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PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗

PubMed2026

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

"Clinical efficacy and expression of antimicrobial resistance genes after using a novel herbal mouthwash compared to chlorhexidine: A Randomised controlled trial in generalised gingivitis patients".

OBJECTIVES: Chlorhexidine, the gold-standard mouthwash, has several disadvantages, like promotion of antimicrobial resistance. Herbal mouthwashes are emerging as alternatives to chlorhexidine. However, its impact on antimicrobial resistance remains unclear. The aim of the study was to compare the clinical efficacy and the expression of antimicrobial resistance genes of chlorhexidine with a novel herbal mouthwash. DESIGN: Sixty patients with generalised gingivitis were randomly assigned to two groups using block randomisation. After professional mechanical plaque removal patients were instructed to use either chlorhexidine or a novel herbal mouthwash (patented composition) for two weeks. Tetracycline resistance (tetM) and macrolide efflux (mefI) gene expression in subgingival plaque were analysed using real-time polymerase chain reaction. Intragroup comparisons were performed with a paired t-test and Wilcoxon signed-rank test for parametric and nonparametric data. Intergroup comparisons employed unpaired t-test, chi-square test, and Mann-Whitney test. RESULTS: A significant reduction in bleeding, plaque, pocket depth and and patient reported outcomes were noticed in both groups. But reduction in plaque was more significant in chlorhexidine group. tetM and mefI genes significantly upregulated in the chlorhexidine group, while it was downregulated with herbal mouthwash (fold change 1.79 ± 0.74 and 0.60 ± 0.43 for tetM, and 1.83 ± 0.87 and 0.51 ± 0.44 for mefI). However, patients' perception of taste, freshness, and overall satisfaction was better in the chlorhexidine group. CONCLUSIONS: The increased expression of antimicrobial resistance genes following chlorhexidine use warrants careful consideration. Herbal mouthwash is an effective, safer alternative with comparable clinical benefits and less impact on antimicrobial resistance.

Humans↗

PubMed2026

Genomic epidemiology of clinically critical antibiotic resistance in Salmonella enterica causing bloodstream infections across six Chinese provinces, 1994-2023.

Clinically critical antibiotic-resistant Salmonella enterica (S. enterica) causing bloodstream infections remains a public health challenge. Here, we aim to reveal the emergence and trends of clinically important antibiotic resistance in S. enterica causing bloodstream infections using 833 isolates from six Chinese provincial-level administrative areas during 1994-2023. We identified 48 serovars and 64 sequence types (STs). Overall, 8.52% of 833 isolates were resistant or had decreased susceptibility to ciprofloxacin, 4.32% and 6.84% reported resistance or decreased susceptibility to third- and fourth-generation cephalosporins (3GCs and 4GCs), 1.80% reported resistance to fosfomycin, and 2.16% reported resistance to azithromycin. Across these six regions, azithromycin and fosfomycin resistance is increasing, as is decreased susceptibility or resistance to ciprofloxacin, 3GCs, and 4GCs, especially among younger children and elderly people. Clinically prioritized antibiotic resistance also varies by region, serovar, and age group. S. Paratyphi A genotype 2.3.3 strains are mainly divided into 2 lineages distributed in Guangxi and Shanghai. Within the scope of this passive surveillance dataset, S. Typhi genotype 4.3.1.2.1 was identified as the earliest documented case among the collected isolates. Our retrospective and longitudinal genomic epidemiology study provides critical data for the formulation of treatment guidelines and policies for bloodstream infections and for the monitoring and control of antimicrobial resistance.

Humans↗

PubMed2026

Cationic porphyrin covalent organic framework reinforced hydroxypropyl methylcellulose films for photodynamic-photothermal sterilization and food preservation.

