Introduction In the last years, consumers increased the demand for high-quality and healthy beverages, including coffee. To date, among the techniques potentially available to determine the overall quality of coffee beverages, metabolomics is emerging as a valuable tool. Objective In this study, 47 ground coffee samples were selected during the 2018 Edition of the “International coffee tasting” (ICT) in order to provide discrimination based on both chemical and sensory profiles. In particular, 20 samples received a gold medal (“high quality” group), while lower sensory scores characterized 27 samples (without medal). Methods Untargeted metabolomics based on ultra-high pressure liquid chromatography coupled with quadrupole-time-of-flight (UHPLC-QTOF) and head space-gas chromatography coupled with mass spectrometry platforms followed by multivariate statistical approaches (i.e., both supervised and unsupervised) were used to provide new insight into the searching of potential markers of sensory quality. Results Several compounds were identified, including polyphenols, alkaloids, diazines, and Maillard reaction products. Also, the headspace/GC-MS highlighted the most important volatile compounds. Polyphenols were scarcely correlated to the sensory parameters, whilst the OPLS-DA models built using typical coffee metabolites and volatile/Maillard compounds possessed prediction values > 0.7. The “high quality” group showed specific metabolomic signatures, thus corroborating the results from the sensory analysis. Overall, methyl pentanoate (ROC value = 0.78), 2-furfurylthiol (ROC value = 0.75), and L-Homoserine (ROC value = 0.74) established the higher number of significant (p < 0.05) correlations with the sensory parameters. Conclusion Although ad-hoc studies are advisable to further confirm the proposed markers, this study demonstrates the suitability of untargeted metabolomics for evaluating coffee quality and the potential correlations with the sensory attributes. Graphic abstract
Increasingly sophisticated instrumentation for chemical separations and identification has facilitated rapid advancements in our understanding of the metabolome. Since many analyses are performed using either mass spectroscopy (MS) or nuclear magnetic resonance (NMR) spectroscopy, the spin 1/2 stable C-13 isotope is now widely used as a metabolic tracer. There is a strong interest in quantitative analysis of metabolic flux through pathways in vivo, particularly in human patients. Although instrumentation advances and scientific interests in metabolism are increasing in parallel, a practical and rational design of a C-13 tracer study can be challenging. Prior to planning the details of a tracer experiment, is it important to consider whether the analytical results will be sensitive to flux through the pathways of interest. Here, we briefly summarize the various approaches that have been used to design carbon tracer experiments, outline the sources of complexity, and illustrate the use of a software tool, tcaSIM, to aid in the experimental design of both MS and NMR data in complex systems including patients.
Background: Metabolomics is a relatively new and dominant branch of bioinformatics. Metabolite expression level controls the phenotypic characteristics of any organism. Recently, breast cancer is the leading type of cancer in women across the world, accounting for 25% of all cases. In 2012, it was seen that due to breast cancer, there were 1.68 million cases and 522,000 deaths. Therefore, for drug discovery as well as for early disease status prediction, significant metabolites identification for breast cancer and correct classification of the breast cancer status through classification technique are very important for metabolomics data analysis. Objective: The main objective of this paper is to identify significant metabolites (p-value<0.05) and state of the art classification technique for breast cancer prediction using metabolomics dataset. Methods: Although there are several techniques to identify significant metabolites, here, we took Student's t-test and Kruskal-Wallis test for significant metabolites identification. To classify the breast cancer prediction, we considered five modern classification techniques-(i) Naive Bayes (NB) (ii) Support Vector Machine (SVM) (iii) Linear Discriminant Analysis (LDA) (iv) k-nearest neighbors algorithm (kNN) and (v) Random Forest (RF). We also measured the performances of the classification techniques through accuracy, sensitivity, specificity, Receiver Operating Characteristic (ROC) curve and area under the ROC curve etc. Results: The performance measures of different classification techniques showed that random forest classifier produced higher accuracy, sensitivity, specificity and area under the ROC curve compared to the other classification techniques for breast cancer prediction using metabolomics dataset. The analytical results also showed that there are 24 significant (adjusted p-value <0.05) metabolites influencing breast cancer. Conclusion: On the basis of the experimental results, we could say that there are 24 breast cancer influencing metabolites and for breast cancer prediction as well as metabolomics data analysis, random forest is the state of the art and outlier-robust classifier among the five classification techniques.
