Metabolomics approaches for discovering biomarkers of drug-induced hepatotoxicity and nephrotoxicity

Dinotefuran exposure alters biochemical, metabolomic, gut microbiome, and growth responses in decapoda pacific white shrimp Penaeus vannamei

Dinotefuran, a neonicotinoid insecticide, may impact nontarget organisms such as Decapoda P. vannamei shrimp with nervous systems similar to insects. Exposing shrimp to low dinotefuran concentrations (6, 60, and 600 μg/L) for 21 days affected growth, hepatosomatic index, and survival. Biomarkers erythromycin-N-demethylase, alanine aminotransferase, and catalase increased in all exposed groups, while glutathione S-transferase is the opposite; aminopyrin-N-demethylase, malondialdehyde, and aspartate aminotransferase increased at 60 and 600 μg/L. Concentration-dependent effects on gut microbiota altered the abundance of bacterial groups, increased potentially pathogenic and oxidative stress-resistant phenotypes, and decreased biofilm formation. Gram-positive/negative microbiota changed significantly. Metabolite differences between the exposed and control groups were identified using mass spectrometry and KEGG pathway enrichment. N-acetylcystathionine showed potential as a reliable dinotefuran metabolic marker. Weighted correlation network analysis (WGCNA) results indicated high connectivity of cruecdysone in the metabolite network and significant enrichment at 600 μg/L dinotefuran. The WGCNA results revealed a highly significant negative correlation between two key metabolites, caldine and indican, and the gut microbiota within co-expression modules. Overall, the risk of dinotefuran exposure to non-target organisms in aquatic environments still requires further attention.

Purine Metabolism and Hexosamine Biosynthetic Pathway Abnormalities in Diarrheal Weaned Piglets Identified Using Metabolomics

Post-weaning diarrhea significantly contributes to the high mortality in pig production, but the metabolic changes in weaned piglets with diarrhea remain unclear. This study aimed to identify the differential metabolites in the urine of diarrheal weaned piglets and those of healthy weaned piglets to reveal the metabolic changes associated with diarrhea in weaned piglets. Nine 25-day-old piglets with diarrhea scores above 16 and an average body weight of 5.41 ± 0.18 kg were selected for the diarrhea group. Corresponding to the body weight and sex of the diarrhea group, nine 25-month-old healthy piglets with similar sex and body weights of 5.49 ± 0.21 kg were selected as the control group. Results showed that the serum C-reactive protein and cortisol of piglets in the diarrhea group were higher than those in the control group (p < 0.05). The mRNA expression of TNF-α, IFN-γ in the jejunum and colon, and IL-1β in the jejunum were increased in diarrhea piglets (p < 0.05), accompanied by a reduction in the mRNA expression of ZO-1, ZO-2, and CLDN1 in the jejunum and colon (p < 0.05); mRNA expression of OCLN in the colon also occurred (p < 0.05). Metabolomic analysis of urine revealed increased levels of inosine, hypoxanthine, guanosine, deoxyinosin, glucosamine, glucosamine-1-p, N-Acetylmannosamine, chitobiose, and uric acid, identified as differential metabolites in diarrhea piglets compared to the controls. In summary, elevated weaning stress and inflammatory disease were associated with the abnormalities of purine metabolism and the hexosamine biosynthetic pathway of weaned piglets. This study additionally indicated the presence of energy metabolism-related diseases in diarrheal weaned piglets.

Experimental Models for Studying Structural and Functional State of the Pathological Liver (Review)

Liver pathologies remain one of the leading causes of mortality worldwide. Despite a high prevalence of liver diseases, the possibilities of diagnosing, prognosing, and treating non-alcoholic and alcoholic liver diseases still have a number of limitations and require the development of new methods and approaches. In laboratory studies, various models are used to reconstitute the pathological conditions of the liver, including cell cultures, spheroids, organoids, microfluidic systems, tissue slices. We reviewed the most commonly used in vivo, in vitro, and ex vivo models for studying non-alcoholic fatty liver disease and alcoholic liver disease, toxic liver injury, and fibrosis, described their advantages, limitations, and prospects for use. Great emphasis was placed on the mechanisms of development of pathological conditions in each model, as well as the assessment of the possibility of reconstructing various key aspects of pathogenesis for all these pathologies. There is currently no consensus on the choice of the most adequate model for studying liver pathology. The choice of a certain effective research model is determined by the specific purpose and objectives of the experiment.

Metabolomics acts as a powerful tool for comprehensively evaluating vaccines approved under emergency: a CoronaVac retrospective study

Introduction

To control the COVID-19 pandemic, great efforts have been made to realize herd immunity by vaccination since 2020. Unfortunately, most of the vaccines against COVID-19 were approved in emergency without a full-cycle and comprehensive evaluation process as recommended to the previous vaccines. Metabolome has a close tie with the phenotype and can sensitively reflect the responses to stimuli, rendering metabolomic analysis have the potential to appraise and monitor vaccine effects authentically.

Methods

In this study, a retrospective study was carried out for 330 Chinese volunteers receiving recommended two-dose CoronaVac, a vaccine approved in emergency in 2020. Venous blood was sampled before and after vaccination at 5 separate time points for all the recipients. Routine clinical laboratory analysis, metabolomic and lipidomic analysis data were collected.

Results and discussion

It was found that the serum antibody-positive rate of this population was around 81.82%. Most of the laboratory parameters were slightly perturbated within the relevant reference intervals after vaccination. The metabolomic and lipidomic analyses showed that the metabolic shift after inoculation was mainly in the glycolysis, tricarboxylic acid cycle, amino acid metabolism, urea cycle, as well as microbe-related metabolism (bile acid metabolism, tryptophan metabolism and phenylalanine metabolism). Time-course metabolome changes were found in parallel with the progress of immunity establishment and peripheral immune cell counting fluctuation, proving metabolomics analysis was an applicable solution to evaluate immune effects complementary to traditional antibody detection. Taurocholic acid, lysophosphatidylcholine 16:0 sn-1, glutamic acid, and phenylalanine were defined as valuable metabolite markers to indicate the establishment of immunity after vaccination. Integrated with the traditional laboratory analysis, this study provided a feasible metabolomics-based solution to relatively comprehensively evaluate vaccines approved under emergency.

