Biology subjects

Wang, X.

Publications and source records attributed to Wang, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Bacterial-derived cyclic lipopeptides suppress dauer arrest in C. elegans

Secondary bacterial metabolites can regulate animal physiology, but the specific bacterial genes and molecules responsible for regulating, synthesizing, and transporting these molecules and the mechanisms by which they impact animal physiology often remain unclear. Here, we used Caenorhabditis elegans dauer formation as a gross morphological readout to identify bacterial mechanisms that promote development when animal TGF-{beta} or insulin signaling is impaired. We found that the native C. elegans microbiome constituent, Pseudomonas lurida, suppresses dauer arrest and that this activity requires the two-component system, GacS/GacA, and the downstream massABC[KD2.1][KN2.2][XW2.3] nonribosomal peptide synthetase cluster. Using sequential chromatography followed by mass spectrometry and NMR, we identified Massetolide F, a bacterial cyclic lipopeptide biosurfactant, as a massABC-dependent product. In addition, we found that purified Massetolide F was sufficient to restore dauer suppression to P. lurida {triangleup}massBC. We also found that surfactin[AT3.1][KN3.2][XW3.3] C, a cyclic lipopeptide from B. subtilis, similarly suppressed dauer formation whereas the cyclic lipopeptide antibiotic daptomycin did not, indicating that dauer suppression is shared by a subset of cyclic lipopeptides rather than being a general property of the class. Lastly, we found that massABC-dependent Massetolide F production induces the expression of the acid sphingomyelinase asm-3 in C. elegans, that asm-3 is required for Massetolide F induced dauer suppression, and that loss of Massetolide F production also leads to reduced bacterial clearance in host animals. Together, these findings identify Massetolide F as a microbiome-derived molecule that promotes animal development and reveal an unexpected function for bacterial biosurfactants in regulating animal physiology.

microbiology↗

bioRxiv2026

High-throughput physics-based enzyme engineering

Enzyme engineering aims to tailor natural enzymes for industrial and therapeutic applications, yet physically grounded rational design has been limited by a trade-off between accuracy and cost, leaving the field heavily dependent on expert intuition. Here we present a scalable physics-based framework that combines field-aware machine learning with molecular mechanics to capture enzyme electrostatics at quantum-mechanical accuracy while enabling efficient, atomistic exploration of reaction free-energy landscapes. Coupled with microkinetic modelling, the framework translates molecular free-energy landscapes into catalytic rates and selectivity across competing, multistep reaction pathways. Applied to a newly engineered oxidative amidase (OxiAm), the framework predicts catalytic rate constants with near-experimental accuracy, quantitatively resolves the selectivity between hydrolysis and aminolysis, and generalizes across substrates, mutations and enzyme homologues. Transition-state ensemble analysis further reveals the reaction mechanism and guides the design of enzyme variants for pharmaceutical synthesis. By bringing chemical accuracy and high-throughput sampling to enzyme catalysis, this approach shifts rational design from static, empirical practice toward dynamic, free-energy-driven design, and should accelerate the engineering of biocatalysts.

biophysics↗

bioRxiv2026

Parallel Arg/N-degron recognition systems regulate coenzyme A biosynthesis

Coenzyme A (CoA) is an essential metabolic cofactor whose biosynthesis is controlled by pantothenate kinases (PANKs), the rate-limiting enzymes in CoA synthesis. Although CoA production is extensively regulated, whether PANK abundance is controlled by selective protein degradation remains unknown. Here, we identify PANK1{beta} and PANK3 as substrates of the Arg/N-degron pathway. Two mechanistically distinct E3 ligase systems, UBR4-KCMF1 and MKLN1-CTLH, independently converge on a common N-terminal MK Arg/N-degron to promote PANK degradation and restrict CoA biosynthesis. UBR4-KCMF1 recognizes the MK Arg/N-degron through KCMF1 ZZ domain, whereas CTLH complex employs the B30.2-domain proteins RanBP9 and RanBP10 as previously unrecognized Arg/N-degron recognins. Structural, biochemical, and cellular analyses demonstrate that RanBP9 and RanBP10 recognize both Met-X and canonical Arg/N-degrons through their B30.2 domains, using a mechanism distinct from canonical UBR proteins. Together, these findings establish a new branch of the mammalian Arg/N-degron pathway and reveal ubiquitin-dependent control of PANK abundance in CoA homeostasis.

