Biology subjects

Wong, J.

Publications and source records attributed to Wong, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Neonatal T cell maternal microchimerism is common and associates with early pregnancy SARS2 vaccination

The fetus acquires a graft of maternal cells in utero, known as maternal microchimerism (MMc), which may be enriched for T cells. However, little is known regarding the determinants of T cell trafficking into the fetus or regarding the prevalence of T cell MMc in healthy neonates. Using a closely followed cohort, we determined the association between maternal vaccination and acute infection and the detection of T cell MMc in cord blood, as measured using polymorphism-specific qPCR. We identified an association between early pregnancy SARS2 mRNA vaccination, a potent T cell stimulus, and increased detection of T cell MMc.

immunology↗

bioRxiv2026

Multigenerational machine learning-based genomic prediction for dermo resistance in eastern oyster Crassostrea virginica

Dermo disease caused by the protist Perkinsus marinus poses a major threat to Eastern oyster aquaculture. We previously conducted genomic selection for dermo resistance and found increased effectiveness over phenotypic selection. Here, we report improved genomic predictions using combined data from three successive generations. We evaluated nine different genomic selection models, including three supervised machine learning architectures: gradient boosting, logistic regression, and random forest. Combining data across multiple generations did not, by itself, substantially improve the accuracy of most models, but the increased sample size provided genotyping confidence of loci with rare alleles. Correlation accuracy of all models significantly increased with the inclusion of low-frequency variants and strong-effect markers identified through a genome-wide association study. Gradient boosting machine learning models outperformed other genomic selection models across all training scenarios, suggesting enhanced capacity to learn generalizable genomic signals associated with dermo resistance. The best gradient boosting model achieved a peak correlation accuracy of 0.410, a substantial improvement over the previous peak accuracy of 0.274 from traditional models. Together, our results highlight the potential of machine learning for genomic selection and the significance of rare variants in determining dermo resistance.

genomics↗

bioRxiv2026

Gut-derived ammonia modulates hypothalamic stress responses during viral infection

The gut-brain axis integrates microbial and host metabolism to regulate systemic physiology, yet its role during viral infection remains poorly defined. Viral infection induces behavioral changes and neuroendocrine stress responses accompanied by profound alterations in gut microbial metabolism. Here, we show that chronic viral infection in mice increases systemic levels of microbiota-derived ammonia in a CD8 T cell-dependent manner. Increased ammonia accumulates in the brain and selectively activates neurons within the paraventricular hypothalamus (PVH), driving corticosterone release into the circulation. Pharmacological inhibition of ammonia detoxification exacerbates these effects, leading to increased corticosterone levels, aggravated sickness behavior, and dampened antiviral responses. Together, these findings identify gut-derived ammonia as a previously unrecognized immunometabolic signal linking antiviral T cell responses to hypothalamic control of systemic stress during viral infection. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=186 SRC="FIGDIR/small/736796v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@1291dbcorg.highwire.dtl.DTLVardef@5f223corg.highwire.dtl.DTLVardef@1c0aafaorg.highwire.dtl.DTLVardef@190502_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

A Cross-Species Systems Genetics Framework Identifies Causal Genes in Diabetic Nephropathy

Diabetic nephropathy (DN) is the leading cause of kidney failure in the developed world, but the genetic architecture of DN susceptibility is not well characterised. Here we apply a systems genetics approach in a mouse model of DN to discover novel QTLs for clinically relevant phenotypes including albuminuria, glomerulosclerosis, and macrophage infiltration. For context and prioritisation, we combined single-cell-transcriptomics-guided pQTL and eQTL mapping with cell-type-specific co-expression networks, identifying 192 candidate pGenes for albuminuria. While many were novel, 27% had prior genetic associations, and 40% were validated in a human diabetic cohort. Twelve genes belong to a podocyte network enriched for human GWAS signals. Among those, functional significance of the E3 ubiquitin ligases DCAF6 and ZNRF2 was confirmed by knockdown in Drosophila nephrocytes. Our systems genetics approach identified DN susceptibility genes previously validated in human GWAS while uncovering potential new genes and pathways that could be exploited for risk stratification and therapeutics development.

