PubMed

Metabolites. 2024 May 7;14(5):269. doi: 10.3390/metabo14050269.ABSTRACTMetabolomics can allow for the comprehensive identification of metabolites within biological systems, at given time points, in physiological and pathological conditions. In the last few years, metabolomic analysis has gained popularity both in human and in veterinary medicine, showing great potential for novel applications in clinical activity. The aim of applying metabolomics in clinical practice is understanding the mechanisms underlying pathological conditions and the influence of certain stimuli (i.e., drugs, nutrition, exercise) on body systems, in the attempt of identifying biomarkers that can help in the diagnosis of diseases. Proton Nuclear Magnetic Resonance spectroscopy (1H-NMR) is well tailored to be used as an analytical platform for metabolites' detection at the base of metabolomics studies, due to minimal sample preparation and high reproducibility. In this mini-review article, the scientific production of NMR metabolomic applications to equine medicine is examined. The research works are very different in methodology and difficult to compare. Studies are mainly focused on exercise, reproduction, and nutrition, other than respiratory and musculoskeletal diseases. The available information on this topic is still scant, but a greater collection of data could allow researchers to define new reliable markers to be used in clinical practice for diagnostic and therapeutical purposes.PMID:38786746 | DOI:10.3390/metabo14050269

Metabolites. 2024 May 7;14(5):268. doi: 10.3390/metabo14050268.ABSTRACTMetabolomics has proven to be a sensitive tool for monitoring biochemical processes in cell culture. It enables multi-analysis, clarifying the correlation between numerous metabolic pathways. Together with other analysis, it thus provides a global view of a cell's physiological state. A comprehensive analysis of molecular changes is also required in the case of mesenchymal stem cells (MSCs), which currently represent an essential portion of cells used in regenerative medicine. Reproducibility and correct measurement are closely connected to careful metabolite extraction, and sample preparation is always a critical point. Our study aimed to compare the efficiencies of four harvesting and six extraction methods. Several organic reagents (methanol, ethanol, acetonitrile, methanol-chloroform, MTBE) and harvesting approaches (trypsinization vs. scraping) were tested. We used untargeted nuclear magnetic resonance spectroscopy (NMR) to determine the most efficient method for the extraction of metabolites from human adherent cells, specifically human dermal fibroblasts adult (HDFa) and dental pulp stem cells (DPSCs). A comprehensive dataset of 29 identified and quantified metabolites were determined to possess statistically significant differences in the abundances of several metabolites when the cells were detached mechanically to organic solvent compared to when applying enzymes mainly in the classes of amino acids and peptides for both types of cells. Direct scraping to organic solvent is a method that yields higher abundances of determined metabolites. Extraction with the use of different polar reagents, 50% and 80% methanol, or acetonitrile, mostly showed the same quality. For both HDFa and DPSC cells, the MTBE method, methanol-chloroform, and 80% ethanol extractions showed higher extraction efficiency for the most identified and quantified metabolites Thus, preparation procedures provided a cell sample processing protocol that focuses on maximizing extraction yield. Our approach may be useful for large-scale comparative metabolomic studies of human mesenchymal stem cell samples.PMID:38786745 | DOI:10.3390/metabo14050268

Metabolites. 2024 May 7;14(5):266. doi: 10.3390/metabo14050266.ABSTRACTA major limitation of most metabolomics datasets is the sparsity of pathway annotations for detected metabolites. It is common for less than half of the identified metabolites in these datasets to have a known metabolic pathway involvement. Trying to address this limitation, machine learning models have been developed to predict the association of a metabolite with a "pathway category", as defined by a metabolic knowledge base like KEGG. Past models were implemented as a single binary classifier specific to a single pathway category, requiring a set of binary classifiers for generating the predictions for multiple pathway categories. This past approach multiplied the computational resources necessary for training while diluting the positive entries in the gold standard datasets needed for training. To address these limitations, we propose a generalization of the metabolic pathway prediction problem using a single binary classifier that accepts the features both representing a metabolite and representing a pathway category and then predicts whether the given metabolite is involved in the corresponding pathway category. We demonstrate that this metabolite-pathway features pair approach not only outperforms the combined performance of training separate binary classifiers but demonstrates an order of magnitude improvement in robustness: a Matthews correlation coefficient of 0.784 ± 0.013 versus 0.768 ± 0.154.PMID:38786743 | DOI:10.3390/metabo14050266