molecular biology↗

bioRxiv2026

Programmable DNA Assemblies Reconstitute Supramolecular Protein Function

Biological processes are often regulated through reactions involving supramolecular protein complexes organized with nanoscale precision, such as the apoptosome that activates procaspase-9 through defined stoichiometry to induce apoptosis. Here we report designer CASCAD (CARD Assembly on SCAffold DNA), a self-assembled DNA nanoplatform that spatially organizes caspase recruitment domains (CARDs), exhibiting catalytic intracellular caspase-9 activation. By functioning like a natural apoptosome, CASCAD enhances caspase-9 oligomerization and promotes valency-dependent enzymatic activation. Further, after incorporating targeting aptamers and membrane-interacting peptides for cellular uptake and cytosolic delivery, CASCAD has successfully reconstituted apoptosome function and downstream apoptotic signaling in in-vitro 2D and 3D cultures. Our molecular design paradigm establishes CASCAD as versatile and programmable DNA nanomaterial for reconstructing signaling pathways driven by diverse supramolecular complexes, including inflammasomes and myddosomes, providing a general chemical framework for engineering cellular signaling and directing cellular function and fate.

synthetic biology↗

bioRxiv2026

Test-Retest Reproducibility of Single- and Cross-Population White Matter Atlases in Diffusion MRI Tractography

Diffusion MRI tractography enables noninvasive mapping of white matter fiber tracts. Atlas-based white matter parcellation supports automated tract identification by assigning individual streamlines to atlas-defined clusters and anatomical tract labels. Because clustering-based white matter atlases are constructed from cohort-specific tractography data, they capture common white matter organization represented in the atlas-construction population. Although major white matter anatomy is shared across populations, subtle population-related anatomical variability may influence atlas representation and test-retest correspondence. Therefore, the reproducibility and cross-population generalizability of tractography-based white matter atlases are important considerations for quantitative neuroimaging studies. In this study, we evaluated whether incorporating cross-population anatomical variability during atlas construction improves test-retest reproducibility. To do so, we compared a single-population ORG atlas constructed from a Western cohort with the cross-population East-West White Matter Atlas constructed from both Eastern and Western cohorts. Test-retest diffusion MRI scans from the Human Connectome Project Young Adult (HCP-YA) dataset and the Connectivity-based Brain Imaging Research Database (C-BIRD) were analyzed as independent Western and Eastern test-retest cohorts, respectively. Whole-brain tractography was reconstructed for each dMRI scan and parcellated using both atlases. Reproducibility was assessed using tract detection rate at both cluster level and anatomical tract level, weighted Dice coefficient, and the relative difference of mean fractional anisotropy (FA). Both atlases showed stable tract detection across test-retest scans in both cohorts. Compared with the ORG atlas, the East-West White Matter Atlas achieved higher overall spatial overlap and lower test-retest variability in mean FA, although atlas performance varied across individual tracts. These findings suggest that integrating cross-population information during atlas construction improves the reproducibility and generalizability of white matter atlas mapping across independent populations and imaging protocols.

neuroscience↗

bioRxiv2026

Isoleucine and asparagine influence the growth of staphylococcal strains in atopic dermatitis

Atopic dermatitis (AD) is a multifactorial, chronic skin disease associated with microbial factors. It is known that staphylococcal skin microbes play a role in the pathophysiology of AD, notably S. aureus. However, how staphylococcal strain variation affects disease aetiology and progression remains unclear. Using a culture-dependent approach, we analyzed the genomic and phenotypic profile of staphylococcal strains isolated from a Hong Kong children cohort (n = 70). Presence of S. aureus was positively associated with AD skin, whilst S. epidermidis and S. hominis were positively associated with healthy skin, but no overall strain type was associated with AD. In vitro experimentation revealed that there is demarcation in S. aureus strain growth, biofilm biomass formation, and metabolite production by disease severity. While isoleucine and asparagine promoted S. aureus growth, these amino acids suppressed S. hominis growth. These collective findings highlight the importance of strain-level and metabolic interactions of staphylococci in AD pathophysiology.

