PubMed

BMC Complement Med Ther. 2024 Jul 11;24(1):263. doi: 10.1186/s12906-024-04574-3.ABSTRACTLung cancer is a malignant tumor with highly heterogeneous characteristics. A classic Chinese medicine, Pinellia ternata (PT), was shown to exert therapeutic effects on lung cancer cells. However, its chemical and pharmacological profiles are not yet understood. In the present study, we aimed to reveal the mechanism of PT in treating lung cancer cells through metabolomics and network pharmacology. Metabolomic analysis of two strains of lung cancer cells treated with Pinellia ternata extracts (PTE) was used to identify differentially abundant metabolites, and the metabolic pathways associated with the DEGs were identified by MetaboAnalyst. Then, network pharmacology was applied to identify potential targets against PTE-induced lung cancer cells. The integrated network of metabolomics and network pharmacology was constructed based on Cytoscape. PTE obviously inhibited the proliferation, migration and invasion of A549 and NCI-H460 cells. The results of the cellular metabolomics analysis showed that 30 metabolites were differentially expressed in the lung cancer cells of the experimental and control groups. Through pathway enrichment analysis, 5 metabolites were found to be involved in purine metabolism, riboflavin metabolism and the pentose phosphate pathway, including D-ribose 5-phosphate, xanthosine, 5-amino-4-imidazolecarboxyamide, flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD). Combined with network pharmacology, 11 bioactive compounds were found in PT, and networks of bioactive compound-target gene-metabolic enzyme-metabolite interactions were constructed. In conclusion, this study revealed the complicated mechanisms of PT against lung cancer. Our work provides a novel paradigm for identifying the potential mechanisms underlying the pharmacological effects of natural compounds.PMID:38992647 | DOI:10.1186/s12906-024-04574-3

BMC Bioinformatics. 2024 Jul 11;25(1):234. doi: 10.1186/s12859-024-05845-z.ABSTRACTBACKGROUND: The growing abundance of in vitro omics data, coupled with the necessity to reduce animal testing in the safety assessment of chemical compounds and even eliminate it in the evaluation of cosmetics, highlights the need for adequate computational methodologies. Data from omics technologies allow the exploration of a wide range of biological processes, therefore providing a better understanding of mechanisms of action (MoA) related to chemical exposure in biological systems. However, the analysis of these large datasets remains difficult due to the complexity of modulations spanning multiple biological processes.RESULTS: To address this, we propose a strategy to reduce information overload by computing, based on transcriptomics data, a comprehensive metabolic sub-network reflecting the metabolic impact of a chemical. The proposed strategy integrates transcriptomic data to a genome scale metabolic network through enumeration of condition-specific metabolic models hence translating transcriptomics data into reaction activity probabilities. Based on these results, a graph algorithm is applied to retrieve user readable sub-networks reflecting the possible metabolic MoA (mMoA) of chemicals. This strategy has been implemented as a three-step workflow. The first step consists in building cell condition-specific models reflecting the metabolic impact of each exposure condition while taking into account the diversity of possible optimal solutions with a partial enumeration algorithm. In a second step, we address the challenge of analyzing thousands of enumerated condition-specific networks by computing differentially activated reactions (DARs) between the two sets of enumerated possible condition-specific models. Finally, in the third step, DARs are grouped into clusters of functionally interconnected metabolic reactions, representing possible mMoA, using the distance-based clustering and subnetwork extraction method. The first part of the workflow was exemplified on eight molecules selected for their known human hepatotoxic outcomes associated with specific MoAs well described in the literature and for which we retrieved primary human hepatocytes transcriptomic data in Open TG-GATEs. Then, we further applied this strategy to more precisely model and visualize associated mMoA for two of these eight molecules (amiodarone and valproic acid). The approach proved to go beyond gene-based analysis by identifying mMoA when few genes are significantly differentially expressed (2 differentially expressed genes (DEGs) for amiodarone), bringing additional information from the network topology, or when very large number of genes were differentially expressed (5709 DEGs for valproic acid). In both cases, the results of our strategy well fitted evidence from the literature regarding known MoA. Beyond these confirmations, the workflow highlighted potential other unexplored mMoA.CONCLUSION: The proposed strategy allows toxicology experts to decipher which part of cellular metabolism is expected to be affected by the exposition to a given chemical. The approach originality resides in the combination of different metabolic modelling approaches (constraint based and graph modelling). The application to two model molecules shows the strong potential of the approach for interpretation and visual mining of complex omics in vitro data. The presented strategy is freely available as a python module ( https://pypi.org/project/manamodeller/ ) and jupyter notebooks ( https://github.com/LouisonF/MANA ).PMID:38992584 | DOI:10.1186/s12859-024-05845-z

