Biology subjects

Nguyen, S.

Publications and source records attributed to Nguyen, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Kinetic Control of Nuclear-encoded Mitochondrial mRNA Localization and Local Translation

Most biological processes are dynamic, yet experimental methods predominantly rely on steady-state measurements to investigate their underlying mechanisms. RNA localization is a fundamental aspect of eukaryotic cell organization and is dynamically regulated by cells. While extensively studied in specialized cell types for a limited number of candidate RNAs, the general principles governing dynamic RNA localization at a transcriptome-wide scale remain largely unexplored. Existing transcriptome-wide studies provide only a static snapshot of RNAs residing in specific cellular locales, in part due to the limited availability of tools for probing cellular spatial organization at biologically relevant scales. Here, we leverage the high spatial (tens of nanometers) and temporal (minute) resolution of APEX-seq to quantitatively measure the dependence of RNA transport on molecular motors at a transcriptome-wide scale in living cells. We conducted these experiments in the context of the localization of mRNAs to the mitochondria, which are essential for cellular function. Our findings indicate that the majority of nuclear-encoded RNAs encoding mitochondrial proteins localize to the outer mitochondrial membrane (OMM) for local translation. We reveal a crucial role of retrograde dynein-based motor transport in RNA localization, demonstrating that its disruption severely impairs RNA targeting to the OMM. Time-resolved profiling of RNAs at the OMM revealed that localization is an active process, and even a brief disruption of transport for a few minutes results in a dramatic loss of localization. Moreover, we demonstrate that the translation efficiency (TE) of localized RNAs is a critical determinant of RNA localization in the context of motor-driven transport, as RNAs that delocalize following motor-transport perturbations exhibit lower TE. Using our temporal perturbation data, we also developed a spatiotemporal model that utilizes translation kinetics to capture key features of RNA localization dynamics at the OMM. Together, experiments and modeling suggest that the process of local translation at the OMM is kinetically controlled by the cell, and reveal an unappreciated mechanism by which active transport of RNAs enables cells to modulate their translation within minutes through RNA localization control. Our study demonstrates how simultaneously capturing the kinetics of hundreds of transcripts with minute resolution can uncover general principles of cellular and organelle organization. Together, these experiments and modeling reveal how active transport and translation jointly maintain the OMM-localized transcriptome. More broadly, they identify RNA localization to cellular membranes as a rapidly tunable mechanism for controlling local translation, even in non-polarized cells.

cell biology↗

bioRxiv2026

Targeting the Mannitol Biosynthesis Pathway in Aspergillus fumigatus: Characterisation and Inhibition of Mannitol-2-Dehydrogenase

Infections caused by the opportunistic fungal pathogen Aspergillus fumigatus pose a serious public health system burden. The inherent limitations in existing antifungal drugs in conjunction with a rising emergence of antifungal resistance emphasizes an urgent need to identify and target alternative pathways crucial to survival and virulence. Targeting the fungal mannitol biosynthesis enzymes provides a promising avenue in the development of new antifungals due to the multifaceted roles mannitol fulfils in the fungal life cycle. However, a distinct lack of available structural information for these enzymes has hindered drug discovery efforts. We report the first crystal structure of mannitol-2-dehydrogenase from A. fumigatus in an unbound monomeric state (1.8 [A]) and bound to its co-factor NADH (2.1 [A]), via. a large, central cavity lined with positively charged residues that readily accommodates NADH. This interaction is further stabilised by a network of hydrogen bond interactions and {pi}-{pi} stacking between Phe45 and the nicotinamide ring of NADH. Furthermore, rigorous kinetic characterisation of A. fumigatus mannitol-2-dehydrogenase demonstrates the dose-dependent inhibitory activity of 1,4-benzoquinone, a cysteine-modifying small molecule inhibitor (IC50 = 1.2 {+/-} 0.2 nM). In addition, intact MS and proteomic analysis further reveal that 1,4-benzoquinone modifies up to five cysteine residues of mannitol-2-dehydrogenase and displays antifungal activity against A. fumigatus, which is enhanced in combination with a front-line antifungal voriconazole. From this work, we have established the foundations for a novel antifungal drug discovery avenue that targets the fungal mannitol biosynthesis pathway to better treat aspergillosis and related pathogenic infections.

biochemistry↗

bioRxiv2026

The splicing paralogues SNRPB and SNRPN control differential metabolic states.

