Biology subjects

Hu, X.

Publications and source records attributed to Hu, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Sleep reactivation of positive self-evaluation reveals neural-evaluative alignment that varies with depressive symptoms

Positive self-evaluation underpins resilience and mental health, yet how to enhance positive self-evaluation and the underlying neurocognitive mechanisms remain poorly understood. Existing data mostly examined self-evaluative processing of the wakeful minds, with the role of sleep remain unexplored. Here, we demonstrated that reactivation of positive self-evaluation during sleep revealed fine-grained neural-evaluative alignment that varies with depressive symptoms. We found that targeted reactivation of positive personality traits during non-rapid eye movement (NREM) sleep enhanced positive self-evaluation, but this benefit diminished with elevated depressive symptoms. Moreover, cueing positive traits during NREM sleep elicited trait-specific, 11-16 Hz EEG sigma power-based neural representations that aligned with post-sleep positive self-evaluative representational structures, as revealed by representational similarity analyses. Notably, individuals with elevated depressive symptoms exhibited weaker neural-evaluative representational alignments, identifying a maladaptive self-evaluative processing that bridges across sleep and wakefulness states. These findings provide mechanistic insights on how fine-grained neural-evaluative alignment can substantiate positive self-evaluation, and why it was disrupted as depressive symptoms increased. HighlightsO_LIPositive-trait reactivation during NREM sleep enhances positive self-evaluation C_LIO_LIThis behavioral benefit decreases as depressive symptoms increase C_LIO_LISleep cueing evokes trait-specific sigma-band neural representations C_LIO_LINeural-evaluative alignment weakens as depressive symptoms increase C_LI

neuroscience↗

bioRxiv2026

AI4Life Open Calls and Public Challenges: why, how, and what we have learned.

Within AI4Life, we ran three Open Calls and three Public Challenges (2023-2025), supporting 22 bioimage analysis projects from 151 applications and engaging 225 challenge participants, with the aim of applying FAIR deep learning in the life sciences. Our experience offers a view of the current state of bioimage analysis, the landscape of available tools, as well as the existing gaps between method developers, tool producers and potential users. It highlights that even after careful selection for AI-ready projects, most still require substantial effort to apply deep learning, and that the field still relies heavily on established, well-rounded methods to solve common problems. We come to the conclusion that for scientific AI in biology, the rate-limiting step is not methods and models but data, annotations, and shared infrastructure underneath them.

bioinformatics↗

bioRxiv2026

Tumor-derived stearic acid induces macrophage Egr2 signaling to suppress anti-tumor immunity in breast cancer

BackgroundMacrophages in breast cancer are highly heterogeneous and targeting both tissue-resident and bone marrow-derived macrophages represents a high-potential strategy in breast cancer immunotherapy. MethodsMyeloid-specific Egr2 knockout (KO) mice were used to determine roles of macrophage Egr2 signaling in tumor progression and anti-tumor immune responses. RNA-seq analysis and Flow cytometry were used to examine regulation of Egr2 in tumor-associated macrophages (TAMs) and fatty acid-stimulated macrophages. Tumor cell and macrophage admixture study was used to evaluate effects of fatty acid educated macrophages on anti-tumor responses. ResultsHere we showed that early growth response 2 (Egr2) was highly expressed in mammary tissue macrophages and recruited macrophages upon tumor progression. Depletion of Egr2 in myeloid cells significantly decreased the immunosuppressive function of polarized M2-like macrophages and TAMs. Tumor progression was delayed in myeloid cell Egr2 knockout mice, which was associated with enhanced function of effector CD8+ T cells and NK cells. Mechanistically, we showed that retinol and nicotinamide metabolism in TAMs were impaired after Egr2 depletion. Further, tumor cell-derived stearic acid (SA) was identified as an important fatty acid inducing Egr2 expression. SA stimulation induced macrophage-mediated immunosuppression in an Egr2 dependent manner. Addition of oleic acid (OA) uniquely repressed SA-induced Egr2 expression and immunosuppressive activity in macrophages. ConclusionsOur study thus uncovers a novel SA-Egr2 pathway driving macrophage immunosuppression and novel molecular mechanism of OA mediated anti-tumor effect. WHAT IS ALREADY KNOWN ON THIS TOPICLipid-associated macrophages (LAMs) accumulate lipids and promote immune suppression, tumor growth and metastasis in breast cancers. Fatty acids play a dual, complex role in tumor immunity, acting as both pro-tumorigenic and anti-tumorigenic effects. However, molecular mechanisms underlying fatty acid modulated macrophages and their roles in tumor remain not fully elucidated. WHAT THIS STUDY ADDSWe demonstrate that Egr2 is essential for the immunosuppressive function of IL-4 polarized M2-like macrophages and TAMs. Tumor cell-derived stearic acid (SA) was identified as an important fatty acid inducing Egr2 expression and immunosuppression in macrophages. Adding oleic acid (OA) uniquely repressed SA-induced Egr2 expression and immunosuppression. HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICYSA-Egr2 axis is a novel pathway driving macrophage immunosuppression. OA treatment enhances macrophage anti-tumor immunity via inhibiting Egr2 signaling and immunosuppression. The data supports the notion that diets enriched in OA may have potential for prevention and suppression of breast cancer.

