Scandinavian cardiovascular journal : SCJBjørn Edvard Seim, Yusuf Khan, Margrethe Flesvig Holt, Aleksandra Ratajska, Annika Michelsen, Monica Myklebust Ringseth, Runar Lundblad, Bente Halvorsen, Kirst…
Objectives. Thoracic aortic aneurysms (TAAs) are often found in younger individuals and approximately 20% may be associated with heritable thoracic aortic disease (HTAD). There are some data on genomic biomarkers reflecting inflammation and extracellular matrix remodelling in HTAD. However, data that accurately reflect the corresponding protein changes are scarce. Our aim was to quantify proteins by using targeted proteomics in HTAD patients versus healthy controls, to better understand the underlying pathophysiology. Methods. Patients with Loeys-Dietz syndrome (LDS, n = 8), Marfan syndrome (MFS, n = 11), and familial TAA 6, i.e. actin alpha 2 (ACTA2, n = 7) pathogenic variants were recruited at our outpatient clinic. For comparison, blood samples were drawn from 16 healthy controls. Plasma samples were analysed by targeted proteome analysis of 276 proteins using immunoaffinity proteomics. Results. Whereas oncostatin M and pentraxin 3 levels appeared generally higher in HTAD patients, after adjusting for several confounders, significantly higher levels for these markers as well as TNF receptor superfamily member 9 (TNFRSF9), granulysin (GNLY), CD5, vasorin and glycoprotein 1b-α (GP1BA) were only observed in LDS patients compared to healthy controls. Levels of TNFRSF9, GNLY, GP1BA and CD5 correlated positively with Th17 and platelet counts. Conclusions. This discovery study suggests that LDS could represent a particular inflammatory subgroup of HTAD patients potentially reflecting the involvement of Th17 and platelet related mechanisms in the progression of TAA. Larger studies are needed to evaluate if the identified proteins could be used as biomarkers in these patients.
Gut microbesEmily N Yeo, Ashley W Scadden, Zachary T Caterer, Kristen J Sutton, Iain R Konigsberg, Joanne B Cole, Elizabeth M Litkowski, Zhaoxing Pan, Catherine A Lozupone…
Obesity is a multifactorial condition, and there is wide heterogeneity in responses to weight loss interventions. Although it remains challenging, modeling responses to weight loss interventions can help tailor treatments, increase weight loss success, or improve our understanding of underlying pathophysiology. We leveraged multi-omic (genetics; gut microbiota: taxonomy, inferred gene pathways and metabolite dynamics; blood metabolomics) and clinical data (e.g., lipids, blood glucose) from a 12-month behavioral weight loss trial of adults (n = 150) with overweight/obesity, to forecast longitudinal body mass index (BMI) and BMI change (ΔBMI) using Mixed Effects Random Forests (MERF) and GLMM-Lasso. Across modeling approaches and outcomes, routinely available clinical variables and blood metabolomics consistently improved prediction over basic demographics, and metabolomics added value beyond clinical information. Across models, the combined omic risk score most improved models of longitudinal BMI trajectories, explaining 20.5-26.0% marginal variance (R2m), whereas metabolomic risk scores most improved BMI change prediction (R2m = 52.9-59.3%). Gut microbial taxonomy and inferred gene pathways offered modest but significant gains for some models and outcomes, while metabolite dynamics consistently failed to enhance performance. The most important features in the models included insulin, glycoprotein acetyls, lipoprotein sizes, and certain amino acids, aligning with known inflammatory and metabolic mechanisms. These findings support that select blood-based biomarkers correlate with individual responses to weight loss efforts.