Gene duplication underlies evolutionary innovation, yet many paralogues remain highly similar, raising questions about their functional divergence and physiological relevance. The spliceosomal Sm core protein SNRPB and its mammalian-specific paralogue SNRPN share over 90% sequence identity, but their distinct expression patterns - SNRPB being ubiquitous and SNRPN confined to the brain - suggest specialized functions. Why mammals have two different spliceosomes has remained obscure. Here, we generated isogenic human cell lines expressing ectopically either SNRPB or SNRPN exclusively and found that SNRPN stabilizes transcripts involved in energy metabolism and mitochondrial function, leading to increased mitochondrial abundance and oxygen consumption. Despite similar spliceosomal interactomes, SNRPN more strongly associates with the PRMT5 methylosome complex and exhibits dynamic arginine methylation in its C-terminal region that is sensitive to translation inhibition and amino acid availability. The SNRPN-dependent transcriptome responds to translation inhibition by stabilizing long, intron-rich genes involved in amino acid and energy metabolism. Our findings reveal a nutrient-sensitive, methylation-dependent mechanism that differentiates the two paralogues. This suggests that SNRPN functions as a metabolic-specialized spliceosomal subunit thereby providing tissue-specific adaptation of RNA processing in mammals.

molecular biology↗

bioRxiv2025

Toward Site-Specific Characterization of Structural Perturbations on Glycosylated Fc Using NMR at Natural Abundance

Monoclonal antibodies (mAbs) are leading therapeutic agents due to their high specificity and limited side effects. Ensuring their structural integrity under stress and maintaining batch consistency require robust quality control. Methyl 2D NMR has emerged as a powerful tool to probe mAb structure at natural isotopic abundance, enabling spectral fingerprint comparisons across production batches to detect subtle structural changes. However, extracting atomic-level structural information requires assignment of methyl resonances to their amino acids. While such assignments are available for several antigen-binding fragments (Fabs), no comprehensive assignment has been reported for the crystallisable fragment (Fc). In this study, we present the methyl group assignment of the 50-kDa Fc fragment of an immunoglobulin G1 (IgG1) antibody. Using cell-free expression, strategic isotopic labelling, and high-quality 2D and 3D NMR experiments, we successfully assigned 94% of methyl resonances of a non-glycosylated Fc. Given that therapeutic mAbs are typically produced in Chinese Hamster Ovary (CHO) cells, we transferred this assignment to the methyl spectrum of a glycosylated Fc fragment obtained by the enzymatic cleavage of a CHO-produced mAb at natural abundance, achieving 83% assignment coverage. This assignment was then used to investigate the impact of methionine oxidation on Fc structure at atomic resolution using NMR. The methyl group assignment transforms 2D methyl NMR fingerprinting into a powerful tool for quality control. It enables the direct comparison of spectra acquired on mAbs produced at natural abundance, allowing the detection and localisation of chemical modifications and structural changes without the need for isotopic labelling. This approach offers a robust solution for monitoring the structural integrity of therapeutic antibodies throughout development and manufacturing.

biochemistry↗

bioRxiv2025

Proteomic characterization of neuronal extracellular vesicle interactomes in Alzheimer's disease mouse model through TurboID-based proximity labeling

Extracellular vesicles (EVs) are critical mediators of neuronal communication and have been implicated in propagating pathological processes in neurodegenerative diseases, including Alzheimers disease (AD). However, the molecular interactome of neuronal EVs in vivo remains poorly defined. Here, we employed TurboID-CD9-based proximity biotinylation to label and capture EV-interacting proteins in the hippocampus of wild-type (WT) and APPNLGF knock-in AD mouse models. Adeno-associated viral delivery of hSyn1 promoter-driven TurboID-CD9 enabled neuron-specific EV tagging, followed by in vivo biotinylation and affinity purification of labeled proteins. Proteomic analysis using data independent acquisition liquid chromatography - mass spectrometry identified 5,502 proteins, with enriched pathways involving synaptic transmission, vesicle trafficking, and inhibitory neurotransmission. Comparative analyses revealed robust enrichment of GABAergic signaling components, including GABAA receptor subunits (Gabrb3, Gabra1, Gabbr2), Ncam1, and chloride transporters, in both WT and APPNLGF EV interactomes, with additional disease-associated proteins (Mapt, Snca) and potassium channel enrichment observed in APPNLGF mice. Proximity ligation assays validated direct EV-associated biotinylation of Ncam1, Gabrb3, and Gad1, with Gad1 showing significant upregulation in the APPNLGF cohort. In silico HADDOCK docking supported stable interactions between CD9 and these target proteins, revealing plausible EV-protein interfaces. These findings define the in vivo neuronal EV interactome and its remodeling in amyloid pathology, implicating EV-associated GABAergic and ion channel proteins in network excitability regulation. This work establishes a proteomic and structural framework for understanding EV-mediated signaling in health and disease, providing candidate targets for therapeutic modulation of excitatory / inhibitory balance in AD.

