Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Structural brain networks shape individual-level progression of brain atrophy after stroke

Stroke starts as a focal vascular lesion, but its structural consequences often extend beyond the lesion site, resulting in distributed brain atrophy whose organizing principles remain unclear. Here, using longitudinal MRI data from two stroke cohorts spanning the hyperacute to chronic stages, we tested whether and how post-stroke grey matter volume (GMV) change over time is constrained by large-scale brain networks across individuals. Coordinated deformation modelling showed that longitudinal GMV atrophy patterns were more strongly shaped by structural than by functional connectivity, with structural constraints already detectable in the acute phase. Network diffusion modelling further showed that atrophy patterns at 3 and 12 months were consistent with lesion-initiated propagation on the structural connectome, whereas model performance was weak in the early acute stage. The model-derived propagation stage did not increase monotonically with chronological time, indicating that it reflects the degree to which observed atrophy conforms to a network-consistent diffusion-like pattern rather than elapsed biological time. Inter-individual variation in propagation stage was associated with lesion size and with the topological and molecular properties of lesioned regions. Finally, lesion information combined with network diffusion modelling supported individualized prediction of later GMV atrophy patterns. These findings provide a network-based account of secondary degeneration after stroke and may inform individualized characterization of post-stroke structural reorganization.

neuroscience↗

bioRxiv2026

Molecular cloning of a novel, nervous system-specific RGS6 isoform lacking canonical G protein regulatory effects and with dominant negative actions

Regulator of G protein Signaling 6 (RGS6), heavily implicated in neurological and neuropsychiatric disorders, is enriched in mouse and human brain. Our initial cloning effort identified 36 RGS6 mRNAs in human brain. However, we recently identified an additional RGS6 protein isoform that is larger ([~]69kDa) than the ubiquitously expressed [~]56kDa RGS6L(+GGL) isoforms. Notably, this isoform, named "RGS6B" for "brain-specific", is selectively expressed in the nervous system of mice and humans. Here, we report the cloning of a new RGS6-encoding mRNA, which resembles the RGS6L1(+GGL) transcript identified in our initial cloning effort but includes a highly conserved novel exon (Alternative 3, A3) that alters the reading frame of terminal exon resulting in an extension of the protein C-terminus. When expressed in cells, RGS6LA31(+GGL) co-migrates with RGS6B, and, importantly, interfering RNA targeting exon A3 results in selective depletion of RGS6B in isolated primary cortical astrocytes. RGS6B is capable of stabilizing RGS6 binding partners R7BP and G{beta}5 and, in fact, exhibits an increased protein half-life relative to RGS6L. Both RGS6L and RGS6B are downregulated in human gliomas and share the ability to kill U87MG glioblastoma cells when overexpressed indicating conservation of non-canonical cytotoxic activity between RGS6L and RGS6B species. However, RGS6B lacks the ability to counteract Gi/o-dependent suppression of cAMP signaling, indicating a lack of functional GTPase activating protein (GAP) activity. Instead, RGS6B functions in a dominant negative manner to block Gi/o regulation by RGS6L. RGSB is the first identified RGS protein member that functions to promote, rather than inhibit, G protein signaling. The discovery of the molecular identity of RGS6B will now allow for delineation of unique functions for RGS6 protein isoforms in both physiological and pathophysiological brain states.

neuroscience↗

bioRxiv2026

Single-cell Transcriptomics Analyses Reveal Specialized Microglial Subsets with Oligodendrocyte-like Signatures