microbiology↗

bioRxiv2026

Host soluble inositol phosphate signaling promotes coronavirus replication

Coronaviruses rely extensively on host pathways for replication, making host-directed therapies an attractive strategy for broad-spectrum antivirals with reduced risk of viral resistance. Here we identify the host soluble inositol phosphate pathway as a previously unrecognized dependency for coronavirus infection. Genetic or pharmacologic inhibition of several kinases in this pathway markedly suppresses replication of both alpha- and betacoronaviruses, while increasing pathway activity promotes viral replication. We developed UNC7844, a potent multi-target inhibitor of these kinases, which reduces coronavirus replication by more than four orders of magnitude in cultured cells and suppresses coronavirus infection in mice. Mechanistically, UNC7844 suppresses inositol (pyro)phosphates production, disrupts phosphoinositide homeostasis, and impairs late endosomal dynamics, blocking early post-entry steps required for viral genome release and replication. Together, our findings establish the soluble inositol (pyro)phosphate pathway as an important regulator of coronavirus infection and highlight its inhibition as a promising host-directed antiviral strategy.

microbiology↗

bioRxiv2026

Rtel1 in hypothalamic oxytocin neurons regulates oxytocin output and social behaviors in mice

RTEL1, a DNA helicase that resolves G-quadruplexes to maintain telomere and genome stability, has emerged as a candidate autism spectrum disorder risk gene, but its neural functions remain unknown. Here, we show that Rtel1 haploinsufficiency in mice impairs social novelty and increases marble burying and anxiety-related behaviors without affecting locomotion or spatial learning. RTEL1 is expressed in oxytocin (OXT) neurons of the hypothalamic paraventricular nucleus, where Rtel1 haploinsufficiency reduces OXT abundance and blunts social-evoked OXT sensor responses. RTEL1 associates with a G-quadruplex-forming sequence near the Oxt transcription start site, and purified RTEL1 binds and unwinds this structure in an ATP-dependent manner. Rtel1 reduction in Oxt-lineage cells recapitulates the social and OXT phenotypes, whereas adult RTEL1 re-expression in paraventricular OXT neurons increases OXT abundance and ameliorates behavioral abnormalities. These findings uncover a non-telomeric function for RTEL1 linking promoter DNA structure to hypothalamic oxytocin output and social behavior.

neuroscience↗

bioRxiv2026

Genetic regulation of circulating metabolome in cattle

The circulating metabolome is a vital intermediate layer linking genetics to complex phenotypes, yet existing genome-wide studies-even in humans-rarely capture dynamic physiological contexts or cellular regulatory mechanisms. Here, we present the Cattle Metabolome Atlas (https://cattlema.farmgtex.org/), a comprehensive resource of 3,436 plasma metabolites and 4,851 serum metabolites from 4,651 animals with matched sequence-level genotypes across highly dynamic parity and lactation stages. We mapped 728 plasma and 622 serum metabolite quantitative trait loci (mQTL), revealing widespread context-dependent regulatory architectures. Integrating these mQTL with the multi-tissue expression quantitative trait loci (eQTL) and single-cell atlas of 59 tissues demonstrates that 74-79% of mQTL colocalize with eQTL across 29 tissues, prioritizing the liver as the primary systemic hub and resolving metabolic programs at single-cell resolution. Furthermore, we charted 538 causal gene-tissue-metabolite-trait cascades across 11 complex traits in cattle. Finally, cross-species analyses demonstrate partial evolutionary conservation of genetic metabolism between cattle and humans, establishing this atlas as a powerful asset for cattle genetics and genomics, selective breeding, and comparative biology.

genetics↗

bioRxiv2026

Complementary prefrontal and thalamic representational dynamics during response planning