Background: Controlling aquatic pollution with natural resources is a worldwide hot topic of research, according to its positive environmental impact. Methods: Chitosan is cross linked with sodium Tripolyphosphate (TPP) to form microsphere. Then microsphere could be effectively utilized to remove Pb ion from water with a removal rate of 59.2% in 90 minutes. The microsphere is further enhanced as dried water hyacinth is mixed with chitosan to produce modified water hyacinth/chitosan microsphere up to 50% water hyacinth. The crosslinking process for chitosan as well as chitosan/water hyacinth is indicated with the help of Fourier Transform Infrared Spectroscopy (FTIR). The interaction between chitosan and water hyacinth is simulated with ab initio using HF/STO-3G model. Results: The produced water hyacinth/chitosan microsphere shows removal of Pb ions up to 90.6% in 180 minutes. The produced microsphere is cost effective. Conclusion: Applying two stages of removal one can obtain good results of removal up to 90.6%. In this manner the cost effective water hyacinth cross linked chitosan is produced effectively with good removal percentage. Finally, the structure of water hyacinth is simulated with molecular modeling at HF/STO-3G.
Background: The intensity of the blood as well as tissue autofluorescence (fluorescence of endogenous fluorophores) shows current structure of protein mixture, its current conformation (native or denatured state), concentration or activity depending on the external and internal conditions. Nicotine amide adenine dinucleotide (NAD(+)) is a cofactor in redox reactions of glycolysis and the citric acid cycle in eukaryotic cells and it can be a marker of the intensity of mitochondria metabolism as well as the presence of oxygen in the cells. The concentration of reduced nicotinamide adenine dinucleotide (NADH) varies during normoxia, hypoxia and hyperoxia cells. Cancer cells increase the concentration of NADH during hypoxia and anoxia. The reason of NADH cumulation is microenvironment with low or no oxygen supply which induces glycolysis as a preferential source of energy. Glycolysis is faster, does not need oxygen but is less effective than oxidative phosphorylation. Focus: The aim of this work was to measure the structure of blood plasma and mammary gland homogenates of patients at three stages of breast cancer in comparison to healthy subjects using fluorescence analysis and atomic force microscopy. The blood plasma of patients with breast cancer had a different structure of proteins in comparison to healthy subjects. The blood plasma and homogenate of patients with breast cancer showed significant increase in autofluorescence intensity, which represents mixture of various endogenous fluorophores in particular porphyrins, collagen, NAD and flavins. Prospect: The information about complex summary of fluorescence intensity of all mixtures of endogenous fluorophores may in the future serve as rapid preliminary markers of cancer. The fluorescence analysis might be a non-traditional methodology for an early rapid diagnosis of breast cancer in the next clinical practice.
Background: Blood serum is characteristic mixture of naturally occurring endogenous fluorophores which are sensitive to endogenous and exogenous stress during physiological as well as pathological processes in the body. Methods: Dynamic changes of blood serum in patients with positive troponin and creatine kinase during myocardial infarction compared to control blood serum of healthy subjects were studied by synchronous fluorescence fingerprint and atomic force microscopy at 0, 1st, 16th, and 24th hour time points. Results: While creatine kinase and troponin T values were in physiological range, fluorescence intensity of patient's blood serum was significantly increased at lambda = 280 nm, p < 0.001 at the first zero time point. In addition, at spectrum record appeared a second fluorescence peak place at. = 306 nm in comparison with control blood serum fluorescence. Blood serum proteins changed structure from globular to fibrils during acute myocardial infarction in early 0 and 1st hour timepoints in comparison to control samples with regularly arranged globular proteins studied by atomic force microscopy. Otherwise, creatine kinase and troponin T values were positive in blood serum of patients several hours after beginning of acute myocardial infarction while fluorescence intensity exhibited decrease. Conversion of fibrils to irregular bigger globular proteins in comparison to blood serum with regular smaller globular proteins in control during later 16th and 24th hour time points was observed. Conclusion: Mentioned new nontraditional techniques may be used in future for the early study of progress of the various cardiovascular diseases in patients with differential diagnosis which in daily practice meets some difficulties.
