Biology subjects

Tang, W.

Publications and source records attributed to Tang, W..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Cellular heterogeneity and therapeutic response profiling of human IDH+ glioma stem cell cultures

Summary/AbstractGlioblastoma stem cell (GSC) cultures are initiated from glioblastoma (GBM) surgical resection tissue. They can capture and propagate key GBM primary tumor molecular and cellular features. We have deeply characterized four isocitrate dehydrogenase (IDH)-expressing (or IDH+) GSC cultures from unrelated adults to serve as cellular models for the majority of adult primary GBM. We demonstrate that GSC cultures can be continuously propagated in defined, serum-free media and 5% oxygen without requiring specialized growth substrates; have well-defined genomic and mtDNA variants and gene/protein expression profiles; and highly reproducible dose-survival curves when treated with the GBM standard-of-care therapies of ionizing radiation (IR) and temozolomide (TMZ). We also illustrate how expressed lentiviral barcodes, mtDNA variants and single cell gene expression profiling can be used to define and track cellular heterogeneity over 40 days after IR treatment. These well-characterized IDH+ GSC cultures can support many high throughput in vitro assay formats, including xenograft, organoid and other GBM disease modeling protocols. They should prove a useful resource to better understand GBM biology, and to identify new and more effective GBM therapies and treatment regimens. HighlightsO_LIGlioblastoma (GBM)-derived IDH-expressing Glioma Stem Cell (GSC) cultures can capture and propagate GBM genomic variants, gene and protein expression programs. C_LIO_LIMitochondrial DNA (mtDNA) variants identified by high accuracy Duplex DNA sequencing are abundant and sub-clonally organized in GSC cultures. C_LIO_LIGSC cultures have highly reproducible dose-survival curves for ionizing radiation and temozolomide, the GBM standard-of-care therapies. C_LIO_LIGSC culture cellular heterogeneity can be captured, characterized and tracked by using expressed lentiviral barcodes, mtDNA variants and scRNA sequencing. C_LI eTOC blurbIDH-expressing glioma stem cell cultures (GSCs) are experimentally tractable and versatile glioblastoma (GBM) cellular disease models. Deeply characterized GSC cultures can enable new work to understand GBM biology, and help identify new and more effective GBM therapies and treatment regimens. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/667532v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@82aceeorg.highwire.dtl.DTLVardef@1277c18org.highwire.dtl.DTLVardef@144188eorg.highwire.dtl.DTLVardef@1a84bb3_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Dorsal Attention Network as a Convergent Hub of Diverse Non-pharmacological Interventions Preserving Functional Gradients and Cognition in Aging

Non-pharmacological interventions (NPIs) in aging neuroscience have largely focused on intervention-specific regional effects, with limited understanding of generalizable network-level mechanisms. Here, adopting a previously unexplored gradient-based perspective of functional brain organization, we analyzed an NPI dataset involving four interventions in older adults (training/control group: n = 112/59). NPIs led to strengthened intra-network functional integration and maintained macroscale gradient architecture. Virtual lesion analyses identified the dorsal attention network (DAN) as a key contributor to gradient maintenance. Critically, enhanced post-intervention DAN connectivity was associated with maintained gradient structure and improved global cognition. These findings establish a unifying framework in which the DAN acts as a convergent hub through which diverse NPIs preserve functional brain organization and attenuate cognitive aging.

neuroscience↗

bioRxiv2025

DANCE 2.0: Transforming single-cell analysis from black box to transparent workflow

