Biomedical subjects

Tian Li

Publications and source records attributed to Tian Li.

6 recordsLinked to original sources

PubMed2026

Microplastic aging drives convergence of the plastisphere microbiome and resistome toward agricultural soils.

The degree of microplastic (MP) aging varies substantially in agricultural soils; however, how this common aging gradient influences the plastisphere microbiome and resistome remains largely unknown. We therefore collected polyethylene MPs from long‑term mulched farmlands and classified them into low‑aged plastispheres (LAPs) and high‑aged plastispheres (HAPs). Bacterial community dissimilarity to soil decreased progressively from LAPs to HAPs, accompanied by broadening niche breadth, increasing bacterial diversity, and a shift toward more stochastic community assembly. The diversity and abundance of antibiotic resistance genes (ARGs) declined significantly along the aging gradient, with clinically relevant high-risk ARGs (e.g., vanR, ugd, and aac(6')-I) decreasing by 53.34-84.01%. Furthermore, the ARG hosts shifted from Actinomycetota in LAPs to Pseudomonadota in soils. Variance partitioning showed that the carbonyl index uniquely explained 57.03% of the variation in plastisphere ARG profile distance toward soil, identifying MP aging as the primary driver of resistome convergence. Collectively, these findings demonstrate that natural MP aging drives a progressive convergence of the plastisphere resistome toward that of the surrounding soil, indicating that aged MPs may pose a reduced risk of antibiotic resistance compared to newly formed MPs. This convergence underscores the need to incorporate plastic aging into future risk assessment frameworks for plastisphere-associated ARGs.

Soil Microbiology↗

PubMed2025

Impacts of non-spherical polyethylene nanoplastics on microbial communities and antibiotic resistance genes in the rhizosphere of pea (Pisum sativum L.): An integrated metagenomic and metabolomic analysis.

The ecological effects of nanoplastics (NPs) has become a growing concern; however, the influence of non-spherical NPs-which better represent real-world morphologies-remains poorly understood. This study investigated the impact of non-spherical polyethylene (PE) NPs on the growth of pea (Pisum sativum L.) and its rhizosphere microenvironment across different concentration levels (0, 20, and 200 mg/kg) using integrated metagenomics and metabolomics. Results showed that high-dose (200 mg/kg) exposure significantly inhibited plant growth. Although soil physicochemical properties remained unchanged, the rhizosphere microbial communities experienced significant restructuring, characterized by a marked enrichment of Pseudomonas and a reduction in beneficial Rhizobium populations. Metagenomic analysis revealed a concurrent increase in the abundance and diversity of antibiotic resistance genes (ARGs) under non-spherical PE-NP stress. This was accompanied by a shift in bacterial host composition, with a trend toward a higher prevalence of potentially pathogenic taxa such as Pseudomonas aeruginosa. Metabolomics analysis further revealed that non-spherical PE-NPs altered the rhizosphere metabolite profile, thereby significantly driving the succession of ARG hosts. Our integrated analysis enhances the understanding of how non-spherical PE-NPs disrupt microbial communities and elevate the risks of ARGs in rhizosphere soil, highlighting the significance of incorporating environmentally relevant NPs into environmental risk assessments.

Pisum sativum↗

PubMed2025

Targeting FOXK2 in triple-negative breast cancer: Role of the P53/MCAS1/miR-211-5p regulatory axis.

Forkhead box K2 (FOXK2) is over-expressed in several human malignancies, yet how it is regulated triple-negative breast cancer (TNBC) remained unclear. We aimed to clarify whether FOXK2 drives TNBC progression, and elucidate the upstream molecular circuitry that controls FOXK2 abundance. FOXK2 mRNA and protein were quantified by qPCR and Western blot in 30 paired TNBC and adjacent tissues. Some assays assessed proliferation, migration and invasion after FOXK2 knockdown or overexpression. Bioinformatics predicted miR-211-5p targeting FOXK2 and lncRNA MCM3AP-AS1 (MCAS1) targeting miR-211-5p. RNA immunoprecipitation (RIP) and dual-luciferase assays validated these interactions. RNA pulldown, mass spectrometry and ChIP identified p53 binding to the MCAS1 promoter. FOXK2 was upregulated in TNBC tissues as opposed to the para-carcinoma tissues. FOXK2 silencing significantly reduced proliferation, migration and invasion, whereas overexpression accelerated these phenotypes. Mechanistically, MCAS1 acts as a sponge for miR-211-5p, ultimately protecting its target gene FOXK2 from degradation. Furthermore, employing RNA pulldown, mass spectrometry, ChIP, and luciferase reporter assays, our studies revealed a direct interaction between P53 and the promoter of MCAS1. This interaction resulted in the suppression of MCAS1 transcription. Clinical samples from TNBC patients further confirmed a correlation between FOXK2 expression and tumor size, lymphatic involvement, as well as the expression level of Ki-67. Our findings unveil a novel P53/MCAS1/miR-211-5p/FOXK2 regulatory axis that dictates TNBC aggressiveness. FOXK2 may sever as both a prognostic biomarker and a therapeutic target in TNBC.

Humans↗

PubMed2025

Mendel randomization confirmed gastroesophageal reflux disease may increase the risk of mental disorders.

