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Biomedical subjects

Fei Liu

Publications and source records attributed to Fei Liu.

9 recordsLinked to original sources

ARR1 and ARR12 negatively regulate arsenic stress tolerance by controlling flavonoid metabolism in Arabidopsis.

ARR1/12-mediated cytokinin signaling negatively regulates the accumulation of glycosylated flavonoids, thereby increasing plant susceptibility to As(III) stress. Cytokinins negatively regulate arsenic stress tolerance in plants through cytokinin-signaling type-B Arabidopsis response regulators (B-ARRs), specifically ARR1 and ARR12. However, the mechanism by which cytokinin signaling regulates plant metabolite dynamics, particularly antioxidant flavonoids, in response to arsenic toxicity remains largely unknown. Here, we hypothesized that ARR1/12-mediated cytokinin signaling modulates flavonoid metabolism to regulate arsenite [As(III)] tolerance. By comparing the global metabolic changes in roots of the arr1 12 double mutant (rD) and wild-type (WT) plants, we found that As(III) stress globally reduced metabolite abundance in WT roots. Importantly, the rD mutant accumulated significantly more flavonoids, most in glycosylated forms, than WT under As(III) exposure, which was supported by the specific upregulation of UDP-glycosyltransferase genes involved in flavonoid glycosylation. Accordingly, exogenous application of the glycosylated quercitrin-enhanced As(III) tolerance in WT roots, strengthening that the increase of glycosylated flavonoids in rD roots was beneficial for plant survival under As(III) exposure. Our data collectively strongly support that the increased glycosylation of flavonoids in the rD mutant improves their antioxidant functionality, thereby enhancing the As(III) stress tolerance. This study provides a new insight into the negative role of cytokinin signaling in repressing glycosylated flavonoid accumulation, causing increased susceptibility of plants to As(III) stress. Manipulation of cytokinin signaling or flavonoid glycosylation is, therefore, a promising approach for heavy metal stress mitigation in crops.

Arabidopsis

Farming reshapes the gut resistome, virulome, and mobilome of Cervidae.

The rapid expansion of cervid farming raises concerns about antimicrobial resistance (AMR) dissemination, yet its impact on the Cervidae gut microbiome remains poorly characterized. We integrated 89 newly sequenced fecal metagenomes with 599 publicly available datasets, comprising 285 metagenomes from farmed cervids and 370 from wild cervids, to construct a catalog of 15,494 non-redundant metagenome-assembled genomes (MAGs) representing 2,401 species. Our analysis demonstrates that farming profoundly reshapes the gut microbiome's functional composition. Specifically, farmed cervids exhibited significantly higher relative abundance, diversity, and heterogeneity of antimicrobial resistance genes (ARGs) compared to wild counterparts. We observed a robust synergistic relationship between ARGs, virulence factor genes, and mobile genetic element (MGE)-associated genes, identifying 70 ARG-MGE combinations as evidence of potential horizontal gene transfer. Plasmid profiling further suggested that a subset of ARGs may be associated with conjugative plasmids, with plasmid-associated ARGs being significantly more abundant in farmed than in wild cervids. Virome analyses indicated that bacteriophages, particularly Siphoviridae, may serve as mobile reservoirs for ARGs. Notably, Cervidae shared 268 ARG types with humans, including 23 high-risk genes associated with resistance to clinically important antibiotics (e.g. tetX1, vanRD, and bla-CTX-M-178), with Escherichia coli as a key cross-host carrier. These findings highlight that human-impacted cervid gut microbiomes are significant environmental reservoirs of clinically relevant AMR, underscoring the necessity for enhanced antibiotic stewardship and resistance surveillance in managed wildlife within a One Health framework.

Animals

Genome-resolved analysis of colonization factor repertoires reveals ecological stratification in cervid gut microbiomes.

INTRODUCTION: Colonization factors (CFs) are important microbial traits associated with persistence and host adaptation in the gut, yet their large-scale organization in cervid gut microbiomes remains unclear. METHODS: A total of 3,311 non-redundant high-quality metagenome-assembled genomes (MAGs), derived from 688 cervid gut metagenomic samples across 15 publicly available projects and one in-house dataset, were analyzed. CF-associated genes were identified by comparison against the GHA CF database, and CF repertoires were characterized at genome, host-species, and gastrointestinal-segment levels. RESULTS: A total of 138,729 CF-associated genes spanning 71 CF families were identified. MAGs from Cervinae contained richer CF repertoires than those from Caprinae, and CF47 (Peptidase_C69), CF24_29 (QueH), and CF18 (Glycos_transf_2) were among the most prevalent families. CF repertoires were strongly structured by taxonomy, showed a moderate association with bacterial phylogenetic distance, and formed two recurrent genome-level configurations with distinct KEGG functional profiles. Integration of sample metadata further revealed differentiation of CF repertoires across host species and gastrointestinal segments, representing the major ecological dimensions examined in this study. Segment-associated CF variation was accompanied by redistribution of broader functional profiles, including enrichment of carbohydrate and lipid metabolism in the jejunum, membrane transport in the ileum, xenobiotics biodegradation in the cecum, and environmental adaptation in the rumen. DISCUSSION: These findings provide a genome-resolved view of CF repertoire organization in cervid gut microbiomes and demonstrate that colonization-associated functions are structured across microbial lineages and ecological contexts. This study highlights the importance of considering microbial taxonomy and host-associated environments when interpreting the distribution of CF repertoires in mammalian gut ecosystems.

