Biology subjects

Chen, Z.

Publications and source records attributed to Chen, Z..

At least 235 records · Page 13Linked to original sources

bioRxiv2025

CD38⁺ Endothelial Remodeling Defines Spatially Diverse Vasculopathy Programs in Rapidly Advancing Oral Inflammation

Oral inflammatory diseases affect nearly half of the global population. Among them, newly defined peri-implantitis and high-grade periodontitis represent rapidly advancing inflammatory disease types, marked by relatively rapid tissue destruction. Despite their prevalence, the cell mechanisms and spatial architecture driving this severity remain poorly understood. Focusing first on peri-implantitis versus low- and moderate-grade periodontitis, we applied microbial profiling, single-cell RNA sequencing (scRNA-seq), and spatial proteomics (sp-proteomics) to uncover shared pathogenic programs linked to accelerated niche breakdown. Furthermore, to preserve spatial fidelity, each tissue was anatomically orientated along the tooth- or implant- epithelial interface, analogous sites of disease origination. Laser capture microdissection followed by microbiome analysis of unique tissue compartments revealed reduced bacterial load and diversity in peri-implantitis stroma. We then expanded our version-1 Human Periodontal Atlas by integrating newly generated peri-implantitis scRNAseq data (36-total samples; 121395-cells), revealing widespread transcriptional alterations, including oxidative stress, hypoxic, and NAD+ metabolism-associated signatures, primarily in a subpopulation of TNFRSF6B+/ICAM1+post-capillary venules. We then performed high-resolution sp-proteomics (15-total samples; 337260-cells) and analyzed VEC states and associated neighborhoods via AstroSuite using newly developed tri-wise spatial analysis. This revealed CD34+-VEC loss and CD38+-VEC expansion almost exclusively in peri-implantitis. We extended this analysis to high-grade periodontitis. Mucosal biopsies from four lesion-affected and four unaffected sites within the same individuals (1:1 matched; 8-samples; 225137-cells) again demonstrated spatially restricted CD38+-VEC remodeling exclusively in affected tissues, with similar vasculopathy front patterning. The findings nominate spatially distinct vasculopathy patterning as a hallmark of rapidly advancing oral inflammation and a targetable therapeutic axis.

immunology↗

bioRxiv2025

MSF-CPMP: A Novel Multi-Source Feature Fusion Model for Prediction of Cyclic Peptide Membrane Permeability

Cyclic peptides are becoming attractive molecules for drug discovery because of their properties with inherent stability and structural diversity. However, the high potential of cyclic peptide drugs is challenged by the limited membrane permeability cross cell membrane. To predict cyclic peptide membrane permeability (CPMP), an increased number of computational models or tools are designed and used. But these existing algorithms or models do not appropriately capture feature diversity of cyclic peptides. In this study, we introduce a novel multi-source feature fusion model called MSF-CPMP, which aims to increase the accuracy of predicted CPMP. The MSF-CPMP model incorporates three features extracted from SMILES sequences, graph-based molecular structures, and physicochemical properties of cyclic peptides. By benchmarking with other machine learning and deep learning-based methods, MSF-CPMP achieved the highest levels of the evaluation metrics such as accuracy of 0.9062 and AUROC of 0.9546, and further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source fusion. Our result demonstrates that MSF-CPMP outperforms other methods in predicting CPMP, that provides also exemplifies the power of advanced deep learning methods in tackling complex biological challenges, offering contributions to computational biology and clinical treatment. Code is available at https://github.com/wanglabhku/MSF-CPMP Author summaryWe have recognized that cyclic peptides are one type of main macro-molecular drugs useful for treatment of human diseases. However, the structural diversity of cyclic peptides results in limited permeability across cell membranes which is challenging drug research or industrial development. Previously some computational models or tools including machine learning or deep learning ones tried to solve this problem, but they still are not efficient. There are urgent requirement for more effective methodologies. Thus, we introduce a novel multi-source feature fusion model called MSF-CPMP. Our aim is to enhance accuracy and efficiency of predicted CPMP. We carried out evaluation of performance metrics by comparative analysis between MSF-CPMP and other machine learning or deep learning methods. Our result demonstrates that MSF-CPMP outperforms other models in predicting CPMP. We further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source feature fusion. In the future we would further improve our methods that can integrate broader biomedicine and biomedical information and provide guide for drug diversity in clinically treating complex human diseases.

