Biology subjects

McCullumsmith, R.

Publications and source records attributed to McCullumsmith, R..

13 recordsLinked to original sources

bioRxiv2026

Sex-Specific Modulation of Gene Expression by 17beta-Estradiol in Human Meniscal Cells: Pathways to Targeted Osteoarthritis Therapies

Osteoarthritis (OA) disproportionately affects women, and estrogen has been implicated in cartilage and joint homeostasis, yet its effects on meniscal fibrochondrocytes (MFCs), and whether those effects differ by sex, remain poorly defined. We reanalyzed a publicly available RNA-sequencing dataset (Gene Expression Omnibus, GSE199087) comprising human MFCs from a male and a female donor treated with 17{beta}-estradiol (E2) or vehicle. Differential expression, Gene Set Enrichment Analysis, Enrichr, and iLINCS were integrated to identify the transcriptional programs modulated by E2 in each sex. In female MFCs, E2 upregulated pathways governing DNA replication, cell-cycle progression, and genomic maintenance (e.g., MCM8, BRCA1, RAD51), while downregulating inflammatory and extracellular matrix-degrading genes, including MMP1, IL12A, CXCL12, and MYD88. In male MFCs, E2 instead upregulated chromatin remodeling and developmental signaling programs, led by SRCAP, ERCC6, and NOTCH1, and downregulated antigen presentation and mitochondrial genes. These divergent responses indicate that E2 engages distinct, sex-specific transcriptional programs in MFCs, with the female profile favoring proliferation and matrix preservation. Although derived from a limited sample and therefore hypothesis-generating, these findings nominate candidate mechanisms underlying sex differences in meniscal biology and OA susceptibility, and warrant validation in larger, sex-balanced cohorts. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/740612v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@16026fforg.highwire.dtl.DTLVardef@1a048acorg.highwire.dtl.DTLVardef@3246corg.highwire.dtl.DTLVardef@4c598b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Altered molecular signaling pathways in the hippocampus of rhesus monkeys following chronic alcohol use

Context-induced relapse is a significant factor limiting recovery from alcohol use disorder (AUD). However, the molecular processes in the hippocampus, a critical region for contextual memory impacted by chronic alcohol use, remain poorly understood. We used a non-human primate model to test the hypothesis that chronic alcohol use impacts hippocampal molecular pathways that may serve as therapeutic targets for context-induced relapse and memory processing issues associated with chronic alcohol use. We conducted RNAseq profiling on hippocampal samples from adult male rhesus monkeys with chronic alcohol use (n=7) and controls (n=5) from the Monkey Alcohol Tissue Research Resource (MATRR). We identified 2,575 differentially expressed genes (DEGs) in subjects with chronic alcohol use, including genes implicated in genome-wide association studies (GWAS) of alcohol dependence, such as GLP2R and GABBR2. Downregulated pathways included chemical synaptic transmission, trans-synaptic signaling, and neuron development, and upregulated pathways involved mitochondrial function. Targeted pathway analysis highlighted significant downregulation of synaptic signaling (e.g., axonal fasciculation) and upregulation of mitochondrial processes (e.g., electron transport). Leading-edge gene analysis revealed several downregulated genes involved in synaptic signaling including GRIN2B, CACNA1C, and NLGN1 as well as upregulated genes such as NDUFS3 and MT-ND1 involved in mitochondrial processes. Drug repurposing analysis identified several targets including epidermal growth factor receptor (EGFR) inhibitors, and L-type calcium channel blockers as potential therapeutic targets. Our results provide critical insights into molecular pathways underlying hippocampal pathology in chronic alcohol use, emphasizing the roles of mitochondrial function, synaptic regulation and calcium channels, and offering potential novel therapeutic targets.

neuroscience↗

bioRxiv2024

Olfactory combinatorial coding supports risk-reward decision making in C. elegans

