[Differential analysis of aqueous humor metabolomics between presenile cataract and senile cataract].

Objective: To explore the differences in metabolites and metabolic pathways in the aqueous humor between patients with presenile cataracts and senile cataracts. Methods: This metabolomic study was conducted at Tianjin Medical University Eye Hospital from August 2020 to September 2022. Eight patients with presenile cataracts (8 eyes) and 8 patients with senile cataracts (9 eyes) were included. Data were collected, including age, gender, preoperative uncorrected visual acuity, intraocular pressure, lens dysfunction index, and axial length. Aqueous humor and anterior capsule tissue samples were obtained during cataract surgery. Metabolites in the aqueous humor were detected using Liquid Chromatography-Mass Spectrometry in a non-targeted approach. The principal component analysis, differential analysis, clustering analysis, and correlation analysis were performed to identify differentially expressed metabolites. These metabolites were ranked based on the fold change (FC). The receiver operating characteristic (ROC) curve analysis and metabolic enrichment analysis were used to identify differential pathways and potential biomarkers for presenile cataracts. Immunohistochemistry was conducted on anterior capsule tissues, and pyruvate levels were measured by colorimetry to validate metabolomic results. Results: Patients with presenile cataracts included 7 males and 1 female, with a mean age of (37.50±4.90) years. Patients with senile cataracts were 7 males and 1 female, with a mean age of (73.44±5.22) years. Except for age, there were no significant differences in baseline data (P>0.05). A total of 347 differential metabolites were identified, 10 of which were potential biomarkers for presenile cataract according to the ROC curve analysis (all P<0.05), including propoxycaine (log2FC=7.26), 2-methyl-2, 3, 4, 5-tetrahydro-1, 5-benzodiazepine-4-ketone (log2FC=6.35), l-pyroglutamic acid (log2FC=-1.72), leanly-proline (log2FC=-0.77), and choline (log2FC=-0.56) in the positive ion mode, and N-phenylacetyl glutamine (log2FC=-1.84), pyruvate (log2FC=1.07), ascorbic acid (log2FC=0.92), pseudouracil nucleoside (log2FC=-0.68), and palmitic acid (log2FC=-0.51) in the negative ion mode. The metabolic enrichment analysis identified 72 differential pathways (32 cationic and 40 anionic), with significant differences in glutathione metabolism, cysteine and methionine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, and the citric acid cycle (P<0.05). The experimental validation showed reduced lactate dehydrogenase and increased pyruvate levels in patients with presenile cataracts (P<0.05). Conclusions: Pyruvate and nine other metabolites may serve as potential biomarkers for presenile cataracts. Pathways involving glutathione metabolism, cysteine and methionine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, and the citric acid cycle are notably dysregulated in patients with presenile cataracts.

Effect of SlSAHH2 on metabolites in over-expressed and wild-type tomato fruit.

Background: Tomato (Solanum lycopersicum) is an annual or perennial herb that occupies an important position in daily agricultural production. It is an essential food crop for humans and its ripening process is regulated by a number of genes. S-adenosyl-l-homocysteine hydrolase (AdoHcyase, EC 3.3.1.1) is widespread in organisms and plays an important role in regulating biological methylation reactions. Previous studies have revealed that transgenic tomato that over-express SlSAHH2 ripen earlier than the wild-type (WT). However, the differences in metabolites and the mechanisms driving how these differences affect the ripening cycle are unclear. Objective: To investigate the effects of SlSAHH2 on metabolites in over-expressed tomato and WT tomato. Methods: SlSAHH2 over-expressed tomato fruit (OE-5# and OE-6#) and WT tomato fruit at the breaker stage (Br) were selected for non-targeted metabolome analysis. Results: A total of 733 metabolites were identified by mass spectrometry using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the Human Metabolome database (HMDB). The metabolites were divided into 12 categories based on the superclass results and a comparison with the HMDB. The differences between the two databases were analyzed by PLS-DA. Based on a variable important in projection value >1 and P < 0.05, 103 differential metabolites were found between tomato variety OE-5# and WT and 63 differential metabolites were found between OE-6# and WT. These included dehydrotomatine, L-serine, and gallic acid amongst others. Many metabolites are associated with fruit ripening and eight common metabolites were found between the OE-5# vs. WT and OE-6# vs. WT comparison groups. The low L-tryptophan expression in OE-5# and OE-6# is consistent with previous reports that its content decreases with fruit ripening. A KEGG pathway enrichment analysis of the significantly different metabolites revealed that in the OE-5# and WT groups, up-regulated metabolites were enriched in 23 metabolic pathways and down-regulated metabolites were enriched in 11 metabolic pathways. In the OE-6# and WT groups, up-regulated metabolites were enriched in 29 pathways and down-regulated metabolites were enriched in six metabolic pathways. In addition, the differential metabolite changes in the L-serine to flavonoid transformation metabolic pathway also provide evidence that there is a phenotypic explanation for the changes in transgenic tomato. Discussion: The metabolomic mechanism controlling SlSAHH2 promotion of tomato fruit ripening has been further elucidated.

