Biology subjects

Shang, Y.

Publications and source records attributed to Shang, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Mechanism-selective deep mutational scanning distinguishes ERCC2 disease phenotypes

Pathogenic ERCC2 variants cause xeroderma pigmentosum (XP), trichothiodystrophy (TTD) or both, yet variant effect scores are usually interpreted only as measures of pathogenicity rather than of which disease mechanism is disrupted. XPD, the ERCC2-encoded TFIIH subunit, functions in both nucleotide excision repair and transcription. Using yeast complementation deep mutational scanning, we measured the effects of nearly all XPD amino acid substitutions. The assay was mechanism-selective: it preferentially reported transcription-associated function, with pronounced intolerance at the p44 interface, whereas many substitutions affecting DNA binding and helicase activity retained near-wild-type fitness. Accordingly, TTD variants had much lower fitness than XP variants. Computational predictors discriminated pathogenic from benign variants similarly across phenotypes, but the DMS distinguished XP from TTD variants better than all 73 predictors tested. Phenotype-specific ACMG/AMP calibration provided evidence in both directions for TTD but mainly pathogenic evidence for XP. Thus, the selectivity of functional assays, often viewed as a limitation, can reveal disease mechanisms and support phenotype-aware variant interpretation.

genetics↗

bioRxiv2026

Potato Agent: AI-Driven Data and Knowledge Exploration on an Agent-Ready Potato Multi-Omics Platform

Potato is an important non-cereal food crop worldwide. However, the limited number of functionally validated genes remains a major bottleneck to favorable allele stacking and genome design breeding in potato. Rapid advances in AI agents offer a promising means to support crop breeding by translating natural-language questions into coordinated data analysis and knowledge retrieval. Their reliable use for potato breeding, however, is constrained by fragmented multi-omics resources that lack consistent curation and machine-accessible interfaces. Here, we constructed an agent-ready potato multi-omics database integrating genomic resources from 150 potato accessions, 259 bulk RNA-seq samples, and 14 spatial transcriptomic datasets into a pangenome, a tissue expression atlas, co-expression networks, and spatial expression maps accessible through open APIs. We developed 39 potato-specific Agent Skills for reproducible bioinformatics analysis and comprehensive data and knowledge exploration, enabling natural-language questions to be translated into standardized data-retrieval and analysis tasks. By integrating direct evidence from potato studies, functions of homologous genes in Arabidopsis, rice, and maize, and tissue expression patterns, we generated genome-wide functional predictions for 37,658 genes in the DM reference genome. We further developed Potato Agent as a multi-user, browser-based platform with isolated workspaces and online result preview, reducing the technical burden of agent deployment and providing direct access to integrated data, knowledge, and workflows. Case studies demonstrated its capabilities in reproducible bioinformatics analysis, agent-assisted identification of a tuber development regulator, scientific data visualization, and haplotype-aware promoter analysis and sgRNA design. Together, the agent-ready database and Potato Agent provide an integrated infrastructure for functional gene discovery and hybrid breeding in potato.

plant biology↗

bioRxiv2026

Ginsenoside Ro ameliorates diabetic cardiomyopathy by maintaining ciliary homeostasis and enhancing antioxidation