systems biology↗

bioRxiv2026

nanoASM: Long-Read Allele-Specific DNA Methylation Profiling Enables Functional Annotation of Regulatory Noncoding Variants in Human Prostate Tissues

Long-read nanopore sequencing enables simultaneous detection of germline variation and native DNA base modifications on individual DNA molecules, providing a unique opportunity to investigate allele-specific epigenetic regulation. Here, we performed whole-genome nanopore sequencing on normal and tumor prostate tissues to characterize differential methylation, methylation entropy, and allele-specific methylation (ASM) associated with noncoding genetic variants. Genome-wide analysis identified extensive cancer-associated differentially methylated regions (DMRs), with hypermethylated DMRs significantly enriched near transcription start sites and transcriptional regulatory regions. Integration with transcriptomic datasets revealed strong inverse relationships between promoter methylation and gene expression, while 5-hydroxymethylcytosine (5hmC) levels positively correlated with transcriptional activity across gene bodies. Using fragment-level methylation patterns enabled by long-read sequencing, we further quantified methylation entropy incorporating both 5mCG and 5hmCG states. Cancer-hypermethylated DMRs exhibited markedly reduced entropy, consistent with clonal fixation of methylation states during tumor progression. Entropy profiling across chromatin annotations demonstrated maximal epigenetic heterogeneity at partially modified enhancer-associated regions. To investigate cis-regulatory genetic effects, we developed a simple ASM framework (nanoASM) that can partition sequencing reads by allelic state and identifies allele-specific DMRs directly from long-read data. Compared with conventional population-level mQTL analysis, ASM demonstrated substantially improved statistical efficiency by leveraging within-individual contrasts and reducing sample-level heterogeneity. Although germline single nucleotide polymorphisms (SNPs) were largely shared between normal and tumor tissues, ASM patterns differed substantially, with tumor-associated ASM regions displaying significantly larger genomic span and stronger allelic methylation differences. Comparative analysis with TCGA prostate mQTL and GTEx prostate eQTL datasets demonstrated substantial concordance between ASM directionality and downstream transcriptional effects, particularly for variants located within DMRs and near transcription start sites. At the IRX4 prostate cancer risk locus, ASM identified an androgen-responsive regulatory domain overlapping AR ChIP-seq and H3K27ac peaks, nominating rs6885084 as a candidate functional variant. At the PSCA locus, ASM anchored by rs4736369 was associated with allele-specific methylation, chromatin activation, transcript abundance, and isoform usage. Together, these findings establish nanopore-based ASM analysis as a powerful approach for resolving functional noncoding variants and their regulatory domains they control in prostate cancer.

genetics↗

bioRxiv2026

A draft de novo assembly of Diadema antillarum, a keystone herbivore of the Caribbean reefs

We generated the first reference-level nuclear genome assembly of the keystone Caribbean long-spined black sea urchin species, Diadema antillarum (Philippi, 1845). Using whole-genome sequencing data from PacBio HiFi, Oxford Nanopore, and Illumina platforms, we employed multiple assembly strategies to generate a high-quality, near-complete genome. The final assembly spans 1.73 Gbp, consists of 2,964 scaffolds, and has an N50 of 1.56 Mbp. BUSCO analysis (metazoa_odb10) indicates 98.4% completeness. The genome displays a heterozygosity rate of 2.52% and contains 42.85% repetitive elements, of which 29.96% are unclassified. Coverage analysis reveals that while most of the genome was assembled at 11x depth, certain regions exhibit up to 530x coverage. Notably, regions exceeding 33x coverage account for 30.53% of the repetitive content, suggesting localized expansion of repeats. Duplication analysis of the assembled contigs shows that approximately 66% of contigs have duplicated, which supports segmental genome duplication in the past, and is further evidenced by the moderate level of heterozygosity of the assembly. While these characteristics contribute to the complexity of the genome, they do not diminish the quality of our assembly. Despite this complexity, our assembly maintains high completeness and contiguity. Our assembly provides a valuable resource for future genetic studies and serves as a critical framework for conservation, monitoring, and restoration of D. antillarum populations across the Caribbean.