Multi-omics reveals new links between Fructosamine-3-Kinase (FN3K) and core metabolic pathways.

Fructosamine-3-kinases (FN3Ks) are a conserved family of repair enzymes that phosphorylate reactive sugars attached to lysine residues in peptides and proteins. Although FN3Ks are present across the Tree of Life and share detectable sequence similarity to eukaryotic protein kinases, the biological processes regulated by these kinases are largely unknown. To address this knowledge gap, we leveraged the FN3K CRISPR Knock-Out (KO) HepG2 cell line alongside an integrative multi-omics study combining transcriptomics, metabolomics, and interactomics to place these enzymes in a pathway context. The integrative analyses revealed the enrichment of pathways related to oxidative stress response, lipid biosynthesis (cholesterol and fatty acids), and carbon and co-factor metabolism. Moreover, enrichment of nicotinamide adenine dinucleotide (NAD) binding proteins and localization of human FN3K (HsFN3K) to mitochondria suggests potential links between FN3K and NAD-mediated energy metabolism and redox balance. We report specific binding of HsFN3K to NAD compounds in a metal and concentration-dependent manner and provide insight into their binding mode using modeling and experimental site-directed mutagenesis. Our studies provide a framework for targeting these understudied kinases in diabetic complications and metabolic disorders where redox balance and NAD-dependent metabolic processes are altered.

Proteomic and metabolomic analysis of GH deficiency-induced NAFLD in hypopituitarism: insights into oxidative stress.

Objective: Individuals with hypopituitarism (HPs) have an increased risk of developing non-alcoholic fatty liver disease (NAFLD)/non-alcoholic steatohepatitis (NASH) due to growth hormone deficiency (GHD). We aimed to investigate the possible mechanisms underlying the relationship between GHD and NAFLD using proteomic and metabolomic insights. Methods: Serum metabolic alternations were assessed in male HPs using untargeted metabolomics. A rat model of HP was established through hypophysectomy, followed by recombinant human growth hormone (rhGH) intervention. The mechanisms underlying GHD-mediated NAFLD were elucidated through the application of label-free proteomics and phosphorylation proteomics. Results: Metabolomic analysis revealed that biomarkers of mitochondrial dysfunction and oxidative stress, such as alanine, lactate, and creatine, were significantly elevated in HPs compared to age-matched controls. In rats, hypophysectomy led to marked hepatic steatosis, lipid peroxidation, and reduced glutathione (GSH), which were subsequently modulated by rhGH replacement. Proteomic analysis identified cytochrome P450s, mitochondrial translation elongation, and PPARA activating genes as the major distinguishing pathways in hypophysectomized rats. The processes of fatty acid transport, synthesis, oxidation, and NADP metabolism were tightly described. An enhanced regulation of peroxisome ß-oxidation and ω-oxidation, together with a decreased NADPH regeneration, may exacerbate oxidative stress. Phosphoproteome data showed downregulation of JAK2-STAT5B and upregulation of mTOR signaling pathway. Conclusions: This study identified proteo-metabolomic signatures associated with the development of NAFLD in pituitary GHD. Evidence was found of oxidative stress imbalance resulting from abnormal fatty acid oxidation and NADPH regeneration, highlighting the role of GH deficiency in the development of NAFLD.

Identification of blood exosomal metabolomic profiling for high-altitude cerebral edema.

