Biology subjects

Jiang, P.

Publications and source records attributed to Jiang, P..

At least 19 recordsLinked to original sources

bioRxiv2026

U6 promoters in Ulva prolifera enable dual small-RNA/mRNA transcription and vector-based CRISPR-Cas9 genome editing

For establishing vector-based gene editing in the green-tide-forming alga Ulva prolifera, development of endogenous RNA polymerase III (Pol III) promoters is a prerequisite to drive single-guide RNA (sgRNA) transcription. To meet the need, the promoters of U6 snRNA genes in U. prolifera (UpU6) were identified, cloned, and functionally characterized. Results showed that three UpU6 copies shared identical sequences, with divergent 5' upstream sequences containing a positionally conserved TATA box but lacking the USE element typical of seed plants. All three UpU6 promoters were shown to be capable of driving not only small RNA transcription but also protein-coding gene expression in U. prolifera, exhibiting the dual transcriptional activity. Unexpectedly, all three UpU6 promoters also supported GUS reporter gene expression in Agrobacterium, representing the first demonstration of U6 promoter activity in a prokaryotic system. The results of the gene-editing experiment showed that, all three UpU6 promoters supported vector-based CRISPR-Cas9 targeting of the APT gene, yielding mutant strains. The mutation-positive fraction among resistant thalli was 92.3% (48/52), and the editing frequency calculated from the estimated starting cell number averaged 3.26 x 10- across the three UpU6 promoters and did not differ significantly among them. In the mutants, high-frequency occurrences of base substitutions (45.5%) and insertions of long Mutator-like element (MULE) (18.2%) were detected, highlighting a potential association between endogenous DNA transposon insertion and CRISPR-Cas9-mediated gene editing. These findings expanded understanding of eukaryotic U6 promoter functionality and enrich the toolkit for vector-based CRISPR-Cas9 genome editing in U. prolifera.

molecular biology↗

bioRxiv2026

Hierarchical distribution matching enables comprehensive characterization of common and condition-specific cell niches in spatial omics data

Deciphering cell niches in complex tissues is essential for understanding tissue structure and disease. Recent advances in spatial omics have enabled subcellular resolution and accurate cell identity mapping. However, robust delineation of cell niches and disease-associated spatial patterns remains difficult. We introduce Harmonics, a novel computational framework that systematically identifies both common and condition-specific cell niches from spatial omics data through hierarchical distribution matching. Harmonics also includes a suite of downstream modules that facilitate comprehensive niche characterization. We demonstrate its scalability, accuracy and generalizability across datasets spanning diverse species, tissues, diseases, spatial modalities, and technological platforms. For condition-agnostic datasets, Harmonics outperforms baseline methods in both accuracy and robustness, and further demonstrates the capability to resolve niche structures at finer granularity. Across diverse diseases including pulmonary fibrosis, triple-negative breast cancer, and colorectal cancer, Harmonics enables precise identification of condition-specific niches and reveals disease-associated dynamics, subtype-specific spatial patterns, and structured immune architectures. We envision Harmonics as a practical and versatile tool for spatial niche analysis that can be applied across a wide range of biological contexts and seamlessly integrated with existing spatial omics workflows.

bioinformatics↗

bioRxiv2026

Mutation spectra across 3,034 Saccharomyces cerevisiae genomes distinguish the Georgian Wine population

Mutation spectra vary among populations, and a comprehensive view of this variation requires broad sampling and fine-scale population resolution. Here, we profile mutation spectra from single-nucleotide polymorphisms and small insertions and deletions in a uniformly processed collection of 3,034 globally sampled Saccharomyces cerevisiae genomes, and an extended dataset including the previously sampled global 1,011-genome collection. Major mutation spectrum patterns reported from the 1,011 genomes remain evident in the extended dataset, including the pronounced mutation-spectrum differentiation of African Beer strains. At finer population resolution, we identify additional variation among wine-associated populations, including a Georgian Wine-associated signal that is strongest among rare variants and is therefore consistent with a comparatively recent change in mutation processes. We further apply a sequence-context-aware classification to characterize small-indel profiles across the 3,034 natural yeast genomes. Together, our analyses show that expanded sampling and refined population assignments provide a more comprehensive view of mutation-spectrum variation within S. cerevisiae.