Untargeted plasma 1H NMR-based metabolomic profiling in different stages of chronic kidney disease

Chronic kidney disease (CKD) is a serious public health issue affecting thousands of people worldwide. CKD diagnosis is usually made by Estimated Glomerular Filtration Rate (eGFR) and albuminuria, which limit the knowledge of the mechanisms behind CKD progression. The aim of the present study was to identify changes in the metabolomic profile that occur as CKD advances. In this sense, 77 plasma samples from patients with CDK were evaluated by 1D and 2D Nuclear Magnetic Resonance Spectroscopy (NMR). The NMR data showed significant changes in the metabolomic profile of CKD patients and the control group. Principal component analysis (PCA) clustered CKD and control patients into three distinct groups, control, stage 1 (G1)-stage 4 (G4) and stage 5 (G5). Lactate, glucose, acetate and creatinine were responsible for discriminating the control group from all the others CKD stages. Valine, alanine, glucose, creatinine, glutamate and lactate were responsible for the clustering of G1-G4 stages. G5 was discriminated by calcium ethylenediamine tetraacetic acid, magnesium ethylenediamine tetraacetic acid, creatinine, betaine/choline/trimethylamine N-oxide (TMAO), lactate and acetate. CKD G5 plasma pool which was submitted in MetaboAnalyst 4.0 platform (MetPA) analysis and showed 13 metabolic pathways involved in CKD physiopathology. Metabolic changes associated with glycolysis and gluconeogenesis allowed discriminating between CKD and control patients. The determination of involved molecules in TMAO generation in G5 suggests an important role in this uremic toxin linked to CKD and cardiovascular diseases. The aforementioned results propose the feasibility of metabolic assessment of CKD by NMR during treatment and disease progression.

A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data

Drug-induced toxicity damages the health and is one of the key factors causing drug withdrawal from the market. It is of great significance to identify drug-induced target-organ toxicity, especially the detailed pathological findings, which are crucial for toxicity assessment, in the early stage of drug development process. A large variety of studies have devoted to identify drug toxicity. However, most of them are limited to single organ or only binary toxicity. Here we proposed a novel multi-label learning model named Att-RethinkNet, for predicting drug-induced pathological findings targeted on liver and kidney based on toxicogenomics data. The Att-RethinkNet is equipped with a memory structure and can effectively use the label association information. Besides, attention mechanism is embedded to focus on the important features and obtain better feature presentation. Our Att-RethinkNet is applicable in multiple organs and takes account the compound type, dose, and administration time, so it is more comprehensive and generalized. And more importantly, it predicts multiple pathological findings at the same time, instead of predicting each pathology separately as the previous model did. To demonstrate the effectiveness of the proposed model, we compared the proposed method with a series of state-of-the-arts methods. Our model shows competitive performance and can predict potential hepatotoxicity and nephrotoxicity in a more accurate and reliable way. The implementation of the proposed method is available at https://github.com/RanSuLab/Drug-Toxicity-Prediction-MultiLabel.

The Potential Role of Metabolomics in Drug-Induced Liver Injury (DILI) Assessment

Drug-induced liver injury (DILI) is one of the most frequent adverse clinical reactions and a relevant cause of morbidity and mortality. Hepatotoxicity is among the major reasons for drug withdrawal during post-market and late development stages, representing a major concern to the pharmaceutical industry. The current biochemical parameters for the detection of DILI are based on enzymes (alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transpeptidase (GGT), alkaline phosphatase (ALP)) and bilirubin serum levels that are not specific of DILI and therefore there is an increasing interest on novel, specific, DILI biomarkers discovery. Metabolomics has emerged as a tool with a great potential for biomarker discovery, especially in disease diagnosis, and assessment of drug toxicity or efficacy. This review summarizes the multistep approaches in DILI biomarker research and discovery based on metabolomics and the principal outcomes from the research performed in this field. For that purpose, we have reviewed the recent scientific literature from PubMed, Web of Science, EMBASE, and PubTator using the terms “metabolomics”, “DILI”, and “humans”. Despite the undoubted contribution of metabolomics to our understanding of the underlying mechanisms of DILI and the identification of promising novel metabolite biomarkers, there are still some inconsistencies and limitations that hinder the translation of these research findings into general clinical practice, probably due to the variability of the methods used as well to the different mechanisms elicited by the DILI causing agent.

Potential Protective Effects of Antioxidants against Cyclophosphamide-Induced Nephrotoxicity

Cyclophosphamide is an alkylating antineoplastic agent, and it is one of the most successful drugs with wide arrays of clinical activity. It has been in use for several types of cancer treatments and as an immunosuppressive agent for the management of autoimmune and immune-mediated diseases. Nowadays, its clinical use is limited due to various toxicities, including nephrotoxicity. Even though the mechanisms are not well understood, cyclophosphamide-induced nephrotoxicity is reported to be mediated through oxidative stress. This review focuses on the potential role of natural and plant-derived antioxidants in preventing cyclophosphamide-induced nephrotoxicity.

Using intracellular metabolic profiling to identify novel biomarkers of cisplatin-induced acute kidney injury in NRK-52E cells

The aim of this study was to investigate changes in the intracellular metabolism resulting from cisplatin (CDDP)-induced nephrotoxicity in normal kidney tubular epithelial NRK-52E cells. Cytotoxicity, cell cycle analysis, and apoptotic cell death were all evaluated in NRK-52E cells treated with CDDP. Subsequently, proton nuclear magnetic resonance (¹H-NMR) spectroscopy was used to investigate cellular metabolic profiles. CDDP-induced nephrotoxicity was determined in vivo model. Cytotoxicity in the NRK-52E cells significantly rose following treatment with CDDP and these increases were found to be concentration-dependent. Both p53 and Bax protein expression was increased in CDDP-treated NRK-52E cells, correlating with enhanced cellular apoptosis. In addition, a number of metabolites were altered in both media and cell lysates in these cells. In cell lysates, citrate, creatinine, and acetate levels were dramatically reduced following treatment with 20 µM CDDP concentrations, while glutamate level was elevated. Lactate and acetate levels were significantly increased in culture media but citrate concentrations were reduced following high 20 µM CDDP concentrations incubation. In addition, excretion of clusterin, calbindin, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), selenium binding protein 1 (SBP1), and pyruvate kinase M2 (PKM2) into the culture media was significantly increased in CDDP-treated cells while expression of acetyl CoA synthetase 1 (AceCS1) was markedly reduced in these cells. These findings suggest that acetate-dependent metabolic pathway may be a reliable and useful biomarker for detecting CDDP-induced nephrotoxicity. Taken together, data demonstrate that the discovery of novel biomarkers by metabolite profiling in target cells may contribute to the detection of nephrotoxicity and new drug development.