Metabolites. 2024 May 6;14(5):262. doi: 10.3390/metabo14050262.ABSTRACTSkeletal muscles are heterogenous tissues composed of different myofiber types that can be classified as slow oxidative, fast oxidative, and fast glycolytic which are distinguished on the basis of their contractile and metabolic properties. Improving oxidative metabolism in skeletal muscles can prevent metabolic diseases and plays a protective role against muscle wasting in a number of neuromuscular diseases. Therefore, achieving a detailed understanding of the factors that regulate myofiber metabolic properties might provide new therapeutic opportunities for these diseases. Here, we investigated whether peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1) is involved in the control of myofiber metabolic behaviors. Indeed, PIN1 controls glucose and lipid metabolism in a number of tissues, and it is also abundant in adult skeletal muscles; however, its role in the control of energy homeostasis in this tissue is still to be defined. To start clarifying this topic, we compared the metabolome of the tibialis anterior muscle (mainly glycolytic) and soleus muscle (oxidative) in wild-type and Pin1 knockout mice with High-Resolution Magic Angle Spinning (HR-MAS) NMR on intact tissues. Our analysis reveals a clear demarcation between the metabolomes in the two types of muscles and allows us to decode a signature able to discriminate the glycolytic versus oxidative muscle phenotype. We also detected some changes in Pin1-depleted muscles that suggest a role for PIN1 in regulating the metabolic phenotype of skeletal muscles.PMID:38786739 | DOI:10.3390/metabo14050262

Metabolites. 2024 May 1;14(5):261. doi: 10.3390/metabo14050261.ABSTRACTJapanese Brown (JBR) cattle have moderately marbled beef compared to the highly marbled beef of Japanese Black (JBL) cattle; however, their skeletal muscle properties remain poorly characterized. To unveil interbreed metabolic differences over the previous results, we explored the metabolome network changes before and after postmortem 7-day aging in the trapezius muscle of the two cattle breeds by employing a deep and high-coverage metabolomics approach. Using both capillary electrophoresis (CE) and ultra-high-performance liquid chromatography (UHPLC)-Fourier transform mass spectrometry (FT/MS), we detected 522 and 384 annotated peaks, respectively, across all muscle samples. The CE-based results showed that the cattle were clearly separated by breed and postmortem age in multivariate analyses. The metabolism related to glutathione, glycolysis, vitamin K, taurine, and arachidonic acid was enriched with differentially abundant metabolites in aged muscles, in addition to amino acid (AA) metabolisms. The LC-based results showed that the levels of bile-acid-related metabolites, such as tauroursodeoxycholic acid (TUDCA), were high in fresh JBR muscle and that acylcarnitines were enriched in aged JBR muscle, compared to JBL muscle. Postmortem aging resulted in an increase in fatty acids and a decrease in acylcarnitine in the muscles of both cattle breeds. In addition, metabolite set enrichment analysis revealed that JBR muscle was distinctive in metabolisms related to pyruvate, glycerolipid, cardiolipin, and mitochondrial energy production, whereas the metabolisms related to phosphatidylethanolamine, nucleotide triphosphate, and AAs were characteristic of JBL. This suggests that the interbreed differences in postmortem trapezius muscle are associated with carnitine/acylcarnitine transport, β-oxidation, tricarboxylic acid cycle, and mitochondrial membrane stability, in addition to energy substrate and AA metabolisms. These interbreed differences may characterize beef quality traits such as the flavor intensity and oxidative stability.PMID:38786738 | DOI:10.3390/metabo14050261