immunology↗

bioRxiv2026

Gut Virome Diversity and Health Status in Rescued Pangolins: Metaviromics Reveals Parvovirus as a Key Virus Associated with Disease

BackgroundPangolins are critically endangered mammals that suffer from high rates of gastrointestinal disease during captivity, yet the role of the gut virome in their health remains unexplored. This study presents the first comprehensive characterization of the gut DNA virome in Malayan (Manis javanica) and Chinese (M. pentadactyla) pangolins across different health states. ResultsMetaviromic sequencing of 16 fecal samples from healthy, diarrheal, pneumonic, free-ranging, and deceased pangolins generated 7.2-11.8 Gb clean data per sample. A total of 12 viral phyla, 26 families, 219 genera, and 1,132 species were identified. Caudovirales phages (Siphoviridae, Myoviridae, and Podoviridae) dominated the gut virome of healthy individuals, with phage content exceeding 90% in most healthy samples. However, diseased and deceased individuals exhibited a significant reduction in phage proportion (94.5% vs. 53.3%, P = 0.02), accompanied by a dramatic increase in eukaryotic viruses--particularly Parvoviridae, which accounted for 66% of the virome in deceased Malayan pangolins. Iridoviridae (38%) and Polydnaviridae (34%) dominated in deceased Chinese pangolins. SIMPER analysis identified Parvoviridae as the primary contributor to virome dissimilarity between healthy and diseased Malayan pangolins, whereas Iridoviridae and Polydnaviridae were the key contributors for Chinese pangolins. LEfSe analysis revealed 12 biomarker viruses in free-ranging pangolins (predominantly Staphylococcus and Escherichia phages), six in healthy Chinese pangolins (predominantly Streptococcus phages and Lactobacillus viruses), and six in deceased Malayan pangolins (predominantly vertebrate viruses). KEGG functional annotation revealed that genes related to DNA replication, repair, and recombination were the most abundant, suggesting frequent genomic recombination within the pangolin gut virome. ConclusionsThe gut virome of pangolins is closely associated with health status. Disease induces a shift from a phage-dominated to a eukaryotic virus-dominated virome, with Parvoviridae and Iridoviridae emerging as candidate pathogenic viruses in Malayan and Chinese pangolins, respectively. These findings provide molecular evidence for virome monitoring in pangolin conservation and highlight the need for targeted surveillance of ImportancePangolins are the most trafficked mammals in the world, and all eight species are critically endangered. During rescue and captive care, these animals suffer from high rates of gastrointestinal disease, yet the role of viruses in their gut health has never been studied. This research provides the first comprehensive map of the gut virus community in pangolins, revealing that healthy individuals carry a virus community dominated by beneficial bacterial viruses called phages, while sick and dying animals show a dramatic shift toward disease-causing viruses. Notably, parvoviruses emerge as potential pathogens in Malayan pangolins, while iridoviruses dominate in deceased Chinese pangolins. These findings offer a new tool for monitoring pangolin health in rescue centers: by tracking the balance between beneficial phages and harmful viruses, veterinarians may be able to detect illness earlier and improve survival rates. The study also highlights the importance of environmental exposure for maintaining a healthy gut virus community, supporting the creation of semi-natural enclosures for rescued pangolins. Beyond conservation, this work contributes to our understanding of how viruses move between wildlife and humans, which is critical for preventing future disease outbreaks.