genetics↗

bioRxiv2026

Comparison of Machine Learning Surrogate Models for Prediction of Single-Fiber Activation in Deep Brain Stimulation

Machine-learning surrogate models are positioned to help optimize deep brain stimulation (DBS) usage by predicting neural activation in response to electrical stimulation, while minimizing tradeoffs between computational expense and accuracy. Previous work has developed high accuracy artificial neural network (ANN) and convolutional neural network (CNN) surrogate models that predict activation of individual, myelinated axons, to extracellular electrical stimulation for subsets of DBS programming configurations. Moreover, more traditional machine learning methods including extreme gradient boosting (XGBoost) have been used effectively for peripheral-nerve single-fiber activation predictions. We build upon the previous work and compare ANN, CNN and XGBoost methods to a much expanded set of electrode programming configurations including: monopolar, bipolar, tripolar, quadrupolar, multiple monopolar, and multiple cases of directional leads. Training used datasets generated from a finite-element model of an implanted DBS lead together with multi-compartment cable models of synthetically generated axons. We evaluated the machine learning predictors using white matter pathways derived from group-averaged connectome data within a patient-specific tissue conductivity field, comparing both predicted stimulus activation thresholds and pathway recruitment across a clinically relevant range of stimulus amplitudes and pulse widths. Our ANN and CNN models successfully predicted neural fiber activation for almost all electrode configurations with low error, expanding the scope of our previous predictor model. Results also showed key limitations of XGBoost models and superior performance of CNNs for more complex electrostatic fields of the directional leads.

neuroscience↗

bioRxiv2026

Nmur1 and Cckar fail to support functional genetic access in adult dopamine neurons and challenge GPCR atlas assignments

Apuschkin et al. (2024) proposed a GPCR-based transcriptomic atlas for midbrain dopamine (DA) neuron subpopulations, including candidates such as Nmur1, Cckar, and Ffar4. To guide genetic targeting, these markers must reflect functional expression in adult DA neurons. Using in situ hybridization, Cre-dependent reporter lines, and both intracranial and systemic viral approaches, we find no evidence of adult Nmur1-mediated recombination in DA neurons, while Cckar-driven recombination is consistent with developmental expression only. Notably, Ffar4 expression overlaps extensively with Ntsr1 midbrain populations, indicating that it does not define a distinct DA neuron class. Furthermore, analysis of independent spatial transcriptomic datasets together with our MERFISH data shows that many proposed GPCR markers are not detectably expressed in adult DA neurons. These findings demonstrate that transcriptomic enrichment does not always yield reliable adult markers and highlight the need for functional validation prior to use in circuit targeting.

neuroscience↗

bioRxiv2026

Influenza-induced tuft cell expansion alters ILC-mediated inflammation

Tuft cells act as sentinels that amplify type 2 inflammation primarily by activating type 2 innate lymphoid cells (ILC2s). Although normally absent from the distal lung, ectopic tuft cells form after severe lung injury including influenza infection in mice. Here, we investigated the function of these ectopic tuft cells in shaping innate immunity following influenza injury. We observed that IFN{gamma} restrains tuft cell differentiation, whereas ILC2s drive tuft cell expansion, establishing a reciprocal regulatory axis. Tuft cell-deficient mice exhibited reduced eosinophilic inflammation and expansion of ILC1s and ILC3s after influenza injury resolution. Single-cell RNA-seq of influenza infected whole lung revealed transcriptional signatures consistent with type 1 pathway activation, type 2 suppression and oxidative stress. Following influenza injury and subsequent Alternaria alternata challenge, tuft cell-deficient mice also showed neutrophilic and ILC3 expansion. Together, these data identify a distal-airway tuft-cell-ILC2 circuit that helps maintain a balanced inflammatory environment in response to viral injury and aeroallergens.

