The PTM profiling of CTCF reveals the regulation of 3D chromatin structure by O-GlcNAcylation.

CCCTC-binding factor (CTCF), a ubiquitously expressed and highly conserved protein, is known to play a critical role in chromatin structure. Post-translational modifications (PTMs) diversify the functions of protein to regulate numerous cellular processes. However, the effects of PTMs on the genome-wide binding of CTCF and the organization of three-dimensional (3D) chromatin structure have not been fully understood. In this study, we uncovered the PTM profiling of CTCF and demonstrated that CTCF can be O-GlcNAcylated and arginine methylated. Functionally, we demonstrated that O-GlcNAcylation inhibits CTCF binding to chromatin. Meanwhile, deficiency of CTCF O-GlcNAcylation results in the disruption of loop domains and the alteration of chromatin loops associated with cellular development. Furthermore, the deficiency of CTCF O-GlcNAcylation increases the expression of developmental genes and negatively regulates maintenance and establishment of stem cell pluripotency. In conclusion, these results provide key insights into the role of PTMs for the 3D chromatin structure.

Precise prediction of phase-separation key residues by machine learning.

Understanding intracellular phase separation is crucial for deciphering transcriptional control, cell fate transitions, and disease mechanisms. However, the key residues, which impact phase separation the most for protein phase separation function have remained elusive. We develop PSPHunter, which can precisely predict these key residues based on machine learning scheme. In vivo and in vitro validations demonstrate that truncating just 6 key residues in GATA3 disrupts phase separation, enhancing tumor cell migration and inhibiting growth. Glycine and its motifs are enriched in spacer and key residues, as revealed by our comprehensive analysis. PSPHunter identifies nearly 80% of disease-associated phase-separating proteins, with frequent mutated pathological residues like glycine and proline often residing in these key residues. PSPHunter thus emerges as a crucial tool to uncover key residues, facilitating insights into phase separation mechanisms governing transcriptional control, cell fate transitions, and disease development.

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma.

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort. Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package "Seurat" was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the "ssGSEA" algorithm. In order to develop possible medications for patients with high-risk ccRCC, the "pRRophetic" package is employed. Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature's biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications. Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient's prognosis for ccRCC and reflect the disease's complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

CTCF organizes inter-A compartment interactions through RYBP-dependent phase separation.

Chromatin is spatially organized into three-dimensional structures at different levels including A/B compartments, topologically associating domains and loops. The canonical CTCF-mediated loop extrusion model can explain the formation of loops. However, the organization mechanisms underlying long-range chromatin interactions such as interactions between A-A compartments are still poorly understood. Here we show that different from the canonical loop extrusion model, RYBP-mediated phase separation of CTCF organizes inter-A compartment interactions. Based on this model, we designed and verified an induced CTCF phase separation system in embryonic stem cells (ESCs), which facilitated inter-A compartment interactions, improved self-renewal of ESCs and inhibited their differentiation toward neural progenitor cells. These findings support a novel and non-canonical role of CTCF in organizing long-range chromatin interactions via phase separation.

PCGF6 regulates stem cell pluripotency as a transcription activator via super-enhancer dependent chromatin interactions.

Polycomb group (PcG) ring finger protein 6 (PCGF6), though known as a member of the transcription-repressing complexes, PcG, also has activation function in regulating pluripotency gene expression. However, the mechanism underlying the activation function of PCGF6 is poorly understood. Here, we found that PCGF6 co-localizes to gene activation regions along with pluripotency factors such as OCT4. In addition, PCGF6 was recruited to a subset of the super-enhancer (SE) regions upstream of cell cycle-associated genes by OCT4, and increased their expression. By combining with promoter capture Hi-C data, we found that PCGF6 activates cell cycle genes by regulating SE-promoter interactions via 3D chromatin. Our findings highlight a novel mechanism of PcG protein in regulating pluripotency, and provide a research basis for the therapeutic application of pluripotent stem cells.