Biology subjects

Peng, J.

Publications and source records attributed to Peng, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

The role of mating systems in postzygotic reproductive isolation between two recently divergent Aquilegia Species

Mating systems play a crucial role in plant speciation. In particular, hybrid seed inviability is prevalent among species with different mating systems due to parental conflict for resource allocation to offspring. However, whether such a postzygotic barrier can be rapidly established in recently diverged species remains poorly understood. In this study, we integrate population genomic and ecological approaches to address this question using recently diverged species pairs Aquilegia kansuensis and A. ecalcarata, which diverged approximately 0.256 Ma, in a sympatric population from Qinghai, China. Population structure and demographic history results reveal clear genetic differentiation between the two species, corroborating their recent divergence. The results of outcrossing rate estimation based on microsatellite markers indicated that A. kansuensis and A. ecalcarata exhibit high selfing and mixed mating systems, respectively. We performed reciprocal crosses between A. kansuensis and A. ecalcarata and found that A. ecalcarata yielded a very small number of small-sized seeds when selfed A. kansuensis was used as pollen donors, resulting in strong asymmetric reproductive isolation. An approximate Bayesian computation framework identified that approximately 4.6% of genomic loci are associated with reproductive isolation, and gene ontology analyses of these loci highlighted key pathways involved in seed maturation and post-embryonic development. Therefore, our findings provide evidence that A. ecalcarata and A. kansuensis represent a novel case of parental conflict and postzygotic isolation driven by divergent mating systems, suggesting mating systems can play a critical role in rapid plant speciation.

evolutionary biology↗

bioRxiv2025

Palmdelphin facilitates R-spondin2 secretion to activate Wnt signaling and promote colorectal cancer stemness and tumorigenesis

The Wnt signaling pathway is a key driver of stemness and progression which contributes to mortality in colorectal cancer (CRC). R-spondins bind to LGR receptors to inhibit ubiquitin E3 ligases, thus protecting Frizzled from degradation and activating downstream Wnt signaling. Herein, we identify Palmdelphin (PALMD) as a functional marker of CRC stem cells, interspersed between intestinal and colonic crypt base epithelial cells, and predictive of aggressive CMS4 CRC and poor survival. Gene knockdown and overexpression studies revealed that PALMD initiates paracrine activation of Wnt/{beta}-catenin signaling via interacting with and facilitating the secretion of R-spondin2 (RSPO2), resulting in enhanced stemness and tumor growth in vitro and in vivo. Physiologic or pharmacologic inhibition of the PALMD-RSPO2 axis using R-spondin2-specific antibody or 6-methyl-1,3,8-trihydroxyanthraquinone (emodin), respectively, attenuates PALMD- mediated Wnt reporter activation, self-renewal, and tumorigenesis in cell and patient-derived organoid models. Together, these findings identify PALMD as a previously unknown player in Wnt signaling in CRC, and underscore the pro-tumorigenic role of R-spondin2 in this context.

cancer biology↗

bioRxiv2025

Cytokine-driven cellular polarization in preeclampsia revealed through the "Dictionary of immune responses"

BackgroundPreeclampsia (PE) is a pregnancy-related hypertensive disorder and a leading cause of maternal and perinatal mortality. Current treatments focus primarily on symptom management, as delivery remains the only definitive cure. This underscores the urgent need for innovative therapeutic strategies. Cytokines released by placental immune cells may contribute to the progression of PE and represent promising therapeutic targets. MethodsWe conducted single-cell sequencing on placental tissues obtained via cesarean section from patients with severe PE and cases of non-infectious preterm birth. Machine learning was applied to identify critical immune cells. Immune Response Enrichment Analysis was performed on these key cells to evaluate their polarization states and cytokine responses associated with PE. Additionally, we investigated cell-cell communications, key genes, and their related functions ResultsWe identified cell type-specific alterations in PE, including an increased proportion of CD4+ T cells polarized towards an IL-1- and IL-1{beta} enriched T4-c state. Altered SPP1 signaling between macrophages and CD4+ T cells was observed, indicating immune response dysregulation. Additionally, machine learning algorithms identified four hub genes, and six small-molecule drugs were predicted to hold therapeutic potential for PE. ConclusionsThis study emphasizes the importance of further understanding CD4+ T cell dynamics in preeclampsia, providing potential insights into the principles of placental immunity and contributing to the exploration of immunotherapeutic strategies

