Search Results (1,217)

This review explores the biofilm architecture and drug resistance of Enterococcus faecalis in clinical and environmental settings. The biofilm in E. faecalis is a heterogeneous, three-dimensional, mushroom-like or multilayered structure, characteristically forming diplococci or short chains interspersed with water channels for nutrient exchange and waste removal. Exopolysaccharides, proteins, lipids, and extracellular DNA create a protective matrix. Persister cells within the biofilm contribute to antibiotic resistance and survival. The heterogeneous architecture of the E. faecalis biofilm contains both dense clusters and loosely packed regions that vary in thickness, ranging from 10 to 100 µm, depending on the environmental conditions. The pathogenicity of the E. faecalis biofilm is mediated through complex interactions between genes and virulence factors such as DNA release, cytolysin, pili, secreted antigen A, and microbial surface components that recognize adhesive matrix molecules, often involving a key protein called enterococcal surface protein (Esp). Clinically, it is implicated in a range of nosocomial infections, including urinary tract infections, endocarditis, and surgical wound infections. The biofilm serves as a nidus for bacterial dissemination and as a reservoir for antimicrobial resistance. The effectiveness of first-line antibiotics (ampicillin, vancomycin, and aminoglycosides) is diminished due to reduced penetration, altered metabolism, increased tolerance, and intrinsic and acquired resistance. Alternative strategies for biofilm disruption, such as combination therapy (ampicillin with aminoglycosides), as well as newer approaches, including antimicrobial peptides, quorum-sensing inhibitors, and biofilm-disrupting agents (DNase or dispersin B), are also being explored to improve treatment outcomes. Environmentally, E. faecalis biofilms contribute to contamination in water systems, food production facilities, and healthcare environments. They persist in harsh conditions, facilitating the spread of multidrug-resistant strains and increasing the risk of transmission to humans and animals. Therefore, understanding the biofilm architecture and drug resistance is essential for developing effective strategies to mitigate their clinical and environmental impact. Full article

Heavy metal pollution represents a pervasive environmental challenge that significantly exacerbates the ever-increasing crisis of antimicrobial resistance and the capacity of microorganisms to endure and proliferate despite antibiotic interventions. This review examines the intricate relationship between heavy metals and AMR, with an emphasis on the underlying molecular mechanisms and ecological ramifications. Common environmental metals, including arsenic, mercury, cadmium, and lead, exert substantial selective pressures on microbial communities. These induce oxidative stress and DNA damage, potentially leading to mutations that enhance antibiotic resistance. Key microbial responses include the overexpression of efflux pumps that expel both metals and antibiotics, production of detoxifying enzymes, and formation of protective biofilms, all of which contribute to the emergence of multidrug-resistant strains. In the soil environment, particularly the rhizosphere, heavy metals disrupt plant–microbe interactions by inhibiting beneficial organisms, such as rhizobacteria, mycorrhizal fungi, and actinomycetes, thereby impairing nutrient cycling and plant health. Nonetheless, certain microbial consortia can tolerate and detoxify heavy metals through sequestration and biotransformation, rendering them valuable for bioremediation. Advances in biotechnology, including gene editing and the development of engineered metal-resistant microbes, offer promising solutions for mitigating the spread of metal-driven AMR and restoring ecological balance. By understanding the interplay between metal pollution and microbial resistance, we can more effectively devise strategies for environmental protection and public health. Full article

Bladder cancer pathogenesis is closely linked to epigenetic alterations, particularly DNA methylation and demethylation processes. Environmental carcinogens and persistent inflammatory stimuli—such as recurrent urinary tract infections—can induce aberrant DNA methylation, altering gene expression profiles and contributing to malignant transformation. This review synthesizes current evidence on the role of DNA methyltransferases (DNMT1, DNMT3a, DNMT3b) and the hypermethylation of key tumour suppressor genes, including A2BP1, NPTX2, SOX11, PENK, NKX6-2, DBC1, MYO3A, and CA10, in bladder cancer. It also evaluates the therapeutic application of DNA-demethylating agents such as 5-azacytidine and highlights the impact of chronic inflammation on epigenetic regulation. Promoter hypermethylation of tumour suppressor genes leads to transcriptional silencing and unchecked cell proliferation. Urine-based DNA methylation assays provide a sensitive and specific method for non-invasive early detection, with single-target approaches offering high diagnostic precision. Animal models are increasingly employed to validate these findings, allowing the study of methylation dynamics and gene–environment interactions in vivo. DNA methylation represents a key epigenetic mechanism in bladder cancer, with significant diagnostic, prognostic, and therapeutic implications. Integration of human and experimental data supports the use of methylation-based biomarkers for early detection and targeted treatment, paving the way for personalized approaches in bladder cancer management. Full article

