Long-term severe hypoxia adaptation induces non-canonical EMT and a novel Wilms Tumor 1 (WT1) isoform.

The majority of cancer deaths are caused by solid tumors, where the four most prevalent cancers (breast, lung, colorectal and prostate) account for more than 60% of all cases (1). Tumor cell heterogeneity driven by variable cancer microenvironments, such as hypoxia, is a key determinant of therapeutic outcome. We developed a novel culture protocol, termed the Long-Term Hypoxia (LTHY) time course, to recapitulate the gradual development of severe hypoxia seen in vivo to mimic conditions observed in primary tumors. Cells subjected to LTHY underwent a non-canonical epithelial to mesenchymal transition (EMT) based on miRNA and mRNA signatures as well as displayed EMT-like morphological changes. Concomitant to this, we report production of a novel truncated isoform of WT1 transcription factor (tWt1), a non-canonical EMT driver, with expression driven by a yet undescribed intronic promoter through hypoxia-responsive elements (HREs). We further demonstrated that tWt1 initiates translation from an intron-derived start codon, retains proper subcellular localization and DNA binding. A similar tWt1 is also expressed in LTHY-cultured human cancer cell lines as well as primary cancers and predicts long-term patient survival. Our study not only demonstrates the importance of culture conditions that better mimic those observed in primary cancers, especially with regards to hypoxia, but also identifies a novel isoform of WT1 which correlates with poor long-term survival in ovarian cancer.

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se. CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.

Apoptotic endothelial cells release small extracellular vesicles loaded with immunostimulatory viral-like RNAs.

Endothelial cells have multifaceted interactions with the immune system, both as initiators and targets of immune responses. In vivo, apoptotic endothelial cells release two types of extracellular vesicles upon caspase-3 activation: apoptotic bodies and exosome-like nanovesicles (ApoExos). Only ApoExos are immunogenic: their injection causes inflammation and autoimmunity in mice. Based on deep sequencing of total RNA, we report that apoptotic bodies and ApoExos are loaded with divergent RNA cargos that are not released by healthy endothelial cells. Apoptotic bodies, like endothelial cells, contain mainly ribosomal RNA whereas ApoExos essentially contain non-ribosomal non-coding RNAs. Endogenous retroelements, bearing viral-like features, represented half of total ApoExos RNA content. ApoExos also contained several copies of unedited Alu repeats and large amounts of non-coding RNAs with a demonstrated role in autoimmunity such as U1 RNA and Y RNA. Moreover, ApoExos RNAs had a unique nucleotide composition and secondary structure characterized by strong enrichment in U-rich motifs and unstably folded RNAs. Globally, ApoExos were therefore loaded with RNAs that can stimulate a variety of RIG-I-like receptors and endosomal TLRs. Hence, apoptotic endothelial cells selectively sort in ApoExos a diversified repertoire of immunostimulatory "self RNAs" that are tailor-made for initiation of innate immune responses and autoimmunity.

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme.

RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5'-triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homology-derived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson-Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.u-strasbg.fr/rnapuzzles/.

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.

Noncoding regions of C. elegans mRNA undergo selective adenosine to inosine deamination and contain a small number of editing sites per transcript.

ADARs (Adenosine deaminases that act on RNA) "edit" RNA by converting adenosines to inosines within double-stranded regions. The primary targets of ADARs are long duplexes present within noncoding regions of mRNAs, such as introns and 3' untranslated regions (UTRs). Because adenosine and inosine have different base-pairing properties, editing within these regions can alter splicing and recognition by small RNAs. However, despite numerous studies identifying multiple editing sites in these genomic regions, little is known about the extent to which editing sites co-occur on individual transcripts or the functional output of these combinatorial editing events. To begin to address these questions, we performed an ultra-deep sequencing analysis of 4 Caenorhabditis elegans 3' UTRs that are known ADAR targets. Synchronous editing events were determined for the long duplexes in vivo. Furthermore, the validity of each editing event was confirmed by sequencing the same regions of mRNA from worms that lack A-to-I editing. This analysis identified a large number of editing sites that can occur within each 3' UTR, but interestingly, each individual transcript contained only a small fraction of these A-to-I editing events. In addition, editing patterns were not random, indicating that an editing event can affect the efficiency of editing at subsequent adenosines. Furthermore, we identified specific sites that can be both positively and negatively correlated with additional sites leading to mutually exclusive editing patterns. These results suggest that editing in noncoding regions is selective and hyper-editing of cellular RNAs is rare.

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures.

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5-3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson-Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/.

Designing small multiple-target artificial RNAs.

MicroRNAs (miRNAs) are naturally occurring small RNAs that regulate the expression of several genes. MiRNAs' targeting rules are based on sequence complementarity between their mature products and targeted genes' mRNAs. Based on our present understanding of those rules, we developed an algorithm to design artificial miRNAs to target simultaneously a set of predetermined genes. To validate in silico our algorithm, we tested different sets of genes known to be targeted by a single miRNA. The algorithm finds the seed of the corresponding miRNA among the solutions, which also include the seeds of new artificial miRNA sequences potentially capable of targeting these genes as well. We also validated the functionality of some artificial miRNAs designed to target simultaneously members of the E2F family. These artificial miRNAs reproduced the effects of E2Fs inhibition in both normal human fibroblasts and prostate cancer cells where they inhibited cell proliferation and induced cellular senescence. We conclude that the current miRNA targeting rules based on the seed sequence work to design multiple-target artificial miRNAs. This approach may find applications in both research and therapeutics.

