RESUMEN

INTRODUCTION: With an increasing interest in healthy and affordable cereal intake, efforts are made toward exploiting underutilized cereals with high nutritional values. OBJECTIVES: The current study aims to explore the metabolome diversity in 14 cultivars of chia and quinoa collected from Germany, Austria, and Egypt, compared with wheat and oat as major cereals. MATERIAL AND METHODS: The samples were analyzed using gas chromatography-mass spectrometry (GC-MS). Multivariate data analysis (MVA) was employed for sample classification and markers characterization. RESULTS: A total of 114 metabolites were quantified (sugars, alcohols, organic and amino acids/nitrogenous compounds, fatty acids/esters), but the inorganic and phenolic acids were only identified. Fatty acids were the major class followed by amino acids in quinoa and chia. Chia and oats were richer in sucrose. Quinoa encompassed higher amino acids. Quinoa and chia were rich in essential amino acids. Higher levels of unsaturated fatty acids especially omega 6 and omega 9 were detected in quinoa versus omega 3 in chia compared with oat and wheat, whereas ω6/ω3 fatty acid ratio of chia was the lowest. To the best of our knowledge, this is the first comprehensive metabolite profiling of these pseudo cereals. CONCLUSION: Quinoa and chia, especially red chia, are more nutritionally valuable compared with oat and wheat because of their compositional profile of free amino acids, organic acids, and essential fatty acids, besides their low ω6/ω3 fatty acid ratio. Such results pose them as inexpensive alternative to animal proteins and encourage their inclusion in infant formulas.

RESUMEN

Background: Cachexia is a body wasting syndrome that significantly affects well-being and prognosis of cancer patients, without effective treatment. Serum metabolites take part in pathophysiological processes of cancer cachexia, but apart from altered levels of select serum metabolites, little is known on the global changes of the overall serum metabolome, which represents a functional readout of the whole-body metabolic state. Here, we aimed to comprehensively characterize serum metabolite alterations and analyze associated pathways in cachectic cancer patients to gain new insights that could help instruct strategies for novel interventions of greater clinical benefit. Methods: Serum was sampled from 120 metastatic cancer patients (stage UICC IV). Patients were grouped as cachectic or non-cachectic according to the criteria for cancer cachexia agreed upon international consensus (main criterium: weight loss adjusted to body mass index). Samples were pooled by cachexia phenotype and assayed using non-targeted gas chromatography-mass spectrometry (GC-MS). Normalized metabolite levels were compared using t-test (p < 0.05, adjusted for false discovery rate) and partial least squares discriminant analysis (PLS-DA). Machine-learning models were applied to identify metabolite signatures for separating cachexia states. Significant metabolites underwent MetaboAnalyst 5.0 pathway analysis. Results: Comparative analyses included 78 cachectic and 42 non-cachectic patients. Cachectic patients exhibited 19 annotable, significantly elevated (including glucose and fructose) or decreased (mostly amino acids) metabolites associating with aminoacyl-tRNA, glutathione and amino acid metabolism pathways. PLS-DA showed distinct clusters (accuracy: 85.6%), and machine-learning models identified metabolic signatures for separating cachectic states (accuracy: 83.2%; area under ROC: 88.0%). We newly identified altered blood levels of erythronic acid and glucuronic acid in human cancer cachexia, potentially linked to pentose-phosphate and detoxification pathways. Conclusion: We found both known and yet unknown serum metabolite and metabolic pathway alterations in cachectic cancer patients that collectively support a whole-body metabolic state with impaired detoxification capability, altered glucose and fructose metabolism, and substrate supply for increased and/or distinct metabolic needs of cachexia-associated tumors. These findings together imply vulnerabilities, dependencies and targets for novel interventions that have potential to make a significant impact on future research in an important field of cancer patient care.

