Biology subjects

Huang, K.

Publications and source records attributed to Huang, K..

At least 19 recordsLinked to original sources

bioRxiv2026

A unique intestinal epithelial cell that expresses canonical lymphoid genes

Enterocytes and intestinal secretory cells harbor innate immunity. However, certain transcriptional programs -even beyond rearranged T- and B-cell receptor genes- are considered the exclusive purview of adaptive immune cells, including abundant and diverse intestinal intra-epithelial lymphocytes (IELs). Here, we identify and characterize columnar intestinal secretory cells that co-express classic epithelial and lymphoid genes, including Ptprc, Cd3e, Cd8a, and Gzma/b but not T- or B-cell receptors. These previously unrecognized epithelium-derived lymphoid-like cells (EDLCs) differ from any known resident cell type, including IELs or tuft cells. Rare in healthy mouse and human intestines, their numbers increase upon IL-25 stimulation or IL-10 receptor deficiency in vivo and upon IL-13 stimulation in vitro. EDLC chromatin is uniquely accessible at thousands of cis-elements, including lymphoid and epithelial loci. These findings reveal a transcriptionally and epigenetically distinct intestinal epithelial derivative that expresses prominent lymphoid character.

cell biology↗

bioRxiv2026

Programmable design of functional RNAs through multimodal generative learning

RNA engineering is bottlenecked by the tight coupling among sequence, structure, and function, leaving the field reliant on heuristics or screening. We introduce RNAverse, a multimodal generative model that learns a conditionable design grammar from RNA sequences, experimental structural probing profiles, and functional annotations. Beyond setting a new state of the art across 16 predictive modeling tasks, RNAverse inverts into generative design across four distinct RNA classes through three regimes, requiring experimental testing of no more than 20 candidates per-task. Zero-shot in-painting generates snoRNAs that promote premature termination codon (PTC) readthrough, and chimeric aptazymes for ligand-controlled gene regulation, exceeding rational design or large-scale screens. In both settings, RNAverse outperforms family-adapted sequence-only baselines. Fine-tuned in-painting extends to an unseen functional class, yielding IGFBP3-binding aptamers with picomolar affinity that outperform SELEX winners. Iterative optimization engineers 5' UTRs that outperform clinical benchmarks, enhancing protein production in cell-based assays for both the Zolgensma gene therapy and the BNT162b2 COVID-19 vaccine, and boosting antibody responses to BNT162b2 in mice. Together, these results establish multimodal generative learning as a route from predictive RNA modeling to programmable specification of functional RNAs.

bioinformatics↗

bioRxiv2026

The root knot nematode effector MiEFF186 interacts with a splicing factor to reshape plant transcriptome

The root-knot nematode Meloidogyne incognita secretes specific effectors to manipulate root cells and induce their redifferentiation into multinucleate feeding giant cells, which are essential for its development. A dedicated screen identified the M. incognita MiEFF186a effector as a regulator of alternative splicing, a crucial mechanism of transcriptional gene regulation whereby a single gene can produce multiple mature mRNA variants, in plants. EFF186 is expressed in the esophageal glands of nematode juveniles, and in planta, it localizes to the nucleus and accumulates in the nucleolus. A yeast two-hybrid approach identified the nucleolar G-patch protein GDP1/CIS2 as a MiEFF186a target in tomato and Arabidopsis. Transcriptomic analyses of Arabidopsis roots ectopically expressing MiEFF186a or impaired in GDP1/CIS2 function revealed changes in both gene expression and alternative splicing, with partially overlapping responses. Finally, alteration of GDP1/CIS2 expression by virus-induced gene silencing in Solanaceae or in Arabidopsis gdp1 mutants affects susceptibility to M. incognita. Together, these results identify GDP1/CIS2 as a host target of MiEFF186a and support a role for these proteins in the modulation of host RNA metabolism during nematode parasitism.

plant biology↗

bioRxiv2026

Spatial isotope tracing maps compartmentalized nutrient use across the adult fruit fly