Metabolites. 2024 Apr 30;14(5):258. doi: 10.3390/metabo14050258.ABSTRACTAccurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies, given its significant impact on global mortality and morbidity. Here, we propose a novel deep-learning approach to enhance the prediction of incident MI cases by incorporating metabolomics alongside clinical risk factors. We utilized data from the KORA cohort, including the baseline S4 and follow-up F4 studies, consisting of 1454 participants without prior history of MI. The dataset comprised 19 clinical variables and 363 metabolites. Due to the imbalanced nature of the dataset (78 observed MI cases and 1376 non-MI individuals), we employed a generative adversarial network (GAN) model to generate new incident cases, augmenting the dataset and improving feature representation. To predict MI, we further utilized multi-layer perceptron (MLP) models in conjunction with the synthetic minority oversampling technique (SMOTE) and edited nearest neighbor (ENN) methods to address overfitting and underfitting issues, particularly when dealing with imbalanced datasets. To enhance prediction accuracy, we propose a novel GAN for feature-enhanced (GFE) loss function. The GFE loss function resulted in an approximate 2% improvement in prediction accuracy, yielding a final accuracy of 70%. Furthermore, we evaluated the contribution of each clinical variable and metabolite to the predictive model and identified the 10 most significant variables, including glucose tolerance, sex, and physical activity. This is the first study to construct a deep-learning approach for producing 7-year MI predictions using the newly proposed loss function. Our findings demonstrate the promising potential of our technique in identifying novel biomarkers for MI prediction.PMID:38786735 | DOI:10.3390/metabo14050258

Metabolites. 2024 Apr 29;14(5):257. doi: 10.3390/metabo14050257.ABSTRACTThe fruit of Phyllanthus emblica L. (FEPE) has a long history of use in Asian folk medicine. The main bioactive compounds in FEPE are polyphenols, known for their potent antioxidant, anti-inflammatory, and hypolipidemic activities. The present study aimed to investigate the intervention effect of FEPE (100 and 200 mg/kg) on hyperlipidemia for 8 weeks and preliminarily explored the potential mechanism by microbiome-metabolome analysis. The results showed that a high-dose FEPE (200 mg/kg) effectively alleviated dyslipidaemic symptoms and body weight gain in hyperlipidemic mice induced by a high-fat diet (HFD). Microbiome analysis showed that FEPE altered the structure of the intestinal microbiota, which included an increase in specific probiotics (such as Akkermansia, Anaerovorax, and Bacteroides) and a decrease in harmful bacteria (including A2, Acetitomaculum, Candidatus_Arthromitus, Lachnospiraceae_NK4A136_group, Lachnospiraceae_NK4B4_group, Rikenella, and Streptococcus), as well as a reduction in the level of short-chain fatty acids (SCFAs). In addition, significant changes in the hepatic metabolome were observed, and eight key metabolites associated with betaine metabolism, lysine degradation, methionine metabolism, and fatty acid metabolism pathways were primarily filtered. The correlated analysis identified several key "microbiota-metabolite" axes in the treatment of hyperlipidemia by FEPE extract. In conclusion, the present study is expected to provide a basis for treating hyperlipidemia with FEPE from the perspective of the microbiome-liver metabolome axis.PMID:38786734 | DOI:10.3390/metabo14050257

Metabolites. 2024 Apr 29;14(5):256. doi: 10.3390/metabo14050256.ABSTRACTCirculating food metabolites could improve dietary assessments by complementing traditional methods. Here, biomarker candidates of food intake were identified in plasma samples from pregnancy (gestational week 29, N = 579), delivery (mothers, N = 532; infants, N = 348), and four months postpartum (mothers, N = 477; breastfed infants, N = 193) and associated to food intake assessed with semi-quantitative food frequency questionnaires. Families from the Swedish birth cohort Nutritional impact on Immunological maturation during Childhood in relation to the Environment (NICE) were included. Samples were analyzed using untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics. Both exposure and outcome were standardized, and relationships were investigated using a linear regression analysis. The intake of fruits and berries and fruit juice were both positively related to proline betaine levels during pregnancy (fruits and berries, β = 0.23, FDR < 0.001; fruit juice, β = 0.27, FDR < 0.001), at delivery (fruit juice, infants: β = 0.19, FDR = 0.028), and postpartum (fruits and berries, mothers: β = 0.27, FDR < 0.001, infants: β = 0.29, FDR < 0.001; fruit juice, mothers: β = 0.37, FDR < 0.001). Lutein levels were positively related to vegetable intake during pregnancy (β = 0.23, FDR < 0.001) and delivery (mothers: β = 0.24, FDR < 0.001; newborns: β = 0.18, FDR = 0.014) and CMPF with fatty fish intake postpartum (mothers: β = 0.20, FDR < 0.001). No clear relationships were observed with the expected food sources of the remaining metabolites (acetylcarnitine, choline, indole-3-lactic acid, pipecolic acid). Our study suggests that plasma lutein could be useful as a more general food group intake biomarker for vegetables and fruits during pregnancy and delivery. Also, our results suggest the application of proline betaine as an intake biomarker of citrus fruit during gestation and lactation.PMID:38786733 | DOI:10.3390/metabo14050256