Background: The use of Static Magnetic Fields (SMFs) in medicine, industry, and new technologies has significantly increased in the past few years. However, the potential health risks concerning the exposure to static magnetic fields remain a topic of debate. Objective: The objective of this study was to determine the influence of moderate static magnetic fields (SMFs) on human SH-SY5Y neuronal-like cells. Methods: SH-SY5Y differentiated to a neuronal phenotype by retinoic acid were exposed to 2.2 mT SMFs up to 24 h, and then cell viability, mitochondrial transmembrane potential and intracellular reactive oxygen species production were tested. In addition, changes in cellular molecules were evaluated by Fourier Transform Infrared Spectroscopy (FTIR). Results: Although the exposure of neuronal-like cells to SMFs did not induce changes on cell viability, in cell cultures exposed to 2.2 mT SMFs for 24 h a decrease in membrane mitochondrial potential up to 30%, associated to an increase of reactive oxygen species production was observed. Additionally, FTIR analysis evidenced alterations in protein and lipid cell components. In particular, after short times of exposure to 2.2 mT SMFs we found an increase in the intensity of CH2/CH3 ratio, indicating an increase in the lipid content. Instead, prolonged exposure to SMFs induced an increase in beta-sheets content with respect to alpha-helix. Conclusion: On the whole, these findings suggest that the exposure to moderate SMFs may induce substantial alterations in neuronal cell homeostasis, associated to mitochondrial impairment, oxidative stress and changes in protein and lipid structures.
Background: Recent decades have been marked by advances in omics sciences based on high-throughput technologies, which have enabled the measurement of enormous numbers of molecules in biosamples. In metabolomics, a large number of small molecules (metabolome) can be detected in a single run. The goal of this study was to evaluate the capacity for metabolomic analysis of blood plasma for early-stage Parkinson Disease (PD) diagnosis. Methods: Blood plasma samples collected from control subjects (n = 20) and patients with PD (Hoehn and Yahr stages 1, 1.5, and 2; n = 16) were treated with methanol, and low-molecular-weight fractions were analyzed by direct infusion mass spectrometry. Metabolite ions that exhibited strong association with PD were included in a diagnostic signature compilation and corresponding characteristics for PD diagnosis were calculated. For metabolite ions included in the signature, correspondence to specific metabolites in metabolite databases was established. Results: A total of 21 metabolite ions that were strongly associated with PD were used to compile a metabolome signature. The area under a receiver operating characteristic curve (AUC) for PD diagnosis calculated for the signature was 0.95 (accuracy 94%, specificity 95%, and sensitivity 94%). Metabolites identified in this study were consistent with factors that had been associated with the development of PD previously. Conclusion: Direct infusion mass spectrometry of blood plasma metabolites represents a rapid singlestep method with potential for application in early-stage PD diagnosis.
Background: Blood plasma/serum is a characteristic mixture of naturally occurring endogenous fluorophores which are sensitive to endogenous and exogenous stress during physiological as well as pathological processes in the body. Methods: The structure of the patient's blood plasma/serum surfaces with critical limb ischemia and healthy subjects were studied and compared using methods of synchronous fluorescence fingerprint and atomic force microscopy, which are usually not used in clinical practice. The molecules of IGF-2, HIF-1 and VEGF-A in the blood vessels of patients with a critical ischemic limb during the surgery were analyzed by qRT-PCR and electrophoretic detection. Results: Angiogenesis and also ischemia were detected in the ischemic blood vessels tissue of patients as a significant increased expression of mRNA levels of HIF-1 and VEGF-A genes in comparison with healthy subjects. The increased fluorescence intensity of proteins at wavelength lambda = 280 nm/Delta 60 nm was observed in the blood plasma/serum of patients. The fluorescence spectroscopy and atomic force microscopy revealed that the ischemic blood plasma and serum contains changed structures of proteins. Conclusion: Spectroscopic signals can study ischemic changes and these can generally predict morphological changes in the blood plasma/serum. Atomic force microscopy investigated structural changes of proteins in the blood plasma/serum. Methods of molecular analysis detected significant hypoxia in the blood tissue as significant increase of HIF-1 molecule and simultaneously significant angiogenesis as a significant increase of VEGF-A molecules. New nontraditional techniques may contribute to early diagnosis of the various vascular diseases in patients in future.
