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PubMed2026

Diagnostic performance of panfungal PCR on tissue specimens for the diagnosis of invasive fungal diseases: a systematic review and meta-analysis of the Fungal PCR Initiative (FPCRI).

UNLABELLED: Invasive fungal diseases are difficult to diagnose because of the limited sensitivity of culture. Panfungal PCR amplicon sequencing assays (targeting ribosomal RNA, such as 18S, 28S, ITS) are recommended for fungal identification in histopathology samples showing fungal elements. However, data describing its overall performance and consistency are lacking. This systematic literature review and meta-analysis assessed the performance of panfungal PCR on formalin-fixed paraffin-embedded (FFPE) and non-fixed (fresh or frozen) tissue samples. A systematic literature search was performed to include studies reporting the use of panfungal PCR for fungal identification in FFPE or non-fixed tissue samples. PCR sensitivity and specificity were assessed using the reference standard of histopathology showing fungal elements. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled estimates were obtained using random-effects meta-analysis. Twenty-eight studies were included. In FFPE samples (18 studies, 852 samples), sensitivity and specificity were 75.4% (95% confidence interval [CI], 59.2-86.6) and 93.5% (70.2-98.9), respectively. Sensitivity in non-fixed samples (13 studies, 207 samples) was 86.5% (74.7-93.3), while specificity could not be assessed (insufficient data). Comparative analyses showed a significantly higher sensitivity of panfungal PCR over culture (88.2%; 76-94.7 vs 52.2%; 39-65, P = 0.001). Sub-analyses could not demonstrate the superiority of one PCR target over another due to limited data. Panfungal PCR exhibited adequate sensitivity and good specificity in FFPE samples. Sensitivity was even higher in non-fixed samples and largely superior to culture. Nevertheless, large interstudy variability was observed, warranting interlaboratory studies to define the optimal PCR target and standardized protocols. IMPORTANCE: Invasive fungal diseases are difficult to diagnose because of the low sensitivity of culture. Panfungal PCRs are widely used for fungal identification in tissue specimens but suffer from heterogeneous procedures and performance. This meta-analysis shows an acceptable sensitivity (75.4% and 86.5% in fixed and non-fixed samples, respectively) and good specificity (93.5%) of panfungal PCR, supporting its use, not only on histopathology-positive fixed samples but also in non-fixed samples concomitantly with other diagnostic tools (cultures and fungal-specific PCRs if available). These results provide a strong basis for further standardization of panfungal PCR techniques via interlaboratory assays to assess reproducibility and optimize analytical protocols. CLINICAL TRIALS: This study is registered with PROSPERO as CRD42023461148.

Humans↗

PubMed2026

Regional genomic analysis of lineage distribution and transferable multidrug resistance among chicken-associated Salmonella Kentucky isolates in China.

Salmonella enterica serovar Kentucky is an important multidrug-resistant foodborne pathogen in the poultry meat supply chain. Although recent broader genomic studies have elucidated the population structure and epidemiological significance of major lineages in China (e.g., ST198 and ST314), the regional dynamics within local poultry supply chains remain insufficiently characterized. In this study, 31 chicken meat-derived isolates from Shanghai and 39 publicly available genomes from China were analyzed using antimicrobial susceptibility testing, whole-genome sequencing, phylogenetic analysis, conjugation experiments, and complete sequencing of representative plasmids. This enabled a systematic characterization of the molecular epidemiological features of the population and the mechanisms underlying resistance dissemination. Population genomic analysis revealed a lineage composition markedly different from the global epidemiological pattern: ST314 was the predominant sequence type among the Shanghai chicken-derived isolates (74.2%), whereas the internationally recognized high-risk clone ST198 accounted for only 25.8% of the local isolates. However, risk stratification analysis indicated that although ST198 was detected less frequently, it carried a significantly greater burden of acquired resistance genes and therefore represented a higher-risk resistant lineage. Functional and structural validation further elucidated the molecular basis of resistance dissemination within this high-risk lineage. Conjugation experiments confirmed the co-transfer of a multidrug resistance module carrying blaTEM-1 and blaCTX-M-267 to the recipient strain Escherichia coli J53. Complete plasmid analysis revealed that these two β-lactam resistance genes were co-localized on a 242-kb transferable plasmid flanked by Tn1331, Tn3, and multiple transposase-associated elements, thereby providing a structural basis for their horizontal transfer. This study provides important molecular epidemiological evidence for lineage-specific surveillance and risk-stratified control of resistant Salmonella in the poultry meat supply chain and further underscores the need for continuous monitoring of mobile genetic elements within a One Health framework.

