Biology subjects

Zhang, H.

Publications and source records attributed to Zhang, H..

At least 451 records · Page 25Linked to original sources

bioRxiv2025

Exogenous melatonin mitigates drought stress by promoting the living cortical area of roots in cotton

The root cortex plays a critical role in water absorption, influencing root function and metabolic activity. However, the effects of melatonin on root cortical cells and its role in drought resistance remain unclear. This study examines the impact of exogenous melatonin on the root cortex of cotton under drought stress, focusing on its relationship with water uptake and drought resilience. Cotton plants were treated with 8% PEG6000 for drought stress and 100 {micro}M melatonin by foliar application. The results demonstrated that melatonin application significantly increased the living cortical area of roots under drought stress, with notable increases of 26.34% and 59.00% at distances of 1 cm and 13 cm from the root tip, respectively. Melatonin also enhanced root cortical thickness, promoted osmotic regulation, increased respiratory enzyme activity, and improved water and nutrient uptake. Furthermore, melatonin application promoted both root and shoot growth. Notably, the living cortical area positively correlated with osmotic substance accumulation, root respiration, and absorption capacity under drought conditions. In conclusion, exogenous melatonin alleviates drought-induced damage by enhancing the living cortical area, optimizing osmotic regulation, and improving root absorption, thus promoting cotton growth and drought resistance. These findings highlight melatonin as a promising regulator for enhancing drought resistance. HighlightExogenous melatonin increases root cortical integrity of cotton roots under drought stress, improves the absorption of water and nutrients, promotes the growth of cotton, and enhances its drought resistance.

physiology↗

bioRxiv2025

Design and Synthesis of Potent First-in-Class Histones Acetyltransferase Modulators.

Epigenetic regulation governs gene expression through histone modifications, particularly the acetylation of lysine residues. These modifications are orchestrated by enzymes such as histone acetyltransferases (HATs) and histone deacetylases (HDACs). Among them, p300 plays a critical role in various disorders such as neurodegenerative conditions (i.e. Alzheimers disease, and Alzheimers Disease related dementia) and cancer (i.e. glioblastoma and B cell lymphoma). Our aim is to develop therapeutic interventions for these ailments. In this context, we designed and synthesized novel activators of the enzyme. Using an in vitro screening approach combined with structural activity relationship analysis, we successfully identified compounds that modulate histone acetylation.

biochemistry↗

bioRxiv2025

Landscapes of missense variant impact for human superoxide dismutase 1

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease for which important subtypes are caused by variation in the Superoxide Dismutase 1 gene SOD1. Diagnosis based on SOD1 sequencing can not only be definitive but also indicate specific therapies available for SOD1-associated ALS (SOD1-ALS). Unfortunately, SOD1-ALS diagnosis is limited by the fact that a substantial fraction (currently 26%) of ClinVar SOD1 missense variants are classified as "variants of uncertain significance" (VUS). Although functional assays can provide strong evidence for clinical variant interpretation, SOD1 assay validation is challenging, given the current incomplete and controversial understanding of SOD1-ALS disease mechanism. Using saturation mutagenesis and multiplexed cell-based assays, we measured the functional impact of over two thousand SOD1 amino acid substitutions on both enzymatic function and protein abundance. The resulting missense variant effect maps not only reflect prior biochemical knowledge of SOD1 but also provide sequence-structure-function insights. Importantly, our variant abundance assay can discriminate pathogenic missense variation and provides new evidence for 41% of missense variants that had been previously reported as VUS, offering the potential to identify additional patients who would benefit from therapy approved for SOD1-ALS.

genetics↗

bioRxiv2025

TEMI: Tissue Expansion Mass Spectrometry Imaging

The spatial distribution of diverse biomolecules in multicellular organisms is essential for their physiological functions. High-throughput in situ mapping of biomolecules is crucial for both basic and medical research, and requires high scanning speed, spatial resolution, and chemical sensitivity. Here, we developed a Tissue Expansion method compatible with matrix-assisted laser desorption/ionization Mass spectrometry Imaging (TEMI). TEMI reaches single-cell spatial resolution without sacrificing voxel throughput and enables the profiling of hundreds of biomolecules, including lipids, metabolites, peptides (proteins), and N-glycans. Using TEMI, we mapped the spatial distribution of biomolecules across various mammalian tissues and uncovered metabolic heterogeneity in tumors. TEMI can be easily adapted and broadly applied in biological and medical research, to advance spatial multi-omics profiling.

