Biology subjects

Soliman, A.

Publications and source records attributed to Soliman, A..

11 recordsLinked to original sources

bioRxiv2026

16p11.2 Copy Number Variation Alters Genome Architecture and Transcriptional Regulation During Neurodevelopment

Microdeletions and microduplications in 16p11.2 are responsible for a spectrum of neurodevelopmental disorders (NDDs) with partially reciprocal and overlapping symptoms. However, the clinical variability in 16p11.2 microduplication patients is significantly greater than that in patients carrying a microdeletion. Here, we use iPSCs derived from members of a family carrying a 16p11.2 microduplication and model neurodevelopment through in vitro differentiation into neural progenitor cells (NPCs) and neurons. The analysis is complemented by reanalysis of publicly available data from 16p11.2 microdeletion patients. Transcriptome analysis revealed MAPK3-centered hubs of upregulated genes in the microduplication-carrying and downregulated in the microdeletion-carrying cells, indicating that MAPK3 is a central driver of 16p11.2 Copy Number Variation (CNV) pathology. While genes within the 16p11.2 region showed about a two-fold reduction in expression in cells carrying the microdeletion, their expression levels in microduplication-derived NPCs and neurons, but not in iPSCs, were elevated to a degree much higher than expected. This observation was accompanied by a substantial number of dysregulated genes unrelated to the genes in the critical region or their interaction networks. To further investigate whether altered chromatin organization may accompany these transcriptional changes, we generated Hi-C data from patient and control iPSCs and NPCs. This revealed increased chromatin contacts within the duplicated 16p11.2 region in patient-derived iPSCs, while genome-wide compartment analysis showed that increased compartments preferentially co-occurred with upregulated differentially expressed genes, particularly in NPCs. Together, these findings suggest that 16p11.2 microduplication may influence gene expression through both local dosage-dependent mechanisms and broader, differentiation-associated changes in chromatin organization. Our data support a model in which CNV-associated genome architecture changes may modulate transcriptional dysregulation and contribute to the variable neurodevelopmental phenotypes associated with 16p11.2 rearrangements.

pathology↗

bioRxiv2026

Correcting Preprocessing Bias in Sparse Chromatin Contact Data Enables Physically Interpretable Reconstruction of Genome Architecture

DNA is the largest biopolymer in nature, and chromatin contact maps are widely interpreted as quantitative readouts of its three-dimensional organization. However, the validity of such interpretations critically depends on how these maps are processed. Here, we identify a previously overlooked but fundamental source of bias in chromatin contact data analysis. We demonstrate that a widely adopted preprocessing convention, namely whole-matrix percentile clipping, systematically distorts sparse contact maps by collapsing their dynamic range. This effect is strongest in near-diagonal interactions, precisely the regime encoding chromatin domains and looping structures, thereby compromising quantitative interpretation while preserving superficial structural features. We show that this distortion represents a sparsity-dependent failure mode of current preprocessing standards and affects the comparability of datasets and computational methods across technologies and sequencing depths. To address this, we introduce a statistically consistent preprocessing framework based on nonzero-percentile clipping and log-space normalization, which preserves the intrinsic dynamic range of observed contacts. Building on this foundation, we present CCUT, a modular deep learning framework for chromatin contact map reconstruction. Under corrected preprocessing, reconstructed maps recover domain organization, contact decay, and scaling behavior consistent with polymer physics. Importantly, we demonstrate quantitative agreement between reconstructed maps and simulated contact patterns derived from a kinetic Monte Carlo loop extrusion model, enabling direct comparison between experimental data and physical models. Together, our results establish preprocessing as a decisive determinant of the physical interpretability of chromatin contact maps and provide a principled framework for robust and comparable analysis across chromatin conformation capture technologies.

biophysics↗

bioRxiv2025

Dissecting structural and functional determinants of microtubule stabilization through guided chemical modulation

Paclitaxel (PTX) is a widely used chemotherapeutic, but its efficacy is limited by peripheral neuropathy, likely due to its structural impact on neuronal microtubules (MTs). To decouple MT stabilization from adverse structural changes, we designed, synthetized and characterized several PTX analogues. Our compound 1b retains PTXs stabilizing activity in vitro and in cells, and the 1b-bound MTs preserve a native-like structure. These facts allowed us to investigate the influence of specific MT structural features on motor proteins behavior and interaction with MT-associated protein Tau. PTX-induced lattice expansion disrupted dynein-mediated retrograde transport and altered kinesin-1 motility. Additionally, PTX reduced Taus initial non-cooperative binding and envelopes growth rate while increasing dwell time and suppressing dynamic binding. In contrast, 1b preserved more physiological Tau dynamics. These findings reveal that MT stabilization and structural modulation can be separated and highlight the functional importance of MT heterogeneity in maintaining neuronal transport and MAP interactions.

