Biology subjects

Xia, J.

Publications and source records attributed to Xia, J..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Spatiotemporal Analysis of Remyelination Reveals a Concerted Interferon-Responsive Glial State That Coordinates Immune Infiltration

Remyelination, the process by which axons are re-encased in myelin after injury, is a critical step in restoring brain function, yet the dynamics from initial injury to repair remain poorly characterized. Here, we combined optimized single-nucleus RNA-seq with Slide-seqv2, a high-resolution spatial transcriptomics technology, to densely reconstruct the cellular processes that coordinate remyelination after a focal demyelinating injury. This revealed several findings: First, we found extensive transcriptional diversity of glia and monocyte-derived macrophages from demyelination to repair. Second, we identified a population of infiltrating peripheral lymphocytes--predominantly CD8 T-cells and natural killer cells--that are enriched specifically during remyelination. Third, we identified a concerted interferon-response gene signature that is shared across several cell types--microglia, astrocytes, and the oligodendrocyte lineage--just prior to reestablishment of myelin. These interferon-responsive glia (IRG) form clusters around remyelinating white matter and their formation is solely dependent on the type I interferon receptor. Functionally, we found that IRG secrete the cytokine CXCL10 which mediates infiltration of peripheral lymphocytes into the repairing white matter. Depletion of the most abundant infiltrating lymphocyte, CD8 T-cells, attenuated the differentiation of mature oligodendrocytes during remyelination. Together, our data reveals the diversity of glial-immune interactions that orchestrate white matter repair and a type I-dependent glial state that drives lymphocyte influx into damaged white matter to modulate oligodendrocyte differentiation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=57 SRC="FIGDIR/small/649486v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@2c7e07org.highwire.dtl.DTLVardef@1063719org.highwire.dtl.DTLVardef@10b8862org.highwire.dtl.DTLVardef@26dd8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Interrupting Elmsan1 repression of nuclear Acetyl-CoA production therapeutically reprograms cancer cells

Metabolites are essential substrates for epigenetic modifications. Although nuclear acetyl-CoA constitutes a small fraction of the whole cell pool, it regulates cell fate by locally providing histone acetylation substrate. Here, we combined phenotypic chemical screen and genome-wide CRISPR screen to demonstrate a nucleus-specific acetyl-CoA regulatory mechanism that can be modulated to achieve therapeutic cancer cell reprogramming. While previously thought that nucleus-localized pyruvate dehydrogenase complex (nPDC) is constitutively active, we found that nPDC is constitutively inhibited by the nuclear protein ELMSAN1 through direct interaction. Pharmacologic inhibition of the ELMSAN1-nPDC interaction derepressed nPDC activity, enhancing nuclear acetyl-CoA generation and reprogramming cancer cells to a postmitotic state with diminished cell-of-origin signatures. Reprogramming was synergistically enhanced by histone deacetylase 1/2 inhibition, resulting in inhibited tumor growth, durably suppressed tumor-initiating ability, and improved survival in multiple cancer types in vivo, including therapy-resistant sarcoma patient-derived xenografts and carcinoma cell line xenografts. Our findings highlight the potential of targeting ELMSAN1-nPDC as epigenetic cancer therapy.

cancer biology↗

bioRxiv2025

Excitation Spectral Phasor Microscopy (ExSPM) unveils spatiotemporal heterogeneities in polarity of intracellular lipid droplets

Spatiotemporal heterogeneities in intracellular LD polarity are central to cellular homeostasis but remain largely unexplored. Here, we introduce Excitation Spectral Phasor Microscopy (ExSPM), which integrates high-throughput excitation spectral imaging with phasor analysis to map LD polarity with exceptional sensitivity and spatiotemporal resolution. Using the lipophilic dye Nile Red, ExSPM revealed extensive heterogeneity and dynamics of LD polarity within single cells, reflecting lipid metabolism and energy status. Notably, high-polarity LDs emerged dynamically at lysosome- and mitochondria-contact sites, revealing pathway-specific kinetics of LD catabolism that distinguish lipophagy from neutral lipolysis. ExSPM further uncovered a tightly interconnected regulatory network among lipolytic pathways, in which perturbation of one pathway reshapes others while preserving overall energy supply. ExSPM thus provides a versatile platform to dissect intracellular compositional heterogeneity and the coordinated regulation of lipid metabolism, offering new insights into organelle function and cellular homeostasis.

