Biology subjects

McDermott, M.

Publications and source records attributed to McDermott, M..

17 recordsLinked to original sources

bioRxiv2026

CTR1-mediated copper uptake orchestrates metabolic-epigenetic regulation of pathogenic TH17 cells in autoimmune disease

Pathogenic T helper 17 (pTH17) cells are a subset of CD4+ T cells driving autoimmune diseases including multiple sclerosis (MS). Compared to homeostatic TH17 cells and other TH subsets, pTH17 have enhanced mitochondrial function and oxidative phosphorylation (OXPHOS) that supports their differentiation and pathogenic function. Here we identify Copper Transporter 1 (CTR1), encoded by Slc31a1, as essential for copper uptake in CD4+ T cells, OXPHOS and pTH17 cell differentiation and function. While copper levels are known to be higher in the cerebrospinal fluid of patients with MS compared to healthy individuals, and excess copper contributes to oligodendrocyte loss in murine models of MS, the effect of copper on T cell function and pathogenicity in MS are unclear. We demonstrate that deletion of Slc31a1 in CD4+ T cells decreased intracellular copper levels, disrupting mitochondrial respiration and rewiring metabolism. These changes altered the epigenetic landscape of pTH17 cells by impairing DNA demethylation capacity, leading to hypermethylated DNA and altered chromatin accessibility at key binding sites for AP-1 transcription factors essential for pTH17 differentiation. As a result, CTR1-deficient T cells showed defective differentiation into pTH17 cells, with decreased production of IL-17A and expression of TH17 signature genes, while the differentiation of other CD4+ T cell subsets remained largely unaffected. Moreover, T cell-specific deletion of Slc31a1 protected mice from central nervous system (CNS) inflammation in the experimental autoimmune encephalomyelitis (EAE) model of MS by suppressing clonal expansion of autoreactive CD4+ T cells. These findings establish copper as a critical regulator of pTH17 differentiation and function, revealing a previously unknown molecular link between copper homeostasis, metabolism and epigenetic regulation governing pTH17-mediated autoimmunity.

immunology↗

bioRxiv2026

CD11c+ microglia promote dysfunctional T cell activation in diffuse midline glioma

Paediatric diffuse midline glioma (DMG) remains refractory to immunotherapy despite T-cell infiltration, indicating that local mechanisms actively suppress anti-tumour immunity. Using complementary genetic and orthotopic mouse models, we performed lineage-resolved profiling of the DMG immune microenvironment, resolving myeloid ontogeny and microglial states by distinguishing resident microglia from infiltrating bone marrow-derived macrophages. We identified microglia as the predominant tumour-associated myeloid population and discovered selective expansion of CD11c positive; microglia exhibiting enriched antigen-presentation and immune-regulatory transcriptional programs. Tumour-infiltrating CD4+; and CD8+; T cells exhibited chronic activation and exhaustion, while ligand receptor analysis predicted inhibitory microglia T cell communication. Pharmacological CSF1R inhibition depleted CD11c positive; microglia, attenuated antigen-presentation and immune-regulatory programs, and shifted tumour-infiltrating T cells toward a less exhausted phenotype. Together, these findings identify a previously unrecognised CD11 positive; microglia T-cell axis that establishes immune dysfunction in DMG and provide a rationale for combining myeloid- and T cell-targeted immunotherapies.

cell biology↗

bioRxiv2026

ER cholesteryl ester phase separation underlies switch-like cholesterol sensing

Cellular lipid homeostasis requires mechanisms that detect subtle changes in lipid abundance and trigger rapid, coordinated responses. The INSIG/SCAP/SREBP2 pathway provides a central feedback system linking endoplasmic reticulum (ER) cholesterol levels to the transcriptional control of cholesterol genes, yet the origin of its remarkable cooperative switch mechanism remains unclear. Here we identify cholesterol esterification as a physical mechanism that amplifies sterol sensing and generates switch-like pathway regulation. We show that cholesteryl oleate (CE), produced by SOAT1 and opposed by NCEH1-mediated hydrolysis, undergoes a cooperative phase transition within the ER membrane to form transient CE-rich domains. These lipid assemblies create a threshold-dependent platform that concentrates SCAP and promotes formation of the SCAP-INSIG retention complex, thereby coupling ER lipid organization to SREBP inhibition. Because CE domain formation is nucleation-driven, variations in cholesterol availability are converted into an abrupt transition between distinct membrane states. Perturbing CE metabolism uncouples cholesterol abundance from pathway activity: SOAT1 inhibition prevents CE domain formation, releases SCAP from the ER, and activates SREBP2 despite cholesterol sufficiency, whereas NCEH1 inhibition stabilizes the domains and reduces SREBP2 activation under cholesterol-limiting conditions. Thus, the balance between esterification and hydrolysis determines a membrane physical state that serves as the functional output sensed by the cholesterol regulatory machinery. Our findings reveal ER lipid phase transitions as a general principle for creating ultrasensitive control in cellular homeostasis and establish cholesterol esterification as an active regulatory process rather than a passive storage pathway.

