NMR-based metabolomics coupled with pattern recognition methods in biomarker discovery and disease diagnosis

What do patients on methotrexate need and expect at the clinic? An online patient survey

To verify, via a survey, the experience and needs of patients receiving methotrexate (MTX), their general management and the quality of the information provided by the rheumatologist. We conducted a 51-item online survey between May and July 2020 addressed to persons diagnosed with an immune-mediated disease and treated with MTX (regardless of the route of administration). Recruitment was done via Twitter. We obtained 294 responses, of which 283 were complete and could be analysed. Almost 82% of the respondents were women, 80% resided in Spain, 75% were between 31 and 60 years old, and 57% were active workers. Diseases included psoriasis (41%), lupus, Sjögren's or vasculitides (33%), and rheumatoid arthritis (16%), among others. Eighty per cent had read the leaflet inserted in the package, of whom 62% found it helpful. Only 15% of the respondents reported having been offered additional written material, which was considered barely functional (33 out of 100). Most patients (88%) responded that they had not received advice on any reliable sources to consult on the internet, and those who received it considered it unhelpful (24 out of 100). Patients receiving MTX due to an autoimmune disease demand more and better-quality written or web-based information than what is currently offered at their clinics.

Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics

Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.

Dynamics of microbial populations and metabolites of fermenting saps throughout tapping process of ron and oil palm trees in Côte d'Ivoire

Palm wine fermentation is a complex microbial process that evolves with tapping times. The dynamics in microbiota and metabolites throughout palm wine tapping days is still not established, which are critical for the distinctive characteristics of palm wine taste and quality, and thus the mastery of the daily quality fluctuation during tapping. We analyzed the changes in microbial community structure by amplicon sequencing of bacterial 16S rRNA gene and fungal internal transcribed spacer (ITS) region, and metabolite profile changes using mass spectrometry in palm wine collected over 25-30 days tapping of ron (Borassus aethiopum) and oil palms (Elaeis guineensis) from Côte d'Ivoire. The stage-wise collected palm wine samples showed distinct changes in microbial diversity and pH, supporting microbial community dynamics during palm wine tapping. Results highlighted the dominance of Saccharomyces cerevisiae in early stages and the emergence of non-Saccharomyces yeasts, particularly Hanseniaspora spp. in the later stages of oil palm wine tapping, vice versa in the case of ron palm wine tapping, with a unique presence of Saccharomycodes in the later stages (15-30 days). Fructophilic lactic acid bacteria (FLAB), mainly Fructobacillus and Leuconostoc, encountered in both types of palm wine tapping showed a decline at later stages of oil palm wine tapping. In this type of palm wine, acetic acid bacteria with genera Acetobacter and Glucanoacetobacter, by surpassing Lactobacillus in the last stage become dominant, whereas Lactobacillus remained dominant in ron palm wine throughout tapping days. The decline in the relative abundance of gevotroline and essential amino acids during the later stages of palm wine tapping (15-25 days) supports the difference in the health benefits of the palm wine obtained from different days of tapping, indicating that early stages of tapping is more nutritional and healthy than the later stages. The microbial dynamics may be a potential indicator of metabolite changes during palm sap fermentation, thus contributing to establish particular features of palm wines in different stages of tapping. This understanding of microbial ecology and chemical composition changes during palm wine tapping can be used as biomarkers to assess palm wine's quality and help to design an optimum starter culture.

Quantitative NMR-Based Lipoprotein Analysis Identifies Elevated HDL-4 and Triglycerides in the Serum of Alzheimer’s Disease Patients

Alzheimer’s disease (AD) is the most common form of dementia in the elderly and has been associated with changes in lipoprotein metabolism. We performed quantitative lipoprotein analysis in a local cohort of cognitively impaired elderly and control subjects using standardized nuclear magnetic resonance (NMR) spectroscopy. A commercially available quantitative NMR-based assay covering 112 lipoprotein main and subtype variables was used to investigate blood serum samples from a moderate cohort size of 161 persons (71 female, 90 male), including measures of quality control. Additionally, clinical metadata and cerebrospinal fluid AD biomarkers were collected and used for analysis. High-density lipoprotein (HDL) HDL-4 subfraction levels were mostly high in female individuals with mild cognitive impairment (MCI), followed by AD. Low-density lipoprotein (LDL) LDL-2 cholesterol was slightly elevated in male AD patients. HDL-2 apolipoprotein Apo-A1, HDL-2 phospholipids, and HDL-3 triglycerides were highly abundant in AD and MCI women compared to men. When considering clinical biomarkers (Aβ, tau), very low-density lipoprotein (VLDL) VLDL-1 and intermediate-density lipoprotein (IDL) triglycerides were substantially higher in AD compared to MCI. In addition, triglyceride levels correlated positively with dementia. Different lipoprotein serum patterns were identified for AD, MCI, and control subjects. Interestingly, HDL-4 and LDL-2 cholesterol parameters revealed strong gender-specific changes in the context of AD-driven dementia. As gender-based comparisons were based on smaller sub-groups with a low n-number, several statistical findings did not meet the significance threshold for multiple comparisons testing. Still, our finding suggests that serum HDL-4 parameters and various triglycerides correlate positively with AD pathology which could be a read-out of extended lipids traveling through the blood-brain barrier, supporting amyloid plaque formation processes. Thereof, we see herein a proof of concept that this quantitative NMR-based lipoprotein assay can generate important and highly interesting data for refined AD diagnosis and patient stratification, especially when larger cohorts are available.

Precision Medicine: Determination of Ribavirin Urinary Metabolites in Relation to Drug Adverse Effects in HCV Patients

The most commonly used antiviral treatment against hepatitis C virus is a combination of direct-acting antivirals (DAAs) and ribavirin (RBV), which leads to a shortened duration of therapy and a sustained virologic response until 98%. Nonetheless, several dose-related side effects of RBV could limit its applications. This study aims to measure the urinary concentration of RBV and its main metabolites in order to evaluate the drug metabolism ability of HCV patients and to evaluate the adverse effects, such as anemia, with respect to RBV metabolite levels. RBV and its proactive and inactive metabolites were identified and quantified in the urine of 17 HCV males with severe liver fibrosis using proton nuclear magnetic resonance (¹H-NMR) at the fourth week (TW4) and at the twelfth week of treatment (EOT). Four prodrug urinary metabolites, including RBV, were identified and three of them were quantified. At both the TW4 and EOT stages, six HCV patients were found to maintain high concentrations of RBV, while another six patients maintained a high level of RBV proactive metabolites, likely due to nucleosidase activity. Furthermore, a negative correlation between the reduction in hemoglobin (Hb) and proactive forms was observed, according to RBV-triphosphate accumulation causing the hemolysis. These findings represent a proof of concept regarding tailoring the drug dose in relation to the specific metabolic ability of the individual, as expected by the precision medicine approach.

