Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Relapse-founding cancer persister cells in follicular lymphoma

Follicular lymphoma (FL) is an incurable, prototypical relapse-remitting cancer, implying the existence of therapy-persistent cells that survive frontline treatment and seed disease recurrence1-3. However, these persister cells remain difficult to study directly in patients because immediate post-treatment sampling is ethically and practically challenging. Using a genetically defined mouse model that allows sampling of persistent cells immediately after frontline R-CHOP therapy, we prospectively isolate and functionally define relapse-founding cancer persister cells (CPC). The CPC is an IgM memory-like B-cell with high germinal center re-entry capacity. This state represents a discrete component of a heterogeneous residual pool indicating that residual disease is polytypic and that relapse potential may depend on which cells persist rather than on residual tumour burden alone. By integrating mouse CPC with human FL datasets, we show that an analogous transcriptional programme is detectable at diagnosis and is enriched in patients with inferior clinical outcome across independent cohorts4,5. These findings support the concept that relapse risk is linked to a conserved, genotype-agnostic CPC programme present before therapy. To explore therapeutic vulnerabilities, we developed a scalable in-vitro platform that models the CPC-like state and used it to identify sensitivity to histone deacetylase inhibition. Romidepsin and panobinostat killed CPC-like cells in-vitro, and decreased therapy-persistent cells after R-CHOP treatment in-vivo and in patient-derived organoids. Together, these data define a tractable CPC state in FL, with a validated clinical readout and an immediately testable therapeutic entry point, opening CPC-directed strategies for durable FL control.

cancer biology↗

bioRxiv2026

Developmental programming of adrenal chromaffin cell connexin plasticity by neonatal maternal separation

Adrenal chromaffin cells are key effectors of the sympathoadrenal response and play a central role in the organisms adaptation to environmental and physiological challenges. While cholinergic and pituitary adenylate cyclase-activating polypeptide (PACAP)-dependent mechanisms have long been recognized as major regulators of catecholamine secretion, increasing evidence indicates that connexin-mediated gap junctional communication provides an additional and highly dynamic level of control. Whether early-life experience modifies the adult capacity of chromaffin-cell networks to undergo stress-induced connexin remodeling remains unclear. Here, we examined adrenal medullary connexin expression in adult rats exposed to neonatal maternal separation (MS; 3 h daily, postnatal days 2-15) and later challenged with an 8-day unpredictable mild stress (UMS) protocol. Under basal adult conditions, MS did not produce an overt change in adrenal medullary Cx36 or Cx43 immunoreactivity relative to animal-facility-reared controls. In contrast, UMS increased connexin immunoreactivity in the adrenal medulla, and this response was amplified in animals with a history of MS. MS+UMS animals also displayed enhanced corticosterone responses to acute restraint stress. These findings suggest that neonatal MS does not impose a constitutively altered adult chromaffin-cell phenotype, but instead primes the future stress responsiveness of adrenal medullary connexin remodeling. We propose that chromaffin-cell gap junctions represent a substrate sensitive to stress history, through which developmental experience may influence sympathoadrenal and endocrine adaptation in adulthood.

physiology↗

bioRxiv2026

Killer-cell dominance dichotomy governs tumor immune networks and stratifies inflamed cancers

Cancer immunotherapy benefits remain limited, even among "hot" tumors with high killer lymphocyte infiltration. Here, we investigated the population-level architecture of killer cells based on nearly 5,000 pan-cancer scRNA-seq samples, together with orthogonal validation by spectral cytometry and spatial transcriptomics. Unlike the prevailing "hot-cold" paradigm, which assumes coordinated infiltration of multiple cytotoxic lineages, we uncovered a conserved framework wherein terminal cytotoxic immunity in individuals or malignancies diverges into states dominated by either exhausted CD8+ T cells (Tex) or CD56dimCD16hi NK (NK1) cells. Despite the complexity of the tumor microenvironment, Tex-NK1 divergence governs the primary axis of tumor-intrinsic and tumor-extrinsic variance. Distinct from the conventional view that NK cells positively contribute to immunotherapy efficacy, NK1-skewed tumors, although highly cytolytic, are refractory to current immune checkpoint blockade regimens. This killer divergence defines a foundational axis of cancer immunity and provides a resource for prioritizing next-generation targets for NK-directed immunotherapy.

