Biology subjects

Yuan, S.

Publications and source records attributed to Yuan, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Inhibition of CKAMP44 attenuated seizure activity via protein phosphatase 3 regulatory subunit B-mediated GluA1 phosphorylation and synaptic transmission

Temporal lobe epilepsy (TLE) is a complex neurological disorder characterized by spontaneous recurrent seizures and its underlying mechanism remains elusive. This study aimed to investigate the role of cystine-knot AMPAR modulating protein 44 (CKAMP44) in the pathological process of TLE and its potential as a therapeutic target using kainic acid (KA)-induced epilepsy mouse model of TLE. Our results showed that CKAMP44 protein and mRNA expression was significantly increased and primarily localized to neurons during the chronic phase of TLE. Nkx2-1 regulated the transcription of CKAMP44 in the hippocampus brain tissues of KA-induced TLE mice. Inhibition of CKAMP44 suppressed seizure susceptibility and severity in the KA-induced epilepsy mice via behavioral and local field potential monitoring. Furthermore, inhibition of CKAMP44 decreased frequency and amplitudes of spontaneous excitatory postsynaptic currents indicating that the excitatory synaptic transmission was reduced in an in vitro epilepsy model. Mechanistically, inhibition of CKAMP44 specifically upregulated the membrane surface expression of GluA1 and the phosphorylation level of GluA1-ser831 by downregulating protein phosphatase 3 regulatory subunit B(PPP3r2) expression. Overexpression of PPP3r2 downregulated the phosphorylation level and surface expression of GluA1, which ultimately exacerbated the seizure activity suppressed by CKAMP44 knockdown. Collectively, our results indicate that CKAMP44 may be a potential therapeutic target for the treatment of TLE.

pathology↗

bioRxiv2026

Generation and long-term expansion of human pancreatic islet organoids in vitro

The scarcity of expandable, functional human islet cells remains a major barrier to diabetes therapy. Here, we identify PROCR+ cells within adult human islets and establish a defined culture system to generate pancreatic islet organoids. These organoids self-organize into -, {beta}-, {delta}-, and PP cells at near-native ratios, exhibit regulated insulin and glucagon secretion, and support exponential in vitro expansion. Single-cell transcriptomics reveals a unique progenitor-like cell population that is transcriptionally primed for endocrine differentiation but shares molecular features with fetal trunk cells and endocrine progenitors. When transplanted, the organoids rapidly ameliorate hyperglycemia in diabetic mice. Importantly, in a non-human primate model, intraportal transplantation of these organoids reduced exogenous insulin requirements, restored glucose-stimulated C-peptide secretion, and achieved sustained glycemic control-representing a critical step toward clinical translation. This study provides a strategy for expanding human islet organoids, offering a scalable platform for diabetes treatment, disease modeling, and regenerative medicine.

cell biology↗

bioRxiv2026

Testing and Estimating Causal Treatment Effect Heterogeneity in Observational Studies via Revised Deep Semiparametric Regression: A Lung Transplant Case Study

Lung transplantation programs must decide when bilateral lung transplantation (BLT) offers meaningful functional benefit over single lung transplantation (SLT). Because donor and recipient characteristics jointly shape outcomes, the BLT-SLT contrast may differ across patients. However, analyzing observational registries poses a statistical challenge: apparent subgroup differences can be artifacts of complex confounding, while true heterogeneity can be missed or poorly quantified. Using a large national registry, we investigate whether the BLT effect varies across recipients and identify clinically relevant profiles of benefit using post-transplant lung function measured by forced expiratory volume in 1 second (FEV1). We develop deepHTL, a framework that tests for treatment effect heterogeneity and estimates how the BLT-SLT effect varies with patient features. In extensive simulations designed to resemble registry-like confounding, deepHTL controls false positives for detecting heterogeneity and yields more accurate individualized effect estimates than common machine learning methods. In the lung transplant cohort, we find strong evidence of heterogeneity in the BLT-SLT effect on FEV1: younger, lower risk recipients with better baseline status show the largest FEV1 gains from BLT, whereas older, higher risk candidates exhibit diminished marginal benefit. These findings provide statistically grounded guidance for patient selection and allocation of scarce donor organs.