molecular biology↗

bioRxiv2025

In silico reconstruction of primary and metastatic tumor architecture using GIS-augmented spatial transcriptomics

The tumor microenvironment (TME) comprises different cell populations that interact, contributing to tumor heterogeneity and therapy response. Spatial transcriptomics offers valuable insights into transcriptional complexity and heterogeneity of the TME. We established Geographic Information System (GIS)-augmented In-Silico Reconstruction of Tumor Architecture (GIS-ROTA), a biologically informed analytic framework that integrates pathway or cell type-based enrichment analysis with local Morans I to uncover functional spatial domains. In our Visium dataset of primary and metastatic estrogen receptor-positive breast tumor samples, GIS-ROTA revealed extensive co-localization of estrogen response with metabolic pathway gene sets and mutual exclusivity with metastasis-related and specific immune-related pathway gene sets. The novelty of our approach lies in considering biological functions prior to identifying any spatial domains, providing direct interpretability and minimizing the subjectivity of interpreting clusters observed from conventional analytic methods. Overall, our GIS-ROTA framework integrates biological knowledge first, yielding spatial patterns with functional relevance and enabling identification of novel targets for development of therapeutic strategies.

cancer biology↗

bioRxiv2025

A regulatory loop regulating signaling between LRRK2 and PP2A in cellular models of Parkinsons disease

Mutations in Leucine-rich repeat kinase 2 (LRRK2) are the most frequent cause of late-onset familial and idiopathic Parkinsons disease (PD), known to date. Importantly, recent data from post-mortem tissue as well as biomarker studies suggest that independent of mutations, increased kinase activity of LRRK2 plays an essential role in idiopathic PD pathogenesis. Despite extensive research on LRRK2, its activation mechanism(s) and how the various mutations result in increased kinase activity and neuronal death is still not completely understood. Accumulating evidence points to LRRK2 phospho-regulation, both auto-phosphorylation and phosphorylation by other kinases, as one potential molecular trigger of its activation. LRRK2 activation and localization is regulated by phosphatases such as Protein phosphatase 1 (PP1) and Protein phosphatase 2A (PP2A), however the exact mechanism of this phospho-regulation is not known. Our data reveal that in vitro PP2A dephosphorylates sites within the RocCOR-GTPase domain of LRRK2 and as a result de-stabilizes LRRK2 dimers, with consequent reduction of its kinase activity. Strikingly, our data further highlight that LRRK2 in turn phosphorylates the catalytic subunit of the PP2A holoenzyme PPP2CA at its critical residue T304. Furthermore, LRRK2-mediated phosphorylation of PP2CA T304 alters the methylation of the C-terminus, which is crucial for both holoenzyme formation and catalytic activity. Importantly, expression of WT-PPP2CA protects from LRRK2-G2019S induced neuronal cell death, while PPP2CA-T304 mutants fail to do so, suggesting that impaired PP2A holoenzyme formation might be detrimental for LRRK2-PD.

neuroscience↗

bioRxiv2024

Premature upregulation of miR-92a's target RBFOX2 hijacks PTBP splicing and impairs cortical neuronal differentiation.

