Low Molecular Weight Metabolites Research Articles

Phytotoxicity of Dactylonectria spp. exudates on kiwifruit vine and profile of secondary metabolites for understanding their relationship with the host plant

Kiwifruit vine decline syndrome (KVDS), which is responsible for a progressive decline in yields in Italy, is linked to a non-specific reduction in root development, the biotic or abiotic causes of which are still unclear. Dactylonectria is one of the most common soil-borne fungi associated with kiwifruit vines, However, its role in KVDS has not yet been clarified; therefore, Dactylonectria functional relationship with kiwifruit vine at rhizosphere level was investigated focusing solely on its exudates. Six isolates, four from kiwifruit-bearing soils belonging to D. torresensis. D. ecuadoriensis, D. novozelandica and D. pauciseptata, and two D. torresensis from a virgin soil, was tested for phytotoxicity of exudates by growing kiwifruit in vitro plants on MS media amended at 50% with sterile fungal filtrates. Parallelly, low molecular weight (LMW) metabolic profile of fungal filtrates was evaluated with untargeted metabolomics approach using LC-MS/TOF. The fungal isolates from kiwifruit bearing soil were much richer in LMW metabolites than those from virgin soil. Non host specific mycotoxins such as Aflaxoxin B2, Alternariol and Alterlactone were found in these isolates along with a number of metabolites most of which were characterised by antimicrobial properties. D. torresensis isolates were clearly discriminated from the other three species based on metabolic profile. A negative Pearson correlation between the growth index of kiwifruit vitro-plants and LMW metabolite count per isolate (richness) showed that the latter were associated with phytotoxicity, but the degree of correlation (r = −0.639) indicated that they were not the only component responsible. The results suggest that kiwifruit vines may alter the composition of the Dactylonectria spp. community in the root zone, which in turn may directly or indirectly contribute to kiwifruit vine decline syndrome.

Probing the alterations in mice cecal content due to high-fat diet

The global prevalence of obesity more than doubled between 1990 and 2022. By 2022, 2.5 billion adults aged 18 and older were overweight, with over 890 million of them living with obesity. The urgent need for understanding the impact of high fat diet, together with the demanding of analytical methods with low energy/chemicals consumption, can be fulfilled by rapid, high throughputs spectroscopic techniques.To understand the impact of high-fat diet on the metabolic signatures of mouse cecal contents, we characterized metabolite variations in two diet-groups (standard vs. high-fat diet) using FTIR spectroscopy and multivariate analysis. Their cecal content showed distinct spectral features corresponding to high- and low-molecular-weight metabolites. Further quantification of 13 low molecular weight metabolites using liquid chromatography showed significant reduction in production of short chain fatty acids and amino acids associated with high-fat diet samples. These findings demonstrated the potential of spectroscopy to follow changes in gut metabolites.

In vitro simulated saliva, gastric, and intestinal digestion followed by faecal fermentation reveals a potential modulatory activity of Epimedium on human gut microbiota

Herba Epimedii, known for its rich array of bioactive ingredients and widespread use in ethnopharmacological practices, still lacks a comprehensive understanding of its gastrointestinal biotransformation. In this study, we qualitatively explored the dynamic changes in Epimedium sagittatum components during in vitro simulated digestions, with a quantitative focus on its five major flavonoids. Notably, significant metabolism of E. sagittatum constituents occurred in the simulated small intestinal fluid and colonic fermentation stages, yielding various low molecular weight metabolites. Flavonoids like kaempferol glycosides were fully metabolized in the simulated intestinal fluid, while hyperoside digestion occurred during simulated colon digestion. Colonic fermentation led to the production of two known bioactive isoflavones, genistein, and daidzein. The content and bioaccessibility of the five major epimedium flavonoids—icariin, epimedin A, epimedin B, epimedin C, and baohuoside I—significantly increased after intestinal digestion. During colon fermentation, these components gradually decreased but remained incompletely metabolized after 72 h. Faecal samples after E. sagittatum fermentation exhibited shift towards dominance by Lactobacillus (Firmicutes), Bifidobacterium (Actinobacteria), Streptococcus (Firmicutes), and Dialister (Firmicutes). These findings enhance our comprehension of diverse stages of Herba Epimedii constituents in the gut, suggesting that the primary constituents become bioaccessible in the colon, where new bioactive compounds may emerge.

