Metabolomics as a Challenging Approach for Medicinal Chemistry and Personalized Medicine

Cooperative STAT3-NFkB signaling modulates mitochondrial dysfunction and metabolic profiling in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) continues to pose a significant health challenge and is often diagnosed at advanced stages. Metabolic reprogramming is a hallmark of many cancer types, including HCC and it involves alterations in various metabolic or nutrient-sensing pathways within liver cells to facilitate the rapid growth and progression of tumours. However, the role of STAT3-NFκB in metabolic reprogramming is still not clear.

APPROACH AND RESULTS

Diethylnitrosamine (DEN) administered animals showed decreased body weight and elevated level of serum enzymes. Also, Transmission electron microscopy (TEM) analysis revealed ultrastructural alterations. Increased phosphorylated signal transducer and activator of transcription-3 (p-STAT3), phosphorylated nuclear factor kappa B (p-NFκβ), dynamin related protein 1 (Drp-1) and alpha-fetoprotein (AFP) expression enhance the carcinogenicity as revealed in immunohistochemistry (IHC). The enzyme-linked immunosorbent assay (ELISA) concentration of IL-6 was found to be elevated in time dependent manner both in blood serum and liver tissue. Moreover, immunoblot analysis showed increased level of p-STAT3, p-NFκβ and IL-6 stimulated the upregulation of mitophagy proteins such as Drp-1, Phosphatase and tensin homolog (PTEN)-induced putative kinase 1 (PINK-1). Meanwhile, downregulation of Poly [ADP-ribose] polymerase 1 (PARP-1) and cleaved caspase 3 suppresses apoptosis and enhanced expression of AFP supports tumorigenesis. The mRNA level of STAT3 and Drp-1 was also found to be significantly increased. Furthermore, we performed high-field 800 MHz Nuclear Magnetic Resonance (NMR) based tissue and serum metabolomics analysis to identify metabolic signatures associated with the progression of liver cancer. The metabolomics findings revealed aberrant metabolic alterations in liver tissue and serum of 75th and 105th days of intervention groups in comparison to control, 15th and 45th days of intervention groups. Tissue metabolomics analysis revealed the accumulation of succinate in the liver tissue samples, whereas, serum metabolomics analysis revealed significantly decreased circulatory levels of ketone bodies (such as 3-hydroxybutyrate, acetate, acetone, etc.) and membrane metabolites suggesting activated ketolysis in advanced stages of liver cancer.

CONCLUSION

STAT3-NFκβ signaling axis has a significant role in mitochondrial dysfunction and metabolic alterations in the development of HCC.

Unveiling Innovative Approaches to Mitigate Metals/Metalloids Toxicity for Sustainable Agriculture

Due to anthropogenic activities, environmental pollution of heavy metals/metalloids (HMs) has increased and received growing attention in recent decades. Plants growing in HM-contaminated soils have slower growth and development, resulting in lower agricultural yield. Exposure to HMs leads to the generation of free radicals (oxidative stress), which alters plant morpho-physiological and biochemical pathways at the cellular and tissue levels. Plants have evolved complex defense mechanisms to avoid or tolerate the toxic effects of HMs, including HMs absorption and accumulation in cell organelles, immobilization by forming complexes with organic chelates, extraction via numerous transporters, ion channels, signaling cascades, and transcription elements, among others. Nonetheless, these internal defensive mechanisms are insufficient to overcome HMs toxicity. Therefore, unveiling HMs adaptation and tolerance mechanisms is necessary for sustainable agriculture. Recent breakthroughs in cutting-edge approaches such as phytohormone and gasotransmitters application, nanotechnology, omics, and genetic engineering tools have identified molecular regulators linked to HMs tolerance, which may be applied to generate HMs-tolerant future plants. This review summarizes numerous systems that plants have adapted to resist HMs toxicity, such as physiological, biochemical, and molecular responses. Diverse adaptation strategies have also been comprehensively presented to advance plant resilience to HMs toxicity that could enable sustainable agricultural production.

