PubMed

Microorganisms. 2023 Jan 5;11(1):135. doi: 10.3390/microorganisms11010135.ABSTRACTMicrobiome-based therapeutics are increasingly evaluated as a strategy to reduce recurrent Clostridioides difficile infection (rCDI), with proposed mechanisms including restoration of the microbiota and microbiota-mediated functions, such as bile acid (BA) metabolism. This study reports a quantitative and sensitive assay for targeted metabolomic assessment, and the application of the assay to profile BA composition in a Phase 2 trial of the investigational microbiota-based live biotherapeutic RBX2660 for reduction of rCDI. A liquid chromatography tandem mass spectrometry method was developed to extract and quantify 35 BAs from 113 participant stool samples from 27 RBX2660-treated rCDI participants in the double-blinded, placebo-controlled clinical trial. The results demonstrate a high-confidence assay as represented by sensitivity, linearity, accuracy, and precision. Furthermore, the assay enabled the observation of primary BAs as the dominant BA species at baseline in stool samples from clinical trial participants, consistent with the expected loss of commensals after broad-spectrum antibiotic treatment. After RBX2660 administration, there was a significant drop in primary BAs concurrent with increased secondary BAs that sustained through 24 months post-RBX2660. Taken together, we describe a robust assay that demonstrates altered BA metabolism in rCDI patients treated with RBX2660 administration.PMID:36677428 | DOI:10.3390/microorganisms11010135

Microorganisms. 2022 Dec 29;11(1):92. doi: 10.3390/microorganisms11010092.ABSTRACTAdaptive laboratory evolution (ALE) is a useful experimental methodology for fundamental scientific research and industrial applications to create microbial cell factories. By using ALE, cells are adapted to the environment that researchers set based on their objectives through the serial transfer of cell populations in batch cultivations or continuous cultures and the fitness of the cells (i.e., cell growth) under such an environment increases. Then, omics analyses of the evolved mutants, including genome sequencing, transcriptome, proteome and metabolome analyses, are performed. It is expected that researchers can understand the evolutionary adaptation processes, and for industrial applications, researchers can create useful microorganisms that exhibit increased carbon source availability, stress tolerance, and production of target compounds based on omics analysis data. In this review article, the methodologies for ALE in microorganisms are introduced. Moreover, the application of ALE for the creation of useful microorganisms as cell factories has also been introduced.PMID:36677384 | DOI:10.3390/microorganisms11010092

Metabolites. 2023 Jan 16;13(1):135. doi: 10.3390/metabo13010135.ABSTRACTEgg yolks contain abundant lipids, proteins, and minerals that provide not only essential nutrients for embryonic development but also cheap sources of nutrients for consumers worldwide. Previous composition analyses of egg yolks primarily focused on nutrients such as lipids and minerals. However, few studies have reported the effects of domestication and heating on yolk composition and characteristics. The objective of this study was to investigate the impact of domestication and boiling on the metabolite contents of egg yolks via untargeted metabolomics using GC-MS and LC-MS. In this study, eggs were collected from Fenghua teals, captive mallards, and Shaoxing ducks. Twelve duck eggs (half raw and half cooked) were randomly selected from each variety, and the egg yolks were separated for metabolic profiling. The analysis identified 1205 compounds in the egg yolks. Domestication generated more differential metabolites than boiling, which indicated that the changes in the metabolome of duck egg yolk caused by domestication were greater than those caused by boiling. In a comparative analysis of domestic and mallard ducks, 48 overlapping differential metabolites were discovered. Among them, nine metabolites were upregulated in domesticated ducks, including monoolein, emodin, daidzein, genistein, and glycitein, which may be involved in lipid metabolism; some of them may also act as phytoestrogens (flavonoids). Another 39 metabolites, including imethylethanolamine, harmalan, mannitol, nornicotine, linoleic acid, diphenylamine, proline betaine, alloxanthin, and resolvin d1, were downregulated by domestication and were linked to immunity, anti-inflammatory, antibacterial, and antioxidant properties. Furthermore, four overlapping differential metabolites that included amino acids and dipeptides were discovered in paired comparisons of the raw and boiled samples. Our findings provided new insights into the molecular response of duck domestication and supported the use of metabolomics to examine the impact of boiling on the composition of egg yolks.PMID:36677059 | DOI:10.3390/metabo13010135