cell biology↗

bioRxiv2025

A Comprehensive Reference Catalog of Human Skin DNA Virome Reveals Novel Viral Diversity and Microenvironmental Influences

IntroductionHuman skin serves as a dynamic habitat for a diverse microbiome, including a complex array of viruses whose diversity and roles are not fully understood. ObjectivesThis study aims to enhance our understanding of this skin viral diversity through the construction of a detailed, non-redundant DNA viral reference catalog. MethodsA total of 2,760 skin metagenomes from six published skin studies were collected. A skin virome catalog was constructed using methods independent of reference databases. Viral characteristics were identified through cross-cohort meta-analysis and used to characterize viral features across different skin environments. ResultsWe identified 20,927 viral sequences, which clustered into 2,873 viral operational taxonomic units (vOTUs). Among these, 2,610 represent previously unrecorded viral sequences, uncovering a substantial breadth of viral diversity on human skin. The results also highlight significant differences in viral communities that are associated with varying skin microenvironments. The oily skin is enriched in Papillomaviridae; the dry skin area is enriched in Autographiviridae, Inoviridae and Mitoviridae; and the moist skin is enriched in Herelleviridae, indicating the adaptive nature of viruses. We also investigated the relationship between bacteriophages and bacteria on the skin surface. We found that skin bacteria such as Pseudomonas, Klebsiella, and Staphylococcus are infected by phages from the class Caudoviricetes. ConclusionThis comprehensive skin DNA viral catalog significantly advances our understanding of the viromes role within the skin ecosystem. The findings highlight the adaptive nature of viruses to different skin microenvironments and their interactions with resident bacteria. This catalog serves as a valuable resource for further epidemiological and therapeutic research, potentially leading to better management and treatment of skin conditions influenced by the skins virome.

microbiology↗

bioRxiv2025

Linking molecular pathways and islet cell dysfunction in human type 1 diabetes

Type 1 diabetes (T1D) is characterized by the autoimmune destruction of most insulin-producing {beta}-cells, along with dysregulated glucagon secretion from pancreatic -cells. We conducted an integrated analysis that combines electrophysiological and transcriptomic profiling, along with machine learning, of islet cells from T1D donors to investigate the mechanisms underlying their dysfunction. Surviving {beta}-cells exhibit altered electrophysiological properties and transcriptomic signatures indicative of increased antigen presentation, metabolic reprogramming, and impaired protein translation. In -cells, we observed hyper-responsiveness and increased exocytosis, which are associated with upregulated immune signaling, disrupted transcription factor localization and lysosome homeostasis, as well as dysregulation of mTORC1 complex signaling. Notably, key genetic risk signals for T1D were enriched in transcripts related to -cell dysfunction, including MHC class I which were closely linked with -cell dysfunction. Our data provide novel insights into the molecular underpinnings of islet cell dysfunction in T1D, highlighting pathways that may be leveraged to preserve residual {beta}-cell function and modulate -cell activity. These findings underscore the complex interplay between immune signaling, metabolic stress, and cellular identity in shaping islet cell phenotypes in T1D. HighlightsO_LISurviving {beta}-cells in T1D show disrupted electrical function linked to metabolic reprogramming and immune stress. C_LIO_LITranscripts associated with -cell dysfunction are enriched in genetic risk alleles for T1D. C_LIO_LIUpregulated MHC class I and impaired nuclear localization of key transcription factors associate with -cell dysfunction in T1D. C_LIO_LIT1D -cells exhibit increased hyper-activity, lysosomal imbalance and impaired mTORC1 signaling, which promotes dysregulated glucagon secretion. C_LI

cell biology↗

bioRxiv2025

High-throughput, unbiased single-molecule displacement mapping with deep learning reveals spatiotemporal heterogeneities in intracellular diffusivity

