Mass Spectrometry-based Metabolomics Approach Research Articles

Influence of calcium channel modulators on the production of serotonin, gentisic acid, and a few other biosynthetically related phenolic metabolites in seedling leaves of salt tolerant rice variety Nonabokra

ABSTRACT Rice, a most salt-sensitive cereal plant, adopts diverse pathways to withstand sodium chloride–induced salinity-related adversities. During the present study, attempt was made to understand the role of calcium on metabolite profile of the leaves of salt tolerant rice seedlings of variety of Nonabokra under sodium chloride induced salinity, by Gas Chromatography–Mass Spectrometry-based metabolomics approach. Calcium availability in the seedlings was reduced or enhanced applying inhibitors (vanadyl sulfate, lanthanum chloride, and verapamil) or promoters of calcium influx (calcimycin also known as calcium ionophore A23187) in the sodium chloride (100 mM) supplemented growth medium. Growth medium of ten-day-old seedlings was replaced by sodium chloride supplemented hydroponic solution with promotor or inhibitors of calcium channel. Fifteen days old seedlings were harvested. It was observed that depletion of calcium availability increased the level of serotonin and gentisic acid whereas increased calcium level decreased these metabolites. It was concluded from the results that production of the signaling molecules serotonin and gentisic acids was elevated in calcium-deficient seedlings under salt stress the condition that was considered as control during the experiment. The two signaling molecules probably help this tolerant rice variety Nonabokra to withstand the salt-induced adversities.

Comparing Metabolites and Functional Properties of Various Tomatoes Using Mass Spectrometry-Based Metabolomics Approach.

Tomato is one of the world's most consumed vegetables, and thus, various cultivars have been developed. Therefore, metabolic differences and nutrient contents of various tomatoes need to be discovered. To do so, we performed metabolite profiling along with evaluation of morphological and physicochemical properties of five representative tomato types. Common tomato cultivars, bigger and heavier than other tomatoes, contained higher levels of amino acids, organic acids, and lipids. On the contrary, cherry tomato cultivars contained a higher proportion of phenylpropanoids, lycopene, β-carotene, and α-carotene than the other tomatoes. Also, the highest antioxidant activity and total phenolic and flavonoid contents were observed in cherry tomato cultivars. Furthermore, to understand metabolic distributions in various tomato cultivars, we constructed a metabolic pathway map. The higher metabolic flux distribution of most primary metabolite synthetic pathways was observed in common tomatoes, while cherry tomato cultivars showed a significantly elevated flux in secondary metabolite synthetic pathways. Accordingly, these results provide valuable information of different characteristics in various tomatoes, which can be considered while purchasing and improving tomato cultivars.

Cell metabolomics analyses revealed a role of altered fatty acid oxidation in neurotoxicity pattern difference between nab-paclitaxel and solvent-based paclitaxel.

Peripheral neuropathy (PN) is a dose-limiting, painful adverse reaction associated with the use of paclitaxel. This common side effect was often partially attributed to the solvent used for solubilization of the highly hydrophobic drug substance. Therefore, the development of alternative formulations thrived, which included that of Abraxane® containing nanoparticle albumin-bound paclitaxel (nab-paclitaxel). However, studies demonstrated inconsistent conclusions regarding the mitigation of PN in comparison with the traditional formulation. The mass spectrometry-based cell metabolomics approach was used in the present study to explore the potentially associated mechanisms. Although no significant difference in the effects on cell viability was observed, fold changes in carnitine, several acylcarnitines and long-chain fatty acid(s) were significantly different between treatment groups in differentiated and undifferentiated SH-SY5Y cells. The most prominent difference observed was the significant increase of octanoylcarnitine in cells treated with solvent-based paclitaxel, which was found to be associated with significant decrease of medium-chain acyl-CoA dehydrogenase (MCAD). The findings suggested the potential role of altered fatty acid oxidation in the different neurotoxicity patterns observed, which may be a possible target for therapeutic interventions worth further investigation.

Differences in Fatty Acid Oxidation between Nab-Paclitaxel- and Solvent-Based Paclitaxel-Treated A549 Cells Based on Metabolomics.