High-altitude cerebral edema (HACE) is a severe neurological condition that can occur at high altitudes. It is characterized by the accumulation of fluid in the brain, leading to a range of symptoms, including severe headache, confusion, loss of coordination, and even coma and death. Exosomes play a crucial role in intercellular communication, and their contents have been found to change in various diseases. This study analyzed the metabolomic characteristics of blood exosomes from HACE patients compared to those from healthy controls (HCs) with the aim of identifying specific metabolites or metabolic pathways associated with the development of HACE conditions. A total of 21 HACE patients and 21 healthy controls were recruited for this study. Comprehensive metabolomic profiling of the serum exosome samples was conducted using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC‒MS/MS). Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed to identify the metabolic pathways affected in HACE patients. Twenty-six metabolites, including ( +)-camphoric acid, choline, adenosine, adenosine 5'-monophosphate, deoxyguanosine 5'-monophosphate, guanosine, and hypoxanthine-9-ß-D-arabinofuranoside, among others, exhibited significant changes in expression in HACE patients compared to HCs. Additionally, these differentially abundant metabolites were confirmed to be potential biomarkers for HACE. KEGG pathway enrichment analysis revealed several pathways that significantly affect energy metabolism regulation (such as purine metabolism, thermogenesis, and nucleotide metabolism), estrogen-related pathways (the estrogen signaling pathway, GnRH signaling pathway, and GnRH pathway), cyclic nucleotide signaling pathways (the cGMP-PKG signaling pathway and cAMP signaling pathway), and hormone synthesis and secretion pathways (renin secretion, parathyroid hormone synthesis, secretion and action, and aldosterone synthesis and secretion). In patients with HACE, adenosine, guanosine, and hypoxanthine-9-ß-D-arabinofuranoside were negatively correlated with height. Deoxyguanosine 5'-monophosphate is negatively correlated with weight and BMI. Additionally, LPE (18:2/0:0) and pregnanetriol were positively correlated with age. This study identified potential biomarkers for HACE and provided valuable insights into the underlying metabolic mechanisms of this disease. These findings may lead to potential targets for early diagnosis and therapeutic intervention in HACE patients.

Unconventional raw materials used in beer and beer-like beverages production: Impact on metabolomics and sensory profile.

Beer is the third most consumed beverage in the world, trailing only water and tea but ranking first among alcoholic beverages. In recent years, producers and researchers have shown a growing interest in brewing diversification and innovation, due to of the widespread consumption of beer. In order to create beers and beer-like products with unique and consumer-pleasing characteristics, the use of unconventional raw materials has become a subject of intensive research. The purpose of this paper is to identify, evaluate and summarize the findings of all relevant unconventional raw materials used in relevant scientific studies, as well as the effect on the metabolomics of beer and beer-like beverages.For the enhancement of beer characteristics, the production process may involve the use of an extremely diverse variety of unconventional raw materials that are not included on thelist of usual ingredients for the beer industry. However, the general trend is to use locally available ingredients as well as functional ingredients. Twoof the most studied functional characteristics involve phenolic compounds and antioxidant activity, which is why the fruit is by far the most commonly used adjunct category, as fruits are particularly important sources of polyphenols and antioxidants. Other uncommon adjuncts used in brewing includeplants, starch sources, spices or even propolis. Moreover, unconventional raw materials are used to enhance the sensory profile by create new characteristics such as new tastes and flavors, accentuation of the cooling sensation or even increasing acceptability among potential consumers, who do not appreciate traditional beers due to their specific characteristics.

Nucleolin myocardial-specific knockout exacerbates glucose metabolism disorder in endotoxemia-induced myocardial injury.

Background: Sepsis-induced myocardial injury, as one of the important complications of sepsis, can significantly increase the mortality of septic patients. Our previous study found that nucleolin affected mitochondrial function in energy synthesis and had a protective effect on septic cardiomyopathy in mice. During sepsis, glucose metabolism disorders aggravated myocardial injury and had a negative effect on septic patients. Objectives: We investigated whether nucleolin could regulate glucose metabolism during endotoxemia-induced myocardial injury. Methods: The study tested whether the nucleolin cardiac-specific knockout in the mice could affect glucose metabolism through untargeted metabolomics, and the results of metabolomics were verified experimentally in H9C2 cells. The ATP content, lactate production, and oxygen consumption rate (OCR) were evaluated. Results: The metabolomics results suggested that glycolytic products were increased in endotoxemia-induced myocardial injury, and that nucleolin myocardial-specific knockout altered oxidative phosphorylation-related pathways. The experiment data showed that TNF-α combined with LPS stimulation could increase the lactate content and the OCR values by about 25%, and decrease the ATP content by about 25%. However, interference with nucleolin expression could further decrease ATP content and OCR values by about 10-20% and partially increase the lactate level in the presence of TNF-α and LPS. However, nucleolin overexpression had the opposite protective effect, which partially reversed the decrease in ATP content and the increase in lactate level. Conclusion: Down-regulation of nucleolin can exacerbate glucose metabolism disorders in endotoxemia-induced myocardial injury. Improving glucose metabolism by regulating nucleolin was expected to provide new therapeutic ideas for patients with septic cardiomyopathy.