HLA class I presentation of pathogen-derived peptides is essential for CD8+ T-cell recognition of Toxoplasma gondii. While in vitro MHC ligands have been documented, the in vivo ligandome during infection progression remains poorly characterized. Here, we employed an MS-based immunopeptidomics approach to directly profile the T. gondii immunopeptidome presented by HLA-A *02:01 in transgenic mice. By employing a hierarchical discovery funnel, our analysis identified a comprehensive repertoire of 3,744 unique T. gondii-derived peptides. Subsequent filtering for canonical 8-12mers, matching the typical binding length for HLA-A *02:01 ligands, established a high-confidence foundational ligandome of 3,433 peptides. Source protein analysis revealed that these peptides originate from diverse parasite proteins, including a substantial proportion of previously uncharacterized hypothetical proteins. Notably, specific ligands were consistently detected across both acute and chronic stages, suggesting stable MHC-I presentation throughout the infection cycle. By integrating in silico predictions with experimental validation, we prioritized 73 high-affinity candidates, five of which exhibited robust HLA-A *02:01 binding capacity in vitro and in vivo. Specifically, we identified a novel ligand derived from glycogen synthase (PGS) and determined its co-crystal structure with HLA-A *02:01, revealing favorable binding architecture. Overall, these findings expand the known HLA-A *02:01-restricted ligand landscape of T. gondii and provide a high-priority list of candidates for future functional validation of CD8+ T-cell immunogenicity.
Parasitology internationalChao Jiang, Yang Zhang, Zhiqun Wang, Xuguang Sun
Acanthamoeba keratitis (AK) is a severe, vision-threatening protozoan infection with a rising global incidence linked to contact lens use, necessitating robust genotyping to clarify its epidemiology and pathogenesis. This study analyzed the genotype distribution of 102 Acanthamoeba isolates collected from clinical settings in China between 1991 and 2014, comprising 100 isolates from corneal scrapings of clinically diagnosed AK patients, one from soil, and one from a patient's contact lens solution. Genetic analysis was conducted via amplification and sequencing of the 18S rRNA hypervariable DF3 region, followed by phylogenetic reconstruction and sequence identity assessment against reference clades. Twenty-eight distinct DF3 sequence types were identified, with genotype T4 demonstrating overwhelming dominance (99.0%; 101/102). Three novel T4 variants (T4/42-T4/44) were discovered, expanding the known diversity of this pathogenic lineage. Notably, T4/31 and T4/41 together accounted for 36% of clinical isolates, suggesting regionally endemic, infection-enriched variants. Only one isolate belonged to the rarely reported T11 genotype in China. Molecular source tracing confirmed two transmission chains: one linking a patient's corneal infection to their contact lens solution (both T4/6 variant), and another linking infection to periresidential soil (both T4/25 variant). These findings confirm the near-exclusive dominance of T4 among Chinese AK cases, identify prevalent local T4 variants, and demonstrate the utility of high-resolution DF3 genotyping for transmission tracing and disease control.
Microbiological researchJie Wang, Changying Guo, Xiaojian Pu
Climate-driven lake expansion across the Qinghai-Tibet Plateau induces profound edaphic shifts, but how these abiotic changes shape soil microbial assembly remains unclear. Soil metagenomics and metabolomics were integrated along a 0-10 km spatial gradient at Gahai. Redundancy analysis (RDA) identified moisture (NDWI) and salinity (SI) as primary ecosystem drivers. Structural equation modeling (SEM) provided exploratory evidence consistent with a mediation pathway (P = 0.64, CFI = 1, RMSEA = 0), in which environmental factors potentially influenced microbial community structure indirectly, via reshaping the soil metabolome rather than through a direct path. Moisture availability exerted a strong negative effect on soil metabolic profiles (λ = -0.93), leading to a pronounced negative correlation between the metabolome and microbial community (λ= -0.97). Multi-omics integration attributed this pattern to stress-induced accumulation of defensive metabolites, including Feruloylputrescine and 3-Methylthiopropyl-desulfoglucosinolate. These compounds showed significant negative correlations with dominant genera (e.g., Candidatus Kryptobacter). This "metabolic filtering" is hypothesized to selectively limit the presence of non-adapted taxa based solely on correlational SEM and network analyses, supporting our tentative hypothesis that increasing environmental stress may promote a transition from competitive interactions toward patterns consistent with stronger deterministic filtering. Our exploratory findings suggest that the soil metabolome acts as a functional interface mediating microbial adaptation and strategic resource allocation to lake expansion in this high-altitude saline-alkali system. However, due to regional heterogeneity, these patterns provide a theoretical baseline for plateau lake ecosystems and should be applied with caution to broader geographic areas.