ObjectiveTo investigate and clarify the role of Ginsenoside Ro (GRo) in diabetic cardiomyopathy (DiaCM) and to elucidate the molecular mechanism by which GRo ameliorates DiaCM. Methods[circled1] The construct of type 2 diabetic mouse model. The bought C57BL/6 male mice were housed in a specific pathogen-free (SPF) animal facility and randomly divided into control, STZ (model), STZ + GRo, and control+GRo groups. The STZ (model) and STZ + GRo groups were fed a high-fat and high-glucose diet combined with intraperitoneal injection of streptozotocin (STZ). The control and control + GRo groups were fed a normal diet, while the control + GRo and STZ + GRo groups were treated with GRo via oral gavage. Then, all groups were evaluated for cardiac function and structure by small animal echocardiography and histological staining including hematoxylin and eosin (HE) and Massons trichrome staining to screen and confirm diabetic cardiomyopathy in mice. Finally, immunofluorescence staining of cilia in mouse heart tissue was performed to determine whether GRo inhibits abnormal ciliary growth. [circled2] The construct of cell models. First, the CCK-8 (Cell Counting Kit-8) assay was used to separately evaluate the cytotoxicity of GRo and the combination of TGF-{beta}1 and PA in myocardial fibroblasts and cardiomyocytes. Subsequently, mouse myocardial fibroblast lines (MCFs) were treated with transforming growth factor-beta 1 (TGF-{beta}1), and H9c2 cardiomyocytes were treated with palmitic acid (PA). Both cell types then received the GRo treatment. [circled3] Molecular and cellular testing. Firstly, we measured serum levels of cardiac injury markers (CK-MB, MYO, and TNNI3), glutathione (GSH), and malondialdehyde (MDA). Secondly, we examined the expression of myocardial fibrosis-related genes (Col1a1, etc.), myocardial hypertrophy markers (Nppa, etc.), cilia-specific genes (Pkd1, etc.), and oxidative stress-related genes (Nrf2, etc.) in both animal and cell samples by Western blotting and RT-qPCR. Finally, we used immunofluorescence staining of myocardial fibroblasts to detect cilia length and phalloidin staining of cardiomyocytes to measure their cross-sectional area. [circled4] The correlation mechanism. Firstly, the cilia-specific inhibitory drug HIP-4 was used to disrupt cilia homeostasis by inhibiting cilia growth. Secondly, small activating RNA (saRNA) was used to upregulate the Pkd1 gene to verify whether GRo exerts its anti-fibrotic effects through the inhibition of PC1. Results[circled1] Animal level. A diabetic cardiomyopathy mouse model was successfully established by combining STZ injection with a high-fat and high-glucose diet, and treatment with GRo significantly ameliorated the associated symptoms. [circled2] Cellular level. We successfully established a myocardial fibrosis model by treating myocardial fibroblasts with TGF-{beta}1, and a myocardial hypertrophy model by treating cardiomyocytes with PA. Immunofluorescence staining demonstrated that GRo significantly decreased cilia length in the fibrosis model, while phalloidin staining showed that GRo significantly attenuated the increase in cardiomyocyte cross-sectional area. [circled3] Molecular level. Compared with the model group, GRo treatment significantly reduced serum levels of cardiac injury markers (CK-MB, MYO and TNNI3), glutathione (GSH) and malondialdehyde (MDA). Western blotting and RT-qPCR analyses of both animal and cell samples revealed that GRo markedly alleviated indicators of myocardial fibrosis and hypertrophy, while also suppressing cilia-specific genes and oxidative stress-related genes. Overall, GRo significantly ameliorated the markers associated with myocardial fibrosis and hypertrophy, and inhibited cilia-specific protein expression as well as oxidative stress parameters. [circled4] The correlation mechanism. The cilia-specific drug hedgehog pathway inhibitor 4 (HPI-4) was used to revealed that cilia homeostasis is closely linked to myocardial fibrosis and shortened cilia inhibit the fibrosis progression. Furthermore, upregulation of the Pkd1 gene by small activating RNA demonstrated that PC1 overexpression abrogates the therapeutic effect of GRo. Finally, GRo can alleviate DiaCM.