molecular biology↗

bioRxiv2025

Endogenously generated Dutch-type Aβ nonfibrillar aggregates dysregulate presynaptic neurotransmission in the absence of detectable inflammation

Structured AbstractO_ST_ABSBackgroundC_ST_ABSAPPE693Q ("Dutch") transgenic mice develop aging-related learning deficits and accumulate endogenously generated nonfibrillar aggregates of A{beta} (NFA-A{beta}) and APP -carboxy terminal fragments. NFA-A{beta} correlates with synaptic loss and memory deficits more closely than does fibrillar A{beta}. MethodsWe assessed the physiological, transcriptomic, ultrastructural, histological, and metabolic changes associated with the accumulation of NFA of Dutch A{beta} in brains of APPE693Q mice. ResultsAging-related accumulation of NFA-A{beta} in APPE693Q mice was revealed by A11 immunohistochemistry and cyclic D,L--peptide-FITC microscopy. Presynaptic termini of APPE693Q mice developed physiological abnormalities in post-tetanic potentiation, synaptic fatigue, synaptic vesicle replenishment, and an aging-related reduction in mitochondrial complex I activity. Single-cell RNA sequencing showed that excitatory neurons exhibited an altered transcriptomic profile involving "protein translation" and "oxidative phosphorylation". DiscussionAccumulation of NFA-A{beta} alters neuronal metabolism but does not activate inflammation. Depletion of all forms of A{beta} may be required to eliminate A{beta} toxicity with anti-amyloid antibodies.

neuroscience↗

bioRxiv2025

Quinpirole ameliorates the dysfunction of microglia in human LRRK2-R1441G transgenic mice

Microglia-mediated neuroinflammation is a key contributor to Parkinsons disease (PD) pathogenesis. Leucine-rich repeat kinase 2 (LRRK2), the leading genetic contributor to both familial and sporadic PD, has been implicated in driving this connection. However, its precise role remains incompletely understood due to technical challenges. To address this, we utilized a bacterial artificial chromosome (BAC) transgenic mouse model overexpressing human LRRK2-R1441G, which replicates key features of PD. These mice were crossed with Cx3cr1-EGFP mice to enable assessment of microglial dynamics and function using two-photon imaging in awake mice in vivo and acute brain slices ex vivo. Furthermore, spatial transcriptomic analysis was performed using GeoMx Digital Spatial Profiler technology to compare transgenic mice with their wild-type counterparts. The R1441G mutation upregulated antigen processing and presentation pathways, increased activated microglia, and enhanced microglial polarization in the dorsal striatum. Mutant microglia exhibited reduced motility and slower responses to focal injury, with processes retracting faster and extending more slowly. Quinpirole, a dopamine D2 receptor (D2R) agonist, successfully reversed microglial deficits. This study provides the first evidence that pathogenic LRRK2 mutations alter microglial motility and responsiveness in vivo, highlighting D2R activation as a promising therapeutic strategy to mitigate neuroinflammation and neurodegeneration in PD.

neuroscience↗

bioRxiv2025

Single-cell multiomics of neuronal activation reveals context-dependent genetic control of brain disorders

Most causal variants for neuropsychiatric disorders (NPD) remain unknown. A major hurdle is that disease variants may act in specific contexts, such as during neuronal activation, which is difficult to study in vivo at the population level. We profiled single-nucleus neuron-activation multiomics in human induced pluripotent stem cell (iPSC)-derived neurons from 100 donors, revealing the NPD-relevant transcriptomic/epigenomic landscape of neuronal activation. We identified abundant genetic variants associated with activity-dependent gene expression (eQTL) and chromatin accessibility (caQTL), the latter explaining larger proportions of NPD heritability. Integrating multiomic data with genome-wide association studies (GWAS) further revealed NPD risk variants and genes with effects detected only upon stimulation, such as activity-dependent cholesterol metabolism. Our work highlights the power of cell stimulation to reveal context-specific "hidden" genetic effects.