Research progress of metabolomics in psoriasis

ABSTRACT

Psoriasis is a chronic inflammatory skin disease with significant physical and psychological burdens. The interplay between the innate and adaptive immune systems is thought to contribute to the pathogenesis; however, the details of the pathogenesis remain unclear. In addition, reliable biomarkers for diagnosis, assessment of disease activity, and monitoring of therapeutic response are limited. Metabolomics is an emerging science that can be used to identify and analyze low molecular weight molecules in biological systems. During the past decade, metabolomics has been widely used in psoriasis research, and substantial progress has been made. This review summarizes and discusses studies that applied metabolomics to psoriatic disease. These studies have identified dysregulation of amino acids, carnitines, fatty acids, lipids, and carbohydrates in psoriasis. The results from these studies have advanced our understanding of: (1) the molecular mechanisms of psoriasis pathogenesis; (2) diagnosis of psoriasis and assessment of disease activity; (3) the mechanism of treatment and how to monitor treatment response; and (4) the link between psoriasis and comorbid diseases. We discuss common research strategies and progress in the application of metabolomics to psoriasis, as well as emerging trends and future directions.

Metabolomics of infectious diseases in the era of personalized medicine

Infectious diseases continue to be a major cause of morbidity and mortality worldwide. Diseases cause perturbation of the host's immune system provoking a response that involves genes, proteins and metabolites. While genes are regulated by epigenetic or other host factors, proteins can undergo post-translational modification to enable/modify function. As a result, it is difficult to correlate the disease phenotype based solely on genetic and proteomic information only. Metabolites, however, can provide direct information on the biochemical activity during diseased state. Therefore, metabolites may, potentially, represent a phenotypic signature of a diseased state. Measuring and assessing metabolites in large scale falls under the omics technology known as "metabolomics". Comprehensive and/or specific metabolic profiling in biological fluids can be used as biomarkers of disease diagnosis. In addition, metabolomics together with genomics can be used to differentiate patients with differential treatment response and development of host targeted therapy instead of pathogen targeted therapy where pathogens are more prone to mutation and lead to antimicrobial resistance. Thus, metabolomics can be used for patient stratification, personalized drug formulation and disease control and management. Currently, several therapeutics and in vitro diagnostics kits have been approved by US Food and Drug Administration (FDA) for personalized treatment and diagnosis of infectious diseases. However, the actual number of therapeutics or diagnostics kits required for tailored treatment is limited as metabolomics and personalized medicine require the involvement of personnel from multidisciplinary fields ranging from technological development, bioscience, bioinformatics, biostatistics, clinicians, and biotechnology companies. Given the significance of metabolomics, in this review, we discussed different aspects of metabolomics particularly potentials of metabolomics as diagnostic biomarkers and use of small molecules for host targeted treatment for infectious diseases, and their scopes and challenges in personalized medicine.

A proposed framework to evaluate the quality and reliability of targeted metabolomics assays from the UK Consortium on Metabolic Phenotyping (MAP/UK)

Targeted metabolite assays that measure tens or hundreds of pre-selected metabolites, typically using liquid chromatography-mass spectrometry, are increasingly being developed and applied to metabolic phenotyping studies. These are used both as standalone phenotyping methods and for the validation of putative metabolic biomarkers obtained from untargeted metabolomics studies. However, there are no widely accepted standards in the scientific community for ensuring reliability of the development and validation of targeted metabolite assays (referred to here as 'targeted metabolomics'). Most current practices attempt to adopt, with modifications, the strict guidance provided by drug regulatory authorities for analytical methods designed largely for measuring drugs and other xenobiotic analytes. Here, the regulatory guidance provided by the European Medicines Agency, US Food and Drug Administration and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use are summarized. In this Perspective, we have adapted these guidelines and propose a less onerous 'tiered' approach to evaluate the reliability of a wide range of metabolomics analyses, addressing the need for community-accepted, harmonized guidelines for tiers other than full validation. This 'fit-for-purpose' tiered approach comprises four levels-discovery, screening, qualification and validation-and is discussed in the context of a range of targeted and untargeted metabolomics assays. Issues arising with targeted multiplexed metabolomics assays, and how these might be addressed, are considered. Furthermore, guidance is provided to assist the community with selecting the appropriate degree of reliability for a series of well-defined applications of metabolomics.

