PubMed

Metabolites. 2023 Aug 18;13(8):953. doi: 10.3390/metabo13080953.ABSTRACTAging is the system-wide loss of homeostasis, eventually leading to death. There is growing evidence that the microbiome not only evolves with its aging host, but also directly affects aging via the modulation of metabolites involved in important cellular functions. The widely used model organism C. elegans exhibits high selectivity towards its native microbiome members which confer a range of differential phenotypes and possess varying functional capacities. The ability of one such native microbiome species, Chryseobacterium sp. CHNTR56 MYb120, to improve the lifespan of C. elegans and to promote the production of Vitamin B6 in the co-colonizing member Comamonas sp. 12022 MYb131 are some of its beneficial effects on the worm host. We hypothesize that studying its metabolic influence on the different life stages of the worm could provide further insights into mutualistic interactions. The present work applied LC-MS untargeted metabolomics and isotope labeling to study the impact of the native microbiome member Chryseobacterium sp. CHNTR56 MYb120 on the metabolism of C. elegans. In addition to the upregulation of biosynthesis and detoxification pathway intermediates, we found that Chryseobacterium sp. CHNTR56 MYb120 upregulates the glyoxylate shunt in mid-adult worms which is linked to the upregulation of trehalose, an important metabolite for desiccation tolerance in older worms.PMID:37623896 | DOI:10.3390/metabo13080953

Metabolites. 2023 Aug 16;13(8):951. doi: 10.3390/metabo13080951.ABSTRACTCOVID-19, a systemic multi-organ disease resulting from infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is known to result in a wide array of disease outcomes, ranging from asymptomatic to fatal. Despite persistent progress, there is a continued need for more accurate determinants of disease outcomes, including post-acute symptoms after COVID-19. In this study, we characterised the serum metabolomic changes due to hospitalisation and COVID-19 disease progression by mapping the serum metabolomic trajectories of 71 newly hospitalised moderate and severe patients in their first week after hospitalisation. These 71 patients were spread out over three hospitals in Switzerland, enabling us to meta-analyse the metabolomic trajectories and filter consistently changing metabolites. Additionally, we investigated differential metabolite-metabolite trajectories between fatal, severe, and moderate disease outcomes to find prognostic markers of disease severity. We found drastic changes in serum metabolite concentrations for 448 out of the 901 metabolites. These results included markers of hospitalisation, such as environmental exposures, dietary changes, and altered drug administration, but also possible markers of physiological functioning, including carboxyethyl-GABA and fibrinopeptides, which might be prognostic for worsening lung injury. Possible markers of disease progression included altered urea cycle metabolites and metabolites of the tricarboxylic acid (TCA) cycle, indicating a SARS-CoV-2-induced reprogramming of the host metabolism. Glycerophosphorylcholine was identified as a potential marker of disease severity. Taken together, this study describes the metabolome-wide changes due to hospitalisation and COVID-19 disease progression. Moreover, we propose a wide range of novel potential biomarkers for monitoring COVID-19 disease course, both dependent and independent of the severity.PMID:37623894 | DOI:10.3390/metabo13080951

Metabolites. 2023 Aug 15;13(8):950. doi: 10.3390/metabo13080950.ABSTRACTThis review analyzed 21 scientific papers on the determination of amino acids in various types of cancer in saliva. Most of the studies are on oral cancer (8/21), breast cancer (4/21), gastric cancer (3/21), lung cancer (2/21), glioblastoma (2/21) and one study on colorectal, pancreatic, thyroid and liver cancer. The amino acids alanine, valine, phenylalanine, leucine and isoleucine play a leading role in the diagnosis of cancer via the saliva. In an independent version, amino acids are rarely used; the authors combine either amino acids with each other or with other metabolites, which makes it possible to obtain high values of sensitivity and specificity. Nevertheless, a logical and complete substantiation of the changes in saliva occurring in cancer, including changes in salivary amino acid levels, has not yet been formed, which makes it important to continue research in this direction.PMID:37623893 | DOI:10.3390/metabo13080950