bioinformatics↗

bioRxiv2025

Midkine Attenuates Aβ Fibril Assembly and Amyloid Plaque Formation

Proteomic profiling of Alzheimers disease (AD) brains has identified numerous understudied proteins, including midkine (MDK), that are highly upregulated and correlated with A{beta} since the early disease stage, but their roles in disease progression are not fully understood. Here we present that MDK attenuates A{beta} assembly and influences amyloid formation in the 5xFAD amyloidosis mouse model. MDK protein mitigates fibril formation of both A{beta}40 and A{beta}42 peptides in Thioflavin T fluorescence assay, circular dichroism, negative stain electron microscopy, and NMR analysis. Knockout of Mdk gene in 5xFAD increases amyloid formation and microglial activation. Further comprehensive mass spectrometry-based profiling of whole proteome and detergent-insoluble proteome in these mouse models indicates significant accumulation of A{beta} and A{beta}-correlated proteins, along with microglial components. Thus, our structural and mouse model studies reveal a protective role of MDK in counteracting amyloid pathology in Alzheimers disease.

biochemistry↗

bioRxiv2025

DisConST: Deciphering Spatial Domains Using Distribution-aware Contrastive Learning for Spatial Transcriptomics

Spatial transcriptomics (ST) is a cutting-edge technology that provides comprehensive insights into gene expression patterns from a spatial perspective. A key research focus within this field is spatial domain identification, which is essential for exploring tissue organization, biological development, and disease mechanisms. Although methods have been developed, they still face challenges in modeling the gene expression information together with the spatial locations, resulting in suboptimal accuracy. We introduce DisConST (Distribution-aware Contrastive Learning for Spatial Transcriptomics), a novel deep-learning method designed to improve spatial domain detection within spatial transcriptomics datasets. DisConST addresses key challenges, such as the high dropout rates and the complex integration of spatial and gene expression data, by incorporating contrastive learning strategies that are aware of the underlying data distributions. It employs the zero-inflated negative binomial (ZINB) distribution, along with graph contrastive learning, to generate more informative latent representations. These representations efficiently integrate spatial positions, transcriptomic profiles, and cell-type proportions within spots. We validated DisConST across diverse ST datasets of tissues, organs, and embryos from various sequencing platforms in both normal and disease states. Our results consistently demonstrated that DisConST achieves superior spatial domain recognition accuracy compared to existing state-of-the-art methods. Furthermore, our experiments highlighted the utility of DisConST in advancing research on tissue organization, embryonic development, and tumor immune microenvironment dissection. The source code for DisConST is freely available at https://github.com/Zhenpm/DisConST/.

bioinformatics↗

bioRxiv2025

Formaldehyde Exposure Induces Systemic Epigenetic Alterations in Histone Methylation and Acetylation

Formaldehyde (FA) is a pervasive environmental organic pollutant and a Group 1 human carcinogen. While FA has been implicated in various cancers, its genotoxic effects, including DNA damage and DNA-protein crosslinking, have proven insufficient to fully explain its role in carcinogenesis, suggesting the involvement of epigenetic mechanisms. Histone post-translational modifications (PTMs) on H3 and H4, critical for regulating gene expression, may contribute to FA-induced pathogenesis as lysine and arginine residues serve as targets for FA-protein adduct formation. This study aimed to elucidate the effects of FA on histone methylation and acetylation patterns. Human bronchial epithelial cells (BEAS-2B) were exposed to low-dose (100 M) and high-dose (500 M) FA for 1 hour, and their histone extracts were analyzed using high-resolution liquid chromatography-tandem mass spectrometry-based proteomics, followed by PTM-combined peptide analysis and single PTM site/type comparisons. We identified 40 peptides on histone H3 and 16 on histone H4 bearing epigenetic marks. Our findings revealed that FA exposure induced systemic alterations in H3 and H4 methylation and acetylation, including hypomethylation of H3K4 and H3K79 and changes in H3K9, H3K14, H3K18, H3K23, H3K27, H3K36, H3K37, and H3R40, as well as modifications in H4K5, H4K8, H4K12, and H4K16. These FA-induced histone modifications exhibited strong parallels with epigenetic alterations observed in cancers, leukemia, and Alzheimers disease. This study provides novel evidence of FA epigenetic toxicity, offering new insights into the potential mechanisms underlying FA-driven pathogenesis.