Int J Biol Macromol. 2024 Jul 9:133779. doi: 10.1016/j.ijbiomac.2024.133779. Online ahead of print.ABSTRACTIntervertebral disc degeneration (IDD) is a highly prevalent musculoskeletal disorder that is associated with considerable morbidity. However, there is currently no drug available that has a definitive therapeutic effect on IDD. In this study, we aimed to identify the molecular features and potential therapeutic targets of IDD through a comprehensive multiomics profiling approach. By integrating transcriptomics, proteomics, and ultrastructural analyses, we discovered dysfunctions in various organelles, including mitochondria, the endoplasmic reticulum, the Golgi apparatus, and lysosomes. Metabolomics analysis revealed a reduction in total phosphatidylcholine (PC) content in IDD. Through integration of multiple omics techniques with disease phenotypes, a pivotal pathway regulated by the lysophosphatidylcholine acyltransferase 1 (LPCAT1)-PC axis was identified. LPCAT1 exhibited low expression levels and exhibited a positive correlation with PC content in IDD. Suppression of LPCAT1 resulted in inhibition of PC synthesis in nucleus pulposus cells, leading to a notable increase in nucleus pulposus cell senescence and damage to cellular organelles. Consequently, PC exhibits potential as a therapeutic agent, as it facilitates the repair of the biomembrane system and alleviates senescence in nucleus pulposus cells via reversal of downregulation of the LPCAT1-PC axis.PMID:38992527 | DOI:10.1016/j.ijbiomac.2024.133779

Cell Mol Gastroenterol Hepatol. 2024 Jul 9:101378. doi: 10.1016/j.jcmgh.2024.101378. Online ahead of print.ABSTRACTBACKGROUND & AIMS: Addition of sialic acids (sialylation) to glycoconjugates is a common capping step of glycosylation. Our study aims to determine the roles of the overall sialylation in intestinal mucosal homeostasis.METHODS: Mice with constitutive deletion of intestinal epithelial sialylation (IEC Slc35a1-/- mice) and mice with inducible deletion of sialylation in intestinal epithelium (TM-IEC Slc35a1-/- mice) were generated, which were used to determine the roles of overall sialylation in intestinal mucosal homeostasis by ex vivo and muti-omics studies.RESULTS: IEC Slc35a1-/- mice developed mild spontaneous microbiota-dependent colitis. Additionally, 30% of IEC Slc35a1-/- mice had spontaneous tumors in the rectum over the age of 12 months. TM-IEC Slc35a1-/- mice were highly susceptible to acute inflammation induced by 1% DSS vs controls. Loss of total sialylation was associated with reduced mucus thickness on fecal sections and within colon tissues. TM-IEC Slc35a1-/- mice showed altered microbiota with an increase in Clostridia disporicum, which is associated a global reduction in the abundance of at least 20 unique taxa; however, metabolomic analysis did not show any significant differences in short-chain fatty acid levels. Treatment with 5-fluorouracil (5-FU) led to more severe small intestine mucositis in the IEC Slc35a1-/- mice vs. WT littermates, which was associated with reduced Lgr5+ cell representation in small intestinal crypts in IEC Slc35a1-/-;Lgr5-GFP mice.CONCLUSIONS: Loss of overall sialylation impairs mucus stability and the stem cell niche leading to microbiota-dependent spontaneous colitis and tumorigenesis.PMID:38992465 | DOI:10.1016/j.jcmgh.2024.101378

