As the global population ages, the development of methods that can accurately quantify individual aging status and overcome the limitations of chronological age assessment has become an important need in aging research and precision medicine. Biological age serves as an important tool for assessing an individual's true physiological aging process and disease risk by integrating multi-omics data and organ-specific biomarkers. In this review, we systematically summarize the development of methods for assessing aging, with a focus on the construction strategies and evolution of aging clocks based on epigenetic, transcriptomic, proteomic, and metabolomic markers. We also discuss emerging approaches for organ-specific aging assessment based on imaging data and the integration of multi-omics data. By synthesizing evidence for the clinical applications of these approaches in the early screening and risk stratification of aging-related diseases, personalized interventions, and health management, we further highlight the importance and translational potential of biological age in precision aging assessment and intervention.
Vascular development begins with vasculogenesis during early embryogenesis. This process is controlled by a highly integrated, multi-layered molecular network. However, the role of post-transcriptional regulation in this context remains poorly understood. Cytoplasmic poly(A) binding protein 1a (Pabpc1a) is a key RNA-binding protein that regulates gene expression at the post-transcriptional level and participates in many physiological and pathological processes. Its role in vascular development, however, is still unclear. In this study, we first found that pabpc1a is highly expressed in endothelial cells during the critical window of vasculogenesis. We then generated a pabpc1a knockout model using CRISPR/Cas9. Functional analyses showed that loss of pabpc1a disrupted the expression of genes involved in arterial-venous specification and altered the arterial-to-venous diameter ratio. In contrast, overexpression of pabpc1a effectively rescued the vascular defects. Mechanistically, transcriptomic analysis revealed widespread gene expression changes in endothelial cells lacking pabpc1a. Pathways related to translation, ribosome biogenesis, and energy metabolism were significantly downregulated. These findings suggest that Pabpc1a regulates vasculogenesis by coordinating protein synthesis and metabolic homeostasis. In summary, our study demonstrates Pabpc1a as an essential post-transcriptional regulator during vasculogenesis and provides new insight into the regulatory network governing vascular development.
As the largest agricultural producer in the European Union, France has established a mature and systematic livestock and poultry genetic resources management system. Based on comprehensive domestic legislation and effectively aligned with EU regulations, this system forms a governance structure characterized by clear responsibilities and multi-stakeholder collaboration. National regulatory authorities, public research institutions, industry organizations, and breeding service institutions work in a coordinated manner, with close linkages among the government, research community, and industry to ensure the conservation, dynamic monitoring, and sustainable utilization of genetic resources. For different livestock and poultry species such as ruminants, pigs, and poultry, France has developed differentiated genetic improvement pathways, supported by quality assurance and lifetime animal traceability mechanisms. This paper puts forward targeted suggestions for the conservation of livestock and poultry genetic resources in China, focusing on key areas such as forming a multi-stakeholder collaborative governance pattern, improving conservation mechanisms, promoting the layout of genetic improvement adapted to different livestock and poultry species, and ensuring quality traceability.
Suicide is defined as an intentional act of ending one's own life. Suicide attempt (SA) is a significant risk factor for suicide death. Research on SA has progressed from socio-psychological perspectives to the molecular and genetic levels. While the biological mechanisms underlying genome-wide association studies (GWAS) identified risk loci remain largely unclear. To investigate the potential risk mechanisms, we constructed a systematic analytic pipeline using brain protein quantitative trait locus (pQTL) datasets (Banner, N=152; ROSMAP, N=376), a brain expression quantitative trait locus (eQTL) datasets (N=452), and SA GWAS summary statistics (Ncase=35,786, Ncontrol=779,392). We performed proteome-wide association study (PWAS), Mendelian randomization (MR), Bayesian colocalization analysis, transcriptome-wide association study (TWAS), and multi-marker analysis of genomic annotation (MAGMA) to systematically identify and screen for novel genetically supported candidate proteins related to the biological mechanism of SA in the brain. For functional annotation, we used the GeneMANIA to bulid a functional prediction network integrating co-expression, physical interactions, and pathway colocalization to identify core proteins. PWAS identified three brain proteins whose genetically predicted abundance was significantly associated with SA. Among them, GMPPB was prioritized as putative causal protein, supported by MR analysis (false discovery rate, FDR<0.05) and Bayesian colocalization analysis (posterior probability PPH4≥0.8). Specifically, higher genetically predicted GMPPB protein levels were associated with increased risk of SA. Although our analyses primarily relied on datasets from European-ancestry populations, the shared genetic architecture across populations and the generalizability of genome-wide data analytical approaches suggest that our findings may still provide useful insights into the biological mechanisms underlying SA and help inform the development of intervention strategies and genetic counseling in Chinese populations.