neuroscience↗

bioRxiv2025

RAPID: Reliable and efficient Automatic generation of submission rePortIng checklists with large language moDels

ImportanceMedical reporting guidelines are significant in improving the transparency, quality, and integrity of medical research, particularly in randomized clinical trials; adherence to these guidelines supports research interpretability and has direct implications for downstream applications, such as patient treatment. However, with over 600 distinct reporting guidelines, manual assessments are often time-consuming and labor-intensive. ObjectiveTo evaluate an automated reporting checklist generation tool using large language models and retrieval augmentation generation technology, called RAPID. Design, Setting, and ParticipantsThis study used large language models to design a retrieval augmentation generation architecture and collected published journal articles as training and validation sets to optimize prompts within the framework and comprehensively evaluate the performance of the framework. Medical reporting experiments were collected from 50 randomized controlled trials without the intervention of AI tools and 41 randomized controlled trials with the intervention of AI tools. Main Outcomes and MeasuresFor effective evaluation of the performance of this tool, a classification accuracy metric (Reported/Not Reported) defined as the number of correct judgments divided by all judgments and a content consistent score metric defined as the number of contents retrieved by the tool that are the same as those retrieved by researchers divided by the total number of judgments were calculated. ResultsThe RAPID tool uses the widely used Word document and Portable Document Format as an input file. Fifty published journal articles without the intervention of AI tools and 41 published journal articles with the intervention of AI tools were collected as CONSORT and CONSORT-AI datasets. All of the CONSORT reporting items (37) were included in the tool. RAPID achieved a high average accuracy rate of 92.11% and a content consistency score of 81.14% on the CONSORT dataset. Of the CONSORT-AI reporting items, 11 items related to the intervention of AI tools were included in the tool. RAPID achieved an average accuracy of 83.81% with a content consistency score of 72.51% on the CONSORT-AI dataset. For these two reporting guidelines, a training set of 5 articles was selected from each dataset to refine the prompts used in the tools for CONSORT and CONSORT-AI reporting checklist. The validation set of the remaining articles was used to assess the performance of the RAPID. The RAPID tool used the Word document and Portable Document Format of the articles as input files. A RAPID graphical user interface was built using JavaScript and Vue. Conclusions and RelevanceThe RAPID tool is designed to assist in the reporting of various types of trials. RAPID has strong scalability, which can be easily adapted to different medical reporting guidelines without transfer learning on a large dataset. RAPID may effectively save time and improve working efficiency for different user groups, for example, 1) simplifying the submission process and improving report quality by verifying manuscript completeness for medical authors; 2) facilitating evaluation of report quality for medical researchers; 3) expediting manuscript distribution for medical editors; and 4) identifying reporting deficiencies and providing deeper insights for review comments for reviewers. Key PointsO_ST_ABSQuestionC_ST_ABSCan large language model tools automatically generate medical reporting checklists for manuscripts of different types of clinic trials? FindingsAn automated reporting checklist generation tool using large language models and retrieval augmentation generation technology, RAPID, was developed. RAPID was fully evaluated on all items across two separate datasets related to the Consolidated Standards of Reporting Trials (CONSORT) and CONSORT-AI reporting guidelines. In the first dataset corresponding to CONSORT, RAPID achieved an average accuracy of 92.11%, while in the second dataset associated with CONSORT - AI, it reached an average accuracy of 83.81%. Additionally, RAPID is highly scalable. It can be easily and smoothly adapted to different medical reporting guidelines without transfer learning on a large dataset. MeaningRAPID can effectively save time and improve working efficiency for different user groups such as medical authors, researchers, editors, and reviewers.

bioinformatics↗

bioRxiv2025

Conditional success of adaptive therapy: the role of treatment-pausing thresholds revealed by mathematical modeling

