PubMed

J Neurol. 2024 Nov 19. doi: 10.1007/s00415-024-12722-5. Online ahead of print.NO ABSTRACTPMID:39560724 | DOI:10.1007/s00415-024-12722-5

Proc Natl Acad Sci U S A. 2024 Nov 26;121(48):e2407842121. doi: 10.1073/pnas.2407842121. Epub 2024 Nov 19.ABSTRACTThe human lens is composed of a monolayer of lens epithelial cells (LECs) and elongated fibers that align tightly but are separated by the plasma membrane. The integrity of the lens plasma membrane is crucial for maintaining lens cellular structure, homeostasis, and transparency. Glutathione peroxidase 4 (GPX4), a selenoenzyme, plays a critical role in protecting against lipid peroxidation. This study aims to elucidate the role of GPX4 in lens plasma membrane stability during lens development using in vitro, ex vivo, and in vivo systems. Our findings reveal that GPX4 deficiency triggers lens epithelial apoptosis-independent but ferroptosis-mediated cell death. Blocking lens GPX4 activity during ex vivo culture induces lens opacification, LEC death, and disruption of lens fiber cell arrangement. Deletion of lens-specific Gpx4 results in significant unsaturated phospholipid loss and an increase in oxidized phospholipids. Consequently, lenses with Gpx4 deficiency exhibit massive disruption of lens fiber cell structure, significant loss of LECs via ferroptosis, and formation of newborn cataracts. Remarkably, administering the lipid peroxidation inhibitor, liproxstatin-1, to pregnant mothers at embryonic days 9.5 significantly prevents lipid peroxidation, LEC death, and lens developmental defects. Our study unveils the crucial role of GPX4 in lens development and transparency, and also provides a successful intervention approach to prevent lens developmental defects through lipid peroxidation inhibition.PMID:39560644 | DOI:10.1073/pnas.2407842121

J Periodontal Res. 2024 Nov 19. doi: 10.1111/jre.13363. Online ahead of print.ABSTRACTAIMS: This research sought to assess the efficacy of Bacillus subtilis (B. subtilis) R0179 and explore potential metabolites in mitigating experimental periodontitis in mice induced by Porphyromonas gingivalis (P. gingivalis) ATCC 33277.METHODS: B. subtilis R0179 was administered to 8-week-old male C57BL/6J mice with periodontitis. Oral load of P. gingivalis ATCC 33277 and periodontal tissue loss were quantified. The cell-free supernatant (CFS) was separated to assess its anti-P. gingivalis effect. Proteomic and metabolomic analyses identified potential antibacterial components in the CFS, further evaluated for anti-P. gingivalis effects.RESULTS: B. subtilis R0179 significantly reduced P. gingivalis ATCC 33277 levels and mitigated periodontal tissue loss in mice. The CFS, rather than inactivated B. subtilis R0179 cells, exhibited antibacterial activity. Proteomic and metabolomic analyses identified mesaconate and citraconate as key antibacterial agents. Disk diffusion assays confirmed the efficacy of mesaconate against P. gingivalis, while citraconate had no effect. Mesaconate showed a dose-dependent reduction in P. gingivalis ATCC 33277 population and periodontal tissue loss in mice.CONCLUSION: These findings highlight B. subtilis R0179 and its metabolite mesaconate as promising candidates for therapeutic development against periodontitis by inhibiting P. gingivalis ATCC 33277 effectively.PMID:39560450 | DOI:10.1111/jre.13363