Microbial contamination in food necessitates effective antimicrobial packaging. While cellulose-based packaging materials suffer from limited antimicrobial efficacy, lack of active functionality, and susceptibility to inducing microbial resistance. To address these challenges, this study synthesized a cationic porphyrin-based covalent organic framework (Por-ICOF) as a multimodal photosensitizer. Por-ICOF was uniformly dispersed via non-covalent interaction within hydroxypropyl methylcellulose (HPMC), creating an HPMC/Por-ICOF composite film. This integration enhanced mechanical strength (increased by 26%), hydrophobicity (WCA 71°), and gas barrier properties (OP reduced by 42%, WVP reduced by 36%). Under visible light, the HPMC/Por ICOF film superior absorption generated reactive oxygen species (ROS) and photothermal effects, inactivating 99.2% of Escherichia coli and 99.95% of Staphylococcus aureus within 20 min. The composite film exhibited excellent biocompatibility and effectively extended the shelf life of strawberries. This cationic modification strategy for cellulose-based films offers a novel avenue for the design of high-performance antimicrobial food packaging materials.

Food Preservation↗

PubMed2026

Genomic and One Health insights into Vibrio parahaemolyticus from environmental, seafood and clinical sources.

Vibrio parahaemolyticus is a leading cause of seafood-borne gastroenteritis worldwide, with climate warming facilitating its spread to high-latitude areas. In this study, we analyzed 212 genomes of environmental and seafood-associated isolates collected from seven cities in Zhejiang Province, China (2019-2024), alongside 228 clinical genomes from public databases. The 212 isolates were assigned to 172 sequence types (STs), with ST490 being the most frequent (5/212, 2.36%). Forty-four serotypes were identified, dominated by OL3:KUT (12.68%). High ST and serotype diversity were observed across different sample types and sources, with median pairwise single nucleotide polymorphisms (SNPs) ranging from 57,431 to 58,378, indicating comparable genetic diversity across groups. All isolates carried tlh and T3SS1 but lacked tdh and T3SS2. Resistance rates against ampicillin and cefazolin were 54.72% (116/212) and 44.34% (94/212), respectively, with multidrug resistance (MDR) detected in nine isolates, predominantly from seafood (7/9). A total of 63 distinct antimicrobial resistance genes (ARGs) spanning seven classes were identified. Isolates from aquaculture farms and wet markets exhibited greater resistance category diversity and higher ARG carriage than those from coastal or riverine sites. In contrast, the 228 clinical isolates harbored only 25 ARGs across two classes, with a significantly lower proportion of isolates carrying multiple ARG classes (0.44% vs. 6.13%, P < 0.001). Human isolates formed tighter phylogenetic clusters, although a minority were closely related to environmental/foodborne strains. Overall, our findings demonstrate the genetic diversity and resistance potential of V. parahaemolyticus across environmental, seafood, and clinical sources, highlighting the importance of the One Health approach to comprehensive public health risk assessment.

Vibrio parahaemolyticus↗

PubMed2026

Efficacy of the NMIC-150 system in identifying extended-spectrum beta-lactamases in clinical isolates.

Extended-spectrum beta-lactamases (ESBLs) are significant contributors to the growing global crisis of antimicrobial resistance. This study evaluated the performance of the NMIC-150 System for susceptibility testing of third-generation cephalosporins (3GCs) and assessed whether ceftazidime-avibactam and aztreonam-avibactam could identify ESBL-producing carbapenem-resistant Enterobacterales (CREs). A total of 278 non-duplicate clinical isolates (Klebsiella pneumoniae, E. coli, and Proteus mirabilis) were analyzed. Antimicrobial susceptibility was determined using reference broth microdilution (BMD) and the NMIC-150 System. ESBL production was defined as an ≥eight-fold reduction in the minimum inhibitory concentration (MIC) of 3GCs in the presence of clavulanic acid, according to CLSI criteria. Whole-genome sequencing was performed to characterize ESBL and carbapenemase genes among 3GC-resistant isolates. A Random Forest model was used to predict ESBL-producing isolates based on MIC values. The NMIC-150 System demonstrated over 90% categorical and essential agreement with BMD for ceftazidime and ceftriaxone, along with robust predictive performance via Random Forest analysis. These findings suggest that the NMIC-150 System is a reliable platform for 3GC susceptibility testing and that an ≥eight-fold MIC reduction with ceftazidime-avibactam or aztreonam-avibactam may serve as a phenotypic indicator of ESBL production in CRE isolates. In conclusion, the NMIC-150 System shows potential for routine antimicrobial resistance surveillance and may facilitate the rapid identification of ESBL-producing CREs in clinical settings.