Adaptive therapy improves cancer treatment by controlling the competition between sensitive and resistant cells through treatment holidays. This study highlights the critical role of treatmentholiday thresholds in adaptive therapy for tumors composed of drug-sensitive and resistant cells. Using a Lotka-Volterra model, adaptive therapy outcomes are compared with maximum tolerated dose therapy and intermittent therapy outcomes, showing that adaptive therapy success depends critically on the threshold for pausing and resuming treatment and on competitive interactions between cell populations. Three comparison scenarios between adaptive therapy and other therapies emerge: uniform-decline where adaptive therapy underperforms regardless of threshold, conditional-improve where efficacy requires threshold optimization, and uniform-improve where adaptive therapy consistently outperforms alternatives. Tumor composition including initial burden and resistant cell proportion influences outcomes. Threshold adjustments enable adaptive therapy to suppress resistant subclones while preserving sensitive cells, extending progression-free survival. Crucially, this work establishes an optimal control problem for time-to-progression and mathematically proves that under biological constraints like neutral competition or low initial burden, the theoretically optimal strategy is unrealizable as it requires infinitely many treatment holidays, rendering it clinically impractical. These findings emphasize personalized treatment strategies for enhancing long-term therapeutic outcomes. Mathematics Subject Classification92C50,92C42.

systems biology↗

bioRxiv2025

Pneumo-Typer: a high-throughput capsule genotype visualization tool with integrated serotype and sequence type prediction for Streptococcus pneumoniae

BackgroundStreptococcus pneumoniae persists as a leading global pathogen, with current capsule-based vaccines like PCV13 offering limited coverage against its extensive serotype diversity (>100 serotypes). This restricted coverage drives the emergence of non-vaccine serotypes. Moreover, vaccine efficacy is further compromised by immune evasion caused by capsule genotype (CapT) variations within vaccine-covered serotypes, while existing genome-based tools lack robust analytical capabilities for CapT. ResultsWe developed Pneumo-Typer, a CapT visualization tool enabling rapid identification of CapT variations in S. pneumoniae. Application to 17,407 publicly available genomes from the NCBI database revealed widespread CapT variations across vaccine-covered serotypes, providing critical insights for optimizing vaccine formulations. In addition, Pneumo-Typer integrates high-accuracy serotype prediction (98.44% accuracy across 93 serotypes) and multilocus sequence typing (ST), facilitating comprehensive genomic surveillance. Besides, CapT and ST information can assist in serotype determination. Pneumo-Typer enables integrated analysis of serotype-CapT-ST relationships, demonstrating that while most serotypes associate with multiple STs and CapTs, ST and CapT lineages evolve independently. Strikingly, multi-serotype serogroups exhibited pronounced CapT diversity, suggesting evolutionary processes driving serogroup expansion through CapT plasticity. ConclusionsIn summary, Pneumo-Typer is an integrated platform for genomic surveillance of pneumococcal populations. By resolving previously underexplored serotype-CapT-ST linkages, the tool provides a framework for next-generation vaccine design, emphasizing the need for vaccine formulations that address both serotype replacement and CapT-driven immune evasion.

bioinformatics↗

bioRxiv2025

Machine Learning-Enhanced Extraction of Protein Signatures of Renal Cell Carcinoma from Proteomics Data

In this study, we generated label-free data-independent acquisition (DIA)-based liquid chromatography (LC)-mass spectrometry (MS) proteomics data from 261 renal cell carcinomas (RCC) and 195 normal adjacent tissues (NAT). The RCC tumors included 48 non-clear cell renal cell carcinomas (non-ccRCC) and 213 ccRCC. A total of 219,740 peptides and 11,943 protein groups were identified with 9,787 protein groups per sample on average. We adopted a comprehensive approach to select representative samples with different mutation sites, considering histopathological, immune, methylation, and non-negative matrix factorization (NMF)-based subtypes, along with clinical characteristics (gender, grade, and stage) to capture the complexity and diversity of ccRCC tumors. We used machine learning identified 55 protein signatures that distinguish RCC tumors from NATs. Furthermore, 39 protein signatures that differentiate different RCC tumor subtypes were also identified. Our findings offer an extensive perspective of the proteomic landscape in RCC, illuminating specific proteins that serve to distinguish RCC tumors from NATs and among various RCC tumor subtypes.