Animals↗

PubMed2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals↗

PubMed2026

The gut microbiota-obesity axis in the pathogenesis and prognosis of breast cancer.

BACKGROUND: Breast cancer (BC) remains a major global health concern, accounting for 11.7% of all cancer cases and ranking as the second leading cause of female cancer-related deaths worldwide. Increasing evidence highlights the interplay between gut microbiota (GM) dysbiosis and obesity-associated metabolic dysfunction in BC progression. This review aims to elucidate the role of GM in obese patients with BC. METHODS: A systematic literature search was conducted in PubMed and Web of Science databases for publications from July 2015 to January 2025. Search terms combined BC, GM, obesity, dysbiosis, immunity, and microbiome. Article selection prioritized studies investigating microbial alterations in BC patients, mechanistic links between obesity and cancer progression, and GM-targeted interventions. Both original studies and authoritative reviews were included, supplemented by manual reference screening. DISCUSSION: Obesity may trigger systemic inflammation, altered adipokine secretion, and disrupted steroid hormone metabolism via gut-derived β-glucuronidase activity, thereby exacerbating BC occurrence and recurrence. GM dysbiosis-driven metabolites such as branched-chain amino acids (BCAAs) and short-chain fatty acids (SCFAs) can activate oncogenic signaling pathways and immunosuppressive myeloid-derived suppressor cells (MDSCs), fostering tumor immune evasion. Conversely, dietary interventions, probiotics, and fecal microbiota transplantation (FMT) can alleviate dysbiosis, strengthen gut barriers, and restore anti-tumor immunity, improving chemotherapy response and reducing recurrence. However, challenges persist in deciphering BC subtype-related microbial signatures and optimizing microbiota-targeted therapies. CONCLUSION: Future longitudinal studies are needed to clarify causal relationships, validate microbial biomarkers, and translate preclinical findings into clinical applications. Addressing the gut-breast axis may offer transformative potential for precision oncology in obesity-driven BC.

Humans↗

PubMed2026

Exploratory proteomic and metabolomic profiling of pleural effusions identifies histone H4 and alanine as promising complementary markers for pleural tuberculosis.

The diagnosis of pleural tuberculosis (Pl-TB) remains challenging. Histopathological analysis and pathogen detection in pleural biopsies are informative but limited. We investigated differentially expressed proteins and metabolites in pleural effusions from patients with Pl-TB, malignancies, and other pathologies. A proteomic analysis of pooled pleural effusions identified 45 proteins exclusively detected or upregulated in Pl-TB samples, many linked to infectious processes. Conversely, 18 proteins were uniquely found or upregulated in malignant pleural effusions, mainly associated with detoxification and hemostasis. To validate these findings, we employed targeted proteomics in individual samples. Eight proteins were validated: S100-A9, histone H4, insulin-like growth factor-binding protein 2, fibrinogen beta chain, ficolin-3, immunoglobulin heavy constant alpha 1, sulfhydryl oxidase 1, and histidine-rich glycoprotein. Additionally, NMR-based metabolomics identified 13 metabolites with differential abundance between Pl-TB and non-TB samples. Notably, N-acetyl-glycoprotein and the branched-chain amino acids, alanine and lysine differed between groups. Proteomic and metabolomic analyses revealed distinct molecular profiles between Pl-TB and non-TB patients, despite intra-group variability. To address this, we applied classification models. Histone H4 and alanine consistently emerged as discriminative features. Overall, this study provides novel insights into the molecular landscape of Pl-TB. The combined quantification of proteins and metabolites may improve differential diagnosis, although should be further validated in larger, independent cohorts before clinical application.

Humans↗

PubMed2026

Integrated transcriptomic and metabolomic analyses provide new insights into the response of black rockfish (Sebastes schlegelii) larvae to temperature fluctuations.