Metabolites. 2023 Aug 15;13(8):948. doi: 10.3390/metabo13080948.ABSTRACTMetabolomics is an analytical approach that involves profiling and comparing the metabolites present in biological samples. This scoping review article offers an overview of current metabolomics approaches and their utilization in evaluating metabolic changes in biological fluids that occur in response to viral infections. Here, we provide an overview of metabolomics methods including high-throughput analytical chemistry and multivariate data analysis to identify the specific metabolites associated with viral infections. This review also focuses on data interpretation and applications designed to improve our understanding of the pathogenesis of these viral diseases.PMID:37623891 | DOI:10.3390/metabo13080948

Metabolites. 2023 Aug 15;13(8):947. doi: 10.3390/metabo13080947.ABSTRACTAlthough metabolic alterations are observed in many monogenic and complex genetic disorders, the impact of most mammalian genes on cellular metabolism remains unknown. Understanding the effect of mouse gene dysfunction on metabolism can inform the functions of their human orthologues. We investigated the effect of loss-of-function mutations in 30 unique gene knockout (KO) lines on plasma metabolites, including genes coding for structural proteins (11 of 30), metabolic pathway enzymes (12 of 30) and protein kinases (7 of 30). Steroids, bile acids, oxylipins, primary metabolites, biogenic amines and complex lipids were analyzed with dedicated mass spectrometry platforms, yielding 827 identified metabolites in male and female KO mice and wildtype (WT) controls. Twenty-two percent of 23,698 KO versus WT comparison tests showed significant genotype effects on plasma metabolites. Fifty-six percent of identified metabolites were significantly different between the sexes in WT mice. Many of these metabolites were also found to have sexually dimorphic changes in KO lines. We used plasma metabolites to complement phenotype information exemplified for Dhfr, Idh1, Mfap4, Nek2, Npc2, Phyh and Sra1. The association of plasma metabolites with IMPC phenotypes showed dramatic sexual dimorphism in wildtype mice. We demonstrate how to link metabolomics to genotypes and (disease) phenotypes. Sex must be considered as critical factor in the biological interpretation of gene functions.PMID:37623890 | DOI:10.3390/metabo13080947

Metabolites. 2023 Aug 15;13(8):946. doi: 10.3390/metabo13080946.ABSTRACTThis study aimed to determine the metabolic response of growing German Simmental bulls fed rations low in crude protein (CP) supplemented with rumen-protected methionine (RPMET). In total, 69 bulls (on average 238 ± 11 days of age at start and 367 ± 25 kg of bodyweight) were assigned to three dietary treatments (n = 23/group): Positive control (CON; 13.7% CP; 2.11 g methionine/kg DM), negative control deficient in CP (RED; 9.04% CP; 1.56 g methionine/kg DM) and crude protein-deficient ration supplemented with RPMET (RED+RPMET; 9.04% CP; 2.54 g methionine/kg DM). At slaughter, samples of liver, muscle and blood serum were taken and underwent subsequent metabolomics profiling using a UHPLC-QTOF-MS system. A total of 6540 features could be detected. Twenty metabolites in the liver, five metabolites in muscle and thirty metabolites in blood serum were affected (p < 0.05) due to dietary treatments. In total, six metabolites could be reliably annotated and were thus subjected to subsequent univariate analysis. Reduction in dietary CP had minimal effect on metabolite abundance in target tissues of both RED and RED+RPMET bulls as compared to CON bulls. The addition of RPMET altered the hepatic anti-oxidant status in RED+RPMET bulls compared to both RED and CON bulls. Results exemplify nutrient partitioning in growing German Simmental bulls: bulls set maintenance as the prevailing metabolic priority (homeostasis) and nutrient trafficking as the second priority, which was directed toward special metabolic functions, such as anti-oxidant pathways.PMID:37623889 | DOI:10.3390/metabo13080946