Background: The vast catalog of metabolites and extensive set of interactions within even the simplest cells can present a daunting task for analyzing, and especially simulating, metabolic networks. Yet many metabolites have associations with functionally related processes, convenient for organizing metabolites into pathways. Any perturbation in concentration of a single metabolite involves dynamic changes in concentrations of metabolites involved in a particular metabolic pathway and beyond. A standard approach to model such changes is the use of sets of ordinary differential equations; but because of the total number of dependent variables, a solution to such a set of equations is very computationally intensive and carries significant error. There is also no guarantee that the solution is always non-negative and numerically stable. Objective: The main purpose of the study is to overcome the deficiencies of standard ODE modeling of metabolic networks. Methods: In this paper, we propose to model in-silico metabolic networks as queueing networks, similar to the way that computer networks are modeled. Results: The proposed approach builds on successful applications of queueing theory to model other biological processes, such as gene delivery or molecular signaling. The basic mathematical underpinning of the modeling method is introduced. This is followed by the description of a general building block that can be used to model changes in concentration of a single metabolite and which can be interconnected with the interacting metabolites modeled by similar blocks. Conclusion: The presented simulation method has a potential to become a standard scalable method of modeling metabolomics networks.
Background: Temperature behavior of a class of PolyEthylene Oxide and Ethylene Glycol (EG) by means of InfraRed spectroscopy as a function of temperature and concentration. Methods: EG and PEO with Mw of 1000 were purchased from Aldrich-Chemie; To collect the FTIR spectra in the 39 degrees C-80 degrees C temperature range by means of a FTIR Vertex 70V spectrometer by Bruker Optics. Spectra were obtained using an average of 36 scans with a resolution of 4 cm(-1) in a window range of 400 / 4000 cm(-1). Each measure was performed under vacuum in order to minimize spectral contributions due to residual water vapor and finally the data were processed through the OPUS/Mentor software interface, Mathematica and Matlab. Results: The addition of EG to PEO increases the thermal restraint of the polymeric matrix due an increase of the H-bond connectivity. Conclusion: The analysis highlights an increased H-bonded connectivity in the polymeric mixture, which determines a higher resistance to temperature changes of the mixture.
Background: During plant life, there are several factors affecting plant growth, development and finally their productivity. Water is one of the most important environmental factors, as it is the major constituent of all living organisms. This stress influences plant metabolism both directly and indirectly. Thymus vulgaris or common thyme is well known since ancient times for its medicinal and culinary uses. Its extract has antiseptic, antibacterial and spasmolytic properties. Objective: To optimise the developed general scheme of DI FT-ICR metabolite profiling of plant extracts along with some basic physiological indices in Thymus vulgaris during water deficit stress. Methods: Combined morpho-physiological parameters (including water potential, water content, shoot fresh weight and soil moisture) with metabolite profiling were used during water deficit stress. Non-targeted metabolite profiling was carried out by DI FTICR mass spectrometry. Results: All physiological parameters that significantly changed corresponded to the soil moisture decrease. Likewise, the patterns of metabolite changes indicated by the results of DI FT-ICR reflected the physiological responses. Of 4755 peaks, 65 were selected as the most effective peaks based on their PCA loading scores. The selected peaks followed 3 major patterns over time, which have been described in detail. Major compounds, namely phenylalanine, tryptophan, asparagine, N-Carbamyl-beta Alanin and D-Xylulose-5P were affected under water shortage conditions. Conclusion: We highlighted the important role of these compounds in water deficit stress tolerance via plant hormones, secondary metabolite biosynthesis and purine, pyrimidine and histidine metabolism. Here, the results confirm the application of high-throughput approach DI-FTICR to study water deficit stress responses of thyme.