bioinformatics↗

bioRxiv2025

Single Cell RNA Sequencing and Spatial Profiling Identify Mechanisms of Neonatal Brain Hemorrhage Development and Resolution

Precise control of cell-cell communication networks within brain neurovascular units (NVUs) promotes normal tissue physiology, and dysregulation of these networks can lead to pathologies including intracerebral hemorrhage (ICH). The cellular and molecular mechanisms underlying ICH development and subsequent tissue repair processes remain poorly understood. Here we employed quantitative single cell RNA sequencing coupled with spatial in situ gene expression profiling to characterize NVU signaling pathways associated with ICH in neonatal mouse brain tissue. The initial stages of ICH pathogenesis are characterized by downregulation of extracellular matrix (ECM)-associated signaling factors (Adamtsl2, Htra3, and Lama4) that functionally connect to canonical TGF{beta} activation and signaling in vascular endothelial cells. Conversely, the progressive resolution of ICH involves upregulation of neuroinflammatory signaling networks (Gas6 and Axl) alongside activation of iron metabolism pathway components (Hmox1, Cp, and Slc40a1) in astrocytes and microglial cells. Integrated computational modeling identifies additional ligand-receptor signaling networks between perivascular glial cells and endothelial cells during both ICH pathogenesis and resolution. Collectively, these findings illuminate the molecular signaling networks that promote NVU maturation and provide novel mechanistic insights into the pathways controlling ICH pathogenesis and repair.

developmental biology↗

bioRxiv2025

Integrative Omics Identifies Candidate Plasma Biomarkers and Cellular Targets Associated with Thoracic Aortic Aneurysm

ObjectivesTo define the cellular landscape of thoracic aortic aneurysm (TAA) and identify circulating biomarkers associated with disease burden. BackgroundTAA is marked by progressive aortic wall weakening and dilation, predisposing to rupture and dissection. However, its cellular architecture remains incompletely defined, and reliable circulating biomarkers are lacking. MethodsSingle-cell RNA sequencing was performed on 17 aortic tissue samples from 10 patients undergoing TAA repair and integrated with publicly available datasets to characterize disease-associated cell states. In parallel, tomographic imaging and plasma proteomics were used to identify biomarkers associated with aortic diameter. Key findings were further assessed through integration with single-cell data, external validation, and in vitro stimulation of primary human adventitial fibroblasts with fibroblast growth factor 23 (FGF-23). ResultsWe identified 25 cellular subsets, including macrophages, endothelial cells, vascular smooth muscle cells, and fibroblasts, with substantial heterogeneity in cellular composition and transcriptional state. Genome-wide association study candidate genes, including JUN and TPM3, showed cell type-specific upregulation. Plasma proteomics identified multiple biomarkers associated with aortic diameter, of which FGF-23 was independently validated in the UK Biobank as elevated in individuals with TAA. FGFR1, the receptor for FGF-23, was selectively expressed in fibroblasts and subsets of vascular smooth muscle cells, with strongest downstream signaling in fibroblasts. FGF-23 stimulation induced inflammatory and extracellular matrix remodeling programs in primary human adventitial fibroblasts. ConclusionsThese findings define the cellular landscape of TAA and identify the FGF-23-FGFR1 axis as a biomarker-linked pathway that may contribute to aneurysm progression. Condensed AbstractThoracic aortic aneurysm (TAA) is characterized by progressive aortic dilation and risk of rupture, yet its cellular architecture and circulating biomarkers remain incompletely defined. We performed single-cell RNA sequencing on 17 aortic samples from 10 patients and integrated these data with public datasets to define the cellular landscape of TAA. In parallel, imaging and plasma proteomics (n=10) were used to identify biomarkers associated with aortic diameter. We identified 25 cellular subsets, including macrophages, endothelial cells, vascular smooth muscle cells, and fibroblasts, with notable transcriptional heterogeneity and cell type-specific upregulation of GWAS-associated genes (e.g., JUN, TPM3). Plasma proteomics identified fibroblast growth factor 23 (FGF-23) as associated with aortic diameter and elevated in TAA in the UK Biobank. FGFR1, its receptor, was selectively expressed in fibroblasts and VSMCs, and FGF-23 stimulation induced inflammatory and extracellular matrix remodeling programs in fibroblasts. These findings link a circulating biomarker to stromal cell signaling in TAA. HighlightsO_LIIntegrative single-cell RNA sequencing defined a diverse cellular landscape in thoracic aortic aneurysm tissue, identifying 25 distinct cell populations. C_LIO_LICross-dataset harmonization revealed marked differences in cellular composition across studies while supporting shared stromal and immune programs in thoracic aortic aneurysm. C_LIO_LIPlasma proteomics identified FGF-23 as a candidate biomarker associated with aortic diameter and independently linked to thoracic aortic aneurysm presence in the UK Biobank C_LIO_LIFGFR1 was enriched in fibroblasts and subsets of vascular smooth muscle cells, and FGF-23 induced inflammatory and extracellular matrix remodeling programs in human primary adventitial fibroblasts. C_LI