Metabolites. 2023 Aug 14;13(8):945. doi: 10.3390/metabo13080945.ABSTRACTThis article illustrates how dietary flaxseed can be used to reduce cancer risk, specifically by attenuating obesity, type 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). We utilize a targeted metabolomics dataset in combination with a reanalysis of past work to investigate the "metabo-bioenergetic" adaptations that occur in White Leghorn laying hens while consuming dietary flaxseed. Recently, we revealed how the anti-vitamin B6 effects of flaxseed augment one-carbon metabolism in a manner that accelerates S-adenosylmethionine (SAM) biosynthesis. Researchers recently showed that accelerated SAM biosynthesis activates the cell's master energy sensor, AMP-activated protein kinase (AMPK). Our paper provides evidence that flaxseed upregulates mitochondrial fatty acid oxidation and glycolysis in liver, concomitant with the attenuation of lipogenesis and polyamine biosynthesis. Defatted flaxseed likely functions as a metformin homologue by upregulating hepatic glucose uptake and pyruvate flux through the pyruvate dehydrogenase complex (PDC) in laying hens. In contrast, whole flaxseed appears to attenuate liver steatosis and body mass by modifying mitochondrial fatty acid oxidation and lipogenesis. Several acylcarnitine moieties indicate Randle cycle adaptations that protect mitochondria from metabolic overload when hens consume flaxseed. We also discuss a paradoxical finding whereby flaxseed induces the highest glycated hemoglobin percentage (HbA1c%) ever recorded in birds, and we suspect that hyperglycemia is not the cause. In conclusion, flaxseed modifies bioenergetic pathways to attenuate the risk of obesity, type 2 diabetes, and NAFLD, possibly downstream of SAM biosynthesis. These findings, if reproducible in humans, can be used to lower cancer risk within the general population.PMID:37623888 | DOI:10.3390/metabo13080945

Metabolites. 2023 Aug 13;13(8):944. doi: 10.3390/metabo13080944.ABSTRACTLarge-scale metabolomics assays are widely used in epidemiology for biomarker discovery and risk assessments. However, systematic errors introduced by instrumental signal drifting pose a big challenge in large-scale assays, especially for derivatization-based gas chromatography-mass spectrometry (GC-MS). Here, we compare the results of different normalization methods for a study with more than 4000 human plasma samples involved in a type 2 diabetes cohort study, in addition to 413 pooled quality control (QC) samples, 413 commercial pooled plasma samples, and a set of 25 stable isotope-labeled internal standards used for every sample. Data acquisition was conducted across 1.2 years, including seven column changes. In total, 413 pooled QC (training) and 413 BioIVT samples (validation) were used for normalization comparisons. Surprisingly, neither internal standards nor sum-based normalizations yielded median precision of less than 30% across all 563 metabolite annotations. While the machine-learning-based SERRF algorithm gave 19% median precision based on the pooled quality control samples, external cross-validation with BioIVT plasma pools yielded a median 34% relative standard deviation (RSD). We developed a new method: systematic error reduction by denoising autoencoder (SERDA). SERDA lowered the median standard deviations of the training QC samples down to 16% RSD, yielding an overall error of 19% RSD when applied to the independent BioIVT validation QC samples. This is the largest study on GC-MS metabolomics ever reported, demonstrating that technical errors can be normalized and handled effectively for this assay. SERDA was further validated on two additional large-scale GC-MS-based human plasma metabolomics studies, confirming the superior performance of SERDA over SERRF or sum normalizations.PMID:37623887 | DOI:10.3390/metabo13080944