VirulenceXia Li, Xin' Ao Ma, Xiaoyu Wang, Qingjun Li, Qi Yuan, Jiahua Wang, He Bai, Yong Liu, Feipeng Zhao
Porcine sapelovirus (PSV) is increasingly detected in swine enteric disease complexes, but its evolutionary dynamics and transmission patterns remain insufficiently characterized. In this study, we analyzed 327 fecal samples collected from diarrheic piglets between 2015 and 2022 and identified persistent PSV detection in northeastern China. Because PSV was detected in the context of mixed enteric viral infections in this dataset, our data do not establish PSV as an independent causative agent of diarrhea. Comparative whole-genome and evolutionary analyses of globally circulating PSV strains revealed substantial genetic diversity, with higher apparent short-term substitution-rate estimates observed in the African and Japanese datasets. In China, inter-strain genetic recombination appeared to represent an additional driver of viral diversification. Temporal evolutionary analyses indicated a dynamic and complex evolutionary landscape within China. Phylogeographic reconstruction identified multiple putative transmission nodes within the currently available genome dataset, suggesting broad geographic dissemination of PSV lineages but not definitive source-sink relationships. These findings enhance our understanding of PSV genomic epidemiology and provide useful information for molecular surveillance of PSV and other diarrhea-associated viruses in swine populations.
He Xue Ming Mu Tablets (HXMMT) are traditional Chinese medicine formulations used in clinical practice for the treatment of diabetic retinopathy. The primary purpose of this article is to illuminate the potential mechanistic pathways underlying its therapeutic efficacy in non-proliferative diabetic retinopathy. UHPLC/QE-MS was used for plasma metabolomics analysis of 10 HXMMT-treated NPDR patients, 10 untreated NPDR patients, and 10 healthy controls. To identify differential metabolites, principal component analysis (PCA) for visualizing metabolic variation and hierarchical clustering for grouping samples by metabolic profiles, were combined with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to investigate related biological pathways. Intraocular pressure (IOP), best-corrected visual acuity (BCVA), central foveal thickness (CFT), and inflammatory/angiogenic markers (IL-6, TNF-α, VEGF, Ang-2) were assessed, with correlations analyzed between altered metabolites and clinical indices. HXMMT significantly improved macular edema, reduced fundus hemorrhage, and attenuated retinal inflammation (P < 0.05). Metabolomic profiling identified a total of 813 plasma metabolites, and 283 metabolites exhibited distinct expression patterns that effectively discriminated NPDR patients from healthy controls, while 39 metabolites were found to distinguish between untreated NPDR patients and those who received HXMMT treatment. Consequently, 12 key metabolites showed significant covariance with clinical parameters of NPDR (P < 0.05), suggesting their potential role as critical mediators in the pharmacodynamic mechanism of HXMMT. HXMMT exerts therapeutic effects on NPDR by targeting 12 plasma metabolites, particularly via the glycerophospholipid metabolic axis, providing a mechanistic basis for its clinical use.
BACKGROUND: Tuberculosis (TB) continues to be a major cause of global morbidity and mortality, particularly in low- and middle-income countries. A persistent challenge in TB control is the inability of current immunodiagnostic tools to effectively differentiate active TB from latent tuberculosis infection (LTBI). This diagnostic limitation hampers timely case detection and appropriate treatment, thereby sustaining community transmission. OBJECTIVES: This study aimed to identify and validate serum metabolomic biomarkers capable of distinguishing active TB from LTBI using high-resolution 1H Nuclear Magnetic Resonance (NMR) spectroscopy coupled with multivariate statistical and machine-learning analyses in an Indian cohort. METHODS: Serum samples from 52 microbiologically confirmed active TB patients and 51 individuals with LTBI were analyzed using an 800 MHz NMR spectrometer. Spectral data underwent standard pre-processing, followed by Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Random Forest (RF) classification. Diagnostic performance was evaluated using univariate statistics and Receiver Operating Characteristic (ROC) curve analysis. RESULTS: Distinct metabolic differences were observed between TB and LTBI, primarily involving lipid/lipoprotein, energy, and amino acid metabolism. PCA and PLS-DA demonstrated clear group separation (accuracy >90%, Q2 = 0.596), identifying VLDL/LDL, polyunsaturated fatty acids (PUFA), lactate, N-acetyl glycoprotein (NAG), and glucose as key discriminatory metabolites. RF and ROC analyses demonstrated consistent discriminatory performance of these markers within the study cohort (AUC up to 0.934). CONCLUSIONS: Serum metabolomics using high-resolution 1H NMR offers a promising, non-invasive approach to distinguish active TB from LTBI. The identified metabolic signatures, particularly those related to lipid and energy metabolism, may provide a foundation for future translational development, subject to validation in independent cohorts.