molecular biology↗

bioRxiv2026

Energetic benefits of differential migration strategies shift under climate change for a migratory bird

Understanding how migratory birds balance energetic costs of movement with wintering benefits requires quantifying their energy expenditure across the full annual cycle. Here, we present a novel approach to reconstruct annual energy budget from multi-sensor geolocator data on atmospheric pressure and activity. We apply this method to tracking data of Eurasian Wrynecks from a European breeding population exhibiting striking variation in migration distance: short-distance migration to southern Europe, medium-distance to northern Africa, and long-distance to sub-Saharan Africa. Long-distance migrants had 21-26% lower annual energy expenditure than shorter-distance migrants, primarily due to reduced thermoregulation costs during boreal winter. However, they faced extreme physiological demands during migration, with daily energy expenditure exceeding 9.5 times basal metabolic rate. Since 1950, climate warming has progressively reduced winter thermoregulation demands disproportionately benefiting and potentially promoting shorter-distance strategies. These results reveal shifting energetic trade-offs under climate change, potentially driving evolution of migration patterns.

ecology↗

bioRxiv2026

Whole-body 3D kinematics of freely behaving Drosophila

Understanding how nervous systems generate coordinated movement requires precise measurement of body kinematics during natural behavior. The fruit fly, Drosophila, is a model organism with sophisticated behavior and well-studied neural circuits, but tracking fly movements in 3D remains challenging because of their teeny bodies, rapid movements, and frequent self-occlusions. Here we present a pipeline for markerless, full-body 3D pose estimation of fly terrestrial behavior, combining seven synchronized high-speed cameras to capture whole-body kinematics at 800 frames per second. We trained a hybrid 2D/3D deep learning model to track 50 keypoints, then refined them to produce anatomically feasible kinematic trajectories through a retargeting process that solved an inverse kinematics problem constrained by a biomechanical body model. Analysis of 3D kinematics revealed that flies perform grounded running across their full speed range, without transitioning between discrete gaits. Using multi-animal tracking, we found that courting males coordinate both wings during song and modulate body pitch to track the female's vertical position. Our open-source pipeline and large 3D kinematic dataset of fly behavior provide a foundation for neuromechanical modeling and mechanistic studies of motor control in a genetically tractable model organism.

neuroscience↗

bioRxiv2026

Dysplastic Epithelial Repair Propagates Chronic Pathology Through the Paracrine Transformation of Pulmonary Fibroblasts

Severe lung injury promotes the ectopic accumulation of basal cells in the alveoli and the presence of these dysplastic epithelial cells are strongly associated with regions of pulmonary fibrosis (PF) in diseased lungs. Recent studies have identified a unique subset of "inflammatory" fibroblasts expressing pro-inflammatory genes, especially cytokines involved in monocyte recruitment, that are also enriched in disease and thought to contribute to the onset and progression of PF. Here we show that these two injury-induced cell types are intricately connected, in that dysplastic basal cells generate diffusible signals to robustly induce the inflammatory phenotype in pulmonary fibroblasts. Capitalizing on transcriptomic analysis, we identify the enriched inflammatory signaling pathways in treated fibroblasts and specifically demonstrate that IL-1 secreted by dysplastic basal cells is responsible for this fibroblastic transformation. IL-1 neutralization in vivo is sufficient to significantly reduce the inflammatory fibroblast burden in regions of alveolar bronchiolization, and the resolution of inflammatory fibroblasts in turn reduces CCR2+ immune cell recruitment to these areas. These results suggest dysplastic basal cells play an indirect role in chronic inflammation and fibrotic remodeling through the induction of a proinflammatory fibroblast phenotype and subsequent recruitment of immune cells, establishing a chronic wound healing microenvironment that prolongs localized pathologic remodeling.

