In higher eukaryotes, tRNAs with the same anticodon are encoded by multiple nuclear genes and little is known about how mutations in these genes affect translation and cellular homeostasis. Similarly, the surveillance systems that respond to such defects in higher eukaryotes are not clear. Here, we discover that loss of GTPBP2, a novel binding partner of the ribosome recycling protein Pelota, in mice with a mutation in a tRNA gene that is specifically expressed in the central nervous system causes ribosome stalling and widespread neurodegeneration. Our results not only define GTPBP2 as a ribosome rescue factor, but also unmask the disease potential of mutations in nuclear-encoded tRNA genes.

Ribosome stalling during translation has recently been shown to cause neurodegeneration, yet the signaling pathways triggered by stalled elongation complexes are unknown. To investigate these pathways we analyzed the brain of C57BL/6J-Gtpbp2nmf205-/- mice in which neuronal elongation complexes are stalled at AGA codons due to deficiencies in a tRNAArgUCU tRNA and GTPBP2, a mammalian ribosome rescue factor. Increased levels of phosphorylation of eIF2α (Ser51) were detected prior to neurodegeneration in these mice and transcriptome analysis demonstrated activation of ATF4, a key transcription factor in the integrated stress response (ISR) pathway. Genetic experiments showed that this pathway was activated by the eIF2α kinase, GCN2, in an apparent deacylated tRNA-independent fashion. Further we found that the ISR attenuates neurodegeneration in C57BL/6J-Gtpbp2nmf205-/- mice, underscoring the importance of cellular and stress context on the outcome of activation of this pathway. These results demonstrate the critical interplay between translation elongation and initiation in regulating neuron survival during cellular stress.DOI: http://dx.doi.org/10.7554/eLife.14295.001

Chemical and enzymatic footprinting experiments, such as shape (selective 2′-hydroxyl acylation analyzed by primer extension), yield important information about RNA secondary structure. Indeed, since the -hydroxyl is reactive at flexible (loop) regions, but unreactive at base-paired regions, shape yields quantitative data about which RNA nucleotides are base-paired. Recently, low error rates in secondary structure prediction have been reported for three RNAs of moderate size, by including base stacking pseudo-energy terms derived from shape data into the computation of minimum free energy secondary structure. Here, we describe a novel method, RNAsc (RNA soft constraints), which includes pseudo-energy terms for each nucleotide position, rather than only for base stacking positions. We prove that RNAsc is self-consistent, in the sense that the nucleotide-specific probabilities of being unpaired in the low energy Boltzmann ensemble always become more closely correlated with the input shape data after application of RNAsc. From this mathematical perspective, the secondary structure predicted by RNAsc should be ‘correct’, in as much as the shape data is ‘correct’. We benchmark RNAsc against the previously mentioned method for eight RNAs, for which both shape data and native structures are known, to find the same accuracy in 7 out of 8 cases, and an improvement of 25% in one case. Furthermore, we present what appears to be the first direct comparison of shape data and in-line probing data, by comparing yeast asp-tRNA shape data from the literature with data from in-line probing experiments we have recently performed. With respect to several criteria, we find that shape data appear to be more robust than in-line probing data, at least in the case of asp-tRNA.

Synthetic biology is a rapidly emerging discipline with long-term ramifications that range from single-molecule detection within cells to the creation of synthetic genomes and novel life forms. Truly phenomenal results have been obtained by pioneering groups--for instance, the combinatorial synthesis of genetic networks, genome synthesis using BioBricks, and hybridization chain reaction (HCR), in which stable DNA monomers assemble only upon exposure to a target DNA fragment, biomolecular self-assembly pathways, etc. Such work strongly suggests that nanotechnology and synthetic biology together seem poised to constitute the most transformative development of the 21st century. In this paper, we present a Constraint Programming (CP) approach to solve the RNA inverse folding problem. Given a target RNA secondary structure, we determine an RNA sequence which folds into the target structure; i.e. whose minimum free energy structure is the target structure. Our approach represents a step forward in RNA design--we produce the first complete RNA inverse folding approach which allows for the specification of a wide range of design constraints. We also introduce a Large Neighborhood Search approach which allows us to tackle larger instances at the cost of losing completeness, while retaining the advantages of meeting design constraints (motif, GC-content, etc.). Results demonstrate that our software, RNAiFold, performs as well or better than all state-of-the-art approaches; nevertheless, our approach is unique in terms of completeness, flexibility, and the support of various design constraints. The algorithms presented in this paper are publicly available via the interactive webserver http://bioinformatics.bc.edu/clotelab/RNAiFold; additionally, the source code can be downloaded from that site.