Preprocessing is a critical step in single-cell data analysis, yet current practices remain largely a black-box, trial-and-error process driven by user intuition, legacy defaults, and ad hoc heuristics. The optimal combination of steps such as normalization, gene selection, and dimensionality reduction varies across tasks, model architectures, and dataset characteristics, hindering reproducibility and method development. We present DANCE 2.0, an automated and interpretable preprocessing platform featuring two key modules: the Method-Aware Preprocessing (MAP) module, which discovers optimal pipelines for task-specific methods via hierarchical search, and the Dataset-Aware Preprocessing (DAP) module, which recommends pipelines for new datasets via similarity-based matching to a reference atlas. Together, MAP and DAP execute over 325,000 pipeline searches across six major tasks - clustering, cell type annotation, imputation, joint embedding, spatial domain identification, and cell type deconvolution - yielding robust and generalizable recommendations. MAP-recommended pipelines consistently outperform original method defaults, with substantial gains across all tasks. Beyond automation, DANCE 2.0 reveals interpretable preprocessing patterns across tasks, methods, and datasets, transforming preprocessing into a transparent, data-driven process. All resources are openly available at https://github.com/OmicsML/dance to support broad community adoption and future methodological advances.

bioinformatics↗

bioRxiv2025

Design principles of the common Gly-X6-Gly membrane protein building block

Protein behavior in lipid is poorly understood and inadequately represented in current computational models. Design and prediction abilities for bilayer-embedded molecular structures may be improved by characterizing membrane proteins most frequent, favored structural features to glean both context-specific and general principles. We used protein design to proactively interrogate the sequence-structure relationship and stabilizing atomic details of two highly prevalent antiparallel transmembrane (TM) motifs with Small-X6-Small consensus sequences. A fragment-based data-mining and sequence statistical inference method including cross-evolutionary structure-aligned covariance enabled engineering of de novo multi-span TM protein assemblies by successfully encoding Gly-X6-Gly and Ala-X6-Ala building blocks. A highly stable glycine-based designs X-ray structure hosts C-H{middle dot}{middle dot}{middle dot}O=C H-bonding alongside extensive backbone-directed van der Waals packing, idealizing features of this motif in Nature. Data-driven design navigates sequence space to directly inquiry upon how to encode and stabilize vital membrane protein structural elements, facilitating efficacious construction of lipid-embedded architectures of increasing complexity. SignificanceMembrane proteins comprised of -helices pack together within lipid bilayers, establishing stabilities and architectures that brace function and guide evolution. De novo design was used to clarify the consensus sequences and molecular features encoding of one exceedingly common TM helix packing architecture ([~]10% of those in membrane folds). Small-X6-Small residue patterns were proven to reliably drive minimal proteins into these antiparallel TM geometries, revealing glycine mainchain hydrogen bonding or via fully apolar interfaces can encode the motif. Optimizing steric packing was the most decisive feature amongst the synthetic proteins. New membrane-specific design methods and model molecules are validated in route to outlining this important sequence-structure relationship broadly impacting the membrane proteome and revealing generalized structure-energetic imperatives governing interactions in lipid.

biophysics↗

bioRxiv2025

miRNA/mRNA analysis of increased TGF-β pathways drive epithelial-mesenchymal transition and regulatory T cell differentiation

Chlamydia trachomatis genital tract infection is linked to severe reproductive complications in women, including ectopic pregnancy, infertility, and adverse pregnancy outcomes. Mouse models of infection suggest that chlamydia-induced dysregulation of microRNAs (miRNAs) can drive harmful cytokine responses, pathogenic epithelial-mesenchymal transition (EMT), and fibrosis. To investigate these mechanisms in humans, we profiled miRNA and mRNA expression in endometrial biopsies from women with endometrial infection (Endo+) and compared them to profiles from women with cervix-only infection (Endo-) or no infection. Ingenuity Pathway Analysis (IPA) revealed that Endo+ tissues had upregulated genes associated with innate and adaptive immune response pathways, as well as EMT regulation, while downregulated genes were linked to cell cycle control. An integrative miRNA-mRNA analysis, which combined a review of published miRNA regulation in human infections and immune responses with IPAs miRNA target filter, identified differentially expressed miRNAs that modulate these pathways in the endometrium of Endo+ women. Functional annotation of these miRNAs showed a predominance of downregulated miRNAs that typically suppress EMT and regulatory T cell (Treg) differentiation, along with miRNAs that usually enhance Th17 responses. Comparisons with previously identified mRNA pathways in blood samples from women with endometrial Chlamydia infection indicated that alterations in TGF-{beta} signaling and EMT were specific to the endometrium. Overall, the miRNA-mRNA interactions inferred from Endo+ tissue suggest increased activity in TGF-{beta} pathways that promote enhanced EMT and Treg differentiation, while reducing Th17 activation. These changes highlight a dual potential for promoting tissue scarring while dampening inflammatory responses that could otherwise limit infection.

