Biology subjects

Zhou, J.

Publications and source records attributed to Zhou, J..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Subthalamic nucleus controls cautious action timing under threat

Adaptive goal-directed actions performed under the threat of punishment introduce a demand for caution, often expressed as delayed response timing that balances urgency against error risk by allowing more time for cognitive evaluation. Although this form of temporal regulation is essential for survival, its underlying neural mechanisms remain poorly understood. We show that glutamatergic neurons in the subthalamic nucleus (STN) regulate the timing of cued actions to avoid harm. Optogenetic activation of the STN, or its projections to the midbrain but not the globus pallidus, modulates action timing in a frequency-dependent manner, accelerating initiation to the extent that animals can no longer respond cautiously, defer actions, or stop initiated actions. These results show that the STN shapes goal-directed behavior by gating action-initiation timing, establishing its midbrain projections as a key circuit for balancing urgency and caution under threat. Significance statementThis work shows that activity in the subthalamic nucleus (STN) helps set the timing of actions triggered by warning cues. By activating STN neurons and their projections to the midbrain, we found that stimulation made animals respond faster, and high-frequency activation eliminated their ability to delay actions when caution was required or to withhold actions that would otherwise be punished. These findings highlight a key brain pathway that governs when actions are initiated, a function that is often disrupted in neurological and psychiatric disorders.

neuroscience↗

bioRxiv2025

Unraveling Candidatus Dermatophostum as a Novel Genus of Polyphosphate-Accumulating Organisms for High-Strength Wastewater Treatment

Dermatophilaceae polyphosphate-accumulating organisms (PAOs), formerly classified as Tetrasphaera PAOs, play pivotal roles in enhanced biological phosphorus removal (EBPR). However, their phylogenetic diversity, ecological preferences, and metabolic traits remain poorly characterized, and a robust marker gene for their classification is lacking. Here, we performed an extensive phylogenomic and metabolic analysis of Dermatophilaceae PAOs utilizing 46 newly recovered metagenome-assembled genomes (MAGs) from a laboratory-scale EBPR reactor treating high-strength wastewater and full-scale wastewater treatment plants. These analyses revealed a previously uncharacterized PAO genus, named Candidatus Dermatophostum, which is adapted to high-phosphorus environments. Its representative species, Ca. D. ammonifactor, was enriched in the EBPR reactor and its PAO phenotype was confirmed by polyphosphate staining and fluorescence in situ hybridization. Genomic, transcriptomic, and protein structure analyses revealed its specialized metabolic capabilities for phosphate metabolism, glycogen synthesis and dissimilatory nitrate reduction to ammonium. Moreover, Ca. Dermatophostum was found to be widely distributed across WWPTs worldwide, underscoring both its ecological importance and its potential role in mitigating nitrous oxide (N2O) emissions. Finally, we propose a ppk1-based classification framework that resolves Dermatophilaceae PAOs into six distinct clades, consistent with whole-genome phylogeny, and demonstrates that ppk1 can serve as a reliable marker gene for tracking these populations. Together, these findings expand the ecological and functional understanding of Dermatophilaceae PAOs and highlight their promise for advancing sustainable wastewater treatment and resource recovery.

microbiology↗

bioRxiv2025

Fully computational design of PAM-relaxed Staphylococcus aureus Cas9 with expanded targeting capability

CRISPR-Cas9 nucleases have transformed genome engineering, yet their application is often constrained by protospacer-adjacent motif (PAM) requirements. Staphylococcus aureus Cas9 (SaCas9) is particularly attractive for in vivo applications due to its compact size; however, its NNGRRT PAM limits targetable genomic sites. Here, we report KRH, a SaCas9 variant designed entirely from the wild-type enzyme through a fully computational point-mutation design workflow, UniDesign, without additional experimental optimization. As expected, KRH efficiently recognizes an expanded NNNRRT PAM and exhibits substantially enhanced editing efficiency at non-canonical PAM sites, with improvements of up to 116-fold over the wild type. KRH achieves genome- and base-editing efficiencies comparable to, or exceeding, those of the well-known evolution-derived KKH variant. Computational modeling by UniDesign provides a mechanistic explanation for the PAM relaxation observed in both KRH and KKH, with structural and energetic analyses revealing that KRH relaxes PAM specificity by fine-tuning the balance between sequence-specific interactions with PAM bases and nonspecific contacts with the DNA backbone. Beyond its practical utility, KRH demonstrates that computational design can identify a minimal set of mutations sufficient to remodel the PAM interface while preserving high nuclease activity. This approach recapitulates--and in some cases surpasses--the performance of evolution-derived variants, offering a scalable strategy for high-throughput Cas9 engineering. Overall, these results establish KRH as a blueprint for rationally engineered, PAM-relaxed nucleases and underscores the power of computational design to accelerate next-generation genome editing.