bioinformatics↗

bioRxiv2026

Nucleoid-associated proteins sense phage-induced genome damage to elicit abortive infection

Bacteria have evolved diverse immune strategies to detect and neutralize bacteriophage infection. Here, we describe an unprecedented paradigm in which a chromosome-architecting nucleoid-associated protein (NAP) is repurposed as a viral infection sensor. When phage attack leads to genome degradation, the NAP sensor is released from the nucleoid to the cytoplasm, where it binds and activates diverse immune effectors. One such effector is a nucleotide-modifying toxin normally existing as an inactive homotetramer. NAP binding converts it into a catalytically active heterotrimer that halts both transcription and translation. Phylogenetic analyses unveiled the high modularity, polyphyletic origin, and wide distribution of NAP-mediated defenses. Collectively, we define a distinct class of defense systems in which bacteria sense phage-induced genome damage through NAP relocation, highlighting an unexpected but essential role for these proteins as sentinels of genome integrity.

microbiology↗

bioRxiv2026

nELAVL phosphorylation by CDKL5 regulates inter-condensates composition and communication to promote experience-dependent maturation of the visual cortex

Mutations in Cyclin-Dependent Kinase-Like 5 (CDKL5) cause CDKL5 deficiency disorder (CDD), an X-linked neurodevelopmental condition. Through a phosphoproteomic screen, we identified the neuron-specific nELAVL family of RNA-binding proteins as direct activity-dependent substrates of CDKL5. In support of this regulatory axis, single-nuclei transcriptomics of Cdkl5 knockout (KO) cortices revealed an enriched reduction in activity-dependent mRNAs. Mechanistically, we show that nELAVL proteins undergo phase separation to form biomolecular condensates, the size of which is gated by CDKL5 phosphorylation. Loss of CDKL5 leads to enlarged nELAVL condensates, which exhibit reduced binding affinity for the target mRNA Fos, resulting in its accelerated degradation. This disruption extends to inter-condensate communication: phosphodeficient nELAVL show diminished interaction with P-bodies, which themselves become enlarged in CDD mutant iNeurons. Functionally, the absence of nELAVL phosphorylation recapitulates the deficits in experience-dependent visual function observed in Cdkl5 KO mice. Our findings establish a critical molecular mechanism by which CDKL5-mediated phosphorylation governs mRNA metabolism by tuning the properties of nELAVL condensates and their communication with other biomolecular condensates, ultimately promoting experience-dependent maturation of the visual cortex.

neuroscience↗

bioRxiv2026

AI-Enforced Ultra-Large Virtual Screening Discovers Potent CD28 Binders

Targeting protein-protein interactions (PPIs) with small molecules is historically challenging due to shallow, solvent-exposed interfaces that lack classical binding pockets. Furthermore, employing traditional structure-based virtual screening (SBVS) across ultra-large chemical spaces to find novel chemotypes imposes prohibitive computational bottlenecks. Here, we report the first prospective, real-world application of the PyRMD2Dock platform, an AI-enforced SBVS workflow that integrates machine learning and standard docking available within the PyRMD Studio suite. To target the structurally demanding immune receptor CD28, a chemically diverse subset of 2.4 million molecules from the Enamine REAL Diversity Space was docked into a cleft adjacent to the canonical ligand interface. These data were used to train 672 classification models, and the optimized model rapidly screened the remaining [~]46 million compounds. Following interaction filtering and clustering, 232 highly prioritized ligands were identified. Experimental validation of 150 purchased candidates yielded a remarkable hit rate, identifying multiple direct CD28 binders. Lead compounds 100 and 104 exhibited submicromolar affinity (Kd = 343.8 nM and 407.1 nM, respectively), potent CD28-CD80 disruption, and functional blockade in cellular reporter assays. Furthermore, these compounds successfully reduced cytokine secretion in primary human tumor-PBMC and epithelial tissue co-culture models. This study validates PyRMD2Dock as a highly scalable, effective protocol for mining massive chemical libraries to discover small-molecule modulators of challenging immune receptor interfaces.

