Chemometrics in metabonomics

Four cypermethrin isomers induced stereoselective metabolism in H295R cells

Cypermethrin (CP) is widely used for controlling agricultural and indoor vermin. Previous studies have reported the stereoselective difference of CP in biological activities. However, little is known about their potential mechanisms between metabolic phenotypes and endocrine-disrupting effects. Herein, nuclear magnetic resonance (NMR)-based metabolomics combining metabolite identification and pathway analysis were applied to evaluate the stereoselective metabolic cdisorders induced by CP isomers in human adrenocortical carcinoma cells (H295R) culture medium. Then, gene expression levels related to disturbed metabolic pathways were assessed to verify according to metabolic phenotypes. Metabolomics profiles showed that [(S)-cyano(3-phenoxyphenyl)methyl](1R,3R)-3-(2,2-dichloroethenyl)-2,2-dimethylcyclopropane-1-carboxylate [(1R,3R,αS)-CP] induced the most significant changes in metabolic phenotypes than did the other stereoisomers. There are 10 differential metabolites (isoleucine, valine, leucine, ethanol, alanine, acetate, aspartate, arginine, lactate, and glucose) as well as two significantly disturbed pathways, including "pyruvate metabolism" and "alanine, aspartate, and glutamate metabolism," that were confirmed in H295R cells culture medium of (1R,3R,αS)-CP compared with other stereoisomers. Polymerase chain reaction (PCR) array also confirmed the results of metabolomics. Our results can help to understand the potential mechanisms between the isomer selectivity in metabolic phenotypes and endocrine-disrupting effects. Data provided here not only lend authenticity to the cautions issued by the scientists and researchers but also offer a solution for the balance between environment and political regulations.

Neuroprotective potential of Ayahuasca and untargeted metabolomics analyses: applicability to Parkinson's disease

ETHNOPHARMACOLOGY RELEVANCE

Ayahuasca is a tea produced through decoction of Amazonian plants. It has been used for centuries by indigenous people of South America. The beverage is considered to be an ethnomedicine, and it is traditionally used for the treatment of a wide range of diseases, including neurological illness. Besides, some scientific evidence suggests it may be applicable to Parkinson's disease (PD) treatment. Thus, Ayahuasca deserves in depth studies to clarify its potential role in this disease.

AIM OF THE STUDY

This study aimed to use an untargeted metabolomics approach to evaluate the neuroprotective potential of the Ayahuasca beverage, the extracts from its matrix plants (Banisteriopsis caapi and Psychotria viridis), its fractions and its main alkaloids on the viability of SH-SY5Y neuroblastoma cells in an in vitro PD model.

MATERIAL AND METHODS

The cytotoxicity of Ayahuasca, crude extracts, and fractions of B. caapi and P. viridis, as well as neuroprotection promoted by these samples in a 6-hydroxydopamine (6-OHDA)-induced neurodegeneration model, were evaluated by the MTT assay at two time-points: 48 h (T1) and 72 h (T2). The main alkaloids from Ayahuasca matrix plants, harmine (HRE) and N,N-dimethyltryptamine (DMT), were also isolated and evaluated. An untargeted metabolomics approach was developed to explore the chemical composition of samples with neuroprotective activity. Ultra-Performance Liquid Chromatography coupled to Electrospray Ionisation and Time-of-Flight (UPLC-ESI-TOF) metabolome data was treated and further analysed using multivariate statistical analyses (MSA): principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The metabolites were dereplicated using the Dictionary of Natural Products and an in house database. The main alkaloids were also quantified by UPLC-MS/MS.

RESULTS

The samples did not cause cytotoxicity in vitro and three of samples intensely increased cell viability at T1. The crude extracts, alkaloid fractions and HRE demonstrated remarkable neuroprotective effect at T2 while the hydroalcoholic fractions demonstrated this neuroprotective effect at T1 and T2. Several compounds from different classes, such as β-carbolines and monoterpene indole alkaloids (MIAs) were revealed correlated with this property by MSA. Additionally, a total of 2419 compounds were detected in both ionisation modes. HRE showed potent neuroprotective action at 72 h, but it was not among the metabolites positively correlated with the most efficacious neuroprotective profile at either time (T1 and T2). Furthermore, DMT was statistically important to differentiate the dataset (VIP value > 1), although it did not exhibit sufficient neuroprotective activity by in vitro assay, neither a positive correlation with T1 and T2 neuroprotective profile, which corroborated the MSA results.

CONCLUSION

The lower doses of the active samples stimulated neuronal cell proliferation and/or displayed the most efficacious neuroprotection profile, namely by preventing neuronal damage and improving cell viability against 6-OHDA-induced toxicity. Intriguingly, the hydroalcoholic fractions exhibited enhanced neuroprotective effects when compared to other samples and isolated alkaloids. This finding corroborates the significance of a holistic approach. The results demonstrate that Ayahuasca and its base plants have potential applicability for PD treatment and to prevent its progression differently from current drugs to treat PD.

Simultaneous Quantitative Analysis of Q-Marker with One Single Reference in Glycyrrhiza uralensis Fisch

In traditional Chinese medicine (TCM) studies, it is difficult to choose evaluation markers for the strict quality control of herbs. A high performance liquid chromatography coupled with metabolomics for simultaneous quantitative analysis of quality markers (Q-markers) in Glycyrrhiza uralensis Fisch was established, which could not only ensure the quality and batch-to-batch consistency of TCMs, but also achieve a quantitative analysis of multi-components by the single reference standard. Based on the construction of chromatographic profiles by high performance liquid chromatography (HPLC) and HPLC-Q-Exactive/MS methods, different multivariate analyses were employed. Seven quantitative indices were selected as the Q-markers, and a reliable quantification method was established. The quantitative method was acceptable with good linearity with correlation coefficients >0.9993 and satisfactory repeatability (relative standard deviation (RSD) < 0.05%), precision (RSD < 0.24%), reproducibility (RSD < 0.97%), stability (RSD < 2.52%) and recoveries (96.96%-98.52%, RSD < 3.24%), and no significant differences were observed between the external standard method and the new method as determined by calculating standard method difference. Overall, the study suggests that the simultaneous quantitative analysis of main Q-marker in G. uralensis Fisch with one single marker can be considered good quality criteria for performing quality control of G. uralensis Fisch.

Relations of prediabetes and type 2 diabetes to the thyroid cancer

OBJECTIVE

Patients with type 2 diabetes (T2DM) generally experience a higher incidence of cancer. However, the association between T2DM and thyroid cancer is inconclusive.

METHODS

Case-control prospective study, 722 patients were screened for T2DM and prediabetes (PDM) and underwent thyroid ultrasound and biochemical tests. The patients were assigned to groups of PDM (n=55), T2DM (n=79) or a non-diabetes group (NDM) (n=588). Fine needle aspiration biopsy was carried out in 263 patients. Histological examinations were done for 109 patients after surgery, with findings of 52 benign (BS) and 57 malignant tumors (MS).

RESULTS

33 % of patients with T2DM and especially PDM were newly diagnosed by our screening: 6.5 % with T2DM and 72 % with PDM, respectively. The percentage of thyroid cancers did not significantly differ between the groups (χ2 test=0.461; p=0.794). Relevant positive thyroid predictors for T2DM (t-statistic=25.87; p<0.01) and PDM (21.69; p<0.01) contrary to NDM (-26.9; p<0.01) were thyroid volume (4.79; p<0.01), thyroid nodule volume (3.25; p<0.01) and multinodular thyroid gland (4.83; p<0.01), while negative relevant predictors included the occurrence of autoimmune thyroid disease (AITD) (-2.01; p<0.05).

CONCLUSION

In general, we did not observe an increased risk for thyroid cancer in the diabetic and prediabetic groups in comparison to controls, in spite of well-established increased risk for other malignancies. Structural and benign changes such as larger and multinodular thyroid glands, in comparison to autoimmune thyroid disease, are present more often in diabetics.