cancer biology↗

bioRxiv2025

Tumor suppressor collateral damage screens reveal mRNA homeostasis protein HBS1L as a novel vulnerability in ch9p21 driven FOCAD deleted cancer

Chromosomal deletion of tumor suppressor genes often occurs in an imprecise manner, leading to co-deletion of neighboring genes. This collateral damage can create novel dependencies specific to the co-deleted context. One notable example is the dependency on PRMT5 activity in tumors with MTAP deletion, which co-occurs with CDKN2A/B loss, leading to the development of MTA-cooperative PRMT5 inhibitors. To identify additional collateral damage context/target pairs for chromosome 9p and other common loci of chromosomal deletions, we conducted a combinatorial CRISPR screen knocking out frequently co-deleted genes in combination with a focused target library. We identified the gene encoding the ribosome rescue factor PELO as synthetic lethal with loss of gene encoding the SKI complex interacting protein FOCAD, which is frequently co-deleted alongside MTAP and CDKN2A/B on chromosome 9p. A genome-wide screen in FOCAD isogenic cells further identified the ribosome rescue GTPase and PELO binding partner HBS1L as the top synthetic lethal target for FOCAD loss. Analysis of publicly available data and genetic manipulation of HBS1L using orthogonal modalities validated this interaction. HBS1L dependency in FOCAD-deleted cells was rescued by FOCAD re-expression, and FOCAD intact cells could be rendered HBS1L-dependent by FOCAD knockout, demonstrating the context specificity of this interaction. Mechanistically, HBS1L loss led to translational arrest and activated the unfolded protein response in FOCAD-deleted cells. In vivo, HBS1L deletion eliminated growth of FOCAD-deleted tumors. Here we propose a model where the FOCAD/SKI complex and HBS1L/PELO work together to resolve aberrant mRNA-induced ribosomal stalling, making the HBS1L/PELO complex an intriguing novel target for treating FOCAD-deleted tumors.

cancer biology↗

bioRxiv2025

Developing Foundation Models for Predicting Viral Animal Host Range in Intelligent Surveillance

Emerging human infectious viruses originating from animals continue to pose a persistent threat to global public health. Understanding the host range of animal viruses is crucial for identifying potential spillover pathways and mitigating the risk of future pandemics. Here, we present VirHRanger, a prediction method that integrates foundation models trained on viral genome and protein sequences, alongside genomic and protein compositional traits, viral phylogeny, and protein-protein interactions. To systematically predict the animal host range, VirHRanger incorporates host taxonomy-aware neural networks trained on a comprehensive collection of animal-virus associations spanning mammals, birds, and arthropods. Within a dataset of 4,006 virus species spanning 99 viral families, our model achieved robust performance with a micro-averaged AUROC of 0.938 across all host categories, demonstrating its effectiveness in capturing generalizable host signals from viral genetic data. On a dataset of 315 novel viruses, which are associated with key reservoir animal hosts and insect vectors, VirHRanger notably outperformed the homology-based method, exhibiting a strong generalizability to novel viruses. Furthermore, VirHRanger identified host range variations among closely related viruses within the Coronaviridae family and successfully predicted the ability of SARS-CoV-2 to infect humans and other animal hosts. These findings highlight the potential of VirHRanger to transform sequencing data into timely insights for disease control during the early stages of zoonotic outbreaks.

bioinformatics↗

bioRxiv2025

The Protective Role of Intestinal Alkaline Phosphatase in Inflammatory Bowel Disease-Associated Non-Alcoholic Fatty Liver Disease