RESUMEN

Studies have demonstrated avocado seeds are a good source of bioactive compounds. This study investigated the effects of roasting on the metabolites and anticancer activities of fermented avocado seeds. All three anti-cancer activities of fermented avocado seeds were higher at lower roasting temperature and time. The best inhibition effect was found against Hep G2 followed by the MDA-MB-231 and MCF-7 cancer cell lines. Untargeted metabolite profiling using gas chromatography-mass spectrometry resulted in identification of 208 metabolites. In total, 41 metabolites identified had VIP values more than 1 using PLS-R that were related to anticancer activities. All amino acids and most sugars were higher at lower roasting temperature and positively correlated to anticancer activity. The roasting conditions for optimal antioxidant and anticancer activities were determined to be 121 °C for 9 min. Findings showed that fermented avocado seed powder has the potential to become a functional food ingredient with beneficial bioctive properties.

Asunto(s)

RESUMEN

Kale is a group of diverse Brassicaceae species that are nutritious leafy greens consumed for their abundance of vitamins and micronutrients. Typified by their curly, serrated and/or wavy leaves, kale varieties have been primarily defined based on their leaf morphology and geographic origin, despite having complex genetic backgrounds. Kale is a very promising crop for vertical farming due to its high nutritional content; however, being a non-model organism, foundational, systems-level analyses of kale are lacking. Previous studies in kale have shown that time-of-day harvesting can affect its nutritional composition. Therefore, to gain a systems-level diel understanding of kale across its wide-ranging and diverse genetic landscape, we selected nine publicly available and commercially grown kale cultivars for growth under near-sunlight LED light conditions ideal for vertical farming. We then analyzed changes in morphology, growth and nutrition using a combination of plant phenotyping, proteomics and metabolomics. As the diel molecular activities of plants drive their daily growth and development, ultimately determining their productivity as a crop, we harvested kale leaf tissue at both end-of-day (ED) and end-of-night (EN) time-points for all molecular analyses. Our results reveal that diel proteome and metabolome signatures divide the selected kale cultivars into two groups defined by their amino acid and sugar content, along with significant proteome differences involving carbon and nitrogen metabolism, mRNA splicing, protein translation and light harvesting. Together, our multi-cultivar, multi-omic analysis provides new insights into the molecular underpinnings of the diel growth and development landscape of kale, advancing our fundamental understanding of this nutritious leafy green super-food for horticulture/vertical farming applications.

RESUMEN

INTRODUCTION: Combretum platypetalum is used in traditional African healing practices against different infections. Unfortunately, no scientific knowledge of its phytochemical composition exists, except for the isolation of two compounds from the leaves. Scientific study has been limited to the leaves only, despite the applications of stems and roots in traditional medicine practice and natural product drug discovery programs. OBJECTIVE: Omics was applied to identify and classify different volatile and semivolatile bioactive compounds in the leaf, stem, and root parts of C. platypetalum. The thermal stability of the plant constituents at 60-65°C extraction temperature by Soxhlet and maceration at room temperature on the type, class, and concentration of compounds in the leaf was further investigated. METHOD: A GC-MS untargeted metabolomics approach, automated deconvolution by the Automated Mass Spectral Deconvolution and Identification System (AMDIS) for GC-MS data, preprocessing by Metab R, and multivariate statistical data analysis were employed in this study. RESULTS: A total of 97 phytoconstituents, including 17 bioactive compounds belonging to the terpenoids, flavonoids, long-chain fatty acids, and other unclassified structural arrangements distributed across C. platypetalum, were identified for the first time. A correlation (r = 0.782; P = 0.000) between Soxhlet and maceration extraction methods relative to resolved chromatographic peak areas of metabolites was established. CONCLUSION: Findings corroborate the reported bio-investigation of its leaf extracts, its traditional uses, and previous findings from the Combretum genus. The results substantiate the possible applications of C. platypetalum in natural product drug discovery and provide a guide for future investigations.