HPV-mediated Cervical Cancer: A Systematic review on Immunological Basis, Molecular Biology and Immune evasion mechanisms

BACKGROUND

Human papillomavirus (HPV), one of the most frequently transmitted viruses globally, causing several malignancies including cervical cancer.

AIM

Owing to their unique pathogenicity HPV viruses can persist in the host organism for a longer duration than other virus types, to complete their lifecycle. During its association with the host, HPV causes various pathological conditions affecting the immune system by evading the host immune- mechanisms leading to the progression of various diseases, including cancer.

METHOD

To date, ~ 150 serotypes were identified, and certain high-risk HPV types are known to be associated with genital warts and cervical cancer. As of now, two prophylactic vaccines are in use for the treatment of HPV infection, however, no effective antiviral drug is available for HPV-associated disease/infections. Numerous clinical and laboratory studies are being investigated to formulate an effective and specific vaccine again HPV infections and associated diseases.

RESULT

As the immunological basis of HPV infection and associated disease progress persist indistinctly, deeper insights on immune evasion mechanism and molecular biology of disease would aid in developing an effective vaccine.

CONCLUSION

Thus this review focuses, aiming a systematic review on the immunological aspects of HPV-associated cervical cancer by uncovering immune evasion strategies adapted by HPV.

Comparative metabolomics unveils molecular changes and metabolic networks of syringin against hepatitis B mice by untargeted mass spectrometry

Untargeted metabolomics technology was used to discover the metabolic pathways and biomarkers for revealing the potential biological mechanism of syringin on hepatitis B virus. Serum samples were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS)-based comparative metabolomics coupled with pattern recognition methods and network pathway. In addition, the histopathology, HBV DNA detection of liver tissue, and biochemical indicators of liver function change were also explored for investigating the antiviral effect of syringin. In comparison to the model group, the metabolic profiles of the turbulence in transgenic mice tended to recover to the same as the control group after syringin therapy. A total of 33 potential biomarkers were determined to explore the metabolic disorders in the hepatitis B animal model, of which 25 were regulated by syringin, and 8 metabolic pathways, such as phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism, were involved. Syringin markedly reduced the liver pathology change, inhibited HBV DNA replication, and improved liver function. Amino acid metabolism is a potential target for the treatment of hepatitis B. The hepatoprotective effect of syringin may contribute to ameliorating oxidative stress and preventing protein and DNA replication. Comparative metabolomics is a promising tool for discovering metabolic pathways and biomarkers of the hepatitis B animal model as targets to reveal the effects and mechanism of syringin, which benefits the development of natural products and advances the treatment of diseases.

Untargeted metabolomics technology was used to discover the metabolic pathways and biomarkers for revealing the potential biological mechanism of syringin on hepatitis B virus.

Exploring the metabolic biomarkers and pathway changes in crucian under carbonate alkalinity exposure using high-throughput metabolomics analysis based on UPLC-ESI-QTOF-MS

The aims of this study is to explore the metabolomic biomarker and pathway changes in crucian under carbonate alkalinity exposures using high-throughput metabolomics analysis based on ultra-performance liquid chromatography-electrospray ionization-quadrupole time of flight-tandem mass spectrometry (UPLC-ESI-QTOF-MS) for carrying out adaptive evolution of fish in environmental exposures and understanding molecular physiological mechanisms of saline–alkali tolerance in fishes. Under 60 day exposure management, the UPLC-ESI-QTOF-MS technology, coupled with a pattern recognition approach and metabolic pathway analysis, was utilized to give insight into the metabolic biomarker and pathway changes. In addition, biochemical parameters in response to carbonate alkalinity in fish were detected for chronic impairment evaluation. A total of twenty-seven endogenous metabolites were identified to distinguish the biochemical changes in fish in clean water under exposure to different concentrations of carbonate alkalinity (CA); these mainly involved amino acid synthesis and metabolism, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism, pyruvate metabolism and the citrate cycle (TCA cycle). Compared with the control group, CA exposure increased the level of blood ammonia; TP; ALB; Gln in the liver and gills; GS; urea in blood, the liver and gills; CREA; CPS; Glu and LDH; and decreased the level of weight gain rate, oxygen consumption, discharge rate of ammonia, SOD, CAT, ALT, AST and Na⁺/K⁺-ATPase. At low concentrations, CA can change the normal metabolism of fish in terms of changing the osmotic pressure regulation capacity, antioxidant capacity, ammonia metabolism and liver and kidney function to adapt to the CA exposure environment. As the concentration of CA increases, various metabolic processes in crucian are inhibited, causing chronic damage to the body. The results show that the metabolomic strategy is a potentially powerful tool for identifying the mechanisms in response to different environmental exposomes and offers precious information about the chronic response of fish to CA.

We explore the metabolic biomarker and pathway changes accompanying the adaptive evolution of crucian subjected to carbonate alkalinity exposure, using UPLC-ESI-QTOF-MS, in order to understand the molecular physiological mechanisms of saline–alkali tolerance.

Urine and serum NMR-based metabolomics in pre-procedural prediction of contrast-induced nephropathy

Contrast induced nephropathy (CIN) has been reported to be the third foremost cause of acute renal failure. Metabolomics is a robust technique that has been used to identify potential biomarkers for the prediction of renal damage. We aim to analyze the serum and urine metabolites changes, before and after using contrast for coronary angiography, to determine if metabolomics can predict early development of CIN. 66 patients undergoing elective coronary angiography were eligible for enrollment. Urine and serum samples were collected prior to administration of CM and 72 h post procedure and analyzed by nuclear magnetic resonance. The significant differential metabolites between patients who develop CIN and patients who have stable renal function after angiography were identified using U test and receiver operating characteristic analysis was performed for each metabolite candidate. Potential susceptible pathways to cytotoxic effect of CM were investigated by pathway analysis. A predictive panel composed of six urinary metabolites had the best area under the curve. Glutamic acid, uridine diphosphate, glutamine and tyrosine were the most important serum predictive biomarkers. Several pathways related to amino acid and nicotinamide metabolism were suggested as impaired pathways in CIN prone patients. Changes exist in urine and serum metabolomics patterns in patients who do and do not develop CIN after coronary angiography hence metabolites may be potential predictive identifiers of CIN.

Functional metabolomics using UPLC-Q/TOF-MS combined with ingenuity pathway analysis as a promising strategy for evaluating the efficacy and discovering amino acid metabolism as a potential therapeutic mechanism-related target for geniposide against alcoholic liver disease

Metabolomics has been used as a strategy to evaluate the efficacy of and potential targets for natural products.

