PubMed

Metabolites. 2022 Nov 4;12(11):1068. doi: 10.3390/metabo12111068.ABSTRACTCardiac function is closely related to heart metabolism. Heart failure patients undergoing LVAD support have shown varying degrees of remodeling of both cardiac function and morphology. However, the metabolic changes in patients with different outcomes are unclear. This study aimed to identify metabolic differences and evaluate metabolomics-based biomarkers in patients with non-improved/improved cardiac function after LVAD support. Sixteen patients were enrolled in this study. Plasma samples were analyzed by using untargeted metabolomic approaches. Multivariate statistical analysis and a Mann-Whitney U-test was performed to clarify the separation in metabolites and to identify changes in plasma metabolites between the two groups, respectively. The efficacy of candidate biomarkers was tested by the area under the curve receiver operating characteristic curve. Using the Metabolomics Standards Initiative level 2, a total of 1542 and 619 metabolites were detected in the positive and negative ion modes, respectively. Enrichment analysis showed that metabolites in improved cardiac function patients were mainly involved in carbohydrate metabolism and amino acid metabolism. Metabolites from non-improved cardiac function patients were mainly involved in hormone metabolism. Furthermore, we found tris(hydroxymethyl)aminomethane and 5-guanidino-3-methyl-2-oxopentanoic acid could serve as biomarkers to predict whether a patient's cardiac function would improve after LVAD support.PMID:36355151 | DOI:10.3390/metabo12111068

Metabolites. 2022 Nov 4;12(11):1066. doi: 10.3390/metabo12111066.ABSTRACTCell metabolism represents the coordinated changes in genes, proteins, and metabolites that occur in health and disease. The metabolic fluxome, which includes both intracellular and extracellular metabolic reaction rates (fluxes), therefore provides a powerful, integrated description of cellular phenotype. However, intracellular fluxes cannot be directly measured. Instead, flux quantification requires sophisticated mathematical and computational analysis of data from isotope labeling experiments. In this review, we describe isotope-assisted metabolic flux analysis (iMFA), a rigorous computational approach to fluxome quantification that integrates metabolic network models and experimental data to generate quantitative metabolic flux maps. We highlight practical considerations for implementing iMFA in mammalian models, as well as iMFA applications in in vitro and in vivo studies of physiology and disease. Finally, we identify promising new frontiers in iMFA which may enable us to fully unlock the potential of iMFA in biomedical research.PMID:36355149 | DOI:10.3390/metabo12111066

Metabolites. 2022 Nov 2;12(11):1061. doi: 10.3390/metabo12111061.ABSTRACTMicrobiota-derived metabolites have biological importance for their host. Spermidine, a metabolite described for its protective effect in age-related diseases, is now studied for its role in the resolution of inflammation and gut homeostasis. Strategies to modulate its production in the gastrointestinal tract are of interest to increase host spermidine intakes. Here, we show that metabolic engineering can be used to increase spermidine production by the probiotic Escherichia coli Nissle 1917 (EcN), used in humans. First, we found that increasing the expression of genes involved in polyamine biosynthesis, namely the S-adenosylmethionine synthase speD and the spermidine synthase speE, resulted in an increase in spermidine produced and excreted by our engineered bacteria. The major drawback of this first attempt was the production of acetylated forms of spermidine. Next, we propose to solve this problem by increasing the expression of the spermidine exporter system MdtI/MdtJ. This second strategy had a major impact on the spermidine profile found in the culture supernatant. Our results demonstrate, for the first time, the feasibility of rationally engineering bacterial probiotic strains to increase their ability to deliver the microbiota-derived metabolite, spermidine. This work illustrates how metabolomic and synthetic biology can be used to design and improve engineered Live Biotherapeutic Products that have the potential to be used in personalized medicine.PMID:36355144 | DOI:10.3390/metabo12111061