Integrated physiological, transcriptomic and metabolomic analyses provide insights into phosphorus-mediated cadmium detoxification in Salix caprea roots.

Phosphorus (P) plays a crucial role in facilitating plant adaptation to cadmium (Cd) stress. However, the molecular mechanisms underlying P-mediated responses to Cd stress in roots remain elusive. This study investigates the effects of P on the growth, physiology, transcriptome, and metabolome of Salix caprea under Cd stress. The results indicate that Cd significantly inhibits plant growth, while sufficient P alleviates this inhibition. Under Cd exposure, P sufficiency resulted in increased Cd accumulation in roots, along with reduced oxidative stress levels (superoxide anion and hydrogen peroxide contents were reduced by 16.8% and 30.1%, respectively). This phenomenon can be attributed to the enhanced activities of antioxidant enzymes such as superoxide dismutase (SOD) and catalase (CAT), as well as increased levels of antioxidants including ascorbic acid (AsA) and flavonoids under sufficient P conditions. A total of 4208 differentially expressed genes (DEGs) and 552 differentially accumulated metabolites (DAMs) were identified in the transcriptomic and metabolomic analyses, with 2596 DEGs and 113 DAMs identified among treatments with different P levels under Cd stress, respectively. Further combined analyses reveal the potential roles of several pathways in P-mediated Cd detoxification, including flavonoid biosynthesis, ascorbate biosynthesis, and plant hormone signal transduction pathways. Notably, sufficient P upregulates the expression of genes including HMA, ZIP, NRAMP and CAX, all predicted to localize to the cell membrane. This may elucidate the heightened Cd accumulation under sufficient P conditions. These findings provide insights into the roles of P in enhancing plant resistance to Cd stress and improving of phytoremediation.

Metabolomic screening of radioiodine refractory thyroid cancer patients and the underlying chemical mechanism of iodine resistance.

Radioiodine refractory (RAIR) patients do not benefit from iodine-131 therapy. Thus, timely identification of RAIR patients is critical for avoiding ineffective radioactive iodine therapy. In addition, determining the causes of iodine resistance will facilitate the development of novel treatment strategies. This study was comprised of 20 RAIR and 14 non-radioiodine refractory (non-RAIR) thyroid cancer patients. Liquid chromatography-mass spectrometry was used to identify differences in the serum metabolites of RAIR and non-RAIR patients. In addition, chemical assays were performed to determine the effects of the differential metabolites on iodine uptake. Metabolic pathway enrichment analysis of the differential metabolites revealed significant differences in the phenylalanine and tyrosine metabolic pathways. Notably, quinate and shikimic acid, metabolites of the tyrosine pathway, were significantly increased in the RAIR group. In contrast, the phenylalanine pathway metabolites, hippuric acid and 2-phenylacetamide, were markedly decreased in the RAIR group. Thyroid peroxidase plays an important role in catalyzing the iodination of tyrosine residues, while the ionic state of iodine promotes the iodination reaction. Quinate, shikimic acid, hippuric acid, and 2-phenylacetamide were found to be involved in the iodination of tyrosine, which is a key step in thyroid hormone synthesis. Specifically, quinate and shikimic acid were found to inhibit iodination, while hippuric acid and 2-phenylacetamide promoted iodination. Abnormalities in phenylalanine and tyrosine metabolic pathways are closely associated with iodine resistance. Tyrosine is required for thyroid hormone synthesis and could be a potential cause of iodine resistance.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Rapid evaporative ionization mass spectrometry: A survey through 15 years of applications.