Advance contextual information can guide behavioral responses, but how prospective action representations unfold across prefrontal and thalamic neuronal populations of the cognitive control network remains unclear. Here, we trained mice on a contextual response-planning task in which auditory cues either predicted the upcoming instructed movement or left response identity unresolved until a later instruction. Predictive contexts improved accuracy and produced subthreshold, directionally biased movements, indicating that mice used contextual information before instruction onset. Extracellular recordings revealed prospective response-side information in prelimbic cortex (PL) and mediodorsal thalamus (MD), but with distinct dynamics. MD represented prospective response side earlier during the context epoch and showed a planning-related temporal advance after instruction onset. In contrast, PL exhibited enhanced instruction-epoch coding and stronger cross-epoch generalization, which could be localized to sparse neuronal subpopulations. These complementary representational dynamics suggest distinct but coordinated roles for prefrontal-thalamic circuits in using advance information to support flexible action planning.

neuroscience↗

bioRxiv2026

Vision Transformers Enable Advanced Plant Phenotyping in Controlled Environments

Reliable plant segmentation in high-throughput phenotyping must transfer across species and imaging conditions without repeated model tuning or extensive reannotation. We compare three segmentation strategies using images from Oak Ridge National Laboratory's Advanced Plant Phenotyping Laboratory: (i) fixed color-based thresholding, (ii) supervised U-Nets trained from scratch, and (iii) pretrained vision transformers fine-tuned for binary segmentation. Models were evaluated on a held-out test set and a generalization set that comprised unseen species. On the held-out test set, thresholding, the best U-Net, and the best vision transformer achieved mean Dice scores of 58.3, 96.6, and 97.3, respectively. On the generalization set, the corresponding Dice scores were 56.5, 86.2, and 95.7. Thresholding remained effective on some datasets but failed when plant appearance changed. Supervised U-Net training resolved within-distribution errors but failed to generalize to novel species and backgrounds. Pretrained vision transformers consistently produced high-accuracy segmentations across the evaluated species, views, soil backgrounds, and tray types. These results benchmark the practical progression from fixed rules to task-specific supervision and pretrained visual representations for controlled-environment plant phenotyping.

plant biology↗

bioRxiv2026

AutoScreen: AI Co-Scientist System for Target Discovery in Functional Genomics

Target discovery in functional genomics remains largely manual and time-consuming, lacking systematic tools for efficient and reproducible gene-level hypothesis generation. We introduce AutoScreen, an AI co-scientist system supporting target discovery through both Pre-screen Design, which constructs perturbation libraries de novo from free-text research descriptions, and Post-screen Analysis, which re-ranks experimental screen hits by integrating statistical scores with biological context. AutoScreen leverages the complementary strengths of multiple specialist agents that perform deep research into multi-modal evidence, information restructuring, parallel searches across >26 biomedical databases, evidence synthesis, and target review to provide transparent, explainable gene prioritization with pipeline provenance. Across 320 genome-scale CRISPR screens as expert-curated benchmarks, AutoScreen achieved a ~19% increase in validated-hit recovery among its top 100 predictions, relative to the strongest agent baseline, and required a 1.2-fold smaller library to recover the same number of hits at the top-500 reference point. AutoScreen reached mean average precision more than two orders-of-magnitude above random baseline. Further, we validated AutoScreen in cancer immune-evasion case studies focusing on natural killer (NK) and T-cell therapeutics. AutoScreen recovered NK-resistance genes that were initially lower-ranked in a leukemia screen, moving MUC1, PDPN, and LRRC15 from raw ranks of 118, 81, 1384 to 5, 44, 659, respectively. In follow-up tumor killing assay with primary human NK cells, individual perturbation validated all three hits successfully. Next, in prospective benchmarking across two cytotoxic T-cell-killing screens, AutoScreen recovered 77.1% of ground-truth hits called by the consensus of two gold-standard analysis pipelines (FDR<0.1), achieving 8% improvement over the strongest general-purpose LLM agent baseline. Finally, we re-analyzed >500 public datasets to construct the AutoScreen Resource Hub, a growing knowledge base of pre-computed, annotated reports for CRISPR screens, RNA-seq differential expression, and gene-level UK Biobank genome-wide association studies. This agentic AI approach enables real-time genomics benchmark construction that are continuously updated, expanded, for evaluating frontier AI co-scientists. Overall, AutoScreen enables AI-powered target discovery to be more auditable, scalable, extensible, and reproducible.