cell biology↗

bioRxiv2025

Polycomb Repressive-Deubiquitinase Complex Safeguards Oocyte Epigenome and Female Fertility by Restraining Polycomb Activity

Mouse oocytes exhibit a unique chromatin landscape characterized by broad H3K27ac and H3K27me3 domains, demarcating euchromatin and facultative heterochromatin, respectively. However, the mechanisms underlying this non-canonical landscape remain elusive. Here we report BAP1, a core component of the Polycomb Repressive-Deubiquitinase (PR-DUB) complex, as a key negative regulator of Polycomb activity during oogenesis. BAP1 restricts pervasive H2AK119ub1 accumulation in oocytes and protects oocyte-specific broad H3K27ac, particularly within gene-poor regions, from ectopic H3K27me3 deposition. While PR-DUB has been linked to gene repression, in oocytes BAP1 primarily promotes transcription and contributes minimally to Polycomb-mediated silencing. BAP1-dependent transcriptional activation is essential for oocyte developmental competence and female fertility. BAP1 loss disrupts the maternal-to-zygotic transition and impairs embryonic enhancer activation, ultimately compromising preimplantation development. Notably, while H3K27ac patterns are reset after fertilization, the aberrant H3K27me3 landscape established in BAP1-deficient oocytes persists in early embryos. Together, these findings reveal a critical role for PR-DUB in safeguarding the oocyte epigenome by protecting euchromatin from ectopic Polycomb activity, rather than enforcing transcriptional repression.

developmental biology↗

bioRxiv2025

C1q limits cystoid edema by maintaining basal beta-catenin-dependent signaling and blood-retina barrier function

Macular edema (ME) causes significant vision impairment and occurs in several prevalent retinal diseases including diabetic retinopathy (DR), choroidal neovascularization (CNV), retinal vein occlusion, and uveitis. Retinal edema typically results from dysfunction of the blood-retina barrier (BRB), which is associated with increased retinal expression of complement components. It is unclear whether the classical complement pathway has detrimental or protective roles in the context of BRB dysfunction. Here, we characterize Tspan12 KODBM (Disrupted Barrier Maintenance) mice, a new mouse model of cystoid edema based on genetically and pharmacologically manipulating beta-catenin-dependent norrin/frizzled4 (FZD4) signaling. We assess BRB function, cystoid edema, ERG, and microglia activation outcomes in an aging study with WT, C1qa KO, Tspan12 KODBM, and Tspan12 KODBM; C1qa KO compound mutant mice. Phenotypic analyses and cell-based experiments indicate that C1QA contributes to maintaining basal beta-catenin-dependent signaling and that the absence of C1QA exacerbates BRB dysfunction, cystoid edema, and neuroinflammation in Tspan12 KODBM; C1qa compound mutant mice. Activation of beta-catenin-dependent signaling by a FZD4/LRP5 agonist antibody modality achieves complete resolution of cystoid edema. This study shows that reducing or enhancing norrin/frizzled4 signaling can increase or decrease cystoid edema, respectively, underscoring its potential as a therapeutic target in ME. Furthermore, this study provides novel insights into the contribution of C1QA to BRB maintenance.