W. Emerging technologies and their impact on regulatory science

There is an evolution and increasing need for the utilization of emerging cellular, molecular and in silico technologies and novel approaches for safety assessment of food, drugs, and personal care products. Convergence of these emerging technologies is also enabling rapid advances and approaches that may impact regulatory decisions and approvals. Although the development of emerging technologies may allow rapid advances in regulatory decision making, there is concern that these new technologies have not been thoroughly evaluated to determine if they are ready for regulatory application, singularly or in combinations. The magnitude of these combined technical advances may outpace the ability to assess fit for purpose and to allow routine application of these new methods for regulatory purposes. There is a need to develop strategies to evaluate the new technologies to determine which ones are ready for regulatory use. The opportunity to apply these potentially faster, more accurate, and cost-effective approaches remains an important goal to facilitate their incorporation into regulatory use. However, without a clear strategy to evaluate emerging technologies rapidly and appropriately, the value of these efforts may go unrecognized or may take longer. It is important for the regulatory science field to keep up with the research in these technically advanced areas and to understand the science behind these new approaches. The regulatory field must understand the critical quality attributes of these novel approaches and learn from each other's experience so that workforces can be trained to prepare for emerging global regulatory challenges. Moreover, it is essential that the regulatory community must work with the technology developers to harness collective capabilities towards developing a strategy for evaluation of these new and novel assessment tools.

Drug toxicity in the proximal tubule: new models, methods and mechanisms

The proximal tubule (PT) reabsorbs most of the glomerular filtrate and plays an important role in the uptake, metabolism and excretion of xenobiotics. Some therapeutic drugs are harmful to the PT, and resulting nephrotoxicity is thought to be responsible for approximately 1 in 6 of cases of children hospitalized with acute kidney injury (AKI). Clinically, PT dysfunction leads to urinary wasting of important solutes normally reabsorbed by this nephron segment, leading to systemic complications such as bone demineralization and a clinical scenario known as the renal Fanconi syndrome (RFS). While PT defects can be diagnosed using a combination of blood and urine markers, including urinary excretion of low molecular weight proteins (LMWP), standardized definitions of what constitutes clinically significant toxicity are lacking, and identifying which patients will go on to develop progressive loss of kidney function remains a major challenge. In addition, much of our understanding of cellular mechanisms of drug toxicity is still limited, partly due to the constraints of available cell and animal models. However, advances in new and more sophisticated in vitro models of the PT, along with the application of high-content analytical methods that can provide readouts more relevant to the clinical manifestations of nephrotoxicity, are beginning to extend our knowledge. Such technical progress should help in discovering new biomarkers that can better detect nephrotoxicity earlier and predict its long-term consequences, and herald a new era of more personalized medicine.

The enantioselective toxicity and oxidative stress of dinotefuran on zebrafish (Danio rerio)

Dinotefuran is a widely used neonicotinoid pesticides in agriculture and it has certain ecological toxicity to aquatic organisms. Studies on the potential toxicological effects of dinotefuran on fish are limited. In the present study, 96 h acute toxicity test indicated that enantiomers of R-(-)-dinotefuran had a greater toxic effect than Rac-dinotefuran on zebrafish, and S-(+)-dinotefuran was the least. In chronic assay, R-(-)-dinotefuran exerted more effects on the development of zebrafish than S-(+)-dinotefuran, and dinotefuran also had enantioselective effect on oxidative stress. Significant changes were observed in the superoxide dismutase (SOD), glutathione S-transferase (GST) and acetylcholinesterase (AChE) activities and malondialdehyde (MDA) contents, which demonstrated dinotefuran induced oxidative stress in zebrafish. Besides, through an ultra-performance liquid chromatography quadrupole-TOF mass spectrometry (UPLC-Q-TOF-MS)-based metabolomics method was used to evaluate the enantioselectivity of dinotefuran enantiomers in zebrafish. The results indicated that R-(-)-dinotefuran caused greater disturbances of endogenous metabolites. Phenylalanine metabolic pathways, glycine, serine and threonine metabolic pathways are only involved in zebrafish exposed to R-(-)-dinotefuran; whereas phenylalanine, tyrosine and tryptophan biosynthesis was only involved in zebrafish exposed to S-(+)-dinotefuran. This study provides a certain reference value for assessing the environmental risks of dinotefuran enantiomers to aquatic organisms, and has practical significance for guiding the ecologically and environmentally safety use of dinotefuran.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

Metabolomics as a Truly Translational Tool for Precision Medicine

Metabolomics is unique among omics technologies in being applicable to metabolism and toxicity studies broadly across organisms (e.g., humans, other mammals, model organisms, and even bacteria) and across biological materials (e.g., blood, urine, saliva, biopsy, and stool), including cultured cells and subcellular fractions. Metabolomics can be used to characterize biologic response patterns in humans as well as to support mechanistic studies in model systems and ex vivo studies. A broad range of resources are available, including publicly accessible data repositories (e.g., Metabolomics Workbench), tools for biostatistics and bioinformatics (e.g., MetaboAnalyst), metabolite identification (e.g., Metlin), and pathway analysis (e.g., Kyoto Encyclopedia of Genes and Genomes). Thus, metabolomics is more than a promise of the future; metabolomics is already available as a translational approach to facilitate precision medicine. This ACT Symposium review will contain an introduction to metabolomics in toxicity studies followed by sections on translational metabolic networks, translational metabolite biomarkers of acetaminophen-induced acute liver injury, translational framework using high-resolution metabolomics for integrated pharmacokinetics and pharmacodynamics, and precision medicine applications: extracting actionable targets from untargeted metabolomics data following one year in space.