BackgroundMicroglial heterogeneity is a fundamental feature of brain homeostasis and pathology. The purpose of this study was to investigate the complexity of microglial plasticity by characterizing specialized oligodendrocyte-like microglial subsets. MethodsThe study was performed utilizing single-cell transcriptomics analyses and immunofluorescence staining to identify and profile microglial subpopulations. Additionally, spatial transferring and morphological analyses were conducted to determine the anatomical distribution and structural features of these specific cells. ResultsWe identified a distinct microglial subset termed dual-phenotype microglia (DPM), which co-expresses microglial and oligodendrocyte markers. DPM consisted of two subtypes with distinct functions: myelin-associated DPM (mDPM) and neuron-associated DPM (nDPM). Spatial and morphological evaluations revealed that mDPMs were sparsely distributed across the whole brain and exhibited a highly ramified architecture, whereas nDPMs were enriched in the hippocampal dentate gyrus. Mechanistically, we found that mDPM function was driven by the Sox10 regulon to modulate myelin maintenance and axonal ensheathment, while nDPM was orchestrated by Glis2, facilitating essential neuron-glia crosstalk and synaptic regulation. Furthermore, we demonstrated that nDPM and mDPM were predicted to undergo significant alterations in multiple sclerosis and Alzheimers disease. Notably, mDPMs were selectively enriched in active multiple sclerosis lesions, revealing that DPM were closely related to neuropsychiatric disorders. ConclusionsBy comprehensively characterizing the morphology, molecular signatures, and spatial logic of these oligodendrocyte-like microglial subsets, our study elucidated the complexity of microglial plasticity. These findings provided new insights into their diverse roles in central nervous system health and disease. Graphical abstractIdentification, Molecular Profiling, and Functional Modeling of Dual-Phenotype Microglia (DPM). (1) Discovery: Identification of the dual-phenotype microglia (DPM) population through single-cell transcriptomics. (2) Molecular Signatures: The transcriptomic identity of DPM subtypes is governed by specific regulatory networks. (3) Distribution & Pathology: Spatial mapping reveals divergent anatomical logic and disease relations for DPM subtypes. (4) Mechanism/Theory: A proposed functional model of mDPMs as "metabolic relay" and support units. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/724239v2_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@b7db1dorg.highwire.dtl.DTLVardef@9265e7org.highwire.dtl.DTLVardef@1605d82org.highwire.dtl.DTLVardef@19b048f_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Retrosplenial PV and SST interneurons shape egocentric spatial precision and stability

Accurate navigation requires egocentric representations of environmental geometry to be continuously updated by self-motion while remaining stable over time. The retrosplenial cortex (RSC) is central to this process, yet how local inhibitory circuits support this balance remains unclear. We show that parvalbumin (PV) and somatostatin (SST) interneurons regulate distinct components of egocentric spatial coding in RSC. PV interneurons are strongly modulated by self-motion and exhibit bearing-aligned synchrony that precedes SST activation, linking movement to egocentric coding precision. In contrast, SST interneurons display weak self-motion modulation but robust boundary-anchored activity with globally coherent dynamics that stabilize representations over time. Optogenetic silencing revealed dissociable effects: PV perturbation degraded egocentric coding precision while SST perturbation disrupted global population organization. Behaviorally, PV silencing impaired initial egocentric orientation while SST silencing preserved initial orientation but impaired its sustained update. These findings identify separable inhibitory mechanisms balancing rapid updating with representational stability during navigation.

neuroscience↗

bioRxiv2026

Serine Stabilizes SLC7A11 and Enhances Cystine Influx to Protect Against Acute Pancreatitis

Lethal sterile inflammatory diseases are linked to amino acid metabolism, but the role of serine remains unclear. Here, we show that dysregulated serine metabolism and reduced plasma serine levels correlate with disease severity of acute pancreatitis (AP) in patients and mouse models. Elevating serine levels via exogenous serine supplementation or pancreatic phosphoglycerate dehydrogenase (PHGDH) overexpression mitigates pancreatic injury, whereas a serine deprivation diet or pancreatic PHGDH knockdown exacerbates AP. Serine prevents cell death and oxidative stress in pancreatic acinar cells, human induced pluripotent stem cells-derived pancreatic organoids and mouse pancreatic tissue. Serine enhances cysteine and glutathione biosynthesis primarily by promoting solute carrier family 7 member 11 (SLC7A11)-dependent cystine uptake rather than by serving as a direct substrate. Mechanistically, the E3 ubiquitin ligase NEDD4 mediates ubiquitination and degradation of SLC7A11, whereas serine binds to NEDD4 and thereby inhibits SLC7A11 degradation. Similarly to serine, pharmacological inhibition of NEDD4 alleviates lipid peroxidation and pancreatic injury. These findings identify serine as a critical signaling regulator of SLC7A11 stability and oxidative stress, and provides a new therapeutic strategy for AP and associated sterile inflammatory disorders. HighlightsAcute pancreatitis (AP) is linked to abnormal serine metabolism and serine depletion. Serine prevents cell death in AP acinar cells, human pancreatic organoids and mice. Serine promotes SLC7A11-dependent cystine uptake and glutathione levels in acinar cells. Serine reduces NEDD4-mediated ubiquitination of SLC7A11. In briefSerine protects against cell death and pancreatic injury in acute pancreatitis by stabilizing SLC7A11 through disruption of NEDD4-mediated ubiquitination in acinar cells.