bioengineering↗

bioRxiv2026

A SUN1-ApoD feedback loop promotes cellular aging via microtubule-nuclear mechanotransduction

Alterations in nuclear envelope proteins such as SUN1 and prelamin A are known hallmarks of cellular aging, but how they cause aging phenotypes beyond the expressing cells is unknown. With a tissue culture version of parabiosis, we found that aged fibroblasts secrete an activity that induces aging-related polarity defects in young fibroblasts. Secretomics identified the factor as apolipoprotein D (ApoD), a circulating protein whose levels are known to rise with age. ApoD increased SUN1 levels and disrupted polarity in fibroblasts via SUN1-promoted coupling of microtubules to the nucleus. In turn, elevated SUN1 enhanced ApoD expression and secretion, forming a feedback loop that promotes acquisition of aged phenotypes. In mice, ApoD induced aging-related phenotypes in muscle. Elevated ApoD expression required coupling between SUN1, its outer nuclear membrane binding partner nesprin-2, and microtubules. Broader analysis revealed that this pathway regulates hundreds of genes. These findings define microtubule-nuclear coupling as a direct mechanotransduction pathway controlling gene expression and promoting aging-associated phenotypes.

cell biology↗

bioRxiv2026

Targeting Macrophage Connexin 43 Hemichannels Suppresses Synovial Inflammation and Osteoarthritis

Osteoarthritis (OA) is the most common chronic joint disease and a leading cause of disability worldwide, yet no disease-modifying therapies are available. Although OA has traditionally been viewed as a cartilage-centered degenerative disease, growing evidence suggests that synovial inflammation is a critical driver of disease progression. However, the upstream mechanisms and actionable targets that govern this inflammatory response remain poorly defined. Connexin 43 (Cx43), a key regulator of musculoskeletal homeostasis that forms both gap junctions and hemichannels (HCs), is upregulated in osteoarthritic cartilage and synovium, but the specific contribution of Cx43 channels remains unclear. Here, we show that selective inhibition of Cx43 HCs attenuates OA progression in a murine post-traumatic OA model. Using adeno-associated virus (AAV)-mediated gene deletion, we found that Cx43 knockdown in joint tissues reduced cartilage erosion, synovial hyperplasia, subchondral bone sclerosis, and OA-associated pain. To dissect HC-specific functions, we developed a monoclonal antibody, Cx43(M1), that blocks Cx43 HCs without affecting junctional communication. Cx43(M1) preserved cartilage integrity, suppressed synovial inflammation, and alleviated pain behaviors, even when treatment was initiated after established cartilage damage. Mechanistically, the antibody preferentially localized to synovial macrophages, where it inhibited HC activity, reduced ATP and PGE2 release, and suppressed pro-inflammatory gene expression. Macrophage-specific Cx43 deletion recapitulated these protective effects, and Cx43 HC blockade in primary human OA synovial macrophages similarly inhibited inflammatory and catabolic responses. These findings identify synovial macrophage Cx43 HCs as upstream drivers of OA and support a paradigm shift from a predominantly chondrocyte-centered view toward synovial macrophage directed intervention.

immunology↗

bioRxiv2026

FFPERescuer: deep unsupervised domain adaptation for the reconstruction of gene expression profiles derived from formalin-fixed paraffin-embedded samples