The Han Chinese population exhibits a complex genetic structure characterized by subtle yet discernible regional differentiation. Elucidating this fine-scale population structure and developing robust models for biogeographical ancestry inference are of great significance for revealing population evolutionary patterns and achieving precise ancestry inference. However, ancestry inference models specifically tailored to the genetic diversity within the domestic Han Chinese population remain scarce. In this study, we analyzed high-density SNP data from 1,229 Han Chinese individuals across eight provinces to investigate the correlation between genetic variation and geographic distribution, and to construct a machine learning-based model for regional ancestry prediction. After stringent quality control (including linkage disequilibrium pruning), we retained 208,193 SNPs for downstream analysis. Principal component analysis (PCA) and ADMIXTURE clustering revealed measurable genetic stratification corresponding to geography, supporting the delineation of seven distinct genetic clusters within the Han population. Leveraging the top principal components as features, we trained and compared multiple classifiers-XGBoost, random forest, and K-nearest neighbors-via five-fold cross-validation on the reference set, with model performance evaluated using both top-rank prediction accuracy and likelihood ratio (LR)-based metrics. The results showed that the PCA-XGBoost model achieved the optimal prediction performance in the reference set, with a first-rank prediction accuracy of 87.66% and an LR-based accuracy of 96.87%. In independent test sets, the PCA-XGBoost model maintained strong performance (first-rank prediction accuracy >85%; LR-based accuracy >95%), demonstrating excellent generalizability and stability. In summary, the PCA-XGBoost predictive model developed in this study demonstrates high efficiency, robustness, and accuracy, offering a reliable methodological tool for research in population genetics and forensic genetics.
In the new era, the teaching of Medical Genetics requires medical students to not only master solid knowledge, but also possess practical abilities in diagnosing and treating clinical genetic diseases. This paper systematically elaborates on the design and practical exploration of teaching reform in the Medical Genetics course under the Outcome-Based Education (OBE) concept. By constructing a structured teaching system closely aligned with clinical practice, building a teaching model centered on clinical cases, carrying out diverse teaching activities, developing a "boundless classroom", and establishing a multi-dimensional assessment system, we have achieved a deep integration of knowledge transmission and clinical reasoning training. The teaching effectiveness has shown that this model significantly enhances students' case analysis abilities, learning motivation, and innovative capacity. However, the implementation process has also revealed deep-seated challenges in the practical teaching component, such as students facing difficulties in getting started, employing unsystematic methods, producing superficial results, and the imperfection of the evaluation mechanism. Drawing on exemplary domestic teaching cases, this paper proposes that future efforts must synergize two dimensions: "resource support" and "pedagogical design". This involves constructing a tiered, progressive practical ability training chain, improving the faculty development support system, and exploring the use of artificial intelligence to establish process-oriented data platforms and diversified evaluation mechanisms. By putting the OBE concept into practice, we aim to promote a deep transformation of the Medical Genetics course from "knowledge transmission" to "competency development", thereby laying a solid foundation for cultivating outstanding medical talent capable of meeting future medical demands.