Orphan Nuclear Receptor RORγ Modulates the Genome-Wide Binding of the Cholesterol Metabolic Genes during Mycotoxin-Induced Liver Injury

Maintaining lipid homeostasis is crucial to liver function, the key organ that governs the whole-body energy metabolism. In contrast, lipid dysregulation has been implicated in mycotoxin-induced liver injury, by which the pathophysiological regulation and the molecular components involved remain elusive. Here we focused on the potential roles of orphan nuclear receptor (NR) RORγ in lipid programming, and aimed to explore its action on cholesterol regulation in the liver of mycotoxin-exposed piglets. We found that liver tissues were damaged in the mycotoxin-exposed piglets compared to the healthy controls, revealed by histological analysis, elevated seral ALT, AST and ALP levels, and increased caspase 3/7 activities. Consistent with the transcriptomic finding of down-regulated cholesterol metabolism, we demonstrated that both cholesterol contents and cholesterol biosynthesis/transformation gene expressions in the mycotoxin-exposed livers were reduced, including HMGCS1, FDPS, SQLE, EBP, FDFT1 and VLDLR. Furthermore, we reported that RORγ binds to the cholesterol metabolic genes in porcine hepatocytes using a genome-wide ChIP-seq analysis, whereas mycotoxin decreased the RORγ binding occupancies genome-wide, especially at the cholesterol metabolic pathway. In addition, we revealed the enrichment of co-factors p300 and SRC, the histone marks H3K27ac and H3K4me2, together with RNA Polymerase II (Pol-II) at the locus of HMGCS1 in hepatocytes, which were reduced by mycotoxin-exposure. Our results provide a deep insight into the cholesterol metabolism regulation during mycotoxin-induced liver injury, and propose NRs as therapeutic targets for anti-mycotoxin treatments.

Metabolic profiling of 19 amino acids in triptolide-induced liver injured rats by gas chromatography-triple quadrupole mass spectrometry

The liver is an important organ for amino acid metabolism, and its damage can be reflected in the changes of amino acid level in the body. Triptolide (TP) has broad anti-inflammatory and anti-tumor activities, but its clinical application is limited due to hepatotoxicity. In this work, a simple, accurate and sensitive gas chromatography-triple quadrupole mass spectrometry (GC-QqQ-MS/MS) method was developed and validated for evaluating the serum levels of amino acids from control and TP-induced liver injured rats, and chemometric analysis was employed for amino acid metabolic profiles analysis. It was found that 11 amino acids showed significant changes after TP administration, and they were mainly involved in 5 metabolic pathways that are phenylalanine, tyrosine and tryptophan biosynthesis, alanine, aspartate and glutamate metabolism, glutamine and glutamate metabolism, phenylalanine metabolism and arginine biosynthesis. Five amino acids including tyrosine, glutamine, glutamic acid, tryptophan and alanine were identified as biomarkers of TP hepatotoxicity by further analysis. These results indicated that the novel amino acid metabolic profiling study based on the GC-QqQ-MS/MS provided not only exact concentrations of serum amino acids, but also a prospective methodology for evaluation of chemically induced liver injury.

Hepatotoxicity and nephrotoxicity assessment on ethanol extract of Fructus Psoraleae in Sprague Dawley rats using a UPLC-Q-TOF-MS analysis of serum metabolomics

Fructus Psoraleae (FP) is commonly used in the treatment of vitiligo, osteoporosis, and other diseases in clinic. As a result, the toxicity caused by FP is frequently encountered in clinical practice; however, the underlying toxicity mechanism remains unclear. The purpose of this study was to investigate the toxic effect of the ethanol extract of FP (EEFP) in rats and to explore the underlying toxic mechanisms using a metabolomics approach. The toxicity was evaluated by hematological indicators, biochemical indicators, and histological changes. In addition, a serum metabolomic method based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight MS (UPLC-Q-TOF-MS) had been established to investigate the hepatorenal toxicity of FP. Multivariate statistical approaches, such as partial least squares discriminant analysis and orthogonal partial least squares discriminant analysis, were built to evaluate the toxic effects of FP and find potential biomarkers and metabolic pathways. Ten endogenous metabolites had been identified and the related metabolic pathways were involved in phospholipid metabolism, amino acid metabolism, purine metabolism, and antioxidant system activities. The results showed that long-term exposure to high-dose EEFP may cause hepatorenal toxicity in rats. Therefore, serum metabolomics can improve the diagnostic efficiency of FP toxicity and make it more accurate and comprehensive.

Investigating metabolism by mass spectrometry: From steady state to dynamic view

Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.

Lindera aggregata intervents adenine-induced chronic kidney disease by mediating metabolism and TGF-β/Smad signaling pathway

INTRODUCTION

Lindera aggregata is a main Chinese herb of ancient prescriptions Suoquan pill applied for treating the chronic kidney disease (CKD). A large number of application histories of Lindera aggregata in the treatment of CKD have been recorded in Chinese traditional medical literature. The previous reports revealed that Lindera aggregata can treat CKD.

METHODS

Rats were randomly divided into control, model, Huangkui,Lindera aggregata ethanol extract (LEE) and Lindera aggregata water extract (LWE) groups. hematoxylin-eosin (HE) staining was used to detect the pathology of kidney. The levels of serum creatinine (Scr), serum Neutrophil gelatinase-associated lipocalin (NGAL), blood urea nitrogen (BUN), urine protein (UP), kidney index(KI) were evaluated. The UPLC - QTOF/MS were applied to probe the metabolic profile. Furthermore, Indoxyl sulfate-induced human renal tubular epithelial (HK-2) cell model was built to determine the expression levels of pathogenesis-related proteins.

RESULTS

The results demonstrated that LEE and LWE significantly inhibited the rebound in Scr, BUN, NGAL, UP and KI in models, except for the effect of LWE at low dose (LWE-L) and LEE at low dose (LEE-L) on KI and the effect of LWE-H at high dose (LWE-H) and LEE-L on BUN and NGAL. Moreover,Lindera aggregata extracts alleviated renal tubular dilatation, interstitial fibrosis and interstitial inflammation. By analysis, twenty-eight metabolites were related to CKD. After intervention of Lindera aggregata extracts, some metabolites approach to a normal-like level, such as Indoxyl sulfate. These metabolites are mainly involved in tryptophan, fatty acid, glycerophospholipid, tyrosine and arachidonic acid metabolic pathways. Furthermore, Lindera aggregata extracts mediate the expression of smad2, smad3, smad7 and TGF-β in Indoxyl sulfate-induced HK-2 cell.

CONCLUSIONS

Lindera aggregata extracts can mitigate adenine-induced CKD by modulating the metabolic profile and TGF-β/Smad signaling pathway, providing important supports for developing protective agent of Lindera aggregata for CKD.