Cercarial dermatitis is an important occupational health problem among rice farmers in Assam and other parts of India. We surveyed 1657 paddy farmers from sixteen villages across four districts of Assam, Northeast India, to determine the prevalence of cercarial dermatitis. Of these, 555 (33.5%) reported dermatitis during the preceding three months, and a subset of affected farmers from Barpeta district showed a high proportion of moderate-to-severe disease, often complicated by secondary bacterial infection. Snail surveys were conducted in thirteen villages across eight districts. Examination of 13,309 freshwater snails representing six species identified Indoplanorbis exustus as the only intermediate host shedding Schistosome cercariae, with an infection prevalence of 6.3% among I. exustus. Experimental infections in mice yielded adult worms that were used for morphological, molecular, immunological, and proteomic studies. Molecular identification based on partial 28S rDNA sequencing confirmed the Assamese isolates as Schistosoma spindale, and phylogenetic analysis placed them firmly within the S. spindale clade together with reference sequences from Nepal and Sri Lanka. SDS-PAGE and immunoblotting identified four dominant immunoreactive antigens of approximately 25, 38, 60, and 100 kDa. Two-dimensional PAGE coupled with MALDI-TOF/TOF MS identified several conserved proteins, including paramyosin, tropomyosin, actin, and heat shock protein 70, based on best database matches. ELISA developed using adult worm antigen showed high diagnostic performance (96% sensitivity and 100% specificity) and outperformed the cercarial antigen-based ELISA. This integrated epidemiological, malacological, molecular, proteomic, and immunological investigation provides comprehensive insight into S. spindale the causative agent of cercarial dermatitis in Assam. The findings highlight the need to recognize cercarial dermatitis as a neglected occupational and zoonotic disease within a One Health framework.
Leaf spot disease caused by species of the genus Curvularia is an emerging constraint to maize production under warm agro-climatic conditions. However, integrated analyses linking taxonomy, virulence determinants, toxin production, and metabolomic diversity of regional Curvularia populations remain limited. In this study, fifteen Curvularia isolates associated with maize leaf spot in southern Rajasthan, India, were characterized using a polyphasic approach combining morphology, multilocus phylogeny (ITS, GAPDH, TEF1), pathogenicity assays, extracellular enzyme profiling, quantitative HPLC, and LC-HRMS-based metabolomics. All isolates were pathogenic, but virulence varied significantly (p ≤ 0.05). Isolates MZ4, MZ9, and MZ11 exhibited high Disease Severity Index (DSI > 75%) and produced significantly greater extracellular enzyme activities (amylase, cellulase, lipase, and pectinase). Quantitative HPLC confirmed the presence of methyl-5-hydroxyfuran-2-carboxylate (M5HF2C) in all isolates, with the highest concentrations recorded in the most virulent strains. LC-HRMS profiling of these isolates revealed diverse and largely isolate-specific secondary metabolite signatures, with limited overlap among them. Principal component analysis explained 80.1% of total variance and clearly associated virulence with toxin production and enzymatic activity. Overall, this integrative study demonstrates a strong link between phylogenetic identity, metabolic specialization, and pathogenic variability in Curvularia spp., providing mechanistic insight into maize leaf spot development and supporting targeted disease management strategies.