Molecular Biology↗

bioRxiv2026

Collagen Rope Trick: Cell-Laden Fibre Assembly at 1 Liquid Interfaces

Summary ParagraphTissues and organs in living organisms represent centimeter-scale hierarchical architectures comprising nano-to microscale, uniaxially aligned extracellular matrix (ECM) fibres with high mechanical strength, integrated with cellular components, as exemplified in tendon, skin, cartilage, bone, and blood vessels1. Here, we present a liquid-liquid interfacial spinning method to produce highly uniaxially aligned, centimeter-scale collagen fibres. The dried fibres exhibit exceptional mechanical properties, with fracture strength of 280 MPa, Youngs modulus of 6 GPa, and toughness of 17 MJ m-3, comparable to spider silk and tendon collagen, and exceeding supramolecular and double-network hydrogels1. Incorporating living cells into the collagen solution yielded centimeter-scale, cell-laden aligned fibres, with densely adherent, uniaxially aligned cells and over 80% viability. Myoblast-laden fibres recapitulate biological features of fibrotic muscle tissues, as observed in type II diabetes2. Interfacial collagen assembly further enables fabrication of dimension-controlled constructs, like 2D sheets, 0D capsules, and 1D tubes, thus providing modular building blocks for centimeter-scale 3D tissues and organ-like structures. This approach offers a versatile platform to engineer mechanically robust, cell-laden tissues with controlled hierarchical architecture.

bioengineering↗

bioRxiv2026

Curvature-mediated prewetting organize mitochondrial nucleoid

The emergence of spatiotemporal order in diffusive cellular environments requires physical mechanisms to overcome the entropic drive toward disorder. While the organizing role of chemical signaling is well characterized, how complex membrane curvature regulate soluble molecular organization remains a fundamental open question. Here, we establish membrane curvature as a thermodynamic control parameter for the condensation of soluble proteins through prewetting. Using the mitochondrial transcription factor TFAM, we demonstrate that intrinsic membrane curvature locally drives a prewetting transitiona surface-mediated phase separation distinct from bulk condensation. By combining in vitro reconstitution, live-cell super-resolution imaging, cryo-electron tomography, and thermodynamic theory, we show that negatively high-curvature regions lower the nucleation energy barrier of Tfam, driving localized protein condensation at physiological concentrations. These results reveal that membrane curvature does not merely scaffold cellular machinery but manipulates the local free energy landscape, establishing a geometric principle for the spatial control of biological processes.

biophysics↗

bioRxiv2026

Clinical evidence yield as a framework for evaluating computational predictors and multiplexed assays of variant effect

Interpreting the clinical significance of missense variants of uncertain significance (VUS) remains a major challenge in clinical genetics. Although computational variant effect predictors (VEPs) and multiplexed assays of variant effect (MAVEs) can generate large-scale functional scores, their value is typically assessed using discrimination metrics such as AUROC rather than by the strength of evidence they provide under ACMG/AMP guidelines. Here, we introduce mean evidence strength (MES), a quantitative metric that summarises the pathogenic and benign evidence assigned across missense variants following gene-level Bayesian calibration. Using the acmgscaler framework, we calibrated 12 population-free VEPs across 367 disease genes and analysed 15 MAVE datasets with sufficient clinical data. MES revealed important discrepancies with AUROC, including cases where methods with similar discrimination differed substantially in evidence yield. MAVEs achieved high average MES despite lower AUROC, while several VEPs showed strong discrimination but more limited calibrated evidence. Among predictors, CPT-1 achieved the highest MES and provided moderate or stronger evidence for the largest fraction of ClinVar VUS. MES therefore provides a practical framework for evaluating computational and experimental variant effect datasets in terms of calibrated clinical evidence yield.

bioinformatics↗

bioRxiv2026

APOE4 Accelerates Menopause-Associated Brain Metabolic Shift and Disrupts Bioenergetic Adaptation

IntroductionDisruption of brain glucose and lipid metabolism contributes to Alzheimers disease (AD) and often emerges before clinical symptoms. Women are at elevated AD risk due to menopause-associated estrogen decline, which impairs mitochondrial function and glucose metabolism. Womens risk of AD is further elevated by the APOE4 allele, the strongest genetic risk factor for late-onset AD. MethodsTo investigate the impact of APOE genotype on the menopausal metabolic transition, brain metabolomic and lipidomic profiling was conducted in humanized female APOE3/3, APOE3/4, and APOE4/4 mice across chronological and endocrinological stages of peri-to postmenopausal transition. ResultsAPOE3/3 mice exhibited dynamic regulation of brain metabolic systems that supported postmenopausal bioenergetic demand. In contrast, APOE3/4 and APOE4/4 mice displayed accelerated and altered metabolic shifts, resulting in postmenopausal amino acid depletion, reduced tricarboxylic acid (TCA) cycle intermediates, lipid accumulation, and alterations in brain lipid composition. A single APOE4 allele was sufficient to impair metabolic adaptation, while APOE4 homozygosity resulted in greater severity of deficits. DiscussionOutcomes of these analyses revealed that APOE4 accelerated menopause-related metabolic decline and compromised bioenergetic adaptation, providing a mechanistic basis for increased AD susceptibility and earlier onset in APOE4-positive women.