cell biology↗

bioRxiv2026

A Quartet of Native Orai Channel Isoforms Orchestrates Graded NFAT Activation and Transcription

The Ca{superscript 2} release-activated Ca{superscript 2} (CRAC) channel mediates store-operated calcium entry (SOCE), a ubiquitous pathway essential for many cell types, including immune cells. Three Orai (Orai1/2/3) proteins constitute the plasma membrane pore-forming units of CRAC channels that are activated by the endoplasmic reticulum (ER) Ca2+-sensing STIM1/2 proteins when ER Ca2+ stores are depleted. Orai1/2/3 are differentially expressed across primary cells with discernible differences in their structures and biophysical properties. Further, Orai1 has two alternatively translated isoforms: long mammalian-specific Orai1 and the 63-residue shorter Orai1{beta}, which is evolutionarily older and conserved across vertebrates. Whether Orai1/1{beta}/2/3 produce unique cytosolic Ca{superscript 2} signatures that bias transcriptional responses through effectors like NFAT is unclear. Here, we used HEK293 cells engineered to express one native Orai isoform and show that all Orai isoforms couple to NFAT1/4 induction. The magnitude of NFAT1/4 induction for each Orai isoform matches that of SOCE, with the following profile: Orai1{beta}>Orai1>>Orai2>Orai3. Near-native re-expression of either Orai1 or Orai1{beta} in primary murine Orai1-/- CD4 T cells restored SOCE, NFAT activation, cytokine production and promoted near identical transcriptional responses enriched for immune activation pathways. An analysis of genetic and clinical data of human individuals showed that homozygous null mutations selectively abolishing Orai1 are not associated with disease resembling CRAC channelopathy. Primary T cells from individuals homozygous or heterozygous for an Orai1 null mutation showed enhanced, rather than impaired, SOCE and NFAT induction. Our data indicate that NFAT activation and transcriptional outputs are primarily driven by the graded strength of SOCE mediated by each isoform of the Orai quartet.

cell biology↗

bioRxiv2026

A Mecom—Cdk6 toggle switch governs hematopoietic stem-to-multipotent fate transitions via distinct multistable landscapes

Hematopoietic stem cells are required to regenerate the blood system throughout life. We previously discovered that transitions between quiescent stem and multipotent progenitor states are controlled by mutual inhibition between Mecom and Cdk6, with upstream regulation from the insulin-like growth factor (IGF) signaling pathway. To investigate the dynamics of exit from quiescence and the stem-to-multipotent cell state transition, we modeled the Mecom-Cdk6 regulatory network via coupled nonlinear differential equations. Bifurcation analysis revealed that the model permits tetrastability, with two stable intermediate states, suggesting that stem cell exit from quiescence proceeds via multiple fine-scale transitions. Perturbation of Mecom self-activation reorganized the multistable landscape, producing two IGF-dependent landscapes with distinct geometries. At high IGF, transitions proceeded only through an intermediate state, whereas at low IGF, a distinct landscape emerged permitting direct transitions between cell states. Stochastic simulations and minimum action path analysis showed that the multipotent attractor is deep at high IGF, whereas low IGF promotes a transition to quiescence by stabilizing the stem cell state. Simulated pharmacological intervention via CDK4/6 inhibitors destabilized the multipotent state and favored transitions towards a more stem-like quiescent state. Together, these results demonstrate how IGF signaling, Mecom self-activation, and Cdk6 inhibition jointly shape early stem cell fate decisions by dictating the accessible cell states on multistable landscapes and the transition paths that connect them.