Aggressiveness in dogs is a complex behavioral trait with implications for animal welfare and public safety. Despite domestication, dogs retain aggressive tendencies shaped by both genetic and environmental factors. This systematic review synthesizes the literature from 2000 to 2024 on the genetic and environmental bases of canine aggression. Using PRISMA 2020 guidelines, 144 articles were retrieved from Scopus and PubMed and screened in two phases, resulting in 33 studies selected for analysis. These were evaluated using a 20-question grid across seven categories, including phenotyping, genetic analysis, population structure, and future directions. The studies support a polygenic model of aggressiveness, with associations reported for genes involved in neurotransmission, hormone signaling, and brain function. However, inconsistencies in phenotyping, small sample sizes, and a limited consideration of environmental factors hinder robust conclusions. Most studies focused on popular companion breeds, while those commonly labeled as aggressive were underrepresented. The findings highlight the relevance of gene–environment interactions but underscore that aggression is often poorly defined and measured across studies. Future research should prioritize standardized phenotyping tools, broader breed inclusion, and the functional validation of genetic findings. These efforts will improve the understanding of dog aggression and inform breeding, behavioral assessment, and public policy. Full article

Background/Objectives: Impulsivity is a key psychological construct implicated in the onset and maintenance of behavioural addictions. Dysregulation of impulsivity is central to behavioural addictions, yet its genetic basis remains unclear. This study examined the association between the DAT1 variable number tandem repeat polymorphism and impulsivity in individuals with behavioural addictions. Methods: A total of 328 males (128 with behavioural addictions and 200 controls) completed the Barratt Impulsiveness Scale. DAT1 genotyping was performed via PCR and gel electrophoresis. Statistical analyses included chi-square tests, Mann–Whitney U-tests, and two-way ANOVA. Results: No differences in DAT1 genotype frequencies were found between groups. However, a significant interaction emerged for attentional impulsivity: individuals with behavioural addictions and the 9/9 genotype had the highest BIS-AI scores (F_{2, 322} = 5.48; p = 0.0046). Conclusions: The DAT1 9/9 genotype may increase vulnerability to attentional impulsivity, but only in the context of behavioural addictions. These findings highlight a gene–environment interaction and support the role of dopaminergic mechanisms in cognitive dysregulation. Future studies should validate these findings using longitudinal designs and neurobiological methods. Full article

Background: Polygenic risk scores (PRS) have emerged as promising tools for disease risk stratification. However, their validity across different populations remains unclear, particularly for autoimmune diseases, where environmental factors may play crucial roles. Methods: We calculated the population-level PRS for Sjögren’s syndrome using seven validated genetic variants (PGS001308) and allele frequency data from the 1000 Genomes Project Phase 3 for five European populations (CEU, TSI, FIN, GBR, and IBS). PRS values were correlated with published prevalence estimates from a systematic literature review. Statistical analyses included Pearson’s correlation and sensitivity analyses. Results: PRS values varied across European populations, ranging from 0.317 in the Spanish population to 0.370 in the Northern European population. A non-significant negative trend was observed between population PRS and Sjögren’s syndrome prevalence (r = −0.407, R² = 0.166). Italy showed the lowest genetic risk score (TSI: 0.349) but the highest disease prevalence (58.2 per 100,000), while Northern European populations demonstrated a higher PRS but lower prevalence. Conclusions: No significant correlation was found between genetic risk scores and disease prevalence in this limited sample of five European populations. Larger studies are needed to clarify the relationship between polygenic risk and disease prevalence. Full article