Metabolic Variations between Low-Grade and High-Grade Gliomas-Profiling by 1H NMR Spectroscopy

Altered cellular metabolism is one of the crucial hallmarks of glioma that deserves exploration, as the metabolites act as direct indicators of protein function and genetic variations. The current study focused on the metabolomic profiling of patients from whom glioma specimens were obtained for the identification of specific metabolites that could distinguish the low grade and high grade. In the current study, ¹H NMR spectroscopy was carried out and the data were analyzed by partial least-squares discriminant analysis (PLS-DA) and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). Pathway analysis was done to associate characteristic metabolites with the grades of sample using MetaboAnalyst 4.0 software based on the KEGG metabolic pathways database. Distinctive metabolic profiles among low- and high-grade gliomas with top 15 characteristic metabolites that could discriminate these grades were identified on the basis of their VIP scores from the OPLS-DA model. The major altered metabolic pathways include choline, taurine and hypotaurine, glutamate/glutamine, glutathione, and phenyl alanine/tyrosine, which were found to be consistent with the particular grade of a sample. Our study clearly demonstrated a characteristic metabolic profile of individual grades of glioma, suggesting that an altered metabolism is consistent with the specific grades of glioma appreciation and could lead to the development novel treatment strategies.

Serum metabolic signatures of high myopia among older Chinese adults

PURPOSE

High myopia is associated with blinding ocular morbidities. Identifying novel biomarkers may provide clues on pathogenic pathways that are currently unknown. We aimed to identify serum metabolic biomarkers and investigate the metabolic alterations in relation to high myopia.

METHODS

Forty adults with high myopia and 40 with low myopia aged 60 years or older from the Weitang Geriatric Diseases study were included in the case-control study. Refractive error was determined by autorefraction followed by subjective refraction. We performed the metabolomic analysis of serum samples from patients with high myopia and age- and sex- matched controls with low myopia, using a nontargeted gas chromatography coupled to time-of-flight mass spectrometer. The area under the receiver operating characteristic curve (AUC) was computed to assess the discrimination capacities of each metabolite marker. Databases including KEGG and MetaboAnalyst were utilized to search for the potential pathways of metabolites.

RESULTS

Serum metabolomic profiles could well distinguish high myopia from low myopia. Twenty metabolic biomarkers were identified as potential serum biomarkers for high myopia, yielding AUC values of 0.59-0.71. Metabolic pathways in relation to high myopia, mainly characterized by increased energy metabolism, increased oxidative stress, abnormal amino acid metabolism, and altered biotin metabolism, provide a foundation to support myopia progression.

CONCLUSIONS

This study identified valuable metabolic biomarkers and pathways that may facilitate an improved understanding of the disease pathogenesis. The finding holds translational value in the development of new therapeutic measures for high myopia-related complications.

Differential metabolic markers associated with primary open-angle glaucoma and cataract in human aqueous humor

Background

We aimed to identify metabolic biomarkers and investigate the metabolic alterations in relation to primary open-angle glaucoma (POAG) and cataract in human aqueous humor.

Methods

Sixteen POAG patients undergoing surgical treatments and 24 patients undergoing cataract surgeries were included in this case-control study. We performed the metabolomic analysis of aqueous humor samples using a non-targeted gas chromatography coupled to time-of-flight mass spectrometer. The area under the receiver operating characteristic curve (AUC) was computed to assess the discrimination capacities of each metabolite marker. Databases including the Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaboAnalyst were utilized to search for the potential pathways of metabolites.

Results

Aqueous humor metabolomic profiles could well distinguish POAG from controls. Fourteen metabolic biomarkers were identified as potential aqueous humor biomarkers for POAG, yielding AUC values from 0.62 to 0.86. In pathway analysis, Biotin metabolism was highly impacted, implying that these metabolic markers play important roles in the regulation of this pathway.

Conclusions

This study identified valuable metabolic biomarkers and pathways that may facilitate an improved understanding of the POAG pathogenesis. The finding holds translational value in the development of new therapeutic measures for POAG.

Study on the dynamic changes and formation pathways of metabolites during the fermentation of black waxy rice wine

Black waxy rice wine fermentation metabolites are closely related to the product's final quality. However, little is known about dynamic metabolite changes during fermentation. Here, we used gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) metabolomics and multivariate statistical analysis to explore the relationship between metabolites and fermentation time. A total of 159 metabolites were identified during the entire fermentation process. The PCA analysis revealed a clear separation between the samples after 4 days and 2 days, and the samples after 4-24 days clustered together. This indicated that BGRW fermentation progresses rapidly in the first 48 hr of fermentation. A total of 40 metabolites were identified as differential during fermentation (VIP > 1 and p < .05), including 12 organic acids, four amino acids, one fatty acid, 17 sugars and sugar alcohols, one alcohol, and five other metabolites. Pathway analysis showed that the differential metabolites were involved in 28 metabolic pathways, and the most commonly influenced pathways (impact value > 0.1 and p < .05) were galactose metabolism, pyruvate metabolism; starch and sucrose metabolism; alanine, aspartic acid, and glutamate metabolism; the tricarboxylic acid cycle, glyoxylic acid, and dicarboxylic acid metabolism; and amino sugar and nucleotide sugar metabolism. Moreover, the integrated metabolic pathway was generated to understand the transformation and accumulation of differential metabolites. Overall, these results provide a comprehensive overview of metabolite changes during black waxy rice wine fermentation.

A biochemical comparison of the lung, colonic, brain, renal, and ovarian cancer cell lines using 1H-NMR spectroscopy

Cancer cell lines are often used for cancer research. However, continuous genetic instability-induced heterogeneity of cell lines can hinder the reproducibility of cancer research. Molecular profiling approaches including transcriptomics, chromatin modification profiling, and proteomics are used to evaluate the phenotypic characteristics of cell lines. However, these do not reflect the metabolic function at the molecular level. Metabolic phenotyping is a powerful tool to profile the biochemical composition of cell lines. In the present study, 1H-NMR spectroscopy-based metabolic phenotyping was used to detect metabolic differences among five cancer cell lines, namely, lung (A549), colonic (Caco2), brain (H4), renal (RCC), and ovarian (SKOV3) cancer cells. The concentrations of choline, creatine, lactate, alanine, fumarate and succinate varied remarkably among different cell types. The significantly higher intracellular concentrations of glutathione, myo-inositol, and phosphocholine were found in the SKOV3 cell line relative to other cell lines. The concentration of glutamate was higher in both SKOV3 and RCC cells compared with other cell lines. For cell culture media analysis, isopropanol was found to be the highest in RCC media, followed by A549 and SKOV3 media, while acetone was the highest in A549, followed by RCC and SKOV3. These results demonstrated that 1H-NMR-based metabolic phenotyping approach allows us to characterize specific metabolic signatures of cancer cell lines and provides phenotypical information of cellular metabolism.

The biochemical and metabolic profiles of dairy cows with mycotoxins-contaminated diets

BACKGROUND

Previous studies on the effects of mycotoxins have solely focused on their biochemical profiles or products in dairy ruminants. Changes in metabolism that occur after exposure to mycotoxins, as well as biochemical changes, have not been explored.

METHODS

We measured the biochemical and metabolic changes in dairy cows after exposure to mycotoxins using biochemical analyses and nuclear magnetic resonance. Twenty-four dairy cows were randomly assigned to three different treatment groups. Control cows received diets with 2 kg uncontaminated cottonseed. Cows in the 50% replacement group received the same diet as the control group, but with 1 kg of uncontaminated cottonseed and 1 kg of cottonseed contaminated with mycotoxins. Cows in the 100% replacement group received the same diet as the control, but with 2 kg contaminated cottonseed.

RESULTS

The results showed that serum γ-glutamyl transpeptidase and total antioxidant capacities were significantly affected by cottonseed contaminated with mycotoxins. There were also significant differences in isovalerate and NH3-N levels, and significant differences in the eight plasma metabolites among the three groups. These metabolites are mainly involved in amino acid metabolism pathways. Therefore, the results suggest that amino acid metabolism pathways may be affected by mycotoxins exposure.

Integration analysis of metabolites and single nucleotide polymorphisms improves the prediction of drug response of celecoxib

INTRODUCTION

Pharmacogenetics and pharmacometabolomics are the common methods for personalized medicine, either genetic or metabolic biomarkers have limited predictive power for drug response.

OBJECTIVES

In order to better predict drug response, the study attempted to integrate genetic and metabolic biomarkers for drug pharmacokinetics prediction.

METHODS

The study chose celecoxib as study object, the pharmacokinetic behavior of celecoxib was assessed in 48 healthy volunteers based on UPLC-MS/MS platform, and celecoxib related single nucleotide polymorphisms (SNPs) were also detected. Three mathematic models were constructed for celecoxib pharmacokinetics prediction, the first one was mainly based on celecoxib-related SNPs; the second was based on the metabolites selected from a pharmacometabolomic analysis by using GC-MS/MS method, the last model was based on the combination of the celecoxib-related SNPs and metabolites above.