pharmacology and toxicology↗

bioRxiv2025

Transcriptomic and spatial GABAergic neuron subtypes in zona incerta mediate distinct innate behaviors

Understanding the anatomical connection and behaviors of transcriptomic neuron subtypes is critical to delineating cell type-specific functions in the brain. Here we integrated single-nucleus transcriptomic sequencing, in vivo circuit mapping, optogenetic and chemogenetic approaches to dissect the molecular identity and function of heterogeneous GABAergic neuron populations in the zona incerta (ZI) in mice, a region involved in modulating various behaviors. By microdissecting ZI for transcriptomic and spatial gene expression analyses, our results revealed two non-overlapping Ecel1- and Pde11a-expressing GABAergic neurons with dominant expression in the rostral and medial zona incerta (ZIrEcel1 and ZImPde11a), respectively. The GABAergic projection from ZIrEcel1 to periaqueductal gray mediates self-grooming, while the GABAergic projection from ZImPde11a to the oral part of pontine reticular formation promotes transition from sleep to wakefulness. Together, our results revealed the molecular markers, spatial organization and specific neuronal circuits of two discrete GABAergic projection neuron populations in segregated subregions of the ZI that mediate distinct innate behaviors, advancing our understanding of the functional organization of the brain.

neuroscience↗

bioRxiv2024

Bipolar and schizophrenia risk gene AKAP11 encodes an autophagy receptor coupling the regulation of PKA kinase network homeostasis to synaptic transmission

Human genomic studies have identified protein-truncating variants in AKAP11 associated with both bipolar disorder (BD) and schizophrenia (SCZ), implicating a shared disease mechanism driven by loss-of-function. AKAP11, a protein kinase A (PKA) adaptor, plays a key role in degrading the PKA-RI complex through selective autophagy. However, the neuronal functions of AKAP11 and the impact of its loss-of-function remains largely uncharacterized. Through multi-omics approaches, cell biology, and electrophysiology analysis in mouse models and human induced neurons, we delineated a central role of AKAP11 in coupling PKA kinase network regulation to synaptic transmission. Loss of AKAP11 distorted compartment-specific PKA and GSK3/{beta} activities and impaired cellular functions that significantly overlap with pathways associated with BD and SCZ. Moreover, we identified interactions between AKAP11, the PKA-RI adaptor SPHKAP, and the ER-resident autophagy-related proteins VAPA/B, which co-adapt and mediate PKA-RI complex degradation in neurons. Notably, AKAP11 deficiency impaired neurotransmission, providing key insights into the mechanism underlying AKAP11-associated psychiatric diseases.

neuroscience↗

bioRxiv2024

Molecular mechanisms of dynamics-mediated effects of pathogenic missense mutations on Menin protein function

Understanding how disease-causing missense mutations (DCMMs) affect protein function is fundamental. The traditional structure-function paradigm for proteins has evolved into a structure-dynamics-function model, as dynamics is increasingly recognized as a key regulator of protein function. Consequently, it is essential to incorporate dynamics into the once heavily emphasized structure-function framework to explain the effects of DCMMs. Although research in this area is emerging, evidence supporting a definitive role of dynamics in mediating DCMM effects on protein function remains limited. In this study, we used Menin--a mutation-prone scaffold protein involved in various pathologies--as a model system to explore how DCMMs affect Menins function. By performing molecular dynamics (MD) simulations on 24 clinically confirmed DCMMs, we showed that DCMMs do not necessarily destabilize protein stability. Instead, they induce similar dynamic changes in the protein. The consequences of DCMMs on Menins function were further assessed through umbrella sampling of the Menin-JunD protein protein interaction (PPI). We found that DCMMs attenuate this interaction and disrupt a highly conserved JunD dissociation pathway in wild-type (WT) Menin. The underlying mechanism was revealed through allosteric analysis, which showed that, despite being located far from the JunD binding site, DCMMs uniformly disturbed the coupling between residue E179 and the binding pocket. Additionally, forced maintenance of E197-pocket coupling restored the impaired Menin-JunD PPI in DCMMs. Together, these data demonstrate that DCMMs alter Menins function through dynamics, with allostery playing a crucial role. This study further supports the incorporation of dynamics into the traditional "structure-function" diagram to better explain the effects of DCMMs.

