Biology subjects

Sobie, E.

Publications and source records attributed to Sobie, E..

7 recordsLinked to original sources

bioRxiv2026

GluD1 Modulates GluN2B-containing NMDAR Function and Plasticity at Subicular Synapses

Dysregulation of the delta-type glutamate receptor GluD1 and N-methyl-D-aspartate receptors (NMDARs) is implicated in neuropsychiatric disorders including schizophrenia and intellectual disability, and GluD1 modulates NMDAR response in hippocampal neurons. However, the precise mechanisms by which GluD1 influences specific NMDAR subtypes remain undefined, representing a critical gap given the reliance of synaptic plasticity and cognition on NMDAR composition. GluN2A- and GluN2B-containing NMDARs are essential for synaptic long-term potentiation (LTP) and contextual learning and memory. Here, we used CRISPR/Cas9 to generate GluD1 knockout (KO) in cultured hippocampal neurons and observed a selective decrease in GluN2B-containing NMDAR responses. In acute hippocampal slices, GluD1 KO similarly reduced GluN2B-containing NMDAR currents at ventral CA1[->]subiculum synapses and impaired LTP at these synapses. In vivo, region-specific GluD1 deficiency in the ventral subiculum disrupted long-term contextual memory, indicating a critical role for GluD1 in cognitive processes. These findings demonstrate that GluD1 is indispensable for preserving GluN2B-containing NMDAR function, synaptic plasticity, and memory, providing molecular insight into how GluD1 regulates NMDAR subtypes implicated in synaptic dysfunction in neuropsychiatric disorders. Understanding this mechanism will guide the development of therapeutic strategies that selectively target GluD1-dependent modulation of NMDAR subtypes in brain disease.

neuroscience↗

bioRxiv2025

predicTox: An integrated database of clinical risk frequencies and human gene expression signatures for cardiotoxic drugs

We have used drug-induced transcriptomic responses and whole-genome sequences in healthy human induced pluripotent stem cells (iPSC)-derived cardiomyocyte lines to identify cellular functional pathways and genomic variants potentially associated with the cardiotoxic effects of tyrosine kinase inhibitors (TKIs) and other cancer drugs. Here, we describe predicTox.org, an interactive website that organizes our data and its integration with knowledge from cell pathways and genomic databases. DrugTox summary cards give results of these analyses and metadata for each drug. Fields include FDA Adverse Event Reporting System (FAERS) cardiotoxicity risk scores, cell pathways, and genomic variants potentially associated with drug-induced cardiotoxicity. At a detailed level, predicTox provides ranked lists of pathway signatures that are common for cardiotoxic TKIs, up- and downregulated pathways associated with cardiotoxicity induced by specific TKIs and TKI-regulated genes mapping to those pathways. predicTox provides downloadable lists of drug-induced differentially expressed genes (DEGs) and pathways, drug-related genomic variants associated with cardiotoxicity, all with their statistical metrics, and mathematical models to simulate drug effects on heart physiology. Building on the results of our algorithm for independent reidentification of the well-known rs2229774 variant for anthracycline-induced cardiotoxicity, we describe how our data can be queried to identify potential variants associated with drug-induced cardiotoxicity by affecting a drugs pharmacodynamics and pharmacokinetics.

cancer biology↗

bioRxiv2024

Transient Notch Activation Converts Pluripotent Stem Cell-Derived Cardiomyocytes towards a Purkinje Fiber Fate