Clin Gastroenterol Hepatol. 2024 Jul 9:S1542-3565(24)00598-6. doi: 10.1016/j.cgh.2024.05.048. Online ahead of print.ABSTRACTArtificial intelligence (AI) refers to computer-based methodologies which use data to teach a computer to solve pre-defined tasks; these methods can be applied to identify patterns in large multi-modal data sources. AI applications in inflammatory bowel disease (IBD) includes predicting response to therapy, disease activity scoring of endoscopy, drug discovery, and identifying bowel damage in images. As a complex disease with entangled relationships between genomics, metabolomics, microbiome, and the environment, IBD stands to benefit greatly from methodologies that can handle this complexity. We describe current applications, critical challenges, and propose future directions of AI in IBD.PMID:38992406 | DOI:10.1016/j.cgh.2024.05.048

Sci Total Environ. 2024 Jul 9:174395. doi: 10.1016/j.scitotenv.2024.174395. Online ahead of print.ABSTRACTGinger, a vegetable export from China, is well-known for its spicy flavour and use in traditional Chinese medicine. By examining the interactions of ginger plants' microbiome and metabolome, we can gain insights to advance agriculture, the environment, and other fields. Our study used metataxonomic analysis to investigate ginger plants' prokaryotic and fungal microbiomes in open fields and greenhouses. We also conducted untargeted metabolomic analysis to identify specific metabolites closely associated with ginger microbiome assembly under both agricultural conditions. Various bacteria and fungi were classified as generalists or specialists based on their ability to thrive in different environments and microbial niches. Our results indicate that ginger plants grown in greenhouses have a greater prokaryotic diversity, while those grown in open fields exhibit a greater fungal diversity. We have identified specific co-occurring prokaryotic and fungal genera associated with ginger plant agroecosystems that can enhance the health and growth of ginger plants while maintaining a healthy environment. In the open field these genera include Sphingomonas, Methylobacterium-Methylorubrum, Bacillus, Acidovorax, Rhizobium, Microbacterium, unclassified_f_Comamonadaceae, Herbaspirillum, Klebsiella, Enterobacter, Chryseobacterium, Nocardioides, Subgroup_10, Enterococcus, Pseudomonas, Devosia, g_unclassified_f_Chaetomiaceae, Pseudaleuria, Mortierella, Cheilymenia, and Pseudogymnoascus. In the greenhouse, the enriched genera were Rhizobium, Stenotrophomonas, Aureimonas, Bacillus, Nocardioides, Pseudomonas, Enterobacter, Delftia, Trichoderma, Mortierella, Cheilymenia, Schizothecium, and Actinomucor. Our research has identified several previously unknown microbial genera for ginger plant agroecosystems. Furthermore, our study has important implications for understanding the correlation between ginger's microbiome and metabolome profiles in diverse environments and may pave the way for future research. Specific microbial genera in crop production environments are associated with essential metabolites, including Safingol, Docosatrienoic acid, P-acetaminophen, and Hypoglycin B.PMID:38992353 | DOI:10.1016/j.scitotenv.2024.174395

Sci Rep. 2024 Jul 12;14(1):16083. doi: 10.1038/s41598-024-66779-3.ABSTRACTExtracellular vesicles (EVs) are a new mechanism of cellular communication, by delivering their cargo into target cells to modulate molecular pathways. EV-mediated crosstalk contributes to tumor survival and resistance to cellular stress. However, the role of EVs in B-cell Acute Lymphoblastic Leukaemia (B-ALL) awaits to be thoroughly investigated. We recently published that ActivinA increases intracellular calcium levels and promotes actin polymerization in B-ALL cells. These biological processes guide cytoskeleton reorganization, which is a crucial event for EV secretion and internalization. Hence, we investigated the role of EVs in the context of B-ALL and the impact of ActivinA on this phenomenon. We demonstrated that leukemic cells release a higher number of EVs in response to ActivinA treatment, and they can actively uptake EVs released by other B-ALL cells. Under culture-induced stress conditions, EVs coculture promoted cell survival in B-ALL cells in a dose-dependent manner. Direct stimulation of B-ALL cells with ActivinA or with EVs isolated from ActivinA-stimulated cells was even more effective in preventing cell death. This effect can be possibly ascribed to the increase of vesiculation and modifications of EV-associated microRNAs induced by ActivinA. These data demonstrate that ActivinA boosts EV-mediated B-ALL crosstalk, improving leukemia survival in stress conditions.PMID:38992199 | DOI:10.1038/s41598-024-66779-3