BackgroundInflammatory bowel disease (IBD) is a chronic and progressive inflammatory condition characterized by weight loss as a prominent feature. Non-alcoholic fatty liver disease (NAFLD), typically linked to obesity and metabolic dysregulation, is increasingly recognized as being influenced by the gut-liver axis. Notably, IBD patients exhibit a heightened susceptibility to NAFLD, although the underlying mechanisms remain poorly understood. Intestinal alkaline phosphatase (IAP), an endogenous enzyme, plays a critical role in preventing intestinal bacterial translocation. We hypothesized that IAP may serve as a potential therapeutic agent for mitigating IBD-associated NAFLD. MethodsAn IBD model was established using three cycles of 2% dextran sulfate sodium (DSS) administration. Mice were subsequently treated with L-phenylalanine or IAP. The activity of stool IAP, gut microbiota composition, hepatic lipid accumulation, inflammatory markers, and gut microbiome diversity were assessed. ResultsDSS treatment markedly reduced IAP levels. Suppression of IAP significantly increased gut permeability and exacerbated hepatic inflammation and lipid deposition. Conversely, IAP supplementation restored these parameters, improved gut microbial diversity, and normalized microbiota composition. However, IAP failed to ameliorate hepatic inflammation and lipid accumulation in Toll-like receptor 4 (TLR4) knockout mice. ConclusionDeficiency in endogenous IAP contributes to the onset of NAFLD in the context of IBD. Oral IAP supplementation enhances gut barrier integrity, stabilizes gut microbiota, and prevents NAFLD development in IBD through a TLR4-dependent mechanism.

microbiology↗

bioRxiv2025

Decoding semantics from natural speech using human intracranial EEG

Brain-computer interfaces (BCIs) hold promise for restoring natural language production capabilities in patients with speech impairments, potentially enabling smooth conversation that conveys meaningful information via synthesized words. While considerable progress has been made in decoding phonetic features of speech, our ability to extract lexical semantic information (i.e. the meaning of individual words) from neural activity remains largely unexplored. Moreover, most existing BCI research has relied on controlled experimental paradigms rather than natural conversation, limiting our understanding of semantic decoding in ecological contexts. Here, we investigated the feasibility of decoding lexical semantic information from stereo-electroencephalography (sEEG) recordings in 14 participants during spontaneous conversation. Using multivariate pattern analysis, we were able to decode word level semantic features during language production with an average accuracy of 21% across all participants compared to a chance level of 10%. This semantic decoding remained robust across different semantic representations while maintaining specificity to semantic features. Further, we identified a distributed left-lateralized network spanning precentral gyrus, pars triangularis, and middle temporal cortex, with low-frequency oscillations showing stronger contributions. Together, our results establish the feasibility of extracting word meanings from neural activity during natural speech production and demonstrate the potential for decoding semantic content from unconstrained speech.

neuroscience↗

bioRxiv2025

Brucella proline racemase protein A targets Tpl2 to promote IL-10 secretion for establishment of chronic infection

IL-10, an anti-inflammatory cytokine, plays a crucial role in limiting immune responses to pathogens, preventing host damage. However, the mechanisms underlying Brucella-mediated IL- 10 production remain incompletely understood. In this study, we demonstrate that the proline racemase protein A (PrpA) of Brucella melitensis M5-90 induces macrophages to secrete IL-10 by activating the Tpl2-ERK signaling pathway, thereby promoting chronic infection. Moreover, Tpl2 deletion impairs macrophage bactericidal ability, accompanied by reduced TNF- and IL-1{beta} but unaffected IL-10 levels. Additionally, Trp309, Glu103, and Glu129 of PrpA participate in interaction with Tpl2, but these residues do not influence PrpA-mediated IL-10 production in macrophages. PrpA deletion enhances IFN-{gamma} levels, specific anti-Brucella IgG, and CD4+ and CD8+ T cell numbers in mice. Furthermore, the Brucella melitensis M5-90 prpA mutant provides higher protection than the parental strain against virulent Brucella melitensis M28 infection in mice. Our findings suggest that Brucella PrpA promotes IL-10 secretion by macrophages through Tpl2 activation for bacterial survival and persistent infection, making the Brucella melitensis M5-90 prpA mutant a promising vaccine for enhanced protection. Author SummaryIL-10, an anti-inflammatory cytokine, is exploited by Brucella for survival. We identified Brucella PrpA as a potent IL-10 inducer, activating the Tpl2-ERK signaling pathway. Tpl2 deletion increased Brucella survival in macrophages, accompanied by reduced TNF- and IL-1{beta} but unaffected IL-10 secretion. Residues (Trp309, Glu103, and Glu129) of PrpA were crucial for interaction with Tpl2, yet did not impact PrpA-mediated IL-10 production. The B. melitensis M5-90 prpA mutant induced higher anti-Brucella IgG, IFN-{gamma}, and CD4+ and CD8+ T cell numbers in mice, providing better protection than B. melitensis M5-90. These findings unveil PrpAs role in IL-10 production and highlight the potential of the B. melitensis M5-90 prpA mutant as a promising vaccine for further evaluation.