Olfactory-driven behaviors are essential for animal survival, but mechanisms for decoding olfactory inputs remain poorly understood. We have used whole-network Ca++ imaging to study olfactory coding in Caenorhabditis elegans. We show that the odorant 1-octanol is encoded combinatorially in the periphery as both an attractant and a repellant. These inputs are integrated centrally, and their relative strengths determine the sensitivity and valence of the behavioral response through modulation of locomotory reversals and speed. The balance of these pathways also dictates the activity of the locomotory command interneurons, which control locomotory reversals. This balance serves as a regulatory node for response modulation, allowing C. elegans to weigh opportunities and hazards in its environment when formulating behavioral responses. Thus, an odorant can be encoded simultaneously as inputs of opposite valence, focusing attention on the integration of these inputs in determining perception, response, and plasticity.

neuroscience↗

bioRxiv2023

In Silico Transcriptome-based Screens Identify Epidermal Growth Factor Receptor Inhibitors as Therapeutics for Noise-induced Hearing Loss

Noise-Induced Hearing Loss (NIHL) represents a widespread disease for which no therapeutics have been approved by the Food and Drug Administration (FDA). Addressing the conspicuous void of efficacious in vitro or animal models for high throughput pharmacological screening, we utilized an in silico transcriptome-oriented drug screening strategy, unveiling 22 biological pathways and 64 promising small molecule candidates for NIHL protection. Afatinib and zorifertinib, both inhibitors of the Epidermal Growth Factor Receptor (EGFR), were validated for their protective efficacy against NIHL in experimental zebrafish and murine models. This protective effect was further confirmed with EGFR conditional knockout mice and EGF knockdown zebrafish, both demonstrating protection against NIHL. Molecular analysis using Western blot and kinome signaling arrays on adult mouse cochlear lysates unveiled the intricate involvement of several signaling pathways, with particular emphasis on EGFR and its downstream pathways being modulated by noise exposure and Zorifertinib treatment. Administered orally, Zorifertinib was successfully detected in the perilymph fluid of the inner ear in mice with favorable pharmacokinetic attributes. Zorifertinib, in conjunction with AZD5438 - a potent inhibitor of cyclin dependent kinase 2 - produced synergistic protection against NIHL in the zebrafish model. Collectively, our findings underscore the potential application of in silico transcriptome-based drug screening for diseases bereft of efficient screening models and posit EGFR inhibitors as promising therapeutic agents warranting clinical exploration for combatting NIHL. HighlightsO_LIIn silico transcriptome-based drug screens identify pathways and drugs against NIHL. C_LIO_LIEGFR signaling is activated by noise but reduced by zorifertinib in mouse cochleae. C_LIO_LIAfatinib, zorifertinib and EGFR knockout protect against NIHL in mice and zebrafish. C_LIO_LIOrally delivered zorifertinib has inner ear PK and synergizes with a CDK2 inhibitor. C_LI

neuroscience↗

bioRxiv2023

Ribosomal dysregulation: A conserved pathophysiological mechanism in human depression and mouse chronic stress.

The underlying biological mechanisms that contribute to the heterogeneity of major depressive disorder (MDD) presentation remain poorly understood, highlighting the need for a conceptual framework that can explain this variability and bridge the gap between animal models and clinical endpoints. Here, we hypothesize that comparative analysis of molecular data from different experimental systems of chronic stress and MDD has the potential to provide insight into these mechanisms and address this gap. Thus, we compared transcriptomic profiles of brain tissue from postmortem MDD subjects and from mice exposed to chronic variable stress (CVS) to identify orthologous genes. Ribosomal protein genes (RPGs) were downregulated, and associated RP-pseudogenes were upregulated in both conditions. Analysis across independent cohorts confirmed that this dysregulation was specific to the prefrontal cortex of both species. A seeded gene co-expression analysis using altered RPGs common between the MDD and CVS groups revealed that downregulated RPGs homeostatically regulated the synaptic changes in both groups through a RP-pseudogene-driven mechanism. In-vitro and in-silico analysis further demonstrated that the inverse RPG/RP-pseudogene association was a glucocorticoid-driven endocrine response to stress that was reversed during remission from MDD. This study provides the first evidence that ribosomal dysregulation during stress is a conserved phenotype in human MDD and CVS exposed mouse. Our results establish a foundation for the hypothesis that stress-induced alterations in RPGs and, consequently, ribosomes contribute to the synaptic dysregulation underlying MDD and chronic stress-related mood disorders. We discuss a ribosome-dependent mechanism for the variable presentations of depression and other mood disorders. Significance StatementThe presented study highlights the pressing need for a connection between animal models of depression and clinical endpoints. The lack of concordance between these two areas has hindered our understanding of MDDs biological underpinnings. The studys hypothesis that orthologous gene from experimental systems of chronic stress and MDD can bridge this gap is a major advance in this field. The study indicates that dysregulation of ribosomes in the synapse is a common feature in both human MDD and mice exposed to CVS. This dysregulation is a response to endocrine disturbances and is driven by mechanisms that involve pseudogenes. These findings support the hypothesis that stress-induced alterations in RPGs and, consequently, ribosomes may contribute to the variable presentations of depression.

