Quantification of mRNA ribosomal engagement in human neurons using parallel translating ribosome affinity purification (TRAP) and RNA sequencing

METTL3 and STAT3 form a positive feedback loop to promote cell metastasis in hepatocellular carcinoma

BACKGROUND

It is well-established that most Hepatocellular carcinoma (HCC) patients die of metastasis, yet the potential mechanisms orchestrating metastasis remain poorly understood. Current evidence suggests that the dysregulation of METTL3-mediated m6A methylation modification is closely associated with cancer progression. STAT3 is an oncogenic transcription factor that reportedly plays a central role in the occurrence and development of HCC. However, the relationship between METTL3 and STAT3 in HCC metastasis remains unclear.

METHODS

The relationship between METTL3 expression and the survival of HCC patients was assessed by online tools GEPIA and Kaplan-Meier Plotter. Western blotting, Tissue microarray (TMA), and immunohistochemistry (IHC) staining were used to evaluate the expression levels of METTL3 and STAT3 in HCC cell lines and metastatic and non-metastatic tissues. Methylated RNA immunoprecipitation (MeRIP), MeRIP sequencing (MeRIP-seq), qRT-PCR, RNA immunoprecipitation (RIP), Western blotting and luciferase reporter gene assay were utilized to clarify the mechanism of METTL3 regulating STAT3 expression. Immunofluorescence staining, Western blotting, qRT-PCR, Co-immunoprecipitation (Co-IP), IHC staining, TMA and Chromatin immunoprecipitation (ChIP) assay were performed to explore the mechanism of STAT3 modulating METTL3 localization. Cell viability, wound healing and transwell assay, and orthotopic xenograft model were used to evaluate the role of METTL3-STAT3 feedback loop in the promotion of HCC metastasis in vitro and in vivo.

RESULTS

METTL3 and STAT3 are both abundantly expressed in high-metastatic HCC cells and tissues. Moreover, a positive correlation was found between the expression of STAT3 and METTL3 in HCC tissues. Mechanistically, METTL3 could induce the m6A modification of STAT3 mRNA, and then promote the translation of m6A-contained STAT3 mRNA by interacting with the translation initiation machinery. In contrast, STAT3 promoted nuclear localization of METTL3 via transcriptionally upregulating WTAP, a vital member of the methyltransferase complex, and facilitated the methyltransferase function of METTL3. METTL3 and STAT3 form a positive feedback loop to accelerate HCC metastasis in vitro and in vivo.

CONCLUSIONS

Our findings reveal a novel mechanism of HCC metastasis and uncover the METTL3-STAT3 feedback signaling as a potential target for the anti-metastatic treatment of HCC. Video Abstract.

Buffering of transcription rate by mRNA half-life is a conserved feature of Rett syndrome models

Transcriptional changes in Rett syndrome (RTT) are assumed to directly correlate with steady-state mRNA levels, but limited evidence in mice suggests that changes in transcription can be compensated by post-transcriptional regulation. We measure transcription rate and mRNA half-life changes in RTT patient neurons using RATEseq, and re-interpret nuclear and whole-cell RNAseq from Mecp2 mice. Genes are dysregulated by changing transcription rate or half-life and are buffered when both change. We utilized classifier models to predict the direction of transcription rate changes and find that combined frequencies of three dinucleotides are better predictors than CA and CG. MicroRNA and RNA-binding Protein (RBP) motifs are enriched in 3'UTRs of genes with half-life changes. Nuclear RBP motifs are enriched on buffered genes with increased transcription rate. We identify post-transcriptional mechanisms in humans and mice that alter half-life or buffer transcription rate changes when a transcriptional modulator gene is mutated in a neurodevelopmental disorder.

TRACE-seq: A transgenic system for unbiased and non-invasive transcriptome profiling of living cells

Dynamic profiling of changes in gene expression in response to stressors in specific microenvironments without requiring cellular destruction remains challenging. Current methodologies that seek to interrogate gene expression at a molecular level require sampling of cellular transcriptome and therefore lysis of the cell, preventing serial analysis of cellular transcriptome. To address this area of unmet need, we have recently developed a technology allowing transcriptomic analysis over time without cellular destruction. Our method, TRACE-seq (TRanscriptomic Analysis Captured in Extracellular vesicles using sequencing), is characterized by a cell-type specific transgene expression. It provides data on the transcriptome inside extracellular vesicles that provides an accurate representation of stress-responsive cellular transcriptomic changes. Thus, the transcriptome of cells expressing TRACE can be followed over time without destroying the source cell, which is a powerful tool for many fields of fundamental and translational biology research.

•

TRanscriptomic Analysis Captured in Extracellular vesicles using RNA-sequencing

•

Excellent correlation of cellular and EV transcriptome using this method

•

Accurate profiling of gene expression changes in response to stress signals