immunology↗

bioRxiv2026

Programming Brain Cell-Type-Selective Delivery In Vivo with Transporter-Guided Therapeutics

Many diseases arise from dysfunction of defined cell populations, yet most therapeutics distribute broadly, limiting efficacy and causing toxicity. We developed ExACT, a platform for cell-type-selective intracellular delivery that exploits membrane transporters. In vivo screening of combinatorial fluorescent small-molecule libraries in mouse brain identified chemistries whose uptake is dictated by endogenous transporter expression, yielding compounds with preferential entry into neurons, astrocytes, pericytes and endothelial cells. One series showed strong selectivity for brain and retinal endothelium, where Slco1a4 mediated uptake. This selectivity principle extended to the human orthologue SLCO1A2, highly expressed in brain endothelium and oligodendrocytes, where it mediated selective uptake in a humanized mouse model and human iPSC-derived oligodendrocytes. Ectopic expression of SLCO1A2 in neurons via gene therapy created a synthetic entry port, conferring ExACT conjugate uptake on otherwise inaccessible cells. Bifunctional compounds linking transporter-targeting motifs to antisense oligonucleotides or small-molecule drugs retained pharmacological activity while conferring transporter-dependent cell-type selectivity, illustrating how transporter diversity can be harnessed for precision pharmacotherapy.

bioengineering↗

bioRxiv2026

Annotation-Based Gene-Peak Links Improve Regulatory Network Prediction of Gene Expression in Human Kidney Multi-Omics

BackgroundLinking distal regulatory elements to their target genes is a central problem for interpreting chromatin accessibility and other non-coding genomic data. Proximity-based mapping is convenient but ignores three-dimensional enhancer-promoter architecture and can misassign long-range regulatory effects. Correlation-based approaches can also miss regulatory links because of limited statistical power and restrictive distance or significance thresholds. Single-cell and single-nucleus multi-omic datasets, such as 10x Multiome profiles that jointly measure chromatin accessibility and gene expression in the same cells or nuclei, now provide a way to evaluate gene-peak linkage strategies by testing how well linked accessibility features predict gene expression. Existing methods often focus on scoring individual enhancer-gene pairs. In this study, we proposed and constructed a fast annotation-based candidate gene-peak network and tested whether it improves downstream prediction of gene expression. MethodsWe first built a unified gene-peak regulatory network by integrating enhancer-based, promoter-based, and proximity-based linkage strategies. We then used single-cell multiome data from the Kidney Precision Medicine Project (KPMP) 10x Multiome cohort to evaluate whether the proposed links captured regulatory signals. We aggregated RNA expression and ATAC accessibility at the cell-type cluster level and trained predictive models to evaluate how well different linkage strategies could explain gene expression based on accessibility. Model performance was compared between annotation-based (including both enhancer- and promoter-based links) and proximity-based gene-peak links using testing R{superscript 2} and mean squared error (MSE) in a strict set of 1,704 genes and an adaptive set of 7,973 genes with more relaxed requirements. ResultsIn the strict regime (1,704 genes with [≥]20 peaks assigned by the nearest-TSS rule and [≥]10 annotated enhancer-based peaks), the annotation-based model consistently achieved higher testing R{superscript 2} and lower testing MSE than the proximity-based model. In the larger adaptive regime (7,973 genes with [≥]5 proximity-based and [≥]2 enhancer-based peaks), we defined for each gene a balanced number of selected peaks based on its available closest and enhancer links; the annotation-based model again showed globally higher testing R{superscript 2} and lower testing MSE. These improvements were observed over a broad range of candidate-linked peak numbers. ConclusionsUsing human kidney 10x Multiome data, we show that a fast annotation-based gene-peak linkage framework can improve prediction of gene expression from chromatin accessibility compared with conventional approaches. These results support the use of biologically informed enhancer and promoter annotations when constructing candidate gene regulatory networks. Our framework also showed concordance with the correlation-based Signac LinkPeaks method while providing broader coverage and greater computational efficiency. We have implemented these annotation-based linkage methods in the GPlinksR R package, providing a fast and scalable tool for constructing regulatory networks.