Cardiac Purkinje fibers form the most distal part of the ventricular conduction system. They coordinate contraction and play a key role in ventricular arrhythmias. While many cardiac cell types can be generated from human pluripotent stem cells, methods to generate Purkinje fiber cells remain limited, hampering our understanding of Purkinje fiber biology and conduction system defects. To identify signaling pathways involved in Purkinje fiber formation, we analyzed single cell data from murine embryonic hearts and compared Purkinje fiber cells to trabecular cardiomyocytes. This identified several genes, processes, and signaling pathways putatively involved in cardiac conduction, including Notch signaling. We next tested whether Notch activation could convert human pluripotent stem cell-derived cardiomyocytes to Purkinje fiber cells. Following Notch activation, cardiomyocytes adopted an elongated morphology and displayed altered electrophysiological properties including increases in conduction velocity, spike slope, and action potential duration, all characteristic features of Purkinje fiber cells. RNA-sequencing demonstrated that Notch-activated cardiomyocytes undergo a sequential transcriptome shift, which included upregulation of key Purkinje fiber marker genes involved in fast conduction such as SCN5A, HCN4 and ID2, and downregulation of genes involved in contractile maturation. Correspondingly, we demonstrate that Notch-induced cardiomyocytes have decreased contractile force in bioengineered tissues compared to control cardiomyocytes. We next modified existing in silico models of human pluripotent stem cell-derived cardiomyocytes using our transcriptomic data and modeled the effect of several anti-arrhythmogenic drugs on action potential and calcium transient waveforms. Our models predicted that Purkinje fiber cells respond more strongly to dofetilide and amiodarone, while cardiomyocytes are more sensitive to treatment with nifedipine. We validated these findings in vitro, demonstrating that our new cell-specific in vitro model can be utilized to better understand human Purkinje fiber physiology and its relevance to disease.

developmental biology↗

bioRxiv2020

Protein structure-based gene expression signatures

Gene expression signatures (GES) connect phenotypes to mRNA expression patterns, providing a powerful approach to define cellular identity, function, and the effects of perturbations. However, the use of GES has suffered from vague assessment criteria and limited reproducibility. The structure of proteins defines the functional capability of genes, and hence, we hypothesized that enrichment of structural features could be a generalizable representation of gene sets. We derive structural gene expression signatures (sGES) using features from various levels of protein structure (e.g. domain, fold) encoded by the transcribed genes in GES, to describe cellular phenotypes. Comprehensive analyses of data from the Genotype-Tissue Expression Project (GTEx), ARCHS4, and mRNA expression of drug effects on cardiomyocytes show that structural GES (sGES) are useful for identifying robust signatures of biological phenomena. sGES also enables the characterization of signatures across experimental platforms, facilitates the interoperability of expression datasets, and can describe drug action on cells.

bioinformatics↗

bioRxiv2018

Holistic optimization of RNA-seq workflow for multi-threaded environments

SummaryFor many next-generation sequencing pipelines, the most computationally intensive step is the alignment of reads to a reference sequence. As a result, alignment software such as the Burrows-Wheeler Aligner (BWA) is optimized for speed and and is often executed in parallel on the cloud. However, there are other less demanding steps that can also be optimized and significantly increase the speed especially when using many threads. We demonstrate this using a Unique-molecular-identifier (UMI) RNA sequencing pipeline consisting of 3 steps: split, align, and merge. Optimization of all three steps yields a 40% increase in speed when executed using a single thread. However, when executed using 16 threads, we observe a 4-fold improvement over the original parallel imple-mentation and more than an 8-fold improvement over the original single-threaded implementation. In contrast, optimizing only the alignment step results in just a 13% improvement over the original parallel workflow using 16 threads.

bioinformatics↗

bioRxiv2017

Building containerized workflows for RNA-seq data using the BioDepot-workflow-Builder (BwB)

We present the BioDepot-workflow-builder (Bwb), a software tool that allows users to create and execute reproducible bioinformatics workflows using a drag-and-drop interface. Graphical widgets represent Docker containers executing a modular task. Widgets are then graphically linked to build bioinformatics workflows that can be reproducibly deployed across different local and cloud platforms. Each widget contains a form-based user interface to facilitate parameter entry and a console to display intermediate results. Bwb provides tools for rapid customization of widgets, containers and workflows. Saved workflows can be shared using Bwbs native format or exported as shell scripts.

bioinformatics↗

bioRxiv2017

Software solutions for reproducible RNA-seq workflows

Computational workflows typically consist of many tools that are usually distributed as compiled binaries or source code. Each of these software tools typically depends on other installed software, and performance could potentially vary due to versions, updates, and operating systems. We show here that the analysis of mRNA-seq data can depend on the computing environment, and we demonstrate that software containers represent practical solutions that ensure the reproducibility of RNAseq data analyses.

bioinformatics↗