PubMed

PeerJ. 2023 Sep 1;11:e15856. doi: 10.7717/peerj.15856. eCollection 2023.ABSTRACTBACKGROUND: Ambient fine particulate matter ≤ 2.5 µm (PM2.5) air pollution exposure has been identified as a global health threat, the epidemiological evidence suggests that PM2.5 increased the risk of chronic kidney disease (CKD) among the diabetes mellitus (DM) patients. Despite the growing body of research on PM2.5 exposure, there has been limited investigation into its impact on the kidneys and the underlying mechanisms. Past studies have demonstrated that PM2.5 exposure can lead to lipid metabolism disorder, which has been linked to the development and progression of diabetic kidney disease (DKD).METHODS: In this study, db/db mice were exposed to different dosage PM2.5 for 8 weeks. The effect of PM2.5 exposure was analysis by assessment of renal function, pathological staining, immunohistochemical (IHC), quantitative real-time PCR (qPCR) and liquid chromatography with tandem mass spectrometry (LC-MS/MS) based metabolomic analyses.RESULTS: The increasing of Oil Red staining area and adipose differentiation related protein (ADRP) expression detected by IHC staining indicated more ectopic lipid accumulation in kidney after PM2.5 exposure, and the increasing of SREBP-1 and the declining of ATGL detected by IHC staining and qPCR indicated the disorder of lipid synthesisandlipolysis in DKD mice kidney after PM2.5 exposure. The expressions of high mobility group nucleosome binding protein 1 (HMGN1) and kidney injury molecule 1 (KIM-1) that are associated with kidney damage increased in kidney after PM2.5 exposure. Correlation analysis indicated that there was a relationship between HMGN1-KIM-1 and lipid metabolic markers. In addition, kidneys of mice were analyzed using LC-MS/MS based metabolomic analyses. PM2.5 exposure altered metabolic profiles in the mice kidney, including 50 metabolites. In conclusion the results of this study show that PM2.5 exposure lead to abnormal renal function and further promotes renal injury by disturbance of renal lipid metabolism and alter metabolic profiles.PMID:37671359 | PMC:PMC10476618 | DOI:10.7717/peerj.15856

PeerJ. 2023 Sep 1;11:e16034. doi: 10.7717/peerj.16034. eCollection 2023.ABSTRACTOBJECTIVE: The classification and clinical usage of the different species of bead ginseng are often confused. Therefore, we conducted an integrated metabolomics and transcriptome analysis of three main species of Panax, including Panax japonicas, Panax pseudoginseng, and Panax pseudo-ginseng var. elegantior.METHODS: A broad metabolome and transcriptome analysis for three origins of bead ginseng plants was performed using UPLC-ESI-MS/MS, RNA sequencing and annotation, and bioinformatic analysis of transcriptome data.RESULTS: The levels of 830 metabolites were determined. A total of 291 differentially accumulated metabolites (DAMs) between Panax pseudo-ginseng var. elegantior and Panax japonicas (Group A), with 73 upregulated and 218 downregulated. A total of 331 DAMs (110 upregulated and 221 downregulated) were found between Panax pseudoginseng and Panax japonicas (group B). There were 160 DAMs (102 up-regulated and 58 down-regulated) between Panax pseudoginseng and Panax pseudo-ginseng var. elegantior (group C). In addition, RNA sequencing was performed in the above three ways. A total of 16,074 differential expression genes (DEGs) were detected between Group A, in which 7,723 genes were upregulated and 8,351 genes were downregulated by RNA sequencing. Similarly, 15,705 genes were differentially expressed between group B, in which 7,436 genes were upregulated and 8,269 genes were downregulated. However, only 1,294 genes were differentially expressed between group C, in which 531 genes were upregulated and 763 genes were downregulated. We performed differential gene analysis on three groups of samples according to the Venn diagram and found that 181 differential genes were present. A total of 3,698 and 2,834 unique genes were in groups A and B, while 130 unique genes were in group C.CONCLUSIONS: This study provides metabolome and transcriptome information for three bead ginseng plants. The analysis of the metabolite content showed differences in the attributes of the three bead ginseng, contained mainly flavonoids, phenolic acids as well as terpenes.PMID:37671355 | PMC:PMC10476608 | DOI:10.7717/peerj.16034