genomics↗

bioRxiv2026

Ventricular Expansion Couples Hyperosmotic Stress to Thirst

Thirst is thought to arise from osmotic signals detected by circumventricular organs, yet how hyperosmotic stress activates mechanosensitive channels remains unclear because cell shrinkage should reduce membrane tension. Here we identify a brain-scale mechanical signal that couples systemic osmotic stress to drinking. In mice, hypertonic saline rapidly increased serum and cerebrospinal fluid osmolality, expanded the lateral ventricles, and promoted water intake. Relieving or blocking ventricular deformation attenuated drinking without eliminating osmotic gradients. Hyperosmotic challenge also produced localized deformation of periventricular cells, where spatial transcriptomics revealed candidate mechanosensitive channels, including Tmem63b and Piezo1. Thus, ventricular expansion provides a mechanical component of osmotic thirst, uncovering an osmo-mechanical layer of interoceptive regulation.

neuroscience↗

bioRxiv2026

A pleiotropic EPAS1 enhancer mediating Tibetan adaptation to hypoxia is active in adipocytes

In response to hypoxic stress at high altitudes, variation at the EPAS1 locus has experienced strong selection in Tibetans. Functional dissection of the selection signals at this locus identified ENH5, an enhancer within the adaptive haplotype that has a blunted response to hypoxic stress in Tibetans. ENH5 was shown to be pleiotropic in several tissues related to hypoxia response, suggesting that a possible mechanism behind the strong selection signatures could be adaptive pleiotropy. Tibetans not only experience hypoxic conditions, but also cold temperatures due to the altitude and climate of the Tibetan Plateau. However, it is unclear whether cold temperatures affect ENH5 activity possibly contributing to the selective pressure at this locus. Here, we further characterized the role of ENH5 in subcutaneous white adipose tissue, an important tissue type that regulates body temperature in response to cold temperatures by releasing stored fat as heat through a process called thermogenesis. In this work, we investigated the role of ENH5 in adipocytes using ENH5 knockout mice (ENH5 KO), which phenocopy the reduced activity of the Tibetan allele. We show that ENH5 KO mice at normoxia and room temperature do not have significant differences in organismal phenotypes related to adiposity and metabolism compared to WT mice on a high fat diet. However, we detected effects of ENH5 conditional on thermogenic stimulation and hypoxia exposure, independently, in adipocytes cultured in vitro. Under either of these conditions, ENH5 KO has stronger differential expression of key genes involved in thermogenesis activity and adipocyte differentiation compared to WT. This differential response to thermogenic stimulation expands on the pleiotropic effects of the Tibetan ENH5 allele(s), in addition to those previously shown in well-established hypoxia-responsive tissues. Our results raise the possibility that pleiotropic effects of ENH5 may implicate unforeseen mechanisms, such as cellular energetics and thermogenesis, possibly contributing to the phenotypic adaptation to high altitude in Tibetans.

genetics↗

bioRxiv2026

Cellfm-datasets: A Unified Data Infrastructure for Single-Cell and Spatial Transcriptomics Foundation Model Pretraining