Cutaneous Thermal Injury Modulates Blood and Skin Metabolomes Differently in a Murine Model

As the field of metabolomics develops further, investigations of how the metabolome is affected following thermal injury may be helpful to inform diagnostics and guide treatments. In this study, changes to the metabolome were tested and validated in a murine burn injury model. After a 30% total body surface scald injury or sham procedure sera and skin biopsies were collected at 1, 2, 6, or 24 hr.

Burn-specific changes in the metabolome were detected compared to sham animals. The sera metabolome exhibited a more rapid response to burn injury than that of the skin and it peaked more proximal to injury (6 vs 24 hr). Progression of metabolic response in the skin was less synchronous and showed a higher overlap of the significantly modified metabolites (SMMs) among tested time-points. Top affected pathways identified by SMMs of skin included inositol phosphate metabolism, ascorbate and alderate metabolism, caffeine metabolism, and the pentose phosphate pathway. Future research is warranted in human and larger animal models to further elucidate the role of metabolomic perturbations and the pathophysiology following burn injury.

Enantioselectivity effects of imazethapyr enantiomers to metabolic responses in mice

Imazethapyr (IMZT) is a typical chiral pesticide with two enantiomers with the R-IMZT having the main herbicidal activity. However, the enantioselectivity of the effects of IMZT enantiomers on human and animals is still unclear. In this study, a nuclear magnetic resonance (NMR)-based metabolomics method and determination of oxidative stress were used to evaluate the enantioselectivity of IMZT enantiomers in mice. The results showed that the R-IMZT caused larger disturbances of endogenous metabolites and the S-IMZT had stronger interferences to oxidation defense system. The significantly perturbed metabolic pathways in mice exposed to the R-enantiomer were the valine, leucine and isoleucine biosynthesis pathway as well as the phenylalanine, tyrosine and tryptophan biosynthesis pathway. However, exposure of mice to the S-enantiomer did not significantly affect the metabolic pathways, but exposure led to an increase of catalase (CAT) activity and an increase in malondialdehyde (MDA) content in the liver. These results indicate that we need to conduct a more comprehensive assessment of the health risks of pesticide monomers in the future. In a word, these results provide more evidence for assessing the differences in health risks of IMZT enantiomers to mammals as well as provide more references for the promotion and use of pesticide monomers in the future.

Metabolomic biomarkers in urine of rats following long-term low-dose exposure of cadmium and/or chlorpyrifos

Heavy metals and pesticides can be easily enriched in food chains and accumulated in organisms, thus pose significant threat to human health. However, their combined effects for long-term exposure at low dose has not been thoroughly investigated; especially there was no biofluid biomarker available to noninvasively diagnose the toxicosis of the combined exposure of the two chemicals at their low levels. In this study, we investigated the change of urine metabolites of rats with 90-day exposure to heavy metal cadmium (Cd) and/or organophosphorus pesticide chlorpyrifos (CPF) using gas chromatography-mass spectrometry (GC-MS)-based metabolomics approach. Our results showed that the interaction of Cd and CPF mainly displayed an antagonistic effect. We identified the panels of metabolite biomarkers in urine: benzoic acid and mannose were unique biomarkers for Cd exposure; creatinine and N-phenylacetyl glycine were unique biomarkers for CPF exposure; anthranilic acid, ribitol, and glucose were unique biomarkers for Cd plus CPF exposure. Our results suggest that 90-day exposure to Cd and/or CPF could cause a disturbance in energy and amino acid metabolism. And urine metabolomics analysis can help understand the toxicity of low dose exposure to mixed environmental chemicals.

Identification of metabolite biomarkers in serum of rats exposed to chlorpyrifos and cadmium

Chlorpyrifos (CPF) and cadmium (Cd) are widespread environmental pollutants, which are often present in drinking water and foods. However, the combined effects of CPF and Cd were not entirely clear at present. There was also no biomarker available to diagnose the poisoning of the two chemicals at low dose for long-term exposures. In this study, we investigated the change of serum metabolites of rats with subchronic exposure to CPF, Cd, and CPF plus Cd using gas chromatography-mass spectrometer-based metabolomics approach. We performed a stepwise optimization algorithm based on receiver operating characteristic to identify serum metabolite biomarkers for toxic diagnosis of the chemicals at different doses after 90-day exposure. We found that aminomalonic acid was the biomarker for the toxicity of Cd alone administration, and serine and propanoic acid were unique biomarkers for the toxicities of CPF plus Cd administrations. Our results suggest that subchronic exposure to CPF and Cd alone, or in combination at their low doses, could cause disturbance of energy and amino acid metabolism. Overall, we have shown that analysis of serum metabolomics can make exceptional contributions to the understanding of the toxic effects following long-term low-dose exposure of the organophosphorus pesticide and heavy metal.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

Integrated Plasma and Bile Metabolomics Based on an UHPLC-Q/TOF-MS and Network Pharmacology Approach to Explore the Potential Mechanism of Schisandra chinensis-Protection From Acute Alcoholic Liver Injury

Schisandra chinensis (SC) is a well-known important traditional Chinese medicine (TCM) that has been used to treat liver disease in China for a long time. However, its overall effects and mechanism of action are unclear. The present study aimed to explore the potential mechanism of SC in protection against alcoholic liver injury (ALI). In this research, to enable a full assessment of metabolic changes in ALI in Sprague-Dawley rats and to increase our understanding of physiological changes in normal and pathological states, ultra-high performance liquid chromatography combined with quadrupole time of flight mass spectrometry (UHPLC-Q/TOF-MS) was used to probe potential biomarkers to learn more about ALI and to evaluate the overall effect of SC for ALI in rats. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate global metabolomic alterations and to evaluate the therapeutic effects of SC in rats. The component–target–pathway network of SC was then constructed on the basis of the network pharmacology, and the liver injury-relevant signaling pathways were thus dissected and validated. The results showed that SC has conspicuous therapeutic efficacy for ALI, as suggested by the results of the pathological section and biochemical index assays, such as those for Alanine aminotransferase (ALT), Aspartate transaminase (AST), Alkaline phosphatase (AKP), γ-glutamyl transferase (γ-GT/GGT), Reactive oxygen species (ROS), and Malondialdehyde (MDA). Furthermore, 21 kinds of potential biomarkers were identified in plasma samples of ALI rats, and 20 kinds of potential biomarkers were identified in their bile samples. The biomarkers were mainly related to inflammation and dysfunctions of amino acids and energy metabolism. The recovery of these dysfunctions partly led to the curative effect of SC on ALI.