Microbial Sensitivity Tests↗

PubMed2026

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans↗

PubMed2026

From commensal to pathobiont: The emergence of virulence-enhanced Escherichia coli in China's food-animal systems - insights with future implications.

A fundamental shift in Escherichia coli epidemiology is being driven by convergence of virulence determinants and antimicrobial resistance within linked human-animal-environment systems. In China, the rapid growth of food-animal production, extensive antimicrobial use, and complex food networks are accelerating the emergence and dissemination of virulence-enhanced E. coli pathobionts. This review synthesizes recent epidemiological, genomics, and outbreak data to characterize China's evolving landscape of food-animal-associated E. coli. We highlight a significant shift from classical pathotypes to hybrid lineages that simultaneously carry virulence factors and last-resort antibiotic resistance determinants, including mcr-1, tet(X4), and blaNDM. These traits disseminate rapidly via plasmid-mediated horizontal gene transfer, facilitating rapid adaptation and enabling cross-sectoral One Health transmission. National surveillance, foodborne outbreak investigations, and whole-genome sequencing data show that food-animal reservoirs are active evolutionary niches that drive pathogen diversity and fitness, rather than serving merely as contamination sources. Whole-genome sequencing also pinpoints high-risk clones (e.g., ST394) and plasmid-mediated co-selection of virulence and AMR. The emergence of hybrid pathotypes (e.g., STEC/ETEC) and AMR-virulence co-selection challenges traditional classification and limits the effectiveness of conventional surveillance approaches. The 2017 colistin ban reduced mcr-1, yet ongoing resistance and emerging tet(X4) demand integrated surveillance. Collectively, these findings call for reconceptualizing E. coli as a dynamic genomic entity embedded within a unified ecological network. Addressing this threat requires an integrated One Health strategy including genomic surveillance, agricultural antimicrobial stewardship, and coordinated food-environment-clinical monitoring to prevent high-risk clone emergence and global spread.

Animals↗

PubMed2026

Emergence of an optrA-positive Enterococcus faecalis ST699 lineage in animal-derived foods in Beijing, China.

Enterococci from animal-derived foods are key reservoirs for antimicrobial resistance (AMR) in the food chain. However, comparative genomic studies investigating the distribution of the oxazolidinone resistance gene optrA among food- and human-derived Enterococci remain limited. This study assessed linezolid-resistant Enterococci from retail meat and healthy humans in Beijing, China (2023-2024). Among 87 isolates, E. faecalis and E. faecium predominated. Food-derived isolates showed broader resistance profiles than human isolates. Fourteen optrA-positive strains were identified, accounting for 92.9% of food isolates. optrA frequently co-localized with erm(A), ant(9)-Ia, and fexA on Tn554-family transposons, suggesting a potentially transferable multidrug resistance module. Notably, an optrA-positive E. faecalis ST699 clone was identified for the first time in Chinese retail meat. This clone formed a distinct lineage and carried a complete Tn554-optrA island. A representative ST699 isolate exhibited enhanced fitness and virulence potential in the Galleria mellonella model. These findings highlight animal-derived foods as important reservoirs of linezolid-resistant Enterococci and provide genomic evidence consistent with their role as potential sources of optrA-mediated resistance. The emergence of a multidrug-resistant E. faecalis ST699 clone with enhanced fitness characteristics underscores the need for continued surveillance of foodborne antimicrobial resistance within the One Health framework.

Enterococcus faecalis↗

PubMed2026

The Brazilian contribution to ant toxinology: challenges and perspectives.

Ant toxinology in Brazil is a small but growing field that has revealed wide biochemical diversity and clear potential for bioprospecting therapeutic molecules. This review compiles the Brazilian contribution, focusing on advances in the characterization of venoms from medically and ecologically important species of Dinoponera, Solenopsis, Paraponera, Pachycondyla, Neoponera, and Ectatomma. Brazilian groups applied omics approaches, including transcriptomics and proteomics, to resolve the composition of these venoms and identified peptide-rich arsenals with antimicrobial, antiparasitic, antitumor, and neuroactive activity. Studies of venom phenotypic plasticity showed ecological factors such as diet and seasonality shape venom composition. Two challenges persist: assigning function to still unidentified components and obtaining venom in the quantities that broad analysis requires. The near-term prospects are the rational design of peptide analogues with improved activity and continued bioprospecting of new species, which together position Brazil as a central contributor to ant toxinology.

