Biology subjects

Xue, B.

Publications and source records attributed to Xue, B..

At least 19 recordsLinked to original sources

bioRxiv2026

A comprehensive analysis of flagellar mutations in Vibrio cholerae: Trade-off mechanisms between motility loss and host adaptability

IntroductionCholera, caused by Vibrio cholerae, is a severe diarrheal disease threatening global health. The flagellum of V. cholerae functions not only for motility but also as an environmental sensor regulating virulence. The trade-off mechanism between motility loss and enhanced host adaptation remains unclear. ObjectiveThis study aimed to elucidate how flagellar mutations, which lead to a loss of motility, affect host adaptability in V. cholerae and to uncover the underlying molecular basis. MethodsWe analyzed 3,135 cholera-related samples to identify mutation hotspots in flagellar genes. A relevant flagellar mutant library was constructed and assessed for host adaptability. Multiple approaches, including molecular, genetic, transcriptomic, and proteomic analyses, were applied to dissect the FlgM-mediated pathway, with key findings revalidated in an adult mouse model using a specifically constructed 6N-labeled mutant pool. ResultsBig data analysis reveals those flagellar mutations in V. cholerae cluster in key structural and regulatory genes, including flhB, fliA, fliF, fliD, and fliM. Flagellar mutations led to a scenario where the secretion level of the regulator FlgM was negatively correlated with host adaptability. Intracellular FlgM inactivates either the {sigma}28 factor FliA directly or acts through the VarS/VarA-CsrA/BCD system, ultimately leading to the derepression of the quorum-sensing master regulator named hapR. HapR can directly bind to the promoters of genes involving in methionine transportation to regulate adaptability of V. cholerae. The 6N-labeled mutants pool experiment reconfirmed that motility loss promotes host adaptability via the FlgM-FliA-HapR-methionine axis. ConclusionOur findings demonstrate that secretion levels of the flagellar regulator FlgM drive an adaptive shift in V. cholerae from motility to host adaptability, mediated through quorum sensing and methionine metabolic reprogramming. This reveals a novel mechanism underlying bacterial evolution and pathogenicity.

microbiology↗

bioRxiv2025

OVEREXPRESSION OF TUMORPROTECTIVE CLUSTERIN PREVENTS EXHAUSTION OF TRANSGENIC T CELLS

1T cell therapies, such as chimeric antigen receptor (CAR) T cells and T cell receptor (TCR) transgenic (tg) T cells, are a promising approach in the treatment of solid malignancies but are limited by T cell exhaustion caused by chronic antigen stimulation. Clusterin (CLU) is a chaperone protein known to protect both normal and malignant cells, from metabolic stress and reactive oxygen species (ROS). In this study, we investigated whether overexpression (OE) of CLU in TCRtg T cells and CAR-T cells respectively can reduce exhaustion induced by chronic antigen stimulation and enhance T cell functionality against Ewing sarcoma (EwS). Among other cytoprotective genes, we found that CLU was significantly downregulated in dysfunctional tumor infiltrating lymphocytes. Therefore, we engineered EwS-directed TCRtg T cells targeting a Chondromodulin-1 (Chm1)-derived peptide and GD2 CAR-T cells to overexpress CLU. We show here that CLU is downregulated in T cells following activation by tumor cells. CLU-overexpressing T cells exhibit decreased expression of exhaustion markers (PD1, LAG3) and reduced apoptosis after repetitive stimulation. These cells demonstrated improved infiltration into tumor spheroids and maintained functionality under hypoxic conditions. In vivo, CLU-overexpressing T cells showed enhanced persistence and a trend towards reduced tumor growth. Mechanistically, proteomic analysis suggested that reduced ribosomal activity might delay T cell exhaustion, implicating metabolic reprogramming. In conclusion, CLU OE in tg T cells enhances their persistence and functionality by mitigating exhaustion, possibly through modulation of ribosomal activity and metabolic pathways. This strategy holds potential for improving adoptive T cell therapies against solid tumors.

immunology↗

bioRxiv2025

Information Network Flux interprets the importance of regulatory circuits in the protein and gene spaces