genomics↗

bioRxiv2025

MemPPI platform for measuring and engineering membrane protein-protein interactions in mammalian cells via split nanoluciferase

Membrane protein-protein interactions (memPPIs) underlie critical biological processes including mediating signal transduction, transport, cell communication, and membrane organization. Despite their importance, systematic and quantitative measurement of protein transmembrane (TM) domains laterally interacting in mammalian cells remains challenging. Conventional fusion protein assays directed at memPPIs suffer from low dynamic range, due to the crowded membrane environment and interference from overexpression, trafficking, or self-complementation artifacts. Here, we assessed and further developed the split luciferase complementation NanoBit system to establish suitable expression constructs and working conditions for robust quantification of TM PPIs within human cells. We benchmarked the platform using a panel of natural and synthetic memPPI pairs with diverse architectures, insertion topologies, and trafficking patterns, finding assay settings that robustly distinguish true positive interactions from co-expressed non-interacting pairs. Adding a novel procedure measuring and normalizing protein expression levels in situ in parallel, we drastically improve assay dynamic range and consistency in discerning relative interaction propensities across broad expression levels - which also enhanced compatibility with protein engineering screens. To extend measurements to versatile protein contexts, we developed membrane expression constructs and validated tagging strategies to improve trafficking with defined TM orientations. By incorporating topological control and accounting for variations in expression levels, this memPPI platform becomes a viable approach for high-throughput interaction analyses and experimental screens for membrane protein design such as TM binders targeting human membrane proteins. Owing to its sensitivity, scalability, and adaptability, we expect this assay platform to have broad cross-disciplinary utility in protein science, design, and drug discovery.

bioengineering↗

bioRxiv2025

An intergenerational lipid memory of the social environment in C. elegans

Information about the environment can, in some cases, be transmitted to an organisms offspring by epigenetic inheritance. Here, we describe a novel form of epigenetics in C. elegans where information is transmitted between generations not by alterations in DNA, chromatin, or RNA, but by changes in the composition of lipids. Specifically, we delineate an environment-to-neuron-to-intestine-to-oocyte signalling axis that alters progeny thermotolerance by remodelling lipid provisioning to oocytes when animals detect social pheromones. Intergenerational information transmission via lipid memories may represent an underappreciated form of epigenetics.

genetics↗

bioRxiv2025

Stochastic gates for covariate selection in population pharmacokinetics modelling