RESULTS

The result proved that the last model showed an improved prediction power, the integration model could explain 71.0% AUC variation and predict 62.3% AUC variation. To facilitate clinical application, ten potential celecoxib-related biomarkers were further screened, which could explain 68.3% and predict 54.6% AUC variation, the predicted AUC was well correlated with the measured values (r = 0.838).

CONCLUSION

This study provides a new route for personalized medicine, the integration of genetic and metabolic biomarkers can predict drug response with a higher accuracy.

Lipidomic identification of plasma lipids associated with pain behaviour and pathology in a mouse model of osteoarthritis

INTRODUCTION

Osteoarthritis (OA) is the most common form of joint disease, causing pain and disability. Previous studies have demonstrated the role of lipid mediators in OA pathogenesis.

OBJECTIVES

To explore potential alterations in the plasma lipidomic profile in an established mouse model of OA, with a view to identification of potential biomarkers of pain and/or pathology.

METHODS

Pain behaviour was assessed following destabilisation of the medial meniscus (DMM) model of OA (n = 8 mice) and compared to sham controls (n = 7). Plasma and knee joints were collected at 16 weeks post-surgery. Plasma samples were analysed using ultra-high performance liquid chromatography accurate mass high resolution mass spectrometry (UHPLC-HR-MS) to identify potential differences in the lipidome, using multivariate and univariate statistical analyses. Correlations between pain behaviour, joint pathology and levels of lipids were investigated.

RESULTS

24 lipids, predominantly from the lipid classes of cholesterol esters (CE), fatty acids (FA), phosphatidylcholines (PC), N-acylethanolamines (NAE) and sphingomyelins (SM), were differentially expressed in DMM plasma compared to sham plasma. Six of these lipids which were increased in the DMM model were identified as CE(18:2), CE(20:4), CE(22:6), PC(18:0/18:2), PC(38:7) and SM(d34:1). CEs were positively correlated with pain behaviour and all six lipid species were positively correlated with cartilage damage. Pathways shown to be involved in altered lipid homeostasis in OA were steroid biosynthesis and sphingolipid metabolism.

CONCLUSION

We identify plasma lipid species associated with pain and/or pathology in a DMM model of OA.

Metabolic phenotyping to monitor chronic enteritis canceration

INTRODUCTION

Colorectal cancer (CRC) remains an incurable disease. Previous metabolomic studies show that metabolic signatures in plasma distinguish CRC patients from healthy controls. Chronic enteritis (CE) represents a risk factor for CRC, with a 20 fold greater incidence than in healthy individuals. However, no studies have performed metabolomic profiling to investigate CRC biomarkers in CE.

OBJECTIVE

Our aims were to identify metabolomic signatures in CRC and CE and to search for blood-derived metabolite biomarkers distinguishing CRC from CE, especially early-stage biomarkers.

METHODS

In this case-control study, 612 subjects were prospectively recruited between May 2015 and May 2016, and including 539 CRC patients (stage I, 102 cases; stage II, 259 cases; stage III, 178 cases) and 73 CE patients. Untargeted metabolomics was performed to identify CRC-related metabolic signatures in CE.

RESULTS

Five pathways were significantly enriched based on 153 differential metabolites between CRC and CE. 16 biomarkers were identified for diagnosis of CRC from CE and for guiding CRC staging. The AUC value for CRC diagnosis in the external validation set was 0.85. Good diagnostic performances were also achieved for early-stage CRC (stage I and stage II), with an AUC value of 0.84. The biomarker panel could also stage CRC patients, with an AUC of 0.72 distinguishing stage I from stage II CRC and AUC of 0.74 distinguishing stage II from stage III CRC.

CONCLUSIONS

The identified metabolic biomarkers exhibit promising properties for CRC monitoring in CE patients and are superior to commonly used clinical biomarkers (CEA and CA19-9).

Metabolomics analysis identifies lysine and taurine as candidate prognostic biomarkers for AML-M2 patients

There is an ongoing search for potential biomarkers for acute myeloid leukemia (AML) patients using metabolic analysis. However, only few studies to date have focused on bone marrow samples or a specific subtype of AML. In the present study, we used gas chromatography time-of-flight mass spectrometry of plasma and bone marrow supernatants to compare the metabolic characteristics of patients with AML with maturation (AML-M2). This approach identified significantly altered metabolites. We next performed pathway analysis and determined relative mRNA expression by qRT-PCR. Our results show that lysine, methionine and serine were significantly decreased in AML-M2 patients compared with healthy control. Moreover, plasma abundance of lysine was negatively associated with patients' risk stratification. Taurine had higher plasma abundance in AML-M2 patients and plasma level of taurine was positively related with AML-M2 risk status, while the expression level of taurine transporter showed a negative correlation. Receiver operating characteristic curve analysis showed these four metabolites had high diagnostic value with lysine showing the highest sensitivity and specificity. These results suggest that plasma abundances of lysine and taurine may serve as potential metabolic biomarkers for the prognosis of patients with AML-M2.

Seminal Fluid Metabolomic Markers of Oligozoospermic Infertility in Humans

Infertility affects 12–15% of couples worldwide, and male factors are the cause of nearly half of all cases. Studying seminal fluid composition could lead to additional diagnostic accuracy and a better understanding of the pathophysiology of male factor infertility. Metabolomics offers a new opportunity to evaluate biomarkers and better understand pathological mechanisms. The aim of the study was to identify new markers or therapeutic targets to improve outcomes in male factor or idiopathic infertility patients. Semen samples were obtained from 29 men with a normal spermogram test, and from 18 oligozoospermic men. Samples were processed and analyzed by Nuclear Magnetic Resonance spectroscopy and, subsequently, multivariate and univariate statistical analyses. Receiving Operator Curves (ROC) and Spearman correlations were also performed. An Orthogonal Partial Least Square Discriminant Analysis supervised multivariate model was devised to compare the groups. The levels of fructose, myo-inositol, aspartate and choline were altered. Moreover, Spearman Correlation associated fructose, aspartate and myo-inositol with the total amount of spermatozoa, total motile spermatozoa, % of immotility and % of “in situ” spermatozoic motility respectively. NMR-based metabolomics allowed the identification of a specific metabolic fingerprint of the seminal fluids of patients affected by oligozoospermia.

Early Human-Milk Metabolome in Cases of Intrauterine Growth-Restricted and Macrosomic Infants

BACKGROUND

Abnormal fetal growth is associated with short-term and long-term metabolic dysregulation and susceptibility to obesity-related disorders. Maternal milk, the ideal source of infantile nutrition, protects from metabolic diseases in adulthood. By applying nuclear magnetic resonance (NMR) metabolomics, this study investigated the metabolic profile of early human milk/colostrum (EHM/C) at the extremes of fetal-growth conditions, which could affect its nutritional value.

METHODS

From 98 mothers delivering 60 appropriate-for-gestational-age (AGA), 19 large-for-gestational-age (LGA), and 19 intrauterine growth-restricted (IUGR) full-term neonates, milk samples collected on the third to fourth day post partum were examined by NMR spectroscopy. Multivariate data analysis elicited information from NMR spectra and probed to metabolic signatures of EHM/C.

RESULTS

LGA and IUGR EHM/C samples depicted increased content in lactose, citric acid, choline, phosphocholine, and N-acetylglutamine. AGA samples exhibited increased isoleucine and valine. Metabolic pathways involved were valine, leucine/isoleucine biosynthesis and degradation, glycerophospholipid metabolism, aminoacyl-transfer RNA biosynthesis, and citrate cycle. Orthogonal projections to latent structures discriminant analysis models were validated.

CONCLUSION

This holistic metabolomics study framed an increased content of certain essential nutrients in EHM/C samples following the birth of LGA and IUGR infants prone to short- and long-term metabolic disorders, thus stressing additional benefits of early breastfeeding. Assessing the metabolic profile of EHΜ/C enables evaluation of its nutrition value, adjusted to fetal growth, and introduction of appropriate dietary interventions.