Cells receive information from environment, make decisions, and execute biological functions. This sensor-actuator controlling mode is common, and has benefits for system stability especially when there exist feedback-loops for action correction. In cells, transcription factors (TFs) play the role of "brain" since they control the expression levels of about 20,000 protein-coding genes. However, the detailed topological structure of the regulating relationships among them is far from clear. Circuitlike pathways, which usually contain protein-protein interactions (PPIs), TF-gene regulations and gene expressions, are pervasive in cells, however, their importance is yet to be systematically elucidated by unifying information at both protein and gene levels. Here we developed Information Network Flux (INF), an algorithm that could simulate information transmit on multi-layer networks, and integrate protein and gene level information for cell type specific pathways that respond to given perturbation. We used topological analysis to identify regulatory circuits and found that the TFs participating in these circuits, especially those acted as "sensor" or "actuator" are highly relevant to cellular response to external signals. At the gene level, circuit genes serve as efficient cell type indicators, which showed better performance than commonly used gene expression levels. At the circuit level, shorter circuits enrich housekeeping functions and longer circuits exhibit increased tissue-specificity. These findings suggest that these circuit pathways may contribute to the identity and stability of cell states.

biophysics↗

bioRxiv2025

An ultra-low background far-red light-responsive optogenetic tool based on an engineered biliverdin-binding domain

The robustness and broad applicability of an optogenetic tool depends heavily on the properties of the underlying photoreceptor protein and its cognate binding partner - the light responsive core. Current red light optogenetic systems for use in mammalian cells all rely on phytochrome based photoreceptors. These are large (70 kDa) proteins that act as dimers, thereby enforce dimerization on attached proteins. Naturally occurring or engineered binding partners can function effectively in certain cases, but large size, complex mode of interaction, background binding, relatively weak affinity and/or low fold changes between on and off states are significant limitations. Using structure-based design and directed evolution we developed a small (17 kDa) monomeric bilverdin binding photoreceptor FenixS, and a highly selective, high-affinity binder, Ash1 (6 kDa). Negligible off-state binding and a >1200-fold increase in binding affinity upon 700 nm illumination result in a high performance, ultra-low background, light responsive core for a diverse range of applications. An optogenetic tool for red light activation of transcription in mammalian cells based on the FenixS-Ash1 core exhibits robust performance without the need for biliverdin supplementation.

synthetic biology↗

bioRxiv2025

OSM-11 modulates salinity-stress tolerance in Caenorhabditis elegans

Most terrestrial animals exhibit narrow salinity tolerance compared to their marine counterparts. Previous studies identified osm-11 (which encodes a Notch co-ligand) mutations as a driver of hyper-saline tolerance in Caenorhabditis elegans, but mechanistic insights remained unclear. This study employs RNA sequencing and CRISPR/Cas-9 genome editing to demonstrate that osm-11 mutations enhance salinity stress resistance through up-regulation of fatty acid metabolism (acdh-12, acs-17) and cytochrome P450 pathways (ugt-15), while suppressing calcium signaling. Furthermore, we demonstrated that acdh-12 mutation impairs salinity-stress tolerance by activating ferroptosis and mitophagy, accompanied by down-regulated oxidative phosphorylation and up-regulated autophagic pathways. Morphological observations show that mitochondrial fragmentation contributes to wild-type nematode mortality under high salinity, while enlarged lipid droplets in wild-types correlate with reduced {beta}-oxidation gene expression (dhs-28, daf-22), whose knockout disrupts tolerance in mutants. These findings unravel the multi-pathway regulatory network of osm-11-mediated salinity tolerance, providing mechanistic insights for developing protective strategies against environmental salinity stressors impacting animal survival.

genetics↗

bioRxiv2025

Missense Mutation ADNP p.C687R Disrupts Chromatin Regulation and GABAergic Differentiation in HVDAS

