Biology subjects

Tabaro, F.

Publications and source records attributed to Tabaro, F..

8 recordsLinked to original sources

bioRxiv2025

The transcription of a single olfactory receptor per neuron is enforced by epigenetic silencing of their enhancers

The ability to discriminate thousands of odors in our environment requires each olfactory neuron to express a single olfactory receptor from hundreds of available genes. The biochemical mechanism enforcing this monogenic expression remains unknown. We show that deletion of the chromatin protein TRIM66 causes individual olfactory neurons to express multiple receptors at a high level, demonstrating that monogenic expression relies on an epigenetic silencing mechanism. Moreover, TRIM66 is specifically recruited to olfactory receptor gene super-enhancers during neuronal progenitor maturation, thereby silencing nearby olfactory receptor genes. Loss of monogenic expression disrupted axonal projections to the olfactory bulb, resulting in an aberrant topographic map and impaired social odor discrimination and reproductive behaviors. These findings uncover the chromatin-based silencing of super-enhancers as the mechanism underlying the organization of the mammalian olfactory system.

molecular biology↗

bioRxiv2024

Trim66 paternal deficiency causes intrauterine overgrowth

The tripartite motif-containing protein 66 (TRIM66, also known as TIF1-delta) is a PHD-Bromo containing protein primarily expressed in post-meiotic male germ cells known as spermatids. Biophysical assays showed that TRIM66 PHD-Bromo domain binds to H3 N-terminus only when lysine 4 is unmethylated. We addressed TRIM66s role in reproduction by loss-of-function genetics in the mouse. Males homozygous for Trim66-null mutations produced functional spermatozoa. Round spermatids lacking TRIM66 upregulated a network of genes involved in histone acetylation and H3K4 methylation. Profiling of H3K4me3 patterns in the sperm produced by Trim66-null mutant showed minor alterations below statistical significance. Unexpectedly, Trim66-null males, but not females, sired pups overweight at birth, hence revealing that Trim66 mutations cause a paternal effect phenotype.

developmental biology↗

bioRxiv2022

RAS and PP2A activities converge on epigenetic gene regulation

RAS-mediated human cell transformation requires inhibition of the tumor suppressor Protein Phosphatase 2A (PP2A). Both RAS and PP2A mediate their effects by phosphoregulation, but phosphoprotein targets and cellular processes in which RAS and PP2A activities converge in human cancers have not been systematically analyzed. Here, based on mass spectrometry phosphoproteome data we discover that phosphosites co-regulated by RAS and PP2A are enriched on proteins involved in epigenetic gene regulation. As examples, RAS and PP2A co-regulate the same phosphorylation sites on HDAC1/2, KDM1A, MTA1/2, RNF168 and TP53BP1. Mechanistically, we validate co-regulation of NuRD chromatin repressor complex by RAS and PP2A. Consistent with their known synergistic effects in cancer, RAS activation and PP2A inhibition resulted in epigenetic reporter de-repression and activation of oncogenic transcription. Notably, transcriptional de-repression by PP2A inhibition was associated with increased euchromatin and decrease in global DNA methylation. Further, targeting of RAS- and PP2A-regulated epigenetic proteins decreased viability of KRAS-mutant human lung cancer cells. Collectively the results indicate that epigenetic protein complexes involved in oncogenic gene expression constitute a significant point of convergence for RAS hyperactivity and PP2A inhibition in cancer. Further, the results provide a rich source for future understanding of phosphorylation as a previously unappreciated layer of regulation of epigenetic gene regulation in cancer, and in other RAS/PP2A-regulated cellular processes.

cancer biology↗

bioRxiv2021

iCn3D: from Web-based 3D Viewer to Structure Analysis Tool in Batch Mode

iCn3D was initially developed as a web-based 3D molecular viewer. It then evolved from visualization into a full-featured interactive structural analysis software. It became a collaborative research instrument through the sharing of permanent, shortened URLs that encapsulate not only annotated visual molecular scenes, but also all underlying data and analysis scripts in a FAIR manner. More recently, with the growth of structural databases, the need to analyze large structural datasets systematically led us to use Python scripts and convert the code to be used in Node.js scripts. We showed a few examples of Python scripts at https://github.com/ncbi/icn3d/tree/master/icn3dpython to export secondary structures or PNG images from iCn3D. Users just need to replace the URL in the Python scripts to export other annotations from iCn3D. Furthermore, any interactive iCn3D feature can be converted into a Node.js script to be run in batch mode, enabling an interactive analysis performed on one or a handful of protein complexes to be scaled up to analysis features of large ensembles of structures. Currently available Node.js analysis scripts examples are available at https://github.com/ncbi/icn3d/tree/master/icn3dnode. This development will enable ensemble analyses on growing structural databases such as AlphaFold or RoseTTAFold on one hand and Electron Microscopy on the other. In this paper, we also review new features such as DelPhi electrostatic potential, 3D view of mutations, alignment of multiple chains, assembly of multiple structures by realignment, dynamic symmetry calculation, 2D cartoons at different levels, interactive contact maps, and use of iCn3D in Jupyter Notebook as described at https://pypi.org/project/icn3dpy.

bioinformatics↗

bioRxiv2020

Chromatin accessibility analysis uncovers regulatory element landscape in prostate cancer progression