An NMR based panorama of the heterogeneous biology of acute respiratory distress syndrome (ARDS) from the standpoint of metabolic biomarkers

Acute respiratory distress syndrome (ARDS), manifested by intricate etiology and pathophysiology, demands careful clinical surveillance due to its high mortality and imminent life support measures. NMR based metabolomics provides an approach for ARDS which culminates from a wide spectrum of illness thereby confounding early manifestation and prognosis predictors. ¹ H NMR with its manifold applications in critical disease settings can unravel the biomarker of ARDS thus holding potent implications by providing surrogate endpoints of clinical utility. NMR metabolomics which is the current apogee platform of omics trilogy is contributing towards the possible panacea of ARDS by subsequent validation of biomarker credential on larger datasets. In the present review, the physiological derangements that jeopardize the whole metabolic functioning in ARDS are exploited and the biomarkers involved in progression are addressed and substantiated. The following sections of the review also outline the clinical spectrum of ARDS from the standpoint of NMR based metabolomics which is an emerging element of systems biology. ARDS is the main premise of intensivists textbook, which has been thoroughly reviewed along with its incidence, progressive stages of severity, new proposed diagnostic definition, and the preventive measures and the current pitfalls of clinical management. The advent of new therapies, the need for biomarkers, the methodology and the contemporary promising approaches needed to improve survival and address heterogeneity have also been evaluated. The review has been stepwise illustrated with potent biometrics employed to selectively pool out differential metabolites as diagnostic markers and outcome predictors. The following sections have been drafted with an objective to better understand ARDS mechanisms with predictive and precise biomarkers detected so far on the basis of underlying physiological parameters having close proximity to diseased phenotype. The aim of this review is to stimulate interest in conducting more studies to help resolve the complex heterogeneity of ARDS with biomarkers of clinical utility and relevance.

Mechanistic evaluation of gastro-protective effects of KangFuXinYe on indomethacin-induced gastric damage in rats

KangFuXinYe (KFX), the ethanol extract of the dried whole body of Periplaneta americana, is a well-known important Chinese medicine preparation that has been used to treat digestive diseases such as gastric ulcers for many years in China. However, its therapeutic effect and mechanism are not yet well understood. Thus, the aim of this study was to investigate the gastro-protective effects of KangFuXinYe (KFX) in indomethacin-induced gastric damage. Rats were randomly divided into six groups as follows: control, treated with indomethacin (35 mg·kg^-1), different dosages of KFX (2.57, 5.14 and 10.28 mL·kg^-1, respectively) plus indomethacin, and sucralfate (1.71 mL·kg^-1) plus indomethacin. After treatment, rat serum, stomach and gastric homogenates were collected for biochemical tests and examination of histopathology firstly. Rat serum was further used for metabolomics analysis to research possible mechanisms. Our results showed that KFX treatment alleviated indomethacin-induced histopathologic damage in rat gastric mucosa. Meanwhile, its treatment significantly increased cyclooxygenase-1 (COX-1), prostaglandin E₂ (PGE₂) and epidermal growth factor (EGF) levels in rat serum and gastric mucosa. Moreover, KFX decreased cyclooxygenase-2 (COX-2) and interleukin-6 (IL-6) levels. Nine metabolites were identified which intensities significantly changed in gastric damage rats, including 5-hydroxyindoleacetic acid, indoxylsulfuric acid, indolelactic acid, 4-hydroxyindole, pantothenic acid, isobutyryl carnitine, 3-methyl-2-oxovaleric acid, sphingosine 1-phosphate, and indometacin. These metabolic deviations came to closer to normal levels after KFX intervention. The results indicate that KFX (10.28 mL·kg^-1) exerts protective effects on indomethacin-induced gastric damage by possible mechanisms of action (regulating tryptophan metabolism, protecting the mitochondria, and adjusting lipid metabolism, and reducing excessive indomethacin).

Influence of Brevibacterium linens RS16 on foliage photosynthetic and volatile emission characteristics upon heat stress in Eucalyptus grandis

Heat stress induces secondary metabolic changes in plants, channeling photosynthetic carbon and energy, away from primary metabolic processes, including, growth. Use of ACC (1-aminocyclopropane-1-carboxylate) deaminase containing plant growth promoting bacteria (PGPB) in conferring heat resistance in plants and the role of PGPB, in altering net carbon assimilation, constitutive and stress volatile emissions has not been studied yet. We exposed leaves of Eucalyptus grandis inoculated and non-inoculated with PGPB Brevibacterium linens RS16 to two levels of heat stress (37 °C and 41 °C for 5 min) and quantified temporal changes in foliage photosynthetic characteristics and volatile emission rates at 0.5 h, day 1 and day 5 after the stress application. Heat stress resulted in immediate reductions in dark-adapted photosystem II (PSII) quantum yield (F_v/F_m), net assimilation rate (A), stomatal conductance to water vapor (g_s), and enhancement of stress volatile emissions, including enhanced emissions of green leaf volatiles (GLV), mono- and sesquiterpenes, light weight oxygenated volatile organic compounds (LOC), geranyl-geranyl diphosphate pathway volatiles (GGDP), saturated aldehydes, and benzenoids, with partial recovery by day 5. Changes in stress-induced volatiles were always less in leaves inoculated with B. linens RS16. However, net assimilation rate was enhanced by bacterial inoculation only in the 37 °C treatment and overall reduction of isoprene emissions was observed in bacterially-treated leaves. Principal component analysis (PCA), correlation analysis and partial least squares discriminant analysis (PLS-DA) indicated that different stress applications influenced specific volatile organic compounds. In addition, changes in the expression analysis of heat shock protein 70 gene (DnaK) gene in B. linens RS16 upon exposure to higher temperatures further indicated that B. linens RS16 has developed its own heat resistance mechanism to survive under higher temperature regimes. Taken together, this study demonstrates that foliar application of ACC deaminase containing PGPB can ameliorate heat stress effects in realistic biological settings.

Nanoparticle Conjugation of Ginsenoside Rg3 Inhibits Hepatocellular Carcinoma Development and Metastasis

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. The prognosis of HCC remains very poor; thus, an effective treatment remains urgent. Herein, a type of nanomedicine is developed by conjugating Fe@Fe₃ O₄ nanoparticles with ginsenoside Rg3 (NpRg3), which achieves an excellent coupling effect. In the dimethylnitrosamine-induced HCC model, NpRg3 application significantly prolongs the survival of HCC mice. Further research indicates that NpRg3 application significantly inhibits HCC development and eliminates HCC metastasis to the lung. Notably, NpRg3 application delays HCC-induced ileocecal morphology and gut microbial alterations more than 12 weeks during HCC progression. NpRg3 administration elevates the abundance of Bacteroidetes and Verrucomicrobia, but decreases Firmicutes. Twenty-nine predicted microbial gene functions are enriched, while seven gene functions are reduced after NpRg3 administration. Moreover, the metabolomics profile presents a significant progression during HCC development, but NpRg3 administration corrects tumor-dominant metabolomics. NpRg3 administration decreases 3-indolepropionic acid and urea, but elevates free fatty acids. Importantly, NpRg3 application remodels the unbalanced correlation networks between gut microbiota and metabolism during HCC therapy. In conclusion, nanoparticle conjugation of ginsenoside Rg3 inhibits HCC development and metastasis via the remodeling of unbalanced gut microbiota and metabolism in vivo, providing an antitumor therapy strategy.

Changes of BMI, steroid metabolome and psychopathology in patients with anorexia nervosa during hospitalization

Anorexia nervosa (AN) is associated with various alterations including the dysfunction of the HPA axis and consequently the hypercortisolemia and deficit in sex hormones but the comprehensive evaluation of changes in circulating steroids during the hospitalization of AN patients is lacking. We investigated the effect of realimentation of women with AN during hospitalization on 45 circulating steroids, the relationships between BMI, its change during hospitalization and physical activity, on one side and initial levels and their changes for two adipokines, circulating steroids, anorexia-specific (hunger, appetite and satiety), and anorexia non-specific symptoms (anxiety, depression fatigue, sleep, and body pain) on the other side. We included 33 women with anorexia who were hospitalized for 38(35, 44) days (median with quartiles). The increase of BMI from the initial value 15.2 (13.2, 16.6) kg/m² was 1.69 (1.37, 2.66) kg/m². The patients with more severe anorexia showed higher activity in 7β-, and 16α-hydroxylation of androgen precursors, which declined during hospitalization. Otherwise, the 7α-hydroxylation activity is higher in AN patients with less severe malnutrition and the ratio of 5-androstene-3β,7α,17β-triol to 5-androstene-3β,7β,17β-triol increased during the realimentation. Our data allow to speculate that the intensive 7β-, and 16α- and possibly also the 7α-hydroxylation of C19 Δ⁵ steroids participate in the pathophysiology of anorexia by additional catabolism of substrates available for synthesis of active androgens and estrogens. However, the question remains whether the synthetic analogues of 7α/β- and 16α-hydroxy-steroids prevent the catabolism of the sex steroid precursors, or further activate the "energy wasting" mitochondrial thermogenic metabolism.