Activity-dependent neuroprotective protein (ADNP) is a key regulator of neurodevelopment and a high-risk gene for autism spectrum disorder (ASD). Most pathogenic variants cause loss-of-function in Helsmoortel-Van der Aa syndrome (HVDAS), yet the impact of missense mutations remains unclear. Here, we characterized a ADNP missense mutation (p.C687R) identified from a HVDAS patient, predicted to disrupt its ninth zinc finger domain. Overexpression of p.C687R altered subnuclear localization and affected wild-type ADNP distribution. In utero electroporation revealed impaired neuronal migration and cortical branching. CUT&Tag profiling showed mutant- specific chromatin binding, preferentially targeting histone modification genes through both direct and distal interactions. Patient-derived iPSCs carrying p.C687R exhibited upregulated bivalent histone marks (H3K4me3 and H3K27me3) on neurodevelopmental genes, including regulators of GABAergic differentiation, which became transcriptionally activated in neural progenitors. These findings reveal a gain-of-function mechanism by which ADNP p.C687R perturbs chromatin regulation and disrupts GABAergic lineage specification, expanding the molecular framework of ADNP pathogenesis. The Paper Explained ProblemMutations in the gene ADNP cause Helsmoortel-Van der Aa syndrome (HVDAS), a severe neurodevelopmental disorder, and also increase the risk for autism spectrum disorder (ASD). While most known ADNP mutations lead to loss of protein function, many missense mutations that alter a single amino acid remain poorly understood regarding their effects on brain development and disease contribution. ResultsWe characterized a specific missense mutation, ADNP p.C687R, from a patient diagnosed with HVDAS, and found that it does not simply inactivate the protein but instead confers a disruptive new function. Across multiple models, from cells to mice, the p.C687R mutant exhibits abnormal chromatin binding, altered subnuclear localization, and impaired neuronal migration and differentiation. Importantly, in patient-derived iPSCs, it marks distinct neurodevelopmental genes with bivalent histone modifications, which become aberrantly activated during differentiation into GABAergic neural progenitor cells. ImpactThese findings confirm the pathogenicity of the missense mutation ADNP p.C687R in HVDAS, reveal a gain-of-function mechanism whereby the mutant disrupts chromatin regulation and GABAergic lineage specification, and advance our understanding of ADNP-related neurodevelopmental disorders.

neuroscience↗

bioRxiv2025

Sorghum Metabolic Atlas: Large-Scale Mapping of Subcellular Enzyme Localization in Sorghum bicolor

Plant metabolism drives traits essential for productivity and resilience, yet understanding metabolic networks requires subcellular, cellular, and tissue-level spatial context that remains limited, particularly in crop species. Experimentally-derived subcellular localization data for enzymes are sparse, constraining analyses of metabolic organization in the cell. We developed a high-throughput protoplast transformation and fluorescent protein (FP) tagging system optimized for Sorghum bicolor, a climate-resilient C4 crop. Using this platform, we experimentally determined the subcellular localization of 234 metabolic enzymes spanning 184 pathways. The sorghum enzymes we characterized localize to 12 subcellular compartments. Comparison with computational predictions highlights variable accuracy across compartments, and cross-species comparison with Arabidopsis thaliana shows partial agreement with available experimental data. All data are accessible through the Sorghum Metabolic Atlas (www.sorghummetabolicatlas.org) web platform, enabling search, visualization, and download. This study presents a large-scale experimental dataset of enzyme localization in sorghum, providing a resource for studies of plant metabolic organization and comparative analyses.

plant biology↗

bioRxiv2025

Modeling and Inferring Metacommunity Dynamics with Maximum Caliber

A major challenge for community ecology is using spatio-temporal data to infer parameters of dynamical models without conducting laborious experiments. We present a novel framework from statistical physics - Maximum Caliber - to characterize the temporal dynamics of complex ecological systems in spatially extended landscapes and infer parameters from empirical data. As an extension of Maximum Entropy modeling, Maximum Caliber aims at modeling the probability of possible trajectories of a stochastic system, rather than focusing on system states. We demonstrate the ability of the Maximum Caliber framework to capture ecological processes ranging from near-to far from-equilibrium, using an array of species interaction motifs including random interactions, apparent competition, intraguild predation, and non-transitive competition, along with dispersal among multiple patches. For spatio-temporal data of species occupancy in a metacommunity, the parameters of a Maximum Caliber model can be estimated through a simple logistic regression to reveal migration rates between patches, interactions between species, and local environmental suitabilities. We test the accuracy of the method over a range of system sizes and time periods, and find that these parameters can be estimated without bias. We introduce "entropy production" as a measure of irreversibility in system dynamics, and use "pseudo-R2" to characterize predictability of future states. We show that our model can predict the dynamics of metacommunities that are far from equilibrium. The capacity to estimate basic parameters of dynamical metacommunity models from spatio-temporal data represents an important breakthrough for the study of metacommunities with application to practical problems in conservation and restoration ecology.

