p73 is required for vessel integrity controlling endothelial junctional dynamics through Angiomotin

Preservation of blood vessel integrity, which is critical for normal physiology and organ function, is controlled at multiple levels, including endothelial junctions. However, the mechanism that controls the adequate assembly of endothelial cell junctions is not fully defined. Here, we uncover TAp73 transcription factor as a vascular architect that orchestrates transcriptional programs involved in cell junction establishment and developmental blood vessel morphogenesis and identify Angiomotin (AMOT) as a TAp73 direct transcriptional target. Knockdown of p73 in endothelial cells not only results in decreased Angiomotin expression and localization at intercellular junctions, but also affects its downstream function regarding Yes-associated protein (YAP) cytoplasmic sequestration upon cell–cell contact. Analysis of adherens junctional morphology after p73-knockdown in human endothelial cells revealed striking alterations, particularly a sharp increase in serrated junctions and actin bundles appearing as stress fibers, both features associated with enhanced barrier permeability. In turn, stabilization of Angiomotin levels rescued those junctional defects, confirming that TAp73 controls endothelial junction dynamics, at least in part, through the regulation of Angiomotin. The observed defects in monolayer integrity were linked to hyperpermeability and reduced transendothelial electric resistance. Moreover, p73-knockout retinas showed a defective sprout morphology coupled with hemorrhages, highlighting the physiological relevance of p73 regulation in the maintenance of vessel integrity in vivo. We propose a new model in which TAp73 acts as a vascular architect integrating transcriptional programs that will impinge with Angiomotin/YAP signaling to maintain junctional dynamics and integrity, while balancing endothelial cell rearrangements in angiogenic vessels.

Hypoxia classifier for transcriptome datasets

Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and cell types and are often restricted to a set of gene identities. Focusing on the transcriptional response to hypoxia, we aimed to generate widely applicable classifiers sourced from the results of a meta-analysis of 69 differential expression datasets which included 425 individual RNA-seq experiments from 33 different human cell types exposed to different degrees of hypoxia (0.1–5%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hbox {O}_{2}$$\end{document}O2) for 2–48 h. The resulting decision trees include both gene identities and quantitative boundaries, allowing for easy classification of individual samples without control or normoxic reference. Each tree is composed of 3–5 genes mostly drawn from a small set of just 8 genes (EGLN1, MIR210HG, NDRG1, ANKRD37, TCAF2, PFKFB3, BHLHE40, and MAFF). In spite of their simplicity, these classifiers achieve over 95% accuracy in cross validation and over 80% accuracy when applied to additional challenging datasets. Our results indicate that the classifiers are able to identify hypoxic tumor samples from bulk RNAseq and hypoxic regions within tumor from spatially resolved transcriptomics datasets. Moreover, application of the classifiers to histological sections from normal tissues suggest the presence of a hypoxic gene expression pattern in the kidney cortex not observed in other normoxic organs. Finally, tree classifiers described herein outperform traditional hypoxic gene signatures when compared against a wide range of datasets. This work describes a set of hypoxic gene signatures, structured as simple decision tress, that identify hypoxic samples and regions with high accuracy and can be applied to a broad variety of gene expression datasets and formats.

The SIN3A histone deacetylase complex is required for a complete transcriptional response to hypoxia

Cells adapt to environmental changes, including fluctuations in oxygen levels, through the induction of specific gene expression programs. To identify genes regulated by hypoxia at the transcriptional level, we pulse-labeled HUVEC cells with 4-thiouridine and sequenced nascent transcripts. Then, we searched genome-wide binding profiles from the ENCODE project for factors that correlated with changes in transcription and identified binding of several components of the Sin3A co-repressor complex, including SIN3A, SAP30 and HDAC1/2, proximal to genes repressed by hypoxia. SIN3A interference revealed that it participates in the downregulation of 75% of the hypoxia-repressed genes in endothelial cells. Unexpectedly, it also blunted the induction of 47% of the upregulated genes, suggesting a role for this corepressor in gene induction. In agreement, ChIP-seq experiments showed that SIN3A preferentially localizes to the promoter region of actively transcribed genes and that SIN3A signal was enriched in hypoxia-repressed genes, prior exposure to the stimulus. Importantly, SINA3 occupancy was not altered by hypoxia in spite of changes in H3K27ac signal. In summary, our results reveal a prominent role for SIN3A in the transcriptional response to hypoxia and suggest a model where modulation of the associated histone deacetylase activity, rather than its recruitment, determines the transcriptional output.