Drug-Induced Liver Injury: Biomarkers, Requirements, Candidates, and Validation

The hepatotoxicity of drugs is the main cause of drug withdrawal from the pharmaceutical market and interruption of the development of new molecules. Biomarkers are useful in several situations. In case of suspected drug-induced liver injury (DILI), biomarkers can be used to confirm liver damage, its severity, prognosis, confirm drug causality, or define the type of DILI. In this review, we will first present the currently used biomarkers and candidate biomarkers for the future. The current biomarkers are certainly very helpful including with the assistance of diagnostic method such the Roussel Uclaf Causality Assessment Method, but provide a limited information for the early detection of liver injury, the role of specific drug and the prediction of DILI. Some biomarkers are promising but they are not yet available for routine use. Studies are still needed to confirm their interest, particularly in comparison to Roussel Uclaf Causality Assessment Method.

Genome-Scale Characterization of Toxicity-Induced Metabolic Alterations in Primary Hepatocytes

Context-specific GEnome-scale metabolic Network REconstructions (GENREs) provide a means to understand cellular metabolism at a deeper level of physiological detail. Here, we use transcriptomics data from chemically-exposed rat hepatocytes to constrain a GENRE of rat hepatocyte metabolism and predict biomarkers of liver toxicity using the Transcriptionally Inferred Metabolic Biomarker Response algorithm. We profiled alterations in cellular hepatocyte metabolism following in vitro exposure to four toxicants (acetaminophen, carbon tetrachloride, 2,3,7,8-tetrachlorodibenzodioxin, and trichloroethylene) for six hour. TIMBR predictions were compared with paired fresh and spent media metabolomics data from the same exposure conditions. Agreement between computational model predictions and experimental data led to the identification of specific metabolites and thus metabolic pathways associated with toxicant exposure. Here, we identified changes in the TCA metabolites citrate and alpha-ketoglutarate along with changes in carbohydrate metabolism and interruptions in ATP production and the TCA Cycle. Where predictions and experimental data disagreed, we identified testable hypotheses to reconcile differences between the model predictions and experimental data. The presented pipeline for using paired transcriptomics and metabolomics data provides a framework for interrogating multiple omics datasets to generate mechanistic insight of metabolic changes associated with toxicological responses.

NMR Spectroscopy for Metabolomics Research

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

A Quantitative HILIC-MS/MS Assay of the Metabolic Response of Huh-7 Cells Exposed to 2,3,7,8-Tetrachlorodibenzo-p-Dioxin

A hydrophilic interaction liquid chromatography (HILIC)–ultra high-pressure liquid chromatography (UHPLC) coupled with tandem mass spectrometry (MS/MS) method was developed and applied to profile metabolite changes in human Huh-7 cells exposed to the potent aryl hydrocarbon receptor (AHR) ligand 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Comparisons of sensitivity (limit of detection as low as 0.01 µM) and reproducibility (84% of compounds had an interday relative standard deviation (RSD) less than 10.0%; 83% of compounds had an intraday RSD less than 15.0%) were assessed for all the metabolites. The exposure of Huh-7 cells to the hepatotoxic carcinogen TCDD at low doses (1 nM and 10 nM for 4 h and 24 h, respectively) was reflected by the disturbance of amino acid metabolism, energy metabolism (glycolysis, TCA cycle), and nucleic acid metabolism. TCDD caused a significant decrease in amino acids such as serine, alanine, and proline while promoting an increase in arginine levels with 24 h treatment. Energy metabolism intermediates such as phosphoenolpyruvate and acetyl–CoA and nucleosides such as UMP, XMP, and CMP were also markedly decreased. These results support the application of HILIC–UHPLC–MS/MS for robust and reliable analysis of the cellular response to environmentally relevant toxicants at lower doses.

Targeted UPLC-MS/MS high-throughput metabolomics approach to assess the purine and pyrimidine metabolism

Purines and pyrimidines, the important components of DNA and RNA, are closely related to metabolic syndrome and disorder, such as renal disease, gout and diabetic nephropathy etc. Given the importance of the biological significance of purines and pyrimidines, it is necessary to further develop a rapid and sensitive method for practical detection of a large-scale analyses. In this study, based on 96-well solid phase extraction plates-ultra performance liquid chromatography-triple quadrupole mass spectrometry (SPE-UPLC-QqQ-MS/MS), a novel approach for simultaneous determination of 23 purines and pyrimidines in biological samples was developed. First, plasma samples were pretreated by SPE using 96-well plates, which lead to an automated, simplified and rapid sample preparation process. In the methodology development, a large-scale test was performed to evaluate the stability and reliability of the approach. Finally, the levels of purines and pyrimidines in the biological samples were analyzed by this strategy. Experimental results showed that lowest limit of quantification (LLOQ) range from 6.678 × 10^-2 μg/mL to 4.275 × 10^-6 μg/mL; intra- and inter-day precision are <15% for all analytes. The stability and maximal capability of a single analytical batch could be extended to at least 431 injections (about 70 h). Analysis time of a single run was controlled in 10 min. Under the optimized conditions, wide linear ranges and good correlation coefficients (R² > 0.99) were acquired. The successful development of this method provides a feasible protocol for a large-scale metabolomics study and it also lays the foundation of quantitative analysis in endogenous analytes.

Modified insoluble dietary fibers in okara affect body composition, serum metabolic properties, and fatty acid profiles in mice fed high-fat diets: an NMR investigation

The potential health benefit of dietary fiber has attracted considerable attention in recent decades. In this study, the effects of modified dietary fibers (MDF) derived from okara on body composition, fat distribution, serum metabolomic parameters, and fatty acid profiles in mice fed high-fat diets (HFD) were evaluated by nuclear magnetic resonance (NMR)-based metabolic approach. HFD-induced C57BL mice were fed with a diet containing 100 g/kg MDF for 12 weeks. Compared with control mice, MDF-fed mice exhibited less fat and lower body weights, altered serum metabolomic profiles, and distinct fatty acid profiles. The levels of choline, phosphatidylcholine, glycerophosphorylcholine, glucose, lysine, scyllo-inositol, and glutamate for MDF group were higher than those for both CONT and HFD groups. A remarkable reduction of total cholesterol, total triglycerides, ω-6 fatty acids, alanine, citrate, creatine, or succinate was also observable for MDF group compared with HFD group. These findings demonstrated that the intake of MDF derived from okara clearly ameliorated some of the HFD-induced adverse metabolic effects and prevented adipose tissue accumulation.