Cureus. 2023 Aug 5;15(8):e42985. doi: 10.7759/cureus.42985. eCollection 2023 Aug.ABSTRACTBackground Basal, reflex, and emotional tears differ in chemical components. It is not yet known whether chemical differences exist in tears of different emotions. We investigated the biochemical basis of emotional tears by performing non-targeted metabolomics analyses of positive and negative emotional tears of humans. Methods Samples of reflex, negative, and positive emotional tears were obtained from 12 healthy college participants (11 females and one male). Untargeted metabolomics was performed to identify metabolites in different types of tears. The differentially altered metabolites were screened and assessed using univariate and multivariate analyses. Results The orthogonal partial least squares discriminant analysis model showed that reflex, negative, and positive emotional tears were clearly separated. A total of 133 significantly differentially expressed metabolites of electrospray ionization source (ESI-) mode were identified between negative and positive emotional tears. The top 50 differentially expressed metabolites between negative and positive emotional tears were highly correlated. Pathway analysis revealed that secretion of negative emotional tears was associated with some synapses in the brain, regulation of a series of endocrine hormones, including the estrogen signaling pathway, and inflammation activities, while secretion of positive emotional tears was correlated with biotin and caffeine metabolism. Conclusions It is indicated that metabolic profiles of reflex, positive, and negative emotional tears of humans are distinct, and secretion of the tears involves distinct biological activities. Therefore, we present a chemical method for detecting human emotions, which may become a powerful tool for the diagnosis of mental diseases and the identification of fake tears.PMID:37671209 | PMC:PMC10476548 | DOI:10.7759/cureus.42985

Open Life Sci. 2023 Aug 31;18(1):20220708. doi: 10.1515/biol-2022-0708. eCollection 2023.ABSTRACTNucleosides, organic acids, and amino acids separated from Morchella esculenta are well known for their nutritional value and flavor. However, how to increase their content in a better way has been a challenge. In this study, the effect of adding jujube kernel on the active components of M. esculenta was investigated by untargeted metabolomics using UPLC-MS/MS. A total of 1,243 metabolites were identified, of which 262 metabolites (21.078%) were organic acids and derivatives, 245 metabolites (19.71%) were lipids and lipid-like molecules, and 26 metabolites (2.092%) were nucleosides, nucleotides, and analogues. Subsequently, differential metabolites between groups were screened by the orthogonal partial least squares-discriminant analysis model, which showed that 256 metabolites were identified as significantly different for the positive ion model and 149 for the negative ion model. Moreover, significant differential metabolites (VIP > 1, P < 0.05) in annotation of kyoto encyclopedia of genes and genomes pathway were investigated, which showed that ABC transporters were the most commonly observed transporters, followed by pyrimidine metabolism and purine metabolism. The results indicated that the main components of jujube kernel might be conducive to the accumulation of nucleoside organic acids and amino acid metabolites in M. esculenta. These results provide important information for the understanding of more suitable way for cultivation of M. esculenta.PMID:37671097 | PMC:PMC10476485 | DOI:10.1515/biol-2022-0708

Cell Rep Methods. 2023 Jul 26;3(8):100539. doi: 10.1016/j.crmeth.2023.100539. eCollection 2023 Aug 28.ABSTRACTThe metabolic "handshake" between the microbiota and its mammalian host is a complex, dynamic process with major influences on health. Dissecting the interaction between microbial species and metabolites found in host tissues has been a challenge due to the requirement for invasive sampling. Here, we demonstrate that secondary electrospray ionization-mass spectrometry (SESI-MS) can be used to non-invasively monitor metabolic activity of the intestinal microbiome of a live, awake mouse. By comparing the headspace metabolome of individual gut bacterial culture with the "volatilome" (metabolites released to the atmosphere) of gnotobiotic mice, we demonstrate that the volatilome is characteristic of the dominant colonizing bacteria. Combining SESI-MS with feeding heavy-isotope-labeled microbiota-accessible sugars reveals the presence of microbial cross-feeding within the animal intestine. The microbiota is, therefore, a major contributor to the volatilome of a living animal, and it is possible to capture inter-species interaction within the gut microbiota using volatilome monitoring.PMID:37671025 | PMC:PMC10475793 | DOI:10.1016/j.crmeth.2023.100539