Metabolites. 2023 Jan 15;13(1):131. doi: 10.3390/metabo13010131.ABSTRACTMetabolic inflexibility is a hallmark of insulin resistance and can be extensively explored with high-throughput metabolomics techniques. However, the dynamic regulation of the metabolome during an oral glucose tolerance test (OGTT) in subjects with type 2 diabetes (T2D) is largely unknown. We aimed to identify alterations in metabolite responses to OGTT in subjects with T2D using untargeted metabolomics of both plasma and subcutaneous adipose tissue (SAT) samples. Twenty subjects with T2D and twenty healthy controls matched for sex, age, and body mass index (BMI) were profiled with untargeted metabolomics both in plasma (755 metabolites) and in the SAT (588) during an OGTT. We assessed metabolite concentration changes 90 min after the glucose load, and those responses were compared between patients with T2D and controls. Post-hoc analyses were performed to explore the associations between glucose-induced metabolite responses and markers of obesity and glucose metabolism, sex, and age. During the OGTT, T2D subjects had an impaired reduction in plasma levels of several metabolite families, including acylcarnitines, amino acids, acyl ethanolamines, and fatty acid derivates (p < 0.05), compared to controls. Additionally, patients with T2D had a greater increase in plasma glucose and fructose levels during the OGTT compared to controls (p < 0.05). The plasma concentration change of most metabolites after the glucose load was mainly associated with indices of hyperglycemia rather than insulin resistance, insulin secretion, or BMI. In multiple linear regression analyses, hyperglycemia indices (glucose area under the curve (AUC) during OGTT and glycosylated hemoglobin (HbA1c)) were the strongest predictors of plasma metabolite changes during the OGTT. No differences were found in the adipose tissue metabolome in response to the glucose challenge between T2D and controls. Using a metabolomics approach, we show that T2D patients display attenuated responses in several circulating metabolite families during an OGTT. Besides the well-known increase in monosaccharides, the glucose-induced lowering of amino acids, acylcarnitines, and fatty acid derivatives was attenuated in T2D subjects compared to controls. These data support the hypothesis of inflexibility in several metabolic pathways, which may contribute to dysregulated substrate partitioning and turnover in T2D. These findings are not directly associated with changes in adipose tissue metabolism; therefore, other tissues, such as muscle and liver, are probably of greater importance.PMID:36677056 | DOI:10.3390/metabo13010131

Metabolites. 2023 Jan 14;13(1):129. doi: 10.3390/metabo13010129.ABSTRACTAs a complex endocrine and metabolic condition, polycystic ovarian syndrome (PCOS) affects women's reproductive health. These common symptoms include hirsutism, hyperandrogenism, ovulatory dysfunction, irregular menstruation, and infertility. No one knows what causes it or how to stop it yet. Alterations in gut microbiota composition and disruptions in secondary bile acid production appear to play a causative role in developing PCOS. PCOS pathophysiology and phenotypes are tightly related to both enteric and vaginal bacteria. Patients with PCOS exhibit changed microbiome compositions and decreased microbial diversity. Intestinal microorganisms also alter PCOS patient phenotypes by upregulating or downregulating hormone release, gut-brain mediators, and metabolite synthesis. The human body's gut microbiota, also known as the "second genome," can interact with the environment to improve metabolic and immunological function. Inflammation is connected to PCOS and may be caused by dysbiosis in the gut microbiome. This review sheds light on the recently discovered connections between gut microbiota and insulin resistance (IR) and the potential mechanisms of PCOS. This study also describes metabolomic studies to obtain a clear view of PCOS and ways to tackle it.PMID:36677054 | DOI:10.3390/metabo13010129

Metabolites. 2023 Jan 13;13(1):127. doi: 10.3390/metabo13010127.ABSTRACTHigh-dimensional omics datasets frequently contain missing data points, which typically occur due to concentrations below the limit of detection (LOD) of the profiling platform. The presence of such missing values significantly limits downstream statistical analysis and result interpretation. Two common techniques to deal with this issue include the removal of samples with missing values and imputation approaches that substitute the missing measurements with reasonable estimates. Both approaches, however, suffer from various shortcomings and pitfalls. In this paper, we present "rox", a novel statistical model for the analysis of omics data with missing values without the need for imputation. The model directly incorporates missing values as "low" concentrations into the calculation. We show the superiority of rox over common approaches on simulated data and on six metabolomics datasets. Fully leveraging the information contained in LOD-based missing values, rox provides a powerful tool for the statistical analysis of omics data.PMID:36677052 | DOI:10.3390/metabo13010127