Cervidae

Advancing cancer detection and treatment using longitudinal routine clinical data.

Cancer management remains fragmented across its continuum, from late-stage diagnosis and salvage therapies to non-personalized surveillance. Here, we present Oncoformer, a unified multimodal transformer model trained on the China Oncology Multimodal Prediction and Surveillance Study (COMPASS) cohort (3.67 million individuals, 17.7 million clinical visits) and validated on independent external cohorts, including the UK Biobank. Oncoformer integrates longitudinal electronic health records with chest X-ray imaging to address multiple clinical tasks: pan-cancer diagnosis (area under the receiver operating characteristic curve [AUROC] = 0.956), future cancer prediction up to 1 year before diagnosis (AUROC = 0.869), tumor stage inference (mean AUROC > 0.90), patient-specific treatment-response forecasting, and recurrence-free survival stratification across ten cancer types (all p < 0.01). Staging predictions were independently validated against postoperative pathological endpoints and shown to converge on core cancer genomic pathways. By translating routine clinical data into a dynamic view of cancer evolution, Oncoformer provides a framework for risk-informed cancer prediction and treatment stratification using routine clinical data.

Humans

Efficacy and safety of microwave ablation for the treatment of pulmonary osteosarcoma oligometastases.

PURPOSE: Evaluate efficacy and safety of microwave ablation (MWA) for pulmonary osteosarcoma oligometastases. METHODS: Twenty-two patients (median age, 16&#x2009;years [range, 9-41&#x2009;years]; 15 male) with pulmonary osteosarcoma oligometastases who underwent MWA from January 2018 to December 2023 were included, with 27 MWA sessions for 36 lung metastases. Technical success and complications were evaluated in all 22 patients, while efficacy and survival were evaluated in 19 patients with 24 MWA sessions in treatment of 32 tumors. Technical success was assessed for each tumor. Local tumor control, progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan-Meier method. Complications were classified using Common Terminology Criteria for Adverse Events version 5.0. RESULTS: Technical success was achieved in all 36 tumors (100.0%). Local tumor progression occurred in five of 32 tumors (15.6%). The estimated local tumor control rates at 12, 24 and 36&#x2009;months were 96.9%, 86.1% and 81.5%, respectively. No significant difference in local control was found between tumors &#x2264; 10&#x2009;mm and > 10&#x2009;mm (p&#x2009;=&#x2009;.470). Twelve of 19 patients (63.2%) developed new lung metastases outside the ablation area, including one with concurrent newly developed bone metastases and one with recurrence of primary osteosarcoma. The median PFS was 21.5&#x2009;months. The estimated OS rates at 12, 24 and 60&#x2009;months were 100.0%, 94.4% and 94.4%, respectively. Major complications occurred in five of 27 sessions (18.5%). CONCLUSIONS: MWA preliminarily demonstrates a high technical success rate, notable local tumor control, promising overall survival and acceptable safety for pulmonary osteosarcoma oligometastases.

Adolescent

Dual genetic loci and flavonoid metabolism orchestrate fruiting body coloration in Flammulina filiformis: a multi-omic roadmap for fungal pigmentation.

BACKGROUND: The fruiting bodies of macrofungi exhibit diverse coloration, traditionally attributed to melanin and carotenoid biosynthesis. This study is the first to reveal that flavonoids, rather than these classical pigments, are the predominant contributors to yellow pigmentation in the Flammulina filiformis. OBJECTIVE: To uncover the genetic basis and key regulatory genes involved in pigment formation in F. filiformis fruiting bodies, and to establish a model framework for studying color genetics in macrofungi. METHODS: Metabolomic profiling was conducted on yellow and white F. filiformis fruiting bodies to identify key pigment components. A segregating population was constructed, followed by integrated multi-omics analyses-including bulk segregant analysis (BSA), genome-wide association study (GWAS), and transcriptomics-to map regulatory loci and candidate genes. Functional roles were validated via genetic transformation and protein structural modeling. RESULTS: Flavonoid accumulation was identified as the biochemical hallmark of pigmented fruiting bodies. Genetic analysis revealed a dual regulatory mechanism: a qualitative locus governing pigmentation presence and a quantitative trait determining color intensity. Combined BSA and GWAS pinpointed a major locus, Ffcrs, within a recombination-suppressed region. Transcriptomic analysis identified two key regulators, Ffakr (a transcriptional activator) and Ffpal (encoding phenylalanine ammonia-lyase). Functional verification via transformation, structural modeling, and metabolite profiling in transgenic lines confirmed their essential roles in flavonoid biosynthesis and pigmentation. CONCLUSION: This study uncovers a flavonoid-based pigmentation mechanism in F. filiformis and elucidates a complex genetic architecture shaped by both qualitative and quantitative loci, providing a new paradigm for understanding pigment formation in macrofungi. The identified regulatory factors establish a molecular foundation for the precise manipulation of economically important pigmentation traits in edible mushroom.