The pharmacokinetics, safety, and anticancer efficacy profiles of nanoparticle albumin-bound (nab)-paclitaxel formulations are superior to those of solvent-based paclitaxel formulations. The aims of the present study were to study the effects of nab-paclitaxel and solvent-based paclitaxel formulations on the metabolic profiles of the model cell line (A549) and attempt to elucidate the associated metabolic pathways. A mass spectrometry-based cell metabolomics approach and viability evaluation were used to explore the potential difference. Western blotting was utilized to measure the levels of relevant proteins, and carnitine palmitoyltransferase 1 (CPT1) activities were quantified. Fold changes normalized to controls in levels of carnitine and several acylcarnitines were significantly different (p < 0.05) between A549 cells treated with nab-paclitaxel and those treated with solvent-based paclitaxel. Relative to the controls, there were also significant fold change differences in palmitic and linoleic acid levels in the cell lysates, mitochondrial CPT1 activities, and mitochondrial medium-chain acyl-CoA dehydrogenase (MCAD) protein levels in the A549 cells subjected to the nab-paclitaxel and solvent-based paclitaxel formulations. Results suggested that the two formulations differentially modulated fatty acid oxidation in the A549 cells. While cell viability results did not reveal significant differences, the findings implied that a mass spectrometry-based cell metabolomics approach could be a sensitive tool to explore the differences caused by formulation changes without using animals. Since uncertainties of products containing nanomaterials warrant holistic screening to address safety concerns, the aforementioned approach may be of regulatory importance and is worth further investigation.

Metabolomic Biomarkers for the Detection of Obesity-Driven Endometrial Cancer.

Simple SummaryEndometrial cancer is the commonest cancer of the female genital tract and obesity is its main modifiable risk factor. Over 80% of endometrial cancers develop in the context of obesity-induced metabolic changes. This study focuses on the potential of plasma-based metabolites to enable the early detection of endometrial cancer in a cohort of women with body mass index (BMI) ≥ 30 kg/m2. Specific lipid metabolites including phospholipids and sphingolipids (sphingomyelins) demonstrated good accuracy for the detection of endometrial cancer, especially when combined in a diagnostic model. This study advances our knowledge of the role of metabolomics in endometrial cancer and provides a basis for the minimally invasive screening of women with elevated BMI.Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analysed plasma samples of women with body mass index (BMI) ≥ 30 kg/m2 and endometrioid endometrial cancer (cases, n = 67) or histologically normal endometrium (controls, n = 69), using a mass spectrometry-based metabolomics approach. Eighty percent of the samples were randomly selected to serve as a training set and the remaining 20% were used to qualify test performance. Robust predictive models (AUC > 0.9) for endometrial cancer detection based on artificial intelligence algorithms were developed and validated. Phospholipids were of significance as biomarkers of endometrial cancer, with sphingolipids (sphingomyelins) discriminatory in post-menopausal women. An algorithm combining the top ten performing metabolites showed 92.6% prediction accuracy (AUC of 0.95) for endometrial cancer detection. These results suggest that a simple blood test could enable the early detection of endometrial cancer and provide the basis for a minimally invasive screening tool for women with a BMI ≥ 30 kg/m2.

Comprehensive metabolic profiling of Parkinson\u2019s disease by liquid chromatography-mass spectrometry