mSystems. 2024 Nov 19:e0085624. doi: 10.1128/msystems.00856-24. Online ahead of print.ABSTRACTCoral reefs are experiencing unprecedented loss in coral cover due to increased incidence of disease and bleaching events. Thus, understanding mechanisms of disease susceptibility and resilience, which vary by species, is important. In this regard, untargeted metabolomics serves as an important hypothesis-building tool enabling the delineation of molecular factors underlying disease susceptibility or resilience. In this study, we characterize metabolomes of four species of visually healthy stony corals, including Meandrina meandrites, Orbicella faveolata, Colpophyllia natans, and Montastraea cavernosa, collected at least a year before stony coral tissue loss disease reached the Dry Tortugas, Florida, and demonstrate that both symbiont and host-derived biochemical pathways vary by species. Metabolomes of Meandrina meandrites displayed minimal intraspecies variability and the highest biological activity against coral pathogens when compared to other species in this study. The application of advanced metabolite annotation methods enabled the delineation of several pathways underlying interspecies variability. Specifically, endosymbiont-derived vitamin E family compounds, betaine lipids, and host-derived acylcarnitines were among the top predictors of interspecies variability. Since several metabolite features that contributed to inter- and intraspecies variation are synthesized by the endosymbiotic Symbiodiniaceae, which could be a major source of these compounds in corals, our data will guide further investigations into these Symbiodiniaceae-derived pathways.IMPORTANCE: Previous research profiling gene expression, proteins, and metabolites produced during thermal stress have reported the importance of endosymbiont-derived pathways in coral bleaching resistance. However, our understanding of interspecies variation in these pathways among healthy corals and their role in diseases is limited. We surveyed the metabolomes of four species of healthy corals with differing susceptibilities to the devastating stony coral tissue loss disease and applied advanced annotation approaches in untargeted metabolomics to determine the interspecies variation in host and endosymbiont-derived pathways. Using this approach, we propose the survey of immune markers such as vitamin E family compounds, acylcarnitines, and other metabolites to infer their role in resilience to coral diseases. As time-resolved multi-omics datasets are generated for disease-impacted corals, our approach and findings will be valuable in providing insight into the mechanisms of disease resistance.PMID:39560405 | DOI:10.1128/msystems.00856-24

Anal Methods. 2024 Nov 19. doi: 10.1039/d4ay01569j. Online ahead of print.ABSTRACTScreening differential metabolites is of great significance in biomarker discovery in metabolomics research. However, it is susceptible to unwanted variations introduced during experiments. Previous normalization methods have improved the accuracy of inter-group classification by eliminating systematic errors. Nonetheless, the classification ability of differential metabolites obtained through these methods still requires further enhancement, and the reproducibility evaluation on importance rankings of differential metabolites is often disregarded. The EigenRF algorithm was developed as an improvement over the previous metabolomics normalization method referred to as EigenMS, which aims to normalize metabolomics data. Furthermore, scoring metrics, including the local consistency (LC) and overall difference (OD) scores, were introduced to evaluate the reproducibility of importance rankings of differential metabolites from a dual perspective. After conducting validation on three publicly accessible datasets, the EigenRF method has demonstrated enhanced classification ability of differential metabolites as well as improved reproducibility. In summary, EigenRF enhances the reliability of differential metabolites in metabolomics research, benefiting the further exploration of molecular mechanisms underlying biological alterations in complex matrices. The EigenRF algorithm was implemented in an R package: https://www.github.com/YangHuaLab/EigenRF.PMID:39560372 | DOI:10.1039/d4ay01569j

Cancer Rep (Hoboken). 2024 Nov;7(11):e70042. doi: 10.1002/cnr2.70042.ABSTRACTBACKGROUND: Detection of cancer at the early stage currently offers the only viable strategy for reducing disease-related morbidity and mortality. Various approaches for multi-cancer early detection are being explored, which largely rely on capturing signals from circulating analytes shed by tumors into the blood. The fact that biomarker concentrations are limiting in the early stages of cancer, however, compromises the accuracy of these tests. We, therefore, adopted an alternate approach that involved interrogation of the serum metabolome with machine learning-based data analytics. Here, we monitored for modulations in metabolite patterns that correlated with the presence or absence of cancer. Results obtained confirmed the efficacy of this approach by demonstrating that it could detect a total of 15 cancers in women with an average accuracy of about 99%.AIMS: To further increase the scope of our test, we conducted an investigator-initiated clinical trial involving a total of 6445 study participants, which included both cancer patients and non-cancer volunteers. Our goal here was to maximize the number of cancers that could be detected, while also covering cancers in both females and males.METHODS AND RESULTS: Metabolites extracted from individual serum samples were profiled by ultra-performance liquid chromatography coupled to a high-resolution mass spectrometer using an untargeted protocol. After processing, the data were analyzed by our cancer detection machine-learning algorithm to differentiate cancer from non-cancer samples. Results revealed that our test platform could indeed detect a total of 30 cancers, covering both females and males, with an average accuracy of ~98%. Importantly, the high detection accuracy remained invariant across all four stages of the cancers.CONCLUSION: Thus, our approach of integrating untargeted metabolomics with machine learning-powered data analytics offers a powerful strategy for early-stage multi-cancer detection with high accuracy.TRIAL REGISTRATION: Registration No: CTRI/2023/03/050316.PMID:39559978 | DOI:10.1002/cnr2.70042