Ultra-performance liquid chromatography-mass spectrometry-based metabolomics reveals Huangqiliuyi decoction attenuates abnormal metabolism as a novel therapeutic opportunity for type 2 diabetes

Background: As a typical chronic metabolic disease, type 2 diabetes mellitus causes a heavy health-care burden to society. In this study, we applied the metabolomics strategy to explore the potential molecular mechanism of the Huangqiliuyi decoction (HQLYD) for type-2 diabetes (T2D). Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) combined with pattern recognition methods was utilized to select specific metabolites closely associated with HQLYD. Biomarker pathway analysis and biological network were utilized to uncover the therapeutic effect and action mechanism related to HQLYD. A total of twenty-five biomarkers were identified in the animal model, in which sixteen biomarkers are associated with HQLYD treatment for T2D. They attenuated the abnormalities of metabolic pathways such as phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, and the citrate cycle. HQLYD also significantly elevated the serum FINS and SOD, GSP-x level in the liver and kidney, and reduced the serum TC, TG, HDL, LDL, urea, Scr, AST, ALT, FBG, IRS, MDA, and CAT level. We found that the therapeutic mechanism of HQLYD against T2D affected amino acid metabolism, glucose metabolism and lipid metabolism. Metabolomics revealed that the Huangqiliuyi decoction attenuates abnormal metabolism as a novel therapeutic opportunity for type 2 diabetes.

Untargeted Urinary 1H NMR-Based Metabolomic Pattern as a Potential Platform in Breast Cancer Detection

Breast cancer (BC) remains the second leading cause of death among women worldwide. An emerging approach based on the identification of endogenous metabolites (EMs) and the establishment of the metabolomic fingerprint of biological fluids constitutes a new frontier in medical diagnostics and a promising strategy to differentiate cancer patients from healthy individuals. In this work we aimed to establish the urinary metabolomic patterns from 40 BC patients and 38 healthy controls (CTL) using proton nuclear magnetic resonance spectroscopy (1H-NMR) as a powerful approach to identify a set of BC-specific metabolites which might be employed in the diagnosis of BC. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to a 1H-NMR processed data matrix. Metabolomic patterns distinguished BC from CTL urine samples, suggesting a unique metabolite profile for each investigated group. A total of 10 metabolites exhibited the highest contribution towards discriminating BC patients from healthy controls (variable importance in projection (VIP) >1, p < 0.05). The discrimination efficiency and accuracy of the urinary EMs were ascertained by receiver operating characteristic curve (ROC) analysis that allowed the identification of some metabolites with the highest sensitivities and specificities to discriminate BC patients from healthy controls (e.g. creatine, glycine, trimethylamine N-oxide, and serine). The metabolomic pathway analysis indicated several metabolism pathway disruptions, including amino acid and carbohydrate metabolisms, in BC patients, namely, glycine and butanoate metabolisms. The obtained results support the high throughput potential of NMR-based urinary metabolomics patterns in discriminating BC patients from CTL. Further investigations could unravel novel mechanistic insights into disease pathophysiology, monitor disease recurrence, and predict patient response towards therapy.

Metabolic profiling of dialysate at sensitized acupoints in knee osteoarthritis patients: A study protocol

BACKGROUND

Acupuncture therapy is frequently used to treat Knee Osteoarthritis (KOA) in clinic, and usually used local acupoints near the diseased knees as therapeutic targets. Some local acupoints appeared sensitization phenomenon which was called sensitized acupoints, which were regarded as important therapeutic targets to get better therapeutic effect on clinic. Therefore, it is necessary to explore the biological basis of acupoint sensitization. Meanwhile, there is a lack of an analysis of the metabolism for sensitized acupoints in KOA patients. Considering that acupuncture effect could be multi-targeted, omics (such as metabolomics) may be a useful method to reveal the relationship between sensitized acupoints and clinical efficacy of acupuncture.

METHODS AND ANALYSIS

This study is a parallel design trial. Thirty KOA patients and 30 healthy volunteers will be recruited in this study. Mechanical pain threshold will be measured by Electron Von frey in order to confirm the highest sensitized acupoints. Then collect tissue fluid from the highest sensitized acupoints by micro dialysis technical, then apply electro-acupuncture method on the highest sensitized acupoints to treat KOA patients, after 20 sessions treatments, measure and collect again. Liquid chromatography-tandem mass spectrometry method will be used to analyze the metabonomics of dialysate.

RESULTS

This study will provide a high-quality evidence to reveal the local molecular mechanism of acupuncture sensitized acupoints for patient with KOA.

CONCLUSION

This study will provide up-date evidence of whether acupuncture sensitized acupoints have local molecular mechanism for KOA.

TRIAL REGISTRATION NUMBER

NCT03599180 (24 Jul. 2018).

1H NMR-Based Metabolomics Reveals the Antitumor Mechanisms of Triptolide in BALB/c Mice Bearing CT26 Tumors

Triptolide, the main active ingredient in Tripterygium wilfordii Hook. f. (Celastraceae), has shown promising effects against a variety of tumors. However, the molecular pharmacological mechanisms explaining the action of triptolide remain unknown. In this study, the CT26 colon tumor cell line was inoculated subcutaneously into BALB/c mice, and plasma samples were subjected to ¹H NMR metabolomics analysis. The metabolic signature identified five metabolites whose levels were lower and 15 whose levels were higher in CT26 tumor-bearing mice than in normal control mice. Triptolide treatment significantly reversed the levels of nine of these metabolites, including isoleucine, glutamine, methionine, proline, 3-hydroxybutyric acid, 2-hydroxyisovalerate, 2-hydroxyisobutyrate, and low-density lipoprotein/very low-density lipoprotein. Based on the identities of these potential biomarkers, we conclude that the antitumor mechanism of triptolide might rely on correcting perturbations in branched-chain amino acid metabolism, serine/glycine/methionine biosynthesis, and ketone bodies metabolism.

Interplay between Alzheimer's disease and global glucose metabolism revealed by the metabolic profile alterations of pancreatic tissue and serum in APP/PS1 transgenic mice

Increasing evidence suggests that there is a correlation between type 2 diabetes mellitus (T2D) and Alzheimer's disease (AD). Increased Aβ polypeptide production in AD patients would promote metabolic abnormalities, insulin signaling dysfunction and perturbations in glucose utilization, thus leading to the onset of T2D. However, the metabolic mechanisms underlying the interplay between AD and its diabetes-promoting effects are not fully elucidated. Particularly, systematic metabolomics analysis has not been performed for the pancreas tissues of AD subjects, which play key roles in the glucose metabolism of living systems. In the current study, we characterized the dynamic metabolic profile alterations of the serum and the pancreas of APP/PS1 double-transgenic mice (an AD mouse model) using the untargeted metabolomics approaches. Serum and pancreatic tissues of APP/PS1 transgenic mice and wild-type mice were extracted and subjected to NMR analysis to evaluate the functional state of pancreas in the progress of AD. Multivariate analysis of principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted to define the global and the local (pancreas) metabolic features associated with the possible initiation of T2D in the progress of AD. Our results showed the onset of AD-induced global glucose metabolism disorders in AD mice. Hyperglycemia and its accompanying metabolic disorders including energy metabolism down-regulation and oxidative stress were observed in the serum of AD mice. Meanwhile, global disturbance of branched-chain amino acid (BCAA) metabolism was detected, and the change of BCAA (leucine) was positively correlated to the alteration of glucose. Moreover, increased level of glucose and enhanced energy metabolism were observed in the pancreas of AD mice. The results suggest that the diabetes-promoting effects accompanying the progress of AD are achieved by down-regulating the global utilization of glucose and interfering with the metabolic function of pancreas. Since T2D is a risk factor for the pathogenesis of AD, our findings suggest that targeting the glucose metabolism dysfunctions might serve as a supplementary therapeutic strategy for Alzheimer's disease.