Asunto(s)

RESUMEN

Laboratory investigations on terrestrial model-species, typically of temperate origin, have demonstrated that terrestrial ectotherms can cope with daily temperature variations through rapid hardening responses. However, few studies have investigated this ability and its physiological basis in the field. Especially in polar regions, where the temporal and spatial temperature variations can be extreme, are hardening responses expected to be important. Here, we examined diurnal adjustments in heat and cold tolerance in the Greenlandic seed bug Nysius groenlandicus by collecting individuals for thermal assessment at different time points within and across days. We found a significant correlation between observed heat or cold tolerance and the ambient microhabitat temperatures at the time of capture, indicating that N. groenlandicus continuously and within short time-windows respond physiologically to thermal changes and/or other environmental variables in their microhabitats. Secondly, we assessed underlying metabolomic fingerprints using GC-MS metabolomics in a subset of individuals collected during days with either low or high temperature variation. Concentrations of metabolites, including sugars, polyols, and free amino acids varied significantly with time of collection. For instance, we detected elevated sugar levels in animals caught at the lowest daily field temperatures. Polyol concentrations were lower in individuals collected in the morning and evening and higher at midday and afternoon, possibly reflecting changes in temperature. Additionally, changes in concentrations of metabolites associated with energetic metabolism were observed across collection times. Our findings suggest that in these extreme polar environments hardening responses are marked and likely play a crucial role for coping with microhabitat temperature variation on a daily scale, and that metabolite levels are actively altered on a daily basis.

RESUMEN

Transcriptomics and metabolomics data often contain missing values or outliers due to limitations of the data acquisition techniques. Most of the statistical methods require complete datasets for downstream analysis. A number of methods have been developed for missing value imputation using the classical mean and variance based on maximum likelihood estimators, which are not robust against outliers. Consequently, the performance of these methods deteriorates in the presence of outliers. Hence precise imputation of missing values and outliers handling are both concurrently important. Therefore, in this paper, we developed a robust iterative approach using robust estimators based on the minimum beta divergence method, which simultaneously impute missing values and outliers. We investigate the performance of the proposed method in a comparison with six frequently used missing value imputation methods such as Zero, KNN, robust SVD, EM, random forest (RF) and weighted least square approach (WLSA) through feature selection using both simulated and real datasets. Ten performance indices were used to explore the optimal method such as Frobenius norm (FOBN), accuracy (ACC), sensitivity (SN), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), detection rate (DR), misclassification error rate (MER), the area under the ROC curve (AUC) and computational runtime. Evaluation based on both simulated and real data suggests the superiority of the proposed method over the other traditional methods in terms of various rates of outliers and missing values. The suggested approach also keeps almost equal performance in absence of outliers with the other methods. The proposed method is accurate, simple, and consumes lower computational time compared to the other methods. Therefore, our recommendation is to apply the proposed procedure for large-scale transcriptomics and metabolomics data analysis. The computational tool has been implemented in an R package, which is publicly available from https://CRAN.R-project.org/package=rMisbeta.

Asunto(s)

RESUMEN

BACKGROUND: The New Zealand Green-lipped mussel industry is well-established providing vastly to aquaculture exports. To assess mussel health and reproduction status, visual examination of organs and/or collection of haemolymph is commonly applied. Anesthetics, such as magnesium chloride (MgCl2) can be utilized to prevent muscle contraction and keep shells open during sampling. The specific effects of muscle relaxing agents on baseline metabolism in invertebrates is unknown, but it is evident that molecular, cellular and physiological parameters are altered with these chemical applications. To this end, metabolomics approaches can help elucidate the effects of relaxing agents for better assessment of their use as a research tool. METHODS: Adult Green-lipped mussels were anaesthetized for 3 h in a MgCl2 bath, whereafter haemolymph samples were collected and analyzed via gas chromatography-mass spectrometry applying methyl chloroformate alkylation derivatization. RESULTS: Anesthetized mussels were characterized as non-responsive to manual manipulation, with open valves, and limited siphoning function. Metabolite profiling revealed significant increases in the abundances of most metabolites with an array of metabolic activities affected, resulting in an energy imbalance driven by anaerobic metabolism with altered amino acids acting as neurotransmitters and osmolytes. CONCLUSION: This research is the first to use a metabolomics approach to identify the metabolic consequences of this commonly used bivalve relaxing technique. Ultimately the use of MgCl2 anesthetization as a sampling strategy should be carefully evaluated and managed when performing metabolomics-related research.