Plant J. 2024 Nov 19. doi: 10.1111/tpj.17149. Online ahead of print.ABSTRACTCotton stands as a pillar in the textile industry due to its superior natural fibers. Lignin, a complex polymer synthesized from phenylalanine and deposited in mature cotton fibers, is believed to be essential for fiber quality, although the precise effects remain largely unclear. In this study, we characterized two ubiquitously expressed cinnamyl alcohol dehydrogenases (CAD), GhCAD37A and GhCAD37D (GhCAD37A/D), in Gossypium hirsutum. GhCAD37A/D possess CAD enzymatic activities, to catalyze the generation of monolignol products during lignin biosynthesis. Analysis of transgenic cotton knockout and overexpressing plants revealed that GhCAD37A/D are important regulators of fiber quality, positively impacting breaking strength but negatively affecting fiber length and elongation percentage by modulating lignin biosynthesis in fiber cells. Moreover, GhCAD37A/D are shown to modulate anther vitality and affect stem lodging trait in cotton by influencing lignin biosynthesis in the vascular bundles of anther and stem, respectively. Additionally, our study revealed that Ghcad37A/D knockout plants displayed red stem xylem, likely due to the overaccumulation of aldehyde intermediates in the phenylpropanoid metabolism pathway, as indicated by metabolomics analysis. Thus, our work illustrates that GhCAD37A/D are two important enzymes of lignin biosynthesis in different cotton organs, influencing fiber quality, anther vitality, and stem lodging.PMID:39559968 | DOI:10.1111/tpj.17149

Drug Des Devel Ther. 2024 Nov 13;18:5161-5182. doi: 10.2147/DDDT.S478072. eCollection 2024.ABSTRACTBACKGROUND: Modified Suanmei-Tang (MST) comprises four plants common to both traditional Chinese medicine and culinary applications, and it can potentially alleviate metabolic-associated fatty liver disease (MAFLD) triggered by a high-fat diet (HFD).PURPOSE: This research aims to investigate the impact and underlying mechanisms of MST in ameliorating MAFLD caused by an HFD.METHODS: UHPLC-Q-Orbitrap-MS/MS was used to determine the constituents of MST and to evaluate its effects on MAFLD mouse models. Transcriptomics, network pharmacology, and bioinformatics analysis (including Kyoto Encyclopedia of Genes and Genomes and Gene Set Enrichment Analysis) were utilized to further clarify the mechanisms by which MST acts on MAFLD. The experimental methods included ELISA, real time quantitative PCR (RT-qPCR), Western blot, immunohistochemistry, molecular docking, and metabolomics. Transcriptomics was integrated with metabolomics to find correlations between differentially expressed genes and metabolites, and crucial genes were validated through RT-qPCR.RESULTS: A total of 23 components of MST were identified. The formulation was found to alleviate metabolic disorders, obesity, insulin resistance, inflammation, and oxidative stress in mice with MAFLD. The findings indicate that MST promoted autophagy by suppressing phosphorylation in the PI3K/AKT/mTOR pathway and enhancing lipid management in the livers of MAFLD mice.CONCLUSION: MST could effectively improve lipid metabolism disorders and liver lipid deposition in MAFLD mice, and its mechanism might be related to regulating the PI3K/AKT/mTOR pathway to improve autophagy.PMID:39559790 | PMC:PMC11572505 | DOI:10.2147/DDDT.S478072