biophysics↗

bioRxiv2024

Gene regulatory networks and essential transcription factors for de novo originated genes

The regulation of gene expression is crucial for the functional integration of evolutionarily young genes, particularly those that emerge de novo. However, the regulatory programs governing the expression of de novo genes remain unknown. To address this, we applied computational methods to single-cell RNA sequencing data, identifying key transcription factors likely instrumental in regulating de novo genes. We found that transcription factors do not have the same propensity for regulating de novo genes; some transcription factors contain more de novo genes than others in their regulon. Leveraging genetic and genomic tools in Drosophila, we further examined the role of two key transcription factors and the regulatory architecture of novel genes. Our findings identify key transcription factors associated with the expression of de novo genes and provide new insights into how modifications in existing transcription factors enable the emergence, maintenance, and regulation of de novo genes.

evolutionary biology↗

bioRxiv2024

Multimodal single-cell analyses reveal molecular markers of neuronal senescence in human drug-resistant epilepsy

The histopathological neurons in the brain tissue of drug-resistant epilepsy exhibit aberrant cytoarchitecture and imbalanced synaptic circuit function. However, the gene expression changes of these neurons remain unknown, making it difficult for the diagnosis or to dissect the mechanism of drug-resistant epilepsy. By integrating whole-cell patch clamp recording and single-cell RNA sequencing approaches, we identified a transcriptionally distinct subset of cortical pyramidal neurons. These neurons highly expressed genes CDKN1A (P21), CCL2 and NFKBIA that associated with mTOR pathway, inflammatory response and cellular senescence. We confirmed the expression of senescent marker genes in a subpopulation of cortical pyramidal neurons with enlarged soma size in the brain tissue of drug-resistant epilepsy. We further revealed the expression of senescent cell markers P21, P53, COX2, {gamma}-H2AX, {beta}-Gal and reduction of nuclear integrity marker Lamin B1 in histopathological neurons in the brain tissue of drug-resistant epilepsy patients with different pathologies, but not in control brain tissue with no history of epilepsy. Additionally, chronic, but not acute, epileptic seizures induced senescent markers expression in cortical neurons in mouse models of drug-resistant epilepsy. These results provide important molecular markers for histopathological neurons and new insights into the pathophysiological mechanisms of drug-resistant epilepsy.

neuroscience↗

bioRxiv2024

The comprehensive detection of hemoglobinopathy variants via long-read sequencing

BACKGROUNDThe genetic complexity of hemoglobin genes, characterized by high GC content and homologous sequences, poses significant challenges for detecting hemoglobin variants in clinical settings. METHODSA long-read indexed PCR method utilizing the novel CycloneSEQ nanopore sequencing platform was developed to detect all variant types, including single nucleotide variants (SNVs), deletions, structural variants (SVs) in HBA, HBB, HBD, and HBG genes. The method was validated using 507 clinical samples to assess its performance. RESULTSThe long-read indexed PCR system employed 13 primers targeting the hemoglobin gene clusters. This design enabled the detection of 37 types of HBA deletions, 5 SV (3 multicopies (, anti3.7, anti4.2) and 2 fusion allele (HK and anti-HK)), 37 HBB deletions, and all SNVs in the targeted regions. Validation across 507 samples (84 with HBA variants, 60 with HBB variants, 256 with both HBA and HBB variants, and 107 with no known variants) demonstrated 100.0% sensitivity and specificity. Additionally, the long-read sequencing enabled phasing of variants within hemoglobin genes, providing insights critical for clinical interpretation. CONCLUSIONSThe long-read indexed PCR method, combined with the CycloneSEQ nanopore sequencing platform, proved to be a robust and efficient solution for detecting hemoglobinopathy variants. The integration of indexed primers and barcoding enhances scalability, making this method ideal for large-scale population screening programs in the future.