BackgroundParkinson’s disease (PD) is a prevalent neurological disease in the elderly with increasing morbidity and mortality. Despite enormous efforts, rapid and accurate diagnosis of PD is still compromised. Metabolomics defines the final readout of genome-environment interactions through the analysis of the entire metabolic profile in biological matrices. Recently, unbiased metabolic profiling of human sample has been initiated to identify novel PD metabolic biomarkers and dysfunctional metabolic pathways, however, it remains a challenge to define reliable biomarker(s) for clinical use.MethodsWe presented a comprehensive metabolic evaluation for identifying crucial metabolic disturbances in PD using liquid chromatography-high resolution mass spectrometry-based metabolomics approach. Plasma samples from 3 independent cohorts (n = 460, 223 PD, 169 healthy controls (HCs) and 68 PD-unrelated neurological disease controls) were collected for the characterization of metabolic changes resulted from PD, antiparkinsonian treatment and potential interferences of other diseases. Unbiased multivariate and univariate analyses were performed to determine the most promising metabolic signatures from all metabolomic datasets. Multiple linear regressions were applied to investigate the associations of metabolites with age, duration time and stage of PD. The combinational biomarker model established by binary logistic regression analysis was validated by 3 cohorts.ResultsA list of metabolites including amino acids, acylcarnitines, organic acids, steroids, amides, and lipids from human plasma of 3 cohorts were identified. Compared with HC, we observed significant reductions of fatty acids (FFAs) and caffeine metabolites, elevations of bile acids and microbiota-derived deleterious metabolites, and alterations in steroid hormones in drug-naïve PD. Additionally, we found that L-dopa treatment could affect plasma metabolome involved in phenylalanine and tyrosine metabolism and alleviate the elevations of bile acids in PD. Finally, a metabolite panel of 4 biomarker candidates, including FFA 10:0, FFA 12:0, indolelactic acid and phenylacetyl-glutamine was identified based on comprehensive discovery and validation workflow. This panel showed favorable discriminating power for PD.ConclusionsThis study may help improve our understanding of PD etiopathogenesis and facilitate target screening for therapeutic intervention. The metabolite panel identified in this study may provide novel approach for the clinical diagnosis of PD in the future.

Metabolomics study on the therapeutic mechanism of Schisandra chinensis polysaccharides on concanavalin A-induced immunological liver injury in mice

Background: Schisandra chinensis is a traditional Chinese herbal medicine which protects hepatic function. Its primary component is polysaccharides which is used in the treatment of hepatic injury, but the mechanism of action of S. chinensis polysaccharides (SCP) in immunological liver injury induced by concavalin A (Con A) is still not clear. Aim: In this study, we aimed to evaluate the hepatoprotective mechanism of SCP in immunological liver injury. Subjects and Methods: In this study, we performed rapid-resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry-based serum metabolomics approach to investigate the hepatoprotective effects of SCP against Con A-induced immunological liver injury in mice. Results: According to our results, SCP significantly increased the activity of superoxide dismutase in the liver; decreased the level of serum aspartate aminotransaminase (AST), serum alanine aminotransaminase (ALT), tumor necrosis factor-α, interferon-γ, interleukin (IL)-1 β, and IL-6 in the serum, and decreased the level of malondialdehyde and nitric oxide in the liver of mice with immunological liver injury induced by Con A. In this study, we identified 17 biomarkers through metabolomic analysis, and after the administration of SCP, 16 of them were found to return to the normal levels. Our analysis suggested that some metabolic pathways are involved in the mechanisms of action of SCP for the treatment of the immunological liver injury, including energy metabolism, amino acid metabolism, taurine metabolism, amino saccharide and nucleotide metabolism, arachidonic acid metabolism, and lipid metabolism. Conclusion: SCP could alleviate the oxidative stress and inflammatory reaction in the immunological liver injury and recover the metabolic dysfunction caused by Con A.

A metabolomic signature of FIGO stage I and II endometrial cancer.

Endometrial cancer (EC) is a malignant tumor of the female reproductive tract. Due to its rapid growth and invasiveness, EC is currently the only gynecological neoplasm with rising incidence and mortality rates. It is of great significance to explore the metabolomics signature of stage I and II EC for the diagnosis and treatment. A mass spectrometry-based untargeted metabolomics approach was used to explore preoperative serum metabolites in the normal and stage I and II EC patients. The metabolites were mapped to the Ingenuity pathway analysis (IPA) database to determine the potential biomarkers and metabolic pathways that differ between EC patients and healthy controls. The top analysis-ready molecules of upregulated D-glucose thiamine and downregulated cholesterol, arachidonic acid, palmitic acid, oleic acid, stearic acid, linoleic acid may be the most related metabolites. These potential biomarkers have essential functions in regulating vital metabolic pathways associated with stage I and II EC. Additionally, our pathway analysis revealed five significantly related pathways according to the metabolite differentials. Finally, the disease and function prediction of the initial pathway analysis suggested that small molecule biochemistry, lipid metabolism, and organismal injury and abnormalities were associated with EC cases. Over 25 metabolites were differentially expressed in stage I and II EC. In addition, the six most significant metabolites were related to stage I and stage II EC cases. Ingenuity pathway analysis revealed potential biomarkers and metabolic pathways revolved to EC. In this paper, candidate endogenous biomarkers were defined as the basis for disease diagnosis and individualized treatment monitoring and revealed the mechanism of EC occurrence and development.