Front Pharmacol. 2024 Nov 4;15:1418063. doi: 10.3389/fphar.2024.1418063. eCollection 2024.ABSTRACTLomatogonium rotatum (LR) is a folk medicinal herb traditionally used as a lipid-lowering and anti-obesity agent; but its pharmacological mechanism is unclear. In this study, we assessed the alterations of LR on gut microbes and serum metabolites in obese mice and their associated mechanisms of modulation on visceral fat and serum lipid by integrating gut microbiota and metabolomics analyses. Mice were fed a high-fat diet (HFD) to generate obesity and were then given LR and Orlistat orally at different doses (0.18, 0.9, 1.8 g/kg for LR and 0.048 g/kg for Orlistat) for a duration of 9 weeks. The impact of LR on weight loss was assessed through the examination of fat deposition, serum lipid indices, liver indices, and HE pathohistology. The effects of LR on gut microbiota and serum metabolites in obese mice were then investigated by 16S rRNA sequencing technology and untargeted metabolomics, and correlation analysis was performed. LR significantly reduced body weight, feed intake, Lee's index, visceral fat accumulation, serum TG, TC, AST and ALT, and elevated serum HDL levels in obese mice. In addition, 16S rRNA sequencing results indicated that the LR intervention remodeled microbial diversity and composition, increased the relative abundance of gut microbes Bacteroidetes and Porphyromonadaceae in HFD-induced obese mice, and decreased the Deferribacteres, Firmicutes and the Firmicutes/Bacteroidetes ratio. Correlation analyses showed that LR regulation of L-tyrosine and hesperetin metabolism, as well as alterations in the metabolic pathways of Phenylalanine, tyrosine and tryptophan biosynthesis, were associated with the changes in abundance of Bacteroidetes, Firmicutes, Porphyromonadaceae and Deferribacteres. Our study demonstrated that LR has lipid lowering and visceral fat reduction effects and its function may be closely related to the improvement of the gut microbiota and its associated metabolites.PMID:39559734 | PMC:PMC11570273 | DOI:10.3389/fphar.2024.1418063

Front Immunol. 2024 Nov 4;15:1475528. doi: 10.3389/fimmu.2024.1475528. eCollection 2024.ABSTRACTSystemic sclerosis (SSc) is a rare and highly heterogeneous chronic autoimmune disease characterized by multi-organ and tissue fibrosis, often accompanied by a poor prognosis and high mortality rates. The primary pathogenic mechanisms of SSc are considered to involve tissue fibrosis, autoimmune dysfunction, and microvascular abnormalities. Recent studies have shed light on the gut microbiota (GM) and metabolites in SSc patients, revealing their association with gastrointestinal symptoms and disease phenotypes. However, further elucidation is needed on the specific mechanisms underlying the interactions between GM, metabolites, and the immune system and their roles in the pathogenesis of SSc. This review outlines the characteristics of GM and metabolites in SSc patients, exploring their interrelationships and analyzing their correlations with the clinical phenotypes of SSc. The findings indicate that while the α-diversity of GM in SSc patients resembles that of healthy individuals, notable differences exist in the β-diversity and the abundance of specific bacterial genera, which are closely linked to gastrointestinal symptoms. Moreover, alterations in the levels of amino acids and lipid metabolites in SSc patients are prominently observed and significantly associated with clinical phenotypes. Furthermore, this review delves into the potential immunopathological mechanisms of GM and metabolites in SSc, emphasizing the critical role of interactions between GM, metabolites, and the immune system in comprehending the immunopathological processes of SSc. These insights may offer new scientific evidence for the development of future treatment strategies.PMID:39559369 | PMC:PMC11570262 | DOI:10.3389/fimmu.2024.1475528