Drosophila melanogaster is a powerful model for studying systemic metabolism. Although metabolism is compartmentalized across tissues, prior work in adult Drosophila has mostly measured it in dissected tissues rather than in situ, limiting the spatial information that can be gained. Here, we combine whole-fly mass-spectrometry imaging with stable-isotope tracing and flux modeling to quantify metabolic activities across the adult fruit fly in a spatially resolved manner. Across 68 tracer-fed Oregon-R female flies and 187,709 pixels, we map 81 metabolites onto eight annotated regions, including muscle, fat body, gut, and nervous system. Glucose labeling and fitted relative fluxes indicate higher glycolytic and tricarboxylic acid cycle turnover in thoracic muscle than in abdominal fat body; proline labels the nervous system and eye; glutamine the abdominal reproductive system and gut. Alanine carries glucose-derived carbon through the hemolymph and transfers nitrogen into glutamate. In flies bearing yorkie-driven gut tumors, alanine contribution to malate rises in gut and abdomen, and reducing gut alanine uptake lowers tumor burden. Together, this work establishes a framework for quantitative spatial metabolic analysis, showing compartmentalized nutrient use across the adult fruit fly.

genetics↗

bioRxiv2026

FlyAnatoView: Visualization of Drosophila Single-cell RNA-seq Datasets on Anatomographs

Single-cell RNA sequencing (scRNA-seq) is a powerful approach for measuring the transcriptomic landscape at single-cell resolution. However, while scRNA-seq data reveals what genes each cell expresses, they do not indicate where that cell was located within the tissue or organ, anatomically. We developed FlyAnatoView (https://www.flyrnai.org/tools/rna_seq_base/web/svg_files/), a resource that projects scRNA-seq data onto anatomical diagrams, restoring this missing spatial context.

bioinformatics↗

bioRxiv2026

Tracking gene flow in the gut microbiome reveals phage activation and host-range expansion in response to diet

Horizontal gene transfer (HGT) drives microbial evolution, but what determines when genes move between species within complex communities remains unclear. We developed a junction-resolved metagenomic framework using short-read sequencing to distinguish mobile genetic element activation from de novo transfer and track both longitudinally. In a defined human gut community colonizing mice, mobile element activation was widespread but successful transfer was rare. A prophage carried by invading Phocaeicola vulgatus transferred reproducibly to resident species when the community resisted invasion, but not when dietary perturbation allowed the invader to expand. Transfer required prophage activation and persistence of a permissive recipient and coincided with diversification of a phage receptor-binding protein. Dietary polysaccharides reproduced prophage-associated fitness costs in vitro, and rhamnogalacturonan I induced cell lysis consistent with productive prophage activation. The framework also detected interspecies transfer retrospectively in longitudinal human metagenomes. Thus, diet and community ecology can redirect gene flow through the gut microbiome.

microbiology↗

bioRxiv2026

A genetic screen to identify novel interactions of the phosphatidylinositol phosphate signaling pathway in Drosophila spermatogenesis

Phosphatidylinositol (PI) phosphates (PIPs) are membrane lipids with crucial roles in intracellular signaling, membrane trafficking and cytoskeletal organization. To perturb PIP function in Drosophila melanogaster sperm development, we previously expressed the Salmonella PIP phosphatase SigD (also known as SopB) under control of a spermatocyte- specific promoter. SigD expression results in reduced levels of plasma membrane PI 4,5-bisphosphate [PI(4,5)P2; henceforth PIP2] and male sterility. Transgenic lines expressing high levels of SigD (SigD-high) exhibit defects in spermatocyte cytokinesis, ciliary transition zone maturation and spermatid elongation, whereas lines expressing low levels of SigD (SigD-low) have defects in nuclear shaping and spermatid cell polarization. To further investigate the role of PIPs during Drosophila sperm development, we conducted a sensitized genetic screen to identify suppressors and enhancers of SigD-low phenotypes. From a screen of 760 chromosomal deficiencies spanning 83.6% of chromosomes 2 and 3, we identified 80 interacting regions that were further narrowed down to 40 individual suppressors. Among the strongest interactors were genes involved in microtubule dynamics, nucleocytoplasmic transport and membrane trafficking. The novel genetic interactions identified by our screen pave the way for further investigation into molecular mechanisms underlying the affected aspects of sperm development.

genetics↗

bioRxiv2026

Ketogenic diet is protective during endotoxin-induced lung injury through the elevation of BHB