neuroscience↗

bioRxiv2025

Integrative genomic and transcriptomic analyses uncover regulatory landscape of symbiotic nitrogen fixation in soybean natural population

Symbiotic nitrogen fixation (SNF) is a key trait in legume productivity, yet the genetic and regulatory basis underlying its natural variation remains poorly understood. Here, we integrated genome, transcriptome, and chromatin accessibility data from a soybean diversity panel comprising 380 accessions, including 108 wild and 272 cultivated lines. Genome-wide association studies (GWAS) detected multiple loci for SNF traits but with limited resolution due to polygenic architecture and environmental influences. Independent component analysis (ICA) identified 136 co-expression modules; ten ICs were strongly correlated with SNF phenotypes and enriched in circadian clock components (e.g., GmLHY1a/b), lipid metabolism, or defense signaling pathways. Transcriptome-wide association studies (TWAS) linked 1,453, 806, and 178 genes to NFP, NW, and NFE traits, respectively. Among TWAS hits, 185 transcription factors were identified, with 39.0% overlapping selective sweeps, suggesting regulatory evolution under domestication. To further dissect expression regulation, we performed eQTL mapping and detected 4,654 significant eQTLs, including 1,241 local (cis), 2,505 distal (trans), and 908 mixed. By integrating ATAC-seq data from sorted nodule nuclei, we found that eQTLs, particularly local eQTLs, are significantly enriched within open chromatin regions, indicating their regulatory potential. Notably, we validated the circadian clock gene GmLHY1b as a negative regulator of nodulation using CRISPR mutagenesis and CUT&Tag. Our integrative study provides comprehensive genomic and transcriptomic resources from a diverse soybean population, offering novel insights into SNF regulatory networks and a valuable foundation for future SNF research and soybean improvement.

plant biology↗

bioRxiv2025

Inbreeding and resultant homozygosity across key inflammation and DNA repair genes linked to chlamydial infection in New South Wales koalas

Inbreeding and resultant homozygosity can reduce genetic diversity and increase disease susceptibility. Koalas (Phascolarctos cinereus) are one species suffering genomic diversity loss and inbreeding and concurrent significant disease pressure (particularly chlamydiosis). Using 259 whole genomes with a pathogen sampling regime we identify potential links between inbreeding, genome-wide variation and chlamydial infection. We found a general trend of reduced genomic diversity and increased inbreeding from north to south across six sites in New South Wales. A genome-wide association study of 153 individuals from sites with known Chlamydia pecorum presence were used to investigate the potential relationship between inbreeding and infection. Chlamydia positive individuals (average FH = 0.026) were significantly more inbred than Chlamydia negative individuals (average FH= -0.0051) (t = - 2.31, df = 151, p-value = 0.022). We identified several genes involved in host-pathogen interactions and DNA mismatch repair within in runs of homozygosity that were unique to Chlamydia positive individuals. Interestingly, populations considered putatively Chlamydia-free had similar allele frequencies across candidate loci as Chlamydia positive individuals. Combined with gene flow analyses, this result suggests that isolation may have protected these populations more than harbouring alleles conferring infection resilience and supports the concept that disease should be carefully considered in any conservation measures that increase connectivity or translocations. Our genome-wide approach has identified several avenues for investigations into the pathogenesis of Chlamydia infection and chlamydiosis. We showcase the value of high-quality re-sequenced genomes for understanding the implications of inbreeding, genomic diversity loss, and infection susceptibility, all universal problems for threatened species.