Aberrant oncogene functions and structural variation alter the chromatin structure in cancer cells. While gene regulation by chromatin states has been studied extensively, chromatin accessibility and its relevance in aberrant gene expression during prostate cancer progression is not well understood. Here, we report a genome-wide chromatin accessibility analysis of clinical tissue samples of benign prostatic hyperplasia (BPH), untreated primary prostate cancer (PC) and castration-resistant prostate cancer (CRPC) and integrative analysis with transcriptome, methylome, and proteome profiles of the same samples to uncover disease-relevant regulatory elements and their association to altered gene expression during prostate cancer progression. While promoter accessibility is consistent during disease initiation and progression, at distal sites chromatin accessibility is variable enabling transcription factors (TFs) binding patterns that are differently activated in different patients and disease stages. We identify consistent progression-related chromatin alterations during the progression to CRPC. By studying the TF binding patterns, we demonstrate the activation and suppression of androgen receptor-driven regulatory programs during PC progression and identify complementary TF regulatory modules characterized by e.g. MYC and glucocorticoid receptor. By correlation analysis we assign at least one putative regulatory region for 62% of genes and 85% of proteins differentially expressed during prostate cancer progression. Taken together, our analysis of the chromatin landscape in PC identifies putative regulatory elements for the majority of cancer-associated genes and characterizes their impact on the cancer phenotype.

cancer biology↗

bioRxiv2020

Prediction of disordered regions in proteins with recurrent Neural Networks and protein dynamics

The role of intrinsically disordered protein regions (IDRs) in cellular processes has become increasingly evident over the last years. These IDRs continue to challenge structural biology experiments because they lack a well-defined conformation, and bioinformatics approaches that accurately delineate disordered protein regions remain essential for their identification and further investigation. Typically, these predictors use only the protein amino acid sequence, without taking into account likely emergent properties that are sequence context dependent, such as protein backbone dynamics. The DisoMine method predicts protein disorder with recurrent neural networks not directly from the amino acid sequence, but instead from more generic predictions of key biophysical properties, here protein dynamics, secondary structure and early folding. The tool is fast and requires only a single sequence, making it applicable for large-scale screening, including poorly studied and orphan proteins. DisoMine compares well to 10 state of the art predictors, also if these use evolutionary information. DisoMine is freely available through an interactive webserver at http://bio2byte.com/disomine/

bioinformatics↗

bioRxiv2018

Insights into the molecular features of the von Hippel-Lindau like protein

We present an in silico characterization of the von Hippel-Lindau like protein (VLP), the only known human paralogue of the von Hippel-Lindau tumor suppressor protein (pVHL). Phylogenetic investigation showed VLP to be mostly conserved in upper mammals and specifically expressed in brain and testis. Structural analysis and molecular dynamics simulation show VLP to be very similar to pVHL three-dimensional organization and binding dynamics. In particular, conservation of elements at the protein interfaces suggests VLP to be a functional pVHL homolog potentially possessing multiple functions beyond HIF-1-dependent binding activity. Our findings show that VLP may share at least seven interactors with pVHL, suggesting novel functional roles for this under-studied human protein. These may occur at precise hypoxia levels where functional overlap with pVHL may permit a finer modulation of pVHL functions.

cancer biology↗

bioRxiv2018

Genotype-Phenotype Relations of the von Hippel-Lindau Tumor Suppressor Inferred from a Large-Scale Analysis of Disease Mutations and Interactors

Familiar cancers represent a privileged point of view for studying the complex cellular events inducing tumor transformation. Von Hippel-Lindau syndrome, a familiar predisposition to develop cancer is a clear example. Here, we present our efforts to decipher the role of von Hippel-Lindau tumor suppressor protein (pVHL) in cancer insurgence. We collected high quality information about both pVHL mutations and interactors to investigate the association between patient phenotypes, mutated protein surface and impaired interactions. Our data suggest that different phenotypes correlate with localized perturbations of the pVHL structure, with specific cell functions associated to different protein surfaces. We propose five different pVHL interfaces to be selectively involved in modulating proteins regulating gene expression, protein homeostasis as well as to address extracellular matrix (ECM) and ciliogenesis associated functions. These data were used to drive molecular docking of pVHL with its interactors and guide Petri net simulations of the most promising alterations. We predict that disruption of pVHL association with certain interactors can trigger tumor transformation, inducing metabolism imbalance and ECM remodeling. Collectively taken, our findings provide novel insights into VHL-associated tumorigenesis. This highly integrated in silico approach may help elucidate novel treatment paradigms for VHL disease.\n\nAuthor summaryCancer is generally caused by a series of mutations accumulating over time in a healthy tissue, which becomes re-programmed to proliferate at the expense of the hosting organism. This process is difficult to follow and understand as events in a multitude of different genes can lead to similar outcomes without apparent cause. The von Hippel-Lindau (VHL) tumor suppressor is one of the few genes harboring a familiar cancer syndrome, i.e. VHL mutations are known to cause a predictable series of events leading cancer in the kidneys and a few selected other tissues. This article describes a large-scale analysis to relate known VHL mutations to specific cancer pathways by looking at the molecular interactions. Different cancer types appear to be caused by mutations changing the surface of specific parts of the VHL protein. By looking at the VHL interactors involved, it is therefore possible to identify other candidate genes for mutations leading to very similar cancer types.

cancer biology↗