Journal of pharmaceutical and biomedical analysisMeng-Hua Pan, Shu-Fan Liu, Jia-Lin Yu, Yong-Jian Ai, Fei Li
Curculigo rhizome (CR) a phenolic acid-rich plant, is widely utilized as a raw material for health products, traditional Chinese medicine (TCM) preparations, and as a flavoring agent in the food industry. In the present study, a comprehensive multi-technique approach combining UPLC-Q-TOF-MS/MS, GC-MS, intelligent sensory technology (electronic nose and electronic tongue), and metabolic analysis was employed to investigate the effects of yellow rice wine processing on the chemical composition, bioactive metabolic properties, and sensory characteristics of CR. Wine-processed Curculigo rhizome (WCR) exhibited significantly decreased L* and b* values alongside reduced sweetness, whereas the a* value and total color difference (Eab*) markedly increased compared to raw Curculigo rhizome (RCR). Notably, enhanced sensory responses to nitrogen-containing compounds, particularly amines, were observed following wine processing. Metabolic assessments across bacterial, cellular, and mouse models demonstrated improved bioactivity in WCR. Non-targeted metabolomics analysis identified 84 compounds in total, with 15 differential metabolites (VIP > 1, fold change ≥ 1, P < 0.05) discriminating RCR and WCR. Post-processing reductions were observed for orcinol, palmitic acid, and oleic acid, while orcinol glucoside (SAK), orcinol gentiobioside (ANA), and curculigoside B showed elevated levels. Pearson correlation analysis revealed that downregulated compounds were negatively correlated with a* values, bioactivity-related metabolic parameters, and electronic nose sensors (EN1-EN18) as well as electronic tongue sensors (ET1, ET4, ET7, ET10, ET13); conversely, upregulated compounds displayed positive correlations with these indices. These findings elucidate the critical role of yellow rice wine processing in modulating the sensory attributes, bioactivity profile, and chemical composition of CR, thereby providing scientific foundations for establishing standardized processing protocols and offering practical guidance for industrial-scale production.
Annals of diagnostic pathologyYan Wang, Yeli Yao, Haiyan Shi, Weiguo Lu, Bingjian Lu
HPV-associated adenocarcinoma in situ (AIS) is the main precursor to endocervical adenocarcinoma. The differential immunoprofiles remain poorly characterized among HPV-associated AIS variants (such as usual-type and stratified mucin-producing intraepithelial lesion [SMILE]). This study aimed to investigate the expression of stem cell markers (SOX2 and SOX17) in 159 HPV-associated AIS (124 usual-type, 11 with intestinal differentiation, 24 SMILE) by immunohistochemistry. Compared to normal endocervical glands, AIS exhibited significantly increased expression of SOX2 (69.2% vs. 0, p < 0.001), but decreased SOX17 (40.9% vs. 98.1%, p < 0.001). Positive SOX2 and negative SOX17 had a specificity of 100% and 98.1% in the differential diagnosis of AIS from normal glands, respectively. SOX2 expression was significantly higher in SMILE (22/24, 91.7%) than in usual-type AIS (80/124, 64.5%, p = 0.030). In contrast, SOX17 expression was absent in all SMILE (0/24) and most AIS with intestinal differentiation (1/11, 9.1%), but was significantly higher in usual-type AIS (64/124, 51.6%, p < 0.001). The SOX2/SOX17 composite profile may aid in the diagnosis of AIS and its variants. The SOX2-positive (overexpression) /SOX17-negative profile suggest a divergent pathway with squamous differentiation potential in SMILE. These findings provide novel insights into the cellular histogenesis of AIS variants.
Annals of medicineZizhen Zhou, Qiwei Liu, Shuangshuang Ma, Anke Shi, Yuzhi Tao, Tianpeng Hu, Shengtao Yan, Yinong Chen, Xiaofan Ji, Lu Sun, Hong Zhang, Wanlu Song, Zhu Zhang, Pe…
BACKGROUND: COVID-19 has been closely associated with coagulation abnormalities. However, existing biomarkers, including D-dimer and fibrin degradation products (FDP), exhibit limited accuracy in stratifying disease severity and predicting long-term clinical outcomes. OBJECTIVES: This study aimed to use proteomic analysis to identify plasma biomarkers associated with COVID-19 severity and prognosis, and validate their predictive utility for mortality and thromboembolic complications. METHODS: Plasma proteomic profiles were analyzed across three COVID-19 severity classes. Differential expression analysis and functional analysis were performed. Clustering analysis was used to identify proteins correlated with disease severity. Candidate biomarkers were validated in an independent cohort. Predictive performance of the biomarkers for mortality, sepsis and venous thromboembolism was evaluated using bootstrap-corrected ROC analyses and multivariable regression analyses. RESULTS: Proteomic analysis revealed progressive involvement of the coagulation and complement pathway with increasing disease severity. SERPINA1 and CD59 were identified as candidate biomarkers and exhibited significantly higher plasma levels in severe cases. Bootstrap-corrected ROC analyses demonstrated strong predictive performance: SERPINA1 achieved AUCs of 0.775 and 0.924 for 30-day and 12-month mortality, and CD59 achieved AUCs of 0.720 for sepsis; the combined model further improved prediction of 12-month mortality (AUC 0.946) and sepsis (AUC 0.904), outperforming D-dimer and FDP. Multivariable regression confirmed their independent prognostic value. CONCLUSION: This exploratory study identifies SERPINA1 and CD59 as candidate prognostic biomarkers in COVID-19, highlighting the role of coagulation and complement-related pathways in disease severity and warranting further prospective validation.
