Biology subjects

Xu, K.

Publications and source records attributed to Xu, K..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Temporal-orbitofrontal pathway regulates choices across physical reward and visual novelty

Perceptually novel objects have profound impacts on our daily decisions. People often pay to try novel meals over familiar ones, or to see novel visual scenes at art exhibits and travel destinations. This suggests that perceptual novelty and the value of physical rewards, such as food, interact at the level of neural circuits to guide decisions, but where and how is unknown. We designed a behavioral task to study this novelty-reward interaction in animals and to uncover its neural underpinnings. Subjects chose among familiar offers associated with different expectations of novel objects and different expectations of juice rewards. Expectation of novel objects increased the preference for expected rewards. This novelty-reward interaction was reflected by neural activity in the anterior ventral temporal cortex (AVMTC) - a region previously implicated in the detection and prediction of novelty - and in the orbitofrontal cortex (OFC) - an area that receives prominent AVMTC inputs and is known for its capacity to signal subjective value of visual objects. Neural activity patterns suggested that AVMTC was upstream of OFC in the decision process. Chemogenetic disruption of the AVMTC[->]OFC circuit altered the impact of expected novelty on the valuation of physical reward. Hence, the ventral visual system impacts novelty-reward interactions during decisions through direct projections to OFC.

neuroscience↗

bioRxiv2025

Predicting 3D Chromatin Interactions Using Transformer-Enhanced Deep Learning Models

The three-dimensional (3D) structure of the human genome is essential for regulating gene expression and cellular functions. Chromatin interactions bring distant genomic regions into physical contact, enabling processes like gene regulation, DNA replication, and repair. Disruptions in this organization can lead to diseases such as cancer and genetic disorders. In this study, we propose a Transformer-based deep learning model to predict the chromatin interactions from DNA sequences. By developing a streamlined and efficient data pipeline to handle the sparse and noisy high-throughput chromosome conformation capture (Hi-C) sequencing data, our approach improves both data processing speed and model performance. The Transformers ability to capture long-range interactions among genomic regions via attention mechanism, combined with nucleotide position encoding, enables more accurate predictions than purely convolution-based models. This work highlights the potential of Transformer-based network architectures to advance our understanding of genome organization and paves the way for future research with large datasets and advanced network designs.

bioinformatics↗

bioRxiv2025

SpeedyTrack: Direct microsecond wide-field single-molecule tracking and super-resolution mapping via CCD vertical shift

We introduce spatially-encoded dynamics tracking (SpeedyTrack), a strategy to enable direct microsecond wide-field single-molecule tracking/imaging on common microscopy setups. Capitalizing on the native sub-microsecond vertical charge shifting capability of popular electron-multiplying charge-coupled devices (EM-CCDs), SpeedyTrack staggers wide-field single-molecule images along the CCD chip at [~]10-row spacings between consecutive timepoints, effectively projecting the time domain to the spatial domain. Wide-field tracking is thus achieved for freely diffusing molecules at down to 50 {micro}s temporal resolutions for >30 timepoints, permitting trajectory analysis to quantify diffusion coefficients up to 1,000 {micro}m2/s. Concurrent acquisition of single-molecule diffusion trajectories and Forster resonance energy transfer (FRET) time traces further elucidates conformational dynamics and binding states for diffusing molecules. Moreover, with a temporally patterned vertical shifting scheme, we deconvolve the spatial and temporal information to map long, fast single-molecule trajectories at the super-resolution level, thus resolving the diffusion mode of a fluorescent protein in live cells with nanoscale resolution. While these demonstrated capabilities substantially outperform existing approaches, SpeedyTrack further stands out for its simplicity by directly working off the built-in functionalities of EM-CCDs without the need to modify existing optics or electronics. We thus provide a facile solution to the microsecond tracking/imaging of single molecules and their super-resolution mapping in the wide field.