Corn smut, caused by Ustilago maydis, significantly threatens maize production. This study evaluated 199 maize inbred lines at the seedling stage under greenhouse conditions for resistance to U. maydis, identifying 39 highly resistant lines. A genome-wide association study (GWAS) using the mrMLM model detected 19 significant single-nucleotide polymorphism (SNP) loci. Based on a linkage disequilibrium (LD) decay distance of 260 kb, 226 candidate genes were identified. Utilizing the significant loci chr1_244281660 and chr5_220156746, two kompetitive allele-specific PCR (KASP) markers were successfully developed. A PCR-based sequence-specific oligonucleotide probe hybridization technique applied to the 199 experimental lines and 60 validation lines confirmed polymorphism for both markers, with selection efficiencies of 48.12% and 43.33%, respectively. The tested materials were derived from foundational inbred lines of domestic and foreign origin. Analysis of 39 highly resistant lines showed that the advantageous alleles carrying thymine/cytosine (T/C) predominated at frequencies of 94.87% and 53.84%, respectively. The genotype TTCC conferred high resistance, while CCTT was highly susceptible. The resistance exhibited high heritability and significant gene-by-environment interaction. This work systematically dissects the genetic basis of common smut resistance in maize, identifies favorable alleles, and provides a novel KASP marker-based strategy for developing disease-resistant germplasm. Full article

Background/Objectives: Maternal exposures are known to influence the risk of isolated cleft lip with or without cleft palate (CL/P)—a common and highly heritable birth defect with a multifactorial etiology. Methods: To identify new risk loci, we conducted a genome-wide gene–environment interaction (GEI) analysis of CL/P with maternal smoking and vitamin use in Filipinos (N_cases = 540, N_controls = 260). Since GEI analyses are typically low in power and the results can be difficult to interpret, we applied multiple testing frameworks to evaluate potential GEI effects: a one degree-of-freedom (1df) GxE test, the 3df joint test, and the two-step EDGE approach. Results: While no genome-wide significant interactions were detected, we identified 11 suggestive GEIs with smoking and 24 with vitamin use. Several implicated loci contain biologically plausible genes. Notable interactions with smoking include loci near FEZF1, TWIST2, and NET1. While FEZF1 is involved in early neuronal development, TWIST2 and NET1 regulate epithelial–mesenchymal transition, which is required for proper lip and palate fusion. Interactions with vitamins encompass CECR2—a chromatin remodeling protein required for neural tube closure—and FURIN, a critical protease during early embryogenesis that activates various growth factors and extracellular matrix proteins. The activity of both proteins is influenced by folic acid. Conclusions: Our findings highlight the critical role of maternal exposures in identifying genes associated with structural birth defects such as CL/P and provide new paths to explore for CL/P genetics. Full article

Understanding the interactions between specific cell types within tissue environments is essential for elucidating key biological processes, such as immune responses, cancer progression, inflammation, and development, in both physiological and pathological studies. The predominant methods for analyzing cell–cell interactions (CCI) rely primarily on statistical inference using mapping or network-based techniques. However, these approaches often struggle to prioritize meaningful interactions owing to the high sparsity and heterogeneity inherent in single-cell RNA sequencing (scRNA-seq) data, where small but biologically important differences can be easily overlooked. To overcome these limitations, we developed PriorCCI, a deep-learning framework that leverages a convolutional neural network (CNN) alongside Grad-CAM++, an explainable artificial intelligence algorithm. This study aims to provide a scalable, interpretable, and biologically meaningful framework for systematically identifying and prioritizing key ligand–receptor interactions between defined cell-type pairs from single-cell RNA-seq data, particularly in complex environments such as tumors. PriorCCI effectively prioritizes interactions between cancer and other cell types within the tumor microenvironment and accurately identifies biologically significant interactions related to angiogenesis. By providing a visual interpretation of gene-pair contributions, our approach enables robust inference of gene–gene interactions across distinct cell types from scRNA-seq data. Full article