Metabolites. 2023 Jan 13;13(1):122. doi: 10.3390/metabo13010122.ABSTRACTIdentification of plant species is a crucial process in natural products. Ocimum, often referred to as the queen of herbs, is one of the most versatile and globally used medicinal herbs for various health benefits due to it having a wide variety of pharmacological activities. Despite there being significant global demand for this medicinal herb, rapid and comprehensive metabolomic fingerprinting approaches for species- and variety-specific classification are limited. In this study, metabolomic fingerprinting of five Ocimum species (Ocimum basilicum L., Ocimum sanctum L., Ocimum africanum Lour., Ocimum kilimandscharicum Gurke., and Hybrid Tulsi) and their varieties was performed using LC-MS, GC-MS, and the rapid fingerprinting approach FT-NIR combined with chemometrics. The aim was to distinguish the species- and variety-specific variation with a view toward developing a quality assessment of Ocimum species. Discrimination of species and varieties was achieved using principal component analysis (PCA), partial least squares discriminate analysis (PLS-DA), data-driven soft independent modelling of class analogy (DD-SIMCA), random forest, and K-nearest neighbours with specificity of 98% and sensitivity of 99%. Phenolics and flavonoids were found to be major contributing markers for species-specific variation. The present study established comprehensive metabolomic fingerprinting consisting of rapid screening and confirmatory approaches as a highly efficient means to identify the species and variety of Ocimum, being able to be applied for the quality assessment of other natural medicinal herbs.PMID:36677046 | DOI:10.3390/metabo13010122

Metabolites. 2023 Jan 11;13(1):117. doi: 10.3390/metabo13010117.ABSTRACTLiver transplantation can be performed with deceased or living donor allografts. Deceased liver grafts are donated from brain- or circulation-death patients, and they have usually suffered from a certain degree of damage. Post-transplant graft function and patient survival are closely related to liver allograft recovery. How to define the damage of liver grafts is unclear. A total of 47 liver donors, 23 deceased and 24 living, were enrolled in this study. All deceased donors had suffered from severe brain damage, and six of them had experienced cardio-pulmonary-cerebral resuscitation (CPR). The exploration of liver graft metabolomics was conducted by liquid chromatography coupled with mass spectrometry. Compared with living donor grafts, the deceased liver grafts expressed higher levels of various diacylglycerol, lysophosphatidylcholine, lysophosphatidylethanolamine, oleoylcarnitine and linoleylcarnitine; and lower levels of cardiolipin and phosphatidylcholine. The liver grafts from the donors with CPR had higher levels of cardiolipin, phosphatidic acid, phosphatidylcholine, phatidylethanolamine and amiodarone than the donors without CPR. When focusing on amino acids, the deceased livers had higher levels of histidine, taurine and tryptophan than the living donor livers. In conclusion, the deceased donors had suffered from cardio-circulation instability, and their lipid metabolites were increased. The elevation of lipid metabolites can be employed as an indicator of liver graft suffering.PMID:36677042 | DOI:10.3390/metabo13010117

Metabolites. 2023 Jan 9;13(1):113. doi: 10.3390/metabo13010113.ABSTRACTThe current therapeutic approach for gout is through the inhibition of the xanthine oxidase (XO) enzyme. Allopurinol, a clinically used XO inhibitor, causes many side effects. This study aimed to investigate the interaction between XO and inhibitors identified from Chrysanthemum morifolium by using computational simulation and multispectroscopic methods. The crude extract, petroleum ether, ethyl acetate (EtOAc), and residual fractions were subjected to an XO inhibitory assay and 1H NMR analysis. The EtOAc fraction was shown to be strongly correlated to the XO inhibitory activity by using PLS biplot regression analysis. Kaempferol, apigenin, homovanillic acid, and trans-cinnamic acid were suggested to contribute to the XO inhibitory activity. Molecular docking showed that kaempferol and apigenin bound to the active site of XO with their benzopyran moiety sandwiched between Phe914 and Phe1009, interacting with Thr1010 and Arg880 by hydrogen bonding. Kaempferol showed the lowest binding energy in molecular dynamic simulation. The residues that contributed to the binding energy were Glu802, Arg880, Phe 914, and Phe 1009. A fluorescence quenching study showed a combination of static and dynamic quenching for all four inhibitors binding to XO. Circular dichroism spectroscopy revealed that there was no major change in XO conformation after binding with each inhibitor.PMID:36677038 | DOI:10.3390/metabo13010113