pharmacology and toxicology↗

bioRxiv2026

An apical junction protein antagonizes mechanosensitive calcium signaling to establish stochastic choices of olfactory neuron subtypes

Mechanical forces regulate brain development and left-right body patterning. However, the role of mechanical signaling in brain lateralization remains unclear. In Caenorhabditis elegans, the left and right AWC olfactory neurons communicate via a gap junction network to stochastically differentiate into the default AWCOFF and induced AWCON subtypes. SLO BK potassium channels, SLO-1 and SLO-2, act redundantly to inhibit a calcium-regulated protein kinase pathway in the specification of the AWCON subtype. Here, we identified a role for AJM-1 (apical junction molecule 1) in promoting AWCON from an unbiased forward genetic screen for mutants that suppress the slo-1(gf) 2AWCON phenotype. AJM-1 is located at three distinct tight junctions between amphid neurons (including AWC) and sheath glia, sheath and socket glia, and socket glia and hypodermal cells (also known as epidermal cells) at the anterior tip of the animal. In addition to its cell-autonomous function, the non-cell-autonomous function of AJM-1 in glial and hypodermal cells is required for the specification of the AWCON subtype. Furthermore, we identified a role for the DEL-1 mechanosensitive DEG/ENaC channel in the calcium signaling pathway, mediated by UNC-2 and EGL-19 voltage-activated calcium channels, that specifies AWCOFF. Together, our results suggest a mechanism in which AJM-1 promotes SLO-1 expression and antagonizes mechanosensitive calcium signaling, thereby promoting the AWCON subtype. This study provides insight into the role of mechanical force in the stochastic lateralization of olfactory neurons.

developmental biology↗

bioRxiv2026

An Organotypic Oral Squamous Cell Carcinoma Model Recapitulates Epithelial-Stromal Complexity at Single-cell Resolution and Reveals Matrix-derived Signalling as a Therapeutic Target.

Three-dimensional (3D) organotypic cultures recapitulate key structural features of oral tumours and provide controlled, ethical, and reproducible research platforms. However, their ability to faithfully recapitulate in vivo tissue composition and their translational relevance require rigorous validation. Here, we characterised a head and neck squamous cell carcinoma (HNSCC) model using single-cell RNA sequencing to assess maturation, cellular heterogeneity, functionality, and inter- and intra-tissue interactions within epithelial and stromal compartments. The epithelial layer of the model differentiated into populations closely resembling the tissue of tumour origin, including dividing and precursor cells, heterogeneous basal layer, suprabasal cells, and metabolically specialised populations. All epithelial lineages emerged from proliferative progenitors, driven by dynamic transcription factor programmes. The collagen-rich stroma contained functionally diverse fibroblasts reflecting the heterogeneity of cancer-associated fibroblasts in vivo, including dividing, matrix-producing, immune-responsive, and tumour-like populations. Importantly, extensive epithelial-stromal communication networks developed, essential for cancer epithelium maintenance and tumour microenvironment regulation. Matrix-derived signals, particularly fibronectin, osteopontin, and laminins, constituted dominant inputs to CD44-expressing cancer cells and are associated with patient survival in HNSCC, highlighting potential therapeutic targets. Overall, this organotypic HNSCC model exhibits high functional fidelity, captures key tumour elements relevant for therapy and resistance and brings confidence in non-animal drug testing.

cancer biology↗

bioRxiv2026

MetaSAG: A Tool for Multi-level Exploration and Taxonomic Analysis of Microbial Single-Amplified Genomes