neuroscience↗

bioRxiv2026

BiOmics: A Foundational Agent for Grounded and Autonomous Multi-omics Interpretation

While AI has automated bioinformatic workflows, biological interpretation remains fragmented and often disconnected from mechanistic insights. Existing AI is bifurcated between statistical "black-box" models that lack logical grounding and simple agents restricted to shallow knowledge retrieval. To bridge this divide, we introduce BiOmics, a foundational agent that synthesizes multi-omics data with adaptive knowledge for biological interpretation. BiOmics introduces a novel dual-track architecture comprising a harmonized explicit reasoning space for grounded logic and a unified latent embedding space for high-dimensional association mapping. This architecture enables a transformative "Retrieving-Reasoning-Predicting" paradigm for purposeful, cross-scale inference traversing the biological hierarchy, from molecular variants to disease phenotypes. Empirical evaluations demonstrate that BiOmics surpasses state-of-the-art AI agents and specialized algorithms, markedly augmenting the granularity and depth of biological insights. Specifically, BiOmics exhibits unique superiority in uncovering indirect pathogenic variants, achieving reference-free cell annotation, and prioritizing drug repurposing candidates tailored to specific datasets. BiOmics further enriches the interpretive landscape of biological entities, leveraging its reasoning-grounded knowledge graph to uncover deep functional contexts. Ultimately, BiOmics provides a versatile engineering foundation to transition AI for Science from descriptive "data fitting" to autonomous, knowledge-driven interpretation.

bioinformatics↗

bioRxiv2026

Carbon Cybernetics Array: a miniaturized carbon-based microelectrode array for intracortical recording

Implantable brain-machine interfaces, capable of capturing high-resolution neural signals, hold great promise for treating neurological conditions and advancing neuroscience research. As the field moves toward chronic, fully implantable systems, ensuring the long-term safety and stability of the microelectrode arrays, the core component of these interfaces, remains a significant challenge. Hermetic sealing, which prevents moisture and contaminants from entering the device, is a critical yet often overlooked factor in array designs. This study reports the Carbon Cybernetics Array, a hermetically sealed, carbon-based microelectrode array for neural interfacing. Carbon fiber electrodes are anchored on a diamond substrate via a hermetic feedthrough structure, with hermeticity validated through helium leak testing. These ultrathin and flexible carbon fibers require minimal insertion force, cause little tissue damage after six months of implantation in rats and enable single-unit neural recordings. Furthermore, a low-cost, manually controllable insertion toolset is developed for precise array implantation in the sheep brain through a small burr hole, demonstrating a step toward clinical translation. Finally, the scalability of the fabrication approach is exemplified by arrays with over 1000 fibers. Together, this hermetically sealed feedthrough structure will lay the foundation for a future fully implantable device with wireless capabilities.

bioengineering↗

bioRxiv2025

Targeting Endothelial PERK Accelerates Lymphoid Regeneration by Enhancing DLL4-NOTCH3 Signaling at the Pre-B Niche