Metabolites. 2022 Nov 2;12(11):1058. doi: 10.3390/metabo12111058.ABSTRACTPneumonia is a common cause of morbidity and mortality and is most often caused by bacterial pathogens. COVID-19 is characterized by lung infection with potential progressive organ failure. The systemic consequences of both disease on the systemic blood metabolome are not fully understood. The aim of this study was to compare the blood metabolome of both diseases and we hypothesize that plasma metabolomics may help to identify the systemic effects of these diseases. Therefore, we profiled the plasma metabolome of 43 cases of COVID-19 pneumonia, 23 cases of non-COVID-19 pneumonia, and 26 controls using a non-targeted approach. Metabolic alterations differentiating the three groups were detected, with specific metabolic changes distinguishing the two types of pneumonia groups. A comparison of venous and arterial blood plasma samples from the same subjects revealed the distinct metabolic effects of pulmonary pneumonia. In addition, a machine learning signature of four metabolites was predictive of the disease outcome of COVID-19 subjects with an area under the curve (AUC) of 86 ± 10 %. Overall, the results of this study uncover systemic metabolic changes that could be linked to the etiology of COVID-19 pneumonia and non-COVID-19 pneumonia.PMID:36355140 | DOI:10.3390/metabo12111058

Metabolites. 2022 Nov 2;12(11):1056. doi: 10.3390/metabo12111056.ABSTRACTThe COVID-19 pandemic boosted the development of diagnostic tests to meet patient needs and provide accurate, sensitive, and fast disease detection. Despite rapid advancements, limitations related to turnaround time, varying performance metrics due to different sampling sites, illness duration, co-infections, and the need for particular reagents still exist. As an alternative diagnostic test, we present urine analysis through flow-injection-tandem mass spectrometry (FIA-MS/MS) as a powerful approach for COVID-19 diagnosis, targeting the detection of amino acids and acylcarnitines. We adapted a method that is widely used for newborn screening tests on dried blood for urine samples in order to detect metabolites related to COVID-19 infection. We analyzed samples from 246 volunteers with diagnostic confirmation via PCR. Urine samples were self-collected, diluted, and analyzed with a run time of 4 min. A Lasso statistical classifier was built using 75/25% data for training/validation sets and achieved high diagnostic performances: 97/90% sensitivity, 95/100% specificity, and 95/97.2% accuracy. Additionally, we predicted on two withheld sets composed of suspected hospitalized/symptomatic COVID-19-PCR negative patients and patients out of the optimal time-frame collection for PCR diagnosis, with promising results. Altogether, we show that the benchmarked FIA-MS/MS method is promising for COVID-19 screening and diagnosis, and is also potentially useful after the peak viral load has passed.PMID:36355139 | DOI:10.3390/metabo12111056

Metabolites. 2022 Oct 31;12(11):1047. doi: 10.3390/metabo12111047.ABSTRACTDoxorubicin (DOX) is a chemotherapeutic agent is used for various cancer cells. To characterize the chemical structural components and metabolic inhibition, we applied a DOX to HCT116 colon cancer cells using an independent metabolites profiling approach. Chemical metabolomics has been involved in the new drug delivery systems. Metabolomics profiling of DOX-applied HCT116 colon cancer cellular metabolisms is rare. We used 1H nuclear magnetic resonance (NMR) spectroscopy in this study to clarify how DOX exposure affected HCT116 colon cancer cells. Metabolomics profiling in HCT116 cells detects 50 metabolites. Tracking metabolites can reveal pathway activities. HCT116 colon cancer cells were evenly treated with different concentrations of DOX for 24 h. The endogenous metabolites were identified by comparison with healthy cells. We found that acetate, glucose, glutamate, glutamine, sn-glycero-3-phosphocholine, valine, methionine, and isoleucine were increased. Metabolic expression of alanine, choline, fumarate, taurine, o-phosphocholine, inosine, lysine, and phenylalanine was decreased in HCT116 cancer cells. The metabolic phenotypic expression is markedly altered during a high dose of DOX. It is the first time that there is a metabolite pool and phenotypic expression in colon cancer cells. Targeting the DOX-metabolite axis may be a novel strategy for improving the curative effect of DOX-based therapy for colon cancer cells. These methods facilitate the routine metabolomic analysis of cancer cells.PMID:36355130 | DOI:10.3390/metabo12111047