Large-scale cell foundation models are increasingly limited not only by model architecture, but also by the data infrastructure required to repeatedly sample sparse transcriptomic profiles from out-of-core cohorts. AnnData/H5AD has become a standard exchange format for single-cell and spatial omics analysis, yet its HDF5-backed layout is not designed for high-frequency random mini-batch loading under multi-worker and distributed pretraining. We present Cellfm-datasets, a data infrastructure artifact that converts H5AD cohorts into a self-describing compressed sparse row (CSR) memmap layout and exposes the resulting corpus through Hugging Face Dataset and IterableDataset interfaces. The artifact stores a shared gene vocabulary, per-sample metadata, optional spatial coordinates, observation metadata, manifests, and checksums, and reconstructs sparse cell or group records at runtime without dense expansion. A unified sampling abstraction supports random-cell groups, manifest-defined biological regions, and coordinate-based spatial blocks, with deterministic sharding across distributed ranks and data-loader workers. Spatial demonstrations on P14 mouse brain transcriptomics sections illustrate region- and block-level sampling over real anatomical structures. In controlled benchmarks on a public heterogeneous ModelScope scRNA-seq subset, Cellfm-datasets reached 60,571 {+/-} 1,734 samples/s in single-core random loading, scaled to approximately 160,000 samples/s with eight workers, and maintained near-constant process-private memory while reading up to one million cells. By moving sparse single-cell and spatial corpora from model-specific loader code into reusable, validated, and framework-native dataset artifacts, this design may reduce the engineering burden of reproducible cell foundation model pretraining and make repeated training runs, model comparisons, and mixed-modality data reuse easier to standardize. Code availabilityhttps://github.com/PangJiangShuan/cellfm-datasets

bioinformatics↗

bioRxiv2026

GYS2 Promotes the Progression of Aortic Dissection and Aortic Aneurysm via C5a/NF-κB-Mediated Pro-Inflammatory Macrophage Polarization

BackgroundAortic aneurysm and aortic dissection (AAD) are lethal cardiovascular emergencies characterized by sudden onset and extremely high early mortality. The pro-inflammatory polarization of macrophages is one of the core factors driving the pathogenesis of AAD, but its underlying mechanism remains unclear. This study focuses on the aberrant expression of glycogen synthase 2 (GYS2) in the AAD microenvironment and its role in driving macrophage polarization toward the pro-inflammatory M1 phenotype. MethodsProteomic analysis was conducted to identify protein heterogeneity associated with AAD. Clinical and animal samples were used to evaluate the correlation between GYS2 expression and AAD progression. Whole-body GYS2 knockout mice and adeno-associated virus (AAV)-mediated macrophage-specific gain- and loss-of-function models were utilized to investigate the regulatory role of GYS2 in macrophage polarization and complement activation. Downstream molecular pathways were identified and validated through in vitro stimulation and in vivo exogenous C5a rescue experiments. ResultsGYS2 expression was significantly upregulated in AAD tissues and primarily localized in macrophages. Activation of GYS2 by LiCl or macrophage-specific overexpression of GYS2 exacerbated aortic dilation and extracellular matrix degradation, and increased mortality in AAD mice. Conversely, whole-body GYS2 knockout or macrophage-specific GYS2 knockdown suppressed inflammatory factors, significantly reduced the incidence of AAD, and attenuated vascular injury. Mechanistically, excessive GYS2 in macrophages specifically triggered the complement-coagulation cascade, promoting the generation of the potent anaphylatoxin C5a. C5a further bound to its receptor C5AR1, activating the downstream PLC{beta}3/NF-{kappa}B signaling pathway, thereby inducing M1 macrophage polarization and matrix metalloproteinase-mediated extracellular matrix degradation. In vivo exogenous C5a rescue completely reversed the vascular protective effects conferred by GYS2 deficiency. ConclusionsThis study demonstrates that highly expressed GYS2 regulates the pro-inflammatory polarization of macrophages and extracellular matrix degradation via the complement C5a/PLC{beta}3/NF-{kappa}B signaling axis, which is a key mechanism driving AAD progression. Specific inhibition of macrophage GYS2 can effectively alleviate aortic vascular inflammation and prevent AAD progression, providing a promising novel strategy for the clinical conservative treatment of AAD.