biophysics↗

bioRxiv2025

Identification of Novel Mutations Causing Clofazimine Resistance in Mycobacterium intracellulare

Clofazimine (CFZ) is a promising repurposed drug for treating Mycobacterium avium-intracellulare complex pulmonary disease (MAC-PD), but its resistance mechanisms in M. intracellulare remain poorly understood. In this study, we generated 36 CFZ-resistant M. intracellulare mutants in vitro and identified various mutations in the marR gene (WP_009952290.1) in 61% of resistant mutants through whole-genome sequencing. Mutations were identified in additional genes encoding flavin-dependent oxidoreductase (ssuD, C67A), membrane lipoprotein (lppI, C207 deletion), glucose-methanol-choline oxidoreductase (G157 deletion), MASE1 domain-containing protein (C62G), and PPE family protein (222C deletion). Gene complementation experiments demonstrated that introducing the wild-type marR in CFZ-resistant strains (L72 and L74) with marR mutations reduced CFZ minimum inhibitory concentrations (MICs) from 1 g/mL to the susceptible baseline (0.25 g/mL), confirming its critical role in CFZ resistance. Notably, the M. intracellulare MarR lacks homology to M. tuberculosis MarR family protein Rv0678 (MmpR) whose mutations are involved in CFZ and bedaquiline (BDQ) resistance and is flanked by non-efflux pump genes (dhmA and doxX), and unlike M. tuberculosis, its mutation does not cause bedaquiline cross-resistance, indicating a different MarR and distinct regulatory mechanism for CFZ resistance in M. intracellulare. This work highlights marR as a key determinant of CFZ resistance in M. intracellulare and underscores the need for further mechanistic studies with implications for clinical diagnostics and therapeutic strategies.

microbiology↗

bioRxiv2025

Super-Resolution Diffusivity Mapping Reveals Spatial Correlations Between Lateral Mobility and Structural Heterogeneities on Cellular Membranes

Cellular membranes orchestrate critical processes such as molecular transport and signal transduction, both regulated by the lateral mobility of lipids and proteins. However, resolving nanoscale diffusional heterogeneities and elucidating their underlying mechanisms remains a formidable challenge due to the membranes intricate architecture and compositional diversity. Here, we present point-cloud single-molecule diffusivity mapping (pc-SMdM), a cutting-edge super-resolution technique that offers a point-cloud data format with enhanced spatial resolution for diffusivity mapping. Using pc-SMdM, we visualize nanoscale diffusion slowdown clusters with [~]50 nm in diameter on plasma membranes. These clusters are predominantly governed by cholesterol content, alongside contributions from membrane protein assemblies and topographical features. Leveraging two-color pc-SMdM, we concurrently imaged multiple lipids and membrane probes, revealing distinct "fingerprint" diffusivity maps shaped by their interactions within lipid bilayers. Our findings position pc-SMdM as a transformative tool for spatially resolving molecular interactions and membrane dynamics in live cells, offering new insights into the underlying mechanisms that govern membrane mobility at the nanoscale.

biophysics↗

bioRxiv2025

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

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

cell biology↗

bioRxiv2025

Establishing an ex vivo porcine skin model to investigate the effects of broad spectrum antiseptic on viable skin microbial communities

Incomplete antiseptic efficacy against potentially pathogenic microbial taxa places some patients at disproportionate risk for developing a surgical site infection. Laboratory models capable of interrogating the effects of antiseptics on the skin and its complex microbial communities are desperately needed to improve and better tailor antiseptic formulations. This work aims to establish an ex vivo porcine skin model to explore the impact of topical antiseptics on complex skin microbial communities and superficial skin lipids. Microbiome samples were treated with propidium-monoazide to selectively evaluate DNA from viable microorganisms. Bacterial abundances were assessed via viability-qPCR and quantitative culture. Viable community populations were evaluated with 16S rRNA gene sequencing. Epidermal biopsies were collected at multiple timepoints for lipidomic assessment via LC/MS. The ex vivo environment promoted shifts in porcine skin lipid composition and microbial communities over the experiments duration. Compared to water treated control skin, skin treated with the antiseptic chlorhexidine gluconate had significantly lower culturable and bioburden determined by viability-qPCR. Compared to water treated skin, viable microbial communities on CHG treated skin displayed greater relative abundance of several gut associated and Gram-negative bacterial taxa, including SMB53, Turicibacter, Pseudomonas and Proteus. Collectively these findings highlight the utility of an ex vivo porcine skin system for interrogating the impacts of antimicrobial disruption to complex microbial ecosystems, and ultimately for the future testing and development of improved antiseptic formulations.