neuroscience↗

bioRxiv2021

Proteoglycan Clusters as a Site of Coordinated, Multi-Dendritic Plasticity

Experience-dependent learning depends on synaptic plasticity. While plasticity in individual synapses has been extensively investigated, the mechanisms underlying coordinated changes across sets of synapses on multiple dendrites, likely needed to encode effective adaptations to a salient stimulus, are not well understood. The extracellular matrix is uniquely well suited to fulfill this function, as rapid glia-driven remodeling of its local composition powerfully impact synaptic plasticity. We show that extracellular matrix microenvironments, named CS6 clusters, dynamically form around several dendrites in response to sensory stimuli in coincidence to stimulus-driven synaptic plasticity. CS6 clusters, formed by glia-dependent secretion of extracellular matrix components surrounding sets of adjacent dendrites, may represent a novel structure supporting coordinated synaptic plasticity. One Sentence SummaryExtracellular matrix clusters form microenvironments for coordinated multi-dendrite synaptic plasticity.

neuroscience↗

bioRxiv2020

Accelerating Drug Discovery and Repurposingby Combining Transcriptional Signature Connectivity with Docking

The development of targeted treatment options for precision medicine is hampered by a slow and costly process of drug screening. While small molecule docking simulations are often applied in conjunction with cheminformatic methods to reduce the number of candidate molecules to be tested experimentally, the current approaches suffer from high false positive rates and are computationally expensive. Here, we present a novel in silico approach for drug discovery and repurposing, dubbed connectivity enhanced Structure Activity Relationship (ceSAR) that improves on current methods by combining docking and virtual screening approaches with pharmacogenomics and transcriptional signature connectivity analysis. ceSAR builds on the landmark LINCS library of transcriptional signatures of over 20,000 drug-like molecules and ~5,000 gene knock-downs (KDs) to connect small molecules and their potential targets. For a set of candidate molecules and specific target gene, candidate molecules are first ranked by chemical similarity to their concordant LINCS analogs that share signature similarity with a knock-down of the target gene. An efficient method for chemical similarity search, optimized for sparse binary fingerprints of chemical moieties, is used to enable fast searches for large libraries of small molecules. A small subset of candidate compounds identified in the first step is then re-scored by combining signature connectivity with docking simulations. On a set of 20 DUD-E benchmark targets with LINCS KDs, the consensus approach reduces significantly false positive rates, improving the median precision 3-fold over docking methods at the extreme library reduction. We conclude that signature connectivity and docking provide complementary signals, offering an avenue to improve the accuracy of virtual screening while reducing run times by multiple orders of magnitude.

bioinformatics↗

bioRxiv2020

KRSA: Network-based Prediction of Differential Kinase Activity from Kinome Array Data