Metabolites. 2022 Oct 30;12(11):1045. doi: 10.3390/metabo12111045.ABSTRACTThe selection of sows that are reproductively fit and produce large litters of piglets is imperative for success in the pork industry. Currently, low heritability of reproductive and litter-related traits and unfavourable genetic correlations are slowing the improvement of pig selection efficiency. The integration of biomarkers as a supplement or alternative to the use of genetic markers may permit the optimization and increase of selection protocol efficiency. Metabolite biomarkers are an advantageous class of biomarkers that can facilitate the identification of cellular processes implicated in reproductive condition. Metabolism and metabolic biomarkers have been previously implicated in studies of female mammalian fertility, however a systematic analysis across multiple biofluids in infertile and high reproductive potential phenotypes has not been explored. In the current study, the serum, urinary and salivary metabolomes of infertile (INF) sows and high reproductive potential (HRP) sows with a live litter size ≥ 13 piglets were examined using LC-MS/MS techniques, and a data pipeline was used to highlight possible metabolite reproductive biomarkers discriminating the reproductive groups. The metabolomes of HRP and INF sows were distinct, including significant alterations in amino acid, fatty acid, membrane lipid and steroid hormone metabolism. Carnitines and fatty acid related metabolites were most discriminatory in separating and classifying the HRP and INF sows based on their biofluid metabolome. It appears that urine is a superior biofluid than saliva and serum for potentially predicting the reproductive potential level of a given female pig based on the performance of the resultant biomarker models. This study lays the groundwork for improving gilt and sow selection protocols using metabolomics as a tool for the prediction of reproductive potential.PMID:36355128 | DOI:10.3390/metabo12111045

Metabolites. 2022 Oct 30;12(11):1041. doi: 10.3390/metabo12111041.ABSTRACTIncreases in longevity and obesity have led to a higher prevalence of Metabolic Syndrome (MetS) and several chronic conditions, such as hypertension. The prevalence of MetS and hypertension increases with advancing age and their detrimental effects on health can be attenuated by physical activity. Combined aerobic and resistance exercise training (CT) is recommended to maintain good health in older adults and is known to generate important metabolic adaptations. In this study we performed a metabolomics analysis, based on Hydrogen Nuclear Magnetic Resonance (1H NMR), to investigate the kinetics of changes in metabolism in non-physically active older women with MetS in response to 16 weeks of CT. A subset of women with MetS were selected from a larger randomized trial (that included men and women without MetS), with 12 participants on CT and 13 from the Control Group (CG). CT comprised walking/running at 63% of VO2max, three times/week, and resistance training (RT), consisting of 15 repetitions of seven exercises at moderate intensity, twice/week. Serum metabolomic profile was analysed at baseline (0W), 4 (4W), 8 (8W), 12 (12W) and 16 weeks (16W) for CT or CG. Cardiorespiratory fitness, RT load, blood pressure, body composition, lipid and glycaemic profile were also assessed. After 16 weeks CT increased cardiorespiratory fitness (13.1%, p < 0.05) and RT load (from 48% in the lat pulldown to 160% in the leg press, p < 0.05), but there were no changes in MetS parameters, such as body composition (Body Mass, Body Mass Index (BMI), body fat percentage and waist circumference), blood pressure, lipid and glycaemic profile. However, we identified potential higher substrate to the tricarboxylic acid cycle (increase in 2-Oxobutyrate from 0W (0.0029 ± 0.0009) to 4W (0.0038 ± 0.0011) and 8W (0.0041 ± 0.0015), p < 0.05), followed by alterations (different from 0W, p < 0.05) in the production of ketone bodies (3-Hydroxybutyrate, 0W (0.0717 ± 0.0377) to 16W (0.0397 ± 0.0331), and Acetoacetate, 0W (0.0441 ± 0.0240) to 16W (0.0239 ± 0.0141)), which together might explain the known improvement in fatty acid oxidation with exercise. There was also a late increase in ornithine at 16W of CT. Further studies are needed to investigate the association between these metabolic pathways and clinical outcomes in this population.PMID:36355124 | DOI:10.3390/metabo12111041