microbiology↗

bioRxiv2026

Single cell multi-omics enables high-resolution identification and functionalpurification of human acute myeloid leukemia stem cells

In human acute myeloid leukemia (AML), a sub-population of leukemia stem cells (LSCs) drive disease initiation, therapeutic resistance, and relapse. However, the lack of reliable markers to distinguish LSCs from bulk leukemia cells has impeded progress in studying LSC pathogenesis and developing meaningful LSC-specific diagnostics and therapeutics. Existing LSC gene signatures, derived from bulk populations, cannot definitively identify LSCs at single-cell resolution. To address this, we analyzed large patient cohorts with bulk gene expression data and single-cell multi-omic assays to identify a prognostic gene signature that is specifically enriched in a clinically adverse AML sub-population. Using this signature, we defined and prospectively isolated CD34+CD90-CLL1-CD69+CD53- immunophenotypic LSCs that are significantly enriched for LSC content based on limiting dilution xenotransplantation assays. Our findings demonstrate the power of single-cell multi-omics to precisely identify a clinically relevant LSC population and establish a clear framework for future translational research in AML. Key PointsO_LISingle cell multi-omics identifies human AML LSCs at high resolution. C_LIO_LIHOPX and SOCS2 co-expression (hrLSC2) defines a prognostic gene signature in de novo acute myeloid leukemia. C_LIO_LIhrLSC2 marks an AML subpopulation (iLSCs) with a distinct immunophenotype. C_LIO_LIiLSCs can be purified using flow cytometry and are significantly enriched for LSCs. C_LI

cancer biology↗

bioRxiv2026

Integrin-engaged Cellular Patches Mechanically Impose a Mitochondrial Respiratory Bottleneck to Suppress Cancer Cell Motility

The nanoscale organization of cell-adhesive ligands is increasingly recognized as a determinant of cell behavior, yet whether it directly regulates cellular metabolism remains unclear. Here we show that supramolecular clustering of integrin-binding ligands regulates mitochondrial respiratory capacity through integrin-mediated mechanotransduction. Supramolecular ligand clustering induces integrin redistribution and cytoskeletal remodeling, leading to mitochondrial reorganization and a selective constraint on oxidative phosphorylation. This respiratory limitation functionally constrains tumor cell migration and invasion and cannot be overcome by restoring cytoskeletal contractility, whereas replenishing mitochondrial metabolic substrates effectively rescues motility. In a HeLa xenograft model, the integrin-binding supramolecular system suppresses tumor growth and reduces extracellular matrix deposition. These findings identify mitochondrial respiratory capacity as a critical downstream effector of integrin mechanosignaling and establish extracellular ligand organization as a previously unrecognized driver of mechanically encoded metabolic regulation.

biophysics↗

bioRxiv2026

Targeting folate-dependent purine synthesis sensitizes melanoma cells to immune attack through suppressing glycolysis