bioengineering↗

bioRxiv2025

A changing hierarchy of environmental time cues guide development of the migratory pest moth Loxostege sticticalis

Insects use environmental cycling cues to align developmental progression. In holometabolous insects, the progression from larva to adulthood entails decision points, i.e., larval diapause and adult eclosion, that engage circadian timing mechanisms. What environmental time cues dynamically interact to regulate these developmental checkpoints lying at the intersection of the orthogonal timing systems, remains elusive. We used the seasonally migratory insect Loxostege sticticalis to disentangle the influence of photoperiod regimes and temperature conditions at distinct checkpoints of larval growth and metamorphosis. We here employed sensory conflict paradigms to reveal that the relative dominance of these cues changes over ontogeny. Our results confirm that diapause is induced primarily by the photoperiod during early larval development, rather than by the diel thermoperiod. In contrast, the circadian clock-controlled adult eclosion, normally locked to the first hour of the daybreak, is jointly controlled by light and temperature cycles. An increase in the constant temperature advanced the peak timing of daily eclosion. On the other hand, the interval timing mechanism regulating the duration of the eclosion event is tuned specifically by the night temperatures. Together, photoperiod dominates early developmental decisions, but thermoperiod gains weight at later stages. This shifting hierarchy provides a mechanistic framework for understanding phenological plasticity. Since the timing of eclosion presents a window of increased vulnerability for this pest insect, our results could help to optimize the daily timing of pest management intervention under variable thermal and light conditions.

ecology↗

bioRxiv2025

Spacing effect improves generalization in biological and artificial systems

Generalization is a fundamental criterion for evaluating learning effectiveness, a domain where biological intelligence excels yet artificial intelligence continues to face challenges. In biological learning and memory, the well-documented spacing effect shows that appropriately spaced intervals between learning trials can significantly improve behavioral performance. While multiple theories have been proposed to explain its underlying mechanisms, one compelling hypothesis is that spaced training promotes integration of input and innate variations, thereby enhancing generalization to novel but related scenarios. Here we examine this hypothesis by introducing a bio-inspired spacing effect into artificial neural networks, integrating input and innate variations across spaced intervals at the neuronal, synaptic, and network levels. These spaced ensemble strategies yield significant performance gains across various benchmark datasets and network architectures. Biological experiments on Drosophila further validate the complementary effect of appropriate variations and spaced intervals in improving generalization, which together reveal a convergent computational principle shared by biological learning and machine learning.

neuroscience↗

bioRxiv2025

Normative modeling of brain morphology reveals neuroanatomical heterogeneity and biological subtypes in major depressive disorder

BACKGROUNDMajor Depressive Disorder (MDD) is characterized by high neurobiological heterogeneity, which hinders precise diagnosis and treatment. Traditional group-level neuroimaging analyses fail to capture individual differences, while normative modeling offer a promising approach to quantify individual deviations from healthy brain structure patterns, facilitating the identification of biological subtypes and offering a data-driven framework to dissect this heterogeneity. METHODSUsing 1,190 healthy controls, we constructed normative developmental trajectories of gray matter volume (GMV) across 246 Brainnetome-defined regions using Bayesian linear regression. Deviation maps were derived for 398 MDD patients. k-means clustering was employed to identify GMV-based biotypes. Then, the clinical characteristics and anatomical differences among these subtypes were explored, along with the post-treatment clinical features and treatment responses of participants who completed the 8-week antidepressant treatment within each subtype. RESULTSPatients with MDD exhibited widespread yet individually variable GMV deviations. Clustering analysis revealed two subtypes: Subtype 1 displayed predominantly negative deviations in sensorimotor and occipital cortices, whereas Subtype 2 showed widespread positive deviations in temporal and posterior cingulate regions. Subtype 1 had higher extraversion and symptom-linked deviation patterns; in Subtype 2, deviation burden correlated with generalized anxiety. Longitudinally, Subtype 1s GMV deviation changes predicted symptom improvement, while Subtype 2s deviations correlated with baseline severity. CONCLUSIONSNormative modeling of GMV reveals marked neuroanatomical heterogeneity in MDD and identifies subtypes with distinct clinical and treatment-related characteristics, laying a foundation for precision psychiatry and individualized interventions.

