m6A RNA Modification Controls Cell Fate Transition in Mammalian Embryonic Stem Cells

N6-methyl-adenosine (m[superscript 6]A) is the most abundant modification on messenger RNAs and is linked to human diseases, but its functions in mammalian development are poorly understood. Here we reveal the evolutionary conservation and function of m[superscript 6]A by mapping the m[superscript 6]A methylome in mouse and human embryonic stem cells. Thousands of messenger and long noncoding RNAs show conserved m[superscript 6]A modification, including transcripts encoding core pluripotency transcription factors. m[superscript 6]A is enriched over 3′ untranslated regions at defined sequence motifs and marks unstable transcripts, including transcripts turned over upon differentiation. Genetic inactivation or depletion of mouse and human Mettl3, one of the m[superscript 6]A methylases, led to m[superscript 6]A erasure on select target genes, prolonged Nanog expression upon differentiation, and impaired ESC exit from self-renewal toward differentiation into several lineages in vitro and in vivo. Thus, m[superscript 6]A is a mark of transcriptome flexibility required for stem cells to differentiate to specific lineages

Myc Localizes to Histone Locus Bodies during Replication in Drosophila

Myc is an important protein at the center of multiple pathways required for growth and proliferation in animals. The absence of Myc is lethal in flies and mice, and its over-production is a potent inducer of over-proliferation and cancer. Myc protein is localized to the nucleus where it executes its many functions, however the specific sub-nuclear localization of Myc has rarely been reported. The work we describe here began with an observation of unexpected, punctate spots of Myc protein in certain regions of Drosophila embryos. We investigated the identity of these puncta and demonstrate that Myc is co-localized with coilin, a marker for sub-nuclear organelles known as Cajal Bodies (CBs), in embryos, larvae and ovaries. Using antibodies specific for U7 snRNP component Lsm11, we show that the majority of Myc and coilin co-localization occurs in Histone Locus Bodies (HLBs), the sites of histone mRNA transcription and processing. Furthermore, Myc localizes to HLBs only during replication in mitotic and endocycling cells, suggesting that its role there relates to replication-dependent canonical histone gene transcription. These results provide evidence that sub-nuclear localization of Myc is cell-cycle dependent and potentially important for histone mRNA production and processing

MicroRNA miR-308 regulates dMyc through a negative feedback loop in Drosophila

Summary The abundance of Myc protein must be exquisitely controlled to avoid growth abnormalities caused by too much or too little Myc. An intriguing mode of regulation exists in which Myc protein itself leads to reduction in its abundance. We show here that dMyc binds to the miR-308 locus and increases its expression. Using our gain-of-function approach, we show that an increase in miR-308 causes a destabilization of dMyc mRNA and reduced dMyc protein levels. In vivo knockdown of miR-308 confirmed the regulation of dMyc levels in embryos. This regulatory loop is crucial for maintaining appropriate dMyc levels and normal development. Perturbation of the loop, either by elevated miR-308 or elevated dMyc, caused lethality. Combining elevated levels of both, therefore restoring balance between miR-308 and dMyc levels, resulted in lower apoptotic activity and suppression of lethality. These results reveal a sensitive feedback mechanism that is crucial to prevent the pathologies caused by abnormal levels of dMyc

Genome-Wide Maps of m6A circRNAs Identify Widespread and Cell-Type-Specific Methylation Patterns that Are Distinct from mRNAs

N6-methyladenosine (m6A) is the most abundant internal modification of mRNAs and is implicated in all aspects of post-transcriptional RNA metabolism. However, little is known about m6A modifications to circular (circ) RNAs. We developed a computational pipeline (AutoCirc) that, together with depletion of ribosomal RNA and m6A immunoprecipitation, defined thousands of m6A circRNAs with cell-type-specific expression. The presence of m6A circRNAs is corroborated by interaction between circRNAs and YTHDF1/YTHDF2, proteins that read m6A sites in mRNAs, and by reduced m6A levels upon depletion of METTL3, the m6A writer. Despite sharing m6A readers and writers, m6A circRNAs are frequently derived from exons that are not methylated in mRNAs, whereas mRNAs that are methylated on the same exons that compose m6A circRNAs exhibit less stability in a process regulated by YTHDF2. These results expand our understanding of the breadth of m6A modifications and uncover regulation of circRNAs through m6A modification

DIGIT Is a Conserved Long Noncoding RNA that Regulates GSC Expression to Control Definitive Endoderm Differentiation of Embryonic Stem Cells

Long noncoding RNAs (lncRNAs) exhibit diverse functions, including regulation of development. Here, we combine genome-wide mapping of SMAD3 occupancy with expression analysis to identify lncRNAs induced by activin signaling during endoderm differentiation of human embryonic stem cells (hESCs). We find that DIGIT is divergent to Goosecoid (GSC) and expressed during endoderm differentiation. Deletion of the SMAD3-occupied enhancer proximal to DIGIT inhibits DIGIT and GSC expression and definitive endoderm differentiation. Disruption of the gene encoding DIGIT and depletion of the DIGIT transcript reveal that DIGIT is required for definitive endoderm differentiation. In addition, we identify the mouse ortholog of DIGIT and show that it is expressed during development and promotes definitive endoderm differentiation of mouse ESCs. DIGIT regulates GSC in trans, and activation of endogenous GSC expression is sufficient to rescue definitive endoderm differentiation in DIGIT-deficient hESCs. Our study defines DIGIT as a conserved noncoding developmental regulator of definitive endoderm

lncRNA DIGIT and BRD3 protein form phase-separated condensates to regulate endoderm differentiation

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. Cooperation between DNA, RNA and protein regulates gene expression and controls differentiation through interactions that connect regions of nucleic acids and protein domains and through the assembly of biomolecular condensates. Here, we report that endoderm differentiation is regulated by the interaction between the long non-coding RNA (lncRNA) DIGIT and the bromodomain and extraterminal domain protein BRD3. BRD3 forms phase-separated condensates of which the formation is promoted by DIGIT, occupies enhancers of endoderm transcription factors and is required for endoderm differentiation. BRD3 binds to histone H3 acetylated at lysine 18 (H3K18ac) in vitro and co-occupies the genome with H3K18ac. DIGIT is also enriched in regions of H3K18ac, and the depletion of DIGIT results in decreased recruitment of BRD3 to these regions. Our findings show that cooperation between DIGIT and BRD3 at regions of H3K18ac regulates the transcription factors that drive endoderm differentiation and suggest that protein–lncRNA phase-separated condensates have a broader role as regulators of transcription

Electro-Oxidation Method Applied for Activated Sludge Treatment: Experiment and Simulation Based on Supervised Machine Learning Methods

In the present research, an electro-oxidation method was applied to decrease the organic compounds and remove the available micro-organisms in activated sludge of the sewage. Within this method, low cost electrodes were used, including stainless steel, graphite, and Pb/PbO2, and the operating parameters (pH, current density, and operating time) were experimentally optimized. In order to determine sludge stabilization (removal of organic matters and microorganisms), the decrease of parameters like chemical oxygen demand, the increase of electroconductivity and the total dissolved solids, total coli form, and fecal coli form were investigated. Two machine learning techniques (artificial neural networks and support vector machines) were applied comparatively for prediction of the process efficiency. Accurate results were obtained by simulation, in agreement with experimental data