Untargeted mass spectrometry-based metabolomics approach unveils molecular changes in milk fermented by Lactobacillus plantarum P9

This study applied the ultra-performance liquid chromatography coupled with time-of-flight mass spectrometry metabolomics to investigate changes in the metabolites of fermented milk with novel probiotic Lactobacillus plantarum P9. The analysis of changes in viable counts and acidity during fermentation and storage indicated that the P9 strain fermented the milk effectively and reached a fermentation end point (pH 4.5) after 13.5 h. The fermented milk was relatively stable after 28-day of cold storage. These results suggested P9 was a suitable starter culture for fermented milk production. Significant differences were observed in the milk metabolome after fermentation and after different periods of cold storage. A total of thirty-five differentially abundant metabolites were identified, including 25 significantly increased and 10 significantly decreased metabolites in the fermented milk. These metabolites included fatty acids, peptides, carbohydrates, and other metabolites, some of them could offer functional attributes to the final products. No previous study has evaluated metabolomics changes of P9 during fermentation and storage. Thus, our data provide a valuable reference for the future development and improvement of fermented dairy products using the P9 strain.

Identification of a Reliable Biomarker Profile for the Diagnosis of Gaucher Disease Type 1 Patients Using a Mass Spectrometry-Based Metabolomic Approach.

Gaucher disease (GD) is a rare autosomal recessive multisystemic lysosomal storage disorder presenting a marked phenotypic and genotypic variability. GD is caused by a deficiency in the glucocerebrosidase enzyme. The diagnosis of GD remains challenging because of the large clinical spectrum associated with the disease. Moreover, GD biomarkers are often not sensitive enough and can be subject to polymorphic variations. The main objective of this study was to perform a metabolomic study using an ultra-performance liquid chromatography system coupled to a time-of-flight mass spectrometer to identify novel GD biomarkers. Following the analysis of plasma samples from patients with GD, and age- and gender-matched control samples, supervised statistical analyses were used to find the best molecules to differentiate the two groups. Targeted biomarkers were structurally elucidated using accurate mass measurements and tandem mass spectrometry. This metabolomic study was successful in highlighting seven biomarkers associated with GD. Fragmentation tests revealed that these latter biomarkers were lyso-Gb1 (glucosylsphingosine) and four related analogs (with the following modifications on the sphingosine moiety: -C2H4, -H2, -H2+O, and +H2O), sphingosylphosphorylcholine, and N-palmitoyl-O-phosphocholineserine. Based on the plasma biomarker distribution, we suggest the evaluation of this GD biomarker profile, which might facilitate early diagnosis, monitoring, and follow-up of patients.

Identification of biomarkers for early diagnosis of diabetic nephropathy disease using direct flow through mass spectrometry