neuroscience↗

bioRxiv2025

A haplotype-resolved T2T genome assembly of Indigofera pseudotinctoria reveals the genetic basis of flavonoid biosynthesis in Chinese Indigo

Indigofera pseudotinctoria, commonly known as Chinese Indigo, is a multifunctional leguminous shrub widely distributed in East Asia, valued for its medicinal, ecological, and forage importance, and naturally adapted to drought and nutrient-poor soils. However, the absence of genomic resources has hindered insights into the genetic basis of its bioactive metabolites and adaptive traits. Here, we present a haplotype-resolved, telomere-to-telomere (T2T) reference genome of I. pseudotinctoria, which represents the first complete genome within the genus Indigofera. By integrating PacBio HiFi sequencing, Oxford Nanopore ultra-long reads, and Hi-C chromatin conformation sequencing technologies, we successfully constructed two gap-free haplotypes assemblies (647.38 Mb and 657.52 Mb), characterized by high BUSCO completeness and QV scores, and fully captured all telomeric sequences. Comparative analysis between haplotypes revealed extensive synteny but notable structural heterozygosity but notable structural heterozygosity. Approximately 46% of structural variations overlap with genic or regulatory regions, leading to allele-specific expression divergence. Between the two haplotypes, we identified 2,607 and 2,331 haplotype-specific genes, reflecting a complementary functional specialization in defense and repair versus metabolism and growth. Integrative transcriptomic and metabolomic profiling across six tissues reconstructed the flavonoid biosynthetic network and identified MYB, bHLH, NAC, WRKY, and ERF transcription factors regulating five key pharmacologically active flavonoids (Calycosin, Butein, Sulfuretin, Chrysoeriol, and Genistin). These results collectively uncover the haplotype-specific regulatory and structural basis of Indigofera pseudotinctoria and establish a high-quality genomic framework for evolutionary, medicinal, and metabolic engineering studies in leguminous plants, and provide a framework for molecular breeding and bioactive compound discovery in medicinal legumes.

genomics↗

bioRxiv2025

scProtoTransformer: Scalable Reference Mapping Across Molecules, Cells and Donors

The rapid accumulation of single-cell data has made it possible to comprehensively characterize biological systems at molecular, cellular, and donor levels. However, scalable reference mapping across different resolutions remains a major challenge in current research. Here, we propose scProtoTransformer, a prototype-based Transformer architecture designed to achieve scalable reference mapping across molecular, cell, and donor levels. scProtoTransformer introduces a knowledge-guided prototype tokenizer that projects gene expression into biologically interpretable pathway prototypes, effectively reducing numerical batch effects while preserving biological semantic patterns. Furthermore, by leveraging knowledge distilled from the foundation model and a dynamic supervised fine-tuning strategy, scProtoTransformer achieves robust biological representations with reduced pre-training requirements. Benchmark experiments across molecular, cell, and donor-level reference mapping demonstrate that scProtoTransformer delivers competitive or even superior performance compared with state-of-the-art approaches, while providing interpretability through biologically prototypes. Together, these results establish scProtoTransformer as a unified framework for scalable reference mapping, laying the foundation for systematic understanding from genes to individuals.

bioinformatics↗

bioRxiv2025

RamanOmics Decodes Spatial Vibrational-Molecular Architecture and Rewiring in Aging and Repair