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.

Cellular Metabolomics by a Universal Redox-Reactive Nanosensors Array: From the Cell Level to Tumor-on-a-Chip Analysis

Although biosensors based on nanowires-field effect transistor were proved extraordinarily efficient in fundamental applications, screening of charges due to the high-ionic strength of most physiological solutions imposes severe limitations in the design of smart, "real-time" sensors, as the biosample solution has to be previously desalted. This work describes the development of a novel nanowire biosensor that performs extracellular real-time multiplex sensing of small molecular metabolites, the true indicators of the body's chemistry machinery, without any preprocessing of the biosample. Unlike other nanoFET devices that follow direct binding of analytes to their surfaces, our nanodevice acts by sensing the oxidation state of redox-reactive chemical species bound to its surface. The device's surface array is chemically modified with a reversible redox molecular system that is sensitive to H₂O₂ down to 100 nM, coupled with a suite of corresponding oxidase enzymes that convert target metabolites to H₂O₂, enabling the direct prompt analysis of complex biosamples. This modality was successfully demonstrated for the real-time monitoring of cancer cell samples' metabolic activity and evaluating chemotherapeutic treatment options for cancer. This distinctive system displays ultrasensitive, selective, noninvasive, multiplex, real-time, label-free, and low-cost sensing of small molecular metabolites in ultrasmall volumes of complex biosamples, in the single-microliter scale, placing our technology at the forefront of this cutting-edge field.

Current Trends in Cancer Biomarker Discovery Using Urinary Metabolomics: Achievements and New Challenges

BACKGROUND

The development of effective screening methods for early cancer detection is one of the foremost challenges facing modern cancer research. Urinary metabolomics has recently emerged as a potentially transformative approach to cancer biomarker discovery owing to its noninvasive sampling characteristics and robust analytical feasibility.

OBJECTIVE

To provide an overview of new developments in urinary metabolomics, cover the most promising aspects of hyphenated techniques in untargeted and targeted metabolomics, and to discuss technical and clinical limitations in addition to the emerging challenges in the field of urinary metabolomics and its application to cancer biomarker discovery.

METHODS

A systematic review of research conducted in the past five years on the application of urinary metabolomics to cancer biomarker discovery was performed. Given the breadth of this topic, our review focused on the five most widely studied cancers employing urinary metabolomics approaches, including lung, breast, bladder, prostate, and ovarian cancers.

RESULTS

As an extension of conventional metabolomics, urinary metabolomics has benefitted from recent technological developments in nuclear magnetic resonance, mass spectrometry, gas and liquid chromatography, and capillary electrophoresis that have improved urine metabolome coverage and analytical reproducibility. Extensive metabolic profiling in urine has revealed a significant number of altered metabolic pathways and putative biomarkers, including pteridines, modified nucleosides, and acylcarnitines, that have been associated with cancer development and progression.

CONCLUSION

Urinary metabolomics presents a transformative new approach toward cancer biomarker discovery with high translational capacity to early cancer screening.

Metabolomics biotechnology, applications, and future trends: a systematic review

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed. Mass spectrometry-based metabolomics has been used in a variety of disease research areas. However, the deep research of metabolites remains a difficult and lengthy process. Fortunately, mass spectrometry is considered to be a universal tool with high specificity and sensitivity and is widely used around the world. Mass spectrometry technology has been applied to various basic disciplines, providing technical support for the discovery and identification of endogenous substances in living organisms. The combination of metabolomics and mass spectrometry is of great significance for the discovery and identification of metabolite biomarkers. The mass spectrometry tool could further improve and develop the exploratory research of the life sciences. This mini review discusses metabolomics biotechnology with a focus on recent applications of metabolomics as a powerful tool to elucidate metabolic disturbances and the related mechanisms of diseases.

Given the highly increased incidence of human diseases, a better understanding of the related mechanisms regarding endogenous metabolism is urgently needed.

High-throughput untargeted metabolomics and chemometrics reveals pharmacological action and molecular mechanism of chuanxiong by ultra performance liquid chromatography combined with quadrupole-time-of-flight-mass spectrometry

Metabolomics methods can be used to explore the effect mechanisms underlying treatments with traditional medicine. Lung cancer (LC) causes the highest morbidity and mortality among tumors disease, and has become a serious public health problem. Chuanxiong (CX) is a dried rhizome of Ligusticum Chuanxiong Hort., often used in traditional Chinese medicine and has been widely used in the treatment for tumors. However, the pharmacological effect of CX on the metabolism process of LC mice is still unclear. This study used high-throughput untargeted metabolomics aims to discover biomarkers and metabolic pathways of LC as a potential target to provide insight into the pharmacological action and effective mechanism of CX against LC. The precise structural identification of the LC biomarker has been established using ultra performance liquid chromatography (UPLC) combined with quadrupole-time-of-flight-mass spectrometry (Q-TOF-MS) technology. UPLC-Q-TOF-MS and chemometrics methods were used to analyze the blood metabolism of LC model mice, and revealed the intervention effect of CX on LC model mice and potential therapeutic targets. The results showed that the metabolic profile clustering among the groups was obvious, and 31 potential biomarkers were finally locked, involving 7 related metabolic pathways. After treatment with CX, we found that 22 kinds of biomarkers were recalled to the main metabolic pathway which are associated with lipid metabolism. This study provides an effective biomarker reference for early clinical diagnosis of LC, and also provides a foundation for the expansion of new drugs for CX treatment of LC.

Metabolomics methods can be used to explore the effect mechanisms underlying treatments with traditional medicine.

NMR-based metabolomics reveals that plant-derived smoke stimulates root growth via affecting carbohydrate and energy metabolism in maize

INTRODUCTION

It is well known that plant-derived smoke stimulates seed germination and seedling growth in many plants. Although a number of transcriptomics and proteomics studies have been carried out to understand the mode of action of smoke, less is known about the biochemical alterations associated with smoke exposure in plants.

OBJECTIVES

The aims of this study were (1) to determine the metabolic alterations in maize roots pre-treated with various concentrations of smoke solution, and (2) to identify the smoke-responsive metabolic pathways during early root growth period.