Background: Fecal water provides information on the state of the gut microbiota and host physiology and is a common biofluid to study, particularly for metabonomic purposes. Despite the interest in fecal water, a method of preparation has yet to be standardized. Current methods of preparing fecal water usually involve an extraction protocol combined with ultracentrifugation and filtration steps. If metabonomic analysis is the final means of examining fecal water samples, consideration should be given to the potential impacts of these preparation steps on the metabolites observed. Objective: This work examines metabonomic effects of ultracentrifugation during fecal water preparation, and provides an easily adaptable method based on considerations to metabonomic impacts of the procedure. Methods: Both fecal water (prepared from human stool samples) as well as a controlled surrogate for fecal water samples (prepared from in vitro fecal microbial communities) were used to perform systematic evaluations of various preparation steps, and used metabonomic profiles to assess the protocols' impact on the sample. Results: 52 metabolites were observed and found that ultracentrifugation speed decreased metabolite concentrations by approximately -2% per 10000 rpm increase, with one exception. P-cresol increased by approximately +50% per 10000 rpm. Upon investigation of the potential sources of p-cresol, we found evidence that these were tyrosine-rich cell proteins which broke down upon ultracentrifugation. Conclusion: Based on these findings, we suggest that ultracentrifugation is an effective means of preparing fecal water samples, with negligible impact on metabonomic analyses, though measurement of p-cresol concentrations should be treated with discretion.
Background: Agmatine, an endogenous amine, is cosidered a novel neuromodulator with neuroprotective properties. However, the mechanisms involved in these protective effects are poorly understood. Methods: Fourier Transform Infrared (FTIR) spectroscopy analysis detects biomolecular changes in disordered cells and tissues. In the present study, we employ FTIR spectroscopy to characterize the changes in rotenone-induced damage in neuronal-like differentiated SH-SY5Y neuroblastoma cells in the presence or absence of agmatine. Results: The analysis of the FTIR spectra evidences significant alterations in rotenone-treated cells that are reduced by the pre-incubation with agmatine (250 nM). In particular, rotenone-damaged cells demonstrate spectral alterations related to amide I, which correspond to an increase in beta-sheet components, and decreases in the amide II absorption intensity, suggesting a loss of N-H bending and C-N stretching. These alterations were also evident by Fourier self-deconvolution analysis. Thus, rotenone induced increases in the levels of stretching vibration band related to the protein carboxyl group would account for a significant amount of misfolded proteins in the cell. Agmatine effectively reduces these effects of rotenone on protein structure. Conclusion: In conclusion, antioxidant and scavenging properties of agmatine reduce rotenone-produced cellular damage at the level of protein structure. Our results, together with other previous observations, make agmatine a potential therapeutic agent in the treatment of Parkinson's disease.
Globally, cancer is one of the leading causes of death, so the development of strategies for an early diagnosis of cancer is of great importance. Biochemical alterations precede morphological changes in cells and tissues, so studying cancer metabolome seems like a reasonable approach for early diagnosis, prognosis and to follow treatment progression. Fourier-Transform Infrared (FTIR) spectroscopy is a valuable tool for studying the metabolome of biological samples, such as cancer cell lines. Unlike staining procedures and other histopathologic approaches, this technique is rapid, non-destructive and does not require reagents. The spectral differences that result from probing the biochemical composition of cancer and normal cells are indicative of distinct metabolic profiles, which allow the discrimination of different cells. Using FTIR spectroscopy and multivariate statistical analysis, several alterations concerning the content of lipids, proteins, nucleic acids and carbohydrates have been identified in cancer cells, some of which can be regarded as potential biomarkers. This review focuses on FTIR spectroscopy as a metabolomics tool to study and characterize cancer cell lines.