J Cachexia Sarcopenia Muscle. 2024 Nov 19. doi: 10.1002/jcsm.13613. Online ahead of print.ABSTRACTBACKGROUND: Sarcopenia is thought to be underlined by age-associated anabolic resistance and dysregulation of intracellular signalling pathways. However, it is unclear whether these phenomena are driven by ageing per se or other confounding factors.METHODS: Lean and healthy young (n = 10, 22 ± 3 years, BMI; 23.4 ± 0.8 kg/m2) and old men (n = 10, 70 ± 3 years, BMI; 22.7 ± 1.3 kg/m2) performed unilateral resistance exercise followed by intake of essential amino acids (EAA). Muscle biopsies were collected from the rested and the exercised leg before, immediately after and 60 and 180 min after EAA intake. Muscle samples were analysed for amino acid concentrations, muscle protein synthesis (MPS) and associated anabolic signalling.RESULTS: Following exercise, peak plasma levels of EAA and leucine were similar between groups, but the area under the curve was ~11% and ~28% lower in Young (p < 0.01). Absolute levels of muscle EAA and leucine peaked 60 min after exercise, with ~15 and ~21% higher concentrations in the exercising leg (p < 0.01) but with no difference between groups. MPS increased in both the resting (~0.035%·h-1 to 0.056%·h-1, p < 0.05) and exercising leg (~0.035%·h-1 to 0.083%·h-1, p < 0.05) with no difference between groups. Phosphorylation of S6K1Thr389 increased to a similar extent in the exercising leg in both groups but was 2.8-fold higher in the resting leg of Old at the 60 min timepoint (p < 0.001). Phosphorylation of 4E-BP1Ser65 increased following EAA intake and exercise, but differences between legs were statistically different only at 180 min (p < 0.001). However, phosphorylation of this site was on average 78% greater across all timepoints in Old (p < 0.01). Phosphorylation of eEF2Thr56 was reduced (~66% and 39%) in the exercising leg at both timepoints after EAA intake and exercise, with no group differences (p < 0.05). However, phosphorylation at this site was reduced by ~27% also in the resting leg at 60 min, an effect that was only seen in Old (p < 0.01). Total levels of Rheb (~45%), LAT1 (~31%) and Rag B (~31%) were higher in Old (p < 0.001).CONCLUSION: Lean and healthy old men do not manifest AR as evidenced by potent increases in MPS and mTORC1 signalling following EAA intake and exercise. Maintained anabolic sensitivity with age appears to be a function of a compensatory increase in basal levels of proteins involved in anabolic signalling. Therefore, our results suggest that age per se does not appear to cause AR in human skeletal muscle.PMID:39558870 | DOI:10.1002/jcsm.13613

Age Ageing. 2024 Nov 4;53(11):afae256. doi: 10.1093/ageing/afae256.ABSTRACTBACKGROUND: Metabolomic scores based on age (MetaboAge) and mortality (MetaboHealth) are considered indicators of overall health, but their association with cognition in the general population is unknown. Therefore, the association between MetaboAge/MetaboHealth and level and decline in cognition was studied, as were differences between men and women.METHODS: Data of 2821 participants (50% women, age range 45-75) from the Doetinchem Cohort Study was used. MetaboAge and MetaboHealth were calculated from 1H-NMR metabolomics data at baseline. Cognitive domain scores (memory, flexibility and processing speed) and global cognitive functioning were available over a 10-year period. The association between MetaboAge/MetaboHealth and level of cognitive functioning was studied using linear regressions while for the association between MetaboAge/MetaboHealth and cognitive decline longitudinal linear mixed models were used. Analyses were adjusted for demographics and lifestyle factors.RESULTS: Higher MetaboAge, indicating poorer metabolomic ageing, was only associated with lower levels of processing speed in men. Higher MetaboHealth, indicating poorer immune-metabolic health, was associated with lower levels of cognitive functioning for all three domains and global cognitive functioning in both men and women. Only in men, MetaboHealth was also associated with 10-year decline in flexibility, processing speed and global cognition. Metabolites that contributed to the observed associations were in men mainly markers of protein metabolism, and in women mainly markers of lipid metabolism and inflammatory metabolites.CONCLUSIONS: MetaboHealth, not MetaboAge, was associated with cognitive functioning independent of conventional risk factors. Individual metabolites affect cognitive functioning differently in men and women, suggesting sex-specific pathophysiological pathways underlying cognitive functioning.PMID:39558869 | DOI:10.1093/ageing/afae256