Single-molecule displacement/diffusivity mapping (SMdM) has revolutionized the study of molecular motion in live cells by providing high spatial resolution insights. However, its utility is restricted by measurement biases and low throughput, making it challenging to capture temporal dynamics of intracellular diffusivity. Here we report a high-throughput single-molecule diffusivity microscopy approach (Hi-SMdM) that rapidly and unbiasedly maps nanoscale heterogeneities in molecular motion inside mammalian cells, enabling time-resolved imaging of local diffusivity dynamics. Hi-SMdM employs a self-supervised deep-learning denoising framework with a general noise model to effectively restore the scarce signals of fast-moving single molecules, while eliminating artifact motions without relying on spatial redundancies or temporal correlations. It then provides unbiased estimations of nanoscale diffusion coefficient and improve both throughput and temporal resolution by up to an order of magnitude. We demonstrate the versatility of Hi-SMdM through time-resolved mapping of the spatially heterogeneous diffusivity of free proteins in the cytoplasm. Hi-SMdM also unveils the temporal dynamics of intracellular diffusion under hypotonic conditions in live cells. Additionally, Hi-SMdM tracks the spatiotemporal dynamics of intraorganellar diffusivity during rapid rearrangements of the ER network and functional activities of mitochondria. Overall, Hi-SMdM provides exceptional opportunities for high-throughput and unbiased single-molecule diffusivity mapping with excellent spatiotemporal resolution.

biophysics↗

bioRxiv2025

Integrated Techniques for Extracellular Particle Separation and Single-Particle Multiparametric Characterization to Track Cancer Biomarkers from Tissue to Biofluids

Gastric cancer (GC) remains a formidable global health challenge, with late-stage diagnosis and high recurrence rates resulting in poor patient outcomes. This study explores the potential of advanced technologies, namely Bessel Beam Excitation Separation Technology (BEST) and multiparametric biochip assay (MBA), to track single extracellular vesicle and particle (EVP) cargo from organs of pathology into biofluids such as plasma and saliva. Using GC as a study model, we conducted high throughput, multiparametric analyses of EVPs derived from plasma, saliva, and tissue samples. Our findings demonstrate the feasibility of these techniques in isolating and characterizing EVPs, revealing consistent EVP morphology and size across biofluids. Furthermore, differential expression patterns of the developed and validated salivary GC biomarkers, miR-140-5p and miR-301a-3p, were observed in GC patient biofluids, supporting the diagnostic relevance of EVP cargo. Notably, saliva emerged as the most promising biofluid for GC diagnosis, achieving superior Receiver Operating Characteristic (ROC) curve values compared to plasma and tissue. This study highlights the role of BEST and MBA in advancing single-EVP analysis and elucidating EVP trafficking, paving the way for future diagnostic applications of EVP cargo.

cancer biology↗

bioRxiv2024

Geometry-based BERT: an experimentally validated deep learning model for molecular property prediction in drug discovery

Various deep learning based methods have significantly impacted the realm of drug discovery. The development of deep learning methods for identifying novel structural types of active compounds has become an urgent challenge. In this paper, we introduce a self-supervised representation learning framework, i.e., GEO-BERT. GEO-BERT considers the information of atoms and chemical bonds in chemical structures as the input, and integrates the positional information of the three-dimensional conformation of the molecule for training. Specifically, GEO-BERT enhances its ability to characterize molecular structures by introducing three different positional relationships: atom-atom, bond-bond, and atom-bond. By benchmarking study, GEO-BERT has demonstrated optimal performance on multiple benchmarks. We also performed prospective study to validate the GEO-BERT model, with screening for DYRK1A inhibitors as a case. Two potent and novel DYRK1A inhibitors (IC50: <1 M) were ultimately discovered at a hit rate of 10%. Taken together, we have developed the Geometry-based BERT model for molecular property prediction and proved its practical utility in early-stage drug discovery. Graphical Abstract GEO-BERT is a model pretrained on large-scale drug molecule data, while improving the accuracy of property prediction by using three-dimensional structural information within the molecule. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/630211v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1e9bc54org.highwire.dtl.DTLVardef@4b6832org.highwire.dtl.DTLVardef@a5d8eeorg.highwire.dtl.DTLVardef@44f7be_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2024