Systems Biology↗

bioRxiv2026

A CURE for synthetic regulation of gene expression: Rapid screening of guide RNA efficacy as a framework for enabling undergraduate research in plant synthetic biology

Course-based Undergraduate Research Experiences (CUREs) have emerged as a transformative approach to science education, expanding access to authentic research opportunities beyond the traditional undergraduate research assistant (URA) training. By embedding research into a curriculum, CUREs engage a broad and diverse population of students in a classroom environment that emphasizes experimental design, data analysis, and scientific communication. However, this has been difficult to develop for fields such as plant synthetic biology due to the long timescales of plant transformation. One avenue around this problem is to utilize a recent innovation that enables high throughput and rapid screening of gRNA efficacy by leveraging viral-based delivery of guide RNAs (gRNAs). In this work, we develop and validate a CURE with undergraduate students at Colorado State University (CSU). Students worked in teams to design and test efficacy of gRNAs targeting a Cas9-based transcriptional repressor to different regions of the promoters of the three GIBBERELLIN INSENSITIVE 1 genes (GID1a, GID1b, and GID1c) in Arabidopsis thaliana. Over the semester, students generated and analyzed gene expression data to understand the efficiency of twelve new gRNAs. We further validated CURE student-identified gRNAs with an undergraduate research assistant (URA) that assessed target gene expression and phenotypic outcomes in stable transgenic lines expressing SynTF constructs with the strongest gRNAs from the class. We further describe the curriculum structure to facilitate adoption at other institutions and present student-generated datasets demonstrating the utility of ViN-based screening for identifying effective SynTF gRNAs for plant functional genomics and engineering.

synthetic biology↗

bioRxiv2024

Machine Learning Approach to Single Cell Transcriptomic Analysis of Sjogren's Disease Reveals Altered Activation States of B and T Lymphocytes

Sjogrens Disease (SjD) is an autoimmune disorder characterized by salivary and lacrimal gland dysfunction and immune cell infiltration leading to gland inflammation and destruction. Although SjD is a common disease, its pathogenesis is not fully understood. In this study, we conducted a single-cell transcriptome analysis of peripheral blood mononuclear cells (PBMC) from patients with SjD and symptomatic non-SjD controls to identify cell types and functional changes involved in SjD pathogenesis. All PBMC populations showed marked differences in gene expression between SjD patients and controls, particularly an increase in interferon (IFN) signaling gene signatures. T and B cells of SjD patients displayed a depletion of ribosomal gene expression and pathways linked to protein translation. SjD patients had increased frequencies of naive B cells, which featured a unique gene expression profile (GEP) distinct from controls and had hallmarks of B cell hyperactivation. Non-negative matrix factorization (NMF) also identified several non-overlapping GEPs in CD4+ and CD8+ T cells with differential usage in SjD patients and controls. Of these, only the Th1 activation GEP was enriched in T cells of SjD patients whereas the other two GEPs were depleted in T cells, emphasizing the important role of Th1 cells in SjD. Our study provides evidence for aberrant and unique gene expression patterns in both B and T lymphocytes of SjD patients that point to their altered activation states and may provide new insights into the pathogenesis of SjD.

immunology↗

bioRxiv2024

Modeling the dynamics of EMT reveals genes associated with pan-cancer intermediate states and plasticity

Epithelial-mesenchymal transition (EMT) is a developmental cell state transition co-opted by cancer to drive metastasis and resistance. Stable EMT intermediate states play a particularly important role in cell state plasticity and confer metastatic potential. To explore the dynamics of EMT and identify marker genes of highly metastatic intermediate cells, we analyzed EMT across multiple tumor types and stimuli via mathematical modeling with single-cell RNA-sequencing (scRNA-seq) data. We identified pan-cancer genes consistently expressed or upregulated in EMT intermediate states, most of which were not previously annotated as markers of EMT. Using Bayesian parameter inference, we fit a simple mathematical model to scRNA-seq data, revealing tumor-specific transition rates. This mathematical model offers a framework to quantify EMT progression. A consensus analysis of differential intermediate expression, regulation, and model-derived dynamics identified marker genes associated with persistence of the intermediate EMT state. SFN and NRG1 emerged as genes with the strongest evidence for their role influencing intermediate EMT dynamics. Through analysis of an independent cell line, we verified the role of SFN as a marker intermediate EMT transition. Modeling and inference of genes associated with EMT dynamics offer means to find biomarkers and to identify therapeutic approaches to harness or reverse tumor-promoting cell state transitions driven by EMT.