neuroscience↗

bioRxiv2025

Prostate-specific EV capture with sufficient RNA yield to enable transcriptomic profiling

Prostate-specific antigen (PSA) screening has reduced prostate cancer (PCa) mortality but suffers from limited specificity, contributing to unnecessary biopsies and overdiagnosis of indolent disease. There is a critical need for biofluid-based biomarkers that improve the precision of PCa detection. Extracellular vesicles (EVs) offer a promising platform for noninvasive diagnostics, as they carry molecular cargo reflective of their tissue of origin. The ExoDx Prostate IntelliScore (EPI) test, a urine-based EV assay, is currently the only commercial EV diagnostic for clinically significant (cs)PCa, but its performance may be constrained by contamination from renal and bladder-derived EVs. To address this, we developed Exosome Diagnostics Depletion and Enrichment (EDDE), a novel immunocapture-based method for isolating prostate-derived EVs with high specificity. By targeting Prostate Specific Membrane Antigen (PSMA), we optimized EDDE to selectively enrich prostate EVs from post-DRE urine and recover sufficient RNA for transcriptomic analysis. Throughout development, we implemented a quantitative framework to track EV stoichiometry and assess depletion efficiency and yield, enabling rigorous optimization of the workflow. Our findings demonstrate that PSMA EDDE enriches prostate-specific EVs and yields RNA quantities compatible with sequencing. This platform enhances the specificity of EV-based biomarker discovery and holds promise for determining if tissue-specific EV biomarkers contribute advantages over bulk EVs.

cancer biology↗

bioRxiv2025

Extracellular Vesicle Gene Expression Enables Sensitive Detection of Colorectal Neoplasia

BACKGROUND & AIMSExtracellular vesicles (EVs), including exosomes, are emerging as promising carriers of disease-specific biomarkers due to their molecular cargo reflective of cellular origin. While cell-free DNA (cfDNA) methylation assays have recently been developed for colorectal cancer (CRC) screening and perform well for cancer detection, they show limited sensitivity for advanced adenomas (AA), a key precursor in the CRC pathway. To address this gap, we sought to determine whether other blood-based analytes, specifically EV-derived long and small RNA transcriptomes and EV proteomes, could improve detection of AA and early-stage CRC. In a prospective cohort, we performed a head-to-head comparison of EV transcriptomics, EV proteomics, and their combinations against cfDNA methylation, all measured from the same patient cohort, enabling a direct performance benchmark and identification of the most promising modality for larger-scale CRC screening studies. METHODSWe prospectively collected pre-colonoscopy plasma samples from 220 participants across three clinical sites. EVs were isolated and profiled using long RNA-seq, small RNA-seq, and Olink-based proteomics. cfDNA was analyzed for methylation patterns. Analyses were conducted according to a statistical analysis plan pre-specified before unblinding. Machine learning models were developed under nested cross-validation to evaluate sensitivity for detecting AA and CRC at a fixed specificity of 91%, consistent with clinical screening benchmarks. RESULTSEV-derived gene expression on long RNA demonstrated the highest sensitivity for detecting AA as well as CRC: 54.8% (95% CI, 26.4%-75.6%) for AA and 94.1% (95% CI, 79.2%-100%) for CRC. This outperformed cfDNA methylation (33.6% [95% CI, 9.7%-60.3%] for AA, 81.3% [95% CI, 64.6%- 93.9%] for CRC) and other EV-based modalities. In addition, for small RNA the sensitivities were 42.6% (95% CI, 35.9%-47.4%) for AA, and 78.9% (95% CI, 69.2%-83.0%) for CRC, while for proteomics the sensitivities were 30.0% (95% CI, 13.9%-40.0%) for AA, and 64.2% (95% CI, 43.6%-87.2%) for CRC. Transcriptomic profiles revealed progressive enrichment of hallmarks of cancer pathways, including apoptosis and epithelial-mesenchymal transition, across disease stages. Multiomic integration did not improve performance beyond EV transcriptomics alone. CONCLUSIONSBy directly comparing multiple EV-based and cfDNA analytes within the same patient cohort, we found that EV transcriptomics delivers the strongest diagnostic performance for both AA and CRC. This rigorous benchmarking approach allows clear prioritization of the most promising modality guiding the design of larger validation studies and accelerating development of next-generation, blood-based CRC screening tools.