Preclinical Evaluation of Dimethyl Itaconate Against Hepatocellular Carcinoma via Activation of the e/iNOS-Mediated NF-κB-Dependent Apoptotic Pathway

Hepatocellular carcinoma (HCC) is one of the most common tumors affecting a large population worldwide, with the fifth and seventh greatest mortality rates among men and women, respectively, and the third prime cause of mortality among cancer victims. Dimethyl itaconate (DI) has been reported to be efficacious in colorectal cancer by decreasing IL-1β release from intestinal epithelial cells. In this study, diethylnitrosamine (DEN)-induced HCC in male albino Wistar rats was treated with DI as an anticancer drug. The function and molecular mechanism of DI against HCC in vivo were assessed using histopathology, enzyme-linked immunosorbent assay (ELISA), and Western blot studies. Metabolomics using ¹H-NMR was used to investigate metabolic profiles. As per molecular insights, DI has the ability to trigger mitochondrial apoptosis through iNOS- and eNOS-induced activation of the NF-κB/Bcl-2 family of proteins, CytC, caspase-3, and caspase-9 signaling cascade. Serum metabolomics investigations using ¹H-NMR revealed that aberrant metabolites in DEN-induced HCC rats were restored to normal following DI therapy. Furthermore, our data revealed that the DI worked as an anti-HCC agent. The anticancer activity of DI was shown to be equivalent to that of the commercial chemotherapeutic drug 5-fluorouracil.

Metabolomics: Paving the path for personalized periodontics – A literature review

The pathogenesis of periodontal disease is governed by a multitude of factors ranging from the macroscopic to the microscopic scale. Among the factors that constitute the etiological agents of the disease, a major element is the role played by the body's metabolome–i.e., the complete collection of microscopic molecules and metabolic products of cells and tissues in the body. Being of a regulatory nature, the interplay of these molecules exerts a considerable effect on the development as well as the progression of disease, which differs in each individual based on their phenotype. Exploring this connection and application into the field of diagnostic as well as prediction of risk for periodontitis will ultimately result in a personalized standard of care for patients in the future.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Omics and CRISPR-Cas9 Approaches for Molecular Insight, Functional Gene Analysis, and Stress Tolerance Development in Crops

Plants are regularly exposed to biotic and abiotic stresses that adversely affect agricultural production. Omics has gained momentum in the last two decades, fueled by statistical methodologies, computational capabilities, mass spectrometry, nucleic-acid sequencing, and peptide-sequencing platforms. Functional genomics—especially metabolomics, transcriptomics, and proteomics—have contributed substantially to plant molecular responses to stress. Recent progress in reverse and forward genetics approaches have mediated high-throughput techniques for identifying stress-related genes. Furthermore, web-based genetic databases have mediated bioinformatics techniques for detecting families of stress-tolerant genes. Gene ontology (GO) databases provide information on the gene product’s functional features and help with the computational estimation of gene function. Functional omics data from multiple platforms are useful for positional cloning. Stress-tolerant plants have been engineered using stress response genes, regulatory networks, and pathways. The genome-editing tool, CRISPR-Cas9, reveals the functional features of several parts of the plant genome. Current developments in CRISPR, such as de novo meristem induction genome-engineering in dicots and temperature-tolerant LbCas12a/CRISPR, enable greater DNA insertion precision. This review discusses functional omics for molecular insight and CRISPR-Cas9-based validation of gene function in crop plants. Omics and CRISPR-Cas9 are expected to garner knowledge on molecular systems and gene function and stress-tolerant crop production.

Chemometrics-based LC-UV-ESIMS analyses of 50 Salvia species for detecting their antioxidant constituents

Iran is one of the main hubs for sage's diversity in Asia. Generally, prediction and characterization of the chemical structures of the specialized metabolites that have significant role in the bioactivity of a plant remains a significant challenge. In this study, 50 different accessions of 32 Salvia species in 2015 and 2017 were collected and extracted for their phenolics, using 80 % methanol. LC-PDA-ESIMS analyses was coupled with multivariate analysis to identify the specific metabolites in the plant extracts, responsible for the antioxidant activity. Based on the variable importance in projection (VIP) method on the Genetic algorithm combined with PLS (GA-PLS) models, eighteen peaks were detected as multifunctional compounds. The putative phenolic compounds were attributed to apigenin-O-diglucoside, rutin, cynaroside, luteolin-7-O-glucoronide, apigenin-7-O-glucoside, apigenin-7-O-glucuronide, hispidulin-7-O-glucuronide, hispidulin-7-O-glucoside, rosmarinic acid, salvianolic acid B derivative, cirsimaritin, eupatorin, and carnosol. This investigation showed that the Salvia's extract can facilitate an opportunity for rapid detection, isolation and development of antioxidant agents.