Metabolites. 2022 Oct 28;12(11):1039. doi: 10.3390/metabo12111039.ABSTRACTClostridioides difficile infection (CDI) is responsible for an increasing number of cases of post-antibiotic diarrhea worldwide, which has high severity and mortality among hospitalized elderly patients. The disruption of gut microbiota due to antibacterial medication facilitates the intestinal colonization of C. difficile. In the present study, a murine model was used to investigate the potential effects of antibiotic administration and subsequent colonization by C. difficile, as well as the effects of three different 10-day treatments (metronidazole, probiotics, and fecal microbiota transplantation), on the brain metabolome for the first time. Four different metabolomic-based methods (targeted HILIC-MS/MS, untargeted RP-LC-HRMS/MS, targeted GC-MS/MS, and untargeted GC-MS) were applied, resulting in the identification of 217 unique metabolites in the brain extracts, mainly glycerophospholipids, glycerolipids, amino acids, carbohydrates, and fatty acids. Univariate and multivariate statistical analysis revealed that CDI, as well as the subsequent treatments, altered significantly several brain metabolites, probably due to gut dysbiosis, and affected the brain through the gut-brain axis. Notably, none of the therapeutic approaches completely restored the brain metabolic profile to the original, healthy, and non-infected phenotype, even after 10 days of treatment.PMID:36355122 | DOI:10.3390/metabo12111039

Metabolites. 2022 Oct 28;12(11):1037. doi: 10.3390/metabo12111037.ABSTRACTExosomes released from tumor cells treated with cancer-targeting drugs reflect altered metabolic processes within the cells. Therefore, metabolites in exosomes can be used as markers to predict the therapeutic response or identify therapeutic targets. In this study, metabolite changes in exosomes were investigated by co-administration of the herbal extract SH003 and docetaxel (DTX), which exert a synergistic anti-cancer effect on lung cancer cells. Exosomes released from cells treated with SH003 and DTX were purified, and untargeted metabolic profiling was performed by liquid chromatography-tandem mass spectrometry. Analysis of altered metabolic-based pathways showed that the combined treatment synergistically increased pyrimidine metabolism compared with single-drug treatment. Additionally, xenobiotic metabolism by cytochrome P450 was specifically increased in cells treated with the combination. However, the released exosomes and increased metabolites in exosomes did not affect the anti-cancer effect of SH003 and DTX. Therefore, our study suggests that metabolite profiling can be used to evaluate the efficacy of combined treatments. Furthermore, such exosome-based metabolism may facilitate understanding the physiological endpoints of combination therapy in human biofluids.PMID:36355120 | DOI:10.3390/metabo12111037

Metabolites. 2022 Oct 27;12(11):1030. doi: 10.3390/metabo12111030.ABSTRACTThe lipid composition of lipoprotein particles is determinative of their respective formation and function. In turn, the combination and correlation of nuclear magnetic resonance (NMR)-based lipoprotein measurements with mass spectrometry (MS)-based lipidomics is an appealing technological combination for a better understanding of lipid metabolism in health and disease. Here, we developed a combined workflow for subsequent NMR- and MS-based analysis on single sample aliquots of human plasma. We evaluated the quantitative agreement of the two platforms for lipid quantification and benchmarked our combined workflow. We investigated the congruence and complementarity between the platforms in order to facilitate a better understanding of patho-physiological lipoprotein and lipid alterations. We evaluated the correlation and agreement between the platforms. Next, we compared lipid class concentrations between healthy controls and rheumatoid arthritis patient samples to investigate the consensus among the platforms on differentiating the two groups. Finally, we performed correlation analysis between all measured lipoprotein particles and lipid species. We found excellent agreement and correlation (r > 0.8) between the platforms and their respective diagnostic performance. Additionally, we generated correlation maps detailing lipoprotein/lipid interactions and describe disease-relevant correlations.PMID:36355113 | DOI:10.3390/metabo12111030

Metabolites. 2022 Oct 27;12(11):1029. doi: 10.3390/metabo12111029.ABSTRACTThis study aimed to elucidate the metabolomic signature associated with obesity and periodontitis during pregnancy in plasma and saliva biofluids. Ninety-eight pregnant women were divided into: with obesity and periodontitis (OP = 20), with obesity but without periodontitis (OWP = 27), with normal BMI but with periodontitis (NP = 21), with normal BMI and without periodontitis (NWP = 30). Saliva and plasma were analyzed by 1H-NMR for metabolites identification. Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA (sPLS-DA), and Variable Importance of Projection (VIP) were performed. ANOVA and Pearson's correlation were applied (p < 0.05). Plasmatic analysis indicated the levels of glucose (p = 0.041) and phenylalanine (p = 0.015) were positively correlated with periodontal parameters and BMI, respectively. In saliva, periodontitis was mainly associated with high levels of acetic acid (p = 0.024), isovaleric acid, butyric acid, leucine, valine, isoleucine, and propionic acid (p < 0.001). High salivary concentrations of glycine (p = 0.015), succinic acid (p = 0.015), and lactate (p = 0.026) were associated with obesity. Saliva demonstrated a more elucidative difference than plasma, indicating the glucose-alanine cycle, alanine metabolism, valine, leucine and isoleucine degradation, glutamate metabolism, and Warburg effect as the main metabolic pathways.PMID:36355112 | DOI:10.3390/metabo12111029