Microbial single-amplified genome (SAG) sequencing technologies have elevated microbial research resolution to the single-cell level. However, neither upstream data processing nor downstream analysis has been fully developed, greatly limiting the research in strain level. Herein, we developed MetaSAG (Multi-level Exploration and Taxonomic Analysis of microbial Single-Amplified Genomes), which enables accurate and rapid taxonomic classification of microbial SAGs. MetaSAG outperforms existing method in species classification certainty, computational efficiency, and sensitivity of low abundance species identification. In addition, MetaSAG enables species-level functional analysis, as well as strain-level evolutionary analysis. With the help of MetaSAG, we discovered the parasitic relationship between phages and bacteria, identifying multiple susceptible bacteria and a broad spectrum of phages. Furthermore, we developed MetaK-Lytic (k-mer-based meta-learning framework to predict phage lytic ability) to achieve accurate prediction of phage lytic activity based on 31-mer short sequences, which is well adapted to the characteristics of incomplete SAG sequences. Overall, we offer a comprehensive integrated tool that can parse microbial SAG data from raw data to the strain level to decipher the functional ecology of microbial dark matter, with broad implications for microbial ecology and phage therapy (https://github.com/liangcheng-hrbmu/MetaSAG). Significance StatementThis work provides a comprehensive framework for high-resolution SAG data analysis. The developed pipeline improves taxonomic annotation sensitivity and speed. Strain-level tracking enables dynamic evolutionary and functional insights, while single-cell bacterial-virus network reconstruction reveals precise interaction patterns. The novel annotation-free short sequence-based MetaK-Lytic facilitates functional prediction of uncharacterized phage sequences. Integrated into the MetaSAG platform, these tools deliver a streamlined, multi-level solution for interpreting SAG data, advancing studies in microbial ecology, evolution, and virology.

microbiology↗

bioRxiv2026

Leaf age modulates physiological and metabolic responses to contrasting nitrogen forms in Chinese fir (Cunninghamia lanceolata (Lamb.) Hook)

Atmospheric nitrogen (N) deposition is increasingly affecting global ecosystems, with nitrate contributing a growing proportion alongside ammonium. However, the interaction between N forms and leaf developmental stage in shaping physiological and metabolic strategies in Chinese fir remains poorly understood. In this study, a field experiment was conducted to explore the physiological and metabolic responses of young and old leaves to ammonium and nitrate N addition. Our findings showed that N addition enhanced photosynthetic performance in young leaves, with a stronger effect from nitrate. In contrast, old leaves exhibited limited photosynthetic response but accumulated higher non-structural carbohydrates and showed elevated N assimilation enzyme activities, particularly under nitrate addition. Phytohormone profiles varied between leaf ages, with young leaves having higher auxin levels while old leaves exhibiting increased abscisic and salicylic acid contents under N addition. Additionally, N addition induced differential reprogramming of amino acid metabolism, with age-dependent accumulation patterns. Metabolomic analysis identified key amino acids involved in coordinating carbon-nitrogen metabolism. These results highlighted the complementary metabolic strategies by young and old leaves of Chinese fir under contrasting N forms addition and emphasized the importance of considering both N form and leaf age in optimizing N management for sustainable plantation practices. HighlightsO_LINitrate enhanced photosynthesis in young Chinese fir leaves more effectively than ammonium. C_LIO_LIOld leaves prioritized C storage and N assimilation under N addition, especially nitrate. C_LIO_LIComplementary metabolic strategies between leaf ages optimized resource use under different N forms addition. C_LI

plant biology↗

bioRxiv2026

Discovery and Optimization of Small Molecule Inhibitors of the SLIT2/ROBO1 Protein-Protein Interaction Using DNA-Encoded Libraries

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=63 SRC="FIGDIR/small/707154v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1e81c3borg.highwire.dtl.DTLVardef@1958c6borg.highwire.dtl.DTLVardef@1360015org.highwire.dtl.DTLVardef@3f9388_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG Protein-protein interactions (PPIs) mediated by extracellular ligands remain challenging targets for small molecule intervention due to their large and dynamic interfaces. The interaction between SLIT2 and its receptor ROBO1 plays a critical role in cell migration and tumor progression, yet remains largely unexplored. Here, we report the discovery and optimization of small molecule inhibitors of the SLIT2/ROBO1 interaction enabled by DNA-encoded library (DEL) screening. Affinity selection against SLIT2 identified four structurally diverse hit compounds, which were subsequently validated using orthogonal biophysical assays. Among these, one hit exhibited measurable SLIT2 binding and functional inhibition of the SLIT2/ROBO1 interaction in a time-resolved FRET assay. Guided by physicochemical considerations, a solubility-optimized analog was designed, resulting in a [~]50-fold improvement in binding affinity and an [~]9-fold enhancement in functional potency. Molecular dynamics simulations and induced-fit docking revealed a stable binding mode within the SLIT2 LRR2 domain and suggested that a benzothiophene substituent was dispensable for target engagement. Fragment-based experimental validation confirmed this prediction, leading to the identification of a minimal azaindole-based pharmacophore that retained nanomolar binding affinity. Collectively, this study demonstrates how DEL-enabled hit discovery combined with rational optimization and fragment deconstruction can yield potent small molecule modulators of a challenging extracellular PPI, providing a foundation for further development of SLIT2/ROBO1 pathway inhibitors.

