratin filaments when injected into Xenopus oocytes. A computational analysis of three homologous Xenopus VegT mRNAs has revealed the presence, within this 300-nucleotide region, of a conserved base-pairing (hairpin) configuration that might function in RNA/protein interactions.

Comprehensive Signaling Profiles Reveal Unsuspected Functional Selectivity of δ-Opioid Receptor Agonists and Allow the Identification of Ligands with the Greatest Potential for Inducing Cyclase Superactivation.

Prolonged exposure to opioid receptor agonists triggers adaptations in the adenylyl cyclase (AC) pathway that lead to enhanced production of cyclic adenosine monophosphate (cAMP) upon withdrawal. This cellular phenomenon contributes to withdrawal symptoms, hyperalgesia and analgesic tolerance that interfere with clinical management of chronic pain syndromes. Since δ-opioid receptors (DOPrs) are a promising target for chronic pain management, we were interested in finding out if cell-based signaling profiles as generated for drug discovery purposes could inform us of the ligand potential to induce sensitization of the cyclase path. For this purpose, signaling of DOPr agonists was monitored at multiple effectors. The resulting signaling profiles revealed marked functional selectivity, particularly for Met-enkephalin (Met-ENK) whose signaling bias profile differed from those of synthetic ligands like SNC-80 and ARM390. Signaling diversity among ligands was systematized by clustering agonists according to similarities in E max and Log(τ) values for the different responses. The classification process revealed that the similarity in Gα/Gßγ, but not in ß-arrestin (ßarr), responses was correlated with the potential of Met-ENK, deltorphin II, (d-penicillamine2,5)-enkephalin (DPDPE), ARM390, and SNC-80 to enhance cAMP production, all of which required Ca2+ mobilization to produce this response. Moreover, superactivation by Met-ENK, which was the most-effective Ca2+ mobilizing agonist, required Gαi/o activation, availability of Gßγ subunits at the membrane, and activation of Ca2+ effectors such as calmodulin and protein kinase C (PKC). In contrast, superactivation by (N-(l-tyrosyl)-(3S)-1,2,3,4-tetrahydroisoquinoline-3-carbonyl)-l-phenylalanyl-l-phenylalanine (TIPP), which was set in a distinct category through clustering, required activation of Gαi/o subunits but was independent of the Gßγ dimer and Ca2+ mobilization, relying instead on Src and Raf-1 to induce this cellular adaptation.

Author Correction: Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Exploring use of unsupervised clustering to associate signaling profiles of GPCR ligands to clinical response.

Signaling diversity of G protein-coupled (GPCR) ligands provides novel opportunities to develop more effective, better-tolerated therapeutics. Taking advantage of these opportunities requires identifying which effectors should be specifically activated or avoided so as to promote desired clinical responses and avoid side effects. However, identifying signaling profiles that support desired clinical outcomes remains challenging. This study describes signaling diversity of mu opioid receptor (MOR) ligands in terms of logistic and operational parameters for ten different in vitro readouts. It then uses unsupervised clustering of curve parameters to: classify MOR ligands according to similarities in type and magnitude of response, associate resulting ligand categories with frequency of undesired events reported to the pharmacovigilance program of the Food and Drug Administration and associate signals to side effects. The ability of the classification method to associate specific in vitro signaling profiles to clinically relevant responses was corroborated using ß2-adrenergic receptor ligands.

Analyzing biased responses of GPCR ligands.

G protein-coupled receptors (GPCRs) are valuable targets for drug discovery. They exist in interconverting states differentially stabilized by diverse signaling partners. A ligand's capacity to distinguish among receptors associated with different partners is the basis of bias. This feature of GPCR signaling may allow development of ligands which specifically modulate effectors supporting desired actions. However, bias is time-dependent and cell-dependent such that in vitro bias may not predict bias displayed in vivo. Then again, certain signaling idiosyncrasies transcend these limitations and emerging signaling characteristics may be used to categorize ligands in terms of the signaling diversity, which is the other face of bias. Here, we discuss how time and cellular background influence magnitude/directionality of bias, and highlight approaches to categorize ligands according to signaling diversity.

Exploring Alternative RNA Structure Sets Using MC-Flashfold and db2cm.

We created an accelerated version of MC-Fold called MC-Flashfold that allows us to compute large numbers of competing secondary structures including noncanonical base pairs. We visualize the base pairs in these sets using high quality intuitive dot plots and arc plots. Our new tools allow us to explore RNA dynamics by visualizing the competing structures in free energy bands. Here we describe how to use these tools to generate dot plots that reveal the postulated anti-terminator stem in the E. coli trp operon leader sequence. These plots show the anti-terminator hairpin loop during transcription and as a minor population of the full-length leader sequence. This is a case of switching RNA structure that had been originally postulated based on short dyad inverted repeats. Other switching RNA sequences can be analyzed by using our method.