pharmacology and toxicology↗

bioRxiv2026

Learning the Language of the Microbiome with Transformers

Self-supervised pretraining has become central to biological machine learning, yet microbiome data remains comparatively underexplored in terms of both modeling approaches and evaluation frameworks. To address this gap, we present Atlas, a pretraining dataset of 539,308 microbiome datapoints from the MGnify database. Using Atlas, we train the Waypoint family of microbiome foundation models: a series of GPT-2 style causal language models ranging from 6M to 170M parameters. We also introduce Compass, a curated benchmark of eight predictive tasks spanning biome classification, drug-microbiome interactions, drug degradation, and infant gut development. Using this benchmark, we compare the performance of Waypoint models against classical baselines and the existing MGM foundation model. Our results show that pretraining leads to consistent and significant improvements in downstream task performance, that both dataset scale and tokenization strategy impact model quality, that pretraining is essential for achieving favorable scaling behavior and that representations learned during pretraining generalise between microbiome domains. Furthermore, pretrained transformer models begin to reliably outperform classical methods once training data exceeds roughly 10,000 examples - a threshold that is attainable for modern microbiome studies. Finally, we demonstrate that the Waypoint models achieve state-of-the-art performance among microbiome foundation models. Overall, our work highlights the importance of large-scale self-supervised pretraining in this domain and establishes Atlas, Compass, and the Waypoint models as valuable resources for the research community in this emerging field.

bioinformatics↗

bioRxiv2026

Identification of functional non-coding variants affecting Alzheimer's disease risk by Massively Parallel Reporter Assay

The majority of genetic risk variants for late-onset Alzheimers disease (LOAD) reside within non-coding genomic regions, suggesting they exert pathogenic effects by disrupting transcriptional regulatory programs. To systematically identify functional variants, we performed an unbiased, high-throughput Massively Parallel Reporter Assay (MPRA) in the THP-1 human monocytic cell line, screening 2,231 SNPs across 24 LOAD GWAS loci. We identified 62 variants exhibiting significant allele-specific transcriptional regulatory output, including rs636317 in the MS4A locus. The risk allele of rs636317 disrupts a CTCF binding motif, altering fine-scale chromatin looping. To validate these findings, we employed CRISPR/Cas9 to generate an allele-specific deletion of the rs636317 T allele in H9 human embryonic stem cells. Monocytes differentiated from these edited cells displayed increased expression of MS4A4E, MS4A6A, and TREM2, along with highly elevated levels of soluble TREM2 (sTREM2). These results provide a mechanistic link between a non-coding genetic variant, transcriptional regulation of the MS4A family, and TREM2-mediated immune responses in Alzheimers disease pathogenesis.

genetics↗

bioRxiv2026

A JNK-interacting protein 1 acts across the midline to mediate synaptic localization of the SARM1 calcium-signaling scaffold protein for asymmetric neuronal fate choice