Front Endocrinol (Lausanne). 2023 Aug 21;14:1180415. doi: 10.3389/fendo.2023.1180415. eCollection 2023.ABSTRACTBACKGROUND AND PURPOSE: Nonproliferative diabetic retinopathy (NPDR) occurs in the early stages of Diabetic retinopathy (DR), and the study of its metabolic markers will help to prevent DR. Hence, we aimed to establish a risk score based on multiple metabolites through untargeted metabolomic analysis of venous blood from NPDR patients and diabetic non-DR patients.EXPERIMENTAL APPROACH: Untargeted metabolomics of venous blood samples from patients with NPDR, diabetes melitus without DR were performed using high-performance liquid chromatography-mass spectrometry.RESULTS: Detailed metabolomic evaluation showed distinct clusters of metabolites in plasma samples from patients with NPDR and diabetic non-DR patients. NPDR patients had significantly higher levels of phenylacetylglycine, L-aspartic acid, tiglylglycine, and 3-sulfinato-L-alaninate, and lower level of indolelactic acid, threonic acid, L-arginine (Arg), and 4-dodecylbenzenesulfonic acid compared to control. The expression profiles of these eight NPDR risk-related characteristic metabolites were analyzed using Cox regression to establish a risk score model. Subsequently, univariate and multivariate Cox regression analyses were used to determine that this risk score model was a predictor of independent prognosis for NPDR.CONCLUSIONS: Untargeted metabolome analysis of blood metabolites revealed unreported metabolic alterations in NPDR patients compared with those in diabetic non-DR patients or MH. In the venous blood, we identified depleted metabolites thA and Arg, indicating that they might play a role in NPDR development.PMID:37670880 | PMC:PMC10476524 | DOI:10.3389/fendo.2023.1180415

Front Plant Sci. 2023 Aug 21;14:1247913. doi: 10.3389/fpls.2023.1247913. eCollection 2023.NO ABSTRACTPMID:37670867 | PMC:PMC10476098 | DOI:10.3389/fpls.2023.1247913

Front Plant Sci. 2023 Aug 21;14:1273010. doi: 10.3389/fpls.2023.1273010. eCollection 2023.NO ABSTRACTPMID:37670864 | PMC:PMC10476088 | DOI:10.3389/fpls.2023.1273010

iScience. 2023 Aug 14;26(9):107619. doi: 10.1016/j.isci.2023.107619. eCollection 2023 Sep 15.ABSTRACTIgG antibodies are important mediators of vaccine-induced immunity through complement- and Fc receptor-dependent effector functions. Both are influenced by the composition of the conserved N-linked glycan located in the IgG Fc domain. Here, we compared the anti-Spike (S) IgG1 Fc glycosylation profiles in response to mRNA, adenoviral, and protein-based COVID-19 vaccines by mass spectrometry (MS). All vaccines induced a transient increase of antigen-specific IgG1 Fc galactosylation and sialylation. An initial, transient increase of afucosylated IgG was induced by membrane-encoding S protein formulations. A fucose-sensitive ELISA for antigen-specific IgG (FEASI) exploiting FcγRIIIa affinity for afucosylated IgG was used as an orthogonal method to confirm the LC-MS-based afucosylation readout. Our data suggest that vaccine-induced anti-S IgG glycosylation is dynamic, and although variation is seen between different vaccine platforms and individuals, the evolution of glycosylation patterns display marked overlaps.PMID:37670790 | PMC:PMC10475480 | DOI:10.1016/j.isci.2023.107619