Pharmacodynamic and urinary metabolomics studies on the mechanism of Schisandra polysaccharide in the treatment of Alzheimer's disease

This study was designed to investigate the antagonism of SCP in Aβ25–35-induced AD rats by intervening in neurotransmitters and metabolites.

Characterization of Iron Core⁻Gold Shell Nanoparticles for Anti-Cancer Treatments: Chemical and Structural Transformations During Storage and Use

Finding a cancer-selective drug that avoids damaging healthy cells and organs is a holy grail in medical research. In our previous studies, gold-coated iron (Fe@Au) nanoparticles showed cancer selective anti-cancer properties in vitro and in vivo but were found to gradually lose that activity with storage or "ageing." To determine the reasons for this diminished anti-cancer activity, we examined Fe@Au nanoparticles at different preparation and storage stages by means of transmission electron microscopy combined with and energy-dispersive X-ray spectroscopy, along with X-ray diffraction analysis and cell viability tests. We found that dried and reconstituted Fe@Au nanoparticles, or Fe@Au nanoparticles within cells, decompose into irregular fragments of γ-F₂O₃ and agglomerated gold clumps. These changes cause the loss of the particles' anti-cancer effects. However, we identified that the anti-cancer properties of Fe@Au nanoparticles can be well preserved under argon or, better still, liquid nitrogen storage for six months and at least one year, respectively.

Metabolomic evaluation of Euphorbia pekinensis induced nephrotoxicity in rats

CONTEXT

Euphorbia pekinensis Rupr. (Euphorbiaceae) has long been used in the Orient, while its clinical use was limited due to its nephrotoxic effect.

OBJECTIVE

The possible mechanism of nephrotoxicity of Euphorbia pekinensis (EPR) and its related constituents were investigated.

MATERIALS AND METHODS

Petroleum ether (PE), acetic ether (AE) and n-butanol (BUT) extracted sections of EPR were separately given to Wistar rats by gavage at the dose of 3 g/kg/day for 10 weeks to determine the nephrotoxic section of EPR. Then, renal metabolic profiling of EPR after oral administration of nephrotoxic section was investigated and its related constituents were identified by LC/Q-TOF-MS method.

RESULTS

The average values of creatinine (CREA) in PE, AE, BUT and control groups were 76.54 ± 9.52, 54.12 ± 10.34, 51.33 ± 5.19 and 48.23 ± 6.67 μmol/L. The average values of blood urea nitrogen (BUN) in PE, AE, BUT and control groups were 15.25 ± 3.37, 8.32 ± 0.89, 9.22 ± 1.78 and 8.47 ± 1.33 mmol/L, respectively. Only kidney section of rats in PE group showed that glomeruli had cellular or fibrocellular crescents. Renal metabolic profiling showed disturbed metabolic pathways of purine, amino acid, phospholipids and sphingolipids in EPR nephrotoxicity. A total of 25 compounds [(-)-(1S)-15-hydroxy-18-carboxycembrene is a new compound] in PE section and 10 compounds in rat serum after administration of PE section were identified.

CONCLUSIONS

This is the first time that the toxic compounds of PER and action mechanism of EPR nephrotoxicity were explored to provide a new reference for studying the toxic components of Traditional Chinese Medicine (TCM).

A method of inferring the relationship between Biomedical entities through correlation analysis on text

Background

One of the most important processes in a machine learning-based natural language processing is to represent words. The one-hot representation that has been commonly used has a large size of vector and assumes that the features that make up the vector are independent of each other. On the other hand, it is known that word embedding has a great effect in estimating the similarity between words because it expresses the meaning of the word well. In this study, we try to clarify the correlation between various terms in the biomedical texts based on the excellent ability of estimating similarity between words shown by word embedding. Therefore, we used word embedding to find new biomarkers and microorganisms related to a specific diseases.

Methods

In this study, we try to analyze the correlation between diseases-markers and diseases-microorganisms. First, we need to construct a corpus that seems to be related to them. To do this, we extract the titles and abstracts from the biomedical texts on the PubMed site. Second, we express diseases, markers, and microorganisms’ terms in word embedding using Canonical Correlation Analysis (CCA). CCA is a statistical based methodology that has a very good performance on vector dimension reduction. Finally, we tried to estimate the relationship between diseases-markers pairs and diseases-microorganisms pairs by measuring their similarity.

Results

In the experiment, we tried to confirm the correlation derived through word embedding using Google Scholar search results. Of the top 20 highly correlated disease-marker pairs, about 85% of the pairs have actually undergone a lot of research as a result of Google Scholars search. Conversely, for 85% of the 20 pairs with the lowest correlation, we could not actually find any other study to determine the relationship between the disease and the marker. This trend was similar for disease-microbe pairs.

Conclusions

The correlation between diseases and markers and diseases and microorganisms calculated through word embedding reflects actual research trends. If the word-embedding correlation is high, but there are not many published actual studies, additional research can be proposed for the pair.

Visualization of oxidative injury in the mouse kidney using selective superoxide anion fluorescent probes

Drug-induced acute kidney injury (AKI), caused by renal drug metabolism, has been regarded as a main problem in clinical pharmacology and practice. However, due to the lack of effective biomarkers and noninvasive real-time tools, the early diagnosis of drug-induced AKI is still a crucial challenge. The superoxide anion (O2˙-), the preliminary reactive oxidative species, is closely related to drug-induced AKI. In this paper, we reported two new mitochondria-targeted fluorescent probes for investigating AKI via mapping the fluctuation of O2˙- with high sensitivity and selectivity by the combination of rational design and a probe-screening approach. Small-molecule fluorescent probes (Naph-O2˙- and NIR-O2˙- ) with high accuracy and excellent selectivity were successfully applied to detect endogenously produced O2˙- in living cells and tissues by dual-model confocal imaging, and to trap the fluctuation of the O2˙- level during the drug-induced nephrotoxicity. Moreover, probe NIR-O2˙- was also used to elucidate the protective effects of l-carnitine (LC) against drug-induced nephrotoxicity for the first time. Therefore, these probes may be potential chemical tools for exploring the roles of O2˙- in complex nephrotoxicity disease systems.