METHODS

Maize seeds were pre-treated with different concentrations of smoke solutions for 24 h and then grown for 10 days. 600-MHz ¹H NMR spectroscopy was performed on the aqueous root extracts of maize seedlings. The metabolite data obtained from the NMR spectra were analyzed by several statistical and functional methods, including one-way ANOVA, PCA, PLS-DA and pathway analysis.

RESULTS

Our study identified a total of 29 metabolites belonging to various chemical groups. Concentrations of 20 out of these 29 metabolites displayed significant (p < 0.05) changes after at least one smoke pre-treatment compared to the control. Moreover, functional analyses revealed that smoke pre-treatments markedly affected the carbohydrate- and energy-related metabolic pathways, such as galactose metabolism, glycolysis, glyoxylate metabolism, tricarboxylic acid cycle, and starch/sucrose metabolism.

CONCLUSIONS

To our knowledge, this is the first study that investigates smoke-induced biochemical alterations in early root growth period using NMR spectroscopy. Our findings clearly indicate that smoke either directly or indirectly influences many metabolic processes in maize roots.

High-throughput metabolomics for discovering metabolic biomarkers from intestinal tumorigenesis in APC min/+ mice based on liquid chromatography/mass spectrometry

As a major public health concern, colon cancer is one of the most common cancer types, which is also the second cause of cancer death in developed countries and the third most common cancer in other parts of the world. It was reported that patients diagnosed at early stage have a chance to obtain 5-year survival rates at least compared to patients with late stage. Facing the multistep process in intestinal tumorigenesis, there is an urgent need to develop more effective early detection strategies for ameliorating the patient clinical outcome. Metabolomics open up a novel avenue of seeking valuable potential biomarkers for assessing disease severity and prognosticating course by dynamic snapshot of small molecule metabolites. The study aims to provide deeper insights into the discovery, identification and functional pathways analysis of differentially expressed metabolites in intestinal tumorigenesis in APC ^min/+ mice used by the serum metabolomics, and bring about useful information for further effective prevention and treatment of the disease. 17 marker metabolites and related metabolism pathway were identified using non-targeted metabolomics based on liquid chromatography/mass spectrometry (LC/MS) associated with multivariate statistical analysis. The ingenuity pathway analysis platform involved multiple-pathways was applied to metabolic network analysis for further understanding the relationship between functional metabolic pathways and disease.

Side effects of methotrexate therapy for rheumatoid arthritis: A systematic review

Methotrexate (MTX) is used as an anchor disease-modifying anti-rheumatic drugs (DMARDs) in treating rheumatoid arthritis (RA) because of its potent efficacy and tolerability. MTX benefits a large number of RA patients but partially suffered from side effects. A variety of side effects can be associated with MTX when treating RA patients, from mild to severe or discontinuation of the treatment. In this report, we reviewed the possible side effects that MTX might cause from the most common gastrointestinal toxicity effects to less frequent malignant diseases. In order to achieve regimen with less side effects, the administration of MTX with appropriate dose and a careful pretreatment inspection is necessary. Further investigations are required when combining MTX with other drugs so as to enhance the efficacy and reduce side effects at the same time. The management of MTX treatment is also discussed to provide strategies for occurred side effects. Thus, this review will provide scholars with a comprehensive understanding the side effects of MTX administration by RA patients.

Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach

Metabolomics, as a promising and powerful approach, refers to comprehensive assessment and identification of small molecule endogenous metabolites in a biological system which is capable of further understanding the mechanisms of diseases for early diagnosis, effective treatment and prognosis. Acute kidney injury (AKI) induced by contrast is a serious complication in patients undergoing administration of iodinated contrast media. It is becoming a major health concern in clinic, however, the molecular mechanisms of contrast-induced acute kidney injury (CI-AKI) have not been well characterized. In this study, we used serum metabolomics based on liquid chromatography-mass spectrometry (LC-MS) combined with pattern recognition to explore and characterize potential metabolites and metabolic pathway in an experimental model for CI-AKI. Seventeen differentiating metabolites in the serum were identified involving the pivotal metabolic pathways related to tryptophan metabolism, glycerophospholipid metabolism, steroid hormone biosynthesis, pyrimidine metabolism, sphingolipid metabolism, aminoacyl-tRNA biosynthesis. Our study provides novel insight into pathophysiologic mechanisms of AKI by changing biomarkers and pathways.

UPLC-G2Si-HDMS untargeted metabolomics for identification of metabolic targets of Yin-Chen-Hao-Tang used as a therapeutic agent of dampness-heat jaundice syndrome

Yin-Chen-Hao-Tang (YCHT), the classic formulae of traditional Chinese medicine (TCM), is widely used to treat dampness-heat jaundice syndrome (DHJS) and various liver diseases. However, the therapeutic mechanism of YCHT is yet to have an integrated biological interpretation. In this work, we used metabolomics technology to reveal the adjustment of small molecule metabolites in body during the treatment of YCHT. Aim to discover the serum biomarkers which are associated with the treatment of DHJS against YCHT. Pathological results and biochemical indicators showed that the hepatic injury and liver index abnormalities caused by DHJS was effectively improve after treatment with YCHT. On the basis of effective treatment, ultra-high performance liquid chromatography (UPLC-G2Si-HDMS) combined with the multivariate statistical analysis method was utilized to analyze the serum samples. Finally, 22 biomarkers were identified by using mass spectrometry and illuminated the correlative metabolic pathways which play a significant role and as therapeutic targets in the treatment of DHJS. This work demonstrated that mass spectrometry metabolomics provides a new insight to elucidate the action mechanism of formulae.

LC-MS-based plasma metabolomics reveals metabolic variations in ovariectomy-induced osteoporosis in female Wistar rats

Osteoporosis with a reduction in bone mineral density has become one of the most common metabolic bone diseases.

Chemical metabolomics for investigating the protective effectiveness ofAcanthopanax senticosusHarms leaf against acute promyelocytic leukemia

Recent advances in the study of high-throughput metabolomics combined with high-resolution mass spectrometry have accelerated our understanding of the efficacy, mechanisms, and application of natural products. In this study, we have used chemical metabolomics to investigate and discover small molecule metabolites for the potential mechanism of Acanthopanax senticosus Harms leaf (ASL) against acute promyelocytic leukemia (APL). Based on high-throughput metabolomics, the underlying biomarker was found by combining chromatography coupled with quadrupole time-of-flight mass spectrometry with multivariate data analysis. The protective effect of ASL was dissected using biochemical indicators, pathology sections, immunohistochemistry, and multivariate analysis. Furthermore, 13 potential biomarkers associated with the pathway of sugar metabolism, amino-acid metabolism, nucleotide metabolism, and the metabolism of arachidonic acid were identified from serum samples. This study would help to understand chemical metabolomics for investigating the anti-APL effectiveness of ASL.

We have used chemical metabolomics to investigate and discover small molecule metabolites for the potential mechanism of Acanthopanax senticosus Harms leaf (ASL) against acute promyelocytic leukemia (APL).