Formalin-fixed paraffin-embedded (FFPE) tumor tissues often suffer from RNA degradation, posing a long-standing challenge for reliable transcriptomic profiling. Here, we propose FFPERescuer, a deep learning framework employing unsupervised domain adaptation, to rectify distorted gene expression data. FFPERescuer comprises a partial encoder that maps a small subset of genes to high-level representations and a decoder to reconstruct full gene expression profiles. On simulated data with varying noise levels, FFPERescuer faithfully recovered gene expression profiles, achieving high Pearson correlation coefficients (PCCs > 0.85) with the ground truth. In FF-FFPE-matched cohorts, FFPERescuer significantly enhanced expression profile concordance, with average PCCs increased by 23% (P < 0.05). Applying to cancer subtyping, FFPERescuer improved classification accuracy from 67% to 92%, recapitulated subtype-specific biological properties lost in the FFPE-derived data, and enhanced survival associations. Our studies provide a powerful framework for reliable transcriptomic profiling from FFPE-archived tumor samples that are widely available in the clinic.

bioinformatics↗

bioRxiv2026

A positively selected microRNA controls a reversible aging program in striated muscle

Aging is the primary risk factor for most chronic diseases and is characterized in striated muscle by progressive functional decline, mitochondrial dysfunction, and chronic inflammation. The miR-128-1 locus resides within a positively selected haplotype on chromosome 2q21.3 associated with variation in grip strength, pulmonary function, and cardiometabolic traits in humans. Here, we show that antisense oligonucleotide-mediated inhibition of miR-128-3p restores muscle mass and function in aged mice, improves cardiac function while limiting adverse remodeling following myocardial infarction, and ameliorates skeletal and cardiac muscle pathology in mouse and pig models of Duchenne muscular dystrophy. Across these contexts, miR-128-3p inhibition induces a conserved transcriptional response characterized by activation of mitochondrial programs and suppression of inflammatory and fibrotic signaling, resembling the effects of established longevity interventions. These findings identify miR-128-3p as a regulator of a conserved aging-associated program and establish its inhibition as a strategy to restore tissue function across aging-related muscle pathologies.

molecular biology↗

bioRxiv2026

A Multi-Omics Study of Cognitive Resilience to Alzheimer's Disease

Alzheimers disease (AD) is the most severe form of dementia. While significant efforts have been made to identify AD risk factors and develop therapeutics, much less attention has been given to neurobiological factors and molecular signatures associated with cognitive resilience. Substantial evidence suggests that modifiable factors, such as physical and mental activity, may contribute to cognitive reserve and resilience. To this end, we developed a resilient cohort of paired genetics, transcriptomics and proteomics data from the prefrontal cortex of 282 cognitively normal older adults. We conducted extensive preprocessing and rigorous quality control (QC), including QC on sequence metrics and sample matching across multiomics. This cohort can be leveraged for identification of molecular signatures of cognitive resilience to AD and is freely shared with the research community.

genomics↗

bioRxiv2026

ReTIF: Granularity-Aware Multitask Interaction Routing for RNA-Compound Interaction Prediction and Binding-Site Localization

RNA-targeted drug discovery requires both RNA-compound interaction prediction and nucleotide-level binding-site (BS) localization. These two tasks rely on different levels of interaction information: DTI prediction summarizes overall RNA-compound compatibility, whereas BS localization requires preserving nucleotide-level compound-associated signals. However, existing multitask models often use shared cross-modal representations for both tasks before task-specific prediction layers, which may limit their ability to preserve task-dependent interaction patterns. We therefore propose ReTIF (Relation-enhanced Task-specific Interaction Framework), which constructs separate cross-modal interaction representations for DTI prediction and BS localization before aggregation. ReTIF integrates multi-source RNA-compound representations from frozen RNA-FM, StructRFM, Mole-BERT, and MolFormer encoders, and builds separate interaction representations for DTI scoring and BS localization. The DTI branch captures global compatibility through aggregation, whereas the BS branch preserves nucleotide-compound resolution and enhances local evidence through relation-guided propagation with RNA structural and compound topological priors. An asymmetric DTI-derived compatibility signal provides global context to BS prediction while maintaining local evidence. Across five-fold evaluations under unseen pair, RNA, compound, and joint shifts with 13 baselines, ReTIF has the highest mean in 13 of 16 scenario-metric combinations, including BS AUPR in all four settings.

bioinformatics↗