Search PubMedSearch

SEARCH · Search PubMed

Results for “Genome, Bacterial”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

244 records · Page 12Linked to original sources

Effects of faba bean-based crisping culture on phenotypic characteristics, muscle quality, and serum metabolome in Nile tilapia: Screening biomarkers to assess the degree of crisping.

Feeding Nile tilapia (Oreochromis niloticus) a faba bean-based crisping diet enhances muscle hardness (crispness) and overall flesh quality. However, the underlying mechanisms and reliable biomarkers remain insufficiently defined. This study integrated phenotypic traits, muscle texture, collagen content, serum antioxidant enzyme activities (SOD, CAT, and GSH-Px), MDA levels, and serum metabolomics to understand the determinants of muscle crisping. Fish were assigned to a crisping diet or a control group for 90&#xa0;days. Individuals in the crisping group were implanted with passive integrated transponder (PIT) tags to enable correlation analyses among phenotypic traits (body weight/length/frame changes), serum indicators (NAM, FAD, and GSH-Px) and muscle hardness. Compared with controls, the crisping diet significantly increased muscle hardness, gumminess, and chewiness, accompanied by elevated collagen content. Antioxidant profiles were altered, with higher activities of serum SOD and CAT, together with elevated MDA levels and reduced GSH-Px activity (P&#xa0;<&#xa0;0.05). Metabolomic analysis identified 830 differential metabolites (682 upregulated and 148 downregulated), predominantly comprising carboxylic acids and derivatives, glycerophospholipids, and benzene derivatives. Enrichment analysis indicated significant involvement in general metabolic pathways, ATP-binding cassette (ABC) transporters, amino acid biosynthesis, and glycine, serine, and threonine metabolism (P&#xa0;<&#xa0;0.05). Notably, acetylpyruvate was upregulated in glutathione metabolism, nicotinate and nicotinamide metabolism, and galactose metabolism; pantothenic acid was upregulated in glycine, serine, and threonine metabolism; whereas &#x3b4;-tocotrienol was downregulated. Correlation analysis revealed weak negative associations between muscle hardness and phenotypic traits (body weight/length/frame changes D5-7, D5-10, D7-8) (P&#xa0;<&#xa0;0.05). In contrast, serum NAM and FAD were weakly positively correlated with muscle hardness, whereas GSH-Px showed a weak negative correlation (P&#xa0;<&#xa0;0.05). Collectively, these findings suggest that body weight, body length, frame measurements (D5-7, D5-10, and D7-8), and serum NAM, FAD, and GSH-Px are associated with the degree of muscle crispness in Nile tilapia fed a faba bean-based crisping diet and may serve as candidate biomarkers under these culture conditions.

Animals

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature&#x2011;supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR&#x2009;=&#x2009;0.52) and its potential regulation of risk factors IL2RA (OR&#x2009;=&#x2009;0.46) and HLA-DR (OR&#x2009;=&#x2009;0.40). Conversely, IL2RA (OR&#x2009;=&#x2009;1.42), HLA-DR (OR&#x2009;=&#x2009;1.88), and MIF (OR&#x2009;=&#x2009;1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+&#x2009;HLA-DR+&#x2009;CD74+&#x2009;monocytes and CD4+&#x2009;IL2RA+&#x2009;T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans

Algae-to-host horizontal gene transfer in Paramecium bursaria is associated with host adaptation during endosymbiosis.

Paramecium bursaria maintains a stable endosymbiosis with green algae, yet the evolutionary consequences of this association remain unclear. Here, we screened the host genome for algal-derived horizontally transferred genes (HTGs) using a lineage-aware workflow designed to detect horizontal gene transfer (HGT) between two defined lineages. We identified 16 candidate HTGs, including four putative newly transferred genes and 12 homologous transferred genes, most of which were functionally associated with redox homeostasis and metabolism. Five HTGs showed symbiosis-dependent expression. RNAi knockdown of GH32s and SATs reduced host proliferation, total cell area, and motility, while GH32s knockdown also reduced endosymbiont load. Duplication patterns suggest that most transfers may have occurred after the P. bursaria lineage diverged from the sampled Paramecium species but before its lineage-specific whole-genome duplication (WGD). The HTGs also showed host-associated shifts in GC content and gene length, while representative HTGs retained conserved domains and functional motifs. Together, our results support algae-to-host HGT in P. bursaria and suggest that some transferred genes may contribute to metabolic integration during endosymbiosis.