Soil metabolomics - current challenges and future perspectives

Soil is an extremely complex and dynamic matrix, in part, due to the wide diversity of organisms living within it. Soil organic matter (SOM) is the fundamental substrate on which the delivery of ecosystem services depends, providing the metabolic fuel to drive soil function. As such, studying the soil metabolome (the diversity and concentration of low molecular weight metabolites), as a subset of SOM, holds the potential to greatly expand our understanding of the behaviour, fate, interaction and functional significance of small organic molecules in soil. Encompassing a wide range of chemical classes (including amino acids, peptides, lipids and carbohydrates) and a large number of individual molecules (ca. n = 105 to 106), the metabolome is a resultant (indirect) output of several layers of a biological hierarchy, namely the metagenome, metatranscriptome and metaproteome. As such, it may also provide support and validation for these “multi-omics” datasets. We present a case for the increased use of untargeted metabolomics in soil biochemistry, particularly for furthering our fundamental understanding of the functions driving SOM composition and biogeochemical cycling. Further, we discuss the scale of the challenge in terms of metabolite extraction, analysis and interpretation in complex plant-soil-microbial systems. Lastly, we highlight key knowledge gaps which currently limit our use of metabolomic approaches to better understand soil processes, including: (i) interpretation of large untargeted metabolomic datasets; (ii) the source, emission and fate of soil-derived volatile organic compounds (VOCs), (iii) assessing temporal fluxes of metabolites, and (iv) monitoring ecological interactions in the rhizosphere. While the application of metabolomics in ecosystem science is still in its relative infancy, its importance in understanding the biochemical system in relation to regulation, management and underpinning the delivery of ecosystem services is key to further elucidating the complex links between organisms, as well as the fundamental ability of the biological community to process and cycle key nutrients.

Metabolic profiling of bacteria with the application of polypyrrole-MOF SPME fibers and plasmonic nanostructured LDI-MS substrates

Here we present application of innovative lab-made analytical devices such as plasmonic silver nanostructured substrates and polypyrrole-MOF solid-phase microextraction fibers for metabolic profiling of bacteria. For the first time, comprehensive metabolic profiling of both volatile and non-volatile low-molecular weight compounds in eight bacterial strains was carried out with utilization of lab-made devices. Profiles of low molecular weight metabolites were analyzed for similarities and differences using principal component analysis, hierarchical cluster analysis and random forest algorithm. The results showed clear differentiation between Gram positive (G+) and Gram negative (G−) species which were identified as distinct clusters according to their volatile metabolites. In case of non-volatile metabolites, differentiation between G+ and G− species and clustering for all eight species were observed for the chloroform fraction of the Bligh & Dyer extract, while methanolic fraction failed to recover specific ions in the profile. Furthermore, the results showed correlation between volatile and non-volatile metabolites, which suggests that lab-made devices presented in the current study might be complementary and therefore, useful for species differentiation and gaining insights into bacterial metabolic pathways.

Simultaneous determination of multiple urine biomarkers for kidney injury using SPE combined with LC-MS/MS

Background and ObjectivesUrinary biomarkers such as low molecular weight proteins and small molecular weight metabolites are crucial in the diagnosis of kidney injury. The objective of this study was to develop and preliminarily validate a sensitive and specific method using solid-phase extraction (SPE) in conjunction with liquid chromatography–tandem mass spectrometry (LC-MS/MS) for the simultaneous measurement of these biomarkers in human urine. MethodThis study presents the development of a solid-phase extraction method integrated with LC-MS/MS analyzing biomarkers including creatinine, urea, β2-microglobulin, α1-microglobulin, and cystatin C in human urine. An enhanced solid-phase cartridge technique was employed for peptide purification and dilution of small molecule metabolites during sample preparation. ResultsThe developed LC-MS/MS method achieved satisfactory separation of the five analytes within 15 min. Accuracy levels ranged from −8.6% to 13.6%. Both intra-assay and inter-assay imprecision rates were maintained below 7.9% for all analytes. ConclusionsThe established LC-MS/MS method effectively quantifies creatinine, urea, β2-microglobulin, α1-microglobulin and cystatin C concurrently. This offers a viable alternative for the detection of kidney injury biomarkers in human urine, demonstrating potential for clinical application in kidney injury diagnosis.

Advancing athletic assessment by integrating conventional methods with cutting-edge biomedical technologies for comprehensive performance, wellness, and longevity insights.