Aging and tissue repair involve multilayered and spatially heterogeneous remodeling across transcriptional, biochemical, and cellular dimensions, yet prevailing definitions rely on isolated molecular markers that obscure how biochemical and transcriptional states co-evolve in tissues. Here we present RamanOmics, a multimodal framework that integrates single-nucleus RNA sequencing (snRNA-seq), spatial transcriptomics, and label-free Raman imaging to map the spatial vibrational-biochemical and molecular architecture of aging and senescence directly in intact tissues. Applied to mouse lung and skin, RamanOmics generates spatially resolved biochemical-molecular maps revealing tissue-specific programs: lung senescent cells are enriched for extracellular matrix (ECM) remodeling and TGF-{beta} signaling (Serpine1, Dab2, Igfbp7), whereas skin senescence is dominated by keratinization and barrier homeostasis modules (Krt10, Lor, Sbsn). Across tissues, we identify a conserved branched-chain fatty-acid-linked biochemical profile and Raman signature (1131-1135 cm-{superscript 1}) that robustly marks p21 senescent cells. To unify these layers, we develop a machine learning derived "multimodal barcode" that quantitatively integrates biochemical and transcriptional features, enabling non-destructive identification of senescence in situ. In a wound-healing model, RamanOmics further reveals coordinated reactivation of barrier-repair programs in senescent cells, marked by upregulation of Krt10, Lor, Sbsn, Sfn, and Dmkn together with matching increases in lipid-associated Raman signatures, confirming biological generalizability beyond steady-state aging. By directly integrating gene programs to spatial vibrational-biochemical states, RamanOmics provides a general framework and resource for scalable, multimodal profiling of cellular states.

systems biology↗

bioRxiv2025

Neddylation Regulates Mitochondrial Dynamics and Turnover in the Adult Heart

BACKGROUNDDisruption of mitochondrial homeostasis drives cardiomyopathy and heart failure, yet upstream regulatory mechanisms remain poorly defined. Neddylation, a reversible post-translational conjugation of the ubiquitin-like protein NEDD8 by E1/E2/E3 enzymes, is essential for cardiac morphogenesis, but its role in the adult heart is unknown. METHODSWe assessed the relevance of neddylation to human cardiac disease by gene set enrichment analysis of ischemic (ICM) and non-ischemic cardiomyopathy (NICM) datasets and by immunoblotting and qPCR of ventricular tissue from patients with ICM or dilated cardiomyopathy (DCM). In adult mice, we induced cardiomyocyte-restricted deletion of the NEDD8-activating enzyme 1 (NAE1) by tamoxifen injection and monitored cardiac function at baseline and after transverse aortic constriction (TAC). Bulk RNA-seq 4 weeks post-tamoxifen was combined with bioenergetic, biochemical, and ultrastructural analyses. To assess mitochondrial dynamics, we generated NAE1/MFN2 and NAE1/DRP1 double-knockout mice. Cullin activity, mitochondrial ubiquitination, and mitophagy were measured in hearts and cultured cardiomyocytes. RESULTSNeddylation pathways were dysregulated in human ICM and NICM datasets and in failing ICM/DCM myocardium. Cardiomyocyte-specific NAE1 deletion caused systolic dysfunction and heart failure by 10 weeks post-tamoxifen, culminating in premature death and exacerbating TAC-induced pressure-overload heart failure. At 4 weeks, NAE1 loss repressed metabolic and mitochondrial bioenergetic programs, reduced ATP production, and impaired respiration. Electron microscopy revealed elongated mitochondria and accumulated mitophagic vesicles, with dysregulation of DRP1, MFN2, PINK1, LC3-II, and p62. DRP1/NAE1 co-deletion accelerated systolic failure relative to either single knockout, whereas MFN2/NAE1 co-deletion did not alter early disease progression, implicating pathogenic mitochondrial hyperfusion. Genetic NAE1 depletion in vivo and pharmacologic NAE1 inhibition in vitro impaired mitophagic vesicle formation and flux, inactivated cullin scaffold proteins, reduced mitochondrial ubiquitination, and blunted mitophagic clearance. CONCLUSIONSCardiac neddylation preserves adult heart function by coordinating mitochondrial fusion-fission dynamics and sustaining cullin-dependent ubiquitination and turnover of damaged mitochondria. These findings identify neddylation as a key regulator of mitochondrial quality control and link its disruption to human cardiomyopathy. Therapeutically, targeting the neddylation-cullin axis may limit mitochondrial dysfunction, enhance mitophagy, and improve energetic reserve in failing hearts, while neddylation signatures in patient myocardium may help guide stratification and precision therapy for cardiomyopathy. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABS* Demonstrates for the first time that the NEDD8-activating enzyme (NAE1)driven neddylation pathway is indispensable for maintaining mitochondrial quality control in the adult heart. * Links loss of neddylation to mitochondrial hyperfusion, impaired mitophagy, and rapid progression to heart failure. * Reveals that neddylation promotes cullin-RING ligase-mediated ubiquitination of damaged mitochondria, coupling mitochondrial dynamics with turnover. What Are the Clinical Implications?* Restoring or enhancing cardiac neddylation may represent a novel therapeutic avenue for cardiomyopathies characterized by mitochondrial dysfunction. * Pharmacologic agents that bolster DRP1-dependent fission or activate cullin neddylation could potentially normalize mitochondrial dynamics and improve myocardial energetics. * Conversely, systemic neddylation inhibitors now in oncology trials warrant careful cardiac monitoring, as they may precipitate mitochondrial injury and heart failure. * Circulating or tissue markers of neddylation might help stratify patients at heightened risk for mitochondrial-driven cardiac disease and guide precision therapy.