cell biology↗

bioRxiv2026

aaKomp: Alignment-free amino acid k-mer matching for genome completeness assessment at scale

In de novo sequencing projects, genome assembly optimization requires evaluating a number of candidate assemblies to identify optimal tool parameters. Yet, current completeness assessment tools like BUSCO and compleasm require 10-80 minutes per evaluation for gigabase-scale genomes, transforming what should be rapid iteration into time-intensive processes. These tools rely on alignment-based approaches and fixed ortholog databases, limiting their scalability across the tree of life. We present aaKomp, a scalable alignment-free tool that leverages amino acid k-mer matching and multi-index Bloom filters for rapid genome completeness assessment. Unlike current utilities, aaKomp supports user-defined reference databases, enabling customized assessments for any organism. In benchmarking against state-of-the-art tools using simulated T2T-CHM13 datasets, aaKomp achieved 68-fold faster execution and 15-fold lower memory consumption while maintaining accuracy. Testing on 94 Human Pangenome Reference Consortium assemblies and a European Eel assembly, aaKomp maintained one-minute runtimes (1.2 {+/-} 0.35 min) and low memory usage (<13.64 GB). aaKomps scoring system provides nuanced estimates rather than threshold-based classifications, offering increased resolution for tracking incremental improvements during iterative workflows. aaKomps speed, memory efficiency, and flexible database generation makes it well-suited for modern and biodiverse projects requiring the evaluation of hundreds of assemblies.

bioinformatics↗

bioRxiv2026

A Knock-in Ntsr1-Flp Driver Enables Intersectional and Systemic Targeting of Heterogeneous Midbrain Dopamine Circuits

Precise genetic access to molecularly defined neuronal subpopulations is essential for dissecting circuit heterogeneity. We developed and validated a knock-in neurotensin receptor 1 (Ntsr1)Flpmouse line for intersectional targeting of Ntsr1-expressing neurons. Following delivery of Flp-dependent adeno-associated viral (AAV) reporters, robust recombination was observed throughout the the midbrain and several other brain regions. A subset of Ntsr1+ neurons in the substantia nigra and ventral tegmental area lacked dopaminergic markers, indicating that midbrain Ntsr1 populations comprise both dopaminergic and non-dopaminergic neurons. Systemic delivery of a Cre and Flp-dependent reporter in complementary dual-recombinase configurations revealed configuration-dependent differences in dopaminergic targeting. Cis-gene controls (DatCre;DatFlp) defined the maximal dopaminergic targeting ceiling and helped distinguish true non-dopaminergic targeting from recombinase-dependent off-target labeling. Finally, a dual-recombinase-dependent taCaspase-3 construct enabled selective ablation of midbrain dopamine neurons in vivo, establishing Ntsr1Flp as a versatile driver for scalable Boolean targeting.

neuroscience↗

bioRxiv2026

Hormone signaling and immune programs define differential endocrine responsiveness in high-risk breast tissue

Hormone therapies are frequently used to reduce breast cancer risk in individuals at increased risk for primary or subsequent disease; however, tissue-level responses to these therapies are heterogeneous and incompletely understood. Background parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) provides a non-invasive radiologic readout of breast tissue features associated with endocrine responsiveness and cancer risk. Although BPE is associated with hormonal exposure, a subset of patients with BPE do not show a response to preventive endocrine therapy and therefore may remain at increased breast cancer risk. In this study, we integrated single-nucleus RNA sequencing and spatial transcriptomics to define the determinants of endocrine responsiveness in the setting of BPE. We identify hormone-driven epithelial cells with high levels of estrogen signaling and endocrine responsiveness, together with immune-associated epithelial programs characterized by diminished luminal identity and increased expression of immune-modulatory pathways, including major histocompatibility complex (MHC) class II and CD74. Functional organoid assays validate that these epithelial states exhibit differential sensitivity to tamoxifen and demonstrate that inflammatory signals can induce immune-modulatory epithelial programs. Together, our findings identify hormone signaling and immune programs as key determinants of endocrine responsiveness in breast tissue and provide a biological basis for interpreting radiologic markers relevant to cancer prevention.