Delayed immune recovery after hematopoietic stem cell (HSC) transplantation is associated with a poor clinical outcome, yet strategies to enhance lymphocyte regeneration are limited. We studied the role of unfolded protein response (ER stress) in hematopoietic regeneration within the bone marrow (BM) microenvironment. We revealed that PERK activation is a prominent feature of BM endothelium in leukemia patients and is a hallmark response in mouse BM following ionizing irradiation. Ablating endothelial Perk boosted Notch ligand DLL4 expression and promoted DLL4-dependent early HSC and B progenitor regeneration. Single-cell analysis shows that endothelial DLL4 activates NOTCH3 expressed by mesenchymal stroma cells, and that the PERK-DLL4 axis coordinates the regulation of lymphoid commitment and niche cytokine production. NOTCH3 is critical for the upregulation of IL7 following irradiation and for supporting the expansion of lymphoid progenitors in mesenchymal sphere cultures. These findings not only unveil a previously unrecognized ER stress-controlled vascular-stroma signaling mechanism in regenerative hematopoiesis but also highlight PERK blockade as a promising therapeutic strategy to improve immune recovery after myeloablative transplantation. SummaryZou et al unravel that the adaptive ER stress response in bone marrow blood vessels restricts the post-transplant regeneration of immune progenitor cells by attenuating the expression of Notch ligand DLL4. Targeting ER stress sensor PERK can accelerate immune recovery after transplantation by enhancing DLL4-NOTCH3 signaling and IL7 cytokine production.

cell biology↗

bioRxiv2025

Metabolic Immunosuppression Mediated by Proliferative CD168+TAMs in Colon Cancer

The role of non-monocyte-derived, in situ proliferating tumor associated macrophages (TAMs) in tumor progression has been underappreciated. Proliferative TAM subsets likely represent critical mediators in establishing the immunosuppressive microenvironment, given the susceptibility of TAMs to be hijacked by malignant cells for pro-tumorigenic functions. However, the regulatory networks governing their self-renewal circuitry and lineage bifurcation remained undefined. Combining single cell RNA sequencing of human and murine colon tumors, we identified CD168+ TAMs, a hyperproliferative subpopulation with FOXM1-dependent maintenance of replicative competence. Spatial multi-omics and functional validation revealed that this subset exhibited peritumoral localization and underwent immunosuppressive polarization through cholesterol-coordinated CX3CL1-CX3CR1 signaling. Colon cancer-specific lipid metabolic rewiring elevates glycerophospholipid and cholesterol flux, with PLA2G7-mediated glycerophospholipid catabolism promoting CX3CR1 expression in TAMs. Thus, the CX3CR1 signaling-driven immunosuppressive effect of CD168+ TAM is an integrated response to tumor-specific metabolic features. Targeting the CD168+ TAMs may enable therapeutic strategies for metabolic-immune reshaping in colon cancers.

cancer biology↗

bioRxiv2025

Integrated Single-Cell and Spatial Transcriptomic Analysis Reveals an Aging-Associated Fibroblast Subtype Linked to Tumor Progression in Human Skin

Aging is a major risk factor for the development of many cancers, yet the mechanisms underlying this increased susceptibility remain incompletely understood. Traditionally, the accumulation of genetic mutations over time has been considered a primary driver of age-related tumorigenesis. However, emerging evidence highlights the critical role of the aging tissue microenvironment--including changes in immune, stromal, and epithelial compartments--in shaping cancer initiation and progression. In this study, we employed integrated single-cell and spatial transcriptomics to systematically characterize age-associated alterations in human skin and skin cancers. Our analysis uncovered widespread, cell type-specific transcriptional reprogramming with age, revealing key pathways and cellular populations that may contribute to a pro-tumorigenic environment. Notably, we identified a previously unrecognized fibroblast subtype marked by SFRP2 expression, which expands with age and is associated with poor prognosis in basal cell carcinoma. These fibroblasts appear to enhance Wnt signaling within the tumor niche, suggesting a potential mechanism by which the aging stroma supports malignancy. Collectively, our findings shed light on how age-related changes in tissue ecosystems may predispose to cancer and point to novel therapeutic opportunities for targeting the aged tumor microenvironment.

cancer biology↗

bioRxiv2025

The genomic and transcriptional landscape of the spinal cord H3K27-altered diffuse midline glioma suggests the potential therapeutic strategy