Brain researchAlisha Braun, Phat Tai Vo, Larisa Bobrovskaya
The aim of this pilot study was to assess a time-dependent loss of orexin neurons in the unilateral intrastriatal 6-OHDA mouse model and to optimise the immunohistochemistry protocol for formalin-fixed, paraffin-embedded mouse brain tissue. A progressive loss of orexin A positive neurons in the lateral hypothalamus was observed in the lesioned side relative to the non-lesioned side. A significant reduction of orexin A positive neurons in the lateral hypothalamus was observed at 4 weeks with further loss at 6-8 weeks post 6-OHDA induction. Orexin neuron loss in the lateral hypothalamus has been reported in post-mortem Parkinson's disease patients and multiple animal studies, particularly in rats; however, evidence in neurotoxic mouse models remains limited. Orexin A positive neuron loss occurred alongside transient motor deficits, olfactory impairments, subtle cognitive changes and gastrointestinal dysfunction. Additionally, an orexin A immunohistochemistry protocol was successfully established for formalin-fixed, paraffin-embedded mouse brain tissue, enabling reproducible and reliable detection of orexin neurons as an alternative to frozen sections. This pilot study serves as a proof of concept that the unilateral intrastriatal 6-OHDA mouse model can successfully recapitulate the progressive loss of orexin A positive neurons and validates this model's suitably for investigating the longitudinal mechanisms of PD symptoms and pathology.
International journal of food microbiologyMei Li, Haoyi Wang, Zhiwei Zhang, Jianxin Cao, Qian Chen, Yanjie Chen, Xiaoyu Yin
This study aimed to elucidate the mechanisms underlying flavour differentiation in Xuanwei ham across different quality grades (A, B, and C), using a combined approach involving electronic nose (E-nose), gas chromatography-mass spectrometry (GC-MS), gas chromatography-ion mobility spectrometry (GC-IMS), metabolomics, and high-throughput sequencing. The instrumental evaluation was consistent with the traditional "three sticks" grading system, confirming distinct flavour profiles for each grade. Aldehydes, particularly 3-methylbutanal and nonanal, were identified as the primary contributors to the aroma of Grade A samples. In contrast, Grade C samples were characterised by the accumulation of short-chain fatty acids, such as valeric acid and hexanoic acid. Metabolomic analysis identified 52 differential metabolites, with amino acids, fatty acids, and their derivatives serving as key metabolites distinguishing ham quality. Furthermore, pathway enrichment analysis highlighted 33 metabolic pathways associated with quality, of which eight were significant based on topological pathway impact values (impact >0.1, P < 0.05). Microbiological analysis revealed that Meyerozyma and Aspergillus were the dominant fungal genera. Multi-omics association analysis demonstrated significant positive correlations between specific fungal species (e.g., Meyerozyma amylolytica and Aspergillus fumigatus) and multiple key flavour compounds and precursor metabolites. These findings elucidate the microbial and metabolic factors influencing flavour differentiation in Xuanwei ham and provide a scientific basis for precision quality control and process optimisation.