Asunto(s)

RESUMEN

In clinical practice, differences in glucocorticoid sensitivity among healthy subjects may influence the outcome and any adverse effects of glucocorticoid therapy. Thus, a fast and accurate methodology that could enable the classification of individuals based on their tissue glucocorticoid sensitivity would be of value. We investigated the usefulness of untargeted plasma metabolomics in identifying a panel of metabolites to distinguish glucocorticoid-resistant from glucocorticoid-sensitive healthy subjects who do not carry mutations in the human glucocorticoid receptor (NR3C1) gene. Applying a published methodology designed for the study of glucocorticoid sensitivity in healthy adults, 101 healthy subjects were ranked according to their tissue glucocorticoid sensitivity based on 8:00 a.m. serum cortisol concentrations following a very low-dose dexamethasone suppression test. Ten percent of the cohort, i.e., 11 participants, on each side of the ranking, with no NR3C1 mutations or polymorphisms, were selected, respectively, as the most glucocorticoid-sensitive and most glucocorticoid-resistant of the cohort to be analyzed and compared with untargeted blood plasma metabolomics using gas chromatography-mass spectrometry (GC-MS). The acquired metabolic profiles were evaluated using multivariate statistical analysis methods. Nineteen metabolites were identified with significantly lower abundance in the most sensitive compared to the most resistant group of the cohort, including fatty acids, sugar alcohols, and serine/threonine metabolism intermediates. These results, combined with a higher glucose, sorbitol, and lactate abundance, suggest a higher Cori cycle, polyol pathway, and inter-tissue one-carbon metabolism rate and a lower fat mobilization rate at the fasting state in the most sensitive compared to the most resistant group. In fact, this was the first study correlating tissue glucocorticoid sensitivity with serine/threonine metabolism. Overall, the observed metabolic signature in this cohort implies a worse cardiometabolic profile in the most glucocorticoid-sensitive compared to the most glucocorticoid-resistant healthy subjects. These findings offer a metabolic signature that distinguishes most glucocorticoid-sensitive from most glucocorticoid-resistant healthy subjects to be further validated in larger cohorts. Moreover, they support the correlation of tissue glucocorticoid sensitivity with insulin resistance and metabolic syndrome-associated pathways, further emphasizing the need for nutritionists and doctors to consider the tissue glucocorticoid sensitivity in dietary and exercise planning, particularly when these subjects are to be treated with glucocorticoids.

Asunto(s)

RESUMEN

The macronutrient potassium (K) has vital physiological functions in plants and its availability can strongly impact quality of crops like tomato. The impact of K nutrition on conventional tomato fruit quality parameters has been described several times, but detailed investigations on the effect of K supply on the fruit metabolite profile are still rare. To fill this gap, we investigated the influence of K fertilization on the metabolite profile of tomato fruits. For this purpose, an outdoor pot experiment with three different cocktail tomato cultivars was performed. A fertilization regimen with five K levels was applied, ranging from deficiency to sufficient supply. Fruit samples were analyzed by untargeted GC×GC-MS to cover the primary metabolite profile as well as some secondary metabolites. As verified using ICP-OES, fruit K content was highly proportional to the supplied amount of K. At the metabolite profile level, the most prominent and cultivar-independent effect of increased K fertilization was the rise of tricarboxylic acid (TCA) cycle intermediates. Further effects were more cultivar-specific, for example an increase of the mobile nitrogen pool (e.g. amines like putrescine and amides like asparagine), changes in the profile of minor sugars (especially disaccharides) as well as higher levels of some secondary metabolites. Pronounced response patterns were mainly observed in the cultivars Primavera and Yellow Submarine that were recently characterized as higher yielding, demanding a stronger consideration of cultivar differences in future studies.