Flavonoids

Genomic-based revelation of genetic structure and adaptive characterization of Schizopygopsis malacanthus in the Jinsha River and Yalong River.

BACKGROUND: As a highly specialized class of schizothoracine fishes, Schizopygopsis malacanthus has attracted much attention due to its widespread distribution. To investigate the impact of the Qinghai&#x2012;Tibet movement on S. malacanthus, we analyzed the genetic evolutionary history of this species. RESULTS: These results showed that there was a high level of genetic differentiation between Jinsha River (JSR) populations and Yalong River (YLR) populations. The genetic diversity of intra-YLR populations was higher than that of the intra-JSR populations. There was gene exchange of the Suwalong population to the Huoqu and Ganzi populations. Furthermore, both of the JSR and YLR populations exhibited a gradual increase in the genetic differentiation index from low to high altitudes, and the effective population of high-elevation populations has gradually expanded. In high-altitude populations, the selected genes were enriched in DNA repair, light transduction, and energy metabolism, reflecting the genetic basis for their migration to higher altitudes. CONCLUSIONS: S. malacanthus populations had the higher genetic differentiation and genetic diversity in the JSR and its main tributary YLR. Therefore, we should preserve high-elevation natural river sections as much as possible and reserve habitats for their migration and diffusion.

Animals

HallmarkGraph: a cancer hallmark informed graph neural network for classifying hierarchical tumor subtypes.

MOTIVATION: Accurate tumor subtype diagnosis is crucial for precision oncology, yet current methodologies face significant challenges. These include balancing model accuracy with interpretability and the high costs of generating multi-omics data in clinical settings. Moreover, there is a lack of validated models capable of classifying hierarchical tumor subtypes across a comprehensive pan-cancer cohort. RESULTS: We present a graph neural network, HallmarkGraph, the first biologically informed model developed to classify hierarchical tumor subtypes in human cancer. Inspired by cancer hallmarks, the model's architecture integrates transcriptome profiles and gene regulatory interactions to perform multi-label classification. We evaluate the model on a comprehensive pan-cancer cohort comprising 11&#xa0;476 samples from 26 primary cancers with 405 subtypes up to eight levels. The model demonstrates exceptional performance, achieving 5-fold cross-validation accuracy between 85% and 99% for tumor subtypes labeled with increasing details of genomic information. It also shows good generalizability on a validation dataset of 887 samples, assessed using three metrics that consider tumor subtypes at individual, combined, and sample levels. Benchmarking and ablation experiments show that hallmark-based embeddings slightly influence model performance, while the integrated multilayer perceptron plays a significant role in determining classifier accuracy. Additionally, we use the SHAP method to link cancer hallmarks with genes, identifying key features that influence model decisions. Our findings present a biologically informed machine learning framework capable of tracking tumor transcriptomic trajectories and distinguishing inter- and intra-tumor heterogeneity in pan-cancer. This approach holds promise for enhancing cancer diagnostics. AVAILABILITY AND IMPLEMENTATION: HallmarkGraph is accessible at https://github.com/laixn/HallmarkGraph.

Humans

Impact of polymorphisms on gene expression and splicing in response to exercise and diet-induced weight loss in human skeletal muscle tissues.

Weight loss through exercise and diet reduces the risk of type 2 diabetes, but the genetic regulation of gene expression and splicing in response to weight loss remains unclear in humans. We collected clinical data and skeletal muscle biopsies from 54 overweight/obese Asian individuals before and after a 16-week lifestyle intervention, which resulted in an average of &#x223c;10% weight loss, accompanied by an &#x223c;30% increase in insulin-stimulated glucose uptake. Improvements were observed in 118 of 252 clinical traits and six blood lipids. Transcriptomic analysis of paired skeletal muscle biopsies identified 505 differentially expressed genes enriched in mitochondrial function and insulin sensitivity. Thousands of muscle-specific expression/splicing quantitative trait loci (e/sQTLs) were detected pre- and post-intervention, including hundreds of lifestyle-responsive e/sQTLs. Notably, approximately 4.2% of eQTLs and 7.3% of sQTLs showed Asian specificity. Joint analysis with genome-wide association study (GWAS) identified 16 putative metabolic risk genes. Our study reveals gene-by-lifestyle interactions and how lifestyle modulates gene regulation in skeletal muscle.

Humans