evolutionary biology↗

bioRxiv2026

TxCyto: A machine learning framework for estimating cytokine activity from whole transcriptome

Cytokines are critical mediators of intercellular communication, and a comprehensive characterization of their activity is essential for understanding health and disease. Existing tools to infer cytokine activity rely on experimental measurements. However, such measurements are available only for a small minority (43) of cytokines, and moreover, cytokine activity and response are highly context-specific, making a comprehensive experimental profiling across tissues, disease states, and biological contexts impractical. To address this gap, we developed TxCyto - a deep learning-based framework that infers the activity of cytokines, and more broadly of the tumor secretome, directly from the whole transcriptome profile of a sample. Trained on pan-cancer TCGA tumor transcriptomes, TxCyto was extensively validated in multiple independent datasets, including cytokine perturbation experiments. Across multiple cancer immunotherapy cohorts, TxCyto identified cytokines whose predicted activity was associated with therapeutic response. Furthermore, in spatial transcriptomic data for Liver cancer, TxCyto discovered spatial niches associated with response to immunotherapy. Overall, we develop a machine learning tool -TxCyto, for predicting the activity of 645 cytokines and tumor secretome from readily available whole transcriptomes. The TxCyto framework is generally applicable to other classes of regulatory molecules and TxCyto code base, and the tools are provided at https://github.com/Rahulncbs/TxCyto.

systems biology↗

bioRxiv2026

Distinct Spatial Immune Architectures in Tumor and Tumor-Adjacent Tissues of Early-Stage Non-Small Cell Lung Cancer

Background: Lung cancer remains the leading cause of cancer-related deaths in the United States with over 124,000 estimated deaths for 2026. Previous studies have found that tumor-adjacent lung tissues may provide additional insight into the immune microenvironment of early-stage NSCLC. Methods: Multiplex immunofluorescence (mIF) imaging was performed on 192 tissues from 101 early-stage non-small cell lung cancer patients including 91 matched tumor-adjacent pairs, using three mIF panels. Spatial analyses were performed to identify distinctions between tissues and identify associations with clinical and genomic features. Results: Tumor tissue showed significantly higher densities of T cells, macrophages, B cells, and memory/regulatory populations than adjacent tissue (p<0.001). Tumors exhibited greater spatial heterogeneity, with higher prevalence of spatial patterning (47.7% vs. 31.2%) and more consistently localized organization, whereas adjacent tissue showed stronger individual-cell clustering. Pairwise colocalization (Ripley's L-cross) revealed selective spatial segregation in tumors (including B-cells from memory/regulatory cells and among cytotoxic T-cell subsets) and reduced immune proximity to malignant cells relative to the strong immune-epithelial association in adjacent tissue. Spatial features were linked to genomic features or patient outcomes: tumor neoantigen burden exhibited a positive association with CD3+ T cells in the tumor, while colocalization between CD45RO+CD57+GZMB+ cells and CD57+GZMB+ cells was negatively associated with overall survival outside the tumor. Conclusion: Tumor and adjacent tissues harbor distinct spatial immune architectures, with spatial features displaying associations with genomic features or patient outcomes. These findings highlight immune microenvironment reorganization and the importance of incorporating spatial context from both compartments into risk assessment in NSCLC.

immunology↗

bioRxiv2026

Diffusion MR Microscopy of the Human Hippocampus at 50 μm Resolution at 14.1 T for 3D Virtual Histology