genomics↗

bioRxiv2025

Longitudinal transcriptomic analysis of SIV-infected rhesus macaques reveals peripheral immune dynamics throughout untreated SIV infection and long-term antiretroviral therapy

Developing a working knowledge of immune dynamics during prolonged infection and treatment has become critical for both advancing HIV cure strategies and understanding non-AIDS comorbidities, given rises in the age and average time spent on antiretroviral therapy (ART) among people living with HIV. However, at present, we do not fully appreciate the ways in which prolonged suppressive therapy influences immune function. Toward addressing this key knowledge gap comprehensively, we applied single-cell RNA-sequencing (scRNA-seq) to longitudinally profile peripheral blood mononuclear cells from SIV-infected non-human primates longitudinally. Our data reveal significant immune shifts during acute and chronic infection, as well as over five years of subsequent ART. We observe a decline in CD4+ T cells and an increase in aberrant B cells and CD16+ monocytes during untreated chronic infection, as well as widespread dampened transcriptional activity. Further, we uncover transcriptional signatures suggestive of unresolved immune dysregulation during long-term suppressive therapy - most prominently among myeloid cell populations. By examining concurrent measurements of intact proviral DNA, we link peripheral responses to reservoir size via IPDA. We furthermore identify ribosomal-associated pathways as key differentiators of infection stage, treatment status, and time on ART. Finally, we tested whether previously published transcriptional correlates of differential outcomes (e.g. viral rebound, vaccine efficacy) changed over time on ART. Overall, our findings capture dynamic immune remodeling from acute infection through long-term ART, highlighting complexities in achieving complete immune recovery that may influence future therapeutic strategies.

immunology↗

bioRxiv2025

Salivary Extracellular Vesicle RNA Profiling Reveals Biomarkers for Sjogrens

Sjogrens is a chronic autoimmune disease affecting exocrine glands and is subclassified into SSA-positive (SSA+) and SSA-negative (SSA-) subtypes, with a complex diagnostic journey and an average diagnostic delay of almost 4 years. While SSA+ cases can be detected via serological testing, current assays lack specificity. For SSA-patients, no non-invasive diagnostic tools exist, and diagnosis often requires invasive lip biopsy. A saliva-based liquid biopsy capable of diagnosing both subtypes is therefore of high clinical interest. However, saliva poses challenges due to its abundant oral microbiome, which complicates unbiased biomarker discovery. In this study, we present a novel RNA sequencing workflow that efficiently depletes microbial content, enabling deep profiling of long RNAs within salivary extracellular vesicles (EVs). This approach identified both known and novel RNA biomarkers capable of diagnosing SSA+ and SSA-subtypes with high sensitivity and specificity. Moreover, we uncovered distinct RNA signatures that allow molecular stratification of Sjogrens subtypes. Pathway analysis in SSA+ cases revealed enrichment of immune and glandular pathways consistent with prior tissue-based studies, supporting the utility of salivary EVs as a non-invasive surrogate for tissue biopsy. Importantly, our data provides new molecular insights into the under-characterized SSA-subtype, laying the foundation for future mechanistic studies and facilitating their broader inclusion in clinical trials.

genomics↗

bioRxiv2025

Deep Profiling of EV Long RNAs Reveals Biofluid-Specific Transcriptomes and Splicing Landscapes

RNA profiling of extracellular vesicles (EVs) from human biofluids has historically been limited to small RNA species, with long RNAs--such as mRNA exons and long non-coding RNAs--remaining largely underexplored. Moreover, the dominance of hematopoietic-derived EVs in complex fluids like plasma has posed significant challenges for detecting low-abundance, tissue-specific transcripts. Here, we establish foundational transcriptomic maps of long RNAs in EVs from plasma, urine, and cerebrospinal fluid (CSF) using ultra-deep whole transcriptome sequencing (WTS), revealing both fluid-specific and shared expression and splicing signatures. We then introduce a targeted RNA capture method that enriches for all protein-coding and long non-coding transcripts, dramatically enhancing sensitivity for gene and splice variant detection. Applying this approach to brain-specific transcripts, we achieve >85-fold enrichment of target gene expression and, on average, 3.1-fold increase in detected splice junctions per gene compared to untargeted WTS. As a proof of concept, we apply this brain-targeted RNA panel to EVs from plasma in a Parkinsons disease cohort of 40 plasma samples and compare its performance to exome sequencing as well as untargeted WTS. This work advances EV transcriptomics into the long RNA domain and establishes a framework for high-sensitivity, noninvasive biomarker profiling across tissues and diseases.