The Caenorhabditis elegans AWC olfactory neuron pair specifies asymmetric subtypes, AWCOFF and AWCON, through stochastic and coordinated cell signaling events. UNC-104/kinesin-3 (KIF1A) and UNC-116/kinesin-1 motor proteins act in the AWCON cell to regulate the synaptic localization of the TIR-1/SARM1-assembled calcium signaling complex in the AWCOFF cell to promote AWCOFF. However, the molecular mechanism in the AWCON cell that acts non-cell autonomously to control synaptic TIR-1 calcium signaling to promote AWCOFF remains unclear. Here, we show that JIP-1, a conserved c-Jun N-terminal kinase (JNK)-interacting protein 1, mediates the synaptic localization of TIR-1 in the AWC axon to specify the AWCOFF subtype. A jip-1 loss-of-function mutant, identified from an unbiased forward genetic screen, has reduced localization of TIR-1 at synapses in the AWC axon and accumulation of TIR-1 in the AWC cell body. jip-1 mutants significantly enhance the 2AWCON phenotype of a hypomorphic tir-1 mutant. JIP-1, like UNC-104 and UNC-116, mainly acts non-cell autonomously in AWCON to specify the AWCOFF subtype. Our findings provide mechanistic insights into how cell-specific Ca2+ signaling proteins, such as TIR-1, target synaptic regions via intercellular signaling to promote neuronal diversification.

developmental biology↗

bioRxiv2026

Stromal Gasdermin D-mediated Pyroptosis Drives Maladaptive CD4⁺ T-cell Remodeling in Tet2-Deficient Hematopoiesis

An inflammatory bone marrow microenvironment is increasingly recognized as critical in myeloid disease evolution, yet how stromal inflammation interfaces with adaptive immunity remains poorly defined. Here, we show that stromal pyroptosis drives mutation-specific myeloid expansion by coordinating monocytic remodeling and CD4 T-cell activation. Genetic ablation of gasdermin D in the bone marrow stroma suppressed stromal pyroptosis and attenuated Tet2-deficient myeloid expansion. Tet2 deficiency skewed monocyte and macrophage differentiation toward an activated, antigen-presenting state that interacted with pyroptotic stromal cells to promote expansion of a distinct CD4 T-cell population. These cells expressed canonical T follicular helper markers (Bcl6, Cxcr5, Il21, and Cd40l) together with interferon-responsive and tissue-interaction programs, consistent with an inflammation-adapted TFH-like state. CD40L produced by these cells reinforced the expansion of Tet2-deficient monocytes and macrophages, establishing a feed-forward stromal-immune circuit. Disruption of this axis through stromal gasdermin D deficiency or CD40L blockade attenuated myeloid expansion in vivo. Consistent with these findings, patients with isolated TET2 loss-of-function mutations exhibited CD4 T-cell skewing and CD40L+ T-cell-rich tertiary lymphoid structures in the bone marrow. Together, these data identify a pyroptosis-dependent stromal-immune axis that links early myeloid inflammation to maladaptive remodeling of adaptive immunity and reveals a context-dependent therapeutic vulnerability in Tet2-deficient hematopoiesis.

cancer biology↗

bioRxiv2026

Nitrogen adaptation and phenotypic transitions from wild to improved sorghum

Crop domestication and subsequent improvement under modern agronomic conditions have altered the nitrogen (N) regimes experienced by crops, yet how selection has reshaped the genetic architecture of phenotypic responses to N availability remains poorly understood. Here, we integrated population genomic analyses of n = 289 sorghum accessions spanning multiple stages of domestication and improvement with N-response (NR) trait-associated variants identified through genome-wide association studies (GWAS) of phenotypic data collected under two contrasting N conditions in n = 347 diverse sorghum accessions. Unlike maize and sunflower, sorghum showed a reduced deleterious burden both genome-wide and within historically balanced and recently selected regions following domestication and improvement. Additionally, we identified 470 trait-associated loci (TALs), including 273 associated with NR traits. The effects of these NR-associated loci showed no apparent bias toward derived alleles, suggesting that selection on NR traits in sorghum has not been sufficiently strong or directional to consistently overcome genetic drift. Together, these results reveal distinct patterns of selection in sorghum and provide promising genetic targets for improving N-use efficiency in sustainable agricultural systems.