Transposons, also known as jumping genes, are DNA sequences capable of relocating within or between chromosomes. Long interspersed element-1 (LINE-1), the only autonomously active retrotransposon in the human genome, plays a critical role in maintaining genomic stability through its dynamic regulation. Under normal physiological conditions, the host employs epigenetic and other mechanisms to maintain LINE-1 in a silenced state. However, when this precise regulatory control is disrupted, aberrant LINE-1 activation can lead to insertional mutations, resulting in genomic instability and the development of various genetic disorders and malignant tumors. Recent evidence has demonstrated elevated LINE-1 expression in multiple cancers, such as breast, esophageal, lung, and colorectal cancer, suggesting a close association between LINE-1 dysregulation and tumorigenesis. This review summarizes the multi-layered regulatory network governing LINE-1, encompassing epigenetic modifications, non-coding RNAs, and various host restriction factors. It also explores the molecular mechanisms underlying LINE-1 aberrant activation in the tumor microenvironment and outlines the diverse pathways through which LINE-1 influences tumor development, such as compromising genomic stability, triggering inflammation and immune responses, and participating in cellular immortalization. This review not only provides a theoretical foundation for utilizing LINE-1 as a molecular biomarker in cancer diagnosis but also offers new perspectives for developing novel anti-tumor therapeutic strategies based on LINE-1 regulation.
In recent years, multiple panels containing varying numbers of single nucleotide polymorphisms (SNPs) have been reported in forensic genetics for kinship inference. However, systematic exploration of the impact of SNP number on inference performance and the application of machine learning algorithms remains lacking. Therefore, we evaluated the impact of SNP number on kinship inference performance and the optimization effects of machine learning methods on the identity-by-state (IBS) algorithm. We constructed multiple SNP panels with SNP numbers ranging from 15,476 to 20,838, and evaluated the performance of the likelihood ratio (LR) method and the IBS algorithm for kinship inference under different SNP numbers based on simulated pedigrees. After selecting the optimal SNP panel, we validated it using real pedigrees and further combined the IBS algorithm with machine learning methods to enhance inference performance. Our results showed that for the LR method, the sensitivity in inferring sixth and seventh degree kinships exhibited a significant positive correlation with SNP number. For the IBS algorithm, although the sensitivity in inferring fourth to seventh degree kinships showed a significant positive correlation with SNP number, the actual improvement was limited (only 0.5%~2.2% increase). Based on these results, we determined the optimal panel containing 20,838 SNPs (21K panel). The 21K panel based on the LR method could accurately infer kinships within sixth degree (with a sensitivity of 93.65% for sixth degree kinship inference), and the 21K panel based on the IBS algorithm could accurately infer kinships within third degree (with a sensitivity of 86.79% for third degree kinship inference). After combining the IBS algorithm with machine learning, the sensitivity for fourth degree kinship inference improved from 69.10% to 87.66%, the sensitivities for fifth and sixth degree kinships improved from 38.03% and 21.41% to 48.75% and 37.80%, respectively.
Ecdysone signaling is necessary for maintaining intestinal homeostasis in adult Drosophila melanogaster by promoting stem cell proliferation and differentiation. However, the role of its downstream target broad (br) in this process remains largely unclear. Here, this study demonstrates that br is required for the maintenance of intestinal stem cells (ISCs) and intestinal injury repair. Clonal analysis shows that br regulates both the proliferation and differentiation of ISCs. Knockdown of br severely impairs the differentiation of stem cells into enterocytes (ECs), whereas overexpression of br promotes ECs differentiation. Further analysis reveals that br knockdown reduces Jak/STAT signaling activity in ISCs. Moreover, upregulating the activity of Jak/STAT or EGFR signaling significantly rescues the br knockdown phenotype. These results suggest that br may regulate the proliferation and differentiation of ISCs through Jak/STAT and EGFR signaling in adult Drosophila. This study highlights the critical role of br in adult Drosophila ISCs and provides a preliminary exploration of its underlying mechanism.