ecology↗

bioRxiv2025

Epigenetic Programming of Estrogen Receptor in Adipose Tissue by High Fat Diet Regulates Obesity-Induced Inflammation

Adipose inflammation plays a key role in obesity-induced metabolic abnormalities. Epigenetic regulation, including DNA methylation, is a molecular link between environmental factors and complex diseases. Here we found that high fat diet (HFD) feeding induced a dynamic change of DNA methylome in mouse white adipose tissue (WAT) analyzed by reduced representative bisulfite sequencing. Interestingly, DNA methylation at the promoter of estrogen receptor (Esr1) was significantly increased by HFD, concomitant with a down-regulation of Esr1 expression. HFD feeding in mice increased the expression of DNA methyltransferase 1 (Dnmt1) and Dnmt3a, and binding of DNMT1 and DNMT3a to Esr1 promoter in WAT. Mice with adipocyte-specific Dnmt1 deficiency displayed increased Esr1 expression, decreased adipose inflammation and improved insulin sensitivity upon HFD challenge; while mice with adipocyte-specific Dnmt3a deficiency showed a mild metabolic phenotype. Using a modified CRISPR/RNA-guided system to specifically target DNA methylation at the Esr1 promoter in WAT, we found that reducing DNA methylation at Esr1 promoter increased Esr1 expression, decreased adipose inflammation and improved insulin sensitivity in HFD-challenged mice. Our study demonstrates that DNA methylation at Esr1 promoter plays an important role in regulating adipose inflammation, which may contribute to obesity-induced insulin resistance.

physiology↗

bioRxiv2025

Dnmt3b deficiency in adipocyte progenitor cells ameliorates obesity in female mice

Obesity arises from chronic energy imbalance where energy intake exceeds energy expenditure. Emerging evidence supports a key role of DNA methylation in the regulation of adipose tissue development and metabolism. We recently discovered a key role of DNA methylation, catalyzed by DNA methyltransferase 1 or 3a (Dnmt1 or 3a), in the regulation of adipocyte differentiation and metabolism. Here, we aimed to investigate the role of adipocyte progenitor cell Dnmt3b, an enzyme mediating de novo DNA methylation, in energy metabolism and obesity. We generated a genetic model with Dnmt3b knockout in adipocyte progenitor cells (PD3bKO) by crossing Dnmt3b-floxed mice with platelet-derived growth factor receptor alpha (Pdgfr)-Cre mice. Dnmt3b gene deletion in adipocyte progenitors enhanced thermogenic gene expression in brown adipose tissue, increased overall energy expenditure, and mitigated high-fat diet (HFD)-induced obesity in female mice. PD3bKO mice also displayed a lower respiratory exchange ratio (RER), indicative of a metabolic shift favoring fat utilization as an energy source. Furthermore, female PD3bKO mice exhibited improved insulin sensitivity alongside their lean phenotype. In contrast, male PD3bKO mice showed no changes in body weight but demonstrated decreased insulin sensitivity, revealing a sexually dimorphic metabolic response to Dnmt3b deletion in adipocyte progenitor cells. These findings underscore the critical role of Dnmt3b in regulating energy homeostasis, body weight, and metabolic health, with significant implications for understanding sex-specific mechanisms of obesity and metabolism.

systems biology↗

bioRxiv2024

Trait-dependent biogeography offers insights on the dispersal of Meiogyne (Annonaceae) across the Australasia-Pacific region