genomics↗

bioRxiv2025

The Calcium Pump ATP2B1/PMCA1 Regulates CNS Vascular Development by Facilitating Norrin- and WNT7A/B-induced Frizzled4 signaling

Frizzled4 (FZD4) is a receptor for Norrin and WNT7A/B ligands, is expressed in endothelial cells (ECs), is required for endothelial blood-central nervous system (CNS) barrier function as well as CNS angiogenesis, and transduces {beta}-catenin-dependent signaling. Despite its fundamental importance in neurovascular biology, including as a drug target, the molecular mechanisms governing FZD4 regulation remain poorly understood. Here, we employed proximity biotinylation to identify proteins that regulate FZD4. We identified ATPase Plasma Membrane Ca{superscript 2} Transporting 1 (ATP2B1, also known as PMCA1) as a FZD4 proximity interactor. Functional analyses revealed that ATP2B1 depletion increased EC Ca2+, activated NFAT, and significantly attenuated Norrin/Frizzled4 signaling. Endothelial-specific Atp2b1 deletion caused CNS vascular phenotypes consistent with compromised Norrin/Frizzled4 signaling. This study identifies ATP2B1 as a novel regulator of Norrin- and WNT7A/B-induced FZD4 signaling and suggests that in pathological contexts with elevated EC Ca2+-levels, EC function may be modulated by suppression of {beta}-catenin-dependent signaling.

developmental biology↗

bioRxiv2025

Procrastination partly reflects an evolutionary byproduct of non-planning impulsivity

Procrastination has immediately visible repercussions on health and survival resilience, yet shows stably heritable and remains increasingly pervasive across human societies. Despite a paradox, this behavior is theoretically explained to represent a byproduct of evolutionary advantages underlying impulsivity, yet not deciphered well by scientific evidences. After adjusting psychometric endogeneity, we demonstrate the unique predictive roles of non-planning impulsivity (NPI) during late adolescence and early adulthood uniquely predicts procrastination in later adulthood in a twin cohort (N = 154). This association was further replicated in two independent cohorts (N = 327, N = 1,543). Using AE models, in conjunction of single-paper meta-analytic synthesis (N = 3,656 twin pairs), we observed significant shared genetic contributions underlying this NPI-procrastination association (rg = 0.51, 95% CI: 0.18 - 0.84). Beyond to the phenotypic heritability, employing a Genome-Wide-Association Study (GWAS), six NPI-procrastination overlapping SNPs are identified, functionally accounting for neural dysregulation. Thus, leveraging neurodevelopmental normative modelling (N = 37,407), online meta-analytic estimations (k = 198, loci = 5,855) and seed-based d mapping estimates (N = 893), cortical deviations in the left dorsolateral prefrontal cortex (DLPFC) - the brain region showing highest probabilistic overlap mapping NPI to procrastination, partly explains their shared genetic variants, but are substantially independent in genetic contribution. Mendelian Randomization analysis finally indicates causal roles of NPI and procrastination both, to DLPFC deviations. Our findings empirically clarified this theory that procrastination partly derives from NPI as an evolutionary byproduct indeed, but is still unique in neurogenetic entities. Brief summaryProcrastination is a puzzling human behavior that compromises survival-relevant outcomes yet remains both widespread and heritable. Although theorized as a byproduct of impulsivitys evolutionary advantages, empirical support for this account has been limited. Here, we provide converging evidence across psychometric, genetic, and neuroimaging modalities to show that non-planning impulsivity during late adolescence and early adulthood uniquely predicts later procrastination, and that the two traits share significant genetic overlap. We further identify specific genetic variants and morphological deviations in the DLPFC that link, but also partially dissociate, their biological pathways. These findings clarify the evolutionary and neurogenetic architecture of procrastination and underscore its partial derivation from impulsivity alongside distinct developmental origins.