Molecular Biology↗

bioRxiv2026

SCD1 inhibition synergizes with TMZ to improve IDH1 MUT glioma survival of mice via lipotoxic stress

Mutations in the isocitrate dehydrogenase enzyme (IDH1) are prevalent in low-grade gliomas, such as oligodendrogliomas. Other than surgery, radiation, and chemotherapy, few options for treatment exist. The standard of care for patients currently consists of maximal safe resection, as well as the potential use of radiation and chemotherapy, typically followed by radiographic surveillance. Although significant advances have been achieved, these have not translated into meaningful improvements in overall survival, warranting the development of novel therapies. Herein, we demonstrate that the inhibition of SCD1 in vitro leads to decreased colony formation and is more specific to IDH1MUT glioma than the IDH1WT cells, We further identified MF-438 as an active inhibitor of this enzyme and showed that this inhibitor is linked with iron transport and ferroptosis. MF438 depleted oleic (C18:1) and palmitoleic acid (C16:1) levels, driving saturated phosphatidylcholine (PC) accumulation and ER stress (INSIG1, SEL1L upregulation). TS603 exhibited selective polyunsaturated phosphatidylcholine reduction with downregulation of GPX4, FTH1, and KEAP1, and upregulation of NCOA4, SLC11A2, ALDH7A1, and DPP4, consistent with ferroptosis priming via ferritinophagy-driven expansion of the labile iron pool, as confirmed by FerroOrange flow cytometry. Neutral lipid metabolism genes (LPIN1, LDLR, PNPLA3, ACSL1), intracellular lipid transport genes (TMEM41B, OSBP, STARD4), and lipid droplet organization genes (SQLE, CHKA, AUP1) were coordinately upregulated in TS603 after treatment with MF-438. MF438+TMZ activated the integrated stress response (ATF3, DDIT3, IRF1, CDKN1A, GADD45B) and synergistically suppressed TS603 neurosphere growth (p=0.0326). In vivo combination between MF-438 and TMZ showed improved survival versus the TMZ-alone group, in an IDH1-mutant oligodendroglioma model. Tissue analyses showed significant reduced Ki67 expression, a marker of cellular proliferation, in the combination treatment. Collectively, these findings suggest that targeting lipid metabolism may enhance the efficacy of standard-of-care therapy in IDH1-mutant oligodendroglioma.

Cancer Biology↗

bioRxiv2026

PanKbase Integrated Single-Cell Map: A Comprehensive Atlas of Human Pancreatic Islets

Single-cell RNA sequencing (scRNA-seq) of human pancreatic islet tissue is a powerful tool for investigating type 1 diabetes (T1D). However, individual datasets are limited in size and fragmented across donors, laboratories, and experimental conditions. To address this, we constructed a comprehensive, integrated scRNA-seq atlas of isolated human pancreatic islets by collating publicly available data generated from tissue provided by resources including the Human Pancreas Analysis Program, the Integrated Islet Distribution Program, and Prodo Labs. Systematic quality controls were implemented to select high-quality samples, reads, and cells. During integration, we accounted for important variables such as age, sex, body mass index, origin study, treatments, islet distribution resources, and sequencing chemistry. Our single-cell atlas comprises 191 high-quality samples from 140 donors (59 female, 81 male) across five phenotypic groups: no diabetes (controls, n=69), autoantibody positivity without diabetes (n=12), pre-diabetes (n=11), T1D (n=12), and type 2 diabetes (T2D) (n=36). In total, the atlas contains 448,935 cells, capturing 13 distinct populations, including alpha cells (43.3%) and beta cells (26.8%), as well as groups such as immune cells (0.6%). Publicly available at www.pankbase.org, this atlas provides a platform for hypothesis-driven investigation of diabetes pathophysiology and, given rigorous quality control, is well-suited for downstream machine-learning applications. Article HighlightsO_LICurrent scRNA-seq datasets of pancreatic islet tissue are limited in size and scattered across donors, laboratories, and experimental conditions, underscoring the need for a consolidated resource. C_LIO_LIWe harmonized datasets from multiple sources to build a comprehensive single-cell map of isolated human pancreatic islets. C_LIO_LIOur atlas captures 448,935 cells from 191 high-quality samples across 140 donors and multiple phenotypic groups, identifying 13 distinct cell populations. C_LIO_LIAvailable at www.pankbase.org, the atlas provides a scalable, rigorously curated platform to support hypothesis-driven diabetes research and can enable a broad range of downstream computational applications. C_LI