Pediatrics. 2024 Nov 19:e2024068477. doi: 10.1542/peds.2024-068477. Online ahead of print.ABSTRACTJuvenile parkinsonism is an exceedingly rare condition in which clinical signs of parkinsonism manifest before 21 years of age. Although the genetic underpinnings of this disorder are increasingly recognized, the full range of inherited metabolic contributors remains undefined. We present the first case of levodopa-responsive juvenile parkinsonism associated with dihydropyrimidinase deficiency caused by a novel DPYS variant. A 13-year-old patient presented with rapid progression of dysphagia, dysarthria, and loss of ambulation over 18 months. Whole-exome sequencing revealed compound heterozygous variants in the DPYS gene (NM_001385: c.1393C>T, p.R465X, and c.905G>A, p.R302Q). In silico analysis predicted both variants to be pathogenic. Further urinary metabolome analysis demonstrated markedly elevated dihydrouracil and dihydrothymine levels, confirming impaired pyrimidine metabolism. Levodopa treatment effectively relieved the patient's motor symptoms. This report identifies DPYS as a novel genetic cause of juvenile parkinsonism and underscores the potential efficacy of levodopa therapy in managing motor dysfunction in DYPS-related parkinsonism.PMID:39558747 | DOI:10.1542/peds.2024-068477

Bioinformatics. 2024 Nov 18:btae694. doi: 10.1093/bioinformatics/btae694. Online ahead of print.ABSTRACTSUMMARY: Fast computational evaluation and classification of concentration responses for hundreds of metabolites represented by their mass-to-charge (m/z) ratios is indispensable for unraveling complex metabolomic drug actions in label-free, whole-cell Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry (MALDI MS) bioassays. In particular, the identification of novel pharmacodynamic biomarkers to determine target engagement, potency and potential polypharmacology of drug-like compounds in high-throughput applications requires robust data interpretation pipelines. Given the large number of mass features in cell-based MALDI MS bioassays, reliable identification of true biological response patterns and their differentiation from any measurement artefacts that may be present is critical. To facilitate the exploration of metabolomic responses in complex MALDI MS datasets, we present a novel software tool, M2ara. Implemented as a user-friendly R-based shiny application, it enables rapid evaluation of Molecular High Content Screening (MHCS) assay data. Furthermore, we introduce the concept of Curve Response Score (CRS) and CRS fingerprints to enable rapid visual inspection and ranking of mass features. In addition, these CRS fingerprints allow direct comparison of cellular effects among different compounds. Beyond cellular assays, our computational framework can also be applied to MALDI MS-based (cell-free) biochemical assays in general.AVAILABILITY AND IMPLEMENTATION: The software tool, code and examples are available at https://github.com/CeMOS-Mannheim/M2ara and https://dx.doi.org/10.6084/m9.figshare.25736541.SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.PMID:39558590 | DOI:10.1093/bioinformatics/btae694