Asunto(s)

RESUMEN

The aim of this study was to demonstrate the altered metabolic infrastructure of pregnant women with methylenetetrahydrofolate reductase (MTHFR) polymorphisms at first trimester and during delivery. Eight singleton pregnant women with MTHFR polymorphisms were compared with 10 normal pregnant women. Maternal blood samples were obtained twice during their pregnancy period (between the 11th and 14th gestational weeks and during delivery). Metabolomic analysis was performed using GC-MS. The GC-MS based metabolomic profile helped identify 95 metabolites in the plasma samples. In the MTHFR group, the levels of 1-monohexadecanoylglycerol, pyrophosphate, benzoin, and linoleic acid significantly decreased (P ˂ 0.05 for all), whereas the levels of glyceric acid, l-tryptophan, l-alanine, l-proline, norvaline, l-threonine, and myo-inositol significantly increased (P ˂ 0.01 for the first two metabolites, P ˂ 0.05 for the others) at 11-14 gestational weeks. Conversely, the levels of benzoin, 1-monohexadecanoylglycerol, pyruvic acid, l-proline, phosphoric acid, epsilon-caprolactam, and pipecolic acid significantly decreased in the MTHFR group, whereas metabolites such as hexadecanoic acid and 2-hydroxybutyric acid increased significantly in the study group during delivery. An impaired energy metabolism pathway, vitamin B complex disorders, tendency for metabolic acidosis (oxidative stress), and the need for cell/tissue support seem prevalent in pregnancies with MTHFR polymorphisms.

Asunto(s)

RESUMEN

BACKGROUND: Cardiovascular adverse events (CV-AEs) are considered critical complications in chronic myeloid leukemia (CML) patients treated with second- and third-generation tyrosine kinase inhibitors (TKIs). The aim of our study was to assess the correlation between metabolic profiles and CV-AEs in CML patients treated with TKIs. METHODS: We investigated 39 adult CML patients in chronic-phase (mean age 49 years, range 24-70 years), with no comorbidities evidenced at baseline, who were consecutively identified with CML and treated with imatinib, nilotinib, dasatinib, and ponatinib. All patients performed Gas-Chromatography-Mass-Spectrometry-based metabolomic analysis and were divided into two groups (with and without CV-AEs). RESULTS: Ten CV-AEs were documented. Seven CV-AEs were rated as 3 according to the Common Toxicity Criteria, and one patient died of a dissecting aneurysm of the aorta. The patients' samples were clearly separated into two groups after analysis and the main discriminant metabolites were tyrosine, lysine, glutamic acid, ornithine, 2-piperdinecarboxylic acid, citric acid, proline, phenylalanine, threonine, mannitol, leucine, serine, creatine, alanine, and 4-hydroxyproline, which were more abundant in the CV-AE group. Conversely, myristic acid, oxalic acid, arabitol, 4-deoxy rithronic acid, ribose, and elaidic acid were less represented in the CV-AE group. CONCLUSIONS: CML patients with CV-AEs show a different metabolic profile, suggesting probable mechanisms of endothelial damage.

RESUMEN

Stone leaf (Tetracera scandens) is a Southeast Asian medicinal plant that has been traditionally used for the management of diabetes mellitus. The underlying mechanisms of the antidiabetic activity have not been fully explored yet. Hence, this study aimed to evaluate the α-glucosidase inhibitory potential of the hydromethanolic extracts of T. scandens leaves and to characterize the metabolites responsible for such activity through gas chromatography-mass spectrometry (GC-MS) metabolomics. Crude hydromethanolic extracts of different strengths were prepared and in vitro assayed for α-glucosidase inhibition. GC-MS analysis was further carried out and the mass spectral data were correlated to the corresponding α-glucosidase inhibitory IC50 values via an orthogonal partial least squares (OPLS) model. The 100%, 80%, 60% and 40% methanol extracts displayed potent α-glucosidase inhibitory potentials. Moreover, the established model identified 16 metabolites to be responsible for the α-glucosidase inhibitory activity of T. scandens. The putative α-glucosidase inhibitory metabolites showed moderate to high affinities (binding energies of -5.9 to -9.8 kcal/mol) upon docking into the active site of Saccharomyces cerevisiae isomaltase. To sum up, an OPLS model was developed as a rapid method to characterize the α-glucosidase inhibitory metabolites existing in the hydromethanolic extracts of T. scandens leaves based on GC-MS metabolite profiling.