Alternative splicing is a crucial component of neuronal differentiation, yet the mechanisms that regulate splicing transitions during embryonic brain development remain incompletely understood. Here, we identify a post-transcriptional mechanism that times the expression of the splicing factor Rbfox2 during neurogenesis. RBFOX2 is normally expressed at low levels in neural progenitor cells (NPCs) and becomes upregulated in newborn neurons where it promotes neuronal differentiation. Unexpectedly, premature expression of Rbfox2 in NPCs of the embryonic mouse neocortex blocked their differentiation into neurons rather than promoting it. Genome-wide analysis revealed widespread alternative splicing changes enriched for NDD genes and associated with a hybrid NPC- and neuron-like splicing pattern that significantly deviates from the normal splicing developmental trajectory. Remarkably, premature Rbfox2 expression induced the inclusion of validated target exons that are otherwise repressed by PTBP2 pointing to an antagonistic splicing relationship. Integrative scRNA-seq analysis confirmed a negatively correlated expression between these two RNA-binding proteins (RBP) along differentiation pseudotime. Strikingly, we identified the NPC-specific miRNA 92a-3p as a regulator of the Rbfox2 expression switch: expression of miR-92a reduced RBFOX2 levels and reversed splicing patterns of target genes in vitro, while silencing miR-92a in vivo increased RBFOX2 expression in the embryonic cortex. Together, these findings reveal a previously unrecognized miRNA-RBP regulatory axis that ensures the proper timing of NPC-to-neuron splicing transitions in the developing cortex and provide new insights into splicing dysregulation as a contributing factor to the emergence of neurodevelopmental disorders. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=152 HEIGHT=200 SRC="FIGDIR/small/614071v3_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@16248caorg.highwire.dtl.DTLVardef@198dd0dorg.highwire.dtl.DTLVardef@d8887aorg.highwire.dtl.DTLVardef@1e8419e_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical Abstract Schematic representation of the proposed splicing regulation for the transition of undifferentiated NPCs to neurons in the developing cerebral cortex.

genomics↗

bioRxiv2023

A core Nrf2 gene set defined through comprehensive transcriptomic analysis predicts drug resistance and poor multi-cancer prognosis

The NRF2-KEAP1 pathway plays an important role in the cellular response to oxidative stress but may also contribute to metabolic changes and drug resistance in cancer. We investigated the activation of NRF2 in human cancers and fibroblast cells through KEAP1 inhibition and cancer associated KEAP1/NRF2 mutations. We define a core set of 14 upregulated NRF2 target genes from seven RNA-Sequencing databases that we generated and analyzed, which we validated this gene set through analyses of published databases and gene sets. An NRF2 activity score based on expression of these core target genes correlates with resistance to drugs such as PX-12 and necrosulfonamide but not to paclitaxel or bardoxolone methyl. We validated these findings and also found NRF2 activation led to radioresistance in cancer cell lines. Finally, our NRF2 score is prognostic for cancer survival and validated in additional independent cohorts for novel cancers types not associated with NRF2-KEAP1 mutations. These analyses define a core NRF2 gene set that is robust, versatile, and useful as a NRF2 biomarker and for predicting drug resistance and cancer prognosis.

cancer biology↗

bioRxiv2022

Quantitative live cell imaging of a tauopathy model enables the identification of a polypharmacological drug candidate that restores physiological microtubule regulation

Tauopathies such as Alzheimers disease are characterized by the aggregation and increased phosphorylation of the microtubule-associated protein tau. The pathological changes in tau are closely linked to neurodegeneration, making tau a prime candidate for intervention. However, the multiple facets of tau function and the lack of cellular tauopathy models that could support mechanism-based drug development hampers progress. Here we report the development of a live-cell imaging approach to quantitatively monitor pathological changes of human tau as it interacts with axonal microtubules. We show that a full-length aggregation-prone tau construct exhibits reduced interaction with microtubules as it increasingly aggregates. Through chemoinformatic analyses, we identified 2-phenyloxazole (PHOX) derivatives as putative polypharmacological small molecules that inhibit tau aggregation and modulate tau phosphorylation. We found that PHOX15 restores the physiological microtubule interaction of aggregation-prone tau in neurons and inhibits the first phase of tau aggregation in vitro. Furthermore, we report that PHOX15 inhibits the tau kinases GSK3{beta} and Cdk5, alters the kinome activity of model neurons, and reduces tau phosphorylation at disease-relevant sites. Molecular dynamics simulations highlight cryptic channel-like pockets crossing tau protofilaments and indicate that the binding of PHOX15 in one of the channels reduces the protofilaments ability to adopt a PHF-like conformation. The data show that our imaging approach provides a useful tool for identifying compounds that modulate tau-microtubule interaction in axons. We demonstrate that a polypharmacological approach to simultaneously treat tau aggregation and tau phosphorylation is able to restore physiological microtubule regulation, identifying PHOX15 as a promising drug candidate to counteract tau-induced neurodegeneration.

neuroscience↗

bioRxiv2021

Novel graph theoretic biological pathway network analytics methods for analyzing and discovering Alzheimer's disease related genes