genomics↗

bioRxiv2024

Diverse quorum sensing systems regulate microbial communication and biogeochemical processes in deep-sea cold seeps

Quorum sensing is a fundamental chemical communication mechanism that enables microorganisms to coordinate behavior and adapt to environmental conditions. In deep-sea cold seep ecosystems, where diverse microbial communities thrive, quorum sensing is likely a key mechanism driving microbial interactions. However, the distribution, mechanisms, and ecological roles of quorum sensing in cold seeps remain poorly understood. To address this, we analyzed 173 metagenomes, 33 metatranscriptomes, and 18 metabolomes from 17 global cold seep sites. We identified 299,355 quorum sensing genes from the seep non-redundant gene catalog, representing 34 gene types across six quorum sensing systems, with distribution patterns influenced by sediment depth and seep type. These quorum sensing genes were present in 3,576 metagenome-assembled genomes from 12 archaeal and 108 bacterial phyla, revealing a complex network of intraspecies and interspecies communication. Microbial groups involved in key metabolic processes, such as sulfate-reducing bacteria, anaerobic methanotrophic archaea, diazotrophs and organohalide reducers, were extensively regulated by quorum sensing, influencing biogeochemical cycles of carbon, nitrogen, and sulfur. Phylogenetic analysis and protein domain identification highlighted the functional roles of key quorum sensing-related proteins (e.g., PDEs, CahR, RpfC/G and LuxR) in modulating microbial behaviors, such as motility and chemotaxis. Heterologous expression and metabolomic profiling further confirmed the activity of representative LuxI-R pairs and identified inhibitors of quorum sensing in cold seep sediments. Overall, these findings highlight complexity and significance of quorum sensing in microbial interactions, ecological adaptation, and biogeochemical cycling within cold seep ecosystems, advancing our understanding of microbial communication in the deep biosphere.

microbiology↗

bioRxiv2024

scMoE: single-cell Multi-Modal Multi-Task Learning via Sparse Mixture-of-Experts

Recent advances in measuring high-dimensional modalities, including protein levels and DNA accessibility, at the single-cell level have prompted the need for frameworks capable of handling multi-modal data while simultaneously addressing multiple tasks. Despite these advancements, much of the work in the single-cell domain remains limited, often focusing on either a single-modal or single-task perspective. A few recent studies have ventured into multimodal, multi-task learning, but we identified a [circled1] Optimization Conflict issue, leading to suboptimal results when integrating additional modalities, which is undesirable. Furthermore, there is a [circled2] Costly Interpretability challenge, as current approaches predominantly rely on costly post-hoc methods like SHAP. Motivated by these challenges, we introduce scMoE1, a novel framework that, for the first time, applies Sparse Mixture-of-Experts (SMoE) within the single-cell domain. This is achieved by incorporating an SMoE layer into a transformer block with a cross-attention module. Thanks to its design, scMoE inherently possesses mechanistic interpretability, a critical aspect for understanding underlying mechanisms when handling biological data. Furthermore, from a post-hoc perspective, we enhance interpretability by extending the concept of activation vectors (CAVs). Extensive experiments on simulated datasets, such as Dyngen, and real-world multi-modal single-cell datasets, including {DBiT-seq, Patch-seq, ATAC-seq}, demonstrate the effectiveness of scMoE. Source code of scMoE is available at: https://github.com/UNITES-Lab/scMoE.

bioinformatics↗

bioRxiv2024

A Multi-Property Optimizing Generative Adversarial Network for de novo Antimicrobial Peptide Design