Predicting and Defining Steroid Resistance in Pediatric Nephrotic Syndrome Using Plasma Metabolomics

INTRODUCTION

Nephrotic syndrome (NS) is a kidney disease that affects both children and adults. Glucocorticoids have been the primary therapy for >60 years but are ineffective in approximately 20% of children and approximately 50% of adult patients. Unfortunately, patients with steroid-resistant NS (SRNS; vs. steroid-sensitive NS [SSNS]) are at high risk for both glucocorticoid-induced side effects and disease progression.

METHODS

We performed proton nuclear magnetic resonance (1H NMR) metabolomic analyses on plasma samples (n = 86) from 45 patients with NS (30 SSNS and 15 SRNS) obtained at initial disease presentation before glucocorticoid initiation and after approximately 7 weeks of glucocorticoid therapy to identify candidate biomarkers able to either predict SRNS before treatment or define critical molecular pathways/targets regulating steroid resistance.

RESULTS

Stepwise logistic regression models identified creatinine concentration and glutamine concentration (odds ratio [OR]: 1.01; 95% confidence interval [CI]: 0.99-1.02) as 2 candidate biomarkers predictive of SRNS, and malonate concentration (OR: 0.94; 95% CI: 0.89-1.00) as a third candidate predictive biomarker using a similar model (only in children >3 years). In addition, paired-sample analyses identified several candidate biomarkers with the potential to identify mechanistic molecular pathways/targets that regulate clinical steroid resistance, including lipoproteins, adipate, pyruvate, creatine, glucose, tyrosine, valine, glutamine, and sn-glycero-3-phosphcholine.

CONCLUSION

Metabolomic analyses of serial plasma samples from children with SSNS and SRNS identified elevated creatinine and glutamine concentrations, and reduced malonate concentrations, as auspicious candidate biomarkers to predict SRNS at disease onset in pediatric NS, as well as additional candidate biomarkers with the potential to identify mechanistic molecular pathways that may regulate clinical steroid resistance.

Exploring Cancer Metabolism: Applications of Metabolomics and Metabolic Phenotyping in Cancer Research and Diagnostics

Altered metabolism is one of the key hallmarks of cancer. The development of sensitive, reproducible and robust bioanalytical tools such as Nuclear Magnetic Resonance Spectroscopy and Mass Spectrometry techniques offers numerous opportunities for cancer metabolism research, and provides additional and exciting avenues in cancer diagnosis, prognosis and for the development of more effective and personalized treatments. In this chapter, we introduce the current state of the art of metabolomics and metabolic phenotyping approaches in cancer research and clinical diagnostics.

FTICR mass spectrometry-based multivariate analysis to explore distinctive metabolites and metabolic pathways: A comprehensive bioanalytical strategy toward time-course metabolic profiling of Thymus vulgaris plants responding to drought stress

In this research, metabolic profiling/pathways of Thymus vulgaris (thyme) plant were assessed during a water deficit stress using an FTICR mass spectrometry-based metabolomics strategy incorporating multivariate data analysis and bioinformatics techniques. Herein, differences of MS signals in specific time courses after water deficit stress and control cases without any timing period were distinguished significantly by common pattern recognition techniques, i.e., PCA, HCA-Heatmap, and PLS-DA. Subsequently, the results were compared with supervised Kohonen neural network (SKN) ones as a non-linear data visualization and capable mapping tool. The classification models showed excellent performance to predict the level of drought stress. By assessing variances contribution on the PCA-loadings of the MS data, the discriminant variables related to the most critical metabolites were identified and then confirmed by ANOVA. Indeed, FTICR MS-based multivariate analysis strategy could explore distinctive metabolites and metabolic pathways/profiles, grouped into three metabolism categories including amino acids, carbohydrates (i.e., galactose, glucose, fructose, sucrose, and mannose), and other metabolites (rosmarinic acid and citrate), to indicate biological mechanisms in response to drought stress for thyme. It was achieved and approved through the MS signals, genomics databases, and transcriptomics factors to interpret and predict the plant metabolic behavior. Eventually, a comprehensive pathway analysis was used to provide a pathway enrichment analysis and explore topological pathway characteristics dealing with the remarkable metabolites to demonstrate that galactose metabolism is the most significant pathway in the biological system of thyme.

Analysis of NMR Metabolomics Data

In this chapter, we summarize data preprocessing and data analysis strategies used for analysis of NMR data for metabolomics studies. Metabolomics consists of the analysis of the low molecular weight compounds in cells, tissues, or biological fluids, and has been used to reveal biomarkers for early disease detection and diagnosis, to monitor interventions, and to provide information on pathway perturbations to inform mechanisms and identifying targets. Metabolic profiling (also termed metabotyping) involves the analysis of hundreds to thousands of molecules using mainly state-of-the-art mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy technologies. While NMR is less sensitive than mass spectrometry, NMR does provide a wealth of complex and information rich metabolite data. NMR data together with the use of conventional statistics, modeling methods, and bioinformatics tools reveals biomarker and mechanistic information. A typical NMR spectrum, with up to 64k data points, of a complex biological fluid or an extract of cells and tissues consists of thousands of sharp signals that are mainly derived from small molecules. In addition, a number of advanced NMR spectroscopic methods are available for extracting information on high molecular weight compounds such as lipids or lipoproteins. There are numerous data preprocessing, data reduction, and analysis methods developed and evolving in the field of NMR metabolomics. Our goal is to provide an extensive summary of NMR data preprocessing and analysis strategies by providing examples and open source and commercially available analysis software and bioinformatics tools.

Phenyl-γ-valerolactones and phenylvaleric acids, the main colonic metabolites of flavan-3-ols: synthesis, analysis, bioavailability, and bioactivity

Covering: 1958 to June 2018 Phenyl-γ-valerolactones (PVLs) and their related phenylvaleric acids (PVAs) are the main metabolites of flavan-3-ols, the major class of flavonoids in the human diet. Despite their presumed importance, these gut microbiota-derived compounds have, to date, in terms of biological activity, been considered subordinate to their parent dietary compounds, the flavan-3-ol monomers and proanthocyanidins. In this review, the role and prospects of PVLs and PVAs as key metabolites in the understanding of the health features of flavan-3-ols have been critically assessed. Among the topics covered, are proposals for a standardised nomenclature for PVLs and PVAs. The formation, bioavailability and pharmacokinetics of PVLs and PVAs from different types of flavan-3-ols are discussed, taking into account in vitro and animal studies, as well as inter-individual differences and the existence of putative flavan-3-ol metabotypes. Synthetic strategies used for the preparation of PVLs are considered and the methodologies for their identification and quantification assessed. Metabolomic approaches unravelling the role of PVLs and PVAs as biomarkers of intake are also described. Finally, the biological activity of these microbial catabolites in different experimental models is summarised. Knowledge gaps and future research are considered in this key area of dietary (poly)phenol research.

NMR-based fragment screening and lead discovery accelerated by principal component analysis

Protein-based NMR spectroscopy has proven to be a very robust method for finding fragment leads to protein targets. However, one limitation of protein-based NMR is that the data acquisition and analysis can be time consuming. In order to streamline the scoring of protein-based NMR fragment screening data and the determination of ligand affinities using 2D NMR experiments we have developed a data analysis workflow based on principal component analysis (PCA) within the TREND NMR Pro software package. We illustrate this using four different proteins and sets of ligands which interact with these proteins over a range of affinities. Also, these PCA-based methods can be successfully applied even to systems where ligand binding to target proteins is in intermediate or even slow exchange on the NMR time scale. Finally, these methods will work for scoring of fragment binding data using protein spectra that are either highly overlapped or lower in resolution.

The progressive alteration of urine metabolomic profiles of rats following long-term and low-dose exposure to permethrin

Background: Permethrin is a type of widely used pyrethroid pesticide. Although acute toxicity of permethrin has been well-characterised, the non-acute toxicity of permethrin upon long-term exposure at low dose has been seldom studied yet. The current study investigates the time-course change of the metabolomic profiles of urine following the low level long-term exposure of permethrin and identified biomarkers of the chronic toxicity of permethrin.Methods: Male Wistar rats were administrated orally with permethrin (75 mg/kg body weight/day, 1/20 LD₅₀) daily for consecutive 90 days. The urine samples from day 30, day 60, and day 90 after the first dosing were collected and analysed by ¹H NMR spectrometry. Serum biochemical analysis was also carried out.Results: Permethrin caused significant changes in the urine metabolites such as taurine, creatinine, acetate, lactate, dimethylamine, dimethylglycine, and trimethylamine-N-oxide. These biological markers indicated prominent kidney and liver toxicity induced by permethrin. However, there was no change in serum biochemical parameters for the toxicity, indicating that metabolomic approach was much more sensitive in detecting the chronic toxicity.Conclusion: The time-course alteration of metabolomic profiles of the urine based on ¹H NMR reflects the progressive development of the chronic toxicity with the long-term low-level exposure of permethrin.