Metallomics. 2024 Jul 11:mfae033. doi: 10.1093/mtomcs/mfae033. Online ahead of print.ABSTRACTIron is essential for life, but its imbalances can lead to severe health implications. Iron deficiency is the most common nutrient disorder worldwide, and iron disregulation in early life has been found to cause long-lasting behavioral, cognitive, and neural effects. However, little is known about the effects of dietary iron on gut microbiome function and metabolism. In this study, we sought to investigate the impact of dietary iron on the fecal metabolome and microbiome by using mice fed with three diets with different iron content: an iron deficient, an iron sufficient (standard), and an iron overload diet for seven weeks. Additionally, we sought to understand whether any observed changes would persist past the 7-week period of diet intervention. To assess this, all feeding groups were switched to a standard diet, and this feeding continued for an additional 7 weeks. Analysis of the fecal metabolome revealed that iron overload and deficiency significantly alter levels of peptides, nucleic acids, and lipids, including di- and tri-peptides containing branched-chain amino acids, inosine and guanosine, and several microbial conjugated bile acids. The observed changes in the fecal metabolome persist long after the switch back to a standard diet, with the cecal gut microbiota composition and function of each group distinct after the 7-week standard diet wash-out. Our results highlight the enduring metabolic consequences of nutritional imbalances, mediated by both host and gut microbiome, which persist after returning to original standard diets.PMID:38992131 | DOI:10.1093/mtomcs/mfae033

Sci Rep. 2024 Jul 11;14(1):16064. doi: 10.1038/s41598-024-67054-1.ABSTRACTMentha haplocalyx essential oil (MEO) has demonstrated inhibitory effects on Fusarium oxysporum. Despite its environmentally friendly properties as a natural product, the limited water solubility of MEO restricts its practical application in the field. The use of nanoemulsion can improve bioavailability and provide an eco-friendly approach to prevent and control Panax notoginseng root rot. In this study, Tween 80 and anhydrous ethanol (at a mass ratio of 3) were selected as carriers, and the ultrasonic method was utilized to produce a nanoemulsion of MEO (MNEO) with an average particle size of 26.07 nm. Compared to MTEO (MEO dissolved in an aqueous solution of 2% DMSO and 0.1% Tween 80), MNEO exhibited superior inhibition against F. oxysporum in terms of spore germination and hyphal growth. Transcriptomics and metabolomics results revealed that after MNEO treatment, the expression levels of certain genes related to glycolysis/gluconeogenesis, starch and sucrose metabolism were significantly suppressed along with the accumulation of metabolites, leading to energy metabolism disorder and growth stagnation in F. oxysporum. In contrast, the inhibitory effect from MTEO treatment was less pronounced. Furthermore, MNEO also demonstrated inhibition on meiosis, ribosome function, and ribosome biogenesis in F. oxysporum growth process. These findings suggest that MNEO possesses enhanced stability and antifungal activity, which effectively hinders F. oxysporum through inducing energy metabolism disorder, meiotic stagnation, as well as ribosome dysfunction, thus indicating its potential for development as a green pesticide for prevention and control P. notoginseng root rot caused by F.oxyosporum.PMID:38992117 | DOI:10.1038/s41598-024-67054-1