systems biology↗

bioRxiv2024

Data-driven model discovery and model selection for noisy biological systems

Biological systems exhibit complex dynamics that differential equations can often adeptly represent. Ordinary differential equation models are widespread; until recently their construction has required extensive prior knowledge of the system. Machine learning methods offer alternative means of model construction: differential equation models can be learnt from data via model discovery using sparse identification of nonlinear dynamics (SINDy). However, SINDy struggles with realistic levels of biological noise and does not incorporate prior knowledge of the system. We propose a data-driven framework for model discovery and model selection using hybrid dynamical systems: partial models containing missing terms. Neural networks are used to approximate the unknown dynamics of a system, enabling the denoising the data while simultaneously learning the latent dynamics. Simulations from the fitted neural network are then used to infer models using SINDy. We show, via model selection, that model discovery in SINDy with hybrid dynamical systems outperforms alternative approaches. We find it possible to infer models correctly up to high levels of biological noise of different types. We demonstrate the potential to learn models from sparse, noisy data in application to a canonical cell state transition using data derived from single-cell transcriptomics. Overall, this approach provides a practical framework for model discovery in biology in cases where data are noisy and sparse, of particular utility when the underlying biological mechanisms are partially but incompletely known.

systems biology↗

bioRxiv2024

Regulatory T cells and IFN-γ-producing Th1 cells play a critical role in the pathogenesis of Sjögren's Syndrome

ObjectivesSjogrens Disease (SjD) is an autoimmune disorder characterized by progressive dysfunction, inflammation and destruction of salivary and lacrimal glands, and by extraglandular manifestations. Its etiology and pathophysiology remain incompletely understood, though a role for autoreactive B cells has been considered key. Here, we investigated the role of effector and regulatory T cells in the pathogenesis of SjD. MethodsHistological analysis, RNA-sequencing and flow cytometry were conducted on glands, lungs, eyes and lymphoid tissues of mice with regulatory T cell-specific deletion of stromal interaction proteins (STIM) 1 and 2 (Stim1/2Foxp3), which play key roles in calcium signaling and T cell function. The pathogenicity of T cells from Stim1/2Foxp3mice was investigated through adoptively transfer into lymphopenic host mice. Additionally, single-cell transcriptomic analysis was performed on peripheral blood mononuclear cells (PBMCs) of patients with SjD and control subjects. ResultsStim1/2Foxp3 mice develop a severe SjD-like disorder including salivary gland (SG) and lacrimal gland (LG) inflammation and dysfunction, autoantibodies and extraglandular symptoms. SG inflammation in Stim1/2Foxp3 mice is characterized by T and B cell infiltration, and transcriptionally by a Th1 immune response that correlates strongly with the dysregulation observed in patients with SjD. Adoptive transfer of effector T cells from Stim1/2Foxp3 mice demonstrates that the SjD-like disease is driven by interferon (IFN)-{gamma} producing autoreactive CD4+ T cells independently of B cells and autoantiboodies. scRNA-seq analysis identifies increased Th1 responses and attenuated memory Treg function in PBMCs of patients with SjD. ConclusionsWe report a more accurate mouse model of SjD while providing evidence for a critical role of Treg cells and IFN-{gamma} producing Th1 cells in the pathogenesis of SjD, which may be effective targets for therapy.

immunology↗

bioRxiv2022

Comparative Mucomic Analysis of Three Functionally Distinct Cornu aspersum Secretions

Every animal secretes mucus, placing them among the most diverse biological materials. Mucus hydrogels are complex mixtures of water, ions, carbohydrates, and proteins. Uncertainty surrounding their composition and how interactions between components contribute to mucus function complicates efforts to exploit their properties. There is substantial interest in commercializing mucus from the garden snail, Cornu aspersum, for skincare, drug delivery, tissue engineering, and composite materials. C. asperum secretes three mucus -- one shielding the animal from environmental threats, one adhesive mucus from the pedal surface of the foot, and another pedal mucus that is lubricating. It remains a mystery how compositional differences account for their substantially different properties. Here, we characterize mucus proteins, glycosylation, ion content, and mechanical properties to understand structure-function relationships through an integrative "mucomics" approach. We identify new macromolecular components of these hydrogels, including a novel protein class termed Conserved Anterior Mollusk Proteins (CAMPs). Revealing differences between C. aspersum mucus shows how considering structure at all levels can inform the design of mucus-inspired materials.

biochemistry↗

bioRxiv2021

Steroid hormone catabolites activate the pyrin inflammasome through a non-canonical mechanism