Zhonghua Bing Li Xue Za Zhi. 2023 Sep 8;52(9):981-984. doi: 10.3760/cma.j.cn112151-20221202-01019.ABSTRACT空间代谢组学是基于质谱成像技术，对组织中代谢物的种类、含量、空间分布差异进行分析，具有无需标记、免基质、灵敏度高的特点，相比传统代谢组学增加了对空间信息的研究。本文介绍代谢组学和质谱成像技术以及它们的研究现状，重点综述空间代谢组学在肿瘤各个领域的应用，介绍了空间代谢组学技术的现有瓶颈并展望了其未来发展方向。.PMID:37670638 | DOI:10.3760/cma.j.cn112151-20221202-01019

Nucleic Acids Res. 2023 Sep 6:gkad725. doi: 10.1093/nar/gkad725. Online ahead of print.ABSTRACTTranslational fidelity is critical for microbial fitness, survival and stress responses. Much remains unknown about the genetic and environmental control of translational fidelity and its single-cell heterogeneity. In this study, we used a high-throughput fluorescence-based assay to screen a knock-out library of Escherichia coli and identified over 20 genes critical for stop-codon readthrough. Most of these identified genes were not previously known to affect translational fidelity. Intriguingly, we show that several genes controlling metabolism, including cyaA and crp, enhance stop-codon readthrough. CyaA catalyzes the synthesis of cyclic adenosine monophosphate (cAMP). Combining RNA sequencing, metabolomics and biochemical analyses, we show that deleting cyaA impairs amino acid catabolism and production of ATP, thus repressing the transcription of rRNAs and tRNAs to decrease readthrough. Single-cell analyses further show that cAMP is a major driver of heterogeneity in stop-codon readthrough and rRNA expression. Our results highlight that carbon metabolism is tightly coupled with stop-codon readthrough.PMID:37670559 | DOI:10.1093/nar/gkad725

Proteomics. 2023 Sep 5:e2300032. doi: 10.1002/pmic.202300032. Online ahead of print.ABSTRACTMetabolomics, the systematic measurement of small molecules (<1000 Da) in a given biological sample, is a fast-growing field with many different applications. In contrast to transcriptomics and proteomics, sharing of data is not as widespread in metabolomics, though more scientists are sharing their data nowadays. However, to improve data analysis tools and develop new data analytical approaches and to improve metabolite annotation and identification, sharing of reference data is crucial. Here, different possibilities to share (metabolomics) data are reviewed and some recent approaches and applications regarding the (re-)use and (re-)analysis are highlighted.PMID:37670538 | DOI:10.1002/pmic.202300032

Clin Transl Med. 2023 Sep;13(9):e1392. doi: 10.1002/ctm2.1392.NO ABSTRACTPMID:37670478 | DOI:10.1002/ctm2.1392

WIREs Mech Dis. 2023 Sep 5:e1628. doi: 10.1002/wsbm.1628. Online ahead of print.ABSTRACTGlaucoma is a heterogeneous group of progressive diseases that leads to irreversible blindness. Secondary glaucoma refers to glaucoma caused by a known underlying condition. Pseudoexfoliation and pigment dispersion syndromes are common causes of secondary glaucoma. Their respective deposits may obstruct the trabecular meshwork, leading to aqueous humor outflow resistance, ocular hypertension, and optic neuropathy. There are no disease-specific interventions available for either. Pseudoexfoliation syndrome is characterized by fibrillar deposits (pseudoexfoliative material) on anterior segment structures. Over a decade of multiomics analyses taken together with the current knowledge on pseudoexfoliative glaucoma warrant a re-think of mechanistic possibilities. We propose that the presence of nucleation centers (e.g., vitamin D binding protein), crosslinking enzymes (e.g., transglutaminase 2), aberrant extracellular matrix, flawed endocytosis, and abnormal aqueous-blood barrier contribute to the formation of proteolytically resistant pseudoexfoliative material. Pigment dispersion syndrome is characterized by abnormal iridolenticular contact that disrupts iris pigment epithelium and liberates melanin granules. Iris melanogenesis is aberrant in this condition. Cytotoxic melanogenesis intermediates leak out of melanosomes and cause iris melanocyte and pigment epithelium cell death. Targeting melanogenesis can likely decrease the risk of pigmentary glaucoma. Skin and melanoma research provides insights into potential therapeutics. We propose that specific prostanoid agonists and fenofibrates may reduce melanogenesis by inhibiting cholesterol internalization and de novo synthesis. Additionally, melatonin is a potent melanogenesis suppressor, antioxidant, and hypotensive agent, rendering it a valuable agent for pigmentary glaucoma. In pseudoexfoliative glaucoma, where environmental insults drive pseudoexfoliative material formation, melatonin's antioxidant and hypotensive properties may offer adjunct therapeutic benefits. This article is categorized under: Neurological Diseases > Molecular and Cellular Physiology.PMID:37669762 | DOI:10.1002/wsbm.1628