Bridging the Gap between Database Search and De Novo Peptide Sequencing with SearchNovo

AO_SCPLOWBSTRACTC_SCPLOWAccurate protein identification from mass spectrometry (MS) data is fundamental to unraveling the complex roles of proteins in biological systems, with peptide sequencing being a pivotal step in this process. The two main paradigms for peptide sequencing are database search, which matches experimental spectra with peptide sequences from databases, and de novo sequencing, which infers peptide sequences directly from MS without relying on pre-constructed database. Although database search methods are highly accurate, they are limited by their inability to identify novel, modified, or mutated peptides absent from the database. In contrast, de novo sequencing is adept at discovering novel peptides but often struggles with missing peaks issue, further leading to lower precision. We introduce SearchNovo, a novel framework that synergistically integrates the strengths of database search and de novo sequencing to enhance peptide sequencing. SearchNovo employs an efficient search mechanism to retrieve the most similar peptide spectrum match (PSM) from a database for each query spectrum, followed by a fusion module that utilizes the reference peptide sequence to guide the generation of the target sequence. Furthermore, we observed that dissimilar (noisy) reference peptides negatively affect model performance. To mitigate this, we constructed pseudo reference PSMs to minimize their impact. Comprehensive evaluations on multiple datasets reveal that SearchNovo significantly outperforms state-of-the-art models. Also, analysis indicates that many retrieved spectra contain missing peaks absent in the query spectra, and the retrieved reference peptides often share common fragments with the target peptides. These are key elements in the recipe for SearchNovos success. The code for reproducing the results are available in the supplementary materials.

bioinformatics↗

bioRxiv2024

Sidechain chemistry-encoded solid/liquid phase transitions of condensates

Nature effectively leverages multivalent interactions among fundamental building blocks in solvents to create remarkable materials for various purposes. One prominent example is the formation of biomolecular condensates through the phase separation of proteins and nucleic acids. In particular, these condensates play crucial roles in regulating cellular functions and constructing natural materials. During the phase separation, solvents not only provide liquid environments for solvating molecules but play crucial roles in affecting the material properties of condensates. However, it remains controversial in the literature that alcohol molecules, as one type of solvents, can solidify some condensates while also melting others, leading to liquid-to-solid phase transition (LSPT) or solid-to-liquid phase transitions (SLPT), respectively. The mechanism underlying the alcohol-induced solid/liquid phase transitions of condensates remains poorly understood. Here, we combine systematic experimental characterizations with molecular dynamics simulations to demonstrate that the phase transitions of condensates depend on their sidechain chemistry and dominant molecular interactions. Specifically, "hydrophilic" condensates, which consist of many charged sidechains, undergo LSPT by adding alcohols due to strengthened electrostatic interactions. In contrast, "hydrophobic" condensates comprised of abundant aromatic sidechains undergo SLPT with the addition of alcohols because of weakened cation-{pi} and {pi}-{pi} interactions. Importantly, these findings are generally applicable for predicting phase transitions of a wide range of condensates formed by synthetic polyelectrolytes and intrinsically disordered proteins based on their sidechain hydrophobicity or amino acid compositions. Our work not only reconciles a conundrum in the literature but provides a fundamental framework for understanding the responsiveness of condensates to environmental stimuli. These insights are instrumental for developing therapeutic drugs to treat pathological aggregates and engineering stimuli-responsive biomaterials from the perspective of sidechain chemistry and molecular interactions.

biophysics↗

bioRxiv2024

Discovery of novel 1,4-dicarbonylthiosemicarbazides as DNA gyrase inhibitors for the treatment of MRSA infection