Metabolites. 2023 Jan 9;13(1):112. doi: 10.3390/metabo13010112.ABSTRACTThe metabolic basis of Parkinson's disease pathology is poorly understood. However, the involvement of mitochondrial and endoplasmic reticulum stress in dopamine neurons in disease aetiology is well established. We looked at the effect of rotenone- and tunicamycin-induced mitochondrial and ER stress on the metabolism of wild type and microtubule-associated protein tau mutant dopamine neurons. Dopamine neurons derived from human isolated iPSCs were subjected to mitochondrial and ER stress using RT and TM, respectively. Comprehensive metabolite profiles were generated using a split phase extraction analysed by reversed phase lipidomics whilst the aqueous phase was measured using HILIC metabolomics. Mitochondrial and ER stress were both shown to cause significant dysregulation of metabolism with RT-induced stress producing a larger shift in the metabolic profile of both wild type and MAPT neurons. Detailed analysis showed that accumulation of triglycerides was a significant driver of metabolic dysregulation in response to both stresses in both genotypes. Whilst the consequence is similar, the mechanisms by which triglyceride accumulation occurs in dopamine neurons in response to mitochondrial and ER stress are very different. Thus, improving our understanding of how these mechanisms drive the observed triglyceride accumulation can potentially open up new therapeutic avenues.PMID:36677037 | DOI:10.3390/metabo13010112

Metabolites. 2023 Jan 9;13(1):110. doi: 10.3390/metabo13010110.ABSTRACTWe aim to establish a noninvasive diagnostic platform to capture early phenotypic transformation for metastasis using 18F-FDG PET and 1H-NMR-based serum metabolomics. Mice with implantation of NCI-H460 cells grew only primary lung tumors in the localized group and had both primary and metastatic lung tumors in the metastatic group. The serum metabolites were analyzed using 1H-NMR at the time of PET/CT scan. The glycolysis status and cell proliferation were validated by Western blotting and staining. A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic accuracy of SUVmean and serum metabolites in metastasis. In the metastatic mice, the SUVmean of metastatic tumors was significantly higher than that of primary lung tumors in PET images, which was supported by elevated glycolytic protein expression of HK2 and PKM2. The serum pyruvate level in the metastatic group was significantly lower than that in the localized group, corresponding to increased pyruvate-catalyzed enzyme and proliferation rates in metastatic tumors. In diagnosing localized or metastatic tumors, the areas under the ROC curves of SUVmean and pyruvate were 0.92 and 0.91, respectively, with p < 0.05. In conclusion, the combination of 18F-FDG PET and 1H-NMR-based serum metabolomics demonstrated the feasibility of a glycolytic platform for diagnosing metastatic lung cancers.PMID:36677035 | DOI:10.3390/metabo13010110

Metabolites. 2023 Jan 9;13(1):107. doi: 10.3390/metabo13010107.ABSTRACTBoth genetic improvement and the application of N fertilizer increase the quality and yields of wheat. However, the molecular kinetics that underlies the differences between them are not well understood. In this study, we performed a non-targeted metabolomic analysis on wheat cultivars from different release years to comprehensively investigate the metabolic differences between cultivar and N treatments. The results revealed that the plant height and tiller number steadily decreased with increased ears numbers, whereas the grain number and weight increased with genetic improvement. Following the addition of N fertilizer, the panicle numbers and grain weights increased in an old cultivar, whereas the panicle number and grain number per panicle increased in a modern cultivar. For the 1950s to 2010s cultivar, the yield increases due to genetic improvements ranged from -1.9% to 96.7%, whereas that of N application ranged from 19.1% to 81.6%. Based on the untargeted metabolomics approach, the findings demonstrated that genetic improvements induced 1.4 to 7.4 times more metabolic alterations than N fertilizer supply. After the addition of N, 69.6%, 29.4%, and 33.3% of the differential metabolites were upregulated in the 1950s, 1980s, and 2010s cultivars, respectively. The results of metabolic pathway analysis of the identified differential metabolites via genetic improvement indicated enrichment in 1-2 KEGG pathways, whereas the application of N fertilizer enriched 2-4 pathways. Our results provide new insights into the molecular mechanisms of wheat quality and grain yield developments.PMID:36677032 | DOI:10.3390/metabo13010107