Covariate selection in population pharmacokinetics modelling is essential for understanding interindividual variability in drug response and optimizing dosing. Traditional stepwise covariate modelling is often time-consuming, compared to the new machine learning alternatives. This study investigates the use of Neural Networks with Stochastic Gates for automated covariate selection, aiming to efficiently identify relevant covariates while penalizing excessive covariate inclusion. On various synthetic datasets the approach demonstrated robustness in detecting important covariates, overcoming challenges such as high correlations, low covariate frequencies, high interindividual variability and complex covariate dependencies. In real clinical data from a monalizumab study, the method successfully identified covariates that matched those found by experts. However, for tixagevimab/cilgavimab, it identified a superset of covariates, indicating a potential need for further pruning. This machine learning-based method enhances the covariate pre-selection process in population pharmacokinetics model development, offering significant time savings and improving efficiency even under challenging scenarios. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/656586v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@1f5180borg.highwire.dtl.DTLVardef@1fd97e7org.highwire.dtl.DTLVardef@1ffc3d0org.highwire.dtl.DTLVardef@90c207_HPS_FORMAT_FIGEXP M_FIG C_FIG Study HighlightsO_ST_ABSWHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?C_ST_ABSCovariate selection in population pharmacokinetics modelling is a crucial step in drug development and dosing determination. Traditionally, this process is conducted in a stepwise manner, which can be very time-consuming. Recently, fast machine learning (ML)-based methods for covariate selection have emerged in the literature, offering more efficient alternatives. WHAT QUESTION DID THIS STUDY ADDRESS?Can we use Neural Networks with Stochastic Gates, incorporating explicit penalization on the number of covariates, to select superior set of covariates compared to prior ML-based methods? WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?Neural Networks with Stochastic Gates provide a reliable approach in accurately detecting covariates because they can effectively eliminate irrelevant covariates even in cases with high inter-covariates correlation. HOW MIGHT THIS CHANGE DRUG DISCOVERY, DEVELOPMENT, AND/OR THERAPEUTICS?This approach accelerates pharmacokinetic model development by significantly reducing the time required for covariate evaluation. Additionally, it allows for the screening of a wider set of covariates, potentially leading to fewer falsely missed covariates and better-quality models, a task that would be infeasible with traditional stepwise covariate modelling.

pharmacology and toxicology↗

bioRxiv2025

Advanced eTAM-seq enables high-fidelity, low-input N6-methyladenosine profiling in human cells and embryonic mouse tissues

Functional dissection of N6-methyladenosine (m6A), the most abundant internal messenger RNA modification in mammals, demands quantitative, scalable detection technology. We previously reported eTAM-seq, which supports transcriptome-wide quantification of m6A by enzyme-assisted adenosine deamination. While effective, TadA8.20--the enzyme used in our first-generation technology--is sensitive not only to m6A but also to RNA structure, making accurate detection dependent on the inclusion of control transcriptomes. Here, we introduce eTAM-seq-v2, in which we replace TadA8.20 with TadA8r, a further evolved adenosine deaminase with superior catalytic efficiency. eTAM-seq-v2 supports control-free m6A calling with high fidelity. Because enzyme treatment preserves RNA integrity, eTAM-seq surveys >51% of A sites in all expressed genes with moderate sequencing depth (60 million uniquely mapped reads) and delivers robust performance with as little as 10 ng of total RNA ([~]500 cells). With eTAM-seq-v2, we delineate the m6A landscape across six human cell lines and seven embryonic mouse tissues. While uncovering broadly conserved m6A patterns, we reveal that most neighboring m6A sites are independently deposited at the single-molecule level. Moving forward, we envision that eTAM-seq-v2 will enable researchers to survey m6A in diverse biological contexts and uncover new insights into its regulatory roles.

molecular biology↗

bioRxiv2025

Unbiased genetics identifies a glutamatergic signaling network as a mediator of daily sleep patterns.