cancer biology↗

bioRxiv2026

The capsule of hypervirulent Klebsiella pneumoniae maintains neutrophils in neutral activation state

Hypervirulent Klebsiella pneumoniae (hvKp) cause invasive infections despite robust neutrophil recruitment, yet the mechanisms enabling persistence in neutrophil-rich environments remain poorly defined. Here, we show that hvKp do not simply resist neutrophil antimicrobial mechanisms but instead constrain neutrophils into a neutral functional state characterised by limited bactericidal activity. Using genetic dissection of the rmpADC locus, pharmacological inhibition of neutrophil effector pathways, and analysis of a diverse panel of clinical isolates, we demonstrate that rmpADC-driven capsule properties uncouple neutrophil recognition and activation from bacterial killing. Deletion of rmpADC restores phagocytosis, degranulation, and intraphagosomal killing, whereas loss of individual rmpD or rmpC permits neutrophil activation without bacterial killing. Moreover, hypermucoviscosity alone is sufficient to protect bacteria from neutrophil-mediated killing across multiple genetic backgrounds. Together, these findings identify capsule-driven immune state control as a central mechanism of hvKp neutrophil evasion and reveal distinct thresholds governing neutrophil activation and bactericidal outcome.

immunology↗

bioRxiv2025

Colibactin produced by a honeybee symbiont defends against pathogens and shapes the gut community

Colibactin is a bacterial genotoxin that is linked to colorectal cancer and implicated in interbacterial competition; however, its role in natural communities remains unknown. Frischella perrara, a symbiont living only in honeybee guts, produces colibactin and causes DNA damage. Here, we found that F. perrara mono-colonization reduces bee lifespan but increases survivorship following challenge with an opportunistic pathogen. F. perrara reduces pathogen loads by causing colibactin-dependent DNA damage and prophage induction. clbS, a gene conferring protection from colibactin, is ubiquitous among bacteria restricted to bee guts but is absent from opportunistic colonizers including bee pathogens. Our findings provide evidence that colibactin functions in interbacterial competition, exerts selective pressure on community members, and confers protection against pathogens, while permitting co-evolved gut symbionts to persist.

microbiology↗

bioRxiv2025

A minor muscle stem cell population functions as metabolic Trojan horse fueling systemic aging by succinate induced epigenetic reprogramming

Inflammaging, the sustained chronic inflammation, is a hallmark of aging, yet its sustained activation mechanism remains elusive. Here, we identified muscle stem cells (MuSCs) as a driver of systemic inflammaging, evidenced by the multi-organ inflammation and aging phenotypes in MuSC specific Tet2 knockout mice. Tet2-Hdac11-Acod1-SDH axis maintained normal succinate level in MuSCs. Tet2 knockout disrupted this enzymatic cascade and led to succinate accumulation, fueling H4K31succ elevation to directly activate inflammatory gene transcription in MuSCs. The excess succinate was delivered to muscle fibers by sporadic fusion of Tet2 knockout MuSCs during muscle homeostasis, activated pro-inflammatory program, and transformed muscle to a persistent pro-inflammatory factor secretory organ, sustaining systemic inflammaging. Moreover, Tet2 was downregulated in aged MuSCs suggesting that this coupled metabolic-epigenetic mechanism was active in physiological aging. These findings reveal that a small subset of dysregulated MuSCs activate sustained whole-body inflammaging and multi-organ aging, providing new targets for rejuvenation strategy development.

cell biology↗