Sci Rep. 2024 Jul 11;14(1):16050. doi: 10.1038/s41598-024-66977-z.ABSTRACTIn this study, optical photothermal infrared (O-PTIR) spectroscopy combined with machine learning algorithms were used to evaluate 46 tissue cores of surgically resected cervical lymph nodes, some of which harboured oral squamous cell carcinoma nodal metastasis. The ratios obtained between O-PTIR chemical images at 1252 cm-1 and 1285 cm-1 were able to reveal morphological details from tissue samples that are comparable to the information achieved by a pathologist's interpretation of optical microscopy of haematoxylin and eosin (H&E) stained samples. Additionally, when used as input data for a hybrid convolutional neural network (CNN) and random forest (RF) analyses, these yielded sensitivities, specificities and precision of 98.6 ± 0.3%, 92 ± 4% and 94 ± 5%, respectively, and an area under receiver operator characteristic (AUC) of 94 ± 2%. Our findings show the potential of O-PTIR technology as a tool to study cancer on tissue samples.PMID:38992088 | DOI:10.1038/s41598-024-66977-z

Sci Rep. 2024 Jul 11;14(1):16010. doi: 10.1038/s41598-024-66491-2.ABSTRACTAporosa cardiosperma is a plant species majorly found in the Indian Western Ghats that belongs to the phyllanthaceae family with ethnobotanical importance. Using a Fourier Transform-Infrared Spectrometer (FT-IR) and Gas Chromatography-Mass Spectrometry (GC-MS) for evaluating leaf extracts of A. cardiosperma, significant functional groups and metabolite constituents were determined, and its total flavonoid, phenol, and tannin content were quantified. Further, its antibacterial efficacy was investigated against microorganisms that cause fish and human disease and are resistant to common antibiotics, including Staphylococcus aureus, Bacillus subtilis, Mycobacterium tuberculosis, Klebsiella pneumoniae, Aeromonas hydrophila, and Pseudomonas aeruginosa. Regarding the outcomes of GC-MS analysis, the primary metabolites in the A. cardiosperma leaf extracts were heneicosane (57.06%), silane (13.60%), 1-heptadecene (10.09%), 3-hexadecene (9.99%), and pentadecane (9.54%). In comparison to other solvents, methanolic extract of A. cardiosperma leaves had increased phenolic, flavonoid, and tannin content; these findings are consistent with in vitro antioxidant potential and obtained that the methanolic extract (100 µg/mL) exhibited the higher percentage of inhibition in DPPH (82.35%), FRAP (86.20%), metal chelating (72.32%), and ABTS (86.06%) antioxidant assays respectively. Similar findings were found regarding the antibacterial efficacy against pathogenic bacteria. Comparatively, to other extracts, methanolic extracts showed more significant antibacterial activity at a lower minimum inhibitory concentration (MIC) value (250 µg/mL), whilst ethyl acetate and hexane solvent extracts of A. cardiosperma leaves had higher MIC values 500 µg/mL and 1000 µg/mL respectively. The antimicrobial potential was validated by investigating bacterial growth through the extracts acquired MICs and sub-MICs range. Bacterial growth was completely inhibited at the determined MIC range. In conclusion, A. cardiosperma leaf extract's phytochemical fingerprint has been determined, and its potent antibacterial and antioxidant activities were discovered. These findings of the current study will pave the way for developing herbal treatments from A. cardiosperma for various fish and human diseases.PMID:38992053 | DOI:10.1038/s41598-024-66491-2

Science. 2024 Jul 12;385(6705):174-178. doi: 10.1126/science.adn3856. Epub 2024 Jul 11.ABSTRACTOne of the hallmarks of living organisms is their capacity for self-organization and regeneration, which requires a tight integration of metabolic and genetic networks. We sought to construct a linked metabolic and genetic network in vitro that shows such lifelike behavior outside of a cellular context and generates its own building blocks from nonliving matter. We integrated the metabolism of the crotonyl-CoA/ethyl-malonyl-CoA/hydroxybutyryl-CoA cycle with cell-free protein synthesis using recombinant elements. Our network produces the amino acid glycine from CO2 and incorporates it into target proteins following DNA-encoded instructions. By orchestrating ~50 enzymes we established a basic cell-free operating system in which genetically encoded inputs into a metabolic network are programmed to activate feedback loops allowing for self-integration and (partial) self-regeneration of the complete system.PMID:38991083 | DOI:10.1126/science.adn3856