genomics↗

bioRxiv2025

Deep Learning-based Framework for Mycobacterium tuberculosis Bacterial Growth Detection for Antimicrobial Susceptibility Testing

Tuberculosis (TB) kills more people annually than any other pathogen. Resistance is an ever-increasing global problem, not least because diagnostics remain challenging and access limited. 96-well broth microdilution plates offer one approach to high-throughput phenotypic testing, but they can be challenging to read. Automated Mycobacterial Growth Detection Algorithm (AMyGDA) is a software package that uses image processing techniques to read plates, but struggles with plates that exhibit low growth or images of low quality. We developed a new framework, TMAS (TB Microbial Analysis System), which leverages state-of-the-art deep learning models to detect M. tuberculosis growth in images of 96-well microtiter plates. TMAS is designed to measure Minimum Inhibitory Concentrations (MICs) rapidly and accurately while differentiating between true bacterial growth and artefacts. Using 4,018 plate images from the CRyPTIC (Comprehensive Resistance Prediction for Tuberculosis: An International Consortium) dataset to train models and refine the framework, TMAS achieved an essential agreement of 98.8%. TMAS offers a reliable, automated and complementary evaluation to support expert interpretation, potentially improving accuracy and efficiency in tuberculosis drug susceptibility testing (DST). Author summaryTuberculosis (TB) is one of the worlds leading causes of death from infectious diseases, with drug resistance making treatment increasingly difficult. Accurate and timely drug susceptibility testing (DST) is essential to determine which antibiotics remain effective against a given TB strain. A widely used DST method involves 96-well broth microdilution plates, where bacteria are exposed to different antibiotic concentrations to determine the minimum inhibitory concentration (MIC), the lowest concentration that fully prevents bacterial growth. However, manually interpreting these plates is time-consuming and prone to human error, while existing automated methods often struggle with imaging artifacts such as condensation, shadows, and contamination. In this study, we developed the Tuberculosis Microbial Analysis System (TMAS), a machine learning-based tool designed to automate MIC determination from plate images. Training on advanced deep learning models, TMAS can learn to detect bacterial growth with high precision, distinguishing true growth from artefacts such as shadows, bubbles, sediment, condensation and contamination. When tested on a large dataset, TMAS outperformed existing automated methods in accuracy, reliability and efficiency. By reducing the reliance on manual interpretation, TMAS has the potential to streamline TB diagnostics, improve efficiency in laboratories, and improve access to high-quality DST, particularly in resource-limited settings.

microbiology↗

bioRxiv2024

A Rhodopseudomonas strain with a substantially smaller genome retains the core metabolic versatility of its genus

Rhodopseudomonas are a group of phototrophic microbes with a marked metabolic versatility and flexibility that underpins their potential use in production of value-added products, bioremediation and plant growth promotion. Members of this group have an average genome size of about 5.5 Mb, but two closely related strains have genome sizes of about 4.0 Mb. To identify the types of genes missing in a reduced genome strain, we compared strain DSM127 with other Rhodopseudomonas isolates at the genomic and phenotypic levels. We found that DSM127 can grow as well as other members of the Rhodopseudomonas genus and retains most of their metabolic versatility, but it has many fewer genes associated with high affinity transport of nutrients, iron uptake, nitrogen metabolism and biodegradation of aromatic compounds. This analysis indicates genes that can be deleted in genome reduction campaigns and suggests that DSM127 could be a favorable choice for biotechnology applications using Rhodopseudomonas or as a strain that can be engineered further to reside in a specialized natural environment. IMPORTANCERhodopseudomonas are a cohort of phototrophic bacteria with broad metabolic versatility. Members of this group are present in diverse soil and water environments and some strains are found associated with plants and have plant growth promoting activity. Motivated by the idea that it may be possible to design bacteria with reduced genomes that can survive well only in a specific environment or that may be more metabolically efficient, we compared Rhodopseudomonas strains with typical genome sizes of about 5.5 Mb to a strain with a reduced genome size of 4.0 Mb. From this we concluded that metabolic versatility is part of the identity of the Rhodopseudomonas group, but high-affinity transport genes and genes of apparent redundant function can be dispensed with.