Gene Transfer, Horizontal

Construction of an infectious clone of Spodoptera frugiperda densovirus and its biological characteristics.

Densoviruses are highly pathogenic to their insect hosts and have great potential for biocontrol. Spodoptera frugiperda densovirus (SfDV) was isolated from diseased larvae of Spodoptera frugiperda, while its biological functions remain unclear. Herein, we successfully constructed an infectious clone of SfDV. The S. frugiperda larvae transfected with the infectious clone exhibited anorexia, stunted growth, and reduced activity. Histopathological analysis further showed that the epidermis, fat body and trachea were infected instead of muscle and midgut tissues. Transmission electron microscopy (TEM) revealed that numerous virions of about 22&#x202f;nm were distributed within both the nucleoplasm and cytoplasm of epidermal cells. Moreover, many virions were also found contained within vesicles in the cytoplasm. The replication kinetics of the rescued SfDV (rSfDV) was similar to that of the parental SfDV. The median lethal dose (LD50) and median lethal time (LT50) values of rSfDV were 6.63&#x202f;&#xd7;&#x202f;107 viral genome copies (vgc), 5.23&#x202f;d, respectively, which were also comparable to those of the parental SfDV. Taken together, the infectious clone of SfDV provides an important tool for further exploring the genome function, pathogenesis, and interactions with its hosts.

Animals

UNCX/SIN3A-Mediated H4K8 decrotonylation suppresses FOXO3 to drive TNBC progression and docetaxel resistance.

Triple-negative breast cancer (TNBC) remains a clinically challenging subtype characterized by aggressive behavior and limited treatment options. Though docetaxel remains a cornerstone chemotherapy for TNBC, the frequent emergence of resistance highlights the urgent need to identify novel therapeutic targets. In this study, we report that uncoordinated homeobox (UNCX) is upregulated in docetaxel-resistant breast cancer cells, genomically amplified in breast cancer, and associated with poor survival in breast carcinoma patients. Functional studies revealed that UNCX promotes breast cancer cell proliferation, migration and reduces the docetaxel sensitivity. Mechanistically, UNCX functions as a transcriptional repressor by recruiting the SIN3A complex. Genome-wide profiling indicated that the UNCX/SIN3A complex directly binds to the promoters of tumor-suppressor genes including FOXO3, and represses their transcription by removing histone H4K8 crotonylation (H4K8cr). Additionally, the UNCX/SIN3A complex enhances FOXO3 phosphorylation and inhibits its nuclear translocation, further inhibiting its activity. Notably, SIN3A knockdown, FOXO3 overexpression, or crotonylation restoration effectively reverses UNCX-induced malignant phenotypes. These findings collectively establish the UNCX/SIN3A-H4K8cr-FOXO3 axis as a pivotal epigenetic regulator of TNBC progression and chemoresistance, revealing new avenues for targeted therapeutic development against this aggressive breast cancer subtype.

Humans

Viral replication through phase separation: Cytosolic and nuclear condensates.

Replication of many RNA and DNA viruses occurs within specialized intracellular hubs organized as membraneless biomolecular condensates (BCs) driven by liquid-liquid phase separation. As obligate intracellular parasites, viruses depend on the host cell machinery to complete their replication cycles and therefore actively remodel the intracellular environment to favor viral genome replication, transcription, and assembly. Cytosolic and nuclear phase-separated replication compartments (RC) provide concentrated and dynamic platforms that promote efficient interactions between viral genomes and viral or host proteins essential for infection. The formation of viral replication BCs is typically facilitated by viral proteins enriched in intrinsically disordered regions and low-complexity domains, which enable multivalent interactions with viral nucleic acids and cellular factors. These interactions are mediated by diverse biophysical forces, including hydrophobic and &#x3c0; interactions, hydrogen bonding, molecular crowding, and osmotic effects. Throughout infection, viral BCs remain highly dynamic, allowing continuous exchange of components and functional maturation of replication hubs. Their properties and activities are further regulated by post-translational modifications of viral and host proteins, such as phosphorylation, acetylation, and methylation. In this review, we summarize current evidence supporting liquid-liquid phase separation as a central organizing principle of viral RCs. We focus on representative RNA and DNA viruses that replicate in the cytosol or nucleus, highlighting virus-specific strategies, conserved mechanisms, and the consequences of BC formation for viral replication efficiency, host antiviral responses, and therapeutic intervention.