Sebastes schlegelii usually encounter elevated and fluctuating water temperatures near its upper thermal limit in summer, yet the hepatic responses of larvae to repeated temperature fluctuation regimes remain unclear. To address this question, S. schlegelii larvae were exposed for 8 days to four thermal regimes: constant 18 °C (CT), constant 28 °C (HT), intermittent cooling from 18 to 8 °C followed by recovery to 18 °C (FL), and intermittent warming from 18 to 28 °C followed by recovery to 18 °C (FH). Survival rate was evaluated, and integrated liver transcriptomic and metabolomic analyses were performed. Final survival rates were 96.67% in the CT group, 97.78% in the FL group, and 77.78% in the FH group. Survival rate in the HT group (38.89%) was significantly lower than that in the other three groups (P < 0.05). HTvsCT, FLvsCT, FHvsCT, and FHvsHT comparisons identified 2598, 1207, 622, and 2404 differentially expressed genes and 627, 606, 690, and 610 differential metabolites, respectively. KEGG enrichment analyses of DEGs and SDMs in HTvsCT highlighted HSP-mediated proteostasis, endoplasmic-reticulum protein processing, branched-chain and sulfur amino acid metabolism, glutathione metabolism, and central carbon metabolism, with upregulated hsp90aa1, bckdha, gclc, and pfkp and reduced levels of branched-chain amino acids and methionine. Compared with HT, FH showed attenuated disturbances in proteostasis, amino acid and redox regulation, and central carbon metabolism, together with recovery-associated glycerophospholipid turnover. FL primarily induced polyunsaturated fatty acid (PUFA)-related membrane lipid remodeling. These findings indicate that hepatic responses differed between continuous high-temperature exposure and temperature fluctuations and between fluctuation regimes.

Animals↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Electron shuttles facilitate methane-dependent arsenate reduction in paddy soils.

Methane-dependent arsenate reduction (M-AsR) occurs widely in paddy soils and can substantially enhance arsenic mobilization, posing potential ecological risks. However, the role of electron shuttles in this process remains poorly understood. In this study, we investigated the influence of anthraquinone-2,6-disulfonate (AQDS) on M-AsR in paddy soils. Fourteen-day incubation showed that 1 mmol/L AQDS facilitated 50.88 % of arsenate reduction and 31.31 % of methane oxidation. Quantitative polymerase chain reaction analysis revealed that AQDS significantly increased the abundance of functional genes associated with arsenate reduction (arrA, arsC) and anaerobic methane oxidation (mcrA) (P < 0.05). Microbial community analysis revealed that AQDS addition enriched Cloacibacterium, Sphingorhabdus, and Methylocystis, while decreasing the relative abundance of Methylobacter and Methylomonas. These findings indicate that electron shuttles facilitate M-AsR by modulating functional microbial populations, providing valuable insights into arsenic biogeochemistry and the coupled cycling of methane and arsenic in paddy soils.

Methane↗

PubMed2026

Carboxyl group number and acidity of organic acids regulate structural reorganization and low glycemic index in cassava pyrodextrins via molecular interactions.

Transforming high-glycemic cassava starch into functional dietary fiber via pyrodextrinization is a promising way to valorize tuber crops, yet the molecular mechanisms catalyzed by organic acids with different carboxyl numbers and acidity remain unclear. This study investigates how carboxyl number and acidity of acetic acid (AA), tartaric acid (TA), and citric acid (CA) affect structural reorganization and low glycemic properties of cassava pyrodextrins. Compared with AA, TA, and CA with stronger acidity and more carboxyl groups promoted more extensive hydrolysis, transglycosylation, repolymerization, and esterification. These changes increased indigestible glycosidic linkages and the branching degree, while reducing molecular weight. Molecular docking confirmed stronger hydrogen-bonding interactions between TA/CA and starch chains. Furthermore, TA- and CA-catalyzed pyrodextrins exhibited superior anti-digestive properties with resistant starch up to 54.26% and an estimated glycemic index as low as 42.46, highlighting the critical role of carboxyl numbers and acidities in modulating the functionality of pyrodextrins.