Metabolites. 2023 Aug 13;13(8):943. doi: 10.3390/metabo13080943.ABSTRACTMetabolomics is a method that provides an overview of the physiological and cellular state of a specific organism or tissue. This method is particularly useful for studying the influence the environment can have on organisms, especially those used as bio-indicators, e.g., Mytilus galloprovincialis. Nevertheless, a scarcity of data on the complete metabolic baseline of mussel tissues still exists, but more importantly, the effect of mussel exposure to certain heavy metals on spermatozoa is unknown, also considering that, in recent years, the reproductive system has proved to be very sensitive to the effects of environmental pollutants. In order to fill this knowledge gap, the similarities and differences in the metabolic profile of spermatozoa of mussels exposed to metallic chlorides of copper, nickel, and cadmium, and to the mixture to these metals, were studied using a metabolomics approach based on GC-MS analysis, and their physiological role was discussed. A total of 237 endogenous metabolites were identified in the spermatozoa of these mussel. The data underwent preprocessing steps and were analyzed using statistical methods such as PLS-DA. The results showed effective class separation and identified key metabolites through the VIP scores. Heatmaps and cluster analysis further evaluated the metabolites. The metabolite-set enrichment analysis revealed complex interactions within metabolic pathways and metabolites, especially involving glucose and central carbon metabolism and oxidative stress metabolism. Overall, the results of this study are useful to better understand how some pollutants can affect the specific physiological functions of the spermatozoa of this mussel, as well as for further GC-MS-based metabolomic health and safety studies of marine bivalves.PMID:37623886 | DOI:10.3390/metabo13080943

Metabolites. 2023 Aug 12;13(8):941. doi: 10.3390/metabo13080941.ABSTRACTMetabolomics has advanced to an extent where it is desired to standardize and compare data across individual studies. While past work in standardization has focused on data acquisition, data processing, and data storage aspects, metabolomics databases are useless without ontology-based descriptions of biological samples and study designs. We introduce here a user-centric tool to automatically standardize sample metadata. Using such a tool in frontends for metabolomic databases will dramatically increase the FAIRness (Findability, Accessibility, Interoperability, and Reusability) of data, specifically for data reuse and for finding datasets that share comparable sets of metadata, e.g., study meta-analyses, cross-species analyses or large scale metabolomic atlases. SMetaS (Sample Metadata Standardizer) combines a classic database with an API and frontend and is provided in a containerized environment. The tool has two user-centric components. In the first component, the user designs a sample metadata matrix and fills the cells using natural language terminology. In the second component, the tool transforms the completed matrix by replacing freetext terms with terms from fixed vocabularies. This transformation process is designed to maximize simplicity and is guided by, among other strategies, synonym matching and typographical fixing in an n-grams/nearest neighbors model approach. The tool enables downstream analysis of submitted studies and samples via string equality for FAIR retrospective use.PMID:37623884 | DOI:10.3390/metabo13080941

Metabolites. 2023 Aug 11;13(8):938. doi: 10.3390/metabo13080938.ABSTRACTAccording to studies, the microbiome may contribute to the emergence and spread of breast cancer. E. coli is one of the Enterobacteriaceae family recently found to be present as part of the breast tissue microbiota. In this study, we focused on the effect of E. coli secretome free of cells on MCF-7 metabolism. Liquid chromatography-mass spectrometry (LC-MS) metabolomics was used to study the E. coli secretome and its role in MCF-7 intra- and extracellular metabolites. A comparison was made between secretome-exposed cells and unexposed controls. Our analysis revealed significant alterations in 31 intracellular and 55 extracellular metabolites following secretome exposure. Several metabolic pathways, including lactate, aminoacyl-tRNA biosynthesis, purine metabolism, and energy metabolism, were found to be dysregulated upon E. coli secretome exposure. E. coli can alter the breast cancer cells' metabolism through its secretome which disrupts key metabolic pathways of MCF-7 cells. These microbial metabolites from the secretome hold promise as biomarkers of drug resistance or innovative approaches for cancer treatment, either as standalone therapies or in combination with other medicines.PMID:37623881 | DOI:10.3390/metabo13080938