Phase Separation

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU&#xb7;mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans

Genetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1, and CMIP variants.

BACKGROUND: Gestational diabetes mellitus (GDM) has a high global prevalence and arises from complex interactions between genetic predisposition and environmental factors. GDM is associated with metabolic disturbances and chronic low-grade inflammation, both of which contribute to its pathogenesis. This study aimed to investigate the association between GDM and 135 single-nucleotide polymorphisms (SNPs) across 20 genes related to metabolic traits. METHODS: In this case-control study, 152 pregnant women with GDM and 684 pregnant women with normal glucose tolerance (NGT) who underwent antenatal examination at Siriraj Hospital, Bangkok, were enrolled. Clinical data and blood samples were collected from all participants. Genomic DNA was isolated and subjected to whole-genome sequencing using the DNBSEQ-T7RS high-throughput sequencing platform. Genotype analyses were performed using R software, and haplotype analyses were conducted using the online SNPStats software. RESULTS: After adjusting for maternal age and pre-pregnancy body mass index, polymorphisms in TCF7L2 (rs34872471, rs7901695, rs4506565, rs7903146, rs12243326, and rs12255372), NEDD1 (rs10431408, rs11830756, rs249579, rs249585, and rs4762339), CMIP (rs2306115 and rs201681534), CDKAL1 (rs4710942), GCKR (rs2293572 and rs2293571), and GCK (rs5883890) were significantly associated with the risk of GDM. Haplotype analysis demonstrated that the TCF7L2 rs12243326-rs12255372 CA haplotype was associated with a decreased risk of GDM (OR = 0.44, 95% CI: 0.23-0.81), while the NEDD1 rs249579-rs249585-rs4762339 GGT haplotype was associated with an increased risk of GDM (OR = 1.40, 95% CI: 1.08-1.82). CONCLUSIONS: These findings suggest that genetic variations in TCF7L2, NEDD1, CMIP, CDKAL1, GCK, and GCKR contribute to GDM susceptibility in the Thai population.

Humans

Systematic review of the mutations in the active antigenic site &#xd8; of the prefusion F protein of the Respiratory Syncytial Virus (RSV) following the implementation of monoclonal antibody prophylaxis.

BACKGROUND: Monoclonal antibody (mAb) nirsevimab, which targets the antigenic site &#xd8; of the prefusion F protein (pre-F) of RSV, was introduced for RSV prophylaxis in several countries. METHODS: A systematic search was conducted between January 1, 2022, and July 31, 2026 for studies analyzing substitutions within the epitope of pre-F RSV protein, which is the target of nirsevimab, after the implementation of the mAb. We searched across PubMed, Scopus, Web of Science and ClinicalTrial.gov for studies involving children with confirmed RSV infection, that conducted genomic analysis. RESULTS: Seven studies (five observational and two randomized controlled trials) including 2156 RSV-positive samples (RSV-A: 1347, RSV-B: 809) were analyzed. RSV-A strains showed limited variability within antigenic site &#xd8;, with K65R being the most common substitution and K209E being the only intermediate-resistance RSV-A substitution. RSV-B strains demonstrated substantially higher substitution frequencies, particularly involving I206M, Q209R, and S211N. Most identified substitutions appeared to represent naturally occurring polymorphisms and retained susceptibility to nirsevimab, while multiple RSV-B substitutions and combinations involving residues 64-68 and 204-208 demonstrated reduced susceptibility or high-level resistance. Resistance-associated variants were detected in 28 of 2156 (1.3%) RSV-positive samples and exclusively among nirsevimab breakthrough infections. In a sub-analysis restricted to nirsevimab-treated individuals, resistance-associated variants were significantly more frequent among RSV-B than RSV-A (9.8% vs 0.5%; p&#xa0;<&#xa0;0.001). CONCLUSION: Most substitutions that were detected within the nirsevimab antigenic site reflect ongoing natural RSV evolution and do not significantly affect nirsevimab susceptibility. However, detection of resistance-associated variants highlights the importance of continuous genomic and phenotypic surveillance.

Humans

The identification of growth-promoting lncRNAs in oral cavity squamous cell carcinoma.