Antibiotic resistance has become a serious threat to public health, thus novel antibiotics are urgently needed to combat drug-resistant bacteria including MRSA (methicillin-resistant S. aureus). The 1,4-dicarbonylthiosemicarbazide is an interesting chemotype that could exhibit antibacterial activity. However, the currently available compounds are not as potent as clinical antibiotics. Herein, we adopted the computer-aided drug design strategy, substructure search, to retrieve antibacterial 1,4-dicarbonylthiosemicarbazide derivatives, and identified compound B5 (Specs ID: AG-690/15432331) from the Specs chemical library that exhibited moderate activity (minimum inhibitory concentration (MIC): 6.25 {micro}g/mL) against S. aureus (ATCC 29213). Based on that compound, we further designed and synthesized 45 derivatives, and evaluated their antibacterial activity. Eight derivatives were more potent than or equivalent to vancomycin (MIC: 1.56 {micro}g/mL). We compared the three most potent ones for their cytotoxicity to HepG2 and HUVEC cells and selected compound 1b as our lead compound for comprehensive biological evaluation. As a result, compound 1b exhibited a bacteriostatic mode, and was active against a panel of gram-positive bacteria strains, metabolically stable, and effective to protect the mice from MRSA infection. More importantly, we applied 2D similarity calculation and reverse docking to predict potential targets of compound 1b. Through experimental validation and molecular dynamics simulation, we were able to confirm that compound 1b inhibited S. aureus DNA gyrase (IC50: 1.81 {micro}M) and DNA supercoiling, potentially by binding to the ATPase domain, where ASP81, GLU58 and GLN91 formed key hydrogen bonds. Taken together, we have discovered a new class of DNA gyrase inhibitors represented by compound 1b for the treatment of MRSA infection, through the design, synthesis, and biological evaluation of novel 1,4-dicarbonylthiosemicarbazides. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/611349v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@549dadorg.highwire.dtl.DTLVardef@13bff64org.highwire.dtl.DTLVardef@1fc2c00org.highwire.dtl.DTLVardef@acee76_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIAn interesting 1,4-dicarbonylthiosemicarbazide derivative B5 with moderate antibacterial activity for S. aureus was discovered by substructure search. C_LIO_LIBased on B5, 45 new 1,4-dicarbonylthiosemicarbazides were designed, synthesized and biologically evaluated, which led to the discovery of a promising lead compound 1b. C_LIO_LICompound 1b exhibited good antibacterial activity for a panel of gram-positive bacteria strains, and was effective to protect mice from MRSA infection. C_LIO_LIThe 1,4-dicarbonylthiosemicarbazides represented by compound 1b were discovered as a new class of DNA gyrase inhibitors, by target prediction and experimental validation. C_LI

pharmacology and toxicology↗

bioRxiv2024

Vagal TRPV1+ sensory neurons regulate myeloid cell dynamics and protect against influenza virus infection

Influenza viruses are a major global cause of morbidity and mortality. Vagal TRPV1+ nociceptive sensory neurons, which innervate the airways, are known to mediate defenses against harmful agents. However, their function in lung antiviral defenses remains unclear. Our study reveals that both systemic and vagal-specific ablation of TRPV1+ nociceptors reduced survival in mice infected with influenza A virus (IAV), despite no significant changes in viral burden or weight loss. Mice lacking nociceptors showed exacerbated lung pathology and elevated levels of pro-inflammatory cytokines. The increased mortality was not attributable to the loss of the TRPV1 ion channel or neuropeptides CGRP or substance P. Immune profiling through flow cytometry and single-cell RNA sequencing identified significant nociceptor deficiency-mediated changes in the lung immune landscape, including an expansion of neutrophils and monocyte-derived macrophages. Transcriptional analysis revealed impaired interferon signaling in these myeloid cells and an imbalance in distinct neutrophil sub-populations in the absence of nociceptors. Furthermore, anti-GR1-mediated depletion of myeloid cells during IAV infection significantly improved survival, underscoring a role of nociceptors in preventing pathogenic myeloid cell states that contribute to IAV-induced mortality. One Sentence Summary: TRPV1+ neurons facilitate host survival from influenza A virus infection by controlling myeloid cell responses and immunopathology.