Environ Pollut. 2023 Sep 3:122486. doi: 10.1016/j.envpol.2023.122486. Online ahead of print.ABSTRACTSulfadiazine and its derivatives (sulfonamides, SAs) could induce distinct biotoxic, metabolic and physiological abnormalities, potentially due to their subtle structural differences. This study conducted an in-depth investigation on the interactions between SA homologues, i.e. sulfadiazine (SD), sulfamerazine (SD1), and sulfamethazine (SD2), and the key metabolic enzyme (glycosyltransferase, GT) in rice (Oryza sativa L.). Untargeted screening of SA metabolites revealed that GT-catalyzed glycosylation was the primary transformation pathway of SAs in rice. Molecular docking identified that the binding sites of SAs on GT (D0TZD6) were responsible for transferring sugar moiety to synthesize polysaccharides and detoxify SAs. Specifically, amino acids in the GT-binding cavity (e.g., GLY487 and CYS486) formed stable hydrogen bonds with SAs (e.g., the sulfonamide group of SD). Molecular dynamics simulations revealed that SAs induced conformational changes in GT ligand binding domain, which was supported by the significantly decreased GT activity and gene expression level. As evidenced by proteomics and metabolomics, SAs inhibited the transfer and synthesis of sugar but stimulated sugar decomposition in rice leaves, leading to the accumulation of mono- and disaccharides in rice leaves. While the differences in the increased sugar content by SD (24.3%, compared with control), SD1 (11.1%), and SD2 (6.24%) can be attributed to their number of methyl groups (0, 1, 2, respectively), which determined the steric hindrance and hydrogen bonds formation with GT. This study suggested that the disturbances on crop sugar metabolism by homologues contaminants are determined by the interaction between the contaminants and the target enzyme, and are greatly dependent on the steric hindrance effects contributed by their side chains. The results are of importance to identify priority pollutants and ensure crop quality in contaminated fields.PMID:37669699 | DOI:10.1016/j.envpol.2023.122486

Biol Sex Differ. 2023 Sep 5;14(1):56. doi: 10.1186/s13293-023-00539-2.ABSTRACTBACKGROUND: Exercise training elicits changes in muscle physiology, epigenomics, transcriptomics, and proteomics, with males and females exhibiting differing physiological responses to exercise training. However, the molecular mechanisms contributing to the differing adaptations between the sexes are poorly understood.METHODS: We performed a meta-analysis for sex differences in skeletal muscle DNA methylation following an endurance training intervention (Gene SMART cohort and E-MTAB-11282 cohort). We investigated for sex differences in the skeletal muscle proteome following an endurance training intervention (Gene SMART cohort). Lastly, we investigated whether the methylome and proteome are associated with baseline cardiorespiratory fitness (maximal oxygen consumption; VO2max) in a sex-specific manner.RESULTS: Here, we investigated for the first time, DNA methylome and proteome sex differences in response to exercise training in human skeletal muscle (n = 78; 50 males, 28 females). We identified 92 DNA methylation sites (CpGs) associated with exercise training; however, no CpGs changed in a sex-dependent manner. In contrast, we identified 189 proteins that are differentially expressed between the sexes following training, with 82 proteins differentially expressed between the sexes at baseline. Proteins showing the most robust sex-specific response to exercise include SIRT3, MRPL41, and MBP. Irrespective of sex, cardiorespiratory fitness was associated with robust methylome changes (19,257 CpGs) and no proteomic changes. We did not observe sex differences in the association between cardiorespiratory fitness and the DNA methylome. Integrative multi-omic analysis identified sex-specific mitochondrial metabolism pathways associated with exercise responses. Lastly, exercise training and cardiorespiratory fitness shifted the DNA methylomes to be more similar between the sexes.CONCLUSIONS: We identified sex differences in protein expression changes, but not DNA methylation changes, following an endurance exercise training intervention; whereas we identified no sex differences in the DNA methylome or proteome response to lifelong training. Given the delicate interaction between sex and training as well as the limitations of the current study, more studies are required to elucidate whether there is a sex-specific training effect on the DNA methylome. We found that genes involved in mitochondrial metabolism pathways are differentially modulated between the sexes following endurance exercise training. These results shed light on sex differences in molecular adaptations to exercise training in skeletal muscle.PMID:37670389 | DOI:10.1186/s13293-023-00539-2