Identification and Validation of Plasma Metabolomics Reveal Potential Biomarkers for Coronary Heart Disease

Coronary heart disease (CHD) is a prevalent and chronic life-threatening disease. However, there is no reliable way for early diagnosis and prevention of CHD so far. The precise molecular pathological mechanism of CHD remains obscure. Therefore, developing novel biomarkers is urgently needed.In order to evaluate the potential of untargeted plasma metabolomics in biomarker discovery for characterizing CHD, plasma metabolites from patients newly diagnosed with CHD and controls were profiled using liquid chromatography quadrupole time-of-flight mass spectrometry. Differential metabolites were identified using both univariate and multivariate statistical analyses. Metabolites with significant changes were subjected to binary logistic regression analysis, and a CHD prediction model was established. A total of 28 differential plasma metabolites were identified, of which the concentrations of 11 increased significantly and those of 17 decreased significantly in patients with CHD compared with controls. The altered metabolic pathways included reduced phospholipid metabolism, increased monoglyceride metabolism, and abnormal fatty acid metabolism. Furthermore, binary logistic regression showed that nine metabolites could be used as potential plasma biomarkers for the diagnosis of CHD. The prediction model based on these nine metabolites was then tested with an independent cohort of samples (area under the curve = 0.929).Our plasma metabolomics study not only yielded fundamental insights into dysregulated metabolism in CHD but also presented a combinatorial biomarker that might support the clinical diagnosis of CHD.

Rutin, γ-Aminobutyric Acid, Gallic Acid, and Caffeine Negatively Affect the Sweet-Mellow Taste of Congou Black Tea Infusions

The sweet-mellow taste sensation is a unique and typical feature of premium congou black tea infusions. To explore the key taste-active compounds that influence the sweet-mellow taste, a sensory and molecular characterization was performed on thirty-three congou black tea infusions presenting different taste qualities, including the sweet-mellow, mellow-pure, or less-mellow taste. An integrated application of quantitative analysis of 48 taste-active compounds, taste contribution analysis, and further validation by taste supplementation experiments, combined with human sensory evaluation revealed that caffeine, γ-aminobutyric acid, rutin, succinic acid, citric acid, and gallic acid negatively affect the sweet-mellow taste, whereas glucose, sucrose, and ornithine positively contribute to the sweet-mellow taste of congou black tea infusions. Particularly, rutin, γ-aminobutyric acid, gallic acid, and caffeine, which impart the major inhibitory effect to the manifestation of the sweet-mellow taste, were identified as the key influencing components through stepwise screening and validation experiments. A modest level of these compounds was found to be favorable for the development and manifestation of the sweet-mellow taste. These compounds might potentially serve as the regulatory targets for oriented-manufacturing of high-quality sweet-mellow congou black tea.

Time-Course Changes in Urine Metabolic Profiles of Rats Following 90-Day Exposure to Propoxur

As a major kind of carbamate insecticide, propoxur plays an important role in agriculture, veterinary medicine, and public health. The acute toxicity of propoxur is mainly neurotoxicity due to the inhibition of cholinesterase. However, little is known regarding the toxicity of propoxur upon long-term exposure at low dose. In this study, Wistar rats were orally administrated with low dose (4.25 mg/kg body weight/day) for consecutive 90 days. And the urine samples in rats treated with propoxur for 30, 60, and 90 days were collected and analyzed by employing ¹H NMR-based metabolomics approach. We found that propoxur caused significant changes in the urine metabolites, including taurine, creatinine, citrate, succinate, dimethylamine, and trimethylamine-N-oxide. And the alteration of the metabolites was getting more difference compared with that of the control as the exposure time extending. The present study not only indicated that the changed metabolites could be used as biomarkers of propoxur-induced toxicity but also suggested that the time-course alteration of the urine metabolomic profiles could reflect the progressive development of the toxicity following propoxur exposure.

Effects of honey-extracted polyphenols on serum antioxidant capacity and metabolic phenotype in rats

It is generally known that honey polyphenols have antioxidant capacity and numerous biological functions. However, their metabolic phenotype after digestion has not been studied. In this study, the effects of honey-extracted polyphenols (HEPs) on serum antioxidant capacity and metabolic phenotype were revealed for the first time. Herein, sixteen male Sprague-Dawley rats were randomly divided into two groups: one group was administered HEPs (200 mg per kilogram body weight dose) and the other group was fed distilled water three times. Then, 1 h after the last gavage, the metabolic profiling of serum was analyzed by UHPLC-Orbitrap-HRMS and multivariate statistical analysis, and the following results were obtained. At first, twenty-five metabolites, including polyphenols, unsaturated fatty acids, and amino acids, were selected as potential biomarkers. Then, metabolic pathway analysis showed that several amino acid metabolism pathways, ubiquinone and other terpenoid-quinone biosynthesis, arachidonic acid metabolism, nicotinate and nicotinamide metabolism, and inositol phosphate metabolism were affected. Association analysis demonstrated that the alteration of metabolites may be responsible for the increased serum antioxidant capacity. This new insight into the effects on the metabolic phenotype after HEP intake prompted the study on the biological functions and emerging health benefits of HEPs.

Metabolic profiling of cold adaptation of a deep-sea psychrotolerant Microbacterium sediminis to prolonged low temperature under high hydrostatic pressure

The most wide-spread "hostile" environmental factor for marine microorganisms is low temperature, which is usually accompanied by high hydrostatic pressure (HHP). Metabolic mechanisms of marine microorganisms adapting to prolonged low temperature under HHP remain to be clarified. To reveal the underlying metabolic mechanisms, we performed NMR-based metabolomic analysis of aqueous extracts derived from a psychrotolerant Microbacterium sediminis YLB-01, which was isolated from deep-sea sediment and possess great biotechnology potentials. The YLB-01 cells were firstly cultivated at the optimal condition (28 °C, 0.1 MPa) for either 18 h (logarithmic phase) or 24 h (stationary phase), then continually cultivated at either 28 °C or 4 °C under HHP (30 MPa) for 7 days. The cells cultivated at low temperature, which experienced cold stress, were distinctly distinguished from those at normal temperature. Cold stress primarily induced metabolic changes in amino acid metabolism and carbohydrate metabolism. Furthermore, the logarithmic and stationary phase cells cultivated at low temperature exhibited distinct metabolic discrimination, which was mostly reflected in the significantly disturbed carbohydrate metabolism. The logarithmic phase cells displayed suppressed TCA cycle, while the stationary phase cells showed decreased pyruvate and increased lactate. In addition, we performed transcriptome analysis for the stationary phase cells to support the metabolomic analysis. Our results suggest that the cold adaptation of the psychrotroph YLB-01 is closely associated with profoundly altered amino acid metabolism and carbohydrate metabolism. Our work provides a mechanistic understanding of the metabolic adaptation of marine psychrotrophs to prolonged low temperature under HHP.

Postoperative serum metabolites of patients on a low carbohydrate ketogenic diet after pancreatectomy for pancreatobiliary cancer: a nontargeted metabolomics pilot study

A ketogenic diet is a potential adjuvant cancer therapy that limits glucose availability to tumours while fuelling normal tissues with ketone bodies. We examined the effect of a low carbohydrate ketogenic diet (LCKD) (80% kcal from fat, ketogenic ratio 1.75:1, w/w) compared to a general hospital diet (GD) on serum metabolic profiles in patients (n = 18, ≥ 19 years old) who underwent pancreatectomy for pancreatobiliary cancer. Serum samples collected preoperatively (week 0) and after the dietary intervention (week 2) were analysed with a nontargeted metabolomics approach using liquid chromatography-tandem mass spectrometry. Serum β-hydroxybutyrate and total ketone levels significantly increased after 2 weeks of LCKD compared to GD (p < 0.05). Principal component analysis score plots and orthogonal partial least squares discriminant analysis also showed significant differences between groups at week 2, with strong validation. In all, 240 metabolites differed between LCKD and GD. Pathways including glycerophospholipid and sphingolipid metabolisms were significantly enriched in the LCKD samples. LCKD decreased C22:1-ceramide levels, which are reported to be high in pancreatic cancer, while increasing lysophosphatidylcholine (18:2), uric acid, citrulline, and inosine levels, which are generally low in pancreatic cancer. Postoperative LCKD might beneficially modulate pancreatic cancer-related metabolites in patients with pancreatobiliary cancer.