pharmacology and toxicology↗

bioRxiv2026

Hierarchy in neuronal representations of multiple tasks in prefrontal cortex

The ability to perform multiple tasks is one of the fundamental hallmarks of general intelligence in the brain. However, the underlying neural mechanisms remain largely unknown. We trained macaque monkeys to perform four tasks with identical spatial layouts but different cognitive demands, and recorded activities of thousands of prefrontal neurons using two-photon calcium imaging. Within the same neuronal population, we identified a multitask neural geometry composed of multiple low-dimensional subtask spaces, each encoding spatial information within a specific subtask. These subtask spaces shared a ring-like representational structure, forming a generalized spatial code across different subtasks. Task separation arose from separable bases and offsets of subtask spaces, modulated primarily by meta-task features. Thus, the neural geometry is organized by a three-level hierarchical structure: location codes are nested within subtask spaces, which are grouped as different meta-tasks. This hierarchy supported generalization across both locations and tasks, and explained monkeys error behaviors. Together, the hierarchically organized neural geometry underlies flexible multitask behavior.

neuroscience↗

bioRxiv2026

Immune cells adapt to distinct stem cell niches to govern tissue homeostasis

Summary ParagraphIn adult tissues, epithelial stem cells exist within distinct residences, each endowing them with exclusive instructions for regenerative fitness under homeostasis and stress. Key components of these niches are immune cells, which classically protect the host against external and internal threats. Whether and how stem cell:immune cell crosstalk contributes to normal tissue biology remains less clear. Here, we discover functional adaptation of resident lymphocytes within two distinct skin stem cell niches and show that through this communication, each niche adjusts to meet diverse tissue demands. In the upper hair follicle, where microbial load is high, T cells express lymphotoxin-{beta} and stimulate adjacent receptor-positive epithelial stem cells to form an immune-competent niche that controls microbial expansion. By contrast, in the epidermis, these T cells produce amphiregulin to maintain continuous stem cell reconstitution of the skins barrier. Concomitantly, they express the immune checkpoint protein LAG-3, which autorestricts lymphocyte numbers, and hence amphiregulin levels, thereby preventing over-proliferative responses. Finally, when epidermal T cells are absent, dermal lymphocytes restore the imbalance by colonizing and adapting to their new niche. Our findings unveil functional specialization and homeostatic resilience of immune-stem cell niches, each tailored to suit the demands of distinct tissue microenvironments.

immunology↗

bioRxiv2026

Dual-channel graph learning reveals similarity and complementarity in protein-protein interaction networks