physiology↗

bioRxiv2025

Structural Basis of Human Kinetochore-Microtubule Coupling by the Ndc80 and Ska Complexes

Faithful chromosome segregation depends on kinetochore-microtubule attachments that must be load-bearing, dynamic, and tightly regulated. In human cells, the Ska and Ndc80 complexes (SkaC and Ndc80C) cooperate to sustain these attachments, but how they are organized on microtubules and coupled to end dynamics remains unclear. Here, our cryo-EM structure shows that Ndc80C and SkaC form a coupled assembly across neighboring protofilaments. A phosphorylation-sensitive SKA3 tether binds a defined kink in the Ndc80 coiled-coil, positioning SKA1 beside Ndc80C. These two complexes jointly sandwich the -tubulin tail and sense its polyglutamylation state. SkaC recognizes the extended microtubule lattice and, through the SKA3 tether, confers this selectivity onto Ndc80C, enabling Ndc80C tip tracking while strengthening microtubule stabilization. Together, our findings define the structural basis of Ndc80C-SkaC cooperation and uncover a phosphorylation-regulated, polyglutamylation-sensitive, and lattice-state-dependent mechanism for robust and regulated KT-MT coupling during chromosome segregation in mitosis.

biophysics↗

bioRxiv2025

ERAD Activity Distinguishes the Functional Heterogeneity of Hematopoietic Stem Cells

Hematopoietic stem cells (HSCs) rely on precisely controlled proteostasis to sustain lifelong self-renewal, yet whether intrinsic proteostatic characteristics can prospectively define functional diversity within the HSC pool remains unknown. In this study, we developed a dual-fluorescence reporter system to visualize endoplasmic reticulum-associated degradation (ERAD) activity in vivo and discovered that ERAD activity can prospectively predicts the long-term reconstitution potential of HSCs. Remarkably, ERAD states were maintained through self-renewal, revealing an inheritable "proteostatic memory" within the HSC pool. Transcriptomic and functional analyses identified SOCS2 as a key regulator of this process: SOCS2 inhibits JAK2 signaling to sustain ERAD activity, whereas hyperactive JAK2 interacts with the ERAD E3 ligase Hrd1 and suppresses VCP-mediated misfolded substrate. These findings define a SOCS2-JAK2-ERAD axis that connects cytokine signaling to intrinsic proteostasis remodeling, establishing ERAD activity as a predictive and heritable marker of HSC function and providing a conceptual framework for understanding hematopoietic stem cell heterogeneity.