Sleep is a fundamental, conserved behavior important for survival. In many species, sleep behavior is controlled by poorly understood interactions between a system of circadian rhythms (CR), which promote sleep at ecologically appropriate times, and a homeostatic sleep drive that accumulates with time awake. The CR is a cellular phenomenon, driven by molecular oscillations of "clock genes" in nearly all cells. Emerging evidence indicates neuronal synapses are a key locus for the accumulation and resolution of sleep need, supporting a cellular basis of sleep need. Indeed, efforts to understand the genetic basis of sleep need identified Homer1a, a regulator of synapse homeostasis. To develop further insight into the genetic basis of sleep regulation, we measured daily sleep patterns in genetically diverse strains of mice from the Collaborative Cross. Strains with 1) highly consolidated light-phase sleep, or 2) fragmented, arrhythmic sleep, were identified for genetic analysis using quantitative trait loci (QTL) mapping. Excitingly, in F2 hybrids, 19 of 32 metrics of sleep and circadian behavior mapped to a narrow QTL containing GRM5, a postsynaptic glutamate receptor and binding partner of Homer1a, and GCPII, an astrocytic enzyme that regulates NAAG, a peptide agonist for the presynaptic/astrocytic glutamate receptor GRM3. Collectively, these genes form a coordinated glutamatergic signaling network across the tri-partite synapse. Pharmacology targeting GRM5, GCPII, and GRM3 strongly modulated sleep, functionally validating them as sleep-regulating genes. Our findings support a model in which synapses act as a cellular site for integration of circadian and sleep-need signals to regulate daily sleep patterns. Significance StatementSleep is a fundamental pillar of human health. Restorative sleep is supported by circadian rhythms (CR). Sleep and CR disruptions are prevalent in neuropsychiatric conditions and are increasingly understood as causal drivers of altered brain function and behavior. Therefore, sleep and CR are attractive therapeutic targets to improve health. However, the basic biological mechanisms that couple our need to sleep with the CR are not understood. Genetic discovery using diverse strains of mice identifies a glutamatergic signaling network coordinated across the synapse as an underlying genetic basis for daily sleep patterns. This work builds upon a growing body showing that excitatory synapses are a cellular site for the resolution of sleep need and interaction with the CR.

neuroscience↗

bioRxiv2025

p53-induced RNA-binding protein ZMAT3 inhibits transcription of a hexokinase to suppress mitochondrial respiration

The tumor suppressor p53 is a transcription factor that controls the expression of hundreds of genes. Emerging evidence indicates that the p53-induced RNA-binding protein ZMAT3 acts as a key splicing regulator that contributes to p53-dependent tumor suppression in vitro and in vivo. However, the mechanism by which ZMAT3 functions within the p53 pathway remains largely unclear. Here, we discovered a function of ZMAT3 in inhibiting transcription of HKDC1, a hexokinase that regulates glucose metabolism and mitochondrial respiration. Quantitative proteomics revealed HKDC1 as the most significantly upregulated protein in ZMAT3-depleted colorectal cancer cells. ZMAT3 depletion resulted in increased mitochondrial respiration, which was rescued by simultaneous depletion of HKDC1, suggesting that HKDC1 is a critical downstream effector of ZMAT3. Unexpectedly, ZMAT3 did not bind to HKDC1 RNA or DNA; however, proteomic analysis of the ZMAT3 interactome identified its interaction with the oncogenic transcription factor JUN. ZMAT3 depletion enhanced JUN binding to the HKDC1 locus, leading to increased HKDC1 transcription that was rescued upon JUN depletion, suggesting that JUN activates HKDC1 transcription in ZMAT3-depleted cells. Collectively, these findings uncover a mechanism by which ZMAT3 regulates transcription through JUN and demonstrate that HKDC1 is a key component of the ZMAT3-regulated transcriptome in the context of mitochondrial respiration regulation.

cancer biology↗

bioRxiv2025

Cross-species Standardised Cortico-Subcortical Tractography

Despite their importance for brain function, cortico-subcortical white matter tracts are underrepresented in diffusion MRI tractography studies. Their non-invasive mapping is more challenging and less explored compared to other major cortico-cortical bundles. We introduce a set of standardised tractography protocols for delineating tracts between the cortex and various deep subcortical structures, including the caudate, putamen, amygdala, thalamus and hippocampus. To enable comparative studies, our protocols are designed for both human and macaque brains. We demonstrate how tractography reconstructions follow topographical principles obtained from tracers in the macaque and how these translate to humans. We show that the proposed protocols are robust against data quality and preserve aspects of individual variability stemming from family structure in humans. Lastly, we demonstrate the value of these species-matched protocols in mapping homologous grey matter regions in humans and macaques, both in cortex and subcortex.

neuroscience↗

bioRxiv2025

Investigating the Impact of Measurement Variance on Gene Circuit Model Parameterization