Background and aimsAlbuminuria is not an effective marker for early diagnosis of diabetic renal complication with several subjects progressing to chronic kidney disease without any albuminuria. A biomarker that can predict early changes of the diabetic kidney will be useful in effective management of type 2 diabetes. Mass spectrometry based metabolomics approach offers tremendous promise for the identification of novel metabolite biomarkers. MethodsA case-control approach was carried out to identify renal biomarkers among Asian Indian subjects in a hospital setting. A total of 29 subjects were included in the study that included groups of diabetic controls, diabetic subjects with eGFR >90 ml/min/1.72 m2 and diabetic subjects with eGFR between 60 and 89 ml/min/1.72 m2 and eGFR between 15 and 30 ml/min/1.72 m2. We employed an un-targeted mass spectrometry method for the identification of plasma metabolites. ResultsA total of 1414 and 975 metabolites were identified in the positive and negative ion mode respectively. 19 metabolites were up regulated and 18 metabolites were down regulated in CKD2 and CKD4 groups when compared to control. Correlation analysis of the differential metabolites revealed Pregnenolone sulfate, creatinine and ganglioside GA1 to be negatively correlated and hexyl glucoside, all-trans-carophyll yellow and PG to be positively correlated with eGFR. ConclusionWe have identified Pregnenolone sulfate, GA1, PG and all-trans-Carophyll yellow as biomarkers for early identification of diabetic nephropathy. These markers could aid in better management of diabetic nephropathy that may result delaying the progression of the disease.

The Effects of Graded Levels of Calorie Restriction: XVI. Metabolomic Changes in the Cerebellum Indicate Activation of Hypothalamocerebellar Connections Driven by Hunger Responses.

Calorie restriction (CR) remains the most robust intervention to extend life span and improve healthspan. Though the cerebellum is more commonly associated with motor control, it has strong links with the hypothalamus and is thought to be associated with nutritional regulation and adiposity. Using a global mass spectrometry-based metabolomics approach, we identified 756 metabolites that were significantly differentially expressed in the cerebellar region of the brain of C57BL/6J mice, fed graded levels of CR (10, 20, 30, and 40 CR) compared to mice fed ad libitum for 12 hours a day. Pathway enrichment indicated changes in the pathways of adenosine and guanine (which are precursors of DNA production), aromatic amino acids (tyrosine, phenylalanine, and tryptophan) and the sulfur-containing amino acid methionine. We also saw increases in the tricarboxylic acid cycle (TCA) cycle, electron donor, and dopamine and histamine pathways. In particular, changes in l-histidine and homocarnosine correlated positively with the level of CR and food anticipatory activity and negatively with insulin and body temperature. Several metabolic and pathway changes acted against changes seen in age-associated neurodegenerative disorders, including increases in the TCA cycle and reduced l-proline. Carnitine metabolites contributed to discrimination between CR groups, which corroborates previous work in the liver and plasma. These results indicate the conservation of certain aspects of metabolism across tissues with CR. Moreover, this is the first study to indicate CR alters the cerebellar metabolome, and does so in a graded fashion, after only a short period of restriction.

Differences in Intestinal Metabolism of Ginseng Between Normal and Immunosuppressed Rats.

Ginseng is usually consumed as a dietary supplement for health care in the normal state or prescribed as a herbal medicine in pathologic conditions. Although metabolic studies of ginseng are commonly performed on healthy organisms, the metabolic characteristics in pathologic organisms remain unexplored. This study aimed to uncover the difference in intestinal metabolism of ginseng between normal and cyclophosphamide-induced immunosuppressed rats and further discuss the potential mechanisms involved. Twelve Sprague-Dawley rats (6-8weeks old) were randomly divided into two groups: the normal group (NG) and immunosuppressed group (ISG). Rats in the NG and ISG groups were intraperitoneally administered normal saline and cyclophosphamide injections (40mg/kg) on the 1st, 2nd, 3rd and 10th days; on the 12th day, all rats were intragastrically administered ginseng water extract (900mg/kg). The difference in intestinal metabolism of ginseng was compared using an ultra-high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry-based metabolomics approach, and the diversities of gut microbiota were analyzed by 16S rRNA gene sequencing between the two groups. The intestinal metabolomic characteristics of ginseng were significantly different between the normal and immunosuppressed rats, with the ginsenoside F2 (F2), 20S-ginsenoside Rg3 (20(S)-Rg3), pseudo-ginsenoside Rt5 (Pseudo-Rt5), ginsenoside Rd (Rd), ginsenoside Rh1 (Rh1), 20S-ginsenoside Rg1 (20(S)-Rg1), ginsenoside compound K (CK), ginsenoside Rg2 (Rg2) and 20S-panaxatriol (S-PPT) more abundant in immunosuppressed ones (P < 0.05). Additionally, the composition of gut microbiota was remarkably altered in the two groups, with some specific bacterial communities such as Bacteroides spp., Eubacterium spp. and Lachnospiraceae_UCG-010 spp. increased and Bifidobacterium spp. decreased in immunosuppressed rats compared with normal ones. The intestinal metabolism of ginseng in immunosuppressed rats was significantly different from that in normal ones, which might be partly attributed to the changes in the intensity of specific gut bacteria. The outcomes of this study could provide scientific data for rationalization of ginseng use as both a dietary supplement and herbal medicine.