Metabolites. 2023 Jan 9;13(1):105. doi: 10.3390/metabo13010105.ABSTRACTComputational methods for creating in silico libraries of molecular descriptors (e.g., collision cross sections) are becoming increasingly prevalent due to the limited number of authentic reference materials available for traditional library building. These so-called "reference-free metabolomics" methods require sampling sets of molecular conformers in order to produce high accuracy property predictions. Due to the computational cost of the subsequent calculations for each conformer, there is a need to sample the most relevant subset and avoid repeating calculations on conformers that are nearly identical. The goal of this study is to introduce a heuristic method of finding the most dissimilar conformers from a larger population in order to help speed up reference-free calculation methods and maintain a high property prediction accuracy. Finding the set of the n items most dissimilar from each other out of a larger population becomes increasingly difficult and computationally expensive as either n or the population size grows large. Because there exists a pairwise relationship between each item and all other items in the population, finding the set of the n most dissimilar items is different than simply sorting an array of numbers. For instance, if you have a set of the most dissimilar n = 4 items, one or more of the items from n = 4 might not be in the set n = 5. An exact solution would have to search all possible combinations of size n in the population exhaustively. We present an open-source software called similarity downselection (SDS), written in Python and freely available on GitHub. SDS implements a heuristic algorithm for quickly finding the approximate set(s) of the n most dissimilar items. We benchmark SDS against a Monte Carlo method, which attempts to find the exact solution through repeated random sampling. We show that for SDS to find the set of n most dissimilar conformers, our method is not only orders of magnitude faster, but it is also more accurate than running Monte Carlo for 1,000,000 iterations, each searching for set sizes n = 3-7 out of a population of 50,000. We also benchmark SDS against the exact solution for example small populations, showing that SDS produces a solution close to the exact solution in these instances. Using theoretical approaches, we also demonstrate the constraints of the greedy algorithm and its efficacy as a ratio to the exact solution.PMID:36677030 | DOI:10.3390/metabo13010105

Metabolites. 2023 Jan 8;13(1):103. doi: 10.3390/metabo13010103.ABSTRACTFeeding thermally oxidized lipids to pigs has been shown to compromise growth and health, reduce energy digestibility, and disrupt lipid metabolism. However, the effects of feeding oxidized lipids on amino acid metabolism in pigs have not been well defined even though amino acids are indispensable for the subsistence of energy metabolism, protein synthesis, the antioxidant system, and many other functions essential for pig growth and health. In this study, oxidized corn oil (OCO)-elicited changes in amino acid homeostasis of nursery pigs were examined by metabolomics-based biochemical analysis. The results showed that serum and hepatic free amino acids and metabolites, including tryptophan, threonine, alanine, glutamate, and glutathione, as well as associated metabolic pathways, were selectively altered by feeding OCO, and more importantly, many of these metabolic events possess protective functions. Specifically, OCO activated tryptophan-nicotinamide adenosine dinucleotide (NAD+) synthesis by the transcriptional upregulation of the kynurenine pathway in tryptophan catabolism and promoted adenine nucleotide biosynthesis. Feeding OCO induced oxidative stress, causing decreases in glutathione (GSH)/oxidized glutathione (GSSG) ratio, carnosine, and ascorbic acid in the liver but simultaneously promoted antioxidant responses as shown by the increases in hepatic GSH and GSSG as well as the transcriptional upregulation of GSH metabolism-related enzymes. Moreover, OCO reduced the catabolism of threonine to α-ketobutyrate in the liver by inhibiting the threonine dehydratase (TDH) route. Overall, these protective metabolic events indicate that below a certain threshold of OCO consumption, nursery pigs are capable of overcoming the oxidative stress and metabolic challenges posed by the consumption of oxidized lipids by adjusting antioxidant, nutrient, and energy metabolism, partially through the transcriptional regulation of amino acid metabolism.PMID:36677028 | DOI:10.3390/metabo13010103