Animals↗

PubMed2026

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4 = 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4 = 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗

PubMed2026

Alginate-based edible coating incorporating green tea extract for preserving postharvest quality and safety of white mushrooms (Agaricus bisporus).

This study aimed to evaluate the effects of a sodium alginate based edible coating incorporated with green tea extract (GTE) (Camellia sinensis) on the postharvest quality attributes and antimicrobial activity against Listeria monocytogenes in white mushrooms during refrigerated storage. The phenolic profile of GTE was characterized, and its minimum inhibitory concentration (MIC) against L. monocytogenes (1.6 mg/mL) was determined. Sodium alginate coatings, with (ALG-GTE) or without GTE (ALG) at MIC (1.6 mg/mL), were characterized (functional groups, solubility in water, moisture, thickness, water contact angle and color) for their chemical and physical properties. The effects of ALG-GTE coatings on quality parameters (firmness, weight loss, color, pH, sugars and organic acids), enzymatic activity [polyphenol oxidase (PPO), peroxidase (POD) and pectin methylesterase (PME)], antimicrobial activity against L. monocytogenes (5 log CFU/g), and surface characteristics (3D optical profilometry) were assessed in white mushrooms (Agaricus bisporus) during refrigerated storage (8 days, 4 ± 1 °C, 90-95% RH). The ALG-GTE coatings preserved sugar composition, particularly rhamnose, reduced organic acids accumulation and delayed weight and firmness loss, reduced color changes, and decreased PME activity in coated white mushrooms. L. monocytogenes counts decreased by 1.4 log CFU/g after 1 day, and no viable cells were detected after 2 days (< 1.5 log CFU/g) in ALG-GTE coated white mushrooms. In addition, ALG-GTE coated white mushrooms exhibited smoother surfaces than uncoated samples. These findings highlight the potential of ALG-GTE coatings as a sustainable alternative capable of improving the microbiological safety and delaying the postharvest changes in fresh mushrooms.

Agaricus↗

PubMed2026

Comparative genomic epidemiology of food- and patient-derived diarrheagenic Escherichia coli from sentinel surveillance in Southeast China.

Diarrheagenic Escherichia coli (DEC) remains an important foodborne pathogen, yet long-term comparative genomic surveillance data jointly characterizing food-derived and patient-derived isolates remain limited. This surveillance-based comparative study integrated antimicrobial susceptibility testing and whole-genome sequencing to characterize diarrheagenic Escherichia coli isolates recovered from food and patient sources in Lishui, Southeast China, during 2018-2025, with emphasis on occurrence, resistance profiles, genomic backgrounds, and plasmid replicon-associated features. Antimicrobial susceptibility testing was performed for 258 selected isolates, and whole-genome sequencing was conducted for a curated analytical subset of 204 isolates. The sequenced subset was used for diversity-oriented comparative genomic analysis rather than for unbiased prevalence estimation of the entire DEC collection. EAEC predominated in both sources, although food-associated occurrence was heterogeneous across categories, with the highest recovery rate observed in raw meat. Patient-derived isolates showed a broader overall resistance burden, whereas food-derived isolates retained substantial resistance to tetracycline, chloramphenicol, and florfenicol. Phylogenetic analysis showed partial overlap in genomic backgrounds between food-derived and patient-derived isolates, while representative resistance determinants displayed both broadly distributed and lineage-enriched patterns. Replicon-based plasmid profiling identified 42 plasmid types, including 12 detected in both sources, with IncF-related replicons predominating among these shared profiles. Several food-derived isolates carried multiple plasmid replicon types that were also observed in patient-derived isolates. Overall, food-derived and patient-derived DEC showed partial overlap in genomic backgrounds, resistance determinants, and replicon-defined plasmid profiles within this surveillance setting, while retaining source-associated heterogeneity. These findings should be interpreted as surveillance-based comparative evidence rather than as evidence of direct source attribution or transmission.