Metabolites. 2022 Oct 26;12(11):1026. doi: 10.3390/metabo12111026.ABSTRACTExercise intolerance is a major manifestation of post-acute sequelae of severe acute respiratory syndrome coronavirus infection (PASC, or "long-COVID"). Exercise intolerance in PASC is associated with higher arterial blood lactate accumulation and lower fatty acid oxidation rates during graded exercise tests to volitional exertion, suggesting altered metabolism and mitochondrial dysfunction. It remains unclear whether the profound disturbances in metabolism that have been identified in plasma from patients suffering from acute coronavirus disease 2019 (COVID-19) are also present in PASC. To bridge this gap, individuals with a history of previous acute COVID-19 infection that did not require hospitalization were enrolled at National Jewish Health (Denver, CO, USA) and were grouped into those that developed PASC (n = 29) and those that fully recovered (n = 16). Plasma samples from the two groups were analyzed via mass spectrometry-based untargeted metabolomics and compared against plasma metabolic profiles of healthy control individuals (n = 30). Observational demographic and clinical data were retrospectively abstracted from the medical record. Compared to plasma of healthy controls or individuals who recovered from COVID-19, PASC plasma exhibited significantly higher free- and carnitine-conjugated mono-, poly-, and highly unsaturated fatty acids, accompanied by markedly lower levels of mono-, di- and tricarboxylates (pyruvate, lactate, citrate, succinate, and malate), polyamines (spermine) and taurine. Plasma from individuals who fully recovered from COVID-19 exhibited an intermediary metabolic phenotype, with milder disturbances in fatty acid metabolism and higher levels of spermine and taurine. Of note, depletion of tryptophan-a hallmark of disease severity in COVID-19-is not normalized in PASC patients, despite normalization of kynurenine levels-a tryptophan metabolite that predicts mortality in hospitalized COVID-19 patients. In conclusion, PASC plasma metabolites are indicative of altered fatty acid metabolism and dysfunctional mitochondria-dependent lipid catabolism. These metabolic profiles obtained at rest are consistent with previously reported mitochondrial dysfunction during exercise, and may pave the way for therapeutic intervention focused on restoring mitochondrial fat-burning capacity.PMID:36355108 | DOI:10.3390/metabo12111026

Metabolites. 2022 Oct 26;12(11):1024. doi: 10.3390/metabo12111024.ABSTRACTCardamine violifolia, a species belonging to the Brassicaceae family, is a selenium hyperaccumulator and a nutritious leafy vegetable. Our previous study showed that C. violifolia leaves are rich in total phenolic acids, but the composition and corresponding genes remain unknown. In this study, we investigated the phenolic acid compounds and potential gene regulation network in the outer leaves (OL) and central leaves (CL) of C. violifolia using transcriptome and metabolome analyses. Results showed that the OL contained a higher total phenolic acid content than the CL. Metabolome analysis revealed a total of 115 phenolic acids, 62 of which (e.g., arbutin, rosmarinic acid, hydroxytyrosol acetate, and sinapic acid) were differentially accumulated between the CL and OL of C. violifolia. Transcriptome analysis showed that the differentially expressed genes were significantly enriched in the pathways of secondary metabolite biosynthesis and phenylpropanoid biosynthesis. Conjoint analysis of the transcriptome and metabolome indicated that seven genes (CYP84A1, CYP84A4, CADH9, SGT1, UGT72E1, OMT1, and CCR2) and eight phenolic acids (sinapic acid, sinapyl alcohol, 5-O-caffeoylshikimic acid, sinapoyl malate, coniferin, coniferyl alcohol, L-phenylalanine, and ferulic acid) constituted a possible regulatory network. This study revealed the phenolic acid compounds and possible regulatory network of C. violifolia leaves and deepened our understanding of its nutrient value.PMID:36355107 | DOI:10.3390/metabo12111024