Bridging the gap between macroscopic neuroimaging and microscopic histology remains a challenge in neuroscience. Here, we present a technical feasibility study of diffusion MR microscopy (dMRM) in the ex vivo human hippocampus using a 14.1 T ultrahigh-field MRI system. Mid-hippocampal blocks from control and Alzheimers disease (AD) patients were acquired at 50 x 50 x 100 {micro}m3, representing, to our knowledge, the highest resolution reported for human brain diffusion MRI. At a spatial scale approaching cellular dimensions, dMRM maps and tractography showed close correspondence with immunohistological markers of axons and dendrites. The acquired data delineated six hippocampal laminae, distinguished the inner and outer molecular layers, and preserved short, lamina-specific trajectories that became attenuated or blurred at 100 {micro}m resolution. Tractography further depicted the major components of the hippocampal tri-synaptic circuit--the perforant path, mossy fibers, and Schaffer collaterals in 3D. In the AD specimen, dMRM revealed reduced laminar contrast, local discontinuities, and altered radial and tangential fibers that were paralleled by pathological staining. With the 3D nondestructive characterization of human brain microstructure and circuitry, ex vivo dMRM showed its potential toward the goal of 3D virtual histology.

neuroscience↗

bioRxiv2026

CellART: a unified framework for extracting single-cell information from high-resolution spatial transcriptomics

Understanding how different cell types assemble into tissues and organs, as well as how they interact to transmit and receive biological signals, is essential for advancing biomedical and biological research. Recent advancements in spatial transcriptomics (ST) technologies have opened new avenues for investigating biological systems by achieving subcellular spatial resolution. Since cells are the fundamental units of life, extracting single-cell information from high-resolution ST data is crucial. However, existing ST platforms often capture sparse transcript counts per spot or measure only a limited number of genes, complicating the extraction of comprehensive single-cell information. In this study, we introduce CellART, a unified framework designed to extract single-cell information across diverse high-resolution ST platforms, including VisiumHD, Xenium, MERFISH, and Stereo-seq. By leveraging multimodal data, such as staining images, spatial transcriptomics data, and single-cell RNA sequencing references, CellART simultaneously performs cell segmentation and cell type annotation through a seamless integration of deep learning and probabilistic modeling. We demonstrate the efficiency, generalizability, and robustness of CellART across various high-resolution spatial transcriptomics platforms, capable of processing datasets containing millions of spots. Comprehensive experiments validate the biological relevance and accuracy of the recovered cellular information within spatial configurations. Notably, we highlight the utility of CellART in breast and colorectal cancer datasets, showcasing its ability to fully leverage high-resolution ST data. By enhancing cellular resolution, CellART facilitates the identification of transient cancer cell states and immune cell subtypes. Furthermore, CellART enables investigations into cancer-immune cell communication, uncovering both established interactions and novel ligand-receptor pairs. The outputs of CellART are compatible with widely used community tools, facilitating a variety of downstream analyses.

bioinformatics↗

bioRxiv2026

HER2 mutation-derived neoantigens in NSCLC as actionable targets for TCR therapy

HER2 mutations are oncogenic drivers in 1-6% of non-small cell lung cancers (NSCLC), but therapeutic resistance limits the durability of current HER2-targeted treatments. Here, we identify T-cell receptors (TCRs) targeting recurrent HER2 hotspot mutations as a potential immunotherapeutic strategy for HER2-mutant NSCLC. Using neoepitope prediction and antigen-specific T-cell enrichment, we isolated HLA-A*02:01restricted TCRs recognizing HER2 A775insYVMA, S310F, and G776delinsVC mutations, collectively covering approximately 60% of HER2-mutant NSCLC. These TCRs selectively recognized mutant HER2 epitopes without detectable wild-type reactivity and some displayed cross-recognition of related hotspot variants, expanding the spectrum of targetable tumors. The G776delinsVC-specific TCR also exhibited co-receptorindependent activity showcased by its ability to activate CD4+ T cells. Importantly, timelapse single-cell flow cytometry analyses demonstrated that TCR-engineered T cells repeatedly reacquired activated polyfunctional states following serial antigen stimulation, while serial tumor rechallenge assays confirmed sustained cytotoxic activity across multiple rounds of tumor killing. These findings identify recurrent HER2 mutations as shared immunotherapeutic targets and provide a foundation for the development of TCR-based therapies for HER2-mutant NSCLC.

immunology↗

bioRxiv2026

Bidirectional hybridization between Ulva prolifera and U. linza (Ulvophyceae, Chlorophyta): Evidence for compatibility and paternal chloroplast inheritance