BMC Musculoskelet Disord. 2024 Nov 18;25(1):920. doi: 10.1186/s12891-024-08061-1.ABSTRACTOBJECTIVE: To assess the mechanism of supraspinatus tendinopathy induced by type 2 diabetes mellitus (T2DM) in rats using untargeted metabolomics analysis.METHODS: The liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics approach was used to screen tendon biomarkers of supraspinatus tendinopathy in rats with T2DM. Seventy-eight Sprague-Dawley rats were divided into normal group (NG) and T2DM groups. Rats in T2DM groups were divided into 12-week (T2DM-12w), and 24-week (T2DM-24w) subgroups according to the time point of the establishment of the T2DM rat model. Histological evaluation (modified Bonar score) and biomechanical testing were used to analyze the adverse effects of type 2 diabetes on the tendon of the supraspinatus muscle in rats.Three comparable groups were set up, including T2DM-12w group vs. NG, T2DM-24w group vs. NG, and T2DM-24w group vs. T2DM-12w group. Differentially expressed metabolites (DEMs) in the supraspinatus tendons in the three groups of rats were analyzed using LC-MS, and data were analyzed using multivariate statistical methods to screen potential biomarkers. The DEMs included in the intersection of the three groups were identified as those associated with the development of diabetic supraspinatus tendinopathy, and trend analysis and pathway topology analysis were performed.RESULTS: With the progression of diabetes, the tendinopathy of the supracinatus muscle of diabetic rats gradually intensified, mainly manifested as inflammatory reactions, disordered collagen fibers, fat infiltration, and increased modified Bonar score. The intersection of DEMs among the three comparable groups was resulted in the identification of 10 key DEMs, in which melezitose and raffinose showed a continuous increasing trend with the prolongation of disease course. By pathway topology analysis, 10 DEMs (P < 0.01) were mainly associated with the pathways of galactose metabolism, which could be involved in the development of diabetes-induced supraspinatus tendinopathy.CONCLUSION: T2DM causes tendinopathy of the supraspinatus muscle in rats. 10 key DEMs obtained by untargeted metabolomics assay suggested that the development of diabetes-induced supraspinatus tendinopathy was associated with changes in metabolic pathways, such as galactose metabolism. melezitose and raffinose hold promise as a biomarker for disease discrimination and/or disease indication in diabetic supraspinatus tendinopathy.PMID:39558291 | DOI:10.1186/s12891-024-08061-1

Nat Microbiol. 2024 Nov 18. doi: 10.1038/s41564-024-01858-9. Online ahead of print.ABSTRACTAlthough diet is a substantial determinant of the human gut microbiome, the interplay between specific foods and microbial community structure remains poorly understood. Coffee is a habitually consumed beverage with established metabolic and health benefits. We previously found that coffee is, among >150 items, the food showing the highest correlation with microbiome components. Here we conducted a multi-cohort, multi-omic analysis of US and UK populations with detailed dietary information from a total of 22,867 participants, which we then integrated with public data from 211 cohorts (N = 54,198). The link between coffee consumption and microbiome was highly reproducible across different populations (area under the curve of 0.89), largely driven by the presence and abundance of the species Lawsonibacter asaccharolyticus. Using in vitro experiments, we show that coffee can stimulate growth of L. asaccharolyticus. Plasma metabolomics on 438 samples identified several metabolites enriched among coffee consumers, with quinic acid and its potential derivatives associated with coffee and L. asaccharolyticus. This study reveals a metabolic link between a specific gut microorganism and a specific food item, providing a framework for the understanding of microbial dietary responses at the biochemical level.PMID:39558133 | DOI:10.1038/s41564-024-01858-9

Sci Rep. 2024 Nov 18;14(1):28490. doi: 10.1038/s41598-024-79402-2.ABSTRACTCitrus tristeza virus (CTV) causes economically important stem pitting in sensitive citrus types however the exact mechanisms of stem pitting development in citrus remain unclear. In this study, CTV infectious clones were used to study stem pitting induction in 'Duncan' grapefruit and 'Mexican' lime. A panel of open reading frame (ORF) replacement clones was generated focusing on the CTV ORFs implicated in stem pitting development and pathogenicity, namely p33, p18, p13 and p23. ORF replacements from severe- and mild-pitting CTV isolates were introduced into a mild-pitting infectious clone (genotype T36) to determine if stem pitting could be induced. A broad range of stem pitting outcomes were observed with ORF p18 (from isolate T3-KB) and ORF p23 (from isolate GFMS12-1.3) associated with enhanced stem pitting development. Metabolomic trends underlying the different stem pitting outcomes were further assessed by untargeted metabolite profiling. In each citrus host, the metabolite profiling identified statistically significant compounds that differed between stem pitting groups. These compounds were mainly phenolic acids and phenolic glycosides and are known to function as antioxidant and stress-signaling molecules. These metabolites can serve as targets for future time-course observations to potentially use mass spectrometry profiling to inform CTV management practices.PMID:39557999 | DOI:10.1038/s41598-024-79402-2