Ordinary differential equation (ODE)-based modeling is a powerful tool in the design and characterization of synthetic gene circuits. Despite its popularity, identifying the model parameters based off experimental measurement is a nontrivial task. In this study, we leverage cell-free experimental measurement of two RNA-based regulators to investigate the impact and the incorporation of measurement variance in the pair-wise squared error objective function used for ODE-model parameterization. Our findings suggest that while unweighted objective function and weighting by the inverse variance can provide reasonably accurate parameter estimation, weighing the objective function with the inverse stabilized variance could further improve the parameterization, by also capturing the system variance with a mitigated prediction variance.

synthetic biology↗

bioRxiv2025

A hippocampal population code for rapid generalization

Generalizing from experience and applying prior knowledge to new situations is essential for intelligent behavior. Traditional models attribute this generalization to gradual statistical learning in the neocortex. However, such a slow process cannot account for animals rapid generalization from limited experience. Here, we demonstrate that the hippocampus supports rapid generalization in mice by generating disentangled memory representations, where different aspects of experience are encoded independently. This code enabled the transfer of prior knowledge to solve new tasks. We identify specific circuit mechanisms underlying this rapid generalization. We show that the seemingly random changes in individual neuronal activity over time and across environments result from structured circuit-level processes, governed by the dynamics of local inhibition and cross-regional cell assemblies, respectively. Our findings provide computational and mechanistic insights into how the geometric structure and underlying circuit organization of hippocampal population dynamics facilitate both memory discrimination and generalization, enabling efficient and flexible learning.

neuroscience↗

bioRxiv2025

Harnessing Neutrophils to Deliver Antibiotics Non-Invasively across the Tympanic Membrane for Otitis Media Treatment

Acute otitis media (AOM) is a leading cause of pediatric antibiotic prescriptions. Systemic antibiotics cause side effects and antibiotic resistance, whereas local delivery of antibiotics (directly to the middle ear) is hindered by an impermeable biological barrier, the tympanic membrane (TM). Here, we report on a liposome that hitchhikes on neutrophils to deliver antibiotics to the site of infection. Distinct from previous immune-cell-based therapies, we enable neutrophil hitchhiking via a topical application of hydroxylated liposomes, thus bypassing the invasive neutrophil harvesting procedures. The hydroxylated liposomes are opsonized by the complement protein fragments and subsequently internalized by native neutrophils. A simple topical application completely cures AOM in an established chinchilla model. It points to a low-cost and non-invasive treatment for this prevalent disease, poised to reduce pediatric antibiotic usage.

bioengineering↗

bioRxiv2025

Trifluoroacetate reduces plasma lipid levels and the development of atherosclerosis in mice

Trifluoroacetate (TFA) has been assumed to be an innocuous counterion (to cationic amino acid side chains) present in countless synthetic bioactive peptides and a few FDA-approved therapeutics. We show here that TFA is in fact bioactive and causes dramatic biological effects in multiple strains of mice and cultured human and rat liver cells. In high-fat diet (HFD)-fed low-density lipoprotein receptor-null (LDLr-/-) mice, TFA reduces the levels of plasma cholesterol, triglycerides, and the development of atherosclerotic lesions following either oral or intraperitoneal administration. These physiological effects were observed with TFA alone, or with TFA present as a counterion of a variety of short, unrelated synthetic peptide sequences. Mechanistic investigations including RNA-seq, confocal microscopy, western blotting, metabolomics, proteomics, pharmacokinetics, and biochemical assays indicated that TFA induces peroxisome proliferation by activating peroxisome proliferator-activated receptor (PPAR)-alpha. We confirmed that TFA also caused peroxisome proliferation and downstream phenotypic effects in cultured human and rat liver cells, wild-type C57/Bl mice, and apolipoprotein E-null (apoE-/-) mice, leading to anti-atherosclerotic effects in the latter strain. Given that TFA is a counterion in many peptides employed in early research and development settings, these findings raise the possibility that TFA may be confounding or contributing to phenotypic changes observed in many studies involving peptides. Although our studies suggest that TFA or its analogues might have therapeutic applications, it should be noted that TFA is also a persistent environmental contaminant that is found at high levels in humans relative to other polyfluoroalkyl substances (PFAS), and is a major metabolite following treatment of patients with common inhaled anesthetics, suggesting that the biological effects reported here could have other implications for human health.