Ulva prolifera and U. linza are closely related species, with abundant adult thalli and reproductive cells co-occurring extensively in time and space during the Yellow Sea green tides. Elucidating their hybridization compatibility is crucial for species delimitation, assessing interspecific gene flow, and evaluating the ecological impacts of green tides. Previous studies suggested asymmetric gamete compatibility (only U. prolifera mt+ x U. linza mt-), but lacked sex-linked markers to reliably identify hybrid diploids and their reproductive modes, and did not examine chloroplast inheritance. Here, we performed bidirectional crosses using sexual strains of different geographic origins from both parents, with sex-linked markers to quantify progeny genotypes, examine fertility and reproduction pathway of F1 hybrids, and trace chloroplast inheritance using the species-specific petB marker. Our results showed that: (1) F1 hybrids were obtained in both cross directions, with significantly higher frequency in the direct cross (U. linza mt+ x U. prolifera mt-), indicating no complete reproductive isolation in either direction; the biased compatibility likely reflected genetic background differences among the limited strain combinations in a single study. (2) A considerable number of germinated progeny arose from parthenogenesis of parental gametes. (3) F1 hybrids from both crosses could undergo meiosis to form gametes and develop into gametophytes; additionally, F1 from the reciprocal cross produced diploid spores for asexual reproduction, suggesting meiotic disturbance. (4) Chloroplasts were maternally inherited in selfing of U. prolifera parent, but in all F1 hybrids they were paternally inherited, indicating a potential reversal of the inheritance pattern due to interspecific hybridization. These findings provided new insights into the potential for genetic exchange between U. prolifera and U. linza.

genetics↗

bioRxiv2026

A rapid sporozoite viability assay identifies anti-Cryptosporidium parvum leads and targetable enzymatic activities in the invasive stage

Current phenotypic screens for anti-Cryptosporidium compounds typically quantify intracellular parasite growth in host cell cultures after two days of infection. Here, we developed a rapid, host cell-free phenotypic assay that directly measures compound-induced loss of viability in excysted Cryptosporidium parvum sporozoites, the invasive stage that initiates infection. We first compared qRT-PCR, luminescence ATP, and resazurin fluorescence readouts for detecting viable sporozoites. The luminescence ATP assay provided the best balance of linear dynamic range, assay time, parasite input, and cost, and was therefore adapted for high-throughput screening. Screening 5,000 bioactive compounds at 40 M identified 28 primary hits with [≥]50% inhibition of sporozoite viability, including 14 with >60% inhibition. Secondary screening of these 14 compounds at 4 M identified five hits retaining >50% inhibition: ZL0420, sulbactam, abexinostat, kojic acid, and SIB-1757. All five showed submicromolar activity against free sporozoites, with EC50 values of 0.073-0.311 M. Four compounds, abexinostat, ZL0420, SIB-1757, and sulbactam, also inhibited intracellular parasite growth in vitro, with EC50 values of 0.316-11.87 M and selectivity indices from >17 to >107. In an IFN-{gamma}-knockout mouse model, these four compounds reduced oocyst shedding over the 35-day experiment by 53.7-79.0% based on area-under-the-curve analysis and improved body-weight trajectories and ileal histopathology. Biochemical assays further showed that abexinostat inhibited native parasite HDAC activity at low nanomolar concentrations, while sulbactam inhibited a {beta}-lactamase-like activity in sporozoite lysates. These findings establish sporozoite viability as a rapid screening endpoint and identify anti-Cryptosporidium leads associated with targetable enzymatic activities in the invasive stage. Author summaryCryptosporidium parvum is a major cause of diarrheal disease in humans and young animals, but treatment options remain limited. Most laboratory screens for new drugs against this parasite require infection of host cells and measurement of parasite growth after one or more days. We developed a faster approach that tests whether compounds can directly damage freshly excysted sporozoites -- the parasite stage that first invades intestinal cells -- or reduce their viability. This assay can be completed within a few hours and does not require host cells. Using this approach, we screened 5,000 bioactive compounds and identified several molecules that rapidly reduced sporozoite viability. Four of these compounds also inhibited parasite growth in cell culture and reduced infection severity in a mouse model, as measured by parasite shedding, body-weight changes, and intestinal pathology. We further showed that one compound inhibits parasite histone deacetylase activity, while another inhibits a {beta}-lactamase-like activity present in sporozoites. Our study provides a rapid screening strategy and highlights vulnerable biological activities in the invasive stage of C. parvum.