Acute respiratory distress syndrome (ARDS) is marked by severe pulmonary edema and concomitant hypoxia, affecting hundreds of thousands of people a year, especially those in critical care conditions or suffering from septic shock. Previous studies have implicated that the ketogenic diet, a high-fat and low-carbohydrate diet, modulates inflammatory responses. However, the impact of the ketogenic diet on septic ARDS outcomes is unknown. Here, we demonstrated that mice on a ketogenic diet showed strikingly reduced lung injury and inflammation compared to those on a control diet during a murine model of endotoxin-induced lung injury, induced by intratracheal lipopolysaccharide (LPS) injection. Immune mass cytometry studies on lung tissue indicated that the ketogenic diet reduces immune cell infiltration. Treating mice with beta-hydroxybutyrate (BHB), the primary metabolite of ketogenesis, after the onset of ARDS reduced pulmonary edema and lung inflammation, as well as NF-kB activity, suggesting strong therapeutic potential. By multiplex analysis in bronchial alveolar lavage fluid, we observed that the ketogenic diet or BHB administration attenuates the chemotaxis and activation of immune cells. Altogether, our findings reveal that the ketogenic diet provides lung protection during endotoxin-induced lung injury through BHB.

physiology↗

bioRxiv2026

ARSA: an autonomous research scientist for target nomination in Alzheimer's disease and related dementias

Expanding therapeutic options for Alzheimer's disease and related dementias (ADRD) requires biologically grounded targets, yet nomination demands labor-intensive analysis and multidisciplinary evidence synthesis. To address this challenge, we present ARSA, an autonomous research scientist that transforms natural-language research interests and molecular data into prioritized, evidence-grounded target shortlists. ARSA formulates and audits hypotheses, adapts molecular analyses to observed results, and prioritizes targets using cross-cohort evidence and disease-specific knowledge, preserving the evidence and decisions underlying each nomination. Across three complementary evaluations, we show that ARSA generates hypotheses corresponding to subsequent research and identifies credible candidates within and beyond community nomination records. In structured assessment by 14 experts spanning all four technical cores of the Indiana University School of Medicine-Purdue University TREAT-AD Center, every expert assigned higher mean credibility to ARSA-retained candidates than to rejected comparators. ARSA enables systematic, transparent target exploration, opening opportunities to broaden the therapeutic mechanisms investigated in ADRD.

bioinformatics↗

bioRxiv2026

An integrated platform for genome-wide functional analysis in Aspergillus niger through Ac/Ds insertion profiling and metabolic modeling

Genome-scale metabolic models guide rational strain engineering, while high-throughput insertional mutagenesis enables systematic investigation of gene function and condition-dependent growth requirements. However, a platform integrating high-density transposon insertion sequencing with matched stoichiometric, thermodynamic, enzyme-constrained and combined metabolic models has not, to our knowledge, been reported in Aspergillus. Here, we establish a unified experimental and computational platform in Aspergillus niger ATCC1015 by combining curated metabolic reconstruction, Ac/Ds transposon mutagenesis and machine-learning-based essentiality prediction. Our stoichiometric reconstruction, FBA1015, expands reaction coverage and compartmental resolution beyond four published reconstructions. From FBA1015, we developed three models sharing its biochemical network: GECKO light with enzyme-capacity constraints, TFA with thermodynamic constraints and ecTFA combining both. FBA1015 and its derivatives performed competitively in phenotype benchmarks, with added constraints improving agreement with measured growth and gas exchange. Insertion libraries grown in rich medium, glucose or xylose achieved genome-wide densities of one distinct site per 21--112bp across individual libraries. A machine-learning classifier integrated insertion patterns and gene structure to predict essentiality across 11,111 genes. Applying a stringent consensus criterion identified 709 genes predicted essential on both glucose and xylose as sole carbon sources, and 91 predicted essential on one but nonessential on the other. Integration with simulated gene deletions prioritizes candidate genes and testable pathway hypotheses, connecting high-throughput genetic screening with mechanistic analysis for fungal functional investigation and strain engineering.

microbiology↗

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

Tumor-tropic E. coli engineered as living T and NK cell engagers

Despite advances in immunotherapy, most solid tumors remain resistant to treatment. Immune cell engagers redirect cytotoxic lymphocytes against cancer, but limited tumor access, immunosuppressive microenvironments and systemic immune activation limit efficacy. Here we develop live immune modulating engagers (LIME), a modular platform where non-pathogenic, tumor-tropic Escherichia coli display tandem single-chain variable fragments targeting a tumor-associated antigen and an activating receptor on T or natural killer cells. LIME bridged effector and tumor cells, induced transcriptional programs of T cell activation, metabolism and proliferation, and enhanced cytotoxicity across cancer cell lines and patient-derived organoids. In mouse models, LIME safely accumulated in tumors, outperformed tarlatamab in small cell lung cancer, and induced durable immunity in lymphoma. RAS inhibition and PD-L1 blockade enhanced LIME activity in pancreatic cancer and induced humoral responses. Multi-lineage immune modulation remained tumor-confined, without organ toxicity. These findings establish LIME as a versatile living therapeutic platform for programmable, tumor-restricted immune orchestration.