biochemistry↗

bioRxiv2025

Characterisation of guided entry of tail-anchored proteins in Magnaporthe oryzae

Rice (Oryza sativa L.) is one of the most important staple foods for human population worldwide. However, rice production continues to be severely threatened by rice blast disease caused by an ascomycete fungus Magnaporthe oryzae. Tail-anchored (TA) proteins are conserved across diverse organisms, and belongs to a class of polypeptides that are inserted into the membrane by a hydrophobic sequence located at the C- terminal region. The Guided Entry of Tail-anchored (GET) complex is responsible for the post-translational insertion of nascent TA proteins into the ER lipid bilayer. In Saccharomyces cerevisiae, the GET pathway comprises of six known associated components Get1, Get2, Get3, Get4, Get5, Sgt2 and Ssa1 that have been identified and extensively studied. However, the role of the GET complex in rice blast fungus has not been elucidated. Here in, we identified five proteins of the GET Complex in M. oryzae namely MoGet1, MoGet2, MoGet3, MoGet4 and MoSgt2 and generated the gene knock-out mutants. Deletion of MoGET1 and MoGET2 revealed that they are required for vegetative growth, asexual reproduction and pathogenesis, while MoGet3 negatively regulates hyphal growth, asexual development and pathogenesis of M. oryzae. In contrast, loss of MoGet4 and MoSgt2 had no effect on the normal development of the rice blast fungus. We demonstrated that the MoGet2 is important in osmotic stress response while MoGet2 and MoGet3 positively and negatively regulate cell wall integrity, respectively. The MoGet1 and MoGet2 were ER-localised and indispensable for DTT-induced ER stress response. In vitro and in vivo interaction assay revealed MoGet3 has physical interaction with both MoGet1 and MoGet2 indicating the existence of possible synergistic function amongst the Get components in rice blast fungus. In summary, this finding indicates the GET Components offers an excellent target for the development of antifungal components against recalcitrant plant fungal pathogens.

genetics↗

bioRxiv2025

Active surveillance of cats and dogs from households with human COVID-19 cases reveals over one quarter of pets infected with SARS-CoV-2 in 2020-2021 in Texas, United States

Households where people have COVID-19 are high risk environments for companion animals that are susceptible to SARS-CoV-2. We sampled 579 pets from 281 households with one or more laboratory-confirmed person with COVID-19 in central Texas from June 2020 to May 2021. Nineteen out of 396 (4.8%) dogs and 21 out of 157 (13.4%) cats were positive for SARS-CoV-2 by RT-qPCR. Additionally, 95/382 (25%) dogs and 52/146 (36%) cats harbored SARS-CoV-2 neutralizing antibodies. Twenty-six companion animals of ten other species were negative. Overall, 164 (29%) pets were positive for SARS-CoV-2 by molecular and/or serological tests; a total of 110 (39%) out of 281 households had at least one animal with active or past SARS-CoV-2 infection. Cats were more likely to be infected by SARS-CoV-2 and had higher endpoint antibody titers than dogs. Through viral isolation from a subset of respiratory swabs, we documented 6 different lineages in dogs and cats, including the B.1.1 lineage in a cat one month prior to the first known human case in the country. We observed animal and human-pet interaction factors associated with higher risk of infection for dogs and cats, such as days after COVID-19 diagnosis and sharing food. Frequency of clinical signs of disease reported by owners of pets with active infections did not differ from uninfected ones, suggesting that not all reported signs are attributed to SARS-CoV-2 infection. Characterizing animal infections using active SARS-CoV-2 surveillance in pets at risk of infection may aid in One Health pandemic prevention, response, and management.

microbiology↗