Metabolites. 2023 Jan 7;13(1):97. doi: 10.3390/metabo13010097.ABSTRACTUntargeted metabolomics (UM) is increasingly being deployed as a strategy for screening patients that are suspected of having an inborn error of metabolism (IEM). In this study, we examined the potential of existing outlier detection methods to detect IEM patient profiles. We benchmarked 30 different outlier detection methods when applied to three untargeted metabolomics datasets. Our results show great differences in IEM detection performances across the various methods. The methods DeepSVDD and R-graph performed most consistently across the three metabolomics datasets. For datasets with a more balanced number of samples-to-features ratio, we found that AE reconstruction error, Mahalanobis and PCA reconstruction error also performed well. Furthermore, we demonstrated the importance of a PCA transform prior to applying an outlier detection method since we observed that this increases the performance of several outlier detection methods. For only one of the three metabolomics datasets, we observed clinically satisfying performances for some outlier detection methods, where we were able to detect 90% of the IEM patient samples while detecting no false positives. These results suggest that outlier detection methods have the potential to aid the clinical investigator in routine screening for IEM using untargeted metabolomics data, but also show that further improvements are needed to ensure clinically satisfying performances.PMID:36677022 | DOI:10.3390/metabo13010097

Metabolites. 2023 Jan 6;13(1):91. doi: 10.3390/metabo13010091.ABSTRACTLichen planus is a chronic inflammatory mucocutaneous disease that belongs to the group of papulosquamous skin diseases among diseases like psoriasis, a widely studied disease in dermatology. The aim of the study was to identify the changes between the blood sera of lichen planus patients and healthy controls to widen the knowledge about the metabolomic aspect of lichen planus and gain a better understanding about the pathophysiology of the disease. We used high-throughput nuclear magnetic resonance (NMR) spectroscopy to measure the levels of blood serum metabolites, lipoproteins and lipoprotein particles. Dyslipidemia has relatively recently been shown to be one of the comorbidities of lichen planus, but the changes in the components of lipoproteins have not been described yet. We found statistically significant changes in the concentrations of 16 markers regarding lipoproteins, which included the components of intermediate-density lipoproteins, low-density lipoproteins and large low-density lipoproteins. We propose that the detected changes may increase the risk for specific comorbidities (e.g., dyslipidemia) and resulting cardiovascular diseases, as the turnover and hepatic uptake of the altered/modified lipoprotein particles are disturbed.PMID:36677016 | DOI:10.3390/metabo13010091

Metabolites. 2023 Jan 5;13(1):88. doi: 10.3390/metabo13010088.ABSTRACTMicrobial metabolism is strongly dependent on the environmental conditions. While these can be well controlled under laboratory conditions, large-scale bioreactors are characterized by inhomogeneities and consequently dynamic conditions for the organisms. How Saccharomyces cerevisiae response to frequent perturbations in industrial bioreactors is still not understood mechanistically. To study the adjustments to prolonged dynamic conditions, we used published repeated substrate perturbation regime experimental data, extended it with proteomic measurements and used both for modelling approaches. Multiple types of data were combined; including quantitative metabolome, 13C enrichment and flux quantification data. Kinetic metabolic modelling was applied to study the relevant intracellular metabolic response dynamics. An existing model of yeast central carbon metabolism was extended, and different subsets of enzymatic kinetic constants were estimated. A novel parameter estimation pipeline based on combinatorial enzyme selection supplemented by regularization was developed to identify and predict the minimum enzyme and parameter adjustments from steady-state to dynamic substrate conditions. This approach predicted proteomic changes in hexose transport and phosphorylation reactions, which were additionally confirmed by proteome measurements. Nevertheless, the modelling also hints at a yet unknown kinetic or regulation phenomenon. Some intracellular fluxes could not be reproduced by mechanistic rate laws, including hexose transport and intracellular trehalase activity during substrate perturbation cycles.PMID:36677014 | DOI:10.3390/metabo13010088