Cytotoxic T lymphocytes (CTLs) play a central role in antitumor immunity; however, metabolic reprogramming within the tumor microenvironment often compromises their effector function, making metabolic targeting crucial for the improvement of T cell function. Folate-dependent purine synthesis, a core pathway sustaining the nucleotide pool, is highly activated in tumors, yet its role in regulating tumor immune sensitivity remains unclear. Here, by establishing a co-culture system of melanoma cells and human T Cell Receptor (TCR)-engineered T cells, we systematically evaluated the effects of folate-dependent purine synthesis inhibitors on tumor cell response to CD8+ T cell cytotoxicity. We found that inhibition of key enzymes such as methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) and glycinamide ribonucleotide transformylase (GART) markedly enhanced tumor cell sensitivity to T cell killing, an effect also observed with exogenous nucleoside supplementation. Mechanistically, inhibition of folate-dependent purine synthesis suppresses glycolysis by downregulating critical glycolytic enzymes, thereby reducing lactate production. Reduction in lactate further weakens lactylation and stability of the immune checkpoint protein PD-L1. In parallel, impaired purine synthesis disrupts uridine metabolism, blocks ribose salvage, and distally influences glycolysis. Collectively, our study identified the folate-dependent purine synthesis - glycolysis axis as key regulator of tumor immune response and highlights metabolic targeting as a promising strategy to improve cancer immunotherapy.

cancer biology↗

bioRxiv2026

MycoCirc: A Pan-Fungal Multi-Modal Pretrained Model for Fungal circRNA Prediction from Genome Sequence

MotivationExploring the fungal circular RNA (circRNA) landscape is bottlenecked by both experimental and computational limits. While standard mRNA-seq systematically discards circRNAs due to their lack of poly(A) tails, high-cost total RNA-seq remains prohibitive for large-scale screening. Consequently, discovery relies heavily on computational prediction. However, existing models trained exclusively on human or plant sequences fail in fungi because of the extreme genomic divergence across fungal lineages, which span from intron-poor Candida to intron-rich filamentous fungi. As a result, no computational framework currently exists for de novo fungal circRNA prediction, leaving the vast majority of non-model fungi entirely inaccessible. ResultsWe present mycoCirc, the first end-to-end pan-fungal multi-modal pretrained model for fungal circRNA prediction, integrating three mandatory modalities with bidirectional cross-attention for donor-acceptor site interaction. Pre-trained on 22 strains with 16,483 positive gene-circRNA associations spanning Ascomycete yeast, Basidiomycete yeast, and Filamentous fungi groups and fine-tuned per group using 5-fold cross-validation, mycoCirc achieved AUROC 0.69-0.70 on held-out test species under Mode A (Genome+GTF, no RNA-seq), substantially outperforming JEDI (0.51-0.57) and CircPCBL (0.49-0.53). Cross-species evaluation on four independent fungi datasets demonstrated robust generalization across all fine-tuned variants (AUROC 0.63-0.72). Beyond gene-level classification, the JunctionEncoder module enabled backsplicing junction identification for detailed circRNA validation. We further build mycoCircAtlas, a companion database providing 319,860 high-confidence gene-circRNA predictions across 768 fungal species from Ensembl Fungi Release 113, enabling researchers to query precomputed predictions and design validation primers without local model deployment. Availability and ImplementationmycoCirc is freely available under the MIT license at https://github.com/yukkikou/mycoCirc and https://doi.org/10.5281/zenodo.20823962. The mycoCircAtlas database is available at http://116.62.58.192.

bioinformatics↗

bioRxiv2026

A p53-ΔNp73 signaling axis drives selective motor neuron degeneration in spinal muscular atrophy

Selective neuronal vulnerability is a hallmark of many neurodegenerative diseases, yet how ubiquitous genetic insults cause highly selective neuronal loss remains poorly understood. In spinal muscular atrophy (SMA), reduced SMN levels trigger degeneration of specific motor neuron pools. Although non-apoptotic, p53-mediated death pathways have been implicated, p53 is expressed in both vulnerable and resistant neurons, leaving the downstream determinants of selective vulnerability unresolved. Here, we identify a p53-{Delta}Np73 signaling axis as a previously unrecognized execution pathway driving motor neuron degeneration. Using differential transcriptional profiling of SMA motor neurons following pharmacological modulation of p53 activity, we uncover p73 as a critical downstream mediator of neuronal death. Notably, SMN deficiency induces cell-autonomous, p53-dependent expression of the {Delta}Np73 isoform selectively in vulnerable, but not resistant, motor neurons. {Delta}Np73 induction precisely parallels the spatial and temporal pattern of degeneration in mouse models and is also detected in motor neurons from SMA patients. Strikingly, despite its established role as a pro-survival antagonist of p53, depletion of {Delta}Np73 improves motor neuron survival and partially preserves neuromuscular junction integrity in SMA mice. These findings reveal a context-dependent, isoform-specific functional switch in p53 family signaling that redirects a canonical survival factor into a driver of neurodegeneration, identifying a novel molecular mechanism underlying selective neuronal vulnerability in SMA and a potential therapeutic target for neuroprotection.