Pyruvate dehydrogenase kinase/lactate axis: a therapeutic target for neovascular age-related macular degeneration identified by metabolomics

Neovascular age-related macular degeneration (nAMD) is the leading cause of blindness in aging populations. Here, we applied metabolomics to human sera of patients with nAMD during an active (exudative) phase of the pathology and found higher lactate levels and a shift in the lipoprotein profile (increased VLDL-LDL/HDL ratio). Similar metabolomics changes were detected in the sera of mice subjected to laser-induced choroidal neovascularization (CNV). In this experimental model, we provide evidence for two sites of lactate production: first, a local one in the injured eye, and second a systemic site associated with the recruitment of bone marrow-derived inflammatory cells. Mechanistically, lactate promotes the angiogenic response and M2-like macrophage accumulation in the eyes. The therapeutic potential of our findings is demonstrated by the pharmacological control of lactate levels through pyruvate dehydrogenase kinase (PDK) inhibition by dichloroacetic acid (DCA). Mice treated with DCA exhibited normalized lactate levels and lipoprotein profiles, and inhibited CNV formation. Collectively, our findings implicate the key role of the PDK/lactate axis in AMD pathogenesis and reveal that the regulation of PDK activity has potential therapeutic value in this ocular disease. The results indicate that the lipoprotein profile is a traceable pattern that is worth considering for patient follow-up. KEY MESSAGES: Lactate and lipoprotein profile are associated with the active phase of AMD and CNV development. Lactate is a relevant and functional metabolite correlated with AMD progression. Modulating lactate through pyruvate dehydrogenase kinase led to a decrease of CNV progression. Pyruvate dehydrogenase kinase is a new therapeutic target for neovascular AMD.

Preclinical studies on metal based anticancer drugs as enabled by integrated metallomics and metabolomics

Resistance development is a major obstacle for platinum-based chemotherapy, with the anticancer drug oxaliplatin being no exception. Acquired resistance is often associated with altered drug accumulation. In this work we introduce a novel -omics workflow enabling the parallel study of platinum drug uptake and its distribution between nucleus/protein and small molecule fraction along with metabolic changes after different treatment time points. This integrated metallomics/metabolomics approach is facilitated by a tailored sample preparation workflow suitable for preclinical studies on adherent cancer cell models. Inductively coupled plasma mass spectrometry monitors the platinum drug, while the metabolomics tool-set is provided by hydrophilic interaction liquid chromatography combined with high-resolution Orbitrap mass spectrometry. The implemented method covers biochemical key pathways of cancer cell metabolism as shown by a panel of >130 metabolite standards. Furthermore, the addition of yeast-based 13C-enriched internal standards upon extraction enabled a novel targeted/untargeted analysis strategy. In this study we used our method to compare an oxaliplatin sensitive human colon cancer cell line (HCT116) and its corresponding resistant model. In the acquired oxaliplatin resistant cells distinct differences in oxaliplatin accumulation correlated with differences in metabolomic rearrangements. Using this multi-omics approach for platinum-treated samples facilitates the generation of novel hypotheses regarding the susceptibility and resistance towards oxaliplatin.

Benchtop Low-Frequency 60 MHz NMR Analysis of Urine: A Comparative Metabolomics Investigation

Metabolomics techniques are now applied in numerous fields, with the ability to provide information concerning a large number of metabolites from a single sample in a short timeframe. Although high-frequency (HF) nuclear magnetic resonance (NMR) analysis represents a common method of choice to perform such studies, few investigations employing low-frequency (LF) NMR spectrometers have yet been published. Herein, we apply and contrast LF and HF ¹H-NMR metabolomics approaches to the study of urine samples collected from type 2 diabetic patients (T2D), and apply a comparative investigation with healthy controls. Additionally, we explore the capabilities of LF ¹H-¹H 2D correlation spectroscopy (COSY) experiments regarding the determination of metabolites, their resolution and associated analyses in human urine samples. T2D samples were readily distinguishable from controls, with several metabolites, particularly glucose, being associated with this distinction. Comparable results were obtained with HF and LF spectrometers. Linear correlation analyses were performed to derive relationships between the intensities of 1D and 2D resonances of several metabolites, and R² values obtained were able to confirm these, an observation attesting to the validity of employing 2D LF experiments for future applications in metabolomics studies. Our data suggest that LF spectrometers may prove to be easy-to-use, compact and inexpensive tools to perform routine metabolomics analyses in laboratories and ‘point-of-care’ sites. Furthermore, the quality of 2D spectra obtained from these instruments in half an hour would broaden the horizon of their potential applications.