Antimicrobial peptides (AMPs) play a crucial role in developing novel antiinfective drugs due to their broad-spectrum antimicrobial activity and lower likelihood of causing bacterial resistance. However, laboratory synthesis of AMPs is tedious and time-consuming. Existing computational methods have limited capability in optimizing multiple desired properties simultaneously. Here, we propose a Multi-Property Optimizing Generative Adversarial Network (MPOGAN), a feedback-loop framework that iteratively learns from data with multiple desired properties. This approach enables de novo design of AMPs with potent antimicrobial activity, reduced cytotoxicity, and diversity. Through extensive computational tests, MPOGAN exhibits superior performance in optimizing multiple desired properties of generated AMPs. Ten of the most promising candidates are chemically synthesized, with nine showing potent antimicrobial activity against three bacterial strains and low cytotoxicity against eukaryotic cells. MPOGAN offers a powerful computational approach for effective multi-property optimization of AMPs, thereby advancing the field of AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

Spotiphy enables single-cell spatial whole transcriptomics across the entire section

Spatial transcriptomics (ST) has advanced our understanding of tissue regionalization by enabling the visualization of gene expression within whole tissue sections1, but the approach remains dogged by the challenge of achieving single-cell resolution without sacrificing whole genome coverage2,3. Here we present Spotiphy (Spot imager with pseudo single-cell resolution histology), a novel computational toolkit that transforms sequencing-based ST data into single-cell-resolved whole-transcriptome images. In evaluations with Alzheimers disease (AD) and normal mouse brains, Spotiphy delivers the most precise cellular compositions. For the first time, Spotiphy reveals novel astrocyte regional specification in mouse brains. It distinguishes sub-populations of DAM (Disease-Associated Microglia) located in different AD mouse brain regions. Spotiphy also identifies multiple spatial domains as well as changes in the patterns of tumor-tumor microenvironment interactions using human breast ST data. Spotiphy enables visualization of cell localization and gene expression in tissue sections, offering key insights into the function of complex biological systems.

systems biology↗

bioRxiv2024

Better Prior Distribution for Antibody Complementarity-Determining Regions Design

Designing antibodies with desired binding specificity and affinity is essential for pharmaceutical research. While diffusion-based models have advanced the co-design of the Complementarity-Determining Regions (CDRs) sequences and structures, challenges remain, including non-informative prior distribution, incompatibility with discrete amino acid types, and impractical computational cost in large-scale sampling. To address these, we proposed FlowDesign, a sequence-structure co-design approach based on Flow Matching, offering: (1) Flexible selection of prior distributions; (2) Direct matching of discrete distributions; (3) Enhanced computational efficiency for large-scale sampling. By leveraging various priors, data-driven structural models proved the most informative. FlowDesign outperformed baselines in Amino Acid Recovery (AAR), RMSD, and Rosetta energy. We also applied FlowDesign to design antibodies targeting the HIV-1 receptor CD4. FlowDesign yielded antibodies with improved binding affinity and neutralizing potency compared to the antibody Ibalizumab across multiple HIV mutants, validated by Biolayer Interferometry (BLI) and pseudovirus neutralization. This highlights FlowDesigns potential in antibody and protein design. A record of this papers Transparent Peer Review process is included in the Supplemental Information.

bioinformatics↗

bioRxiv2024

Human-mouse proteomics reveals the shared pathways in Alzheimer's disease and delayed protein turnover in the amyloidome

Murine models of Alzheimers disease (AD) are crucial for elucidating disease mechanisms but have limitations in fully representing AD molecular complexities. We comprehensively profiled age-dependent brain proteome and phosphoproteome (n > 10,000 for both) across multiple mouse models of amyloidosis. We identified shared pathways by integrating with human metadata, and prioritized novel components by multi-omics analysis. Collectively, two commonly used models (5xFAD and APP-KI) replicate 30% of the human protein alterations; additional genetic incorporation of tau and splicing pathologies increases this similarity to 42%. We dissected the proteome-transcriptome inconsistency in AD and 5xFAD mouse brains, revealing that inconsistent proteins are enriched within amyloid plaque microenvironment (amyloidome). Determining the 5xFAD proteome turnover demonstrates that amyloid formation delays the degradation of amyloidome components, including A{beta}-binding proteins and autophagy/lysosomal proteins. Our proteomic strategy defines shared AD pathways, identify potential new targets, and underscores that protein turnover contributes to proteome-transcriptome discrepancies during AD progression.

biochemistry↗