High-throughput metabolomics used to identify potential therapeutic targets of Guizhi Fuling Wan against endometriosis of cold coagulation and blood stasis

Metabolomics is an emerging and robust discipline and involves the comprehensive evaluation of small molecule endogenous metabolites and enables the exploration of the pathogenesis of diseases. For example, endometriosis – a common disease which mostly occurs in women of childbearing age. A cure for endometriosis of cold coagulation and blood stasis (ECB) is highly sought after. This study was conducted to discover the potential biomarkers of ECB and the effective mechanism undertaken by Guizhi Fuling Wan (GFW) in treating ECB in rats. Urinary metabolomics were performed by using UPLC-Q-TOF-MS with pattern recognition methods to evaluate the changes in metabolic profiles and to identify biomarkers for elucidating the mechanism of the treatment of ECB with GFW. The results showed that urinary metabolism in the two groups were distinctly separated on the 28^th day, and a total of 20 differential biomarkers (16 in the positive mode, 4 in the negative mode) were confirmed involving several key metabolic pathways which included phenylalanine, tyrosine and tryptophan biosynthesis, valine, leucine and isoleucine biosynthesis, glyoxylate and dicarboxylate metabolism, tyrosine metabolism and the citrate cycle. Following the oral administration of GFW, certain pathways were affected; these included the following: phenylalanine, tyrosine and tryptophan biosynthesis, valine, leucine and isoleucine biosynthesis, glyoxylate and dicarboxylate metabolism, tyrosine metabolism, citrate cycle, steroid hormone biosynthesis, tryptophan metabolism, phenylalanine metabolism, primary bile acid biosynthesis, and aminoacyl-tRNA biosynthesis. This study also demonstrated that the administration of GFW affected the levels of urine endogenous metabolites, thereby laying a foundation for further study of the pharmacodynamical mechanism of GFW.

Metabolomics is an emerging and robust discipline and involves the comprehensive evaluation of small molecule endogenous metabolites and enables the exploration of the pathogenesis of diseases.

Network pharmacology combined with functional metabolomics discover bile acid metabolism as a promising target for mirabilite against colorectal cancer

In this study, a combination of network pharmacology and metabolomics was used to explore the mechanism by which mirabilite regulates bile acid metabolism in the treatment of colorectal cancer.

High-throughput system metabolomics method reveals new mechanistic insights of chlorogenic acid by using liquid chromatography coupled to high resolution mass spectrometry

It has increasingly been recognized that metabolism is highly interconnected with disease, and system metabolomics studies have aimed to discover metabolic biomarkers and analyze the pathways of metabolome phenotypes. To better understand the metabolic alteration related with disease, a urine metabolic profile using a high-throughput system metabolomics technology approach was applied to probe the underlying molecular mechanisms of alcohol-induced liver injury and the therapeutic effects of chlorogenic acid (CA). In this study, endogenous low-molecular-weight metabolites were characterized using liquid chromatography coupled with mass spectrometry (LC-MS). The acquired data was parsed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) to identify potential biomarkers. A total of 19 biomarkers were identified in a model of alcohol-induced liver injury rats, and it was found that chlorogenic acid had a regulatory effect on 14 of them, associated with multiple metabolic pathways. Comprehensive pathway analysis suggests that CA has the ability to regulate abnormal metabolic states. In addition, accessory examinations such as biochemical analysis and histopathological observations were also performed that showed similar results. As a natural product agent against ethanol-induced liver injury, CA was validated in the rebalancing of a wide range of metabolic disorders. High-throughput system metabolomics represents a powerful approach for revealing new mechanistic insights of natural products.

It has increasingly been recognized that metabolism is highly interconnected with disease, and system metabolomics studies have aimed to discover metabolic biomarkers and analyze the pathways of metabolome phenotypes.

NMR-based metabolomics for the environmental assessment of Kaohsiung Harbor sediments exemplified by a marine amphipod (Hyalella azteca)

Inflow of wastewater from upstream causes a large flux of pollutants to enter Kaohsiung Harbor in Taiwan daily. To reveal the ecological risk posed by Kaohsiung Harbor sediments, an ecological metabolomic approach was employed to investigate environmental factors pertinent to the physiological regulation of the marine amphipod Hyalella azteca. The amphipods were exposed to sediments collected from different stream inlets of the Love River (LR), Canon River (CR), Jen-Gen River (JR), and Salt River (SR). Harbor entrance 1 (E1) was selected as a reference site. After 10-day exposure, metabolomic analysis of the Hyalella azteca revealed differences between two groups: {E1, LR, CR} and {JR, SR}. The metabolic pathways identified in the two groups of amphipods were significantly different. The results demonstrated that NMR-based metabolomics can be effectively used to characterize metabolic response related to sediment from polluted areas.

Quantitative NMR analysis of intra- and extracellular metabolism of mammalian cells: A tutorial

Metabolomics analysis of body fluids as well as cells is depended on many factors. While several well-accepted standard operating procedures for the analysis of body fluids are available, the NMR based quantitative analysis of cellular metabolites is less well standardized. Experimental designs depend on the cell type, the quenching protocol and the applied post-acquisition workflow. Here, we provide a tutorial for the quantitative description of the metabolic phenotype of mammalian cells using NMR spectroscopy. We discuss all key steps of the process, starting from the selection of the appropriate culture medium, quenching techniques to arrest metabolism in a reproducible manner, the extraction of the intracellular components and the profiling of the culture medium. NMR data acquisition and methods for both qualitative and quantitative analysis are also provided. The suggested methods cover experiments for adherent cells and cells in suspension. We ultimately describe the application of the discussed workflow to a thyroid cancer cell line. Although this tutorial focuses on mammalian cells, the given guidelines and procedures may be adjusted for the analysis of other cell types.

Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics

Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼10³-10⁴) and dynamic range (∼10³-10⁴), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.

Nuclear Magnetic Resonance technique in tumor metabolism

Cancer is one of the most serious diseases that cause an enormous number of deaths all over the world. Tumor metabolism has great discrimination from that of normal tissues. Exploring the tumor metabolism may be one of the best ways to find biomarkers for cancer detection, diagnosis and to provide novel insights into internal physiological state where subtle changes may happen in metabolite concentrations. Nuclear Magnetic Resonance (NMR) technique nowadays is a popular tool to analyze cell extracts, tissues and biological fluids, etc, since it is a relatively fast and an accurate technique to supply abundant biochemical information at molecular levels for tumor research. In this review, approaches in tumor metabolism are discussed, including sample collection, data profiling and multivariate data analysis methods etc. Some typical applications of NMR are also summarized in tumor metabolism.