microbiology↗

bioRxiv2025

Validation of bronchial airway gene expression associated with bronchiectasis in nasal epithelium

ObjectivesExamination of bronchial epithelium-derived gene expression signature of bronchiectasis (BE) in nasal epithelium. MethodsWe studied 220 participants from the Detection of Early Lung Cancer Among Military Personnel study with bulk RNA-seq of nasal epithelium brushings. Gene set enrichment analysis (GSEA) was used to examine whether genes previously identified as increased or decreased in the bronchial epithelium of individuals with radiologic BE are significantly enriched among the genes most significantly altered in the nasal epithelium. GSEA and cell-type specific gene expression signatures were used to examine changes in the cellular composition of nasal epithelium associated with radiologic BE. ResultsGenes previously found to have significantly altered expression in bronchial epithelium in radiologic BE are concordantly enriched among the genes most increased or decreased in nasal epithelium in radiologic BE in this validation set (p = 3x10-7, increased; p = 6x10-8, decreased). GSEA performed using cell-type signatures demonstrates that in nasal epithelium, BE is associated with increased multiciliated and deuterosomal cell-related gene expression and decreased expression of basal cell- related gene expression, consistent with our previous findings in bronchial epithelium. ConclusionOur work validates our bronchial signature of BE in an independent dataset and demonstrates that similar gene expression changes are associated with radiologic BE in the bronchial and nasal epithelium. These findings support considering nasal epithelium brushing as a less invasive tool for screening and monitoring BE. SummaryThis study validates a previously reported bronchial signature of bronchiectasis (BE) in nasal epithelium. Changes in gene expression and cell-type composition associated with radiologic BE are similar across both bronchial and nasal epithelium.

bioinformatics↗

bioRxiv2025

Intraductal Papillary Mucinous Neoplasm Cellular Plasticity linked with Repeat Element Dysregulation

BackgroundIntraductal papillary mucinous neoplasms (IPMNs) are preinvasive pancreatic lesions with a spectrum of histologic phenotypes and variable risk in progressing to invasive cancer. Aberrant repetitive element expression has been shown to be functionally linked to cell state changes in pancreatic cancer. ObjectiveThis study utilized spatial transcriptomics with customized repeat element probes to better understand the relationship of histologic subtypes, repeat element dysregulation, and molecular profiles of different cell populations in IPMN. DesignA total of 52 lesions from 18 patients with resected IPMNs of different histologies and degrees of dysplasia were analyzed with whole transcriptome spatial analysis (GeoMx). Of these, 50 lesions from 17 patients were also processed for single-cell spatial molecular imaging (CosMx). Repeat element probes for LINE1, HSATII, HERVK, and HERVH were used for GeoMx and CosMx. ResultsPancreaticobiliary-type IPMN was enriched for basal-like epithelium and infiltration of Treg cells. Intestinal-type IPMN was enriched for classical epithelium and macrophage infiltrates. Gastric-type IPMN was found to have equal basal-like and classical epithelium with a diverse immune infiltrate. Repeat RNAs were expressed at high levels across IPMN phenotypes and enriched in high-grade dysplasia. Single-cell transcriptional trajectory analysis revealed a phylogeny starting from gastric toward intestinal and pancreaticobiliary branches associated with higher-grade dysplasia and repeat RNA expression. ConclusionSpatial transcriptomics of IPMN identified a molecular continuum between histological subtypes supporting a common gastric-type origin that transitions to intestinal and pancreatobiliary phenotypes. This cell state plasticity is linked with repeat element expression that can be a potential biomarker for IPMN progression. What is already known on this topicO_LIMolecular characterization of IPMN subtypes using regional spatial transcriptomics has described the differences between histologies C_LIO_LIRepeat element expression is associated with cell state changes in pancreatic ductal neoplasm C_LI What this study addsO_LISingle cell spatial molecular imaging of IPMN subtypes reveals a cellular and molecular continuum starting from gastric histology with distinct branches to Intestinal and pancreatobiliary subtypes C_LIO_LIRepeat element expression is associated with higher grade IPMN histology C_LIO_LIRepeat element expression is elevated in the histologic and molecular continuum from gastric to intestinal and pancreatobiliary-type IPMN C_LI How this study might affect research, practice, or policyO_LIThese results support a common gastric histology origin of IPMN subtypes with different molecular trajectories towards higher grade disease C_LIO_LIOur findings suggest that repeat RNA expression can be used in conjunction with other transcriptional markers of cell state as a biomarker for IPMN progression C_LI