Overview of Recent Strategic Advances in Medicinal Chemistry

Introducing novel strategies, concepts, and technologies that speed up drug discovery and the drug development cycle is of great importance both in the highly competitive pharmaceutical industry as well as in academia. This Perspective aims to present a "big-picture" overview of recent strategic innovations in medicinal chemistry and drug discovery.

Metabolomics toward personalized medicine

Metabolomics, which is the metabolites profiling in biological matrices, is a key tool for biomarker discovery and personalized medicine and has great potential to elucidate the ultimate product of the genomic processes. Over the last decade, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Most diseases result in signature metabolic profiles that reflect the sums of external and internal cellular activities. Metabolomics has a major role in clinical practice as it represents >95% of the workload in clinical laboratories worldwide. Many of these metabolites require different analytical platforms, such as Nuclear Magnetic Resonance (NMR), Mass Spectrometry (MS), and Ultra Performance Liquid Chromatography (UPLC), while many clinically relevant metabolites are still not routinely amenable to detection using currently available assays. Combining metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. This comprehensive approach will represent a major step forward toward providing precision medical care, in which individual is accounted for variability in genes, environment, and personal lifestyle. In this review, we compare and evaluate the metabolomics strategies and studies that focus on the discovery of biomarkers that have "personalized" diagnostic, prognostic, and therapeutic value, validated for monitoring disease progression and responses to various management regimens.

Aqueous Humor Analysis Identifies Higher Branched Chain Amino Acid Metabolism as a Marker for Human Leukocyte Antigen-B27 Acute Anterior Uveitis and Disease Activity

PURPOSE

Human leukocyte antigen-B27 (HLA-B27)-positive acute anterior uveitis (AAU) has a higher recurrence rate and shows more anterior chamber cell infiltration compared with HLA-B27-negative patients, suggesting distinct etiologies of these clinically overlapping conditions. To advance our understanding of the biology of AAU, we characterized the metabolic profile of aqueous humor (AqH) of patients with HLA-B27-associated AAU (B27-AAU) and noninfectious idiopathic AAU (idiopathic AAU).

DESIGN

Experimental laboratory study.

METHODS

AqH samples from 2 independent cohorts totaling 30 patients with B27-AAU, 16 patients with idiopathic AAU, and 20 patients with cataracts underwent 2 individual rounds of direct infusion mass spectrometry. Features predicted by direct infusion mass spectrometry that facilitated maximum separation between the disease groups in regression models were validated by liquid chromatography/tandem mass spectrometry-based quantification with appropriate standards.

RESULTS

Partial least square-discriminant analysis revealed metabolite profiles that were able to separate patients with B27-AAU from those with iodiopathic AAU. Pathway enrichment analysis, based on metabolites on which separation of the groups in the partial least square-discriminant analysis model was based, demonstrated the involvement of branched-chain amino acid biosynthesis, ascorbate and aldarate metabolism, the tricarboxylic acid cycle, and glycolysis-diverting pathways (eg, serine biosynthesis) across all investigated cohorts. Notably, the metabolite ketoleucine was elevated in B27-AAU across all 3 runs and moderately-but robustly-correlated with anterior chamber cell count (correlation coefficient range 0.41-0.81).

CONCLUSIONS

These results illustrate metabolic heterogeneity between HLA-B27-positive and HLA-B27-negative AAU, including an increase of branched-chain amino acid biosynthesis, that reflects disease activity in AAU.