immunology↗

bioRxiv2024

A novel functional coordination in UNC-13 regulates neurotransmitter release

Munc13 plays a crucial role in short-term synaptic plasticity by regulating synaptic vesicle (SV) exocytosis and neurotransmitter release at the presynaptic terminals. However, the intricate mechanisms governing these processes have remained elusive due to the presence of multiple functional domains within Munc13, each playing distinct roles in neurotransmitter release. Here we report a coordinated mechanism in the C. elegans Munc13 homolog UNC-13 that controls the functional switch of UNC-13 during synaptic transmission. Mutations disrupting the interactions of C1 and C2B with diacylglycerol (DAG) and phosphatidylinositol 4,5-bisphosphate (PIP2) on the plasma membrane induced the gain-of-function state of UNC-13L, the long UNC-13 isoform, resulting in enhanced SV release. Concurrent mutations in both domains counteracted this enhancement, highlighting the functional interdependence of C1 and C2B. Intriguingly, the individual C1 and C2B domains exhibited significantly stronger facilitation of SV release compared to the presence of both domains, supporting a mutual inhibition of C1 and C2B under basal conditions. Moreover, the N-terminal C2A and X domains exhibited opposite regulation on the functional switch of UNC-13L. Furthermore, we identified the polybasic motif in the C2B domain that facilitates SV release. Finally, we found that disruption of C1 and C2B membrane interaction in UNC-13S, the short isoform, leads to functional switch between gain-of-function and loss-of-function. Collectively, our findings provide a novel mechanism for SV exocytosis wherein UNC-13 undergoes functional switches through the coordination of its major domains, thereby regulating synaptic transmission and short-term synaptic plasticity.

neuroscience↗

bioRxiv2024

The state-of-the-art machine learning model for Plasma Protein Binding Prediction: computational modeling with OCHEM and experimental validation

Plasma protein binding (PPB) is closely related to pharmacokinetics, pharmacodynamics and drug toxicity. Prediction of PPB is an alternative to experimental approaches that are known to be time-consuming and costly. Although there are various models and web servers for PPB prediction already available, they suffer from low prediction accuracy and poor interpretability, in particular for molecules with high values, and are most often not properly validated in prospective studies. Here, we carried out strict data curation, and applied consensus modeling to obtain a model with a coefficient of determination of 0.90 and 0.91 on the training set and the test set, respectively. This model was further validated in a prospective study to predict 63 poly-fluorinated and another 25 highly diverse compounds, and its performance for both these sets was superior to that of other previously reported models. To identify structural features related to PPB, we analyzed a model based on Morgan2 fingerprints and identified that features such as aromatic rings, halogen atoms, heterocyclic rings can discriminate high- and low-PPB molecules. In conclusion, we have established a PPB prediction model that showed state-of-the-art performance in prospective screening, which we have made publicly available in the OCHEM platform (https://ochem.eu/article/29). Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/603170v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@660730org.highwire.dtl.DTLVardef@61f81corg.highwire.dtl.DTLVardef@1e80d07org.highwire.dtl.DTLVardef@1af719a_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

Genome-resolved year-round dynamics reveal a broad range of giant virus microdiversity

Giant viruses are crucial for marine ecosystem dynamics because they regulate microeukaryotic community structure, accelerate carbon and nutrient cycles, and drive the evolution of their hosts through co-evolutionary processes. Previously reported long-term observations revealed that these viruses display fluctuations in abundance. However, the underlying genetic mechanisms driving such dynamics in these viruses remain largely unknown. In this study, we investigated population and intra-population dynamics of giant viruses using time-series metagenomes from eutrophic coastal seawater samples collected over 20 months. A newly developed near-automatic computational pipeline generated 1,065 high-quality metagenome-assembled genomes covering six major giant virus lineages. These genomic data revealed year-round recovery of the viral community at the study site and distinct dynamics of different viral populations classified as persistent (n = 9), seasonal (n = 389), sporadic (n = 318), or others. Notably, year-round recovery patterns were observed at the intra-population genetic diversity level for viruses classified as persistent or seasonal. Our results further indicated that the viral genome dynamics were associated with intra-population diversity; specifically, giant viruses with broader niche breadth tended to exhibit greater levels of microdiversity. We argue that greater microdiversity in viruses likely enhances adaptability and thus survival under the virus-host arms race during prolonged interactions with their hosts.

microbiology↗

bioRxiv2024

High Throughput Repurposing Screen Reveals Compounds with Activity Against Toxoplasma gondii Bradyzoites