neuroscience↗

bioRxiv2026

Mechano-Initiated PIEZO1-VEGFR2 Interaction Governs CD34+ Cell Differentiation and Repair in Arteriovenous Fistula

BackgroundEndothelial cell (EC) injury induced by disturbed flow drives neointimal hyperplasia in arteriovenous fistulas (AVFs), where CD34+ cell-mediated repair may be involved. PIEZO1 and VEGFR2 are important mechanosensors with critical role in maintaining endothelial function. However, whether PIEZO1 interacts with VEGFR2 during CD34+ cell differentiation to orchestrate the vascular repair remains unknown. MethodsAVF model was established in several mouse strains. Single cell RNA sequencing was performed for human and mouse samples. Cd34-CreERT2; R26-tdTomato; Piezo1flox/flox mice were used to investigate the effect of Piezo1 deletion on endothelial repair in AVFs. CD34-high human umbilical vein ECs (CD34high HUVECs) was sorted and exposed to different flow patterns to determine the role of shear stress in CD34high cell differentiation. Co-immunoprecipitation, proximal ligation assay and complementary approaches were performed to delineate mechanotransduction initiated by PIEZO1-VEGFR2 interaction. ResultsSingle cell RNA sequencing and immunostaining showed abundant CD34high cells in the vessel wall of AVFs in humans and animal models. Exposure of CD34high HUVECs to different flow patterns showed that laminar shear stress downregulated CD34 while upregulating VE-cadherin and claudin-5 expression. In contrast, oscillatory flow produced the opposite effects, indicating impaired endothelial maturation. PIEZO1 knockdown in CD34high HUVECs attenuated shear stress-induced endothelial marker expression. In Cd34 conditional Piezo1 knockout mouse model of AVF, we observed decreased number of CD34-derived cells, more compact cellular arrangement, and attenuated neointimal hyperplasia. Mechanistically, we found PIEZO1 interacts with VEGFR2, thereby mediating the distinct effects of laminar and oscillatory shear stress on AKT-FoxO1 axis, which critically regulates endothelial marker expression. Furthermore, pharmacological activation of AKT signaling in AVF mouse model enhanced CD34+ cell-mediated endothelial repair and attenuated neointimal hyperplasia. ConclusionPIEZO1-VEGFR2 complex-mediated mechanotransduction plays a key role in regulating CD34+ cell-derived endothelial repair in AVFs via AKT-FoxO1 axis. AKT activation enhances endothelial maturation, thereby attenuating neointimal hyperplasia in AVFs. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIIn arteriovenous fistulas (AVFs), abnormal shear stress induces endothelial cell injury, and the resulting neointimal hyperplasia is a major cause of anastomotic stenosis. C_LIO_LICD34 cells actively participate in vascular endothelial repair. C_LIO_LIPIEZO1 is a mechanoreceptor mediating endothelial sensing of hemodynamic shear stress, contributing to the maintenance of atheroprotective endothelial phenotype under laminar shear stress, whereas its activation induces pro-inflammatory effects under disturbed shear stress. C_LI What New Information Does This Article Contribute?O_LICD34 cells participate in repairing endothelial injury induced by abnormal shear stress in AVFs. PIEZO1 knockout in CD34+ cells improve endothelial repair and attenuates neointimal hyperplasia in AVF. C_LIO_LILaminar shear stress induces CD34 downregulation and upregulates VE-cadherin and claudin-5 expression in CD34-high human umbilical vein endothelial cells, whereas oscillatory shear stress upregulates CD34 expression and suppresses VE-cadherin and claudin-5 expression. C_LIO_LIMechano-stimuli lead to PIEZO1-VEGFR2 complex formation regulating CD34 cell-mediated endothelial repair through the downstream AKT-FoxO1 axis. C_LI Abnormal hemodynamic shear stress-induced endothelial injury initiates neointimal hyperplasia in AVFs. The present study identifies PIEZO1 as a key mechanosensor that regulates CD34+ cell-derived endothelial repair in response to distinct blood flow patterns. PIEZO1 promotes CD34+ cell differentiation into mature ECs for endothelial repair under laminar shear stress, whereas it disrupts the differentiation of CD34+ cells into mature endothelium under oscillatory shear stress. Mechanistically, a novel shear stress-sensing complex comprising PIEZO1 and VEGFR2 was identified in regulating flow-induced differentiation of CD34+ cells into mature ECs via the AKT-FoxO1 signaling axis, thereby controlling the expression of endothelial maturation markers VE-Cadherin and Claudin-5. These findings define a novel PIEZO1-VEGFR2 mechanotransduction axis in CD34+ cell-mediated endothelial repair and support AKT pathway activation as a potential therapeutic strategy against neointimal hyperplasia in AVFs.