A targeted metabolomics approach for clinical diagnosis of inborn errors of metabolism

Metabolome, the ultimate functional product of the genome, can be studied through identification and quantification of small molecules. The global metabolome influences the individual phenotype through clinical and environmental interventions. Metabolomics has become an integral part of clinical research and allowed for another dimension of better understanding of disease pathophysiology and mechanism. More than 95% of the clinical biochemistry laboratory routine workload is based on small molecular identification, which can potentially be analyzed through metabolomics. However, multiple challenges in clinical metabolomics impact the entire workflow and data quality, thus the biological interpretation needs to be standardized for a reproducible outcome. Herein, we introduce the establishment of a comprehensive targeted metabolomics method for a panel of 220 clinically relevant metabolites using Liquid chromatography-tandem mass spectrometry (LC-MS/MS) standardized for clinical research. The sensitivity, reproducibility and molecular stability of each targeted metabolite (amino acids, organic acids, acylcarnitines, sugars, bile acids, neurotransmitters, polyamines, and hormones) were assessed under multiple experimental conditions. The metabolic tissue distribution was determined in various rat organs. Furthermore, the method was validated in dry blood spot (DBS) samples collected from patients known to have various inborn errors of metabolism (IEMs). Using this approach, our panel appears to be sensitive and robust as it demonstrated differential and unique metabolic profiles in various rat tissues. Also, as a prospective screening method, this panel of diverse metabolites has the ability to identify patients with a wide range of IEMs who otherwise may need multiple, time-consuming and expensive biochemical assays causing a delay in clinical management.

Novel 1,3,4-thiadiazoles inhibit colorectal cancer via blockade of IL-6/COX-2 mediated JAK2/STAT3 signals as evidenced through data-based mathematical modeling

We attempted a preclinical study using DMH-induced CRC rat model to evaluate the antitumor potential of our recently synthesized 1,3,4-thiadiazoles. The molecular insights were confirmed through ELISA, qRT-PCR and western blot analyses. The CRC condition was produced in response to COX-2 and IL-6 induced activation of JAK2/STAT3 which, in turn, was due to the enhanced phosphorylation of JAK2 and STAT3. The treatment with 1,3,4-thiadiazole derivatives (VR24 and VR27) caused the significant blockade of this signaling pathway. The behavior of STAT3 populations in response to IL-6 and COX-2 stimulations was further confirmed through data-based mathematical modeling using the quantitative western blot data. Finally, VR24 and VR27 restored the perturbed metabolites associated to DMH-induced CRC as evidenced through ¹H NMR based serum metabolomics. The tumor protecting ability of VR24 and VR27 was found comparable or to some degree better than the marketed chemotherapeutics, 5-flurouracil.

The Effects of Glaucoma Drainage Devices on Oxygen Tension, Glycolytic Metabolites, and Metabolomics Profile of Aqueous Humor in the Rabbit

Purpose

Glaucoma drainage device (GDD) implantation can lead to corneal decompensation. We evaluated changes over time in oxygen tension and in the metabolic environment of the aqueous humor after GDD implantation in the rabbit eye.

Methods

Ahmed Glaucoma Valves were implanted in the left eyes of eight male New Zealand white rabbits. Right eyes were used as a control. Oxygen tension was measured immediately before surgery and at 1 and 2 months postoperation. Aqueous humor was collected from the surgical and control eyes at 1, 2, and 5 months postoperation. Aqueous humor samples collected at 1 and 5 months postoperation were selected for broad-spectrum metabolomics analysis using ultra-performance liquid chromatography-time of flight-mass spectrometry (UPLC TOF-MS). Multivariate analysis methods were used to identify metabolite profiles that separated the surgical and control eye at 1 and 5 months.

Results

There was a significant decrease in oxygen tension in aqueous humor of the surgical eyes (9 mm Hg, 95% confidence interval [CI]: -14.7 to -3.5). Differences in the metabolic profiles between the surgical and control eye at 1 and 5 months were observed, as were differences for the surgical eye at 1 and 5 months. In addition, a metabolite profile was identified that differentiated the surgical eyes at 1 and 5 months.

Conclusion

Changes in the oxygen tension and metabolic intermediates occur within the aqueous humor as early as 1 month after GDD implantation.

Translational Relevance

Corneal decompensation following GDD implantation could be secondary to disruption of the normal aqueous circulation, resulting in hypoxia and an altered metabolic profile. Alterations to the GDD design might minimize aqueous disruption and prevent corneal decompensation.