Crit Rev Anal Chem. 2024 Jul 11:1-25. doi: 10.1080/10408347.2024.2375314. Online ahead of print.ABSTRACTPlant metabolomics, a rapidly advancing field within plant biology, is dedicated to comprehensively exploring the intricate array of small molecules in plant systems. This entails precisely gathering comprehensive chemical data, detecting numerous metabolites, and ensuring accurate molecular identification. Nuclear magnetic resonance (NMR) spectroscopy, with its detailed chemical insights, is crucial in obtaining metabolite profiles. Its widespread application spans various research disciplines, aiding in comprehending chemical reactions, kinetics, and molecule characterization. Biotechnological advancements have further expanded NMR's utility in metabolomics, particularly in identifying disease biomarkers across diverse fields such as agriculture, medicine, and pharmacology. This review covers the stages of NMR-based metabolomics, including historical aspects and limitations, with sample preparation, data acquisition, spectral processing, analysis, and their application parts.PMID:38990786 | DOI:10.1080/10408347.2024.2375314

J Pharm Pharmacol. 2024 Jul 11:rgad102. doi: 10.1093/jpp/rgad102. Online ahead of print.ABSTRACTOBJECTIVE: To explore the effect and anxiolytic mechanism of a natural remedy called Fructus gardeniae (FG).METHODS: The elevated-plus maze (EPM) test was used to confirm the anxiolytic effect of FG. The potential and anxiolytic components, targets, and route processes of FG were investigated using the network pharmacology method in conjunction with metabolomics and molecular docking technologies.RESULTS: FG could greatly enhance the proportion of time and times of opening arms, according to the EPM data. As to the metabolomics findings, a total of 61 distinct metabolites were found, mainly involved in glycine, serine, and threonine metabolism as well as alanine, aspartate, and glutamate metabolism. The primary active ingredients of FG, nicotiflorin, jasminodiol, and crocetin, demonstrated substantial binding affinities with monoamine oxidase A (MAOA), monoamine oxidase A (ACHE), malate dehydrogenase 2 (MDH2), glutamate decarboxylase 2 (GAD2), glutamate decarboxylase 1 (GAD1), and nitric oxide synthase (NOS1), according to the findings of network pharmacology and molecular docking.CONCLUSION: FG exerts an anxiolytic action via targeting MAOA, ACHE, MDH2, GAD2, GAD1, and NOS1, and regulating the metabolism of glycine, serine, and threonine as well as alanine, aspartic acid, and glutamic acid.PMID:38990646 | DOI:10.1093/jpp/rgad102

Anal Chem. 2024 Jul 11. doi: 10.1021/acs.analchem.4c00563. Online ahead of print.ABSTRACTJ-Resolved (J-Res) nuclear magnetic resonance (NMR) spectroscopy is pivotal in NMR-based metabolomics, but practitioners face a choice between time-consuming high-resolution (HR) experiments or shorter low-resolution (LR) experiments which exhibit significant peak overlap. Deep learning neural networks have been successfully used in many fields to enhance quality of natural images, especially with regard to resolution, and therefore offer the prospect of improving two-dimensional (2D) NMR data. Here, we introduce the J-RESRGAN, an adapted and modified generative adversarial network (GAN) for image super-resolution (SR), which we trained specifically for metabolomic J-Res spectra to enhance peak resolution. A novel symmetric loss function was introduced, exploiting the inherent vertical symmetry of J-Res NMR spectra. Model training used simulated high-resolution J-Res spectra of complex mixtures, with corresponding low-resolution spectra generated via blurring and down-sampling. Evaluation of peak pair resolvability on J-RESRGAN demonstrated remarkable improvement in resolution across a variety of samples. In simulated plasma data, 100% of peak pairs exhibited enhanced resolution in super-resolution spectra compared to their low-resolution counterparts. Similarly, enhanced resolution was observed in 80.8-100% of peak pairs in experimental plasma, 85.0-96.7% in urine, 94.4-98.9% in full fat milk, and 82.6-91.7% in orange juice. J-RESRGAN is not sample type, spectrometer or field strength dependent and improvements on previously acquired data can be seen in seconds on a standard desktop computer. We believe this demonstrates the promise of deep learning methods to enhance NMR metabolomic data, and in particular, the power of J-RESRGAN to elucidate overlapping peaks, advancing precision in a wide variety of NMR-based metabolomics studies. The model, J-RESRGAN, is openly accessible for download on GitHub at https://github.com/yanyan5420/J-RESRGAN.PMID:38990576 | DOI:10.1021/acs.analchem.4c00563