Rapid evaporative ionization mass spectrometry (REIMS) is a relatively recent MS technique explored in many application fields, demonstrating high versatility in the detection of a wide range of chemicals, from small molecules (phenols, amino acids, di- and tripeptides, organic acids, and sugars) to larger biomolecules, that is, phospholipids and triacylglycerols. Different sampling devices were used depending on the analyzed matrix (liquid or solid), resulting in distinct performances in terms of automation, reproducibility, and sensitivity. The absence of laborious and time-consuming sample preparation procedures and chromatographic separations was highlighted as a major advantage compared to chromatographic methods. REIMS was successfully used to achieve a comprehensive sample profiling according to a metabolomics untargeted analysis. Moreover, when a multitude of samples were available, the combination with chemometrics allowed rapid sample differentiation and the identification of discriminant features. The present review aims to provide a survey of literature reports based on the use of such analytical technology, highlighting its mode of operation in different application areas, ranging from clinical research, mostly focused on cancer diagnosis for the accurate identification of tumor margins, to the agri-food sector aiming at the safeguard of food quality and security.

[Anti-aging effect and molecular mechanism of Xiyangshen Sanqi Danshen Granules based on metabolomics and bioinformatics].

This study investigated the anti-aging mechanism of Xiyangshen Sanqi Danshen Granules based on metabonomics, network pharmacology, and molecular docking. The aging mice model was induced by intraperitoneal injection of D-galactose(D-gal). Mice were randomly divided into a control group, model group, melatonin group(MT group), and low, medium, and high dose groups of Xiyangshen Sanqi Danshen Granules(XSD-L, XSD-M, and XSD-H). An open-field experiment was conducted, and the expression of cell cycle arrest proteins(p16) and phosphorylated histone family 2A variant(γH2AX) in the brain tissue was detected by immunofluorescence. The expression of interleukin-1ß(IL-1ß) and interleukin-6(IL-6) in the brain tissue was detected by enzyme-linked immunosorbent assay(ELISA). Metabolomics analysis was performed on the serum of mice in control, model, and XSD-H groups to obtain metabolic processes and metabolites. The effective chemical components and potential targets of Xiyangshen Sanqi Danshen Granules were predicted through network pharmacology, and the network diagram of "drug-effective chemical components-key targets" was constructed. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis were carried out, and a protein-protein interaction(PPI) network was constructed to clarify the anti-aging mechanism of Xiyangshen Sanqi Danshen Granules. The results showed that the Xiyangshen Sanqi Danshen Granules could significantly improve the aging degree of D-gal mice, significantly improve the total motion distance and the mean motion speed of D-gal mice, and reduce the rest time. In addition, Xiyangshen Sanqi Danshen Granules could significantly reduce the protein levels of IL-6 and IL-1ß and the expression of p16 and γH2AX in D-gal mice. Compared with the model group, 66 differential metabolites(DMs) were significantly up-regulated, and 91 DMs were down-regulated in the XSD-H group. Moreover, four key metabolic pathways(tryptophan metabolism, glycerophospholipid metabolism, pyrimidine metabolism, and lysine degradation) and 16 biomarkers(lysine, tryptophan, indoleacetaldehyde, PCs, LysoPCs, 3-hydroxyanthranilic acid, melatonin, etc) were screened out. 58 main active components and 62 key targets of Xiyangshen Sanqi Danshen Granules were screened by network pharmacology. The GO functional enrichment analysis found the positive regulation of gene expression, drug response, etc. KEGG pathway enrichment screening involved diabetic complications-related AGE-RAGE signaling pathway, hypoxia inducible factor-1 signaling pathway, etc. Through the PPI network and molecular docking, six potential core targets of STAT3, MAPK1, MAPK14, EGFR, FOS, and STAT1 were screened.

Metabolite profiling of human renal cell carcinoma reveals tissue-origin dominance in nutrient availability.

The tumor microenvironment is a determinant of cancer progression and therapeutic efficacy, with nutrient availability playing an important role. Although it is established that the local abundance of specific nutrients defines the metabolic parameters for tumor growth, the factors guiding nutrient availability in tumor compared to normal tissue and blood remain poorly understood. To define these factors in renal cell carcinoma (RCC), we performed quantitative metabolomic and comprehensive lipidomic analyses of tumor interstitial fluid (TIF), adjacent normal kidney interstitial fluid (KIF), and plasma samples collected from patients. TIF nutrient composition closely resembles KIF, suggesting that tissue-specific factors unrelated to the presence of cancer exert a stronger influence on nutrient levels than tumor-driven alterations. Notably, select metabolite changes consistent with known features of RCC metabolism are found in RCC TIF, while glucose levels in TIF are not depleted to levels that are lower than those found in KIF. These findings inform tissue nutrient dynamics in RCC, highlighting a dominant role of non-cancer-driven tissue factors in shaping nutrient availability in these tumors.

