Biology subjects

Daher, A.

Publications and source records attributed to Daher, A..

3 recordsLinked to original sources

bioRxiv2026

Recognition and Resolution of KRAS 5'UTR RNA G-Quadruplexes by hnRNPA1

The KRAS oncogene, central to cellular signaling via MAPK and PI3K-AKT pathways, is a notorious cancer driver frequently activated in pancreatic, colorectal, and lung carcinomas. Regulation of human KRAS oncogene expression is important due to its capital role in cell growth, proliferation, and survival. Misregulation of its expression contributes directly to the development and progression of multiple types of cancer. In previous studies, the role of G-quadruplexes elements in both the promoter and 5 UTR regions have shown to play important roles in KRAS expression, particularly when these G4s elements interact with regulatory protein hnRNPA1. In this study, we reveal that KRAS expression is also modulated at the post-transcriptional level through the formation of RNA G-quadruplexes (rG4s) situated at the 5 untranslated region (5UTR) of the mRNA. Biophysical and binding studies were carried out to probe the interaction. Through isothermal titration calorimetry (ITC), we quantified a strong binding affinity between the UP1 domain of hnRNPA1 and short-nucleotide RNA segments capable of adopting different G-quadruplex fold. The binding interaction is characterized by a favorable Gibbs free energy change in the range of {Delta}G {approx} -32 to -34 kJ/mol, suggesting a specific and energetically favorable association. One-dimensional and two-dimensional 1H-15N HSQC NMR spectroscopy revealed pronounced chemical shift changes in residues of both RNA recognition motifs (RRMs) of UP1, signifying direct contact with the rG4 structure.

biophysics↗

bioRxiv2025

A Computational Pipeline for Physiologically Informed Calibration of Ligand Reaction-Diffusion Models Using High-Throughput Sequencing

All physiological processes fundamentally rely on continuous cellular cross-talk to maintain organization and ensure proper function. Among the various modes of cellular communication, ligand-mediated chemical signaling, in which a ligand is secreted by one cell, diffuses through the extracellular environment, and binds to a receptor on another (or the same) cell to elicit a downstream response, is arguably the most ubiquitous and foundational. Given its importance, numerous mathematical models have been developed to describe this reaction-diffusion mechanism, capturing ligand secretion, diffusion, decay, and binding under both normal and pathological conditions. However, parameter calibration for such models often lags behind model development. This is due to limited data that faithfully represent the biological microenvironment, as well as due to the absence of a robust, rigorous framework to integrate available data into the mathematical model. To address this gap, we propose that transcriptomics (gene expression) data, namely the combination of single-cell RNA sequencing and spatial transcriptomics, provide a rich, increasingly abundant, and underutilized source of information that can be used to calibrate the parameters of the cellular reaction-diffusion models at the larger mesoscopic scale. To this end, we develop a computational pipeline that leverages these data to extract parameter values for reaction-diffusion models, and illustrate its application through two human wound-healing case studies. Using open-source transcriptomics data, we calibrate the reaction-diffusion model parameters of the isoforms of Transforming Growth Factor Beta (TGF{beta}), a signaling molecule central to tissue repair and development as well as to pathological processes such as cancer and fibrosis. Our pipeline integrates traditional numerical (finite volume) solvers for the ligand concentration fields with bioinformatics, machine learning, and Bayesian inference methods, combining existing and novel computational tools into a single framework for a physiologically informed, data-driven parameter calibration process. The pipeline is modular, allowing easy extension or adjustment depending on user needs. Overall, this framework facilitates rigorous model calibration, an essential step toward ensuring that mathematical models have meaningful research and potential translational utility.

systems biology↗

bioRxiv2023

The sequestration of miR-642a-3p by a complex formed by HIV-1 Gag and human Dicer increases AFF4 expression and viral production

Micro (mi)RNAs are critical regulators of gene expression in human cells, the functions of which can be affected during viral replication. Here, we show that the human immunodeficiency virus type 1 (HIV-1) structural precursor Gag protein interacts with the miRNA processing enzyme Dicer. RNA immunoprecipitation and sequencing experiments show that Gag modifies the retention of a specific miRNA subset without affecting Dicers pre- miRNA processing activity. Among the retained miRNAs, miR-642a-3p shows an enhanced occupancy on Dicer in the presence of Gag and is predicted to target AFF4 mRNA, which encodes an essential scaffold protein for HIV-1 transcriptional elongation. miR-642a-3p gain- or loss-of-function negatively or positively regulates AFF4 protein expression at mRNA and protein levels with concomitant modulations of HIV-1 production, consistent with an antiviral activity. By sequestering miR-642a-3p with Dicer, Gag enhances AFF4 expression and HIV- 1 production without affecting miR-642a-3p levels. These results identify miR-642a-3p as a strong suppressor of HIV-1 replication and uncover a novel mechanism by which a viral structural protein directly disrupts an miRNA function for the benefit of its own replication. IMPORTANCEVirus-host relationships occur at different levels and the human immunodeficiency virus type 1 (HIV-1) can modify the expression of microRNAs in different cells. Here, we identify a virus- host interaction between the HIV-1 structural protein Gag and the miRNA-processing enzyme Dicer. Gag does not affect the microRNA processing function of Dicer but affects the functionality of a subset of microRNAs that are enriched on the Dicer-Gag complex compared to on Dicer alone. We show that miR-642a-3p, the most enriched microRNA on the Dicer- Gag complex targets and degrades AFF4 mRNA coding for a protein from the super transcription elongation complex, essential for HIV-1 and cellular transcription. Interestingly, the silencing capacity by miR-642a-3p is hindered by Gag and heightened in its absence, consequently affecting HIV-1 transcription. These findings unveil a new paradigm that a microRNA function rather than its abundance can be affected by a viral protein through its enhanced retention on Dicer.

microbiology↗