bioengineering↗

bioRxiv2026

GWAS and multi-omics uncover the SLC6A3 locus for canine stranger-directed social anxiety and implicate NRIP3 in dopaminergic network regulation

The social anxiety disorder (SAD) is one of the most common mental health disorders, often developing in adolescence. It can severely impair educational achievement, career progression, and social functioning. Certain individuals within the Chinese Kunming dog (CKD) population display spontaneous, SAD-like behaviors towards strangers, offering a valuable model for genetic investigation. Using whole-genome sequencing data, we conducted a genome-wide association study on this SAD-like behavior in 100 CKDs, identifying several genes previously linked to human psychiatric disorders. Notably, SLC6A3 reached genome-wide significance, whereas CADPS2 exceeded only the suggestive threshold and is therefore considered a network-supported candidate locus. By integrating weighted gene co-expression network analysis with public RNA-seq data from the VTA of 38 mice (after quality control), we further showed that Slc6a3 and Cadps2 are part of a co-expression network module associated with the dopamine system. These findings suggest that this specific module may play a functional role in the stranger-directed anxiety-related behaviours in CKDs. Furthermore, we identified Nrip3 as a key candidate transcriptional coregulator in this specific module. Subsequent virus-mediated overexpression and behavioural experiments showed that Nrip3 regulates gene expression within this network and induces a spectrum of behavioural alterations in mice, including social avoidance, anhedonia, and increased locomotor activity. Collectively, this study highlights the involvement of dopamine system genes in canine social anxiety and suggests Nrip3 as an upstream regulator of Slc6a3 associated with anxiety. The identification of conserved anxiety-related signatures between humans and dogs further supports the dog as a valuable translational model for psychiatric research.

genetics↗

bioRxiv2026

Phagocytic activity of perivascular cell promotes CNS injury pathology

Injury, stroke, and neurological diseases cause persistent accumulation of cellular debris that deteriorates lesion microenvironment and impedes central nervous system (CNS) repair. Debris clearance in the injured CNS has long been attributed primarily to microglia and infiltrating macrophages. Here, we identify perivascular cells as previously unrecognized phagocytes that expand after injury and exhibit robust phagocytic activity. Perivascular cell phagocytosis is conserved across multiple mouse models of CNS injury and human stroke lesions. These cells exhibit key hallmarks of phagocytosis, including LC3-associated phagocytosis for efficient lysosomal degradation. Mechanistically, phosphatidylserine serves as the eat-me signal and Axl mediates myelin debris uptake. Myelin phagocytosis drives perivascular cell proliferation, fibrosis and lesion progression. Genetic deletion of Axl in perivascular cells or pharmacological inhibition with the FDA-approved Axl inhibitor Gilteritinib reduces pathology and improves functional recovery after spinal cord injury. Together, these findings establish Axl-dependent perivascular cell phagocytosis as a therapeutic target for CNS repair.

neuroscience↗

bioRxiv2026

Epitope-Focused Immunogens Confer Broad Protection against Coronaviruses

Variable regions in coronavirus spike dominate antibody responses elicited by infection or conventional vaccination and limit induction of broad neutralization. In contrast, conserved S2 elements, including the stem helix (SH) and fusion peptide proximal region (FPPR), are promising but subdominant targets of protective immunity. Here, we employed computational design to generate de novo epitope-focused immunogens that precisely present the SH and FPPR epitopes. Formulated as combinatorial immunogens, this vaccine elicited consistent serum responses with broad reactivity across known human coronaviruses and induced epitope-specific antibodies with broad neutralizing activity. As a heterologous boost, epitope-focused immunogens protected mice against challenge with phylogenetically distinct coronaviruses, including bat SARS-related RsSHC014-CoV and MERS-CoV, establishing a generalizable strategy for precision immune focusing and advancing universal coronavirus vaccine development.