Manihot↗

PubMed2026

Association Between Ticagrelor and Glucose Homeostasis Regulation: Insights from Genetic and Transcriptomic Analyses.

Emerging evidence has demonstrated the additional therapeutic benefits of ticagrelor in acute coronary syndrome (ACS) patients with diabetes. However, the underlying mechanisms of this association remain elusive. Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data on ticagrelor, plasma proteomics and type 2 diabetes was employed to identify causal mediator proteins. RNA sequencing (RNA-seq) of ticagrelor-treated HepG2 cells revealed the molecular pathways regulating glucose metabolism. Genetically proxied ticagrelor was significantly associated with a reduced risk of diabetes (OR = 0.859, 95% CI: 0.783-0.934, P = 7.98E-05), and 24.41% of this effect was mediated by upregulation of BDH2 protein. In vitro experiments confirmed the enhanced effect of ticagrelor on glucose consumption. Transcriptome analysis revealed that mitochondrial respiratory chain transfer and oxidative phosphorylation (OXPHOS) were significantly enriched, and genes related to ATP biosynthesis were significantly upregulated. These findings highlight the non-platelet function of ticagrelor in maintaining glucose homeostasis, providing insights into potential drug repurposing in the future.

Humans↗

PubMed2026

Structural and physicochemical characterisation of branched dextrans produced by an active α-(1→2) branching sucrase from Apilactobacillus kunkeei PDER37.

Recently, branching sucrases encoded in the genomes of certain Lactic Acid Bacteria (LAB) strains have become novel enzymes to obtain branched α-glucans. In this study an active α-(1 → 2) branching sucrase from Apilactobacillus kunkeei PDER37 was expressed, characterised and distinct branched dextrans was obtained with reactions under different sucrose: dextran ratio. Structural characterisation by 1H and 13C NMR analysis demonstrated the branching of the dextran with (1 → 2)-linked α-d-glucose units with no alteration in the final structure depending on sucrose: dextran ratio (D0) but this ratio was effective for the determination of the molecular weights of the branched dextrans (D1, D2 and D3). FTIR analysis further supported the dextran structures and suggested the higher accumulation of the α-Glc units in the branched dextrans. Thermal characterisation of the branched dextrans obtained by TGA and DSC analysis suggested the increased hygroscopicity of the branching units. Both SEM and AFM analysis demonstrated more porous chain like structures in the branched dextrans. This study provides valuable information on the role of active α-(1 → 2) branching sucrase (BS37) for the production of branched dextrans with potential increased physicochemical status applicable for food and other industries.

Dextrans↗

PubMed2026

Design of an innovative framework based hybrid catalyst for simultaneous and sensitive monitoring of food additive and preservative of vanillin and nitrite in direct samples.

As vanillin (VAN) and nitrite (NIT) contamination in the food chain poses substantial threats to environmental and public health, rapid and portable detection is essential. The present study presents the first electrochemical sensor report based on a hybrid composite of Ni-TPA-MOF and MoS2/Co3O4. The oxidation of VAN and NIT exhibited sharp peaks and less over-potential on Ni-TPA-MOF/MoS2/Co3O4/GCE than on control electrode surfaces. On modified composite electrode surfaces, pH and scan rate were investigated for VAN and NIT. Further, the oxidation current exhibited high linearity at VAN and NIT concentrations of 5 nM-1000 μM and 3 nM-1250 μM, with detection limits of 0.102 nM and 0.073 nM (S/N = 3). We also applied anti-interfering ability (five/ten-fold excess of co-interfering compounds) and practical tests to various food-based real samples, with high recoveries of 98.85-102.41%. This study highlights the catalytic properties of Ni-TPA-MOF/MoS2/Co3O4 and demonstrates the sensor as a promising tool for food safety.

Benzaldehydes↗

PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗

PubMed2026

Prevalence and Factors Associated with Receiving a Prescription for a Direct Oral Anticoagulant Among Patients with Atrial Fibrillation on Hospice Admission.