cell biology↗

bioRxiv2026

Anthocyanin-associated cellular programs underlying terroir variation in Cabernet Sauvignon grape berry revealed by SEED-based deconvolution

Plant tissues consist of diverse cell populations that collectively contribute to development, metabolism, environmental responses, and phenotype formation. Although single-cell and single-nucleus RNA sequencing have greatly advanced the study of plant cellular heterogeneity, their application to large sample cohorts remains limited by cost, technical complexity, tissue dissociation constraints, and throughput. In contrast, bulk RNA-seq datasets have accumulated extensively across plant species, tissues, developmental stages, and environmental conditions, yet the celltype-level information embedded in these datasets remains difficult to resolve because plant-oriented deconvolution frameworks are still lacking. Existing deconvolution methods have largely been developed in mammalian systems and have not been systematically optimized for plant transcriptomic features, leaving their applicability under plant-specific constraints unclear. Here, we present SEED, an adaptive deconvolution framework optimized for plant transcriptomic data. SEED integrates candidate reference-template construction with seven deconvolution strategies and automatically identifies an optimal combination for a given dataset. In grapevine simulated benchmarking, SEED showed its clearest advantage under low-replication conditions and remained broadly competitive, rather than uniformly dominant, when larger pseudo-bulk sample sizes were evaluated. SEED further performed robustly in public Arabidopsis thaliana and Nicotiana tabacum datasets. Finally, we applied SEED to bulk RNA-seq data generated in this study from Vitis vinifera cv. Cabernet Sauvignon berries collected from Yinchuan and Yantai, identifying terroir-associated cell subtypes and coordinated celltype interaction patterns. Together, these results establish SEED as a practical framework for plant transcriptome deconvolution and provide a new tool for dissecting cellular heterogeneity associated with environmental adaptation and phenotype formation in plants.

bioinformatics↗

bioRxiv2026

Closed-loop auditory stimulation during sleep shapes cortical responses and memory consolidation depending on spindle timing

Sleep spindles contribute to memory consolidation, and acoustic stimulation during sleep can modulate spindle activity. However, it remains unclear whether these effects depend on the timing of stimulation relative to the spindle cycle. Using closed-loop spindle detection, we delivered four variants of pink noise either during ongoing spindles or shortly after spindle offset. In Experiment 1, stimulation delivered during a spindle prolonged its duration, whereas stimulation applied shortly after spindle offset, i.e., within the refractory period, delayed the onset of the subsequent spindle. This pattern was consistent across all sound variants, indicating that the stimulation timing, rather than acoustic properties, drove the observed effects. Experiment 2 examined whether post-spindle stimulation influences memory consolidation. Relative to a no-stimulation nap, post-spindle stimulation reduced post-nap deterioration in motor sequence accuracy but did not significantly affect word-pair recall. EEG analyses revealed that stimulation elicited widespread slow oscillation activity without triggering new spindles, demonstrating that cortical processing of external input persists even during the refractory period. Notably, the motor benefit was greatest in participants with lower spindle density during the baseline adaptation nap. Together, these findings challenge the notion that the post-spindle refractory period is a functionally silent interval. Instead, this period remains receptive to external input, capable of eliciting cortical activity and supporting motor memory consolidation even in the absence of new spindle generation.