Plant J. 2024 Jul 11. doi: 10.1111/tpj.16924. Online ahead of print.ABSTRACTMass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.PMID:38990529 | DOI:10.1111/tpj.16924

Anal Bioanal Chem. 2024 Jul 11. doi: 10.1007/s00216-024-05430-6. Online ahead of print.ABSTRACTBecause of the pathological indication and the physiological functions, bile acids (BAs) have occupied the research hotspot in recent decades. Although extensive efforts have been paid onto BAs sub-metabolome characterization, as the subfamily, BA glucuronides (gluA-BAs) profile is seldom concerned. Here, we made efforts to develop a LC-MS/MS program enabling quantitative gluA-BAs sub-metabolome characterization and to explore the differential species in serum between intrahepatic cholestasis of pregnancy (ICP) patients and healthy subjects. To gain as many authentic gluA-BAs as possible, liver microsomes from humans, rats, and mice were deployed to conjugate glucuronyl group to authentic BAs through in vitro incubation. Eighty gluA-BAs were captured and subsequently served as authentic compounds to correlate MS/MS spectral behaviors to structural features using squared energy-resolved MS program. Optimal collision energy (OCE) of [M-H]->[M-H-176.1]- was jointly administrated by [M-H]- mass and glucuronidation site, and identical exciting energies corresponding to 50% survival rate of 1st-generation fragment ion (EE50) were observed merely when the aglycone of a gluA-BA was consistent with the suspected structure. Through integrating high-resolution m/z, OCE, and EE50 information to identify gluA-BAs in a BAs pool, 97 ones were found and identified, and further, quantitative program was built for all annotated gluA-BAs by assigning OCEs to [M-H]->[M-H-176.1]- ion transitions. Quantitative gluA-BAs sub-metabolome of ICP was different from that of the healthy group. More GCDCA-3-G, GDCA-3-G, TCDCA-7-G, TDCA-3-G, and T-β-MCA-3-G were distributed in the ICP group. Above all, this study not only offered a promising analytical tool for in-depth gluA-BAs sub-metabolome characterization, but also clarified gluA-BAs allowing the differentiation of ICP and healthy subjects.PMID:38990360 | DOI:10.1007/s00216-024-05430-6

Semin Immunopathol. 2024 Jul 11;46(1-2):2. doi: 10.1007/s00281-024-01012-x.ABSTRACTThe gut microbiota, housing trillions of microorganisms within the gastrointestinal tract, has emerged as a critical regulator of host health and homeostasis. Through complex metabolic interactions, these microorganisms produce a diverse range of metabolites that substantially impact various physiological processes within the host. This review aims to delve into the intricate relationships of gut microbiota-derived metabolites and their influence on the host homeostasis. We will explore how these metabolites affect crucial aspects of host physiology, including metabolism, mucosal integrity, and communication among gut tissues. Moreover, we will spotlight the potential therapeutic applications of targeting these metabolites to restore and sustain host equilibrium. Understanding the intricate interplay between gut microbiota and their metabolites is crucial for developing innovative strategies to promote wellbeing and improve outcomes of chronic diseases.PMID:38990345 | DOI:10.1007/s00281-024-01012-x

