Biology subjects

D'Souza, R.

Publications and source records attributed to D'Souza, R..

7 recordsLinked to original sources

bioRxiv2026

Decoupled calcium homeostasis and signaling associated with cytoskeletal instability in YWHAG R132C induced pluripotent stem cell-derived cortical neurons

YWHAG Syndrome (Developmental and Epileptic Encephalopathy 56, DEE56) is an ultra- rare childhood epilepsy associated with neurodevelopmental delays, with no therapeutic intervention available. Multiple de novo mutations in the YWHAG gene, encoding for the 14-3-3{gamma} protein, have been identified as causative for YWHAG Syndrome. 14-3-3{gamma} interacts with various targets, including major neurodevelopmental signaling proteins such as components of the ROCK pathway. Despite substantial evidence of the essential role of 14-3-3{gamma} in neurite outgrowth, cytoskeletal rearrangements, and neuronal migration during cortical development, little is known regarding the molecular consequences of YWHAG mutations and their effect on neuronal function and survival. Here, we characterized an isogenic, pluripotent stem cell (iPSC) model of YWHAGR132C/+ cortical neurons. The YWHAGR132C/+iPSC-derived neurons exhibited early cytoskeletal phenotypes, coupled with an elevated calcium baseline, lower frequency of calcium spikes, and reduced network activity. The widespread alterations in the transcriptome of mutant neurons revealed a biphasic dysregulation in the core genes and modulators associated with the ROCK pathway that resulted in maturation-dependent changes to cytoskeletal protein stability and calcium phenotypes. Direct inhibition of ROCK with Y27632 further increased the calcium baseline compared to the isogenic control. Exposure of YWHAGR132C/+ neurons to Trypsin-EDTA revealed underlying cytoskeletal instability, which was partially reversed by lovastatin treatment. Further, lovastatin partially rescued the elevated calcium baseline, but not the frequency or amplitude of calcium spikes. Together, these results suggest decoupling of calcium homeostasis and calcium signaling associated with cytoskeletal instability in YWHAGR132C/+ neurons. These findings lay the groundwork for future mechanistic studies of YWHAG function and molecular therapeutic targets for YWHAG Syndrome and YWHAG-associated conditions.

neuroscience↗

bioRxiv2025

p53 status determines the epigenetic response to demethylating agents Azacitidine and Decitabine.

5-Azacitidine (Aza) and 5-Aza-2-deoxycytidine (Dac) are widely used demethylating drugs that directly integrate into nucleic acids. They are frequently used interchangeably, surprisingly as their selectivity is unique from the other, with no predictors of response or clinical biomarkers to indicate drug preference. Using these drugs to induce demethylation, we combine DRIPc-Seq, Immunostaining, RNA-Seq and Mass spectrometry to uncover unique cellular responses. Activation of p53, exclusively by Aza, sustained accumulation of R-loops in CpG islands of p53 target genes. This effect was abolished by the removal of p53, compounded by destabilisation of heterochromatin marks. Dac treatment induced global chromatin modification, sustaining DNA damage, which was heightened in the absence of p53. Rescue experiments reversed the changes observed in the epigenome, demonstrating a direct role for p53 in preserving H3K9me3 and H3K27me3. These insights further our knowledge of how cells recognize and respond to methylation changes and uncover novel roles for p53 in modulation of the epigenome. Further to this, we determine a first in kind biomarker in p53 status that may be relevant for clinical settings.

molecular biology↗

bioRxiv2023

Harnessing Bilayer Biomaterial Delivery of FTY720 as an Immunotherapy to Accelerate Oral Wound Healing

Orofacial clefts are the most common craniofacial congenital anomaly. Following cleft palate repair, up to 60% of surgeries have wound healing complications leading to oronasal fistula (ONF), a persistent connection between the roof of the mouth and the nasal cavity. The current gold standard methods for ONF repair use human allograft tissues; however, these procedures have risks of graft infection and/or rejection, requiring surgical revisions. Immunoregenerative therapies present a novel alternative approach to harness the bodys immune response and enhance the wound healing environment. We utilized a repurposed FDA-approved immunomodulatory drug, FTY720, to reduce the egress of lymphocytes and induce immune cell fate switching toward pro-regenerative phenotypes. Here, we engineered a bilayer biomaterial system using Tegaderm, a liquid-impermeable wound dressing, to secure and control the delivery of FTY720- nanofiber scaffolds (FTY720-NF). We optimized release kinetics of the bilayer FTY720-NF to sustain drug release for up to 7d with safe, efficacious transdermal absorption and tissue biodistribution. Through comprehensive immunophenotyping, our results illustrate a pseudotime pro-regenerative state transition in recruited hybrid immune cells to the wound site. Additional histological assessments established a significant difference in full thickness ONF closure in mice on Day 7 following treatment with bilayer FTY720-NF, compared to controls. These findings demonstrate the utility of immunomodulatory strategies for oral wound healing, better positing the field to develop more efficacious treatment options for pediatric patients. One Sentence SummaryLocal delivery of bilayer FTY720-nanofiber scaffolds in an ONF mouse model promotes complete wound closure through modulation of pro-regenerative immune and stromal cells.

bioengineering↗

bioRxiv2022

Multi-scale phase separation by explosive percolation with single chromatin loop resolution