Background: Non-digestible carbohydrates are degraded by bacterial fermentation in the large intestine to yield Short-Chain Fatty Acids (SCFAs), such as acetate, propionate and butyrate. SCFAs are known to induce beneficial physiological and metabolic effects in the gut and the host. The pathogenesis of Irritable Bowel Disease (IBD) involves alterations or dysbiosis of the normal intestinal bacterial flora with reductions in butyrate producing bacteria noted in several datasets.Objective: The objective of the study was to develop a Liquid Chromatography (LC-MS) method for the analysis of short chain fatty acids.Methods: Short Chain Fatty Acids (SCFAs) were coupled to N, N-dimethyl-p-phenylenediamine using a carbodimide coupling. The analysis of the derivatised SCFAs was carried out by using Hydrophilic Interaction Chromatography (HILIC) coupled with an Orbitrap Exactive mass spectrometer. The method was calibrated in the range 0.05-1.6 mu g/ml using stable isotope labelled internal standards. The method was applied to urine samples obtained from patients with active Ulcerative Colitis (UC), patients with UC in remission and healthy controls.Results: Repeat analysis (n=5) of a urine sample gave the following values for concentrations of the SCFAs: acetate 134.7 mu M (RSD +/- 11.2%), propionate 1.68 mu M (RSD +/- 23.9%), butyrate 16.1 mu M (RSD +/- 8.0%). The values obtained for SCFAs in plasma were: acetate 60.3 mu M(RSD +/- 9.17%), propionate 6.4 mu M (RSD +/- 30.4%), and butyrate 21.2 mu M (RSD +/- 10.7%). The levels of butyrate were higher in patients in remission than in the other two groups. The method was highly sensitive but contamination with SCFAs from the environment, which was below 50 ng, determined the practical LODs. To work at levels <50 ng, a dedicated laboratory area would be required.Conclusion: The method described was highly sensitive but limited by background levels of SCFAs in the environment. The results suggest its potential future role in the measurment of SCFAs in UC management. However, a larger cohort would be required to validate its usefulness in the diagnosis and monitoring of UC.
Background: Despite cisplatin's effectiveness against ovarian cancer, these cancer cells have shown the ability to resist chemotherapy - a resistance that represents a major obstacle to current therapeutic strategies. Objective: The objective of the study was to determine whether or not cellular resistance could be linked to changes in metabolites. Methods: Liquid Chromatography-mass Spectrometry (LC-MS) hydrophilic interaction chromatography was used to analyze the intracellular metabolomic profile of ovarian cancer cell line A2780 and the cisplatin resistant cell line A2780CR, before and following treatment with cisplatin at inhibitory concentration (IC50). Phenotype MicroArray (TM) (PM) experiments were also applied in order to test carbon substrate utilization or sensitivity in both cell lines after exposure to cisplatin. Data extraction was carried out with MZmine 2.10 with metabolite searching against an in-house database. The data were analyzed using univariate and multivariate Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) methods. Results: There was clear discrimination between the controls and the cisplatin treated samples on the basis of PCA and OPLS-DA. The cisplatin-sensitive cells were as expected more sensitive to cisplatin than the resistant cells with IC50 values of 4.9 and 10.8 mu g/mL, respectively. The results demonstrated that the intracellular metabolomic changes induced by cisplatin in the cisplatin-sensitive cells led to reduced levels of acetylcarnitine, phosphocreatine, arginine, proline and Glutathione Disulfide (GSSG) as well as to increased levels of tryptophan and methionine. While PM experiments showed lowered glucose metabolism in the sensitive cells following treatment which was reflected in decreased levels of ATP. Conclusion: Overall the metabolic changes induced in A2780CR cells by cisplatin were much fewer than those induced in A2780 cells. The sensitive cells had a much quicker onset of apoptosis than the resistant cells as judged by measurement of caspase 3. Increased resistance to oxidative stress in the resistant cells was consistent with higher levels of proline, due to less induction of proline dehydrogenase, and elevated levels of glutathione (GSH) and GSSG following cisplatin treatment.