neuroscience↗

bioRxiv2025

High-Throughput Tracking of Freely Moving Drosophila Reveals Variations in Aggression and Courtship Behaviors

Aggression is a nearly universal behavior used to secure food, territory, and mates across species, including the fruit fly Drosophila melanogaster. In fruit flies, both sexes display aggression through stereotypical motor patterns. This, along with their sophisticated genetic and molecular toolkit, makes Drosophila melanogaster an excellent model for studying aggression. While male- and female-specific aggressive motor programs have been qualitatively described, automated systems for quantifying these behaviors in freely moving flies remain limited in their ability to combine high-resolution analysis with high throughput. Here, we pair a high-resolution, high-throughput imaging system (the Kestrel) with DeepLabCut pose estimation to create a pipeline that tracks multiple freely moving fly pairs and quantifies social dynamics with high fidelity. We validated body-part tracking using published benchmarks. The platform reliably reproduced a known phenotype: heightened female aggression following thermogenetic activation of cholinergic pC1 neurons in female brain. It also detected increased unilateral wing extension, a courtship display inversely related to aggression, between two males upon activating a previously uncharacterized [~]40-neuron group in the male brain. Pose-based analysis revealed locomotive differences between experimental and control groups, and subtle, genotype-specific variations in head butts and UWEs. This workflow enables high-throughput screening and mechanistic dissection of social behaviors.

neuroscience↗

bioRxiv2025

Context-dependent regulatory variants in Alzheimer's disease

Noncoding genetic variants underlie many complex diseases, yet identifying and interpreting their functional impacts remains challenging. Late-onset Alzheimers disease (LOAD), a polygenic neurodegenerative disorder, exemplifies this challenge. The disease is strongly associated with noncoding variation, including common variants enriched in microglial enhancers and rare variants nominated at loci implicated in neurodevelopment and synaptic function. These variants may perturb regulatory sequences by disrupting transcription factor (TF) motifs or altering local regulatory sequence context, with potential consequences for gene expression and chromatin accessibility. However, assessing their impact is complicated by the context-dependent functions of regulatory sequences, underscoring the need to systematically examine variant effects across diverse tissues, cell types, and cellular states. Here, we combined in vitro and in vivo massively parallel reporter assays (MPRAs) with interpretable machine-learning models to systematically characterize common and rare variants across myeloid and neuron-enriched neural contexts. Parallel profiling of variants in four immune states in vitro and three mouse brain regions in vivo revealed that individual variants can differentially and even oppositely modulate reporter activity across cellular contexts, while a subset showed immune-state-dependent effects. Within the assayed candidate set, the relative effect sizes of common and rare variants reversed between contexts, with common variants showing larger effects in THP-1 macrophages and rare variants in brain tissue. Interpretable sequence-to-function models prioritized context-biased variants and generated motif-level hypotheses, including predicted transcription-factor motif disruption and subtler changes in local motif context. To probe endogenous consequences at a prioritized locus, we used CRISPR interference to perturb a rare-variant-containing enhancer at the SEC63-OSTM1 locus, revealing metabolic and biosynthetic transcriptional programs resembling those induced by SEC63 promoter perturbation, together with a stimulation-specific interferon response. These findings show that LOAD-associated noncoding variants exhibit context-dependent effects on reporter activity and predicted chromatin accessibility, and provide a framework for linking genetic association to regulatory activity, sequence grammar and endogenous transcriptional state.

genomics↗

bioRxiv2025

ODFormer: a Virtual Organoid for Predicting Personalized Therapeutic Responses in Pancreatic Cancer