genomics↗

bioRxiv2026

Dynamic Gating Mechanism of the b0,+AT-Mediated Arg Transport: Insights from ASMD Simulations

Heteromeric amino acid transporters (HATs) mediate essential amino acid flux across membranes, but the molecular dynamics of substrate translocation remain poorly defined for many family members. Here, using conventional and adaptive steered molecular dynamics (cMD and ASMD) simulations, we identify residue W230 in the b0,+AT transport channel as a dynamic gate that regulates arginine (Arg) influx through side chain flipping. By integrating dynamic network analysis with dynamical cross-correlation of residue motions, we show that regulatory signals propagate from the Arg binding site through transmembrane helix 5 (TM5), a connecting loop, and TM6 to reach W230. We propose a dynamic gating mechanism for b0,+AT - mediated amino acid transport. Arg binding at V186 triggers signal propagation that enhances cooperative interactions between W230 and Arg, driving the side chain flipping of W230. Our findings reveal a dynamic gating mechanism underlying b0,+AT - dependent Arg transport and suggest that residue-triggered side chain reorientation may represent a conserved and efficient strategy in transporter function. Author SummaryAmino acids are the essential building blocks of life, and their transport across cell membranes is vital for nutrition and cellular signaling. Heteromeric amino acid transporters (HATs) mediate this process, yet how they physically move substrates through the protein at the atomic level remains poorly understood. In this study, we used advanced computer simulations to observe, in unprecedented detail, how b0,+AT--a key HAT member--transports the amino acid arginine. Our simulations revealed that a single residue, tryptophan 230 (W230), functions as a molecular gate: its side chain flips open to allow arginine to pass and then closes behind it, ensuring one-way traffic into the cell. We further discovered that the initial binding of arginine sends a signal through specific structural elements (helices and loops) to trigger this gate opening. This work not only uncovers a dynamic gating mechanism for b0,+AT but also suggests that similar side-chain flipping events may represent a common and efficient strategy used by other transporters to control substrate movement. Our findings provide a new framework for understanding transporter function and could inform future drug design targeting these critical membrane proteins.

biophysics↗

bioRxiv2026

A global regulatory atlas of Streptomyces reveals conserved and diversified transcriptional networks across actinomycetes

Transcriptional regulatory networks determine how bacteria integrate environmental signals with growth, metabolism and stress adaptation. Actinomycetes encode exceptionally large repertoires of transcription factors (TFs) coordinating morphological development, environmental adaptation and specialized metabolism, yet their regulatory networks remain poorly defined. Here, we apply DNA affinity purification sequencing (DAP-seq) to 789 predicted TFs of Streptomyces coelicolor, generating genome-wide binding maps for 393 regulators and expanding the experimentally supported regulome from [~]8% to [~]50%. Integration with ChIP-seq reveals pleiotropic regulators and hierarchical network architecture linking primary metabolism, development and biosynthetic gene clusters (BGCs). Multiplexed DAP-seq (multiDAP) across 16 additional actinomycetes uncovered deeply conserved regulatory circuits alongside widespread divergence in TF-target interactions. Together, these data establish a regulatory atlas for Streptomyces and related actinomycetes, enabling researchers to explore control of genes, pathways, BGCs and conserved network modules. This provides a foundation for predictive analysis and engineering of complex bacterial phenotypes in biotechnology and medicine.