In modern athlete assessment, the integration of conventional biochemical and ergophysiologic monitoring with innovative methods like telomere analysis, genotyping/phenotypic profiling, and metabolomics has the potential to offer a comprehensive understanding of athletes' performance and potential longevity. Telomeres provide insights into cellular functioning, aging, and adaptation and elucidate the effects of training on cellular health. Genotype/phenotype analysis explores genetic variations associated with athletic performance, injury predisposition, and recovery needs, enabling personalization of training plans and interventions. Metabolomics especially focusing on low-molecular weight metabolites, reveal metabolic pathways and responses to exercise. Biochemical tests assess key biomarkers related to energy metabolism, inflammation, and recovery. Essential elements depict the micronutrient status of the individual, which is critical for optimal performance. Echocardiography provides detailed monitoring of cardiac structure and function, while burnout testing evaluates psychological stress, fatigue, and readiness for optimal performance. By integrating this scientific testing battery, a multidimensional understanding of athlete health status can be achieved, leading to personalized interventions in training, nutrition, supplementation, injury prevention, and mental wellness support. This scientifically rigorous approach hereby presented holds significant potential for improving athletic performance and longevity through evidence-based, individualized interventions, contributing to advances in the field of sports performance optimization.

Metabolome analysis reveals that cyclic adenosine diphosphate ribose contributes to the regulation of differentiation in mice adipocyte.

Adipocytes play a key role in energy storage and homeostasis. Although the role of transcription factors in adipocyte differentiation is known, the effect of endogenous metabolites of low molecular weight remains unclear. Here, we analyzed time-dependent changes in the levels of these metabolites throughout adipocyte differentiation, using metabolome analysis, and demonstrated that there is a positive correlation between cyclic adenosine diphosphate ribose (cADPR) and Pparγ mRNA expression used as a marker of differentiation. We also found that the treatment of C3H10T1/2 adipocytes with cADPR increased the mRNA expression of those marker genes and the accumulation of triglycerides. Furthermore, inhibition of ryanodine receptors (RyR), which are activated by cADPR, caused a significant reduction in mRNA expression levels of the marker genes and triglyceride accumulation in adipocytes. Our findings show that cADPR accelerates adipocytic differentiation via RyR pathway.

Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples

The collision cross-sections (CCS) measurement using ion mobility spectrometry (IMS) in combination with mass spectrometry (MS) offers a great opportunity to increase confidence in metabolite identification. However, owing to the lack of sensitivity and resolution, IMS has an analytical challenge in studying the CCS values of very low-molecular-weight metabolites (VLMs ≤ 250 Da). Here, we describe an analytical method using ultrahigh-performance liquid chromatography coupled to a traveling wave ion mobility-quadrupole-time-of-flight mass spectrometer optimized for the measurement of VLMs in human urine samples. The experimental CCS values, along with mass spectral properties were reported for the 174 metabolites. The experimental data included the mass-to-charge ratio (m/z), retention time (RT), tandem MS (MS/MS) spectra, and CCS values. Among the studied metabolites, 263 traveling wave ion mobility spectrometry (TWIMS)-derived CCS values (TWCCSN2) were reported for the first time, and more than 70% of these were CCS values of VLMs. The TWCCSN2 values were highly repeatable, with inter-day variations of < 1% RSD. The developed method revealed excellent TWCCSN2 accuracy with a CCS difference (ΔCCS) within ±2% of the reported drift tube IMS (DTIMS) and TWIMS CCS values. The complexity of the urine matrix did not affect the precision of the method, as evidenced by ΔCCS within ±1.92%. According to the Metabolomics Standards Initiative, 55 urinary metabolites were identified with a confidence level of 1. Among these 55 metabolites, 53 (96%) were VLMs. The larger number of confirmed compounds found in this study was a result of the addition of TWCCSN2 values, which clearly increased metabolite identification confidence.