microbiology↗

bioRxiv2024

Tissue-Like Multicellular Development Triggered by Mechanical Compression in Archaea

The advent of clonal multicellularity is a critical evolutionary milestone, seen often in eukaryotes, rarely in bacteria, and only once observed in archaea. We show that uniaxial compression induces clonal multicellularity in haloarchaea, forming tissue-like structures. These archaeal tissues are mechanically and molecularly distinct from their unicellular lifestyle, mimicking several eukaryotic features. Archaeal tissues undergo a multinucleate stage followed by tubulin-independent cellularization, orchestrated by active membrane tension at a critical cell size. After cellularization, tissue junction elasticity become akin to animal tissues and give rise to two cell types--radial peribasal and central apicobasal cells-- with distinct actin and protein glycosylation polarity patterns. Our findings highlight the potential convergent evolution of a biophysical mechanism in the emergence of multicellular systems across domains of life.

cell biology↗

bioRxiv2024

Long-Term Effects of Early Adolescent Second-Generation Antipsychotic Exposure on Body Weight, Caloric Intake, and Metabolism-Associated Gene Expression

The use of second-generation antipsychotic (SGA) medications in pediatric patients raises concerns about potential long-term adverse outcomes. The current study evaluated the long-term effects of treatment with risperidone or olanzapine on body weight, caloric intake, serum insulin, blood glucose, and metabolism-associated gene expression in C57Bl/6J female mice. Compared to mice treated with vehicle, female mice treated with risperidone or olanzapine gained weight at higher rates during treatment and maintained higher body weights for months following treatment cessation. During high-fat diet feeding, some groups of treated mice gained weight at higher rates than their respective control groups, but the finding was not consistent across experiments. Finally, female mice previously treated with olanzapine also exhibited increased expression of genes associated with inflammation and lipogenesis. These findings suggest that pediatric use of SGA medications that induce excess weight gain during treatment may exert persistent effects on body weight and gene expression and such outcomes may form an important aspect of assessing risk-to-benefit ratios in prescribing decisions.

pharmacology and toxicology↗

bioRxiv2024

Your Blood is Out for Delivery: Considerations of Shipping Time and Temperature on Degradation of RNA from Stabilized Whole Blood

Remote research studies are an invaluable tool for reaching populations in geographical regions with limited access to large medical centers or universities. To expand the remote study toolkit, we have previously developed homeRNA, which allows for at-home self-collection and stabilization of blood and demonstrated the feasibility of using homeRNA in high temperature climates. Here, we expand upon this work through a systematic study exploring the effects of high temperature on RNA integrity through in-lab and field experiments. Compared to the frozen controls (overall mean RIN of 8.2, n = 8), samples kept at 37{degrees}C for 2, 4, and 8 days had mean RINs of 7.6, 5.9, and 5.2 (n = 3), respectively, indicating that typical shipping conditions ([~]2 days) yield samples suitable for downstream RNA sequencing. Shorter time intervals (6 hours) resulted in minimal RNA degradation (median RIN of 6.4, n = 3) even at higher temperatures (50{degrees}C) compared to the frozen control (mean RIN of 7.8, n = 3). Additionally, we shipped homeRNA-stabilized blood from a single donor to 14 different states and back during the summer with continuous temperature probes (7.1 median RIN, n = 42). Samples from all locations were analyzed with 3 mRNA-seq to assess differences in gene counts, with the transcriptomic data suggesting that there was no preferential degradation of transcripts as a result of different shipping times, temperatures, and regions. Overall, our data support that homeRNA can be used in elevated temperature conditions, enabling decentralized sample collection for telemedicine, global health, and clinical research.

bioengineering↗

bioRxiv2024

Glucocorticoids desensitize CRH neurons to norepinephrine via rapid nitrosylation-dependent regulation of α1 adrenoreceptor trafficking