microbiology↗

bioRxiv2025

Age-Dependent Patterns of Gut Bifidobacterium Microbiome Diversity across child Cohorts in a Multi-Ethnic population, Western China

High-throughput sequencing has provided unprecedented opportunities to elucidate the role of human gut microbiota. However, current studies have primarily focused on infant and adult cohorts, leaving biomarkers associated with the development of transitional children unclear, particularly in revealing geographic, multi-ethnic group underrepresented. Here, we analyzed fecal samples from 776 infants and children aged 0 to 15 years with amplicon sequencing of the 16S rRNA and groEL gene, representing multi-ethnic groups from different residential locations in the Yining region of Xinjiang. First, we systematically characterized the gut microbiota Spectrum of children in the Ili region. As age increases, the diversity and functional composition of the microbiota become richer and more stable, with Bifidobacterium consistently dominating the community. Utilizing Bayesian regression models, we identified a cluster of microbiota strongly associated with growth and development in children, which phylogenetically corresponds to Bifidobacterium breve. Finally, we included another similar study in the species-level of Bifidobacterium, and metrics of the age-related effect sizes showed heterogeneity across ethnic groups (Uyghur vs Han: {beta}Deming = 4.40 and Kazakh vs Han: {beta}Deming = 4.33). In conclusion, this study provides novel insights into the developmental trajectories of the gut microbiome in children and its relationship with health. IMPORTANCEThe intestinal microbial markers associated with the development of geographically diverse, multi-ethnic children, particularly those represented by Bifidobacterium species, have been elucidated in this study. Through the application of Bayesian regression models, we identified a microbiome profile closely linked to childhood growth and development, specifically phylogenetically aligned with Bifidobacterium breve. When incorporating a comparable study conducted at the species level of another Bifidobacterium, it was observed that age-related effect sizes varied among different ethnic groups, offering novel insights into the developmental trajectory of childrens gut microbiota and its implications for health.

microbiology↗

bioRxiv2025

Plat safeguards maternally aged oocytes against programmed cell death through activating the Erk1/2 pathway

The decline in oocytes quality and developmental potential with female reproductive aging is well recognized, yet the underlying mechanisms remain insufficiently investigated. In this study, through an integrative analysis of transcriptomes and morphologies of individual oocytes from young and aged mice, morphologically defective aged oocytes are identified with distinct transcriptomic features. Further analysis demonstrates that both apoptotic and ferroptotic pathways are activated in the defective aged oocytes, and simultaneously blocking both pathways reverses the defective morphology to the largest extent. The Plat gene, which encodes tissue-type plasminogen activator (tPA), is downregulated with oocyte aging, and Plat knockdown increases oocytes susceptibility to both apoptosis and ferroptosis. Mechanistically, tPA functions as an upstream signaling molecule for Erk1/2 activation by interacting with particular phosphorylation kinases such as Alk. Consequently, Plat loss downregulates Erk1/2 pathway activity in oocytes, leading to degeneration through programmed cell death. Supplementing exogenous tPA in in vitro oocyte maturation cultures reduces defect rate of aged oocytes, thereby improving oocyte quality and developmental potential. Collectively, Plat plays a pivotal role in protecting aged mouse oocytes from programmed cell death, and tPA supplementation may serve as a potential clinical strategy to enhance oocyte quality in females of advanced maternal age.

developmental biology↗