genomics↗

bioRxiv2026

Rewiring Oncogenic Transcriptional Complexes with Domain-ALTeration Chimeras (DALTACs) in Prostate Cancer

Transcriptional addiction to the androgen receptor (AR) underlies metastatic castration-resistant prostate cancer (mCRPC), where AR maintains oncogenic programs through domain-specific interactions with the acetyltransferases p300/CBP. Here, we describe a distinct therapeutic modality, Domain-ALTerAtion Chimeras (DALTACs), that rewire endogenous protein complexes by enforcing non-native domain-domain interactions. Our first-in-class AR-p300/CBP DALTAC-1 induces synthetic proximity between the AR ligand-binding domain and p300/CBP-bromodomain, misconfiguring their native interface and locking the complex in a non-productive state. DALTAC-1 triggers a super-inhibitory effect, suppressing AR-driven transcription and proliferation more potently than combined AR and p300/CBP inhibition. Mechanistically, DALTAC-1 reprograms p300/CBP substrate engagement, abolishing the histone mark H2B N-terminal acetylation (H2BNTac) while inducing neomorphic acetylation of AR and coactivators, ultimately collapsing the AR neo-enhanceosome. Chromatin profiling revealed redistribution of AR and p300/CBP toward palindromic AREs, accompanied by disruption of cofactor and transcriptional machinery recruitment at oncogenic AR/ERG neo-enhancers. DALTAC-1 exhibits exquisite lineage selectivity, displaying potent activity in AR-p300/CBP dual-dependent cells while sparing AR-negative cells. In multiple in vivo models, DALTAC-1 induces deep and durable tumor regressions. Together, these findings establish DALTACs as a broadly applicable strategy to rewire disease-defining complexes through domain-topology alteration, expanding induced-proximity therapeutics, while DALTAC-1's precise lineage-selectivity supports its translational potential in AR-driven prostate cancer.

cancer biology↗

bioRxiv2026

Identification of a neural circuit that enables safe, long-term torpor in mice

Torpor, a state of regulated hypothermia and hypometabolism, is a critical survival strategy in certain mammals. Previous studies established the primacy of neuron control in initiating acute torpor. However, whether neuromodulation can safely sustain torpor over the long term, and the specific governing pathways, remain unanswered challenges limiting its translational potential. Here we identify a distinct preoptic neuronal population expressing General control nonderepressible 2 ( G neurons) in mice that is essential and sufficient for torpor induction. Strikingly, sustained and selective activation of G neurons induces a stable, weeks-long torpid state (G neuron-driven long-term torpor, GLT), from which animals arouse without obvious behavioral deficits or tissue pathology. In contrast, long-term torpor driven by pan-neuronal activation of the same brain region (PLT) causes multiple post-recovery damages, underscoring the unique safety profile of selective pathway of G neurons. In a mouse cancer model, GLT directly suppressed tumor proliferation and markedly sensitized tumors to chemotherapy, achieving profound therapeutic outcomes. Together, we delineate a distinct neuronal population safely enabling prolonged torpor. This establishes a specific paradigm for inducing a stable and sustained hypometabolic state, providing a transformative platform for fundamental physiological research and pioneering clinical strategies against chronic pathologies such as cancer.

neuroscience↗

bioRxiv2026

RNABag: A Generalizable Transcriptome Foundation Model for Precision Oncology across Biopsy Modalities