neuroscience↗

bioRxiv2026

Flytrap-Inspired Mesh-Trap Bioelectronics for Full Spherical Electrophysiological Interrogation of 3D Tissues

Three-dimensional (3D) in vitro tissue models are emerging as powerful platforms for studying development, disease, and therapeutic responses, where close monitoring of electrophysiological activity is essential. However, existing probing methods remain limited in accessibility or spatiotemporal resolution for comprehensive electrophysiological mapping of suspended 3D tissues that closely mimic the native environments. Here we introduce a Venus flytrap-inspired bioelectronic mesh system that enables the full spherical enclosure of 3D tissues in a suspended configuration. The system consists of two hemispherical meshes that envelop the tissue, constructed from highly flexible, stretchable, cell-scale ribbons interconnected into a tissue-compliant network with integrated recording electrode arrays. This architecture enables intimate, conformal tissue integration and supports stable electrophysiological recordings over 300 days. The high-resolution recordings allow precise tracking of local dynamics and correlated global signaling, enabling comprehensive assessment of tissue development as well as detailed evaluation of drug responses for disease modeling. Beyond single tissues, the mesh architecture is extended to fully enclose assembloids composed of multiple tissues, enabling characterization of cross-tissue signaling relevant to advanced heterogenous tissue modeling. Furthermore, the system is translated into array-based platforms, demonstrated by a 4x4 array integrating 1024 electrodes, for high-throughput tissue sampling and cross-study analysis. The developed bioelectronic system and integration method provide a broadly applicable platform to advance electrophysiological studies across diverse tissues and organoids.

bioengineering↗

bioRxiv2026

WTAP-mediated epitranscriptomic program in alveolar macrophages confers prolonged protection against postinfluenza bacterial pneumonia

Secondary bacterial infections remain an intractable problem of seasonal influenza, primarily due to the depletion and defunctionalization of alveolar macrophages (AMs). Here, we described that N6-methyladenosine (m6A), the most prevalent RNA modification in eukaryotes, critically orchestrates trained immunity (TRIM) establishment in AMs. Influenza A virus (IAV)-trained AMs maintained low Wilms tumor 1-associated protein (WTAP) expression and reduced global m6A deposition for over two months. Mechanistically, this IAV-induced m6A decrease promotes TRIM by enhancing the RNA stability of phagocytic and metabolic genes, thereby boosting antibacterial function. Mimicking this m6A reduction pharmacologically or genetically recapitulates the IAV-trained TRIM phenotype, which improves phagocytosis and protects mice from secondary infection. Clinically, elevated WTAP in AMs correlates with impaired phagocytosis and disease severity in COVID-19 and COPD. These findings for the first time unveil how respiratory virus infection shapes AM TRIM via epitranscriptomic reprogramming, and offer prospective strategies for the prevention and treatment of post-viral bacterial complications.

immunology↗

bioRxiv2026

cGAS bends unpaired DNA to form an unconventional structure that hyperactivates the innate immune response

cGAS is a pattern-recognition receptor for dsDNA and forms 2cGAS:2DNA dimers followed by oligomerization into phase-separated condensates when fully-complementary DNA is studied. However, many DNAs are not fully complementary. We report that DNA with unpaired regions such as those found during transcription, recombination or replication (designated as bubble-DNA, Bu-DNA) causes cGAS hyper-activation. Hyperactivation is observed by Bu-DNA embedded in linear DNA, circular DNA, plasmid DNA and mitochondria DNA. Bu-DNA binds significantly more tightly to the cGAS catalytic domain than paired-DNA but suppresses condensation. Cryo-EM and single-molecule FRET reveal that cGAS forms 2cGAS:1DNA complexes by bending Bu-DNA into a V-shape using the unpaired region as a hinge, limiting its oligomeric state. This uncovers a novel mode of cGAS activation attributed to pattern diversity within pattern ligands.