Microbiol Spectr. 2024 Jul 11:e0404623. doi: 10.1128/spectrum.04046-23. Online ahead of print.ABSTRACTOver-application of chemical fertilizers and continuous cropping obstacles seriously restrict the sustainable development of tobacco production. Localized fertilization of beneficial microbes has potential advantages in achieving higher productivity, but the underlying biological mechanisms of interactions between rhizospheric microorganisms and the related metabolic cycle remain poorly characterized. Here, an integrative analysis of microbiomes with non-targeted metabolomics was performed on 30 soil samples of rhizosphere, root surrounding, and bulk soils from flue-cured tobacco under continuous and non-continuous monocropping systems. The analysis was conducted using UPLC-MS/MS platforms and high-throughput amplicon sequencing targeting the bacterial 16S rRNA gene and fungal ITS gene. The microbial inoculant consisted of Bacillus subtilis, B. velezensis, and B. licheniformis at the ratio of 1:1:1 in effective microbial counts, improved the cured leaf yield and disease resistance of tobacco, and enhanced nicotine and nitrogen contents of tobacco leaves. The bacterial taxa Rhizobium, Pseudomonas, Sphingomonadaceae, and Burkholderiaceae of the phylum Proteobacteria accumulated in high relative abundance and were identified as biomarkers following the application of the microbial inoculant. Under continuous monocropping, metabolomics demonstrated that the application of the microbial inoculant significantly affected the soil metabolite spectrum, and the differential metabolites were significantly enriched to the synthesis and degradation of nicotine (nicotinate and nicotinamide metabolism and biosynthesis of alkaloids derived from nicotinic acid). In addition, microbes were closely related to the accumulation of metabolites through correlation analysis. The interactions between plant roots and rhizospheric microorganisms provide valuable information for understanding how these beneficial microbes affect complex biological processes and the adaption capacity of plants to environments.IMPORTANCEThis study elaborated on how the microbial fertilizer significantly changed overall community structures and metabolite spectrum of rhizospheric microbes, which provide insights into the process of rhizosphere microbial remolding in response to continuous monocropping. we verified the hypothesis that the application of the microbial inoculant in continuous cropping would lead to the selection of distinct microbiota communities by establishing models to correlate biomarkers. Through correlation analysis of the microbiome and metabolome, we proved that rhizospheric microbes were closely related to the accumulation of metabolites, including the synthesis and degradation of nicotine. The interactions between plant roots and rhizospheric microorganisms provide valuable information for understanding how these beneficial microbes affect complex biological processes and the adaption capacity of plants to environments.PMID:38989997 | DOI:10.1128/spectrum.04046-23

Neural Regen Res. 2025 Apr 1;20(4):1042-1057. doi: 10.4103/NRR.NRR-D-23-01604. Epub 2024 Apr 3.ABSTRACTSpinal cord injuries impose a notably economic burden on society, mainly because of the severe after-effects they cause. Despite the ongoing development of various therapies for spinal cord injuries, their effectiveness remains unsatisfactory. However, a deeper understanding of metabolism has opened up a new therapeutic opportunity in the form of metabolic reprogramming. In this review, we explore the metabolic changes that occur during spinal cord injuries, their consequences, and the therapeutic tools available for metabolic reprogramming. Normal spinal cord metabolism is characterized by independent cellular metabolism and intercellular metabolic coupling. However, spinal cord injury results in metabolic disorders that include disturbances in glucose metabolism, lipid metabolism, and mitochondrial dysfunction. These metabolic disturbances lead to corresponding pathological changes, including the failure of axonal regeneration, the accumulation of scarring, and the activation of microglia. To rescue spinal cord injury at the metabolic level, potential metabolic reprogramming approaches have emerged, including replenishing metabolic substrates, reconstituting metabolic couplings, and targeting mitochondrial therapies to alter cell fate. The available evidence suggests that metabolic reprogramming holds great promise as a next-generation approach for the treatment of spinal cord injury. To further advance the metabolic treatment of the spinal cord injury, future efforts should focus on a deeper understanding of neurometabolism, the development of more advanced metabolomics technologies, and the design of highly effective metabolic interventions.PMID:38989936 | DOI:10.4103/NRR.NRR-D-23-01604