A Metabolomic Approach for the In Vivo Study of Gold Nanospheres and Nanostars after a Single-Dose Intravenous Administration to Wistar Rats

Gold nanoparticles (AuNPs) are promising nanoplatforms for drug therapy, diagnostic and imaging. However, biological comparison studies for different types of AuNPs fail in consistency due to the lack of sensitive methods to detect subtle differences in the expression of toxicity. Therefore, innovative and sensitive approaches such as metabolomics are much needed to discriminate toxicity, specially at low doses. The current work aims to compare the in vivo toxicological effects of gold nanospheres versus gold nanostars (of similar ~40 nm diameter and coated with 11-mercaptoundecanoic acid) 24 h after an intravenous administration of a single dose (1.33 × 10¹¹ AuNPs/kg) to Wistar rats. The biodistribution of both types of AuNPs was determined by graphite furnace atomic absorption spectroscopy. The metabolic effects of the AuNPs on their main target organ, the liver, were analyzed using a GC-MS-based metabolomic approach. Conventional toxicological endpoints, including the levels of ATP and reduced and oxidized glutathione, were also investigated. The results show that AuNPs preferentially accumulate in the liver and, to a lesser extent, in the spleen and lungs. In other organs (kidney, heart, brain), Au content was below the limit of quantification. Reduced glutathione levels increased for both nanospheres and nanostars in the liver, but ATP levels were unaltered. Multivariate analysis showed a good discrimination between the two types of AuNPs (sphere- versus star-shaped nanoparticles) and compared to control group. The metabolic pathways involved in the discrimination were associated with the metabolism of fatty acids, pyrimidine and purine, arachidonic acid, biotin, glycine and synthesis of amino acids. In conclusion, the biodistribution, toxicological, and metabolic profiles of gold nanospheres and gold nanostars were described. Metabolomics proved to be a very useful tool for the comparative study of different types of AuNPs and raised awareness about the pathways associated to their distinct biological effects.

LC-MS-based metabolomics analysis of Berberine treatment in ulcerative colitis rats

Inflammatory bowel disease (IBD) is often accompanied by metabolic imbalance and Berberine can relieve the symptoms of IBD, but the mechanism is still unclear. To explore the relationship between IBD, metabolism and Berberine, dextran sulfate sodium-induced ulcerative colitis (UC) model was built and urine and feces samples were analyzed with ultra-performance liquid chromatography combined with quadrupole-time-of-flight mass spectrometry, followed by multivariate statistical analyses. Targeted metabolomics was applied to verify and supplement the result of amino acids tested by non-targeted metabolomics. The study found that Berberine could ameliorate UC and improve metabolic disorders. The level of 4 metabolites increased and 35 decreased in urine and these metabolites mainly belong to amino acid, glucide, organic acid and purine. Besides, Berberine could reduce the level of 5 metabolites and raise the level of 7 metabolites in feces, which mainly belong to amino acid and lipid. Additionally, these altered metabolites were mainly related to amino acids metabolism, purine metabolism, vitamin metabolism, lipid metabolism and citrate cycle pathways. Furthermore, microbiome metabolism may be regulated by Berberine in UC. In general, this study provides a useful approach for exploring the mechanism of Berberine in the treatment of UC from the perspective of metabolomics.

Metabolomics strategies to discover new biomarkers associated to severe allergic phenotypes

In the last decades have emerged new technological platforms that allow evaluation of genes, transcripts, proteins, or metabolites of a living being, so-called omics sciences. More importantly, new technics for their integration have provided access to a complete set of information of the current conditions and features of a specific biological sample in a precise moment. Thus, omic sciences are now considered an essential tool for patient stratification in base to their severity, to understand disease progression and to identify new biomarkers. Severe patients, that are out of control, provide an excellent model to understand disease evolution and to identify new intervention and biomarkers strategies. Here we discuss the use of metabolomics to understand severity in allergic diseases in a strategy that opens new insights as well as identify new biological systems relevant for allergy progression. Metabolomics strategies are based in parallel evaluation of different allergy severity models by mean of untargeted analysis that allows the identification of potential biomarkers. Overlapping of different biomarkers in multiple models, provides information of general as well as specific biological systems involved in each model. Later a selected panel of biomarkers will be used in a target method to explore the diagnosis potential to stratify allergic patients.

Metabolic profiles of serum samples from ground glass opacity represent potential diagnostic biomarkers for lung cancer

Background

Lung cancer is a leading cause of cancer deaths worldwide. Low-dose computed tomography (LDCT) screening trials indicated that LDCT is effective for the early detection of lung cancer, but the findings were accompanied by high false positive rates. Therefore, the detection of lung cancer needs complementary blood biomarker tests to reduce false positive rates.

Methods

In order to evaluate the potential of metabolite biomarkers for diagnosing lung cancer and increasing the effectiveness of clinical interventions, serum samples from subjects participating in a low-dose CT-scan screening were analyzed by using untargeted liquid chromatography-hybrid quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS). Samples were acquired from 34 lung patients with ground glass opacity diagnosed lung cancer and 39 healthy controls.

Results

In total, we identified 9 metabolites in electron spray ionization (ESI)(+) mode and 7 metabolites in ESI(-) mode. L-(+)-gulose, phosphatidylethanolamine (PE)(22:2(13Z,16Z)/15:0), cysteinyl-glutamine, S-japonin, threoninyl-glutamine, chlorate, 3-oxoadipic acid, dukunolide A, and malonic semialdehyde levels were observed to be elevated in serum samples of lung cancer cases when compared to those of healthy controls. By contrast, 1-(2-furanylmethyl)-1H-pyrrole, 2,4-dihydroxybenzoic acid, monoethyl carbonate, guanidinosuccinic acid, pseudouridine, DIMBOA-Glc, and 4-feruloyl-1,5-quinolactone levels were lower in serum samples of lung cancer cases compared with those of healthy controls.

Conclusions

This study demonstrates evidence of early metabolic alterations that can possibly distinguish malignant ground glass opacity from benign ground glass opacity. Further studies in larger pools of samples are warranted.

Unravelling the Metabolic Reconfiguration of the Post-Challenge Primed State in Sorghum bicolor Responding to Colletotrichum sublineolum Infection

Priming is a natural phenomenon that pre-conditions plants for enhanced defence against a wide range of pathogens. It represents a complementary strategy, or sustainable alternative that can provide protection against disease. However, a comprehensive functional and mechanistic understanding of the various layers of priming events is still limited. A non-targeted metabolomics approach was used to investigate metabolic changes in plant growth-promoting rhizobacteria (PGPR)-primed Sorghum bicolor seedlings infected with the anthracnose-causing fungal pathogen, Colletotrichum sublineolum, with a focus on the post-challenge primed state phase. At the 4-leaf growth stage, the plants were treated with a strain of Paenibacillus alvei at 10⁸ cfu mL⁻¹. Following a 24 h PGPR application, the plants were inoculated with a C. sublineolum spore suspension (10⁶ spores mL⁻¹), and the infection monitored over time: 1, 3, 5, 7 and 9 days post-inoculation. Non-infected plants served as negative controls. Intracellular metabolites from both inoculated and non-inoculated plants were extracted with 80% methanol-water. The extracts were chromatographically and spectrometrically analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to high-definition mass spectrometry. The acquired multidimensional data were processed to create data matrices for chemometric modelling. The computed models indicated time-related metabolic perturbations that reflect primed responses to the fungal infection. Evaluation of orthogonal projection to latent structure-discriminant analysis (OPLS-DA) loading shared and unique structures (SUS)-plots uncovered the differential stronger defence responses against the fungal infection observed in primed plants. These involved enhanced levels of amino acids (tyrosine, tryptophan), phytohormones (jasmonic acid and salicylic acid conjugates, and zeatin), and defence-related components of the lipidome. Furthermore, other defence responses in both naïve and primed plants were characterised by a complex mobilisation of phenolic compounds and de novo biosynthesis of the flavones, apigenin and luteolin and the 3-deoxyanthocyanidin phytoalexins, apigeninidin and luteolinidin, as well as some related conjugates.