Orphanet J Rare Dis. 2023 Sep 5;18(1):273. doi: 10.1186/s13023-023-02885-1.ABSTRACTBACKGROUND: Duchenne muscular dystrophy (DMD) is a fatal genetic muscle-wasting disease that affects 1 in 5000 male births with no current cure. Despite great progress has been made in the research of DMD, its underlying pathological mechanism based on the metabolomics is still worthy of further study. Therefore, it is necessary to gain a deeper understanding of the mechanisms or pathogenesis underlying DMD, which may reveal potential therapeutic targets and/or biomarkers.RESULTS: Plasma samples from 42 patients with DMD from a natural history study and 40 age-matched healthy volunteers were subjected to a liquid chromatography-mass spectrometry-based non-targeted metabolomics approach. Acquired metabolic data were evaluated by principal component analysis, partial least squares-discriminant analysis, and metabolic pathway analysis to explore distinctive metabolic patterns in patients with DMD. Differentially expressed metabolites were identified using publicly available and integrated databases. By comparing the DMD and healthy control groups, 25 differential metabolites were detected, including amino acids, unsaturated fatty acids, carnitine, lipids, and metabolites related to the gut microbiota. Correspondingly, linoleic acid metabolism, D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism, and alanine, aspartate, and glutamate metabolism were significantly altered in patients with DMD, compared with those of healthy volunteers.CONCLUSIONS: Our study demonstrated the abnormal metabolism of amino acids, energy, and lipids in patients with DMD, consistent with pathological features, such as recurrent muscle necrosis and regeneration, interstitial fibrosis, and fat replacement. Additionally, we found that metabolites of intestinal flora were disordered in DMD patients, providing support for treatment of intestinal microbia disturbance in DMD diseases. Our study provides a new research strategy for understanding the pathogenesis of DMD.PMID:37670327 | DOI:10.1186/s13023-023-02885-1

Genet Sel Evol. 2023 Sep 5;55(1):61. doi: 10.1186/s12711-023-00835-w.ABSTRACTBACKGROUND: Metabolomics measures an intermediate stage between genotype and phenotype, and may therefore be useful for breeding. Our objectives were to investigate genetic parameters and accuracies of predicted breeding values for malting quality (MQ) traits when integrating both genomic and metabolomic information. In total, 2430 plots of 562 malting spring barley lines from three years and two locations were included. Five MQ traits were measured in wort produced from each plot. Metabolomic features used were 24,018 nuclear magnetic resonance intensities measured on each wort sample. Methods for statistical analyses were genomic best linear unbiased prediction (GBLUP) and metabolomic-genomic best linear unbiased prediction (MGBLUP). Accuracies of predicted breeding values were compared using two cross-validation strategies: leave-one-year-out (LOYO) and leave-one-line-out (LOLO), and the increase in accuracy from the successive inclusion of first, metabolomic data on the lines in the validation population (VP), and second, both metabolomic data and phenotypes on the lines in the VP, was investigated using the linear regression (LR) method.RESULTS: For all traits, we saw that the metabolome-mediated heritability was substantial. Cross-validation results showed that, in general, prediction accuracies from MGBLUP and GBLUP were similar when phenotypes and metabolomic data were recorded on the same plots. Results from the LR method showed that for all traits, except one, accuracy of MGBLUP increased when including metabolomic data on the lines of the VP, and further increased when including also phenotypes. However, in general the increase in accuracy of MGBLUP when including both metabolomic data and phenotypes on lines of the VP was similar to the increase in accuracy of GBLUP when including phenotypes on the lines of the VP. Therefore, we found that, when metabolomic data were included on the lines of the VP, accuracies substantially increased for lines without phenotypic records, but they did not increase much when phenotypes were already known.CONCLUSIONS: MGBLUP is a useful approach to combine phenotypic, genomic and metabolomic data for predicting breeding values for MQ traits. We believe that our results have significant implications for practical breeding of barley and potentially many other species.PMID:37670243 | DOI:10.1186/s12711-023-00835-w