Transcriptomic data is highly sensitive to cancer state and progression, making transcriptome-based foundation models a great promise for diverse clinical ontological inference. However, analyses of transcriptome are conventionally hindered by technical batch effects and limited generalization across platforms. Here, we introduce RNABag, a foundation model designed to generalize well to external datasets. In particular, the model only focuses on highly variable genes to reduce noise; and extensive data augmentation was utilized to pretrain RNABag to learn robust representations, invariant to batch variations. We demonstrate that RNABag achieves superior performance in pan-cancer tissue-of-origin classification and cancer detection in internal validation sets, as well as in zero-shot generalization to external cohorts and in-house clinical samples. Furthermore, RNABag, after specialized finetuning, exhibits strong capabilities in a wide range of clinical applications. The model effectively stratifies patient survival and predicts relapse risks, highlighting key molecular pathways driving tumor progression. Crucially, we extend RNABags utility to liquid biopsies, achieving high diagnostic accuracy in plasma cfRNA and tumor-educated platelets (TEPs), thereby supporting its application in non-invasive cancer monitoring. Interpretability analysis revealed pivotal role of tumor immune escape in the cancer induced plasma cfRNA signals. In summary, our study indicates that cancer states and progression may be monitored in details and precision via comprehensive modeling of transcriptome across biopsy modalities.

bioinformatics↗

bioRxiv2026

Epigenetically constrained astrocyte states underlie prefrontal cortex vulnerability in Down syndrome associated Alzheimer disease

Down syndrome (DS), caused by trisomy 21, confers a near-universal risk for Alzheimers disease (AD), yet individuals exhibit marked variability in cognitive decline, suggesting the presence of cellular mechanisms that modulate vulnerability and resilience. However, these mechanisms remain poorly defined in the human brain. Here, we integrate matched single-nucleus RNA-seq and ATAC-seq profiles from the prefrontal cortex (PFC) and amygdala (AMY) of age-matched individuals with DS with and without AD (DSAD), enabling direct comparison within a shared genetic background. We identify basal astrocytes in the PFC as a selectively vulnerable cell state in DSAD, characterized by both reduced abundance and coordinated transcriptional and regulatory reprogramming. This state exhibits a shift away from homeostatic support functions, with decreased cytokine signaling and lipid-handling programs, alongside increased steroid- and nuclear receptor-associated activity. Concomitantly, chromatin accessibility profiling reveals reduced engagement of immune- and stress-responsive transcription factor programs, including AP-1, STAT, and BACH families, with linked regulatory perturbations at loci such as ABCA1, DAB2IP, and IL1RAP. Together, these findings define a previously unrecognized astrocyte state marked by epigenetic constraint and diminished responsiveness to stress and inflammatory signals, distinguishing it from classical reactive astrocyte phenotypes. Our results nominate PFC basal astrocytes as a key locus of vulnerability in DSAD and suggest that failure to mount appropriate astrocyte responses, rather than overt activation alone, may contribute to neurodegenerative progression.

bioinformatics↗

bioRxiv2026

A sequence-based proactive intelligence for influenza antigenic profiling improves vaccine strain selection

Seasonal influenza viruses accumulate antigenic changes, eroding population immunity and necessitating recurrent vaccine updates. Hemagglutination inhibition (HI) assays are the standard for measuring antigenic relationships between circulating and vaccine strains; however, their limited throughput constrains the scale and timeliness of surveillance. Here, we present fluProfiler, a foundation-model-based framework that learns a stable mapping from viral sequences to antigenic space and uses this representation to support influenza antigenic prediction, vaccine strain evaluation, and diversity-driven sampling. fluAgPredictor aligns hemagglutinin (HA) and neuraminidase (NA) sequence representations with HI-derived antigenicity, enabling accurate and consistent inference of pairwise antigenic distances across surveillance-aligned evaluation settings. Without prior annotation of antigenic sites, it identifies key residues in immunodominant epitopes and reveals the cooperative contributions of HA and NA to antigenic variation. Building on this antigenic-space representation, fluVacSelector provides antigenic coverage scores that are concordant with World Health Organization (WHO) vaccine recommendations while also flagging potential candidates that may offer broader coverage ahead of formal consultations. fluAgEnhancer further leverages the same representation to prioritize antigenically informative and diverse strains for experimental characterization, achieving comparable predictive accuracy with approximately 25% fewer HI measurements than random sampling. Together, these modules provide a high-throughput and interpretable complement to HI testing, converting routine genomic surveillance into a more proactive, data-driven support system for antigenic monitoring and vaccine strain selection.