microbiology↗

bioRxiv2026

Conserved Transcriptomic Signatures of Sirt6 Activity: A Cross-Species RNA-seq Meta-analysis

The NAD+-dependent histone deacetylase Sirt6 regulates transcription of multiple classes of genes, including those involved in metabolism, immune response, oxidative stress response, and development. Defining the Sirt6-regulated transcriptome is relevant to understanding the various important physiological roles of Sirt6, such as extending lifespan, maintaining metabolic health, and tumor suppression. Numerous studies have identified Sirt6 target genes, using both targeted and genome-wide approaches; however, consensus is limited and there has yet to be a systematic analysis of gene expression changes induced by altering Sirt6 levels. In the present study, we conducted a meta-analysis of 19 mammalian RNA-seq datasets in which Sirt6 levels were perturbed (knockout, knockdown, or overexpression). Our analyses included Gene Set Enrichment Analysis, pathway analysis of differentially expressed genes, and identification of individual differentially expressed genes. Our analysis identified consistent gene expression changes associated with lowering Sirt6 levels, including increased expression of immune response and ribosomal protein genes and reduced expression of lipid oxidation and oxidative phosphorylation genes. Extracellular Matrix and E2F target genes also had consistently increased expression upon Sirt6 reduction, highlighting novel regulation by Sirt6. To determine the conservation of gene regulation by Sirt6, we performed additional RNA-Seq meta-analysis on tissues from Drosophila melanogaster with Sirt6 deletion and overexpression. The fly datasets produced similar results to the mammal results, except for lipid oxidation genes, which were found to increase in Sirt6-low conditions. These results provide consensus about conserved and novel pathways transcriptionally regulated by Sirt6.

genomics↗

bioRxiv2026

Coupled Transcriptomic and ECM-Mechanical Remodeling Reveal Mechanotransductive Pathways in Spinal Cord Injury

Spinal cord injury (SCI) leads to the formation of a chronic scar composed of glial and fibrotic components that severely restrict neural regeneration and functional recovery. While the scar composition has been widely studied, the spatiotemporal evolution of tissue mechanics and the role it plays in regulating the post-injury responses remain poorly understood. Here we present an integrated mechanobiological and multi-omics analysis of spinal cord remodeling following a severe thoracic contusion injury. Using nanoindentation and viscoelasticity measurements taken via atomic force microscopy (AFM), we demonstrate that SCI induces a dynamic mechanical response characterized by rapid tissue softening during the acute phase reaching a minimum at one-month post-injury, followed by progressive stiffening associated with chronic scar maturation at six months. Bulk RNA sequencing reveals that early mechanical softening coincides with strong activation of inflammatory and matrix-degrading pathways whereas chronic stiffening correlates with upregulation of collagen synthesis, extracellular matrix (ECM) organization and fibrotic remodeling pathways. Concurrently, mechanotransduction regulators exhibit temporally coordinated activation, indicating that cells dynamically sense and respond to evolving mechanical cues. Viscoelastic analysis further shows that chronic scar tissue exhibited increased stiffness and prolonged relaxation dynamics, reflecting dense collagen deposition and proteoglycan accumulation that reinforces a mechanically restrictive microenvironment. Together, these findings establish that the post-injury scar represents a dynamic mechanobiological system in which the evolving tissue mechanics, viscoelasticity and mechanotransduction collectively regulate ECM remodeling, resulting in regenerative failure. This study provides a comprehensive mechanobiological framework for SCI progression and highlights the opportunities for mechanically informed therapeutic strategies aimed at modulating scar mechanics to promote tissue repair. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/736147v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@543cc4org.highwire.dtl.DTLVardef@6185c6org.highwire.dtl.DTLVardef@95c3ceorg.highwire.dtl.DTLVardef@6a12ea_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Modeling Prenatal Immune Activation in Human Brain Organoids Uncovers IL-6-Dependent Interneuron Dysmaturation