Listeria monocytogenes is a life-threatening bacterial foodborne pathogen that can persist in food-processing facilities for years. Although phages can control L. monocytogenes during food production, phage-resistant bacterial subpopulations can regrow in phage-treated environments. In this study, an L. monocytogenes hly defective strain, NJ05-Δhly, was produced, which considerably regulated the interactions between L. monocytogenes and phages. Specifically, we observed a 76.92-fold decrease in the efficiency of plating of the defective strain following infection with the Listeria phage vB-LmoM-NJ05. The lytic effect was notably diminished at multiplicities of infection of 1 and 10. Furthermore, the inactivation of LLO impaired biofilm formation, which was completely suppressed and eliminated following treatment with 10⁸ PFU/mL of phage. Additionally, phages protected cells from mitochondrial membrane damage and the accumulation of mitochondrial reactive oxygen species induced by L. monocytogenes invasion. Transcriptomic analysis confirmed these findings, revealing the significant downregulation of genes associated with phage sensitivity, pathogenicity, biofilm formation, and motility in L. monocytogenes. These results underscore the vital role of LLO in regulating the pathogenicity, phage susceptibility, and biofilm formation of L. monocytogenes. These observations highlight the important role of virulence factors in phage applications and provide insights into the potential use of phages for developing biosanitizers. Full article

Dysregulated inflammatory processes contribute to depression, and gene–environment interactions may influence an individual’s risk and resilience. Reduced brain-derived neurotrophic factor (BDNF) expression increases susceptibility for developing depressive symptoms, and the Val66Met (rs6265) single-nucleotide polymorphism (SNP) on the BDNF gene is linked to mood disorders. However, whether Val66Met confers increased vulnerability to inflammation-induced depressive tendencies is unknown. Here, we tested the hypothesis that the Val66Met SNP increases vulnerability to inflammation-induced depressive symptoms in a mouse model of lipopolysaccharide (LPS)-induced depression-like behavior. Behavior and neuroinflammation, following a 24 h LPS challenge, were measured in mice expressing the human BDNF Val66Met gene variant or Val66Val littermates (control). The Val66Met genotype did not affect the peripheral inflammatory response, acute neuroinflammation, or the acute sickness behavior response. Val66Met mice exhibited anhedonia-like behavioral responses following LPS challenge, and we found increased mRNA expression of IL-1β and TNFα in the cerebrum compared to controls. The mRNA expression of IL-1β and TNFα in the hippocampus and the nucleus accumbens of Val66Met mice was increased following LPS, and a significant genotype × LPS interaction was detected for CD68 expression in the nucleus accumbens. In summary, these data suggest that immune activation in Val66Met mice increased susceptibility to anhedonic behavior and dysregulated negative regulation of inflammation. Full article

The transforming growth factor beta (TGF-$\mathsf{\beta }$) gene family is widely distributed across the animal kingdom, playing a crucial role in various cellular processes and maintaining overall health and homeostasis. The present study identified 34 TGF-$\mathsf{\beta }$ family genes based on the genome sequence in Tupaia belangeri, which were classified into the TGF-$\mathsf{\beta }$, bone morphogenetic protein (BMP), growth differentiation factor (GDF), glial cell-derived neurotrophic factor (GDNF), and Activin/Inhibin subfamilies. A phylogenetic analysis revealed the evolutionary relationships among members of the TGF-$\mathsf{\beta }$ family in T. belangeri and their homologous genes in Homo sapiens, Mus musculus, and Pan troglodytes, indicating a high degree of conservation throughout evolution. A chromosomal distribution and collinearity analysis demonstrated the localization of these genes within the genome of T. belangeri and their collinearity with genes from other species. A gene structure and motif analysis further illustrated the conservation and diversity among TGF-$\mathsf{\beta }$ family members. A protein interaction network analysis highlighted the central roles of TGFB1, TGFB3, BMP7, and BMP2 in signal transduction. A functional enrichment analysis underscored the significance of the TGF-$\mathsf{\beta }$ signaling pathway in the biological processes of T. belangeri, particularly in cell proliferation, differentiation, and apoptosis. We assessed the impact of cold acclimation treatment on the expression of TGF-$\mathsf{\beta }$ family proteins in the adipose tissue (white adipose tissue [WAT] and brown adipose tissue [BAT]) of T. belangeri using ELISA technology, finding that protein expression levels in the experimental group were significantly higher than those of in the control group. These results suggested that cold acclimation may enhance the adaptability of T. belangeri to cold environments by modulating the expression of TGF-$\mathsf{\beta }$ family genes. This study offers new insights into the role of the TGF-$\mathsf{\beta }$ family in the cold acclimation adaptation of T. belangeri, providing a scientific foundation for future genetic improvements and strategies for cold acclimation. Full article