β-N-Methylamino-L-alanine (BMAA) perturbs alanine, aspartate and glutamate metabolism pathways in human neuroblastoma cells as determined by metabolic profiling

β-Methylamino-L-alanine (BMAA) is a non-proteinogenic amino acid that induces long-term cognitive deficits, as well as an increased neurodegeneration and intracellular fibril formation in the hippocampus of adult rodents following short-time neonatal exposure and in vervet monkey brain following long-term exposure. It has also been proposed to be involved in the etiology of neurodegenerative disease in humans. The aim of this study was to identify metabolic effects not related to excitotoxicity or oxidative stress in human neuroblastoma SH-SY5Y cells. The effects of BMAA (50, 250, 1000 µM) for 24 h on cells differentiated with retinoic acid were studied. Samples were analyzed using LC-MS and NMR spectroscopy to detect altered intracellular polar metabolites. The analysis performed, followed by multivariate pattern recognition techniques, revealed significant perturbations in protein biosynthesis, amino acid metabolism pathways and citrate cycle. Of specific interest were the BMAA-induced alterations in alanine, aspartate and glutamate metabolism and as well as alterations in various neurotransmitters/neuromodulators such as GABA and taurine. The results indicate that BMAA can interfere with metabolic pathways involved in neurotransmission in human neuroblastoma cells.

Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke

Background

Magnetic resonance spectroscopy (MRS) provides non-invasive information about the metabolic pattern of the brain parenchyma in vivo. The SpectraClassifier software performs MRS pattern-recognition by determining the spectral features (metabolites) which can be used objectively to classify spectra. Our aim was to develop an Infarct Evolution Classifier and a Brain Regions Classifier in a rat model of focal ischemic stroke using SpectraClassifier.

Results

A total of 164 single-voxel proton spectra obtained with a 7 Tesla magnet at an echo time of 12 ms from non-infarcted parenchyma, subventricular zones and infarcted parenchyma were analyzed with SpectraClassifier (http://gabrmn.uab.es/?q=sc). The spectra corresponded to Sprague-Dawley rats (healthy rats, n = 7) and stroke rats at day 1 post-stroke (acute phase, n = 6 rats) and at days 7 ± 1 post-stroke (subacute phase, n = 14). In the Infarct Evolution Classifier, spectral features contributed by lactate + mobile lipids (1.33 ppm), total creatine (3.05 ppm) and mobile lipids (0.85 ppm) distinguished among non-infarcted parenchyma (100% sensitivity and 100% specificity), acute phase of infarct (100% sensitivity and 95% specificity) and subacute phase of infarct (78% sensitivity and 100% specificity). In the Brain Regions Classifier, spectral features contributed by myoinositol (3.62 ppm) and total creatine (3.04/3.05 ppm) distinguished among infarcted parenchyma (100% sensitivity and 98% specificity), non-infarcted parenchyma (84% sensitivity and 84% specificity) and subventricular zones (76% sensitivity and 93% specificity).

Conclusion

SpectraClassifier identified candidate biomarkers for infarct evolution (mobile lipids accumulation) and different brain regions (myoinositol content).

Electronic supplementary material

The online version of this article (doi:10.1186/s12868-016-0328-x) contains supplementary material, which is available to authorized users.

Emerging role and recent applications of metabolomics biomarkers in obesity disease research

Metabolomics is a promising approach for the identification of metabolites which serve for early diagnosis, prediction of therapeutic response and prognosis of disease.

Huangqi decoction alleviates dimethylnitrosamine-induced liver fibrosis: An analysis of bile acids metabolic mechanism

ETHNOPHARMACOLOGICAL RELEVANCE

Huangqi Decoction (HQD), a classical traditional Chinese medicine (TCM) formula, is used to treating liver injury in China. The aim of the study is to investigate mechanisms of HQD against dimethylnitrosamine (DMN)-induced liver fibrosis underlying metabolic profiles of bile acids.

MATERIALS AND METHODS

DMN-induced liver fibrosis rats were administrated HQD and its compounds, astragalosides (AS), glycyrrhizic acid (GA) and their combination. The anti-fibrosis effects were evaluated and targeted metabolomics by UPLC-MS was used to examine whether HQD had an influence on bile acid metabolism. The levels of mRNAs associated with bile acid metabolism were expressed by RT-PCR. Chenodeoxycholic acid (CDCA)-induced hepatic stellate cells (HSCs) proliferation and activation were examined using MTS assay and Western blot.

RESULTS

Histopathological changes and serum liver function in HQD group had significant improvements (P<0.01). Concentrations of free bile acids and taurine conjugates were significantly increased in DMN group (P<0.05). HQD and its compounds restored the increased bile acids to normal levels, and HQD was more effected on parts of bile acids. Furthermore, the levels of mRNAs related bile acid synthesis and reabsorption such as CYP7A1, CYP8B1, CYP27A1, OATP2, OATP3, OATP4 and NTCP were significantly down-regulated in DMN group (P<0.05), mRNAs related excretion such as MRP3 and BESP were up-regulated (P<0.01), and CYP7A1, CYP8B1, OATP3, OATP4, NTCP and MRP3 restored to normal levels by HQD treatment. Moreover, CDCA-induced HSCs proliferation and activation were weaken by HQD (P<0.05) with down-regulated α-SMA, TGF-β1, p-Smad2 and p-Smad3 expressions.

CONCLUSIONS

HQD alleviated DMN-induced liver fibrosis with a better effect than its compounds, which may be involved in the regulation of bile acid metabolism enzyme. Moreover, HQD may inhibit CDCA-induced HSCs proliferation and activation.

Discovery of nutritional biomarkers: future directions based on omics technologies

Understanding the interactions between food and human biology is of utmost importance to facilitate the development of more efficient nutritional interventions that might improve our wellness status and future health outcomes by reducing risk factors for non-transmittable chronic diseases, such as cardiovascular diseases, cancer, obesity and metabolic syndrome. Dissection of the molecular mechanisms that mediate the physiological effects of diets and bioactive compounds is one of the main goals of current nutritional investigation and the food industry as might lead to the discovery of novel biomarkers. It is widely recognized that the availability of robust nutritional biomarkers represents a bottleneck that delays the innovation process of the food industry. In this regard, omics sciences have opened up new avenues of research and opportunities in nutrition. Advances in mass spectrometry, nuclear magnetic resonance, next generation sequencing and microarray technologies allow massive genome, gene expression, proteomic and metabolomic profiling, obtaining a global and in-depth analysis of physiological/pathological scenarios. For this reason, omics platforms are most suitable for the discovery and characterization of novel nutritional markers that will define the nutritional status of both individuals and populations in the near future, and to identify the nutritional bioactive compounds responsible for the health outcomes.