The Kelch/Nrf2 Antioxidant System as a Target for Some Marine Fungal Metabolites

Marine fungal metabolites often exhibit antioxidant activity, but their effects on the Keap1/Nrf2 cellular system are rarely studied, possibly due to insufficient isolated amounts. In this work, we used a bioinformatics approach to evaluate the ability of some promising cytoprotective compounds to bind Kelch domain of Keap1 protein, and thus inhibit its interaction with Nrf2. The molecular docking data suggested that gliorosein, niveoglaucin A, 6-hydroxy-N-acetyl-β-oxotryptamine, 4-hydroxyscytalone and 4-hydroxy-6-dehydroxyscytalone can form the hydrogen building with Arg415 or Arg483 amino acid residues of P1-P2 sub-pockets in the Nrf2 binding site of Keap1′s Kelch domain. These positions of the small molecules in the Kelch domain of Keap1 can inhibit the interaction of Keap1 with Nrf2 and enhance the nuclear translocation of Nrf2 from cytosol that can result in overexpression of relative genes. This assumption, based on virtual screening of a number of low molecular weight metabolites of marine fungi, makes them promising for further studies.

A-216 Measuring Inflammation and Cardiovascular Markers at Benchtop NMR using Diffusion and Relaxation Edited Experiments

Abstract Background Metabolic phenotyping is an established tool in systems medicine that captures a profile of one’s individual health status and reflects the interaction between genes and external stressors. It uses analytical platforms such as NMR or MS to acquire molecular profiles, and modelling to extract actionable knowledge. Applying these techniques to a cohort of Australians infected by SARS-CoV-2 revealed a strong alteration in regions of 1D NMR spectra associated with lipoproteins and glycoproteins, and referred as Supramolecular Phospholipid Composite SPC (δ = 3.2 ppm) and Glyc (δ = 2.07 ppm). The latter is an established marker of inflammation. These results were later confirmed using larger cohorts from Spain (n = 525) and the UK (n = 1022). The urgent need for very rapid testing, at the early stage of the pandemic, prompted the development of bespoke NMR experiments able to measure this lipoproteins/glycoproteins signature without requiring complex modelling. Methods Physico-chemical properties of lipoprotein particles, such as diffusion, transverse and longitudinal relaxation rates, differ from low molecular weight metabolites. Therefore, an edited experiment JEDI (PGPE) was designed that combines diffusion, relaxation and scalar coupling editing blocks to produce a lipoprotein profile devoid of chemical noise (overlapping peaks) and where peaks give quantitative results. Results The SPC peak was further broken down into 3 sub-regions that are related to the main subfraction HDL and LDL (choline headgroups of phospholipids). Interestingly the ratio of SPC3/SPC2 highly correlates with the Apo-B100/Apo-A1 ratio, an established cardiovascular risk marker that is increased in patients with COVID19. Longitudinal data suggest this latter remains elevated even 30 days after onset in some patients. Furthermore, the edited experiment performs equally well at low field using a benchtop NMR. Conclusion Translation of a spectral signature relevant for monitoring COVID patients from high to low field NMR is possible using sophisticated editing techniques.

Serum branch-chained amino acids are increased in type 2 diabetes and associated with atherosclerotic cardiovascular disease

Background and aimCirculating biomarkers of metabolic and cardiovascular diseases can help in the early detection and prevention of those diseases. Using proton nuclear magnetic resonance (1H-NMR), we aimed to study the plasma levels of low-molecular-weight metabolites (LMWMs) in a cohort of 307 patients with metabolic diseases to assess their relationships with type-2 diabetes (T2D) and incident atherosclerotic cardiovascular disease (ASCVD).MethodsWe conducted a cross-sectional and prospective study. We included 307 patients attending the Lipid Unit of our University Hospital for the treatment of the following metabolic disturbances and associated disorders: T2D (73.9%), obesity (58.7%), and hypertension (55.1%). 1H-NMR was used to study the plasma levels of 13 LMWMs. LMWM serum concentrations were evaluated in patients with and without T2D. and the correlations with several parameters and their associations with T2D were analyzed. The association between LMWM levels at baseline and the development of ASCVD in patients with T2D after 10 years of follow-up was also evaluated.ResultsAmong the LMWMs measured, the branched-chain amino acids (BCAAs) valine, leucine and isoleucine showed a positive association with several clinical and lipid-related biochemical parameters and inflammatory markers (p < 0.05). Likewise, these three BCAAS were associated with diabetes even after adjusting for covariates (p < 0.05). During the follow-up period of 10 years, 29 of the 185 patients with diabetes at baseline (15.68%) developed ASCVD. After adjusting for clinical covariates, baseline levels of valine and alanine were associated with the development of ASCVD (p < 0.05).ConclusionOverall, our results indicated that plasma levels of LMWMs measured by 1H-NMR could be potential biomarkers associated with T2D. Moreover, alanine and valine can help in the early detection of the cardiovascular risk associated with this metabolic disease.