Tubulointerstitial fibrosis (TIF) is an inevitable outcome of progressive chronic kidney disease (CKD). Niaoduqing particles (NDQ) were developed for the treatment of CKD. However, the molecular mechanisms underlying the effect of NDQ on TIF remain unclear. Fecal gut microbiota (GM) and serum metabolites were analyzed using metagenomics and metabolomics in unilateral ureteral obstruction (UUO)-induced TIF rats. NDQ treatment attenuated UUO-induced TIF in rats in a dose- and time-dependent manner. The increased abundance of eight pathogenic bacteria, including Bacillus wiedmannii, Enterococcus mundtii and Fusobacterium varium, showed strong positive correlations with TID scores, whereas the reduced abundance of two probiotic bacteria, Ruminococcus flavefaciens and Clostridium celatum, showed strong negative correlations with tubulointerstitial damage (TID) scores. NDQ treatment reversed these aberrant microbial alterations, indicating its capacity to remodel GM dysbiosis. TID scores were strongly correlated with host- and GM-mediated tryptophan co-metabolites, including indoxyl sulfate, tryptamine and indole-3-acetic acid, in both TIF- and NDQ-treated TIF rats, and NDQ intervention normalized these metabolic disturbances. Notably, Fusobacterium varium and Enterococcus faecium exhibited strong linear correlations with indoxyl sulfate, indole-3-acetic acid, and indole-3-aldehyde in the TIF rat model. Furthermore, NDQ suppressed IκB/NF-κB signaling pathway in both TIF rats and TGF-β1-induced NRK-52E cells. These inhibitory effects were partially reversed by NF-κB p65 knockdown. This study is the first to demonstrate that NDQ alleviates TIF by reshaping microbial dysbiosis and modulating host- and GM-mediated tryptophan metabolism. These findings support that NDQ mitigates TIF by suppressing IκB/NF-κB signaling pathway through regulation of host-microbiota-derived tryptophan metabolism.
Journal of pharmaceutical and biomedical analysisMarziyeh Ghanbarian, Deborah Michel, Maryam Alyari, Amir Khajavinia, Oleg Y Dmitriev, Anas El-Aneed
Metabolites of the tricarboxylic acid (TCA) cycle play crucial roles in cancer biology, and their accurate quantification is essential for understanding energy metabolism, signaling dynamics, and identifying metabolic vulnerabilities in cancer cells. However, traditional liquid chromatograph-tandem mass spectrometry (LC-MS/MS) methods for these polar metabolites often encounter challenges, such as limited retention on reversed-phase columns and ion suppression. This study developed and validated two LC-MS/MS methods for the accurate quantification of seven key TCA cycle metabolites in MDA-MB-231, M67-2 (MEMO1 knockdown), and M67-9 (MEMO1 knockout) breast cancer cell lines. For five metabolites, namely citrate (CA), L-malate (MA), fumarate (FA), α-ketoglutarate (AKG), and glutamate (GA), an isotope-coded derivatization approach utilizing 12C/13C-labeled dimethylaminophenacyl (DmPA) bromide was employed to develop a targeted high-performance liquid chromatography (HPLC)-MS/MS method. Inefficient DmPA derivatization in aqueous matrices was addressed by optimizing sample preparation in non-aqueous conditions, and the presence of multiple peaks of AKG was resolved by selecting triethanolamine (TEOA) as the reaction base to improve specificity. Conversely, due to persistent interferences with DmPA derivatization, pyruvic acid (PA) and succinic acid (SA) were quantified using another novel hydrophilic interaction liquid chromatography (HILIC)-MS/MS method in their native underivatized forms. Both methods were validated according to regulatory bodies, ensuring linearity, accuracy, precision, selectivity, and stability. The methods ensured the utilization of two multiple reaction monitoring (MRM) transitions to enhance specificity. The validation approach was adjusted to fit tissue culture studies. The validated methods were successfully used to measure the TCA metabolites in tested cell lines, providing valuable tools for investigating metabolic dynamics in cancer research.