Mass spectrometry-based untargeted metabolomics approach for differentiation of beef of different geographic origins

Beef is a common staple food in many countries, and there is a growing concern over misinformation of beef products, such as false claims of origin, species and production methods. In this study, we used a mass spectrometry-based metabolomics approach to study the metabolite profiles of beef samples purchased from local retailers in Hong Kong. Using multivariate analysis, beef samples from different a) geographical origins, namely the United States (US), Japan and Australia, and b) feeding regimes could be differentiated. We identified twenty-four metabolites to distinguish beef samples from different countries, ten metabolites to identify Angus beef samples from others and seven metabolites to discriminate Australian beef produced by the organic farming from that produced using other farming modes. Based on results of this study, it is concluded that metabolomics provides an efficient strategy for tracing and authenticating beef products to ensure their quality and to protect consumer rights.

Developmental Signatures of Microbiota-Derived Metabolites in the Mouse Brain.

The gut microbiome is recognized to exert a wide-ranging influence on host health and disease, including brain development and behavior. Commensal bacteria can produce bioactive molecules that enter the circulation and impact host physiology and homeostasis. However, little is known about the potential for these metabolites to cross the blood–brain barrier and enter the developing brain under normal physiological conditions. In this study, we used a liquid chromatography–mass spectrometry-based metabolomic approach to characterize the developmental profiles of microbial-derived metabolites in the forebrains of mice across three key postnatal developmental stages, co-occurring with the maturation of the gut microbiota. We demonstrate that direct metabolites of the gut microbiome (e.g., imidazole propionate) or products of the combinatorial metabolism between the microbiome and host (e.g., 3-indoxyl-sulfate, trimethylamine-N-oxide, and phenylacetylglycine) are present in the forebrains of mice as early as the neonatal period and remain into adulthood. These findings demonstrate that microbial-associated molecules can cross the BBB either in their detected form or as precursor molecules that undergo further processing in the brain. These chemical messengers are able to bind receptors known to be expressed in the brain. Alterations in the gut microbiome may therefore influence neurodevelopmental trajectories via the regulation of these microbial-associated metabolites.

Mass spectrometry-based metabolomics approach in the isolation of bioactive natural products

Metabolomics is a powerful tool in the analysis and identification of metabolites responsible for biological properties. Regarding natural product chemistry, it constitutes a potential strategy to streamline the classic and laborious process of isolating natural products, which often involves the re-isolation and identification of known compounds. In this contribution, we establish a mass spectrometry-based metabolomics strategy to discover compounds with larvicidal activity against Aedes aegypti. We analyse the Brazilian plant Annona crassiflora using different platforms to annotate the active compounds in different extracts/fractions of various plant parts. The MetaboAnalyst and GNPS platforms, which consider LC-MS and LC-MS/MS data, respectively, were chosen to identify compounds that differentiate active and inactive samples. Bio-guided isolation was subsequently performed to confirm compound activity. Results proved the capacity of metabolomics to predict metabolite differences between active and inactive samples using LC-MS and LC-MS/MS data. Moreover, we discuss the limitations, possibilities, and strategies to have a broad view of vast data.

The Mechanisms of Improving IVF Outcomes of Liu-Wei-Di-Huang Pill Acting on DOR Patients.