Prenatal inflammation has been associated with an increased likelihood of the child developing neurodevelopmental conditions, such as autism spectrum disorder (ASD). Several pro-inflammatory cytokines are significantly upregulated and play critical roles during immune activation, with interleukin-6 (IL-6) being particularly prominent. However, the specific impact of elevated IL-6 levels on human neural development remains to be elucidated. To address this, we established a human pluripotent stem cell-based forebrain organoid model enriched for multiple interneuron lineages, validated through immunohistochemistry and transcriptomic alignment with human fetal reference datasets. We showed IL-6 responsiveness via the activation of the JAK/STAT pathway and characterized downstream effects using bulk and single-nucleus RNA sequencing (RNA-seq). Bulk RNA-seq at the end of IL-6 exposure uncovered activation of inflammatory pathways, upregulation of MHC-I machinery, and early disruption of GABAergic signaling programs. Notably, single-nucleus RNA-sequencing performed one month after IL-6 withdrawal revealed a persistent inflammatory transcriptional signature across interneuron development, accompanied by accelerated progression through maturation stages and altered interneuron subtype output. Together, these findings demonstrate that transient prenatal IL-6 exposure is sufficient to reshape human interneuron fate specification and maturation trajectories, providing mechanistic insights into neuroimmune contributions to ASD.

neuroscience↗

bioRxiv2026

A suture-specific oocyst wall protein COWP4 is essential for excystation and infectivity, while COWP6 links wall architecture to host interaction in Cryptosporidium parvum

The oocyst of Cryptosporidium is a highly resilient transmission stage that protects sporozoites in the environment and mediates infection through a specialized opening known as the suture. While recent studies have identified Cryptosporidium oocyst wall proteins (COWPs) as structural components of the oocyst wall, the functional roles of individual COWPs and the molecular basis of suture biology remain poorly understood. Here, we performed a detailed characterization of two COWP family members, COWP4 and COWP6, combining immunolocalization, ultrastructural analysis, protein interaction assays, and genetic manipulation. We show that COWP4 is strictly localized to the oocyst suture, whereas COWP6 is distributed throughout the oocyst wall inner layer and enriched at the suture. COWP6 is additionally present in sporozoites and is secreted during parasite motility and host cell invasion, where it exhibits high-affinity binding to host cells. Structural analyses indicate that both proteins are cysteine-rich and likely form disulfide-stabilized architectures consistent with roles in wall assembly. Functional analyses reveal that COWP4 is essential for proper suture formation, excystation, and parasite infectivity, establishing the suture as a genetically defined gatekeeper for parasite transmission. In contrast, COWP6 functions as a multifunctional protein linking oocyst wall architecture to host interaction. We further demonstrate that COWP4 and COWP6 interact, suggesting coordinated assembly within the oocyst wall. Together, these findings provide a functional dissection of the Cryptosporidium oocyst suture and reveal distinct, non-redundant roles for individual COWPs. This work advances our understanding of oocyst wall biology and identifies COWP4 as an essential determinant of parasite transmission that may be targeted to disrupt the infectious cycle. Author summaryCryptosporidium is a major cause of diarrheal disease worldwide and is transmitted through environmentally resistant oocysts that protect infectious stages of the parasite. A defining feature of the oocyst is a specialized seam-like structure, called the suture, through which parasites exit to initiate infection. Although oocyst wall proteins (COWPs) have been identified, how individual proteins contribute to the structure and function of the oocyst wall, particularly the suture, has remained unclear. In this study, we investigated two oocyst wall proteins, COWP4 and COWP6, and uncovered distinct roles for each. We found that COWP4 is specifically localized to the suture and is essential for its proper formation, enabling parasites to exit the oocyst and establish infection. In contrast, COWP6 is distributed more broadly in the oocyst wall and also functions beyond it, being secreted during parasite movement and interacting with host cells. These findings reveal that the oocyst wall is composed of specialized proteins with non-redundant functions and identify the suture as a critical control point for parasite transmission. Understanding these mechanisms may help guide the development of new strategies to block infection by disrupting oocyst integrity or parasite release. HighlightsO_LICOWP4 is a suture-specific protein essential for oocyst excystation and infectivity C_LIO_LIGenetic disruption of COWP4 produces non-infectious oocysts with impaired viability C_LIO_LIThe oocyst suture is a genetically defined gatekeeper for parasite transmission C_LIO_LICOWP6 localizes to the wall inner layer and is enriched at the suture C_LIO_LICOWP6 is secreted by sporozoites and binds host cells with nanomolar affinity C_LIO_LI{middle dot} COWP4 and COWP6 directly interact, linking wall architecture to host interaction C_LI