Bacillus cereus is a major foodborne pathogen characterized by robust biofilm formation and increasing antimicrobial resistance. This study identified 2-Methoxycinnamaldehyde (MCA) from Toona sinensis as the principal antibacterial compound and evaluated its inhibitory mechanisms and preservation potential. MCA exhibited potent activity against B. cereus ATCC 11778 (MIC = 150 μg/mL; MBC = 200 μg/mL) and resistant strains. In vitro assays demonstrated that MCA induced concentration-dependent membrane disruption, DNA damage, and intracellular protein leakage. Furthermore, treatment at 1 MIC and 2 MIC significantly impeded biofilm maturation; the secretion of extracellular proteins was reduced by 45.3% and 54.5%, polysaccharides by approximately 93%, and extracellular DNA (eDNA) by over 99%. Correspondingly, biofilm metabolic activity declined by 85.9% and 90.3%, and initial cellular adhesion was reduced by up to 88.1%. Untargeted metabolomic analysis revealed that these phenotypic defects stem from profound disturbances in amino acid biosynthesis, the TCA cycle, and nucleotide metabolism. Molecular docking revealed that MCA targets multiple essential bacterial enzymes, including ribonucleotide reductase, lysyl-tRNA synthetase, pyruvate kinase, betaine aldehyde dehydrogenase, and 5'-nucleotidase, through stable hydrogen bonding and π-interactions. In a refrigerated pork model, MCA completely eliminated B. cereus by day 7 while significantly delaying pH increases and color deterioration. These findings provide the first evidence for MCA as an antibacterial and antibiofilm agent against B. cereus, highlighting its potential in food preservation.
Food research international (Ottawa, Ont.)Xinmin Liang, Jing Han, Tianhai Liu, Yang Yu, Di Wang, Bo Wang, Dinghong Jia, Weihong Peng, Xiaolan He, Xun Liu
The cap color of Flammulina filiformis represents a significant commercial trait, directly affecting consumer purchasing preferences and market value, making it a primary target for genetic improvement. However, the biochemical mechanisms underlying pigmentation, particularly in newly developed dark-brown strains, remain insufficiently understood. In this study, dark-brown F. filiformis was used to investigate the role of reactive oxygen species (ROS) in cap color. Exogenous application of the ROS scavenger N,N'-Dimethylthiourea (DMTU) significantly induced the fading of dark-brown phenotype to yellow, concomitant with reduced activity of key enzymes involved in melanin biosynthesis and an increased pheomelanin/eumelanin ratio. Metabolomic analysis revealed that DMTU treatment significantly activated the glutathione metabolism pathway, with marked accumulation of pathway-associated metabolites. Further validation demonstrated that both oxidized glutathione (GSSG) and its reduced form (GSH) induced a cap fading phenotype similar to that induced by DMTU. Furthermore, quantitative real-time PCR (qRT-PCR) analysis revealed that DMTU treatment significantly upregulated the expression of genes associated with glutathione synthesis and regeneration, while downregulating the transcription levels of key genes involved in melanin synthesis. In conclusion, this study illustrates that alterations in ROS levels can profoundly affect the cap pigmentation process in dark-brown F. filiformis by modulating the glutathione-mediated redox balance. These findings elucidate the critical regulatory role of ROS-glutathione metabolism in the color formation of F. filiformis, offering a novel theoretical framework for the quality control and future breeding aimed at developing cultivars with optimized color traits and enhanced market appeal.
Brown milk beverages have garnered widespread attention due to their unique flavor and potential as a functional matrix for probiotic delivery. This study aimed to identify Lacticaseibacillus paracasei strains suitable for fermenting brown milk beverages by combining artificial intelligence-driven predictive screening with experimental validation and metabolomic analysis. Using the iProbiotics platform, 27 L. paracasei strains underwent initial screening, yielding seven candidates for further evaluation. These trains were systematically evaluated for gastrointestinal tolerance and bile salt tolerance, fermentation performance, storage stability, and metabolic profiles. Strains PC724 and PC646 demonstrated superior probiotic and technological properties, outperforming the commercial control strain LC-01 in acidification capacity, viable cell counts, and textural attributes. Over 35 days of refrigerated storage, both strains maintained high viability (>108 CFU/mL) and stable metabolic activity, confirming remarkable storage stability. Non-targeted metabolomics revealed sustained enrichment of carbohydrate metabolism, amino acid metabolism, and global metabolic regulation in PC724 and PC646. These metabolic signatures likely underpin their robust stress tolerance long-term survival. Collectively, integrating artificial intelligence prediction with metabolomic profiling provides a scalable strategy for identifying industrially viable probiotic candidates, offering a valuable framework for developing functional fermented milk beverages.