Metabolites. 2022 Oct 25;12(11):1020. doi: 10.3390/metabo12111020.ABSTRACTThe study of post-mortem changes is a crucial component of forensic investigation. Human forensic taphonomic facilities (HFTFs) are the only institutions allowing the design and execution of controlled human decomposition experiments. When bodies are skeletonized, bones are normally stored in skeletal collections and used for anthropological studies. However, HFTFs apply chemical and/or thermal treatments to the remains prior bone long-term storage. These treatments are believed to alter heavily the original biochemical and molecular signature of bone material. The present study aims to evaluate the effect of these procedures on the bone metabolome and lipidome by using an animal bone model. Three intact bovine tibiae were processed using three protocols routinely applied at HFTFs, and their three counterparts were used as non-treated controls. Bone powder samples were subjected to biphasic extraction and both metabolites and lipids were analysed via liquid chromatography tandem mass-spectrometry. Results showed severe reductions in the abundances of both metabolites and lipids, and the presence of contamination introduced by cleaning agents. Despite the preliminary nature of the study, we demonstrated that the biochemical profile of bone is heavily affected by the maceration procedures. Ideally, these treatments should be avoided, or replaced by minimally invasive procedures agreed across HFTFs.PMID:36355103 | DOI:10.3390/metabo12111020

Metabolites. 2022 Oct 23;12(11):1011. doi: 10.3390/metabo12111011.ABSTRACTGlucose absorption promoters perform insulin mimic functions to enhance blood glucose transport to skeletal muscle cells and accelerate glucose consumption, thereby reducing blood glucose levels. In our screening exploration of food ingredients for improving glucose transportation and metabolism, we found that the saponins in American ginseng (Panaxquinquefolius L.) showed potential activity to promote glucose uptake, which can be used for stabilizing levels of postprandial blood glucose. The aim of this study was to identify key components of American ginseng with glucose uptake-promoting activity and to elucidate their metabolic regulatory mechanisms. Bio-guided isolation using zebrafish larvae and 2-NBDG indicator identified ginsenoside Rb1 (GRb1) as the most potential promotor of glucose uptake. Using UPLC-QTOF-MS/MS combined with RT-qPCR and phenotypic verification, we found that riboflavin metabolism is the hinge for GRb1-mediated facilitation of glucose transport. GRb1-induced restoration of redox homeostasis was mediated by targeting riboflavin transporters (SLC52A1 and SLC52A3) and riboflavin kinase (RFK).PMID:36355094 | DOI:10.3390/metabo12111011

Metabolites. 2022 Oct 23;12(11):1010. doi: 10.3390/metabo12111010.ABSTRACTCarotenoids are important compounds of quality and coloration within sweet potato storage roots, but the mechanisms that govern the accumulation of these carotenoids remain poorly understood. In this study, metabolomic and transcriptomic analyses of carotenoids were performed using young storage roots (S2) and old storage roots (S4) from white-fleshed (variety S19) and yellow-fleshed (variety BS) sweet potato types. S19 storage roots exhibited significantly lower total carotenoid levels relative to BS storage roots, and different numbers of carotenoid types were detected in the BS-S2, BS-S4, S19-S2, and S19-S4 samples. β-cryptoxanthin was identified as a potential key driver of differences in root coloration between the S19 and BS types. Combined transcriptomic and metabolomic analyses revealed significant co-annotation of the carotenoid and abscisic acid (ABA) metabolic pathways, PSY (phytoene synthase), CHYB (β-carotene 3-hydroxylase), ZEP (zeaxanthin epoxidase), NCED3 (9-cis-epoxycarotenoid dioxygenase 3), ABA2 (xanthoxin dehydrogenase), and CYP707A (abscisic acid 8'-hydroxylase) genes were found to be closely associated with carotenoid and ABA content in these sweet potato storage roots. The expression patterns of the transcription factors OFP and FAR1 were associated with the ABA content in these two sweet potato types. Together, these results provide a valuable foundation for understanding the mechanisms governing carotenoid biosynthesis in storage roots, and offer a theoretical basis for sweet potato breeding and management.PMID:36355093 | DOI:10.3390/metabo12111010