Metabolites. 2024 Apr 27;14(5):254. doi: 10.3390/metabo14050254.ABSTRACTGraft injury affects over 50% of liver transplant (LT) recipients, but non-invasive biomarkers to diagnose and guide treatment are currently limited. We aimed to develop a biomarker of graft injury by integrating serum metabolomic profiles with clinical variables. Serum from 55 LT recipients with biopsy confirmed metabolic dysfunction-associated steatohepatitis (MASH), T-cell mediated rejection (TCMR) and biliary complications was collected and processed using a combination of LC-MS/MS assay. The metabolomic profiles were integrated with clinical information using a multi-class Machine Learning (ML) classifier. The model's efficacy was assessed through the Out-of-Bag (OOB) error estimate evaluation. Our ML model yielded an overall accuracy of 79.66% with an OOB estimate of the error rate at 19.75%. The model exhibited a maximum ability to distinguish MASH, with an OOB error estimate of 7.4% compared to 22.2% for biliary and 29.6% for TCMR. The metabolites serine and serotonin emerged as the topmost predictors. When predicting binary outcomes using three models: Biliary (biliary vs. rest), MASH (MASH vs. rest) and TCMR (TCMR vs. rest); the AUCs were 0.882, 0.972 and 0.896, respectively. Our ML tool integrating serum metabolites with clinical variables shows promise as a non-invasive, multi-class serum biomarker of graft pathology.PMID:38786731 | DOI:10.3390/metabo14050254

Metabolites. 2024 Apr 26;14(5):253. doi: 10.3390/metabo14050253.ABSTRACTThe Cannabis species is one of the potent ancient medicinal plants acclaimed for its medicinal properties and recreational purposes. The plant parts are used and exploited all over the world for several agricultural and industrial applications. For many years Cannabis spp. has proven to present a highly diverse metabolomic profile with a pool of bioactive metabolites used for numerous pharmacological purposes ranging from anti-inflammatory to antimicrobial. Cannabis sativa has since been an extensive subject of investigation, monopolizing the research. Hence, there are fewer studies with a comprehensive understanding of the composition of bioactive metabolites grown in different environmental conditions, especially C. indica and a few other Cannabis strains. These pharmacological properties are mostly attributed to a few phytocannabinoids and some phytochemicals such as terpenoids or essential oils which have been tested for antimicrobial properties. Many other discovered compounds are yet to be tested for antimicrobial properties. These phytochemicals have a series of useful properties including anti-insecticidal, anti-acaricidal, anti-nematicidal, anti-bacterial, anti-fungal, and anti-viral properties. Research studies have reported excellent antibacterial activity against Gram-positive and Gram-negative multidrug-resistant bacteria as well as methicillin-resistant Staphylococcus aureus (MRSA). Although there has been an extensive investigation on the antimicrobial properties of Cannabis, the antimicrobial properties of Cannabis on phytopathogens and aquatic animal pathogens, mostly those affecting fish, remain under-researched. Therefore, the current review intends to investigate the existing body of research on metabolomic profile and anti-microbial properties whilst trying to expand the scope of the properties of the Cannabis plant to benefit the health of other animal species and plant crops, particularly in agriculture.PMID:38786730 | DOI:10.3390/metabo14050253