Drug-Abuse Nanotechnology: Opportunities and Challenges

Opioid drug abuse and dependence/addiction are complex disorders regulated by a wide range of interacting networks of genes and pathways that control a variety of phenotypes. Although the field has been extensively progressed since the birth of the National Institute on Drug Abuse in 1974, the fundamental knowledge and involved mechanisms that lead to drug dependence/addiction are poorly understood, and thus, there has been limited success in the prevention of drug addiction and development of therapeutics for definitive treatment and cure of addiction disease. The lack of success in both identification of addiction in at-risk populations and the development of efficient drugs has resulted in a serious social and economic burden from opioid drug abuse with global increasing rate of mortality from drug overdoses. This perspective aims to draw the attention of scientists to the potential role of nanotechnologies, which might pave the way for the development of more practical platforms for either drug development or identification and screening of patients who may be vulnerable to addiction after using opioid drugs.

SECIMTools: a suite of metabolomics data analysis tools

Background

Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists.

Results

SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net).

Conclusions

SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2134-1) contains supplementary material, which is available to authorized users.

Protective effects of Salvia miltiorrhiza on adenine-induced chronic renal failure by regulating the metabolic profiling and modulating the NADPH oxidase/ROS/ERK and TGF-β/Smad signaling pathways

ETHNOPHARMACOLOGICAL RELEVANCE

Chronic renal failure (CRF) is defined as a progressive and irreversible loss of renal function and associated with inflammation and oxidative stress. Salvia miltiorrhiza (SM) is an important Chinese herb used in traditional Chinese medicine for treating cardiovascular diseases. The previous studies showed the SM exhibited significant protective effects on CRF. In this present study, the metabolic profiling changes and action mechanism of SM on CRF were explored.

AIMS OF THE STUDY

The aims of this study were to illustrate the metabolic profiling changes of adenine induced CRF and analyze the protective effects and action mechanisms of SM ethanol extract (SMEE) and water extract (SMWE).

MATERIALS AND METHODS

The animals were divided into normal group, CRF model group, Huangkui capsule-treated group, SMEE-treated group and SMWE-treated group. The UPLC-QTOFMS coupled with multivariate statistical methods were used to explore the changes of metabolic profile in plasma, urine and renal tissue from CRF rats simultaneously after treatment with SMEE and SMWE. Hematoxylin eosin (HE) staining and Masson staining were applied to observe pathological changes in renal tissue. Biochemical indicators including serum urea nitrogen (BUN), urine protein (UP) and serum creatinine (Scr) were measured according to the manufacturer's instructions of kits. Furthermore, HK-2 cell damaged model induced by ISF was established to access the protective effects and action mechanism. The dichlorodihydrofluorescein diacetate (DCFH-DA) assay was used to determine the reactive oxygen species (ROS) and Western blot was applied to analyze the expression of pathogenesis-related proteins in different groups.

RESULTS

The results showed that the ethanol extract (SMEE) and water extract (SMWE) of SM significantly inhibited the elevation of serum creatinine (Scr), blood urea nitrogen (BUN), urine protein (UP) and indoxyl sulfate (ISF) in adenine-induced CRF rats, especially SMEE exhibited more significant effects. Moreover, SM extracts obviously improved the symptoms of glomerular and tubular atrophy, focal calcium deposits, interstitial fibrosis, interstitial inflammation, and renal tissues. By metabolomics analysis, fifty-nine metabolites (thirteen in plasma, twenty-seven in urine and nineteen in kidney tissue) were up-regulated or down-regulated and contributed to CRF progress. After treatment of SM extracts, the altered metabolites were restored back to normal level. These potential biomarkers underpinning the metabolic pathways are including phenylalanine metabolism, pyrimidine metabolism, purine metabolism and tryptophan metabolism. Furthermore, SM extracts prevent epithelial-mesenchymal transition (EMT) of human renal tubular epithelial (HK-2) cell by inhibiting NADPH oxidase/ROS/ERK and TGF-β/Smad signaling pathways.

CONCLUSIONS

SMEE and SMWE can significantly alleviate adenine-induced CRF via regulation of the metabolic profiling and modulation of NADPH oxidase/ROS/ERK and TGF-β/Smad signaling pathways, which provided important supports for the development of protective agent of SM for CRF.

Are existing standard methods suitable for the evaluation of nanomedicines: some case studies

The use of nanotechnology in medical products has been demonstrated at laboratory scale, and many resulting nanomedicines are in the translational phase toward clinical applications, with global market trends indicating strong growth of the sector in the coming years. The translation of nanomedicines toward the clinic and subsequent commercialization may require the development of new or adaptation of existing standards to ensure the quality, safety and efficacy of such products. This work addresses some identified needs, and illustrates the shortcomings of currently used standardized methods when applied to medical-nanoparticles to assess particle size, drug loading, drug release and in vitro safety. Alternative physicochemical, and in vitro toxicology methods, with the potential to qualify as future standards supporting the evaluation of nanomedicine are provided.

Metabolomics and transcriptomics reveal the toxicity of difenoconazole to the early life stages of zebrafish (Danio rerio)

Difenoconazole is widely used to inhibit the growth of fungi, but its residue in the water environment may threaten ecosystem and human health. Here, ¹H nuclear magnetic resonance (NMR) and LC-MS/MS based metabolomics and transcriptomics approaches were used to assess the response of zebrafish to difenoconazole exposure. Early life stages of zebrafish were exposed to difenoconazole at environmentally relevant concentrations for 168h. Their comparison with the control group suggested an adverse development and disturbance of steroid hormones and VTG. KEGG pathway analysis identified five biological processes on the basis of differentially expressed genes (DEGs), as well as altered metabolites and amino acids in zebrafish following difenoconazole exposure. These affected processes included energy metabolism, amino acids metabolism, lipid metabolism, nucleotide metabolism, and an immune-related pathway. Collectively, these results bring us closer to an incremental understanding of the toxic effects of difenoconazole on zebrafish in its early development, and lend support to the continued use of the early life stages of zebrafish as a classical model to evaluate underlying environmental risks of xenobiotics in aquatic organisms.

Urinary metabolomic study of the antagonistic effect of P. ginseng in rats with estrogen decline using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

This study investigates the antagonistic effect of Panax ginseng in rats with estrogen decline by its intervention in some major endogenous metabolic pathways.