Associations of phthalates, phthalate replacements, and their mixtures with eicosanoid biomarkers during pregnancy

Humans are exposed to complex mixtures of phthalates. Gestational exposure to phthalates has been linked to preeclampsia and preterm birth through potential pathways such as endocrine disruption, oxidative stress, and inflammation. Eicosanoids are bioactive signaling lipids that are related to a variety of homeostatic and inflammatory processes. We investigated associations between urinary phthalates and their mixtures with plasma eicosanoid levels during pregnancy using the PROTECT cohort in Puerto Rico (N = 655). After adjusting for covariates, we estimated pair-wise associations between the geometric mean of individual phthalate metabolite concentrations across pregnancy and eicosanoid biomarkers using multivariable linear regression. We used bootstrapping of adaptive elastic net regression (adENET) to evaluate phthalate mixtures associated with eicosanoids and subsequently create environmental risk scores (ERS) to represent weighted sums of phthalate exposure for each individual. After adjusting for false-discovery, in single-pollutant analysis, 14 of 20 phthalate metabolites or parent compound indices showed significant and primarily negative associations with multiple eicosanoids. In our mixture analysis, associations with several metabolites of low molecular weight phthalates – DEP, DBP, and DIBP – became prominent. Additionally, MEHHTP and MECPTP, metabolites of a new phthalate replacement, DEHTP, were selected as important predictors for determining the concentrations of multiple eicosanoids from different pathway groups. A unit increase in phthalate ERS derived from bootstrapping of adENET was positively associated with several eicosanoids mainly from Cytochrome P450 pathway. For example, an increase in ERS was associated with 11(S)-HETE (β = 1.6, 95% CI: 0.020, 3.180), (±)11,12-DHET (β = 2.045, 95% CI: 0.250, 3.840), 20(S)-HETE (β = 0.813, 95% CI: 0.147, 1.479), and 9 s-HODE (β = 2.381, 95% CI: 0.657, 4.104). Gestational exposure to phthalates and phthalate mixtures were associated with eicosanoid levels during pregnancy. Results from the mixture analyses underscore the complexity of physiological impacts of phthalate exposure and call for further in-depth studies to examine these relationships.

Metabolomics investigation of post-mortem human pericardial fluid

IntroductionDue to its peculiar anatomy and physiology, the pericardial fluid is a biological matrix of particular interest in the forensic field. Despite this, the available literature has mainly focused on post-mortem biochemistry and forensic toxicology, while to the best of authors’ knowledge post-mortem metabolomics has never been applied. Similarly, estimation of the time since death or post-mortem interval based on pericardial fluids has still rarely been attempted.ObjectivesWe applied a metabolomic approach based on 1H nuclear magnetic resonance spectroscopy to ascertain the feasibility of monitoring post-mortem metabolite changes on human pericardial fluids with the aim of building a multivariate regression model for post-mortem interval estimation.MethodsPericardial fluid samples were collected in 24 consecutive judicial autopsies, in a time frame ranging from 16 to 170 h after death. The only exclusion criterion was the quantitative and/or qualitative alteration of the sample. Two different extraction protocols were applied for low molecular weight metabolites selection, namely ultrafiltration and liquid-liquid extraction. Our metabolomic approach was based on the use of 1H nuclear magnetic resonance and multivariate statistical data analysis.ResultsThe pericardial fluid samples treated with the two experimental protocols did not show significant differences in the distribution of the metabolites detected. A post-mortem interval estimation model based on 18 pericardial fluid samples was validated with an independent set of 6 samples, giving a prediction error of 33–34 h depending on the experimental protocol used. By narrowing the window to post-mortem intervals below 100 h, the prediction power of the model was significantly improved with an error of 13–15 h depending on the extraction protocol. Choline, glycine, ethanolamine, and hypoxanthine were the most relevant metabolites in the prediction model.ConclusionThe present study, although preliminary, shows that PF samples collected from a real forensic scenario represent a biofluid of interest for post-mortem metabolomics, with particular regard to the estimation of the time since death.