Diffuse midline glioma with H3K27-altered (DMG) is a lethal pediatric malignancy that primarily occurs in the brainstem of children. In adults, DMG arising in the spinal cord is rarely reported and remains poorly understood. The cellular architecture and clinical outcomes of DMG vary depending on the tumors location. To dissect the genomic and transcriptional architecture of a cohort of spinal cord DMG patients, we conducted whole-exome sequencing and single-cell RNA sequencing on 19 tumor samples from 7 patients. We identified previously underappreciated stem-like cells associated with hypoxia in malignant tumor cells, which were present in all samples of spinal cord DMG but absent in published intracranial DMG, corroborating cellular heterogeneity based on tumor location. We discovered that tumor-associated myeloid cells constituted the largest population of non-malignant cells in adult spinal cord DMG. Our research revealed a transition from microglia to macrophages, characterized by enhanced cell-to-cell interactions mediated through the VEGF signaling pathway network. Notably, we found that epigenetic agents can repress the expression of hypoxia-related gene programs in patient-derived spinal cord DMG cultures and inhibit cell proliferation in vitro. Collectively, our study reveals a crucial anatomical dimension that DMG exhibits a location-specific genomic and transcriptional landscape despite shared H3K27 alterations, providing the paradigm for developing precision therapeutic strategies that extend beyond DMG to other molecularly defined yet anatomically divergent malignancies.

cancer biology↗

bioRxiv2025

Mechanism of clinically relevant neurosecretory and metabolic impairment in Alzheimers and identification of engineered nanotherapy

A central challenge in Alzheimers disease is understanding the mechanism of neuronal secretory dysfunction. By exploiting AI, we reveal how beta-amyloid disrupts key protein interactions within the neuronal secretory machinery. In a combinatorial strategy of reprogramming the neuronal secretory and metabolic components, we established a dual-target therapeutic framework that repairs synaptic and mitochondrial defects to counteract neurodegeneration in Alzheimers.

neuroscience↗

bioRxiv2025

RegFormer: A Single-Cell Foundation Model Powered by Gene Regulatory Hierarchies

Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular diversity, but current computational models often fail to incorporate regulatory priors, handle data sparsity, or efficiently process long gene sequences. Here, we present RegFormer, a foundation model that integrates gene regulatory networks (GRNs) with Mamba-based state-space modeling, overcoming the scalability and context-length limitations of Transformer architectures. RegFormer encodes each gene through dual embeddings, a value embedding for quantitative expression and a token embedding for regulatory identity, organized within a GRN-guided gene order to capture both expression dynamics and hierarchical regulation. Pretrained on 26 million human single cells spanning 45 tissues and diverse biological contexts, RegFormer achieves superior scalability and biological fidelity. Across comprehensive benchmarks, it consistently outperforms state-of-the-art single-cell foundation models (scGPT, Geneformer, scFoundation, and scBERT), delivering higher clustering accuracy, improved batch integration, and more precise cell type annotation. RegFormer also reconstructs biologically coherent GRNs, accurately models transcriptional responses to genetic perturbations, and enhances drug response prediction across cancer cell lines. By combining regulatory priors with efficient long-sequence Mamba modeling, RegFormer establishes a biologically grounded and scalable framework for single-cell representation learning, enabling deeper mechanistic insight into gene regulation and cellular state transitions.

bioinformatics↗

bioRxiv2024

Engineering tissue-mimetic hydrogels with continuous viscoelastic gradient for programmed cell migration

The dynamic, viscoelastic nature of the extracellular matrix (ECM), with variations in stiffness and viscosity, plays a key role in cellular behaviors like mechano-sensing, migration, and force generation. Viscoelastic hydrogels are important for mimicking the ECM to study cell migration and tissue engineering. However, creating hydrogels with continuous viscoelastic gradients is challenging due to issues with spatial resolution, reproducibility, and accurately replicating native tissue properties. Here we present a novel approach to generate hydrogels with precisely controllable viscoelastic gradients using drop-by-drop condensation. This approach allows fine-tuned replication of the tissue-specific local mechanical properties, resulting in hydrogels of heterogeneous viscoelasticity. Directed migration and separation of multiple cell lines are thus driven by local viscosity and elasticity rather than solely stiffness. By incorporating non-linear mechanical gradients, this technique provides insights into ECM viscoelasticitys role in cellular behavior and offers a versatile platform for advanced tissue engineering and regenerative medicine applications.