The 2m-long human DNA is tightly intertwined into the cell nucleus of the size of 10m. The DNA packing is explained by folding of chromatin fiber. This folding leads to the formation of such hierarchical structures as: chromosomal territories, compartments; densely packed genomic regions known as Chromatin Contact Domains (CCDs), and loops. We propose models of dynamical genome folding into hierarchical components in human lymphoblastoid, stem cell, and fibroblast cell lines. Our models are based on explosive percolation theory. The chromosomes are modeled as graphs where CTCF chromatin loops are represented as edges. The folding trajectory is simulated by gradually introducing loops to the graph following various edge addition strategies that are based on topological network properties, chromatin loop frequencies, compartmentalization, or epigenomic features. Finally, we propose the genome folding model - a biophysical pseudo-time process guided by a single scalar order parameter. The parameter is calculated by Linear Discriminant Analysis. We simulate the loop formation by using Loop Extrusion Model (LEM) while adding them to the system. The chromatin phase separation, where fiber folds into topological domains and compartments, is observed when the critical number of contacts is reached. We also observe that 80% of the loops are needed for chromatin fiber to condense in 3D space, and this is constant through various cell lines. Overall, our in-silico model integrates the high-throughput 3D genome interaction experimental data with the novel theoretical concept of phase separation, which allows us to model event-based time dynamics of chromatin loop formation and folding trajectories.

genomics↗

bioRxiv2020

Canonical and noncanonical features of the mouse visual cortical hierarchy

Neocortical circuit computations underlying active vision are performed by a distributed network of reciprocally connected, functionally specialized areas. Mouse visual cortex is a dense, hierarchically organized network, comprising subnetworks that form preferentially interconnected processing streams. To determine the detailed layout of the mouse visual hierarchy, laminar patterns formed by interareal axonal projections, originating in each of ten visual areas were analyzed. Reciprocally connected pairs of areas, and shared targets of pairs of source areas, exhibited structural features consistent with a hierarchical organization. Beta regression analyses, which estimated a continuous measure of hierarchical distance, indicated that the network comprises multiple hierarchies embedded within overlapping processing levels. Single unit recordings showed that within each processing stream, receptive field sizes typically increased with increasing hierarchical level; however, ventral stream areas showed overall larger receptive field diameters. Together, the results reveal canonical and noncanonical hierarchical network motifs in mouse visual cortex.

neuroscience↗

bioRxiv2019

Spatial clustering of inhibition in mouse primary visual cortex

Whether mouse visual cortex contains orderly feature maps is debated. The overlapping pattern of geniculocortical (dLGN) inputs with M2 muscarinic acetylcholine receptor-rich patches in layer 1 (L1) suggests a non-random architecture. Here, we found that L1 inputs from the lateral posterior thalamus (LP) avoid patches and target interpatches. Channelrhodopsin-assisted mapping of EPSCs in L2/3 shows that the relative excitation of parvalbumin-expressing interneurons (PVs) and pyramidal neurons (PNs) by dLGN, LP and cortical feedback are distinct and depend on whether the neurons reside in clusters aligned with patches or interpatches. Paired recordings from PVs and PNs shows that unitary IPSCs are larger in interpatches than patches. The spatial clustering of inhibition is matched by dense clustering of PV-terminals in interpatches. The results show that the excitation/inhibition balance across V1 is organized into patch and interpatch subnetworks which receive distinct long-range inputs and are specialized for the processing of distinct spatiotemporal features.

neuroscience↗

bioRxiv2018

Machine learning versus logistic regression methods for 2-year mortality prognostication in a small, heterogeneous glioma database

BackgroundMachine learning (ML) is the application of specialized algorithms to datasets for trend delineation, categorization or prediction. ML techniques have been traditionally applied to large, highly-dimensional databases. Gliomas are a heterogeneous group of primary brain tumors, traditionally graded using histopathological features. Recently the World Health Organization proposed a novel grading system for gliomas incorporating molecular characteristics. We aimed to study whether ML could achieve accurate prognostication of 2-year mortality in a small, highly-dimensional database of glioma patients.\n\nMethodsWe applied three machine learning techniques: artificial neural networks (ANN), decision trees (DT), support vector machine (SVM), and classical logistic regression (LR) to a dataset consisting of 76 glioma patients of all grades. We compared the effect of applying the algorithms to the raw database, versus a database where only statistically significant features were included into the algorithmic inputs (feature selection).\n\nResultsRaw input consisted of 21 variables, and achieved performance of (accuracy/AUC): 70.7%/0.70 for ANN, 68%/0.72 for SVM, 66.7%/0.64 for LR and 65%/0.70 for DT. Feature selected input consisted of 14 variables and achieved performance of 73.4%/0.75 for ANN, 73.3%/0.74 for SVM, 69.3%/0.73 for LR and 65.2%/0.63 for DT.\n\nConclusionsWe demonstrate that these techniques can also be applied to small, yet highly-dimensional datasets. Our ML techniques achieved reasonable performance compared to similar studies in the literature. Though local databases may be small versus larger cancer repositories, we demonstrate that ML techniques can still be applied to their analysis, though traditional statistical methods are of similar benefit.

neuroscience↗