microbiology↗

bioRxiv2026

Neurogenin-2 Reprograms Human Microglial Lineage Cells into Neurons In Vitro and in Chimeric Brains

Progressive neuronal loss is a hallmark of many neurological disorders, yet the adult human brain has a limited capacity for endogenous neuronal replacement. Direct neuronal reprogramming represents an alternative strategy for generating new neurons. Microglia, the brains resident immune cells, are uniquely positioned as candidate cellular substrates due to their abundance, self-renewal capacity, high motility, and rapid recruitment to sites of injury. Here, using live-cell imaging and electrophysiological recordings, we show that human pluripotent stem cell (hPSC)-derived primitive macrophage progenitors (PMPs) and their microglial derivatives exhibit neuronal reprogramming competence. Inducible expression of NEUROG2 in hPSC-derived PMPs drives acquisition of neuronal morphology, sequential expression of early and mature neuronal markers, organization of synaptic proteins, and functional excitability characterized by action potential firing. Single-nucleus RNA sequencing reveals a continuous, directionally ordered reprogramming trajectory marked by suppression of myeloid transcriptional programs, progression through intermediate remodeling states, and progressive activation of neuronal gene regulatory networks, consistent with a regulated lineage conversion rather than partial identity switching. Using a xenotransplantation-based human microglia chimeric brain model, we further demonstrate that inducible NEUROG2 expression reprograms donor-derived human microglia toward a neuronal identity in vivo. Together, these findings establish human microglial lineage cells as a previously unexplored substrate for neuronal reprogramming, providing a conceptual framework for microglia-based strategies aimed at neuronal replacement and neural repair.

neuroscience↗

bioRxiv2026

Anticipatory metabolic reprogramming distinguishes caloric restriction from fasting-refeeding cycles

Interest in fasting-based dietary interventions to improve metabolic health is growing. Caloric restriction (CR) with one meal per day includes an extended fasting component that contributes to its metabolic and longevity benefits, yet the specific role of fasting within CR remains unclear. Here, we compared mice under CR with those subjected to a fasting-refeeding-fasting (FRF) regimen while controlling pre-fasting food intake and fasting duration. Simultaneous comparison of diet induced changes in plasma insulin and free fatty acids, hepatic mTOR signaling and ketogenesis, total body metabolic rhythms with kinetics of food digestion suggested that gastric emptying served as a primary metabolic trigger in acute fasting. In contrast, in CR, fasting responses were actively regulated and suggested anticipatory mechanisms. At the transcriptomic level, CR enhanced circadian rhythmicity and metabolic gene coordination, whereas FRF disrupted it. In agreement with the expression data, CR improves glucose and fatty acid metabolism while fasting leads to glucose intolerance and fat accumulation in the liver induced glucose intolerance and hepatic steatosis. These findings reveal that CR engages clock-aligned, anticipatory metabolic control, while fasting-refeeding cycles rely on direct nutrient cues. This mechanistic distinction between active and passive metabolic regulation may underlie the superior metabolic and longevity outcomes of caloric restriction.

molecular biology↗

bioRxiv2026

VC-RDAgent: An efficient rare disease diagnosis agent via virtual case construction informed by hybrid statistical-metric and hyperbolic-semantic prioritization