cancer biology↗

bioRxiv2025

A comprehensive benchmark and guide for sequence-function interpretable deep learning models in genomics

The development of sequence-based deep learning methods has greatly increased our understanding of how sequence determines function. In parallel, numerous interpretable algorithms have been developed to address complex tasks, such as elucidating sequence regulatory syntax and analyzing non-coding variants from trained models. However, few studies have systematically compared and evaluated the performance and interpretability of these algorithms. Here, we introduce a comprehensive benchmark framework for evaluating sequence-to-function models. We systematically evaluated multiple models and DNA language foundation models using 369 ATAC-seq datasets, employing diverse training strategies and evaluation metrics to uncover their critical strengths and limitations. Our benchmark study highlights that different model architectures and interpretability methods are better suited to specific scenarios. Negative samples derived from naturally inactive regions outperform synthetic sequences, whereas single-cell tasks require specialized models. Additionally, we demonstrate that interpretable sequence-function models can complement traditional sequence alignment methods in studying cross-species enhancer regulatory logic. We also provide a pipeline to help researchers select the optimal sequence-function prediction and interpretability algorithms.

bioinformatics↗

bioRxiv2024

Causal considerations can determine the utility of machine learning assisted GWAS

Machine Learning (ML) is increasingly employed to generate phenotypes for genetic discovery, either by imputing existing phenotypes into larger cohorts or by creating novel phenotypes. While these ML-derived phenotypes can significantly increase sample size, and thereby empower genetic discovery, they can also inflate the false discovery rate (FDR). Recent research has focused on developing estimators that leverage both true and machine-learned phenotypes to properly control the type-I error. Our work complements these efforts by exploring how the true positive rate (TPR) and FDR depend on the causal relationships among the inputs to the ML model, the true phenotypes, and the environment. Using a simulation-based framework, we study architectures in which the machine-learned proxy phenotype is derived from biomarkers (i.e. inputs) either causally upstream or downstream of the target phenotype. We show that no inflation of the false discovery rate occurs when the proxy phenotype is generated from upstream biomarkers, but that false discoveries can occur when the proxy phenotype is generated from downstream biomarkers. Next, we show that power to detect variants truly associated with the target phenotype depends on its heritability and correlation with the proxy phenotype. However, the source of the correlation is key to evaluating a proxy phenotype's utility for genetic discovery. We demonstrate that evaluating machine-learned proxy phenotypes using out-of-sample predictive performance (e.g. phenotypic correlation) provides a poor lens on utility. This is because overall predictive performance does not differentiate between genetic and environmental correlation. In addition to parsing these properties of machine-learned phenotypes via simulations, we further illustrate them using real-world data from the UK Biobank.

genetics↗

bioRxiv2024

When does sexual selection through mate choice deplete versus exaggerate genetic variation: is there a lek paradox?