Recognition and coupling of A-to-I edited sites are determined by the tertiary structure of the RNA.

Adenosine-to-inosine (A-to-I) editing has been shown to be an important mechanism that increases protein diversity in the brain of organisms from human to fly. The family of ADAR enzymes converts some adenosines of RNA duplexes to inosines through hydrolytic deamination. The adenosine recognition mechanism is still largely unknown. Here, to investigate it, we analyzed a set of selectively edited substrates with a cluster of edited sites. We used a large set of individual transcripts sequenced by the 454 sequencing technique. On average, we analyzed 570 single transcripts per edited region at four different developmental stages from embryogenesis to adulthood. To our knowledge, this is the first time, large-scale sequencing has been used to determine synchronous editing events. We demonstrate that edited sites are only coupled within specific distances from each other. Furthermore, our results show that the coupled sites of editing are positioned on the same side of a helix, indicating that the three-dimensional structure is key in ADAR enzyme substrate recognition. Finally, we propose that editing by the ADAR enzymes is initiated by their attraction to one principal site in the substrate.

Staufen1 regulates diverse classes of mammalian transcripts.

It is currently unknown how extensively the double-stranded RNA-binding protein Staufen (Stau)1 is utilized by mammalian cells to regulate gene expression. To date, Stau1 binding to the 3'-untranslated region (3'-UTR) of ADP ribosylation factor (ARF)1 mRNA has been shown to target ARF1 mRNA for Stau1-mediated mRNA decay (SMD). ARF1 SMD depends on translation and recruitment of the nonsense-mediated mRNA decay factor Upf1 to the ARF1 3'-UTR by Stau1. Here, we demonstrate that Stau1 binds to a complex structure within the ARF1 3'-UTR. We also use microarrays to show that 1.1 and 1.0% of the 11 569 HeLa-cell transcripts that were analyzed are upregulated and downregulated, respectively, at least two-fold upon Stau1 depletion in three independently performed experiments. We localize the Stau1 binding site to the 3'-UTR of four mRNAs that we define as natural SMD targets. Additionally, we provide evidence that the efficiency of SMD increases during the differentiation of C2C12 myoblasts to myotubes. We propose that Stau1 influences the expression of a wide variety of physiologic transcripts and metabolic pathways.

An E2F/miR-20a autoregulatory feedback loop.

The E2F family of transcription factors is essential in the regulation of the cell cycle and apoptosis. While the activity of E2F1-3 is tightly controlled by the retinoblastoma family of proteins, the expression of these factors is also regulated at the level of transcription, post-translational modifications and protein stability. Recently, a new level of regulation of E2Fs has been identified, where micro-RNAs (miRNAs) from the mir-17-92 cluster influence the translation of the E2F1 mRNA. We now report that miR-20a, a member of the mir-17-92 cluster, modulates the translation of the E2F2 and E2F3 mRNAs via binding sites in their 3'-untranslated region. We also found that the endogenous E2F1, E2F2, and E2F3 directly bind the promoter of the mir-17-92 cluster activating its transcription, suggesting an autoregulatory feedback loop between E2F factors and miRNAs from the mir-17-92 cluster. Our data also point toward an anti-apoptotic role for miR-20a, since overexpression of this miRNA decreased apoptosis in a prostate cancer cell line, while inhibition of miR-20a by an antisense oligonucleotide resulted in increased cell death after doxorubicin treatment. This anti-apoptotic role of miR-20a may explain some of the oncogenic capacities of the mir-17-92 cluster. Altogether, these results suggest that the autoregulation between E2F1-3 and miR-20a is important for preventing an abnormal accumulation of E2F1-3 and may play a role in the regulation of cellular proliferation and apoptosis.

Genetic mapping of activity determinants within cellular prion proteins: N-terminal modules in PrPC offset pro-apoptotic activity of the Doppel helix B/B' region.

The PrP-like Doppel (Dpl) protein causes apoptotic death of cerebellar neurons in transgenic mice, a process prevented by expression of the wild type (wt) cellular prion protein, PrP(C). Internally deleted forms of PrP(C) resembling Dpl such as PrPDelta32-121 produce a similar PrP(C)-sensitive pro-apoptotic phenotype in transgenic mice. Here we demonstrate that these phenotypic attributes of wt Dpl, wt PrP(C), and PrPDelta132-121 can be accurately recapitulated by transfected mouse cerebellar granule cell cultures. This system was then explored by mutagenesis of the co-expressed prion proteins to reveal functional determinants. By this means, neuroprotective activity of wt PrP(C) was shown to be nullified by a deletion of the N-terminal charged region implicated in endocytosis and retrograde axonal transport (PrPDelta23-28), by deletion of all five octarepeats (PrPDelta51-90), or by glycine replacement of four octarepeat histidine residues required for selective binding of copper ions (Prnp"H/G"). In the case of Dpl, overlapping deletions defined a requirement for the gene interval encoding helices B and B' (DplDelta101-125). These data suggest contributions of copper binding and neuronal trafficking to wt PrP(C) function in vivo and place constraints upon current hypotheses to explain Dpl/PrP(C) antagonism by competitive ligand binding. Further implementation of this assay should provide a fuller understanding of the attributes and subcellular localizations required for activity of these enigmatic proteins.