Oral Cavity Squamous Cell Carcinoma (OCSCC) is an aggressive tumor that develops within the mouth of patients. Tumor-suppressor gene loss and genomic arrangements fuel tumorigenesis and transcriptional reprogramming. Understanding how these alterations contribute to OCSCC growth and cell survival may identify new therapeutic vulnerabilities or biomarkers. We profiled the role of long non-coding RNAs (lncRNAs) in the growth of three OCSCC cell lines using a CRISPRi-screen and identified 19 lncRNAs that contribute to OCSCC proliferation. By comparing these lncRNAs to other screens, we find that these lncRNAs are uniquely required in OCSCC and not other malignancies. We show that these lncRNAs are abundantly expressed in OCSCC cells and tumors. Independent testing of candidate lncRNAs confirms their role in supporting OCSCC growth. Our results show that a novel subset of lncRNAs are required for the growth of OCSCC cancer cells and that these lncRNAs are cell lineage specific.

CRISPRi

Genetic overlap between estimated glomerular filtration rate and cardiovascular disease identifies potential targets for cardiorenal syndrome.

Heart and kidney diseases frequently coexist, but the genetic basis of this relationship remains unclear. We analyzed genetic data from large-scale studies to investigate how kidney function (estimated glomerular filtration rate, eGFR) and six common cardiovascular diseases share genetic risk factors. Using MiXeR method, and conjunctional false discovery rate (conjFDR) to identify overlapping genetic regions, we found 478 shared genomic loci between eGFR and cardiovascular diseases. These shared genes are involved in tissue development and structure. We also identified 29 genes that could be targeted by existing medications approved by the US Food and Drug Administration, such as PRKAG2, PDE1A, and IGF1R. Among these, genetically predicted higher level of IGF1R expression is associated with a higher eGFR, which reflects good kidney function and is protective against cardiorenal diseases, such as atrial fibrillation, and myocardial infarction. These findings reveal genetic overlap between kidney function and cardiovascular diseases, highlighting potential targets for understanding and treating cardiorenal syndrome.

Humans

O'nyong-nyong virus adaptive mutations in non-structural protein 1 and 3 enhance RNA replication and overcome FHL1 requirement.

Arthritogenic alphaviruses, like o'nyong-nyong virus (ONNV), cause debilitating musculoskeletal diseases and are geographically expanding. To predict their emergence, we seek to better understand evolutionary mechanisms that enable changes in virus tropism. Here, we identify adaptive mutations in the ONNV non-structural proteins (nsPs) that arose during cellular serial passaging and enabled ONNV to infect non-permissive Lunet cells. Using shotgun proteomics, we show that this human hepatoma cell line lacks the four-and-a-half-LIM domain protein 1 (FHL1), an essential host factor in ONNV RNA replication. Individual single nucleotide mutations in the nsP1 ring-aperture membrane-binding and oligomerization domain, the nsP3 macrodomain, and the nsP3 opal stop codon overcome FHL1 deficiency in Lunet cells by enhanced RNA replication. These findings demonstrate how subtle genomic changes in nsPs can profoundly influence alphavirus replication and tropism.

LIM Domain Proteins

Pervasive hybridization and introgression in Diervilleae (Caprifoliaceae).

Diervilleae (Caprifoliaceae) is a horticulturally important lineage with striking floral diversity and a long history of interspecific crossing, suggesting reticulate evolution. We integrated nuclear SNPs and whole plastome data to reconstruct a phylogenomic backbone for the tribe and to identify hybrids, cultivated accessions, and introgression among lineages. Nuclear and plastid phylogenies consistently recover Weigela and Diervilla as reciprocally monophyletic and resolve four major lineages within Weigela, providing a reproducible framework for revising sectional limits and species boundaries. Cultivated accessions form a well supported clade sister to W. florida and show predominantly W. florida ancestry while retaining contributions from multiple wild lineages, consistent with recurrent crossing, backcrossing, and selection. Analyses of wild populations reveal recurrent hybrids and enable plausible parental combinations to be inferred. Tests across the genome further indicate strong evidence for historical introgression across Diervilleae, with the strongest signals involving W. middendorffiana, W. maximowiczii, and Diervilla. Fossil evidence, divergence time estimation, and paleodistribution modelling together suggest range expansion during the Miocene and Pliocene followed by climate driven contraction, providing a spatiotemporal context for episodic contact, introgression, and the East Asia-North America disjunction.

Hybridization, Genetic

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9