Metabolites. 2023 Aug 9;13(8):932. doi: 10.3390/metabo13080932.ABSTRACTMost studies on single ventricle (SV) circulation take a physiological or anatomical approach. Although there is a tight coupling between cardiac contractility and metabolism, the metabolic perspective on this patient population is very recent. Early findings point to major metabolic disturbances, with both impaired glucose and fatty acid oxidation in the cardiomyocytes. Additionally, Fontan patients have systemic metabolic derangements such as abnormal glucose metabolism and hypocholesterolemia. Our literature review compares the metabolism of patients with a SV circulation after Fontan palliation with that of patients with a healthy biventricular (BV) heart, or different subtypes of a failing BV heart, by Pubmed review of the literature on cardiac metabolism, Fontan failure, heart failure (HF), ketosis, metabolism published in English from 1939 to 2023. Early evidence demonstrates that SV circulation is not only a hemodynamic burden requiring staged palliation, but also a metabolic issue with alterations similar to what is known for HF in a BV circulation. Alterations of fatty acid and glucose oxidation were found, resulting in metabolic instability and impaired energy production. As reported for patients with BV HF, stimulating ketone oxidation may be an effective treatment strategy for HF in these patients. Few but promising clinical trials have been conducted thus far to evaluate therapeutic ketosis with HF using a variety of instruments, including ketogenic diet, ketone esters, and sodium-glucose co-transporter-2 (SGLT2) inhibitors. An initial trial on a small cohort demonstrated favorable outcomes for Fontan patients treated with SGLT2 inhibitors. Therapeutic ketosis is worth considering in the treatment of Fontan patients, as ketones positively affect not only the myocardial energy metabolism, but also the global Fontan physiopathology. Induced ketosis seems promising as a concerted therapeutic strategy.PMID:37623876 | DOI:10.3390/metabo13080932

Metabolites. 2023 Aug 8;13(8):928. doi: 10.3390/metabo13080928.ABSTRACTStress caused by noise is becoming widespread globally. Noise may lead to deafness, endocrine disorders, neurological diseases, and a decline in mental health. The mechanism behind noise-induced neurodevelopmental abnormalities is unclear, but apoptosis and pro-inflammatory signals may play an important role. In this study, weaned piglets were used as a model to explore noise-induced neurodevelopmental abnormalities. We hypothesized that long-term noise exposure would induce anxiety and cause acute stress, exhibited by alterations in neurotransmission in the amygdala. A total of 72 hybrid piglets (Large White × Duroc × Min Pig) were randomly divided into three groups, including noise (exposed to mechanical noise, 80-85 dB), control (blank, exposed to natural background sound, <40 dB), and music (positive control, exposed to Mozart K.448, 60-70 dB) groups. The piglets were exposed to 6 h of auditory noise daily (10:00-16:00) for 28 days. Compared with the control group, piglets exposed to noise showed more aggressive behavior. The expression of Caspase3, Caspase9, Bax, NF-κB (p56), TLR4, MYD88, I κ B α, IL-1 β, TNF-α, and IL-12RB2 was significantly upregulated in the amygdala, while the expression of Nrf2, HO-1, CAT, and SOD was downregulated in piglets in the noise group. Cell death occurred, and numerous inflammatory cells accumulated in the amygdala of piglets in the noise group. Targeted metabolomics showed that the content of inhibitory neurotransmitter GABA was higher in the amygdala of piglets in the noise group. Compared with the noise group, piglets in the music group displayed more positive emotion-related behaviors. Compared with the noise group, the expression of genes related to apoptosis, inflammation, and oxidative damage was lower in the music group. Cells of the amygdala in the music group were also of normal morphology. Our results show that noise-induced stress causes apoptosis and neuroinflammation in the amygdala and induces anxiety during the early neonatal neural development of piglets. In contrast, to some extent, music alleviates noise-induced anxiety.PMID:37623873 | DOI:10.3390/metabo13080928

Metabolites. 2023 Aug 8;13(8):929. doi: 10.3390/metabo13080929.ABSTRACTNon-alcoholic fatty liver disease is a multifaceted disease that progresses through multiple phases; it involves metabolic as well as structural changes. These alterations can be measured directly or indirectly through blood, non-invasive imaging, and/or tissue analyses. While some studies have evaluated the correlations between two sets of measurements (e.g., histopathology with cross-sectional imaging or blood biomarkers), the interrelationships, if any, among histopathology, clinical blood profiles, cross-sectional imaging, and metabolomics in a pediatric cohort remain unknown. We created a multiparametric clinical MRI-histopathologic NMR network map of pediatric NAFLD through multimodal correlation networks, in order to gain insight into how these different sets of measurements are related. We found that leptin and other blood markers were correlated with many other measurements; however, upon filtering out the blood biomarkers, the network was decomposed into three independent hubs centered around histopathological features, each with associated MRI and plasma metabolites. These multi-modality maps could serve as a framework for characterizing disease status and progression and could potentially guide medical interventions.PMID:37623872 | DOI:10.3390/metabo13080929