Meiogyne is a genus of trees and treelets occurring in Indomalaya and Australasia-Pacific, an unusually wide distribution across Australasia and Western Pacific compared to the rest of the family Annonaceae. Previous chloroplast phylogenies of the genus offered poor resolution and support for many internal nodes. Here, a molecular phylogeny was reconstructed based on seven chloroplast and 11 nuclear markers of 33 Meiogyne taxa (ca. 70% sampling). The combined dataset generated a well resolved and supported phylogeny. Estimation of divergence time was calibrated with two fossils using uncorrelated lognormal relaxed clock model. Trait-dependent and trait-independent biogeographical models in BioGeoBEARS were compared using AICc weight and likelihood ratio test. The results suggest that narrow monocarp width and fruit colour associated with bird dispersal are correlated with increased macroevolutionary dispersal. Under the best-fitting monocarp width-dependent DEC model, a single colonisation event from Sunda to Sahul during the middle to late Miocene and two dispersal events from New Guinea and Australia into the Pacific during the late Miocene to early Pliocene were detected. BayesTraits analysis strongly supports a correlation between narrow fruits and avian fruit colours. This study reveals that Meiogyne lineages with narrow fruitlets and fruit colour associated to bird dispersal (black, red & orange) are associated with increased macroevolutionary dispersal. Bird dispersal and the associated traits may be important drivers for macroevolutionary dispersal for plants with fleshy fruits in Australasia-Pacific.

evolutionary biology↗

bioRxiv2024

Fungus-infected Meiogyne flowers offer a brood site for beetle pollinators in a tripartite nursery pollination system

Fungi are widely known for their pathological impact on flowers, but some play a beneficial role in pollination. We report a case of tripartite pollination system in the flowering plant Meiogyne hainanensis (Annonaceae) in Hainan, China. The flowers emit a fruity scent composed of a mixture of mostly sesquiterpenes and aliphatic esters, attracting the primary beetle pollinators Paraphloeostiba sp. (Staphylinidae) and Mimemodes sp. (Monotomidae). The pollinators utilise the floral chamber as a mating ground and oviposit onto the adaxial corrugations of the inner petals. After the end of anthesis, extensive growth of filamentous fungi was observed to be restricted on these corrugated tissues. Upon hatching, the Paraphloeostiba and Mimemodes larvae consumed the fungal mycelia. ITS2 metabarcoding analysis reveals that the diet of the larvae consists of similar fungal taxa as those found on the inner petals. Both were primarily composed of ascomycete fungi such as Fusarium, Penicillium and Cladosporium species. The flower has an unusually long post-anthetic phase that lasts at least 21 days and up to 2 months, during which the fungus-infested petals remain arboreal, offering suitable microclimate and shelter for the broods. This is the second reported angiosperm genus that exhibits tripartite brood-site pollination in which filamentous fungi are an essential mutualistic partner.

ecology↗

bioRxiv2024

Discovery of novel quinoline papain-like protease inhibitors for COVID-19 through topology constrained molecular generative model

The rapid emergence of drug-resistant SARS-CoV-2 variants poses a persistent challenge to current antiviral strategies. Mutations in key viral targets, including RNA-dependent RNA polymerase (RdRp), main protease (3CLpro), and papain-like protease (PLpro), have been shown to markedly reduce the efficacy of approved therapeutics, highlighting the urgent need for next-generation antivirals capable of overcoming resistance. Here, we report the discovery of a novel class of PLpro inhibitors through an AIDD strategy based on a topology-constrained molecular generative model (Tree-Invent) integrated with structure-guided optimization. Scaffold hopping from a previously reported lead enabled the identification of a quinoline-based chemical series with substantially improved metabolic stability and antiviral potency. Structure-guided optimization yielded compound GZNL-2016, which exhibited potent enzymatic inhibition of PLpro (IC50 = 10.5 nM), robust antiviral activity against multiple SARS-CoV-2 variants, including Omicron BA.5 and XBB.1, and favorable pharmacokinetic properties following oral administration. Notably, GZNL-2016 retained substantial inhibitory activity against the clinically relevant drug-resistant mutant PLpro E167K (IC50 = 480.2 nM; Ki = 439.3 nM), in contrast to previously reported inhibitors that exhibit markedly reduced potency. In a SARS-CoV-2 infection mouse model, oral administration of GZNL-2016 significantly reduced pulmonary viral titers, demonstrating in vivo antiviral efficacy. Collectively, this study establishes an AI-enabled strategy for rapid antiviral discovery and identifies GZNL-2016 as a promising lead compound to address the threat of coronavirus infections caused by drug-resistant mutant SARS-CoV-2 variants. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/611841v3_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@ecbd3eorg.highwire.dtl.DTLVardef@7c663corg.highwire.dtl.DTLVardef@11c0e37org.highwire.dtl.DTLVardef@e950f0_HPS_FORMAT_FIGEXP M_FIG C_FIG We leveraged an AI generative model to discover a novel PLpro inhibitor with excellent liver stability, low CYP, hERG inhibition and reasonable oral PK properties. At the same time, the compound 16 exhibits high efficacy for the resistance mutation E167K, which resulted in severe resistance to the previously reported inhibitor Jun12682 and PF-07957472.