Background/Objectives: Inter-individual metabolic responses to caffeine are shaped by CYP1A2 clearance rate and by concurrent lipid- or glucose-lowering drugs. We investigated how habitual caffeine intake relates to serum cholesterol and fasting glucose under different CYP1A2 rs762551 genotypes and statin or oral antidiabetic (OAD) use. Methods: A prospective cross-sectional analysis was performed on 358 adults (AA = 65, AC = 163, CC = 130) with recorded genotype, daily caffeine intake, total cholesterol, fasting glucose, and medication status. Multivariable linear regression tested the main and interaction effects of caffeine (mg day⁻¹), genotype, and therapy. Results: Caffeine intake was positively associated with cholesterol levels (β = 0.30; p < 0.001). A significant genotype × caffeine interaction (β = 0.27; p < 0.001) revealed the steepest rise in fast metabolisers (AA) not on statins, an effect largely blunted by statin therapy. For glucose, the genotype × caffeine term was also significant (β = 0.30; p < 0.001). Among slow metabolisers (CC) without OADs, caffeine correlated positively with glycaemia (r = 0.34; p = 0.028), whereas in fast metabolisers on OADs the association reversed (r = −0.36; p = 0.015). No meaningful associations occurred in AC carriers. Conclusions: Caffeine’s metabolic impact depends jointly on CYP1A2 genotype and medication. It raises cholesterol in fast metabolisers lacking statins and elevates glucose in slow metabolisers without OADs, yet may lower glucose when rapid metabolisation coincides with antidiabetic therapy. Accounting for this gene–diet–drug interplay could refine caffeine guidance within precision nutrition frameworks. Full article

Heat stress (HS) in dairy cattle triggers systemic physiological disruptions, including milk yield decline, immune suppression, and reproductive dysfunction, jeopardizing sustainable livestock production. While conventional single-omics or phenotypic studies have provided fragmented insights, they fail to decipher the multi-layered regulatory networks and gene–environment interactions underlying HS. This review integrates current knowledge on HS-induced physiological responses and molecular adaptations in dairy cattle from a multi-omics perspective, highlighting integrative approaches that combine IoT-enabled monitoring and AI-driven genetic improvement strategies. However, key challenges persist, such as complexities in bioinformatic data integration, CRISPR off-target effects, and ethical controversies. Future directions will emphasize the development and application of AI-aided predictive models to enable precision breeding, thereby advancing climate-resilient genetic improvement in dairy cattle. Full article

Soybeans are a primary source of plant-based protein, with seeds containing approximately 40% protein—a key quality trait. Selecting superior hybrid combinations and managing progeny effectively are crucial for developing high-protein soybean varieties. Using a recombinant inbred line population (RIL3613) derived from Dongnong L13 × Heihe 36 and its previously constructed high-density genetic linkage map, QTLs and QTL × environment interactions (QEIs) associated with seed protein content (SPC) were identified through the bi-parental population (BIP) model and multi-environment trials (MET) model in QTL IciMapping v4.2. Candidate genes were then predicted via sequence alignment and haplotype analysis between the parents. Finally, simulated breeding was conducted using the B4L function in the In Silico Breeding (ISB) module of the Blib platform to determine optimal breeding strategies across diverse environments. The analysis identified 19 QTLs associated with SPC and 97 QEIs linked to SPC. These QTLs collectively explained 84.442% of the phenotypic variance, with four QTLs exhibiting significant contributions. A key candidate gene, Glyma.12G231400, associated with soybean SPC, was predicted within the 38,995,090–39,293,825 bp interval on chromosome 12. Across 11 environments, three to six optimal breeding schemes were selected, all employing modified pedigree selection. These findings enhance our understanding of the genetic basis of soybean protein formation and provide technological support for molecular breeding for seed quality improvement. Full article