The evolution of female preferences for male display traits relies on females receiving indirect benefits from their mate. This requires substantial genetic variation in display traits or male quality. Nevertheless, sexual selection through mate choice has been assumed to deplete this genetic variation, ultimately diminishing strong preferences. However, sexual traits often have higher genetic variation than non-sexual traits. This contradiction, and, relatedly, how costly preferences and display traits are maintained, is called the "lek paradox". Using infinitesimal models, we show that sexual selection through mate choice allows variation in male display traits and female preferences to mutually exaggerate each other, in a process analogous to runaway sexual selection but in terms of genetic variation. Therefore, contrary to prior suppositions, sexual selection may increase equilibrium genetic variance in display traits and preferences over that under random mating, provided that the variance of female preferences relative to male traits during mate choice is not too small and preferences are not too weak. Notably, even if equilibrium preference variation is substantially smaller than trait variation, trait variation can still increase over that under random mating, provided selection on the trait compared to the preference is sufficiently strong. Furthermore, when trait variation does decrease, this reduction is generally slight. It is under situations such as lekking, where females can simultaneously choose from many males so that mate discrimination is effectively strong and fitness costs of choice weak, that sexual selection through mate choice may be most powerful in exaggerating genetic variance in male displays. Significance statementThe "lek paradox"--the dissonance between a hypothesized loss of variation in sexual display traits due to mate choice, leading to the subsequent cessation of sexual selection, and evidence of high variation in such traits in nature, accompanied by the long-term persistence of sexual selection--is an enduring mystery of the sexual selection literature. We clarify and quantify multiple pathways by which sexual selection via mate preferences alters genetic variance in both display traits and female preferences. Using mathematical models, we show the lek paradox is built upon a false premise. We find a wide range of conditions under which sexual selection increases or minimally reduces variation in display traits, allowing the maintenance of substantial variance in traits and preferences.

evolutionary biology↗

bioRxiv2024

Engineering kidney developmental trajectory using culture boundary conditions

Kidney explant cultures are traditionally carried out at air-liquid interfaces, which disrupts 3D tissue structure and limits interpretation of developmental data. To overcome this limitation, we developed a 3D culture technique using hydrogel embedding to capture morphogenesis in real time. We show that 3D culture better approximates in vivo-like niche spacing and dynamic tubule tip rearrangement, as well as in vivo-like presentation of branching defects under perturbations to glial cell-derived neurotrophic factor (GDNF)-REarranged during Transfection (RET) tyrosine kinase signaling. We find that the concentration of the embedding matrix influences the number of nephrons per ureteric bud (UB) tip and the spacing between tips. To isolate the effect of specific material properties on explant development, we introduce engineered acrylated hyaluronic acid hydrogels that allow independent tuning of stiffness and adhesion. We find that sufficient stiffness and adhesion are both required to maintain kidney shape. Matrix stiffness has a "Goldilocks effect" on the nephron per UB tip balance centered at [~]2 kPa, while higher matrix adhesion increases nephron per UB tip ratio. Our technique captures large-scale, in vivo-like tissue morphogenesis in 3D, providing a platform suited to contrasting normal and congenital disease contexts. Moreover, understanding the impact of boundary condition mechanics on kidney development benefits fundamental renal research and advances the engineering of next-generation kidney replacement tissues.

developmental biology↗

bioRxiv2024

The high quality Chinese white truffle genome and novel fossil-calibrated estimate of Pezizomycetes divergence reveal the tempo and mode of true truffles genome evolution