microbiology↗

bioRxiv2024

UnigeneFinder: An automated pipeline for gene calling from transcriptome assemblies without a reference genome

For most species in nature, transcriptome data is much more readily available than genome data. Without a reference genome, however, gene calling is cumbersome and inaccurate due to the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared to existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high quality reference genomes. These features, coupled with the pipelines cross-platform implementation and focus on automation and an accessible user interface, make UnigeneFinder a useful tool for many downstream sequence-based analyses in non-model organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high-performance computing (HPC) systems and personal computers, further reducing barriers to use.

bioinformatics↗

bioRxiv2024

IL-13 decreases susceptibility to airway epithelial SARS-CoV-2 infection but increases disease severity in vivo

Treatments available to prevent progression of virus-induced lung diseases, including coronavirus disease 2019 (COVID-19) are of limited benefit once respiratory failure occurs. The efficacy of approved and emerging cytokine signaling-modulating antibodies is variable and is affected by disease course and patient-specific inflammation patterns. Therefore, understanding the role of inflammation on the viral infectious cycle is critical for effective use of cytokine-modulating agents. We investigated the role of the type 2 cytokine IL-13 on SARS-CoV-2 binding/entry, replication, and host response in primary HAE cells in vitro and in a model of mouse-adapted SARS-CoV-2 infection in vivo. IL-13 protected airway epithelial cells from SARS-CoV-2 infection in vitro by decreasing the abundance of ACE2- expressing ciliated cells rather than by neutralization in the airway surface liquid or by interferon-mediated antiviral effects. In contrast, IL-13 worsened disease severity in mice; the effects were mediated by eicosanoid signaling and were abolished in mice deficient in the phospholipase A2 enzyme PLA2G2D. We conclude that IL-13-induced inflammation differentially affects multiple steps of COVID-19 pathogenesis. IL-13-induced inflammation may be protective against initial SARS-CoV-2 airway epithelial infection; however, it enhances disease progression in vivo. Blockade of IL-13 and/or eicosanoid signaling may be protective against progression to severe respiratory virus-induced lung disease. RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSPrior to this study, various pieces of evidence indicated the significant role of cytokines in the pathogenesis and progression of COVID-19. Severe COVID-19 cases were marked by cytokine storm syndrome, leading to immune activation and hyperinflammation. Treatments aimed at modulating cytokine signaling, such as IL-6 receptor antagonists, had shown moderate effects in managing severe COVID-19 cases. Studies also revealed an excessive production of type 2 cytokines, particularly IL-13 and IL-4, in the plasma and lungs of COVID-19 patients, which was associated with adverse outcomes. Treatment with anti-IL-13 monoclonal antibodies improved survival following SARS-CoV-2 infection, suggesting that IL-13 plays a role in disease severity. Type 2 cytokines were observed to potentially suppress type 1 responses, essential for viral clearance, and imbalances between these cytokine types were linked to negative COVID-19 outcomes. These findings highlighted the complex interactions between cytokines and the immune response during viral infections, underscoring the importance of understanding IL-13s role in COVID-19 and related lung diseases for developing effective therapeutic interventions. Added value of this studyIn this study, we explored the impact of IL-13-induced inflammation on various stages of the SARS-CoV-2 infection cycle using both murine (in vivo) and primary human airway epithelial (in vitro) culture models. Our findings indicated that IL-13 provided protection to airway epithelial cells against SARS-CoV-2 infection in vitro, partly by reducing the number of ACE2- expressing ciliated cells. Conversely, IL-13 exacerbated the severity of SARS2-N501YMA30-induced disease in mice, primarily through Pla2g2d-mediated eicosanoid biosynthesis. Implications of the available evidenceCurrent evidence indicates that PLA2G2D plays a crucial role in the IL-13-driven exacerbation of COVID-19 in mice, suggesting that targeting the IL-13-PLA2G2D axis could help protect against SARS-CoV-2 infection. These insights are important for clinical research, especially for studies focusing on drugs that modify IL-13 signaling or modulate eicosanoids in the treatment of asthma and respiratory virus-induced lung diseases.