Metabolites. 2023 Aug 7;13(8):923. doi: 10.3390/metabo13080923.ABSTRACTThe untargeted approach to mass spectrometry-based metabolomics has a wide potential to investigate health and disease states, identify new biomarkers for diseases, and elucidate metabolic pathways. All this holds great promise for many applications in biological and chemical research. However, the complexity of instrumental parameters on advanced hybrid mass spectrometers can make the optimization of the analytical method immensely challenging. Here, we report a strategy to optimize the selected settings of a hydrophilic interaction liquid chromatography-tandem mass spectrometry method for untargeted metabolomics studies of human plasma, as a sample matrix. Specifically, we evaluated the effects of the reconstitution solvent in the sample preparation procedure, the injection volume employed, and different mass spectrometry-related operating parameters including mass range, the number of data-dependent fragmentation scans, collision energy mode, duration of dynamic exclusion time, and mass resolution settings on the metabolomics data quality and output. This study highlights key instrumental variables influencing the detection of metabolites along with suggested settings for the IQ-X tribrid system and proposes a new methodological framework to ensure increased metabolome coverage.PMID:37623867 | DOI:10.3390/metabo13080923

Metabolites. 2023 Aug 7;13(8):921. doi: 10.3390/metabo13080921.ABSTRACTTo gain confidence in results of omic-data acquisitions, methods must be benchmarked using validated quality control materials. We report data combining both untargeted and targeted metabolomics assays for the analysis of four new human fecal reference materials developed by the U.S. National Institute of Standards and Technologies (NIST) for metagenomics and metabolomics measurements. These reference grade test materials (RGTM) were established by NIST based on two different diets and two different samples treatments, as follows: firstly, homogenized fecal matter from subjects eating vegan diets, stored and submitted in either lyophilized (RGTM 10162) or aqueous form (RGTM 10171); secondly, homogenized fecal matter from subjects eating omnivore diets, stored and submitted in either lyophilized (RGTM 10172) or aqueous form (RGTM 10173). We used four untargeted metabolomics assays (lipidomics, primary metabolites, biogenic amines and polyphenols) and one targeted assay on bile acids. A total of 3563 compounds were annotated by mass spectrometry, including 353 compounds that were annotated in more than one assay. Almost half of all compounds were annotated using hydrophilic interaction chromatography/accurate mass spectrometry, followed by the lipidomics and the polyphenol assays. In total, 910 metabolites were found in at least 4-fold different levels in fecal matter from vegans versus omnivores, specifically for peptides, amino acids and lipids. In comparison, only 251 compounds showed 4-fold differences between lyophilized and aqueous fecal samples, including DG O-34:0 and methionine sulfoxide. A range of diet-specific metabolites were identified to be significantly different between vegans and omnivores, exemplified by citrinin and C17:0-acylcarnitine for omnivores, and curcumin and lenticin for vegans. Bioactive molecules like acyl alpha-hydroxy-fatty acids (AAHFA) were differentially regulated in vegan versus omnivore fecal materials, highlighting the importance of diet-specific reference materials for dietary biomarker studies.PMID:37623865 | DOI:10.3390/metabo13080921

Metabolites. 2023 Aug 4;13(8):915. doi: 10.3390/metabo13080915.ABSTRACTMetabolomics generates a vast amount of data and heavily relies on data science for biological interpretation [...].PMID:37623859 | DOI:10.3390/metabo13080915