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 500 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrant ions or calibration like some other IMS techniques, they avoid calibration errors which can cause problems in distinguishing structurally similar molecules. All measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites analyzed to date have come from key metabolism pathways such as glycolysis, the pentose phosphate pathway and the tricarboxylic acid cycle, while the secondary metabolites consisted of classes such as terpenes and flavonoids, and the xenobiotics represented a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes and when urine features were matched to the database, the addition of the IMS dimension greatly reduced the possible number of candidate molecules. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added frequently.

Quality assurance procedures for mass spectrometry untargeted metabolomics. a review

Untargeted metabolomics, as a global approach, has already proven its great potential and capabilities for the investigation of health and disease, as well as the wide applicability for other research areas. Although great progress has been made on the feasibility of metabolomics experiments, there are still some challenges that should be faced and that includes all sources of fluctuations and bias affecting every step involved in multiplatform untargeted metabolomics studies. The identification and reduction of the main sources of unwanted variation regarding the pre-analytical, analytical and post-analytical phase of metabolomics experiments is essential to ensure high data quality. Nowadays, there is still a lack of information regarding harmonized guidelines for quality assurance as those available for targeted analysis. In this review, sources of variations to be considered and minimized along with methodologies and strategies for monitoring and improvement the quality of the results are discussed. The given information is based on evidences from different groups among our own experiences and recommendations for each stage of the metabolomics workflow. The comprehensive overview with tools presented here might serve other researchers interested in monitoring, controlling and improving the reliability of their findings by implementation of good experimental quality practices in the untargeted metabolomics study.

From common to rare Zingiberaceae plants - A metabolomics study using GC-MS

Zingiberaceae plants, commonly known as gingers, have been popular for their medicinal and culinary uses since time immemorial. In spite of their numerous health-promoting applications, many Zingiberaceae plants still receive no scientific attention. Moreover, existing reports mostly focused only on the Zingiberaceae rhizomes. Here, untargeted metabolite profiling using Gas Chromatography - Mass Spectrometry (GC-MS) was used to compare the metabolic composition of leaves and rhizomes of the more common gingers, Zingiber officinale Rosc. (ZO), Curcuma longa L. (CL), and Etlingera elatior (Jack) R.M. Smith (EE), and the rare gingers, Amomum muricarpum Elmer (AM), Etlingera philippinensis (Ridl.) R.M. Smith (EP), and Hornstedtia conoidea Ridl. (HC). Principal component analysis (PCA) demonstrated that different species show substantial chemical differentiation and revealed potential markers among the different Zingiberaceae plants. Interestingly, the leaves of AM, CL, EE, EP, and HC had significantly higher levels of chlorogenic acid than ZO. Moreover, rhizomes of EP and HC were found to contain significantly higher levels of amino acids than ZO. Sugars and organic acids were generally less abundant in ZO leaves and rhizomes than in the other gingers. The leaves of EP and rhizomes of AM were found most similar to the leaves and rhizomes of common gingers, respectively. Results of this study provide significant baseline information on assessing the possible usage of the leaves of common gingers and further propagation and exploration of EP and AM. This study, being the first metabolomics report on rare plants such as AM, EP and HC, affirms the usefulness of untargeted metabolite profiling in exploring under-investigated plants.

Review of emerging metabolomic tools and resources: 2015-2016

Data processing and analysis are major bottlenecks in high-throughput metabolomic experiments. Recent advancements in data acquisition platforms are driving trends toward increasing data size (e.g., petabyte scale) and complexity (multiple omic platforms). Improvements in data analysis software and in silico methods are similarly required to effectively utilize these advancements and link the acquired data with biological interpretations. Herein, we provide an overview of recently developed and freely available metabolomic tools, algorithms, databases, and data analysis frameworks. This overview of popular tools for MS and NMR-based metabolomics is organized into the following sections: data processing, annotation, analysis, and visualization. The following overview of newly developed tools helps to better inform researchers to support the emergence of metabolomics as an integral tool for the study of biochemistry, systems biology, environmental analysis, health, and personalized medicine.