Cancer cells convert nutrients into energy differently compared to healthy cells. This difference in metabolism allows them to grow and divide more quickly and sometimes to migrate to different areas of the body. The environment around cancer cells ­ known as the tumor microenvironment ­ contains a variety of different cells and blood vessels, which are bathed in interstitial fluid. This microenvironment provides nutrients for the cancer cells to metabolize, and therefore influences how well a tumor grows and how it might respond to treatment. Recent advances with techniques such as mass spectrometry, which can measure the chemical composition of a substance, have allowed scientists to measure nutrient levels in the tumor microenvironments of mice. However, it has been more difficult to conduct such studies in humans, as well as to compare the tumor microenvironment to the healthy tissue the tumors arose from. Abbott, Ali, Reinfeld et al. aimed to fill this gap in knowledge by using mass spectrometry to measure the nutrient levels in the tumor microenvironment of 55 patients undergoing surgery to remove kidney tumors. Comparing the type and levels of nutrients in the tumor interstitial fluid, the neighboring healthy kidney and the blood showed that nutrients in the tumor and healthy kidney were more similar to each other than those in the blood. For example, both the tumor and healthy kidney interstitial fluids contained less glucose than the blood. However, the difference between nutrient composition in the tumor and healthy kidney interstitial fluids was insignificant, suggesting that the healthy kidney and its tumor share a similar environment. Taken together, the findings indicate that kidney cancer cells must adapt to the nutrients available in the kidney, rather than changing what nutrients are available in the tissue. Future studies will be required to investigate whether this finding also applies to other types of cancer. A better understanding of how cancer cells adapt to their environments may aid the development of drugs that aim to disrupt the metabolism of tumors.

Antifungal mechanisms investigation of lactic acid bacteria against Aspergillus flavus: through combining microbial metabolomics and co-culture system.

AIMS: To develop antifungal lactic acid bacteria (LAB) and investigate their antifungal mechanisms against Aspergillus flavus in aflatoxin (AF) production. METHODS AND RESULTS: We isolated 179 LABs from cereal-based fermentation starters and investigated their antifungal mechanism against A. flavus through liquid chromatography-mass spectrometry and co-culture analysis techniques. Of the 179 isolates, antifungal activity was identified in Pediococcus pentosaceus, Lactobacillus crustorum, and Weissella paramesenteroides. These LABs reduced AF concentration by (i) inhibiting mycelial growth, (ii) binding AF to the cell wall, and (iii) producing antifungal compounds. Species-specific activities were also observed, with P. pentosaceus inhibiting AF production and W. paramesenteroides showing AF B1 binding activity. In addition, crucial extracellular metabolites for selecting antifungal LAB were involved in the 2',3'-cAMP-adenosine and nucleoside pathways. CONCLUSIONS: This study demonstrates that P. pentosaceus, L. crustorum, and W. paramesenteroides are key LAB strains with distinct antifungal mechanisms against A. flavus, suggesting their potential as biological agents to reduce AF in food materials.

Integration of clinical phenoms and metabolomics facilitates precision medicine for lung cancer.

Lung cancer is a common malignancy that is frequently associated with systemic metabolic disorders. Early detection is pivotal to survival improvement. Although blood biomarkers have been used in its early diagnosis, missed diagnosis and misdiagnosis still exist due to the heterogeneity of lung cancer. Integration of multiple biomarkers or trans-omics results can improve the accuracy and reliability for lung cancer diagnosis. As metabolic reprogramming is a hallmark of lung cancer, metabolites, specifically lipids might be useful for lung cancer detection, yet systematic characterizations of metabolites in lung cancer are still incipient. The present study profiled the polar metabolome and lipidome in the plasma of lung cancer patients to construct an inclusive metabolomic atlas of lung cancer. A comprehensive analysis of lung cancer was also conducted combining metabolomics with clinical phenotypes. Furthermore, the differences in plasma lipid metabolites were compared and analyzed among different lung cancer subtypes. Alcohols, amides, and peptide metabolites were significantly increased in lung cancer, while carboxylic acids, hydrocarbons, and fatty acids were remarkably decreased. Lipid profiling revealed a significant increase in plasma levels of CER, PE, SM, and TAG in individuals with lung cancer as compared to those in healthy controls. Correlation analysis confirmed the association between a panel of metabolites and TAGs. Clinical trans-omics studies elucidated the complex correlations between lipidomic data and clinical phenotypes. The present study emphasized the clinical importance of lipidomics in lung cancer, which involves the correlation between metabolites and the expressions of other omics, ultimately influencing clinical phenotypes. This novel trans-omics network approach would facilitate the development of precision therapy for lung cancer.