Metabolites. 2023 Jan 4;13(1):85. doi: 10.3390/metabo13010085.ABSTRACTBasil (Ocimum L.) is widely used as a flavor ingredient, however research on basil flavor is limited. In the current study, nine basil species were selected, including Ocimum basilicum L.var. pilosum (Willd.) Benth., Ocimum sanctum, Ocimum basilicum cinnamon, Ocimum gratissimum var. suave, Ocimum tashiroi, Ocimum basilicum, Ocimum americanum, Ocimum basilicum ct linalool, and Ocimum basilicum var. basilicum, and their fragrance and flavor characteristics were assessed by sensory evaluation. The results indicated that Ocimum basilicum var. basilicum and Ocimum gratissimum var. suave have a strong clove smell and exhibited a piquant taste. Metabolomics and volatilomics analyses measured 100 nonvolatile metabolites and 134 volatiles. Differential analysis showed that eugenol, γ-terpinene, germacrene D and malic acid were among the most varied metabolites in basil species. Combined with sensory evaluation results, correlation analysis revealed that β-pinene and γ-cadinene contributed to the piquant smell, while eugenol and germacrene D contributed to the clove smell, and malic acid and L-(-)-arabitol contributed to the sweet flavor in basil. This study provided comprehensive flavor chemistry profiles of basil species and could be used as a guide for basil flavor improvement. The better understanding of objective sensory attributes and chemical composition of fresh basil could introduce the improved cultivars with preponderant traits, which is also in accordance with the various demands of breeders and growers, food producers, and consumers.PMID:36677010 | DOI:10.3390/metabo13010085

Metabolites. 2023 Jan 3;13(1):81. doi: 10.3390/metabo13010081.ABSTRACTThe exposure to blue and white Light emitting diodes (LED) light leads to damage in the visual system with short-term LED light exposure. Chronic exposure, adaptive responses to light, and self-protective mechanisms against LED light exposures need to be explored, and it would be essential to understand the repercussions of LED radiation on vitreous metabolites. A total of 24 male Wistar rats were used in this study, divided into four groups (n = 6 in each group). Three experimental groups of rats were exposed to either blue, white, or yellow LED light for 90 days (12:12 light-dark cycle routine) with uniform illumination (450-500 lux). Standard lab settings were used to maintain control rats. Vitreous fluids were subjected to untargeted metabolomics analysis using liquid chromatography-mass spectrometry (LC/MS). PLS-DA analysis indicated significant the separation of m metabolites among groups, suggesting that LED exposure induces metabolic reprogramming in the vitreous. Amino acids and their modifications showed significant alterations among groups which included D-alanine, D-serine (p < 0.05), lysine (p < 0.001), aspartate (p = 0.0068), glutathione (p = 0.0263), taurine (p = 0.007), and hypotaurine. In chronic light exposure, the self-protective or reworking system could be depleted, which may decrease the ability to compensate for the defending mechanism. This might fail to maintain the metabolomic structural integrity of the vitreous metabolites.PMID:36677006 | DOI:10.3390/metabo13010081

Metabolites. 2023 Jan 3;13(1):80. doi: 10.3390/metabo13010080.ABSTRACTThe hormone 20-hydroxyecdysone (20E) and the ecdysone receptors (ECR and USP) play critical roles in the growth and metabolism of insects, including honeybees. In this study, we investigated the effect of 20E on the growth and development of honeybee larvae by rearing them in vitro and found reduced food consumption and small-sized pupae with increasing levels of 20E. A liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis of widely targeted metabolomics was used to examine the changes in the metabolites after an exogenous 20E application to honeybee larvae and the underlying mechanisms. A total of 374 different metabolites were detected between the control group and the 20E treatment group, covering 12 subclasses. The most significant changes occurred in 7-day-old larvae, where some monosaccharides, such as D-Glucose and UDP-galactose, were significantly upregulated. In addition, some metabolic pathways, such as glycolysis/gluconeogenesis and galactose metabolism, were affected by the 20E treatment, suggesting that the 20E treatment disrupts the metabolic homeostasis of honeybee larvae hemolymph and that the response of honeybee larvae to the 20E treatment is dynamic and contains many complex pathways. Many genes involved in carbohydrate metabolism, including genes of the glycolysis and glycogen synthesis pathways, were downregulated during molting and pupation after the 20E treatment. In contrast, the expression levels of the genes related to gluconeogenesis and glycogenolysis were significantly increased, which directly or indirectly upregulated glucose levels in the hemolymph, whereas RNA interference with the 20E receptor EcR-USP had an opposite effect to that of the 20E treatment. Taken together, 20E plays a critical role in the changes in carbohydrate metabolism during metamorphosis.PMID:36677005 | DOI:10.3390/metabo13010080