Profiling human blood serum metabolites by nuclear magnetic resonance spectroscopy: a comprehensive tool for the evaluation of hemodialysis efficiency

Hemodialysis remains the standard therapy to treat patients affected with end-stage renal disease by removing metabolites accumulated in blood plasma. The efficiency of hemodialysis is mainly monitored by urea clearance, which is routinely checked in clinical laboratory practice. However, there is mounting evidence that the clearance behavior of selected single metabolites is not sufficient to predict long-term outcome of treatment. To address this problem, we evaluated the potential of nuclear magnetic resonance spectroscopy for monitoring hemodialysis efficiency by comprehensive profiling of blood serum metabolites. We carried out a pilot study with a cohort of end-stage chronic kidney disease patients (n = 29), analyzing their serum prior and immediately after hemodialysis. To account for supposed variability in the accumulation of metabolites and efficiency of hemodialysis, patients' blood sera were repeatedly collected over a period of several months. Our results revealed that the metabolic profile in terms of concentrations varied considerably between patients but was comparably constant on the patient's level over the period of 4 months. Interestingly, also the individual clearance of the metabolites was characteristic for each patient. Thus, it is conceivable that the observed patient-dependent clearance patterns reflect to some extent the patients' long-term perspectives. We conclude that nuclear magnetic resonance spectroscopy is an optimal tool to complement traditional clinical methods based on a single variable, providing comprehensive and much more global information, which is crucial for patient evaluation and the development of improved treatments of kidney failure.

Discrimination of Basal Cell Carcinoma from Normal Skin Tissue Using High-Resolution Magic Angle Spinning 1H NMR Spectroscopy

High-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy is a useful tool for investigating the metabolism of various cancers. Basal cell carcinoma (BCC) is the most common skin cancer. However, to our knowledge, data on metabolic profiling of BCC have not been reported in the literature. The objective of the present study was to investigate the metabolic profiling of cutaneous BCC using HR-MAS ¹H NMR spectroscopy. HR-MAS ¹H NMR spectroscopy was used to analyze the metabolite profile and metabolite intensity of histopathologically confirmed BCC tissues and normal skin tissue (NST) samples. The metabolic intensity normalized to the total spectral intensities in BCC and NST was compared, and multivariate analysis was performed with orthogonal partial least-squares discriminant analysis (OPLS-DA). P values < 0.05 were considered statistically significant. Univariate analysis revealed 9 metabolites that showed statistically significant difference between BCC and NST. In multivariate analysis, the OPLS-DA models built with the HR-MAS NMR metabolic profiles revealed a clear separation of BCC from NST. The receiver operating characteristic curve generated from the results revealed an excellent discrimination of BCC from NST with an area under the curve (AUC) value of 0.961. The present study demonstrated that the metabolite profile and metabolite intensity differ between BCC and NST, and that HR-MAS ¹H NMR spectroscopy can be a valuable tool in the diagnosis of BCC.

Radiation Metabolomics: Current Status and Future Directions

Human exposure to ionizing radiation (IR) disrupts normal metabolic processes in cells and organs by inducing complex biological responses that interfere with gene and protein expression. Conventional dosimetry, monitoring of prodromal symptoms, and peripheral lymphocyte counts are of limited value as organ- and tissue-specific biomarkers for personnel exposed to radiation, particularly, weeks or months after exposure. Analysis of metabolites generated in known stress-responsive pathways by molecular profiling helps to predict the physiological status of an individual in response to environmental or genetic perturbations. Thus, a multi-metabolite profile obtained from a high-resolution mass spectrometry-based metabolomics platform offers potential for identification of robust biomarkers to predict radiation toxicity of organs and tissues resulting from exposures to therapeutic or non-therapeutic IR. Here, we review the status of radiation metabolomics and explore applications as a standalone technology, as well as its integration in systems biology, to facilitate a better understanding of the molecular basis of radiation response. Finally, we draw attention to the identification of specific pathways that can be targeted for the development of therapeutics to alleviate or mitigate harmful effects of radiation exposure.

Metabonomics and diagnostics

Metabonomic techniques have considerable potential in the field of clinical diagnostics, typifying the application of a translational research paradigm. Care must be taken at all stages to apply appropriate methodology with accurate patient selection and profiling, and rigorous data acquisition and handling, to ensure clinical validity.An ever-increasing number of publications in a wide range of diseases and diverse patient groups suggest a variety of potential clinical uses; prospective studies in large validation cohorts are required to bring metabonomics into routine clinical practice. In this chapter, the utility of metabonomics as a diagnostic tool will be discussed.

Nuclear magnetic resonance: a key metabolomics platform in the drug discovery process

Metabolomics is an innovative tool that is now emerging in the drug discovery process. Indeed, its ability to follow the dynamic perturbations in the metabolome resulting from pathologies but also from drug treatment and or/toxicity is of value for the development of new therapeutic approaches. Nuclear magnetic resonance (NMR) spectroscopy, which is an important analytical technique for several steps of the lead discovery, validation and optimization processes, has been described, together with mass spectrometry (MS) as one of the major platform that could be used for metabolomics studies. This review highlights why NMR could be considered a key tool for the application of metabolomics in drug discovery.

1H HR-MAS NMR Based Metabolic Profiling of Cells in Response to Treatment with a Hexacationic Ruthenium Metallaprism as Potential Anticancer Drug

(1)H high resolution magic angle spinning (HR-MAS) NMR spectroscopy was applied in combination with multivariate statistical analyses to study the metabolic response of whole cells to the treatment with a hexacationic ruthenium metallaprism [1](6+) as potential anticancer drug. Human ovarian cancer cells (A2780), the corresponding cisplatin resistant cells (A2780cisR), and human embryonic kidney cells (HEK-293) were each incubated for 24 h and 72 h with [1](6+) and compared to untreated cells. Different responses were obtained depending on the cell type and incubation time. Most pronounced changes were found for lipids, choline containing compounds, glutamate and glutathione, nucleotide sugars, lactate, and some amino acids. Possible contributions of these metabolites to physiologic processes are discussed. The time-dependent metabolic response patterns suggest that A2780 cells on one hand and HEK-293 cells and A2780cisR cells on the other hand may follow different cell death pathways and exist in different temporal stages thereof.

Making a big thing of a small cell--recent advances in single cell analysis

Single cell analysis is an emerging field requiring a high level interdisciplinary collaboration to provide detailed insights into the complex organisation, function and heterogeneity of life. This review is addressed to life science researchers as well as researchers developing novel technologies. It covers all aspects of the characterisation of single cells (with a special focus on mammalian cells) from morphology to genetics and different omics-techniques to physiological, mechanical and electrical methods. In recent years, tremendous advances have been achieved in all fields of single cell analysis: (1) improved spatial and temporal resolution of imaging techniques to enable the tracking of single molecule dynamics within single cells; (2) increased throughput to reveal unexpected heterogeneity between different individual cells raising the question what characterizes a cell type and what is just natural biological variation; and (3) emerging multimodal approaches trying to bring together information from complementary techniques paving the way for a deeper understanding of the complexity of biological processes. This review also covers the first successful translations of single cell analysis methods to diagnostic applications in the field of tumour research (especially circulating tumour cells), regenerative medicine, drug discovery and immunology.