Protein structure prediction is regarded as a highly challenging problem both for the biology and for the computational communities. In recent years, many approaches have been developed, moving to increasingly complex lattice models and off-lattice models. This paper presents a Large Neighborhood Search (LNS) to find the native state for the Hydrophobic-Polar (HP) model on the Face-Centered Cubic (FCC) lattice or, in other words, a self-avoiding walk on the FCC lattice having a maximum number of H-H contacts. The algorithm starts with a tabu-search algorithm, whose solution is then improved by a combination of constraint programming and LNS. The flexible framework of this hybrid algorithm allows an adaptation to the Miyazawa-Jernigan contact potential, in place of the HP model, thus suggesting its potential for tertiary structure prediction. Benchmarking statistics are given for our method against the hydrophobic core threading program HPstruct, an exact method which can be viewed as complementary to our method.

Given an RNA sequence and two designated secondary structures A, B, we describe a new algorithm that computes a nearly optimal folding pathway from A to B. The algorithm, RNAtabupath, employs a tabu semi-greedy heuristic, known to be an effective search strategy in combinatorial optimization. Folding pathways, sometimes called routes or trajectories, are computed by RNAtabupath in a fraction of the time required by the barriers program of Vienna RNA Package. We benchmark RNAtabupath with other algorithms to compute low energy folding pathways between experimentally known structures of several conformational switches. The RNApathfinder web server, source code for algorithms to compute and analyze pathways and supplementary data are available at http://bioinformatics.bc.edu/clotelab/RNApathfinder.

The impact of RNA structures in coding sequences (CDS) within mRNAs is poorly understood. Here, we identify a novel and highly conserved mechanism of translational control involving RNA structures within coding sequences and the DEADbox helicase Dhh1. Using yeast genetics and genome-wide ribosome profiling analyses, we show that this mechanism, initially derived from studies of the Brome Mosaic virus RNA genome, extends to yeast and human mRNAs highly enriched in membrane and secreted proteins. All Dhh1-dependent mRNAs, viral and cellular, share key common features. First, they contain long and highly structured CDSs, including a region located around nucleotide 70 after the translation initiation site; second, they are directly bound by Dhh1 with a specific binding distribution; and third, complementary experimental approaches suggest that they are activated by Dhh1 at the translation initiation step. Our results show that ribosome translocation is not the only unwinding force of CDS and uncover a novel layer of translational control that involves RNA helicases and RNA folding within CDS providing novel opportunities for regulation of membrane and secretome proteins.

Gemin5 is a predominantly cytoplasmic protein that downregulates translation, beyond controlling snRNPs assembly. The C-terminal region harbors a non-canonical RNA-binding site consisting of two domains, RBS1 and RBS2, which differ in RNA-binding capacity and the ability to modulate translation. Here, we show that these domains recognize distinct RNA targets in living cells. Interestingly, the most abundant and exclusive RNA target of the RBS1 domain was Gemin5 mRNA. Biochemical and functional characterization of this target demonstrated that RBS1 polypeptide physically interacts with a predicted thermodynamically stable stem–loop upregulating mRNA translation, thereby counteracting the negative effect of Gemin5 protein on global protein synthesis. In support of this result, destabilization of the stem–loop impairs the stimulatory effect on translation. Moreover, RBS1 stimulates translation of the endogenous Gemin5 mRNA. Hence, although the RBS1 domain downregulates global translation, it positively enhances translation of RNA targets carrying thermodynamically stable secondary structure motifs. This mechanism allows fine-tuning the availability of Gemin5 to play its multiple roles in gene expression control.