Digital sequence information on genetic resources plays an increasingly vital role in research on improving crop yields and reducing impacts of disease. However, there are still problems such as the imperfect rights' protection system, which hinders the protection and sustainable use of genetic resources and constrains the realization of the fair and equitable benefit-sharing objectives established by the Convention on Biological Diversity. To address these issues, we first define the connotation and legal nature of digital sequence information on genetic resources. Then, we elaborate how digital sequence information on genetic resources aligns with the modern intellectual property systems. For digital sequence information on genetic resources to be protected by intellectual property rights, we analyze the substantive conditions of novelty and practicality as well as the procedural conditions of registration. Building on this analysis, we identify the limitations of existing intellectual property frameworks in accommodating digital sequence information on genetic resources, and propose a normative structure of sui generis right of digital sequence information on genetic resources. The subjects of sui generis right are divided into two levels, i.e. static right attributed to the state, and dynamic right exercised by the farmer collective of specific communities and the uploaders of digital sequence information, exercising respectively in accordance with different functions. The contents of sui generis right include the informed consent right, the source indication right and benefit-sharing right based on licensing. Furthermore, we propose to establish the limitations on sui generis right, such as restriction on scope of application, compulsory licensing and protection periods. This framework established here is of great significance for achieving the balance of rights and interests, promoting innovation in plant breeding and protecting genetic diversity.
To enhance the competency of clinical medicine students in evaluating the severity of genetic disorders, this study first modularized an assessment of genetic diseases severity based on the World Health Organization's International Classification of Functioning, Disability and Health (ICF) framework. Then, this modular teaching framework was applied in teaching instruction. During the Medical Genetics course, the 2024 clinical medicine cohort at Hunan University of Medicine were clustered into a experimental group (6 classes, 203 students) and a control group (7 classes, 235 students) randomly. The experimental group engaged in the ICF-based module in the case analysis of genetic diseases, while students in the control group followed the traditional teaching methods. Learning outcomes were evaluated by analyzing the student-written genetic disease severity evaluation reports. Results demonstrated that students in the experimental group achieved significantly higher scores on their assessment reports (73.33±7.16) compared to the control group (64.79±5.45), with a statistically significant difference (t=13.87, P<0.001). Furthermore, textual analysis further revealed that reports from the experimental group contained a significantly higher frequency of keywords related to patient psychology, social functioning, and environmental factors, indicating a broader focus on the patients and more comprehensive and in-depth understanding of the patient's situation. These findings suggest that the ICF-based modular teaching framework significantly improves medical students' ability to conduct individualized assessments of genetic diseases and effectively fosters their humanistic care. This study provides an actionable and scalable teaching practice pathway for cultivating clinical genetic counseling professionals.
China's soybean supply is heavily dependent on international markets, making it an urgent task to enhance domestic self-sufficiency to ensure food security. Data from the national soil census indicate that China possesses approximately 500 million mu of saline-alkali soil resources, of which about 200 million mu have potential for agricultural development. Against the backdrop of tight arable land resources, developing new soybean varieties tolerant to saline-alkali conditions represents a strategic initiative to effectively utilize saline-alkali land, expand cultivation areas, and address the challenge of soil salinization. Rapid alkalinization factors (RALFs) are a class of plant small peptides that act as ligands, initiating downstream signaling by binding to plasma membrane receptor complexes, thereby coordinating plant growth, development, and stress responses. However, the specific molecular mechanisms by which RALF peptides mediate responses to saline-alkali stress in important crops such as soybean remain unclear. Through expression profiling analysis of the soybean RALF family, combined with transcriptome data under alkaline salt treatment, this study identified two homologs of Arabidopsis thaliana AtRALF34, designated GmRALF34a and GmRALF34b, which are predominantly expressed in roots and whose expression is significantly suppressed following alkaline salt treatment. Using gene editing technology, we generated Gmralf34ab double mutants, which exhibited enhanced sensitivity to alkaline salt stress. In contrast, no significant differences were observed between the mutant and wild type plants under neutral salt stress. Field phenotypic characterization further demonstrated that the mutants showed significant reductions in agronomic traits, including plant height, node number, and yield per plant. In conclusion, this study preliminarily reveals that GmRALF34s play an important role in soybean response to alkaline salt stress and adaptation to saline-alkaline environments, provides valuable genetic materials for further elucidating their molecular mechanisms and establishing a theoretical and material foundation for breeding salt-alkali tolerant soybean varieties.