MotivationPhosphorylation by serine-threonine and tyrosine kinases is critical for determining protein function. Array-based approaches for measuring multiple kinases allow for the testing of differential phosphorylation between conditions for distinct sub-kinomes. While bioinformatics tools exist for processing and analyzing such kinome array data, current open-source tools lack the automated approach of upstream kinase prediction and network modeling. The presented tool, alongside other tools and methods designed for gene expression and protein-protein interaction network analyses, help the user better understand the complex regulation of gene and protein activities that forms biological systems and cellular signaling networks. ResultsWe present the Kinome Random Sampling Analyzer (KRSA), a web-application for kinome array analysis. While the underlying algorithm has been experimentally validated in previous publications, we tested the full KRSA application on dorsolateral prefrontal cortex (DLPFC) in male (n=3) and female (n=3) subjects to identify differential phosphorylation and upstream kinase activity. Kinase activity differences between males and females were compared to a previously published kinome dataset (11 female and 7 male subjects) which showed similar patterns to the global phosphorylation signal. Additionally, kinase hits were compared to gene expression databases for in silico validation at the transcript level and showed differential gene expression of kinases. Availability and implementationKRSA as a web-based application can be found at http://bpg-n.utoledo.edu:3838/CDRL/KRSA/. The code and data are available at https://github.com/kalganem/KRSA. Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2020

Region-Specific PSD-95 Interactomes Contribute to Functional Diversity of Excitatory Synapses in Human Brain.

The overarching goal of this exploratory study is to link subcellular microdomain specific protein-protein interactomes with big data analytics. We isolated postsynaptic density-95 (PSD-95) complexes from four human brain regions and compared their protein interactomes using multiple bioinformatics techniques. We demonstrate that human brain regions have unique postsynaptic protein signatures that may be used to interrogate perturbagen databases. Assessment of our hippocampal signature using the iLINCS database yielded several compounds with recently characterized "off target" effects on protein-protein interactions in the posynaptic density compartment.

neuroscience↗

bioRxiv2020

Kaleidoscope: A New Bioinformatics Pipeline Web Application for In Silico Hypothesis Exploration of Omics Signatures

BackgroundIn silico data exploration is a key first step of exploring a research question. There are many publicly available databases and tools that offer appealing features to help with such a task. However, many applications lack exposure or are constrained with unfriendly or outdated user interfaces. Thus, it follows that there are many resources that are relevant to investigation of medical disorders that are underutilized. ResultsWe developed an R Shiny web application, called Kaleidoscope, to address this challenge. The application offers access to several omics databases and tools to let users explore research questions in silico. The application is designed to be user- friendly with a unified user interface, while also scalable by offering the option of uploading user-defined datasets. We demonstrate the application features with a starting query of a single gene (Disrupted in schizophrenia 1, DISC1) to assess its protein-protein interactions network. We then explore expression levels of the gene network across tissues and cell types in the brain, as well as across 34 schizophrenia versus control differential gene expression datasets. ConclusionKaleidoscope provides easy access to several databases and tools under a unified user interface to explore research questions in silico. The web application is open-source and freely available at https://kalganem.shinyapps.io/Kaleidoscope/. This application streamlines the process of in silico data exploration for users and expands the efficient use of these tools to stakeholders without specific bioinformatics expertise.

bioinformatics↗

bioRxiv2020

Transcriptional profile of pyramidal neurons in chronic schizophrenia reveals lamina-specific dysfunction of neuronal immunity

While the pathophysiology of schizophrenia has been extensively investigated using homogenized postmortem brain samples, few studies have examined changes in brain samples with techniques that may attribute perturbations to specific cell types. To fill this gap, we performed microarray assays on mRNA isolated from anterior cingulate cortex (ACC) superficial and deep pyramidal neurons from 12 schizophrenia and 12 control subjects using laser capture microdissection. Among all the annotated genes, we identified 134 significantly increased and 130 decreased genes in superficial pyramidal neurons, while 93 significantly increased and 101 decreased genes were found in deep pyramidal neurons, in schizophrenia compared to control subjects. In these differentially expressed genes, we detected lamina-specific changes of 55 and 31 genes in superficial and deep neurons in schizophrenia, respectively. Gene set enrichment analysis (GSEA) was applied to the entire pre-ranked differential expression gene lists to gain a complete pathway analysis throughout all annotated genes. Our analysis revealed over-represented groups of gene sets in schizophrenia, particularly in immunity and synapse related pathways in pyramidal neurons, suggesting the disruption of these pathways plays an important role in schizophrenia. We also detected pathways previously demonstrated in schizophrenia pathophysiology, including cytokine and chemotaxis, post-synaptic signaling, and glutamatergic synapses. In addition, we observed several novel pathways, including ubiquitin-independent protein catabolic process. By comparing our differential expression gene profiles with 51 antipsychotic treatment datasets, we demonstrated that our results were not influenced by antipsychotic treatment of our subjects. Taken together, we found pyramidal neuron-specific changes in neuronal immunity, synaptic dysfunction, and olfactory dysregulation in schizophrenia, providing new insights for the cell-subtype specific pathophysiology of chronic schizophrenia.