Nat Commun. 2024 Nov 18;15(1):9749. doi: 10.1038/s41467-024-54044-0.ABSTRACTTET-family members play a critical role in cell fate commitment. Indeed, TET3 is essential to postnatal development due to yet unknown reasons. To define TET3 function in cell differentiation, we have profiled the intestinal epithelium at single-cell level from wild-type and Tet3 knockout mice. We have found that Tet3 is mostly expressed in differentiated enterocytes. In the absence of TET3, enterocytes exhibit an aberrant differentiation trajectory and do not acquire a physiological cell identity due to an impairment in oxidative phosphorylation, specifically due to an ATP synthase assembly deficiency. Moreover, spatial metabolomics analysis has revealed that Tet3 knockout enterocytes exhibit an unphysiological metabolic profile when compared with their wild-type counterparts. In contrast, no metabolic differences have been observed between both genotypes in the stem cell compartment where Tet3 is mainly not expressed. Collectively, our findings suggest a mechanism by which TET3 regulates mitochondrial function and, thus, terminal cell differentiation at the metabolic level.PMID:39557858 | DOI:10.1038/s41467-024-54044-0

Mol Diagn Ther. 2024 Nov 18. doi: 10.1007/s40291-024-00757-3. Online ahead of print.ABSTRACTTo better understand ovarian cancer lethality and treatment resistance, sophisticated computational approaches are required that address the complexity of the tumor microenvironment, genomic heterogeneity, and tumor evolution. The ovarian cancer tumor ecosystem consists of multiple tumors and cell types that support disease growth and progression. Over the last two decades, there has been a revolution in -omic methodologies to broadly define components and essential processes within the tumor microenvironment, including transcriptomics, metabolomics, proteomics, genome sequencing, and single-cell analyses. While most of these technologies comprehensively characterize a single biological process, there is a need to understand the biological and clinical impact of integrating multiple -omics platforms. Overall, multi-omics is an intriguing analytic framework that can better approximate biological complexity; however, data aggregation and integration pipelines are not yet sufficient to reliably glean insights that affect clinical outcomes.PMID:39557776 | DOI:10.1007/s40291-024-00757-3

Anal Bioanal Chem. 2024 Nov 18. doi: 10.1007/s00216-024-05646-6. Online ahead of print.ABSTRACTQuality control (QC) samples are commonly used in metabolomics approaches for three main reasons: (i) the initial conditioning of the column; (ii) the correction of analytical drift especially between batches; and (iii) the evaluation of measurement precision. In practice, there are several ways to prepare and conserve QC samples. The most common in untargeted metabolomics is to pool samples after or before extraction, in order to obtain pooled QC samples accounting, respectively, for analytical variance or for both analytical and sample preparation variances. In this study, focusing on untargeted analysis of tea (Camellia sinensis) leaves, we compared three ways of preparing pooled QC samples (two usual and one unusual QC sample preparations) and their efficiency to improve data quality in terms of inter-batch correction, measurement precision, and VIP candidates selection on datasets obtained using two mass spectrometry (MS) technologies (Orbitrap and time of flight (QToF)). We also investigated the effect of data processing modalities, based on the different QC preparations, on data loss and on the global structure of the datasets. Generally, our results show that usual QC sample preparation leads to comparable datasets quality in terms of precision and dispersion on both MS instruments. They also show that QC preparation is crucial for VIP selection; in fact, up to 54% of biomarkers candidates were specific of the QC preparation type used for data processing.PMID:39557686 | DOI:10.1007/s00216-024-05646-6