Pancreatic cancer (PC) patient-derived organoids (PDOs) faithfully recapitulate therapeutic responses but face clinical translation barriers, including high costs and technical complexity. To address these problems and the lack of frameworks for PDO-based drug-response assays, we developed ODFormer, a computational framework that simulates PC PDOs to predict clinically actionable, patient-specific drug responses by integrating transcriptomic and mutational profiles. ODFormer first employed two encoders, pretrained on 30,000 pan-cancer bulk transcriptomics and 1 million PC single-cell profiles respectively, to distil tissue-and organoid-specific representations. Then, trained on our curated 14,000 PDO drug-response assay (across 183 PDOs and 98 drugs) using a transformer-augmented hybrid contrastive network, ODFormer significantly outperformed state-of-the-art methods, notably achieving a PCC >0.9 in predicting standardized drug response. Multi-cohort retrospective analyses further demonstrated that ODFormer-guided personalized therapy significantly improves clinical outcomes, without requiring physical organoid assays. Furthermore, ODFormer identified novel clinico-biological PC subtypes and revealed therapy resistance biomarkers by stratifying predicted responders and non-responders. These were validated using independent datasets including TCGA-PDAC. Notably, ODFormer-guided treatment efficacy showed high concordance with prospective clinical responses by CA19-9.

bioinformatics↗

bioRxiv2025

Structural basis of DNA N6-adenine methylation in eukaryotes

As a transcription-associated epigenetic mark abundantly present in many unicellular eukaryotes, DNA N6-adenine methylation (6mA) is maintained by the AMT1 complex. However, the structure-function relationship of the AMT1 complex remains to be fully elucidated. Here, we employ AlphaFold3 (AF3) for de novo structural modeling of the AMT1 complex, complemented by molecular dynamics simulations. Functional relevance of key structural features, especially those of the AMT1 ternary complex with the double-stranded DNA (dsDNA) substrate and the cofactor, are validated by extensive mutagenesis, both in vivo and in vitro. Our analysis reveals the structural basis for DNA substrate recognition, base flipping, and catalysis in this prototypical eukaryotic DNA 6mA-methyltransferase. It also allows us to delineate the reaction pathway for processive methylation involving translocation of the AMT1 complex along the dsDNA. As the active site is conserved across the MT-A70 family of eukaryotic N6-adenine methyltransferases, the structural insight will facilitate rational design of specific inhibitors.

molecular biology↗

bioRxiv2025

Natural gradient Bayesian sampling: an innate algorithm emerges in canonical cortical circuits

AO_SCPLOWBSTRACTC_SCPLOWAccumulating evidence suggests the canonical cortical circuit, consisting of excitatory (E) and diverse classes of inhibitory (I) interneurons, implements Bayesian posterior sampling. However, most of the identified circuits sampling algorithms are simpler than the nonlinear circuit dynamics, suggesting complex circuits may implement more advanced algorithms. Through comprehensive theoretical analyses, we discover the canonical circuit innately implements natural gradient Bayesian sampling, which is an advanced sampling algorithm that adaptively adjusts the sampling step size based on the local geometry of stimulus posteriors measured by Fisher information. Specifically, the nonlinear circuit dynamics can implement natural gradient Langevin and Hamiltonian sampling of uni- and multi-variate stimulus posteriors, and these algorithms can be switched by interneurons. We also find that the non-equilibrium circuit dynamics when transitioning from the resting to evoked state can further accelerate natural gradient sampling, and analytically identify the neural circuits annealing strategy. Remarkably, we identify the approximated computational strategies employed in the circuit dynamics, which even resemble the ones widely used in machine learning. Our work provides an overarching connection between canonical circuit dynamics and advanced sampling algorithms, deepening our understanding of the circuit algorithms of Bayesian sampling.