microbiology↗

bioRxiv2026

Procedure-Matched Comparison of TNBS/Ethanol Enema and DSS Free-Drinking Models of Ulcerative Colitis in Rats: Immune Endotype Profiling and a Translational Model-Selection Framework

ObjectiveChoosing between TNBS/ethanol enema and DSS free-drinking water protocols for establishing rat ulcerative colitis(UC) models remains a practical challenge in preclinical research. Beyond confirming that both methods induce colitis, no prior study has quantified the independent contribution of enema procedural trauma to inflammatory readouts, reported sex-stratified cytokine responses, or formally linked model-specific immune profiles to human UC endotypes. MethodsTen SPF-grade SD rats(half male and half female) were allocated to a normal control, a procedure-matched saline enema control(anesthesia and enema without chemical agent), a TNBS group(100 mg/kg TNBS + 50% ethanol enema), and a DSS group(3% DSS free-drinking, 7 days). Endpoint assessments included body weight, colon length, macroscopic and histological scoring(modified Macpherson criteria, 0-10), and serum TNF- and IL-6 by ELISA. Post-hoc exploratory analyses included sex-stratified cytokine sub-analysis and coefficient of variation(CV%) for each readout. ResultsBoth model groups successfully induced UC(P<0.05 vs. controls for all endpoints). Critically, the procedure-matched saline enema control confirmed that colonic inflammation in the TNBS group was attributable to the chemical agent rather than mechanical trauma. TNBS induced significantly higher TNF-(90.2{+/-}10.5 vs. 73.5{+/-}9.8 pg/mL, P<0.05) and IL-6(66.5{+/-}8.3 vs. 53.2{+/-}7.6 pg/mL, P<0.05) than DSS,consistent with Th1-polarized vs. innate barrier-disruption immune endotypes, respectively. Coefficient of variation analysis indicated greater intra-group variability in TNBS versus DSS, reflecting the procedural dependency of enema-based models. ConclusionA procedure-matched control design is essential for valid TNBS-vs.-DSS comparisons and has been systematically underutilized in prior studies. Based on immune endotype alignment, TNBS is recommended for screening T-cell-targeted therapies and acute anti-inflammatory agents, while DSS is recommended for epithelial barrier repair and microbiome-modulating interventions. A model-selection decision framework derived from these data is provided to guide preclinical study design.

animal behavior and cognition↗

bioRxiv2026

CytoGem-XAI:A Hypergraph Neural Network Framework for Genome-Scale Metabolic Modeling and Interpretable Analysis

Genome-scale metabolic models are essential for understanding cellular metabolism, yet existing deep learning approaches remain black boxes, and traditional flux balance analysis (FBA) cannot provide sample-specific predictions. To our knowledge, CytoGem-XAI is the first framework to combine hypergraph neural network representation with interpretable, FBA-parallel analysis and sample-specific metabolic characterization. Built upon hypergraph representations where reactions are encoded as hyperedges connecting their participating metabolites, CytoGem-XAI introduces three analysis modules: perturbation-based carbon source importance ranking, hard intervention reaction bottleneck identification, and pathway-level topological attribution. Beyond prediction, CytoGem-XAI uniquely enables condition-dependent carbon source essentiality and reaction bottlenecks that vary with genetic background--capabilities absent from both traditional FBA and existing deep learning methods. Trained on 17,400 E. coli growth conditions using 10-fold cross-validation, our framework achieves R2 = 0.862, substantially outperforming AMN (R2 = 0.81, +6.4%), FBA (R2 = 0.62, +39%), and gradient boosting baselines (R2 = 0.71, +21%). Biological validation confirms that CytoGem-XAI identifies known essential carbon sources (e.g., alanine, malate) and rate-limiting enzymes (e.g., TCA cycle), while also revealing N-acetylmuramate--a peptidoglycan precursor--as a previously underappreciated essential nutrient.

bioinformatics↗

bioRxiv2026

Molecular mechanisms underlying the prepupal-instar-forming metamorphosis in black soldier fly (Hermetia illucens)