The genus Tuber (family: Tuberaceae) includes the most economically valuable ectomycorrhizal (ECM), truffle-forming fungi. Previous genomic analyses revealed that massive transposable element (TE) proliferation represents a convergent genomic feature of mycorrhizal fungi, including Tuberaceae. Repetitive sequences are one of the major drivers of genome evolution shaping its architecture and regulatory networks. In this context, Tuberaceae represent an important model system to study their genomic impact; however, the family lacks high-quality assemblies. Here, we tested the interplay between TEs and Tuberaceae genome evolution by producing a highly contiguous assembly for the endangered Chinese truffle Tuber panzhihuanense, along with a novel timeline for Tuberaceae diversification and comprehensive comparative genomic analyses. We found that concurrently with a Paleogene diversification of the family, pre-existing Chromoviridae-related Gypsy clades independently expand in different truffle lineages leading to increased genome size and high gene family turnover rates, but without resulting in highly scrambled genomes. Additionally, we found an enrichment of ECM-induced gene families among ancestral duplication events. Finally, we explored the repetitive structure of nuclear ribosomal DNA (rDNA) loci for the first time in the clade. We found that most of the 45S rDNA paralogues are undergoing concerted evolution, though an isolated divergent locus raises concerns about potential issues for metabarcoding and biodiversity assessments. Our study provides a fundamental genomic resource for future research on truffle genomics and showcases a clear example on how establishment and self-perpetuating expansion of heterochromatin can drive massive genome size variation due to activity of selfish genetic elements.

evolutionary biology↗

bioRxiv2024

Hepatic HKDC1 Deletion Alleviates Western Diet-Induced MASH in Mice

The global prevalence of Metabolic dysfunction-associated steatohepatitis (MASH) has been rising sharply, closely mirroring the increasing rates of obesity and metabolic syndrome. MASH exhibits a strong sexual dimorphism where females are affected with more severe forms after menopause. Hexokinase domain-containing protein 1 (HKDC1) has recently been recognized for its role in liver diseases, where its expression is minimal under normal conditions but significantly increases in response to metabolic stressors like obesity and liver injury. This selective upregulation suggests HKDC1s potential specialization in hepatic glucose and lipid dysregulation, linking it closely to the progression of MASLD and MASH. This study aims to clarify the role of HKDC1 in Western diet-induced MASH in female mice by examining its impact on hepatic glucose and lipid metabolism, offering insights into its potential as a therapeutic target and addressing the need for sex-specific research in liver disease. This study reveals that HKDC1 expression is elevated in obese women with MASH and correlates with liver pathology. In a mouse model, liver-specific HKDC1 knockout (HKDC1LKO) protected against Western diet-induced obesity, glucose intolerance, and MASH features, including steatosis, inflammation, and fibrosis. Transcriptomic analysis showed that HKDC1 deletion reduced pro-inflammatory and pro-fibrotic gene expression, while gut microbiome analysis indicated a shift toward MASH-protective bacteria. These findings suggest that HKDC1 may exacerbate MASH progression through its role in metabolic and inflammatory pathways, making it a potential therapeutic target.

biochemistry↗

bioRxiv2024

Decreased SNCA Expression in Whole-Blood RNA Analysis of Parkinson's Disease Adjusting for Lymphocytes

Blood-based RNA transcriptomics offers a promising avenue for identifying biomarkers of Parkinsons Disease (PD) progression and may provide mechanistic insights into the systemic biological processes underlying its pathogenesis beyond the well-defined neurodegenerative features. Previous studies have indicated an age-dependent increase in neutrophil-enriched gene expression, alongside a reduction in lymphocyte counts, in individuals with PD. These immune cell changes can obscure disease-relevant transcriptomic signals. In this study, we performed differential expression (DE) analysis of whole-blood RNA sequencing data from PD cohorts, incorporating a correction for immune cell-enriched gene expression, particularly neutrophil-related pathways, to improve the resolution of PD-associated molecular changes. Using 1,254 Parkinsons Progression Markers Initiative (PPMI) samples with complete blood count (CBC) data, we developed a predictive model to estimate neutrophil percentages in a 6,987 PPMI and Parkinsons Disease Biomarkers Program (PDBP) samples. We mitigated the confounding effects of immune cell-enriched gene expression by integrating predicted neutrophil percentages as a covariate in DE analysis. This approach revealed a consistent and significant downregulation of SNCA across all PD cohorts, a finding previously obscured by immune cell signatures. Lowered SNCA expression was found in individuals with known predisposition genes (e.g., SNCA, GBA, LRRK2) and in non-genetic PD cohorts lacking known pathogenic mutations, suggesting it may represent a key transcriptomic hallmark of the disease.