Protein-protein interactions (PPIs) are governed by two fundamental interfacial mechanisms: similarity-driven, often involving symmetric structural motifs, and complementarity-driven, arising from geometric and physicochemical matching between binding surfaces. Despite their biological significance, computational models have largely overlooked the coexistence and interplay of these twofold interaction modes. Here, we introduce DMG-PPI, a dual-channel graph neural network framework that jointly models similarity and complementarity in PPI networks, extending prior heterophilous GNN concepts to explicitly disentangle these dual interaction modes. The model consists of two parallel message-passing pathways: Alignment Message Passing (AMP), which aggregates signals from similar neighbors to capture symmetric interfaces, and Divergence Message Passing (DMP), which contrasts node features to extract complementary binding patterns. The signals captured by AMP and DMP are integrated via an adaptive fusion strategy within each block, and the outputs of blocks are aggregated using the MixHop framework to encode higher-order interaction patterns. DMG-PPI substantially outperforms state-of-the-art methods on classical benchmark datasets, achieving a 7.19% improvement in Micro-F1 over the second-best method. Additionally, the dual-channel framework provides interpretable insights into key binding residues by identifying interfacial mechanisms. Overall, DMG-PPI serves as a powerful tool that reveals the mechanisms behind accurate PPI predictions and facilitates downstream biological analysis. Author summaryProteins interact through multiple interfacial principles rather than a single uniform mechanism, reflecting diverse modes of molecular recognition between binding partners. Accurately modeling this heterogeneity remains a central challenge in protein-protein interaction (PPI) prediction. Existing computational approaches often overlook such complexity and treat all interactions as arising from a dominant pattern. To address this limitation, we present DMG-PPI, a dual-channel graph neural network framework designed to account for distinct interaction principles within a unified model. By modeling both similarity-based and complementarity-based interaction signals, DMG-PPI enables a more comprehensive representation of interaction patterns in PPI networks. Evaluations on widely used benchmark datasets demonstrate that our approach achieves robust and consistent improvements over existing methods. Beyond prediction accuracy, DMG-PPI provides biologically meaningful interpretability by highlighting key residues and revealing distinct interfacial interaction mechanisms, offering valuable insights for downstream structural and functional studies.

bioinformatics↗

bioRxiv2026

Small Molecule Agonists of TREM2 Reprogram Microglia and Protect Synapses in Human Alzheimer's Models

Triggering receptor expressed on myeloid cells-2 (TREM2) is a key immune receptor in the central nervous system that regulates microglial phagocytosis, survival, and neuroinflammatory responses. TRME2 variants have been established as genetic risk factors for Alzheimers disease (AD). However, the therapeutic development of TREM2 modulators has been limited to antibody-based approaches that face limitations in blood-brain barrier penetration and manufacturing scalability. Furthermore, there are no FDA approved TREM2 therapeutics available to date marking an unmet therapeutic gap. Herein, we report the identification of the first TREM2 small molecule submicromolar binders as a result of optimizing compound 4a to yield S9 with TREM2 binding affinity of 0.95 {micro}M. S9 demonstrated robust TREM2 agonism in cellular assays where it induced proximal Syk phosphorylation, activated downstream NFAT transcriptional signaling, enhanced APOE internalization and microglial phagocytic capacity. Pharmacokinetic profiling of the optimized hits revealed S9 to exhibit improved drug-likeness compared to 4a with 7-fold enhanced aqueous solubility, superior metabolic stability, reduced intrinsic clearance and a 9-fold improved hERG safety margin. Functional validation in human iPSC-derived microglia confirmed that S9 suppresses amyloid-beta (A{beta})-induced IL-1{beta} secretion through a TREM2-dependent mechanism. In human neuron-microglia co-culture models exposed to amyloid stress, S9 treatment preserved synaptic integrity as measured by PSD95 expression that indicates promising neuroprotective activity. Together, these findings establish S9 as a first-TREM2 submicromolar small molecule TREM2 agonist which is orally bioavailable with favorable pharmacokinetic properties and promising therapeutic potential for the treatment of Alzheimers disease.

pharmacology and toxicology↗

bioRxiv2026

A CD40-Targeted IL-21 Fusokine Enables Rapid Generation of Human IL-10⁺Granzyme B⁺ Regulatory B Cells

Regulatory B cells (Bregs) have emerged as important modulators of immune homeostasis, complementing the classical roles of B cells in antibody production, antigen presentation, and provision of costimulatory signals and cytokines. Beyond promoting immunity, B cells can actively suppress inflammatory responses through specialized regulatory programs that limit effector T cell expansion and restrain pathogenic myeloid activation. These suppressive functions are mediated by mechanisms including secretion of IL-10, IL-35, and TGF-{beta}, expression of inhibitory ligands, and release of granzyme B. However, Bregs are rare and heterogeneous in humans, typically comprising less than 1-2% of circulating B cells, and defects in their frequency or function are associated with autoimmune and inflammatory diseases. The scarcity of endogenous Bregs has driven interest in their ex vivo generation as a cellular immunotherapy. Although several strategies efficiently induce regulatory B cells in murine systems, translation to human B cells has been limited by inefficiency, lack of scalability, or reliance on poorly defined culture conditions. Consequently, a robust and clinically compatible approach for generating human Bregs has remained elusive. With human peripheral blood B cells as starting materiel, we show that a CD40 targeted IL-21 gain of function fusion protein in combination with TLR9 activation induces a stable regulatory phenotype characterized by IL-10 and granzyme B expression in more than 95% of input B-cells. These induced Bregs display a coordinated transcriptional program distinct from conventional activation, significantly suppress activated human T cell proliferation and modulate inflammatory myeloid responses in vitro. In mice with human T-cell driven xenoGVHD, transfusion of T-cell donor matched Bregs significantly improves survival. These data support the feasibility of Breg manufacturing at scale for use a cellular pharmaceutical.