Asunto(s)

RESUMEN

Curcuma zedoaria (dry stenophora of Curcuma phaeocaulis Val., Curcuma kwangsiensis S. G. Lee et C. F. Liang, or Curcuma wenyujin Y. H. Chen et C.Ling) is a representative herb with clinical effects on liver diseases after being vinegar-processed. The crude Curcuma zedoaria and the processed Curcuma zedoaria (vinegar-boil) have been widely used as mixtures, but their equivalence has not been fully investigated. In this manuscript, quality markers of processed (vinegar-boil) Curcuma zedoaria were investigated by comparison of the compounds and hepatoprotective activities with the crude (three spices) ones. First, GC-MS-based untargeted metabolomics were applied to reveal the discriminatory components and discover potential markers. As a result, a total of six components were identified as potential markers. Then, the hepatoprotective activities were evaluated by dual cell damage models induced by a certain concentration of H2O2 or tertbutyl hydfroperoxide (t-BHP) (55 µM H2O2 or 40 µM t-BHP), which highlighted the potential of the processed Curcuma zedoaria on oxidative stress. Finally, epicurzerenone was identified as its quality marker on oxidative liver injury based on the above results and the cell-based biological assay. Overall, vinegar-processed Curcuma zedoaria was more suitable for the treatment of oxidative liver diseases, and epicurzerenone could be considered as its quality marker.

Asunto(s)

RESUMEN

Impacts of pre-sampling practices on fish plasma biochemistry may bias the outcome of a study if not considered within the general sampling strategy. Acute handling stresses can be imposed on fish during capture, and it is common practice to immobilise fish via sedation prior to obtaining blood samples for non-lethal extraction purposes, and/or to reduce stress, pain, or suffering before being euthanised. We investigated these potential influences using a Chinook salmon model (Oncorhynchus tshawytscha) by measuring levels of 119 biochemical targets comprising ions, metabolites, and enzymes in plasma. Multivariate analyses showed that 2 min of confinement with mild handling manipulation led to a significant departure from baseline metabolism, which was further exasperated during a prolonged 5-min challenge. These changes were characterised by a disruption in osmoregulation, a switch towards anaerobic metabolism, and shifts in ammonia recycling, among others. Sedation of fish with clove oil and AQUI-S® had major impacts on plasma biochemical profiles, with alterations signalling changes in glycolytic metabolism, respiratory modes, carbon flux through the TCA cycle, and lipid compartmentalisation. Sedation also enhanced levels of plasma amino acids, revealing a key difference between responses to handling stress and sedation. These results demonstrate that pre-harvest practices should be carefully managed during fish sampling for biochemical/metabolomic-based analyses, and if manipulations are essential, they should be standardised.

Asunto(s)

RESUMEN

Ripening heterogeneity of Hass avocados results in inconsistent quality fruit delivered to the triggered and ready to eat markets. This research aimed to understand the effect of a heat shock (HS) prior to controlled atmosphere (CA) storage on the reduction of ripening heterogeneity. HS prior to CA storage reduces more drastically the ripening heterogeneity in middle season fruit. Via correlation network analysis we show the different metabolomics networks between HS and CA. High throughput proteomics revealed 135 differentially expressed proteins unique to middle season fruit triggered by HS. Further integration of metabolomics and proteomics data revealed that HS reduced the glycolytic throughput and induced protein degradation to deliver energy for the alternative ripening pathways. l-isoleucine, l-valine, l-aspartic and ubiquitin carboxyl-terminal hydrolase involved in protein degradation were positively correlated to HS samples. Our study provides new insights into the effectiveness of HS in synchronizing ripening of Hass avocados.

Asunto(s)