Myoclonus-dystonia syndrome (MDS) is a movement disorder syndrome characterized primarily by myoclonus as the core feature. In this study, we reported a case of MDS with myoclonus as the prominent feature, which was accompanied by learning disability and special face. We then used copy number variation sequencing (CNV-seq), whole exome sequencing (WES) and Sanger sequencing to verify the MDS related genes of the patient and his family members. We found that the patient carried a heterozygous mutation of SGCE gene c.731dup (p.Asn244Lysfs*6) related to MDS, which inherited from his father. It was the first reported new mutation at home and abroad. And we confirmed via prenatal diagnosis that his fetus also had a heterozygous mutation of SGCE gene c.731dup (p.Asn244Lysfs*6). In addition, we also found that there was a 1.40 Mb repeat fragment at p23.1 on chromosome 8 of the patient, which partially overlapped with 8p23.1 repeat syndrome. It is speculated that it may be related to the learning disability and special facial phenotype of the patient, and it was a de novo variant. This study not only clarified the etiology of the patient's myoclonus, but also enriched the genetic variation database of SGCE gene by the newly discovered heterozygous heterozygous site of c.731dup (p.Asn244Lysfs*6) of SGCE gene, which was helpful to improve the clinician's awareness of diagnosis of MDS and provide guidance for the patient's fertility.
Pathogenic germline variants in TP53 constitute the central etiological driver of hereditary tumor predisposition disorders syndromes. The oncogenic mechanisms of hotspot mutations in the DNA-binding domain of p53 are well-established. However, the functional consequences of non-hotspot missense mutations remain incompletely understood. In this study, we characterized the molecular pathogenesis and clinical significance of the p53 non-hotspot mutation p.Arg267Trp (p.R267W). In addition, evolutionary conservation analysis, structural prediction, and functional assays including CCK-8 cell proliferation, clonogenic assay, Transwell migration, wound healing assay, qPCR, Western blot, single luciferase reporter assay, and flow cytometry techniques were performed to assess the impact of R267W on TP53 target gene (CDKN1A) regulation and tumor-suppressive phenotypes (proliferation, colony formation, migration) in non-small cell lung cancer models (A549/NCI-H1299). Experiments confirmed that the mutant does not affect the p53 protein stability. The impairment of protein function is hypothesized to result from the disruption of the DNA-binding domain conformation. Experimental evidence suggested that the mutant TP53 exhibited significantly reduced transcriptional activity (P<0.001), resulting in a concomitant reduction in CDKN1A mRNA expression and diminished cell cycle arrest capability when compared to wild type. At the tumor-suppressive functional level, the R267W mutant significantly reduced inhibition rates of non-small cell lung cancer cell proliferation, colony formation, and migration relative to wild type (P<0.05). This study reveals that the R267W variant drives cell cycle dysregulation and malignant phenotypes in lung cancer by disrupting TP53's transcriptional functions. These findings establish a molecular basis for the pathogenic classification of TP53 variants of uncertain clinical significance.