A Novel Anti-Hepatitis C Virus and Antiproliferative Agent Alters Metabolic Networks in HepG2 and Hep3B Cells

A series of novel diflunisal hydrazide-hydrazones has been reported together with their anti-hepatitis C virus and antiproliferative activities in a number of human hepatoma cell lines. However, the mechanisms underlying the efficacy of these agents remain unclear. It was chosen to investigate the lead diflunisal hydrazide-hydrazone, 2',4'-difluoro-4-hydroxy-N'- [(pyridin-2-yl)methylidene]biphenyl-3-carbohydrazide (compound 3b), in two cultured human hepatoma cell lines-HepG2 and Hep3B-using a metabolomic protocol aimed at uncovering any effects of this agent on cellular metabolism. One sub-therapeutic concentration (2.5 μM) and one close to the IC₅₀ for antimitotic effect (10 μM), after 72 h in cell culture, were chosen for both compound 3b and its inactive parent compound diflusinal as a control. A GCMS-based metabolomic investigation was performed on cell lysates after culture for 24 h. The intracellular levels of a total of 42 metabolites were found to be statistically significantly altered in either HepG2 or Hep3B cells, only eight of which were affected in both cell lines. It was concluded that compound 3b affected the following pathways-purine and pyrimidine catabolism, the glutathione cycle, and energy metabolism through glycolysis and the pentose phosphate pathway. Although the metabolomic findings occurred after 24 h in culture, significant cytotoxicity of compound 3b to both HepG2 and Hep3B cells at 10 μM were reported not to occur until 72 h in culture. These observations show that metabolomics can provide mechanistic insights into the efficacy of novel drug candidates prior to the appearance of their pharmacological effect.

metaX: a flexible and comprehensive software for processing metabolomics data

Background

Non-targeted metabolomics based on mass spectrometry enables high-throughput profiling of the metabolites in a biological sample. The large amount of data generated from mass spectrometry requires intensive computational processing for annotation of mass spectra and identification of metabolites. Computational analysis tools that are fully integrated with multiple functions and are easily operated by users who lack extensive knowledge in programing are needed in this research field.

Results

We herein developed an R package, metaX, that is capable of end-to-end metabolomics data analysis through a set of interchangeable modules. Specifically, metaX provides several functions, such as peak picking and annotation, data quality assessment, missing value imputation, data normalization, univariate and multivariate statistics, power analysis and sample size estimation, receiver operating characteristic analysis, biomarker selection, pathway annotation, correlation network analysis, and metabolite identification. In addition, metaX offers a web-based interface (http://metax.genomics.cn) for data quality assessment and normalization method evaluation, and it generates an HTML-based report with a visualized interface. The metaX utilities were demonstrated with a published metabolomics dataset on a large scale. The software is available for operation as either a web-based graphical user interface (GUI) or in the form of command line functions. The package and the example reports are available at http://metax.genomics.cn/.

Conclusions

The pipeline of metaX is platform-independent and is easy to use for analysis of metabolomics data generated from mass spectrometry.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1579-y) contains supplementary material, which is available to authorized users.

Metabolomic Study on Idiosyncratic Liver Injury Induced by Different Extracts of Polygonum multiflorum in Rats Integrated with Pattern Recognition and Enriched Pathways Analysis

Currently, numerous liver injury cases related to a famous Chinese herb- Polygonum Multiflorum (Heshouwu in Chinese) have attracted great attention in many countries. Our previous work showed that Heshouwu-induced hepatotoxicity belonged to idiosyncratic drug-induced liver injury (IDILI). Unfortunately, the components and mechanisms attributed to IDILI of Heshouwu are difficult to determine and thus remain unknown. Attempts to explore puzzles, we prepared the chloroform (CH)-, ethyl acetate (EA)-, and residue (RE) extracts of Heshouwu to investigate IDILI constituents and underlying mechanisms, using biochemistry, histopathology, and metabolomics examinations. The results showed that co-treatment with non-toxic dose of lipopolysaccharide (LPS) and EA extract could result in evident liver injury, indicated by the significant elevation of plasma alanine aminotransferase and aspartate aminotransferase activities, as well as obvious liver histologic damage; whereas other two separated fractions, CH and RE extracts, failed to induce observable liver injury. Furthermore, 21 potential metabolomic biomarkers that differentially expressed in LPS/EA group compared with other groups without liver injury were identified by untargeted metabolomics, mainly involved two pathways: tricarboxylic acid cycle and sphingolipid metabolism. This work illustrated EA extract had close association with the idiosyncratic hepatotoxicity of Heshouwu and provided a metabolomic insight into IDILI of different extracts from Heshouwu.