BackgroundAlzheimers disease (AD) is the most common form of dementia among older people. It is a complex disease and the genetics and environmental factors behind it are not conclusive yet. Traditional statistical analyses are inadequate to identify variants, genes, or pathways capable of explaining AD as a unit. In this context, pathway network analysis based on a set of curated AD-specific genes identified in the literature can elucidate biological mechanisms underneath AD. Through the network, we can infer influential pathways that can together explain AD. Consequently, we can target those pathways and corresponding genes for further analysis to develop new drugs, discover novel AD-related genes, combine multiple hypotheses, and so forth. MethodsWe have developed a novel graph theoretic algorithm that can elucidate complex biology from a given set of disease-related genes. It constructs a weighted network of enriched pathways where similarity score between a pair of pathways is defined in a context-specific manner. To make the network robust, we employ topological overlap techniques on top of the raw similarity measure. We then provide the importance of each pathway with respect to the entire network, functional modules and importance of each pathway in a specific module, gene clusters, and so forth. We also provide a method to identify a set of novel genes that can further explain the disease-related genes and the disease itself. ResultsWe have employed our algorithms onto a set of AD-specific genes. It identified three distinct functional modules that are related to metabolism, cancer, and infectious disease related pathways. These findings are matched with three recognized hypotheses in Alzheimers disease, e.g. "metabolism hypothesis," "cell cycle hypothesis," and "infectious disease hypothesis." By analyzing the curated genes common among those functional modules, we can attain more understanding about this fateful disease. We have also identified 24 novel AD-related genes of which at least 14 genes are known to be involved in AD. ConclusionsWe developed a computational framework for analyzing biological pathways in a context-specific manner. It can be used in any sets of disease-related genes. We manifest its efficacy, reliability, and accuracy by employing a set of AD-specific genes.

bioinformatics↗

bioRxiv2021

Nanobodies as allosteric modulators of Parkinson's disease-associated LRRK2

Mutations in the gene coding for Leucine-Rich Repeat Kinase 2 (LRRK2) are a leading cause of the inherited form of Parkinsons disease (PD), while LRRK2 overactivation is also associated with the more common idiopathic form of PD. LRRK2 is a large multi-domain protein, including a GTPase as well as a Ser/Thr protein kinase domain. Common disease-causing mutations increase LRRK2 kinase activity, presenting LRRK2 as an attractive target for inhibitory drug design. Currently, drug development has mainly focused on ATP-competitive kinase inhibitors. Here, we report the identification and characterization of a variety of Nanobodies that bind to different LRRK2 domains and inhibit or activate LRRK2 activity in cells and in vitro. Importantly, diverse groups of Nanobodies were identified that inhibit LRRK2 kinase activity through a mechanism that does not involve binding to the ATP pocket or even to the kinase domain. Moreover, while certain Nanobodies completely inhibit the LRRK2 kinase activity, we also identified Nanobodies that specifically inhibit the phosphorylation of Rab protein substrates. Finally, in contrast to current type-I kinase inhibitors, the studied kinase-inhibitory Nanobodies did not induce LRRK2 microtubule association. These comprehensively characterized Nanobodies represent versatile tools to study the LRRK2 function and mechanism, and can pave the way toward novel diagnostic and therapeutic strategies for PD.

biochemistry↗

bioRxiv2020

RSGSA: a Robust and Stable Gene Selection Algorithm

Nowadays we are observing an explosion of gene expression data with phenotypes. It enables researchers to efficiently identify genes responsible for certain medical condition as well as classify them for drug target. Like any other phenotype data in medical domain, gene expression data with phenotypes also suffers from being very underdetermined system. In a very large set of features but a very small sample size domains (e.g., DNA microarray, RNA-seq data, GWAS data, etc.), it is often reported that several different spurious feature subsets may yield equally optimal results. This phenomenon is known as instability. Considering these facts, we have developed a very robust and stable supervised gene selection algorithm to select the most discriminating non-spurious set of genes from the gene expression datasets with phenotypes. Stability and robustness is ensured by class and instance levels perturbations, respectively. We have performed rigorous experimental evaluations using 10 real gene expression microarray datasets with phenotypes. It revealed that our algorithm outperforms the state-of-the-art algorithms with respect to stability and classification accuracy. We have also done biological enrichment analysis based on gene ontology-biological processes (GO-BP) terms, disease ontology (DO) terms, and biological pathways.

bioinformatics↗