cell biology↗

bioRxiv2025

Beyond correlation: Causal discovery of cell program interactions in lung tissue

Cell-cell communication networks govern tissue function in health and disease, yet existing computational tools rely on static ligand-receptor databases or correlation-based analyses that cannot distinguish direct causal relationships from confounded or indirect associations. We introduce Cell-CLIP (Cellular Causal Learning and Inference Pipeline), a modular framework that combines (i) mask-aware patient-level JASMINE activity scoring with low-percentile imputation in raw activity space, (ii) five complementary causal-discovery algorithms -- PC, GES, FCI, DirectLiNGAM, and GRaSP -- each fed an algorithm-matched per-column transform of the same masked JASMINE matrix, (iii) direction-preserving bootstrap aggregation with a weighted two-phase consensus, (iv) Joint Causal Inference (JCI) for principled pooling of patient cohorts via context indicators, and (v) a residual-independence (RESIT) direction audit, all evaluated under a systematic three-by-three-by-three hyperparameter sweep. Applied to a 611-patient multi-phenotype lung atlas spanning normal tissue, COVID-19 pneumonia, and lung cancer, the cross-cohort joint-causal-inference graph constructed by stratifying patients into normal, COVID-19, and tumour contexts before pooling recovers 100% of evaluable curated ground-truth edges (8/8; Wilson 95% CI 0.68-1.00) with 75.0% direction accuracy (6/8; 95% CI 0.41-0.95) and zero forbidden-orientation violations (0/8; 95% CI 0.00-0.32) -- the only configuration in a comprehensive ablation series spanning 7 cohort/pool configurations, 27 hyperparameter settings, and 3 consensus types to simultaneously reach all three optimal Pareto corners. The single-cohort universal cross-phenotype graph (12 cross-phenotype programs over the full 611-patient atlas) similarly achieves 100% evaluable recall (8/8; 95% CI 0.68-1.00) with 62.5% direction accuracy (5/8; 95% CI 0.31-0.86) and zero forbidden violations (0/3; 95% CI 0.00-0.56) under the same systematic hyperparameter sweep with low-percentile imputation, exceeding an earlier zero-imputation baseline configuration of the pipeline on every reported metric (Table 6, Table 8); given small ground-truth denominators (n_eval = 8), these point-estimate improvements lie within the Wilson 95% intervals of the baseline and should be read as direction-of-effect rather than as confirmatory comparisons. We further show that single-cohort causal inference on the disease-extended pooled cohorts (which apply the COVID- and cancer-extended program sets to all 611 patients) recovers strong skeleton recall (35.0%-55.2% evaluable) but suffers a structural direction collapse (down to 14.3% direction accuracy and 60% forbidden rate at union) caused by within-cohort averaging over heterogeneous normal-plus-disease patient populations; the patient-stratified joint-causal-inference pool dissolves this collapse without altering the underlying algorithms. Cell-CLIP provides a hypothesis-generating framework for inferring directed cell-program networks from patient-level scRNA-seq atlases, with all reported relationships requiring experimental validation due to observational data limitations. O_TBL View this table: org.highwire.dtl.DTLVardef@1b18810org.highwire.dtl.DTLVardef@5c027eorg.highwire.dtl.DTLVardef@a7b806org.highwire.dtl.DTLVardef@122adf2org.highwire.dtl.DTLVardef@1ca0a39_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 6C_FLOATNO O_TABLECAPTIONHeadline validation metrics across reporting cohorts, with Wilson 95% confidence intervals on every binomial rate. C_TABLECAPTION C_TBL O_TBL View this table: org.highwire.dtl.DTLVardef@1653cb1org.highwire.dtl.DTLVardef@173c6baorg.highwire.dtl.DTLVardef@1fc115forg.highwire.dtl.DTLVardef@1d87e39org.highwire.dtl.DTLVardef@46d53b_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 8C_FLOATNO O_TABLECAPTIONAblation matrix: evaluable recall at the recall-best configuration. Variants are defined in the Sensitivity analysis section. Cells marked not run were not executed for that combination of cohort x variant; reasons are given in the table caption. C_TABLECAPTION C_TBL

systems biology↗

bioRxiv2025

Energy Landscape Analysis Reveals Thalamic Modulation of Brain State Transitions During Movie Watching

