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Martens, J.

Publications and source records attributed to Martens, J..

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Polyomavirus T-Antigen Induces APOBEC3B Expression using a LXCXE-Dependent and TP53-Independent Mechanism

APOBEC3B is a single-stranded DNA cytosine deaminase with beneficial innate antiviral functions. However, misregulated APOBEC3B can also be detrimental by inflicting APOBEC signature C-to-T and C-to-G mutations in genomic DNA of multiple cancer types. Polyomaviruses and papillomaviruses use dominant oncoproteins to induce APOBEC3B overexpression, perhaps to their own benefit, but little is known about the cellular mechanisms hijacked by these viruses to do so. Here we investigate the molecular mechanism of APOBEC3B upregulation by the polyomavirus large T-antigen. First, truncated T-antigen (truncT) is sufficient for APOBEC3B upregulation and the RB interacting motif (LXCXE), but not the TP53 inhibition domain, is required. Second, upregulated APOBEC3B is strongly nuclear and partially localized to virus replication centers. Third, genetic knockdown of RB1 alone or in combination with RBL1 and/or RBL2 is insufficient to suppress truncT-mediated induction of APOBEC3B. Fourth, CDK4/6 inhibition by palbociclib is also insufficient to suppress truncT-mediated induction of APOBEC3B. Fifth, global gene expression analyses in a wide range of human cancers show significant associations between expression of APOBEC3B and other genes known to be regulated by the RB/E2F axis. These experiments combine to implicate the RB/E2F axis in promoting APOBEC3B transcription, yet they also suggest that the polyomavirus RB binding motif has in addition to RB inactivation at least one additional function for triggering APOBEC3B upregulation in virus-infected cells.\n\nIMPORTANCEThe APOBEC3B DNA cytosine deaminase is overexpresssed in many different cancers and correlated with elevated frequencies of C-to-T and C-to-G mutations in 5-TC motifs, oncogene activation, acquired drug resistance, and poor clinical outcomes. The mechanisms responsible for APOBEC3B overexpression are not fully understood. Here, we show that the polyomavirus truncated T-antigen (truncT) triggers APOBEC3B overexpression through its RB-interacting motif, LXCXE, which in turn likely enables one or more E2F family transcription factors to promote APOBEC3B expression. This work strengthens the mechanistic linkage between active cell cycling, APOBEC3B overexpression, and cancer mutagenesis. Although this mechanism damages cellular genomes, viruses may leverage it to promote evolution, immune escape, and pathogenesis. The cellular portion of the mechanism may also be relevant to non-viral cancers, where genetic mechanisms often activate the RB/E2F axis and APOBEC3B mutagenesis contributes to tumor evolution.

microbiology

DNA methylation oscillation defines classes of enhancers

Understanding the regulatory landscape of human cells requires the integration of genomic and epigenomic maps, capturing combinatorial levels of cell type-specific and invariant activity states.\n\nHere, we segmented whole-genome bisulfite sequencing-derived methylomes into consecutive blocks of co-methylation (COMETs) to obtain spatial variation patterns of DNA methylation (DNAm oscillations) integrated with histone modifications and promoter-enhancer interactions derived from promoter capture Hi-C (PCHi-C) sequencing of the same purified blood cells.\n\nMapping DNAm oscillations onto regulatory genome annotation revealed that enhancers are enriched for DNAm hyper-oscillations (>30-fold), where multiple machine learning models support DNAm as predictive of enhancer location. Based on this analysis, we report overall predictive power of 99% for DNAm oscillations, 77.3% for DNaseI, 41% for CGIs, 20% for UMRs and 0% for LMRs, demonstrating the power of DNAm oscillations over other methods for enhancer prediction. Methylomes of activated and non-activated CD4+ T cells indicate that DNAm oscillations exist in both states irrespective of activation; hence they can be used to determine the location of latent enhancers.\n\nOur approach advances the identification of tissue-specific regulatory elements and outperforms previous approaches defining enhancer classes based on DNA methylation.

genomics