Insights into modifiers effects in differential mobility spectrometry: A data science approach for metabolomics and peptidomics.

Utilizing a data-driven approach, this study investigates modifier effects on compensation voltage in differential mobility spectrometry-mass spectrometry (DMS-MS) for metabolites and peptides. Our analysis uncovers specific factors causing signal suppression in small molecules and pinpoints both signal suppression mechanisms and the analytes involved. In peptides, machine learning models discern a relationship between molecular weight, topological polar surface area, peptide charge, and proton transfer-induced signal suppression. The models exhibit robust performance, offering valuable insights for the application of DMS to metabolites and tryptic peptides analysis by DMS-MS.

Analysis of the metabolic profile of humans naturally exposed to RF-EM radiation.

INTRODUCTION: The world is experiencing exponential growth in communication, especially wireless communication. Wireless connectivity has recently become a part of everyone's daily life. Recent developments in low-cost, low-power, and miniature devices contribute to a significant rise in radiofrequency-electromagnetic field (RF-EM) radiation exposure in our environment, raising concern over its effect on biological systems. The inconsistent and conflicting research results make it difficult to draw definite conclusions about how RF-EM radiation affects living things. OBJECTIVES: This study identified two micro-environments based on their level of exposure to cellular RF-EM radiation, one with significantly less exposure and another with very high exposure to RF-EM radiation. Emphasis is given to studying the metabolites in the urine samples of humans naturally exposed to these two different microenvironments to understand short-term metabolic dysregulations. METHODS: Untargeted 1H NMR spectroscopy was employed for metabolomics analyses to identify dysregulated metabolites. A total of 60 subjects were recruited with 5 ml urine samples each. These subjects were divided into two groups: one highly exposed to RF-EM (n = 30) and the other consisting of low-exposure populations (n = 30). RESULTS: The study found that the twenty-nine metabolites were dysregulated. Among them, 19 were downregulated, and 10 were upregulated. In particular, Glyoxylate and dicarboxylate and the TCA cycle metabolism pathway have been perturbed. The dysregulated metabolites were validated using the ROC curve analysis. CONCLUSION: Untargeted urine metabolomics was conducted to identify dysregulated metabolites linked to RF-EM radiation exposure. Preliminary findings suggest a connection between oxidative stress and gut microbiota imbalance. However, further research is needed to validate these biomarkers and understand the effects of RF-EM radiation on human health. Further research is needed with a diverse population.

Integration of metabolomics and transcriptomics provides insights into the molecular mechanism of temporomandibular joint osteoarthritis.

The deficiency of clinically specific biomarkers has made it difficult to achieve an accurate diagnosis of temporomandibular joint osteoarthritis (TMJ-OA) and the insufficient comprehension of the pathogenesis of the pathogenesis of TMJ-OA has posed challenges in advancing therapeutic measures. The combined use of metabolomics and transcriptomics technologies presents a highly effective method for identifying vital metabolic pathways and key genes in TMJ-OA patients. In this study, an analysis of synovial fluid untargeted metabolomics of 6 TMJ-OA groups and 6 temporomandibular joint reducible anterior disc displacement (TMJ-DD) groups was conducted using liquid and gas chromatography mass spectrometry (LC/GC-MS). The differential metabolites (DMs) between TMJ-OA and TMJ-DD groups were analyzed through multivariate analysis. Meanwhile, a transcriptomic dataset (GSE205389) was obtained from the GEO database to analyze the differential metabolism-related genes (DE-MTGs) between TMJ-OA and TMJ-DD groups. Finally, an integrated analysis of DMs and DE-MTGs was carried out to investigate the molecular mechanisms associated with TMJ-OA. The analysis revealed significant differences in the levels of 46 DMs between TMJ-OA and TMJ-DD groups, of which 3 metabolites (L-carnitine, taurine, and adenosine) were identified as potential biomarkers for TMJ-OA. Collectively, differential expression analysis identified 20 DE-MTGs. Furthermore, the integration of metabolomics and transcriptomics analysis revealed that the tricarboxylic acid (TCA) cycle, alanine, aspartate and glutamate metabolism, ferroptosis were significantly enriched. This study provides valuable insights into the metabolic abnormalities and associated pathogenic mechanisms, improving our understanding of TMJOA etiopathogenesis and facilitating potential target screening for therapeutic intervention.