While Large Language Models (LLMs) have shown promise in clinical decision support, current Retrieval-Augmented Generation (RAG) paradigms face a fundamental bottleneck in rare disease diagnosis: the scarcity, privacy restrictions, and extreme heterogeneity of real-world patient records. This reliance on sparse or inaccessible data leads to a severe "retrieval mismatch," where the lack of high-quality reference cases causes diagnostic performance to degrade sharply. To break this deadlock, we propose VC-RDAgent, a privacy-preserving and offline-capable framework that decouples diagnostic reasoning from sensitive real-world records by synthesizing virtual standardized cases. The system is powered by VC-Ranker, a multi-dimensional engine that integrates statistical-metric measures with hyperbolic-semantic embeddings to capture deep hierarchical ontology relationships. This approach allows for the dynamic generation of high-fidelity virtual references directly from authoritative knowledge bases. Extensive benchmarking across four diverse datasets demonstrates that VC-RDAgent effectively functions as a "performance equalizer." It boosts average Top-1 hit rates by 8.7% to 85.9% over zero-case baselines, enabling lightweight open-source models to rival frontier commercial systems. Notably, VC-Ranker alone achieved an aggregate Top-10 hit rate of 0.819, outperforming prior state-of-the-art methods by 6%. By eliminating the dependency on real-time web retrieval and private case sharing, VC-RDAgent provides a scalable, robust, and clinically deployable solution to shorten the diagnostic odyssey, which is made accessible through an intuitive, chat-based web application https://rarellm.service.bio-it.tech/rdagent/.

bioinformatics↗

bioRxiv2026

A Multi-tissue Transcriptomic-Metabolomic Map Linking Maternal High-Fiber Diet to Reduced Offspring Type 2 Diabetes

BackgroundEarly-life nutritional exposures are increasingly recognized as critical determinants of long-term metabolic health, yet the molecular mechanisms linking maternal diet to offspring type 2 diabetes susceptibility remain incompletely understood. Experimental models are essential to disentangle maternal dietary effects from later-life metabolic influences. MethodsUsing the Nile rat, a genetically heterogeneous model of diet-induced diabetes, we quantified the impact of maternal high-fiber diet on offspring diabetes incidence using sex-stratified time-to-event analyses in 762 offspring. To identify molecular mediators, we performed transcriptomic profiling across 13 offspring tissues, independently contrasting maternal diet exposure and early-onset diabetes status. Overlapping differentially expressed genes were prioritized and evaluated for cardiometabolic associations in human whole-blood transcriptomic data from the GENE-FORECAST cohort. Untargeted plasma metabolomics was integrated to identify circulating metabolites associated with candidate genes. ResultsOffspring born to dams maintained on a high-fiber diet exhibited a markedly reduced risk of developing type 2 diabetes, with approximately 70% lower hazard of diabetes onset in both males and females compared with offspring from regular chow-fed dams. Multi-tissue transcriptomic analyses identified 147 genes differentially expressed in association with both maternal diet and early-onset diabetes, with most effects being tissue-specific. Asnsd1 uniquely showed consistent regulation across the aorta, brown adipose tissue, and skeletal muscle, with higher expression in offspring exposed to a high-fiber maternal diet and lower expression in offspring with early-onset diabetes. In human whole-blood transcriptomic data, ASNSD1 expression was significantly associated with blood pressure-related cardiometabolic traits, including hypertension, systolic blood pressure, and mean arterial pressure. In the animal model, circulating succinic acid was positively correlated with Asnsd1 expression in the aorta but not in other tissues. ConclusionsThis study provides a multi-tissue transcriptomic-metabolomic framework linking maternal high-fiber diet to reduced offspring type 2 diabetes risk. The findings identify ASNSD1 as a maternal diet-sensitive gene associated with diabetes susceptibility across multiple tissues and with cardiometabolic traits in humans, while highlighting tissue-specific relationships between gene expression and circulating metabolites. Together, these results offer mechanistic insight into how early-life nutrition can durably influence diabetes risk across the life course.

developmental biology↗