neuroscience↗

bioRxiv2019

Protein expression of prenyltransferase subunits in postmortem schizophrenia dorsolateral prefrontal cortex

The pathophysiology of schizophrenia includes altered neurotransmission, dysregulated intracellular signaling pathway activity, and abnormal dendritic morphology that contribute to deficits of synaptic plasticity in the disorder. These processes all require dynamic protein-protein interactions at cell membranes. Lipid modifications target proteins to membranes by increasing substrate hydrophobicity by the addition of a fatty acid or isoprenyl moiety, and recent evidence suggests that dysregulated post-translational lipid modifications may play a role in multiple neuropsychiatric disorders including schizophrenia. Consistent with these emerging findings, we have recently reported decreased protein S-palmitoylation in schizophrenia. Protein prenylation is a lipid modification that occurs upstream of S-palmitoylation on many protein substrates, facilitating membrane localization and activity of key intracellular signaling proteins. Accordingly, we hypothesized that in addition to palmitoylation, protein prenylation may be abnormal in schizophrenia. To test this, we assayed protein expression of the five prenyltransferase subunits (FNTA, FNTB, PGGT1B, RABGGTA, and RABGGTB) in postmortem dorsolateral prefrontal cortex from patients with schizophrenia and paired comparison subjects (N = 13 pairs). We found decreased levels of FNTA (14%), PGGT1B (13%), and RABGGTB (8%) in schizophrenia. To determine if upstream or downstream factors may be driving these changes, we also assayed protein expression of the isoprenoid synthases FDPS and GGPS1, and prenylation-dependent processing enzymes REC and ICMT. We found these upstream and downstream enzymes to have normal protein expression. To rule out effects from chronic antipsychotic treatment, we assayed FNTA, PGGT1B and RABGGTB in cortex from rats treated long-term with haloperidol decanoate, and found no change in the expression of these proteins. Given the role prenylation plays in localization of key signaling proteins found at the synapse, these data offer a potential mechanism underlying abnormal protein-protein interactions and protein localization in schizophrenia.

neuroscience↗

bioRxiv2018

Connectivity analyses of bioenergetic changes in schizophrenia: Identification of novel treatments

We utilized a cell-level approach to examine glycolytic pathways in the DLPFC of subjects with schizophrenia (n=16) and control (n=16) subjects and found decreased mRNA expression of glycolytic enzymes in pyramidal neurons, but not astrocytes. To replicate these novel bioenergetic findings, we probed independent datasets for bioenergetic targets and found similar abnormalities. Next, we used a novel strategy to build a schizophrenia bioenergetic profile by a tailored application of the Library of Integrated Network-Based Cellular Signatures data portal (iLINCS) and investigated connected cellular pathways, kinases, and transcription factors using Enrichr. Finally, with the goal of identifying drugs capable of \"reversing\" the bioenergetic schizophrenia signature, we performed a connectivity analysis with iLINCS and identified peroxisome proliferator-activated receptor (PPAR) agonists as promising therapeutic targets. We administered a PPAR agonist to the GluN1 knockdown model of schizophrenia and found it improved long-term memory. Taken together, our findings suggest that tailored bioinformatics approaches, coupled with the LINCS library of transcriptional signatures of chemical and genetic perturbagens may be employed to identify novel treatment strategies for schizophrenia and related diseases.

neuroscience↗