RESUMEN

INTRODUCTION: As an insulin sensitive tissue, the heart decreases glucose usage during fasting. This response is mediated, in part, by decreasing phosphofructokinase-2 (PFK-2) activity and levels of its product fructose-2,6-bisphosphate. However, the importance of fructose-2,6-bisphosphate in the fasting response on other metabolic pathways has not been evaluated. OBJECTIVES: The goal of this study is to determine how sustaining cardiac fructose-2,6-bisphosphate levels during fasting affects the metabolomic profile. METHODS: Control and transgenic mice expressing a constitutively active form of PFK-2 (GlycoHi) were subjected to either 12-h fasting or regular feeding. Animals (n = 4 per group) were used for whole-heart extraction, followed by gas chromatography-mass spectrometry metabolic profiling and multivariate data analysis. RESULTS: Principal component analysis displayed differences between Control and GlycoHi groups under both fasting and fed conditions while a clear response to fasting was observed only for Control animals. However, pathway analysis revealed that these smaller changes in the GlycoHi group were significantly associated with branched-chain amino acid (BCAA) metabolism (~ 40% increase in all BCAAs). Correlation network analysis demonstrated clear differences in response to fasting between Control and GlycoHi groups amongst most parameters. Notably, fasting caused an increase in network density in the Control group from 0.12 to 0.14 while the GlycoHi group responded oppositely (0.17-0.15). CONCLUSIONS: Elevated cardiac PFK-2 activity during fasting selectively increases BCAAs levels and decreases global changes in metabolism.

Asunto(s)

RESUMEN

To evaluate the taste of ordinary muscle from white-fleshed fish, we used GC-MS metabolomic analysis to characterise the compounds therein, and correlated the obtained data with taste measurements from an electronic tongue. Prediction models using orthogonal partial least squares were produced for different taste attributes, and the primary metabolic components correlated with the taste attributes were identified. Clear differences were observed in the component profiles for different fish species. Using an electronic tongue, differences in tastes were noted among the fish species in terms of sourness, acidic bitterness, umami and saltiness. The obtained correlations allowed the construction of good taste prediction models, especially for sourness, acidic bitterness and saltiness. Compounds such as phosphoric acid, lactic acid and creatinine were found to be highly correlated with some taste attributes. Phosphoric acid in particular showed the highest variable important for prediction (VIP) scores in many of the taste prediction models, and it is therefore a candidate marker to evaluate the tastes of white-fleshed fish.

RESUMEN

Untargeted metabolomics refers to the high-throughput analysis of the metabolic state of a biological system (e.g., tissue, biological fluid, cell culture) based on the concentration profile of all measurable free low molecular weight metabolites. Gas chromatography-mass spectrometry (GC-MS), being a highly sensitive and high-throughput analytical platform, has been proven a useful tool for untargeted studies of primary metabolism in a variety of applications. As an omic analysis, GC-MS metabolomics is a multistep procedure; thus, standardization of an untargeted GC-MS metabolomics protocol requires the integrated optimization of pre-analytical, analytical, and computational steps. The main difference of GC-MS metabolomics compared to other metabolomics analytical platforms, including liquid chromatography-MS, is the need for the derivatization of the metabolite extracts into volatile and thermally stable derivatives, the latter being quantified in the metabolic profiles. This analytical step requires special care in the optimization of the untargeted GC-MS metabolomics experimental protocol. Moreover, both the derivatization of the original sample and the compound fragmentation that takes place in GC-MS impose specialized GC-MS metabolomic data identification, quantification, normalization and filtering methods. In this chapter, we describe the integrated protocol of untargeted GC-MS metabolomics with both the analytical and computational steps, focusing on the GC-MS specific parts, and provide details on any sample depending differences.

Asunto(s)

RESUMEN

Agarwood, the resinous heartwood produced by some Aquilaria species such as Aquilaria crassna, Aquilaria malaccensis and Aquilaria sinensis, has been traditionally and widely used in medicine, incenses and especially perfumes. However, up to now, the authentication of agarwood has been largely based on morphological characteristics, a method which is prone to errors and lacks reproducibility. Hence, in this study, we applied metabolomics and a genetic approach to the authentication of two common agarwood chips, those produced by Aquilaria crassna and Aquilaria malaccensis. Primary metabolites, secondary metabolites and DNA markers of agarwood were authenticated by 1H NMR metabolomics, GC-MS metabolomics and DNA-based techniques, respectively. The results indicated that agarwood chips could be classified accurately by all the methods illustrated in this study. Additionally, the pros and cons of each method are also discussed. To the best of our knowledge, our research is the first study detailing all the differences in the primary and secondary metabolites, as well as the DNA markers between the agarwood produced by these two species.

Asunto(s)