biophysics↗

bioRxiv2024

TurboID-based proximity labeling discovers ABCF2 as an adhesion receptor for the zoonotic pathogen Pasteurella multocida

Pasteurella multocida is a zoonotic pathogen that can cause fatal infections in both animals and humans. A significant number of putative adhesive factors have been predicted to contribute to the pathogenesis of P. multocida, but their interactive proteins on host cells remain unclear. In this study, we experimentally verified the roles of three previously proposed proteins (PlpE, PtfA, Hsf-2) in the adherence of P. multocida. Through turboID-based proximity labeling screening, we identified ATP-binding cassette sub-family F member 2 (ABCF2) as a host interactive protein for PlpE/PtfA/Hsf-2. Crucial amino acid residues in PlpE, PtfA, and/or Hsf-2 that are essential for interacting with ABCF2 included Asp-123 (PlpE), Lys-88 (PtfA), Asp-136 (PtfA), Ala-464 (Hsf-2), Glu-473 (Hsf-2), and Arg-489 (Hsf-2). Knocking down or knocking out ABCF2 significantly reduced the adherence and invasion of P. multocida to host cells, while overexpression of ABCF2 markedly increased these effects. However, ABCF2 did not contribute to the adherence of other bacterial species such as Klebsiella pneumoniae and Bordetella bronchiseptica. Additionally, we demonstrated that P. multocida infection upregulated the expression of host ABCF2 by activating the p38 MAPK and NF-{kappa}B signaling pathways. Furthermore, we showed that ABCF2 was involved in the P. multocida-induced p53-dependent apoptotic signaling pathway. To the best of our knowledge, this is the first identification of ABCF2 as a host factor contributing to the adherence of P. multocida and only the second report of ABCF2s involvement in bacterial pathogenesis. ImportanceP. multocida can cause fatal infections in both animals and humans, yet the mechanisms related to its pathogenesis remain to be fully explored. In this study, we identified ABCF2 as a crucial host interactive protein for three adhesive proteins encoded by P. multocida and experimentally verified its role in the adherence and invasion of P. multocida. Furthermore, we elucidated how P. multocida modulates ABCF2 during its infection and revealed p53-dependent apoptosis as a downstream effect of ABCF2 during P. multocida infection. Given the absence of reports on ABCF2 contributing to the pathogenesis of P. multocida and only one previous report on the involvement of ABCF2 in bacterial pathogenesis prior to this study, this research could be valuable for comprehending the interactions between bacteria and hosts during bacterial infections.

microbiology↗

bioRxiv2024

Reprogramming the neuronal secretory and metabolic machinery using correctors for Alzheimer therapy

Alzheimer disease (AD) is a neurodegenerative disorder characterized by memory loss and personality changes, leading to dementia. The primary cause of the cognitive decline that characterizes AD is the loss of neurons, hypothesized as being due to secretory defects in neurotransmitter release and synaptic plasticity. There is growing evidence that in Alzheimer there is impaired neuronal metabolism due to an increase in free radicals and mitochondrial fission, leading to loss in ATP synthesis required for neurotransmission. Therefore, impaired metabolism in neurons may lead to the observed defects in neurotransmitter release, resulting in the loss of neuronal function and connections in regions of the brain involved in memory and reasoning. In our earlier studies, peptide inhibitor targeting oligomeric ATAD3A, a protein essential for mitochondrial fission and bioenergetics, were found to partially rescue from AD, both in AD neurons and AD mice. In the current study in AD neurons, neuronal porosome reconstitution combined with either a linear or circular peptide inhibitor of ATAD3A oligomers, was able to restore AD neurons to near normal levels of viability and greatly reduce oxidative stress in mitochondria. Additionally, the peptide and a small molecule considered safe by the FDA and used as a food additive, were also able to greatly increase viability in AD neurons and provide reduction to near normal levels of mitochondrial oxidative stress. Collectively, these results demonstrate great promise as secretory and metabolic correctors for AD therapy.

neuroscience↗