Metabolomics. 2023 Sep 5;19(9):79. doi: 10.1007/s11306-023-02042-6.ABSTRACTINTRODUCTION: Stellaria alsine has traditionally been used as both a famine relief food and an alternative medicine in East Asia. Modern pharmacological studies have revealed that S. alsine has various biological effects such as anticancer, anti-hepatoma, anti-inflammatory, and antioxidative effects. However, the anti-inflammatory properties of chemical constituents derived from this plant have not been studied well.OBJECTIVES: To identify potential therapeutic candidate for treating inflammatory diseases such as inflammatory bowel disease (IBD).METHODS: The distribution of chemical compounds was investigated by Global Natural Product Social (GNPS)-based molecular networking (MN) analysis using UPLC-Orbitrap tandem mass spectrometry. The anti-inflammatory and antioxidative effects of S. alsine extracts and fractions were evaluated by measuring interleukin (IL)-8 and reactive oxygen species (ROS) productions.RESULTS: The active EA layer of S. alsine showed the highest percentage of major compounds by feature-based molecular networking. The top candidate structures of EA fraction were rapidly annotated as flavone C- or O-glycosides via an advanced analysis tool, Network Annotation Propagation (NAP). With the GNPS molecular networking-guided isolation strategy, a new C-glycosyl flavone rotamer (1) was isolated. The structures of the major (1a) and minor (1b) rotational isomers were determined by extensive NMR analysis and MS/MS fragmentation. Finally, the anti-inflammatory activity of 1 was predicted by molecular docking simulations with IL-8 protein.CONCLUSION: These results suggested that the compound 1 is a potential therapeutic candidate for inflammatory bowel disease (IBD).PMID:37670170 | DOI:10.1007/s11306-023-02042-6

ISME J. 2023 Sep 5. doi: 10.1038/s41396-023-01501-1. Online ahead of print.ABSTRACTBacterial growth often alters the environment, which in turn can impact interspecies interactions among bacteria. Here, we used an in vitro batch system containing mucin beads to emulate the dynamic host environment and to study its impact on the interactions between two abundant and prevalent human gut bacteria, the primary fermenter Bacteroides thetaiotaomicron and the butyrate producer Roseburia intestinalis. By combining machine learning and flow cytometry, we found that the number of viable B. thetaiotaomicron cells decreases with glucose consumption due to acid production, while R. intestinalis survives post-glucose depletion by entering a slow growth mode. Both species attach to mucin beads, but only viable cell counts of B. thetaiotaomicron increase significantly. The number of viable co-culture cells varies significantly over time compared to those of monocultures. A combination of targeted metabolomics and RNA-seq showed that the slow growth mode of R. intestinalis represents a diauxic shift towards acetate and lactate consumption, whereas B. thetaiotaomicron survives glucose depletion and low pH by foraging on mucin sugars. In addition, most of the mucin monosaccharides we tested inhibited the growth of R. intestinalis but not B. thetaiotaomicron. We encoded these causal relationships in a kinetic model, which reproduced the observed dynamics. In summary, we explored how R. intestinalis and B. thetaiotaomicron respond to nutrient scarcity and how this affects their dynamics. We highlight the importance of understanding bacterial metabolic strategies to effectively modulate microbial dynamics in changing conditions.PMID:37670028 | DOI:10.1038/s41396-023-01501-1