Single nucleotide variations (SNVs) represent the most common form of pathogenic mutations in humans, while base editing technology offers an ideal solution for treating such pathogenic variants. RNA editing has become a hotspot in current gene therapy due to its reversible action, which avoids long-term risks by not permanently altering the genome, and the compact size of the editors. Among these, the mini-dCas13X.1-mediated RNA adenine base editing (mxABE) system demonstrates highly efficient RNA base editing; however, it still suffers from non-target nucleotide editing caused by the bystander editing effect, which constitutes a major off-target risk. In this study, by deleting the nucleotide opposite the non-target adenosine in the sgRNA sequence, we effectively reduced the bystander editing effect of the mxABE system. In vitro results showed that this strategy successfully controlled the bystander editing rate below 5% while maintaining highly efficient on-target editing of approximately 70%. In a murine model of DMD (Duchenne muscular dystrophy), a single administration of AAV (adeno-associated virus)-delivered mxABE system demonstrated significant therapeutic efficacy in the tibialis anterior muscle, with successful elimination of off-target adenosine bystander editing. This study provides a novel precision-targeting strategy for treating monogenic genetic diseases using the mxABE RNA editing system.
Shimao site located at the pastoral-agricultural transition zone of northern Shaanxi, China, with its massive fortification systems and rich sacrificial remains, exemplifies the social complexity of an early state society. However, the origins of its population, social structure, and interactions with neighboring cultures have long been subjects of academic debate. To address these questions, a research team led by Qiaomei Fu from the Institute of Vertebrate Paleontology and Paleoanthropology of the Chinese Academy of Sciences, in collaboration with the Shaanxi Provincial Academy of Archaeology and other institutions, conducted a 13-year systematic study. They performed large-scale, systematic paleogenomic analyses on 169 ancient human skeletal remains from the core Shimao site, its peripheral settlements, and the southern Shanxi region. Breakthroughs were achieved in three key aspects. The study confirmed that the genetic composition of the Shimao population derived mainly from local Late Yangshao populations in northern Shaanxi, demonstrating genetic continuity with earlier local inhabitants. It also revealed close genetic affinities between the Shimao and Taosi populations in southern Shanxi, as well as significant genetic connections with steppe pastoralists associated with the Yumin culture and southern rice-farming communities. Most importantly, the study firstly and successfully reconstructed a four-generation family pedigree within the Shimao site, indicating that Shimao society was patrilineal and highly stratified. This study not only provides an unprecedented model for understanding the formation of early states in China but also offers direct genetic evidence for exploring power inheritance and social stratification in early East Asian states.
The health effects of red and white meat have been debated for decades, and the conventional species-based binary classification fails to capture their nutritional heterogeneity and differential disease risks. This review reconstructs the meat-health evaluation paradigm by integrating multidisciplinary evidence from epidemiology, molecular biology, and food science. Current findings demonstrate that traditional definitions overlook intra-species variation and inter-species paradoxes, underscoring the need to classify meat more precisely by anatomical cut and processing method. Processed meat, recognized as a Group 1 carcinogen, presents fundamentally distinct hazards from unprocessed red meat; moderate consumption of the latter may allow a reasonable balance between essential nutrients such as heme iron and vitamin B12 and associated pathophysiological risks. Mechanistically, the adverse effects of red meat are driven by a convergent network involving heme iron, N-glycolylneuraminic acid (Neu5Gc), trimethylamine-N-oxide (TMAO), and processing-derived toxicants including N-nitroso compounds (NOCs), heterocyclic amines (HCAs), and polycyclic aromatic hydrocarbons (PAHs). In contrast, white meat generally lacks these key toxic components and is enriched in omega-3 polyunsaturated fatty acids (PUFAs) such as EPA and DHA, which provide cardioprotective and neuroprotective benefits, although excessive high-temperature cooking may diminish these advantages. Correspondingly, international dietary guidelines are converging toward the principle of "strictly restrict processed meat, limit unprocessed red meat, and prioritize white meat". Emerging precision strategies include genetic risk stratification, probiotic and dietary fiber interventions targeting the gut microbiota-TMAO axis, and low-temperature/clean-label processing technologies. Future directions should leverage single-cell and spatial multi-omics to elucidate organ-specific toxicity, build tripartite gene-microbiota-nutrient interaction models to enable individualized risk prediction, and apply CRISPR-based breeding to improve the nutritional-toxicological profile of red meat, while integrating AI-driven personalized dietary guidance. Collectively, these advancements will drive meat consumption toward a more nutritionally optimized, health-protective, and environmentally sustainable paradigm.