The pyrin inflammasome acts as a guard of RhoA GTPases and is central to immune defences against RhoA-manipulating pathogens. Pyrin activation proceeds in two steps. Yet, the second step is still poorly understood. Using cells constitutively activated for the pyrin step 1, a chemical screen identified etiocholanolone and pregnanolone, two catabolites of testosterone and progesterone, acting at low concentrations as specific step-2 activators. High concentrations of these metabolites fully and rapidly activated pyrin, in a human-specific, B30.2 domain-dependent manner and without inhibiting RhoA. Mutations in MEFV, encoding pyrin, cause two distinct autoinflammatory diseases (PAAND and FMF). Monocytes from PAAND patients, and to a lower extent from FMF patients, displayed increased responses to these metabolites. This study provides a new perspective on pyrin activation, indicates that endogenous steroid catabolites can drive autoinflammation, through the pyrin inflammasome, and explains the "steroid fever" described in the late 1950s, upon steroid injection in humans.

immunology↗

bioRxiv2021

APIR: a universal FDR-control framework for boosting peptide identification power by aggregating multiple proteomics database search algorithms

Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and control on the false discovery rate (FDR). To fill in this gap, we propose a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard shows that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies show that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR.

bioinformatics↗

bioRxiv2020

Clipper: p-value-free FDR control on high-throughput data from two conditions

High-throughput biological data analysis commonly involves identifying features such as genes, genomic regions, and proteins, whose values differ between two conditions, from numerous features measured simultaneously. The most widely-used criterion to ensure the analysis reliability is the false discovery rate (FDR), which is primarily controlled based on p-values. However, obtaining valid p-values relies on either reasonable assumptions of data distribution or large numbers of replicates under both conditions. Clipper is a general statistical framework for FDR control without relying on p-values or specific data distributions. Clipper outperforms existing methods for a broad range of applications in high-throughput data analysis.

bioinformatics↗

bioRxiv2019

Women and Men Were Proportionally Represented Among Speakers at Major National Neurology Conferences in 2017

ObjectiveTo determine whether speaking roles at five major neurology conferences in 2017 show disproportionate representation by men. MethodsThis study consisted of two cross-sectional analyses. In the first part, we compared speaker characteristics across meetings and by gender using descriptive statistics. In the second part, we linked presenters to the American Medical Association (AMA) Masterfile. For the primary analysis in the second part using linked AMA speaker data, we built models to estimate the influence of gender on speaker roles. Results1493 speakers were identified and included in our cross-sectional analysis. Women made up 28% of presenters from the US and 18% of presenters from other countries. After adjusting for years from medical school graduation and subspecialty, no effect of gender on speaker activity was observed (odds ratio [OR] for women 0.91; 95% confidence interval [CI], 0.77-1.07). ConclusionsFactors aside from national conference speaking activity should be investigated to better understand sex differences in rank at top-ranked academic neurology programs.

neuroscience↗

bioRxiv2018

ENaC-mediated sodium influx drives NLRP3 inflammasome-dependent autoinflammation in Cystic Fibrosis

Cystic Fibrosis (CF) is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene and results in defective CFTR-mediated chloride transport, dysregulation of epithelial sodium channels (ENaC) and exaggerated innate immune responses. We tested the hypothesis that upregulation of ENaC drives autoinflammation in this complex monogenic disease.\n\nWe show that monocytes from patients with CF exhibit a systemic proinflammatory cytokine signature, with associated anti-inflammatory M2-type macrophage deficiency. Cells harboring CF mutations are hyperresponsive to NLRP3 stimulation, as evidenced by increased IL-18, IL-1{beta}, ASC-specks levels in serum and caspase-1 activity in monocytes, and by increased IL-18 production and caspase-1 activity in human bronchial epithelial cells (HBECs). In both cell types there is an associated shift to glycolytic metabolism with succinate release, in response to increased energy requirements. Inhibition of amiloride-sensitive sodium channels partially reverses the NLRP3-dependent inflammation and metabolic shift in these cells. Overexpression of {beta}-ENaC, in the absence of CFTR dysfunction, increases NLRP3-dependent inflammation, indicating a CFTR-independent ENaC axis in CF pathophysiology. Sodium channel modulation provides an important therapeutic strategy to combat lung inflammation in CF.

immunology↗

bioRxiv2017

An integrated genomic analysis of anaplastic meningioma identifies prognostic molecular signatures

Anaplastic meningioma is a rare and aggressive brain tumor characterised by intractable recurrences and dismal outcomes. Here, we present an integrated analysis of the whole genome, transcriptome and methylation profiles of primary and recurrent anaplastic meningioma. A key finding was the delineation of two distinct molecular subgroups that were associated with diametrically opposed survival outcomes. Relative to lower grade meningiomas, anaplastic tumors harbored frequent driver mutations in SWI/SNF complex genes, which were confined to the poor prognosis subgroup. Our analyses discern two biologically distinct variants of anaplastic meningioma with potential prognostic and therapeutic significance.

genomics↗