Mar Drugs. 2022 Oct 27;20(11):673. doi: 10.3390/md20110673.ABSTRACTA detailed examination of a unique molecular family, restricted to the Callyspongia genus, in a molecular network obtained from an in-house Haplosclerida marine sponge collection (including Haliclona, Callyspongia, Xestospongia, and Petrosia species) led to the discovery of subarmigerides, a series of rare linear peptides from Callyspongia subarmigera, a genus mainly known for polyacetylenes and lipids. The structure of the sole isolated peptide, subarmigeride A (1) was elucidated through extensive 1D and 2D NMR spectroscopy, HRMS/MS, and Marfey's method to assign its absolute configuration. The putative structures of seven additional linear peptides were proposed by an analysis of their respective MS/MS spectra and a comparison of their fragmentation patterns with the heptapeptide 1. Surprisingly, several structurally related analogues of subarmigeride A (1) occurred in one distinct cluster from the molecular network of the cyanobacteria strains of the Guadeloupe mangroves, suggesting that the true producer of this peptide family might be the microbial sponge-associated community, i.e., the sponge-associated cyanobacteria.PMID:36354996 | DOI:10.3390/md20110673

J Fungi (Basel). 2022 Nov 10;8(11):1186. doi: 10.3390/jof8111186.ABSTRACTTrichoderma is internationally recognized as a biocontrol fungus for its broad-spectrum antimicrobial activity. Intriguingly, the crosstalk mechanism between the plant and Trichoderma is dynamic, depending on the Trichoderma strains and the plant species. In our previous study, the Trichoderma virens 192-45 strain showed better pathogen inhibition through the secretive non-volatile and volatile substrates. Therefore, we studied transcriptional and metabolic responses altered in creeping bentgrass (Agrostis stolonifera L.) with T. virens colonization prior to a challenge with Clarireedia homoeocarpa. This fungal pathogen causes dollar spot on various turfgrasses. When the pathogen is deficient, the importance of T. virens to the enhancement of plant growth can be seen in hormonal production and microbe signaling, such as indole-3-acrylic acid. Therefore, these substrates secreted by T. virens and induced genes related to plant growth can be the 'pre-defense' for ensuing pathogen attacks. During C. homoeocarpa infection, the Trichoderma-plant interaction activates defense responses through the SA- and/or JA-dependent pathway, induced by T. virens and its respective exudates, such as oleic, citric, and stearic acid. Thus, we will anticipate a combination of genetic engineering and exogenous application targeting these genes and metabolites, which could make creeping bentgrass more resistant to dollar spot and other pathogens.PMID:36354953 | DOI:10.3390/jof8111186

J Fungi (Basel). 2022 Oct 29;8(11):1149. doi: 10.3390/jof8111149.ABSTRACTChaetomiaceae fungi are ascosporulating fungi whose importance as human pathogens has been frequently ignored. In the current study, a new isolate of the genus Subramaniula was described. The fungus was isolated from the soil of Wadi Om Nefa'a, Hurghada in the Red Sea Governorate, Egypt. Previously, Subramaniula were misidentified as Papulaspora spp. According to molecular analysis, the fungus was identified as Subramaniula asteroids OP484336. Remarkably, this species has been found among other fungi responsible for keratitis in humans and has been recorded for the first time in Egypt. Analysing the Subramaniula asteroids' metabolic profile was one of the objectives of the current study because little is known about this family's metabolome. The fungal extract's untargeted metabolic profiling was carried out by gas chromatography-mass spectroscopy (GC/MS), 1H and 1H-HSQC nuclear magnetic resonance (NMR) data, and their corresponding databases. In total, fifty-nine metabolites have been reported in the polar and non-polar extracts. The majority of polar metabolites are amino acids and carbohydrates. The non-polar extract's main components were 1-dodecanamine, N,N-dimethyl-, 1-tetradecanamine, N,N-dimethyl-, and 9-octadecenoic acid ethyl ester. The current study is the first to provide a metabolic profile of Subramaniula asteroids, which can be used in chemotaxonomical classification, antifungal drug development, and biological activity investigation of the studied species.PMID:36354915 | DOI:10.3390/jof8111149