The black soldier fly (Hermetia illucens, Diptera) undergoes an atypical metamorphic program in which a distinct non-feeding prepupal instar precedes pupation, but its developmental and molecular basis remains poorly understood. Here, we investigated this unusual metamorphic program through integrated developmental and RNAi-based analyses. Postembryonic staging confirmed that the 6th instar feeding larva molts into a non-feeding 7th instar prepupa, whose hardened cuticle subsequently serves as the puparium during intra-puparial development. Expression profiles of four key metamorphic genes revealed a stage-specific Chinmo/Kr-h1- Br-c-E93 regulatory shift corresponding to larval, prepupal, and pupal/adult development, with sustained Br-c expression defining the 7th instar prepupal stage. RNAi-mediated knockdown of Kr-h1 and/or Chinmo induced precocious larval-prepupal metamorphosis, supporting their roles in larval stage maintenance, whereas depletion of Br-c or E93 disrupted prepupal-pupal transition and adult differentiation, respectively, consistent with their functions as pupal and adult specifiers. These results support generally conserved functions of the metamorphic gene network while indicating the absence of a repressive effect of Br-c on E93 in H. illucens prepupae. Together, these findings establish the 7th instar prepupa as an independently regulated transitional stage, providing insight into how metamorphic programs are reorganized to diversify life-history strategies in holometabolous insects.

developmental biology↗

bioRxiv2026

Data-Efficient Exploration of Enzyme Function Using Family-Specific Machine Learning

Enzymes are essential biocatalysts across diverse industries, driving demand for high-performing variants. Foundation models are attractive for guiding enzyme discovery, but often lack the resolution to model subtle variations driving function within homologous families. Navigating these rugged functional landscapes to identify elite variants remains challenging and experimentally costly, even when guided by such models. Here we show that coupling dense, family-specific experimental screening with targeted, sequence-based deep learning provides a data-efficient discovery strategy. We experimentally screened 1,513 natural homologues from an esterase superfamily (>7,500 assays) and used this functional landscape to train task-specific models that predict activity, thermostability, and substrate specificity from sequence alone. Prospective experimental validation of previously untested sequences demonstrated that these task-specific models significantly outperformed generalist pre-trained and physics-based models in enriching for target traits. Residue-level attribution further indicated that the models captured sequence patterns consistent with underlying structural features. Finally, retrospective simulations showed that iterative retraining compresses the search space, discovering 60% of top-tier hits using nearly half the samples required by pre-trained baseline models. Together, these results highlight that machine learning can provide mechanistic insight, and that integrating targeted data acquisition with iterative machine learning provides a more data-efficient discovery strategy than relying on generic model scale.

bioengineering↗

bioRxiv2026

Repetition Selectively Reconfigures Offset-Defined Temporal Integration in Auditory Cortex

Auditory perception requires integrating sound over time, but whether cortical integration windows are fixed or adaptively shaped by recent sensory history remains unclear. Because auditory offset responses are shaped by the temporal structure preceding sound termination, they provide a readout of offset-defined temporal integration. Here, we recorded single-unit activity in awake rat auditory cortex while presenting 512-ms click trains with inter-click intervals of 1, 2, 4, 8 or 16 ms. Each stimulus was repeated ten times, allowing repetition number to index increasing adaptation. Across 271 offset-responsive neurons, repetition strongly compressed the maximal ICI capable of evoking a significant offset response and produced a smaller population-level shift in preferred ICI. These preferred-ICI changes were heterogeneous across neurons, with bidirectional shifts at the single-neuron level. In contrast, the effective temporal window measured with irregular-regular click trains remained stable at the population level, despite neuron-level variability. AAF and A1 further showed distinct repetition-dependent tuning profiles. These findings suggest that adaptation selectively reconfigures ICI-based offset tuning while preserving a population-level local regularity window, revealing flexible and stable components of cortical temporal integration.

neuroscience↗