SINEUP non-coding RNA activity depends on specific N6-methyladenosine nucleotides.

SINEUPs are natural and synthetic antisense long non-coding RNAs (lncRNAs) selectively enhancing target mRNAs translation by increasing their association with polysomes. This activity requires two RNA domains: an embedded inverted SINEB2 element acting as effector domain, and an antisense region, the binding domain, conferring target selectivity. SINEUP technology presents several advantages to treat genetic (haploinsufficiencies) and complex diseases restoring the physiological activity of diseased genes and of compensatory pathways. To streamline these applications to the clinic, a better understanding of the mechanism of action is needed. Here we show that natural mouse SINEUP AS Uchl1 and synthetic human miniSINEUP-DJ-1 are N6-methyladenosine (m6A) modified by METTL3 enzyme. Then, we map m6A-modified sites along SINEUP sequence with Nanopore direct RNA sequencing and a reverse transcription assay. We report that m6A removal from SINEUP RNA causes the depletion of endogenous target mRNA from actively translating polysomes, without altering SINEUP enrichment in ribosomal subunit-associated fractions. These results prove that SINEUP activity requires an m6A-dependent step to enhance translation of target mRNAs, providing a new mechanism for m6A translation regulation and strengthening our knowledge of SINEUP-specific mode of action. Altogether these new findings pave the way to a more effective therapeutic application of this well-defined class of lncRNAs.

Predicting genes associated with RNA methylation pathways using machine learning.

RNA methylation plays an important role in functional regulation of RNAs, and has thus attracted an increasing interest in biology and drug discovery. Here, we collected and collated transcriptomic, proteomic, structural and physical interaction data from the Harmonizome database, and applied supervised machine learning to predict novel genes associated with RNA methylation pathways in human. We selected five types of classifiers, which we trained and evaluated using cross-validation on multiple training sets. The best models reached 88% accuracy based on cross-validation, and an average 91% accuracy on the test set. Using protein-protein interaction data, we propose six molecular sub-networks linking model predictions to previously known RNA methylation genes, with roles in mRNA methylation, tRNA processing, rRNA processing, but also protein and chromatin modifications. Our study exemplifies how access to large omics datasets joined by machine learning methods can be used to predict gene function.

Sentinels of chromatin: chromodomain helicase DNA-binding proteins in development and disease.

Chromatin is highly dynamic, undergoing continuous global changes in its structure and type of histone and DNA modifications governed by processes such as transcription, repair, replication, and recombination. Members of the chromodomain helicase DNA-binding (CHD) family of enzymes are ATP-dependent chromatin remodelers that are intimately involved in the regulation of chromatin dynamics, altering nucleosomal structure and DNA accessibility. Genetic studies in yeast, fruit flies, zebrafish, and mice underscore essential roles of CHD enzymes in regulating cellular fate and identity, as well as proper embryonic development. With the advent of next-generation sequencing, evidence is emerging that these enzymes are subjected to frequent DNA copy number alterations or mutations and show aberrant expression in malignancies and other human diseases. As such, they might prove to be valuable biomarkers or targets for therapeutic intervention.

Gene expression regulation by the Chromodomain helicase DNA-binding protein 9 (CHD9) chromatin remodeler is dispensable for murine development.

Chromodomain helicase DNA-binding (CHD) chromatin remodelers regulate transcription and DNA repair. They govern cell-fate decisions during embryonic development and are often deregulated in human pathologies. Chd1-8 show upon germline disruption pronounced, often developmental lethal phenotypes. Here we show that contrary to Chd1-8 disruption, Chd9-/-animals are viable, fertile and display no developmental defects or disease predisposition. Germline deletion of Chd9 only moderately affects gene expression in tissues and derived cells, whereas acute depletion in human cancer cells elicits more robust changes suggesting that CHD9 is a highly context-dependent chromatin regulator that, surprisingly, is dispensable for mouse development.

METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation.

7-methylguanosine (m7G) is present at mRNA caps and at defined internal positions within tRNAs and rRNAs. However, its detection within low-abundance mRNAs and microRNAs (miRNAs) has been hampered by a lack of sensitive detection strategies. Here, we adapt a chemical reactivity assay to detect internal m7G in miRNAs. Using this technique (Borohydride Reduction sequencing [BoRed-seq]) alongside RNA immunoprecipitation, we identify m7G within a subset of miRNAs that inhibit cell migration. We show that the METTL1 methyltransferase mediates m7G methylation within miRNAs and that this enzyme regulates cell migration via its catalytic activity. Using refined mass spectrometry methods, we map m7G to a single guanosine within the let-7e-5p miRNA. We show that METTL1-mediated methylation augments let-7 miRNA processing by disrupting an inhibitory secondary structure within the primary miRNA transcript (pri-miRNA). These results identify METTL1-dependent N7-methylation of guanosine as a new RNA modification pathway that regulates miRNA structure, biogenesis, and cell migration.

DDX3X RNA helicase affects breast cancer cell cycle progression by regulating expression of KLF4.

DDX3X is a multifunctional RNA helicase with documented roles in different cancer types. Here, we demonstrate that DDX3X plays an oncogenic role in breast cancer cells by modulating the cell cycle. Depletion of DDX3X in MCF7 cells slows cell proliferation by inducing a G1 phase arrest. Notably, DDX3X inhibits expression of Kruppel-like factor 4 (KLF4), a transcription factor and cell cycle repressor. Moreover, DDX3X directly interacts with KLF4 mRNA and regulates its splicing. We show that DDX3X-mediated repression of KLF4 promotes expression of S-phase inducing genes in MCF7 breast cancer cells. These findings provide evidence for a novel function of DDX3X in regulating expression and downstream functions of KLF4, a master negative regulator of the cell cycle.

Integrative biology approach identifies cytokine targeting strategies for psoriasis.

Cytokines are critical checkpoints of inflammation. The treatment of human autoimmune disease has been revolutionized by targeting inflammatory cytokines as key drivers of disease pathogenesis. Despite this, there exist numerous pitfalls when translating preclinical data into the clinic. We developed an integrative biology approach combining human disease transcriptome data sets with clinically relevant in vivo models in an attempt to bridge this translational gap. We chose interleukin-22 (IL-22) as a model cytokine because of its potentially important proinflammatory role in epithelial tissues. Injection of IL-22 into normal human skin grafts produced marked inflammatory skin changes resembling human psoriasis. Injection of anti-IL-22 monoclonal antibody in a human xenotransplant model of psoriasis, developed specifically to test potential therapeutic candidates, efficiently blocked skin inflammation. Bioinformatic analysis integrating both the IL-22 and anti-IL-22 cytokine transcriptomes and mapping them onto a psoriasis disease gene coexpression network identified key cytokine-dependent hub genes. Using knockout mice and small-molecule blockade, we show that one of these hub genes, the so far unexplored serine/threonine kinase PIM1, is a critical checkpoint for human skin inflammation and potential future therapeutic target in psoriasis. Using in silico integration of human data sets and biological models, we were able to identify a new target in the treatment of psoriasis.

For better or for worse: the role of Pim oncogenes in tumorigenesis.

Pim oncogenes are overexpressed in a wide range of tumours from a haematological and epithelial origin. Pim genes encode serine/threonine kinases that have been shown to counteract the increased sensitivity to apoptosis induction that is associated with MYC-driven tumorigenesis. Recently, considerable progress has been made in characterizing the pathways of PIM-mediated survival signalling. Given the unique structure of their active site and the minimal phenotype of mice mutant for all Pim family members, these oncogenes might be promising targets for highly specific and selective drugs with favourable toxicity profiles. In this Review, we discuss the physiological functions and oncogenic activities of Pim kinases.