Integrated Metabolomics and Transcriptomics Analysis of Flavonoid Biosynthesis Pathway in Polygonatum cyrtonema Hua.

Flavonoids, a class of phenolic compounds, are one of the main functional components and have a wide range of molecular structures and biological activities in Polygonatum. A few of them, including homoisoflavonoids, chalcones, isoflavones, and flavones, were identified in Polygonatum and displayed a wide range of powerful biological activities, such as anti-cancer, anti-viral, and blood sugar regulation. However, few studies have systematically been published on the flavonoid biosynthesis pathway in Polygonatum cyrtonema Hua. Therefore, in the present study, a combined transcriptome and metabolome analysis was performed on the leaf, stem, rhizome, and root tissues of P. cyrtonema to uncover the synthesis pathway of flavonoids and to identify key regulatory genes. Flavonoid-targeted metabolomics detected a total of 65 active substances from four different tissues, among which 49 substances were first study to identify in Polygonatum, and 38 substances were flavonoids. A total of 19 differentially accumulated metabolites (DAMs) (five flavonols, three flavones, two dihydrochalcones, two flavanones, one flavanol, five phenylpropanoids, and one coumarin) were finally screened by KEGG enrichment analysis. Transcriptome analysis indicated that a total of 222 unigenes encoding 28 enzymes were annotated into three flavonoid biosynthesis pathways, which were "phenylpropanoid biosynthesis", "flavonoid biosynthesis", and "flavone and flavonol biosynthesis". The combined analysis of the metabolome and transcriptome revealed that 37 differentially expressed genes (DEGs) encoding 11 enzymes (C4H, PAL, 4CL, CHS, CHI, F3H, DFR, LAR, ANR, FNS, FLS) and 19 DAMs were more likely to be regulated in the flavonoid biosynthesis pathway. The expression of 11 DEGs was validated by qRT-PCR, resulting in good agreement with the RNA-Seq. Our studies provide a theoretical basis for further elucidating the flavonoid biosynthesis pathway in Polygonatum.

Charting the Cannabis plant chemical space with computational metabolomics.

INTRODUCTION: The chemical classification of Cannabis is typically confined to the cannabinoid content, whilst Cannabis encompasses diverse chemical classes that vary in abundance among all its varieties. Hence, neglecting other chemical classes within Cannabis strains results in a restricted and biased comprehension of elements that may contribute to chemical intricacy and the resultant medicinal qualities of the plant. OBJECTIVES: Thus, herein, we report a computational metabolomics study to elucidate the Cannabis metabolic map beyond the cannabinoids. METHODS: Mass spectrometry-based computational tools were used to mine and evaluate the methanolic leaf and flower extracts of two Cannabis cultivars: Amnesia haze (AMNH) and Royal dutch cheese (RDC). RESULTS: The results revealed the presence of different chemical compound classes including cannabinoids, but extending it to flavonoids and phospholipids at varying distributions across the cultivar plant tissues, where the phenylpropnoid superclass was more abundant in the leaves than in the flowers. Therefore, the two cultivars were differentiated based on the overall chemical content of their plant tissues where AMNH was observed to be more dominant in the flavonoid content while RDC was more dominant in the lipid-like molecules. Additionally, in silico molecular docking studies in combination with biological assay studies indicated the potentially differing anti-cancer properties of the two cultivars resulting from the elucidated chemical profiles. CONCLUSION: These findings highlight distinctive chemical profiles beyond cannabinoids in Cannabis strains. This novel mapping of the metabolomic landscape of Cannabis provides actionable insights into plant biochemistry and justifies selecting certain varieties for medicinal use.