Regulation of Gene Expression by the MYC Transcription Factor Network during Exercise

The results obtained in recent years on numerous functions of the MYC protein convincingly indicate that MYC overexpression induced by physical activity occurs at the transcriptional and epigenetic levels with the participation of low molecular weight metabolites formed during the enhancement of intermediate metabolism. The current hypothesis proposes that MYC network of transcription factors may account substantially for the exercise-induced adaptive changes in muscle and other vital organs through changes in lactate dynamics. This review presents the MYC transcription factor network that is involved in cell cycle regulation, growth, proliferation, and cell metabolism.

Metabolic Adjustment of High Intertidal Alga Pelvetia canaliculata to the Tidal Cycle Includes Oscillations of Soluble Carbohydrates, Phlorotannins, and Citric Acid Content.

The brown alga Pelvetia canaliculata is one of the species successfully adapted to intertidal conditions. Inhabiting the high intertidal zone, Pelvetia spends most of its life exposed to air, where it is subjected to desiccation, light, and temperature stresses. However, the physiological and biochemical mechanisms allowing this alga to tolerate such extreme conditions are still largely unknown. The objective of our study is to compare the biochemical composition of Pelvetia during the different phases of the tidal cycle. To our knowledge, this study is the first attempt to draft a detailed biochemical network underneath the complex physiological processes, conferring the successful survival of this organism in the harsh conditions of the high intertidal zone of the polar seas. We considered the tide-induced changes in relative water content, stress markers, titratable acidity, pigment, and phlorotannin content, as well as the low molecular weight metabolite profiles (GC-MS-based approach) in Pelvetia thalli. Thallus desiccation was not accompanied by considerable increase in reactive oxygen species content. Metabolic adjustment of P. canaliculata to emersion included accumulation of soluble carbohydrates, various phenolic compounds, including intracellular phlorotannins, and fatty acids. Changes in titratable acidity accompanied by the oscillations of citric acid content imply that some processes related to the crassulacean acid metabolism (CAM) may be involved in Pelvetia adaptation to the tidal cycle.

NMR-based metabolomic profiling identifies inflammation and muscle-related metabolites as predictors of incident type 2 diabetes mellitus beyond glucose: The Di@bet.es study

AimsThe aim of this study was to combine nuclear magnetic resonance-based metabolomics and machine learning to find a glucose-independent molecular signature associated with future type 2 diabetes mellitus development in a subgroup of individuals from the Di@bet.es study. MethodsThe study group included 145 individuals developing type 2 diabetes mellitus during the 8-year follow-up, 145 individuals matched by age, sex and BMI who did not develop diabetes during the follow-up but had equal glucose concentrations to those who did and 145 controls matched by age and sex. A metabolomic analysis of serum was performed to obtain the lipoprotein and glycoprotein profiles and 15 low molecular weight metabolites. Several machine learning-based models were trained. ResultsLogistic regression performed the best classification between individuals developing type 2 diabetes during the follow-up and glucose-matched individuals. The area under the curve was 0.628, and its 95% confidence interval was 0.510–0.746. Glycoprotein-related variables, creatinine, creatine, small HDL particles and the Johnson-Neyman intervals of the interaction of Glyc A and Glyc B were statistically significant. ConclusionsThe model highlighted a relevant contribution of inflammation (glycosylation pattern and HDL) and muscle (creatinine and creatine) in the development of type 2 diabetes as independent factors of hyperglycemia.

Cardiometabolic disease risk markers are increased following burn injury in children.

Burn injury in children causes prolonged systemic effects on physiology and metabolism leading to increased morbidity and mortality, yet much remains undefined regarding the metabolic trajectory towards specific health outcomes. A multi-platform strategy was implemented to evaluate the long-term immuno-metabolic consequences of burn injury combining metabolite, lipoprotein, and cytokine panels. Plasma samples from 36 children aged 4-8 years were collected 3 years after a burn injury together with 21 samples from non-injured age and sex matched controls. Three different 1H Nuclear Magnetic Resonance spectroscopic experiments were applied to capture information on plasma low molecular weight metabolites, lipoproteins, and α-1-acid glycoprotein. Burn injury was characterized by underlying signatures of hyperglycaemia, hypermetabolism and inflammation, suggesting disruption of multiple pathways relating to glycolysis, tricarboxylic acid cycle, amino acid metabolism and the urea cycle. In addition, very low-density lipoprotein sub-components were significantly reduced in participants with burn injury whereas small-dense low density lipoprotein particles were significantly elevated in the burn injured patient plasma compared to uninjured controls, potentially indicative of modified cardiometabolic risk after a burn. Weighted-node Metabolite Correlation Network Analysis was restricted to the significantly differential features (q <0.05) between the children with and without burn injury and demonstrated a striking disparity in the number of statistical correlations between cytokines, lipoproteins, and small molecular metabolites in the injured groups, with increased correlations between these groups. These findings suggest a 'metabolic memory' of burn defined by a signature of interlinked and perturbed immune and metabolic function. Burn injury is associated with a series of adverse metabolic changes that persist chronically and are independent of burn severity and this study demonstrates increased risk of cardiovascular disease in the long-term. These findings highlight a crucial need for improved longer term monitoring of cardiometabolic health in a vulnerable population of children that have undergone burn injury.