Toxoplasma gondii causes widespread chronic infections that are not cured by current treatments due to inability to affect semi-dormant bradyzoite stages within tissue cysts. To identify compounds to eliminate chronic infection, we developed a HTS using a recently characterized strain of T. gondii that undergoes efficient conversion to bradyzoites in intro. Stage-specific expression of luciferase was used to selectively monitor growth inhibition of bradyzoites by the Library of Pharmacological Active Compounds, consisting of 1,280 drug-like compounds. We identified 44 compounds with >50% inhibitory effects against bradyzoites, including new highly potent compounds, several of which have precedent for antimicrobial activity. Subsequent characterization of the compound Sanguinarine sulfate revealed potent and rapid killing against in vitro produced bradyzoites and bradyzoites harvested from chronically infected mice. These findings provide a platform for expanded screening and identify promising compounds for further preclinical development against T. gondii bradyzoites responsible for chronic infection.

microbiology↗

bioRxiv2024

Piezo1 and Piezo2 channels in retinal ganglion cells and the impact of Piezo1 stimulation on light-dependent neural activity

Piezo channels are associated with neuropathology in diseases like traumatic brain injury and glaucoma, but pathways linking tissue stretch to aberrant neural signaling remain unclear. The present study demonstrates that Piezo1 activation increases action potential frequency in response to light and the spontaneous dark signal from mouse retinal explants. Piezo1 stimulation was sufficient to increase cytoplasmic Ca2+ in soma and neurites, while stretch increased spiking activity in current clamp recordings from of isolated retinal ganglion cells (RGCs). Axon-marker beta-tubulin III colocalized with both Piezo1 and Piezo2 protein in the mouse optic nerve head, while RGC nuclear marker BRN3A colocalized with Piezo channels in the soma. Piezo1 was also present on GFAP-positive regions in the optic nerve head and colocalized with glutamine synthetase in the nerve fiber layer, suggesting expression in optic nerve head astrocytes and Muller glia end feet, respectively. Human RGCs from induced pluripotent stem cells also expressed Piezo1 and Piezo2 in soma and axons, while staining patterns in rats resembled those in mice. mRNA message for Piezo1 was greatest in the RPE/choroid tissue, while Piezo2 levels were highest in the optic nerve, with both channels also expressed in the retina. Increased expression of Piezo1 and Piezo2 occurred both 1 and 10 days after a single stretch in vivo; this increase suggests a potential role in rising sensitivity to repeated nerve stretch. In summary, Piezo1 and Piezo2 were detected in the soma and axons of RGCs, and stimulation affected the light-dependent output of RGCs. The rise in RGCs excitability induced by Piezo stimulation may have parallels to the early disease progression in models of glaucoma and other retinal degenerations. HighlightsO_LIActivation of Piezo1 excites retinal ganglion cells, paralleling the early neurodegenerative progression in glaucoma mouse models and retinal degeneration. C_LIO_LIPiezo1 and Piezo2 were expressed in axons and soma of retinal ganglion cells in mice, rats, and human iPSC-RGCs. C_LIO_LIFunctional assays confirmed Piezo1 in soma and neurites of neurons. C_LIO_LISustained elevation of Piezo1 and Piezo2 occurred after a single transient stretch may enhance damage from repeated traumatic nerve injury. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/599602v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@7bb1a0org.highwire.dtl.DTLVardef@cab0dcorg.highwire.dtl.DTLVardef@121690eorg.highwire.dtl.DTLVardef@7848fa_HPS_FORMAT_FIGEXP M_FIG Graphical abstract Piezo1 and Piezo2 channels in retinal ganglion cells and the impact of Piezo1 stimulation on light-dependent neural activity. Puttipong Sripinun, Lily P. See, Sergei Nikonov, Venkata Ramana Murthy Chavali, Vrathasha Vrathasha, Jie He, Joan M. OBrien, Jingsheng Xia, Wennan Lu, Claire H. Mitchell*. Activation of Piezo channels through mechanical or pharmacological stimulation leads to an influx of Ca2+ and other cations into RGCs, depolarizing the membrane and increasing the action potential frequency to modulate the visual signal. Created with Biorender.com C_FIG

neuroscience↗

bioRxiv2024

HumanIslets: An integrated platform for human islet data access and analysis

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com, an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca2+-ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.

systems biology↗