cell biology↗

bioRxiv2024

A predominately pulmonary activation of complement in a mouse model of severe COVID-19

Evidence from in vitro studies and observational human disease data suggest the complement system plays a significant role in SARS-CoV-2 pathogenesis, although how complement dysregulation develops in patients with severe COVID-19 is unknown. Here, using a mouse-adapted SARS-CoV-2 virus (SARS2-N501YMA30) and a mouse model of severe COVID-19, we identify significant serologic and pulmonary complement activation following infection. We observed C3 activation in airway and alveolar epithelia, and in pulmonary vascular endothelia. Our evidence suggests that while the alternative pathway is the primary route of complement activation, components of both the alternative and classical pathways are produced locally by respiratory epithelial cells following infection, and increased in primary cultures of human airway epithelia in response to cytokine exposure. This locally generated complement response appears to precede and subsequently drive lung injury and inflammation. Results from this mouse model recapitulate findings in humans, which suggest sex-specific variance in complement activation, with predilection for increased C3 activity in males, a finding that may correlate with more severe disease. Our findings indicate that complement activation is a defining feature of severe COVID-19 in mice and lay the foundation for further investigation into the role of complement in COVID-19.

immunology↗

bioRxiv2024

A reference-free algorithm discovers regulation in the plant transcriptome

Most plant genomes and their regulation remain unknown. We used SPLASH - a new, reference-genome free sequence variation detection algorithm - to analyze transcriptional and post-transcriptional regulation from RNA-seq data. We discovered differential homolog expression during maize pollen development, and imbibition-dependent cryptic splicing in Arabidopsis seeds. SPLASH enables discovery of novel regulatory mechanisms, including differential regulation of genes from hybrid parental haplotypes, without the use of alignment to a reference genome.

bioinformatics↗

bioRxiv2024

SARS-CoV-2 infection unevenly impacts metabolism in the coronal periphery of the lungs

HighlightsO_LICOVID-19 significantly decreases amino acids, fatty acids, and most eicosanoids C_LIO_LISARS-CoV-2 preferentially localizes to central lung tissue C_LIO_LIMetabolic disturbance is highest in peripheral tissue, not central like viral load C_LIO_LISpatial metabolomics allows detection of metabolites not altered overall C_LI SARS-CoV-2, the virus responsible for COVID-19, is a highly contagious virus that can lead to hospitalization and death. COVID-19 is characterized by its involvement in the lungs, particularly the lower lobes. To improve patient outcomes and treatment options, a better understanding of how SARS-CoV-2 impacts the body, particularly the lower respiratory system, is required. In this study, we sought to understand the spatial impact of COVID-19 on the lungs of mice infected with mouse-adapted SARS2-N501YMA30. Overall, infection caused a decrease in fatty acids, amino acids, and most eicosanoids. When analyzed by segment, viral loads were highest in central lung tissue, while metabolic disturbance was highest in peripheral tissue. Infected peripheral lung tissue was characterized by lower levels of fatty acids and amino acids when compared to central lung tissue. This study highlights the spatial impacts of SARS-CoV-2 and helps explain why peripheral lung tissue is most damaged by COVID-19.

microbiology↗