bioinformatics↗

bioRxiv2024

When sexual selection meets genetic drift: the coevolution of male traits and female preferences in finite populations

Fishers mechanism is central to sexual selection theories, where mate choice generates a genetic correlation between male trait and female preference alleles, driving the coevolution of the trait and preference with positive feedback. However, how Fishers mechanism operates in finite populations remains unclear, as sexual selection can interact with genetic drift, influencing both trait-preference correlation and allele frequencies. By using population genetic models, this study addresses the gap in our understanding of interactions between fundamental evolutionary forces. We show that more frequent recombination increases trait-preference correlations in infinitely large populations, unless a positive correlation initially exists. In finite populations, interactions between sexual selection and drift elevate trait-preference correlation when the male trait is rare but reduce the correlation when the trait is common, potentially making it negative when recombination is rare or population size is small. Also, these interactions tend to slow the spread of the male trait while promoting the evolution of preferences. These results differ from the Hill-Robertson effect under natural selection due to two key factors: mate choice generates positive linkage disequilibrium, and the strength of indirect selection on preferences increases with linkage disequilibrium. The fixation of trait and preference alleles is positively correlated. This correlation peaks at intermediate recombination rates and is often stronger in small populations than in large ones, so large population sizes tend to reduce the likelihood that both trait and preference alleles fix. We discuss how the results provide insights into the progression of sexual selection in nature.

evolutionary biology↗

bioRxiv2024

Immune Evasion, Cell-Cell Fusion, and Spike Stability of the SARS-CoV-2 XEC Variant: Role of Glycosylation Mutations at the N-terminal Domain

SARS-CoV-2 continues to evolve, producing new variants that drive global COVID-19 surges. XEC, a recombinant of KS.1.1 and KP.3.3, contains T22N and F59S mutations in the spike proteins N-terminal domain (NTD). The T22N mutation, similar to the DelS31 mutation in KP.3.1.1, introduces a potential N-linked glycosylation site in XEC. In this study, we examined the neutralizing antibody (nAb) response and mutation effects in sera from bivalent-vaccinated healthcare workers, BA.2.86/JN.1 wave-infected patients, and XBB.1.5 monovalent-vaccinated hamsters, assessing responses to XEC alongside D614G, JN.1, KP.3, and KP.3.1.1. XEC demonstrated significantly reduced neutralization titers across all cohorts, largely due to the F59S mutation. Notably, removal of glycosylation sites in XEC and KP.3.1.1 substantially restored nAb titers. Antigenic cartography analysis revealed XEC to be more antigenically distinct from its common ancestral BA.2.86/JN.1 compared to KP.3.1.1, with the F59S mutation as a determining factor. Similar to KP.3.1.1, XEC showed reduced cell-cell fusion relative to its parental KP.3, a change attributed to the T22N glycosylation. We also observed reduced S1 shedding for XEC and KP.3.1.1, which was reversed by ablation of T22N and DelS31 glycosylation mutations, respectively. Molecular modeling suggests that T22N and F59S mutations of XEC alters hydrophobic interactions with adjacent spike protein residues, impacting both conformational stability and neutralization. Overall, our findings underscore the pivotal role of NTD mutations in shaping SARS-CoV-2 spike biology and immune escape mechanisms.

molecular biology↗