Gene-targeted knock-in technology serves as a cornerstone tool in genetic engineering and gene therapy, designed to circumvent the unpredictability and heterogeneityassociated with conventional random integration methods. However, its practical application has long been constrained by off-target activity and low efficiency during the editing process. Recent advances in site-specific recombinase systems (e.g., Bxb1 integrase) and programmable nuclease systems (e.g., CRISPR/Cas9) have significantly enhanced the precision and efficiency of gene knock-in. Notably, the Cas9-Bxb1 integrase system enables targeted integration of large DNA fragments (5-43 kb) into genomic safe harbor (GSH) sites, offering a transformative platform for disease modeling, functional genomics, and clinical therapeutics. This review systematically summarizes the progress of site-specific recombinase and nuclease systems, discusses GSH screening strategies and the role of multi-omics data in optimizing predictive models, and compares the strengths and limitations of twinPE+Bxb1 and PASTE systems. Future research should focus on developing novel integrases with low off-target activity, refining DSB-free editing technologies, and establishing cross-species GSH databases to advance applications in precision medicine and synthetic biology.
Microglial phagocytosis is crucial for maintaining central nervous system (CNS) homeostasis, a process that depends on normal lysosomal acidification and is precisely regulated by vacuolar-type ATPase (V-ATPase). While mutations in the V-ATPase a3 subunit (encoded by the tcirg1b gene in zebrafish) are a major cause of human malignant osteopetrosis, the subunit's function in the CNS remains unknown. To investigate the role of the V-ATPase a3 subunit in the zebrafish CNS, we generated a tcirg1b knockout model. Although mutant zebrafish displayed no early neuronal defects, adult brains exhibited significant pathological alterations and behavioral abnormalities. Previous data showed that loss of tcirg1b resulted in enlarged microglia, suggesting potential functional alterations. In this study, transcriptome sequencing analysis of zebrafish macrophages revealed that phagosome formation and intracellular pH regulation pathway genes were significantly down-regulated. Functional analysis confirmed that V-ATPase a3 subunit deficiency impairs lysosomal acidification and digestive function in microglia, leading to the accumulation of apoptotic cell debris and TMR-dextran. Notably, specific restoration of tcirg1b expression in microglia successfully rescued the behavioral phenotypes of mutants, suggesting that the regulation of CNS homeostasis by the V-ATPase a3 subunit is primarily mediated through microglia. In summary, this study provides the first in vivo evidence that tcirg1b deficiency disrupts microglial function, thereby indirectly leading to an imbalance in CNS homeostasis. Our findings reveal a key role for the V-ATPase a3 subunit in regulating neural homeostasis and offer a new theoretical framework for studying the mechanisms of neurological diseases.
Escherichia coli is a facultative anaerobic bacterium frequently detected rate in the intestines of giant pandas. In this study, we isolated 169 anaerobic bacterial strains from fresh fecal samples of 13 giant pandas, including 13 strains of E. coli. Through whole-genome sequencing and analysis, we classified 13 E. coli strains into 9 distinct sequence types (STs), and identified 96 antibiotic resistance genes, 103 heavy metal resistance genes and 213 virulence genes. Notably, we observed the widespread presence of the mdtA, mdtB, mdtC and cusA, cusB, cusC, cusF gene in all E. coli isolates. Further genetic environment analysis revealed the presence of baeS/baeR upstream of mdtABC, a two-component system capable of regulating efflux pump expression to mediate resistance. The cusABCF operon was flanked by siderophore-related virulence genes (fepA and entD) upstream and the cusS/cusR regulatory system downstream. We also identified mobile genetic elements adjacent to these operons, which may facilitate the horizontal transfer of resistance and virulence determinants. This genome-based investigation systematically characterized antibiotic/metal resistance and virulence profiles in E. coli strains derived from giant panda, providing critical insights for safeguarding the health and welfare of this endangered species.