Understanding how large-scale brain networks dynamically coordinate during complex, real-world experiences remains a crucial topic in contemporary neuroscience. Leveraging naturalistic paradigm, this study employed energy landscape modeling to characterize the temporal dynamics of brain state transitions and their functional significance. Using the Sherlock fMRI dataset, we identified two dominant brain states: a perception- and attention-oriented state, and an introspective, integrative state, each associated with distinct canonical brain networks. State transitions were differentially associated with the recruitment of these networks and manifested as either the "easy" or "hard" route, depending on the energy required for the transition. Notably, we demonstrated that the probability of specific state transitions robustly predicted inter-subject correlation within three clusters: subcortical-rich, salience/attention-rich, and DMN-rich regions. This indicates that flexible reorganization of cortical networks underlies shared neural engagement during ecologically valid experiences. Critically, the thalamus emerged as a central modulator, displaying activity changes and dynamic nucleus-specific thalamocortical connectivity changes tied to distinct transition profiles. Together, our findings shed light on the energetic and network mechanisms that orchestrate brain dynamics during naturalistic cognition and underscore the pivotal role of cortico-thalamo-cortical circuits in governing flexible, collective neural responses to richly structured real-life stimuli.

neuroscience↗

bioRxiv2025

Modeling the structure-conditioned sequence landscape for large-scale protein design with TriFlow

Generative models have revolutionized computational protein design, and the design of high-quality sequences given backbone structure is a critical component for success. Current state-of-the-art design pipelines utilize sequence design methods with local structural context and autoregressive generation. To improve efficiency and quality of sequence design, we developed TriFlow, a model that combines a RoseTTAFold-like three-track architecture for global structural context with discrete flow-matching for efficient few-step sequence generation. We trained TriFlow on a large dataset of interacting protein chains from Protein Data Bank and interacting domains from AlphaFold protein structure Database to enrich its knowledge of natural protein and domain interfaces. TriFlow outperforms existing sequence design methods like ProteinMPNN across diverse benchmarks, including de novo binder design, where it boosts the in silico success rate of state-of-the-art design pipelines such as BindCraft. We demonstrated this by conducting a large-scale benchmark, generating and computationally validating binders for over 500 diverse protein targets. Experimental validation on a small set of targets also suggests that the performance of TriFlow is on par with BindCraft. By leveraging the model to explore the designed sequence landscape, we discovered that we can effectively highlight functional sites, by contrasting designed sequences that reflect structure constraints with natural evolutionary profiles. As a practical demonstration of its capabilities, we applied our pipeline to systematically design specific binders against human class I cytokines, computationally optimizing for on-target affinity while minimizing off-target interactions, demonstrating that specificity also scales with inference time and computational budget. TriFlow thus provides a robust framework both for large-scale protein engineering and for exploring the fundamental principles of the structure-conditioned sequence landscape. TriFlow software and generated resources are available at https://triflow.zhoulab.io/.

bioinformatics↗

bioRxiv2025

Encoding without generation in the medial prefrontal cortex during cautious goal-directed actions

Adaptive behavior under threat requires deciding when to act and when to withhold action to avoid harm, often under conditions where movement, arousal, and task demand covary. Medial prefrontal cortex (mPFC) activity is widely associated with such control, yet it remains unclear whether this activity reflects causal action generation or broader evaluative processes shaped by behavioral state. Here, we combined fiber photometry, single-cell calcium imaging, mixed-effects modeling, and optogenetic inhibition to examine how GABAergic neurons in mouse mPFC represent cues, actions, and outcomes during a series of learned avoidance tasks of increasing complexity that promote cautious responding. By explicitly controlling for baseline activity and movement, we show that much apparent task-related activity in mPFC reflects movement and cue-evoked signals that are also present in a control cortical region, the visual cortex. mPFC GABAergic neurons showed little encoding of simple avoidance contingencies but broadly encoded punished outcomes. A small subset of neurons with strong movement sensitivity encoded more demanding avoidance contingencies requiring selection between action generation and deferment. For equivalent avoidance actions, distinct neuronal populations preferentially encoded either cue onset or the action. Despite this encoding, optogenetic inhibition of mPFC had minimal effects on the learning or performance of the different contingencies. These findings reveal a dissociation between neural encoding and causal necessity, indicating that mPFC GABAergic activity primarily reflects evaluative and contextual aspects of cautious avoidance behavior rather than direct control of action execution. Significance statementAvoiding danger often requires deciding when to act and when to hold back. The dorsomedial prefrontal cortex (mPFC) is widely assumed to support this control, yet the contributions of its neurons have remained unclear. Using neural population and single-neuron recordings together with targeted inhibition in mice performing learned threat-guided tasks, we show that GABAergic mPFC neurons are activated by cues, actions, and outcomes, but are not required for executing the behavior itself. These findings suggest that the mPFC primarily evaluates and contextualizes threat-motivated actions rather than generating them, highlighting a common mismatch between neural encoding and causal necessity.