Atrial fibrillation (AF) is prevalent in hospice care, but anticoagulation decisions in this population are not well understood. In this cross-sectional study, we described the prevalence and characteristics associated with direct oral anticoagulant (DOAC) prescription on hospice admission. We used electronic health data from adult decedents with AF in a large, for-profit hospice chain in the United States between January 1, 2017 and December 31, 2019. We used multivariable logistic regression with results reported as adjusted odds ratios (AORs) and 95% confidence intervals (CIs). Among 13,233 decedents, mean (standard deviation [SD]) age was 84.2 (9.9) years, 53.6% were female, 65.1% were White, and 56.1% were referred to hospice from a hospital. Mean (SD) CHA2DS2-VASc score were 3.8 (1.4) for males and 4.8 (1.3) for females, and mean (SD) HAS-BLED score was 2.2 (1.0). Overall, 8% of patients received a DOAC prescription on hospice admission. Characteristics associated with receiving a DOAC prescription included PPS scores of ≥ 20% (compared to scores < 20%), and receiving hospice care at home, nursing home, assisted living facility, or residential care home (compared to inpatient hospice). Further studies about the risks and benefits of DOAC use are needed to optimize decision-making in this population.

DOAC↗

PubMed2026

Are there any common effects in preclinical models of micro- and nanoplastic (MNP) exposure? A systematic review.

Micro- and nanoplastics (MNPs) are emerging contaminants detected in food sources and the marine food chain, raising concerns about human health. Although no causal relationship has been established between MNP exposure and specific diseases, growing evidence suggests adverse developmental, behavioral, cognitive and biochemical effects. This systematic review synthesized evidence from common preclinical neurotoxicology models, including C. elegans, D. rerio, D. melanogaster, in vitro systems and rodents, to identify convergent developmental, behavioral and biochemical outcomes. The protocol was preregistered in OSF, followed PRISMA-P guidelines, applied PICOS criteria, and assessed methodological quality using the European Commission's ToxRTool. Overall, 185 studies were included. Consistent findings showed impaired survival and disrupted development across all models. Behavioral alterations affecting anxiety, memory, learning, sociability and locomotor activity were also consistently reported. In addition, numerous studies identified disruptions in the serotonergic (5-HT) system, including changes in neurotransmitter levels, transporters and metabolic enzymes. Despite methodological heterogeneity, these findings indicate that MNP exposure produces reproducible neurodevelopmental and neurochemical alterations across experimental models. Future studies should improve methodological harmonization, strengthen cross-model comparability and identify robust biomarkers and key mechanisms underlying MNP-induced neurotoxicity, facilitating translation to human health risk assessment frameworks.

Animals↗

PubMed2026

Mechanistic Insights Into the Association Between Gut Microbiota Diversity and Atherosclerosis, Acute Coronary Syndrome, and Peripheral Arterial Disease Progression.

BACKGROUND: The gut microbiome has emerged as a potential contributor to cardiovascular diseases (CVDs), including atherosclerosis, acute coronary syndrome (ACS), and peripheral arterial disease (PAD). While observational studies link dysbiosis to CVD, causal relationships remain uncertain. METHODS: This narrative review synthesizes evidence from human observational studies, clinical interventions, and experimental models to distinguish association from mechanistic plausibility and clinical causality. Literature was searched through July 2026 in PubMed/MEDLINE, Web of Science, and Scopus. RESULTS: Microbial metabolites-including trimethylamine N-oxide (TMAO), short-chain fatty acids (SCFAs), bile acids, and lipopolysaccharide (LPS)-modulate endothelial function, immune cell programming, platelet activity, and plaque stability through receptor-mediated signaling and epigenetic regulation. SCFAs demonstrate potentially protective effects via GPCR and HDAC pathways, while TMAO is associated with atherothrombotic risk. However, much mechanistic evidence derives from preclinical studies. Heterogeneity from diet, geography, host characteristics, renal function, and medications substantially influences microbiota-CVD associations. CONCLUSION: The gut-vascular connection is biologically plausible, but definitive clinical causality remains unproven. Microbiome-directed therapies (dietary modulation, pre/pro/synbiotics, targeted metabolite inhibition) are investigational. Prospective, standardized, adequately powered human studies with clinically meaningful outcomes are essential before routine cardiovascular application.

Gastrointestinal Microbiome↗

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

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