immunology↗

bioRxiv2026

BiomniBench: Process-level Evaluation of LLM Agents for Real-world Biomedical Research

LLM agents now perform real biomedical research, but evaluating them rigorously is hard. Outcome-only benchmarks fail in two ways. First, a correct final answer can come from memorization, reward hacking, or wrong reasoning that produces the right number by chance. Second, valid alternative analyses are marked wrong simply because they differ from the reference. We introduce BiomniBench, a process-level evaluation framework that scores the full agent trajectory against expert-designed, task-specific rubrics. Our first release, BiomniBench-DA, contains 100 data-analysis tasks across 17 task types, 5 disease areas, and a general-biology category, each based on a paper from journals such as Nature, Cell, and Science and co-developed with an original author or a domain expert. Benchmarking frontier and open-weight models across four agent harnesses reveals three findings. Frontier and open-weight bases cluster within a few points of each other, with substantial headroom for all models. The agent harness shifts scores by more than the gap between successive model generations. Agents reliably ground claims in real sources yet consistently fall short on method selection, biological interpretation, and scientific reasoning. BiomniBench is the first process-level benchmark for LLM agents in biomedical research, providing the dimension-level diagnostics that outcome scoring cannot. Datasethuggingface.co/datasets/phylobio/BiomniBench-DA

bioinformatics↗

bioRxiv2026

High-throughput CRISPR live-cell imaging of low-frequency chromosomal events quantifies the latent efficiency of chromosome engineering

Abstract/SummaryQuantifying low-frequency chromosomal alterations in living cell populations at early stages is essential in many fields including cancer studies and chromosome engineering, yet selection-based readouts impose delays and can lose fragile positives before readout, biasing frequency estimates; CRISPR imaging rarely reports detection limits at 10^-4. Here, we developed High-throughput CRISPR Imaging (Hi-CRI), integrating engineered dCas9-sgRNA ribonucleoprotein (RNP) labeling, suppression of nonspecific aggregates via metabolic modulation and protease treatment, high-speed volumetric imaging by oblique plane microscopy, GPU-accelerated image analysis, and an explicit error-controlled detection-limit framework. Using per-cell signal-to-noise ratio calling, Hi-CRI achieves a 0.01% detection limit for target-positive cell fractions. In microcell-mediated chromosome transfer of a mouse artificial chromosome (MAC) into HT1080 recipients, Hi-CRI measured 0.03% MAC-positive cells among 184,235 recipients at day 1 post-fusion, versus 0.0007% by antibiotic-selection-based clonogenic assay at day 8 post-fusion, consistent with substantial loss before readout (pre-readout attrition). Hi-CRI enables viability-preserving, selection-independent quantification of low-frequency chromosomal states. TeaserRare chromosome events can be counted in living cells by high-throughput CRISPR imaging before selection hides them.

bioengineering↗

bioRxiv2026

Decoding Smell from Receptor Structure

Olfaction enables animals to detect and discriminate a vast array of chemicals, yet how odorant receptors (ORs) encode ligand selectivity remains unclear. Although recent advances in protein structure prediction have expanded access to OR structures, linking these to function at scale has been challenging. Here, we combined AlphaFold3-predicted receptor structures with protein language model embeddings and in vivo pS6-IP-Seq measurements of olfactory sensory neuron activation across a chemically diverse odor panel to train a deep learning model of OR-ligand interactions. The resulting framework predicts receptor responses, organizes receptors by functional similarity independent of sequence, and identifies structural determinants of ligand selectivity. These findings establish a structure-based map of OR function and provide a foundation for predictive and interpretable models of olfactory coding.

molecular biology↗