Diminished ovarian reserve (DOR) is the weakening of ovarian oocyte production and quality. It will further become premature ovarian failure without timely cure. However, disease pathology and diagnostic markers are still incompletely understood. Liu-Wei-Di-Huang (LWDH) pill, a traditional Chinese medicine formula, is commonly used in the treatment of DOR in China. To explore the mechanism of the effect of LWDH on in vitro fertilization (IVF) outcomes in patients with DOR, a pseudotargeted metabolomics study combined with multivariate data processing strategy was carried out. A liquid chromatography tandem mass spectrometry-based metabolomics approach was applied to characterize metabolic biomarker candidates. Multiple pattern recognition was used to determine groups and confirm important variables. A total of 21 potential biomarkers were characterized, and related metabolic pathways were identified. The study displayed that the established pseudotargeted metabolomics strategy is a powerful approach for investigating the mechanism of DOR and LWDH. In addition, the approach may highlight biomarkers and metabolic pathways and can capture subtle metabolite changes from headache, which may lead to an improved mechanism understanding of DOR diseases and LWDH treatment.

Dynamic Alterations of Plasma Metabolites in the Progression of Liver Regeneration after Partial Hepatectomy.

To elucidate the dynamic alterations of metabolites in rat plasma during liver regeneration and search for potential biomarkers of liver regeneration, 65 male Sprague-Dawley rats were divided into three groups: 70% partial hepatectomy group (PHx, n = 30), sham-operated group (Sham, n = 30), and pre-PHx group (pre-PHx, n = 5). Rats in the Sham and PHx groups were sacrificed after 30 min (min), 6 h (h), 24, 48, 72, and 168 h of surgery (n = 5 per time point). The gas chromatography-mass spectrometry-based metabolomic approach was used to identify the dynamic metabolites. Liver regeneration in the rats was evidenced by an increase in the liver weight/body weight ratio, expression of proliferating cell nuclear antigen, and yes-associated protein-1. Thirty-four differentially abundant metabolites between the Sham and PHx groups were identified, which were involved in arginine and proline metabolism, aminoacyl-tRNA biosynthesis, and cysteine and methionine metabolism pathways. Of these metabolites, low 1,5-anhydroglucitol may indicate proliferation of liver parenchymal cells during liver regeneration. Thus, a series of metabolic changes occurred with the progression of liver regeneration, and 1,5-anhydroglucitol could function as a novel hallmark of proliferation of liver parenchymal cells.

Comparative metabolic expressions of fermented soybeans according to different microbial starters

The quality of fermented soybeans can be determined by diverse metabolites produced by microorganisms. Mass spectrometry-based metabolomic approach was applied to investigate the differences in volatile and non-volatile metabolite profiles of fermented soybeans by different microorganisms [e.g., molds, yeasts, lactic acid bacteria (LAB), and other bacteria]. The partial least squares-discriminant analysis (PLS-DA) for volatile metabolites profiles indicated that the fungi group (mold/yeast) was clearly discriminated from the bacteria group (bacteria/LAB). The metabolic pathways related to the formation of volatile metabolites also differed according to microorganisms. In particular, the formation of branched-chain aliphatic alcohols and esters increased in the fungi group, while that of volatiles derived from fatty acids was superior in the bacteria group. In addition, we could determine the microorganism-specific metabolites using a correlation network analysis. This study can provide the fundamental knowledge on the metabolic differences according to the type of microorganisms in fermented soybeans.

Untargeted mass spectrometry-based metabolomics approach unveils molecular changes in raw and processed foods and beverages

In our daily lives, we consume foods that have been transported, stored, prepared, cooked, or otherwise processed by ourselves or others. Food storage and preparation have drastic effects on the chemical composition of foods. Untargeted mass spectrometry analysis of food samples has the potential to increase our chemical understanding of these processes by detecting a broad spectrum of chemicals. We performed a time-based analysis of the chemical changes in foods during common preparations, such as fermentation, brewing, and ripening, using untargeted mass spectrometry and molecular networking. The data analysis workflow presented implements an approach to study changes in food chemistry that can reveal global alterations in chemical profiles, identify changes in abundance, as well as identify specific chemicals and their transformation products. The data generated in this study are publicly available, enabling the replication and re-analysis of these data in isolation, and serve as a baseline dataset for future investigations.