Metabolites. 2024 Apr 25;14(5):251. doi: 10.3390/metabo14050251.ABSTRACTPhytohormones that trigger or repress flower meristem development in apple buds are thought to be locally emitted from adjacent plant tissues, including leaves and fruitlets. The presence of fruitlets is known to inhibit adjacent buds from forming flowers and thus fruits. The resulting absence of fruitlets the following season restores flower-promoting signalling to the new buds. The cycle can lead to a biennial bearing behaviour of alternating crop loads in a branch or tree. The hormonal stimuli that elicit flowering is typically referred to as the floral induction (FI) phase in bud meristem development. To determine the metabolic pathways activated in FI, young trees of the cultivar 'Ruby Matilda' were subjected to zonal crop load treatments imposed to two leaders of bi-axis trees in the 2020/2021 season. Buds were collected over the expected FI phase, which is within 60 DAFB. Metabolomics profiling was undertaken to determine the differentially expressed pathways and key signalling molecules associated with FI in the leader and at tree level. Pronounced metabolic differences were observed in trees and leaders with high return bloom with significant increases in compounds belonging to the cytokinin, abscisic acid (ABA), phenylpropanoid and flavanol chemical classes. The presence of cytokinins, namely adenosine, inosine and related derivatives, as well as ABA phytohormones, provides further insight into the chemical intervention opportunities for future crop load management strategies via plant growth regulators.PMID:38786728 | DOI:10.3390/metabo14050251

Metabolites. 2024 Apr 25;14(5):250. doi: 10.3390/metabo14050250.ABSTRACTSoft tissue sarcoma (STS) is a relatively rare malignancy, accounting for about 1% of all adult cancers. It is known to have more than 70 subtypes. Its rarity, coupled with its various subtypes, makes early diagnosis challenging. The current standard treatment for STS is surgical removal. To identify the prognosis and pathophysiology of STS, we conducted untargeted metabolic profiling on pre-operative and post-operative plasma samples from 24 STS patients who underwent surgical tumor removal. Profiling was conducted using ultra-high-performance liquid chromatography-quadrupole time-of-flight/mass spectrometry. Thirty-nine putative metabolites, including phospholipids and acyl-carnitines were identified, indicating changes in lipid metabolism. Phospholipids exhibited an increase in the post-operative samples, while acyl-carnitines showed a decrease. Notably, the levels of pre-operative lysophosphatidylcholine (LPC) O-18:0 and LPC O-16:2 were significantly lower in patients who experienced recurrence after surgery compared to those who did not. Metabolic profiling may identify aggressive tumors that are susceptible to lipid synthase inhibitors. We believe that these findings could contribute to the elucidation of the pathophysiology of STS and the development of further metabolic studies in this rare malignancy.PMID:38786727 | DOI:10.3390/metabo14050250

Metabolites. 2024 Apr 25;14(5):248. doi: 10.3390/metabo14050248.ABSTRACTTorin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5'-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators.PMID:38786725 | DOI:10.3390/metabo14050248

Metabolites. 2024 Apr 24;14(5):245. doi: 10.3390/metabo14050245.ABSTRACTExposure to ionizing radiation, accidental or intentional, may lead to delayed effects of acute radiation exposure (DEARE) that manifest as injury to organ systems, including the kidney, heart, and brain. This study examines the role of activated protein C (APC), a known mitigator of radiation-induced early toxicity, in long-term plasma metabolite and lipid panels that may be associated with DEARE in APCHi mice. The APCHi mouse model used in the study was developed in a C57BL/6N background, expressing the D168F/N173K mouse analog of the hyper-activatable human D167F/D172K protein C variant. This modification enables increased circulating APC levels throughout the mouse's lifetime. Male and female cohorts of C57BL/6N wild-type and APCHi transgenic mice were exposed to 9.5 Gy γ-rays with their hind legs shielded to allow long-term survival that is necessary to monitor DEARE, and plasma was collected at 6 months for LC-MS-based metabolomics and lipidomics. We observed significant dyslipidemia, indicative of inflammatory phenotype, upon radiation exposure. Additionally, observance of several other metabolic dysregulations was suggestive of gut damage, perturbations in TriCarboxylic Acid (TCA) and urea cycles, and arginine metabolism. We also observed gender- and genotype-modulated metabolic perturbations post radiation exposure. The APCHi mice showed near-normal abundance for several lipids. Moreover, restoration of plasma levels of some metabolites, including amino acids, citric acid, and hypoxanthine, in APCHi mice is indicative of APC-mediated protection from radiation injuries. With the help of these findings, the role of APC in plasma molecular events after acute γ-radiation exposure in a gender-specific manner can be established for the first time.PMID:38786722 | DOI:10.3390/metabo14050245