Humans↗

PubMed2026

Nasopharyngeal Carriage Rate, Risk Factors, and Co-Resistance Patterns of Methicillin-Resistant Staphylococcus aureus in Ethiopia: Systematic Review and Meta-Analysis.

Methicillin-resistant Staphylococcus aureus (MRSA) nasopharyngeal carriage is a major global health concern linked to severe infections and transmission. However, comprehensive evidence on the burden of MRSA carriage, antimicrobial resistance, and associated risk factors in Ethiopia remains limited. This study aimed to estimate pooled prevalence, resistance pattern, and determinants of nasopharyngeal MRSA carriage. PubMed, ScienceDirect, Scopus, Web of Science, Google Scholar, and gray literature were searched for cross-sectional studies published between January 2015 and December 2025. Two groups of reviewers screened studies based on predefined criteria. The risk of bias was assessed using the Joanna Briggs Institute tool. Pooled prevalence and resistance proportions were estimated using a random-effects model, and pooled odds ratios (ORs) were calculated using the Mantel-Haenszel method. Heterogeneity and publication bias were assessed, and a sensitivity analysis was conducted. A total of 1040 records were identified, and 20 studies (6869 participants) were included. The pooled carriage prevalence was 7.3% (95% CI, 5.0-10.8), with substantial heterogeneity (I2 = 95.5%). Resistance was highest to tetracycline (55.75%) and lowest to clindamycin (12.66%). Increased odds of carriage were associated with prior hospitalization (OR, 3.49) and antibiotic use (OR, 2.35). Inconsistent variable coding across included studies limited the inclusion of other potential risk factors. Evidence of publication bias was detected, suggesting that the pooled prevalence should be interpreted with appropriate caution. The findings indicate a considerable burden of MRSA and highlight the need for strengthened antimicrobial stewardship, improved surveillance, and targeted prevention efforts in higher-risk populations. This review was registered in PROSPERO (CRD420251047192).

Ethiopia↗

PubMed2026

Probiotic-derived extracellular vesicles as food-based nanocarriers: Mechanisms, functional applications, and future perspectives in food systems.

Probiotic-derived extracellular vesicles (PDEVs) are a promising type of postbiotic nanoparticle derived by fermentation of probiotics, and have gained growing interest as a potential application in food science and nutrition. These are lipid bilayer vesicles of nanoscale, which are naturally released by probiotic cells and contain a wide variety of bioactive molecules, such as proteins, nucleic acids, and metabolites. Moreover, PDEVs are highly stable, biocompatible, and can be easily engineered to have surfaces with high functionality, which makes them good candidates in functional engineering. In contrast to traditional live probiotics, PDEVs overcome the difficulties of preserving microbial viability during processing and storage, thus providing superior safety, stability, and predictable biological performance. This is a systematic review of the various functions of PDEVs in food systems. We conclude on the processes through which PDEVs control intestinal barrier integrity, alter gut microbiota composition, and alter host immune responses, and their potential to enhance gut health when added to functional foods. In addition to their health-promoting effects, PDEVs have shown significant potential as natural antimicrobial agents to preserve food and as effective nanocarriers of hydrophobic bioactive compounds, including fucoxanthin, to improve their stability, bioavailability, and targeted delivery. Moreover, PDEVs can be used as new regulators of microbial fermentation. However, it should be noted that a lot of the evidence that is available is still preliminary and the effectiveness of these applications in real food-processing and storage conditions has not been fully proven. Although they have potential, there are a number of challenges that still hinder the widespread use of PDEVs in the food industry. These involve the creation of scalable and cost-effective production processes, batch-to-batch consistency, vesicle stability in a variety of food matrices, and regulatory and safety considerations. Other emerging engineering approaches, such as surface functionalization and cargo loading, are also discussed in this review and could further increase the specificity, functionality, and application versatility of PDEVs in food systems. Moving forward, the incorporation of PDEVs into the next generation functional foods, novel food preservation methods, and customized nutrition plans should be prioritized in future studies. Further developments in these fields can make PDEVs useful platforms at the interface of food microbiology, nanotechnology, and human health.

Probiotics↗