bioinformatics↗

bioRxiv2026

Benchmarking MSA pairing for protein-protein complex structure prediction reveals a depth-over-pairing principle

AlphaFold-Multimer (AFM) and AlphaFold3 (AF3) have revolutionized protein-protein complex structure prediction. However, it remains unclear whether elaborate MSA pairing is a strict prerequisite for achieving high accuracy. Here, we systematically evaluated diverse MSA construction strategies using a rigorous benchmark of 439 heterodimers. We found that incorporating paired MSAs yields only marginal improvements in structure prediction. Crucially, experiments using shuffled pairing patterns reveal that these gains stem not from specific pairing constraints, but rather from the increased depth of input MSAs, a finding that also extends to higher-order multimers. Furthermore, we demonstrate that prioritizing the inclusion of more homologs without pairing proves to be a superior strategy, enhancing performance for both intra- and inter-species dimers as well as the more challenging antibody-antigen complexes. This observation is substantiated by the recent success of the omicMSA strategy. Mechanistic analysis indicates that this capability is driven by inter-subunit physicochemical complementarity and the intrinsic architecture of the AF3 network. Furthermore, we identify critical bottlenecks that limit prediction accuracy, including large complex dimensions, restricted interface areas, and low experimental resolution. These findings establish a "depth-over-pairing" principle, offering new insights for improving protein complex prediction.

bioinformatics↗

bioRxiv2026

Multi-Agent Orchestration for Knowledge Extraction and Retrieval: AI Expert System for GPCRs

We present GPCR-Nexus, an AI-driven platform for integrated exploration of G protein-coupled receptor (GPCR) biology that unifies structured databases with unstructured scientific literature. The system combines a GPCR-ligand knowledge graph with vector-based semantic retrieval to enable comprehensive, up-to-date information access. Central to GPCR-Nexus is a multi-agent architecture in which specialized components coordinate query planning, evidence retrieval, validation, and synthesis. This design ensures that generated responses are grounded in verifiable sources while maintaining coherence across heterogeneous data modalities. By jointly leveraging curated databases and primary literature, GPCR-Nexus enables context-aware reasoning over molecular interactions, functional mechanisms, and disease associations. The platform produces citation-backed outputs with traceable evidence, addressing limitations of conventional database queries and standalone language models. We detail the system architecture, data integration strategy, and agent orchestration framework, and demonstrate its utility through representative query scenarios. GPCR-Nexus provides a scalable approach to combining structured and unstructured biomedical knowledge using agent-based AI, offering improved accuracy, interpretability, and coverage. This work establishes a foundation for trustworthy, AI-assisted knowledge synthesis in GPCR research and drug discovery.

bioinformatics↗

bioRxiv2026

Development of host-mimicking legume-based media for robust induction of sporulation in soybean-associated Cercospora species

Cercospora species associated with soybean cause Cercospora leaf spot and purple seed stain, which are major diseases affecting soybean production worldwide and can lead to significant yield and seed quality losses. However, unstable and poor sporulation under laboratory conditions remains a critical challenge, hindering the recovery of genetically homogeneous isolates and the establishment of standardized experimental protocols. These limitations further restrict our understanding of the biology, epidemiology, and pathogenicity of these pathogens. In this study, we developed specialized legume-based culture media derived from soybean and pea tissues to mimic host-associated environmental conditions. We compared the sporulation efficacy of these media with commonly used artificial media, including potato dextrose agar (PDA) and V8 juice agar. Our results demonstrated that legume-based media consistently supported higher levels of sporulation than PDA and V8 across multiple strains, although conidial yields varied depending on the strain and medium concentration. Transcriptional analysis of sporulation-related genes revealed that while abaA, wetA, and steA did not show significant differential expression among media, velB exhibited distinct medium-dependent expression patterns. Further evaluation using additional field isolates confirmed that legume-based media provide a more reliable method for inducing sporulation than PDA. Overall, legume-based media represent a practical and effective approach for promoting sporulation in soybean-associated Cercospora species under laboratory conditions.

microbiology↗