J Fungi (Basel). 2024 May 16;10(5):356. doi: 10.3390/jof10050356.ABSTRACTCordyceps sinensis is a precious medicinal and edible fungus, which is widely used in body health care and disease prevention. The current research focuses on the comparison of metabolite characteristics between a small number of samples and lacks a comprehensive evaluation of the quality of C. sinensis in a large-scale space. In this study, LC-MS/MS, principal component analysis (PCA), hierarchical cluster analysis (HCA), and the membership function method were used to comprehensively evaluate the characteristics and quality of metabolites in 15 main producing areas of C. sinensis in China. The results showed that a total of 130 categories, 14 supercategories, and 1718 metabolites were identified. Carboxylic acids and derivatives, fatty acyls, organo-oxygen compounds, benzene and substituted derivatives, prenol lipids, and glycerophospholipids were the main components of C. sinensis. The HCA analysis and KEGG pathway enrichment analysis of 559 differentially accumulated metabolites (DAMs) showed that the accumulation models of fatty acids and conjugates and carbohydrates and carbohydrate conjugates in glycerophospholipid metabolism and arginine and proline metabolism may be one of the reasons for the quality differences in C. sinensis in different producing areas. In addition, a total of 18 biomarkers were identified and validated, which had a significant discrimination effect on the samples (p < 0.05). Overall, YS, BR, and ZD, with the highest membership function values, are rich and balanced in nutrients. They are excellent raw materials for the development of functional foods and provide scientific guidance for consumers to nourish health care.PMID:38786711 | DOI:10.3390/jof10050356

J Fungi (Basel). 2024 May 15;10(5):354. doi: 10.3390/jof10050354.ABSTRACTThe enticing aroma of truffles is a key factor for their culinary value. Although all truffle species tend to be pricy, the most intensely aromatic species are the most sought after. Research into the aroma of truffles encompasses various disciplines including chemistry, biology, and sensory science. This study focusses on the chemical composition of the aroma of black truffles (Tuber melanosporum) and the changes occurring under different storage conditions. For this, truffle samples were stored under different treatments, at different temperatures, and measured over a total storage time of 12 days. Measurements of the truffle aroma profiles were taken with SPME/GC-MS at regular intervals. To handle the ample data collected, a systematic approach utilizing multivariate data analysis techniques was taken. This approach led to a vast amount of data which we made publicly available for future exploration. Results reveal the complexity of aroma changes, with 695 compounds identified, highlighting the need for a comprehensive understanding. Principal component analyses offer initial insights into truffle composition, while individual compounds may serve as markers for age (formic acid, 1-methylpropyl ester), freshness (2-Methyl-1-propanal; 1-(methylthio)-propane), freezing (tetrahydrofuran), salt treatment (1-chloropentane), or heat exposure (4-hydroxy-3-methyl-2-butanone). This research suggests that heat treatment or salt contact significantly affects truffle aroma, while freezing and cutting have less pronounced effects in comparison. The enrichment of compounds showing significant changes during storage was investigated with a metabolomic pathway analysis. The involvement of some of the enriched compounds on the pyruvate/glycolysis and sulfur pathways was shown.PMID:38786709 | DOI:10.3390/jof10050354

J Fungi (Basel). 2024 May 8;10(5):337. doi: 10.3390/jof10050337.ABSTRACTThe effect of dimethyl sulfoxide (DMSO) on fungal metabolism has not been well studied. This study aimed to evaluate, by metabolomics, the impact of DMSO on the central carbon metabolism of Candida albicans. Biofilms of C. albicans SC5314 were grown on paper discs, using minimum mineral (MM) medium, in a dynamic continuous flow system. The two experimental conditions were control and 0.03% DMSO (v/v). After 72 h of incubation (37 °C), the biofilms were collected and the metabolites were extracted. The extracted metabolites were subjected to gas chromatography-mass spectrometry (GC/MS). The experiment was conducted using five replicates on three independent occasions. The GC/MS analysis identified 88 compounds. Among the 88 compounds, the levels of 27 compounds were markedly different between the two groups. The DMSO group exhibited enhanced levels of putrescine and glutathione and decreased levels of methionine and lysine. Additionally, the DMSO group exhibited alterations in 13 metabolic pathways involved in primary and secondary cellular metabolism. Among the 13 altered pathways, seven were downregulated and six were upregulated in the DMSO group. These results indicated a differential intracellular metabolic profile between the untreated and DMSO-treated biofilms. Hence, DMSO was demonstrated to affect the metabolic pathways of C. albicans. These results suggest that DMSO may influence the results of laboratory tests when it is used as a solvent. Hence, the use of DMSO as a solvent must be carefully considered in drug research, as the effect of the researched drugs may not be reliably translated into clinical practice.PMID:38786692 | DOI:10.3390/jof10050337