bioengineering↗

bioRxiv2026

Spatium: A Protein Language Foundation Model for Spatial Proteomics

Spatial proteomics provides single-cell protein measurements under highly constrained and heterogeneous protein panels across datasets, resulting in limited and partially overlapping measurement spaces for cellular characterization. Existing analyses predominantly rely on statistical or task-specific modeling, while learning scalable representations of spatial protein data remain underexplored. This gap motivates the need for models that can learn stable representations of cellular identity from constrained protein measurements. Here we introduce Spatium, a protein language foundation model trained on over 51 million cells across multiple spatial proteomics platforms. Spatium learns intrinsic co-expression hierarchies that capture cell identity in a manner robust to panel composition and measurement scale. Spatium builds a generalizable representation of cell states grounded in biologically interpretable protein expression patterns. We demonstrate that Spatium learns biologically meaningful cell representations across multiple downstream tasks. Spatium recovers accurate cell identities with marker expression patterns consistent with known biology and reveals functionally distinct spatial microenvironments characterized by coherent marker enrichment signatures. It further enables reconstruction of missing protein measurements while preserving biologically meaningful expression patterns. Across these analyses, Spatium demonstrates stable and interpretable performance with lightweight task-specific adaptation, highlighting the robustness of the learned representations across diverse biological and experimental contexts.

bioinformatics↗

bioRxiv2026

Fasting disrupts the InsP6 HDAC3 axis to drive ER stress-mediated clearance of DNA-damaged cells and enforce tissue quality control.

Fasting drives metabolic adaptation but also elicits acute cellular stress. How this stress shapes tissue integrity is unknown. Here, we show that in the intestine, fasting depletes growth factor signaling, which triggers cellular stress. This response functions as a tissue quality-control checkpoint that selectively eliminates pre-existing DNA-damaged cells while sparing healthy counterparts. A short-term fast diminishes TGF-{beta} signaling and elicits endoplasmic reticulum (ER) stress, driving DNA-damaged intestinal cells beyond an apoptotic threshold, thereby reducing the inflammatory burden. Mechanistically, loss of TGF-{beta} signaling triggers FBXO22-Cullin1-mediated degradation of the inositol kinase IPMK, leading to depletion of inositol hexaphosphate (InsP). InsP loss attenuates HDAC3 activity and initiates coordinated epigenetic and post-translational reprogramming, thereby increasing CDK5RAP3 abundance. Elevated CDK5RAP3 inhibits ribosomal RPL26 UFMylation, thereby amplifying ER stress and selectively licensing apoptosis in DNA-damaged cells. Collectively, fasting disrupts a TGF-{beta}-InsP6-HDAC3 axis to drive ER stress-dependent clearance of DNA-damaged cells, enforcing tissue quality control.

cell biology↗

bioRxiv2026

Appetite for change: How psilocybin reshapes food reward learning through striatal dopamine function

Psilocybin has emerged as a promising therapeutic agent for psychiatric disorders characterised by cognitive rigidity and disrupted reward processing, including anorexia nervosa. While its pro-cognitive effects have been mechanistically probed almost exclusively through serotonin receptor subtype antagonism, the downstream contributions of dopaminergic systems to these outcomes remain poorly understood. Here, we examined how psilocybin (1.5 mg/kg) alters cognitive flexibility across multiple operant paradigms in female rats and whether ventral striatal dopamine, nutritional state or prior activity-based anorexia (ABA) exposure moderate these effects. In food-restricted rats, psilocybin improved reversal learning with an apparent temporal delay relative to our previously published ad libitum fed cohort. In vivo fiber photometry revealed that psilocybin broadly amplified nucleus accumbens core (NAc) dopamine transients time-locked to both expected and unexpected outcomes during probabilistic reversal learning across 7 days. Computational modelling identified psilocybin-specific increases in learning rate and reductions in prior value weighting, consistent with strengthened feedback-driven updating. In touchscreen paradigms, psilocybin enhanced discrimination accuracy and accelerated reversal learning acquisition when administered prior to initial discrimination, but impaired serial reversal accuracy when administered after initial discrimination. ABA exposure constrained psilocybin's pro-cognitive effects, abolishing discrimination accuracy benefits, suggesting that metabolic disruption and stress alter the neural substrates required for psilocybin-enhanced neuroplasticity and reward learning. These findings provide the first direct evidence that psilocybin modulates striatal dopamine signalling in a behaving animal and demonstrate that current nutritional state and prior experience with pathological weight loss and reward learning moderate its cognitive effects.

neuroscience↗