Chemical Composition and Antimicrobial Properties of Honey Bee Venom.

Due to its great medical and pharmaceutical importance, honey bee venom is considered to be well characterized both chemically and in terms of biomedical activity. However, this study shows that our knowledge of the composition and antimicrobial properties of Apis mellifera venom is incomplete. In this work, the composition of volatile and extractive components of dry and fresh bee venom (BV) was determined by GC-MS, as well as antimicrobial activity against seven types of pathogenic microorganisms. One-hundred and forty-nine organic C1-C19 compounds of different classes were found in the volatile secretions of the studied BV samples. One-hundred and fifty-two organic C2-C36 compounds were registered in ether extracts, and 201 compounds were identified in methanol extracts. More than half of these compounds are new to BV. In microbiological tests involving four species of pathogenic Gram-positive and two species of Gram-negative bacteria, as well as one species of pathogenic fungi, the values of the minimum inhibitory concentration (MIC) and minimum bactericidal/fungicidal concentration (MBC/MFC) were determined for samples of dry BV, as well as ether and methanol extracts from it. Gram-positive bacteria show the greatest sensitivity to the action of all tested drugs. The minimum MIC values for Gram-positive bacteria in the range of 0.12-7.63 ng mL-1 were recorded for whole BV, while for the methanol extract they were 0.49-125 ng mL-1. The ether extracts had a weaker effect on the tested bacteria (MIC values 31.25-500 ng mL-1). Interestingly, Escherichia coli was more sensitive (MIC 7.63-500 ng mL-1) to the action of bee venom compared to Pseudomonas aeruginosa (MIC ≥ 500 ng mL-1). The results of the tests carried out indicate that the antimicrobial effect of BV is associated with the presence of not only peptides, such as melittin, but also low molecular weight metabolites.

Characterization of the Key Compounds of Bell Pepper by Spectrophotometry and Gas Chromatography on the Effects of Induced Stress on the Concentration of Secondary Metabolite.

Sweet peppers are consumed worldwide, and traditional uses have sparked interest in their applications as dietary antioxidants, which can be enhanced in plants using elicitors. These are endowed with phytochemicals with potential health benefits such as antioxidants, bioavailability, and bioaccessibility. The trend in metabolomics shows us chemical fingerprints linking metabolomics, innovative analytical form, and bioinformatics tools. The objective was to evaluate the impact of multiple stress interactions, elicitor concentrations, and electrical conductivity on the concentration of secondary metabolites to relate their response to metabolic pathways through the foliar application of a cocktail of said elicitors in pepper crops under greenhouse conditions. The extracts were analyzed by spectrophotometry and gas chromatography, and it was shown that the PCA analysis identified phenolic compounds and low molecular weight metabolites, confirming this as a metabolomic fingerprint in the hierarchical analysis. These compounds were also integrated by simultaneous gene and metabolite simulants to obtain effect information on different metabolic pathways. Showing changes in metabolite levels at T6 (36 mM H2O2 and 3.6 dS/m) and T7 (0.1 mM SA and 3.6 dS/m) but showing statistically significant changes at T5 (3.6 dS/m) and T8 (0.1 mM SA, 36 mM H2O2, and 3.6 dS/m) compared to T1 (32 dS/m) or control. Six pathways changed significantly (p < 0.05) in stress-induced treatments: aminoacyl t-RNA and valine-leucine-isoleucine biosynthesis, and alanine-aspartate-glutamate metabolism, glycoxylate-dicarboxylate cycle, arginine-proline, and citrate. This research provided a complete profile for the characterization of metabolomic fingerprint of bell pepper under multiple stress conditions.