J Fungi (Basel). 2024 Apr 27;10(5):320. doi: 10.3390/jof10050320.ABSTRACTSodium butyrate (SB) is a histone deacetylase inhibitor that can induce changes in gene expression and secondary metabolite titers by inhibiting histone deacetylation. Our preliminary analysis also indicated that SB significantly enhanced the biosynthesis of carotenoids in the Rhodotorula glutinis strain YM25079, although the underlying regulatory mechanisms remained unclear. Based on an integrated analysis of transcriptomics and metabolomics, this study revealed changes in cell membrane stability, DNA and protein methylation levels, amino acid metabolism, and oxidative stress in the strain YM25079 under SB exposure. Among them, the upregulation of oxidative stress may be a contributing factor for the increase in carotenoid biosynthesis, subsequently enhancing the strain resistance to oxidative stress and maintaining the membrane fluidity and function for normal cell growth. To summarize, our results showed that SB promoted carotenoid synthesis in the Rhodotorula glutinis strain YM25079 and increased the levels of the key metabolites and regulators involved in the stress response of yeast cells. Additionally, epigenetic modifiers were applied to produce fungal carotenoid, providing a novel and promising strategy for the biosynthesis of yeast-based carotenoids.PMID:38786675 | DOI:10.3390/jof10050320

Antibiotics (Basel). 2024 May 16;13(5):459. doi: 10.3390/antibiotics13050459.ABSTRACTActinomycetes have long been recognized as important sources of clinical antibiotics. However, the exploration of rare actinomycetes, despite their potential for producing bioactive molecules, has remained relatively limited compared to the extensively studied Streptomyces genus. The extensive investigation of Streptomyces species and their natural products has led to a diminished probability of discovering novel bioactive compounds from this group. Consequently, our research focus has shifted towards less explored actinomycetes, beyond Streptomyces, with particular emphasis on Kitasatospora setae (K. setae). The genome of K. setae was annotated and analyzed through whole-genome sequencing using multiple bio-informatics tools, revealing an 8.6 Mbp genome with a 74.42% G + C content. AntiSMASH analysis identified 40 putative biosynthetic gene clusters (BGCs), approximately half of which were recessive and unknown. Additionally, metabolomic mining utilizing mass spectrometry demonstrated the potential for this rare actinomycete to generate numerous bioactive compounds such as glycosides and macrolides, with bafilomycin being the major compound produced. Collectively, genomics- and metabolomics-based techniques confirmed K. setae's potential as a bioactive secondary metabolite producer that is worthy of further exploration.PMID:38786187 | DOI:10.3390/antibiotics13050459

Cells. 2024 May 13;13(10):827. doi: 10.3390/cells13100827.ABSTRACTPlant structure-related agronomic traits like plant height and leaf size are critical for growth, development, and crop yield. Defining the types of genes involved in regulating plant structure size is essential for the molecular-assisted breeding of peppers. This research conducted comparative transcriptome analyses using Capsicum baccatum germplasm HNUCB0112 and HNUCB0222 and their F2 generation as materials. A total of 6574 differentially expressed genes (DEGs) were detected, which contain 379 differentially expressed transcription factors, mainly including transcription factor families such as TCP, WRKY, AUX/IAA, and MYB. Seven classes of DEGs were annotated in the plant hormone signal transduction pathway, including indole acetic acid (IAA), gibberellin (GA), cytokinin (CK), abscisic acid (ABA), jasmonic acid (JA), ethylene (ET), and salicylic acid (SA). The 26 modules were obtained by WGCNA analysis, and the MEpink module was positively correlated with plant height and leaf size, and hub genes associated with plant height and leaf size were anticipated. Differential genes were verified by qRT-PCR, which was consistent with the RNA-Seq results, demonstrating the accuracy of the sequencing results. These results enhance our understanding of the developmental regulatory networks governing pepper key traits like plant height and leaf size and offer new information for future research on the pepper plant architecture system.PMID:38786049 | DOI:10.3390/cells13100827