neuroscience↗

bioRxiv2025

Expanding the RNA Virus Universe by Scalable Structure-Guided Discovery

The discovery of RNA viruses from metatranscriptomic data remains challenging due to their extreme sequence divergence and frequent lack of conserved motifs. We present Rider, a lightweight two-stage framework that couples fast, structure-informed sequence screening with targeted structural validation. Stage 1 uses a compact 35M-parameter protein language model to prioritize RdRp-like fragments at whole-sample scale, achieving over 44x higher end-to-end screening throughput on commodity hardware. Stage 2 applies structure prediction and Foldseek-based alignment against a dedicated RdRp structure resource ([~]200k ESMFold-predicted structures), providing orthogonal evidence for remote homologs. Applied to >10,000 metatranscriptomes spanning marine, freshwater, soil and host-associated microbiomes, Rider matches or outperforms leading tools (e.g., LucaProt, PalmScan) and additionally recovers divergent and truncated sequences. Multiple orthogonal indicators, including structure consistency and low DNA read mapping to corresponding contigs, support genuine RNA origin. In a human IBD cohort, Rider agrees with state-of-the-art calls for clinically relevant RNA viruses while extending discovery to divergent lineages. Rider turns structure-guided homology search into a practical, scalable pipeline for RNA virome discovery. HighlightO_LIA two-stage framework enables structure-guided RNA virus discovery at sample scale, achieving up to 44-fold higher throughput on standard computing hardware. C_LIO_LIThe method matches or surpasses LucaProt and PalmScan across >10,000 metatranscriptomes from diverse environments, while recovering RdRp fragments missed by existing tools. C_LIO_LIStructural validation using [~]200,000 ESMFold-predicted RdRp models and Foldseek alignment supports the detection of remote homologs with high confidence. C_LIO_LIOrthogonal evidence, including low DNA read mapping, strand-specific expression, and ORF metrics, confirms RNA origin and reduces false positives.. C_LIO_LIOpen-source code and an openly released RdRp structure database enable scalable, reproducible RNA virome discovery in environmental and clinical settings. C_LI

bioinformatics↗

bioRxiv2025

RoBep: A Region-Oriented Deep Learning Model for B-Cell Epitope Prediction

MotivationAccurate in silico identification of B-cell epitope residues is crucial for antibody design and structure-guided vaccine development. Although recent protein language models and structure-aware methods can capture spatial information of tertiary structure when generating residue embeddings, most existing epitope predictors use these embeddings to perform classification for individual residues one by one, without enforcing spatial continuity for reported epitope residues. Such methods often result in biologically implausible predictions because B-cell epitope residues always cluster together on the antigen surface. ResultsWe present RoBep, a region-oriented B-cell epitope predictor that explicitly models the spatial clustering of epitope residues. RoBep introduces a novel region constraint mechanism and combines the advanced protein language model ESM-Cambrian with an equivariant graph neural network. Our method outperforms existing structure-based methods on the benchmark dataset, demonstrating improvements of 26%, 45%, 13%, and 43% in F1, MCC, AUPR, and AUROC0.1, respectively. In addition to residue-level predictions, RoBep can also provide antibody-antigen binding regions. Importantly, the predicted epitope residues are ensured to be spatially compact, enhancing biological plausibility and practical relevance for immunotherapeutic design. AvailabilityA user-friendly website for using RoBep is provided at https://huggingface.co/spaces/NielTT/RoBep. All datasets, source code used in this work, and implementation instructions of the website are publicly available at https://github.com/YitaoXU/RoBep.

bioinformatics↗