immunology↗

bioRxiv2026

Kinesin-1 trans-synaptically regulates synaptic localization of SARM1 for asymmetric neuron diversification

The Caenorhabditis elegans AWC olfactory neuron pair differentiates stochastically into two distinct subtypes, default AWCOFF and induced AWCON. A calcium signaling complex assembled by the TIR-1/SARM1 adaptor protein is transported from the AWC cell body to the axons, where it cell autonomously specifies the AWCOFF subtype through lateral signaling. UNC-104, the C. elegans homolog of the kinesin-3 motor protein KIF1A, acts non-cell autonomously in AWCON to control the synaptic localization of the TIR-1 signaling complex in promoting AWCOFF. Here, we identify a non-cell-autonomous role of unc-116/kinesin-1, similar to that of unc-104/kinesin-3, in promoting AWCOFF. unc-116 mutants, similar to unc-104 mutants, enhance the 2AWCON phenotype of a hypomorphic tir-1 mutant. Overexpression of unc-116 in AWC causes a 2AWCOFF phenotype, the same as the tir-1 overexpression phenotype. Like UNC-104, UNC-116 plays a non-cell-autonomous role in the AWCON cell to promote AWCOFF cell subtype by regulating the dynamic trafficking of TIR-1 along the AWC axon. UNC-116 is strikingly colocalized with UNC-104, while both are generally adjacent to TIR-1. Taken together, these results suggest a model in which UNC-116/kinesin-1 and UNC-104/kinesin-3 may work cooperatively to transport some unknown presynaptic factor(s) in the future AWCON cell that trans-synaptically regulates the dynamic trafficking of the TIR-1/SARM1 signaling complex to postsynaptic regions of the AWC axons in promoting the AWCOFF subtype.

developmental biology↗

bioRxiv2026

EssTFNet: Integration of Adaptive Time - Frequency and DNA Language Models for Interpretable Human Essential Gene Prediction

Essential genes are defined as those that are indispensable for an organisms survival. The loss of function of these genes results in cell death or an inability to complete the normal life cycle. Research on essential genes is pivotal in elucidating the origin and evolution of life, as well as in identifying potential therapeutic targets. Therefore, accurately predicting essential genes is of great scientific importance and has many applications in basic research and the biomedical field. In this study, we propose EssTFNet, a novel and interpretable deep learning framework that combines adaptive time-frequency analysis with a DNA language model to achieve accurate prediction of human essential genes while enabling mechanistic biological interpretation. Specifically, EssTFNet leverages the architecture of ATFNet, which innovatively maps DNA and protein sequences into equivalent time-series signals to extract periodic and non-stationary features, thereby enhancing the models capacity to capture complex sequence patterns. Through effective feature selection and architectural optimization, EssTFNet strikes a favorable balance among prediction accuracy, model interpretability, and cross-tissues generalization capability, significantly outperforming current mainstream sequence-based deep learning methods with an AUC of 0.8336 and an AUPR of 0.8212. Additionally, the DeepLIFT attribution method was employed to identify functional motifs closely associated with gene essentiality, offering valuable insights for experimental validation. For the convenience of researchers, we have developed an easy-to-use web server and made it along with the source code in a GitHub repository: https://github.com/QIANJINYDX/EssTFNet. Overall, this study presents a potentially useful methodological framework for human essential genes prediction, which could provide valuable insights for future research and applications in this field.

bioinformatics↗