neuroscience↗

bioRxiv2025

Oscillatory Control of Cortical Space as a Computational Dimension

Flexible cognition depends on the ability to represent and apply relevant information to the current task at hand. This allows the brain to interpret sensory input and guide behavior in a context-dependent manner. Recent work has proposed Spatial Computing as a mechanism for this flexibility, suggesting that task-related signals organize information processing through spatial patterns of oscillatory activity across the cortical surface. These patterns are proposed to act as "inhibitory stencils" that constrain where sensory-related information (the "content" of cognition) can be expressed in spiking activity. Here, we provide a comprehensive empirical test of Spatial Computing using multi-electrode recordings from the lateral prefrontal cortex in non-human primates performing a range of cognitive tasks (object working memory, sequence working memory, categorization). We found that alpha/beta oscillations encoded task-related information, were organized into spatial patterns that changed with task conditions, and inversely correlated with the spatial expression of sensory-related spiking activity. Furthermore, we found that alpha/beta oscillations reflected misattributions of task conditions and correlated with subjects trial-by-trial decisions. These findings validate core predictions of Spatial Computing suggesting that oscillatory dynamics not only gate information in time but also shape where in the cortex cognitive content is represented. This framework offers a unifying principle for understanding how the brain flexibly coordinates cognition through structured population dynamics.

neuroscience↗

bioRxiv2025

TaPGS1 Driven Flavonol Accumulation Delays Endosperm Cellularization and Enlarges Wheat Grains

Flavonols play a crucial role in seed development by regulating multiple physiological processes, including seed coat pigmentation, dormancy, fertilization, and endosperm formation. Notably, flavonols influence the polar transport of auxin, thereby affecting seed growth dynamics. In our previous work, we found that overexpression of the wheat bHLH transcription factor TaPGS1 results in increased grain size; however, the underlying mechanism remained unclear. In this study, metabolomic and transcriptomic analyses of TaPGS1 overexpressing wheat lines revealed enhanced flavonol accumulation and upregulation of key flavonol biosynthetic genes. Further investigations suggested that flavonol accumulation in the seed coat may disrupt auxin transport, leading to localized auxin buildup, delayed endosperm cellularization, and an increase in endosperm cell number. These changes collectively contribute to grain enlargement. Our findings uncover a TaPGS1 flavonol regulatory module that links auxin distribution to endosperm development and seed size control in wheat.

plant biology↗

bioRxiv2025

Combining Machine Learning and Multiplexed, In Situ Profiling to Engineer Cell Type and Behavioral Specificity

A promising strategy for the precise control of neural circuits is to use cis-regulatory enhancers to drive transgene expression in specific cells. However, enhancer discovery faces key challenges: low in vivo success rates, species-specific differences in activity, challenges with multiplexing adeno-associated viruses (AAVs), and the lack of spatial detail from single-cell sequencing. In order to accelerate enhancer discovery for the dorsal spinal cord--a region critical for pain and itch processing--we developed an end-to-end platform, ESCargoT (Engineered Specificity of Cargo Transcription), combining machine learning (ML)-guided enhancer prioritization, modular AAV assembly, and multiplexed, in situ screening. Using cross-species chromatin accessibility data, we trained ML models to predict enhancer activity in oligodendrocytes and in 15 dorsal horn neuronal subtypes. We first demonstrated that an initial enhancer, Excit-1, targeted excitatory dorsal horn neurons and drove reversal of mechanical allodynia in an inflammatory pain model. To enable parallel profiling of a 27-enhancer-AAV library delivered intraspinally in mice, we developed a Spatial Parallel Reporter Assay (SPRA) by integrating a novel Golden-Gate assembly pipeline with multiplexed, in situ screening. Regression adjustment for spatial confounding enabled specificity comparisons between enhancers, demonstrating the ability to screen enhancers targeting diverse cell types (oligodendrocytes, motoneurons, dorsal neuron subtypes) in one experiment. We then validated two candidates, targeting Exc-LMO3 and Exc-SKOR2 neurons, respectively. In a companion paper by Noh et al, our colleagues show that the functional specificity of the Exc-SKOR2-targeting enhancer, unlike Excit-1, is capable of blocking the sensation of chemical itch in mice. These enhancers were derived from the macaque genome but displayed functional sensitivity in mice. This platform enables spatially resolved, multiplexed in vivo enhancer profiling to accelerate discovery of cell-targeting tools and gene therapy development.

neuroscience↗