Compound danshen dripping pills normalize a reprogrammed metabolism of myocardial ischemia rats to interpret its time-dependent efficacy in clinic trials: a metabolomic study

INTRODUCTION

Clinical trials of Compound danshen dripping pills (CDDP) indicated distinct improvement in patients with chronic stable angina. Daily fluctuation of therapeutic effect agreed with a peak-valley PK profile during a 4-week CDDP regimen, but stabilized after 8-week treatment.

OBJECTIVES

This article aims to explore the underlying mechanism for the time-dependent drug efficacy of the up-down fluctuation or stabilization in clinic trials.

METHODS

A rat model of myocardial ischemia was established via isoproterenol induction. Metabolomics was employed to analyze the energy-related substances both in circulatory system and myocardium in the myocardial ischemia model.

RESULTS

CDDP treatment ameliorated myocardial ischemia, reversed the reprogramming of the metabolism induced by ISO and normalized the level of most myocardial substrates and the genes/enzymes associated with those metabolic changes. After 1- or 2-week treatment, CDDP regulated plasma and myocardial metabolome in an analogous, time-dependent way, and modulated metabolic patterns of ischemic rats that perfectly matched with the fluctuated or stabilized effects observed in clinical trials with 4 or 8-week treatment, respectively.

CONCLUSION

Metabolic modulation by CDDP contributes to the fluctuated or stabilized therapeutic outcome, and is a potential therapeutic approach for myocardial ischemia diseases.

Exploring Radiation Response in Two Head and Neck Squamous Carcinoma Cell Lines Through Metabolic Profiling

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common form of cancer worldwide. Radiotherapy, with or without surgery, represents the major approach to curative treatment. However, not all tumors are equally sensitive to irradiation. It is therefore of interest to apply newer system biology approaches (e.g., metabolic profiling) in squamous cancer cells with different radiosensitivities in order to provide new insights on the mechanisms of radiation response. In this study, two cultured HNSCC cell lines from the same donor, UM-SCC-74A and UM-SCC-74B, were first genotyped using Short Tandem Repeat (STR), and assessed for radiation response by the means of clonogenic survival and growth inhibition assays. Thereafter, cells were cultured, irradiated and collected for subsequent metabolic profiling analyses using liquid chromatography-mass spectrometry (LC-MS). STR verified the similarity of UM-SCC-74A and UM-SCC-74B cells, and three independent assays proved UM-SCC-74B to be clearly more radioresistant than UM-SCC-74A. The LC-MS metabolic profiling demonstrated significant differences in the intracellular metabolome of the two cell lines before irradiation, as well as significant alterations after irradiation. The most important differences between the two cell lines before irradiation were connected to nicotinic acid and nicotinamide metabolism and purine metabolism. In the more radiosensitive UM-SCC-74A cells, the most significant alterations after irradiation were linked to tryptophan metabolism. In the more radioresistant UM-SCC-74B cells, the major alterations after irradiation were connected to nicotinic acid and nicotinamide metabolism, purine metabolism, the methionine cycle as well as the serine, and glycine metabolism. The data suggest that the more radioresistant cell line UM-SCC-74B altered the metabolism to control redox-status, manage DNA-repair, and change DNA methylation after irradiation. This provides new insights on the mechanisms of radiation response, which may aid future identification of biomarkers associated with radioresistance of cancer cells.

Multi-omics studies in cellular models of methylmalonic acidemia and propionic acidemia reveal dysregulation of serine metabolism

BACKGROUND

Methylmalonic acidemia (MMA) and propionic acidemia (PA) are related disorders of mitochondrial propionate metabolism, caused by defects in methylmalonyl-CoA mutase (MUT) and propionyl-CoA carboxylase (PCC), respectively. These biochemical defects lead to a complex cascade of downstream metabolic abnormalities, and identification of these abnormal pathways has important implications for understanding disease pathophysiology. Using a multi-omics approach in cellular models of MMA and PA, we identified serine and thiol metabolism as important areas of metabolic dysregulation.

METHODS

We performed global proteomic analysis of fibroblasts and untargeted metabolomics analysis of plasma from individuals with MMA to identify novel pathways of dysfunction. We probed these novel pathways in CRISPR-edited, MUT and PCCA null HEK293 cell lines via targeted metabolomics, gene expression analysis, and flux metabolomics tracing utilization of ¹³C-glucose.

RESULTS

Proteomic analysis of fibroblasts identified upregulation of multiple proteins involved in serine synthesis and thiol metabolism including: phosphoserine amino transferase (PSAT1), cystathionine beta synthase (CBS), and mercaptopyruvate sulfurtransferase (MPST). Metabolomics analysis of plasma revealed significantly increased levels of cystathionine and glutathione, central metabolites in thiol metabolism. CRISPR-edited MUT and PCCA HEK293 cells recapitulate primary defects of MMA and PA and have upregulation of transcripts associated with serine and thiol metabolism including PSAT1. ¹³C-glucose flux metabolomics in MUT and PCCA null HEK293 cells identified increases in serine de novo biosynthesis, serine transport, and abnormal downstream TCA cycle utilization.

CONCLUSION

We identified abnormal serine metabolism as a novel area of cellular dysfunction in MMA and PA, thus introducing a potential new target for therapeutic investigation.

Metabolomic Profiling of the Host Response of Tomato (Solanum lycopersicum) Following Infection by Ralstonia solanacearum

Tomato (Solanum lycopersicum) is an important dietary source of bioactive phytochemicals and active breeding programs constantly produce new cultivars possessing superior and desirable traits. The phytopathogenic Ralstonia solanacearum, the causal agent of bacterial wilt, is a highly destructive bacterial disease with a high economic impact on tomato production. This study followed an untargeted metabolomic approach involving four tomato cultivars and aimed at the identification of secondary metabolites involved in plant defense after infection with R. solanacearum. Liquid chromatography coupled to mass spectrometry (LC-MS) in combination with multivariate data analysis and chemometric modelling were utilized for the identification of discriminant secondary metabolites. The total of 81 statistically selected features were annotated belonging to the metabolite classes of amino acids, organic acids, fatty acids, various derivatives of cinnamic acid and benzoic acids, flavonoids and steroidal glycoalkaloids. The results indicate that the phenylpropanoid pathway, represented by flavonoids and hydroxycinnamic acids, is of prime importance in the tomato defense response. The hydroxycinnamic acids esters of quinic acid, hexoses and glucaric acids were identified as signatory biomarkers, as well as the hydroxycinnamic acid amides to polyamines and tyramine. Interestingly, the rapid and differential accumulation of putrescine, dopamine, and tyramine derivatives, along with the presence of a newly documented metabolite, feruloyl serotonin, were documented in the infected plants. Metabolite concentration variability in the different cultivar tissues point to cultivar-specific variation in the speed and manner of resource redistribution between the host tissues. These metabolic phenotypes provide insights into the differential metabolic signatures underlying the defense metabolism of the four cultivars, defining their defensive capabilities to R. solanacearum.

Metabolomic modulations of HepG2 cells exposed to bisphenol analogues

Bisphenol analogues including bisphenol A (BPA), bisphenol AF (BPAF), bisphenol F (BPF), and bisphenol S (BPS) share similar chemical structures and endocrine disrupting effects. Their effects on metabolisms, however, are so far only marginally understood. In this study, NMR-based metabonomic profiles of HepG2 cell culture media and PCR array were used to assess the metabolomics disturbances and gene expression levels of HepG2 in response to four BPs (BPA, BPAF, BPF, and BPS). The results indicated that BP analogues resulted in disturbances in 7-15 metabolites that were classified as amino acid (alanine, glutamine, glutamate), intermediates and end-products in the glycolysis (pyruvate) and the tricarboxylic acid cycle (acetate, lactate). Their rank in order according to the number of metabolites and pathways was BPF > BPA > BPAF > BPS. The common disrupted pathways (pyruvate metabolism; alanine, aspartate, and glutamate metabolism) indicated enhanced glycolysis. The following glucometabolic PCR array analysis suggested that although four BPs shared the capability of disrupting glucose metabolism, they may act through different mechanisms: BPAF has increased the pyruvate kinase (PKLR) expression level, which implied enhanced glycolysis that was agreed with NMR results. The other three BP analogues, however, decreased the expression level of glucokinase (GCK) that indicated glucose sensing impairment. Our results demonstrated the potential for using metabolomic and PCR array to understand the underlying action of mechanisms and identify the potential targets for future targeted risk assessment.