Metabolites. 2023 Aug 4;13(8):913. doi: 10.3390/metabo13080913.ABSTRACTOsteoarthritis (OA) is a common cause of lameness in sport horses with a significant economic impact. The prevention of OA is crucial since no effective treatment is available. This study aimed to apply untargeted metabolomic analysis to investigate the differences in synovial fluid (SF) composition between healthy and OA-affected joints in horses. SF collected from healthy (n.8) and OA (n.11) horses was analyzed using H-NMR analysis. Metabolomic analysis allowed 55 different metabolites to be identified and quantified in SF samples. Nineteen metabolites were found to be differently concentrated in OA compared to control horses. Synovial fluids from the OC group were found to be higher in 1,3-dihydroxyacetone but lower in tryptophan, phenylalanine, tyrosine, uridine, creatinine, creatine, glycine, choline, asparagine, glutamine, arginine, 3-hydroxybutyrate, valine, 2-hydroxyisovalerate, α-ketoisovaleric acid, 3-methyl-2-oxovalerate, 3-hydroxyisobutyrate, isoleucine, and methionine compared to the controls. A variety of SF metabolites significantly changed following joint disease, demonstrating the complex mechanism underlying osteoarthritis in horses and highlighting the value of applying the metabolomic approach in clinical research.PMID:37623857 | DOI:10.3390/metabo13080913

Metabolites. 2023 Aug 3;13(8):909. doi: 10.3390/metabo13080909.ABSTRACTMatthiola longipetala subsp. livida is an annual herb in Brassicaceae that has received little attention despite the family's high reputation for health benefits, particularly cancer prevention. In this study, UPLC-HRMS-MS analysis was used for mapping the chemical constituents of different plant parts (i.e., flowers, leaves, and roots). Also, spectral similarity networks via the Global Natural Products Social Molecular Networking (GNPS) were employed to visualize their chemical differences and similarities. Additionally, the cytotoxic activity on HCT-116, HeLa, and HepG2 cell lines was evaluated. Throughout the current analysis, 154 compounds were annotated, with the prevalence of phenolic acids, glucosinolates, flavonol glucosides, lipids, peptides, and others. Predictably, secondary metabolites (phenolic acids, flavonoids, and glucosinolates) were predominant in flowers and leaves, while the roots were characterized by primary metabolites (peptides and fatty acids). Four diacetyl derivatives tentatively assigned as O-acetyl O-malonyl glucoside of quercetin (103), kaempferol (108 and 112), and isorhamnetin (114) were detected for the first time in nature. The flowers and leaves extracts showed significant inhibition of HeLa cell line propagation with LC50 values of 18.1 ± 0.42 and 29.6 ± 0.35 µg/mL, respectively, whereas the flowers extract inhibited HCT-116 with LC50 24.8 ± 0.45 µg/mL, compared to those of Doxorubicin (26.1 ± 0.27 and 37.6 ± 0.21 µg/mL), respectively. In conclusion, the flowers of M. longipetala are responsible for the abundance of bioactive compounds with cytotoxic properties.PMID:37623853 | DOI:10.3390/metabo13080909

Metabolites. 2023 Aug 3;13(8):908. doi: 10.3390/metabo13080908.ABSTRACTTo represent the composition of small molecules circulating in HepG2 cells and the formation of the "core" of characteristic metabolites that often attract researchers' attention, we conducted a meta-analysis of 56 datasets obtained through metabolomic profiling via mass spectrometry and NMR. We highlighted the 288 most commonly studied compounds of diverse chemical nature and analyzed metabolic processes involving these small molecules. Building a complete map of the metabolome of a cell, which encompasses the diversity of possible impacts on it, is a severe challenge for the scientific community, which is faced not only with natural limitations of experimental technologies, but also with the absence of transparent and widely accepted standards for processing and presenting the obtained metabolomic data. Formulating our research design, we aimed to reveal metabolites crucial to the Hepg2 cell line, regardless of all chemical and/or physical impact factors. Unfortunately, the existing paradigm of data policy leads to a streetlight effect. When analyzing and reporting only target metabolites of interest, the community ignores the changes in the metabolomic landscape that hide many molecular secrets.PMID:37623852 | DOI:10.3390/metabo13080908