Noradrenergic afferents to hypothalamic corticotropin releasing hormone (CRH) neurons provide a major excitatory drive for somatic stress activation of the hypothalamic-pituitary-adrenal (HPA) axis. We showed that glucocorticoids rapidly desensitize CRH neurons to norepinephrine and suppress inflammation-induced HPA activation via a glucocorticoid receptor- and endocytosis-dependent mechanism. Here, we show that 1 adrenoreceptor (AR1) trafficking is regulated by convergent glucocorticoid and nitric oxide synthase signaling mechanisms. Live-cell imaging of AR1b-eGFP-expressing hypothalamic cells revealed rapid corticosterone-stimulated redistribution of internalized AR1 from rapid recycling endosomes to late endosomes and lysosomes via a nitrosylation-regulated mechanism. Proximity assay demonstrated interaction of glucocorticoid receptors with AR1b and {beta}-arrestin, and showed corticosterone blockade of norepinephrine-stimulated AR1b/{beta}-arrestin interaction, which may prevent AR1b from entering the rapid recycling endosomal pathway. These findings demonstrate a rapid glucocorticoid regulation of G protein-coupled receptor trafficking and provide a molecular mechanism for rapid glucocorticoid desensitization of noradrenergic signaling in CRH neurons.

neuroscience↗

bioRxiv2023

RECLUSIVE CHANDELIERS: FUNCTIONAL ISOLATION OF DENTATE AXO-AXONIC CELLS AFTER EXPERIMENTAL STATUS EPILEPTICUS

Axo-axonic cells (AACs) provide specialized inhibition to the axon initial segment (AIS) of excitatory neurons and can regulate network output and synchrony. Although hippocampal dentate AACs are structurally altered in epilepsy, physiological analyses of dentate AACs are lacking. We demonstrate that parvalbumin neurons in the dentate molecular layer express PTHLH, an AAC marker, and exhibit morphology characteristic of AACs. Dentate AACs show high-frequency, non-adapting firing but lack persistent firing in the absence of input and have higher rheobase than basket cells suggesting that AACs can respond reliably to network activity. Early after pilocarpine-induced status epilepticus (SE), dentate AACs receive fewer spontaneous excitatory and inhibitory synaptic inputs and have significantly lower maximum firing frequency. Paired recordings and spatially localized optogenetic stimulation revealed that SE reduced the amplitude of unitary synaptic inputs from AACs to granule cells without altering reliability, short-term plasticity, or AIS GABA reversal potential. These changes compromised AAC-dependent shunting of granule cell firing in a multicompartmental model. These early post-SE changes in AAC physiology would limit their ability to receive and respond to input, undermining a critical brake on the dentate throughput during epileptogenesis.

neuroscience↗

bioRxiv2023

Nuclear speckles regulate HIF-2α programs and correlate with patient survival in kidney cancer

Nuclear speckles are membrane-less bodies within the cell nucleus enriched in RNA biogenesis, processing, and export factors. In this study we investigated speckle phenotype variation in human cancer, finding a reproducible speckle signature, based on RNA expression of speckle-resident proteins, across >20 cancer types. Of these, clear cell renal cell carcinoma (ccRCC) exhibited a clear correlation between the presence of this speckle expression signature, imaging-based speckle phenotype, and clinical outcomes. ccRCC is typified by hyperactivation of the HIF-2 transcription factor, and we demonstrate here that HIF-2 drives physical association of a select subset of its target genes with nuclear speckles. Disruption of HIF-2-driven speckle association via deletion of its speckle targeting motifs (STMs)--defined in this study--led to defective induction of speckle-associating HIF-2 target genes without impacting non-speckle-associating HIF-2 target genes. We further identify the RNA export complex, TREX, as being specifically altered in speckle signature, and knockdown of key TREX component, ALYREF, also compromises speckle-associated gene expression. By integrating tissue culture functional studies with tumor genomic and imaging analysis, we show that HIF-2 gene regulatory programs are impacted by specific manipulation of speckle phenotype and by abrogation of speckle targeting abilities of HIF-2. These findings suggest that, in ccRCC, a key biological function of nuclear speckles is to modulate expression of a specific subset of HIF-2-regulated target genes that, in turn, influence patient outcomes. We also identify STMs in other transcription factors, suggesting that DNA-speckle targeting may be a general mechanism of gene regulation. HIGHLIGHTS- Nuclear speckles shown to reproducibly vary in cancer, predicting patient survival in ccRCC - HIF-2 drives DNA/gene-speckle contacts dependent on identified speckle targeting motifs within HIF-2 - Putative speckle targeting motifs are highly enriched among regulators of gene expression - Partitioning of transcription factor functional programs may be a major biological function of nuclear speckles

cancer biology↗