BACKGROUND: The potential causal relationship between gastroesophageal reflux disease (GERD) and mental disorder was analyzed using the mendelian randomization (MR) method. METHODS: Data are derived from genome-wide association study (GWAS) summary data, using gastroesophageal reflux disease (GERD) as the exposure factor. Single nucleotide polymorphisms (SNPs) significantly associated with GERD were selected as instrumental variables (IVs), and mental disorders (bipolar disorder, major depression, Alzheimer's disease, anorexia nervosa, anxiety, and obsessive-compulsive disorder) were used as outcome variables. The inverse variance weighted (IVW) method is used as the main analysis method, and MR-Egger regression, weighted median (WM) method, simple mode and weighted mode are used as supplementary methods for Mendelian randomization (MR) analysis. Cochran's Q test and P value are used to quantify heterogeneity, MR-Egger regression was used to evaluate the multilevel effect test of SNPs, and leave-one-out method to determine whether there are potential SNPs, and to evaluate the stability of the results. Odds ratio (OR) and 95% confidence interval (CI) were used as effect indicators to evaluate whether there is a causal relationship between GERD and mental disorders. RESULTS: IVW demonstrated a causal relationship between GERD and bipolar disorder (OR = 1.70, 95%CI = 1.39-2.09, P < 0.05) and anorexia nervosa (OR = 0.71, 95%CI = 0.52-0.99, P < 0.05). Furthermore, there is a weak causal relationship between GERD and major depression (OR = 1.01, 95%CI = 1.01-1.02, P < 0.05) and anxiety (OR = 1.01, 95%CI = 1.01-1.01, P < 0.05). Similarly, there is no evidence of a causal relationship between GERD and Alzheimer's disease (OR = 0.95, 95%CI = 0.87-1.03, P > 0.05) or obsessive-compulsive disorder (OR = 0.95, 95%CI = 0.67-1.36, P > 0.05). Cochran's Q test for heterogeneity shows that there is no significant heterogeneity (P > 0.05) for bipolar disorder, anxiety, and obsessive-compulsive disorder. However, major depression, Alzheimer's disease, and anorexia nervosa have some degree of heterogeneity (P < 0.05). Horizontal pleiotropic analysis showed that the P values for six mental disorders (0.750, 0.296, 0.154, 0.798, 0.893, 0.451) were all greater than 0.05. Leave-one-out analysis and funnel plot showed that MR analysis results can be considered relatively stable. All F are > 10, indicating no weak IVs bias. CONCLUSION: GERD can obviously increase the risk of bipolar disorder; the increased risk of anxiety disorder is very slight. There is no clear evidence to support the causal relationship between GERD and four other mental disorders, including major depression, Alzheimer's disease, anorexia nervosa, and obsessive-compulsive disorder.

Humans↗

PubMed2025

Cis-regulatory elements: systematic identification and horticultural applications.

Cis-regulatory elements (CREs) are the genetic DNA fragments bound by transcription factors (TFs). CREs function as molecular switches that precisely modulate the dosage and spatiotemporal patterns of gene expression. The systematic identification of CREs not only facilitates the annotation of the functional non-coding genome but also provides essential insights into the architecture of gene regulatory networks and sheds light on an accurate selection of the target sites for genetic engineering of crops. In this review, we summarize the current high-throughput methodologies used for identifying CREs, illustrate the associations between CREs and agronomic traits in horticultural crops, and discuss how CREs can be exploited to facilitate crop breeding.

Breeding↗

PubMed2025

dbscATAC: a resource of single-cell super-enhancers/enhancers and gene markers derived from scATAC-seq data.

MOTIVATION: scATAC-seq enables high-resolution mapping of cis-regulatory elements. It has been widely applied to uncover cell-type-specific regulatory networks and complement scRNA-seq analysis in numerous studies. However, a large number of datasets generated by scATAC-seq remain underutilized due to limited exploration of super-enhancers/typical enhancers and gene markers. A comprehensive resource enabling cell-type-specific annotation of cis-regulatory elements and their dynamic enhancer-gene linkages remains an urgent unmet need for scATAC-seq. RESULTS: We present dbscATAC, a specialized single-cell database for annotating super-enhancers, gene markers, and enhancer-gene interactions derived from scATAC-seq data. Using improved machine learning algorithms, we identified 213 835 super-enhancers across 520 tissue/cell types from three species, as well as 347 484 gene markers, 13 470 526 enhancers, and 10 402 346 enhancer-gene interactions derived from 1 668 076 single cells spanning 1028 tissue/cell types in 13 species. An easy-to-use online platform with multiple analytic modules and hierarchical query options was developed for searching, browsing and visualizing single-cell super-enhancers, enhancers, and gene markers. dbscATAC provides a comprehensive resource to facilitate the exploration of enhancer landscapes, gene regulation, and cell-type-specific characteristics in single-cell epigenomics. AVAILABILITY AND IMPLEMENTATION: The database with all the super-enhancer/enhancer annotation data is available at http://singlecelldb.com/dbscATAC/index.php. And the source code of dbscATAC for prediction of SEs, enhancers, and gene markers are available at https://github.com/EvansGao/dbscATAC. The source code, tissue/cell type description, and data summary can be downloaded at DOI: 10.6084/m9.figshare.28706414.scATAC-seq, Database, Super-enhancers/enhancers, Gene markers.

Enhancer Elements, Genetic↗